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Reply to the reviewers
Reviewer #1
Evidence, reproducibility and clarity
Sanial et al. carefully analyze the use of in-gel fluorescence as an alternative to immunoblotting. The authors show that simple modifications of common protein extraction protocols can preserve (to varying extents) fluorescent proteins in their native, fluorescent states. This can be exploited in different applications for in-gel fluorescence quantification, bypassing immunoblotting. The experimental results are clear, showcasing the ease and linearity of in-gel fluorescence quantification.
In my opinion, the trick of this approach is also potentially its main drawback, the partial denaturation conditions. I think the manuscript could be strengthened with more extensive benchmarking of the approach and further discussion of potential caveats as detailed below.
Major points:
- Protein abundance in the original GFP library (and in other FP-tagged libraries constructed in the meanwhile) have been quantified using fluorescence (flow cytometry, microscopy, colony fluorescence) (Ho et al. 2018 10.1016/j.cels.2017.12.004, Weill et al. 2018 10.1038/s41592-018-0044-9, Meurer et al. 2018 10.1038/s41592-018-0045-8). This provides an opportunity to significantly strengthen the manuscript (where most of the test have been done using two abundant cytosolic proteins Bmh1 and Hxk1) if the authors could apply their approach to a representative fraction of the yeast proteome (sampling from such libraries FP-tagged proteins that differ in abundance, localization, membrane vs cytosolic/nuclear, subunits of large stable complexes vs proteins not part of complexes, etc.) and compare their quantification with previous relative abundance estimates. This information would also help future users in case protein-specific issues are identified.
Indeed, Hxk1 and Bmh1 are quite strongly expressed (41,000 and 65,000 copies/cell, according to SGD, ____www.yeastgenome.org____). In the course of our experiments we were able to detect proteins with a much lower expression level (eg. Reg1, 4000 copies/cell). We have selected a number of proteins based on their expression level as detailed in SGD, ranging from 700 to 75000, and plan to detect the signal by IGF and compare it with published data on absolute protein quantifications for ecah protein. However, this will take a bit of time as each gene must be tagged with EGFP – we cannot use the GFP-S65T from the GFP collection which is poorly amenable to IGF because of its sensitivity to denaturation, as we show in our manuscript.
The authors discuss several drawbacks, including the change in apparent molecular weight compared to denatured proteins; differential recognition of folded vs denatured proteins by antibodies.
Other potentials drawbacks should be discussed. For instance, the need of additional steps post-fluorescence imaging for signal normalization against a loading control; the need of antibodies and immunoblotting to decide on the best denaturing temperature for a specific protein or FP tag; complexity of the native protein extraction protocol compared for example to alkaline lysis followed by TCA precipitation (Knop et al. 1999 PMID: 10407276).
- Regarding the the need of additional steps post-fluorescence imaging for signal normalization against a loading control – this doesn’t take extra time for people using gels with protein stain included in the gel (eg. Stain-Free from BioRad). There are other possibilities of total protein fluorescent labeling that will be discussed. We will provide an example of this application.
- On the need of antibodies and immunoblotting to decide on the best denaturing temperature for a specific protein or FP tag – we believe that the system could be set up for a protein of interest for which antibodies are available (as we did for Bmh1 or Hxk1), and once this is done, there is no need to do these controls anymore. We will mention this in the manuscript.
- On the complexity of the native protein extraction protocol compared for example to alkaline lysis followed by TCA precipitation – indeed the protocol is a bit more time-consuming compared to the mentioned method, and we will mention this in the text. However, please note that people studying mammalian cells, for instance, often use this native protocol for total extracts so this is mostly a yeast-model issue. Yet, we will add this comment. Moreover, although the denatured fraction is FP- and temperature-dependent, even under the milder 30{degree sign}C conditions there is a detectable denatured fraction (Fig.s3b). This would seem to preclude the use of this approach for absolute protein quantification.
True, but it depends a lot on the FP used. For instance, sfGFP is not denatured and could potentially be used for absolute quantification. We will comment in the text.
Finally, any evidence that the denatured fraction would depend on the protein tagged with the FP?
We will use several proteins used for point 1 but fused to the most sensitive FP, GFP-S65T, and do a western blot using anti-GFP antibodies to estimate the variation in native vs. denatured forms of the protein.
Minor points: 1. In the experiments designed to test the linearity and sensitivity of the approach, an alternative approach that would not result in dilution of cell extract is to mix wild type cell extract (no GFP fusion) with extract of the GPF-tagged strain in different ratios.
Yes, this was an alternative but it seemed that dilution was easier to control than mixing two extracts.
Define all acronyms at first appearance. For example, DTT and LDS on page 4.
Thank you, we will address all acronyms in the text.
Fig.4D: the colors chosen to represent EGFP and sfGFP data make them hard to tell apart. The same comment to Fig.S6.
Agreed, we will change the figures accordingly.
As the temperature steps are not uniform in Figures 4 and 5, it would be more informative to indicate the exact temperate above each lane (in addition/instead of the ramp cartoon).
Agreed, we will change the figures accordingly.
Regarding linearity, that HRP-based quantification is not linear is expected. A fairer comparison would be to use fluorescently labeled secondary antibodies. It is also puzzling that detection with signal amplification (HRP) is less sensitive than direct quantification of the fluorescence signal from the FP tag.
We will do a sensitivity tets (dilutions) to compare IGF with HRP-based and fluorescent-based antibody-mediated detection.
I appreciate the workflow Figure 10. But in my opinion it is trying to show too much (protocol, troubleshooting, calls to figure panels). Perhaps it could be made clearer by separating the protocol steps/settings from the optimization/troubleshooting tips.
Thank you, we will work on this to make the workflow clearer.
Some of the discussion of different fluorescent proteins, and expression levels of tagged proteins, could be confounded by the different linkers used in the tagging constructs.
Thank you for this remark. Indeed, there are various linkers on these constructs and we don’t know to which extent they contribute to the effect on protein expression level. We will comment his in the text.
Significance
Could be a generally useful and simple approach for in-gel quantification using fluorescent protein tags.
__ ____Thank you for your comments and overall assesment.__
Reviewer #2
Evidence, reproducibility and clarity
The present manuscript "Direct observation of fluorescent proteins in gels: a rapid cost-efficient, and quantitative alternative to immunoblotting" describes a method how to visualize bands of fluorescent protein fusions onto a common SDS-PAGE without antibody staining. It is based on ability of GFP-like fluorescent proteins (FPs) to retain their fluorescence under conditions of SDS-PAGE if step of extensive heating (boiling) of protein sample is omitted. This property of FPs is not novel; it was known for more than 20 years (for example, see Fig. 2 in Yanushevich et al. FEBS Lett. 2002 Jan 30, 511:11-4; Supporting Fig. 7 in Campbell et al. Proc Natl Acad Sci USA. 2002 Jun 11, 99:7877-82). However, the authors did perform a very accurate and robust study to quantitatively assess the behavior of several FP fusion protein in SDS-PAGE. A thorough analysis of different conditions for a variety of FPs and target proteins was done; detailed protocols were developed. A surprisingly high sensitivity of FP detection (even superior to that of standard Western blotting) was demonstrated. Considering the simplicity of the proposed approach, it appears to be the method of choice for those working with FP fusion proteins.
Thank you for this comment. Indeed we do not claim to discover that FP remain fluorescent in mild denaturing conditions, as presented in the text. We did our best to include original publications showing precedent for this and we missed Yanushevich et al. FEBS Lett. 2002 that we will add. However the Campbell paper is cited, precisely for the Supplementary figure 7 that the reviewer mentions.
I have only minor, discretionary comments:
- It is known that under conditions of SDS-PAGE without heating, FPs retain not only fluorescence but also their oligomeric state. The same can be true for proteins of interest (POIs). If so, even for monomeric FPs, the POI-FP band can potentially migrate much slower than expected because of oligomerization of the POI.
__Thank you for this suggestion. Our data in the manuscript already show that Bmh1 and Bmh2, which are tighlty associated 14-3-3 proteins, no longer intereact in these mild denaturation conditions. In the set of proteins that we will use to answer to Reviewer #1 (point 1), we will include proteins in large complexes to assess whether this can happen. __
It might be useful to briefly discuss a possibility to use other types of fluorescent proteins (namely, Flavin-binding FPs, bacteriophytochrome-based FPs, bilirubin-binding FP UnaG) in the same way as proposed here. In particular, biliverdin-binding near-infrared FPs (IFP, iRFP, etc.) can be detected even after fully denaturing SDS-PAGE by zinc-induced orange fluorescence of proteins carrying covalently attached bilin chromophore (Berkelman TR, Lagarias JC. Visualization of bilin-linked peptides and proteins in polyacrylamide gels. Anal Biochem. 1986, 156, 194-201; Stepanenko OV, Kuznetsova IM, Turoverov KK, Stepanenko OV. Impact of Double Covalent Binding of BV in NIR FPs on Their Spectral and Physicochemical Properties. Int J Mol Sci. 2022, 23, 7347).
__Agreed. ____We will extend the discussion to other fluorescent approaches to visualize proteins in gels and compare them. __
Significance
A simple method of specific visualization of fluorescent protein fusion bands on SDS-PAGE is proposed.
Thank you for your comments and overall assesment.
Reviewer #3
Evidence, reproducibility and clarity
In this paper, Sanial et al present in-gel fluorescence detection (IGF), a method that allows the direct detection of fluorescent proteins from SDS-PAGE gels with minimal adaptation of existing protocols. The authors test a range of fluorescent proteins routinely used, especially when working with yeast, and describe their behavior in IGF. They identify heat-induced denaturation of fluorescent proteins as the main component influencing their assay and systematically test this on a selection of fluorescent proteins. Next, they compare the detection limit and the linearity of the signal between IGF and chemiluminescence, showing that IGF is not only comparable but also superior to chemiluminescence. This is particularly significant given that chemiluminescence can suffer from issues such as a limited dynamic range and limitations in accurately quantifying very low or high-abundance proteins. The authors further demonstrate the utility of IGF in co-immunoprecipitation experiments and test whether the mild denaturing conditions are compatible with proteins from other organisms. Overall, the study is well-presented and is an asset to the scientific community. I have one major and some minor comments that, in my opinion, would improve this already informative paper: Major comment 1. In all cases where there is signal quantification the authors should perform replicates to account for variability of the signal (in Fig 6, S6 and S7).
__Agreed, we will perform triplicates for the indicated experiments. __
Minor comments 1. The study mainly focuses on soluble protein. While the authors have tested one plasma membrane protein, the study would benefit from including more membrane proteins from different environments (e.g., cell wall, nuclear envelope, mitochondrial). This would help determine if incubation at higher temperatures is necessary to properly solubilize these proteins, in which case the experiment would need adaptation.
Thank you for this suggestion. __In the set of proteins that we will use to answer to Reviewer #1 (point 1), we will include proteins from various subcellular locations. __
The authors show that when fluorescent proteins are partially denatured, their migration behavior changes. One cannot exclude that in some cases, the tagged proteins themselves might also be partially resistant to denaturing at the low temperatures used for IGF. This would lead to more than one fluorescent bands. In such cases one should be careful with interpretation, especially in the context of PTMs or isoforms. Could the authors briefly discuss this?
Thank you for this comment. __We will discuss this in the text. __
Based on Fig 4D and 5D, some fluorescent proteins seem to have a higher signal variability between replicates than others. It would be helpful to add this information next to the behavior of the proteins in different temperatures so it would be easier to choose the fluorescent protein for specific experiments.
__Indeed, there are variations between experiments, but it is not clear whether this inherent to the FP considered or the experiment. We will look back at the data and modify the text accordingly if pertinent. __
The sensitivity experiment (Figure 6) is convincing and important for IP conditions, where the total protein concentration of the sample is radically decreased. Could the authors additionally test if very low abundant proteins can be detected (without any dilution of the total protein content), and compare this to chemiluminescence? This could be done either by tagging some very low abundant proteins (for example a few hundred copies per cell) or diluting the lysate in wild-type lysate to artificially reduce their concentration while maintaining the overall protein load the same.
__We have planned an experiment in which low abundant proteins will be tagged in response to reviewer 1 (point 1) which should address this point. __
It would be useful to address the detection of very high molecular weight proteins - or proteins that are problematic in terms of transfer during western blotting.
Again, in the experiment planned in ____response to reviewer 1 (point 1), proteins or various MW as well as membrane proteins will be studied, which should address this point. __ __
Significance
The authors already discuss the strengths and limitations of their approach. The main strength of IGF is that it does not require transfer of the proteins to a membrane and also does not rely on antibody binding and (potential) chemical reactions. In addition to the fact that this is time, cost, equipment, waste and expertise effective, the sensitivity and signal linearity of IGF seems to not only compare but outperforme western blotting. There are two main limitations. First, IGF relies on the resilience to denaturing of the chosen fluorescent protein that depends, according to the authors, at least on the temperature and overall protein concentration and pH. Second, IGF relied on tagging proteins with fluorescent proteins which might affect the stability or even function of the tagged protein. As the authors mention, these factors do not diminish the value of IGF, they highlight the need for appropriate controls.
A potential development of the technique (not at the present study) could be the compatibility of IGF with different self-labelling proteins (Halo, Snap) and fluorescent dyes.
We have conducted experiments in which we show the applicability of IGF in combination to SNAP-tagging, that we could show if needed.
I think IGF will benefit a rather broad range of scientists. As already mentioned by the authors, there are different applications of IGF. From checking of clones when creating strains, to comparison of protein levels in different conditions and coIP experiments.
Thank you for your comments and overall assesment.
Cross reviews. Reviewer 1: I agree with the assessment by Reviewer #2. Considering the comment about potential oligomerization of a protein of interest, I stand by my point about testing the method with more proteins of interest. How extensive this testing should be or whether additional discussion of possible issues would suffice is a matter of opinion. It is clear from the manuscript in it's current form that the method works and that it has caveats.
We believed that the experiments we have planned will clarify these points.
Reviewer 2: In general, I agree with the points raised by Reviewer #1. However, in my opinion, there is already a large body of reliable experimental results in the manuscript that are worth publishing without a new round of extensive experiments.
Reviewer 1: Fair enough, I don't insist on the experiments in my point 1.
We think that this is an important point that will likely be a common question for readers so we will still do our best to provide data for this point.
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Referee #1
Evidence, reproducibility and clarity
Sanial et al. carefully analyze the use of in-gel fluorescence as an alternative to immunoblotting. The authors show that simple modifications of common protein extraction protocols can preserve (to varying extents) fluorescent proteins in their native, fluorescent states. This can be exploited in different applications for in-gel fluorescence quantification, bypassing immunoblotting. The experimental results are clear, showcasing the ease and linearity of in-gel fluorescence quantification.
In my opinion, the trick of this approach is also potentially its main drawback, the partial denaturation conditions. I think the manuscript could be strengthened with more extensive benchmarking of the approach and further discussion of potential caveats as detailed below.
Major points:
- Protein abundance in the original GFP library (and in other FP-tagged libraries constructed in the meanwhile) have been quantified using fluorescence (flow cytometry, microscopy, colony fluorescence) (Ho et al. 2018 10.1016/j.cels.2017.12.004, Weill et al. 2018 10.1038/s41592-018-0044-9, Meurer et al. 2018 10.1038/s41592-018-0045-8). This provides an opportunity to significantly strengthen the manuscript (where most of the test have been done using two abundant cytosolic proteins Bmh1 and Hxk1) if the authors could apply their approach to a representative fraction of the yeast proteome (sampling from such libraries FP-tagged proteins that differ in abundance, localization, membrane vs cytosolic/nuclear, subunits of large stable complexes vs proteins not part of complexes, etc.) and compare their quantification with previous relative abundance estimates. This information would also help future users in case protein-specific issues are identified.
- The authors discuss several drawbacks, including the change in apparent molecular weight compared to denatured proteins; differential recognition of folded vs denatured proteins by antibodies.
Other potentials drawbacks should be discussed. For instance, the need of additional steps post-fluorescence imaging for signal normalization against a loading control; the need of antibodies and immunoblotting to decide on the best denaturing temperature for a specific protein or FP tag; complexity of the native protein extraction protocol compared for example to alkaline lysis followed by TCA precipitation (Knop et al. 1999 PMID: 10407276).
Moreover, although the denatured fraction is FP- and temperature-dependent, even under the milder 30{degree sign}C conditions there is a detectable denatured fraction (Fig.s3b). This would seem to preclude the use of this approach for absolute protein quantification.
Finally, any evidence that the denatured fraction would depend on the protein tagged with the FP?
Minor points:
- In the experiments designed to test the linearity and sensitivity of the approach, an alternative approach that would not result in dilution of cell extract is to mix wild type cell extract (no GFP fusion) with extract of the GPF-tagged strain in different ratios.
- Define all acronyms at first appearance. For example, DTT and LDS on page 4.
- Fig.4D: the colors chosen to represent EGFP and sfGFP data make them hard to tell apart. The same comment to Fig.S6.
- As the temperature steps are not uniform in Figures 4 and 5, it would be more informative to indicate the exact temperate above each lane (in addition/instead of the ramp cartoon).
- Regarding linearity, that HRP-based quantification is not linear is expected. A fairer comparison would be to use fluorescently labeled secondary antibodies. It is also puzzling that detection with signal amplification (HRP) is less sensitive than direct quantification of the fluorescence signal from the FP tag.
- I appreciate the workflow Figure 10. But in my opinion it is trying to show too much (protocol, troubleshooting, calls to figure panels). Perhaps it could be made clearer by separating the protocol steps/settings from the optimization/troubleshooting tips.
- Some of the discussion of different fluorescent proteins, and expression levels of tagged proteins, could be confounded by the different linkers used in the tagging constructs.
Referee Cross-commenting
This session contains comments from all reviewers.
Reviewer 1: I agree with the assessment by Reviewer #2. Considering the comment about potential oligomerization of a protein of interest, I stand by my point about testing the method with more proteins of interest. How extensive this testing should be or whether additional discussion of possible issues would suffice is a matter of opinion. It is clear from the manuscript in it's current form that the method works and that it has caveats.
Reviewer 2: In general, I agree with the points raised by Reviewer #1. However, in my opinion, there is already a large body of reliable experimental results in the manuscript that are worth publishing without a new round of extensive experiments.
Reviewer 1: Fair enough, I don't insist on the experiments in my point 1.
Significance
Could be a generally useful and simple approach for in-gel quantification using fluorescent protein tags.
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Reply to the reviewers
Manuscript number:
RC-2024-02569
Corresponding author(s): Mary O'Riordan, Teresa O'Meara
1. General Statements
We thank the reviewers for their positive feedback, highlighting the significance and novelty of our work, especially regarding the novel functions of IRE1a in regulating phagosome biology during infection. We also appreciate some overarching themes that were focused on by multiple reviewers, including the role of XBP1S protein and RIDD activity, which we have addressed here. We have also added additional data, made adjustments to data presentation, and added clarifying language to address concerns from Reviewer 3. We appreciate these constructive suggestions and include our planned experiments to address reviewer concerns here. Our specific responses to the reviewer comments are below.
Specific figures used in the response to reviewers are in the attached file as they cannot be pasted here.
2. Description of the planned revisions
Reviewer 1:
1) The demonstration of protein misfolding independent IRE1 activation should also be demonstrated using molecules such as TUDCA or 4PBA that should be innocuous regarding the splicing of XBP1s. It would also be interesting to evaluate the activation of the other arms of the UPR in particular through the phosphorylation of eIF2a, expression of ATF4 and cleavage of ATF6.
We appreciate the suggestion to strengthen our data regarding protein misfolding-independent activation of IRE1 more robust. We note that canonical UPR transcriptional targets are not induced during C. albicans infection (Fig. 2G,H), suggesting that IRE1 is activated in the absence of a standard unfolded protein response. However, we agree that we can use additional chemical chaperones to assay this. To address this point, we will perform the suggested experiments in the presence or absence of TUDCA with C. albicans, LPS, thapsigargin, and tunicamycin. As 4PBA has been shown to inhibit protein synthesis, rather than promoting protein folding or preventing aggregation (PMC9741500), we will avoid using this compound for these assays.
We will also perform western blots for ATF6 cleavage and eIF2a phosphorylation, although we note that eIF2a can be phosphorylated by multiple kinases and can be triggered by nutrient deprivation or changes in intracellular calcium, both of which occur during C. albicans infection (glucose: PMC6709535; calcium: data within this manuscript).
3) The authors use thioflavin to evaluate the extent of protein misfolding. This type of stain can lead to artefactual results and in general it is rather safer to test several stainers (see for instance the work presented in PMC10720158)
We thank the reviewer for this suggestion. We have previously tried Proteostat staining as an additional method to measure protein misfolding, but we found that it bound strongly to the C. albicans cell wall, which would result in a strong false positive signal that is not indicative of host protein misfolding (see below). Congo Red, an additional dye used in the listed reference, is also known to bind to C. albicans and perturbs cell wall synthesis (PMC266468), therefore we have avoided these dyes.
However, to address this point, we will perform experiments utilizing poly-ubiquitin blotting, as in the suggested reference, as an orthogonal readout of protein misfolding during C. albicans infection or treatment with LPS, depleted zymosan, and thapsigargin.
__Figure legend: Proteostat staining with _C. albicans_ infection. __Macrophages were infected with C. albicans, and subsequently stained with Proteostat to measure protein misfolding. Proteostat bound and displayed strong fluorescence on the C. albicans cell wall.
6) The whole study relies on the use of IRE1deltaR to impair IRE1 signaling. The authors should validate their hypothesis with an orthogonal approach, for instance with IRE1 pharmacological inhibitors (eg MKC8866 or KIRA8).
We consider the use of genetic perturbation of IRE1 to be a strength of this manuscript, as IRE1 inhibitors have been shown to cause off-target effects (KIRA8: PMC9600248). However, to address this point, we will attempt to replicate important phenotypes, including the effect of IRE1 on calcium flux and phagolysosome fusion, using MKC8866 and KIRA8 as representative inhibitors.
3. Description of the revisions that have already been incorporated in the transferred manuscript
__Reviewer 1: __
5) The authors focus on the IRE1/XBP1s signaling arm of the UPR but do not explore RIDD activity which has been linked to several infection mechanisms and lysosomal integrity (in particular by regulating the expression of BLOS1 - see PMC9119680 and PMC6446841). The authors should definitely evaluate how RIDD is activated (or not) in their experimental systems.
We thank the reviewer for this suggestion, as we have considered potential effects of RIDD when analyzing our RNA-seq data, and are aware of the potential links between IRE1, BLOS1 (encoded by Bloc1s1) expression, and lysosome perturbations. We now add additional figures to our supplemental data (Fig. S3C-D; also shown below) showing that established RIDD targets, including Bloc1s1 are not depleted during C. albicans infection, and also not increased in IRE1 null macrophages. We add the following text to describe these findings (lines 322-326): "Additionally, we did not observe depletion of published RIDD targets (14, 65, 66) during C. albicans infection in WT macrophages (Fig. S3C; Table S2), nor increased expression of RIDD targets in IRE1ΔR macrophages, compared to IRE1 WT macrophages (Fig. S3D; Table S1.1), suggesting minimal RIDD activity during C. albicans infection." We also note that experiments with LysoSensor (Fig. 3E) suggested lysosome biogenesis is not impaired in IRE1 null macrophages. Therefore, we expect RIDD activity has negligible effects on our reported phenotypes.
Reviewer #1 (Significance (Required)):
The manuscript is interesting and highlights novel aspects towards the interaction between macrophages and a pathogen, candida albicans, involving the likely selective activation of IRE1. The data are novel and experimentally sound. Several controls are however missing.
The strengths of the study are associated with the novelty of the findings, with the links that could potentially derive from this study to connect ER biology, UPR signaling and phagosome maturation
The main weaknesses are associated i) with the fact that the authors did not evaluate RIDD activity which has already been linked with pathogen infection and with lysosome integrity, ii) with methodological aspects, in particular regarding the demonstration of the IRE1 activation independent on protein misfolding and the sole use of a genetic variant of IRE1 to test their hypotheses
We thank Reviewer 1 for their constructive feedback and for noting the novelty of our findings. We believe that the data we have added regarding RIDD activity and our planned experiments to address additional concerns will add additional evidence to support our findings.
Reviewer 2:
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A point that should be addressed with more detail is the correlation of fungal killing with Ca2+ fluxes and Ire1α activity, given the well-known data regarding the strong ability of the axis dectin/SYK/phospholipase Cγ to induce Ca2+ transients, a response not shared by LPS signaling, and the sequential activation of mitochondrial Ca2+ uniporter (MCU), which is a critical element of fungal killing associated with the citrate-pyruvate shuttle as a NADPH source (Seegren et al., Cell Rep. 33: 108411, 2020). Incidentally, this paper is referred in ref. 46 as a preprint, although it was accessible in Cell Reports in 2020.
This is an excellent suggestion; we have added this topic to our discussion (lines 605-608) and have corrected the citation.
The assay of the expression of V-ATPase complex, mitochondrial calcium uniporter, and mitochondrial uptake 1 and 2 could shed light on the dependence of fungal killing on Ire1α function.
Thank you for this suggestion - below, we plot the transcripts comprising the V-ATPase, as well as Mcu, Micu1, and Micu2. We note that these transcripts are not perturbed in IRE1 null macrophages, suggesting that the basic functions of the V-ATPase complex and mitochondrial calcium uptake are intact in IRE1 null macrophages.
These data are in agreement with our LysoSensor assay (Fig. 3E), which suggested that lysosome biogenesis is not impaired in IRE1 null macrophages.
While we cannot rule out a defect in mitochondrial calcium flux from our RNA-seq data, we have added discussion around this topic to our discussion, as mentioned above.
Expression of V-ATPase subunits and mitochondrial calcium uptake genes in C. albicans-infected IRE1 null macrophages vs C. albicans-infected IRE1 WT macrophages.
Fig. 1A should be explained with more detail to disclose the products of PstI digestion.
Thank you for the suggestion. We have added this information to the Figure 1 legend, "RT-PCR-amplified Xbp1 cDNA was treated with PstI, which recognizes a cleavage site within the 26 base pair intron that is removed by IRE1α activity, resulting in cleavage of the unspliced isoform, specifically."
The anti-XBP1 antibody used to construct the blots in Fig.S1A recognizes epitopes not disclosed by the manufacturers, but they have to pertain to the N-terminal peptide sequence shared by sXBP1 and uXBP1. Showing full lanes encompassing both protein isoforms would allow a better appraisal of protein expression. In connection to point 4, the use of an antibody reactive to the epitopes expressed in sXBP1 in cell lysates or, preferentially in nuclear fractions, could be most valuable to rule out the dependence of the effect of Ire1α on the trans-activating function of sXBP1.
We have un-cropped these westerns and now show spliced and unspliced XBP1 products on a single image in Fig. S1A.
On page 23, the mention to Fig. 5A should be changed to Fig. 5B.
We have fixed this mis-labeling, thank you for calling this to our attention.
Line 209. I understand gene synthesis refers to gene expression.
We have clarified this in the text, thank you for the suggestion.
Line 394. What is the reason to study the cytokine-signature of Candida in LPS-primed cells?
Thank you for the question; we have added the following text (lines 413-414) to clarify that LPS is used for inflammasome priming:
"Therefore, we tested secretion of IL-1β, TNF, and IL-6 from WT and IRE1ΔR macrophages after LPS treatment to transcriptionally prime the NLRP3 inflammasome components, followed by C. albicans infection (Fig. 5D-F)."
Numerous studies have shown that C. albicans can trigger macrophage pyroptosis, resulting in production of pro-inflammatory cytokines like IL-1b, which can also be influenced by phagosome rupture (PMC3910967). However, this requires inflammasome transcriptional priming, and LPS is commonly used to prime macrophages for inflammasome activation in vitro. Therefore, we perform a short pre-treatment with LPS for NLRP3 inflammasome priming to subsequently measure its activation following C. albicans infection, using secreted cytokines as a readout. We also note that macrophages in vivo may not be naive and are often M1-polarized by the microbial or cytokine environment, thus inflammasome priming is likely common during in vivo infection.
Reviewer #2 (Significance (Required)):
This study focuses on an aspect not usually addressed in papers devoted to the UPR.
If more data are shown as suggested, the paper could be of interest for a wider audience
We thank the reviewer for their positive feedback about the novelty of our work and agree that the suggested experiments will bolster our data and story.
Reviewer 3:
Fig. 2:
Panel A-B: same question as for Fig. 1. The variation in TG DMSO-induced splicing is huge. The effects of the treatments with CHX or Act D are smaller than the variation between experiments with TG DMSO alone. As long as that variation is not controlled for, it is impossible to draw any conclusion from the inhibitors. In this regard, it is very difficult to interpret data if they are not done in one and the same experiment.
The variability in thapsigargin fold change over mock likely represents differences in basal Xbp1 expression. We consistently see complete Xbp1 splicing in response to thapsigargin treatment (see Fig. 1A). Additionally, we note that thapsigargin treatment is used only as a positive control, not as a physiologically relevant treatment, as it results in unmitigated ER stress that triggers cell death (PMC6986015).
We have removed the following sentence, "Translation inhibition using cycloheximide was sufficient to alleviate Xbp1 splicing specifically in response to thapsigargin, likely by reducing the nascent protein folding burden (Fig. 2B)," since our data are plotted on separate graphs, matched to their respective controls, for appropriate comparisons.
4. Description of analyses that authors prefer not to carry out
Reviewer 1:
2) Since the IRE1/XBP1 arm of the UPR is also involved in lipid biosynthesis which might be required for phagosome maturation, the authors should perform XBP1s rescues in IRE1 deficient cells to ensure that their observation is XBP1s dependent or IRE1 dependent.
As we do not see XBP1S protein induced in wild-type macrophages at any timepoint during our C. albicans infection scheme (Fig. S1A-B), we interpret our results as being XBP1S-independent. If we were to add back XBP1S with constitutive expression, we would be overexpressing the protein relative to C. albicans infected wild-type macrophages (in which we do not see measurable XBP1S expression). Therefore, we believe these experiments would not address a physiologically-relevant scenario.
4) The authors should evaluate in what compartment IRE1 is activated upon CA infection, does that happen in the ER or in the ER fraction fused to phagosomes?
This is an interesting question for future exploration. In order to answer this question with existing tools, we would need to perform biochemical fractionation of infected cells to isolate an ER-phagosome contact site fraction, followed by phos-tag gel analysis of IRE1 activation in the ER fraction, compared to the ER-phagosome contact site fraction. However, a biochemical fractionation protocol to distinguish the ER fraction from ER-phagosome contact sites has not yet been developed, to our knowledge, and we believe it is outside the scope of this study to develop such a technique.
We have added additional text regarding this intriguing question to our discussion (lines 549-553).
Reviewer 2:
Infection at a MOI 1 of C. albicans is a ratio of infecting agent/susceptible targets not very high for a non-soluble stimulus with limited diffusion in the culture medium. Although I recognize the difficulty of quantitating adhered cell, the mention to 80% confluence makes it more difficult the appraisal of the actual MOI. The delayed time-course of Xbp splicing under these conditions can be explained by the time required for in vitro proliferation, Candida damage, and diffusion of fungal patterns. A study with viable Candida at MOI 5 in human monocyte-derived dendritic cells, which show a robust capacity for non-opsonic phagocytosis associated with C-type lectin receptors only showed initial hypha formation after 2 hours (Rodriguez et al., J. Biol. Chem. 289, P22942-22957, 2014). Consistent with the requirement of a time lag for infecting agent to attain levels of expression consistent with a net response, 16 hours have been considered an appropriate time-course to assay sXBP1 expression following SARS-CoV2 infection (Fernandez et al., Biochim Biophys Acta Mol Basis Dis. 1870(5):167193, 2024). I wonder if a higher MOI could show a similar kinetics.
We use lower MOI in part due to the size and ability of C. albicans to undergo extensive hyphal growth if its numbers greatly exceed the number of host cells. From our microscopy data, we can see that C. albicans spreads well throughout the culture plate (see Fig. 3A, Fig. 4A). We and others have observed considerable death of macrophage cultures after 12 hours with Candida infection, even at low MOI (PMC6709535), therefore we avoid later timepoints in these assays and all other in vitro assays in our manuscript.
As all of our in vitro experiments are performed within an 8 hour window of infection, whether XBP1S is induced at later timepoints by C. albicans or depleted zymosan would not alter the conclusions of the rest of our results.
sXBP1 can be present in nuclear fractions in resting cells, which suggests the involvement of post-translational modifications for the display of transcriptional activity.
As we do not see induction of XBP1S in our lysates after C. albicans infection, it is unlikely that post-translational modification is influencing its function, although we agree post-translational modification is a likely regulatory control over XBP1S during the unfolded protein response.
The independence of sXBP1 transcriptional activity from canonical UPR associated with misfolded protein stress is well known from the seminal paper by Martinon et al., (ref.6). Moreover, the expression of CHOP, the final effector of the PERK route, encoded by DDIT3 gene, has been found to be blunted by Candida (Rodriguez et al., J. Biol. Chem. 289, P22942-22957,2014). This is additional evidence for the recruitment of sXBP1 transcriptional activity in the absence of canonical UPR.
As mentioned, we found that XBP1S protein is not induced during C. albicans infection at any timepoint in our experiments (Fig. S1A-B). Importantly, the work referenced by the reviewer uses RAW267.7 cells, which (as mentioned by the authors) constitutively express CHOP as a result of Abel leukemia virus infection. Based on this specific overexpression, we believe this phenotype is not comparable to our bone marrow-derived macrophages.
Reviewer 3:
Fig. 1:
Panel 1C: please remove outlier in 4h timepoint. This implies that the experiment needs to be redone to reduce variation
We have performed an outlier test on these data, which revealed that this data point is not a statistical outlier, therefore we do not feel that its removal is appropriate (see below).
Panel 1E-H: how is the splicing efficiency determined and normalized? How to explain the big differences in splicing efficiency of Xbp1 upon LPS stimulation (appr. 4 to 6 times in E, G and H versus 30-fold in panel F). Where does this difference come from?
Panel H, outlier needs to be removed.
We do occasionally see differences in magnitude of Xbp1 splicing in different cell lines or experiments, especially with controls, which may be caused by differences in the basal level of Xbp1 expression, especially as Xbp1 levels have been shown to be affected by circadian rhythm in certain cell types (PMCID: PMC11214543; PMCID: PMC6959563).
In panel H, an outlier test reveals that these are not statistical outliers, therefore we feel their removal is inappropriate as we do not wish to mask biological variation. Moreover, this graph includes two cell lines (open and closed circles), showing that our data are robust across multiple independent cell lines and are an appropriate measure of experimental replicates.
Fig. 2:
Panel A-B: same question as for Fig. 1. The variation in TG DMSO-induced splicing is huge. The effects of the treatments with CHX or Act D are smaller than the variation between experiments with TG DMSO alone. As long as that variation is not controlled for, it is impossible to draw any conclusion from the inhibitors. In this regard, it is very difficult to interpret data if they are not done in one and the same experiment.
The variability in thapsigargin fold change over mock likely represents differences in basal Xbp1 expression. We consistently see complete Xbp1 splicing in response to thapsigargin treatment (see Fig. 1A). Additionally, we note that thapsigargin treatment is used only as a positive control, not as a physiologically relevant treatment, as it results in unmitigated ER stress that triggers cell death (PMC6986015).
We have removed the following sentence, "Translation inhibition using cycloheximide was sufficient to alleviate Xbp1 splicing specifically in response to thapsigargin, likely by reducing the nascent protein folding burden (Fig. 2B), since our data are plotted on separate graphs, matched to their respective controls, for appropriate comparisons.
Below, we plot all data together with replicate matching, although our major interpretation of these data is that C. albicans infection can trigger Xbp1 splicing with or without new gene expression, and not about the impact of the inhibitors on the control treatment thapsigargin.
Please provide a scheme of how the experiment was performed, at what time were the inhibitors provided, at what time point the inducers? What are matched mock samples. Which mock samples were chosen since they differ from one experiment to the next? Please plot all the data for one and the same experiment in one graph so that the reader can easily compare the results of DMSO, DMSO + inducer, DMSO + inducer + inhibitor. Indicate whether the points in the graph are technical or experimental repetitions.
-How to explain the increase in XBP1 splicing in combination with ActD? Was this due to differences in Gapdh expression? Where did the authors control for cell death? Please provide the data.
Below is a scheme of the experimental treatments. We have now clarified in the figure legend that inhibitors (ActD and CHX) are added at the same time as experimental treatments (Mock, Ca, TG). All data included in the original submission are biological replicates, as stated in the figure legend. We have now re-written the figure legend to clearly indicate that these are biological replicates.
All data are normalized such that the effects of the drugs are directly compared (for example, the fold change over Mock for Candida is matched to its drug treatment; Mock DMSO vs Ca DMSO and Mock ActD vs Ca ActD, or Mock CHX vs Ca CHX). Actinomycin D does inhibit new transcription, although IRE1 can cleave existing Xbp1 transcript. We now show conditions normalized to DMSO Mock in Supplemental Figure 2, which allows visualization of the effects of ActD and CHX on Xbp1-S abundance in comparison to control DMSO treatment, while also seeing the relative changes in Xbp1 splicing caused by C. albicans or thapsigargin treatment (see below).
-Is RT-qPCR a reliable readout when actinomycinD is used? How can new genes be transcribed.
We interpret RT-qPCR data as a readout of transcript abundance, rather than transcription. Therefore, we are not measuring new gene expression here, but whether the existing Xbp1 transcript can be cleaved by IRE1. Based on the technique, we can still measure changes in Xbp1-S abundance.
Panel D: where is TG at 4h and 6h?
We do not include thapsigargin at later timepoints to avoid autofluorescence from excessive cell death. We include thapsigargin as a positive control at the early 2h timepoint, but note that LPS is sufficient to increase thioflavin T intensity at the 8h timepoint.
Panel G, why was Ddit3 included here as this is not a typical IRE1 dependent gene (rather PERK dependent). What about IRE1 specific genes such as Sec61 or Sec24a?
We have added additional text (lines 235-240; "Finally, we measured induction of UPR-responsive genes by RT-qPCR in response to C. albicans infection, LPS and depleted zymosan treatment, or thapsigargin treatment, to further test whether IRE1α activation occurs without canonical UPR induction (Fig. 2G-H). C. albicans infection and depleted zymosan treatment did not lead to induction of UPR-responsive genes (Ddit3, Grp78, Grp94, and total Xbp1) at 4 or 6 hours.") to clarify that the purpose of this figure is to add evidence that IRE1 activation is independent of the canonical UPR response (indicating that IRE1 is likely specifically activated independently of the other UPR branches) during C. albicans infection. Therefore, the transcripts measured are canonical UPR-responsive transcripts, rather than IRE1/XBP1S targets (although some are overlapping).
Below are RNA-seq data comparing Sec61a1, Sec61a2, and Sec24a in IRE1 null macrophages, compared to IRE1 WT macrophages. While there is less expression of Sec61a1 in IRE1 null macrophages, Sec61a2 and Sec24a are largely unaffected. These data support our finding that XBP1S protein is not induced during C. albicans infection.
Did the authors also check for RIDD activity?
As mentioned above in response to Reviewer 1, we now add additional figures to our supplemental data (Fig. SX; also shown below) showing that established RIDD targets are not depleted during C. albicans infection in WT macrophages, and also not increased in IRE1 null macrophages. Therefore, we expect RIDD activity has negligible effects on our reported phenotypes.
Fig. 3:
Panel C and D look convincing. Lamp1 is a well-known RIDD target gene (see Osorio et al., Nat Imm, 2014). Did the authors check Lamp1 expression in presence and absence of IRE1 and could RIDD explain their phenotype?
As shown above, Lamp1 transcript expression is not strongly perturbed in IRE1 null macrophages. If RIDD activity were depleting Lamp1 transcript abundance, we would expect to see increased Lamp1 expression in IRE1 null macrophages. We also note that our experiments using LysoSensor (Fig. 3E) suggested that lysosome biogenesis is not impaired, but more specifically, lysosome recruitment to the phagosome is impaired in IRE1 null macrophages.
Fig. 4, but especially Fig 5 and Fig 6 suffer from very bad imaging quality. Both Fig 5A and Fig 6A are completely uninterpretable. The SRB staining is all over the cells and it is totally unclear how the authors interpret this as phagosomal leakage or not. Fig. 6A is even worse and appears nothing but vague background. It is difficult to understand how the authors make graphs based on these types of images and dare to draw any conclusions.
In Figure 4, we observe some photobleaching from frequent image acquisition, which is necessary to capture calcium flux dynamics. Image brightness across the timecourse is adjusted in the same way such that we do not attempt to hide the effects of photobleaching. However, our analyses account for photobleaching over time, and the phagosomal calcium flux is clear and quantifiable. `
In Figure 5, the sulforhodamine B pulse-chase assay involves loading of the endosomal system with SRB, thus the cells are expected to ingest a considerable amount of SRB and it will distribute throughout the endosomal network. However, as endosomes fuse, we also observe fusion with the C. albicans-containing phagosome and SRB will surround C. albicans hyphae. Our analysis pipeline first segments C. albicans hyphae (see below) and measures SRB signal in proximity to the phagosome. Thus, we measure loss of phagosome-associated SRB over time, as C. albicans ruptures the phagosome, in hundreds of macrophages. This is a standard assay that has been previously used for this purpose (PMID: 33022213; PMID: 30131363).
For Figure 6, we have added additional wide-field images that we believe will clarify how these images can be readily quantified (Fig. 6A, shown below). The purpose of the previous Fig. 6A (now Fig. 6B) is to demonstrate single cell examples of live and dead C. albicans using the dual-fluorescence assay, although we quantify much wider fields for sufficient numbers. We hope the amended figures provide additional clarity.
Fig. 7 is again an example where differences in expression are mainly due to one or a few complete outliers, and it is hard to understand why the authors did not repeat these experiments to reduce the problems in variation to get proper data sets before submission.
After performing outlier tests, we have found a total of 4 data points that are statistical outliers from all of the panels in Figure 7. These included the highest data point in each genotype in the female IL-1Ra levels (Fig. 7A, second graph), the highest data point among the male IRE1 fl/fl mice IL-1Ra levels (Fig. 7B, second graph), and the highest data point among the male TNF levels in IRE1 fl/fl + LysM-Cre mice (Fig. 7B, third graph). We have removed these data points in our updated graphs and changed the text to only point out differences in serum TNF and IL-6 levels. Moreover, our interpretation includes that serum cytokine levels are not different in male mice. However, no other data points are statistical outliers, therefore we believe their removal is inappropriate.
While the paper started nicely and showed an interesting hypothesis (Fig. 3), the remaining part of the paper was of very poor quality and was not ready for submission.
We thank the reviewer for the constructive feedback and believe that the addition of data and clarifications we have added will demonstrate that our data are of sufficient quality to support our conclusions.
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creativecommons.org creativecommons.org
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Nina Paley’s Sita Sings The Blues, released online a little over two months ago, has been generating great press and even greater viewership, closing in on 70,000 downloads at archive.org alone. For the non-inundated, there is great background information on the film at Paley’s website. We recently had the opportunity to talk with Paley about the film – we touched on the film’s aesthetics and plot points, but perhaps most interesting to those in the CC community is Paley’s decision to utilize our copyleft license, Attribution-ShareAlike, and her thoughts on free licensing and the open source movement in general. Read on to learn more about the licensing trials and tribulations associated with the film’s release, how CC has played a role, and Paley’s opinions on the Free Culture movement as a whole. RamSitaGods, Nina Paley | CC BY-SA One of the major stories surrounding Sita Sings The Blues been your use of songs by musician Annette Hanshaw and the back-and-forth dialogue you have had with the copyright owners as a result. Can you explain why you used these songs? The songs themselves inspired the film. There would be no film without those songs. Until I heard them, the Ramayana was just another ancient Indian epic to me. I was feebly connecting this ancient epic to my own experiences in 2002. But the Hanshaw songs were a revelation: Sita’s story has been told a million times not just in India, not just through the Ramayana, but also through American Blues. Hers is a story so primal, so basic to human experience, it has been told by people who never heard of the Ramayana. The Hanshaw songs deal with exactly the same themes as the epic; but they emerged completely independent of it. Their sound is distinctively 1920’s American, and therein lies their power: the listener/viewer knows I didn’t make them up. They are authentic. They are historical evidence supporting the film’s central point: the story of the Ramayana transcends time, place and culture. What is this story? Sita is a goddess/princess/woman utterly devoted to her husband Rama, the god/prince/man. Sita’s story moves from total enmeshment and romantic joy (Here We Are, What Wouldn’t I Do For That Man) to hopeful longing separation (Daddy Won’t You Please Come Home) to reunion (Who’s That Knockin’ At My Door) to romantic rejection (Mean to Me) to reconciliation (If You Want the Rainbow) to further rejection (Moanin’ Low, Am I Blue) to hopeless longing (Lover Come Back to Me,) back to love – this time self-love (I’ve Got a Feelin’ I’m Fallin’). Sita’s role is to suffer, especially through loving a man who rejects her. Women especially connect emotionally to her story and these emotions are clearly expressed in songs. As Nabaneeta Dev Sen writes in “Lady sings the Blues: When Women retell the Ramayana”: But there are always alternative ways of using a myth. If patriarchy has used the Sita myth to silence women, the village women have picked up the Sita myth to give themselves a voice. They have found a suitable mask in the myth of Sita, a persona through which they can express themselves, speak of their day-to-day problems, and critique patriarchy in their own fashion. Sen is talking about the songs of Indian village women, but she could just as easily been talking about American Blues. That is the point of Sita Sings the Blues: we all struggle with this story, which connects humans through time, space and culture, whether we’re aware of it or not. Just as the Ramayana has mostly been written down and controlled by men, the songs in Sita Sings the Blues were mostly written by men; but sung by a woman – Hanshaw – they pack an emotional wallop and express a woman’s voice. The synchronicity of the Hanshaw songs and Sita’s story is uncanny. This impresses audiences and allows the film’s point to be made: the story of the Ramayana transcends time, place and culture. Because the songs feature an authentic voice from the 1920’s, they demonstrate that this story emerged organically in history. New songs composed by the director, while they could be entertaining, could not make that point. They would be a mere contrivance, whereas the authentic, historical songs give weight to the film’s thesis. They are in fact the basis of the film’s thesis, irrefutable evidence that certain stories – like the story of Sita and Rama – are inherent to human experience. Upon reading the above, Karl Fogel added: Using something that already exists demonstrates that the universality of your theme is external to yourself. Whereas causing something new to exist wouldn’t achieve the same effect. Instead, it would be circular: it would demonstrate that the artist has the ability to make more of what she’s already making. So rather than being connective or expanding, it would be narcissistic (just in a descriptive sense, not necessarily a pejorative one). There has to be a reason so many composers, even non-Catholic ones like Bach, set the Latin Mass to music instead of making up their own words. (Hmm, now imagine if those words had been monopoly-restricted… 🙂 ). What has your experience been in trying to get permission it use Hanshaw’s music in the film, and the current state of affairs? Because distributors were going bankrupt right and left in 2008, it was no longer possible to sell an indie film to a distributor for big money and then “have them take care of” the licenses. Since in February of 2008, when the film premiered in Berlin, I was not yet a Free Culture convert, I thought I needed a conventional distributor. So it fell on me to clear the rights. I had to pay intermediaries to contact the license holders, since they don’t speak to mere riff raff like me; they’re too busy, and under no obligation to do so. Even before that, I needed legal help to research who owned the rights in the first place, since there’s no central copyright registry any more, and rights are traded like baseball cards between corporations. Luckily, I was aided by the student attorneys of the Glushko-Samuelson Intellectual Property Law Clinic of American University. Anyway, in 2008 a lawyer charged me $7,000 to get this response from the licensors: an estimate of $15,000 to $26,000 per song, AFTER I’d paid a $500 per song Festival License. (Festival Licenses last one whole year and require a promise to not make any money showing the film. So a festival license isn’t enough to get the “week-long commercial run” required for Academy Award qualification. Now that “Sita”‘s been broadcast, she will never qualify for an Academy nomination; if I’d really wanted one, I would have had to delayed the release of the film for another year. But I digress.). Even though we made it explicitly clear the entire budget for the film was under $200,000, the licensors came back with the “bargain” estimate of about $220,000. It was simply not possible for me to acquire that kind of money. So legally, my only option was to not show the film or commit civil disobedience. I hired another intermediary, a “rights clearance house” which is less expensive than a lawyer, and they negotiated the “step deal” I eventually signed. This brought the price tag of the licenses down to $50,000, but with many restrictions. If more than 5,000 DVDs (or downloads) are sold, I must pay the licensors more. I wrote about this at length on my website. I borrowed $50,000 to pay these licenses for several reasons. First, to reduce my liability. I may still be sued for releasing the film freely online – after all, the licensors may interpret free sharing as “selling” for zero dollars – but I’ll only be sued for breach of contract, not copyright infringement. Copyright infringement carries much harsher penalties, including possible jail time. I also wanted to make free sharing of “Sita” as legal, and therefore legitimate, as possible. Sharing shouldn’t be the exclusive purview of lawbreakers. Sharing should – and can – be wholesome fun for the whole family. I paid up to indemnify the audience, because the audience is Sita’s main distributor. So it’s now legal to copy and share Sita Sings the Blues. The files went up on Archive.org in early March 2009 and have spread far and wide since. Having paid off the licensors, I could have chosen conventional distribution. But I chose a CC BY-SA license to allow the film to reach a much wider audience; to prohibit the copyrighting – “locking up” – of my art; to give back to the greater culture which gave to me; to exploit the power of the audience to promote and distribute more efficiently than a conventional distributor; and to educate about the dangers of copy restrictions, and the beauty and benefits of sharing. As a result of the trouble you’ve had in regards to Annete Hanshaw’s music, you have turned into a self-proclaimed Free Culture activist. Was this shift gradual? What has that experience in particular informed your views on copyright, fair use, and the public domain? Annette Hanshaw was immensely popular in the late 1920’s. Now almost no one’s heard of her. Why? Because of copy-restrictions. I met many talented filmmakers on my “festival circuit.” Most had conventional distribution deals, but it’s very hard to see any of their films, which had small, brief theatrical runs, and then were never heard from again. Why? Copy-restrictions. I’m an artist. I need money to live, but even more importantly I need my art to reach people. A $10,000 advance in return for having my work locked up for 10 years is a devil’s bargain. More than anything, I wanted people to see my film – now and in years to come. My turning point in choosing a CC license happened in October of 2008. “Sita” had just opened the San Francisco Animation Festival, and I’d disclosed to the audience we’d all just done something illegal. It’s always great to share the film on a big screen in a theater with an audience, and this one was particularly enthusiastic. The next morning I woke up realizing that a free release online wouldn’t in any way prevent theatrical screenings. Why had I never considered that before? Because the film industry insists people won’t go to theaters if they can see a film online. But that’s not true of me, nor many cinephiles. When I lived in San Francisco my favorite movie outings were to classic films at the Catsro: 2001, Nights of Cabiria, Modern Times, Mommy Dearest. These are all available on home video, but I went to the Castro for the big screen and the dark room and the shared experience. If enough people watched and liked “Sita” online, there’d be demand for it in cinemas. And so far that’s proving true. In particular, how have you viewed CC licenses in this whole process? What was your motivation to release Sita Sings the Blues under a CC BY-SA license? Why did you choose that license and not another CC license? What are the obstacles and benefits you’ve seen in using CC licenses? I want my film to reach the widest audience. It costs money to run a theater; it costs money to manufacture DVDs; it costs money to make and distribute 35mm film prints. It’s essential I allow people to make money distributing Sita these ways and others; otherwise, no one will do it. So I eschewed the “non commercial” license. Share Alike would “protect” the work from ever being locked up. It’s better than Public Domain; works are routinely removed from the Public Domain via privatized derivatives (just try making your own Pinocchio). I didn’t want some corporation locking up a play or TV show based on Sita. They are certainly welcome to make derivative works, and make money from them; in fact I encourage this. But they may not sue or punish anyone for sharing those works. I looked to the Free Software movement as a model. The CC BY-SA license most closely resembles the GNU GPL, which is the foundation of Free Software. People make plenty of money in Free Software; there’s no reason they can’t do the same in Free Culture, except for those pernicious “non commercial” licenses. A Share Alike license eliminates the corporate abuse everyone’s so afraid of, while it encourages entrepreneurship and innovation. Everyone wins, especially the artist! What else would you like our reader’s to know? Any plans for the future? I’d love you all to read my essay Understanding Free Content and of course watch the film! I’m currently busy making “containers” like DVDs and T shirts available now at our e-store. QuestionCopyright is my main partner in releasing Sita; we’re trying to prove a model in which freedom and revenue work together. We know other filmmakers are watching what happens to Sita, and we’d like to show that yes, you can make money without impinging on everyone else’s freedom. I’m also negotiating with theatrical distributors in France and Switzerland, as well as a couple book publishers. I’m negotiating not “rights” to the film, which belong to everyone already, but rather my Endorsement and assistance. To understand how this works, please read about the Creator Endorsed Mark. Once I have the Sita Sings the Blues Merchandise Empire started, I hope to work on short musical cartoons about free speech – you can hear one of the songs here. There’s more where that came from. Really, I have more ideas than I have time to implement them – a happy yet vexing problem. I also hope to have all my old Nina’s Adventures and Fluff syndicated comic strips scanned and uploaded at high resolution onto archive.org under a CC BY-SA license. The University of Illinois Library is currently seeking funding to move ahead on this project – interested individuals should contact Betsy Kruger. Lastly, I’m still looking for money, although the Sita Sings the Blues Merchandise Empire should be generating some in a few months. Still, I plan to apply for grants and fellowships. Any foundations with too much money burning a hole in your accounts, please get in touch.
In this text, it dives into how Ramayana as a text is so universal that any set of tunes or music can match it. For example, this text looks into how the music from Annette Hanshaw from the 1920's are able to blend into the Indian epic showing its versatility. One challenge that readers might resonate to is the copyright issues that Paley faced in order to have permission to use Hanshaw's music since there were many legal problems and a bunch of fees. Because of this struggle, it highlights why it can be difficult to use certain words in conjunction with other pieces which might explain why we might not see the types of works that we would like. Even looking at the copyright license that Paley chose for her own film, she chose the one that would allow her to reach a larger group of people because her goal is not to make money but to appreciate art for what it is and to share that with other people. The copyright restrictions that are discussed in this text can be eye-opening for a lot of readers as they can see why creativity might be hindered in a lot of fields and this can help explain why. In this text, the concepts of culture and national identity are closely related to the idea of self. This can be seen in Ramayana as its themes are universal and the ability for it to mesh well with the American Blues songs is proof of that. Not to mention, this is an example that serves to show that cultures can blend together in which a person's self can be a multitude of different aspects reflecting in how modern nation-building does not just rely on one perspective or facet, but it can have many different facets allowing that identity to be fluid as a result. The Indians relating to Ramayana may see themselves as "us" because they resonate to that Indian epic while "them" represents those who know more about the American Blues or western culture in general. With this being said, this contrast in cultures being able to blend and mesh well together show how there is shared human experiences across cultures. There is no sense of otherness in Paley's work because she is able to show how the themes in Ramayana are universal and can be applied to all time periods and all locations. Even though the argument is that Ramayana is universal and can blend with any music types, the choice of American Blues is compelling by Paley and this intention was because she may have wanted to see how English lyrics can mesh with Sanskrit language as a challenge and this weird combination can prove that it would work with all music types as a result. Because of this contrast, it speaks to the power of linguistic authenticity as it is able to prove the themes behind the film and put them into action. The difficulty that Paley faced with copyright laws help explain why people cannot be as creative as they want and why free sharing should exist. As a result, Paley allows her work to be easily more accessed which can be seen in her creative commons license and shows that she backs up the same claim from her own film as well. It shows why artists and all people should move away from exclusive ownership and should embrace a more collaborative model in which all people can contribute and take inspirations from each other in positive ways. CC BY Ajey Sasimugunthan (contact)
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www.biorxiv.org www.biorxiv.org
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Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
This is an interesting study investigating the mechanisms underlying membrane targeting of the NLRP3 inflammasome and reporting a key role for the palmitoylation-depalmitoylation cycle of cys130 in NRLP3. The authors identify ZDHHC3 and APT2 as the specific ZDHHC and APT/ABHD enzymes that are responsible for the s-acylation and de-acylation of NLRP3, respectively. They show that the levels of ZDHHC3 and APT2, both localized at the Golgi, control the level of palmitoylation of NLRP3. The S-acylation-mediated membrane targeting of NLRP3 cooperates with polybasic domain (PBD)-mediated PI4P-binding to target NLRP3 to the TGN under steady-state conditions and to the disassembled TGN induced by the NLRP3 activator nigericin.
However, the study has several weaknesses in its current form as outlined below.
(1) The novelty of the findings concerning cys130 palmitoylation in NLRP3 is unfortunately compromised by recent reports on the acylation of different cysteines in NLRP3 (PMID: 38092000), including palmitoylation of the very same cys130 in NLRP3 (Yu et al https://doi.org/10.1101/2023.11.07.566005), which was shown to be relevant for NLRP3 activation in cell and animal models. What remains novel and intriguing is the finding that NLRP3 activators induce an imbalance in the acylation-deacylation cycle by segregating NLRP3 in late Golgi/endosomes from de-acylating enzymes confined in the Golgi. The interesting hypothesis put forward by the authors is that the increased palmitoylation of cys130 would finally contribute to the activation of NLRP3. However, the authors should clarify the trafficking pathway of acylated-NLRP3. This pathway should, in principle, coincide with that of TGN46 which constitutively recycles from the TGN to the plasma membrane and is trapped in endosomes upon treatment with nigericin.
We think the data presented in our manuscript are consistent with the majority of S-acylated NLRP3 remaining on the Golgi via S-acylation in both untreated and nigericin treated cells. We have performed an experiment with BrefeldinA (BFA), a fungal metabolite that disassembles the Golgi without causing dissolution of early endosomes, that further supports the conclusion that NLRP3 predominantly resides on Golgi membranes pre and post activation. Treatment of cells with BFA prevents recruitment of NLRP3 to the Golgi in untreated cells and blocks the accumulation of NLRP3 on the structures seen in the perinuclear area after nigericin treatment (see new Supplementary Figure 4A-D). We do see some overlap of NLRP3 signal with TGN46 in the perinuclear area after nigericin treatment (see new Supplementary Figure 2E), however this likely represents TGN46 at the Golgi rather than endosomes given that the NLRP3 signal in this area is BFA sensitive. As with 2-BP and GFP-NLRP3C130S, GFP-NLRP3 spots also form in BFA / nigericin co-treated cells but not with untagged NLRP3. These spots also do not show any co-localisation with EEA1, suggesting that under these conditions, endosomes don’t appear to represent a secondary site of NLRP3 recruitment in the absence of an intact Golgi. However, we cannot completely rule out that some NLRP3 may recruited to endosomes at some point during its activation.
(2) To affect the S-acylation, the authors used 16 hrs treatment with 2-bromopalmitate (2BP). In Figure 1f, it is quite clear that NLRP3 in 2-BP treated cells completely redistributed in spots dispersed throughout the cells upon nigericin treatment. What is the Golgi like in those cells? In other words, does 2-BP alter/affect Golgi morphology? What about PI4P levels after 2-BP treatment? These are important missing pieces of data since both the localization of many proteins and the activity of one key PI4K in the Golgi (i.e. PI4KIIalpha) are regulated by palmitoylation.
We thank the reviewer for highlighting this point and agree that it is possible the observed loss of NLRP3 from the Golgi might be due to an adverse effect of 2-BP on Golgi morphology or PI4P levels. We have tested the effect of 2-BP on the Golgi markers GM130, p230 and TGN46. 2BP has marginal effects on Golgi morphology with cis, trans and TGN markers all present at similar levels to untreated control cells (Supplementary Figure 2B-D). We also tested the effect of 2-BP on PI4P levels using mCherry-P4M, a PI4P biosensor. Surprisingly, as noted by the reviewer, despite recruitment of PI4K2A being dependent on S-acylation, PI4P was still present on the Golgi after 2-BP treatment, suggesting that a reduction in Golgi PI4P levels does not underly loss of NLRP3 from the Golgi (Supplementary Figure 2A). The pool of PI4P still present on the Golgi following 2-BP treatment is likely generated by other PI4K enzymes that localise to the Golgi independently of S-acylation, such as PI4KIIIB. We have included this data in our manuscript as part of a new Supplementary Figure 2.
(3) The authors argue that the spots observed with NLRP-GFP result from non-specific effects mediated by the addition of the GFP tag to the NLRP3 protein. However, puncta are visible upon nigericin treatment, as a hallmark of endosomal activation. How do the authors reconcile these data? Along the same lines, the NLRP3-C130S mutant behaves similarly to wt NLRP3 upon 2-BP treatment (Figure 1h). Are those NLRP3-C130S puncta positive for endosomal markers? Are they still positive for TGN46? Are they positive for PI4P?
This is a fair point given the literature showing overlap of NLRP3 puncta formed in response to nigericin with endosomal markers and the similarity of the structures we see in terms of size and distribution to endosomes after 2BP + nigericin treatment. We have tested whether these puncta overlap with EEA1, TGN46 or PI4P (Supplementary Figure 2A, E-G). The vast majority of spots formed by GFP-NLRP3 co-treated with 2-BP and nigericin do not co-localise with EEA1, TGN46 or PI4P. This is consistent with these spots potentially being an artifact, although it has recently been shown that human NLRP3 unable to bind to the Golgi can still respond to nigericin (Mateo-Tórtola et al., 2023). These puncta might represent a conformational change cytosolic NLRP3 undergoes in response to stimulation, although our results suggest that this doesn’t appear to happen on endosomes.
(4) The authors expressed the minimal NLRP3 region to identify the domain required for NLRP3 Golgi localization. These experiments were performed in control cells. It might be informative to perform the same experiments upon nigericin treatment to investigate the ability of NLRP3 to recognize activating signals. It has been reported that PI4P increases on Golgi and endosomes upon NG treatment. Hence, all the differences between the domains may be lost or preserved. In parallel, also the timing of such recruitment upon nigericin treatment (early or late event) may be informative for the dynamics of the process and of the contribution of the single protein domains.
This is an interesting point which we thank the reviewer for highlighting. However, we think that each domain on its own is not capable of responding to nigericin as shown by the effect of mutations in helix115-125 or the PB region in the full-length NLRP3 protein. NLRP3HF, which still contains a functional PB region, isn’t capable of responding to nigericin in the same way as wild type NLRP3 (Supplementary Figure 6C-D). Similarly, mutations in the PB region of full length NLRP3 that leave helix115-125 intact show that helix115-125 is not sufficient to allow enhanced recruitment of NLRP3 to Golgi membranes after nigericin treatment (Supplementary Figure 9A). We speculate that helix115-125, the PB region and the LRR domain all need to be present to provide maximum affinity of NLRP3 for the Golgi prior to encounter with and S-acylation by ZDHHC3/7. Mutation or loss of any one of the PB region, helix115-125 or the LRR lowers NLRP3 membrane affinity, which is reflected by reduced levels of NLRP3 captured on the Golgi by S-acylation at steady state and in response to nigericin.
(5) As noted above for the chemical inhibitors (1) the authors should check the impact of altering the balance between acyl transferase and de-acylases on the Golgi organization and PI4P levels. What is the effect of overexpressing PATs on Golgi functions?
We have checked the effect of APT2 overexpression on Golgi morphology and can show that it has no noticeable effect, ruling out an impact of APT on Golgi integrity as the reason for loss of NLRP3 from the Golgi in the presence of overexpressed APT2. We have included these images as Supplementary Figure 11H-J.
It is plausible that the effects of ZDHHC3 or ZDHHC7 on enhanced recruitment of NLRP3 to the Golgi may be via an effect on PI4P levels since, as mentioned above, both enzymes are involved in recruitment of PI4K2A to the Golgi and have previously been shown to enhance levels of PI4K2A and PI4P on the Golgi when overexpressed (Kutchukian et al., 2021). However, NLRP3 mutants with most of the charge removed from the PB region, which are presumably unable to interact with PI4P or other negatively charged lipids, are still capable of being recruited to the Golgi by excess ZDHHC3. This would suggest that the effect of overexpressed ZDHHC3 on NLRP3 is largely independent of changes in PI4P levels on the Golgi and instead driven by helix115-125 and S-acylation at Cys-130. The latter point is supported by the observation that NLRP3HF and NLRP3Cys130 are insensitive to ZDHHC3 overexpression.
At the levels of HA-ZDHHC3 used in our experiments with NLRP3 (200ng pEF-Bos-HAZDHHC3 / c.a. 180,000 cells) we don’t see any adverse effect on Golgi morphology (Author response image 1), although it has been noted previously by others that higher levels of ZDHHC3 can have an impact on TGN46 (Ernst et al., 2018). ZDHHC3 overexpression surprisingly has no adverse effects on Golgi function and in fact enhances secretion from the Golgi (Ernst et al., 2018).
Author response image 1.
Overexpression of HA-ZDHHC3 does not impact Golgi morphology. A) Representative confocal micrographs of HeLaM cells transfected with 200 ng HA-ZDHHC3 fixed and stained with antibodies to STX5 or TGN46. Scale bars = 10 µm.
Reviewer #2 (Public Review):
Summary:
This paper examines the recruitment of the inflammasome seeding pattern recognition receptor NLRP3 to the Golgi. Previously, electrostatic interactions between the polybasic region of NLRP3 and negatively charged lipids were implicated in membrane association. The current study reports that reversible S-acylation of the conserved Cys-130 residue, in conjunction with upstream hydrophobic residues plus the polybasic region, act together to promote Golgi localization of NLRP3, although additional parts of the protein are needed for full Golgi localization. Treatment with the bacterial ionophore nigericin inhibits membrane traffic and prevents Golgi-associated thioesterases from removing the acyl chain, causing NLRP3 to become immobilized at the Golgi. This mechanism is put forth as an explanation for how NLRP3 is activated in response to nigericin.
Strengths:
The experiments are generally well presented. It seems likely that Cys-130 does indeed play a previously unappreciated role in the membrane association of NLRP3.
Weaknesses:
The interpretations about the effects of nigericin are less convincing. Specific comments follow.
(1) The experiments of Figure 4 bring into question whether Cys-130 is S-acylated. For Cys130, S-acylation was seen only upon expression of a severely truncated piece of the protein in conjunction with overexpression of ZDHHC3. How do the authors reconcile this result with the rest of the story?
Providing direct evidence of S-acylation at Cys-130 in the full-length protein proved difficult. We attempted to detect S-acylation of this residue by mass spectrometry. However, the presence of the PB region and multiple lysines / arginines directly after Cys-130 made this approach technically challenging and we were unable to convincingly detect S-acylation at Cys-130 by M/S. However, Cys-130 is clearly important for membrane recruitment as its mutation abolishes the localisation of NLRP3 to the Golgi. It is feasible that it is the hydrophobic nature of the cysteine residue itself which supports localisation to the Golgi, rather than S-acylation of Cys-130. A similar role for cysteine residues present in SNAP-25 has been reported (Greaves et al., 2009). However, the rest of our data are consistent with Cys-130 in NLRP3 being S-acylated. We also refer to another recently published study which provides additional biochemical evidence that mutation of Cys-130 impacts the overall levels of NLRP3 S-acylation (Yu et al., 2024).
(2) Nigericin seems to cause fragmentation and vesiculation of the Golgi. That effect complicates the interpretations. For example, the FRAP experiment of Figure 5 is problematic because the authors neglected to show that the FRAP recovery kinetics of nonacylated resident Golgi proteins are unaffected by nigericin. Similarly, the colocalization analysis in Figure 6 is less than persuasive when considering that nigericin significantly alters Golgi structure and could indirectly affect colocalization.
We agree that it is likely that the behaviour of other Golgi resident proteins are altered by nigericin. This is in line with a recent proteomics study showing that nigericin alters the amount of Golgi resident proteins associated with the Golgi (Hollingsworth et al., 2024) and other work demonstrating that changes in organelle pH can influence the membrane on / off rates of Rab GTPases (Maxson et al., 2023). However, Golgi levels of other peripheral membrane proteins
that associate with the Golgi through S-acylation, such as N-Ras, appear unaltered (Author response image 2.), indicating a degree of selectivity in the proteins affected. Our main point here is that NLRP3 is amongst those proteins whose behaviour on the Golgi is sensitive to nigericin and that this change in behaviour may be important to the NLRP3 activation process, although this requires further investigation and will form the basis of future studies.
The reduction in co-localisation between NLRP3 and APT2, due to alterations in Golgi organisation and trafficking, was the point we were trying to make with this figure, and we apologise if this was not clear. We think that the changes in Golgi structure and function caused by nigericin potentially affect the ability of APT2 to encounter NLRP3 and de-acylate it. We have added a new paragraph to the results section to hopefully explain this more clearly. We recognise that our results supporting this hypothesis are at present limited and we have toned down the language used in the results section to reflect the nature of these findings..
Author response image 2.
S-acylated peripheral membrane proteins show differential sensitivity to nigericin. A) Representative confocal micrographs of HeLaM cells coexpressing GFP-NRas and an untagged NLRP3 construct. Cells were left untreated or treated with 10 µM nigericin for 1 hour prior to fixation. Scale bars = 10 µm. B) Quantification of GFP-NRas or NLRP3 signal in the perinuclear region of cells treated with or without nigericin
Recommendations for the authors:
Reviewer #2 (Recommendations For The Authors):
(1) Does overnight 2-BP treatment potentially have indirect effects that could prevent NLRP3 recruitment? It would be useful here to show some sort of control confirming that the cells are not broadly perturbed.
Please see our response to point (2) raised by reviewer #1 which is along similar lines.
(2) In Figure 5, "Veh" presumably is short for "Vehicle". This term should be defined in the legend.
We have now corrected this.
References
Ernst, A.M., S.A. Syed, O. Zaki, F. Bottanelli, H. Zheng, M. Hacke, Z. Xi, F. Rivera-Molina, M. Graham, A.A. Rebane, P. Bjorkholm, D. Baddeley, D. Toomre, F. Pincet, and J.E. Rothman. 2018. SPalmitoylation Sorts Membrane Cargo for Anterograde Transport in the Golgi. Dev Cell. 47:479-493 e477.
Greaves, J., G.R. Prescott, Y. Fukata, M. Fukata, C. Salaun, and L.H. Chamberlain. 2009. The hydrophobic cysteine-rich domain of SNAP25 couples with downstream residues to mediate membrane interactions and recognition by DHHC palmitoyl transferases. Mol Biol Cell. 20:1845-1854.
Hollingsworth, L.R., P. Veeraraghavan, J.A. Paulo, J.W. Harper, and I. Rauch. 2024. Spatiotemporal proteomic profiling of cellular responses to NLRP3 agonists. bioRxiv.
Kutchukian, C., O. Vivas, M. Casas, J.G. Jones, S.A. Tiscione, S. Simo, D.S. Ory, R.E. Dixon, and E.J. Dickson. 2021. NPC1 regulates the distribution of phosphatidylinositol 4-kinases at Golgi and lysosomal membranes. EMBO J. 40:e105990.
Mateo-Tórtola, M., I.V. Hochheiser, J. Grga, J.S. Mueller, M. Geyer, A.N.R. Weber, and A. TapiaAbellán. 2023. Non-decameric NLRP3 forms an MTOC-independent inflammasome. bioRxiv:2023.2007.2007.548075.
Maxson, M.E., K.K. Huynh, and S. Grinstein. 2023. Endocytosis is regulated through the pHdependent phosphorylation of Rab GTPases by Parkinson’s kinase LRRK2. bioRxiv:2023.2002.2015.528749.
Yu, T., D. Hou, J. Zhao, X. Lu, W.K. Greentree, Q. Zhao, M. Yang, D.G. Conde, M.E. Linder, and H. Lin. 2024. NLRP3 Cys126 palmitoylation by ZDHHC7 promotes inflammasome activation. Cell Rep. 43:114070.
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Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
In this manuscript, the authors investigate the contributions of the long noncoding RNA snhg3 in liver metabolism and MAFLD. The authors conclude that liver-specific loss or overexpression of Snhg3 impacts hepatic lipid content and obesity through epigenetic mechanisms. More specifically, the authors invoke that the nuclear activity of Snhg3 aggravates hepatic steatosis by altering the balance of activating and repressive chromatin marks at the Pparg gene locus. This regulatory circuit is dependent on a transcriptional regulator SND1.
Strengths:
The authors developed a tissue-specific lncRNA knockout and KI models. This effort is certainly appreciated as few lncRNA knockouts have been generated in the context of metabolism. Furthermore, lncRNA effects can be compensated in a whole organism or show subtle effects in acute versus chronic perturbation, rendering the focus on in vivo function important and highly relevant. In addition, Snhg3 was identified through a screening strategy and as a general rule the authors the authors attempt to follow unbiased approaches to decipher the mechanisms of Snhg3.
Weaknesses:
Despite efforts at generating a liver-specific knockout, the phenotypic characterization is not focused on the key readouts. Notably missing are rigorous lipid flux studies and targeted gene expression/protein measurement that would underpin why the loss of Snhg3 protects from lipid accumulation. Along those lines, claims linking the Snhg3 to MAFLD would be better supported with careful interrogation of markers of fibrosis and advanced liver disease. In other areas, significance is limited since the presented data is either not clear or rigorous enough. Finally, there is an important conceptual limitation to the work since PPARG is not established to play a major role in the liver.
We thank the reviewer for the detailed comment. In this study, hepatocyte-specific Snhg3 deficiency decreased body and liver weight and alleviated hepatic steatosis in DIO mice, whereas overexpression induced the opposite effect (Figure 2 and 3). Furthermore, we investigated the hepatic differentially expressed genes (DEGs) between the DIO Snhg3-HKI and control WT mice using RNA-Seq and revealed that Snhg3 exerts a global effect on the expression of genes involved in fatty acid metabolism using GSEA (Figure 4B). We validated the expression of some DEGs involved in fatty acid metabolism by RT-qPCR. The results showed that the hepatic expression levels of some genes involved in fatty acid metabolism, including Cd36, Cidea/c and Scd1/2 were upregulated in Snhg3-HKO mice and were downregulated in Snhg3-HKI mice compared to the controls (Figure 4C), respectively. Please check them in the first paragraph in p8.
As a transcription regulator of Cd36 and Cidea/c, it is well known that PPARγ plays major adipogenic and lipogenic roles in adipose tissue. Although the expression of PPARγ in the liver is very low under healthy conditions, induced expression of PPARγ in both hepatocytes and non-parenchymal cells (Kupffer cells, immune cells, and HSCs) in the liver has a crucial role in the pathophysiology of MASLD (Lee et al., 2023b, Chen et al., 2023, Gross et al., 2017). The activation of PPARγ in the liver induces the adipogenic program to store fatty acids in lipid droplets as observed in adipocytes (Lee et al., 2018). Moreover, the inactivation of liver PPARγ abolished rosiglitazone-induced an increase in hepatic TG and improved hepatic steatosis in lipoatrophic AZIP mice (Gavrilova et al., 2003). Furthermore, there is a strong correlation between the onset of hepatic steatosis and hepatocyte-specific PPARγ expression. Clinical trials have also indicated that increased insulin resistance and hepatic PPARγ expressions were associated with NASH scores in some obese patients (Lee et al., 2023a, Mukherjee et al., 2022). Even though PPARγ’s primary function is in adipose tissue, patients with MASLD have much higher hepatic expression levels of PPARγ, reflecting the fact that PPARγ plays different roles in different tissues and cell types (Mukherjee et al., 2022). As these studies mentioned above, our result also hinted at the importance of PPARγ in the pathophysiology of MASLD. Snhg3 deficiency or overexpression respectively induced the decrease or increase in hepatic PPARγ. Moreover, administration of PPARγ antagonist T0070907 mitigated the hepatic Cd36 and Cidea/c increase and improved Snhg3-induced hepatic steatosis. However, conflicting findings suggest that the expression of hepatic PPARγ is not increased as steatosis develops in humans and in clinical studies and that PPARγ agonists administration didn’t aggravate liver steatosis (Gross et al., 2017). Thus, understanding how the hepatic PPARγ expression is regulated may provide a new avenue to prevent and treat the MASLD (Lee et al., 2018). We also discussed it in revised manuscript, please refer the first paragraph in the section of Discussion in p13.
Hepatotoxicity accelerates the development of progressive inflammation, oxidative stress and fibrosis (Roehlen et al., 2020). Chronic liver injury including MASLD can progress to liver fibrosis with the formation of a fibrous scar. Injured hepatocytes can secrete fibrogenic factors or exosomes containing miRNAs that activate HSCs, the major source of the fibrous scar in liver fibrosis (Kisseleva and Brenner, 2021). Apart from promoting lipogenesis, PPARγ has also a crucial function in improving inflammation and fibrosis (Chen et al., 2023). In this study, no hepatic fibrosis phenotype was seen in Snhg3-HKO and Snhg3-HKI mice (figures supplement 1D and 2D). Moreover, deficiency and overexpression of Snhg3 respectively decreased and increased the expression of profibrotic genes, such as collagen type I alpha 1/2 (Col1a1 and Col1a2), but had no effects on the pro-inflammatory factors, including transforming growth factor β1 (Tgfβ1), tumor necrosis factor α (Tnfα), interleukin 6 and 1β (Il6 and Il1β) (figures supplement 3A and B). Inflammation is an absolute requirement for fibrosis because factors from injured hepatocytes alone are not sufficient to directly activate HSCs and lead to fibrosis (Kisseleva and Brenner, 2021). Additionally, previous studies indicated that exposure to HFD for more 24 weeks causes less severe fibrosis (Alshawsh et al., 2022). In future, the effect of Snhg3 on hepatic fibrosis in mice need to be elucidated by prolonged high-fat feeding or by adopting methionine- and choline deficient diet (MCD) feeding. Please check them in the second paragraph in the section of Discussion in p13.
References
ALSHAWSH, M. A., ALSALAHI, A., ALSHEHADE, S. A., SAGHIR, S. A. M., AHMEDA, A. F., AL ZARZOUR, R. H. & MAHMOUD, A. M. 2022. A Comparison of the Gene Expression Profiles of Non-Alcoholic Fatty Liver Disease between Animal Models of a High-Fat Diet and Methionine-Choline-Deficient Diet. Molecules, 27. DIO:10.3390/molecules27030858, PMID:35164140
CHEN, H., TAN, H., WAN, J., ZENG, Y., WANG, J., WANG, H. & LU, X. 2023. PPAR-gamma signaling in nonalcoholic fatty liver disease: Pathogenesis and therapeutic targets. Pharmacol Ther, 245, 108391. DIO:10.1016/j.pharmthera.2023.108391, PMID:36963510
GAVRILOVA, O., HALUZIK, M., MATSUSUE, K., CUTSON, J. J., JOHNSON, L., DIETZ, K. R., NICOL, C. J., VINSON, C., GONZALEZ, F. J. & REITMAN, M. L. 2003. Liver peroxisome proliferator-activated receptor gamma contributes to hepatic steatosis, triglyceride clearance, and regulation of body fat mass. J Biol Chem, 278, 34268-76. DIO:10.1074/jbc.M300043200, PMID:12805374
GROSS, B., PAWLAK, M., LEFEBVRE, P. & STAELS, B. 2017. PPARs in obesity-induced T2DM, dyslipidaemia and NAFLD. Nat Rev Endocrinol, 13, 36-49. DIO:10.1038/nrendo.2016.135, PMID:27636730
KISSELEVA, T. & BRENNER, D. 2021. Molecular and cellular mechanisms of liver fibrosis and its regression. Nat Rev Gastroenterol Hepatol, 18, 151-166. DIO:10.1038/s41575-020-00372-7, PMID:33128017
LEE, S. M., MURATALLA, J., KARIMI, S., DIAZ-RUIZ, A., FRUTOS, M. D., GUZMAN, G., RAMOS-MOLINA, B. & CORDOBA-CHACON, J. 2023a. Hepatocyte PPARgamma contributes to the progression of non-alcoholic steatohepatitis in male and female obese mice. Cell Mol Life Sci, 80, 39. DIO:10.1007/s00018-022-04629-z, PMID:36629912
LEE, S. M., MURATALLA, J., SIERRA-CRUZ, M. & CORDOBA-CHACON, J. 2023b. Role of hepatic peroxisome proliferator-activated receptor gamma in non-alcoholic fatty liver disease. J Endocrinol, 257. DIO:10.1530/JOE-22-0155, PMID:36688873
LEE, Y. K., PARK, J. E., LEE, M. & HARDWICK, J. P. 2018. Hepatic lipid homeostasis by peroxisome proliferator-activated receptor gamma 2. Liver Res, 2, 209-215. DIO:10.1016/j.livres.2018.12.001, PMID:31245168
MUKHERJEE, A. G., WANJARI, U. R., GOPALAKRISHNAN, A. V., KATTURAJAN, R., KANNAMPUZHA, S., MURALI, R., NAMACHIVAYAM, A., GANESAN, R., RENU, K., DEY, A., VELLINGIRI, B. & PRINCE, S. E. 2022. Exploring the Regulatory Role of ncRNA in NAFLD: A Particular Focus on PPARs. Cells, 11. DIO:10.3390/cells11243959, PMID:36552725
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Reviewer #2 (Public Review):
Through RNA analysis, Xie et al found LncRNA Snhg3 was one of the most down-regulated Snhgs by a high-fat diet (HFD) in mouse liver. Consequently, the authors sought to examine the mechanism through which Snhg3 is involved in the progression of metabolic dysfunction-associated fatty liver diseases (MASLD) in HFD-induced obese (DIO) mice. Interestingly, liver-specific Snhg3 knockout was reduced, while Snhg3 over-expression potentiated fatty liver in mice on an HFD. Using the RNA pull-down approach, the authors identified SND1 as a potential Sngh3 interacting protein. SND1 is a component of the RNA-induced silencing complex (RISC). The authors found that Sngh3 increased SND1 ubiquitination to enhance SND1 protein stability, which then reduced the level of repressive chromatin H3K27me3 on PPARg promoter. The upregulation of PPARg, a lipogenic transcription factor, thus contributed to hepatic fat accumulation.
The authors propose a signaling cascade that explains how LncRNA sngh3 may promote hepatic steatosis. Multiple molecular approaches have been employed to identify molecular targets of the proposed mechanism, which is a strength of the study. There are, however, several potential issues to consider before jumping to a conclusion.
(1) First of all, it's important to ensure the robustness and rigor of each study. The manuscript was not carefully put together. The image qualities for several figures were poor, making it difficult for the readers to evaluate the results with confidence. The biological replicates and numbers of experimental repeats for cell-based assays were not described. When possible, the entire immunoblot imaging used for quantification should be presented (rather than showing n=1 representative). There were multiple mislabels in figure panels or figure legends (e.g., Figure 2I, Figure 2K, and Figure 3K). The b-actin immunoblot image was reused in Figure 4J, Figure 5G, and Figure 7B with different exposure times. These might be from the same cohort of mice. If the immunoblots were run at different times, the loading control should be included on the same blot as well.
We thank the reviewer for the detailed comment. We have provided the clear figures in revised manuscript, please check them.
The biological replicates and numbers of experimental repeats for cell-based assays had been updated and please check them in the manuscript.
The entire immunoblot imaging used for quantification had been provided in the primary data. Please check them.
The original Figure 2I, Figure 2K, Figure 3K have been revised and replaced with new Figure 2F, Figure 2H, Figure 3H, and their corresponding figure legends has also been corrected in revised manuscript.
The protein levels of CD36, PPARγ and β-ACTIN were examined at the same time and we had revised the manuscript, please check them in revised Figure 7B and 7C.
(2) The authors can do a better job in explaining the logic for how they came up with the potential function of each component of the signaling cascade. Snhg3 is down-regulated by HFD. However, the evidence presented indicates its involvement in promoting steatosis. In Figure 1C, one would expect PPARg expression to be up-regulated (when Sngh3 was down-regulated). If so, the physiological observation conflicts with the proposed mechanism. In addition, SND1 is known to regulate RNA/miRNA processing. How do the authors rule out this potential mechanism? How about the hosting snoRNA, Snord17? Does it involve the progression of NASLD?
We thank the reviewer for the detailed comment. Our results showed that the expression of Snhg3 was decreased in DIO mice which led us to speculate that the downregulation of Snhg3 in DIO mice might be a stress protective reaction to high nutritional state, but the specific details need to be clarified. This is probably similar to fibroblast growth factor 21 (FGF21) and growth differentiation factor 15 (GDF15), whose endogenous expression and circulating levels are elevated in obese humans and mice despite their beneficial effects on obesity and related metabolic complications (Keipert and Ost, 2021). Although FGF21 can be induced by oxidative stress and be activated in obese mice and in NASH patients, elevated FGF21 paradoxically protects against oxidative stress and reduces hepatic steatosis (Tillman and Rolph, 2020). We had added the content the section of Discussion, please check it in the second paragraph in p12.
SND1 has multiple roles through associating with different types of RNA molecules, including mRNA, miRNA, circRNA, dsRNA and lncRNA. SND1 could bind negative-sense SARS-CoV-2 RNA and promoted viral RNA synthesis, and to promote viral RNA synthesis (Schmidt et al., 2023). SND1 is also involved in hypoxia by negatively regulating hypoxia‐related miRNAs (Saarikettu et al., 2023). Furthermore, a recent study revealed that lncRNA SNAI3-AS1 can competitively bind to SND1 and perturb the m6A-dependent recognition of Nrf2 mRNA 3'UTR by SND1, thereby reducing the mRNA stability of Nrf2 (Zheng et al., 2023). Huang et al. also reported that circMETTL9 can directly bind to and increase the expression of SND1 in astrocytes, leading to enhanced neuroinflammation (Huang et al., 2023). However, whether there is an independent-histone methylation role of SND1/lncRNA-Snhg3 involved in lipid metabolism in the liver needs to be further investigated. We also discussed the limitation in the manuscript and please refer the section of Discussion in the third paragraph in p17.
Snhg3 serves as host gene for producing intronic U17 snoRNAs, the H/ACA snoRNA. A previous study found that cholesterol trafficking phenotype was not due to reduced Snhg3 expression, but rather to haploinsufficiency of U17 snoRNA. Upregulation of hypoxia-upregulated mitochondrial movement regulator (HUMMR) in U17 snoRNA-deficient cells promoted the formation of ER-mitochondrial contacts, resulting in decreasing cholesterol esterification and facilitating cholesterol trafficking to mitochondria (Jinn et al., 2015). Additionally, disruption of U17 snoRNA caused resistance to lipid-induced cell death and general oxidative stress in cultured cells. Furthermore, knockdown of U17 snoRNA in vivo protected against hepatic steatosis and lipid-induced oxidative stress and inflammation (Sletten et al., 2021). We determined the expression of hepatic U17 snoRNA and its effect on SND1 and PPARγ. The results showed that the expression of U17 snoRNA decreased in the liver of DIO Snhg3-HKO mice and unchanged in the liver of DIO Snhg3-HKI mice, but overexpression of U17 snoRNA had no effect on the expression of SND1 and PPARγ (figure supplement 5A-C), indicating that Sngh3 induced hepatic steatosis was independent on U17 snoRNA. We also discussed it in revised manuscript, please refer the section of Discussion in p15.
References
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JINN, S., BRANDIS, K. A., REN, A., CHACKO, A., DUDLEY-RUCKER, N., GALE, S. E., SIDHU, R., FUJIWARA, H., JIANG, H., OLSEN, B. N., SCHAFFER, J. E. & ORY, D. S. 2015. snoRNA U17 regulates cellular cholesterol trafficking. Cell Metab, 21, 855-67. DIO:10.1016/j.cmet.2015.04.010, PMID:25980348
KEIPERT, S. & OST, M. 2021. Stress-induced FGF21 and GDF15 in obesity and obesity resistance. Trends Endocrinol Metab, 32, 904-915. DIO:10.1016/j.tem.2021.08.008, PMID:34526227
SAARIKETTU, J., LEHMUSVAARA, S., PESU, M., JUNTTILA, I., PARTANEN, J., SIPILA, P., POUTANEN, M., YANG, J., HAIKARAINEN, T. & SILVENNOINEN, O. 2023. The RNA-binding protein Snd1/Tudor-SN regulates hypoxia-responsive gene expression. FASEB Bioadv, 5, 183-198. DIO:10.1096/fba.2022-00115, PMID:37151849
SCHMIDT, N., GANSKIH, S., WEI, Y., GABEL, A., ZIELINSKI, S., KESHISHIAN, H., LAREAU, C. A., ZIMMERMANN, L., MAKROCZYOVA, J., PEARCE, C., KREY, K., HENNIG, T., STEGMAIER, S., MOYON, L., HORLACHER, M., WERNER, S., AYDIN, J., OLGUIN-NAVA, M., POTABATTULA, R., KIBE, A., DOLKEN, L., SMYTH, R. P., CALISKAN, N., MARSICO, A., KREMPL, C., BODEM, J., PICHLMAIR, A., CARR, S. A., CHLANDA, P., ERHARD, F. & MUNSCHAUER, M. 2023. SND1 binds SARS-CoV-2 negative-sense RNA and promotes viral RNA synthesis through NSP9. Cell, 186, 4834-4850 e23. DIO:10.1016/j.cell.2023.09.002, PMID:37794589
SLETTEN, A. C., DAVIDSON, J. W., YAGABASAN, B., MOORES, S., SCHWAIGER-HABER, M., FUJIWARA, H., GALE, S., JIANG, X., SIDHU, R., GELMAN, S. J., ZHAO, S., PATTI, G. J., ORY, D. S. & SCHAFFER, J. E. 2021. Loss of SNORA73 reprograms cellular metabolism and protects against steatohepatitis. Nat Commun, 12, 5214. DIO:10.1038/s41467-021-25457-y, PMID:34471131
TILLMAN, E. J. & ROLPH, T. 2020. FGF21: An Emerging Therapeutic Target for Non-Alcoholic Steatohepatitis and Related Metabolic Diseases. Front Endocrinol (Lausanne), 11, 601290. DIO:10.3389/fendo.2020.601290, PMID:33381084
ZHENG, J., ZHANG, Q., ZHAO, Z., QIU, Y., ZHOU, Y., WU, Z., JIANG, C., WANG, X. & JIANG, X. 2023. Epigenetically silenced lncRNA SNAI3-AS1 promotes ferroptosis in glioma via perturbing the m(6)A-dependent recognition of Nrf2 mRNA mediated by SND1. J Exp Clin Cancer Res, 42, 127. DIO:10.1186/s13046-023-02684-3, PMID:37202791
(3) The role of PPARg in fatty liver diseases might be a rodent-specific phenomenon. PPARg agonist treatment in humans may actually reduce ectopic fat deposition by increasing fat storage in adipose tissues. The relevance of the findings to human diseases should be discussed.
We thank the reviewer for the detailed comment. As a transcription regulator of Cd36 and Cidea/c, it is well known that PPARγ plays major adipogenic and lipogenic roles in adipose tissue. Although the expression of PPARγ in the liver is very low under healthy conditions, induced expression of PPARγ in both hepatocytes and non-parenchymal cells (Kupffer cells, immune cells, and hepatic stellate cells (HSCs)) in the liver has a crucial role in the pathophysiology of MASLD (Lee et al., 2023b, Chen et al., 2023, Gross et al., 2017). The activation of PPARγ in the liver induces the adipogenic program to store fatty acids in lipid droplets as observed in adipocytes (Lee et al., 2018). Moreover, the inactivation of liver PPARγ abolished rosiglitazone-induced an increase in hepatic TG and improved hepatic steatosis in lipoatrophic AZIP mice (Gavrilova et al., 2003). Apart from promoting lipogenesis, PPARγ has also a crucial function in improving inflammation and fibrosis (Chen et al., 2023). Furthermore, there is a strong correlation between the onset of hepatic steatosis and hepatocyte-specific PPARγ expression. Clinical trials have also indicated that increased insulin resistance and hepatic PPARγ expressions were associated with NASH scores in some obese patients (Lee et al., 2023a, Mukherjee et al., 2022). Even though PPARγ’s primary function is in adipose tissue, patients with MASLD have much higher hepatic expression levels of PPARγ, reflecting the fact that PPARγ plays different roles in different tissues and cell types (Mukherjee et al., 2022). As these studies mentioned above, our result also hinted at the importance of PPARγ in the pathophysiology of MASLD. Snhg3 deficiency or overexpression respectively induced the decrease or increase in hepatic PPARγ. Moreover, administration of PPARγ antagonist T0070907 mitigated the hepatic Cd36 and Cidea/c increase and improved Snhg3-induced hepatic steatosis. However, conflicting findings suggest that the expression of hepatic PPARγ is not increased as steatosis develops in humans and in clinical studies and that PPARγ agonists administration didn’t aggravate liver steatosis (Gross et al., 2017). Thus, understanding how the hepatic PPARγ expression is regulated may provide a new avenue to prevent and treat the MASLD (Lee et al., 2018). We also discussed it in revised manuscript, please refer the first paragraph in the section of Discussion in p13.
References
CHEN, H., TAN, H., WAN, J., ZENG, Y., WANG, J., WANG, H. & LU, X. 2023. PPAR-gamma signaling in nonalcoholic fatty liver disease: Pathogenesis and therapeutic targets. Pharmacol Ther, 245, 108391. DIO:10.1016/j.pharmthera.2023.108391, PMID:36963510
GAVRILOVA, O., HALUZIK, M., MATSUSUE, K., CUTSON, J. J., JOHNSON, L., DIETZ, K. R., NICOL, C. J., VINSON, C., GONZALEZ, F. J. & REITMAN, M. L. 2003. Liver peroxisome proliferator-activated receptor gamma contributes to hepatic steatosis, triglyceride clearance, and regulation of body fat mass. J Biol Chem, 278, 34268-76. DIO:10.1074/jbc.M300043200, PMID:12805374
GROSS, B., PAWLAK, M., LEFEBVRE, P. & STAELS, B. 2017. PPARs in obesity-induced T2DM, dyslipidaemia and NAFLD. Nat Rev Endocrinol, 13, 36-49. DIO:10.1038/nrendo.2016.135, PMID:27636730
LEE, S. M., MURATALLA, J., KARIMI, S., DIAZ-RUIZ, A., FRUTOS, M. D., GUZMAN, G., RAMOS-MOLINA, B. & CORDOBA-CHACON, J. 2023a. Hepatocyte PPARgamma contributes to the progression of non-alcoholic steatohepatitis in male and female obese mice. Cell Mol Life Sci, 80, 39. DIO:10.1007/s00018-022-04629-z, PMID:36629912
LEE, S. M., MURATALLA, J., SIERRA-CRUZ, M. & CORDOBA-CHACON, J. 2023b. Role of hepatic peroxisome proliferator-activated receptor gamma in non-alcoholic fatty liver disease. J Endocrinol, 257. DIO:10.1530/JOE-22-0155, PMID:36688873
LEE, Y. K., PARK, J. E., LEE, M. & HARDWICK, J. P. 2018. Hepatic lipid homeostasis by peroxisome proliferator-activated receptor gamma 2. Liver Res, 2, 209-215. DIO:10.1016/j.livres.2018.12.001, PMID:31245168
MUKHERJEE, A. G., WANJARI, U. R., GOPALAKRISHNAN, A. V., KATTURAJAN, R., KANNAMPUZHA, S., MURALI, R., NAMACHIVAYAM, A., GANESAN, R., RENU, K., DEY, A., VELLINGIRI, B. & PRINCE, S. E. 2022. Exploring the Regulatory Role of ncRNA in NAFLD: A Particular Focus on PPARs. Cells, 11. DIO:10.3390/cells11243959, PMID:36552725
Recommendations for the authors:
Reviewer #1 (Recommendations For The Authors):
As a general strategy for the revision, I would advise the authors to focus on strengthening the analysis of the liver with the two most important figures being Figure 2 and Figure 3. The mechanism as it stands is problematic which reduces the impact of the animal studies despite substantial efforts from the authors. Consider removing or toning down some of the studies focused on mechanisms in the nucleus, including changing the title.
We thank the reviewer for the detailed comment. In this study, hepatocyte-specific Snhg3 deficiency decreased body and liver weight, alleviated hepatic steatosis and promoted hepatic fatty acid metabolism in DIO mice, whereas overexpression induced the opposite effect. The hepatic differentially expressed genes (DEGs) between the DIO Snhg3-HKI and control WT mice using RNA-Seq and revealed that Snhg3 exerts a global effect on the expression of genes involved in fatty acid metabolism using GSEA (Figure 4B). RT-qPCR analysis confirmed that the hepatic expression levels of some genes involved in fatty acid metabolism, including Cd36, Cidea/c and Scd1/2, were upregulated in Snhg3-HKO mice and were downregulated in Snhg3-HKI mice compared to the controls (Figure 4C). Moreover, deficiency and overexpression of Snhg3 respectively decreased and increased the expression of profibrotic genes, such as Col1a1 and Col1a2, but had no effects on the pro-inflammatory factors, including Tgfβ1, Tnfα, Il6 and Il1β (figure supplement 3A and B). The results indicated that Snhg3 involved in hepatic steatosis through regulating fatty acid metabolism. Furthermore, PPARγ was selected to study its role in Snhg3-induced hepatic steatosis by integrated analyzing the data from CUT&Tag-Seq, ATAC-Seq and RNA-Seq. Finally, inhibition of PPARγ with T0070907 alleviated Snhg3 induced Cd36 and Cidea/c increases and improved Snhg3-aggravated hepatic steatosis. In summary, we confirmed that SND1/H3K27me3/PPARγ is partially responsible for Sngh3-inuced hepatic steatosis. As the reviewer suggested, we replaced the title with “LncRNA-Snhg3 Aggravates Hepatic Steatosis via PPARγ Signaling”.
(1) How is steatosis changing in the liver? Is this due to a change in fatty acid uptake, lipogenesis/synthesis, beta-oxidation, trig secretion, etc..? The analysis in Figures 2 and 3 is mostly focused on metabolic chamber studies which seem distracting, particularly in the absence of a mechanism and given a liver-specific perturbation. The authors should use a combination of targeted gene expression, protein blots, and lipid flux measurements to provide better insights here. The histology in Figure 2H suggests a very dramatic effect but does match with lipid measurements in 2I.
We thank the reviewer for the detailed comment. The pathogenesis of MASLD has not been entirely elucidated. Multifarious factors such as genetic and epigenetic factors, nutritional factors, insulin resistance, lipotoxicity, microbiome, fibrogenesis and hormones secreted from the adipose tissue, are recognized to be involved in the development and progression of MASLD (Buzzetti et al., 2016, Lee et al., 2017, Rada et al., 2020, Sakurai et al., 2021, Friedman et al., 2018). In this study, we investigated the hepatic differentially expressed genes (DEGs) between the DIO Snhg3-HKI and control WT mice using RNA-Seq and revealed that Snhg3 exerts a global effect on the expression of genes involved in fatty acid metabolism using GSEA (Figure 4B). We validated the expression of some DEGs involved in fatty acid metabolism by RT-qPCR. The results showed that the hepatic expression levels of some genes involved in fatty acid metabolism, including Cd36, Cidea/c and Scd1/2 were upregulated in Snhg3-HKO mice and were downregulated in Snhg3-HKI mice compared to the controls (Figure 4C), respectively. Additionally, we re-analyzed the metabolic chamber data using CalR and the results showed that there were no obvious differences in heat production, total oxygen consumption, carbon dioxide production or RER between DIO Snhg3-HKO or DIO Snhg3-HKI and the corresponding control mice (figure supplement 1C and 2C). Unfortunately, we did not detect lipid flux due to limited experimental conditions. However, in summary, our results indicated that Snhg3 is involved in hepatic steatosis by regulating fatty acid metabolism. Please check them in the first paragraph in p8.
Additionally, we determined the hepatic TC levels in other batch of DIO Snhg3-HKO and control mice and found there was no difference in hepatic TC (as below) between DIO Snhg3-HKO and control mice fed HFD 18 weeks. Perhaps the apparent difference in TC requires a prolonged high-fat diet feeding time.
Author response image 1.
Hepatic TC contents of in DIO Snhg3-Flox and Snhg3-HKO mice.
References
BUZZETTI, E., PINZANI, M. & TSOCHATZIS, E. A. 2016. The multiple-hit pathogenesis of non-alcoholic fatty liver disease (NAFLD). Metabolism, 65, 1038-48. DIO:10.1016/j.metabol.2015.12.012, PMID:26823198
FRIEDMAN, S. L., NEUSCHWANDER-TETRI, B. A., RINELLA, M. & SANYAL, A. J. 2018. Mechanisms of NAFLD development and therapeutic strategies. Nat Med, 24, 908-922. DIO:10.1038/s41591-018-0104-9, PMID:29967350
LEE, J., KIM, Y., FRISO, S. & CHOI, S. W. 2017. Epigenetics in non-alcoholic fatty liver disease. Mol Aspects Med, 54, 78-88. DIO:10.1016/j.mam.2016.11.008, PMID:27889327
RADA, P., GONZALEZ-RODRIGUEZ, A., GARCIA-MONZON, C. & VALVERDE, A. M. 2020. Understanding lipotoxicity in NAFLD pathogenesis: is CD36 a key driver? Cell Death Dis, 11, 802. DIO:10.1038/s41419-020-03003-w, PMID:32978374
SAKURAI, Y., KUBOTA, N., YAMAUCHI, T. & KADOWAKI, T. 2021. Role of Insulin Resistance in MAFLD. Int J Mol Sci, 22. DIO:10.3390/ijms22084156, PMID:33923817
(2) Throughout the manuscript the authors make claims about liver disease models, but this is not well supported since markers of advanced liver disease are not examined. The authors should stain and show expression for fibrosis and inflammation.
We thank the reviewer for the detailed comment. Metabolic dysfunction-associated fatty liver disease (MASLD) is characterized by excess liver fat in the absence of significant alcohol consumption. It can progress from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH) and fibrosis and eventually to chronic progressive diseases such as cirrhosis, end-stage liver failure, and hepatocellular carcinoma (Loomba et al., 2021). As the reviewer suggested, we detected the effect of Snhg3 on liver fibrosis and inflammation. The results showed no hepatic fibrosis phenotype was seen in Snhg3-HKO and Snhg3-HKI mice (figures supplement 1D and 2D). Moreover, deficiency and overexpression of Snhg3 respectively decreased and increased the expression of profibrotic genes, such as collagen type I alpha 1/2 (Col1a1 and Col1a2), but had no effects on the pro-inflammatory factors including Tgf-β, Tnf-α, Il-6 and Il-1β (figure supplement 3A and 3B). Inflammation is an absolute requirement for fibrosis because factors from injured hepatocytes alone are not sufficient to directly activate HSCs and lead to fibrosis (Kisseleva and Brenner, 2021). Additionally, previous studies indicated that exposure to HFD for more 24 weeks causes less severe fibrosis (Alshawsh et al., 2022). In future, the effect of Snhg3 on hepatic fibrosis in mice need to be elucidated by prolonged high-fat feeding or by adopting methionine- and choline deficient diet (MCD) feeding. Please check them in the second paragraph in the section of Discussion in p13.
References
ALSHAWSH, M. A., ALSALAHI, A., ALSHEHADE, S. A., SAGHIR, S. A. M., AHMEDA, A. F., AL ZARZOUR, R. H. & MAHMOUD, A. M. 2022. A Comparison of the Gene Expression Profiles of Non-Alcoholic Fatty Liver Disease between Animal Models of a High-Fat Diet and Methionine-Choline-Deficient Diet. Molecules, 27. DIO:10.3390/molecules27030858, PMID:35164140
KISSELEVA, T. & BRENNER, D. 2021. Molecular and cellular mechanisms of liver fibrosis and its regression. Nat Rev Gastroenterol Hepatol, 18, 151-166. DIO:10.1038/s41575-020-00372-7, PMID:33128017
LOOMBA, R., FRIEDMAN, S. L. & SHULMAN, G. I. 2021. Mechanisms and disease consequences of nonalcoholic fatty liver disease. Cell, 184, 2537-2564. DIO:10.1016/j.cell.2021.04.015, PMID:33989548
(3) Publicly available datasets show that PPARG protein is not expressed in the liver (Science 2015 347(6220):1260419, PMID: 25613900). Are the authors sure this is not an effect on another PPAR isoform like alpha? ChIP and RNA-seq pathway readouts do not distinguish between different isoforms.
We thank the reviewer for the detailed comment. As a transcription regulator of Cd36 and Cidea/c, it is well known that PPARγ plays major adipogenic and lipogenic roles in adipose tissue. Although the expression of PPARγ in the liver is very low under healthy conditions, induced expression of PPARγ in both hepatocytes and non-parenchymal cells (Kupffer cells, immune cells, and hepatic stellate cells (HSCs)) in the liver has a crucial role in the pathophysiology of MASLD (Lee et al., 2023b, Chen et al., 2023, Gross et al., 2017). The activation of PPARγ in the liver induces the adipogenic program to store fatty acids in lipid droplets as observed in adipocytes (Lee et al., 2018). Moreover, the inactivation of liver PPARγ abolished rosiglitazone-induced an increase in hepatic TG and improved hepatic steatosis in lipoatrophic AZIP mice (Gavrilova et al., 2003). Apart from promoting lipogenesis, PPARγ has also a crucial function in improving inflammation and fibrosis (Chen et al., 2023). Furthermore, there is a strong correlation between the onset of hepatic steatosis and hepatocyte-specific PPARγ expression. Clinical trials have also indicated that increased insulin resistance and hepatic PPARγ expressions were associated with NASH scores in some obese patients (Lee et al., 2023a, Mukherjee et al., 2022). Even though PPARγ’s primary function is in adipose tissue, patients with MASLD have much higher hepatic expression levels of PPARγ, reflecting the fact that PPARγ plays different roles in different tissues and cell types (Mukherjee et al., 2022). As these studies mentioned above, our result also hinted at the importance of PPARγ in the pathophysiology of MASLD. Snhg3 deficiency or overexpression respectively induced the decrease or increase in hepatic PPARγ. Moreover, administration of PPARγ antagonist T0070907 mitigated the hepatic Cd36 and Cidea/c increase and improved Snhg3-induced hepatic steatosis. However, conflicting findings suggest that the expression of hepatic PPARγ is not increased as steatosis develops in humans and in clinical studies and that PPARγ agonists administration didn’t aggravate liver steatosis (Gross et al., 2017). Thus, understanding how the hepatic PPARγ expression is regulated may provide a new avenue to prevent and treat the MASLD (Lee et al., 2018). We also discussed it in revised manuscript, please refer the first paragraph in the section of Discussion in p13 in revised manuscript.
PPARα, most highly expressed in the liver, transcriptionally regulates lipid catabolism by regulating the expression of genes mediating triglyceride hydrolysis, fatty acid transport, and β-oxidation. Activators of PPARα decrease plasma triglycerides by inhibiting its synthesis and accelerating its hydrolysis (Chen et al., 2023). Mice with deletion of the Pparα gene exhibited more hepatic steatosis under HFD induction. As the reviewer suggested, we investigated the effect of Snhg3 on Pparα expression. The result showed that both deficiency of Snhg3 or overexpression of Snhg3 doesn’t affect the mRNA level of Pparα as showing below, indicating that Snhg3-induced lipid accumulation independent on PPARα. Additionally, the exon, upstream 2k, 5’-UTR and intron regions of Pparγ, not Pparα, were enriched with the H3K27me3 mark (fold_enrichment = 4.15697) in the liver of DIO Snhg3-HKO mice using the CUT&Tag assay (table supplement 8), which was further confirmed by ChIP (Figure 6F and G). Therefore, we choose PPARγ to study its role in Sngh3-induced hepatic steatosis by integrated analyzing the data from CUT&Tag-Seq, ATAC-Seq and RNA-Seq.
Author response image 2.
The mRNA levels of hepatic Pparα expression in DIO Snhg3-HKO mice and Snhg3-HKI mice compared to the controls.
References
CHEN, H., TAN, H., WAN, J., ZENG, Y., WANG, J., WANG, H. & LU, X. 2023. PPAR-gamma signaling in nonalcoholic fatty liver disease: Pathogenesis and therapeutic targets. Pharmacol Ther, 245, 108391. DIO:10.1016/j.pharmthera.2023.108391, PMID:36963510
GAVRILOVA, O., HALUZIK, M., MATSUSUE, K., CUTSON, J. J., JOHNSON, L., DIETZ, K. R., NICOL, C. J., VINSON, C., GONZALEZ, F. J. & REITMAN, M. L. 2003. Liver peroxisome proliferator-activated receptor gamma contributes to hepatic steatosis, triglyceride clearance, and regulation of body fat mass. J Biol Chem, 278, 34268-76. DIO:10.1074/jbc.M300043200, PMID:12805374
GROSS, B., PAWLAK, M., LEFEBVRE, P. & STAELS, B. 2017. PPARs in obesity-induced T2DM, dyslipidaemia and NAFLD. Nat Rev Endocrinol, 13, 36-49. DIO:10.1038/nrendo.2016.135, PMID:27636730
LEE, S. M., MURATALLA, J., KARIMI, S., DIAZ-RUIZ, A., FRUTOS, M. D., GUZMAN, G., RAMOS-MOLINA, B. & CORDOBA-CHACON, J. 2023a. Hepatocyte PPARgamma contributes to the progression of non-alcoholic steatohepatitis in male and female obese mice. Cell Mol Life Sci, 80, 39. DIO:10.1007/s00018-022-04629-z, PMID:36629912
LEE, S. M., MURATALLA, J., SIERRA-CRUZ, M. & CORDOBA-CHACON, J. 2023b. Role of hepatic peroxisome proliferator-activated receptor gamma in non-alcoholic fatty liver disease. J Endocrinol, 257. DIO:10.1530/JOE-22-0155, PMID:36688873
LEE, Y. K., PARK, J. E., LEE, M. & HARDWICK, J. P. 2018. Hepatic lipid homeostasis by peroxisome proliferator-activated receptor gamma 2. Liver Res, 2, 209-215. DIO:10.1016/j.livres.2018.12.001, PMID:31245168
MUKHERJEE, A. G., WANJARI, U. R., GOPALAKRISHNAN, A. V., KATTURAJAN, R., KANNAMPUZHA, S., MURALI, R., NAMACHIVAYAM, A., GANESAN, R., RENU, K., DEY, A., VELLINGIRI, B. & PRINCE, S. E. 2022. Exploring the Regulatory Role of ncRNA in NAFLD: A Particular Focus on PPARs. Cells, 11. DIO:10.3390/cells11243959, PMID:36552725
(4) Previous work suggests that SNHG3 regulates its neighboring gene MED18 which is an important regulator of global transcription. Could some of the observed effects be due to changes in MED18 or other neighboring genes?
We thank the reviewer for the detailed comment. Previous work suggested that human SNHG3 promotes progression of gastric cancer by regulating neighboring MED18 gene methylation (Xuan and Wang, 2019). Here, we studied the effect of mouse Snhg3 on Med18 and the result showed that Snhg3 had no effect on the mRNA levels of Med18 (as below). Additionally, we also tested the effect of mouse Snhg3 on its neighboring gene, regulator of chromosome condensation 1 (Rcc1). Although deficiency of Snhg3 inhibited the mRNA level of Rcc1, overexpression of Snhg3 doesn’t affect the mRNA level of Rcc1 as showing below. RCC1, the only known guanine nucleotide exchange factor in the nucleus for Ran, a nuclear Ras-like G protein, directly participates in cellular processes such as nuclear envelope formation, nucleocytoplasmic transport, and spindle formation (Ren et al., 2020). RCC1 also regulates chromatin condensation in the late S and early M phases of the cell cycle. Many studies have found that RCC1 plays an important role in tumors. Furthermore, whether Rcc1 mediates the alleviated effect on MASLD of Snhg3 needs to be further investigated.
Author response image 3.
The mRNA levels of hepatic Rcc1 and Med18 expression in DIO Snhg3-HKO mice and Snhg3-HKI mice compared to the controls.
References
REN, X., JIANG, K. & ZHANG, F. 2020. The Multifaceted Roles of RCC1 in Tumorigenesis. Front Mol Biosci, 7, 225. DIO:10.3389/fmolb.2020.00225, PMID:33102517
XUAN, Y. & WANG, Y. 2019. Long non-coding RNA SNHG3 promotes progression of gastric cancer by regulating neighboring MED18 gene methylation. Cell Death Dis, 10, 694. DIO:10.1038/s41419-019-1940-3, PMID:31534128
(5) The claim that Snhg3 regulates SND1 protein stability seems subtle. There is data inconsistency between different panels regarding this regulation including Figure 5I, Figure 6A, and Figure 7E. In addition, is ubiquitination happening in the nucleus where Snhg3 is expressed?
We thank the reviewer for the detailed comment. The effect of Snhg3-induced SND1 expression had been confirmed by western blotting, please check them in Figure 5I, Figure 6A, Figure 7E and corresponding primary data. Additionally, Snhg3-induced SND1 protein stability seemed subtle, indicating there may be other mechanism by which Snhg3 promotes SND1, such as riboregulation. We had added it in the section of Discussion, please check it in the second paragraph in p16.
Additionally, we did not detect the sites where SND1 is modified by ubiquitination. Our results showed that Snhg3 was more localized in the nucleus (Figure 1D) and Snhg3 also promoted the nuclear localization of SND1 (Figure 5O). We had revised the diagram of Snhg3 action in Figure 8G. Please check them in revised manuscript.
(6) The authors show that the loss of Snhg3 changes the global H3K27me3 level. Few enzymes modify H3K27me3 levels. Did the authors check for an interaction between EZH2, Jmjd3, UTX, and Snhg3/SND1?
We thank the reviewer for the detailed comment. It is crucial to ascertain whether SND1 itself functions as a new demethylase or if it influences other demethylases, such as Jmjd3, enhancer of zeste homolog 2 (EZH2), and ubiquitously transcribed tetratricopeptide repeat on chromosome X (UTX). The precise mechanism by which SND1 regulates H3K27me3 is still unclear and hence requires further investigation. We had added the limitations in the section of Discussion and please check it in the third paragraph in p17.
(7) Can the authors speculate if the findings related to Snhg3/SND1 extend to humans?
We thank the reviewer for the detailed comment. Since the sequence of Snhg3 is not conserved between mice and humans, the findings in this manuscript may not be applicable to humans, but the detail need to be further exploited.
(8) As a general rule the figures are too small or difficult to read with limited details in the figure legends which limits evaluation. For example, Figure 1B and almost all of 4 cannot read labels. Figure 2, cannot see the snapshots show of mice or livers. What figure is supporting the claim that snhg3KI are more 'hyper-accessible'? Can the authors clarify what Figure 4H is referring to?
We thank the reviewer for the detailed comment. We have provided high quality figures in our revised manuscript.
The ‘hyper-accessible’ state in the liver of Snhg3-HKI mice was inferred by the differentially accessible regions (DARs), that is, we discovered 4305 DARs were more accessible in Snhg3-HKI mice and only 2505 DARs were more accessible in control mice and please refer table supplement 3).
The result of Figure 4H about heatmap for Cd36 was from hepatic RNA-seq of DIO Snhg3-HKI and control WT mice. For avoiding ambiguity, we have removed it.
(9) Authors stated that upon Snhg3 knock out, more genes are upregulated(1028) than downregulated(365). This description does not match Figure 4A. It seems in Figure 4A there are equal numbers of up and downregulated genes.
We thank the reviewer for the detailed question. We apologized for this mistake and have corrected it.
(10) Provide a schematic of the knockout and KI strategy in the supplement.
We thank the reviewer for the detailed comment. We had included the knockout and KI strategy in figure supplement 1A and B, and 2A.
Reviewer #2 (Recommendations For The Authors):
(1) Metabolic cage data need to be reanalyzed with CalR (particularly when the body weights are significantly different).
We thank the reviewer for the detailed comment. We reanalyzed the metabolic cage data using CalR (Mina et al., 2018). The results showed that there were no obvious differences in heat production, total oxygen consumption, carbon dioxide production and the respiratory exchange ratio between DIO Snhg3-HKO and control mice. Similar to DIO Snhg3-HKO mice, there was also no differences in heat production, total oxygen consumption, carbon dioxide production, and RER between DIO Snhg3-HKI mice and WT mice. Please check them in figure supplement 1C and 2C, and Mouse Calorimetry in Materials and Methods.
Reference
MINA, A. I., LECLAIR, R. A., LECLAIR, K. B., COHEN, D. E., LANTIER, L. & BANKS, A. S. 2018. CalR: A Web-Based Analysis Tool for Indirect Calorimetry Experiments. Cell Metab, 28, 656-666 e1. DIO:10.1016/j.cmet.2018.06.019, PMID:30017358
(2) ITT in Figure 2F should also be presented as % of the initial glucose level, which would reveal that there is no difference between WT and KO.
We thank the reviewer for the detailed comment. We repeated ITT experiment and include the new data in revised manuscript, please check it in Figure 2C.
(3) The fasting glucose results are inconsistent between ITT and GTT. Is there any difference in fasting glucose?
We thank the reviewer for the questions. The difference between GTT and ITT was caused owing to different fasting time, that is, mice were fasted for 6 h in ITT and were fasted for 16 h in GTT. It seems that Snhg3 doesn’t affect short- and longer-time fasting glucose levels and please refer Figures 2C and 3C.
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Author response:
Reviewer #1 (Public Review):
In this paper, Tompary & Davachi present work looking at how memories become integrated over time in the brain, and relating those mechanisms to responses on a priming task as a behavioral measure of memory linkage. They find that remotely but not recently formed memories are behaviorally linked and that this is associated with a change in the neural representation in mPFC. They also find that the same behavioral outcomes are associated with the increased coupling of the posterior hippocampus with category-sensitive parts of the neocortex (LOC) during a post-learning rest period-again only for remotely learned information. There was also correspondence in rest connectivity (posterior hippocampus-LOC) and representational change (mPFC) such that for remote memories specifically, the initial post-learning connectivity enhancement during rest related to longer-term mPFC representational change.
This work has many strengths. The topic of this paper is very interesting, and the data provide a really nice package in terms of providing a mechanistic account of how memories become integrated over a delay. The paper is also exceptionally well-written and a pleasure to read. There are two studies, including one large behavioral study, and the findings replicate in the smaller fMRI sample. I do however have two fairly substantive concerns about the analytic approach, where more data will be required before we can know whether the interpretations are an appropriate reflection of the findings. These and other concerns are described below.
Thank you for the positive comments! We are proud of this work, and we feel that the paper is greatly strengthened by the revisions we made in response to your feedback. Please see below for specific changes that we’ve made.
1) One major concern relates to the lack of a pre-encoding baseline scan prior to recent learning.
a) First, I think it would be helpful if the authors could clarify why there was no pre-learning rest scan dedicated to the recent condition. Was this simply a feasibility consideration, or were there theoretical reasons why this would be less "clean"? Including this information in the paper would be helpful for context. Apologies if I missed this detail in the paper.
This is a great point and something that we struggled with when developing this experiment. We considered several factors when deciding whether to include a pre-learning baseline on day two. First, the day 2 scan session was longer than that of day 1 because it included the recognition priming and explicit memory tasks, and the addition of a baseline scan would have made the length of the session longer than a typical scan session – about 2 hours in the scanner in total – and we were concerned that participant engagement would be difficult to sustain across a longer session. Second, we anticipated that the pre-learning scan would not have been a ‘clean’ measure of baseline processing, but rather would include signal related to post-learning processing of the day 1 sequences, as multi-variate reactivation of learned stimuli have been observed in rest scans collected 24-hours after learning (Schlichting & Preston, 2014). We have added these considerations to the Discussion (page 39, lines 1047-1070).
b) Second, I was hoping the authors could speak to what they think is reflected in the post-encoding "recent" scan. Is it possible that these data could also reflect the processing of the remote memories? I think, though am not positive, that the authors may be alluding to this in the penultimate paragraph of the discussion (p. 33) when noting the LOC-mPFC connectivity findings. Could there be the reinstatement of the old memories due to being back in the same experimental context and so forth? I wonder the extent to which the authors think the data from this scan can be reflected as strictly reflecting recent memories, particularly given it is relative to the pre-encoding baseline from before the remote memories, as well (and therefore in theory could reflect both the remote + recent). (I should also acknowledge that, if it is the case that the authors think there might be some remote memory processing during the recent learning session in general, a pre-learning rest scan might not have been "clean" either, in that it could have reflected some processing of the remote memories-i.e., perhaps a clean pre-learning scan for the recent learning session related to point 1a is simply not possible.)
We propose that theoretically, the post-learning recent scan could indeed reflect mixture of remote and recent sequences. This is one of the drawbacks of splitting encoding into two sessions rather than combining encoding into one session and splitting retrieval into an immediate and delayed session; any rest scans that are collected on Day 2 may have signal that relates to processing of the Day 1 remote sequences, which is why we decided against the pre-learning baseline for Day 2, as you had noted.
You are correct that we alluded to in our original submission when discussing the LOC-mPFC coupling result, and we have taken steps to discuss this more explicitly. In Brief, we find greater LOC-mPFC connectivity only after recent learning relative to the pre-learning baseline, and cortical-cortical connectivity could be indicative of processing memories that already have undergone some consolidation (Takashima et al., 2009; Smith et al., 2010). From another vantage point, the mPFC representation of Day 1 learning may have led to increased connectivity with LOC on Day 2 due to Day 1 learning beginning to resemble consolidated prior knowledge (van Kesteren et al., 2010). While this effect is consistent with prior literature and theory, it's unclear why we would find evidence of processing of the remote memories and not the recent memories. Furthermore, the change in LOC-mPFC connectivity in this scan did not correlate with memory behaviors from either learning session, which could be because signal from this scan reflects a mix of processing of the two different learning sessions. With these ideas in mind, we have fleshed out the discussion of the post-encoding ‘recent’ scan in the Discussion (page 38-39, lines 1039-1044).
c) Third, I am thinking about how both of the above issues might relate to the authors' findings, and would love to see more added to the paper to address this point. Specifically, I assume there are fluctuations in baseline connectivity profile across days within a person, such that the pre-learning connectivity on day 1 might be different from on day 2. Given that, and the lack of a pre-learning connectivity measure on day 2, it would logically follow that the measure of connectivity change from pre- to post-learning is going to be cleaner for the remote memories. In other words, could the lack of connectivity change observed for the recent scan simply be due to the lack of a within-day baseline? Given that otherwise, the post-learning rest should be the same in that it is an immediate reflection of how connectivity changes as a function of learning (depending on whether the authors think that the "recent" scan is actually reflecting "recent + remote"), it seems odd that they both don't show the same corresponding increase in connectivity-which makes me think it may be a baseline difference. I am not sure if this is what the authors are implying when they talk about how day 1 is most similar to prior investigation on p. 20, but if so it might be helpful to state that directly.
We agree that it is puzzling that we don’t see that hippocampal-LOC connectivity does not also increase after recent learning, equivalently to what we see after remote learning. However, the fact that there is an increase from baseline rest to post-recent rest in mPFC – LOC connectivity suggests that it’s not an issue with baseline, but rather that the post-recent learning scan is reflecting processing of the remote memories (although as a caveat, there is no relationship with priming).
On what is now page 23, we were referring to the notion that the Day 1 procedure (baseline rest, learning, post-learning rest) is the most straightforward replication of past work that finds a relationship between hippocampal-cortical coupling and later memory. In contrast, the Day 2 learning and rest scan are less ‘clean’ of a replication in that they are taking place in the shadow of Day 1 learning. We have clarified this in the Results (page 23, lines 597-598).
d) Fourth and very related to my point 1c, I wonder if the lack of correlations for the recent scan with behavior is interpretable, or if it might just be that this is a noisy measure due to imperfect baseline correction. Do the authors have any data or logic they might be able to provide that could speak to these points? One thing that comes to mind is seeing whether the raw post-learning connectivity values (separately for both recent and remote) show the same pattern as the different scores. However, the authors may come up with other clever ways to address this point. If not, it might be worth acknowledging this interpretive challenge in the Discussion.
We thought of three different approaches that could help us to understand whether the lack of correlations in between coupling and behavior in the recent scan was due to noise. First, we correlated recognition priming with raw hippocampal-LOC coupling separately for pre- and post-learning scans, as in Author response image 1:
Author response image 1.
Note that the post-learning chart depicts the relationship between post-remote coupling and remote priming and between post-recent coupling and recent priming (middle). Essentially, post-recent learning coupling did not relate to priming of recently learned sequences (middle; green) while there remains a trend for a relationship between post-remote coupling and priming for remotely learned sequences (middle; blue). However, the significant relationship between coupling and priming that we reported in the paper (right, blue) is driven both by the initial negative relationship that is observed in the pre-learning scan and the positive relationship in the post-remote learning scan. This highlights the importance of using a change score, as there may be spurious initial relationships between connectivity profiles and to-be-learned information that would then mask any learning- and consolidation-related changes.
We also reasoned that if comparisons between the post-recent learning scan and the baseline scan are noisier than between the post-remote learning and baseline scan, there may be differences in the variance of the change scores across participants, such that changes in coupling from baseline to post-recent rest may be more variable than coupling from baseline to post-remote rest. We conducted F-tests to compare the variance of the change in these two hippocampal-LO correlations and found no reliable difference (ratio of difference: F(22, 22) = 0.811, p = .63).
Finally, we explored whether hippocampal-LOC coupling is more stable across participants if compared across two rest scans within the same imaging session (baseline and post-remote) versus across two scans across two separate sessions (baseline and post-recent). Interestingly, coupling was not reliably correlated across scans in either case (baseline/post-remote: r = 0.03, p = 0.89 Baseline/post-recent: r = 0.07, p = .74).
Finally, we evaluated whether hippocampal-LOC coupling was correlated across different rest scans (see Author response image 2). We reasoned that if such coupling was more correlated across baseline and post-remote scans relative to baseline and post-recent scans, that would indicate a within-session stability of participants’ connectivity profiles. At the same time, less correlation of coupling across baseline and post-recent scans would be an indication of a noisier change measure as the measure would additionally include a change in individuals’ connectivity profile over time. We found that there was no difference in the correlation of hipp-LO coupling is across sessions, and the correlation was not reliably significant for either session (baseline/post-remote: r = 0.03, p = 0.89; baseline/post-recent: r = 0.07, p = .74; difference: Steiger’s t = 0.12, p = 0.9).
Author response image 2.
We have included the raw correlations with priming (page 25, lines 654-661, Supplemental Figure 6) as well as text describing the comparison of variances (page 25, lines 642-653). We did not add the comparison of hippocampal-LOC coupling across scans to the current manuscript, as an evaluation of stability of such coupling in the context of learning and reactivation seems out of scope of the current focus of the experiment, but we find this result to be worthy of follow-up in future work.
In summary, further analysis of our data did not reveal any indication that a comparison of rest connectivity across scan sessions inserted noise into the change score between baseline and post-recent learning scans. However, these analyses cannot fully rule that possibility out, and the current analyses do not provide concrete evidence that the post-recent learning scan comprises signals that are a mixture of processing of recent and remote sequences. We discuss these drawbacks in the Discussion (page 39, lines 1047-1070).
2) My second major concern is how the authors have operationalized integration and differentiation. The pattern similarity analysis uses an overall correspondence between the neural similarity and a predicted model as the main metric. In the predicted model, C items that are indirectly associated are more similar to one another than they are C items that are entirely unrelated. The authors are then looking at a change in correspondence (correlation) between the neural data and that prediction model from pre- to post-learning. However, a change in the degree of correspondence with the predicted matrix could be driven by either the unrelated items becoming less similar or the related ones becoming more similar (or both!). Since the interpretation in the paper focuses on change to indirectly related C items, it would be important to report those values directly. For instance, as evidence of differentiation, it would be important to show that there is a greater decrease in similarity for indirectly associated C items than it is for unrelated C items (or even a smaller increase) from pre to post, or that C items that are indirectly related are less similar than are unrelated C items post but not pre-learning. Performing this analysis would confirm that the pattern of results matches the authors' interpretation. This would also impact the interpretation of the subsequent analyses that involve the neural integration measures (e.g., correlation analyses like those on p. 16, which may or may not be driven by increased similarity among overlapping C pairs). I should add that given the specificity to the remote learning in mPFC versus recent in LOC and anterior hippocampus, it is clearly the case that something interesting is going on. However, I think we need more data to understand fully what that "something" is.
We recognize the importance of understanding whether model fits (and changes to them) are driven by similarity of overlapping pairs or non-overlapping pairs. We have modified all figures that visualize model fits to the neural integration model to separately show fits for pre- and post-learning (Figure 3 for mPFC, Supp. Figure 5 for LOC, Supp. Figure 9 for AB similarity in anterior hippocampus & LOC). We have additionally added supplemental figures to show the complete breakdown of similarity each region in a 2 (pre/post) x 2 (overlapping/non-overlapping sequence) x 2 (recent/remote) chart. We decided against including only these latter charts rather than the model fits since the model fits strike a good balance between information and readability. We have also modified text in various sections to focus on these new results.
In brief, the decrease in model fit for mPFC for the remote sequences was driven primarily by a decrease in similarity for the overlapping C items and not the non-overlapping ones (Supplementary Figure 3, page 18, lines 468-472).
Interestingly, in LOC, all C items grew more similar after learning, regardless of their overlap or learning session, but the increase in model fit for C items in the recent condition was driven by a larger increase in similarity for overlapping pairs relative to non-overlapping ones (Supp. Figure 5, page 21, lines 533-536).
We also visualized AB similarity in the anterior hippocampus and LOC in a similar fashion (Supplementary Figure 9).
We have also edited the Methods sections with updated details of these analyses (page 52, lines 1392-1397). We think that including these results considerably strengthen our claims and we are pleased to have them included.
3) The priming task occurred before the post-learning exposure phase and could have impacted the representations. More consideration of this in the paper would be useful. Most critically, since the priming task involves seeing the related C items back-to-back, it would be important to consider whether this experience could have conceivably impacted the neural integration indices. I believe it never would have been the case that unrelated C items were presented sequentially during the priming task, i.e., that related C items always appeared together in this task. I think again the specificity of the remote condition is key and perhaps the authors can leverage this to support their interpretation. Can the authors consider this possibility in the Discussion?
It's true that only C items from the same sequence were presented back-to-back during the priming task, and that this presentation may interfere with observations from the post-learning exposure scan that followed it. We agree that it is worth considering this caveat and have added language in the Discussion (page 40, lines 1071-1086). When designing the study, we reasoned that it was more important for the behavioral priming task to come before the exposure scans, as all items were shown only once in that task, whereas they were shown 4-5 times in a random order in the post-learning exposure phase. Because of this difference in presentation times, and because behavioral priming findings tend to be very sensitive, we concluded that it was more important to protect the priming task from the exposure scan instead of the reverse.
We reasoned, however, that the additional presentation of the C items in the recognition priming task would not substantially override the sequence learning, as C items were each presented 16 times in their sequence (ABC1 and ABC2 16 times each). Furthermore, as this reviewer suggests, the order of C items during recognition was the same for recent and remote conditions, so the fact that we find a selective change in neural representation for the remote condition and don’t also see that change for the recent condition is additional assurance that the recognition priming order did not substantially impact the representations.
4) For the priming task, based on the Figure 2A caption it seems as though every sequence contributes to both the control and primed conditions, but (I believe) this means that the control transition always happens first (and they are always back-to-back). Is this a concern? If RTs are changing over time (getting faster), it would be helpful to know whether the priming effects hold after controlling for trial numbers. I do not think this is a big issue because if it were, you would not expect to see the specificity of the remotely learned information. However, it would be helpful to know given the order of these conditions has to be fixed in their design.
This is a correct understanding of the trial orders in the recognition priming task. We chose to involve the baseline items in the control condition to boost power – this way, priming of each sequence could be tested, while only presenting each item once in this task, as repetition in the recognition phase would have further facilitated response times and potentially masked any priming effects. We agree that accounting for trial order would be useful here, so we ran a mixed-effects linear model to examine responses times both as a function of trial number and of priming condition (primed/control). While there is indeed a large effect of trial number such that participants got faster over time, the priming effect originally observed in the remote condition still holds at the same time. We now report this analysis in the Results section (page 14, lines 337-349 for Expt 1 and pages 14-15, lines 360-362 for Expt 2).
5) The authors should be cautious about the general conclusion that memories with overlapping temporal regularities become neurally integrated - given their findings in MPFC are more consistent with overall differentiation (though as noted above, I think we need more data on this to know for sure what is going on).
We realize this conclusion was overly simplistic and, in several places, have revised the general conclusions to be more specific about the nuanced similarity findings.
6) It would be worth stating a few more details and perhaps providing additional logic or justification in the main text about the pre- and post-exposure phases were set up and why. How many times each object was presented pre and post, and how the sequencing was determined (were any constraints put in place e.g., such that C1 and C2 did not appear close in time?). What was the cover task (I think this is important to the interpretation & so belongs in the main paper)? Were there considerations involving the fact that this is a different sequence of the same objects the participants would later be learning - e.g., interference, etc.?
These details can be found in the Methods section (pages 50-51, lines 1337-1353) and we’ve added a new summary of that section in the Results (page 17, lines 424- 425 and 432-435). In brief, a visual hash tag appeared on a small subset of images and participants pressed a button when this occurred, and C1 and C2 objects were presented in separate scans (as were A and B objects) to minimize inflated neural similarity due to temporal proximity.
Reviewer #2 (Public Review):
The manuscript by Tompary & Davachi presents results from two experiments, one behavior only and one fMRI plus behavior. They examine the important question of how to separate object memories (C1 and C2) that are never experienced together in time and become linked by shared predictive cues in a sequence (A followed by B followed by one of the C items). The authors developed an implicit priming task that provides a novel behavioral metric for such integration. They find significant C1-C2 priming for sequences that were learned 24h prior to the test, but not for recently learned sequences, suggesting that associative links between the two originally separate memories emerge over an extended period of consolidation. The fMRI study relates this behavioral integration effect to two neural metrics: pattern similarity changes in the medial prefrontal cortex (mPFC) as a measure of neural integration, and changes in hippocampal-LOC connectivity as a measure of post-learning consolidation. While fMRI patterns in mPFC overall show differentiation rather than integration (i.e., C1-C2 representational distances become larger), the authors find a robust correlation such that increasing pattern similarity in mPFC relates to stronger integration in the priming test, and this relationship is again specific to remote memories. Moreover, connectivity between the posterior hippocampus and LOC during post-learning rest is positively related to the behavioral integration effect as well as the mPFC neural similarity index, again specifically for remote memories. Overall, this is a coherent set of findings with interesting theoretical implications for consolidation theories, which will be of broad interest to the memory, learning, and predictive coding communities.
Strengths:
1) The implicit associative priming task designed for this study provides a promising new tool for assessing the formation of mnemonic links that influence behavior without explicit retrieval demands. The authors find an interesting dissociation between this implicit measure of memory integration and more commonly used explicit inference measures: a priming effect on the implicit task only evolved after a 24h consolidation period, while the ability to explicitly link the two critical object memories is present immediately after learning. While speculative at this point, these two measures thus appear to tap into neocortical and hippocampal learning processes, respectively, and this potential dissociation will be of interest to future studies investigating time-dependent integration processes in memory.
2) The experimental task is well designed for isolating pre- vs post-learning changes in neural similarity and connectivity, including important controls of baseline neural similarity and connectivity.
3) The main claim of a consolidation-dependent effect is supported by a coherent set of findings that relate behavioral integration to neural changes. The specificity of the effects on remote memories makes the results particularly interesting and compelling.
4) The authors are transparent about unexpected results, for example, the finding that overall similarity in mPFC is consistent with a differentiation rather than an integration model.
Thank you for the positive comments!
Weaknesses:
1) The sequence learning and recognition priming tasks are cleverly designed to isolate the effects of interest while controlling for potential order effects. However, due to the complex nature of the task, it is difficult for the reader to infer all the transition probabilities between item types and how they may influence the behavioral priming results. For example, baseline items (BL) are interspersed between repeated sequences during learning, and thus presumably can only occur before an A item or after a C item. This seems to create non-random predictive relationships such that C is often followed by BL, and BL by A items. If this relationship is reversed during the recognition priming task, where the sequence is always BL-C1-C2, this violation of expectations might slow down reaction times and deflate the baseline measure. It would be helpful if the manuscript explicitly reported transition probabilities for each relevant item type in the priming task relative to the sequence learning task and discussed how a match vs mismatch may influence the observed priming effects.
We have added a table of transition probabilities across the learning, recognition priming, and exposure scans (now Table 1, page 48). We have also included some additional description of the change in transition probabilities across different tasks in the Methods section. Specifically, if participants are indeed learning item types and rules about their order, then both the control and the primed conditions would violate that order. Since C1 and C2 items never appeared together, viewing C1 would give rise to an expectation of seeing a BL item, which would also be violated. This suggests that our priming effects are driven by sequence-specific relationships rather than learning of the probabilities of different item types. We’ve added this consideration to the Methods section (page 45, lines 1212-1221).
Another critical point to consider (and that the transition probabilities do not reflect) is that during learning, while C is followed either by A or BL, they are followed by different A or BL items. In contrast, a given A is always followed by the same B object, which is always followed by one of two C objects. While the order of item types is semi-predictable, the order of objects (specific items) themselves are not. This can be seen in the response times during learning, such that response times for A and BL items are always slower than for B and C items. We have explained this nuance in the figure text for Table 1.
2) The choice of what regions of interest to include in the different sets of analyses could be better motivated. For example, even though briefly discussed in the intro, it remains unclear why the posterior but not the anterior hippocampus is of interest for the connectivity analyses, and why the main target is LOC, not mPFC, given past results including from this group (Tompary & Davachi, 2017). Moreover, for readers not familiar with this literature, it would help if references were provided to suggest that a predictable > unpredictable contrast is well suited for functionally defining mPFC, as done in the present study.
We have clarified our reasoning for each of these choices throughout the manuscript and believe that our logic is now much more transparent. For an expanded reasoning of why we were motivated to look at posterior and not anterior hippocampus, see pages 6-7, lines 135-159, and our response to R2. In brief, past research focusing on post-encoding connectivity with the hippocampus suggests that posterior aspect is more likely to couple with category-selective cortex after learning neutral, non-rewarded objects much like the stimuli used in the present study.
We also clarify our reasoning for LOC over mPFC. While theoretically, mPFC is thought to be a candidate region for coupling with the hippocampus during consolidation, the bulk of empirical work to date has revealed post-encoding connectivity between the hippocampus and category-selective cortex in the ventral and occipital lobes (page 6, lines 123-134).
As for the use of the predictable > unpredictable contrast for functionally defining cortical regions, we reasoned that cortical regions that were sensitive to the temporal regularities generated by the sequences may be further involved in their offline consolidation and long-term storage (Danker & Anderson, 2010; Davachi & Danker, 2013; McClelland et al., 1995). We have added this justification to the Methods section (page 18, lines 454-460).
3) Relatedly, multiple comparison corrections should be applied in the fMRI integration and connectivity analyses whenever the same contrast is performed on multiple regions in an exploratory manner.
We now correct for multiple comparisons using Bonferroni correction, and this correction depends on the number of regions in which each analysis is conducted. Please see page 55, lines 1483-1490, in the Methods section for details of each analysis.
Reviewer #3 (Public Review):
The authors of this manuscript sought to illuminate a link between a behavioral measure of integration and neural markers of cortical integration associated with systems consolidation (post-encoding connectivity, change in representational neural overlap). To that aim, participants incidentally encoded sequences of objects in the fMRI scanner. Unbeknownst to participants, the first two objects of the presented ABC triplet sequences overlapped for a given pair of sequences. This allowed the authors to probe the integration of unique C objects that were never directly presented in the same sequence, but which shared the same preceding A and B objects. They encoded one set of objects on Day 1 (remote condition), another set of objects 24 hours later (recent condition) and tested implicit and explicit memory for the learned sequences on Day 2. They additionally collected baseline and post-encoding resting-state scans. As their measure of behavioral integration, the authors examined reaction time during an Old/New judgement task for C objects depending on if they were preceded by a C object from an overlapping sequence (primed condition) versus a baseline object. They found faster reaction times for the primed objects compared to the control condition for remote but not recently learned objects, suggesting that the C objects from overlapping sequences became integrated over time. They then examined pattern similarity in a priori ROIs as a measure of neural integration and found that participants showing evidence of integration of C objects from overlapping sequences in the medial prefrontal cortex for remotely learned objects also showed a stronger implicit priming effect between those C objects over time. When they examined the change in connectivity between their ROIs after encoding, they also found that connectivity between the posterior hippocampus and lateral occipital cortex correlated with larger priming effects for remotely learned objects, and that lateral occipital connectivity with the medial prefrontal cortex was related to neural integration of remote objects from overlapping sequences.
The authors aim to provide evidence of a relationship between behavioral and neural measures of integration with consolidation is interesting, important, and difficult to achieve given the longitudinal nature of studies required to answer this question. Strengths of this study include a creative behavioral task, and solid modelling approaches for fMRI data with careful control for several known confounds such as bold activation on pattern analysis results, motion, and physiological noise. The authors replicate their behavioral observations across two separate experiments, one of which included a large sample size, and found similar results that speak to the reliability of the observed behavioral phenomenon. In addition, they document several correlations between neural measures and task performance, lending functional significance to their neural findings.
Thank you for this positive assessment of our study!
However, this study is not without notable weaknesses that limit the strength of the manuscript. The authors report a behavioral priming effect suggestive of integration of remote but not recent memories, leading to the interpretation that the priming effect emerges with consolidation. However, they did not observe a reliable interaction between the priming condition and learning session (recent/remote) on reaction times, meaning that the priming effect for remote memories was not reliably greater than that observed for recent. In addition, the emergence of a priming effect for remote memories does not appear to be due to faster reaction times for primed targets over time (the condition of interest), but rather, slower reaction times for control items in the remote condition compared to recent. These issues limit the strength of the claim that the priming effect observed is due to C items of interest being integrated in a consolidation-dependent manner.
We acknowledge that the lack of a day by condition interaction in the behavioral priming effect should discussed and now discuss this data in a more nuanced manner. While it’s true that the priming effect emerges due to a slowing of the control items over time, this slowing is consistent with classic time-dependent effects demonstrating slower response times for more delayed memories. The fact that the response times in the primed condition does not show this slowing can be interpreted as a protection against this slowing that would otherwise occur. Please see page 29, lines 758-766, for this added discussion.
Similarly, the interactions between neural variables of interest and learning session needed to strongly show a significant consolidation-related effect in the brain were sometimes tenuous. There was no reliable difference in neural representational pattern analysis fit to a model of neural integration between the short and long delays in the medial prefrontal cortex or lateral occipital cortex, nor was the posterior hippocampus-lateral occipital cortex post-encoding connectivity correlation with subsequent priming significantly different for recent and remote memories. While the relationship between integration model fit in the medial prefrontal cortex and subsequent priming (which was significantly different from that occurring for recent memories) was one of the stronger findings of the paper in favor of a consolidation-related effect on behavior, is it possible that lack of a behavioral priming effect for recent memories due to possible issues with the control condition could mask a correlation between neural and behavioral integration in the recent memory condition?
While we acknowledge that lack of a statistically reliable interaction between neural measures and behavioral priming in many cases, we are heartened by the reliable difference in the relationship between mPFC similarity and priming over time, which was our main planned prediction. In addition to adding caveats in the discussion about the neural measures and behavioral findings in the recent condition (see our response to R1.1 and R1.4 for more details), we have added language throughout the manuscript noting the need to interpret these data with caution.
These limitations are especially notable when one considers that priming does not classically require a period of prolonged consolidation to occur, and prominent models of systems consolidation rather pertain to explicit memory. While the authors have provided evidence that neural integration in the medial prefrontal cortex, as well as post-encoding coupling between the lateral occipital cortex and posterior hippocampus, are related to faster reaction times for primed objects of overlapping sequences compared to their control condition, more work is needed to verify that the observed findings indeed reflect consolidation dependent integration as proposed.
We agree that more work is needed to provide converging evidence for these novel findings. However, we wish to counter the notion that systems consolidation models are relevant only for explicit memories. Although models of systems consolidation often mention transformations from episodic to semantic memory, the critical mechanisms that define the models involve changes in the neural ensembles of a memory that is initially laid down in the hippocampus and is taught to cortex over time. This transformation of neural traces is not specific to explicit/declarative forms of memory. For example, implicit statistical learning initially depends on intact hippocampal function (Schapiro et al., 2014) and improves over consolidation (Durrant et al., 2011, 2013; Kóbor et al., 2017).
Second, while there are many classical findings of priming during or immediately after learning, there are several instances of priming used to measure consolidation-related changes to newly learned information. For instance, priming has been used as a measure of lexical integration, demonstrating that new word learning benefits from a night of sleep (Wang et al., 2017; Gaskell et al., 2019) or a 1-week delay (Tamminen & Gaskell, 2013). The issue is not whether priming can occur immediately, it is whether priming increases with a delay.
Finally, it is helpful to think about models of memory systems that divide memory representations not by their explicit/implicit nature, but along other important dimensions such as their neural bases, their flexibility vs rigidity, and their capacity for rapid vs slow learning (Henke, 2010). Considering this evidence, we suggest that systems consolidation models are most useful when considering how transformations in the underlying neural memory representation affects its behavioral expression, rather than focusing on the extent that the memory representation is explicit or implicit.
With all this said, we have added text to the discussion reminding the reader that there was no statistically significant difference in priming as a function of the delay (page 29, lines 764 - 766). However, we are encouraged by the fact that the relationship between priming and mPFC neural similarity was significantly stronger for remotely learned objects relative to recently learned ones, as this is directly in line with systems consolidation theories.
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Author response:
Public Reviews:
Reviewer #1 (Public Review):
Summary:
In Drosophila melanogaster, expression of Sex-lethal (Sxl) protein determines sexual identity and drives female development. Functional Sxl protein is absent from males where splicing includes a termination codon-containing "poison" exon. Early during development, in the soma of female individuals, Sxl expression is initiated by an X chromosome counting mechanism that activates the Sxl establishment promoter (SxlPE) to produce an initial amount of Sxl protein. This then suppresses the inclusion of the "poison" exon, directing the constructive splicing of Sxl transcripts emerging from the Sxl maintenance promotor (SxlPM) which is activated at a later stage during development irrespective of sex. This autoregulatory loop maintains Sxl expression and commits to female development.
Sxl also determines the sexual identity of the germline. Here Sxl expression generally follows the same principles as in somatic tissues, but the way expression is initiated differs from the soma. This regulation has so far remained elusive.
In the presented manuscript, Goyal et al. show that activation of Sxl expression in the germline depends on additional regulatory DNA sequences, or sequences different from the ones driving initial Sxl expression in the soma. They further demonstrate that sisterless A (sisA), a transcription factor that is required for activation of Sxl expression in the soma, is also necessary, but not sufficient, to initiate the expression of functional Sxl protein in female germ cells. sisA expression precedes Sxl induction in the germline and its ablation by RNAi results in impaired expression of Sxl, formation of ovarian tumors, and germline loss, phenocopying the loss of Sxl. Intriguingly, this phenotype can be rescued by the forced expression of Sxl, demonstrating that the primary function of sisA in the germline is the induction of Sxl expression.
Strengths:
The clever design of probes (for RNA FISH) and reporters allowed the authors to dissect Sxl expression from different promoters to get novel insight into sex-specific gene regulation in the germline. All experiments are carefully controlled. Since Sxl regulation differs between the soma and the germline, somatic tissues provide elegant internal controls in many experiments, ensuring e.g. functionality of the reporters. Similarly, animals carrying newly generated alleles (e.g. genomic tagging of the Sxl locus) are fertile and viable, demonstrating that the genetic manipulation does not interfere with protein function. The conclusions drawn from the experimental data are sound and advance our understanding of how Sxl expression is induced in the female germline.
Weaknesses:
The assays employed by the authors provide valuable information on when Sxl promoters become active. However, since no information on the stability of the gene products (i.e. RNA and protein) is available, it remains unclear when the SxlPE promoter is switched off in the germline (conceptually it only needs to be active for a short time period to initiate production of functional Sxl protein). As correctly stated by the authors, the persisting signals observed in the germline might therefore not reflect the continuous activity of the SxlPE promoter.
Mapping of regulatory elements and their function: SxlPE with 1.5 kb of flanking upstream sequence is sufficient to recapitulate early Sxl expression in the soma. The authors now provide evidence that beyond that, additional DNA sequences flanking the SxlPE promoter are required for germline expression. However, a more precise mapping was not performed. Also, due to technical limitations, the authors could not precisely map the sisA binding sites. Since this protein is also involved in the somatic induction of Sxl, its binding sites likely reside in the region 1.5kb upstream of the SxlPE promoter, which has been reported to be sufficient for somatic regulation. The regulatory role of the sequences beyond SxlPE-1.5kb therefore remains unaddressed and it remains to be investigated which trans-acting factor(s) exert(s) its/their function(s) via this region.
We agree that a more precise mapping of the essential elements within the 10.2 kb reporter is an important direction in which to proceed. Unfortunately, this is out of the scope of the current manuscript given current lab personnel. In regard to the 1.5 kb promoter that activates SxlPE in the soma, we do not feel that the Sisa binding sites are necessarily in this region. It is important to note that, while the 1.5 kb promoter is sufficient for female-specific expression in the soma, it may not contain all of the regulatory elements that normally regulate PE from the endogenous locus. Activation of PE in the soma is thought to be regulated by a combination of positive-acting factors (SisA, SisB, etc.) and repressive factors (e.g. Dpn) that set a threshold for PE activation. Much more work would need to be done to determine whether all of these factors bind to the 1.5 kb promoter, or whether additional sequences are also involved to control the proper timing and robustness of normal Sxl PE activation in the soma.
The central question of how Sxl expression is initiated and controlled in the germline still remains unanswered. Since sisA is zygotically expressed in both the male and the female germline (Figure 4D), it is unlikely the factor that restricts Sxl expression to the female germline.
X chromosome “counting” elements like SisA are always expressed in both males and females, but it is thought that the 2X does of them in females activates PE, while the 1X does in males does not. Thus, we do expect SisA to be expressed in both males and females as we observed.
How does weak expression of Sxl in male tissues or expression above background after knockdown of sisA reconcile with the model that an autoregulatory feedback loop enforces constant and clonally inheritable Sxl expression once Sxl is induced? Is the current model for Sxl expression too simple or are we missing additional factors that modulate Sxl expression (such as e.g. Sister of Sex-lethal)? While I do not expect the authors to answer these questions, I would expect them to appropriately address these intriguing aspects in the discussion.
It is difficult to know what is “background” and what is actual weak Sxl expression in males. We agree that, if it is real, then why it doesn’t activate autoregulation of the Sxl PM transcript is mysterious. And yes, the current model for female-specific expression of Sxl in the soma may well be incomplete. Sxl PM transcript is present in the testis based on community RNA-seq data and our own analysis of male vs. female bam-mutant gonads (PMID 31329582), but it is at lower levels. Whether the lower level in the testis is due to tissue differences or sex-specific regulation of RNA levels is unknown. Our observations that the HA-tagged Sxl Early protein remains present in somatic cells in L1 larvae, and that GFP expression from the 10.2 kb Sxl PE-GFP can be detected in the soma until L2 could either be due to perdurance of the protein products, or continued sex-specific expression of PE long after the time that it was thought to shut off. This is also long after dosage compensation should have equalized the expression of X chromosome gene expression, meaning that X chromosomes can no longer be “counted” by factors like SisA and SisB. Thus, sex-specific expression of PE at this time would require another mechanism besides the current model (such as feedback regulation of Sxl PE transcription from downstream factors).
Reviewer #2 (Public Review):
Summary:
The authors wanted to determine whether cis-acting factors of Sxl - two different Sxl promoters in somatic cells - regulate Sxl in a similar way in germ cells. They also wanted to determine whether trans-acting factors known to regulate Sxl in the soma also regulate Sxl in the germline.
Regarding the cis-acting factors, they examine the Sxl "establishment promoter" (SxlPE) that is activated in female somatic cells by the presence of two X chromosomes. Slightly later in development, dosage compensation equalizes X chromosome expression in males and females and so X chromosomes can no longer be counted. The second Sxl promoter is the "maintenance promoter," (SxlPM), which is activated in both sexes. The mRNA produced from the maintenance promoter has to be alternatively splicing from early Sxl protein generated earlier in development by the PE. This leads to an autoregulatory loop that maintains Sxl expression in female somatic cells. The authors used fluorescent in situ hybridization (FISH) with oligopaints to determine the temporal activation of the PE or PM promoters. They find that - unlike the soma - the PE does not precede the PM and instead is activated contemporaneously or later than the PM - this is confusing with the later results (see below). Next, they generated transcriptional reporter constructs containing large segments of the Sxl locus, the 1.5 kb used in somatic studies, a 5.2 kb reporter, and a 10.2 kb. Interestingly the 1.5 kb reporter that was reported to recapitulate Sxl expression in soma and germline was not observed by the authors. The 5.2 kb reporter was observed in female somatic cells but not in germ cells. Only when they include an additional 5 kb downstream of the 5.2 kb reporter (here the 10.2 kb reporter) they did see expression in germ cells but this occurred at the L1 stages. Their data indicate that Sxl activity in the germ requires different cis-regulation than the soma and that the PE is activated later in germ cells than in somatic cells. The authors next use gene editing to insert epitope tags in two distinct strains in the hopes of creating an early Sxl and a later Sxl protein derived from the PE and PM, respectively. The HA-tagged protein from the PE was seen in somatic cells but never in the germline, possibly due to very low expression. The FLAG-tagged late Sxl protein is observed in L2 germ cells. Because the early HA-Sxl protein is not perceptible in germ cells, it is not possible to conclude its role in the germline. However, because late FLAG-Sxl was only observed in L2 germ cells and the PE was detected in L1, this leaves open the possibility that PE produces early HA-Sxl (which currently cannot be detected), which then alternatively splices the transcript from the PM. In other words, the soma and germline could have a similar temporal relationship between the two Sxl promoters. While I agree with the authors about this conclusion, the earlier work with the oligopaints leads to the conclusion that SE is active after PM. This is confusing.
The temporal relationship between Sxl PE and Sxl PM in the germline is indeed confusing. One source of confusion comes from whether one is discussing Sxl protein production or promoter activity. As the reviewer nicely summarizes, our transcription analysis with oligopaints indicates that, unlike in the soma, Sxl PE is NOT on in the germline prior to PM. Our other data indicate that PE is instead likely only active well after transcription from PM has begun. However, this still means that the temporal order of the EARLY and LATE Sxl proteins can be the same as the soma. Even if PM is active well before PE in the germline, the PE transcript cannot produce any functional protein in the absence of being alternatively spliced by the Sxl protein (Sxl autoregulation). Thus, even if PM is active before PE in the germline, we would not expect to observe any LATE Sxl protein until the PE promoter comes on, and produces a pulse of EARLY Sxl protein. The fact that we observe LATE Sxl protein at L2 is consistent with our observation that the 10.2 kb Sxl PE reporter is active at L1. We will attempt to explain all of this better in a revised manuscript.
Next, the authors wanted to turn their attention to the trans-acting factors that regulate Sxl in the soma, including Sisterless A (SisA), SisB, Runt, and the JAK/STAT ligand Unpaired. Using germline RNAi, the authors found that only knockdown of SisA causes ovarian tumors, similar to the loss of Sxl, suggesting that SisA regulates Sxl (ie the PE) in both the soma and the germline. They generated a SisA null allele using CRISPR/Cas9 and these animals had ovarian tumors and germ cell-less ovaries. FISH revealed that sisA is activated in primordial germ cells in stages 3-6 before the activation of Sxl. They used CRISPR-Cas9 to generate an endogenously-tagged SisA and found that tagged SisA was expressed in stage 3-6 PCGs, which is consistent with activating PE in the germline. They showed that sisA is upstream of Sxl as germline depletion of sisA led to a significant decrease in expression from the 10.2 kb PE reporter and in SXL protein. The authors could rescue the ovarian tumors and loss of Sxl protein upon germline depletion of sisA by supplying Sxl from another protein (the otu promoter). These data indicate that sisA is necessary for Sxl activation in the germline. However, ectopic sisA in germ cells in the testis did not lead to ectopic Sxl, suggesting that sisA is not sufficient to activate Sxl in the germline.
Strengths:
(1) The genetic and genomic approaches in this study are top-notch and they have generated reagents that will be very useful for the field.
(2) Excellent use of powerful approaches (oligo paint, reporter constructs, CRISPR-Cas9 alleles).
(3) The combination of state of art approaches and quantification of phenotypes allows the authors to make important conclusions.
Weaknesses:
(1) Confusion in line 127 (this indicates that SxlPE is not activated before SxlPM in the germline) about PE not being activated before the PM in the germline when later figures show that PE is activated in L1 and late Sxl protein is seen in L2. It would be helpful to the readers if the authors edited the text to avoid this confusion. Perhaps more explanation of the results at specific points would be helpful.
We agree--see response above.
Reviewer #3 (Public Review):
Summary:
The mechanisms governing the initial female-specific activation of Sex-lethal (Sxl) in the soma, the subsequent maintenance of female-specific expression and the various functions of Sxl in somatic sex determination and dosage compensation are well documented. While Sxl is also expressed in the female germline where it plays a critical role during oogenesis, the pathway that is responsible for turning Sxl on in germ cells has been a long-standing mystery. This manuscript from Goyal et al describes studies aimed at elucidating the mechanism(s) for the sex-specific activation of the Sex-lethal (Sxl) gene in the female germline of Drosophila.
In the soma, the Sxl establishment promoter, Sxl-Pe, is regulated in pre-cellular blastoderm embryos in somatic cells by several X-linked transcription factors (sis-a, sis-b, sis-c and runt). At this stage of development, the expression of these transcription factors is proportional to gene dose, 2x females and 1x in males. The cumulative two-fold difference in the expression of these transcription factors is sufficient to turn Sxl-Pe on in female embryos. Transcripts from the Sxl-Pe promoter encode an "early" version of the female Sxl protein, and they function to activate a splicing positive autoregulatory loop by promoting the female-specific splicing of the initial pre-mRNAs derived from the Sxl maintenance promoter, Sxl-Pm (which is located upstream of Sxl-Pm). These female Sxl-Pm mRNAs encode a Sxl protein with a different N-terminus from the Sxl-Pe mRNAs, and they function to maintain female-specific splicing in the soma during the remainder of development.
In this manuscript, the authors are trying to understand how the Sxl-Pm positive autoregulatory loop is established in germ cells. If Sxl-Pe is used and its activation precedes Sxl-Pm as is true in the soma, they should be able to detect Sxl-Pe transcripts in germ cells before Sxl-Pm transcripts appear. To test this possibility, they generated RNA FISH probes complementary to the Sxl-Pe first exon (which is part of an intron sequence in the Sxl-Pm transcript) and to a "common sequence" that labels both Sxl-Pe and Sxl-Pm transcripts. Transcripts labeled by both probes were detected in germ cells beginning at stage 5 (and reaching a peak at stage 10), so either the Sxl-Pm and Sxl-Pe promoters turn on simultaneously, or Sxl-Pe is not active.
They next switched to Sxl-Pe reporters. The first Sxl-Pe:gfp reporter they used has a 1.5 kb upstream region which in other studies was found to be sufficient to drive sex-specific expression in the soma of blastoderm embryos. Also like the endogenous Sxl gene it is not expressed in germ cells at this early stage. In 2011, Hashiyama et al reported that this 1.5 kb promoter fragment was able to drive gfp expression in Vasa-positive germ cells later in development in stage 9/10 embryos. However, because of the high background of gfp in the nearby soma, their result wasn't especially convincing. Though they don't show the data, Goyal et al indicated that unlike Hashiyama et al they were unable to detect gfp expressed from this reporter in germ cells. Goyal et al extended the upstream sequences in the reporter to 5 kb, but they were still unable to detect germline expression of gfp.
Goyal et al then generated a more complicated reporter which extends 5 kb upstream of the Sxl-Pe start site and 5 kb downstream-ending at or near 4th exon of the Sxl-Pm transcript (the Sxl-Pe10 kb reporter). (The authors were not explicit as to whether the 5 kb downstream sequence extended beyond the 4th exon splice junction-in which case splicing could potentially occur with an upstream exon(s)-or terminated prior to the splice junction as seems to be indicated in their diagram.) With this reporter, they were able to detect sex-specific gfp expression in the germline beginning in L1 (first instar larva). With the caveat that gfp detection might be delayed compared to the onset of reporter activation, these findings indicated that the sequences in the reporter are able to drive sex-specific transcription in the germline at least as early as L1.
The authors next tagged the N-terminal end of the Sxl-Pe protein with HA (using Crispr/Cas9) and the N-terminal end of Sxl-Pm protein with Flag. They report that the HA-Sxl-Pe protein is first detected in the soma at stage 9 of embryogenesis. Somatic HA-Sxl-Pe protein persists into L1, but is no longer detected in L2. However, while somatic HA-Sxl-Pe protein is detected, they were unable to detect HA-Sxl-Pe protein in germ cells. In the case of FLAG-Sxl-Pm, it could first be detected in L2 germ cells indicating that at this juncture the Sxl-positive autoregulatory loop has been activated. This contrasts with Sxl-Pm transcripts which are observed in a few germ cells at stage 5 of embryogenesis, and in most germ cells by stage 10. The authors propose (based on the expression pattern of the Sxl-Pe10kb reporter and the appearance of Flag-Sxl-Pm protein) that Sxl-Pe comes on in germ cells in L1, and that the Sxl-Pe protein activates the female splicing of Sxl-Pm transcripts, giving detectable Flag-Sxl-Pm proteins beginning in L2.
To investigate the signals that activate Sxl-Pe in germ cells, the authors tested four of the X-linked genes (sis-a, sis-b, sis-c, and runt) that function to activate Sxl-Pe in the soma in early embryos. RNAi knockdown of sis-b, sis-c, and runt had no apparent effect on oogenesis. In contrast, knockdown of sis-a resulted in tumorous ovaries, a phenotype associated with Sxl mutations. (Three different RNAi transgenes were tested-two gave this phenotype, the third did not.) Sxl-Pe10kb reporter activity in L1 female germ cells is also dependent on sis-A.
Several approaches were used to confirm a role for sis-a in a) oogenesis and b) the activation of the Sxl-Pm autoregulatory loop. They showed that sis-a germline clones (using tissue-specific Crispr/Cas9 editing) resulted in the tumorous ovary phenotype and reduced the expression of Sxl protein in these ovaries. They found that sis-a transcripts and GFP-tagged Sis-A protein are present in germ cells. Finally, they showed tumorous ovary phenotype induced by germline RNAi knockdown of sis-a can be partially rescued by expressing Sxl in the germ cells.
Critique:
While this manuscript addresses a longstanding puzzle - the mechanism activating the Sxl autoregulatory loop in female germ cells-and likely identified an important germline transcriptional activator of Sxl, sis-a, the data that they've generated doesn't make a compelling story. At every step, there are puzzle pieces that don't fit the narrative. In addition, some of their findings are inconsistent with many previous studies.
We respect and appreciate this reviewer for the detailed comments. However, we feel that the claim that our work doesn’t “make a compelling story” and that many “pieces…don’t fit the narrative” is incorrect. The main issue that this reviewer raises is that we do not know if Sxl “early” transcription in the germline initiates from the Pe promoter. This is true, which we fully acknowledge, but the detail of whether “germline early” transcription of Sxl initiates from Pe or from other, as yet undefined, germline promoter does not affect the main conclusions of the paper. These conclusions are that a) regulation of Sxl in the germline is fundamentally different from in the soma and 2) despite point (1), sisA acts as an activator of Sxl in both the soma and the germline. Neither of these main points is disputed by this reviewer.
(1) The authors used RNA FISH to time the expression of Sxl-Pe and Sxl-Pm transcripts in germ cells. Transcripts complementary to Sxl-Pe and Sxl-Pm were detected at the same time in embryos beginning at stage 5. This is not a definitive experiment as it could mean a) that Sxl-Pe and Sxl-Pm turn on at the same time, b) that Sxl-Pe comes on after Sxl-Pm (as suggested by the Sxl-Pe10kb reporter) or c) Sxl-Pe never comes on.
When designing this experiment, we wanted to test whether the “soma model” of Pe activation before Pm was also true in the germ cells. Our data clearly demonstrate that transcripts beginning downstream of Pe are not expressed prior to transcripts beginning downstream of Pm. Thus, we can state that the “soma model” of Pe first and then Pm does not occur in the germline, which is very interesting. However, we cannot make any other conclusions about Pe in the germline from these data, as the reviewer indicates.
(2) Hashiyama et al reported that they detected gfp expression in stage 9/10 germ cells from a 1.5 kb Sxl-Pe-gfp. As noted above, this result wasn't entirely convincing and thus it isn't surprising that Goyal et al were unable to reproduce it. Extending the upstream sequences to just before the 1st exon of Sxl-Pm transcripts also didn't give gfp expression in germ cells. Only when they added 5 kb downstream did they detect gfp expression. However, from this result, it isn't possible to conclude that the Sxl-Pe promoter is actually driving gfp expression in L1 germ cells. Instead, the Sxl promoter active in the germ line could be anywhere in their 10 kb reporter.
We agree that we have not determined the transcriptional start sites for Sxl in the germline and it is possible that the 10.2 kb reporter uses a different promoter than Pe, as long as that transcript can also be spliced into exon 4 where the GFP tag has been placed. The three types of experiments conducted—FISH to regions of the nascent transcripts, tagged versions of the different predicted ORFs, and promoter-GFP constructs—are extensive, but all have different limitations. Indeed, it would be challenging to determine the transcription start sites in the germline, as it would require obtaining enough L1 larvae to be able to dissociate the animals, or isolated gonads, into single cells in order to FACS purify the germ cells for RACE or long-read sequencing (I’m not sure that L1 larval single-nucleus seq would be enough for calling start sites). Otherwise, there would be no way to determine if expected or unexpected transcripts came from the soma or the germline. We can consider these experiments in the future.
Fortunately, the main conclusions from this paper do not require knowing whether the germline uses Pe or some other “germline early” promoter that can produce Sxl protein in the absence of autoregulation by existing Sxl protein. The observations that a nascent transcript including the region downstream of Pm is observed in embryonic germ cells, but that the tagged LATE protein is not observed until L2, suggest that the transcript produced in early germ cells cannot produce a functional protein. This is consistent with the need for Sxl autoregulation of the Pm transcript in the germline as in the soma, as was previously thought. This is further supported by the observations that activity of the 10.2 kb reporter is only observed in L1 germ cells, and that the LATE Sxl protein is only observed in germ cells after this point. Thus, we can conclude that either Pe, or another “germline early” promoter, acts to produce female-specific Sxl protein to initiate autoregulation of Sxl splicing and protein production in the germline. We feel that this is a significant advance for the field, and we will make it more clear in the text that the initial expression of Sxl in the germline may not be from the Pe promoter.
Other conclusions of the manuscript are unaffected by the start site for “germline early” Sxl transcription, including that the germline activates Sxl protein expression much later than the soma, which calls into question previous work indicating an early role for Sxl in the germline. Also unaffected is our conclusion that different enhancer sequences are required for activation of Sxl expression in the germline than in the soma, consistent with previous work demonstrating that the genetics of Sxl activation in the germline are different than in the soma. Lastly, our conclusions that sisA acts upstream of Sxl, and is required for Sxl germline expression, either directly or indirectly, are also unaffected by the nature of the Sxl “germline early” start site.
(3) At least one experiment suggests that Sxl-Pe never comes on in germ cells. The authors tagged the N-terminus of the Sxl-Pe protein with HA and the N-terminus of the Sxl-Pm protein with Flag. Though they could detect HA-Sxl-Pe protein in the soma, they didn't detect it in germ cells. On the other hand, the Flag-Sxl-Pm protein was detected in L2 germ cells (but not earlier). These results would more or less fit with those obtained for the 10 kb reporter and would support the following model: Prior to L1, Sxl-Pm transcripts are expressed and spliced in the male pattern in both male and female germ cells. During L1, Sxl protein expressed via a mechanism that depends upon a 10 kb region spanning Sxl-Pe (but not on Sxl-Pe) is produced and by L2 there are sufficient amounts of this protein to switch the splicing of Sxl-Pm transcripts from a male to a female pattern-generating Flag-tagged Sxl-Pm protein.
As described above, it is indeed possible that another promoter besides Pe is active as the “germline early” promoter. We will make this more clear in a revised version, but the major conclusions of the manuscript are unaffected.
(4) The 10kb reporter is sex-specific, but not germline-specific. The levels of gfp in female L1 somatic cells are equal to if not greater than those in L1 female germ cells. That the Sxl-Pe10kb reporter is active in the soma complicates the conclusion that it represents a germ line-specific promoter. Germline activity is, however, sensitive to sis-A knockdowns which is plus. Presumably, somatic expression of the reporter wouldn't be sensitive to a (late) sis-A knockdown- but this wasn't shown.
We are confused by this comment because we do not conclude that the Pe is a germline-specific promoter. Pe is known to be expressed in the soma, from considerable previous work cited by this reviewer, and the simplest model is that Pe is used in both the soma and the germline, as reflected by our 10.2 kb reporter. It is actually quite interesting how late this promoter seems active in the soma, contrary to current dogma, but we did not study somatic activation of Sxl in this work.
(5) Their results with the HA-Sxl-Pe protein don't fit with many previous studies-assuming that the authors have explained their results properly. They report that HA-Sxl-Pe protein is first detected in the soma at stage 9 of embryogenesis and that it then persists till L2. However, previous studies have shown that Sxl-Pe transcripts and then Sxl-Pe proteins are first detected in ~NC11-NC12 embryos. In RNase protection experiments, the Sxl-Pe exon is observed in 2-4 hr embryos, but not detected in 5-8 hr, 14-12 hr, L1, L2, L3, or pupae. Northerns give pretty much the same picture. Western blots also show that Sxl-Pe proteins are first detectable around the blastoderm stage. So it is not at all clear why HA-Sxl-Pe proteins are first observed at stage 9 which, of course, is well after the time that the Sxl-Pm autoregulatory loop is established.
Given the obvious problems with the initial timing of somatic expression described here, it is hard to know what to make of the fact that HA-tagged Sxl-Pe proteins aren't observed in germ cells.
As for the presence of HA-Sxl-Pe proteins later than expected: While RNase protection/Northern experiments showed that Sxl-Pe mRNAs are expressed in 2-4 hr embryos and disappear thereafter, one could argue from the published Western experiments that the Sxl-PE proteins expressed at the blastoderm stage persist at least until the end embryogenesis, though perhaps at somewhat lower levels than at earlier points in development. So the fact that Goyal et al were able to detect HA-Sxl-Pe proteins in stage 9 embryos and later on in L1 larva probably isn't completely unexpected. What is unexpected is that the HA-Sxl-Pe proteins weren't present earlier.
We thank the reviewer for this detailed analysis. Since we were not focused on somatic expression of Sxl in this work, it is possible that stage 9 was the earliest stage we observed in our experiments, rather than the earliest stage in which it is ever observed. We will repeat these experiments to verify when the HA-tagged early Sxl protein is first observed. However, these comments have no bearing on our conclusions about Sxl expression in the germline, which is the focus of this manuscript.
(6) The authors use RNAi and germline clones to demonstrate that sis-A is required for proper oogenesis: when sis-A activity is compromised in germ cells, i) tumorous ovary phenotypes are observed and ii) there is a reduction in the expression of Sxl-Pm protein. They are also able to rescue the phenotypic effects of sis-a knockdown by expressing a Sxl-Pm protein. While the experiments indicating sis-a is important for normal oogenesis and that at least one of its functions is to ensure that sufficient Sxl is present in the germline stem cells seem convincing, other findings would make the reader wonder whether Sis-A is actually functioning (directly) to activate Sxl transcription from promoter X.
It is true that we do not know the binding specificity for SisA, which is why we have made no claims about the directness of SisA regulation of Sxl. This does not change our conclusions that sisA is upstream of Sxl activation, since loss of sisA function has a similar phenotype to loss of Sxl, loss of sisA blocks Sxl protein expression, and expression of Sxl rescues the sisA mutant phenotype.
The authors show that sis-a mRNAs and proteins are expressed in stage 3-5 germ cells (PGCs). This is not unexpected as the X-linked transcription factors that turn Sxl-Pe on are expressed prior to nuclear migration, so their protein products should be present in early PGCs. The available evidence suggests that their transcription is shut down in PGCs by the factors responsible for transcriptional quiescence (e.g., nos and pgc) in which case transcripts might be detected in only one or two PGC-which fits with their images. However, it is hard to believe that expression of Sis-A protein in pre-blastoderm embryos is relevant to the observed activation of the Sxl-Pm autoregulatory loop hours later in L2 larva.
It is also not clear how the very low level of gfp-Sis-A seen in only a small subset of migrating germ cells in stage 10 embryos (Figure S6) would be responsible for activating the Sxl-Pe10kb reporter in L1. It seems likely that the small amount of protein seen in stage 10 embryos is left over from the pre-cellular blastoderm stage. In this case, it would not be surprising to discover that the residual protein is present in both female and male stage 10 germ cells. This would raise further doubts about the relevance of the gfp-Sis-A at these early stages.
In fact, given the evidence presented implicating sis-a in activating Sxl, (the germline activation of the Sxl-Pe10kb reporter, the RNAi knockdowns, and the germ cell-specific sis-a clones) it is clear that the sis-A RNAs and proteins seen in pre-cellular blastoderm PGCs aren't relevant. The germline clone experiment (and also the RNAi knockdowns) indicates that sis-A must be transcribed in germ cells after Cas9 editing has taken place. Presumably, this would be after transcription is reactivated in the germline (~stage 10) and after the formation of the embryonic gonad (stage 14) so that the somatic gonadal cells can signal to the germ cells. With respect to the reporter, the relevant time frame for showing that sis-A is present in germ cells would be even later in L1.
The reviewer is correct in wondering how early sisA transcription can affect late Sxl activation, and we are clear about this conundrum in our manuscript. However, they are incorrect about the early sisA expression. Our experiments examining nascent sisA transcripts indicate that sisA is zygotically expressed in the formed germ cells rather than being leftover from expression in early nuclei. The fact that only a portion of germ cells express sisA at any time may well be due to a timing issue, where not all germ cells express sisA at the same time. They are also incorrect about the timing of Cas9 editing in the germline—the guide RNAs are expressed from a general promoter that is active both maternally and in the early embryo, and the Cas9 RNA from the nos promoter is deposited in the germ plasm where it is translated long before cellularization, meaning that sisA CRISPR knockout can begin at the earliest stages of germ cell formation or before.
(7) As noted above, the data in this manuscript do not support the idea that Sxl-Pe proteins activate the Sxl-Pm female splicing in the germline. Flybase indicates that there is at least one other Sxl promoter that could potentially generate a transcript that includes the male exon but still could encode a Sxl protein. This promoter "Sxl-Px" is located downstream of Sxl-Pm and from its position it could have been included in the authors' 10 kb reporter. The reported splicing pattern of the endogenous transcript skips exon2, and instead links an exon just downstream of Sxl-Px to the male exon. The male exon is then spliced to exon4. If the translation doesn't start and end at one of the small upstream orfs in the exons close to Sxl-Px and the male exon, a translation could begin with an AUG codon in exon4 that is in frame with the Sxl protein coding sequence. This would produce a Sxl protein that lacks aa sequences from N-terminus, but still retains some function.
Another possible explanation for how gfp is expressed from the 10 kb reporter is that the transcript includes the "z" exon described by Cline et al., 2010.
As discussed above, the exact location of the start site for the Sxl transcript in the germline remains to be determined, but does not affect the main conclusions of the paper.
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- Aug 2024
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What typwriter-related project(s) are you working on this weekend?
Maybe you're:
- Learning about typewriters for a future purchase?
- Contemplating buying your first machine?
- Visiting a local typewriter shop?
- Trolling Ebay, Facebook Marketplace, ShopGoodwill, CraigsList, OfferUp for your next machine?
- Buying new ribbon?
- Reading books about typewriters and their history?
- Reading typewritten literature?
- Are you out hunting for a new machine at yard/tag/garage sales or antique vintage shops?
- Exploring a new typewriter for the first time?
- Logging your machines into the typewriter database?
- Cleaning, repairing, or restoring a machine?
- Reading up on typewriter repair?
- Writing something for fun?
- Typing a post for the typosphere or One Typed Page?
- Visiting a typewriter museum?
- Watching videos about typewriters on YouTube?
- Something else?
Let us know what you're doing in the comments...
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www.sciencedirect.com www.sciencedirect.com
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NPC; chromatin organization; cross-linking mass spectrometry; cryo-electron tomography; cryo-focused-ion-beam milling; in-cell structural biology; integrative modeling; mRNA transport; nuclear basket; nuclear pore complex; subtomogram analysis.
denem 123
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learn.cantrill.io learn.cantrill.io
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Welcome back, and in this demo lesson, I want to give you some experience working with Service Control Policies (SCPs).
At this point, you've created the AWS account structure which you'll be using for the remainder of the course. You've set up an AWS organization, with the general account that created it becoming the management account. Additionally, you've invited the production AWS account into the organization and created the development account within it.
In this demo lesson, I want to show you how you can use SCPs to restrict what identities within an AWS account can do. This is a feature of AWS Organizations.
Before we dive in, let's tidy up the AWS organization. Make sure you're logged into the general account, the management account of the organization, and then navigate to the organization's console. You can either type that into the 'Find Services' box or select it from 'Recently Used Services.'
As discussed in previous lessons, AWS Organizations allows you to organize accounts with a hierarchical structure. Currently, there's only the root container of the organization. To create a hierarchical structure, we need to add some organizational units. We will create a development organizational unit and a production organizational unit.
Select the root container at the top of the organizational structure. Click on "Actions" and then "Create New." For the production organizational unit, name it 'prod.' Scroll down and click on "Create Organizational Unit." Next, do the same for the development unit: select 'Route,' click on "Actions," and then "Create New." Under 'Name,' type 'dev,' scroll down, and click on "Create Organizational Unit."
Now, we need to move our AWS accounts into these relevant organizational units. Currently, the Development, Production, and General accounts are all contained in the root container, which is the topmost point of our hierarchical structure.
To move the accounts, select the Production AWS account, click on "Actions," and then "Move." In the dialogue that appears, select the Production Organizational Unit and click "Move." Repeat this process for the Development AWS account: select the Development AWS account, click "Actions," then "Move," and select the 'dev' OU before clicking "Move."
Now, we've successfully moved the two AWS accounts into their respective organizational units. If you select each organizational unit in turn, you can see that 'prod' contains the production AWS account, and 'dev' contains the development AWS account. This simple hierarchical structure is now in place.
To prepare for the demo part of this lesson where we look at SCPs, move back to the AWS console. Click on AWS, then the account dropdown, and switch roles into the production AWS account by selecting 'Prod' from 'Role History.'
Once you're in the production account, create an S3 bucket. Type S3 into the 'Find Services' box or find it in 'Recently Used Services' and navigate to the S3 console. Click on "Create Bucket." For the bucket name, call it 'CatPics' followed by a random number—S3 bucket names must be globally unique. I’ll use 1, lots of 3s, and then 7. Ensure you select the US East 1 region for the bucket. Scroll down and click "Create Bucket."
After creating the bucket, go inside it and upload some files. Click on "Add Files," then download the cat picture linked to this lesson to your local machine. Upload this cat picture to the S3 bucket by selecting it and clicking "Open," then "Upload" to complete the process.
Once the upload finishes, you can view the picture of Samson. Click on it to see Samson looking pretty sleepy. This demonstrates that you can currently access the Samson.jpg object while operating within the production AWS account.
The key point here is that you’ve assumed an IAM role. By switching roles into the production account, you’ve assumed the role called "organization account access role," which has the administrator access managed policy attached.
Now, we’ll demonstrate how this can be restricted using SCPs. Move back to the main AWS console. Click on the account dropdown and switch back to the general AWS account. Navigate to AWS Organizations, then Policies. Currently, most options are disabled, including Service Control Policies, Tag Policies, AI Services, Opt-out Policies, and Backup Policies.
Click on Service Control Policies and then "Enable" to activate this functionality. This action adds the "Full AWS Access" policy to the entire organization, which imposes no restrictions, so all AWS accounts maintain full access to all AWS services.
To create our own service control policy, download the file named DenyS3.json linked to this lesson and open it in a code editor. This SCP contains two statements. The first statement is an allow statement with an effect of allow, action as star (wildcard), and resource as star (wildcard). This replicates the full AWS access SCP applied by default. The second statement is a deny statement that denies any S3 actions on any AWS resource. This explicit deny overrides the explicit allow for S3 actions, resulting in access to all AWS services except S3.
Copy the content of the DenyS3.json file into your clipboard. Move back to the AWS console, go to the policy section, and select Service Control Policies. Click "Create Policy," delete the existing JSON in the policy box, and paste the copied content. Name this policy "Allow all except S3" and create it.
Now, go to AWS Accounts on the left menu, select the prod OU, and click on the Policies tab. Attach the new policy "Allow all except S3" by clicking "Attach" in the applied policies box. We will also detach the full AWS access policy directly attached. Check the box next to full AWS access, click "Detach," and confirm by clicking "Detach Policy."
Now, the only service control policy directly attached to production is "Allow all except S3," which allows access to all AWS products and services except S3.
To verify, go back to the main AWS console and switch roles into the production AWS account. Go to the S3 console and you should receive a permissions error, indicating that you don't have access to list buckets. This is because the SCP attached to the production account explicitly denies S3 access. Access to other services remains unaffected, so you can still interact with EC2.
If we switch back to the general account, reattach the full AWS access policy, and detach "Allow all except S3," the production account will regain access to S3. By following the same process, you’ll be able to access the S3 bucket and view the object once again.
This illustrates how SCPs can be used to restrict access for identities within an AWS account, in this case, the production AWS account.
To clean up, delete the bucket. Select the catpics bucket, click "Empty," type "permanently delete," and select "Empty." Once that's done, you can delete the bucket by selecting it, clicking "Delete," confirming the bucket name, and then clicking "Delete Bucket."
You’ve now demonstrated full control over S3, evidenced by successfully deleting the bucket. This concludes the demo lesson. You’ve created and applied an SCP that restricts S3 access, observed its effects, and cleaned up. We’ll discuss more about boundaries and restrictions in future lessons. For now, complete this video, and I'll look forward to seeing you in the next lesson.
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www.biorxiv.org www.biorxiv.org
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Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.
Learn more at Review Commons
Reply to the reviewers
We thank the reviewers for going through our manuscript and providing valuable feedback. We are grateful to all 3 reviewers for describing our findings as important and valuable, well-designed and robust, and of value to the Parkinson's and Crohn's disease communities studying LRRK2. Below we detail a point-by-point response to the reviewers.
__Reviewer #1 (Evidence, reproducibility and clarity (Required)): __
The paper by Dikovskaya and collaborators investigated the activitiy and expression of LRRK2 in different subtypes of splenic and intestinal immune cells, taking advantage of a novel GFP-Lrrk2 knockin mouse. Interestingly, they found that T-cell-released IL-4 stimulates Lrrk2 expression in B cells. I have a few comments and suggestions for the authors. 1) Figure 1C. LRRK2 KO cells display residual Rab10 phosphorylation. Do the authors have any idea of which kinase other than LRRK2 could be involved in this phosphorylation?
As far as we are aware no other kinase is known to phosphorylate Rab10 at T73 in vivo. In vitro, recombinant Rab10 can be phosphorylated by MST3 at this site (Knebel A. et al, protocols.io https://dx.doi.org/10.17504/protocols.io.bvjxn4pn), but its relevance in vivo or in cells has not been shown. It is possible that the residual band recognised by anti-pT73 Rab10 ab in splenocytes is unspecific background, as it is mainly seen in LRRK2 KO spleen cells and not in other tissues. But to be certain that our assay assesses LRRK2-dependent Rab10 phosphorylation, we have always compared with the MLi-2 control.
2) Since there are no good antibodies for IF/IHC as pointed by the authors, the GFP-Lrrk2 mouse gives the opportunity to check endogenous LRRK2 localization, i.e. in cells untreated or treated with IL-4 or other cytokines. Also, does endogenous GFP-LRRK2 accumulate into filaments/puncta upon MLi2 inhibition? The relocalization into filaments of inhibited LRRK2 has been observed in overexpression but not under endogenous expression. This analysis would be interesting also in light of the observed side effect of type-I inhibitors.
We thank the reviewer for this suggestion. We will attempt a super-resolution microscopy using Airyscan with isolated B-cells treated with cytokine and/or LRRK2 inhibitor to address this question.
3) Figure 5. The authors need to label more clearly the graphs referring to wt mice versus GFP-Lrrk2 KI mice.
We have now labelled the panels referring to the WT mice only with "WT mice", to distinguish them from the other panels that incorporate data from both EGFP-Lrrk2 mice and their WT littermates used as a background.
They should also replace GFP-LRRK2 with GFP-Lrrk2 since they edited the endogenous murine gene.
Thank you, we have corrected it, and also the other mouse genotypes.
4) In the material and methods MLi-2 administration in mice is indicated at 60 mg/kg for 2 hr whereas in suppl. figure 5 the indicated dose is 30 mg/kg. Please correct with the actual dose used.
Thank you, we have corrected the mistake.
5) The discovery of IL-4 as a Lrrk2 activator in B cells is a very interesting and novel finding. The authors could take advantage of the GFP tag to investigate LRRK2 interactome upon IL-4 stimulation (optional). Also, is the signaling downstream of IL-4 attenuated in Lrrk2 KO cells?
We thank the reviewer for these interesting suggestions. The role of LRRK2 in IL-4 activated B-cells is currently under active research in the lab.
Reviewer #1 (Significance (Required)):
The manuscript is well designed and organized, and the experimental approaches are robust. These results are significant for the field as they add additional layers in the complex regulation and regulatory roles of LRRK2 in immunity, with implication for inflammatory disorders and Parkinson's disease.
We thank the reviewer for their positive comments and for recognising our efforts to provide some clarity to a complex field.
__Reviewer #2 (Evidence, reproducibility and clarity (Required)): __
The authors present a flow cytometry methodology to assess LRRK2 expression and pathway markers in mouse models and explore LRRK2 in splenic and intestinal immune cells. This is a highly valuable study given the emerging understanding that LRRK2 pathway activity in peripheral tissues may be of crucial importance to Parkinson's disease and Crohn's disease. P8 : the authors state that their results indicate 'that the effects of LRRK2-R1441C mutation and inflammation on LRRK2 activity represent two different parallel pathways'. This seems like an overinterpretation as pathway suggests the presence of additional partners in the pathway while R1441C is a LRRK2 intrinsic modification. The results can equally be explained by synergistic effects between both activation mechanisms (mutant and inflammation).
We agree with the reviewer, and have added this into the text. The sentence now reads "suggesting that the LRRK2-R1441C mutation and inflammation have different impacts on LRRK2 activity, either in parallel or in synergy."
Methods and experiment descriptions in results : the authors appear to use the terms anti-CD3 stimulation and CD3 stimulation interchangeably, although it is not always clear in the text that these are synonymous. This should be clarified.
We thank reviewer for pointing out this error on our part. We have made the necessary changes to always refer to the stimulation as anti-CD3.
One major observation in this paper is that LRRK2 is not detected in gut epithelial cells as previously has been reported. It would be useful to comment on any differences between the presented protocol and the previous reports, in particular relating to the antigen retrieval step. In order to reinforce the finding, it would be useful to include in situ hybridization data that could further strengthen the observations of which cellular subtypes express LRRK2 and which do not. Indeed, while the KO control shows that there is an unacceptable high non-specific staining, it does not prove absence of expression. Also, can any conclusions be made about expression of LRRK2 in neural cells of the gut? This important information on LRRK2 detection in gut should be mentioned in the abstract and highlighted in the discussion.
We thank the reviewer for pointing this out. In fact, we think the observation that LRRK2 is not detected in epithelial cells is so important that we have a separate manuscript exploring this point. Please see 1. Tasegian, A. et al.https://doi.org/10.1101/2024.03.07.582590 (2024). In this manuscript we have explored the expression of LRRK2 in human and murine intestinal epithelial cells using qPCR. Although we do not have in situ hybridization data, we believe that using both the EGFP-LRRK2 and the pRab10 flow cytometry, as well as qPCR and proteomics on selected cell types, corroborates our findings on the cell types that express LRRK2. We did not analyse LRRK2 expression in the neural cells of the gut, as the focus was on the immune cells, however we hope that others will use the tools developed here to explore this further.
The authors mention in the discussion that they 'show for the first time that eosinophils also express active LRRK2 at levels comparable to B-cells and DCs.' The relevance of this finding should be further developed. Why is this important?
We thank the reviewer for this point. We don't know how LRRK2 is important in these cells. However, as the role of LRRK2 in eosinophils and neutrophils has not yet been explored and both cell types play important roles in IBD, we think it is important to point out. We have now added a sentence to the discussion highlighting the importance of eosinophils in IBD. "Since eosinophils have recently been implicated as key player in intestinal defense and colitis(Gurtner et al, 2022), it will be interesting to evaluate LRRK2 functions in these cells."
In the isolation of lamina propria cells, what efforts were made to characterize the degree of purification of the lamina propria cells compared to cells of other gut wall layers such as epithelium, muscularis mucosa, or deeper layers? Please specify.
Isolation of lamina propria cells is a very well-established process (LeFrancois and Lycke, 'Isolation of Mouse Small Intestinal Intraepithelial Lymphocytes, Peyer's Patch, and Lamina Propria Cells.' Curr. Protocols in Immunology 2001), where we extensively wash off the epithelial layer before digesting the tissue for the LP. After the digestion the muscle and wall of the gut are still intact, so we do not get any contamination with other deeper layers. The subsets of cells we find in the LP are in line with isolations from other labs.
Minor comments Figure 5G, for the graphs indicating LRRK2 activity and LRRK2 phosphorylation, the specific measures should be specified in the graph titles to avoid any ambiguity (pT73-Rab10, pS935-LRRK2).
We have added the specifications to the new version of the figure.
Suppl figure 1 : please specify the figure label and abbreviation AF568 in the legend. Suppl figure 2 : please specify the figure label and abbreviation anti-rb in the legend
Thank you, we added the abbreviations to the legends. The Figure labels for both figures have been already included at the top of figure legends.
Reviewer #2 (Significance (Required)):
The authors present a flow cytometry methodology to assess LRRK2 expression and pathway markers in mouse models and explore LRRK2 in splenic and intestinal immune cells. This is a highly valuable study given the emerging understanding that LRRK2 pathway activity in peripheral tissues may be of crucial importance to Parkinson's disease and Crohn's disease.
We thank the reviewer for recognising the value of this study.
Reviewer #3
Evidence, reproducibility and clarity
The paper describes a set of experiments to analyse LRRK2 activity in tissues and despite it has very important findings and technical developments is largely descriptive. It does look like a collection of experiments more than a defined hypothesis and experiments to address that.
We thank the reviewer for recognising the importance of our findings and the technical developments. We agree that the paper's focus is to describe where LRRK2 is expressed in immune cells, and in which cells is it active or activated after inflammation in a hypothesis-free unbiased manner. We believe this is important data to share as a resource for the wider LRRK2 community and we will submit the manuscript as a Resource.
The flow cytometry assay of the first part is a great technical challenge and represents the establishment of a potentially very useful tool for the field. It would have been important to test other organs, either as controls or for example because of their relevance e.g. lungs. This first part is disconnected from the second part below.
We thank the reviewer for pointing out that the pRab10 assay would be useful to apply to other organs too. Since we are interested in the role of LRRK2 in IBD, we had focused on applying the pRab10 assay on intestinal tissue, with spleens also analysed as major lymphoid organ and a source of immune cells that can translocate to the gut in inflammation. We hope that the publication of this method would allow other researchers to analyse other tissues in the future.
The authors generated a new mouse KI mouse expressing EGFP-LRRK2 and show data the levels of LRRK2 expression are reduced in tissues at different degrees and established a flow cytometry assay to measure LRRK2 expression by monitoring the GFP signal. Interestingly they found that expression does not correlate with activity (as measured by phospho-Rabs). I suggest taking this part out as it breaks the flow of the paper. If data using this mouse is included, then microscopy should be included to complement the flow cytometry data. I understand the mice were used later with the anti-CD3 treatment, but it is very confusing that some experiments are done with EGFP-LRRK2 mice and others not. It does look in general like the mice do not behave as wild types and this is an important caveat. Without microscopy of the tissues or even cells (Figure 4) is hard to conclude much about these experiments.
We thank the reviewer for this point and would like to explain. It is true that in Suppl Figure 5, we show reduction of LRRK2 signal in the EGFP-Lrrk2-KI mice. However, based on immunoblotting, a significant reduction in EGFP-LRRK2 expression levels was seen only in the brain, but not in the tissues we analysed, that is the spleen and the intestine. Further, we have shown clearly using proteomics (Fig. 3D and 5E), that the GFP signal in immune cells correlates very well with the WT LRRK2 expression. Therefore, we think that the GFP signal in these mice reflects WT LRRK2 expression pattern. Further, despite the limitations of reduced kinase activity that we thoroughly describe, we think this model is very useful since no antibodies work to stain for LRRK2 in mice. We therefore respectfully disagree with this reviewer that the EGFP-LRRK2 data should be taken out, as it has proven to be an invaluable tool to measure and track changes in endogenous LRRK2 expression. Moreover, we think the fact that LRRK2 expression does not correlate with levels of activity, that is, LRRK2 is more active in some immune cells than in others, is a very important finding that evidences the cell-specific regulation of LRRK2 activity beyond its expression level.
We tried but failed to visualize the EGFP-LRRK2 signal using fluorescence microscopy in the tissue. This is most likely due to the low expression of LRRK2 (proteomics data suggests that even neutrophils express less than 9000 copies), confounded further by the high background autofluorescence in tissues, especially in the gut. We now explain the lack of tissue images from the EGFP-LRRK2 mice in the text. However, we can visualize the EGFP-LRRK2 in B cells, and we will provide these images in a revised version of the manuscript.
We have also added the following paragraph to the discussion:
"We complemented the pRab10 assay with the development of the EGFP-Lrrk2-KI reporter mouse. Although the reporter was initially designed as a fluorescent tracker for imaging LRRK2 localisation in cells and tissues, the low expression of LRRK2, combined with high and variable autofluorescence in tissues precluded its use for microscopy. Even in neutrophils, which express highest level of LRRK2 among immune cells, there are less than 9000 copies of LRRK2 per cell (Sollberger et al, 2024), making it difficult to identify localization. However, the EGFP signal was sufficient for flow cytometry-based measurements, where background autofluorescence of each cell type was taken into account and subtracted."
Then the authors show that LRRK2 expression and activity is different in different cell types and depends on inflammation. The anti-CD3 strategy to induce inflammation is very different from physiological inflammation such as sepsis and LPS stimulation, so experiments with other stimuli could be important here to contribute to the message of inflammatory trigger of LRRK2 activation and decoupling of cell type.
We thank the reviewer for this suggestion. We used the anti-CD3 model as it also causes intestinal inflammation, and mimics T-cell cytokine storms that happens in many diseases. However, for the revisions we will also test another model of inflammation as suggested, such as LPS stimulation, to measure how inflammation affects LRRK2 expression and activity.
The IL-4 data is intriguing but too preliminary. The lack of strong effect of IFN-gamma is expected as the promoter of LRRK2 in mice and humans is different and human cells responds much better with regards to LRRK2 expression after IFN-gamma stimulation.
We are confused by what the reviewer means by saying the IL-4 data is preliminary. We have shown by flow cytometry, immunoblotting, qPCR and proteomics that IL-4 induced LRRK2 expression in B-cells. So we are uncertain as to how else this can be shown. As to the effect of IFNγ on LRRK2 expression, it may indeed be that human cells respond better than murine cells. Importantly, the IL-4 ability to induce LRRK2 in B-cells is a novel and important finding, regardless of the effects of IFNγ.
Reviewer #3 (Significance (Required))
The paper describes a set of experiments to analyse LRRK2 activity in tissues and despite it has very important findings and technical developments is largely descriptive. It does look like a collection of experiments more than a defined hypothesis and experiments to address that.
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Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Referee #2
Evidence, reproducibility and clarity
The paper by Dikovskaya and collaborators investigated the activitiy and expression of LRRK2 in different subtypes of splenic and intestinal immune cells, taking advantage of a novel GFP-Lrrk2 knockin mouse. Interestingly, they found that T-cell-released IL-4 stimulates Lrrk2 expression in B cells.
I have a few comments and suggestions for the authors.
- Figure 1C. LRRK2 KO cells display residual Rab10 phosphorylation. Do the authors have any idea of which kinase other than LRRK2 could be involved in this phosphorylation?
- Since there are no good antibodies for IF/IHC as pointed by the authors, the GFP-Lrrk2 mouse gives the opportunity to check endogenous LRRK2 localization, i.e. in cells untreated or treated with IL-4 or other cytokines. Also, does endogenous GFP-LRRK2 accumulate into filaments/puncta upon MLi2 inhibition? The relocalizaiton into filaments of inhibited LRRK2 has been observed in overexpression but not under endogenous expression. This analysis would be interesting also in light of the observed side effect of type-I inhibitors.
- Figure 5. The authors need to label more clearly the graphs referring to wt mice versus GFP-Lrrk2 KI mice. They should also replace GFP-LRRK2 with GFP-Lrrk2 since they edited the endogenous murine gene.
- In the material and methods MLi-2 administration in mice is indicated at 60 mg/kg for 2 hr whereas in suppl. figure 5 the indicated dose is 30 mg/kg. Please correct with the actual dose used.
- The discovery of IL-4 as a Lrrk2 activator in B cells is a very interesting and novel finding. The authors could take advantage of the GFP tag to investigate LRRK2 interactome upon IL-4 stimulation (optional). Also, is the signaling downstream of IL-4 attenuated in Lrrk2 KO cells?
Significance
The manuscript is well designed and organized, and the experimental approaches are robust. These results are significant for the field as they add additional layers in the complex regulation and regulatory roles of LRRK2 in immunity, with implication for inflammatory disorders and Parkinson's disease.
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www.researchsquare.com www.researchsquare.com
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Author response:
The following is the authors’ response to the original reviews.
Reviewer #1 (Public Review):
Summary:
The authors used structural and biophysical methods to provide insight into Parkin regulation. The breadth of data supporting their findings was impressive and generally well-orchestrated. Still, the impact of their results builds on recent structural studies and the stated impact is based on these prior works.
Strengths:
(1) After reading through the paper, the major findings are:
- RING2 and pUbl compete for binding to RING0.
- Parkin can dimerize.
- ACT plays an important role in enzyme kinetics.
(2) The use of molecular scissors in their construct represents a creative approach to examining inter-domain interactions.
(3) From my assessment, the experiments are well-conceived and executed.
We thank the reviewer for their positive remark and extremely helpful suggestions.
Weaknesses:
The manuscript, as written, is NOT for a general audience. Admittedly, I am not an expert on Parkin structure and function, but I had to do a lot of homework to try to understand the underlying rationale and impact. This reflects, I think, that the work generally represents an incremental advance on recent structural findings.
To this point, it is hard to understand the impact of this work without more information highlighting the novelty. There are several structures of Parkin in various auto-inhibited states, and it was hard to delineate how this is different.
For the sake of the general audience, we have included all the details of Parkin structures and conformations seen (Extended Fig. 1). The structures in the present study are to validate the biophysical/biochemical experiments, highlighting key findings. For example, we solved the phospho-Parkin (complex with pUb) structure after treatment with 3C protease (Fig. 2C), which washes off the pUbl-linker, as shown in Fig 2B. The structure of the pUbl-linker depleted phospho-Parkin-pUb complex showed that RING2 returned to the closed state (Fig. 2C), which is confirmation of the SEC assay in Fig. 2B. Similarly, the structure of the pUbl-linker depleted phospho-Parkin R163D/K211N-pUb complex (Fig. 3C), was done to validate the SEC data showing displacement of pUbl-linker is independent of pUbl interaction with the basic patch on RING0 (Fig. 3B). In addition, the latter structure also revealed a new donor ubiquitin binding pocket in the linker (connecting REP and RING2) region of Parkin (Fig. 9). Similarly, trans-complex structure of phospho-Parkin (Fig. 4D) was done to validate the biophysical data (Fig. 4A-C, Fig. 5A-D) showing trans-complex between phospho-Parkin and native Parkin. The latter also confirmed that the trans-complex was mediated by interactions between pUbl and the basic patch on RING0 (Fig. 4D). Furthermore, we noticed that the ACT region was disordered in the trans-complex between phospho-Parkin (1-140 + 141-382 + pUb) (Fig. 8A) which had ACT from the trans molecule, indicating ACT might be present in the cis molecule. The latter was validated from the structure of trans-complex between phospho-Parkin with cis ACT (1-76 + 77-382 + pUb) (Fig. 8C), showing the ordered ACT region. The structural finding was further validated by biochemical assays (Fig. 8 D-F, Extended Data Fig. 9C-E).
The structure of TEV-treated R0RBR (TEV) (Extended Data Fig. 4C) was done to ensure that the inclusion of TEV and treatment with TEV protease did not perturb Parkin folding, an important control for our biophysical experiments.
As noted, I appreciated the use of protease sites in the fusion protein construct. It is unclear how the loop region might affect the protein structure and function. The authors worked to demonstrate that this did not introduce artifacts, but the biological context is missing.
We thank the reviewer for appreciating the use of protease sites in the fusion protein construct. Protease sites were used to overcome the competing mode of binding that makes interactions very transient and beyond the detection limit of methods such as ITC or SEC. While these interactions are quite transient in nature, they could still be useful for the activation of various Parkin isoforms that lack either the Ubl domain or RING2 domain (Extended Data Fig. 6, Fig. 10). Also, our Parkin localization assays also suggest an important role of these interactions in the recruitment of Parkin molecules to the damaged mitochondria (Fig. 6).
While it is likely that the binding is competitive between the Ubl and RING2 domains, the data is not quantitative. Is it known whether the folding of the distinct domains is independent? Or are there interactions that alter folding? It seems plausible that conformational rearrangements may invoke an orientation of domains that would be incompatible. The biological context for the importance of this interaction was not clear to me.
This is a great point. In the revised manuscript, we have included quantitative data between phospho-Parkin and untethered ∆Ubl-Parkin (TEV) (Fig. 5B) showing similar interactions using phospho-Parkin K211N and untethered ∆Ubl-Parkin (TEV) (Fig. 4B). Folding of Ubl domain or various combinations of RING domains lacking Ubl seems okay. Also, folding of the RING2 domain on its own appears to be fine. However, human Parkin lacking the RING2 domain seems to have some folding issues, majorly due to exposure of hydrophobic pocket on RING0, also suggested by previous efforts (Gladkova et al.ref. 24, Sauve et al. ref. 29). The latter could be overcome by co-expression of RING2 lacking Parkin construct with PINK1 (Sauve et al. ref. 29) as phospho-Ubl binds on the same hydrophobic pocket on RING0 where RING2 binds. A drastic reduction in the melting temperature of phospho-Parkin (Gladkova et al.ref. 24), very likely due to exposure of hydrophobic surface between RING0 and RING2, correlates with the folding issues of RING0 exposed human Parkin constructs.
From the biological context, the competing nature between phospho-Ubl and RING2 domains could block the non-specific interaction of phosphorylated-ubiquitin-like proteins (phospho-Ub or phospho-NEDD8) with RING0 (Lenka et al. ref. 33), during Parkin activation.
(5) What is the rationale for mutating Lys211 to Asn? Were other mutations tried? Glu? Ala? Just missing the rationale. I think this may have been identified previously in the field, but not clear what this mutation represents biologically.
Lys211Asn is a Parkinson’s disease mutation; therefore, we decided to use the same mutation for biophysical studies.
I was confused about how the phospho-proteins were generated. After looking through the methods, there appear to be phosphorylation experiments, but it is unclear what the efficiency was for each protein (i.e. what % gets modified). In the text, the authors refer to phospho-Parkin (T270R, C431A), but not clear how these mutations might influence this process. I gather that these are catalytically inactive, but it is unclear to me how this is catalyzing the ubiquitination in the assay.
This is an excellent question. Because different phosphorylation statuses would affect the analysis, we ensured complete phosphorylation status using Phos-Tag SDS-PAGE, as shown below.
Author response image 1.
Our biophysical experiments in Fig. 5C show that trans complex formation is mediated by interactions between the basic patch (comprising K161, R163, K211) on RING0 and phospho-Ubl domain in trans. These interactions result in the displacement of RING2 (Fig. 5C). Parkin activation is mediated by displacement of RING2 and exposure of catalytic C431 on RING2. While phospho-Parkin T270R/C431A is catalytically dead, the phospho-Ubl domain of phospho-Parkin T270R/C431would bind to the basic patch on RING0 of WT-Parkin resulting in activation of WT-Parkin as shown in Fig. 5E. A schematic figure is shown below to explain the same.
Author response image 2.
(7) The authors note that "ACT can be complemented in trans; however, it is more efficient in cis", but it is unclear whether both would be important or if the favored interaction is dominant in a biological context.
First, this is an excellent question about the biological context of ACT and needs further exploration. While due to the flexible nature of ACT, it can be complemented both in cis and trans, we can only speculate cis interactions between ACT and RING0 could be more relevant from the biological context as during protein synthesis and folding, ACT would be translated before RING2, and thus ACT would occupy the small hydrophobic patch on RING0 in cis. Unpublished data shows the replacement of the ACT region by Biogen compounds to activate Parkin (https://doi.org/10.21203/rs.3.rs-4119143/v1). The latter finding further suggests the flexibility in this region.
(8) The authors repeatedly note that this study could aid in the development of small-molecule regulators against Parkin to treat PD, but this is a long way off. And it is not clear from their manuscript how this would be achieved. As stated, this is conjecture.
As suggested by this reviewer, we have removed this point in the revised manuscript.
Reviewer #2 (Public Review):
This manuscript uses biochemistry and X-ray crystallography to further probe the molecular mechanism of Parkin regulation and activation. Using a construct that incorporates cleavage sites between different Parkin domains to increase the local concentration of specific domains (i.e., molecular scissors), the authors suggest that competitive binding between the p-Ubl and RING2 domains for the RING0 domain regulates Parkin activity. Further, they demonstrate that this competition can occur in trans, with a p-Ubl domain of one Parkin molecule binding the RING0 domain of a second monomer, thus activating the catalytic RING1 domain. In addition, they suggest that the ACT domain can similarly bind and activate Parkin in trans, albeit at a lower efficiency than that observed for p-Ubl. The authors also suggest from crystal structure analysis and some biochemical experiments that the linker region between RING2 and repressor elements interacts with the donor ubiquitin to enhance Parkin activity.<br /> Ultimately this manuscript challenges previous work suggesting that the p-Ubl domain does not bind to the Parkin core in the mechanism of Parkin activation. The use of the 'molecular scissors' approach to probe these effects is an interesting approach to probe this type of competitive binding. However, there are issues with the experimental approach manuscript that detract from the overall quality and potential impact of the work.
We thank the reviewer for their positive remark and constructive suggestions.
The competitive binding between p-Ubl and RING2 domains for the Parkin core could have been better defined using biophysical and biochemical approaches that explicitly define the relative affinities that dictate these interactions. A better understanding of these affinities could provide more insight into the relative bindings of these domains, especially as it relates to the in trans interactions.
This is an excellent point regarding the relative affinities of pUbl and RING2 for the Parkin core (lacking Ubl and RING2). While we could purify p-Ubl, we failed to purify human Parkin (lacking RING2 and phospho-Ubl). The latter folding issues were likely due to the exposure of a highly hydrophobic surface on RING0 (as shown below) in the absence of pUbl and RING2 in the R0RB construct. Also, RING2 with an exposed hydrophobic surface would be prone to folding issues, which is not suitable for affinity measurements. A drastic reduction in the melting temperature of phospho-Parkin (Gladkova et al.ref. 24) also highlights the importance of a hydrophobic surface between RING0 and RING2 on Parkin folding/stability. A separate study would be required to try these Parkin constructs from different species and ensure proper folding before using them for affinity measurements.
Author response image 3.
I also have concerns about the results of using molecular scissors to 'increase local concentrations' and allow for binding to be observed. These experiments are done primarily using proteolytic cleavage of different domains followed by size exclusion chromatography. ITC experiments suggest that the binding constants for these interactions are in the µM range, although these experiments are problematic as the authors indicate in the text that protein precipitation was observed during these experiments. This type of binding could easily be measured in other assays. My issue relates to the ability of a protein complex (comprising the core and cleaved domains) with a Kd of 1 µM to be maintained in an SEC experiment. The off-rates for these complexes must be exceeding slow, which doesn't really correspond to the low µM binding constants discussed in the text. How do the authors explain this? What is driving the Koff to levels sufficiently slow to prevent dissociation by SEC? Considering that the authors are challenging previous work describing the lack of binding between the p-Ubl domain and the core, these issues should be better resolved in this current manuscript. Further, it's important to have a more detailed understanding of relative affinities when considering the functional implications of this competition in the context of full-length Parkin. Similar comments could be made about the ACT experiments described in the text.
This is a great point. In the revised manuscript, we repeated ITC measurements in a different buffer system, which gave nice ITC data. In the revised manuscript, we have also performed ITC measurements using native phospho-Parkin. Phospho-Parkin and untethered ∆Ubl-Parkin (TEV) (Fig. 5B) show similar affinities as seen between phospho-Parkin K211N and untethered ∆Ubl-Parkin (TEV) (Fig. 4B). However, Kd values were consistent in the range of 1.0 ± 0.4 µM which could not address the reviewer’s point regarding slow off-rate. The crystal structure of the trans-complex of phospho-Parkin shows several hydrophobic and ionic interactions between p-Ubl and Parkin core, suggesting a strong interaction and, thus, justifying the co-elution on SEC. Additionally, ITC measurements between E2-Ub and P-Parkin-pUb show similar affinity (Kd = 0.9 ± 0.2 µM) (Kumar et al., 2015, EMBO J.), and yet they co-elute on SEC (Kumar et al., 2015, EMBO J.).
Ultimately, this work does suggest additional insights into the mechanism of Parkin activation that could contribute to the field. There is a lot of information included in this manuscript, giving it breadth, albeit at the cost of depth for the study of specific interactions. Further, I felt that the authors oversold some of their data in the text, and I'd recommend being a bit more careful when claiming an experiment 'confirms' a specific model. In many cases, there are other models that could explain similar results. For example, in Figure 1C, the authors state that their crystal structure 'confirms' that "RING2 is transiently displaced from the RING0 domain and returns to its original position after washing off the p-Ubl linker". However, it isn't clear to me that RING2 ever dissociated when prepared this way. While there are issues with the work that I feel should be further addressed with additional experiments, there are interesting mechanistic details suggested by this work that could improve our understanding of Parkin activation. However, the full impact of this work won't be fully appreciated until there is a more thorough understanding of the regulation and competitive binding between p-Ubl and RIGN2 to RORB both in cis and in trans.
We thank the reviewer for their positive comment. In the revised manuscript, we have included the reviewer’s suggestion. The conformational changes in phospho-Parkin were established from the SEC assay (Fig. 2A and Fig. 2B), which show displacement/association of phospho-Ubl or RING2 after treatment of phospho-Parkin with 3C and TEV, respectively. For crystallization, we first phosphorylated Parkin, where RING2 is displaced due to phospho-Ubl (as shown in SEC), followed by treatment with 3C protease, which led to pUbl wash-off. The Parkin core separated from phospho-Ubl on SEC was used for crystallization and structure determination in Fig. 2C, where RING2 returned to the RING0 pocket, which confirms SEC data (Fig. 2B).
Reviewer #3 (Public Review):
Summary:
In their manuscript "Additional feedforward mechanism of Parkin activation via binding of phospho-UBL and RING0 in trans", Lenka et al present data that could suggest an "in trans" model of Parkin ubiquitination activity. Parkin is an intensely studied E3 ligase implicated in mitophagy, whereby missense mutations to the PARK2 gene are known to cause autosomal recessive juvenile parkinsonism. From a mechanistic point of view, Parkin is extremely complex. Its activity is tightly controlled by several modes of auto-inhibition that must be released by queues of mitochondrial damage. While the general overview of Parkin activation has been mapped out in recent years, several details have remained murky. In particular, whether Parkin dimerizes as part of its feed-forward signaling mechanism, and whether said dimerization can facilitate ligase activation, has remained unclear. Here, Lenka et al. use various truncation mutants of Parkin in an attempt to understand the likelihood of dimerization (in support of an "in trans" model for catalysis).
Strengths:
The results are bolstered by several distinct approaches including analytical SEC with cleavable Parkin constructs, ITC interaction studies, ubiquitination assays, protein crystallography, and cellular localization studies.
We thank the reviewer for their positive remark.
Weaknesses:
As presented, however, the storyline is very confusing to follow and several lines of experimentation felt like distractions from the primary message. Furthermore, many experiments could only indirectly support the author's conclusions, and therefore the final picture of what new features can be firmly added to the model of Parkin activation and function is unclear.
We thank the reviewer for their constructive criticism, which has helped us to improve the quality of this manuscript.
Major concerns:
(1) This manuscript solves numerous crystal structures of various Parkin components to help support their idea of in trans transfer. The way these structures are presented more resemble models and it is unclear from the figures that these are new complexes solved in this work, and what new insights can be gleaned from them.
The structures in the present study are to validate the biophysical/biochemical experiments highlighting key findings. For example, we solved the phospho-Parkin (complex with pUb) structure after treatment with 3C protease (Fig. 2C), which washes off the pUbl-linker, as shown in Fig. 2B. The structure of pUbl-linker depleted phospho-Parkin-pUb complex showed that RING2 returned to the closed state (Fig. 2C), which is confirmation of the SEC assay in Fig. 2B. Similarly, the structure of the pUbl-linker depleted phospho-Parkin R163D/K211N-pUb complex (Fig. 3C), was done to validate the SEC data showing displacement of pUbl-linker is independent of pUbl interaction with the basic patch on RING0 (Fig. 3B). In addition, the latter structure also revealed a new donor ubiquitin binding pocket in the linker (connecting REP and RING2) region of Parkin (Fig. 9). Similarly, trans-complex structure of phospho-Parkin (Fig. 4D) was done to validate the biophysical data (Fig. 4A-C, Fig. 5A-D) showing trans-complex between phospho-Parkin and native Parkin. The latter also confirmed that the trans-complex was mediated by interactions between pUbl and the basic patch on RING0 (Fig. 4D). Furthermore, we noticed that the ACT region was disordered in the trans-complex between phospho-Parkin (1-140 + 141-382 + pUb) (Fig. 8A) which had ACT from the trans molecule, indicating ACT might be present in the cis molecule. The latter was validated from the structure of trans-complex between phospho-Parkin with cis ACT (1-76 + 77-382 + pUb) (Fig. 8C), showing the ordered ACT region. The structural finding was further validated by biochemical assays (Fig. 8 D-F, Extended Data Fig. 9C-E).
The structure of TEV-treated R0RBR (TEV) (Extended Data Fig. 4C) was done to ensure that the inclusion of TEV and treatment with TEV protease did not perturb Parkin folding, an important control for our biophysical experiments.
(2) There are no experiments that definitively show the in trans activation of Parkin. The binding experiments and size exclusion chromatography are a good start, but the way these experiments are performed, they'd be better suited as support for a stronger experiment showing Parkin dimerization. In addition, the rationale for an in trans activation model is not convincingly explained until the concept of Parkin isoforms is introduced in the Discussion. The authors should consider expanding this concept into other parts of the manuscript.
We thank the reviewer for appreciating the Parkin dimerization. Our biophysical data in Fig. 5C shows that Parkin dimerization is mediated by interactions between phospho-Ubl and RING0 in trans, leading to the displacement of RING2. However, Parkin K211N (on RING0) mutation perturbs interaction with phospho-Parkin and leads to loss of Parkin dimerization and loss of RING2 displacement (Fig. 5C). The interaction between pUbl and K211 pocket on RING0 leads to the displacement of RING2 resulting in Parkin activation as catalytic residue C431 on RING2 is exposed for catalysis. The biophysical experiment is further confirmed by a biochemical experiment where the addition of catalytically in-active phospho-Parkin T270R/C431A activates autoinhibited WT-Parkin in trans using the mechanism as discussed (a schematic representation also shown in Author response image 2).
We thank this reviewer regarding Parkin isoforms. In the revised manuscript, we have included Parkin isoforms in the results section, too.
(2a) For the in trans activation experiment using wt Parkin and pParkin (T270R/C431A) (Figure 3D), there needs to be a large excess of pParkin to stimulate the catalytic activity of wt Parkin. This experiment has low cellular relevance as these point mutations are unlikely to occur together to create this nonfunctional pParkin protein. In the case of pParkin activating wt Parkin (regardless of artificial point mutations inserted to study specifically the in trans activation), if there needs to be much more pParkin around to fully activate wt Parkin, isn't it just more likely that the pParkin would activate in cis?
To test phospho-Parkin as an activator of Parkin in trans, we wanted to use the catalytically inactive version of phospho-Parkin to avoid the background activity of p-Parkin. While it is true that a large excess of pParkin (T270R/C431A) is required to activate WT-Parkin in the in vitro set-up, it is not very surprising as in WT-Parkin, the unphosphorylated Ubl domain would block the E2 binding site on RING1. Also, due to interactions between pParkin (T270R/C431A) molecules, the net concentration of pParkin (T270R/C431A) as an activator would be much lower. However, the Ubl blocking E2 binding site on RING1 won’t be an issue between phospho-Parkin molecules or between Parkin isoforms (lacking Ubl domain or RING2).
(2ai) Another underlying issue with this experiment is that the authors do not consider the possibility that the increased activity observed is a result of increased "substrate" for auto-ubiquitination, as opposed to any role in catalytic activation. Have the authors considered looking at Miro as a substrate in order to control for this?
This is quite an interesting point. However, this will be only possible if Parkin is ubiquitinated in trans, as auto-ubiquitination is possible with active Parkin and not with catalytically dead (phospho-Parkin T270R, C431A) or autoinhibited (WT-Parkin). Also, in the previous version of the manuscript, where we used only phospho-Ubl as an activator of Parkin in trans, we tested Miro1 ubiquitination and auto-ubiquitination, and the results were the same (Author response image 4).
Author response image 4.
(2b) The authors mention a "higher net concentration" of the "fused domains" with RING0, and use this to justify artificially cleaving the Ubl or RING2 domains from the Parkin core. This fact should be moot. In cells, it is expected there will only be a 1:1 ratio of the Parkin core with the Ubl or RING2 domains. To date, there is no evidence suggesting multiple pUbls or multiple RING2s can bind the RING0 binding site. In fact, the authors here even show that either the RING2 or pUbl needs to be displaced to permit the binding of the other domain. That being said, there would be no "higher net concentration" because there would always be the same molar equivalents of Ubl, RING2, and the Parkin core.
We apologize for the confusion. “Higher net concentration” is with respect to fused domains versus the domain provided in trans. Due to the competing nature of the interactions between pUbl/RING2 and RING0, the interactions are too transient and beyond the detection limit of the biophysical techniques. While the domains are fused (for example, RING0-RING2 in the same polypeptide) in a polypeptide, their effective concentrations are much higher than those (for example, pUbl) provided in trans; thus, biophysical methods fail to detect the interaction. Treatment with protease solves the above issue due to the higher net concentration of the fused domain, and trans interactions can be measured using biophysical techniques. However, the nature of these interactions and conformational changes is very transient, which is also suggested by the data. Therefore, Parkin molecules will never remain associated; rather, Parkin will transiently interact and activate Parkin molecules in trans.
(2c) A larger issue remaining in terms of Parkin activation is the lack of clarity surrounding the role of the linker (77-140); particularly whether its primary role is to tether the Ubl to the cis Parkin molecule versus a role in permitting distal interactions to a trans molecule. The way the authors have conducted the experiments presented in Figure 2 limits the possible interactions that the activated pUbl could have by (a) ablating the binding site in the cis molecule with the K211N mutation; (b) further blocking the binding site in the cis molecule by keeping the RING2 domain intact. These restrictions to the cis parkin molecule effectively force the pUbl to bind in trans. A competition experiment to demonstrate the likelihood of cis or trans activation in direct comparison with each other would provide stronger evidence for trans activation.
This is an excellent point. In the revised manuscript, we have performed experiments using native phospho-Parkin (Revised Figure 5), and the results are consistent with those in Figure 2 ( Revised Figure 4), where we used the K211N mutation.
(3) A major limitation of this study is that the authors interpret structural flexibility from experiments that do not report directly on flexibility. The analytical SEC experiments report on binding affinity and more specifically off-rates. By removing the interdomain linkages, the accompanying on-rate would be drastically impacted, and thus the observations are disconnected from a native scenario. Likewise, observations from protein crystallography can be consistent with flexibility, but certainly should not be directly interpreted in this manner. Rigorous determination of linker and/or domain flexibility would require alternative methods that measure this directly.
We also agree with the reviewer that these methods do not directly capture structural flexibility. Also, rigorous determination of linker flexibility would require alternative methods that measure this directly. However, due to the complex nature of interactions and technical limitations, breaking the interdomain linkages was the best possible way to capture interactions in trans. Interestingly, all previous methods that report cis interactions between pUbl and RING0 also used a similar approach (Gladkova et al.ref. 24, Sauve et al. ref. 29).
(4) The analysis of the ACT element comes across as incomplete. The authors make a point of a competing interaction with Lys48 of the Ubl domain, but the significance of this is unclear. It is possible that this observation could be an overinterpretation of the crystal structures. Additionally, the rationale for why the ACT element should or shouldn't contribute to in trans activation of different Parkin constructs is not clear. Lastly, the conclusion that this work explains the evolutionary nature of this element in chordates is highly overstated.
We agree with the reviewer that the significance of Lys48 is unclear. We have presented this just as one of the observations from the crystal structure. As the reviewer suggested, we have removed the sentence about the evolutionary nature of this element from the revised manuscript.
(5) The analysis of the REP linker element also seems incomplete. The authors identify contacts to a neighboring pUb molecule in their crystal structure, but the connection between this interface (which could be a crystallization artifact) and their biochemical activity data is not straightforward. The analysis of flexibility within this region using crystallographic and AlphaFold modeling observations is very indirect. The authors also draw parallels with linker regions in other RBR ligases that are involved in recognizing the E2-loaded Ub. Firstly, it is not clear from the text or figures whether the "conserved" hydrophobic within the linker region is involved in these alternative Ub interfaces. And secondly, the authors appear to jump to the conclusion that the Parkin linker region also binds an E2-loaded Ub, even though their original observation from the crystal structure seems inconsistent with this. The entire analysis feels very preliminary and also comes across as tangential to the primary storyline of in trans Parkin activation.
We agree with the reviewer that crystal structure data and biochemical data are not directly linked. In the revised manuscript, we have also highlighted the conserved hydrophobic in the linker region at the ubiquitin interface (Fig. 9C and Extended Data Fig. 11A), which was somehow missed in the original manuscript. We want to add that a very similar analysis and supporting experiments identified donor ubiquitin-binding sites on the IBR and helix connecting RING1-IBR (Kumar et al., Nature Str. and Mol. Biol., 2017), which several other groups later confirmed. In the mentioned study, the Ubl domain of Parkin from the symmetry mate Parkin molecule was identified as a mimic of “donor ubiquitin” on IBR and helix connecting RING1-IBR.
In the present study, a neighboring pUb molecule in the crystal structure is identified as a donor ubiquitin mimic (Fig. 9C) by supporting biophysical/biochemical experiments. First, we show that mutation of I411A in the REP linker of Parkin perturbs Parkin interaction with E2~Ub (donor) (Fig. 9F). Another supporting experiment was performed using a Ubiquitin-VS probe assay, which is independent of E2. Assays using Ubiquitin-VS show that I411A mutation in the REP-RING2 linker perturbs Parkin charging with Ubiquitin-VS (Extended Data Fig. 11 B). Furthermore, the biophysical data showing loss of Parkin interaction with donor ubiquitin is further supported by ubiquitination assays. Mutations in the REP-RING2 linker perturb the Parkin activity (Fig. 9E), confirming biophysical data. This is further confirmed by mutations (L71A or L73A) on ubiquitin (Extended Data Fig. 11C), resulting in loss of Parkin activity. The above experiments nicely establish the role of the REP-RING2 linker in interaction with donor ubiquitin, which is consistent with other RBRs (Extended Data Fig. 11A).
While we agree with the reviewer that this appears tangential to the primary storyline in trans-Parkin activation, we decided to include this data because it could be of interest to the field.
Recommendations for the authors:
Reviewer #1 (Recommendations For The Authors):
(1) For clarity, a schematic of the domain architecture of Parkin would be helpful at the outset in the main figures. This will help with the introduction to better understand the protein organization. This is lost in the Extended Figure in my opinion.
We thank the reviewer for suggesting this, which we have included in Figure 1 of the revised manuscript.
(2) Related to the competition between the Ubl and RING2 domains, can competition be shown through another method? SPR, ITC, etc? ITC was used in other experiments, but only in the context of mutations (Lys211Asn)? Can this be done with WT sequence?
This is an excellent suggestion. In the revised Figure 5, we have performed ITC experiment using WT Parkin, and the results are consistent with what we observed using Lys211Asn Parkin.
(3) The authors also note that "the AlphaFold model shows a helical structure in the linker region of Parkin (Extended Data Figure 10C), further confirming the flexible nature of this region"... but the secondary structure would not be inherently flexible. This is confusing.
The flexibility is in terms of the conformation of this linker region observed under the open or closed state of Parkin. In the revised manuscript, we have explained this point more clearly.
(4) The manuscript needs extensive revision to improve its readability. Minor grammatical mistakes were prevalent throughout.
We thank the reviewer for pointing out this and we have corrected these in the revised manuscript.
(5) The confocal images are nice, but inset panels may help highlight the regions of interest (ROIs).
This is corrected in the revised manuscript.
(6) Trans is misspelled ("tans") towards the end of the second paragraph on page 16.
This is corrected in the revised manuscript.
(7) The schematics are helpful, but some of the lettering in Figure 2 is very small.
This is corrected in the revised manuscript.
Reviewer #3 (Recommendations For The Authors):
(1) A significant portion of the results section refers to the supplement, making the overall readability very difficult.
We accept this issue as a lot of relevant data could not be added to the main figures and thus ended up in the supplement. In the revised manuscript, we have moved some of the supplementary figures to the main figures.
(2) Interpretation of the experiments utilizing many different Parkin constructs and cleavage scenarios (particularly the SEC and crystallography experiments) is extremely difficult. The work would benefit from a layout of the Parkin model system, highlighting cleavage sites, key domain terminology, and mutations used in the study, presented together and early on in the manuscript. Using this to identify a simpler system of referencing Parkin constructs would also be a large improvement.
This is a great suggestion. We have included these points in the revised manuscript, which has improved the readability.
(3) Lines 81-83; the authors say they "demonstrate the conformational changes in Parkin during the activation process", but fail to show any actual conformational changes. Further, much of what is demonstrated in this work (in terms of crystal structures) corroborates existing literature. The authors should use caution not to overstate their original conclusions in light of the large body of work in this area.
We thank the reviewer for pointing out this. We have corrected the above statement in the revised manuscript to indicate that we meant it in the context of trans conformational changes.
(4) Line 446 and 434; there is a discrepancy about which amino acid is present at residue 409. Is this a K408 typo? The authors also present mutational work on K416, but this residue is not shown in the structure panel.
We thank the reviewer for pointing out this. In the revised manuscript, we have corrected these typos.
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Author response:
The following is the authors’ response to the original reviews.
Reviewer 1:
This research used cell-based signaling assay and Gaussian-accelerated molecular dynamics (GaMD) to study peptide-mediated signaling activation of Polycystin-1 (PC1), which is responsible for the majority of autosomal dominant polycystic kidney disease (ADPKD) cases. Synthetic peptides of various lengths derived from the N-terminal portion of the PC1 C-terminal fragment (CTF) were applied to HEK293T cells transfected with stalkless mouse CTF expression construct. It was shown that peptides including the first 7, 9, and 17 residues of the N-terminal portion could activate signaling to the NFAT reporter. To further understand the underlying mechanism, docking and peptide-GaMD simulations of peptides composed of the first 9, 17, and 21 residues from the N-terminal portion of the human PC1 CTF were performed. These simulations revealed the correlation between peptide-CTF binding and PC1 CTF activation characterized by the close contact (salt bridge interaction) between residues R3848 and E4078. Finally, a Potts statistical model was inferred from diverged PC1 homologs to identify strong/conserved interacting pairs within PC1 CTF, some of which are highly relevant to the findings from the peptide GaMD simulations. The peptide binding pockets identified in the GaMD simulations may serve as novel targets for the design of therapeutic approaches for treating ADPKD.
We greatly appreciate the reviewer’s encouraging and positive comments. The reviewer’ specific comments are addressed pointwise below and changes to the text will be highlighted in yellow in the revised manuscript.
(1) The GaMD simulations all include exogenous peptides, thus lacking a control where no such peptide is present (and only stalkless CTF). An earlier study (PNAS 2022 Vol. 119 No. 19 e2113786119) covered this already, but it should be mentioned here that there was no observation of close/activation for the stalkless CTF.
We appreciate the reviewer’s concern about the lack of a control where no exogenous peptide is present. As suggested by the reviewer, we are adding more details about the study on the stalkless CTF as a control in the Introduction of the revised manuscript.
(2) Although 5 independent trajectories were generated for each peptide, the authors did not provide sufficient details regarding the convergence of the simulation. This leaves some uncertainties in their results. Given that the binding poses changed relative to the starting docked poses for all three peptides, it is possible that some other binding pockets and/or poses were not explored.
We appreciate the reviewer’s comment regarding the convergence of the simulation results. This is clarified in the revised manuscript as:
“We have calculated free energy profiles of individual simulations for each system, including the p9, p17, and p21, as shown below (Figs. S5, S6 and S8). For the p9 peptide, the “Bound” lowenergy state was consistently identified in the 2D free energy profile of each individual simulation (Fig. S5). For the p17 peptide, Pep-GaMD simulations were able to refine the peptide conformation from the "Unbound” to the "Intermediate” and “Bound” states in Sim1 and Sim5, while the peptide reached only the "Intermediate” state in the other three simulations (Fig. S6). For the p21 peptide, Pep-GaMD was able to refine the peptide docking conformation to the
"Bound” state in all the five individual simulations (Fig. S8).”
“It is important to note that the free energy profiles calculated from GaMD simulations of PC1 CTF were not fully converged since certain variations were observed among the individual simulations. Nevertheless, these calculations allowed us to identify representative low-energy binding conformations of the peptides.”
(3) The free energy profiles (Figures 2 to 4) based on the selected coordinates provide important information regarding binding and CTF conformational change. However, it is a coarsegrained representation and complementary analysis such as RDFs, and/or contact maps between the peptide and CTF residues might be helpful to understand the details of their interactions. These details are currently only available in the text.
Following the reviewer's suggestion, we have now included a set of protein contact maps showing contacts between the peptides and the TOP domain for each peptide in the representative "Bound” state in revised Supplementary Information (Fig. S4). The contact maps serve to visualize the list of contacts mentioned in the main text. This will be clarified in the revised manuscript.
(4) The use of a stalkless CTF is necessary for studying the functions of the exogenous peptides. However, the biological relevance of the stalkless CTF to ADPKD was not clearly explained, if any.
We appreciate the reviewer’s comment. As correctly assessed by the reviewer, the stalkless CTF is not a biological form of PC1 observed in ADPKD, but rather was used as the simplest or least complex system in which the activities and binding of exogenous peptides could be studied. However, in ADPKD, there are numerous missense mutations reported within the GPCR autoproteolysis-inducing (GAIN) domain that have been shown to prevent or inhibit cleavage at the GPCR-coupled proteolysis site (GPS). Loss of PC1 GPS cleavage, which is known to cause ADPKD, would retain or sequester the stalk tethered agonist within the interior of the GAIN domain, which would presumably interfere with interactions between stalk tethered agonist residues and the remainder of the CTF. Furthermore, there are 10 single nucleotide polymorphisms reported within the stalk sequence (ADPKD Variant Database; https://pkdb.mayo.edu/welcome), most of which we have found to significantly reduce CTF-mediated activation of the NFAT reporter (Magenheimer BS, et al., Constitutive signaling by the C-terminal fragment of polycystin1 is mediated by a tethered peptide agonist; bioRxiv 2021.08.05.455255). In particular, the ADPKD-associated G3052R stalk mutation that was analyzed along with the stalkless CTF by GaMD simulations (Pawnikar et al, PNAS, 2022) has the same reduction in activity as the stalkless CTF in the cellular signaling reporter assays and the same loss of closed conformation interactions in GaMD analyses. As such, we believe the stalkless CTF has biological relevance from the aspect that it mimics the deficiency in signaling activation observed for PC1 CTF stalk mutants. This is clarified in the revised manuscript in the Introduction, page 5, “constructs encoding a stalkless PC1 CTF (a nonbiological mutant of PC1 with deletion of the first 21 N-terminal residues of CTF) and three ADPKD-associated…”) and near the beginning of the Discussion, page 16, where the biological relevance of studying the stalkless CTF is explained
(5) The authors might want to clarify if a stalkless CTF is commonly seen in ADPKD, or if it is just a construct used for this study.
The stalkless CTF is not a biological form of PC1, but rather a construct used for this study. This was clarified in the revised manuscript (see response above).
(6) (Pages 7-8) "...we generated expression constructs of mouse (m) PC1 consisting of the CD5 signal peptide sequence fused in frame with the stalk sequence of mCTF ...". What is the CD5 signal peptide sequence here? What is its use?
The CD5 signal peptide sequence is “MPMGSLQPLATLYLLGMLVASVLG” from the T cell surface glycoprotein, CD5. Since the N-terminus of PC1 CTF is derived from a posttranslational, autocatalytic, endoproteolytic cleavage event, this isoform is already membraneembedded and therefore lacks its endogenous signal peptide. The CD5 signal peptide coding sequence is added to the PC1 CTF expression constructs in order to ensure translation and insertion of the encoded protein at the endoplasmic reticulum. Additional details were added to the Experimental Procedures, page 2 of Supporting Information.
(7) (Page 8) "All peptides were appended with a C-terminal, 7-residue hydrophilic sequence (GGKKKKK) to increase solubility". How did the authors make sure that this sequence has no influence on the signaling?
To determine the possible effect of the hydrophilic GGKKKKK sequence on signaling, we had a ‘solubility tag’ peptide (LGGKKKKK) synthesized and purified by GenScript. It was necessary to add an N-terminal Leu residue to the 7-residue hydrophilic tag sequence in order for the highly hydrophilic peptide to be recovered. Effect of treatment with the solubility tag peptide on activation of the NFAT reporter was assessed for both empty vector- and ∆stalkCTF-transfected cells in 3 separate signaling experiments (see figure below). Each experiment also included a negative control treatment (no peptide/culture medium only addition) and a positive control treatment (stalk peptide p17). The p17 peptide we had available was derived from the stalk sequence of human PC1 that differs from the mouse PC1 sequence at residues 15 and 17, which are two poorly conserved positions within the stalk sequence (see Reviewer 2, Response 3). In the first experiment with the solubility tag and human p17 peptides (B in figure below), we inadvertently used the empty expression vector and ∆stalkCTF expression construct from mouse PC1. After realizing our error, we then performed 2 additional signaling experiments (C and D in figure below) with the ‘correct’ human ∆stalkCTF expression construct and empty vector. In the revised manuscript, we have provided the results from each of the 3 experiments as Fig. S2 (below).
(8) (Page 9) "Using a computational model of the ΔStalk PC1 CTF developed previously". The authors might want to expand here a little to give a short review about the structure preparation.
We appreciate the reviewer’s suggestion regarding the addition of details for structure preparation for Stalkless CTF. We have added these details in section “Docking and Pep-GaMD simulations of peptide agonist binding to stalkless PC1 CTF” on Page 10 in the revised manuscript: “The cryo-EM structure of human PC1-PC2 complex (PDB: 6A70) was used to build the computational model for WT PC1 CTF. As the protein had several missing regions including the Stalk and several loops, homology modeling of the missing regions was done using I-TASSER web server. Using the WT PC1 CTF model, computational model for ΔStalk was generated by deleting the first 21 residues (3049-3069) of the WT PC1 and using the structure for stalkless CTF, we successfully docked the p9, p17 and p21 stalk peptides with HPEPDOCK. The peptides all bound to the TOP domain and the interface between the TOP domain and extracellular loop 1 (ECL1) of CTF.”
(9) How was "contact" defined when counting the number of contacts used in the 2D PMFs (Figures 2-4). Response: We appreciate the reviewer’s comment regarding the definition of the number of contacts used in the 2D PMFs. This has been clarified in the revised manuscript as: “The number of contacts is calculated between any atom pairs within 4 Å distance of the peptide and extracellular domains of PC1 protein.”
(10) How was the ranking of GaMD clusters done? It looks from Figure 3A that the "intermediate" state is more favorable compared to the "bound" state, but it was claimed in the text the "bound" state was ranked 1st.
Thanks to the reviewer for this comment. It has been clarified in the revised
Supplementary Information: “Three independent Pep-GaMD simulations were combined to perform structural clustering using the hierarchical agglomerative clustering algorithm in CPPTRAJ. A 3 Å RMSD cutoff was used for each peptide system. PyReweighting was then applied to calculate the original free energy values of each peptide structural cluster with a cutoff of 500 frames. The structural clusters were finally ranked according to the reweighted free energy values.” And in the revised main text: “It is important to note that the free energy profiles calculated from GaMD simulations of PC1 CTF were not fully converged since certain variations were observed among the individual simulations. The free energy values of 2D PMF minima shown in Figure 3A could differ from those in the 1D PMF minima of peptide structural clusters, especially with the usage of distinct reaction coordinates. Nevertheless, these calculations allowed us to identify representative low-energy binding conformations of the peptides.”
(11) When mentioning residue pair distances, such as in the sentence "The distance between the TOP domain residue R3848 and PL residue E4078 was 3.8 Å (Fig. 4D)" on page 12, it should be clarified if these distances are average distance, or a statistical error can be given.
We appreciate the reviewer’s comment regarding the TOP Domain and PL distance between residues R3848-E4078. This has been clarified on page 14 in the revised manuscript as:
“The distance between the TOP domain residue R3848 and PL residue E4078 was 3.8 Å. The distance was extracted from the top-ranked structural cluster of the p21 bound to the ΔStalk CTF, corresponding to the “Closed/Active” low-energy conformational state. (Fig. 4E)”.
(12) More analysis of the GaMD can be performed. For example, the authors observed a single "bound" state for p21, but there must be some flexibility in the peptide and the protein itself. The authors might want to consider adding some plots illustrating the flexibility of the peptide residues (for example, a RMSD plot). Contact maps can also be added to visualize the results currently discussed in the text.
We thank the reviewer for their constructive suggestions. To characterize flexibility of the peptide and protein in the revised manuscript, we have added plots of the TOP-PL interaction distance between residues R3848-E4078 in PC1, the radius of gyration (Rg) of p21 and root-mean square deviation (RMSD) of p21 relative to the starting HPEPDOCK conformation of the peptide in the new Fig. S7. The peptide-protein contact map has also been added in the new Fig. S4.
(13) (Page 7) In the sentence `...sampled the "Closed/Active" low-energy state relative to the large number of Stalk-TOP contacts`, I suggest using "related to" instead of "relative to"
We thank the reviewer for the comment, and we have replaced "relative to" to “related to” in the following sentence `...sampled the "Closed/Active" low-energy state relative to the large number of Stalk-TOP contacts`
(14) (Page 7) In the sentence `Our previous study utilized expression constructs of human PC1 CTF, however, in order to prepare for ...`, "PC1 CTF, however," -> "PC1 CTF. However,"
We thank the reviewer for the comment, and we have replaced "PC1 CTF, however," to "PC1 CTF. However," in the following sentence `Our previous study utilized expression constructs of human PC1 CTF, however, in order to prepare for ...`.
Reviewer 2:
The autosomal dominant polycystic kidney disease (ADPKD) is a major form of polycystic kidney disease (PKD). To provide better treatment and avoid side effects associated with currently available options, the authors investigated an interesting GPCR, polycystin-1 (PC1), as a potential therapeutic target. In vitro and in silico studies were combined to identify peptide agonists for PC1 and to elucidate their roles in PC1 signaling. Overall, regarding the significance of the findings, this work described valuable peptide agonists for PC1 and the combined in vitro and in silico approach can be useful to study a complex system like PC1. However, the strength of the evidence is incomplete, as more experiments are needed as controls to validate the computational observations. The work appears premature.
We greatly appreciate the reviewer’s encouraging and positive comments. The reviewer’ specific comments are addressed pointwise below and changes to the text will be highlighted in yellow in the revised manuscript.
(1) The therapeutic potential of PC1 peptide agonists is unclear in the introduction. For example, while the FDA-approved drug Jynarque was mentioned, the text was misleading as it sounded like Jynarque targeted PC1. In fact, it targets another GPCR, the vasopressin receptor 2 (V2). A clear comparison of targeting PC1 over V2 pathways and their therapeutic relevance can help the readers better understand the importance of this work. Importantly, a clear background on the relationship between PC1 agonism and treatments for ADPKD is necessary.
We understand the confusion that was caused by the brevity of our introductory paragraph and will clarify the differences in therapeutic targeting between Jynarque and our PC1 stalk-derived peptides in the revised manuscript. We will also expound on the rationale for targeting PC1 agonism as a therapeutic approach for ADPKD versus Jynarque. For example: It is known that ADPKD disease severity is dependent on the functional levels of PC1. Jynarque is a small molecule antagonist of the arginine vasopressin receptor 2, V2R, whose signaling, and production of cAMP has been shown to be increased in ADPKD. As this drug targets one of the downstream aberrant pathways, it is only capable of slowing disease progression and has numerous undesirable side effects. We reasoned that a therapeutic agent capable of stimulating and thus augmenting PC1 signaling function would be a safer, cyst initiation-proximal treatment capable of preventing cyst formation with few side effects.
(2) PC1 is a complex membrane protein, and most figures focus on the peptide-binding site. For general readers (or readers that did not read the previous PNAS publication), it is hard to imagine the overall structure and understand where the key interactions (e.g., R3848-E4078) are in the protein and how peptide binding affects locally and globally. I suggest enhancing the illustrations.
We thank the reviewer for the constructive comment on adding more illustrations for the PC1 protein to understand the overall structure and the location of the key interaction R3848E4078. We have included these suggestions and modified the main figures in the revised manuscript.
(3) The authors used the mouse construct for the cellular assays and the peptide designs in preparation for future in vivo assays. This is helpful in understanding biology, but the relevance of drug discovery is weakened. Related to Point 1, the therapeutic potential of PC1 peptide agonist is largely missing.
The therapeutic potential of a PC1 peptide agonist is addressed in response #1 above. As mentioned in the manuscript and recognized by the reviewer, the cellular signaling assays were performed with the mouse PC1 CTF expression construct and with peptides based on the mouse PC1 stalk sequence for future, pre-clinical studies, while the peptide binding studies were performed with the human PC1 stalk sequence. We feel the relevance for drug discovery is not significantly weakened for a number of reasons: 1) as shown in Fig. 1A, the stalk sequence is highly conserved between mouse and human PC1, specifically there are only 2 residue differences present within peptides p17 and p21. One of the differences is a ‘semi-conservative’ Gln-Arg substitution at peptide residue 15, while the second difference is a conservative Ile-Val substitution at peptide residue 17; 2) we have found that an Arg to Cys mutation within the mouse PC1 CTF stalk has the same effect on signaling as the corresponding human Gln to Cys ADPKD-associated mutation which was analyzed in Pawnikar et al., 2022; and 3) both peptide residues 15 and 17 represent highly variable positions within the PC1 stalk as shown in the sequence logo (below) of the stalk sequence from 16 vertebrate species; and 4) while addressing the potential effect of the hydrophilic solubility tag on stalk peptide-mediated rescue of CTF∆stalk signaling (see Reviewer 1 comments, point #7), we utilized the ‘human’ version of p17 as a positive control and tested its activation with both mouse and human CTF∆stalk expression constructs and found that human p17 peptide was also capable of stimulating the mouse CTF∆stalk protein (Fig. S2).
Author response image 1.
(4) More control experiments are needed. For example, a 7-residue hydrophilic sequence (GGKKKKK) is attached to the peptide design to increase solubility. This 7-residue peptide should be tested for PC1 activation as a control. Second, there is no justification for why the peptide design must begin with residue T3041. Can other segments of the stalk also be agonists?
As mentioned above for Reviewer 1, the hydrophilic peptide has been synthesized and tested for activation of signaling by the stalkless CTF in the revised manuscript as Fig. S2. The design of peptides that begin with residue T3041 of mouse PC1 CTF is modeled on numerous similar studies for the family of adhesion GPCRs. Optimization of the binding and activity of the PC1 peptide agonist will be investigated in future studies and could include such parameters as whether the peptide must include the first residue and whether subsegments of the stalk are also agonists, however, we feel these questions are beyond the scope of this initial report.
(5) There are some major concerns about the simulations: The GaMD simulations showed different binding sites of p-21, p-17, and p-9, and the results report the simulated conformations as "active conformational states". However, these are only computational findings without structural biology or mutagenesis data to validate. Further, neither docking nor the simulation data can explain the peptide SAR. Finally, it will be interesting if the authors can use docking or GaMD and explain why some peptide designs (like P11-P15) are less active (as control simulations).
The reviewer brings up an important observation regarding differences in binding sites between peptides p9, p17 and p21. We will include discussion of this observation and our interpretations to the revised manuscript. While the present study is focused on identification of initial peptides that are able to activate the PC1 CTF, we shall include further mutation experiments and simulations, peptide SAR and optimization of the lead peptides in future studies. This has been clarified in the revised manuscript.
(6) Additional experiments for the controls and for validating the simulations. Additional simulations to explain the SAR.
We appreciate the reviewer’s comment for additional experiments for the controls and additional simulations to explain the SAR. For future studies, we shall include further mutation experiments and simulations, peptide SAR and optimization of the lead peptides.
(7) What is the selectivity of the peptides between PC1 and PC2?
We have not tested the selectivity of the peptides for PC1 versus PC2 primarily because transfection of PC2 does not activate the NFAT reporter. However, it is possible that co-transfection of PC2 with the PC1 CTF could alter stalk peptide binding. This will be important to consider in future studies.
Reviewer 3:
The authors demonstrate the activation of Polycystin-1 (PC1), a G-protein coupled receptor, using small peptides derived from its original agonist, the stalk TA protein. In the experimental part of the study, the authors performed cellular assays to check the peptide-induced reactivation of a mutant form of PC1 which does not contain the stalk agonist. The experimental data is supported by computational studies using state-of-the-art Gaussian accelerated Molecular Dynamics (GaMD) and bioinformatics analysis based on sequence covariance. The computer simulations revealed the mechanistic details of the binding of the said peptides with the mutant PC1 protein and discovered different bound, unbound, and intermediate conformations depending on the peptide size and sequence. The use of reliable and well-established molecular simulation algorithms and the physiological relevance of this protein autosomal dominant polycystic kidney disease (ADPKD) make this work particularly valuable.
We greatly appreciate the reviewer’s encouraging and positive comments. The reviewer’ specific comments are addressed pointwise below and changes to the text will be highlighted in yellow in the revised manuscript.
(1) No control has been used for the computational (GaMD) study as the authors only report the free energy surface for 3 highly agonistic peptides but for none of the other peptides that did not induce an agonistic effect. Therefore, in the current version, the reliability of the computational results is not foolproof.
We appreciate the reviewer’s concern about the lack of control with the other peptides that did not induce an agonistic effect. To address the reviewer’s concern, we have included more details on the study of the stalkless CTF and the solubility tag peptide (Fig. S2) as controls in the revised manuscript.
(2) All discussions about the residue level interactions focused only on geometric aspects (distance, angle, etc) but not the thermodynamic aspect (e.g. residue-wise interaction energy). Considering they perform a biased simulation; the lack of interaction energy analysis only provides a qualitative picture of the mechanism.
As mentioned by the reviewer, we have added MM/PBSA analysis results in the revised manuscript and SI.
Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) analysis was performed to calculate the binding free energies of peptides p9, p17 and p21 to PC1 CTF. The analysis was performed using the trajectory in which the peptide was bound to the receptor. In MM/PBSA, the binding free energy of the ligand (L) to the receptor (R) to form the complex (RL) is calculated as:
where GRL is the Gibbs free energy of the complex RL, GR is the Gibbs free energy of the molecule R in its unbound state and GL is the Gibbs free energy of the molecule L in its unbound state, respectively.
𝛥𝐺𝑏𝑖𝑛𝑑 can be divided into contributions of different interactions as:
in which
where ΔEMM , ΔGsol , 𝞓H and −TΔS are the changes in the gas-phase molecular mechanics (MM) energy, solvation free energy, enthalpy and conformational entropy upon ligand binding, respectively. ΔEMM includes the changes in the internal energies ΔEint (bond, angle and dihedral energies), electrostatic energies ΔEelec , and the van der Waals energies ΔEvdW. ΔGsol is the sum of the electrostatic solvation energy ΔGPB/GB (polar contribution) and the nonpolar contribution ΔGSA between the solute and the continuum solvent. The polar contribution is calculated using either the Poisson Boltzmann (PB) or Generalized Born (GB) model, while the nonpolar energy is usually estimated using the solvent-accessible surface area (SASA) where 𝞬 is surface tension coefficient and b is the constant offset. The change in conformational entropy −TΔS is usually calculated by normal-mode analysis on a set of conformational snapshots taken from MD simulations. However, due to the large computational cost, changes in the conformational entropy are usually neglected as we were concerned more on relative binding free energies of the similar peptide ligands.
MM/PBSA analysis was performed using the gmx_MMPBSA software with the following command line:
gmx_MMPBSA -O -i mmpbsa.in -cs com.tpr -ci index.ndx -cg 1 13 -ct com_traj.xtc -cp topol.top -o FINAL_RESULTS_MMPBSA.dat -eo FINAL_RESULTS_MMPBSA.csv Input file for running MM/PBSA analysis:
&general
sys_name="Prot-Pep-CHARMM",
startframe=1, endframe=200, # In gmx_MMPBSA v1.5.0 we have added a new PB radii set named charmm_radii.
# This radii set should be used only with systems prepared with CHARMM force fields.
# Uncomment the line below to use charmm_radii set
# PBRadii=7,
/
&pb
# radiopt=0 is recommended which means using radii from the prmtop file for both the PB calculation and for the NP
# calculation
istrng=0.15, fillratio=4.0, radiopt=0
The relative rank of the overall peptide binding free energies (Table S1) was consistent with the experimental signaling data, i.e., p21>p9>p17, for which p21 showed the largest binding free energy value of binding (-40.29±6.94 kcal/mol).
(3) It is not mentioned clearly whether the reader should interpret the free energy landscapes quantitatively or qualitatively. Considering no error analysis or convergence plots are reported for the GaMD free energy surfaces, it may be assumed the results are qualitative. The readers should consider this caveat and not try to quantitatively reproduce these free energy landscapes with other comparable techniques.
We appreciate the reviewer’s comment whether the free energy landscapes should be interpreted quantitatively or qualitatively. The presented free energy landscapes could be considered semi-quantitative since the simulations are not fully converged. This will be clarified in the revised manuscript as: “It is important to note that the free energy profiles calculated from GaMD simulations of PC1 CTF were not fully converged since certain variations were observed among the individual simulations. Nevertheless, these calculations allowed us to identify representative low-energy binding conformations of the peptides.”
(4) Energy decomposition analysis similar to the following paper (https://pubs.acs.org/doi/10.1021/bi201856m) should be provided to understand the residue level enthalpic contribution in the peptide-protein interaction.
As mentioned by the reviewer, we have performed residue-wise interaction energy analysis and included the analysis results in the revised manuscript and SI.
Residue-wise interaction energy analysis was performed on peptides p9, p17 and p21 using the trajectory in which the peptide was bound to the PC1 CTF using the gmx_MMPBSA software with the following command line:
gmx_MMPBSA -O -i mmpbsa.in -cs com.tpr -ct com_traj.xtc -ci index.ndx -cg 3 4 -cp topol.top -o FINAL_RESULTS_MMPBSA.dat -eo FINAL_RESULTS_MMPBSA.csv -do FINAL_DECOMP_MMPBSA.dat -deo FINAL_DECOMP_MMPBSA.csv
Input file for running residue-wise energy decomposition analysis:
&general
sys_name="Decomposition", startframe=1, endframe=200,
# forcefields="leaprc.protein.ff14SB"
/
&gb
igb=5, saltcon=0.150,
/
# make sure to include at least one residue from both the receptor #and peptide in the print_res mask of the &decomp section.
# this requirement is automatically fulfilled when using the within keyword.
# http://archive.ambermd.org/201308/0075.html
&decomp
idecomp=2, dec_verbose=3, print_res="A/854-862 A/1-853”,
/
Residue-wise energy decomposition analysis allowed us to identify key residues that contributed the most to the peptide binding energies. These included residues T1 and V9 in p9 (Table S2), residues T1, R15 and V17 in p17 (Table S3), and residues P10, P11, P19 and P21 in p21 and residue W3726 in the PC1 CTF (Table S4). The energetic contributions of these residues apparently correlated to the sequence coevolution predicted from the Potts model.
(5) To showcase the reliability of the computational approach, the authors should perform the MD simulation studies with one peptide that did not show any significant agonistic effect in the experiment. This will work as a control for the computational protocol and will demonstrate the utility of the pep-GaMD simulation in this work.
We appreciate the reviewer’s concern about the lack of control with the other peptides that did not induce an agonistic effect. It is difficult for us to add more MD simulations on the other peptides, due to student leave after PhD graduation. But to address the reviewer’s concern, we have included more details on the study of the stalkless CTF as a control in the revised manuscript.
(6) To assess the accuracy of the computational results the authors should mention (either in the main text or SI) whether the reported free energy surfaces were the average of the five simulations or computed from one simulation. In the latter case, free energy surfaces computed from the other four simulations should be provided in the SI. In addition, how many binding unbinding events have been observed in each simulation should be mentioned.
We appreciate the reviewer’s comment regarding convergence of the simulation free energy surfaces. In response to Reviewer 1, we have calculated free energy profiles of individual simulations for each system, including the p9, p17, and p21 (Figs. S5, S6 and S8).
“We have calculated free energy profiles of individual simulations for each system, including the p9, p17, and p21 (Figs. S5, S6 and S8). For the p9 peptide, the “Bound” low-energy state was consistently identified in the 2D free energy profile of each individual simulation (Fig. S5). For the p17 peptide, Pep-GaMD simulations were able to refine the peptide conformation from the "Unbound” to the "Intermediate” and “Bound” states in Sim1 and Sim5, while the peptide reached only the "Intermediate” state in the other three simulations (Fig. S6). For the p21 peptide, PepGaMD was able to refine the peptide docking conformation to the "Bound” state in all the five individual simulations (Fig. S8).”
“It is important to note that the free energy profiles calculated from GaMD simulations of PC1 CTF were not fully converged since certain variations were observed among the individual simulations. Nevertheless, these calculations allowed us to identify representative low-energy binding conformations of the peptides.”
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Reviewer #2 (Public Review):
Choi et al. describe a new approach for enabling input-specific CRISPR-based genome editing in cultured cells. While CRISPR-Cas9 is a broadly applied system across all of biology, one limitation is the difficulty in inducing genome editing based on cellular events. A prior study, from the same group, developed ENGRAM - which relies on activity-dependent transcription of a prime editing guide RNA, which records a specific cellular event as a given edit in a target DNA "tape". However, this approach is limited to the detection of induced transcription and does not enable the detection of broader molecular events including protein-protein interactions or exposure to small molecules. As an alternative, this study envisioned engineering the reconstitution of a split prime editing guide RNA (pegRNA) in a protein-protein interaction (PPI)-dependent manner. This would enable location- and content-specific genome editing in a controlled setting.
The authors explored three different design possibilities for engineering a PPI-dependent split pegRNA. First, they tried splitting pegRNA into a functional sgRNA and corresponding prime editing transRNA, incorporating reverse-complementary dimerization sequences on each guide half. This approach, however, resulted in low editing efficiency across 7 different designs with various complementary annealing template lengths (<2% efficiency). They also tried inserting a self-splicing ribozyme within the pegRNA, which produces a functional pegRNA post-transcriptionally. The incorporation of a split-ribozyme, dependent on a PPI, could have been used to reconstitute the split pegRNA in an event-controlled manner. However again, only modest levels of editing were observed with the self-splicing ribozyme design (<2%). Finally, they tried splitting the pegRNA at the repeat:anti-repeat junction that was used to join the original dual-guide system comprised of a crRNA and tracrRNA, into a single-guide RNA. They incorporated the prime editing features into the tracrRNA half, to create petracrRNA. Dimerization was initially induced by different complementary RNA annealing sequences. Using this design, they were able to induce an editing efficiency of ~28% (compared to 37% efficiency using a positive control epegRNA guide).
Having identified a suitable split pegRNA system, they next sought to induce the reconstitution of the two halves in a PPI-dependent manner. They replaced the complementary RNA annealing sequences with two different RNA aptamers (MS2 and BoxB). MS2 detects the MCP protein, while BoxB detects the LambdaN protein. Close proximity between MCP and LambdaN would thus bring together the two split pegRNA halves, creating a functional pegRNA that would enable prime editing at a specific target site. They demonstrated that they could induce MCP-BoxB proximity by fusing them to different dimerizing protein partners: 1) constitutive epitope-nanobody/antibody pairs such as scFv/GCN4 or NbALFA/ALFA-Tag; 2) split-GFP; or 3) chemically-induced protein pairs such as FKBP/FRB or ABI/PYL. For all of these approaches, they could achieve between ~20-60% normalized editing efficiency (relative to positive control editing levels with epegRNA). Additional mutation of the linkers between the RNA and aptamers could increase editing efficiency but also increase non-specific background editing even in the absence of an induced PPI.
Additional applications of this overall strategy included incorporating the design with different DNA base editors, with the most promising examples shown with the base editors CBE4max and ABE8. It should be noted that these specific examples used a non-physiological LambdaN-MCP direct fusion protein as the "bait" that induced reconstitution of the two halves of the guideRNA, rather than relying on a true induced PPI. They also demonstrated that the recently reported RADARS strategy could be incorporated into their system. In this example, they used an ADAR-guide-RNA to drive the expression of a LambdaN-PCP fusion protein in the presence of a specific target RNA molecule, IL6. This induced LambdaN-PCP protein could then reconstitute the split peg-RNAs to drive prime editing. To enable this last application, they replaced the MS2 aptamer in their pegRNA with the PP7 aptamer that binds the PCP protein (this was to avoid crosstalk with RADARS, which also uses MS2/MCP interaction). Using this strategy, they observed a normalized editing efficiency of around 12% (but observed non-specific editing of around 8% in the absence of the target RNA).
Strengths:
The strengths of this paper include an interesting concept for engineering guide RNAs to enable activity-dependent genome editing in living cells in the future, based on discreet protein-protein interactions (either constitutively, spatially, or chemically induced). Important groundwork is laid down to engineer and improve these guide RNAs in the future (especially the work describing altering the linkers in Supplementary Figure 3 - which provides a path forward).
Weaknesses:
In its current state, the editing efficiency appears too low to be applied in physiological settings. Much of the latter work in the paper relies on a LambdaN-MCP direction fusion protein, rather than two interacting protein pairs. Further characterizations in the future, especially varying the transfection amounts/durations/etc of the various components of the system, would be beneficial to improve the system. It will also be important to demonstrate editing at additional sites; to characterize how long the PPI must be active to enable efficient prime editing; and how reversible the reconstitution of the split pegRNA is.
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Reply to the reviewers
We would first like to thank the reviewers for their careful reading and thoughtful feedback.
We have substantially revised the manuscript and included additional experimental evidence on O-GlcNAc and OGT/OGA protein levels in the placenta of embryos bearing the OGT-Y851A hypomorphic mutation.
Overall, we believe our improved manuscript provides compelling evidence that the glycosyltransferase activity of OGT, and thus the O-GlcNAc modification itself, plays a sexually dimorphic function in placental development and the developmental repression of retrotransposons in the developing embryo.
We have addressed each of the reviewers' comments below. The original comments (C) are in italic, our responses (R) in Roman font.
Reviewer #1
Evidence, reproducibility and clarity
C1: Formichetti at el. developed mice with OGT catalytic dead mutations and then studied their function during early embryogenesis. Not surprisingly, dramatic reduction in OGT activity failed to produce embryos; however, mild reduction in OGT did produce animals. The authors then use the T931 animals that have a mild reduction in activity to further characterize the function in the early embryo. Not surprisingly, male mice showed changes in gene expression, implantation sub-lethality, and an uptick in loss of retrotransposon silencing. The authors also show that an even milder reduction in OGT activity (Y851A) effects male placenta function and chromatin remodeling. Finally, the authors make a less stable OGT transgene within the mouse and again found embryogenesis issues in the males and alterations in numerous gene families including mTOR signaling and p53 function. All in all, this is an interesting study that track functions of OGT in early embryonic development. The studies are well-controlled and rigorous.
R1: We thank the reviewer for their clear understanding and their appreciation of the rigor and impact of this work.
Significance
C2: This is a good study and novel. Not only is it of interest to reproductive biologist, but it echos themes found in O-GlcNAc biology.
R1: We are pleased that the reviewer underlined the novelty of the study and its impact across fields.
Reviewer #2
Evidence, reproducibility and clarity
Comments to authors
C3: To investigate the function of OGT at specific developmental stages, the authors perturbed OGT's function in vivo by creating a murine allelic series featuring four single amino acid substitutions that variably reduced OGT's catalytic activity. The goal was to identify the direct effect of O-GlcNAcylation, using a sophisticated collection of genetic mutants to evaluate in vivo the role of this modification at early stages of development. Overall, the severity of embryonic lethality correlated with the extent of catalytic impairment of OGT, demonstrating that the O-GlcNAc modification is essential for early development.The study represents a substantial advance in our understanding of OGT and O-GlcNAcylation in mammalian development. The creation of novel murine models and inducible systems is an important contribution, providing powerful tools for future research in this field. The insights into the role of OGT's catalytic activity and its involvement in epigenetic regulation during embryonic development are noteworthy, opening new avenues for research.
R3: We thank the reviewer for their insightful comments. We are grateful for the supporting statements. Please find below detailed response to all your comments.
However, there are a few considerations and concerns:
Major:
C4: 1. An assumption of the study is that different mutations cause different levels of O-GlcNAcylation rather than alterations in substrate specificity. It might be important to test, at least in cultured cells, that the different mutations do not change the preference of OGT to modify certain proteins rather than others, which can provide alternative explanations for their findings.
R4: Thanks for asking this question, it helped us to better explain the rationale behind the choice of the Ogt amino-acid substitutions.
This is a critical point that we carefully considered in the design of the single amino-acid substitutions. Two lines of evidence support that the precise mutations created impact the catalytic rate without modifying the substrate specificity:
First, as explained in the text, the choice of the single amino-acid substitutions was driven by previous structural and enzymology knowledge. The impact of the four point mutations selected on OGT protein stability and on the Michaelis-Menten kinetic values had previously been determined experimentally (Fig. 1A legend and Martinez-Fleites, C. et al. Nature Structure Molecular Biology 2008; https://doi.org/10.1038/nsmb.1443).
There is a second important rationale that we added in the revised manuscript: the four point mutations selected are all located in the catalytic domain (specifically, H568A in the N-Cat domain and Y851A, T931A and Q849A in the C-Cat domain), while the substrate recognition is operated via two other domains namely the intervening domain (Int-D) https://doi.org/10.1038/s41589-023-01422-2) and the tetratricopeptide Repeat (TPR) superhelix (10.1021/jacs.7b13546; https://doi.org/10.1073/pnas.2303690120). Therefore, for both these reasons, it is extremely unlikely that these mutations could influence the substrate specificity.
C5.1: 2. In Fig 1D and 1H, the thresholds to define a gene or TE as differentially expressed are not strong. According to the figure legends, "any" change in terms of log2Fc was considered as DE and colored. I think the figures should illustrate better that the changes are subtle, by for example adding a dotted line (at least) in the value 0.5 of the y-axis. These subtle transcriptional changes should be reflected better in certain paragraphs where the expression of TEs are presented/and discussed as a hallmark of the absence of O-GlcNAcylation in the OGT-mutants. The same happens with Suppl Fig 3C (changes are very minor). {. Applying a stronger threshold, among the upregulated genes, only Xist will be significantly overexpressed. If a gentle threshold needs to be applied to this data, authors should at least justify the reasons behind doing so. Same for Fig2D.
R5.1: The reviewer means Figure 2D for MA plot of gene expression and Figure 2H for retrotransposons expression. These figures now include a dash line to indicate Log2FC = 0.5 (as all MA plots).
The text is explicit on the subtle changes in transcription, it reads "with 2/3 of the genes downregulated and 90% of the significant changes below 1 log__2__FC"; "most of the Ogt__T931del/Y embryos showed a low magnitude upregulation of retrotransposons".
The revised text states "Notably, most of the OgtT931__del/Y embryos showed a low magnitude (log2FC < 1) upregulation of retrotransposons".
We expand on this topic in the next response (R5.2) noting that changes in gene expression upon O-GlcNAc perturbation in different systems were previously characterized as subtle and widespread. We suggest that this phenotype may arise from the scarcely understood pleiotropic function of O-GlcNAc in fine-tuning gene expression; this phenotype could have a biological significance.
C5.2: If a gentle threshold needs to be applied to this data, authors should at least justify the reasons behind doing so. Same for Fig2D.
R5.2: Previous studies in different systems reported that O-GlcNAc perturbation causes a widespread change in gene expression of low magnitude (https://doi.org/10.1101/2024.01.22.576677, https://www.pnas.org/doi/10.1073/pnas.2218332120). We use the same thresholds as a recent functional Ogt study in ES cells to call differentially expressed genes, specifically: p<0.05 (Wald test), any FC (Li et al. PNAS 2023, https://www.pnas.org/doi/10.1073/pnas.2218332120). The p value threshold is standard; the absence of FC threshold is dictated by the insufficient knowledge of the significance of the low magnitude changes observed across many transcripts.
C6: 3. In Figure 2B, the T931del allele was recovered in the blastocyst population with a very high frequency, even higher than the male WT group (T931del: 10; WT: 3). This observation suggests that the T931del allele did not significantly affect blastocyst survival. Further clarification or additional experiments might be necessary to understand the implications of this finding on early developmental stages.
R6: This is only a hint as the numbers of blastocysts recovered were too small to perform statistics on Mendelian distribution. Thus, more experiments are needed to perform these statistical tests. These experiments are onerous because the low frequency of germline transmission is incompatible with maintaining this mutation by breeding heterozygous animals. Because of this, a new mouse line needs to be created by CRISPR-HDR targeting in the zygote in order to compute statistics on Mandelian ratios. Importantly, this question - does T931del affect blastocyst survival? - is peripheral, and the results of these experiments would not affect our conclusions in any way.
C7: 4. Similarly, in Figure 2G, there is an apparent higher expression of TE expression in the T931A/Y embryos group than in the T931del/Y group, which combined with the higher frequency of blastocyst generated in this latest group it may indicate a deeper molecular consequence after the deletion of the T931. A comparison of the transcriptome between these two cell lines help to address this possibility. Also, the authors should compare the O-GlcNAc levels of WT, T931A, and T931del mutant blastocysts by immunostaining, similar to what was done in Figure S5F.
R7: We agree that a direct comparison between the two mutations of the T931 residue would be interesting; however, this comment is very difficult to address experimentally for the reasons outlined below:
Firstly, it is not possible to perform a statistical comparison of the transcriptome T931A/Y VS. T931del/Y with the data generated because the number of hemizygous T931A/Y (n=2) is too small. Hence, it cannot be ruled out that the seemingly milder retrotransposon reactivation in one of the T931A/Y embryos could have occurred by chance.
Secondly, considering the low magnitude effect on gene expression changes upon O-GlcNAc genetic perturbation, to statistically assess the penetrance of the molecular phenotype and perform the differential expression analysis, numerous (>>3) hemizygous blastocysts of each genotype would be needed. Because females heterozygous for the T931 mutations transmit the mutant allele at very low frequency, these experiments require numerous de novo CRISPR injection sessions.
Thirdly, for the immunostaining of O-GlcNAc to be semi-quantitative, a large number of hemizygous blastocysts for each genotype would be required (note that in Figure S5F, 29 morulae per condition were imaged), thus requiring numerous CRISPR injection experiments as discussed above. Moreover, O-GlcNAc changes could be subtler than what expected based on the strong reduction of OGT activity, since as a compensatory mechanism Ogt expression is upregulated in the Ogt__T931A/del blastocysts (Fig. S2D), making a quantification even more challenging despite a high number of stained embryos.
In sum, these in vivo experiments are difficult and require sacrificing many animals (about 20 females per CRISPR injection experiment). Because the results would bring refinement to the study but would not change our conclusions, we suggest that the cost/benefit is too high.
C8: 5. In Boulard et al. 2019 O-GlcNAcylation was shown to be sufficient to modulate expression of DNA methylation-dependent TEs. It would be interesting to know (or at least discuss) if the changes in TE expression observed in OGT-mutant embryos in this study involve changes in DNA methylation. Ideally, some DNA methylation measurement optimized for low input numbers of cells would be useful.
R8: Thank you for making the link with our previous study. In the PNAS paper, we report that targeted removal of O-GlcNAc at proteins bound to specific TEs (e.g. IAPez) causes their full-blown reactivation without detectable changes in DNA methylation, thus suggesting a role of the O-GlcNAc modification for the silencing of methylated TEs downstream or independent of DNA methylation. We agree that it would be informative to quantify DNA methylation in the T931-mutant blastocysts to test if the in vitro result is the same in vivo, but this would require performing onerous microinjection sessions as explained above.
C9: 6. The data related with the OGT-degron system in MEs seem disconnected with the rest of the manuscript. While the developmental models (blastocyst, etc) elegantly assess the contribution of O-GlcNAcylation to the control of cell survival and gene expression through the use of different OGT mutants, the degron system is a system of graded depletion that unfortunately was only possible to be used in MEFs (instead of embryos). Thus, the results obtained with the degron system in MEFs are difficult to intersect with the data from the use of OGT-mutants in embryos. Even though there are obvious interesting questions that one may want to know about this OGT degron MEF system, none of them would demonstrate a direct role for O-GlcNAcylation in cellular function, the major point addressed in the developmental system. Using the degron system in embryonic stem cells might have provided a more parallel comparison. The authors should discuss this point in more detail and either use ESC instead of MEFs or provide a stronger justification for the use of MEFs over ESC.
R9: We thank the reviewer for their clear understanding of the system. The choice of primary MEF as an in vitro model was imposed by technical limitations we encountered during the study. We fully agree that ES cells is the model of choice for preimplantation embryos; thus we initially derived ES cells and obtained only one male clone bearing the AID degron system. Upon auxin addition to the culture media, OGT's level remained unchanged in ES cells. Thus, the ES cells model was not usable. To test the AID degron in a different cell type, we then derived MEFs and showed its effectiveness (Figures 4C and S4C-E), which also allowed to collect functional data on OGT's cellular function (Figures 4D-F). We took the comment on board and clarified the rationale of studying MEFs in the revised manuscript. We agree that it remains to be verified that the OGT-dependent pathways uncovered in MEFs are relevant in the preimplantation embryo. Despite this caveat, we feel the mouse model for endogenous OGT-degron, as well as the negative results in vivo and conclusions in MEFs should be shared with the community, which could take advantage of our results to refine the system.
Minor:C10: 7. In Fig 2C the color and shape codes are confusing to understand - there are some colors/shapes that are not represented in the PCA plot. The same in Fig 3H, where in the PCA plot there are pink triangles that do not match with the code legends.
R10: We apologize for the confusion with the legends of Figures 2C and 3H, that we have made unambiguous in the revised version (as well as Figures S2B,C and S3C).
C11: 8. In the figure legends of Figures 2D, 2E, 2F, and 2H, the notation should be corrected from "OgtT931A/Y" to "OgtT931del/Y".
R11: This has been corrected; many thanks for bringing it to our attention.
Significance
C12: To investigate the function of OGT at specific developmental stages, the authors perturbed OGT's function in vivo by creating a murine allelic series featuring four single amino acid substitutions that variably reduced OGT's catalytic activity. The goal was to identify the direct effect of O-GlcNAcylation, using a sophisticated collection of genetic mutants to evaluate in vivo the role of this modification at early stages of development. Overall, the severity of embryonic lethality correlated with the extent of catalytic impairment of OGT, demonstrating that the O-GlcNAc modification is essential for early development.
R12: We thank the reviewer for their clear understanding of our work and their appreciation of the biological importance of the findings.
Reviewer #3
Evidence, reproducibility and clarity
C13: This is a conceptually interesting paper that attempts to leverage the knowledge of OGT catalysis to begin to dissect OGT function. The evidence is presented I a straightforward fashion and is in general well documented. The breeding strategies are well informed and the paper draws heavily on previous work carried out in the mouse.
R13: We greatly appreciate the overall supporting review. However, we fail to understand what they mean with "the paper draws heavily on previous work carried out in the mouse". This comment may stem from a misunderstanding because this work is not based on any previously published study. Specifically, neither the seven murine alleles presented and analyzed nor the single embryo-transcriptomic data sets on which our conclusions are based have been published elsewhere.
To put this work into context, before our study there were two seminal studies published two decades ago that reported the essential role of Ogt for mouse development, but no molecular profiling was performed (10.1073/pnas.100471497, 10.1128/mcb.24.4.1680-1690.2004). The two Ogt loss-of-function alleles studied in these papers were deemed as not suitable for interrogating molecular phenotypes because they caused cell death that confounds molecular profiling and embryonic lethality at implantation, thus preventing study of the sexually-dimorphic role of Ogt placenta. To overcome this long-standing problem, we created new seven murine alleles, which allowed us to tease apart molecular phenotypes at key stages of mouse embryonic development, focusing on the blastocyst and the placenta.
Significance
C14: The paper describes tools which will help dissect the many potential roles of O-GlcNAc addition in early development. As it stands, this is a descriptive manuscript that will lead to hypothesis generation and testing and this should not be undervalued. The biological reagents produced and characterized will be of general interest to the field. Most of the findings presented represented a verification of existing ideas in the field but this is not meant as a criticism since part of the motivation for the approach was to generate a reproducible system for analyzing the biological phenomena.
R14: We thank the reviewer for their appreciation of the importance of experimentally testing ideas shared in the field without direct evidence.
However, we must respectfully disagree with the qualification of "descriptive manuscript". This qualification may stem from the particularly difficult challenge to accessing the molecular details on how the O-GlcNAc modification exerts the biological functions we report. We are fully cognizant of the limitations of the study that we discussed in the discussion section and in R20.2. However, we feel that the adjective "descriptive" is not a fair qualification because we provide numerous novel functional evidence. Specifically, we introduce two novel orthogonal in vivo perturbations for endogenous Ogt that allowed us to interrogate for the first time its function in the developing mouse embryo. These perturbations allow us to draw causative conclusions (not descriptive) on the essential role of the O-GlcNAc modification itself for preimplantation development, its sexually-dimorphic role in the placenta and its requirement in vivo for the stable repression of retrotransposons.
C15: There are perhaps some bioinformatic shortcuts taken that may need to be corrected upon thorough review. These do not lessen the overall impact of the contribution.
R15: All the code written for the bioinformatic analyses performed in this study is publicly available: https://github.com/boulardlab/Ogt_mouse_models_Formichetti2024. The reviewer needs to specify which bioinformatic analysis they suggest could be improved.
Reviewer #4 (Evidence, reproducibility and clarity (Required)):
Summary
C16: O-GlcNAcylation is the fundamental post-translational modification of numerous nuclear and cytosolic proteins. OGT is the sole enzyme catalyzing O-GlcNAc addition onto the proteins. The essentiality of OGT for early development and cellular viability has been established by using OGT-KO mice and cell lines. However, it remains to be elucidated whether the catalytic activity of OGT is required for the early development, and if the catalytic activity of OGT is required what are the functions of OGT or O-GlcNAcylation in early development due to a lack of appropriate mouse models. To overcome the technical difficulty of manipulating the levels of O-GlcNAcylation in early embryos, Formichetti et al. created the series of four mouse models (OgtY851A, OgtT931A, OgtQ849N, and OgtH568A) with different OGT activity by introducing single amino acid substitution in the catalytic domain. By analyzing the inheritance of the hypomorphic OGT alleles and the lethality of mouse embryos, they discovered OGT activity is a critical factor for early development. Subsequently, RNA-seq analyses with two mouse models showing the maternal inheritance of the hypomorphic OGT alleles indicated that sever hypo-OGT activity altered transcription and silencing of retrotransposon in preimplantation development while mild reduction of OGT's activity affected placental development in a sexually dimorphic manner rather than preimplantation development. Furthermore, to study the function of OGT at specific developmental stages, they developed a mouse model bearing endogenously AID-tagged OGT for acute degradation of OGT. Although the degron system wasn't efficient in preimplantation embryos, they discovered quick transcriptional changes upon OGT deletion in MEFs. The quality of the manuscript is good because the question to be solved was appropriately set, the approach was well designed, and their findings were interesting, although their writing was sometimes hard to understand as I raised in my following comments. Nevertheless, there are several points to be fixed before being published.
R16: We thank the reviewer for their clear understanding of our work and their appreciation of the biological importance of the findings. Your comprehensive review of the manuscript and the questions you raised were extremely helpful in improving the manuscript and fully addressing its limitations. Below, we respond to comments in full, have revised the manuscript to improve clarity and have included novel results.
Major Comments
C17: 1. Although the authors showed in vitro activity of each mutant of OGT used in this manuscript by referencing the previous literature, they never showed the levels of global O-GlcNAcylation (and OGT itself) in their established mouse embryos. Although it could be impossible to determine O-GlcNAc levels in OgtQ849N and OgtH568A embryos because of the lack of germline transmission and founder line, respectively, they could do that in OgtY851A and OgtT931A embryos. Given that Y851A and T931A mutants had similar VMAX/KM with different VMAX, it is possible that their activity is comparable or Y851A has even lower activity in vivo depending on the concentration of UDP-GlcNAc in embryos. Therefore, it is critical to assess whether in vivo OGT activity is correlated with that in vitro as expected to conclude that severity of sub-Mendelian inheritance is proportional to the reduction of activity of OGT in vivo. Moreover, since the authors developed the elegant system to deplete OGT, the activity of Q849N and H568A mutant OGT can be examined at least in cells by expressing them in MEFs with OGT-degron system. Thus, I propose determination of global O-GlcNAc levels compensated by OGT levels by western blotting in OgtY851A, and OgtT931A embryos or MEFs with the OGT degron system re-expressing the individual four mutant OGTs. If the protein amount is insufficient for western blotting in the embryos because of the sizes of the earlier stages of embryos, I believe the author could address this by utilizing immunofluorescence as shown in Figure S5.
R17: We fully agree that this is an important point that requires revision. The only mutation for which the level of O-GlcNAc and OGT can be assessed by western blot in vivo is Y851A, the other mutations resulting in embryonic lethality before the blastocyst stage.
We have included in the revised manuscript western blot analyses of protein expression for OGT, OGA and O-GlcNAc levels in the placenta of the OgtY851A mutants (new Figures 3C,D). The new data show that OGT is upregulated at the protein level in homozygous females, in good agreement with our transcriptomic analysis. Furthermore, O-GlcNAc levels were slightly reduced in homozygous and hemizygous placentae thus showing the impact of the point mutation on global O-GlcNAc levels in the placentae. Moreover, the analysis of OGA protein level unexpectedly revealed the enrichment of a previously uncharacterized OGA fast migrating isoform in hemizygous and homozygous placentae.
We agree that it would be informative to compare O-GlcNAc levels in OgtT931A versus OgtY851A embryos. A comparison implies performing the experiment at the same developmental stage, which has to be the blastocyst stage or prior because T931A/Y embryos die around implantation. The blastocyst being made of approximately 140 cells, it would require to pool many single blastocysts to obtain the necessary protein input for western blot. We are not aware of another study performing western blot with pooled blastocysts. An additional great challenge for this experiment is the necessity to genotype and sex the blastocysts before pooling. Thus, the feasibility of this experiment is uncertain.
As an alternative, the reviewer suggests measuring O-GlcNAc levels in the degron MEFs after introduction of OGT transgenes bearing the mutation studied. This experiment would not be conclusive because of residual O-GlcNAc after OGT degradation (Figure S4E). Furthermore, the O-GlcNAc proteome is dynamic during development (as shown in the developing brain by Liu et al. https://doi.org/10.1371/journal.pone.0043724), therefore the MEFs results would have limited value to explain our results in the early embryo.
In sum, available technologies to quantify O-GlcNAc (e.g. western bot, mass spectrometry) are inadequate for low input samples as the early embryo. However, our series of hypomorphic alleles backed up with in vitro enzymology measurements brings indirect evidence to this question. Specifically, the qualitative correlation between the measured OGT activity in vitro and the developmental phenotype indicates that the resulting relative levels of O-GlcNAc are consistent with in vitro measurements.
C18.1 : 2. I didn't understand why the authors couldn't find any founder lines of the OgtH568A mutant. Was that because mosaic mice with OgtH568A mutation are lethal?
R18.1: To answer to this question, it is important to recall two key features of the biological system:
1) The mutation H568A was reported to disrupt the glycosyltransferase activity completely (10.1038/nsmb.1443). Hence, OGT-H588A is catalytic dead.
2) We performed the CRISPR-HDR targeting in the 1-cell embryo.
Based on these premises, the absence of F0 with the OgtH568A mutation (0/31) suggests that introducing this mutation causes embryonic lethality in both males and females. This hypothesis is consistent with the previously reported lethality around implementation of Ogt-null alleles (10.1128/mcb.24.4.1680-1690.2004). It is possible that the sgRNA is very efficient and results in homozygous mutations in all female zygotes injected (as we have not obtained heterozygous females bearing these mutations). High efficiency of the targeted mutagenesis in the zygote results in mutants where all or the majority of cells bear the mutation (no or low mosaicism). The high number of microinjections performed (416 embryos over the 3 injection sessions) allows us to make these claims.
C18.2 : Also, I believe there was no explanation why the OgtQ849N allele showed no maternal inheritance. Was that because Q849N possesses enough activity for sustaining mosaic embryos, but not oocytes? The authors should better explain these points in the manuscript text.
R18.2: Thanks for this comment, we agree that this maternal effect phenotype demands further explanation.
The phenotype observed suggests two possibilities: either that the oocyte cannot maturate or that the cleavage-stage embryo cannot develop with the resulting lower levels of O-GlcNAc. The cleavage-stage embryo does not transcribe a catalytically active OGT before the 8-cell stage and thus relies on the OGT protein inherited from the oocyte until this stage (https://doi.org/10.1101/2024.01.22.576677).
Thank you for this comment, we added this interpretation of the result in the text:<br /> "The lack of maternal transmission of the Q849N allele from seemingly mosaic founder females is likely explained by the reliance of the cleavage stage embryo onto the oocyte payload of OGT and O-GlcNAc modified proteins. Specifically, Ogt's exons encoding for the catalytic domains are not detectable before the 8-cell stage, while OGT full-length protein is present and thus maternally inherited (Formichetti et al, 2024)."
C19: 3. The authors serendipitously found a T931del-allele in the "WT" allele of the OgtT931A line, and suggested that T931del had milder activity loss, although the lethality of embryos was greatly mitigated. Nevertheless, transcriptome analyses in male blastocysts revealed that 120 genes' expression was changed in T931del/Y males. This raised the question about which mutant OGT has higher activity, Y851A or T931del. I think comparing the activity of Y851A and T931del mutants in MEFs with OGT-degron system is important to confirm the proportional relationship between activity and phenotypic severity.
R19: We agree that it is a limitation that the effect of the T931del mutation on OGT activity has not been biochemically characterized. However, the important point here is that our assessment of phenotypic severity based on maternal inheritance of the mutant allele and embryonic lethality is based on the point mutations for which the catalytic activity has been determined, namely Y851A, T931A, Q849N and H568A, but not T931del.
We studied the serendipitously discovered T931del mutation to obtain transcriptional insights in the blastocyst. Because the deleted residue T931 is key for the binding to the donor substrate, we can reasonably assume that this mutation affects the catalytic activity, albeit to an undetermined level.
Hence, our conclusions regarding the requirement of O-GlcNAcylation for development are unaffected by the lack of biochemical knowledge on T931del.
C20.1: 4. Regarding transcriptomes of T931del/Y, the authors found the upregulation of proteasomal activity and stress granules along with the downregulation of amino acid metabolism, mitochondrial respiration, and so on. To validate the results, the authors should perform qPCR on several up- or down-regulated genes.
R20.1 : We agree that, in principle, qPCR validation is suitable. However, this validation experiment is particularly expensive in this case because of the requirement of numerous CRISPR zygote pronuclear injection sessions.
The conclusions of the RNA-seq analysis are strongly supported by a high number of biological replicates (n=10). This high number of biological replicates was essential to obtain sufficient statistical power to quantify with a high level of confidence transcriptional changes of low magnitudes (below 2-fold change, see R5.1 and R5.2).
Therefore, the qPCR validation experiment would require to repeat the CRISPR zygote pronuclear injection sessions with the same high number of animals. This represents a major investment in experimental work and the sacrificing of about 40 animals. Importantly, the RNA-seq results presented are authoritative because of a high number of biological replicates and high number of sequencing reads per sample. Thus, we argue that qPCR validation is not essential and thus the high cost of this experiment is difficult to justify.
C20.2: In addition, according to Figure S2E, the authors pointed out that at least for genes upregulated in OgtT931A embryos, the changes were not explained by a developmentally delayed transcriptome, suggesting that upregulation of these genes was the cause of developmental delay. Therefore, I strongly encourage them to discuss in the manuscript text how up-regulated genes could contribute to developmental delay.
R20.2: Throughout the manuscript, we have been cautious to avoid establishing causal relationships between the differentially expressed genes uncovered and the developmental phenotypes (e.g. delayed development). There are two main obstacles which we believe prevent us from establishing causality with the data available. Firstly, it is not possible to disentangle differentially expressed genes and developmental delay (in other words, we have no way to tell which is the cause and which is the consequence). Secondly, O-GlcNAc modifies over 5000 proteins and the developing embryo is a particularly dynamic system; thus we cannot know whether the differentially expressed promoters are direct targets of O-GlcNAc modified proteins (or alternatively secondary effect of another molecular alteration, for example of the proteome). We discuss this limitation of the study in the discussion section.
C21: 5. Regarding the transcriptome in OgtY851A mice, Y851A/Y male mice had huge transcriptomic differences, while Y851A/Y851A female mice barely had any. Although it seems to agree with the number of Ogt alleles, I wonder whether other X-linked genes expressed higher in female placenta as shown in Figure 3C could attenuate the effects of decreased OGT activity. I don't think this possibility can be excluded, unless the authors further decrease OGT activity in Y851A/Y851A female placenta and obtain the similar results as for male placenta. Or if they compared the levels of global O-GlcNAcylation between Y851A/Y and Y851A/Y851A mouse placentas and discovered they had similar levels of O-GlcNAcylation, then the authors could conclude that the number of Ogt alleles was not the reason of sexual-dimorphism. The authors should determine the levels of O-GlcNAcylation in Y851A/Y and Y851A/Y851A mouse placentas and/or at least discuss the above possibilities in the manuscript text.
R21: Thank you for the thoughtful feedback. We agree that the most likely explanation for the higher sensitivity of males placenta as compared to females to OGT reduced activity is the difference in Ogt copy number, especially because Ogt escapes X-chromosome inactivation in the placenta (new Figure S3A).
Western blot quantification of global O-GlcNAc levels was now performed (new Figures 3C,D). We measured similar level of O-GlcNAc in Y851A/Y and Y851A/Y851A placentas (lowered than WT males in both cases), but we cannot exclude that the WB does not have the dynamic range required to detect a subtle difference. In fact, female homozygous were expected to have an intermediate level between WT males and hemizygous males, and the difference between the two male genotypes (also considering sample-to-sample variability) is already small when quantified from the blot (new Figure 3D). It is possible that a X-linked modifier attenuates the impact of hypo-O_GlcNAcylation in female mutant placenta in the case of identical O-GlcNAc levels in homozygous females and hemizygous males. Thank you for the idea that we included in the revised manuscript:
"Of note, the lower sensitivity of the homozygous females' transcriptome to Ogt disruption (Fig. 3F,I and S3B) seems difficult to reconcile with their lower O-GlcNAc level comparable (lower) O-GlcNAc level to the hemizygous males (Fig. 3C). It is possible that the western blot technique is not sensitive enough to detect subtle differences in O-GlcNAcylation. An alternative hypothesis, if O-GlcNAc levels were truly identical between Y851A/Y and Y851A/Y851A, could be the existence of a modifier in female that could be a XCI-escapee."
C22: 6. In terms of the transcriptome in OgtY851A mice, similar to comment 4, the authors should confirm their transcriptomics data shown as Figure 3D by qPCR. In addition, the authors should describe the potential mechanisms by which the differentiation of precursor cells of LaTPs and JZPs were disrupted. Were master regulators of the differentiation known to be O-GlcNAcylated and loss of O-GlcNAcylation perturbed the function?
R22: As for the whole embryo discussed in R20.2, we also interpret cautiously the gene expression phenotype observed in the placenta. Specifically, we state in the manuscript that it could either be caused by an impact of lower O-GlcNAcylation on placental differentiation or by a general delay in placentation or in the development of the embryo as a whole. The hypothesis of a general delay (of the whole embryo and/or of placental formation specifically) is supported by the downregulation of essentially all markers of more differentiated cell types and the upregulation of the precursor marker. We favor this hypothesis because it is consistent with what observed with the T931 mutants and also with the enzymatic removal of O-GlcNAc in the zygote (Formichetti et al., 2024 BioRxiv). Because of the thousands of O-GlcNAcylated proteins present in the cell, it is impossible to know which is the responsible molecular mechanism, which could even start at much earlier stages.
Minor Comments
C23: 1. Regarding DFP461-463 mutant, I couldn't understand the point of this figure because the results had no difference, and the meaning of the mutation was quite different from the others. Thus, the figure was awkward and a little confusing to me. If the authors still want to include the figures, I would suggest that they should reorganize the position of the figure (maybe after figure 3 is better to show you had tried to investigate the effects of nuclear localization of OGT on the changes of transcriptomes) and add some results. Since WT OGT seems to be localized mainly in the cytosol at steady state (Figure S1B and S1C), the effect of mutation on its nuclear localization should not be obvious. Therefore, it is difficult to conclude the mutation had no effect on the nuclear localization unless the ratio of nuclear and cytosol localization is quantified. Also, I wonder whether the O-GlcNAc levels of nuclear and cytosolic proteins in the mutant cells were comparable to those in WT cells. If this is the case, the results would also support the authors' conclusion.
R23: We took the comments on board and made it clearer that the rationale for the DFP461-463 mutant was an attempt to separate OGT's nuclear and cytosolic functions. We fully agree that these results are peripheral, and thus we presented these results in Supplementary Figure 1 (not in the main figure).
The biochemical evidence presented in Fig S1C shows that the genetic substitution of DFP to AAA on endogenous OGT has no detectable impact on its nuclear localization in primary MEFs. This result is far more authoritative than the evidence provided by Seo et al. 2016 (doi: 10.1038/srep34614), which is based on the overexpression of OGT transgenes in HeLa cells. Importantly, Seo et al. 2016 did not assess the impact of their mutations on endogenous OGT.
We believe that the negative results we obtained with the DFP461-463 mouse model shall be extremely valuable for the field. Firstly, science can move forward only if both negative and positive results are shared. In this specific case, we found that mutation of endogenous OGT in MEFs yielded to a different result than previously reported overexpression of the same mutant construct in HeLa cells. Secondly, we want to make the Ogt-NLS- mouse model available for further investigations.
C24: 2. Since OGT or O-GlcNAcylation regulates chromatin status, the authors analyzed the gene expression profiles of retrotransposons in T931del/Y or T931A/Y mice. Is it possible to investigate if the release of gene silencing is also seen in non-retrotransposon genes? I assumed retrotransposons might be a well-established system to analyze gene silencing status, however, if the authors could find similar effects on genes other than retrotransposons, that would be highly valuable.
R24: This is an interesting idea. This notion refers to the activation of promoters that are normally epigenetically repressed (e.g. silent despite the presence of all trans-active factors required for their expression). Epigenetically repressed promoters include retrotransposons, imprinted genes and germline specific genes that are normally expressed in germ cells and maintained in a repressed state in somatic cells (10.1038/s41580-019-0159-6). Testing of mono-allelic expression of imprinted genes required F1-hybrid. Thus, we assessed whether well-studied germline specific genes could be realized from silencing in T931del/Y or T931A/Y blastocyst and found no evidence for it (see dot plot below). The unbiased transcriptomic analysis presented in the manuscript shows that the product of upregulated genes are enriched in mRNA processing (Figure 2E), but these genes are not normally epigenetically repressed. Thus, contrary to retrotransposons, the role of O-GlcNAc at cellular gene promoters appears not to be linked to epigenetic silencing. This could be explained by the many different protein substrates for O-GlcNAc.
C25: 3. OgtY851A mice with milder OGT activity loss didn't exhibit impaired preimplantation development, but did display postimplantation development such as placental development, suggesting that O-GlcNAcylation of proteins required for preimplantation and postimplantation development relies on different degrees of OGT activity. I wonder whether global O-GlcNAc levels in embryos in preimplantation and postimplantation developmental stages are different or not. This might include both the pattern of blotting and intensities. The results would give the authors an explanation why the dependency on OGT activity was different in two developmental stages. Can the authors provide data? If not, then the authors should at least describe hypotheses in the manuscript to address these questions.
R25: We recently reported that the subcellular patterns of O-GlcNAc are highly dynamic during preimplantation development (Formichetti et al. 2024, BioRxiv). The most striking O-GlcNAc remodeling we observed is the enrichment of nuclear O-GlcNAc as compared to cytoplasmic O-GlcNAc that is concomitant to embryonic genome activation (Formichetti et al. 2024, BioRxiv). We quantified the ratio of the nuclear/cytoplasmic signal by immunofluorescence, but absolute quantification is not possible with this method. Due to the limited number of cells of the preimplantation embryo, this analysis cannot be performed by western blot. Hence, there is no appropriate method to quantitatively compare O-GlcNAc levels between preimplantation and postimplantation embryos.
C26: 4. The authors' AID-degron system elegantly worked in MEFs but was inefficient in preimplantation embryos. I wonder if this was because of the high expression of the shorter isoform of OGT detected as OGTp78 in the author's western blot. Is it possible to examine this possibility in the embryos? Either way, the authors should describe a potential explanation for why the efficiency in the embryos was low. In addition, the authors should describe why they inserted the AID tag only into the longest OGT isoform.
R26: This is a good point. The smallest isoform OGTp78 bears the catalytic domain and thus can partially compensate for the degradation of OGTp110. Note that the level of OGTp78 is low and does not increase upon OGTp110 degradation; thus a compensation can only be partial (Figures S4A and S4D). Alternative hypotheses for the ineffectiveness of the degron system in ex vivo grown embryos include: i) the expression level of OsTIR that may be too low in the early embryo (Rosa26 promoter not being activated at EGA), ii) a possible steric hindrance of the N-ter AID tag in these cells, iii) the lower concentration of Auxin imposed by toxicity on the embryo is likely suboptimal. Testing these possibilities is very difficult in preimplantation embryos.
It is unclear how the OGTp78 isoform is produced; it was hypothesized to originate from an alternative transcription start site (https://doi.org/10.1007/s00335-001-2108-9). We initially attempted to target both isoforms by inserting the AID tag at the C-terminus, but we were unsuccessful in producing this mouse model. It is possible that the C-terminus that is near the catalytic site cannot tolerate the AID knock-in.
C27: 5. In Figure S1C, is the band detected right below OGTp78 in nuclei fractions non-specific or do both bands correspond to OGTp78 ?
R27: To answer this question, a knockout control would be needed. OGTp78 being not targeted by our AID-degron, we cannot test the specificity of these bands using our perturbation tool kit.
C28: 6. Figure 1D top row third column: hemizgous -> hemizygous
R28: Many thanks; the embarrassing typo has been corrected.
C29: 7. Figure 1D second row third column: hemyzygous -> hemizygous
R29: Thanks for bringing this other typo to our attention, it is now corrected.
Reviewer #4 (Significance (Required)):
General assessment: strengths and limitations
C30: Strength: This manuscript elegantly revealed the requirement of OGT in mammalian development by taking advantage knock-in mouse models with different OGT activity. In addition, the manuscript provided the interesting and important transcriptomics data in both pre- and post-implantation embryos of OGT mutant mice. These data sets could explain detailed mechanisms how OGT or O-GlcNAcylation regulates mammalian development in the future. Furthermore, development of AID-tagged OGT system would be a useful tool for other researchers studying OGT function.
Limitation: Although they found interesting changes in terms transcriptomes in developing mice with different OGT activity, they lack the data showing how these changes caused the observed phenotypes. In other words, there are less mechanistic insights behind the developmental problems seen in mice with different OGT activity.
In addition, although I agree the question about whether OGT activity itself is crucial for the early development of mammals has not been completely solved for a long time, I assume people thought OGT activity is actually important for the mammalian development thorough the observation of OGT-linked congenital disorders of glycosylation.
Therefore, I would say the novelty of the manuscript is a little less impactful. Furthermore, although AID-tagged OGT system revealed fundamental questions regarding the transcriptional changes upon acute depletion of OGT in cellular levels, the system was inefficient in mouse embryos. So, they showed nothing about developmental-stage specific requirements of OGT.
Advance: The manuscript can fill a current gap regarding requirement of OGT in mammalian development. Also, the manuscript developed a series of mutant mice with different OGT activity and an AID-tagged OGT mouse line. These mice provide technical advances.
Audience: The manuscript will be interested in researchers in specific fields such as glycobiology, developmental biology, and clinical fields.
Describe your expertise: Biochemistry, Glycobiology, Cell biology
R30: We are thankful for the constructive and supportive review.
We fully agree with the limitations of the study and discussed them in the manuscript. Our in vivo approach revealed the most phenotypically relevant transcriptional phenotypes resulting from OGT catalytic impairment during embryonic development. We make the mouse models created for this study available to the community to facilitate follow-up studies aiming at exploring the underlying molecular details.
As pointed out in the comments, the requirement of OGT glycosyltransferase activity for mammalian development was widely assumed by the field, but this belief was without direct experimental evidence. This study provides the first in vivo evidence for this important conclusion.
Conclusion: The reviewers' comments were tremendously useful to improving the clarity of the manuscript and adding important new in vivo evidence. We note that none of the reviewers provided any reason to doubt our important conclusions:
- The demonstration that the enzymatic activity of Ogt, thus the O-GlcNAc modification itself, is essential for preimplantation development.
- The finding that a mild reduction of OGT's activity is sufficient to perturb the silencing of multiple families of retrotransposons in the growing embryo.
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The indication, from transcriptomes of hypo-O-GlcNAcylated embryos, of a developmental retardation upon a mild O-GlcNAc perturbation.
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The discovery that OGT's rapid depletion in vitro downregulates basal cellular function, including translation. This result provides mechanistic support to the embryonic growth delay resulting from decreasing O-GlcNAc in vivo.
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Referee #4
Evidence, reproducibility and clarity
Summary
O-GlcNAcylation is the fundamental post-translational modification of numerous nuclear and cytosolic proteins. OGT is the sole enzyme catalyzing O-GlcNAc addition onto the proteins. The essentiality of OGT for early development and cellular viability has been established by using OGT-KO mice and cell lines. However, it remains to be elucidated whether the catalytic activity of OGT is required for the early development, and if the catalytic activity of OGT is required what are the functions of OGT or O-GlcNAcylation in early development due to a lack of appropriate mouse models. To overcome the technical difficulty of manipulating the levels of O-GlcNAcylation in early embryos, Formichetti et al. created the series of four mouse models (OgtY851A, OgtT931A, OgtQ849N, and OgtH568A) with different OGT activity by introducing single amino acid substitution in the catalytic domain. By analyzing the inheritance of the hypomorphic OGT alleles and the lethality of mouse embryos, they discovered OGT activity is a critical factor for early development. Subsequently, RNA-seq analyses with two mouse models showing the maternal inheritance of the hypomorphic OGT alleles indicated that sever hypo-OGT activity altered transcription and silencing of retrotransposon in preimplantation development while mild reduction of OGT's activity affected placental development in a sexually dimorphic manner rather than preimplantation development. Furthermore, to study the function of OGT at specific developmental stages, they developed a mouse model bearing endogenously AID-tagged OGT for acute degradation of OGT. Although the degron system wasn't efficient in preimplantation embryos, they discovered quick transcriptional changes upon OGT deletion in MEFs. The quality of the manuscript is good because the question to be solved was appropriately set, the approach was well designed, and their findings were interesting, although their writing was sometimes hard to understand as I raised in my following comments. Nevertheless, there are several points to be fixed before being published.
Major Comments
- Although the authors showed in vitro activity of each mutant of OGT used in this manuscript by referencing the previous literature, they never showed the levels of global O-GlcNAcylation (and OGT itself) in their established mouse embryos. Although it could be impossible to determine O-GlcNAc levels in OgtQ849N and OgtH568A embryos because of the lack of germline transmission and founder line, respectively, they could do that in OgtY851A and OgtT931A embryos. Given that Y851A and T931A mutants had similar VMAX/KM with different VMAX, it is possible that their activity is comparable or Y851A has even lower activity in vivo depending on the concentration of UDP-GlcNAc in embryos. Therefore, it is critical to assess whether in vivo OGT activity is correlated with that in vitro as expected to conclude that severity of sub-Mendelian inheritance is proportional to the reduction of activity of OGT in vivo. Moreover, since the authors developed the elegant system to deplete OGT, the activity of Q849N and H568A mutant OGT can be examined at least in cells by expressing them in MEFs with OGT-degron system. Thus, I propose determination of global O-GlcNAc levels compensated by OGT levels by western blotting in OgtY851A, and OgtT931A embryos or MEFs with the OGT degron system re-expressing the individual four mutant OGTs. If the protein amount is insufficient for western blotting in the embryos because of the sizes of the earlier stages of embryos, I believe the author could address this by utilizing immunofluorescence as shown in Figure S5.
- I didn't understand why the authors couldn't find any founder lines of the OgtH568A mutant. Was that because mosaic mice with OgtH568A mutation are lethal? Also, I believe there was no explanation why the OgtQ849N allele showed no maternal inheritance. Was that because Q849N possesses enough activity for sustaining mosaic embryos, but not oocytes? The authors should better explain these points in the manuscript text.
- The authors serendipitously found a T931del-allele in the "WT" allele of the OgtT931A line, and suggested that T931del had milder activity loss, although the lethality of embryos was greatly mitigated. Nevertheless, transcriptome analyses in male blastocysts revealed that 120 genes' expression was changed in T931del/Y males. This raised the question about which mutant OGT has higher activity, Y851A or T931del. I think comparing the activity of Y851A and T931del mutants in MEFs with OGT-degron system is important to confirm the proportional relationship between activity and phenotypic severity.
- Regarding transcriptomes of T931del/Y, the authors found the upregulation of proteasomal activity and stress granules along with the downregulation of amino acid metabolism, mitochondrial respiration, and so on. To validate the results, the authors should perform qPCR on several up- or down-regulated genes. In addition, according to Figure S2E, the authors pointed out that at least for genes upregulated in OgtT931A embryos, the changes were not explained by a developmentally delayed transcriptome, suggesting that upregulation of these genes was the cause of developmental delay. Therefore, I strongly encourage them to discuss in the manuscript text how up-regulated genes could contribute to developmental delay.
- Regarding the transcriptome in OgtY851A mice, Y851A/Y male mice had huge transcriptomic differences, while Y851A/Y851A female mice barely had any. Although it seems to agree with the number of Ogt alleles, I wonder whether other X-linked genes expressed higher in female placenta as shown in Figure 3C could attenuate the effects of decreased OGT activity. I don't think this possibility can be excluded, unless the authors further decrease OGT activity in Y851A/Y851A female placenta and obtain the similar results as for male placenta. Or if they compared the levels of global O-GlcNAcylation between Y851A/Y and Y851A/Y851A mouse placentas and discovered they had similar levels of O-GlcNAcylation, then the authors could conclude that the number of Ogt alleles was not the reason of sexual-dimorphism. The authors should determine the levels of O-GlcNAcylation in Y851A/Y and Y851A/Y851A mouse placentas and/or at least discuss the above possibilities in the manuscript text.
- In terms of the transcriptome in OgtY851A mice, similar to comment 4, the authors should confirm their transcriptomics data shown as Figure 3D by qPCR. In addition, the authors should describe the potential mechanisms by which the differentiation of precursor cells of LaTPs and JZPs were disrupted. Were master regulators of the differentiation known to be O-GlcNAcylated and loss of O-GlcNAcylation perturbed the function?
Minor Comments
- Regarding DFP461-463 mutant, I couldn't understand the point of this figure because the results had no difference, and the meaning of the mutation was quite different from the others. Thus, the figure was awkward and a little confusing to me. If the authors still want to include the figures, I would suggest that they should reorganize the position of the figure (maybe after figure 3 is better to show you had tried to investigate the effects of nuclear localization of OGT on the changes of transcriptomes) and add some results. Since WT OGT seems to be localized mainly in the cytosol at steady state (Figure S1B and S1C), the effect of mutation on its nuclear localization should not be obvious. Therefore, it is difficult to conclude the mutation had no effect on the nuclear localization unless the ratio of nuclear and cytosol localization is quantified. Also, I wonder whether the O-GlcNAc levels of nuclear and cytosolic proteins in the mutant cells were comparable to those in WT cells. If this is the case, the results would also support the authors' conclusion.
- Since OGT or O-GlcNAcylation regulates chromatin status, the authors analyzed the gene expression profiles of retrotransposons in T931del/Y or T931A/Y mice. Is it possible to investigate if the release of gene silencing is also seen in non-retrotransposon genes? I assumed retrotransposons might be a well-established system to analyze gene silencing status, however, if the authors could find similar effects on genes other than retrotransposons, that would be highly valuable.
- OgtY851A mice with milder OGT activity loss didn't exhibit impaired preimplantation development, but did display postimplantation development such as placental development, suggesting that O-GlcNAcylation of proteins required for preimplantation and postimplantation development relies on different degrees of OGT activity. I wonder whether global O-GlcNAc levels in embryos in preimplantation and postimplantation developmental stages are different or not. This might include both the pattern of blotting and intensities. The results would give the authors an explanation why the dependency on OGT activity was different in two developmental stages. Can the authors provide data? If not, then the authors should at least describe hypotheses in the manuscript to address these questions.
- The authors' AID-degron system elegantly worked in MEFs but was inefficient in preimplantation embryos. I wonder if this was because of the high expression of the shorter isoform of OGT detected as OGTp78 in the author's western blot. Is it possible to examine this possibility in the embryos? Either way, the authors should describe a potential explanation for why the efficiency in the embryos was low. In addition, the authors should describe why they inserted the AID tag only into the longest OGT isoform.
- In Figure S1C, is the band detected right below OGTp78 in nuclei fractions non-specific or do both bands correspond to OGTp78 ?
- Figure 1D top row third column: hemizgous -> hemizygous
- Figure 1D second row third column: hemyzygous -> hemizygous
Significance
General assessment: strengths and limitations
Strength: This manuscript elegantly revealed the requirement of OGT in mammalian development by taking advantage knock-in mouse models with different OGT activity. In addition, the manuscript provided the interesting and important transcriptomics data in both pre- and post-implantation embryos of OGT mutant mice. These data sets could explain detailed mechanisms how OGT or O-GlcNAcylation regulates mammalian development in the future. Furthermore, development of AID-tagged OGT system would be a useful tool for other researchers studying OGT function.
Limitation: Although they found interesting changes in terms transcriptomes in developing mice with different OGT activity, they lack the data showing how these changes caused the observed phenotypes. In other words, there are less mechanistic insights behind the developmental problems seen in mice with different OGT activity. In addition, although I agree the question about whether OGT activity itself is crucial for the early development of mammals has not been completely solved for a long time, I assume people thought OGT activity is actually important for the mammalian development thorough the observation of OGT-linked congenital disorders of glycosylation. Therefore, I would say the novelty of the manuscript is a little less impactful. Furthermore, although AID-tagged OGT system revealed fundamental questions regarding the transcriptional changes upon acute depletion of OGT in cellular levels, the system was inefficient in mouse embryos. So, they showed nothing about developmental-stage specific requirements of OGT.
Advance: The manuscript can fill a current gap regarding requirement of OGT in mammalian development. Also, the manuscript developed a series of mutant mice with different OGT activity and an AID-tagged OGT mouse line. These mice provide technical advances.
Audience: The manuscript will be interested in researchers in specific fields such as glycobiology, developmental biology, and clinical fields.
Describe your expertise: Biochemistry, Glycobiology, Cell biology
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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pCMV-Tag-2b
DOI: 10.7554/eLife.90184
Resource: Addgene (RRID:SCR_002037)
Curator: @olekpark
SciCrunch record: RRID:SCR_002037
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www.authorea.com www.authorea.com
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Author response:
The following is the authors’ response to the previous reviews.
Reviewer #1:
(1) Peptides were synthesized with fluorescein isothiocyanate (FITC) and Tat tag, and then PEGylated with methoxy PEG Succinimidyl Succinate.
I have two concerns about the peptide design. First, FTIC was intended "for monitoring" (line 129), but was never used in the manuscript. Second, PEGylation targets the two lysine sidechains on the Tat, which would alter its penetration property.
(1) We conducted an analysis of the cellular trafficking of FITC-tagged peptides following their permeabilization into cells.
Author response image 1.
However, we did not include it in the main text because it is a basic result.
(2) As can be seen in the figure above, after pegylation and permeabilization, the cells were stained with FITC. It appears that this does not affect the ability to penetrate into the cells.
(2) "Superdex 200 increase 10/300 GL column" (line 437) was used to isolate mono/di PEGylated PDZ and separate them from the residual PEG and PDZ peptide. "m-PEG-succinimidyl succinate with an average molecular weight of 5000 Da" (lines 133 and 134).
To my knowledge, the Superdex 200 increase 10/300 GL column is not suitable and is unlikely to produce traces shown in Figure 1B.
As Superdex 200 increase 10/300 GL featrues a fractionation range of 10,000 to 600,000 Da, we used it to fractionate PEGylated products including DiPEGylated PDZ (approx. 15 kDa) and MonoPEGylated PDZ (approx. 10 kDa) from residuals (PDZ and PEG), demonstrating successful isolation of PEGylated products (Figure 1C). Considering the molecular weights of PDZ and PEG are approximately 4.1 kDa and and 5.0 kDa, respectively, the late eluting peaks from SEC were likely to represent a mixed absorbance of PDZ and PEG at 215 nm.
However, as the reviewer pointed out, it could be unreasonable to annotate peaks representing PDZ and PEG, respectively, from mixed absorbance detected in a region (11-12 min) beyond the fractionation range.
In our revised manuscript, therefore, multiple peaks in the late eluting volume (11-12 min) were labeled as 'Residuals' all together. As a reference, the revised figure 1B includes a chromatogram of pure PDZ-WT under the same analytic condition.
Therefore, we changed Fig.1B to new results.
(3) "the in vivo survival effect of LPS and PDZ co-administration was examined in mice. The pretreatment with WT PDZ peptide significantly increased survival and rescued compared to LPS only; these effects were not observed with the mut PDZ peptide (Figure 2a)." (lines 159-160).
Fig 2a is the weight curve only. The data is missing in the manuscript.
We added the survived curve into Fig. 2A.
(4) Table 1, peptide treatment on ALT and AST appears minor.
In mice treated with LPS, levels of ALT and AGT in the blood are elevated, but these levels decrease upon treatment with WT PDZ. However, the use of mut PDZ does not result in significant changes. Figure 3A shows inflammatory cells within the central vein, yet no substantial hepatotoxicity is observed during the 5-day treatment with LPS. Normally, the ranges of ALT and AGT in C57BL6 mice are 16 ~ 200 U/L and 46 ~ 221 U/L, respectively, according to UCLA Diagnostic Labs. Therefore, the values in all experiments fall within these normal ranges. In summary, a 5-day treatment with LPS induces inflammation in the liver but is too short a duration to induce hepatotoxicity, resulting in lower values.
(5) MitoTraker Green FM shouldn't produce red images in Figure 6.
We changed new results (GREEN one) into Figs 6A and B.
(6) Figure 5. Comparison of mRNA expression in PDZ-treated BEAS-2B cells. Needs a clearer and more detailed description both in the main text and figure legend. The current version is very hard to read.
We changed Fig. 5A to new one to understand much easier and added more detailed results and figure legend.
Results Section in Figure 5:
we performed RNA sequencing analysis. The results of RNA-seq analysis showed the expression pattern of 24,424 genes according to each comparison combination, of which the results showed the similarity of 51 genes overlapping in 4 gene categories and the similarity between each comparison combination (Figure 5a). As a result, compared to the control group, it was confirmed that LPS alone, WT PDZ+LPS, and mut PDZ+LPS were all upregulated above the average value in each gene, and when LPS treatment alone was compared with WT PDZ+LPS, it was confirmed that they were averaged or downregulated. When comparing LPS treatment alone and mut PDZ+LPS, it was confirmed that about half of the genes were upregulated. Regarding the similarity between comparison combinations, the comparison combination with LPS…
Figure 5 Legend Section:
Figure 5. Comparison of mRNA expression in PDZ-treated BEAS-2B cells.
BEAS-2B cells were treated with wild-type PDZ or mutant PDZ peptide for 24 h and then incubated with LPS for 2 h, after which RNA sequencing analysis was performed. (a) The heat map shows the general regulation pattern of about 51 inflammation-related genes that are differentially expressed when WT PDZ and mut PDZ are treated with LPS, an inflammatory substance. All samples are RED = upregulated and BLUE = downregulated relative to the gene average. Each row represents a gene, and the columns represent the values of the control group treated only with LPS and the WT PDZ and mut PDZ groups with LPS. This was used by converting each log value into a fold change value. All genes were adjusted to have the same mean and standard deviation, the unit of change is the standard deviation from the mean, and the color value range of each row is the same. (b) Significant genes were selected using Gene category chat (Fold change value of 2.00 and normalized data (log2) value of 4.00). The above pie chart shows the distribution of four gene categories when comparing LPS versus control, WT PDZ+LPS/LPS, and mut PDZ+LPS/LPS. The bar graph below shows RED=upregulated, GREEN=downregulated for each gene category, and shows the number of upregulated and downregulated genes in each gene category. (c) The protein-protein interaction network constructed by the STRING database differentially displays commonly occurring genes by comparing WT PDZ+LPS/LPS, mut PDZ+LPS/LPS, and LPS. These nodes represent proteins associated with inflammation, and these connecting lines denote interactions between two proteins. Different line thicknesses indicate types of evidence used in predicting the associations.
Reviewer #2:
(1) In this paper, the authors demonstrated the anti-inflammatory effect of PDZ peptide by inhibition of NF-kB signaling. Are there any results on the PDZ peptide-binding proteins (directly or indirectly) that can regulate LPS-induced inflammatory signaling pathway? Elucidation of the PDZ peptide-its binding partner protein and regulatory mechanisms will strengthen the author's hypothesis about the anti-inflammatory effects of PDZ peptide.
As mentioned in the Discussion section, we believe it is crucial to identify proteins that directly interact with PDZ and regulate it. This direct interaction can modulate intracellular signaling pathways, so we plan to express GST-PDZ and induce binding with cellular lysates, then characterize it using the LC-Mass/Mass method. We intend to further research these findings and submit them for publication.
(2) The authors presented interesting insights into the therapeutic role of the PDZ motif peptide of ZO-1. PDZ domains are protein-protein interaction modules found in a variety of species. It has been thought that many cellular and biological functions, especially those involving signal transduction complexes, are affected by PDZ-mediated interactions. What is the rationale for selecting the core sequence that regulates inflammation among the PDZ motifs of ZO-1 shown in Figure 1A?
The rationale for selecting the core sequence that regulates inflammation among the PDZ motifs of ZO-1, as shown in Figure 1A, is grounded in the specific roles these motifs play in signal transduction pathways that are crucial for inflammatory processes. PDZ domains are recognized for their ability to function as scaffolding proteins that organize signal transduction complexes, crucial for modulating cellular and biological functions. The chosen core sequence is particularly important because it is conserved across ZO-1, ZO-2, and ZO-3, indicating a fundamental role in maintaining cellular integrity and signaling pathways. This conservation suggests that the sequence’s involvement in inflammatory regulation is not only significant in ZO-1 but also reflects a broader biological function across the ZO family.
(3) In Figure 3, the authors showed the representative images of IHC, please add the quantification analysis of Iba1 expression and PAS-positive cells using Image J or other software. To help understand the figure, an indication is needed to distinguish specifically stained cells (for example, a dotted line or an arrow).
We added the semi-quantitative results into Figs. 3d,e,f.
Result section: The specific physiological mechanism by which WT PDZ peptide decreases LPS-induced systemic inflammation in mice and the signal molecules involved remain unclear. These were confirmed by a semi-quantitative analysis of Iba-1 immunoreactivity and PAS staining in liver, kidney, and lung,respectively (Figures 4d, e, and f). To examine whether WT PDZ peptide can alter LPS-induced tissue damage in the kidney, cell toxicity assay was performed (Figure 3g). LPS induced cell damage in the kidney, however, WT PDZ peptide could significantly alleviate the toxicity, but mut PDZ peptide could not. Because cytotoxicity caused by LPS is frequently due to ROS production in the kidney (Su et al., 2023; Qiongyue et al., 2022), ROS production in the mitochondria was investigated in renal mitochondria cells harvested from kidney tissue (Figure 3h)......
Figure legend section: Indicated scale bars were 20 μm. (d,e,f) Semi-quantitative analysis of each are positive for Iba-1 in liver and kidney, and positive cells of PAS in lung, respectively. (g) After the kidneys were harvested, tissue lysates were used for MTT assay. (h) After.....
(4) In Figure 6G, H, the authors confirmed the change in expression of the M2 markers by PDZ peptide using the mouse monocyte cell line Raw264.7. It would be good to add an experiment on changes in M1 and M2 markers caused by PDZ peptides in human monocyte cells (for example, THP-1).
We thank you for your comments. To determine whether PDZ peptide regulates M1/M2 polarization in human monocytes, we examined changes in M1 and M2 gene expression in THP-1 cells. As a result, wild-type PDZ significantly suppressed the expression of M1 marker genes (hlL-1β, hIL-6, hIL-8, hTNF-ɑ), while increasing the expression of M2 marker genes (hlL-4, hIL-10, hMRC-1). However, mutant PDZ did not affect M1/M2 polarization. These results suggest that PDZ peptide can suppress inflammation by regulating M1/M2 polarization of human monocyte cells. These results are for the reviewer's reference only and will not be included in the main content.
Author response image 2.
Minor point:
The use of language is appropriate, with good writing skills. Nevertheless, a thorough proofread would eliminate small mistakes such as:
• line 254, " mut PDZ+LPS/LPS (45.75%) " → " mut PDZ+LPS/LPS (47.75%) "
• line 296, " Figure 6f " → " Figure 6h "
We changed these points into the manuscript.
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Phillip Hallam-Baker who "wondered about a tag being added to the get protocol to indicate where the text was being accessed from
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Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
In this work, Odenwald and colleagues show that mutant biotin ligases used to perform proximity-dependent biotin identification (TurboID) can be used to amplify signal in fluorescence microscopy and to label phase-separated compartments that are refractory to many immunofluorescence approaches. Using the parasite Trypanosoma brucei, they show that fluorescent methods such as expansion microscopy and CLEM, which require bright signals for optimal detection, benefit from the elevated signal provided by TurboID fusion proteins when coupled with labeled streptavidin. Moreover, they show that phase-separated compartments, where many antibody epitopes are occluded due to limited diffusion and potential sequestration, are labeled reliably with biotin deposited by a TurboID fusion protein that localizes within the compartment. They show successful labeling of the nucleolus, likely phase-separated portions of the nuclear pore, and stress granules. Lastly, they use a panel of nuclear pore-TurboID fusion proteins to map the regions of the T. brucei nuclear pore that appear to be phase-separated by comparing antibody labeling of the protein, which is susceptible to blocking, to the degree of biotin deposition detected by streptavidin, which is not.
Strengths:
Overall, this study shows that TurboID labelling and fluorescent streptavidin can be used to boost signal compared to conventional immunofluorescence in a manner similar to tyramide amplification, but without having to use antibodies. TurboID could prove to be a viable general strategy for labeling phase-separated structures in cells, and perhaps as a means of identifying these structures, which could also be useful.
Weaknesses:
However, I think that this work would benefit from additional controls to address if the improved detection that is being observed is due to the increased affinity and smaller size of streptavidin/biotin compared to IgGs, or if it has to do with the increased amount of binding epitope (biotin) being deposited compared to the number of available antibody epitopes. I also think that using the biotinylation signal produced by the TurboID fusion to track the location of the fusion protein and/or binding partners in cells comes with significant caveats that are not well addressed here, mostly due to the inability to discern which proteins are contributing to the observed biotin signal.
To dissect the contributions of the TurboID fusion to elevating signal, anti-biotin antibodies could be used to determine if the abundance of the biotin being deposited by the TurboID is what is increasing detection, or if streptavidin is essential for this.
We agree with the reviewer, that it would be very interesting to distinguish whether the increase in signal comes from the multiple biotinylation sites or from streptavidin being a very good binder, or perhaps from both. However, this question is very hard to answer, as antibodies differ massively in their affinity to the antigen which is further dependent on the respective IF-conditions, and are therefore not directly comparible. Even if anti-biotin gives a better signal then anti-HA, this can be either caused by the increase in antigen-number (more biotin than HA-tag) or by the higher binding affinity, or by a combination of both, thus hard to distinguish. Nevertheless, we have tested monoclonal mouse anti-biotin targeting the (non-phase-separated) NUP158. We found the signal from the biotin-antibody to be much weaker than from anti-HA, indicating that, at least this particular biotin antibody, is not a very good binder in IF.
Alternatively, HaloTag or CLIP tagging could be used to see if diffusion of a small molecule tag other than biotin can overcome the labeling issue in phase-separated compartments. There are Halo-biotin substrates available that would allow the conjugation of 1 biotin per fusion protein, which would allow the authors to dissect the relative contributions of the high affinity of streptavidin from the increased amount of biotin that the TurboID introduces.
This is a very good idea, as in this case, the signals are both from streptavidin and are directly comparable. We expressed NUP158 with HaloTag and added PEG-biotin as a Halo ligand. However, PEG-biotin is poorly cell-permeable, and is in general only used on lysates. In trypanosomes, cell permeability is particular restricted, and even Halo-ligands that are considered highly cell-penetrant give only a weak signal. Even after over-night incubation, we could not get any signal with PEG-biotin. Our control, the TMR-ligand 647, gave a weak nuclear pore staining, confirming the correct expression and function of the HaloTag-NUP158.
The idea of using the biotin signal from the TurboID fusion as a means to track the changing localization of the fusion protein or the location of interacting partners is an attractive idea, but the lack of certainty about what proteins are carrying the biotin signal makes it very difficult to make clear statements. For example, in the case of TurboID-PABP2, the appearance of a biotin signal at the cell posterior is proposed to be ALPH1, part of the mRNA decapping complex. However, because we are tracking biotin localization and biotin is being deposited on a variety of proteins, it is not formally possible to say that the posterior signal is ALPH1 or any other part of the decapping complex. For example, the posterior labeling could represent a localization of PABP2 that is not seen without the additional signal intensity provided by the TurboID fusion. There are also many cytoskeletal components present at the cell posterior that could be being biotinylated, not just the decapping complex. Similar arguments can be made for the localization data pertaining to MLP2 and NUP65/75. I would argue that the TurboID labeling allows you to enhance signal on structures, such as the NUPs, and effectively label compartments, but you lack the capacity to know precisely which proteins are being labeled.
We fully agree with the reviewer, that tracking proteins by streptavidin imaging alone is problematic, because it cannot distinguish, which protein is biotinylated. We therefore used words like “likely” in the description of the data. However, we still think, it is a valid method, as long as it is confirmed by an orthogonal method. We have added this paragraph to the end of this chapter:
“Importantly, tracking of proteins by streptavidin imaging requires orthogonal controls, as the imaging alone does not provide information about the nature of the biotinylated proteins. These can be proximity ligation assay, mass spectrometry or specific tagging visualisation of protein suspects by fluorescent tags. Once these orthogonal controls are established for a specific tracking, streptavidin imaging is an easy and cheap and highly versatile method to monitor protein interactions in a specific setting.”
Reviewer #2 (Public Review):
Summary:
The authors noticed that there was an enhanced ability to detect nuclear pore proteins in trypanosomes using a streptavidin-biotin-based detection approach in comparison to conventional antibody-based detection, and this seemed particularly acute for phase-separated proteins. They explored this in detail for both standard imaging but also expansion microscopy and CLEM, testing resolution, signal strength, and sensitivity. An additional innovative approach exploits the proximity element of biotin labelling to identify where interacting proteins have been as well as where they are.
Strengths:
The data is high quality and convincing and will have obvious application, not just in the trypanosome field but also more broadly where proteins are tricky to detect or inaccessible due to phase separation (or some other steric limitations). It will be of wide utility and value in many cell biological studies and is timely due to the focus of interest on phase separation, CLEM, and expansion microscopy.
Thank you! We are glad you liked it.
Reviewer #3 (Public Review):
Summary:
The authors aimed to investigate the effectiveness of streptavidin imaging as an alternative to traditional antibody labeling for visualizing proteins within cellular contexts. They sought to address challenges associated with antibody accessibility and inconsistent localization by comparing the performance of streptavidin imaging with a TurboID-HA tandem tag across various protein localization scenarios, including phase-separated regions. They aimed to assess the reliability, signal enhancement, and potential advantages of streptavidin imaging over antibody labeling techniques.
Overall, the study provides a convincing argument for the utility of streptavidin imaging in cellular protein visualization. By demonstrating the effectiveness of streptavidin imaging as an alternative to antibody labeling, the study offers a promising solution to issues of accessibility and localization variability. Furthermore, while streptavidin imaging shows significant advantages in signal enhancement and preservation of protein interactions, the authors must consider potential limitations and variations in its application. Factors such as the fact that tagging may sometimes impact protein function, background noise, non-specific binding, and the potential for off-target effects may impact the reliability and interpretation of results. Thus, careful validation and optimization of streptavidin imaging protocols are crucial to ensure reproducibility and accuracy across different experimental setups.
Strengths:
- Streptavidin imaging utilizes multiple biotinylation sites on both the target protein and adjacent proteins, resulting in a substantial signal boost. This enhancement is particularly beneficial for several applications with diluted antigens, such as expansion microscopy or correlative light and electron microscopy.
- This biotinylation process enables the identification and characterization of interacting proteins, allowing for a comprehensive understanding of protein-protein interactions within cellular contexts.
Weaknesses:
- One of the key advantages of antibodies is that they label native, endogenous proteins, i.e. without introducing any genetic modifications or exogenously expressed proteins. This is a major difference from the approach in this manuscript, and it is surprising that this limitation is not really mentioned, let alone expanded upon, anywhere in the manuscript. Tagging proteins often impacts their function (if not their localization), and this is also not discussed.
- Given that BioID proximity labeling encompasses not only the protein of interest but also its entire interacting partner history, ensuring accurate localization of the protein of interest poses a challenge.
- The title of the publication suggests that this imaging technique is widely applicable. However, the authors did not show the ability to track the localization of several distinct proteins on the same sample, which could be an additional factor demonstrating the outperformance of streptavidin imaging compared with antibody labeling. Similarly, the work focuses only on small 2D samples. It would have been interesting to be able to compare this with 3D samples (e.g. cells encapsulated in an extracellular matrix) or to tissues.
Recommendations for the authors:
To enhance the assessment from 'incomplete' to 'solid', the reviewers recommend that the following major issues be addressed:
Major issues:
(1) Anti-biotin antibodies in combination with TurboID labeling should be used to compare the signal/labelling penetrance to streptavidin results. That would show if elevated biotin deposition matters, or if it is really the smaller size, more fluors, and higher affinity of streptavidin that's making the difference.
We agree with the reviewer, that it would be very interesting to distinguish whether the increase in signal comes from the multiple biotinylation sites or from streptavidin being a very good binder, or perhaps from both, and whether the size matters (IgG versus streptavidin). However, this question is very hard to answer, as antibodies differ massively in their affinity to the antigen. Thus, even if antibiotin would give a better signal then anti-HA, this could be either caused by the increase in antigen-number (more biotin than HA-tag) or by the better binding affinity, or by a combination, and it would not allow to truly answer the question. We have now tested anti-biotin antibodies, also in repsonse to reviewer 1, and got a much poorer signal in comparison to anti-HA or streptavidin.
Please note that we made another attempt using nanobodies to target phase-separated proteins, to see, whether size matters (Fig. 2I). The nanobody did not stain Mex67 at the nuclear pores, but gave a weak nucelolar signal for NOG1, which may suggest that the nanobody can slightly better penetrate than IgG, but it does not rule out that the nanobody simply binds with higher affinity. Reviewer 1 has suggested to use the Halo Tag with PEG-biotin: this would indeed allow to directly compare the streptavidin signal caused by the TurboID with a single biotin added by the Halo tag. Unfortunately, the PEG-biotin does not penetrate trypanosome cells. In conclusion, we are not aware of a method that would allow to establish why streptavidin but not IgGs can penetrate to phase separated areas. We therefore prefer to not overinterpret our data, but stick to what is supported by the data: “the inability to label phase-separated areas is not restricted to anti-HA but applies to other antibodies”.
(3) Figure 4 A-B. The validity of claiming the correct localization demonstrated by streptavidin imaging comes into question, especially when endogenous fluorescence, via the fusion protein, remains undetectable (as indicated by the yellow arrow at apex).
In this figure, the streptavidin imaging does NOT show the correct localisation of the bait protein, but it does show proteins from historic interactions that have a distinct localisation to the bait. We had therefore introduced this chapter with the paragraph below, to make sure, the reader is aware of the limitations (which we also see as an opportunity, if properly controlled):
“We found that in most cases, streptavidin labelling faithfully reflects the steady state localisation of a bait protein, e.g., the localisation resembles those observed with immunofluorescence or direct fluorescence imaging of GFP-fusion proteins. For certain bait proteins, this is not the case, for example, if the bait protein or its interactors have a dynamic localisation to distinct compartments, or if interactions are highly transient. It is thus essential to control streptavidin-based de novo localisation data by either antibody labelling (if possible) or by direct fluorescence of fusion-proteins for each new bait protein.”
In particular, on lines 450-460, there's a fundamental issue with the argument put forward here. It is not possible to formally know that the posterior labeling is ALPH1 vs. another part of the decapping complex that was associated with PABP2-Turbo, or if the higher detection capacity of the Turbo-biotin label is uncovering a novel localization of the PABP2. While it is likely that it is ALPH1, it is not possible to rule out other possibilities with this approach. These issues should be discussed here and more generally the possibility of off-target labeling with this approach should be addressed in the discussion.
We fully agree with the reviewer, that tracking proteins by streptavidin imaging alone is problematic, because it cannot distinguish, which protein is biotinylated. We therefore used words like “likely” in the description of the data. However, we still think, it is a valid method, as long as it is back-uped by an orthogonal method. We have added this paragraph to the end of this chapter:
“Importantly, tracking of proteins by streptavidin imaging requires orthogonal controls, as the imaging alone does not provide information about the nature of the biotinylated proteins. These can be proximity ligation assay, mass spectrometry or specific tagging visualisation of protein suspects by fluorescent tags. Once these orthogonal controls are established for a specific tracking, streptavidin imaging is an easy and cheap and highly versatile method to monitor protein interactions in a specific setting.”
(4) More discussion and acknowledgment of the general limitations in using tagged proteins are needed to balance the manuscript, especially if the hope is to draw a comparison with antibody labeling, which works on endogenous proteins (not requiring a tag). For example: (a) tagging proteins requires genetic/molecular work ahead of time to engineer the constructs and/or cells if trying to tag endogenous proteins; (b) tagged proteins should technically be validated in rescue experiments to confirm the tag doesn't disrupt function in the cell/tissue/context of interest; and (c) exogenous tagged proteins compete with endogenous untagged proteins, which can complicate the interpretation of data.
We have added this paragraph to the first paragraph of the discussion part:
“Like many methods that are frequently used in cell- and molecular biology, streptavidin imaging is based on the expression of a genetically engineered fusion protein: it is essential to validate both, function and localisation of the TurboID-HA tagged protein by orthogonal methods. If the fusion protein is non-functional or mis-localised, tagging at the other end may help, but if not, this protein cannot be imaged by streptavidin imaging. Likewise, target organisms not amenable to genetic manipulation, or those with restricted genetic tools, are not or less suitable for this method.”
Also, we like to point out that for non-mainstream organisms like trypanosomes, antibodies are not commercially available and often genetic manipulation is more time-efficient and cheaper than the production of antiserum against the target protein.
Also, the introduction would ideally be more general in scope and introduce the pros and cons of antibody labeling vs biotin/streptavidin, which are mentioned briefly in the discussion. The fact that the biotin-streptavidin interaction is ~100-fold higher affinity than an IgG binding to its epitope is likely playing a key role in the results here. The difference in size between IgG and streptavidin, the likelihood that the tetrameric streptavidin carries more fluors than a IgG secondary, and the fact that biotin can likely diffuse into phase-separated environments should be clearly stated. The current introduction segues from a previous paper that a more general audience may not be familiar with.
We have now included this paragraph to the introduction:
“It remains unclear, why streptavidin was able to stain biotinylated proteins within these antibody inaccessible regions, but possible reasons are: (i) tetrameric streptavidin is smaller and more compact than IgGs (60 kDa versus a tandem of two IgGs, each with 150 kDa) (ii) the interaction between streptavidin and biotin is ~100 fold stronger than a typical interaction between antibody and antigen and (iii) streptavidin contains four fluorophores, in contrast to only one per secondary IgG.”
Minor issues:
The copy numbers of the HA and Ty1 epitope tags vary depending on the construct being used. For example, Ty1 is found as a single copy tag in the TurboID tag, but on the mNeonGreen tag there are 6 copies of the epitope. It makes it hard to know if differences in detection are due to variations in copies of the epitope tags. Line 372-374: can the authors explain why they chose to use nanobodies in this case? It would be great to show the innate mNeonGreen signal in 2K to compare to the Ty1 labeling. The presence of 6 copies of the Ty1 epitope could be essential to the labeling seen here.
We agree with the reviewer, that these data are a bit confusing. We have now removed Figure 3K, as it is the only construct with 6 Ty1 instead of one, and it does not add to the conclusions. (the mNeonsignal is entirely in the nucleolus, as shown by Tryptag). We have also added an explanation why we used nanobodies (“The absence of a nanobody signal rules out that its simply the size of IgGs that prevents the staining of Mex67 at the nuclear pores, as nanobodies are smaller than (tetrameric) streptavidin”). However, as stated above, we prefer not to overinterpret the data, as signals from different antibodies/nanobodies – antigen combinations are not comparable. Important to us was to stress that the absence of signal in phase-separated areas is NOT restricted to the anti-HA antibody, which is clearly supported by the data.
What is the innate streptavidin background labeling look like in cells that are not carrying a TurboID fusion, from the native proteins that are biotinylated? That should be discussed.
We have now included the controls without the TurboID fusions for trypanosomes and HeLa cells: “Wild type cells of both Trypanosomes and human showed only a very low streptavidin signal, indicating that the signal from naturally biotinylated proteins is neglectable (Figure S8 in supplementary material).”
Line 328-331: This is likely to be dependent on whether or not the protein moves to different localizations within the cell.
True, we agree, and we have added this paragraph:
“The one exception are very motile proteins that produce a “biotinylation trail” distinct to the steady state localisation; these exceptions, and how they can be exploited to understand protein interactions, are discussed in chapter 4 below. “
Line 304-305: Does biotin supplementation not matter at all?
No, we never saw any increase in biotinylation when we added extra biotin to trypanosomes. The 0.8 µM biotin concentration in the medium were sufficient.
Line 326-327: Was the addition of biotin checked for enhancement in the case of the mammalian NUP98? I would argue that there is a significant number of puncta in Figure 1D that are either green or magenta, not both. The amount of extranuclear puncta in the HA channel is also difficult to explain. Biotin supplementation to 500 µM was used in mammalian TurboID experiments in the original Nature Biotech paper- perhaps nanomolar levels are too low.
We now tested HeLa cells with 500 µM Biotin and saw an increase in signal, but also in background; due to the increased background we conclude that low biotin concentrations are more suitable . We have also repeated the experiment using 4HA tags instead of 1HA, and we found a minor improvement in the antibody signal for NUP88 (while the phase separated NUP54 was still not detectable). We have replaced the images in Figure 1D (NUP88) and also in Figure 2F (NUP54) with improved images and using 4HA tags. However, we like to note that single nuclear pore resolution is beyond what can be expected of light microscopy.
Line 371: In 2I, I see a signal that looks like the nucleus, similar to the Ty1 labeling in 2G, so I don't think it's accurate to say that that Mex67 was "undetectable". Does the serum work for blotting?
Thank you, yes, “undetectable” was not the correct phrase here. Mex67 localises to the nuclear pores, to the nuceoplasm and to the nucleolus (GFP-tagging or streptavidin). Antibodies, either to the tag or to the endogenous proteins, fail to detect Mex67 at the nuclear pores and also don’t show any particular enrichment in the nucleolus. They do, however, detect Mex67 in the (not-phase-separated) area of the nucleoplasm. We have changed the text to make this clearer. The Mex67 antiserum works well on a western blot (see for example: Pozzi, B., Naguleswaran, A., Florini, F., Rezaei, Z. & Roditi, I. The RNA export factor TbMex67 connects transcription and RNA export in Trypanosoma brucei and sets boundaries for RNA polymerase I. Nucleic Acids Res. 51, 5177–5192 (2023))
Line 477: "lacked" should be "lagged".
Thank you, corrected.
Line 468-481: My previous argument holds here - how do you know that the difference in detection here is just a matter of much higher affinity/quantity of binding partner for the avidin?
See answer to the second point of (3), above.
483-491: Same issue - without certainty about what the biotin is on, this argument is difficult to make.
See answer to the second point of (3), above.
Line 530: "bone-fine" should be "bonafide"
Thank you, corrected.
Line 602: biotin/streptavidin labeling has been used for expansion microscopy previously (Sun, Nature Biotech 2021; PMID: 33288959).
Thank you, we had overlooked this! We have now included this reference and describe the differences to our approach clearer in the discussion part:
“Fluorescent streptavidin has been previously used in expansion microscopy to detect biotin residues in target proteins produced by click chemistry (Sun et al., 2021). However, to the best of our knowledge, this is the first report that employs fluorescent streptavidin as a signal enhancer in expansion microscopy and CLEM, by combining it with multiple biotinylation sites added by a biotin ligase. Importantly, for both CLEM and expansion, streptavidin imaging is the only alternative approach to immunofluorescence, as denaturing conditions associated with these methods rule out direct imaging of fluorescent tags.”
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apex-magazine.com apex-magazine.com
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For the first time, there was someone else with him: A squat white woman with a plastic name-tag and the kind of squarish perm you can only get in Southern beauty salons with faded glamor-shots in the windows. The boy trailed behind her looking thin and pressed, like a flower crushed between dictionary pages. I wondered how badly you had to fuck up to get assigned a school counselor after hours, until I read her name-tag: Department of Community-Based Services, Division of Protection and Permanency, Child Caseworker (II).Oh. A foster kid.
I like this part a lot because it gives the reader a new perspective of this character that is in the narrator's life. We also get to see how she comes to realize the deeper part of his life.
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Author response:
The following is the authors’ response to the current reviews.
Public Reviews:
Reviewer #1 (Public Review):
This article by Navratna et al. reports the first structure of human HGSNAT in an acetyl-CoA-bound state. Through careful structural analysis, the authors propose potential reasons why certain human mutations lead to lysosomal storage disorders and outline a catalytic mechanism. The structural data are of good quality, and the manuscript is clearly written. This study represents an important step toward understanding the mechanism of HGSNAT and is valuable to the field. I have the following suggestions:
(1) The authors should characterize whether the purified protein is active. Otherwise, how does one know if the detergent used maintains the protein in a biologically relevant state? The authors should at least attempt to do so. If these prove to be challenging, at the very least, the authors should try a cell-based assay to demonstrate that the GFP tag does not interfere with the function.
We have addressed these concerns in the revised version and mentioned these efforts in our previous response letter. We’re briefly mentioning them here again. We attempted measuring HGSNAT catalyzed reaction by monitoring the decrease in acetyl-CoA in the presence of D-glucosamine (acetyl group acceptor) using a coupled enzyme acetyl-CoA assay kit from SIGMA (MAK039) that converts acetyl-CoA to a fluorescent product measurable at Ex/Em of 535/587 nm. We noticed a decrease in the level of acetyl-CoA (gray) upon the addition of HGSNAT (red) (Rebuttal figure 1).
Author response image 1.
Acetyl-CoA levels in absence and presence of HGSNAT purified in digitonin. Decrease in the levels of 10 M acetyl-CoA was measured in presence of 10 M D-glucosamine and 30 nM HGSNAT at pH 7.5.
While optimizing the assay, Xu et al. (2024, Nat Struct Mol Biol) published structural and biochemical characterization of HGSNAT, showing that detergent-purified HGSNAT is active. In addition, we have shown by cryo-EM that GFP-tagged HGSNAT that we purified in detergent was already bound to the endogenous substrate ACO, an observation that has been observed by Xu et al., as well. Finally, we performed LC-MS on GFP-tagged HGSNAT purified in detergent to detect bound ACO, which could be further removed by dialysis. These results have been included in Figure S9. The endogenous binding of ACO to HGSNAT in detergent suggests that neither the tag nor detergent are detrimental to the function.
(2) In Figure 5, the authors present a detailed schematic of the catalytic cycle, which I find to be too speculative. There is no evidence to suggest that this enzyme undergoes isomerization, similar to a transporter, between open-to-lumen and open-to-cytosol states. Could it not simply involve some movements of side chains to complete the acetyl transfer?
We have already changed this figure in our latest submission. Perhaps the changes made were not obvious while reviewing. We agreed with this reviewer that the enzyme could likely achieve catalysis by simple side chain movements without undergoing extensive isomerization steps, as depicted in Figure 5. In the absence of data supporting large movements during the acetyl transfer reaction, old Figure 5 appeared speculative. Hence, we have edited Figure 5 in the revised version of the manuscript based on the observations we made in this study, and different states shown in the figure do not show any conformational changes and only depict acetyl transfer.
Reviewer #2 (Public Review):
Summary:
This work describes the structure of Heparan-alpha-glucosaminide N-acetyltransferase (HGSNAT), a lysosomal membrane protein that catalyzes the acetylation reaction of the terminal alpha-D-glucosamine group required for degradation of heparan sulfate (HS). HS degradation takes place during the degradation of the extracellular matrix, a process required for restructuring tissue architecture, regulation of cellular function and differentiation. During this process, HS is degraded into monosaccharides and free sulfate in lysosomes.
HGSNAT catalyzes the transfer of the acetyl group from acetyl-CoA to the terminal non-reducing amino group of alpha-D-glucosamine. The molecular mechanism by which this process occur has not been described so far. One of the main reasons to study the mechanism of HGSNAT is that multiple mutations spanning the entire sequence of the protein, such as, nonsense mutations, splice-site variants, and missense mutations lead to dysfunction that causes abnormal accumulation of HS within the lysosomes. This accumulation is a cause of mucopolysaccharidosis IIIC (MPS IIIC), an autosomal recessive neurodegenerative lysosomal storage disorder, for which there are no approved drugs or treatment strategies.
This paper provides a 3.26A structure of HGSNAT, determined by single-particle cryo-EM. The structure reveals that HGSNAT is a dimer in detergent micelles, and a density assigned to acetyl-CoA. The authors speculate about the molecular mechanism of the acetylation reaction, map the mutations known to cause MPS IIIC on the structure and speculate about the nature of the HGSNAT disfunction caused by such mutations.
Strengths:
The paper describes a structure of HGSNAT a member of the transmembrane acyl transferase (TmAT) superfamily. The high-resolution of a HGSNAT bound to acetyl-CoA is important for our understanding of HGSNAT mechanism. The density map is of high-quality, except for the luminal domain. The location of the acetyl-CoA allows speculation about the mechanistic role of multiple residues surrounding this molecule. The authors thoroughly describe the architecture of HGSNAT and map the mutations leading to MPS IIIC.
Reviewer #3 (Public Review):
Summary:
Navratna et al. have solved the first structure of a transmembrane N-acetyltransferase (TNAT), resolving the architecture of human heparan-alpha-glucosaminide N-acetyltransferase (HGSNAT) in the acetyl-CoA bound state using single particle cryo-electron microscopy (cryoEM). They show that the protein is a dimer, and define the architecture of the alpha- and beta-GSNAT fragments, as well as convincingly characterizing the binding site of acetyl-CoA.
Strengths:
This is the first structure of any member of the transmembrane acyl transferase superfamily, and as such it provides important insights into the architecture and acetyl-CoA binding site of this class of enzymes.
The structural data is of a high quality, with an isotropic cryoEM density map at 3.3Å facilitating building of a high-confidence atomic model. Importantly, the density for the acetyl-CoA ligand is particularly well-defined, as are the contacting residues within the transmembrane domain.
The structure of HSGNAT presented here will undoubtedly lay the groundwork for future structural and functional characterization of the reaction cycle of this class of enzymes.
Weaknesses:
While the structural data for the state presented in this work is very convincing, and clearly defines the binding site of acetyl-CoA, to get a complete picture of the enzymatic mechanism of this family, additional structures of other states will be required.
A weakness of the study is the lack of functional validation. The enzymatic activity of the enzyme characterized was not measured, and the enzyme lacks native proteolytic processing, so it is a little unclear whether the structure represents an active enzyme.
Recommendations for the authors:
Reviewer #3 (Recommendations For The Authors):
In the response to reviewers, the authors mention revised coordinates, but the revised coordinates provided to this reviewer do not reflect the stated changes (I assume a technical error somewhere)
Perhaps, the old coordinates in the deposition system were resubmitted with the revised draft. Nevertheless, we have made the changes suggested by this reviewer to structure in the previous round and have released the new coordinates (PDB ID: 8TU9).
Is there any evidence for the interprotomer disulfide except for the map? e.g. if it is a disulfide-linked dimer, one should see a shift in mobility on non-reducing vs reducing SDS-PAGE. Without this, the evidence from the map is not conclusive - while the symmetry-related cysteines are nearby to one another, based on the map I could argue that they could just as well be modeled with the cys sidechains reduced and pointing away from one another.
In addition to building the density based on cryo-EM maps, we have performed FSEC-based thermal melt analysis of the Ala mutation of C334 that is involved in disulfide at the dimer interface. C334A is still expressed as a dimer, suggesting that C334A is not the only residue stabilizing the dimer. Upon heating the detergent-solubilized protein, we noticed that the FSEC peak for C334A shows a monomeric HGSNAT (Figure 4-Figure supplement 1 in main manuscript). We hypothesize that in the absence of C334 disulfide, the extensive hydrophobic side-chain interaction network displayed in Figure 2C is responsible for maintaining the integrity of the dimer. Heating disturbs these non-disulfide interactions, thereby rendering the protein monomer. We have also performed PAGE analysis as suggested by this reviewer and noticed that reducing conditions result in a monomeric protein band (Rebuttal figure 2). While we were revising this manuscript, two other groups published structures of HGSNAT (Xu et al., 2024, Nat. Struct Mol Biol, and Zhao et al., 2024, Nat. Comm). These groups have also identified this disulfide at the dimer interface in their HGSNAT structures. Zhao et al. showed that this disulfide is not crucial for dimerization and also suggested that it can break depending on the conformation of HGSNAT. Our FSEC results agree with this observation.
Author response image 2.
Comparison of purified HGSNAT on native and reducing SDS-PAGE. The arrows on both the gels indicate N-GFP-HGSNAT. The two bands on the SDS PAGE are, perhaps, two differentially glycosylated forms of HGSNAT.
The following is the authors’ response to the original reviews.
(1) The authors should characterize whether the purified protein is active. Otherwise, how does one know if the detergent used maintains the protein in a biologically relevant state? The authors should at least attempt to do so. If these prove to be challenging, at the very least, the authors should try a cell-based assay to demonstrate that the GFP tag does not interfere with the function. The authors would need to establish an in vitro assay using purified protein and assess the level of Acetyl-CoA in the reaction (there are commercial kits and a long list of literature showing how to measure this). They could also follow the HS acetylation reaction by e.g. HPLC-MS or NMR (among other methods).
The cryo-EM sample was prepared without the exogenous addition of ligand, as noted in the manuscript. However, we see that acetyl-CoA was intrinsically bound to the protein, indicating the ability of GFP-tagged HGSNAT protein to bind the ligand. Upon dialysis, we see release of acetyl-CoA from the protein, which we have confirmed by LC-MS analysis (Fig S9). We purified the protein at a pH optimal for acetyl-CoA binding, as suggested by Bame, K. J. and Rome, L. H. (1985) and Meikle, P. J. et al., (1995). Because we see acetyl-CoA in a structure obtained using a GFP fusion, we argue that GFP does not interfere with protein stability and ability to bind to the co-substrate. As demonstrated by existing literature HGSNAT catalyzed reaction is compartmentalized spatially and conditionally. The binding of acetyl-CoA happens towards the cytosol and is optimal at pH 7-0.8.0, while the transfer of the acetyl group to heparan sulfate occurs towards the luminal side and is optimal at pH 5.0-6.0. We attempted measuring HGSNAT catalyzed reaction by monitoring decrease in acetyl-CoA in presence of D-glucosamine (acetyl group acceptor) using a coupled enzyme acetyl-CoA assay kit from SIGMA (MAK039) that converts acetyl-CoA to a fluorescent product measurable at Ex/Em of 535/587 nm. We noticed a decrease in the level of acetyl-CoA in the presence of HGSNAT-ACO complex (blue) and apo HGSNAT (red); the difference compared to the ACO standard (gray) was not significant. While optimizing the assay, Xu et al. (2024, Nat Struct Mol Biol) published structural and biochemical characterization of HGSNAT, showing that detergent-purified HGSNAT is active.
Author response image 3.
Acetyl-CoA levels in absence and presence of HGSNAT purified in digitonin. Decrease in the levels of 10 mM acetyl-CoA was measured in presence of 10 mM D-glucosamine and 30 nM HGSNAT at pH 7.5.
(2) In Figure 5, the authors present a detailed schematic of the catalytic cycle, which I find to be too speculative. There is no evidence to suggest that this enzyme undergoes isomerization, similar to a transporter, between open-to-lumen and open-to-cytosol states. Could it not simply involve some movements of side chains to complete the acetyl transfer? The speculative nature of this assumption needs to be clearly acknowledged throughout the manuscript and discussed in more detail. The authors could use HDX-MS or introduce cysteine residues in the hypothetical inward- and outward-facing cavities and test accessibility by incubating the purified protein with maleimides or other agents reacting with free cysteine.
We thank the reviewers for this insightful critique. Yes, the enzyme could likely achieve catalysis by simple side chain movements without undergoing extensive isomerization steps, as depicted in Figure 5. We also agree with the reviewer that HDX-MS could be the best way to monitor the substrate-induced conformational dynamics within HGSNAT experimentally. In the absence of data supporting large movements during the acetyl transfer reaction, figure 5 is speculative. We have now edited Figure 5 in the revised version of the manuscript based on the observations we made in this study.
(3) The acetyl-CoA-bound state is described as the open-to-lumen state. Indeed, from Figure 1C, the lumen opening appears much larger than the cytosol opening. Is there any small tunnel that connects the substrate site to the cytosol? In other words, is this state accessible to both the lumen and the cytosol, albeit with a larger opening toward the lumen? This question arises because, in Figure S5, the tunnel calculated by MOLE seems to also connect to the cytosol.
Yes, it is likely that the ACOS is accessible via lumen and cytosol to varying degrees, as evidenced by MOLE prediction. However, binding of the bulky nucleoside head group of acetyl-CoA at ACOS blocks the cytosolic entrance in the confirmation discussed in this manuscript. MOLE prediction was performed on a structure devoid of acetyl-CoA, and it is possible that the protein doesn’t essentially undergo isomerization between open-to-lumen and open-to-cytosol confirmations during acetyl transfer. Likely, ACOS is always accessible from both the lumen and cytosol, but depending on the substrates or products bound, the accessibility could be limited to either the lysosomal lumen or cytosol. We have rewritten all the statements mentioning an open-to-lumen confirmation to reflect this argument.
(4) The authors state, "Interestingly, in most of the detergent conditions we tested, HGSNAT was predominantly dimeric (Fig S1C-H)," and also mention, "In all the detergents we tested, HGSNAT eluted as a dimer, a testament to the extensive side-chain interaction network." The dimerization is said to be mediated by a disulfide bond. I would be surprised if the detergents the authors tested could break a disulfide bond. Therefore, can this observation truly serve as a testament to an "extensive" side-chain interaction network?
We agree with the reviewer that detergents are unlikely to break a disulfide bond. To address this comment, we generated a C334A mutant of HGSNAT and extracted it from cells in 1% digitonin. It is still expressed as a dimer (Fig S8E). However, upon heating the detergent solubilized protein, we noticed that the FSEC peak for C334A shows a monomeric HGSNAT (Fig S8I and S8K). We hypothesize that in the absence of C334 disulfide, the extensive hydrophobic side-chain interaction network displayed in Figure 2C is responsible for maintaining the integrity of the dimer. Heating disturbs these non-disulfide interactions, thereby rendering the protein monomer.
(5) Apart from the cryo-EM structure, the article does not provide any other experimental evidence to support or explain a molecular mechanism. Due to the complete absence of functional assays, mutagenesis analysis, or other structures such as a ternary complex or an acetylated enzyme intermediate, the mechanistic model depicted in Figure 5 should be taken with caution. This uncertainty needs to be clearly described in the manuscript text. Performing additional mutagenesis experiments to test key hypotheses, or further discussing relevant data from the literature, would strengthen the manuscript.
We agree with the reviewer on the lack of supporting evidence for the mechanistic models proposed in Fig 5. They were made based on previously reported biochemical characterization of HGSNAT by Rome & Crain (1981), Rome et al. (1983), Miekle et al. (1995), and Fan et al. (2011). However, we agree with the reviewer that this schematic is not experimentally proven and is speculative at best. We have edited Figure 5 in the revised version of the manuscript. In addition, we have also performed mutagenesis analysis to study the stability of mutants (Fig S8) and performed LC-MS analysis to identify endogenously bound acetyl-CoA (Fig S9) to strengthen parts of the manuscript. We have discussed our findings in the results and modified the discussion according to these suggestions.
(6) It is discussed that H269 is an essential residue that participates in the acetylation reaction, possibly becoming acetylated during the process. However, there is no solid experimental evidence, e.g. mutagenesis analysis or structural analysis, in this or previous articles, that demonstrates this to be the case. Providing more information, ideally involving additional experimental work, would strengthen this aspect of the mechanism that is proposed. This would require establishing an in vitro assay, as described in 1).
H269, as a crucial catalytic residue, was suggested by monitoring the effect of chemical modifications of amino acids on acetylation of HGSNAT membranes by Bame, K. J. and Rome, L. H. (1986). We generated N258I and H269A mutants of HGSNAT and analyzed their stability. We noticed a greater destabilization in N258I compared to H269A (Fig S8). We believe this is because of the loss of ability to bind acetyl-CoA, as the TMs around a catalytic core of the protein in our cryo-EM structure were stabilized by interactions with acetyl-CoA. Recently, Xu et al. (2024, Nat Struct Mol Biol) suggested that they do not observe acetylated histidine in their structure. However, our structure and that reported by Xu et al. (2024) are obtained at cytosolic pH. Perhaps, acetylation of H269 occurs at acidic lysosomal pH. Extensive structural and catalytic investigation of HGSNAT at low pH is required to rule out H269 acetylation as a step in the HGSNAT catalyzed reaction.
(7) In the discussion part, the authors mention previous studies in which it was postulated that the catalytic reaction can be described by a random order mechanistic model or a Ping Pong Bi Bi model. However, the authors leave open the question of which of these mechanisms best describes the acetylation reaction. The structure presented here does not provide evidence that could support one mechanism or the other. The authors could explore if an in vitro experimental measurement of protein activity would provide any information in this regard.
We agree with the reviewer that a more detailed kinetic analysis is necessary to define the bisubstrate reaction mechanism of HGSNAT. All the existing structural data on two isoforms of HGSNAT is obtained at basic pH. As a result, the existing structures do not unambiguously demonstrate the bisusbtrate mechanism of HGSNAT. We believe low pH structural characterization and a detailed kinetic and structural characterization of HGSNAT in membrane mimetics like nanodiscs could provide more insights into the mechanism. However, these studies are a future undertaking and are not a part of this manuscript.
(8) Although the authors map the mutations leading to MPS IIIC on the structure and use FoldX software to predict the impact of these mutations on folding and fold stability, there is no experimental evidence to support FoldX's predictions. It would be ideal if an additional test for these predictions were included in the manuscript. The authors could follow the unfolding of purified mutants by SEC, FSEC, or changes in intrinsic fluorescence to assess protein stability.
As suggested here, we prepared HGSNAT MPSIIIC variants and tested their expression and stability (please see Fig S8). These results have been included in the revised version of the manuscript.
(9) Some sidechains that have quite strong sidechain density are missing atoms. I would be particularly careful with omitting sidechains that pack in the hydrophobic core, as this can tend to artificially reduce the clash score. Check F81, L62, P91 and V87, for example.
We have revisited the modeling of these regions and deposited new coordinates.
(10) W316 seems to have the wrong rotamer.
This has been corrected in the new coordinate file that has been released.
(11) N134 and N433 seem to have extra density. Are these known glycosylation sites?
As per Hrebicek M. et al., 2006 and Feldhammer M. et al., 2009, there are five predicted glycosylation sites: N66, N114, N134, N433, and N602. However, we see evidence for NAG density at N114, N134, and N433. These have now been modeled in the structure.
(12) At the C-terminal residue (Ile-635), the very C-terminal carboxylate is modeled pointing to a hydrophobic environment. It seems more likely to me that the Ile sidechain is packing here, with the C-terminal carboxylate facing the solvent.
Thank you for pointing this out. We have edited the orientation of the Ile sidechain accordingly.
Presentation and wording of results/methods:
- Figure S3 legend "At places with missing density, the side chains were trimmed to C- alpha" - this is incorrect, I think the authors mean C-beta.
We have corrected this error in the revised version of the manuscript.
- Figure S3 legend - the authors refer to a gray mesh, where a transparent surface is displayed.
Thanks for pointing this error out. We have corrected this in the revised version.
- Some colloquial/vague wording in the main text (a lot of sentences starting with "Interestingly, ...". Making the wording more specific would help the reader I think.
We have edited out ‘interestingly’ from the document and have re-written parts of the manuscript, per reviewers’ suggestion, for brevity.
- Figure S2 legend, "throughout the processing workflow the resolution of luminal domain was used as a guidepost" - it is not entirely clear to me what this means in this context, perhaps revise the wording?
We have rephrased this line in the revised draft of the manuscript.
- Figure S2 and methods, Local refinements of LD and TMD are mentioned, but not indicated on the processing workflow.
We have included a new Fig S2 & edited the legend, including these changes, per the reviewers’ suggestions.
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Reviewer #1 (Public Review):
This article by Navratna et al. reports the first structure of human HGSNAT in an acetyl-CoA-bound state. Through careful structural analysis, the authors propose potential reasons why certain human mutations lead to lysosomal storage disorders and outline a catalytic mechanism. The structural data are of good quality, and the manuscript is clearly written. This study represents an important step toward understanding the mechanism of HGSNAT and is valuable to the field. I have the following suggestions:
(1) The authors should characterize whether the purified protein is active. Otherwise, how does one know if the detergent used maintains the protein in a biologically relevant state? The authors should at least attempt to do so. If these prove to be challenging, at the very least, the authors should try a cell-based assay to demonstrate that the GFP tag does not interfere with the function.
(2) In Figure 5, the authors present a detailed schematic of the catalytic cycle, which I find to be too speculative. There is no evidence to suggest that this enzyme undergoes isomerization, similar to a transporter, between open-to-lumen and open-to-cytosol states. Could it not simply involve some movements of side chains to complete the acetyl transfer?
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The recombinant Pap31 antigen was prepared as described previously.
"Primers for rPap31 were designed according to the ATCC strain 35685 (KC583) sequence determined by L. Hendrix. The sequence has just been submitted to GenBank (accession number DQ207957) (forward primer: gcagcatatgttatgatcccgcaagaaata; reverse primer: ctaaaggcacaaccacaacgcattcttaag). The rPap31 gene segment was amplified using the genomic DNA of a local strain HOSP 800–09 as the template. PCR product was inserted between the NdeI and EcoRI sites of the expression vector pET24a (pET24a-pap31). The rPap31 protein was expressed in E. coli BL21 (DE3) after induction with 1 mM IPTG. The Pap31 gene segment in pET24a was recloned by GenWay Biotech Incorporated (San Diego, CA) to attach a T7 tag to the N-terminus of the rPap31 gene insert. The rPap31 was expressed as an inclusion body, which was washed and solubilized with 8 M urea in the presence of 1% Triton X-100 and 2 mM DTT in 50 mM Tris HCl, pH 8.0. The polypeptide was refolded by dialysis against 0.1 mM EDTA/12% glycerol in 50 mM Tris-HCl, pH 8.0, at 4°C. The refolded protein was further purified using the T7-tag affinity column in the presence of 2 M urea."
https://nyaspubs.onlinelibrary.wiley.com/doi/10.1196/annals.1355.045
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Author response:
Public Reviews:
Reviewer #1 (Public Review):
Summary:
In the manuscript entitled "Rtf1 HMD domain facilitates global histone H2B monoubiquitination and regulates morphogenesis and virulence in the meningitis-causing pathogen Cryptococcus neoformans" by Jiang et al., the authors employ a combination of molecular genetics and biochemical approaches, along with phenotypic evaluations and animal models, to identify the conserved subunit of the Paf1 complex (Paf1C), Rtf1, and functionally characterize its critical roles in mediating H2B monoubiquitination (H2Bub1) and the consequent regulation of gene expression, fungal development, and virulence traits in C. deneoformans or C. neoformans. Specially, the authors found that the histone modification domain (HMD) of Rtf1 is sufficient to promote H2B monoubiquitination (H2Bub1) and the expression of genes related to fungal mating and filamentation, and restores the fungal morphogenesis and pathogenicity defects caused by RTF1 deletion.
Strengths:
The manuscript is well-written and presents the findings in a clear manner. The findings are interesting and contribute to a better understanding of Rtf1-mediated epigenetic regulation of fungal morphogenesis and pathogenicity in a major human fungal pathogen, and potentially in other fungal species, as well.
Weaknesses:
A major limitation of this study is the absence of genome-wide information on Rtf1-mediated H2B monoubiquitination (H2Bub1), as well as a lack of detail regarding the function of the Plus3 domain. Although overexpression of HMD in the rtf1Δ mutant restored global H2Bub1 levels, it did not rescue certain critical biological functions, such as growth at 39 °C and melanin production (Figure 4C-D). This suggests that the precise positioning of H2Bub1 is essential for Rtf1's function. A comprehensive epigenetic landscape of H2Bub1 in the presence of HMD or full-length Rtf1 would elucidate potential mechanisms and shed light on the function of the Plus3 domain.
We thank the reviewer (and other reviewers) for this excellent suggestion. We have planned to carry out CUT&Tag assay to gain a comprehensive epigenetic landscape of H2Bub1 in the presence of HMD or full-length Rtf1 under conditions, where overexpression of HMD failed to rescue the phenotypes in the _rtf1_Δ mutant, such as growth at 39 °C.
Reviewer #2 (Public Review):
Summary:
The authors set out to determine the role of Rtf1 in Cryptococcal biology, and demonstrate that Rtf1 acts independently of the Paf1 complex to exert regulation of Histone H2B monoubiquitylation (H2Bub1). The biological impact of the loss of H2Bub1 was observed in defects in morphogenesis, reduced production of virulence factors, and reduced pathogenic potential in animal models of cryptococcal infection.
Strengths:
The molecular data is quite compelling, demonstrating that the Rtf1-depednent functions require only this histone modifying domain of Rtf1, and are dependent on nuclear localization. A specific point mutation in a residue conserved with the Rtf1 protein in the model yeast demonstrates the conservation of that residue in H2Bub1 modification. Interestingly, whereas expression of the HMD alone suppressed the virulence defect of the rtf1 deletion mutant, it did not suppress defects in virulence factor production.
Weaknesses:
The authors use two different species of Cryptococcus to investigate the biological effect of Rtf1 deletion. The work on morphogenesis utilized C. deneoformans, which is well-known to be a robust mating strain. The virulence work was performed in the C. neoformans H99 background, which is a highly pathogenic isolate. The study would be more complete if each of these processes were assessed in the other strain to understand if these biological effects are conserved across the two species of Cryptococcus. H99 is not as robust in morphogenesis, but reproducible results assessing mating and filamentation in this strain have been performed. Similarly, C. deneoformans does produce capsule and melanin.
This is a fair point raised by the reviewer, and we are going to test whether these biological effects are conserved across the two species. We will access effects of RTF1 deletion on bisexual mating hyphal formation in C. neoformans H99 background and capsule and melanin productions in C. deneoformans XL280 background.
There are some concerns with the conclusions related to capsule induction. The images reported in Figure B are purported to be grown under capsule-inducing conditions, yet the H99 panel is not representative of the induced capsule for this strain. Given the lack of a baseline of induction, it is difficult to determine if any of the strains may be defective in capsule induction. Quantification of a population of cells with replicates will also help to visualize the capsular diversity in each strain population.
We thank the reviewer for raising this concern. We are going to confirm the conclusions related to capsule induction under multiple capsule-inducing conditions, including Dulbecco’s Modified Eagle’s Medium (DMEM), Littman’s medium, and 10% fetal bovine serum (FBS) agar medium [1].
The authors demonstrate that for specific mating-related genes, the expression of the HMD recapitulated the wild-type expression pattern. The RNA-seq experiments were performed under mating conditions, suggesting specificity under this condition. The authors raise the point in the discussion that there may be differences in Rtf1 deposition on chromatin in H99, and under conditions of pathogenesis. The data that overexpression of HMD restores H2Bub1 by western is quite compelling, but does not address at which promoters H2Bub1 is modulating expression under pathogenesis conditions, and when full-length Rtf1 is present vs. only the HMD.
We thank the reviewer for raising these concerns. As mentioned in the response to Reviewer 1, our CUT&Tag assay will provide evidence to address these questions.
Reviewer #3 (Public Review):
Summary:
In this very comprehensive study, the authors examine the effects of deletion and mutation of the Paf1C protein Rtf1 gene on chromatin structure, filamentation, and virulence in Cryptococcus.
Strengths:
The experiments are well presented and the interpretation of the data is convincing.
Weaknesses:
Yet, one can be frustrated by the lack of experiments that attempt to directly correlate the change in chromatin structure with the expression of a particular gene and the observed phenotype. For example, the authors observed a strong defect in the expression of ZNF2, a known regulator of filamentation, mating, and virulence, in the rtf1 mutant. Can this defect explain the observed phenotypes associated with the RTF1 mutation? Is the observed defect in melanin production associated with altered expression of laccase genes and altered chromatin structure at this locus?
We completely agree with the reviewer, and as mentioned in our response to Reviewer 1 and 2, we are going to conduct CUT&Tag assay to investigate the genetic relationship between Rtf1-mediated H2Bub1 and the expression of particular genes.
(1) Jang, E.-H., et al., Unraveling Capsule Biosynthesis and Signaling Networks in Cryptococcus neoformans. Microbiology Spectrum, 2022. 10(6): p. e02866-22.
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Reviewer #2 (Public Review):
Summary:
This manuscript by Wei et al studies the role of ZFP36L1, an RNA-binding protein, in promoting PD-L1 expression in gastric cancer (GC). They used human gastric cancer tissues from six patients and performed H3K27ac CUT&Tag to unbiasedly identify SE specific for the infiltrative type. They identified an SE driving the expression of ZFP36L1 and immune evasion through upregulation of PD-L1. Mechanistically, they show that SPI1 binds to ZFP36L1-SE and ZFP36L1 in turn regulates PD-L1 expression through modulation of the 3'UTR of HDAC3. This mechanism of PD-L1 regulation in gastric cancer is novel, and ZFP36L1 has not been previously implicated in GC progression. However, the data presented are largely correlations and no direct proof is presented that the identified SE regulates ZFP36L1 expression. Furthermore, the effect of ZFP36L1 manipulation elicited a modest effect on PDL1 expression. In fact, several cell lines (XGC1, MNK45) express abundant ZFP36L1 but no PD-L1, suggesting the ZFP36L1 per se is not a key stimulant of PD-L1 expression as IFNg is. Thus, the central conclusions are not supported by the data.
Strengths:
Use of human GC specimens to identify SE regulating PD-L1 expression and immune evasion.
Weaknesses:
Major comments:
(1) The difference in H3K27ac over the ZFP36L1 locus and SE between the expanding and infiltrative GC is marginal (Figure 2G). Although the authors establish that ZFP36L1 is upregulated in GC, particularly in the infiltrative subtype, no direct proof is provided that the identified SE is the source of this observation. CRISPR-Cas9 should be employed to delete the identified SE to prove that it is causatively linked to the expression of ZFP36L1.
(2) In Figure 3C the impact of shZFP36L1 on PD-L1 expression is marginal and it is observed in the context of IFNg stimulation. Moreover, in XGC-1 cell line the shZFP36L1 failed to knock down protein expression thus the small decrease in PD-L1 level is likely independent of ZFP36L1. The same is the case in Figure 3D where forced expression of ZFP36L1 does not upregulate the expression of PDL1 and even in the context of IFNg stimulation the effect is marginal.
(3) In Figure 4, it is unclear why ELF1 and E2F1 that bind ZFP36L1-SE do not upregulate its expression and only SPI1 does. In Figure 4D the impact of SPI overexpression on ZFP36L1 in MKN45 cells is marginal. Likewise, the forced expression of SPI did not upregulate PD-L1 which contradicts the model. Only in the context of IFNg PD-L1 is expressed suggesting that whatever role, if any, ZFP36L1-SPI1 axis plays is secondary.
(4) The data presented in Figure 6 are not convincing. First, there is no difference in the tumor growth (Figure 6E). IHC in Figure 6I for CD8a is misleading. Can the authors provide insets to point CD8a cells? This figure also needs quantification and review from a pathologist.
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all the great ideas come um with a price tag of it's maybe a mistake
for - neuroscience - innovation - great ideas - mistakes and - risk
neuroscience - innovation - great ideas - mistakes and - risk - Any new idea involves taking a risk that it could be wrong - we cannot be innovators if we are not able to risk making mistakes
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Reviewer #1 (Public Review):
The manuscript by Li et al. investigates the metabolism-independent role of nuclear IDH1 in chromatin state reprogramming during erythropoiesis. The authors describe accumulation and redistribution of histone H3K79me3, and downregulation of SIRT1, as a cause for dyserythropoiesis observed due to IDH1 deficiency. The authors studied the consequences of IDH1 knockdown, and targeted knockout of nuclear IDH1, in normal human erythroid cells derived from hematopoietic stem and progenitor cells and HUDEP2 cells respectively. They further correlate some of the observations such as nuclear localization of IDH1 and aberrant localization of histone modifications in MDS and AML patient samples harboring IDH1 mutations. These observations are intriguing from a mechanistic perspective and they hold therapeutic significance, however there are major concerns that make the inferences presented in the manuscript less convincing.
(1) The authors show the presence of nuclear IDH1 both by cell fractionation and IF, and employ an efficient strategy to knock out nuclear IDH1 (knockout IDH1/ Sg-IDH1 and rescue with the NES tagged IDH1/ Sg-NES-IDH1 that does not enter the nucleus) in HUDEP2 cells. However, some important controls are missing.<br /> A) In Figure 3C, for IDH1 staining, Sg-IDH1 knockout control is missing.<br /> B) Wild-type IDH1 rescue control (ie., IDH1 without NES tag) is missing to gauge the maximum rescue that is possible with this system.
(2) Considering the nuclear knockout of IDH1 (Sg-NES-IDH1 referenced in the previous point) is a key experimental system that the authors have employed to delineate non-metabolic functions of IDH1 in human erythropoiesis, some critical experiments are lacking to make convincing inferences.<br /> A) The authors rely on IF to show the nuclear deletion of Sg-NES-IDH1 HUDEP2 cells. As mentioned earlier since a knockout control is missing in IF experiments, a cellular fractionation experiment (similar to what is shown in Figure 2F) is required to convincingly show the nuclear deletion in these cells.<br /> B) Since the authors attribute nuclear localization to a lack of metabolic/enzymatic functions, it is important to show the status of ROS and alpha-KG in the Sg-NES-IDH1 in comparison to control, wild type rescue, and knockout HUDEP2 cells. The authors observe an increase of ROS and a decrease of alpha-KG upon IDH1 knockdown. If nuclear IDH1 is not involved in metabolic functions, is there only a minimal or no impact of the nuclear knockout of IDH1 on ROS and alpha-KG, in comparison to complete knockout? These studies are lacking.<br /> C) Authors show that later stages of terminal differentiation are impacted in IDH1 knockdown human erythroid cells. They also report abnormal nuclear morphology, an increase in euchromatin, and enucleation defects. However, the authors only report abnormal nuclear morphology in Sg-NES-IDH1 cells, as evaluated by cytospins. It is important to show the status of the other phenotypes (progression through terminal differentiation, euchromatin %, and enucleation) similar to the quantitations in the IDH1 knockdown cells.
(3) The authors report abnormal nuclear phenotype in IDH1 deficient erythroid cells. It is not clear what parameters are used here to define and quantify abnormal nuclei. Based on the cytospins (eg., Figure 1A, 3D) many multinucleated cells are seen in both shIDH1 and Sg-NES-IDH1 erythroid cells, compared to control cells. Importantly, this phenotype and enucleation defects are not rescued by the administration of alpha-KG (Figures 1E, F). The authors study these nuclei with electron microscopy and report increased euchromatin in Figure 4B. However, there is no discussion or quantification of polyploidy/multinucleation in the IDH1 deficient cells, despite their increased presence in the cytospins.
A) PI staining followed by cell cycle FACS will be helpful in gauging the extent of polyploidy in IDH1 deficient cells and could add to the discussions of the defects related to abnormal nuclei.<br /> B) For electron microscopy quantification in Figures 4B and C, how the quantification was done and the labelling of the y-axis (% of euchromatin and heterochromatin) in Figure 4 C is not clear and is confusingly presented. The details on how the quantification was done and a clear label (y-axis in Figure 4C) for the quantification are needed.<br /> C) As mentioned earlier, what parameters were used to define and quantify abnormal nuclei (e.g. Figure 1A) needs to be discussed clearly. The red arrows in Figure 1A all point to bi/multinucleated cells. If this is the case, this needs to be made clear.
(4) The authors mention that their previous study (reference #22) showed that ROS scavengers did not rescue dyseythropoiesis in shIDH1 cells. However, in this referenced study they did report that vitamin C, a ROS scavenger, partially rescued enucleation in IDH1 deficient cells and completely suppressed abnormal nuclei in both control and IDH1 deficient cells, in addition to restoring redox homeostasis by scavenging reactive oxygen species in shIDH1 erythroid cells. In the current study, the authors used ROS scavengers GSH and NAC in shIDH1 erythroid cells and showed that they do not rescue abnormal nuclei phenotype and enucleation defects. The differences between the results in their previous study with vitamin C vs GSH and NAC in the context of IDH1 deficiency need to be discussed.
(5) The authors describe an increase in euchromatin as the consequential abnormal nuclei phenotype in shIDH1 erythroid cells. However, in their RNA-seq, they observe an almost equal number of genes that are up and down-regulated in shIDH1 cells compared to control cells. If possible, an RNA-Seq in nuclear knockout Sg-NES-IDH1 erythroid cells in comparison with knockout and wild-type cells will be helpful to tease out whether a specific absence of IDH1 in the nucleus (ie., lack of metabolic functions of IDH) impacts gene expression differently.
(6) In Figure 8, the authors show data related to SIRT1's role in mediating non-metabolic, chromatin-associated functions of IDH1.<br /> A) The authors show that SIRT1 inhibition leads to a rescue of enucleation and abnormal nuclei. However, whether this rescues the progression through the late stages of terminal differentiation and the euchromatin/heterochromatin ratio is not clear.<br /> B) In addition, since the authors attribute a role of SIRT1 in mediating non-metabolic chromatin-associated functions of IDH1, documenting ROS levels and alpha-KG is important, to compare with what they showed for shIDH1 cells.
(7) In Figure 4 and Supplemental Figure 8, the authors show the accumulation and altered cellular localization of H3K79me3, H3K9me3, and H3K27me2, and the lack of accumulation of other three histone modifications they tested (H3K4me3, H3K35me4, and H3K36me2) in shIDH1 cells. They also show the accumulation and altered localization of the specific histone marks in Sg-NES-IDH1 HUDEP2 cells.<br /> A) To aid better comparison of these histone modifications, it will be helpful to show the cell fractionation data of the three histone modifications that did not accumulate (H3K4me3, H3K35me4, and H3K36me2), similar to what was shown in Figure 4E for H3K79me3, H3K9me3, and H3K27me2).<br /> B) Further, the cell fractionation and staining for histone marks is done in human primary erythroid cells on day15 of terminal differentiation, and these studies revealed that H3K79me3, H3K9me3, and H3K27me2 were retained in the nucleus in shIDH1 cells unlike a cellular localization observed in control cells. The authors cite reference #40 in relation to the cellular localization of histones - in this study, it was shown that the cellular export of histone to cytosol happens during later stages of terminal differentiation. In the current manuscript, the authors observe nuclear IDH1 throughout erythropoiesis and have shown this at both early and late time points of differentiation (between day7 to day15 of differentiation in primary erythroid cells, between day0 to day8 in HUDEP2 cells) in Figure 2. To help correlate the dynamics of localization and to discuss the mechanism for the retention of histone marks in the nucleus in IDH1 deficient cells, it will be helpful to show the cellular location of histone marks using cell fractionations for both early and late time points in terminal erythroid differentiation, similar to what they showed for IDH1 localization studies.<br /> C) Among the three histone marks that are dysregulated in IDH1 deficient cells (H3K79me3, H3K9me3, and H3K27me2), the authors show via ChIP-seq (Fig5) that H3K79me3 is the critical factor. However, the ChIP-seq data shown here lacks many details and this makes it hard to interpret the data. For example, in Figure 5A, they do not mention which samples the data shown correspond to (are these differential peaks in shIDH1 compared to shLuc cells?). There is also no mention of how many replicates were used for the ChIP seq studies.
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link.springer.com link.springer.com
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MYC-tag
DOI: 10.1007/s00395-021-00865-9
Resource: (Cell Signaling Technology Cat# 2278, RRID:AB_490778)
Curator: @Naa003
SciCrunch record: RRID:AB_490778
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HA-tag
DOI: 10.1007/s00395-021-00865-9
Resource: (Rockland Cat# 600-401-384, RRID:AB_217929)
Curator: @Naa003
SciCrunch record: RRID:AB_217929
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www.cell.com www.cell.com
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Rabbit anti-myc tag
DOI: 10.1016/j.molcel.2020.11.047
Resource: (Cell Signaling Technology Cat# 2278, RRID:AB_490778)
Curator: @Naa003
SciCrunch record: RRID:AB_490778
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Rabbit anti-HA tag
DOI: 10.1016/j.molcel.2020.11.047
Resource: (Cell Signaling Technology Cat# 3724, RRID:AB_1549585)
Curator: @Naa003
SciCrunch record: RRID:AB_1549585
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hypothes.is hypothes.is
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zettelkasten faq
faq
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card index for business
... "for" ...
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concentration of ideas
... "of" ...
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Erich Fromm's zettelkasten
Person's (thing)
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card index in literature
... "in" ...
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zettelkasten productivity
Lumping two words together
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memory and history zettelkasten and memory
... "and" ...
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zettelkasten examples digitized examples personal websites as commonplace books
... "as" ... And, ... "examples"
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www.codigofonte.com.br www.codigofonte.com.br
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Top 10 frameworks de Node.js O JavaScript fugiu de vez do navegador e nós escolhemos 10 frameworks que você deve usar quando se trata de Node.js.
310724 232004 qua. BEMIG-MG-IPT. Aloj. AlfreDom<br /> o LIDO
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- Jul 2024
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www.biorxiv.org www.biorxiv.org
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Background As biological data increases, we need additional infrastructure to share it and promote interoperability. While major effort has been put into sharing data, relatively less emphasis is placed on sharing metadata. Yet, sharing metadata is also important, and in some ways has a wider scope than sharing data itself.Results Here, we present PEPhub, an approach to improve sharing and interoperability of biological metadata. PEPhub provides an API, natural language search, and user-friendly web-based sharing and editing of sample metadata tables. We used PEPhub to process more than 100,000 published biological research projects and index them with fast semantic natural language search. PEPhub thus provides a fast and user-friendly way to finding existing biological research data, or to share new data.
This work has been peer reviewed in GigaScience (see paper), which carries out open, named peer-review. These reviews are published under a CC-BY 4.0 license and were as follows:
Reviewer name: Weiwen Wang (original submission)
This manuscript by LeRoy et al. introduces PEPhub, a database aimed at enhancing the sharing and interoperability of biological metadata using the PEP framework. One of the key highlights of this manuscript is the visualization of the PEP framework, which improves the adoption of the PEP framework, facilitating the reuse of metadata. Additionally, PEPhub integrates data from GEO, making it convenient for users to access and utilize. Furthermore, PEPhub offers metadata validation, allowing users to quickly compare their PEP with other PEPhub schemas. Another notable feature is the natural language search, which further enhances the user experience. Overall, PEPhub provides a comprehensive solution that promotes efficient metadata sharing, while leveraging the impact of the PEP framework in organizing large-scale biological research projects.While this manuscript was interesting to read, I have several concerns regarding its "semantic" search system and the interaction of PEPHub.1.
The authors mentioned their use of a tool called "pepembed" to embed PEP descriptions into vectors. However, I was unable to locate the tool on GitHub, and there is limited information in the Method section regarding this. Could the authors provide additional details regarding the process of embedding vectors?2. The authors implemented semantic search as an advantage of PEPhub. However, they did not evaluate the effectiveness of their natural language search engine, such as assessing accuracy, recall rate, or F1 score. It would be beneficial for the authors to perform an evaluation of their natural language search engine and provide metrics to demonstrate its performance. This would enhance the credibility and reliability of their claims regarding the advantages of natural language search in PEPhub.3. It would be more beneficial to include the metadata in the search system rather than solely relying on the project description. For instance, when I searched for SRX17165287 (https://pephub.databio.org/geo/gse211736?tag=default), no results were returned.4. When creating a new PEP, it appears that I can submit two samples with identical values. According to the PEP framework guidelines, it is mentioned that "Typically, samples should have unique values in the sample table index column". Therefore, the authors should enhance their metadata validation system to enforce this uniqueness constraint. Additionally, if I enter two identical values in the sample field and then attempt to add a SUBSAMPLE, an error occurs. However, when I modify one of the samples, I am able to save it successfully.5. The error messages should provide more specific guidance. Currently, when attempting to save metadata with an incorrect format, all error messages are displayed as: "Unknown error occurred: Unknown".6.
PEPhub should consider providing user guidelines or examples on how to fill in subsample metadata and any relevant rules associated with it.7. In the Validation module, what are the rules for validation? Does it only check for the required column names in the schema, or does it also validate the content of the metadata, such as whether the metadata is in the correct format (e.g., int or string)? Additionally, it would be beneficial to provide an option to download the relevant schema and clearly specify the required column names in the schema. This would enable users to better organize their PEP to comply with the schema format and ensure that their metadata is accurately validated.8. This version of PEPHub primarily focuses on metadata. Have the authors considered any plans to expand this database to include data/pipeline management within the PEP framework? It would be valuable for the authors to discuss their future plans for PEPHub in this manuscript.Some minor concerns:1. When searching for content within a specific namespace, it would be beneficial for the pagination bar at the bottom of the webpage to display the number of pages. Now there are only Previous/Next buttons.2. As a web service, it is better to show the supporting browsers, such as Google Chrome (version xxx and above), Firefox (version xxx and above). I failed to open PEPHub website using an old version of Chrome.
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github.com github.com
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encrypted by the TLS
Check if east-west traffic is encrypted as well.
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Nydus Snapshotter to enhance the container launch speed
Understand how Nydus might impact the threat model for the CRI.
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security of the data transmission by encrypting the data
Understand how identity/tokens are established/rotated/stored.
- Are tokens short spanned by default?
- What is the blast radius of the token compromise?
- How are tokens/cred stored locally?
- What is the revocation logic that it is dependent on?
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download back-to-source
What does this term mean?
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www.biorxiv.org www.biorxiv.org
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Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
Fita-Torró et al. study the toxic effects of the intermediary lipid degradation product trans-2-hexadecenal (t-2-hex) on yeast mitochondria and suggest a mechanism by which Hfd1 safeguards Tom40 from lipidation by t-2-hex and its consequences, such as mitochondrial protein import inhibition, cellular proteostasis deregulation, and stress-responses.
The authors aimed to dissect a mechanism for t-2-hex' apoptotic consequences in yeast and they suggest it is via lipidation of Tom40 but really under the tested conditions everything seems lipidated. Thus, it is unclear whether Tom40 is the crucial causal target. They also do not provide much biochemical experiments to investigate this phenomenon further functionally. Tom40 is one possible and perhaps, given the cellular consequences, a reasonable candidate but not validated beyond in vitro lipidation by exogenous t-2-hex.
In the revised version of our manuscript, we have now included extensive new experimentation, which shows that protein import at the TOM complex is a physiologically important target of the pro-apoptotic lipid t-2-hex and that enzymes such as the Hfd1 dehydrogenase sensitively regulate this inhibition. In vitro chemoproteomic experiments have now been performed at more physiological t-2hex concentrations of 10µM, which is lower than published data in human cell models. Consistently, several TOM and TIM subunits are enriched in these in vitro lipidation studies (new Fig. 8B). Tom40 lipidation alone is not sufficient to explain t2-hex toxicity, as a cysteine-free version of Tom40 does not confer tolerance to the apoptotic lipid (new Fig. 8D). Importantly however, the loss of function of nonessential accessory Tom subunits 70 or 20 confers t-2-hex tolerance (new Fig. 8D) indicating that pre-protein import at the TOM complex is a physiological target of t2-hex most likely dependent on lipidation of more Tom subunits than just the essential Tom40 pore. Moreover, we now show that mitochondrial protein import is inhibited by the lipid at low physiological doses of 10µM and that this inhibition is modulated by the gene dose of the t-2-hex degrading Hfd1 enzyme (new Fig. 5G).
Strengths:
The effects of lipids and their metabolic intermediates on protein function are understudied thus the authors' research contributing to elucidating direct effects of a single lipid is appreciated. It is particularly unknown by which mechanism t-2hex causes cell death in yeast. The authors elegantly use modulation of the levels of enzyme Hfd1 that endogenously catabolizes t-2-hex as an approach to studying t2-hex stress. Understanding the cause and consequences of this stress is relevant for understanding fundamental regulation mechanisms, and also to human health since the human homolog of Hfd1, ALDH3A2, is mutated in Sjögren-Larsson Syndrome. The application of a variety of global transcriptomic, functional genomic, and chemoproteomic approaches to study t-2-hex stress targets in the yeast model is laudable.
Weaknesses:
- The extent of the contribution of Tom40 lipidation to the general t-2-hex stress phenotype is unclear. Is Tom40 lipidation alone enough to cause the phenotype? An alteration of the cysteine residue in question could help answer this key question.
Deletion of all four cysteine residues in Tom40 is not sufficient to confer resistance to t-2-hex stress. This result had been included in the original manuscript, but was somehow hidden in the Discussion. The revised manuscript now includes t-2hex tolerance assays for the Tom40 cysteine free mutant in new Figure 8. As a result, cysteine lipidation of Tom40 alone is not sufficient to confer t-2-hex toxicity. This implies most likely other lipidation targets within the TOM and TIM complexes, as indicated by our in vitro lipidation studies. We therefore included the non-essential adaptor proteins Tom70 and Tom20 of the TOM complex and tested the tolerance of the respective deletion mutants in t-2-hex tolerance assays. As shown in new Figure 8, the absence of Tom70 and Tom20 function significantly increases tolerance to t-2hex and the tom20 mutant accumulates less Aim17 pre-protein upon t-2-he stress, indicating that the TOM complex is a physiologically important target of the proapoptotic lipid, which acts most likely via lipidation of more subunits than the Tom40 import channel.
- It is unclear whether the exogenously applied amounts of t-2-hex (concentrations chosen between 25-200 uM) are physiologically relevant in yeast cells. For comparison, Chipuk et al. (2012) used at most 1 uM on mitochondria of human cells, while Jarugumilli et al. (2018) considered 25 uM a 'lower dose' on human cells. Since the authors saw responses below 10 uM (Fig. 3B) and at the lowest selected concentration of 25 uM (Fig. 8), why were no lower, likely more specific, concentrations applied for the global transcriptomic and chemoproteomic experiments? Key experiments have to be repeated with the lower concentrations.
We have now performed several experiments with lower t-2-hex concentrations. A new chemoproteomic study with 10µM t-2-hex-alkyne has been conducted and the new results added to the supplementary information, combining 10µM and 100µM in vitro lipidation studies (Suppl. Table 6). Many subunits of the TOM and TIM complexes consistently are enriched significantly in both chemoproteomic experiments. These new data are summarized in revised Figure 8. Additionally we have performed in vivo pre-protein assays with lower t-2-hex concentrations. As shown in new Figure 5, Aim17 mitochondrial import is already inhibited by t-2-hex doses as low as 10µM in a wild type strain, and that this inhibition is enhanced in a hfd1 mutant and alleviated in a Hfd1 overexpressor. It is important to note that a dose of 10µM of external t-2-hex addition is significantly lower than doses applied to human cell cultures such as in Jarugumilli et al. (2018). It proves that mitochondrial protein import is a sensitive and physiologically relevant t2-hex target in our yeast models and that t-2-hex detoxification by enzymes such as the Hfd1 dehydrogenase sensitively regulates this specific inhibition.
- The amount of t-2-hex applied is especially important to consider in light of over 1300 proteins lipidated to an extent equal to or greater than Tom40 (Supp. Table 6). This chemoproteomic experiment (Fig. 8B, Supp. Table 6) is also weakened by the inclusion of only 2 replicates, thus precluding assessment of statistical significance. The selection of targets in Fig. 8B as "among the best hits" is neither immediately comprehensible nor further explained and represents at best cherrypicking. Further evidence based on statistical significance or validation by other means should be provided.
We performed the chemoproteomic screens as described by Jarugumilli et al. (2018) with 2 replicates of mock treated versus 2 replicates of t-2-hex-alkyne treated cell extracts. A new chemoproteomic study with 10µM t-2-hex-alkyne has been conducted and the new results added to the supplementary information combining 10µM and 100µM in vitro lipidation studies (Suppl. Table 6). Differential enrichment analysis of the proteomic data was performed with the amica software (Didusch et al., 2022). Proteins were ranked according to their log2 fold induction comparing lipid- and mock-treated samples with a threshold of ≥1.5, and the adjusted p-value was calculated. Several TOM and TIM subunits were consistently identified as differentially enriched proteins, which is summarized in new Figure 8B.
- The authors unfortunately also underuse the possible contribution of mass spectrometry technology to in addition determine the extent and localization of lipidation on a global scale (especially relevant since Cohen et al. (2020) suggest site-specific mechanisms).
We agree that site-specific modifications of t-2-hex will be most likely important in the inhibition or other type of regulation of specific target proteins. Our collective data show that in the case of the inhibition of mitochondrial protein import, several lipidation events on TOM and TIM are involved. Dissection of individual cysteine lipidations on those subunits will be interesting, but we feel that this is out of the scope of the present work.
- The general novelty of studying t-2-hex stress is lowered in light of existing literature in humans (see e. g. Chipuk et al., 2012; Cohen et al., 2020; Jarugumilli et al., 2018), and in yeast by the same authors (Manzanares-Estreder et al., 2017) and as the authors comment themselves, a significant part of the manuscript may represent rather a confirmation of the already described consequences of t-2-hex stress
We do not agree and we have not commented that our present study is a mere confirmation of t-2-hex stress previously applied in yeast and human models. In humans, t-2-hex has been identified as an efficient pro-apoptotic lipid, which causes mitochondrial dysfunction via direct lipidation of Bax, however the studies of Jarugumilli et al. (2018) revealed that many other direct t-2-hex targets exist, which remained uninvestigated to date. This work continues our previous studies (Manzanares-Estreder et al., 2017), where we show that t-2-hex is a universal proapoptotic lipid applicable in yeast models and contributes important novel findings, such as the massive transcriptional response resembling proteostatic defects caused by t-2-hex, mitochondrial protein import as a physiologically important and direct target of t-2-hex, the function of detoxifying enzymes such as Hfd1 in modulating lipid-mediated inhibition of mitochondrial protein import and general proteostasis. Additionally, we provide transcriptomic, chemoproteomic and functional genomic data to the scientific community, which will be a rich source for future studies on yet undiscovered pro-apoptotic mechanisms employed by t-2-hex.
Reviewer #2 (Public Review):
This study elucidates the toxic effects of the lipid aldehyde trans-2-hexadecenal (t-2-hex). The authors show convincingly that t-2-hex induces a strong transcriptional response, leads to proteotoxic stress, and causes the accumulation of mitochondrial precursor proteins in the cytosol.
The data shown are of high quality and well controlled. The genetic screen for mutants that are hyper-and hypo-sensitive to t-2-hex is elegant and interesting, even if the mechanistic insights from the screen are rather limited. The last part of the study is less convincing. The authors show evidence that t-2-hex affects subunits of the TOM complex. However, they do not formally demonstrate that the lipidation of a TOM subunit is responsible for the toxic effect of t-2-hex. A t-2-hexresistant TOM mutant was not identified. Moreover, it is not clear whether the concentrations of t-2-hex in this study are physiological. This is, however, a critical aspect. The literature is full of studies claiming the toxic effects of compounds such as H2O2; even if such studies are technically sound, they are misleading if nonphysiological concentrations of such compounds were used.
Nevertheless, this is an interesting study of high quality. A few specific aspects should be addressed.
We have now performed t-2-hex toxicity assays using several mutants in Tom subunits, the cysteine free mutant of the essential Tom40 core channel and deletion mutants in the accessory subunits Tom70 and Tom20 (new Figure 8). As a result, cysteine lipidation of Tom40 alone is not sufficient to confer t-2-hex toxicity. This implies most likely other lipidation targets within the TOM and TIM complexes, as indicated by our in vitro lipidation studies. Indeed, as shown in new Figure 8, the absence of Tom70 and Tom20 function significantly increases tolerance to t-2-hex indicating that the TOM complex is a physiologically important target of the proapoptotic lipid, which acts most likely via lipidation of more subunits than the Tom40 import channel.
We have now performed several experiments with lower t-2-hex concentrations. A new chemoproteomic study with 10µM t-2-hex-alkyne has been conducted and the new results added to the supplementary information combining 10µM and 100µM in vitro lipidation studies (Suppl. Table 6). Many subunits of the TOM and TIM complexes consistently are enriched significantly in both chemoproteomic experiments. These new data are summarized in revised Figure 8.
Additionally we have performed in vivo pre-protein assays with lower t-2-hex concentrations. As shown in new Figure 5, Aim17 mitochondrial import is already inhibited by t-2-hex doses as low as 10µM in a wild type strain, and that this inhibition is enhanced in a hfd1 mutant and alleviated in a Hfd1 overexpressor. It is important to note that a dose of 10µM of external t-2-hex addition is significantly lower than doses applied to human cell cultures such as in Jarugumilli et al. (2018). It proves that mitochondrial protein import is a sensitive and physiologically relevant t2-hex target in our yeast models and that t-2-hex detoxification by enzymes such as the Hfd1 dehydrogenase sensitively regulates this specific inhibition.
Reviewer #3 (Public Review):
Summary: The authors investigate the effect of the lipid aldehyde trans-2hexadecenal (t-2-hex) in yeast using multiple omic analyses that show that a large range of cellular functions across all compartments are affected, e.g. transcriptomic changes affect 1/3 of all genes. The authors provide additional analyses, from which they built a model that mitochondrial protein import caused by modification of Tom40 is blocked.
Strengths: Global analyses (transcriptomic and functional genomics approach) to obtain an unbiased overview of changes upon t-2-hex treatment.
Weaknesses: It is not clear why the authors decided to focus on mitochondria, as only 30 genes assigned to the GO term "mitochondria" are increasing, and also the follow-up analyses using SATAY is not showing a predominance for mitochondrial proteins (only 4 genes are identified as hits). The provided additional experimental data do not support the main claims as neither protein import is investigated nor is there experimental evidence that lipidation of Tom40 occurs in vivo and impacts on protein translocation.
30 mitochondrial gene functions are very strongly (>10 fold) up-regulated by t-2-hex. However, when genes up-regulated (>2 log2FC) or down-regulated (<-2 log2FC) by t-2-hex were selected and subjected to GO category enrichment analysis, we found that “Mitochondrial organization” was the most numerous GO group activated by t-2-hex, while it was “Ribosomal subunit biogenesis” for t-2-hex repression (new data in Suppl. Tables 1 and 2).
In the revised version of our manuscript, we have now included extensive new experimentation, which shows that protein import at the TOM complex is a physiologically important target of the pro-apoptotic lipid t-2-hex and that enzymes such as the Hfd1 dehydrogenase sensitively regulate this inhibition. In vitro chemoproteomic experiments have now been performed at more physiological t-2hex concentrations of 10µM, which is lower than published data in human cell models. Consistently, several TOM and TIM subunits are enriched in these in vitro lipidation studies (new Fig. 8B). Tom40 lipidation alone is not sufficient to explain t2-hex toxicity, as a cysteine-free version of Tom40 does not confer tolerance to the apoptotic lipid (new Fig. 8D). Importantly however, the loss of function of nonessential accessory Tom subunits 70 or 20 confers t-2-hex tolerance (new Fig. 8D) indicating that pre-protein import at the TOM complex is a physiological target of t2-hex most likely dependent on lipidation of more Tom subunits than just the essential Tom40 pore. Moreover, we now show that mitochondrial protein import is inhibited by the lipid at low physiological doses of 10µM and that this inhibition is modulated by the gene dose of the t-2-hex degrading Hfd1 enzyme (new Fig. 5G).
Recommendations for the authors:
Reviewer #1 (Recommendations For The Authors):
Private recommendations for the authors
- On the existing data from Supp. Table 6, the authors may include a global assessment of whether or not the protein included a cysteine (the likely site for lipidation).
Although free cysteines in target proteins are the most frequent sites of modification by LDEs such as t-2-hex, other amino acids such as lysines or histidines can be lipidated by these lipid derivatives. Therefore we would like to exclude this information from our chemoproteomic data.
- What determines whether a gene is labeled in Fig. 6B other than fold change? Why is MAC1 with the highest FC not shown?
We analyzed the potential anti-apoptotic SATAY hits with a log2 < -0.75 according to expected detoxification pathways (heat shock response, pleiotropic drug response), to their function in the ER (the intracellular site where t-2-hex is generated) or in mitochondria (the major t-2-hex target identified so far). This is now better described in the text. As for the potential pro-apoptotic SATAY hits, we analyzed gene functions with a log2 > 1.5 and marked the predominant groups “Cytosolic ribosome and translation” and “Amino acid metabolism”. In any case, the interested reader has all SATAY data available in supplemental tables 4 and 5 to find alternative gene functions with a potential role in cellular adaptation to t-2-hex.
- Supplementary Table numbering should be double-checked.
Ok, numbering has been double-checked.
Reviewer #2 (Recommendations For The Authors):
Major points
(1) Identification of the t-2-hex target. Neither Tom70, Tom20 nor the cysteine in Tom40 is essential. If one of these components is critical for the t-2-hex-mediated toxicity, mutants should be t-2-hex-resistant. This is a straight-forward, simple, and critical experiment.
We have now performed t-2-hex toxicity assays in the cysteine free Tom40 mutant, and tom20 and tom70 deletion mutants. As shown in new Figure 8, cysteine lipidation of Tom40 alone is not sufficient to confer t-2-hex toxicity. However, the absence of Tom70 and Tom20 function significantly increases tolerance to t-2-hex indicating that the TOM complex is a physiologically important target of the proapoptotic lipid, which acts most likely via lipidation of more subunits than the Tom40 import channel.
(2) The authors claim that t-2-hex blocks the TOM complex. Since in vitro import assays with yeast mitochondria are a well established and simple technique, the authors should isolate mitochondria from their cells and perform import experiments. It is expected that those mitochondria show reduced import rates, however, swelling of these mitochondria to mitoplasts should suppress the import defect.
We agree that our study does not investigate a direct effect of t-2-hex on the import capacity of purified mitochondria. However, we determine the in vivo accumulation of several mitochondrial precursor proteins, which is widely used to assay for the efficiency of mitochondrial protein import, for example the recent hallmark paper discovering the mitoCPR protein import surveillance pathway exclusively uses epitope-tagged mitochondrial precursors to determine the regulation of mitochondrial protein import (Weidberg and Amon, Science 2018 360(6385)). Additionally, our new results that mutants in accessory TOM subunits 20 and 70 are hyperresistant to t-2-hex (Figure 8D) and that deletion of TOM20 decreases the t-2-hex induced pre-protein accumulation (Suppl. Figure 1) identify the TOM complex and hence protein import at the outer mitochondrial membrane as a physiologically important t-2-hex target.
(3) The first part of the study is very strong. The last figure is also of good quality, however, it is not clear whether the effects on TOM subunits are really causal for the observed t-2-hex effect on gene expression. The authors might cure this by improved data or by avoiding bold statements such as: 'Hfd1 associates with the Tom70 subunit of the TOM complex and t-2-hex covalently lipidates the central Tom40 channel, which altogether indicates that transport of mitochondrial precursor proteins through the outer mitochondrial membrane is directly inhibited by the pro-apoptotic lipid and thus represents a hotspot for pro- and anti-apoptotic signaling.' (Abstract).
We now show that several TOM and TIM subunits are lipidated in vitro by physiological low t-2-hex concentrations, that loss of function of accessory subunits Tom20 or Tom70 rescues t-2-hex toxicity (new Figure 8) and that the gene dose of Hfd1 determines the degree of mitoprotein import block (new Figure 5). These data identify the TOM complex as a physiologically important target of the pro-apoptotic lipid. The Abstract has been modified accordingly.
(4) If the t-2-hex levels are in a physiological range, one would expect that overexpression of Hfd1 prevents the t-2-hex-induced import arrest.
We have now confirmed that overexpression of Hfd1 indeed prevents inhibition of mitochondrial protein import by t-2-hex. As shown in new Figure 5, Aim17 mitochondrial import is already inhibited by t-2-hex doses as low as 10µM in a wild type strain, and that this inhibition is enhanced in a hfd1 mutant and alleviated in a Hfd1 overexpressor.
(5) The authors claim that Fmp52 is a t-2-hex-detoxifying enzyme, but do not show evidence. They should rewrite this sentence and be more cautious, or they should show that increased Fmp52 levels indeed deplete t-2-hex from mitochondria.
We show that loss of Fmp52 function leads to a strong t-2-hex sensitivity. Fmp52 belongs to the NAD-binding short-chain dehydrogenase/reductase (SDR) family and localizes to highly purified mitochondrial outer membranes (Zahedi et al, 2006). These are the indications that suggest that Fmp52 participates in the enzymatic detoxification of t-2-hex in addition to Hfd1. The Results section has been modified accordingly.
Minor points:
(6) Aim17 was recently identified as a characteristic constituent of cytosolic protein aggregates named MitoStores (Krämer et al., 2023, EMBO J). The authors might test whether the cytosolic Aim17 protein colocalizes with the Hsp104-GFP granules that accumulate upon t-2-hex exposure as shown in Fig. 4A.
We agree that determining the fate of unimported mitochondrial precursors upon t-2-hex stress would be interesting. We have made some attempts to co-visualize Aim17-dsRed and Hsp104-GFP upon t-2-hex treatment, but we still have some technical issues. While we clearly see that Aim17 accumulates in cytoplasmic foci upon prolonged t-2-hex exposure, we are not able to determine colocalization with Hsp104, in great part because t-2-hex causes mitochondrial fragmentation, which leads to the appearance of Aim17-stained foci in the cytosol independently of protein aggregates. While so far we are not able to localize Aim17 unambiguously in Hsp104 containing aggregates (mitoStores) upon lipid stress, we would like to move the manuscript farther without those experiments.
(7) In Fig. 1A, the figures of the different lines are difficult to distinguish. Lines of one color with different intensities would be better suited.
We have been working before with dose-response profiles generated by the destabilized luciferase system and found that the color-coded representation of the plots is the most effective way to represent the data, see for example Fita-Torró et al. Mol Ecol. 2023 32(13):3557-3574, Pascual-Ahuir et al. BBA 2019 1862(4):457-471, Rienzo et al., Mol Cell Biol. 2015 35(21):3669-83, and several other publications. Therefore we want to keep the format of the Figure.
(8) A title page should be added to each of the supplemental data files with short descriptions of the information that is provided in the columns of the tables. Response: Explanatory title pages have been now added to the supplemental data files.
Reviewer #3 (Recommendations For The Authors):
Figure 5A: The authors aim to assess protein import, however, their experimental set-up is not suited and does not allow conclusions about protein translocation into mitochondria. The authors monitor protein steady state levels, which does not reflect import capacity. For this e.g. pulse-chase experiments coupled to coIP or in organello import assays with radiolabeled substrate proteins would be required. In addition, the authors lack a non-treated control to show that no precursor accumulates in the absence of CCCP and t-2-hex. At the moment, the conclusion of blocked import cannot be made, as there are many other explanations for the observed steady state levels, e.g. the TAP tag interfered with the import competence of the precursor or t-2-hex could impact on MPP function (in particular as Figure 8B shows that also intra-mitochondrial proteins undergo modification by t-2-hex).
We agree that our study does not investigate a direct effect of t-2-hex on the import capacity of purified mitochondria. However, we determine the in vivo accumulation of several mitochondrial precursor proteins, which is widely used to assay for the efficiency of mitochondrial protein import, for example the recent hallmark paper discovering the mitoCPR protein import surveillance pathway exclusively uses epitope-tagged mitochondrial precursors to determine the regulation of mitochondrial protein import (Weidberg and Amon, Science 2018 360(6385)). Figure 5 contains several non-treated control experiments, which show that no (or less in the case of Ilv6) precursors of Tap-tagged Aim17, Cox5a, Ilv6, or Sdh4 accumulate in the absence of CCCP or t-2-hex. This is shown in Figure 5A for untreated cells or in Figure 5B and new Figure 5G for solvent (DMSO) treated cells. This demonstrates that the Tap-tag does not interfere with the import of the respective precursors. Additionally, our new results that mutants in accessory TOM subunits 20 and 70 are hyperresistant to t-2-hex (Figure 8D) identify the TOM complex and hence protein import at the outer mitochondrial membrane as a physiologically important t-2-hex target.
Figure 8: The conclusion that Tom40 is directly lipidated comes from an in vitro assay, with the conclusion that Tom40 is the main target, because it is the only Tom protein with a cysteine (Tom70 as not being part of the Tom core is excluded, however, lack of Tom70 function would also have detrimental consequences for mitochondrial protein import). However, there is no experiment showing a modification of Tom40 and a consequence for protein import. The proposed model is therefore very far-fetched and several aspects are speculation but not supported by experimental data. To propose such a model, the author needs to show experimental evidence, e.g. by generating a yeast strain in which the cysteine i Tom40 are replaced by e.g. Serine residues, and then assess if protein import (e.g. pulse-chase assays) are not affected anymore upon addition of t-2-hex.
Deletion of all four cysteine residues in Tom40 is not sufficient to confer resistance to t-2-hex stress. This result had been included in the original manuscript, but was somehow hidden in the Discussion. The revised manuscript now includes t-2hex tolerance assays for the Tom40 cysteine free mutant in new Figure 8D. As a result, cysteine lipidation of Tom40 alone is not sufficient to confer t-2-hex toxicity. This implies most likely other lipidation targets within the TOM and TIM complexes, as indicated by our in vitro lipidation studies. We therefore included the non-essential adaptor proteins Tom70 and Tom20 of the TOM complex and tested the tolerance of the respective deletion mutants in t-2-hex tolerance assays. As shown in new Figure 8D, the absence of Tom70 and Tom20 function significantly increases tolerance to t2-hex indicating that the TOM complex is a physiologically important target of the pro-apoptotic lipid, which acts most likely via lipidation of more subunits than the Tom40 import channel.
Figure 8A: The pulldown experiments lack positive (other Tom subunits) and negative controls and were performed with (large) tags on all proteins, which can easily result in false positive interactions. The conclusion that Hfd1 interacts with Tom70 and Tom22 cannot be made. Also, the conclusion if an interaction is robust or not cannot be made as the pull-down lacks control fractions, it is also not clear how much of the eluate was loaded. Finally, Hfd1-HA was not expressed from its endogenous promoter, likely resulting in over-expression, which again strongly hampers conclusions about bona fide interaction partners.
We agree that our pulldown studies are done in an artificial context, such as Hfd1 overexpression needed for sufficient protein level for detection or use of Tapfusion proteins. However, the conclusion that Tom70 is a potential interactor of Hfd1 can be made based on the following observations: Hfd1-HA is preferentially pulled down from total protein extracts containing Tom70-Tap, but not from extracts containing no Tap-protein and significantly less from extracts containing Tom22-Tap, another TOM associated subunit. The pulldown assay has been repeated now several times and the efficiency of Hfd1 pulldown has been quantified and statistically analyzed with respect to the quantity of purified Tom protein, which is shown in modified Figure 8A.
Figure 4A and C: Depletion of proteasomal activity results in larger aggregates in Figure 4A. However, the addition of t-2-hex blocks proteasomal activity (Figure 4C). How can proteasome inhibition result in bigger aggregates if the proteasomal activity is lost upon t-2-hex addition?
The negative effect of t-2-hex on proteasomal activity is most likely an indirect effect caused by protein aggregation (Bence et al., Science 2001 292-1552) and occurs in wild type and rpn4 mutant cells with reduced proteasomal activity (Fig. 4C). t-2-hex causes cytosolic protein aggregation in wild type cells, which is aggravated (more and larger protein aggregates) in rpn4 mutants because of their lower levels of active proteasome (Fig. 4A). The observed protein aggregates will further diminish proteasomal activity, which is confirmed in Fig. 4C.
Figure 1B: The authors use a reporter to determine HFD1 expression that consists of the promoter region of HFD1 fused to luciferase. These fusion constructs have been shown to often not reflect the bona fide expression levels of genes (Yoneda et al., J Cell Sci 2004). qPCR analysis of transcript levels should be included to support the induction of HFD1.
We agree that the live cell luciferase reporters used here are not suitable for the determination of absolute mRNA levels. However, the aim of these reporter experiments is to quantify the inducibility of different genes (HFD1, GRE2) dependent on increasing stress doses. These dose response profiles cannot be obtained by qPCR analysis, while the destabilized reporters are an excellent tool for this, which have been used to accurately describe numerous dynamic stress responses (for example: Dolz-Edo et al. 2013 MCB 33:2228-40, Rienzo et al. 2015 MCB 35:3669-83, PascualAhuir et al. 2019 BBA 862:457-471). Additionally, the induction of HFD1 mRNA levels by salt (NaCl) and oxidative (menadione) stress determined by qPCR has been published before (Manzanares-Estreder et al. 2017 Oxid Med Cell Longevity 2017:2708345).
The authors conclude from Figure 1 that entry into apoptotic cell death is modulated by efficient t-2-hex detoxification. However, this is based on growth curves and no analysis of apoptotic cell death is performed. The data show that the addition of hexadecenal results in a growth arrest, that is overcome likely upon degradation of t-2-hex (depending on the amount of Hfd1).
We agree that our experiments measure growth inhibition and not specifically apoptotic cell death. The text has been changed accordingly.
Figure 4A: Microscopy images show between 1-2 yeast cells. Either more cells need to be shown or quantifications of the aggregates are required. In addition, it is not clear if the control received the same DMSO concentration as the treated cells and also the time point for the control is not specified.
We have now quantified the number of aggregates across cell populations in new Figure 4A in DMSO, t-2-hex and t-2-hex-H2 treated wt and rpn4 mutants. These data show specific aggregate induction by t-2-hex and not by DMSO or the saturated t-2-hex-H2 control, which is aggravated in rpn4 mutants and avoided by CHX pretreatment.
Figure 5: Western blots in figure 5A, B, D, E and F lack a loading control. Without this, conclusions about increases in protein abundance cannot be made. Response: We have now included additional panels with the loading controls for the Western blots in new figure 5, except figure 5B, where the appearance or not of the pre-protein can be compared to the amount of mature protein in the same blot.
Figure 2B: Complex II assembly factors SDH5,6,9 are described here as ETC complexes. As the proteins are not part of the mature complex II, the heading should be modified into ETC complexes and ETC assembly.
Figure 2B has been revised and the classification of ETC proteins changed accordingly.
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hypothes.is hypothes.is
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Go forth and annotate!
my first annotation.
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thinkingonmusic.wordpress.com thinkingonmusic.wordpress.com
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But: HOW were those works made "authoritative" in the first place?
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www.biorxiv.org www.biorxiv.org
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Author response:
The following is the response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
Nitta et al, in their manuscript titled, "Drosophila model to clarify the pathological significance of OPA1 in autosomal dominant optic atrophy." The novelty of this paper lies in its use of human (hOPA1) to try to rescue the phenotype of an OPA1 +/- Drosophilia DOA model (dOPA). The authors then use this model to investigate the differences between dominant-negative and haploinsufficient OPA1 variants. The value of this paper lies in the study of DN/HI variants rather than the establishment of the drosophila model per se as this has existed for some time and does have some significant disadvantages compared to existing models, particularly in the extra-ocular phenotype which is common with some OPA1 variants but not in humans. I judge the findings of this paper to be valuable with regards to significance and solid with regards to the strength of the evidence.
Suggestions for improvements:
(1) Stylistically the results section appears to have significant discussion/conclusion/inferences in section with reference to existing literature. I feel that this information would be better placed in the separate discussion section. E.g. lines 149-154.
We appreciate the reviewer’s suggestion to relocate the discussion, conclusions, and inferences, particularly those that reference existing literature, to a separate discussion section. For lines 149–154, we placed them in the discussion section (lines 343–347) as follows. “Our established fly model is the first simple organism to allow observation of degeneration of the retinal axons. The mitochondria in the axons showed fragmentation of mitochondria. Former studies have observed mitochondrial fragmentation in S2 cells (McQuibban et al., 2006), muscle tissue (Deng et al., 2008), segmental nerves (Trevisan et al., 2018), and ommatidia (Yarosh et al., 2008) due to the LOF of dOPA1.”
For lines 178–181, we also placed them in the discussion section (lines 347–351) as follows. “Our study presents compelling evidence that dOPA1 knockdown instigates neuronal degeneration, characterized by a sequential deterioration at the axonal terminals and extending to the cell bodies. This degenerative pattern, commencing from the distal axons and progressing proximally towards the cell soma, aligns with the paradigm of 'dying-back' neuropathy, a phenomenon extensively documented in various neurodegenerative disorders (Wang et al., 2012). ”
For lines 213–217, 218–220, and 222–223, we also placed them in the discussion section (lines 363– 391) as follows. “To elucidate the pathophysiological implications of mutations in the OPA1 gene, we engineered and expressed several human OPA1 variants, including the 2708-2711del mutation, associated with DOA, and the I382M mutation, located in the GTPase domain and linked to DOA. We also investigated the D438V and R445H mutations in the GTPase domain and correlated with the more severe DOA plus phenotype. The 2708-2711del mutation exhibited limited detectability via HA-tag probing. Still, it was undetectable with a myc tag, likely due to a frameshift event leading to the mutation's characteristic truncated protein product, as delineated in prior studies (Zanna et al., 2008). Contrastingly, the I382M, D438V, and R445H mutations demonstrated expression levels comparable to the WT hOPA1. However, the expression of these mutants in retinal axons did not restore the dOPA1 deficiency to the same extent as the WT hOPA1, as evidenced in Figure 5E. This finding indicates a functional impairment imparted by these mutations, aligning with established understanding (Zanna et al., 2008). Notably, while the 2708-2711del and I382M mutations exhibited limited functional rescue, the D438V and R445H mutations did not show significant rescue activity. This differential rescue efficiency suggests that the former mutations, particularly the I382M, categorized as a hypomorph (Del Dotto et al., 2018), may retain partial functional capacity, indicative of a LOF effect but with residual activity. The I382M missense mutation within the GTPase domain of OPA1 has been described as a mild hypomorph or a disease modifier. Intriguingly, this mutation alone does not induce significant clinical outcomes, as evidenced by multiple studies (Schaaf et al., 2011; Bonneau et al., 2014; Bonifert et al., 2014; Carelli et al., 2015). A significant reduction in protein levels has been observed in fibroblasts originating from patients harboring the I382M mutation. However, mitochondrial volume remains unaffected, and the fusion activity of mitochondria is only minimally influenced (Kane et al., 2017; Del Dotto et al., 2018). This observation is consistent with findings reported by de la Barca et al. in Human Molecular Genetics 2020, where a targeted metabolomics approach classified I382M as a mild hypomorph. In our current study, the I382M mutation preserves more OPA1 function compared to DN mutations, as depicted in Figures 5E and F. Considering the results from our Drosophila model and previous research, we hypothesize that the I382M mutation may constitute a mild hypomorphic variant. This might explain its failure to manifest a phenotype on its own, yet its contribution to increased severity when it occurs in compound heterozygosity.
(2) I do think further investigation as to why a reduction of mitochondria was noticed in the knockdown. There are conflicting reports on this in the literature. My own experience of this is fairly uniform mitochondrial number in WT vs OPA1 variant lines but with an increased level of mitophagy presumably reflecting a greater turnover. There are a number of ways to quantify mitochondrial load e.g. mtDNA quantification, protein quantification for tom20/hsp60 or equivalent. I feel the reliance on ICC here is not enough to draw conclusions. Furthermore, mitophagy markers could be checked at the same time either at the transcript or protein level. I feel this is important as it helps validate the drosophila model as we already have a lot of experimental data about the number and function of mitochondria in OPA+/- human/mammalian cells.
We thank the reviewer for the insightful comments and suggestions regarding our study on the impact of mitochondrial reduction in a knockdown model. We concur with the reviewer’s observation that our initial results did not definitively demonstrate a decrease in the number of mitochondria in retinal axons. Furthermore, we measured mitochondrial quantity by conducting western blotting using antiCOXII and found no reduction in mitochondrial content with the knockdown of dOPA1 (Figure S4A and B). Consequently, we have revised our manuscript to remove the statement “suggesting a decreased number of mitochondria in retinal axons. However, whether this decrease is due to degradation resulting from a decline in mitochondrial quality or axonal transport failure remains unclear.” Instead, we have refocused our conclusion to reflect our electron microscopy findings, which indicate reduced mitochondrial size and structural abnormalities. The reviewer’s observation of consistent mitochondrial numbers in WT versus mutant variant lines and elevated mitophagy levels prompted us to evaluate mitochondrial turnover as a significant factor in our study. Regarding verifying mitophagy markers, we incorporated the mito-QC marker in our experimental design. In our experiments, mito-QC was expressed in the retinal axons of Drosophila to assess mitophagy activity upon dOPA1 knockdown. We observed a notable increase in mCherry positive but GFP negative puncta signals one week after eclosion, indicating the activation of mitophagy (Figure 2D–H). This outcome strongly suggests that dOPA1 knockdown enhances mitophagy in our Drosophila model. The application of mito-QC as a quantitative marker for mitophagy, validated in previous studies, offers a robust approach to analyzing this process. Our findings elucidate the role of dOPA1 in mitochondrial dynamics and its implications for neuronal health. These results have been incorporated into Figure 2, with the corresponding text updated as follows (lines 159–167): “Given that an increase in mitophagy activity has been reported in mouse RGCs and nematode ADOA models (Zaninello et al., 2022; Zaninello et al., 2020), the mitoQC marker, an established indicator of mitophagy activity, was expressed in the photoreceptors of Drosophila. The mito-QC reporter consists of a tandem mCherry-GFP tag that localizes to the outer membrane of mitochondria (Lee et al., 2018). This construct allows the measurement of mitophagy by detecting an increase in the red-only mCherry signal when the GFP is degraded after mitochondria are transported to lysosomes. Post dOPA1 knockdown, we observed a significant elevation in mCherry positive and GFP negative puncta signals at one week, demonstrating an activation of mitophagy as a consequence of dOPA1 knockdown (Figure 2D–H).”
(3) Could the authors comment on the failure of the dOPA1 rescue to return their biomarker, axonal number to control levels. In Figure 4D is there significance between the control and rescue. Presumably so as there is between the mutant and rescue and the difference looks less.
As the reviewer correctly pointed out, there is a significant difference between the control and rescue groups, which we have now included in the figure. Additionally, we have incorporated the following comments in the discussion section (lines 329–342) regarding this significant difference: “In our study, expressing dOPA1 in the retinal axons of dOPA1 mutants resulted in significant rescue, but it did not return to control levels. There are three possible explanations for this result. The first concerns gene expression levels. The Gal4-line used for the rescue experiments may not replicate the expression levels or timing of endogenous dOPA1. Considering that the optimal functionality of dOPA1 may be contingent upon specific gene expression levels, attaining a wild-type-like state necessitates the precise regulation of these expression levels. The second is a nonautonomous issue. Although dOPA1 gene expression was induced in the retinal axons for the rescue experiments, many retinal axons were homozygous mutants, while other cell types were heterozygous for the dOPA1 mutation. If there is a non-autonomous effect of dOPA1 in cells other than retinal axons, it might not be possible to restore the wild-type-like state fully. The third potential issue is that only one isoform of dOPA1 was expressed. In mouse OPA1, to completely restore mitochondrial network shape, an appropriate balance of at least two different isoforms, lOPA1 and s-OPA1, is required (Del Dotto et al., 2017). This requirement implies that multiple isoforms of dOPA1 are essential for the dynamic activities of mitochondria.”
(4) The authors have chosen an interesting if complicated missense variant to study, namely the I382M with several studies showing this is insufficient to cause disease in isolation and appears in high frequency on gnomAD but appears to worsen the phenotype when it appears as a compound het. I think this is worth discussing in the context of the results, particularly with regard to the ability for this variant to partially rescue the dOPA1 model as shown in Figure 5.
As the reviewer pointed out, the I382M mutation is known to act as a disease modifier. However, in our system, as suggested by Figure 5, I382M appears to retain more activity than DN mutations. Considering previous studies, we propose that I382M represents a mild hypomorph. Consequently, while I382M alone may not exhibit a phenotype, it could exacerbate severity in a compound heterozygous state. We have incorporated this perspective in our revised discussion (lines 375-391).
“Notably, while the 2708-2711del and I382M mutations exhibited limited functional rescue, the D438V and R445H mutations did not show significant rescue activity. This differential rescue efficiency suggests that the former mutations, particularly the I382M, categorized as a hypomorph (Del Dotto et al., 2018), may retain partial functional capacity, indicative of a LOF effect but with residual activity. The I382M missense mutation within the GTPase domain of OPA1 has been described as a mild hypomorph or a disease modifier. Intriguingly, this mutation alone does no induce significant clinical outcomes, as evidenced by multiple studies (Schaaf et al., 2011; Bonneau et al., 2014; Bonifert et al., 2014; Carelli et al., 2015). A significant reduction in protein levels has been observed in fibroblasts originating from patients harboring the I382M mutation. However, mitochondrial volume remains unaffected, and the fusion activity of mitochondria is only minimally influenced (Kane et al., 2017; Del Dotto et al., 2018). This observation is consistent with findings reported by de la Barca et al. in Human Molecular Genetics 2020, where a targeted metabolomics approach classified I382M as a mild hypomorph. In our current study, the I382M mutation preserves more OPA1 function compared to DN mutations, as depicted in Figures 5E and F. Considering the results from our Drosophila model and previous research, we hypothesize that the I382M mutation may constitute a mild hypomorphic variant. This might explain its failure to manifest a phenotype on its own, yet its contribution to increased severity when it occurs in compound heterozygosity.”
(5) I feel the main limitation of this paper is the reliance on axonal number as a biomarker for OPA1 function and ultimately rescue. I have concerns because a) this is not a well validated biomarker within the context of OPA1 variants b) we have little understanding of how this is affected by over/under expression and c) if it is a threshold effect e.g. once OPA1 levels reach <x% pathology develops but develops normally when opa1 expression is >x%. I think this is particularly relevant when the authors are using this model to make conclusions on dominant negativity/HI with the authors proposing that if expression of a hOPA1 transcript does not increase opa1 expression in a dOPA1 KO then this means that the variant is DN. The authors have used other biomarkers in parts of this manuscript e.g. ROS measurement and mito trafficking but I feel this would benefit from something else particularly in the latter experiments demonstrated in figure 5 and 6.
The reviewer raised concerns regarding the adequacy of axonal count as a validated biomarker in the context of OPA1 mutants. In response, we corroborated its validity using markers such as MitoSOX, Atg8, and COXII. Experiments employing MitoSOX revealed that the augmented ROS signals resulting from dOPA1 knockdown were mitigated by expressing human OPA1. Conversely, the mutant variants 2708-2711del, D438V, and R445H did not ameliorate these effects, paralleling the phenotype of axonal degeneration observed. These findings are documented in Figure 5F, and we have incorporated the following text into section lines 248–254 of the results:
“Furthermore, we assessed the potential for rescuing ROS signals. Similar to its effect on axonal degeneration, wild-type hOPA1 effectively mitigated the phenotype, whereas the 2708-2711del, D438V, and R445H mutants did not (Figure 5F). Importantly, the I382M variant also reduced ROS levels comparably to the wild type. These findings demonstrate that both axonal degeneration and the increase in ROS caused by dOPA1 downregulation can be effectively counteracted by hOPA1. Although I382M retains partial functionality, it acts as a relatively weak hypomorph in this experimental setup.”
Moreover, utilizing mito-QC, we observed elevated mitophagy in our Drosophila model, with these results now included in Figure 2D–H. Given the complexity of the genetics involved and the challenges in establishing lines, autophagy activity was quantified by comparing the ratio of Atg8-1 to Atg8-2 via Western blot analysis. However, no significant alterations were detected across any of the genotypes. Additionally, mitochondrial protein levels derived from COXII confirmed consistent mitochondrial quantities, showing no considerable variance following knockdown. These insights affirm that retinal axon degeneration and mitophagy activation are present in the Drosophila DOA model, although the Western blot analysis revealed no significant changes in autophagy activation. Such findings necessitate caution as this model may not fully replicate the molecular pathology of the corresponding human disease. These Western blot findings are presented in Figure S4, with the following addition made to section lines 255–263 of the results:
“We also conducted Western blot analyses using anti-COXII and anti-Atg8a antibodies to assess changes in mitochondrial quantity and autophagy activity following the knockdown of dOPA1. Mitochondrial protein levels, indicated by COXII quantification, were evaluated to verify mitochondrial content, and the ratio of Atg8a-1 to Atg8a-2 was used to measure autophagy activation. For these experiments, Tub-Gal4 was employed to systemically knockdown dOPA1. Considering the lethality of a whole-body dOPA1 knockdown, Tub-Gal80TS was utilized to repress the knockdown until eclosion by maintaining the flies at 20°C. After eclosion, we increased the temperature to 29°C for two weeks to induce the knockdown or expression of hOPA1 variants. The results revealed no significant differences across the genotypes tested (Figure S4A–D).”
In assessing the effects of dominant negative mutations, measurements including ROS levels, the ratio of Atg8-1 to Atg8-2, and the quantity of COXII protein were conducted, yet no significant differences were observed (Figure S6). This limitation of the fly model is mentioned in the results, noting the observation of the axonal degeneration phenotype but not alterations in ROS signaling, autophagy activity, or mitochondrial quantity as follows (line 287–290):
“We investigated the impacts of dominant negative mutations on mitochondrial oxidation levels, mitochondrial quantity, and autophagy activation levels; however, none of these parameters showed statistical significance (Figure S6).”
The reviewer also inquired about the effects of overexpressing and underexpressing OPA1 on axonal count and whether these effects are subject to a threshold. In response, we expressed both wild-type and variant forms of human OPA1 in Drosophila in vivo and assessed their protein levels using Western blot analysis. The results showed no significant differences in expression levels between the wild-type and variant forms in the OPA1 overexpression experiments, suggesting the absence of a variation threshold effect. These findings have been newly documented as quantitative data in Figure 5C. Furthermore, we have included a statement in the results section for Figure 6A, clarifying that overexpression of hOPA1 exhibited no discernible impact, as detailed on lines 274–276.
“The results presented in Figure 5C indicate that there are no significant differences in the expression levels among the variants, suggesting that variations in expression levels do not influence the outcomes.”
(6) Could the authors clarify what exons in Figure 5 are included in their transcript. My understanding is transcript NM_015560.3 contains exon 4,4b but not 5b. According to Song 2007 this transcript produces invariably s-OPA1 as it contains the exon 4b cleavage site. If this is true, this is a critical limitation in this study and in my opinion significantly undermines the likelihood of the proposed explanation of the findings presented in Figure 6. The primarily functional location of OPA1 is at the IMM and l-OPA1 is the primary opa1 isoform probably only that localizes here as the additional AA act as a IMM anchor. Given this is where GTPase likely oligomerizes the expression of s-OPA1 only is unlikely to interact anyway with native protein. I am not aware of any evidence s-OPA1 is involved in oligomerization. Therefore I don't think this method and specifically expression of a hOPA1 transcript which only makes s-OPA1 to be a reliable indicator of dominant negativity/interference with WT protein function. This could be checked by blotting UAS-hOPA1 protein with a OPA1 antibody specific to human OPA1 only and not to dOPA1. There are several available on the market and if the authors see only s-OPA1 then it confirms they are not expressing l-OPA1 with their hOPA1 construct.
As suggested by the reviewer, we performed a Western blot using a human OPA1 antibody to determine if the expressed hOPA1 was producing the l-OPA1 isoform, as shown in band 2 of Figure 5D. The results confirmed the presence of both l-OPA1 and what appears to be s-OPA1 in bands 2 and 4, respectively. These findings are documented in the updated Figure 5D, with a detailed description provided in the manuscript at lines 224-226. Additionally, the NM_015560.3 refers to isoform 1, which includes only exons 4 and 5, excluding exons 4b and 5b. This isoform can express both l-OPA1 and s-OPA1 (refer to Figure 1 in Song et al., J Cell Biol. 2007). We have updated the schematic diagram in the figure to include these exons. The formation of s-OPA1 through cleavage occurs at the OMA1 target site located in exon 5 and the Yme1L target site in exon 5b of OPA1. Isoform 1 of OPA1 is prone to cleavage by OMA1, but a homologous gene for OMA1 does not exist in Drosophila. Although a homologous gene for Yme1L is present in Drosophila, exon 5b is missing in isoform 1 of OPA1, leaving the origin of the smaller band resembling s-OPA1 unclear at this point.
Reviewer #2 (Public Review):
The data presented support and extend some previously published data using Drosophila as a model to unravel the cellular and genetic basis of human Autosomal dominant optic atrophy (DOA). In human, mutations in OPA1, a mitochondrial dynamin like GTPase (amongst others), are the most common cause for DOA. By using a Drosophila loss-of-function mutations, RNAi- mediated knockdown and overexpression, the authors could recapitulate some aspects of the disease phenotype, which could be rescued by the wild-type version of the human gene. Their assays allowed them to distinguish between mutations causing human DOA, affecting the optic system and supposed to be loss-of-function mutations, and those mutations supposed to act as dominant negative, resulting in DOA plus, in which other tissues/organs are affected as well. Based on the lack of information in the Materials and Methods section and in several figure legends, it was not in all cases possible to follow the conclusions of the authors.
We appreciate the reviewer's constructive feedback and the emphasis on enhancing clarity in our manuscript. We recognize the concerns raised about the lack of detailed information in the Materials and Methods section and several figure legends, which may have obscured our conclusions. In response, we have appended the detailed genotypes of the Drosophila strains used in each experiment to a supplementary table. Additionally, we realized that the description of 'immunohistochemistry and imaging' was too brief, previously referenced simply as “immunohistochemistry was performed as described previously (Sugie et al., 2017).” We have now expanded this section to include comprehensive methodological details. Furthermore, we have revised the figure legends to provide clearer and more thorough descriptions.
Similarly, how the knowledge gained could help to "inform early treatment decisions in patients with mutations in hOPA1" (line 38) cannot be followed.
To address the reviewer's comments, we have refined our explanation of the clinical relevance of our findings as follows. We believe this revision succinctly articulates the practical application of our research, directly responding to the reviewer’s concerns about linking the study's outcomes to treatment decisions for patients with hOPA1 mutations. By underscoring the model’s value in differential diagnosis and its influence on initiating treatment strategies, we have clarified this connection explicitly, within the constraints of the abstract’s word limit. The revised sentence now reads: "This fly model aids in distinguishing DOA from DOA plus and guides initial hOPA1 mutation treatment strategies."
Reviewer #3 (Public Review):
Nitta et al. establish a fly model of autosomal dominant optic atrophy, of which hundreds of different OPA1 mutations are the cause with wide phenotypic variance. It has long been hypothesized that missense OPA1 mutations affecting the GTPase domain, which are associated with more severe optic atrophy and extra-ophthalmic neurologic conditions such as sensorineural hearing loss (DOA plus), impart their effects through a dominant negative mechanism, but no clear direct evidence for this exists particularly in an animal model. The authors execute a well-designed study to establish their model, demonstrating a clear mitochondrial phenotype with multiple clinical analogs including optic atrophy measured as axonal degeneration. They then show that hOPA1 mitigates optic atrophy with the same efficacy as dOPA1, setting up the utility of their model to test disease-causing hOPA1 variants. Finally, they leverage this model to provide the first direct evidence for a dominant negative mechanism for 2 mutations causing DOA plus by expressing these variants in the background of a full hOPA1 complement.
Strengths of the paper include well-motivated objectives and hypotheses, overall solid design and execution, and a generally clear and thorough interpretation of their results. The results technically support their primary conclusions with caveats. The first is that both dOPA1 and hOPA1 fail to fully restore optic axonal integrity, yet the authors fail to acknowledge that this only constitutes a partial rescue, nor do they discuss how this fact might influence our interpretation of their subsequent results.
As the reviewer rightly points out, neither dOPA1 nor hOPA1 achieve a complete recovery. Therefore, we acknowledge that this represents only a partial rescue and have added the following explanations regarding this partial rescue in the results and discussion sections.
Result:
Significantly —> partially (lines 207 and 228) Discussion (lines 329–342):
In our study, expressing dOPA1 in the retinal axons of dOPA1 mutants resulted in significant rescue, but it did not return to control levels. There are three possible explanations for this result. The first concerns gene expression levels. The Gal4-line used for the rescue experiments may not replicate the expression levels or timing of endogenous dOPA1. Considering that the optimal functionality of dOPA1 may be contingent upon specific gene expression levels, attaining a wild-type-like state necessitates the precise regulation of these expression levels. The second is a non-autonomous issue. Although dOPA1 gene expression was induced in the retinal axons for the rescue experiments, many retinal axons were homozygous mutants, while other cell types were heterozygous for the dOPA1 mutation. If there is a non-autonomous effect of dOPA1 in cells other than retinal axons, it might not be possible to restore the wild-type-like state fully. The third potential issue is that only one isoform of dOPA1 was expressed. In mouse OPA1, to completely restore mitochondrial network shape, an appropriate balance of at least two different isoforms, l-OPA1 and s-OPA1, is required (Del Dotto et al., 2017). This requirement implies that multiple isoforms of dOPA1 are essential for the dynamic activities of mitochondria.
The second caveat is that their effect sizes are small. Statistically, the results indeed support a dominant negative effect of DOA plus-associated variants, yet the data show a marginal impact on axonal degeneration for these variants. The authors might have considered exploring the impact of these variants on other mitochondrial outcome measures they established earlier on. They might also consider providing some functional context for this marginal difference in axonal optic nerve degeneration.
In response to the reviewer’s comment regarding the modest effect sizes observed, we acknowledge that the magnitude of the reported changes is indeed small. To explore the impact of these variants on additional mitochondrial outcomes as suggested, we employed markers such as MitoSOX, Atg8, and COXII for validation. However, we could not detect any significant effects of the DOA plus-associated variants using these methods. We apologize for the redundancy, but to address Reviewer #1's fifth question, we present experimental results showing that while the increased ROS signals observed upon dOPA1 knockdown were rescued by expressing human OPA1, the mutant variants 2708-2711del, D438V, and R445H did not ameliorate this effect. This outcome mirrors the axonal degeneration phenotype and is documented in Figure 5F. The following text has been added to the results section lines 248–254:
“Furthermore, we assessed the potential for rescuing ROS signals. Similar to its effect on axonal degeneration, wild-type hOPA1 effectively mitigated the phenotype, whereas the 2708-2711del, D438V, and R445H mutants did not (Figure 5F). Importantly, the I382M variant also reduced ROS levels comparably to the wild type. These findings demonstrate that both axonal degeneration and the increase in ROS caused by dOPA1 downregulation can be effectively counteracted by hOPA1. Although I382M retains partial functionality, it acts as a relatively weak hypomorph in this experimental setup.”
Moreover, utilizing mito-QC, we observed elevated mitophagy in our Drosophila model, with these results now included in Figure 2D–H. Given the complexity of the genetics involved and the challenges in establishing lines, autophagy activity was quantified by comparing the ratio of Atg8-1 to Atg8-2 via Western blot analysis. However, no significant alterations were detected across any of the genotypes. Additionally, mitochondrial protein levels derived from COXII confirmed consistent mitochondrial quantities, showing no considerable variance following knockdown. These insights affirm that retinal axon degeneration and mitophagy activation are present in the Drosophila DOA model, although the Western blot analysis revealed no significant changes in autophagy activation. Such findings necessitate caution as this model may not fully replicate the molecular pathology of the corresponding human disease. These Western blot findings are presented in Figure S4, with the following addition made to section lines 255–263 of the results:
“We also conducted Western blot analyses using anti-COXII and anti-Atg8a antibodies to assess changes in mitochondrial quantity and autophagy activity following the knockdown of dOPA1. Mitochondrial protein levels, indicated by COXII quantification, were evaluated to verify mitochondrial content, and the ratio of Atg8a-1 to Atg8a-2 was used to measure autophagy activation. For these experiments, Tub-Gal4 was employed to systemically knockdown dOPA1. Considering the lethality of a whole-body dOPA1 knockdown, Tub-Gal80TS was utilized to repress the knockdown until eclosion by maintaining the flies at 20°C. After eclosion, we increased the temperature to 29°C for two weeks to induce the knockdown or expression of hOPA1 variants. The results revealed no significant differences across the genotypes tested (Figure S4A–D).”
In assessing the effects of dominant negative mutations, measurements including ROS levels, the ratio of Atg8-1 to Atg8-2, and the quantity of COXII protein were conducted, yet no significant differences were observed (Figure S6). This limitation of the fly model is mentioned in the results, noting the observation of the axonal degeneration phenotype but not alterations in ROS signaling, autophagy activity, or mitochondrial quantity as follows (line 287–290):
“We investigated the impacts of dominant negative mutations on mitochondrial oxidation levels, mitochondrial quantity, and autophagy activation levels; however, none of these parameters showed statistical significance (Figure S6).”
Despite these caveats, the authors provide the first animal model of DOA that also allows for rapid assessment and mechanistic testing of suspected OPA1 variants. The impact of this work in providing the first direct evidence of a dominant negative mechanism is under-stated considering how important this question is in development of genetic treatments for DOA. The authors discuss important points regarding the potential utility of this model in clinical science. Comments on the potential use of this model to investigate variants of unknown significance in clinical diagnosis requires further discussion of whether there is indeed precedent for this in other genetic conditions (since the model is nevertheless so evolutionarily removed from humans).
As suggested by the reviewer, we have expanded the discussion in our study to emphasize in greater detail the significance of the fruit fly model and the MeDUsA software we have developed, elaborating on the model's potential applications in clinical science and its precedents in other genetic disorders. Our text is as follows (lines 299–318):
“We have previously utilized MeDUsA to quantify axonal degeneration, applying this methodology extensively to various neurological disorders. The robust adaptability of this experimental system is demonstrated by its application in exploring a wide spectrum of genetic mutations associated with neurological conditions, highlighting its broad utility in neurogenetic research. We identified a novel de novo variant in Spliceosome Associated Factor 1, Recruiter of U4/U6.U5 Tri-SnRNP (SART1). The patient, born at 37 weeks with a birth weight of 2934g, exhibited significant developmental delays, including an inability to support head movement at 7 months, reliance on tube feeding, unresponsiveness to visual stimuli, and development of infantile spasms with hypsarrhythmia, as evidenced by EEG findings. Profound hearing loss and brain atrophy were confirmed through MRI imaging. To assess the functional impact of this novel human gene variant, we engineered transgenic Drosophila lines expressing both wild type and mutant SART1 under the control of a UAS promoter.
Our MeDUsA analysis suggested that the variant may confer a gain-of-toxic-function (Nitta et al., 2023). Moreover, we identified heterozygous loss-of-function mutations in DHX9 as potentially causative for a newly characterized neurodevelopmental disorder. We further investigated the pathogenic potential of a novel heterozygous de novo missense mutation in DHX9 in a patient presenting with short stature, intellectual disability, and myocardial compaction. Our findings indicated a loss of function in the G414R and R1052Q variants of DHX9 (Yamada et al., 2023). This experimental framework has been instrumental in elucidating the impact of gene mutations, enhancing our ability to diagnose how novel variants influence gene function.”
Recommendations for the Authors:
Reviewer #1 (Recommendations For The Authors):
Overall I enjoyed reading this paper. It is well presented and represents a significant amount of well executed study. I feel it further characterizes a poorly understood model of OPA1 variants and one which displays significant differences with the human phenotype. However I feel the use of this model with the author's experiments are not enough to validate this model/experiment as a screening tool for dominant negativity. I have therefore suggested the above experiments as a way to both further validate the mitochondrial dysfunction in this model and to ensure that the expressed transcript is able affect oligomerization as this is a pre-requisite to the authors conclusions.
We assessed the extent to which our model reflects mitochondrial dysfunction using COXII, Atg8, and MitoSOX markers. Unfortunately, neither COXII levels nor the ratio of Atg8a-1 to Atg8a-2 showed significant variations across genotypes that would clarify the impact of dominant negative mutations. Nonetheless, MitoSOX and mito-QC results revealed that mitochondrial ROS levels and mitophagy are increased in Drosophila following intrinsic knockdown of dOPA1. These findings are documented in Figures 2, 5, and S6.
Regarding oligomer formation, the specifics remain elusive in this study. However, the expression of dOPA1K273A, identified as a dominant negative variant in Drosophila, significantly disrupted retinal axon organization, as detailed in Figure S7. From these observations, we hypothesize that oligomerization of wild-type and dominant negative forms in Drosophila results in axonal degeneration. Conversely, co-expression of Drosophila wild-type with human dominant negative forms does not induce degeneration, suggesting that they likely do not interact.
Reviewer #2 (Recommendations For The Authors):
Materials and Methods:
The authors used GMR-Gal4 to express OPA1-RNAi. I) GMR is expressed in most cells in the developing eye behind the morphogenetic furrow. So the defects observed can be due to knock- down in support cells rather than in photoreceptor cells.
We have added the following sentences in the result (lines 194–196)."The GMR-Gal4 driver does not exclusively target Gal4 expression to photoreceptor cells. Consequently, the observed retinal axonal degeneration could potentially be secondary to abnormalities in support cells external to the photoreceptors.”
OPA1-RNAi: how complete is the knock-down? Have the authors tested more than one RNAi line?
We conducted experiments with an additional RNAi line, and similarly observed degeneration in the retinal axons (Figure S2 A and B; lines 178–179).
The loss-of-function allele, induced by a P-element insertion, gives several eye phenotypes when heterozygous (Yarosh et al., 2008). Does RNAi expression lead to the same phenotypes?
A previous report indicated that the compound eyes of homozygous mutations of dOPA1 displayed a glossy eye phenotype (Yarosh et al., 2008). Upon knocking down dOPA1 using the GMR-Gal4 driver, we also observed a glossy eye-like rough eye phenotype in the compound eyes. These findings have been added to Figure S3 and lines 192–194.
There is no description on the way the somatic clones were generated. How were mutant cells in clones distinguished from wild-type cells (e. g. in Fig. 4).
In the Methods section, we described the procedure for generating clones and their genotypes as follows (lines 502–505): "The dOPA1 clone analysis was performed by inducing flippase expression in the eyes using either ey-Gal4 with UAS-flp or ey3.5-flp, followed by recombination at the chromosomal location FRT42D to generate a mosaic of cells homozygous for dOPA1s3475." Furthermore, we have created a table detailing these genotypes. In these experiments, it was not possible to differentiate between the clone and WT cells. Accordingly, we have noted in the Results section (lines 201–203): "Note that the mutant clone analysis was conducted in a context where mutant and heterozygous cells coexist as a mosaic, and it was not possible to distinguish between them.”
Why were flies kept at 29{degree sign}C? this is rather unusual.
Increased temperature was demonstrated to induce elevated expression of GAL4 (Kramer and Staveley, Genet. Mol. Res., 2003), which in turn led to an enhanced expression of the target genes. Therefore, experiments involving knockdown assays or Western blotting to detect human OPA1 protein were exclusively conducted at 29°C. However, all other experiments were performed at 25°C, as described in the methods sections: “Flies were maintained at 25°C on standard fly food. For knockdown experiments (Figures 1C–E, 1F–H, 2A–H, 3B–K, 5F, S1, S2 A and B, and S6A), flies were kept at 29°C in darkness.” Furthermore, “We regulated protein expression temporally across the whole body using the Tub-Gal4 and Tub-GAL80TS system. Flies harboring each hOPA1 variant were maintained at a permissive temperature of 20°C, and upon emergence, females were transferred to a restrictive temperature of 29°C for subsequent experiments.”
Legends:
It would be helpful to have a description of the genotypes of the flies used in the different experiments. This could also be included as a table.
We have created a table detailing the genotypes. Additionally, in the legend, we have included a note to consult the supplementary table for genotypes.
Results:
Line 141: It is not clear what they mean by "degradation", is it axonal degeneration? And if so, what is the argument for this here?
In the manuscript, we addressed the potential for mitochondrial degradation; however, recognizing that the expression was ambiguous, the following sentence has been omitted: "Nevertheless, the degradation resulting from mitochondrial fragmentation may have decreased the mitochondrial signal.”
Fig. 2: Axons of which photoreceptors are shown?
We have added "a set of the R7/8 retinal axons" to the legend of Figure 2.
Line 167: The authors write that axonal degeneration is more severe after seven days than after eclosion. Is this effect light-dependent? The same question concerns the disappearance of the rhabdomere (Fig. 3G–J).
We conducted the experiments in darkness, ensuring that the observed degeneration is not light- dependent. This condition has been added to the methods section to clarify the experimental conditions.
Line 178/179: Based on what results do they conclude that there is degeneration of the "terminals" of the axons?
Quantification via MeDUsA has enabled us to count the number of axonal terminals, and a noted decrease has led us to conclude axonal terminal degeneration. We have published two papers on these findings. We have added the following description to the results section to clarify how we defined degeneration (lines 174–176): "We have assessed the extent of their reduction from the total axonal terminal count, thereby determining the degree of axonal terminal degeneration (Richard JNS 2022; Nitta HMG 2023).
Line 189: They write: ".. we observed dOPA1 mutant axons...". How did they distinguish es mutant from the controls?
Fig. 5 and Fig. 6: How did they distinguish genetically mutant cells from genetically control cells in the somatic clones?
Mutant clone analysis was conducted in a context where mutant and heterozygous cells coexist as a mosaic, and it was not possible to distinguish between them. Accordingly, this point has been added to lines 201–203, “Note that the mutant clone analysis was conducted in a context where mutant and heterozygous cells coexist as a mosaic, and it was not possible to distinguish between them.” and the text in the results section has been modified as follows:
(Before “To determine if dOPA1 is responsible for axon neurodegeneration, we observed the dOPA1 mutant axons by expressing full- length versions of dOPA1 in the photoreceptors at one day after eclosion and found that dOPA1 expression significantly rescued the axonal degeneration” —>
(After “To determine if dOPA1 is responsible for axon neurodegeneration, we quantify the number of the axons in the dOPA1 eye clone fly with the expression of dOPA1 at one day after eclosion and found that dOPA1 expression partially rescued the axonal degeneration”
Line 225/226: It is not clear to me how their approach "can quantitatively measure the degree of LOF".
To address the reviewer's question and clarify how our approach quantitatively measures the degree of loss of function (LOF), we revised the statement (lines 238–247):
"Our methodology distinctively facilitates the quantitative evaluation of LOF severity by comparing the rescue capabilities of various mutations. Notably, the 2708-2711del and I382M mutations demonstrated only partial rescue, indicative of a hypomorphic effect with residual activity. In contrast, the D438V and R445H mutations failed to show significant rescue, suggesting a more profound LOF. The correlation between the partial rescue by the 2708-2711del and I382M mutations and their classification as hypomorphic is significant. Moreover, the observed differences in rescue efficacy correspond to the clinical severities associated with these mutations, namely in DOA and DOA plus disorders. Thus, our results substantiate the model’s ability to quantitatively discriminate among mutations based on their impact on protein functionality, providing an insightful measure of LOF magnitude.”
Discussion:
Line 251, 252 and line 358: What is "the optic nerve" in the adult Drosophila?
In humans, the axons of retinal ganglion cells (RGCs) are referred to as the optic nerve, and we posit that the retinal axons in flies are similar to this structure. In the introduction section, where it is described that the visual systems of flies and humans bear resemblance, we have appended the following definition (lines 107–108): “In this study, we defined the retinal axons of Drosophila as analogous to the human optic nerve.”
Line 344: These bands appear only upon overexpression of the hOPA1 constructs, so this part of the is very speculative.
Confirmation was achieved using anti-hOPA1, demonstrating that myc is not nonspecific. These results have been added to Figure 5D. Furthermore, the phrase “The upper band was expected as” has been revised to “From a size perspective, the upper band was inferred to represent the full-length hOPA1 including the mitochondria import sequence (MIS).” (lines 464–465)
I was missing a discussion about the increase of ROS upon loss/reduction of dOPA1 observed by others and described here. Is there an increase of ROS upon expression of any of the constructs used?
We demonstrated that not only axonal degeneration but also ROS can be suppressed by expressing human OPA1 in the genetic background of dOPA1 knockdown. Additionally, rescue was not possible with any variants except for I382M. Furthermore, we assessed whether there were changes in ROS in the evaluation of dominant negatives, but no significant differences were observed in this experimental system. These findings have been added to the discussion section as follows (lines 318–328). “Our research established that dOPA1 knockdown precipitates axonal degeneration and elevates ROS signals in retinal axons. Expression of human OPA1 within this context effectively mitigated both phenomena; it partially reversed axonal degeneration and nearly completely normalized ROS levels. These results imply that factors other than increased ROS may drive the axonal degeneration observed post-knockdown. Furthermore, while differences between the impacts of DN mutations and loss-of- function mutations were evident in axonal degeneration, they were less apparent when using ROS as a biomarker. The extensive use of transgenes in our experiments might have mitigated the knockdown effects. In a systemic dOPA1 knockdown, assessments of mitochondrial quantity and autophagy activity revealed no significant changes, suggesting that the cellular consequences of reduced OPA1 expression might vary across different cell types.”
Reviewer #3 (Recommendations For The Authors):
Consider being more explicit regarding literature that has or has failed to test a direct dominant negative effect by expressing a variant in question in the background of a full OPA1 complement. My understanding is that this is the first direct evidence of this widely held hypothesis. This lends to the main claim promoting the utility of fly as a model in general. The authors might also outline this in the introduction as a knowledge gap they fill through this study.
In the introduction, we have incorporated a passage that highlights precedents capable of distinguishing between LOF and DN effects, and we note the absence of models capable of dissecting these distinctions within an in vivo organism. This study aims to address this gap, proposing a model that elucidates the differential impacts of LOF and DN within the context of a living model organism, thereby contributing to a deeper understanding of their roles in disease pathology. We added the following sentences in the introduction (lines 71–80).
“In the quest to differentiate between LOF and DN effects within the context of genetic mutations, precedents exist in simpler systems such as yeast and human fibroblasts. These models have provided valuable insights into the conserved functions of OPA1 across species, as evidenced by studies in yeast models (Del Dotto et al., 2018) and fibroblasts derived from patients harboring OPA1 mutations (Kane et al., 2017). However, the ability to distinguish between LOF and DN effects in an in vivo model organism, particularly at the structural level of retinal axon degeneration, has remained elusive. This gap underscores the necessity for a more complex model that not only facilitates molecular analysis but also enables the examination of structural changes in axons and mitochondria, akin to those observed in the actual disease state.”
The authors should clarify the language used in the abstract and introduction on the effect of hOPA1 DOA and DOA plus on the dOPA1- phenotype. Currently written as "none of the previously reports mutations known to cause DOA or DOA plus were rescued, their functions seems to be impaired." but presumably the authors mean that these variants failed to rescue to the dOPA1 deficient phenotype.
We thank the reviewer for the constructive feedback. We acknowledge the need for clarity in our description of the effects of hOPA1 DOA and DOA plus mutations on the dOPA1- phenotype in both the abstract and the introduction. The current phrasing, "none of the previously reported mutations known to cause DOA or DOA plus were rescued, their functions seem to be impaired," may indeed be confusing. To address your concern, we have revised this statement to more accurately reflect our findings: "Previously reported mutations failed to rescue the dOPA1 deficiency phenotype." For Abstract site, we have changed as following. "we could not rescue any previously reported mutations known to cause either DOA or DOA plus.”→ “mutations previously identified did not ameliorate the dOPA1 deficiency phenotype.”
DOA plus is associated with a multiple sclerosis-like illness; as written it suggests that the pathogenesis of sporadic multiple sclerosis and that associated with DOA plus share and underlying pathogenic mechanism. Please use the qualifier "-like illness."
We have added the term “multiple sclerosis-like illness” wherever “multiple sclerosis” is mentioned.
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Referee #3
Evidence, reproducibility and clarity
Summary:
Parkin, a E3 ubiquitin ligase, is involved in the clearance of damaged mitochondrial via mitophagy. Upon mitochondrial damage, the activated Parkin ubiquitinates many mitochondrial substrates, leading to the recruitment of mitophagy effectors. However, the mechanism of substrate recognition by Parkin is still not known.
In this manuscript, Koszela et al. utilized diverse biochemical assays and biophysical approaches, combined with AlphaFold prediction, to identify a conserved region in the flexible linker between the Ubl and RING0 domains of Parkin that recognizes mitochondrial GTPase Miro1 via a stretch of hydrophobic residues and is critical for its ubiquitination activity on Miro1. This manuscript reveals the mechanisms by which Parkin recognizes and ubiquitinates substrate Miro1, providing a biochemical explanation for the presence of Parkin at the mitochondrial membrane prior to activation by mitochondrial damage. This study also provides insights into mitochondrial homeostasis and may facilitate new therapeutic approaches for Parkinson's disease.
Major Comments:
- The authors should expand the background introduction to include the biological function of Miro1, the domain architecture of Miro1 and more context of Miro1 K572 ubiquitination in mitophagy.
- Figure 1B is confusing. Due to the presence of various bands, it is hard to assign specific bands in each lane. In addition, there are various unlabeled bands that makes things unclear. The authors should include loading controls to clearly discern pParkin, Ube1, Ube2L3, and all substrates.
- In Figure 1B, it was not possible to identify the ubiquitination bands of E2 enzyme UBE2L3 and the E1 enzyme UBE1. Please indicate these bands on the gel.
- Since ubiquitinated Miro1 and Mfn1 are similar in molecular weight (Fig. 1b), the authors should show a western blot against the Miro1 and Mfn1 tag as done in the supplementary information, At least for the competition assays involving both Miro1 and Mfn1.
- The conclusion that Miro1 is pParkin's preferred substrate is not convincing. In the competition assay used to show substrate preference, Miro1 is at a five-fold higher concentration than the other substrates and 25-fold higher than FANCI/D2. This would ultimately drive pParkin's interaction with Miro1. This is further highlighted by the fact that it adding Mfn1 in excess has a similar effect. The competition assay should be done at equimolar concentrations of Miro1 and substrate. More convincing would be a competition assay where substrate ubiquitination is quantified at several different concentrations of Miro1.
- In Figure 1F, it is unclear what is defined as "high" or "low" ubiquitination levels statistically. Some of the changes in ubiquitination levels are extremely subtle (ex. mitoNEET and FancI/D2 in the presence and absence of Miro1 and Mfn1). In some cases, I find it extremely difficult to tell if there is any change in the ubiquitination levels when comparing lanes containing excess of different substrates. I would like to see band quantifications of this experiment in triplicate to support the conclusions drawn from the competition assay.
- The authors used both unmodified and phosphorylated Parkin for the crosslinking experiments and observe no difference in the intensity of the bands. However, this is not sufficient to draw any conclusion about the affinity between phosphorylated Parkin and Miro1 (which was done in lines 341-343). The authors should comment on why they did not test pParkin binding with Miro1, especially given the statement:
"In our assays in the absence of pUb, pParkin must interact with its substrates without the action of pUb, likely through 158 transient, low affinity interactions" - The reference to Parkin115-124 as a "Substrate Targeting Region (STR)" is misleading. This would imply that this motif in Parkin is responsible for general substrate recognition when there is no direct evidence of this. In Figure 5F, the authors create a synthetic peptide based off the STR sequence. Although this sequence was effective in inhibiting the ubiquitination of Miro1, it was ineffective against Mfn1. This would indicate that Mfn1 relies on a completely different set of interactions for ubiquitination by Parkin. I suggest that the authors tone down the language in describing this region and rename this region (perhaps "Miro1 Targeting Region (MTR)"?). - The authors appear to confuse plDDT and PAE scores in Figure 5B. The PAE describes the expected positional error of each residue in the model. The plot should be colored in terms of Expected Position Error (Ångstrom), not plDDT scores.
Minor Comments:
- Figure 1A would benefit from a schematic showing the domain architecture. If the goal is to appreciate the length of the linker, then showing the actual amino acid length would be beneficial.
- In Supplementary Figure 2D, the authors performed the MST experiment with His6-Smt3-tagged Parkin. The group had previously shown that the presence of the tag artificially interferes with autoubiquitination, potentially by forming intramolecular interactions. The SEC, Native Page, and ITC data of untagged Parkin with Miro1 provide sufficient evidence that the interaction between the two are weak. The authors should consider removing the MST data, since they are not congruent with the other experiments.
- The ITC data in Supplementary Figure 2C look promising. It would be nice if the authors could try to quantify the Kd of their STR peptides to Miro1
- Are STR peptides 1 and/or 2 unable to inhibit ubiquitination of other Parkin substrates besides Mfn1? Do these other substrates utilize the STR for recognition? AlphaFold modeling may provide some insight on Parkin recognition of other substrates.
- The authors shold consider using AlphaFold3 to model the interaction of pParkin with Miro1 compares to unmodified Parkin.
- Please label the protein names in Figure 4A for a better presentation.
- Page 2, line 37. "...by a 65-residue flexible region (linker) to a unique to Parkin RING0 domain..." should be "...by a 65-residue flexible region (linker) to a unique Parkin RING0 domain...". The second "to" should be omitted.
- Page 3, Line 48: "fulfill", not "fulfil"
- Page 5, line 110. In sentence, "...phosphorylation at Ser65 of Parkin...", it is better to explicitly state that this phosphorylation happens on the Parkin Ubl domain.
- Page 7, line151. Figure 1F should be Figure 1G.
- Page 11, line 241. In sentence "...Miro1 residues R263, R265 and D228...", do the authors mean R261 and not R265?
Significance
Parkin is an E3 ubiquitin ligase that is activated to ubiquitinate diverse substrates on the mitochondrial membrane in response to mitochondrial damage, thereby recruiting mitophagy effectors. This study reveals the mechanisms by which Parkin recognizes and ubiquitinates Miro1, providing insights into mitochondrial homeostasis and facilitating new therapeutic approaches for Parkinson's disease.
Readers with a background in protein ubiquitination and mitochondrial homeostasis might be interested in this study. My expertise includes protein ubiquitination and structural biology. However, I do not have sufficient expertise to evaluate the NMR experiments in this manuscript.
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Reviewer #2 (Public Review):
The authors addressed the question of how mitochondrial proteins that are dually localized or only to a minor fraction localized to mitochondria can be visualized on the whole genome scale. For this, they used an established and previously published method called BiG split-GFP, in which GFP strands 1-10 are encoded in the mitochondrial DNA and fused the GFP11 strand C-terminally to the yeast ORFs using the C-SWAT library. The generated library was imaged under different growth and stress conditions and yielded positive mitochondrial localization for approximately 400 proteins. The strength of this method is the detection of proteins that are dually localized with only a minor fraction within mitochondria, which so far has hampered their visualization due to strong fluorescent signals from other cellular localizations. The weakness of this method is that due to the localization of the GFP1-10 in the mitochondrial matrix, only matrix proteins and IM proteins with their C-termini facing the matrix can be detected. Also, proteins that are assembled into multimeric complexes (which will be the case for probably a high number of matrix and inner membrane-localized proteins) resulting in the C-terminal GFP11 being buried are likely not detected as positive hits in this approach. Taking these limitations into consideration, the authors provide a new library that can help in the identification of eclipsed protein distribution within mitochondria, thus further increasing our knowledge of the complete mitochondrial proteome. The approach of global tagging of the yeast genome is the logical consequence after the successful establishment of the BiG split-GFP for mitochondria. The authors also propose that their approach can be applied to investigate the topology of inner membrane proteins, however, for this, the inherent issue remains that it cannot be excluded that even the small GFP11 tag can impact on protein biogenesis and topology. Thus, the approach will not overcome the need to assess protein topology analysis via biochemical approaches on endogenous untagged proteins.
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Reviewer #3 (Public Review):
Summary:
Here, Bykov et al move the bi-genomic split-GFP system they previously established to the genome-wide level in order to obtain a more comprehensive list of mitochondrial matrix and inner membrane proteins. In this very elegant split-GFP system, the longer GFP fragment, GFP1-10, is encoded in the mitochondrial genome and the shorter one, GFP11, is C-terminally attached to every protein encoded in the genome of yeast Saccharomyces cerevisiae. GFP fluorescence can therefore only be reconstituted if the C-terminus of the protein is present in the mitochondrial matrix, either as part of a soluble protein, a peripheral membrane protein, or an integral inner membrane protein. The system, combined with high-throughput fluorescence microscopy of yeast cells grown under six different conditions, enabled the authors to visualize ca. 400 mitochondrial proteins, 50 of which were not visualised before and 8 of which were not shown to be mitochondrial before. The system appears to be particularly well suited for analysis of dually localized proteins and could potentially be used to study sorting pathways of mitochondrial inner membrane proteins.
Strengths:
Many fluorescence-based genome-wide screens were previously performed in yeast and were central to revealing the subcellular location of a large fraction of yeast proteome. Nonetheless, these screens also showed that tagging with full-length fluorescent proteins (FP) can affect both the function and targeting of proteins. The strength of the system used in the current manuscript is that the shorter tag is beneficial for the detection of a number of proteins whose targeting and/or function is affected by tagging with full-length FPs.
Furthermore, the system used here can nicely detect mitochondrial pools of dually localized proteins. It is especially useful when these pools are minor and their signals are therefore easily masked by the strong signals coming from the major, nonmitochondrial pools of the proteins.
Weaknesses:
My only concern is that the biological significance of the screen performed appears limited. The dataset obtained is largely in agreement with several previous proteomic screens but it is, unfortunately, not more comprehensive than them, rather the opposite. For proteins that were identified inside mitochondria for the first time here or were identified in an unexpected location within the organelle, it remains unclear whether these localizations represent some minor, missorted pools of proteins or are indeed functionally important fractions and/or productive translocation intermediates. The authors also allude to several potential applications of the system but do little to explore any of these directions.
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Author response:
The following is the authors’ response to the original reviews.
eLife assessment
The study reports on a previously unrecognized function of ATG6 in plant immunity. The work is valuable because it proposes a direct interaction between ATG6 and a well-studied salicylic acid receptor protein, NPR1, which may interest researchers investigating plant immunity regulation. While the data presented are compelling, more information regarding the specificity of ATG6's role would improve the overall impact of the study, especially with an eye towards consistency with prior work.
We also genuinely thank the editor and reviewers for the constructive and helpful suggestions and comments. These comments have greatly improved the quality and thoroughness of our manuscript. We have carefully studied these comments and have made the appropriate changes as far as possible. Additionally, some minor errors were also corrected during the revision process. New text is shown in blue in the revised manuscript. Our responses to the reviewer's comments are provided below each respective comment.
Public Reviews:
Reviewer #1 (Public Review):<br /> Summary:<br /> The authors showed that autophagy-related genes are involved in plant immunity by regulating the protein level of the salicylic acid receptor, NPR1.<br /> Strengths:<br /> The experiments are carefully designed and the data is convincing. The authors did a good job of understanding the relationship between ATG6 and NRP1.
Thank you very much for recognizing our research.
Weaknesses:<br /> - The authors can do a few additional experiments to test the role of ATG6 in plant immunity.<br /> I recommend the authors to test the interaction between ATGs and other NPR1 homologs (such as NPR2).
Thanks to your valuable feedback, it was discovered that the Arabidopsis NPRs family comprises six members: NPR1, NPR2, NPR3, NPR4, NPR5/PETIOLE 1 (BOP1), and NPR6/BOP2. NPR3/4 function in tandem as negative regulators to modulate SA signaling and plant immune responses (Ding et al., 2018). Similar to NPR1, NPR2 acts as a positive regulator of SA signaling (Castello et al., 2018). NPR5/BOP1 and NPR6/BOP2 primarily participate in the regulation of plant growth and development (McKim et al., 2008). This study specifically investigates the correlation between ATG6 and NPRs in plant resistance to pathogenic bacteria. Consequently, we experimentally confirmed the interaction between ATG6 and NPR1, NPR3, and NPR4 (Fig. 1 and Fig. S1 in the revised manuscript). It would be intriguing to further explore the interactions between ATG6 and other NPRs in the context of regulating plant growth and development in future research endeavors.
-The concentration of SA used in the experiment (0.5-1 mM) seems pretty high. Does a lower concentration of SA induce ATG6 accumulation in the nucleus?
Thank you for pointing this out. The NPR1 protein is known to be unstable and prone to degradation through the 26S proteasome pathway (Spoel et al., 2009; Saleh et al., 2015). Consequently, to investigate the function of NPR1, many scientists and research groups typically employ higher concentrations of SA (e.g., 0.5 mM, 1 mM, or even 5 mM) to elucidate its role (Spoel et al., 2009; Fu et al., 2012; Lee et al., 2015; Saleh et al., 2015; Skelly et al., 2019; Zavaliev et al., 2020; Chen et al., 2021a). In our study, we observed an interaction between ATG6 and NPR1. To enhance the detection of the NPR1 protein, we standardized the SA concentration (Arabidopsis was treated with 0.5 mM SA; Tobacco was treated with 1 mM SA) used in our experiments. Subsequently, we analyzed the nuclear accumulation ATG6 or NPR1 using a relatively high SA concentration (Arabidopsis was treated with 0.5 mM SA; Tobacco was treated with 1 mM SA), consistent with concentrations used in previous studies (Spoel et al., 2009; Lee et al., 2015; Saleh et al., 2015; Skelly et al., 2019; Zavaliev et al., 2020; Chen et al., 2021a).
-Does the silencing of ATG6 affect the cell death (or HR) triggered by AvrRPS4?
Thank you for pointing this out. In this study, we examined changes in Pst DC3000/avrRps4-induced cell death in Col, amiRNAATG6 # 1, amiRNAATG6 # 2, npr1, NPR1-GFP, ATG6-mCherry and ATG6-mCherry × NPR1-GFP plants. The results of Taipan blue staining showed that Pst DC3000/avrRps4-induced cell death in npr1, amiRNAATG6 # 1 and amiRNAATG6 # 2 was significantly higher compared to Col (Fig. S15 in the revised manuscript). Conversely, Pst DC3000/avrRps4-induced cell death in ATG6-mCherry, NPR1-GFP and ATG6-mCherry × NPR1-GFP was significantly lower compared to Col. Notably, Pst DC3000/avrRps4-induced cell death in ATG6-mCherry × NPR1-GFP was significantly lower compared ATG6-mCherry and NPR1-GFP (Fig. S15 in the revised manuscript). These results suggest that ATG6 and NPR1 cooperatively inhibit Pst DC3000/avrRps4-induced cell dead. The relevant description can be found in lines 394-404 of the revised manuscript.
-SA and NPR1 are also required for immunity and are activated by other NLRs (such as RPS2 and RPM1). Is ATG6 also involved in immunity activated by these NLRs?
Thank you for your valuable comments. The most notable event in the NLR-mediated ETI immune response is the induction of hypersensitive response-programmed cell death (HR-PCD) (Jones and Dangl, 2006; Yuan et al., 2021). SA plays a dual role in the ETI response. On one hand, the accumulation of SA during the R gene-mediated ETI defense response is directly linked to the onset of HR-PCD (Nawrath and Metraux, 1999). SA and NPR1 can enhance the ETI response by regulating the expression of downstream target genes (Falk et al., 1999; Feys et al., 2001; Ding et al., 2018; Liu et al., 2020). On the other hand, the activation of SA signaling can have a negative regulatory effect on HR-PCD during the ETI response. High levels of SA have been shown to significantly inhibit HR-PCD triggered by the avrRpt2 effector (Rate and Greenberg, 2001; Devadas and Raina, 2002; Jurkowski et al., 2004). Rate et al. discovered that the inhibition of HR-PCD by SA relies on NPR1 (Rate and Greenberg, 2001).
Arabidopsis AtATG6 or its homologs in other species (such as NbBECLIN1, TaATG6s, etc.) have been identified as positive regulators in plant immunity, playing a crucial role in inhibiting cell death and preventing invasion by pathogenic microorganisms (Liu et al., 2005; Patel and Dinesh-Kumar, 2008; Yue et al., 2015). Patel et al. demonstrated that, akin to autophagy-deficient mutants previously documented, AtATG6 antisense (AtATG6-AS) plants treated with Pst DC3000/avrRpm1 exhibited diffuse cell death, indicating the necessity of ATG6 in restricting cell death (Patel and Dinesh-Kumar, 2008). In tobacco, deficiencies in BECLIN 1 result in the onset of diffuse HR-PCD, underscoring the essential role of BECLIN 1 in limiting HR-PCD (Liu et al., 2005). Despite the genetic evidence supporting the critical function of ATG6 in plant immunity, the precise molecular mechanisms through which ATG6 impedes the invasion of pathogenic microorganisms remain elusive.
In our study, we uncovered that ATG6 interacts with NPR1 to hinder pathogen invasion and inhibit the initiation of cell death. In animals, members of the NLR family have been observed to interact with the autophagy-related protein LC3 to inhibit the survival of pathogen (Zhang et al., 2019). Similar mechanisms may exist in plants. However, it remains to be explored whether NLR directly induces the activation of ATG6 through interaction or the relationship between NPR1-ATG6 interactions and NLR-mediated plant immunity, necessitating further investigation.
Reviewer #2 (Public Review):
Summary:
The manuscript by Zhang et al. explores the effect of autophagy regulator ATG6 on NPR1-mediated immunity. The authors propose that ATG6 directly interacts with NPR1 in the nucleus to increase its stability and promote NPR1-dependent immune gene expression and pathogen resistance. This novel role of ATG6 is proposed to be independent of its role in autophagy in the cytoplasm. The authors demonstrate through biochemical analysis that ATG6 interacts with NPR1 in yeast and very weakly in vitro. They further demonstrate using overexpression transgenic plants that in the presence of ATG6-mcherry the stability of NPR1-GFP and its nuclear pool is increased.
However, the overall conclusions of the study are not well supported experimentally. The significance of the findings is low because of their mostly correlational nature, and lack of consistency with earlier reports on the same protein.
Thank you for your valuable and constructive suggestions. In this article, we unveil a novel relationship in which ATG6 positively regulates NPR1 in plant immunity (Fig. 8 in the revised manuscript). ATG6 interacts with NPR1 to synergistically enhance plant resistance by regulating NPR1 protein levels, stability, nuclear accumulation, and formation of SINCs-like condensates. This may be of interest to researchers studying the regulation of plant immunity. While there may be minor flaws in our current study, the significance of these findings cannot be overstated, as they have the potential to redirect scientific attention towards uncovering novel functions for autophagy genes.
Based on the integrity and quality of the data as well as the depth of analysis, it is not yet clear if ATG6 is a specific regulator of NPR1 or if it is affecting NPR1's stability indirectly, through inducing an elevation of SA levels in plants. As such, the current study demonstrates a correlation between overexpression of ATG6, SA accumulation, and NPR1 stability, however, whether and how these components work together is not yet demonstrated.
Thanks to your valuable feedback. Although as the reviewer said there may be some flaws in our data from the current results, scientific research is an ongoing process and I am confident that future studies will be even better. From the results given to us at the moment at least this study reports a previously undiscovered function of ATG6 in plant immunity. We propose a direct interaction between ATG6 and a well-studied salicylic acid receptor protein, NPR1. We unveil a novel relationship in which ATG6 positively regulates NPR1 in plant immunity (Fig. 8 in the revised manuscript). ATG6 interacts with NPR1 to synergistically enhance plant resistance by regulating NPR1 protein levels, stability, nuclear accumulation, and formation of SINCs-like condensates. This may be of interest to researchers studying the regulation of plant immunity.
Based on the provided biochemical data, it is not yet clear if the ATG6 functions specifically through NPR1 or through its paralogs NPR3 and NPR4, which are negative regulators of immunity. It is quite possible that interaction with NPR1 (or any NPR) is not the major regulatory step in the activity of ATG6 in plant immunity. The effect of ATG6 on NPR1 could well be indirect, through a change in the SA level and redox environment of the cell during the immune response. Both SA level and redox state of the cell were reported to induce accumulation of NPR1 in the nucleus and increase in stability.
Thanks to your valuable feedback. In this study, we validated the interaction between ATG6 and NPR1 through various approaches and identified the key regions mediating their interaction. Our findings indicate that ATG6 interacts with NPR1 to synergistically enhance plant resistance by regulating NPR1 protein levels, stability, nuclear accumulation, and the formation of SINC-like condensates. These results clearly demonstrate the involvement of ATG6 in the regulation of NPR1.Furthermore, we also found that ATG6 interacts with NPR3/4 (Fig. S1 in the revised manuscript). This is particularly relevant given that NPR3 and NPR4 have been shown to act as adaptors for the ubiquitin E3 ligase Cullin 3 (CUL3) to regulate the degradation of NPR1. Therefore, whether ATG6 regulates NPR1 through its interactions with NPR3/4 is an intriguing question worth exploring in future studies. We appreciate the reviewer's concerns and are committed to addressing them in our future research to further elucidate the complex regulatory mechanisms involving ATG6, NPR1, and other key players in plant immunity.
Another major issue is the poor quality of the subcellular analyses. In contradiction to previous studies, ATG6 in this study is not localized to autophagosome puncta, which suggests that the soluble localization pattern presented here does not reflect the true localization of ATG6. Even if the authors propose a novel, non-canonical nuclear localization for ATG6, they still should have detected the canonical autophagy-like localization of this protein.
Thanks to your valuable feedback. We conducted predictions at NLS Mapper (https://nls-mapper.iab.keio.ac.jp/cgi-bin/NLS_Mapper_form.cgi) and identified two bipartite NLSs in ATG6, with the sequences "MRKEEIPDKSRTIPIDPNLPKWVCQNCHHS" and "DPNLPKWVCQNCHHS LTIVGVDSYAGKFFNDP". To further elucidate the nuclear localization of ATG6, we introduced Agrobacterium tumefaciens carrying ATG6-GFP into nls-mCherry tobacco leaves through transient transformation. Subsequently, we observed the localization of ATG6-GFP, along with the canonical autophagy-like patterns. Our findings revealed fluorescence signals of ATG6-GFP in both the cytoplasm and nuclei (Figure 2b). The nuclear-localized ATG6-GFP overlapping with the nuclear-localized marker, nls-mCherry (indicated by white arrows). Additionally, we observed punctate patterns indicative of canonical autophagy-like localization of ATG6-GFP fluorescence signals (indicated by red circles). Based on these results, we are more confident about the authenticity of ATG6's nuclear localization. The revised manuscript includes clearer images to support our observations.
Recommendations for the Authors:
Reviewer #2 (Recommendations For The Authors):
The duration and concentration of SA treatments are quite variable between experiments which makes comparisons difficult.
Thank you for pointing this out. The NPR1 protein is known to be unstable and prone to degradation through the 26S proteasome pathway (Spoel et al., 2009; Saleh et al., 2015). Consequently, to investigate the function of NPR1, many scientists and research groups typically employ higher concentrations of SA (e.g., 0.5 mM, 1 mM, or even 5 mM) to elucidate its role (Spoel et al., 2009; Fu et al., 2012; Lee et al., 2015; Saleh et al., 2015; Skelly et al., 2019; Zavaliev et al., 2020; Chen et al., 2021a). In our study, we observed an interaction between ATG6 and NPR1. To enhance the detection of the NPR1 protein, we standardized the SA concentration used in our experiments. In this study, for the treatment of Arabidopsis, we followed the protocols outlined in Saleh et al. and Spoel et al., utilizing 0.5 mM SA (Spoel et al., 2009; Saleh et al., 2015). For tobacco treatment, we adopted the methodology described in the study by Zavaliev et al., administering 1 mM SA (Zavaliev et al., 2020).
The methods section does not explain some of the essential experimental conditions and reagents used in the study.
Thank you for pointing this out. Due to word limitations we have placed the detailed experimental methods and reagents in Supplemental Data 1. In Supplemental Data 1, we provide a comprehensive overview of the experimental flow and conditions employed in our study.
Lines 62-63: the C-terminal domain of all NPRs has a name (already defined as SA-binding domain (SBD)). Also, it would be worth referring to the structure of NPR1 (Kumar et al 2022, Nat) as the source of information about its domains.
Thank you for pointing this out, we have changed this description in the revised manuscript (lines 62-63).
Lines 66-69: NPR1 doesn't form monomers. A recent study showed that the basic functional unit of NPR1 is a dimer (Kumar et al 2022, Nat).
Thank you for pointing this out. In the revised manuscript (line 67) " monomers " has been changed to “dimer”.
Lines 89-95 and elsewhere: the term "invasion" has a very specific meaning and it doesn't necessarily refer to disease. A pathogen can invade the plant but cause no disease (e.g. ETI). Most plant genetic immune mechanisms act after pathogen invasion, not before it. Those cited works reported the disease resistance, not the invasion resistance.
Thank you for pointing this out. We've changed the incorrect description in the revised manuscript (line 91).
Lines 113-119: the truncation at the aa328 includes half of the ANK domain (repeats 1 and 2), not just BTB. The C-terminal truncation variant contains the other half (repeats 3 and 4) of the ANK domain, not the entire ANK domain. It also contains the SBD, not just the NLS. So, this kind of analysis cannot determine the role of ANK domain in the interaction, nor it can conclusively determine if the interaction is through SBD. The interaction should be tested with the SBD domain only in order to make this conclusion.
Thank you for pointing this out, we have removed the inappropriate description and made the appropriate changes in the revised manuscript (lines 114 and 115).
In Figure S1, the equally strong interaction of atg6 is found for NPR3/NPR4. Does that mean that atg6 functions also through these other NPRs? What's the significance of these data compared to NPR1-ATG6 interaction? This is especially important, because both NPR3 and NPR4 are predominantly nuclear proteins, and they are unlikely to significantly overlap with autophagy components in the cytoplasm.
NPR1 and its paralogues NPR3/NPR4, which frequently interact with other proteins to regulate plant immune responses (Backer et al., 2019; Chen et al., 2019). To identify ATGs that interact with NPRs, we performed yeast two-hybrid (Y2H) screens using NPRs as bait. Interestingly, ATG6 interacted with NPR1, NPR3 and NPR4, respectively, and different concentrations of SA treatment did not significantly affect their interaction (Fig. S1a). NPR1 is an important positive regulator of the plant immune response (Chen et al., 2021b). In Arabidopsis and N. benthamian, ATG6 or its homologues was reported to act as a positive regulator to enhance plant disease resistance to P. syringae pv. tomato (Pst) DC3000 and Pst DC3000/avrRpm1 bacteria (Patel and Dinesh-Kumar, 2008), N. benthamiana mosaic virus (TMV) (Liu et al., 2005). Therefore, in this study we focused on investigating the biological significance of the interaction between ATG6 and NPR1. Whether the interaction between ATG6 and NPR3/4 also has an effect on plant immunity is a question that remains to be explored in future studies.
In Figure 1c and elsewhere: why not use the anti-mCherry antibody to detect atg6-mcherry? Are we seeing the correct protein band of atg6-mcherry? Also, it is not clear what antibodies they used throughout the study: the sources and specificities of antibodies are not provided.
Thank you for pointing this out. We initially synthesized the ATG6 antibody (anti-ATG6, 1:200, peptide, C-KEKKKIEEEERK, Abmart) in order to detect the endogenous ATG6 protein, and we also tested the specificity and potency of the ATG6 antibody (results are shown in Fig. S17). Additionally, in order to determine the location of the ATG6-mCherry bands, we also detected ATG6-mCherry in ATG6-mCherry Arabidopsis using the ATG6 antibody, and we also used Col as a control (results are shown in Fig. S4). These results show that our synthesized ATG6 antibody can effectively and clearly immunize to both ATG6 and ATG6-mCherry. Therefore, in this study, we used the ATG6 antibody to analyze both ATG6-mCherry and endogenous ATG6. Detailed antibody information is presented in Supplementary Data 1, table S4
In Figures 1d, 2a, and 2b, the subcellular localization pattern of atg6 contradicts what was published before (Fujiki et al 2007, Plant Phys; Liu et al 2018, FPlS; Xu et al 2017, Autophagy; Li et al 2018, Nat. Comm.). As an autophagy protein, atg6 was shown to localize to cytoplasmic puncta (autophagosomes), like atg8. No nuclear localization was found in those studies. The lack of puncta and the strong nuclear accumulation are signs that the localization of atg6 reported here has to be interpreted with caution. With the data provided, I am not convinced yet that we are looking at the correct ATG6 subcellular localization. Even if the authors propose a novel, non-canonical localization for atg6, they still should have detected the canonical autophagy-like localization of this protein.
Thanks to your valuable feedback. To further elucidate the nuclear localization of ATG6, we introduced Agrobacterium tumefaciens carrying ATG6-GFP into nls-mCherry tobacco leaves through transient transformation. Subsequently, we observed the localization of ATG6-GFP, along with the canonical autophagy-like patterns. Our findings revealed fluorescence signals of ATG6-GFP in both the cytoplasm and nuclei (Figure 2b). The nuclear-localized ATG6-GFP overlapping with the nuclear-localized marker, nls-mCherry (indicated by white arrows). Additionally, we observed punctate patterns indicative of canonical autophagy-like localization of ATG6-GFP fluorescence signals (indicated by red circles). Based on these results, we are more confident about the authenticity of ATG6's nuclear localization. The revised manuscript includes clearer images to support our observations.
It would make more sense to include the BiFC data (fig. S2) in the main figure, instead of the co-localization (fig. 1d) which cannot serve as evidence for interaction.
Thank you for the feedback. We accept your suggestion. In Fig.1, we have replaced the co-localization image with a BiFC (Bimolecular Fluorescence Complementation) image to better illustrate the interaction.
In Figure S2, the bifc signals have to be quantified to qualify as evidence for interaction. also, a subcellular marker has to be used (e.g. nuclear mcherry). From the current poor-quality images, one cannot determine where in the cell the presumed interaction takes place, nucleus or cytoplasm, or both. Also, no puncta are seen in these images.
Thank you for pointing this out. Despite the lack of clarity in the images we provided, our BiFC results unequivocally demonstrate the interaction between ATG6 and NPR1 in both the cytoplasm and nucleus. Notably, as the reviewer pointed out, punctate signals were not observed in our images. This lack of punctate signals is consistent with previous studies (Figure 2) that have also shown BiFC results between autophagy-associated proteins ATG8s and their interacting partners. For instance, Fig 1G (Marshall et al. 2019, Cell), Fig 2F (Marshall et al. 2019, Cell), Fig 4B (Macharia et al. 2019, BMC Plant Biology), and Fig 3 (Zhou et al. 2018, Autophagy) all did not exhibit punctate signals, aligning closely with our findings.
In Figure S3a, the nuclear localization is shown for stomata. It is known that stomata are especially strong expressors of the transgenes, and localization there could be an artefact of overaccumulation of the fusion protein. Also, why do they present the localization of atg6-gfp, if the analysis and the cross were made with atg6-mcherry?
Thank you for pointing this out. In our previous experiments, we observed the localization of ATG6 in the nucleus of Arabidopsis thaliana plants overexpressing ATG6-GFP (Fig. S3a). To clearly visualize the location of the nucleus, we used the cytosolic DAPI dye, which readily stained the nuclei of the stomatal guard cells. This allowed us to easily identify the nuclear regions for our observations. Additionally, in Fig. 2a and Fig.S3b, we detected the fluorescence signal of ATG6-mCherry within the nucleus, further confirming the nuclear localization of ATG6. Moreover, the nuclear and cytoplasmic fractions were separated. Under SA treatment, ATG6-mCherry and ATG6-GFP were detected in the cytoplasmic and nuclear fractions in N. benthamiana (Fig. 2c and d). Similarly, ATG6 was also detected in the nuclear fraction of UBQ10::ATG6-GFP and UBQ10::ATG6-mCherry overexpressing plants (Fig. 2e and f).
In Figure S3b, the images are low resolution and of poor quality. Why atg6-mcherry is expressed in a single cell if these are transgenic plants? The nuclear co-localization with npr1-gfp has to be shown more clearly with high res. images and also be quantified, because the expression of atg6-mcherry is not as uniform as npr1-gfp.
Thank you for pointing this out. Contrary to the reviewer's assertion, the ATG6-mCherry fluorescence signal depicted in Figure S3b was not exclusive to a single cell. In fact, this fluorescence was also evident in other cells, albeit with relatively weaker intensity. This disparity in fluorescence intensity may be attributed to the irregularities in leaf structure at the time of image capture using the microscope. To bolster our conclusion, we further examined the fluorescence signals in the cells of the root elongation zone in ATG6-mCherry x NPR1-GFP, as depicted in the figure below. Our observations revealed that the fluorescence signals of ATG6-mCherry exhibited uniform distribution, with detection in both the cytoplasm and nucleus. We have replaced the original unclear image with a high-quality image.
Lines 138-143: In fig. S3d, it would make more sense to show the WB on the hybrid npr1-gfp/atg6-mcherry plants with both anti-gfp and anti-mcherry antibodies to detect the free mcherry/gfp. Since the analysis of the level of free FP is done, then why didn't they test the free mcherry levels in Figure S4a? This would be more important than testing the free GFP in ATG6-GFP plants, because the imaging of atg6-mcherry was done in the hybrid plants (fig. S3b).
Thank you for pointing this out. We initially synthesized the ATG6 antibody (anti-ATG6, 1:200, peptide, C-KEKKKIEEEERK, Abmart) in order to detect the endogenous ATG6 protein, and we also tested the specificity and potency of the ATG6 antibody (results are shown in Fig. S17). Additionally, in order to determine the location of the ATG6-mCherry bands, we also detected ATG6-mCherry in ATG6-mCherry Arabidopsis using the ATG6 antibody, and we also used Col as a control (results are shown in Fig. S4). These results show that our synthesized ATG6 antibody can effectively and clearly immunize to both ATG6 and ATG6-mCherry. Therefore, in this study, we used the ATG6 antibody to analyze both ATG6-mCherry and endogenous ATG6. Detailed antibody information is presented in Supplementary Data 1, table S4. In the previous experiments, we procured the mCherry antibody (mCherry-Tag Monoclonal Antibody(6B3), BD-PM2113, China) to immunolabel ATG6-mCherry. However, we encountered challenges with the potency of this mCherry antibody, and considering our budget constraints, as well as the availability of our self-synthesized ATG6 antibody, we chose not to pursue the purchase of another antibody from a different company for the continuation of the Western Blot experiment.
In Figure 2c, there's no atg6-mcherry detected at time 0, in either cytoplasm or nucleus, yet the microscope images in panel a show strong accumulation in both compartments.
Thank you for pointing this out. Previous studies ATG6 can also be degraded via the 26s proteasome pathway (Qi et al., 2017). We speculate that this phenomenon might be attributed to the rapid turnover of ATG6 at time 0.
Lines 156-160: this statement is unsupported by the data. In fig. S5, the bands for native atg6 in the nuclear fraction are extremely weak, and they do not show the reverse pattern of change along the time points compared to the cytoplasmic fraction, which would indicate that the nuclear fraction is complementary to the cytoplasmic pool of the protein. The result more likely suggests that the majority of the ATG6 is in the cytoplasm, and that the weak bands detected in the nucleus are either background signal, or a contamination from the cytoplasmic pool. At this low protein level or poor immuno-detection the background signal is inevitable due to overexposure. Even though the actin marker is not detected in the nuclear fraction, it doesn't necessarily mean that there's no contamination from the cytoplasm in the nuclear fraction. The actin is just too abundant and can be detected at lower exposure.
Thank you for pointing this out. In Fig. S5, we detected the subcellular localization of endogenous ATG6, although the image quality was somewhat low. Nevertheless, the cytosolic and nuclear localization of ATG6 could be clearly observed. In addition to this, we also verified the cytosolic and nuclear localization of ATG6 in Arabidopsis using confocal fluorescence microscopy and nucleoplasmic separation experiments. Actin and H3 were used as cytoplasmic and nucleus internal reference, respectively. (Fig. 2e and f). Furthermore, we observed the cytosolic and nuclear localization of ATG6 when we expressed ATG6-GFP or ATG6-mCherry in tobacco leaves through cis-transfection experiments (Fig. 2a-d). These results are consistent with the prediction of the subcellular location of ATG6 in the Arabidopsis subcellular database (https://suba.live/) (Fig. S3c). The reviewer's feedback has been valuable in helping us present these findings more clearly. We acknowledge the limitations in the image quality for the endogenous ATG6 localization, but we believe the combination of multiple experimental approaches, including the use of fluorescent protein fusions, provides robust evidence for the cytosolic localization of ATG6 in plant cells. Moving forward, we will continue to investigate the significance of ATG6's subcellular distribution and its potential dual roles in both the nucleus and the cytosol, particularly in the context of its interaction with the key immune regulator NPR1. We appreciate the reviewer's constructive comments, as they will help us strengthen the presentation and interpretation of our findings.
In Figure 3a the images are of too low resolution to see the co-localization. The focal planes of the top and bottom panels are quite different: the top is focused on stomata, the bottom - on pavement cells. So, the number of the NPR1-GFP nuclei between these two focal planes is dramatically different. Also, it looks like the atg6-mcherry in these plants are predominantly in the cytoplasm, not the nucleus as the authors claim. A higher resolution and higher quality of images are required to determine this.
Thank you for pointing this out. To ensure the clarity and accuracy of our confocal images, we have supplied a clearer image as supplementary evidence. The Bright images distinctly show that both sets of images are in the same plane of focus. Furthermore, in the figure (third one in the fourth column), the nucleus localization of ATG6-mCherry is clearly visible, and that ATG6-mCherry is co-localized with NPR1-GFP in the nucleus, as indicated by the white arrow.
In Figure 3b, it is not indicated what exactly was measured and in what condition, mock or SA. If these are numbers of nuclei, then it should be indicated what size of the area was sampled, not just "section", and both mock and SA should be included in the measurements. Also, how many independent images have been sampled? what does the error bar represent? What does "normal" mean? Shouldn't this be a mock treatment?
Thank you for pointing out this. The term "Normal" in this context refers to mock treatment, and we have revised the description for clarity. In Figure 3b, the graph illustrates the count of nuclear localizations of NPR1-GFP in ATG6-mCherry × NPR1-GFP and NPR1-GFP Arabidopsis plants following SA treatment. Statistical data were obtained from three independent experiments, each comprising five individual images, resulting in a total of 15 images analyzed for this comparison. Detailed descriptions were also added to the revised manuscript (Lines 568-570, 800-804).
Lines 167-168: the proposed increase of NPR1-GFP in the nucleus could be simply due to a higher accumulation of SA in the hybrid plants, not because of the direct interaction of atg6.
Thank you for pointing out this. Our results confirmed that ATG6 overexpression significantly increased nuclear accumulation of NPR1 (Fig. 3). Notably, the ratio (nucleus NPR1/total NPR1) in ATG6-mCherry × NPR1-GFP was not significantly different from that in NPR1-GFP, and there is a similar phenomenon in N. benthamiana (Fig. 3c-f). These results suggested that the increased nuclear accumulation of NPR1 by ATG6 might result from higher levels and more stable NPR1, rather than the enhanced nuclear translocation of NPR1 facilitated by ATG6. Furthermore, we found that under SA treatment, the protein levels of NPR1 were significantly higher in the ATG6-mCherry × NPR1-GFP line compared to the NPR1-GFP line (Fig. 5a). Notably, even in the absence of differences in SA levels between the two lines, we observed that ATG6 could delay the degradation of NPR1 under normal conditions (Fig. 6). These findings suggest that ATG6 employs both SA-dependent and SA-independent mechanisms to maintain the stability of the key immune regulator NPR1. In summary, we therefore suggest that the increased nuclear accumulation in NPR1 cells is a dual effect of SA and ATG6.
Lines 202-204: "Increased nuclear accumulation" implies increased translocation. However, they found that the ratio of NPR1-GFP does not change (Figure 3), so the reason for higher nuclear accumulation is not translocation, but abundance.
Thank you for pointing out this. Our results confirmed that ATG6 overexpression significantly increased nuclear accumulation of NPR1 (Fig. 3). ATG6 also increases NPR1 protein levels and improves NPR1 stability (Fig. 5 and 6). Therefore, we consider that the increased nuclear accumulation of NPR1 in ATG6-mCherry x NPR1-GFP plants might result from higher levels and more stable NPR1 rather than the enhanced nuclear translocation of NPR1 facilitated by ATG6. To verify this possibility, we determined the ratio of NPR1-GFP in the nuclear localization versus total NPR1-GFP. Notably, the ratio (nucleus NPR1/total NPR1) in ATG6-mCherry × NPR1-GFP was not significantly different from that in NPR1-GFP, and there is a similar phenomenon in N. benthamiana (Fig. 3c-f). These results suggested that the increased nuclear accumulation of NPR1 by ATG6 might result from higher levels and more stable NPR1, rather than the enhanced nuclear translocation of NPR1 facilitated by ATG6. Further we analyzed whether ATG6 affects NPR1 protein levels and protein stability. Our results show that ATG6 increases NPR1 protein levels under SA treatment and ATG6 maintains the protein stability of NPR1 (Fig. 5 and 6). These results suggested that the increased nuclear accumulation of NPR1 by ATG6 result from higher levels and more stable NPR1. The corresponding description is shown in revised manuscript (lines 338~352).
Lines 204-205: the co-localization in Figure 1d cannot be interpreted as interaction.
Thank you for the feedback. We have replaced the co-localization image with a BiFC (Bimolecular Fluorescence Complementation) image to better illustrate the interaction in Fig 1d.
What age of plants were used for the analysis in Figures 4 and S7? The age of the plant might significantly affect the free SA levels under control conditions.
Thank you for the feedback. In Figures 4 and S7, 3-week-old plants were used to determine salicylic acid (SA) levels and the expression of target genes. Figures 4 and S7 figure notes provide detailed descriptions (lines 818-819).
In Figure 5a they treat with SA, but the analysis in Figure S10 is done with the pathogen, so how can these data be correlated?
Thank you for pointing out this. Previous studies have demonstrated that pathogen infestation rapidly increases the salicylic acid (SA) content in plants, and the elevated SA then activates plant immune responses. Therefore, both pathogen treatment and direct SA treatment can activate SA-dependent plant immune responses. The NPR1 protein is known for its instability. In Figure 5a, we utilized a 0.5 mM SA treatment to assess the changes in NPR1 protein levels, as the impact of SA treatment is more immediate and pronounced.
Lines 241-242: In Figure 5b, it is not clear why there's no detection of NPR1-GFP and atg6-mcherry at time 0?? The levels of proteins in the transient assay are sufficiently high for detection by WB.
Thank you for pointing this out. The NPR1 protein is known to be unstable and prone to degradation through the 26S proteasome pathway (Spoel et al., 2009; Saleh et al., 2015). In addition, previous studies ATG6 can also be degraded via the 26s proteasome pathway (Qi et al., 2017). We speculate that this phenomenon might be attributed to the rapid turnover of NPR1 and ATG6 at time 0.
In Figures 5c-d, the quality of these images is very poor, and they do not clearly show the signs. What structure was exactly measured in these images? There are so many fluorescent bodies there, that it is not clear what are we looking at. Also, it is not clear why they did not show the mcherry channel? It would be important to see if the bodies in SA-treated plants show co-localization with atg6-mcherry autophagosomes (if these exist at all).
Thank you for pointing this out. Interestingly, similar to previous reports (Zavaliev et al., 2020), SA promoted the translocation of NPR1 into the nucleus, but still a significant amount of NPR1 was present in the cytoplasm (Fig. 3c and e). Previous studies have shown that SA increased NPR1 protein levels and facilitated the formation of SINCs in the cytoplasm, which are known to promote cell survival (Zavaliev et al., 2020). We therefore observed the fluorescence signal of SINCs-like condensates in the cytoplasm of tobacco leaves. After 1mM SA treatment, more SINCs-like condensates fluorescence were observed in N. benthamiana co-transformed with ATG6-mCherry + NPR1-GFP compared to mCherry + NPR1-GFP (Fig. 5c-d and Supplemental movie 1-2). We have a clearer demonstration in the supplemental video movie 1-2. Additionally, we observed that SINCs-like condensates signaling partial co-localized with certain ATG6-mCherry autophagosomes fluorescence signals.
Lines 245-247: so, is it atg6 or SA that increases the NPR1 levels? If this is due to SA, then the whole study doesn't have novelty, because we already know from previous works that SA increases the stability of npr1.
Thank you for pointing this out. Indeed, previous studies have shown that salicylic acid (SA) increases NPR1 levels and protein stability (Spoel et al., 2009; Saleh et al., 2015). In our experiments, we found that under SA treatment, the protein levels of NPR1 were significantly higher in the ATG6-mCherry × NPR1-GFP line compared to the NPR1-GFP line (Fig. 5a). Additionally, free SA levels were also significantly elevated in the ATG6-mCherry × NPR1-GFP line under pathogen challenge (Pst DC3000/avrRps4), but not under normal conditions (Fig. 4a). Furthermore, even in the absence of differences in SA levels between the two lines, we observed that ATG6 could delay the degradation of NPR1 under normal conditions (Fig. 6). These findings represent one of our new discoveries. These findings suggest that ATG6 employs both SA-dependent and SA-independent mechanisms to maintain the stability of the key immune regulator NPR1.
Lines 313-316: npr1 and atg6 can function independently from each other, so the term "jointly" is misleading. Based on the overall data provided in this manuscript it cannot be concluded that the two proteins work in one complex to control plant immunity.
Thank you for pointing this out. In the revised manuscript "jointly" has been changed to “cooperatively”.
Lines 369-374: this speculation is beyond the main hypothesis claiming that atg6 functions through npr1. If atg6 can activate the transcription alone, then what is the significance of its activation of npr1? How can one distinguish between the two?
Thank you for pointing this out. Transcription activation by transcription factors typically requires at least two conserved structural domains: a transcription activation domain and a DNA-binding domain. However, ATG6 does not possess these two typical conserved structural domains found in canonical transcription factors. Given this structural context, it is unlikely that ATG6 would be able to directly activate transcription on its own. The lack of the canonical transcription factor domains in ATG6 suggests that it may not be able to function as a direct transcriptional activator. Previous studies have shown that acidic activation domains (AADs) in transcriptional activators (such as Gal4, Gcn4 and VP16) play important roles in activating downstream target genes. Acidic amino acids and hydrophobic residues are the key structural elements of AAD (Pennica et al., 1984; Cress and Triezenberg, 1991; Van Hoy et al., 1993). Chen et al. found that EDS1 contains two ADD domains and confirmed that EDS1 is a transcriptional activator with AAD (Chen et al., 2021a). Here, we also have similar results that ATG6 overexpression significantly enhanced the expression of PR1 and PR5 (Fig. 4b-c and S9), and that the ADD domain containing acidic and hydrophobic amino acids is also found in ATG6 (148-295 AA) (Fig. S14). We speculate that ATG6 might act as a transcriptional coactivator to activate PRs expression synergistically with NPR1.
Lines 389-400: the cell death due to AvrRPS4 in Col-0 ecotype is extremely weak as there's no complete receptor complex for this effector. So, one has to use a very high dose to induce cell death in Col-0, certainly higher than the one used for bacterial growth. The authors used the same dose in both assays, so it is likely that what we see as "cell death" is not an effector-triggered response, but rather symptom-associated for the virulent pathogen.
Thank you for pointing this out. Indeed, as the reviewer pointed out, most cell death assays use higher concentrations of Pst DC3000/avrRps4 or Pst DC3000/avrRpt2, but they typically treat Arabidopsis for a relatively short period, usually less than 1 day(Hofius et al., 2009; Zavaliev et al., 2020). In this study, although we used relatively low Pst DC3000/avrRps4 (0.001) injections, we detected cell death under a relatively long period of Pst DC3000/avrRps4 infestation (3 days). Pst DC3000/avrRps4-infested plants multiply significantly in host cells, and therefore we assumed that the propagated pathogens after 3 days of incubation would be sufficient to induce intense cell death. Consequently, we chose this concentration of Pst DC3000/avrRps4 for the experiment.
Lines 407-416: why do you expect "delay of degradation" with autophagy inhibitor? Shouldn't it be the opposite? In Figure S14, if we compare the bands between 120min and 120min+ConA+WM, the effect of autophagy inhibitors is actually quite strong (0.47 vs 0.22), with about 50% more degradation of NPR1 in their presence. So, the conclusion that the degradation of NPR1 is autophagy-independent is wrong according to this result.
Thank you for pointing this out. We have revised the inaccurate description, as outlined in the revised manuscript (lines 413-425).
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Irgendwann kam der Punkt, Ausgangssperre, 3G Regel, Spielplatze abgesperrt, Schulen komplett geschlossen, da gingen die Eingriffe einfach im Verhältnis zur Realität einfach zu weit. uuh ein normie... die "eingriffe" gingen seit tag 1 zu weit, weil der ganze covid hoax von anfang an eine controlled demolition war wie 9/11. wer das nicht von anfang an durchschaut hat, der sollte bei "großen" themen wie politik nicht mitreden dürfen, also kein wahlrecht haben. kein wahlrecht für vollidioten. aber nee, ihr spastis wollt ja "demokratie" haben, und mit euerer dummheit alle anderen mit runter in die hölle ziehen...
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Author response:
Reviewer #1 (Public Review):
Weaknesses:
The weakness of this study lies in the fact that many of the genomic datasets originated from novel methods that were not validated with orthogonal approaches, such as DNA-FISH. Therefore, the detailed correlations described in this work are based on methodologies whose efficacy is not clearly established. Specifically, the authors utilized two modified protocols of TSA-seq for the detection of NADs (MKI67IP TSA-seq) and LADs (LMNB1-TSA-seq). Although these methods have been described in a bioRxiv manuscript by Kumar et al., they have not yet been published. Moreover, and surprisingly, Kumar et al., work is not cited in the current manuscript, despite its use of all TSA-seq data for NADs and LADs across the four cell lines. Moreover, Kumar et al. did not provide any DNA-FISH validation for their methods. Therefore, the interesting correlations described in this work are not based on robust technologies.
An attempt to validate the data was made for SON-TSA-seq of human foreskin fibroblasts (HFF) using multiplexed FISH data from IMR90 fibroblasts (from the lung) by the Zhuang lab (Su et al., 2020). However, the comparability of these datasets is questionable. It might have been more reasonable for the authors to conduct their analyses in IMR90 cells, thereby allowing them to utilize MERFISH data for validating the TSA-seq method and also for mapping NADs and LADs.
We disagree with the statement that the TSA-seq approach and data has not been validated by orthogonal approaches and with the conclusion that the TSA-seq approach is not robust as summarized here and detailed below in “Specific Comments”. TSA-seq is robust because it is based only on the original immunostaining specificity provided by the primary and secondary antibodies plus the diffusion properties of the tyramide-free radical. TSA-seq has been extensively validated by microscopy and by the orthogonal genomic measurements provided by LMNB1 DamID and NAD-seq. This includes: a) the initial validation by FISH of both nuclear speckle (to an accuracy of ~50 nm) and nuclear lamina TSA-seq and the cross-validation of nuclear lamina TSA-seq with lamin B1 DamID in a first publication (Chen et al, JCB 2018, doi: 10.1083/jcb.201807108); b) the further validation of SON TSA-seq by FISH in a second publication ((Zhang et al, Genome Research 2021, doi:10.1101/gr.266239.120); c) the cross-validation of nucleolar TSA-seq using NAD-seq and the validation by light microscopy of the predictions of differences in the relative distributions of centromeres, nuclear speckles, and nucleoli made from nuclear speckle, nucleolar, and pericentric heterochromatin TSA-seq in the Kumar et al, bioRxiv preprint (which is in a last revision stage involving additional formatting for the journal requirements) doi:https://doi.org/10.1101/2023.10.29.564613; d) the extensive validation of nuclear speckle, LMNB1, and nucleolar TSA-seq generated in HFF human fibroblasts using published light microscopy distance measurements of hundreds of probes generated by multiplexed immuno-FISH MERFISH data (Su et al, Cell 2020, https://doi.org/10.1016/j.cell.2020.07.032), as we described for nucleolar TSA-seq in the Kumar et al, bioRxiv preprint and to some extent for LMNB1 and SON TSA-seq in the current manuscript version (see Specific Comments with attached Author response image 2).
Reviewer 1 raised concerns regarding this FISH validation given that the HFF TSA-seq and DamID data was compared to IMR90 MERFISH measurements. The Su et al, Cell 2020 MERFISH paper came out well after the 4D Nucleome Consortium settled on HFF as one of the two main “Tier 1” cell lines. We reasoned that the nuclear genome organization in a second fibroblast cell line would be sufficiently similar to justify using IMR90 FISH data as a proxy for our analysis of our HFF data. Indeed, there is a high correlation between the HFF TSA-seq and distances measured by MERFISH to nuclear lamina, nucleoli, and nuclear speckles (Author response image 1). Comparing HFF SON-TSA-seq data with published IMR90 SON TSA-seq data (Alexander et al, Mol Cell 2021, doi.org/10.1016/j.molcel.2021.03.006), the HFF SON TSA-seq versus MERFISH scatterplot is very similar to the IMR90 SON TSA-seq versus MERFISH scatterplot. We acknowledge the validation provided by the IMR90 MERFISH is limited by the degree to which genome organization relative to nuclear locales is similar in IMR90 and HFF fibroblasts. However, the correlation between measured microscopic distances from nuclear lamina, nucleoli, and nuclear speckles and TSA-seq scores is already quite high. We anticipate the conclusions drawn from such comparisons are solid and will only become that much stronger with future comparisons within the same cell line.
Author response image 1.
Scatterplots showing the correlation between TSA-seq and MERFISH microscopic distances. Top: IMR90 SON TSA-seq (from Alexander et al, Mol Cell 2021) (left) and HFF SON TSA-seq (right) (x-axis) versus distance to nuclear speckles (y-axis). Bottom: HFF Lamin B1 TSA-seq (x-axis) versus distance to nuclear lamina (y-axis) (left) and HFF MKI67IP (nucleolar) TSA-seq (x-axis) versus distance to nucleolus (y-axis) (right).
In our revision, we will add justification of the use of IMR90 fibroblasts as a proxy for HFF fibroblasts through comparison of available data sets.
Reviewer #2 (Public Review):
Weaknesses:
The experiments are largely descriptive, and it is difficult to draw many cause-and-effect relationships. Similarly, the paper would be very much strengthened if the authors provided additional summary statements and interpretation of their results (especially for those not as familiar with 3D genome organization). The study would benefit from a clear and specific hypothesis.
We acknowledge that this study was hypothesis-generating rather than hypothesis-testing in its goal. This research was funded through the NIH 4D-Nucleome Consortium, which had as its initial goal the development, benchmarking, and validation of new genomic technologies. Our Center focused on the mapping of the genome relative to different nuclear locales and the correlation of this intranuclear positioning of the genome with functions- specifically gene expression and DNA replication timing. By its very nature, this project has taken a discovery-driven versus hypothesis-driven scientific approach. Our question fundamentally was whether we could gain new insights into nuclear genome organization through the integration of genomic and microscopic measurements of chromosome positioning relative to multiple different nuclear compartments/bodies and their correlation with functional assays such as RNA-seq and Repli-seq.
Indeed, as described in this manuscript, this study resulted in multiple new insights into nuclear genome organization as summarized in our last main figure. We believe our work and conclusions will be of general interest to scientists working in the fields of 3D genome organization and nuclear cell biology. We anticipate that each of these new insights will prompt future hypothesis-driven science focused on specific questions and the testing of cause-and-effect relationships.
Given the extensive scope of this manuscript, we were limited in the extent that we could describe and summarize the background, data, analysis, and significance for every new insight. In our editing to reach the eLife recommended word count, we removed some of the explanations and summaries that we had originally included.
As suggested by Reviewer 2, in our revision we will add back additional summary and interpretation statements to help readers unfamiliar with 3D genome organization.
Specific Comments in response to Reviewer 1:
(1) We disagree with the comment that TSA-seq has not been cross-validated by other orthogonal genomic methods. In the first TSA-seq paper (Chen et al, JCB 2018, doi: 10.1083/jcb.201807108), we showed a good correlation between the identification of iLADs and LADs by nuclear lamin and nuclear speckle TSA-seq and the orthogonal genomic method of lamin B1 DamID, which is reproduced using our new TSA-seq 2.0 protocol in this manuscript. Similarly, in the Kumar et al, bioRxiv preprint (doi:https://doi.org/10.1101/2023.10.29.564613), we showed a general agreement between the identification of NADs by nucleolar TSA-seq and the orthogonal genomic method of NAD-seq. (We expect this preprint to be in press soon; it is now undergoing a last revision involving only reformatting for journal requirements.) Additionally, we also showed a high correlation between Hi-C compartments and subcompartments and TSA-seq in the Chen et al, JCB 2018 paper. Specifically, there is an excellent correlation between the A1 Hi-C subcompartment and Speckle Associated Domains as detected by nuclear speckle TSA-seq. Additionally, the A2 Hi-C subcompartment correlated well with iLAD regions with intermediate nuclear speckle TSA-seq scores, and the B2 and B3 Hi-C subcompartments with LADs detected by both LMNB TSA-seq and LMNB1 DamID. More generally, Hi-C A and B compartment identity correlated well with predictions of iLADs versus LADs from nuclear speckle and nuclear lamina TSA-seq.
(2) In the Chen et al, JCB 2018 paper we also qualitatively and quantitatively validated TSA-seq using FISH. Qualitatively, we showed that both nuclear speckle and nuclear lamin TSA-seq correlated well with distances to nuclear speckles versus the nuclear lamina, respectively, measured by immuno-FISH.
Quantitatively, we showed that SON TSA-seq could be used to estimate the microscopic mean distance to nuclear speckles with mean and median residuals of ~50 nm. First, we used light microscopy to show that the spreading of tyramide-biotin signal from a point-source of TSA staining fits well with the exponential decay predicted theoretically by reaction-diffusion equations assuming a steady rate of tyramide-biotin free radical generation by the HRP enzyme and a constant probability throughout the nucleus of free-radical quenching (through reaction with protein tyrosine residues and nucleic acids). Second, we used the exponential decay constant measured by light microscopy together with FISH measurements of mean speckle distance for several genomic regions to fit an exponential function and to predict distance to nuclear speckles genome-wide directly from SON TSA-seq sequencing reads. Third, we used this approach to test the predictions against a new set of FISH measurements, demonstrating an accuracy of these predictions of ~50 nm.
(3) The importance of the quantitative validation by immuno-FISH of using TSA-seq to estimate mean distance to nuclear speckles is that it demonstrates the robustness of the TSA-seq approach. Specifically, it shows how the TSA-seq signal is predicted to depend only on the specificity of the primary and secondary antibody staining and the diffusion properties of the tyramide-biotin free radicals produced by the HRP peroxidase. This is fundamentally different from the significant dependence on antibodies and choice of marker proteins for molecular proximity assays such as DamID, ChIP-seq, and Cut and Run/Tag which depend on molecular proximity for labeling and/or pulldown of DNA.
This robustness leads to specific predictions. First, it predicts similar TSA-seq signals will be produced using antibodies against different marker proteins against the same nuclear compartment. This is because the exponential decay constant (distance at which the signal drops by one half) for the spreading of the TSA is in the range of several hundred nm, as measured by light microscopy for several TSA staining conditions. Indeed, we showed in the Chen et al, JCB 2018 paper that antibodies against two different nuclear speckle proteins produced very similar TSA-seq signals while antibodies against LMNB versus LMNA also produced very similar TSA-seq signals. Similarly, we showed in the Kumar et al preprint that antibodies against four different nucleolar proteins showed similar TSA-seq signals, with the highest correlation coefficients for the TSA-seq signals produced by the antibodies against two GC nucleolar marker proteins and the TSA-seq signals produced by the antibodies against two FC/DFC nucleolar marker proteins.
Author response image 2.
Comparison of TSA-seq data from different cell lines versus IMR90 MERFISH. The observed correlation between SON (nuclear speckle) TSA-seq versus MERFISH is nearly as high for TSA-seq data from HFF as it is for TSA-seq data from the IMR90 cell line (Alexander et al, Mol Cell 2021) in which the MERFISH was performed. The correlations for SON, LMNB1 (nuclear lamina) and MKI67IP (nucleolus) versus MERFISH are highest for HFF TSA-seq data as compared to TSA-seq data from other cell lines (H1, K562, HCT116). Comparison of measured distances to nuclear locale (y-axis) versus TSA-seq scores (x-axis) from different cell lines labeled in red. Left to right: SON, LMNB1, and MKI67IP. Top to bottom: SON TSA-seq versus MERFISH for two TSA-seq replicates; TSA-seq from HFF, H1, K562, and HCT116 versus MERFISH.
Second, it predicts that the quantitative relationship between TSA-seq signal and mean distance from a nuclear compartment will depend on the convolution of the predicted exponential decay of spreading of the TSA signal produced by a point source with the more complicated staining distribution of nuclear compartments such as the nuclear lamina or nucleoli. We successfully used this concept to explain the differences emerging between LMNB1 DamID and TSA-seq signals for flat nuclei and to recognize the polarized distribution of different LADs over the nuclear periphery.
(4) After our genomic data production and during our data analysis, a valuable resource from the Zhuang lab was published, using MERFISH to visualize hundreds of genomic loci in IMR90 cells. We acknowledge that the much more extensive validation of TSA-seq by the multiplexed immuno-FISH MERFISH data is dependent on the degree to which the nuclear genome organization is similar between IMR90 and HFF fibroblasts. However, the correlation between distances to nuclear speckles, nucleoli, and the nuclear lamina measured in IMR90 fibroblasts and the nuclear speckle, nucleolar, and nuclear lamina TSA-seq measured in HFF fibroblasts is already striking (See Author response image 1). With regard to SON TSA-seq, the MERFISH versus HFF TSA-seq correlation is close to what we observe using published IMR90 SON TSA-seq data (correlation coefficients of 0.89 (IMR90 TSA-seq) versus 0.86 (HFF TSA-seq). Moreover, this correlation is highest using TSA-seq data from HFF cells as compared to the three other cell lines. (see Author response image 2). We believe these correlations can be considered a lower bound on the actual correlations between the FISH distances and TSA-seq that we would have observed if we had performed both assays on the same cell line.
(5) Currently, we still require tens of millions of cells to perform each TSA-seq assay. This requires significant expansion of cells and a resulting increase in passage numbers of the IMR90 cells before we can perform the TSA-seq. During this expansion we observe a noticeable slowing of the IMR90 cell growth as expected for secondary cell lines as we approach the Hayflick limit. We still do not know to what degree nuclear organization relative to nuclear locales may change as a function of cell cycle composition (ie percentage of cycling versus quiescent cells) and cell age. Thus, even if we performed TSA-seq on IMR90 cells we would be comparing MERFISH from lower passages with a higher percentage of actively proliferating cells with TSA-seq from higher passages with a higher percentage of quiescent cells.
We are currently working on a new TSA-seq protocol that will work with thousands of cells. We believe it is better investment of time and resources to wait until this new protocol is optimized before we repeat TSA-seq in IMR90 cells for a better comparison with multiplexed FISH data.
Specific Comments in response to Reviewer 2:
(1) As we acknowledge in our Response summary, we were limited in the degree to which we could actually follow-up our findings with experiments designed to test specific hypotheses generated by our data. However, we do want to point out that our comparison of wild-type K562 cells with the LMNA/LBR double knockout was designed to test the long-standing model that nuclear lamina association of genomic loci contributes to gene silencing. This experiment was motivated by our surprising result that gene expression differences between cell lines correlated strongly with differences in positioning relative to nuclear speckles rather than the nuclear lamina. Despite documenting in these double knockout cells a decreased nuclear lamina association of most LADs, and an increased nuclear lamina association of the “p-w-v” fiLADs identified in this manuscript, we saw no significant change in gene expression in any of these regions as compared to wild-type K562 cells. Meanwhile, distances to nuclear speckles as measured by TSA-seq remained nearly constant.
We would argue that this represents a specific example in which new insights generated by our genomics comparison of cell lines led to a clear and specific hypothesis and the experimental testing of this hypothesis.
In response to Reviewer 2, we are modifying the text to make this clearer and to explicitly describe how we were testing the hypothesis that distance to nuclear lamina is correlated with but not causally linked to gene expression and how to test this hypothesis we used a DKO of LMNA and LBR to change distances relative to the nuclear lamina and to test the effect on gene expression.
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Reviewer #2 (Public Review):
Summary:
In this study, Liu et al. explore the interplay between G-quadruplexes (G4s) and R-loops. The authors developed novel techniques, HepG4-seq and HBD-seq, to capture and map these nucleic acid structures genome-wide in human HEK293 cells and mouse embryonic stem cells (mESCs). They identified dynamic, cell-type-specific distributions of co-localized G4s and R-loops, which predominantly localize at active promoters and enhancers of transcriptionally active genes. Furthermore, they assessed the role of helicase Dhx9 in regulating these structures and their impact on gene expression and cellular functions.
The manuscript provides a detailed catalogue of the genome-wide distribution of G4s and R-loops. However, the conceptual advance and the physiological relevance of the findings are not obvious. Overall, the impact of the work on the field is limited to the utility of the presented methods and datasets.
Strengths:
(1) The development and optimization of HepG4-seq and HBD-seq offer novel methods to map native G4s and R-loops.
(2) The study provides extensive data on the distribution of G4s and R-loops, highlighting their co-localization in human and mouse cells.
(3) The study consolidates the role of Dhx9 in modulating these structures and explores its impact on mESC self-renewal and differentiation.
Weaknesses:
(1) The specificity of the biotinylation process and potential off-target effects are not addressed. The authors should provide more data to validate the specificity of the G4-hemin.
(2) Other methods exploring a catalytic dead RNAseH or the HBD to pull down R-loops have been described before. The superior quality of the presented methods in comparison to existing ones is not established. A clear comparison with other methods (BG4 CUT&Tag-seq, DRIP-seq, R-CHIP, etc) should be provided.
(3) Although the study demonstrates Dhx9's role in regulating co-localized G4s and R-loops, additional functional experiments (e.g., rescue experiments) are needed to confirm these findings.
(4) The manuscript would benefit from a more detailed discussion of the broader implications of co-localized G4s and R-loops.
(5) The manuscript lacks appropriate statistical analyses to support the major conclusions.
(6) The discussion could be expanded to address potential limitations and alternative explanations for the results.
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Reviewer #3 (Public Review):
Summary:
The authors developed and optimized the methods for detecting G4s and R-loops independent of BG4 and S9.6 antibody, and mapped genomic native G4s and R-loops by HepG4-seq and HBD-seq, revealing that co-localized G4s and R-loops participate in regulating transcription and affecting the self-renewal and differentiation capabilities of mESCs.
Strengths:
By utilizing the peroxidase activity of G4-hemin complex and combining proximity labeling technology, the authors developed HepG4-seq (high throughput sequencing of hemin-induced proximal labelled G4s) , which can detect the dynamics of G4s in vivo. Meanwhile, the "GST-His6-2xHBD"-mediated CUT&Tag protocol (Wang et al., 2021) was optimized by replacing fusion protein and tag, the optimized HBD-seq avoids the generation of GST fusion protein aggregates and can reflect the genome-wide distribution of R-loops in vivo.
The authors employed HepG4-seq and HBD-seq to establish comprehensive maps of native co-localized G4s and R-loops in human HEK293 cells and mouse embryonic stem cells (mESCs). The data indicate that co-localized G4s and R-loops are dynamically altered in a cell type-dependent manner and are largely localized at active promoters and enhancers of transcriptionally active genes.
Combined with Dhx9 ChIP-seq and co-localized G4s and R-loops data in wild-type and dhx9KO mESCs, the authors confirm that the helicase Dhx9 is a direct and major regulator that regulates the formation and resolution of co-localized G4s and R-loops.
Depletion of Dhx9 impaired the self-renewal and differentiation capacities of mESCs by altering the transcription of co-localized G4s and R-loops-associated genes.
In conclusion, the authors provide an approach to studying the interplay between G4s and R-loops, shedding light on the important roles of co-localized G4s and R-loops in development and disease by regulating the transcription of related genes.
Weaknesses:
As we know, there are at least two structure data of S9.6 antibody very recently, and the questions about the specificity of the S9.6 antibody on RNA:DNA hybrids should be finished. The authors referred to (Hartono et al., 2018; Konig et al., 2017; Phillips et al., 2013) need to be updated, and the authors' bias against S9.6 antibodies needs also to be changed. However, as the authors had questioned the specificity of the S9.6 antibody, they should compare it in parallel with the data they have and the data generated by the widely used S9.6 antibody.
Although HepG4-seq is an effective G4s detection technique, and the authors have also verified its reliability to some extent, given the strong link between ROS homeostasis and G4s formation, and hemin's affinity for different types of G4s, whether HepG4-seq reflects the dynamics of G4s in vivo more accurately than existing detection techniques still needs to be more carefully corroborated.
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Author response:
eLife assessment
This useful study describes an antibody-free method to map G-quadruplexes (G4s) in vertebrate cells. While the method might have potential, the current analysis is primarily descriptive and does not add substantial new insights beyond existing data (e.g., PMID:34792172). While the datasets provided might constitute a good starting point for future functional studies, additional data and analyses would be needed to fully support the major conclusions and, at the same time, clarify the advantage of this method over other methods. Specifically, the strength of the evidence for DHX9 interfering with the ability of mESCs to differentiate by regulating directly the stability of either G4s or R-loops is still incomplete.
We thank the editors for their helpful comments.
Given that antibody-based methods have been reported to leave open the possibility of recognizing partially folded G4s and promoting their folding, we have employed the peroxidase activity of the G4-hemin complex to develop a new method for capturing endogenous G4s that significantly reduces the risk of capturing partially folded G4s. We will be happy to clarify the advantage of our method.
In the Fig. 7, we applied the Dhx9 CUT&Tag assay to identify the G4s and R-loops directly bound by Dhx9 and further characterized the differential Dhx9-bound G4s and R-loops in the absence of Dhx9. Dhx9 is a versatile helicase capable of directly resolving R-loops and G4s or promoting R-loop formation (PMID: 21561811, 30341290, 29742442, 32541651, 35905379, 34316718). Furthermore, we showed that depletion of Dhx9 significantly altered the levels of G4s or R-loops around the TSS or gene bodies of several key regulators of mESC and embryonic development, such as Nanog, Lin28a, Bmp4, Wnt8a, Gata2, and Lef1, and also their RNA levels (Fig.7 I). The above evidence is sufficient to support the transcriptional regulation of mESCs cell fate by directly modulating the G4s or R-loops within the key regulators of mESCs.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
Non-B DNA structures such as G4s and R-loops have the potential to impact genome stability, gene transcription, and cell differentiation. This study investigates the distribution of G4s and R-loops in human and mouse cells using some interesting technical modifications of existing Tn5-based approaches. This work confirms that the helicase DHX9 could regulate the formation and/or stability of both structures in mouse embryonic stem cells (mESCs). It also provides evidence that the lack of DHX9 in mESCs interferes with their ability to differentiate.
Strengths:
HepG4-seq, the new antibody-free strategy to map G4s based on the ability of Hemin to act as a peroxidase when complexed to G4s, is interesting. This study also provides more evidence that the distribution pattern of G4s and R-loops might vary substantially from one cell type to another.
We appreciate your valuable points.
Weaknesses:
This study is essentially descriptive and does not provide conclusive evidence that lack of DHX9 does interfere with the ability of mESCs to differentiate by regulating directly the stability of either G4 or R-loops. In the end, it does not substantially improve our understanding of DHX9's mode of action.
In this study, we aimed to report new methods for capturing endogenous G4s and R-loops in living cells. Dhx9 has been reported to directly unwind R-loops and G4s or promote R-loop formation (PMID: 21561811, 30341290, 29742442, 32541651, 35905379, 34316718). To understand the direct Dhx9-bound G4s and R-loops, we performed the Dhx9 CUT&Tag assay and analyzed the co-localization of Dhx9-binding sites and G4s or R-loops. We found that 47,857 co-localized G4s and R-loops are directly bound by Dhx9 in the wild-type mESCs and 4,060 of them display significantly differential signals in absence of Dhx9, suggesting that redundant regulators exist as well. We showed that depletion of Dhx9 significantly altered the RNA levels of several key regulators of mESC and embryonic development, such as Nanog, Lin28a, Bmp4, Wnt8a, Gata2, and Lef1, which coincides with the significantly differential levels of G4s or R-loops around the TSS or gene bodies of these genes (Fig.7). The comprehensive molecular mechanism of Dhx9 action is indeed not the focus of this study. We will work on it in the future studies. Thank you for the comments.
There is no in-depth comparison of the newly generated data with existing datasets and no rigorous control was presented to test the specificity of the hemin-G4 interaction (a lot of the hemin-dependent signal seems to occur in the cytoplasm, which is unexpected).
The specificity of hemin-G4-induced peroxidase activity and self-biotinylation has been well demonstrated in previous studies (PMID: 19618960, 22106035, 28973477, 32329781). In the Fig.1A, we compared the hemin-G4-induced biotinylation levels in different conditions. Cells treated with hemin and Bio-An exhibited a robust fluorescence signal, while the absence of either hemin or Bio-An almost completely abolished the biotinylation signals, suggesting a specific and active biotinylation activity. To identify the specific signals, we have included the non-label control and used this control to call confident HepG4 peaks in all HepG4-seq assays.
The hemin-RNA G4 complex has also been reported to have mimic peroxidase activity and trigger similar self-biotinylation signals as DNA G4s (PMID: 32329781, 31257395, 27422869). Therefore, it is not surprising to observe hemin-dependent signals in the cytoplasm generated by cytoplasmic RNA G4s.
In the revised version, we will include careful comparison between our data and previous datasets.
The authors talk about co-occurrence between G4 and R-loops but their data does not actually demonstrate co-occurrence in time. If the same loci could form alternatively either R-loops or G4 and if DHX9 was somehow involved in determining the balance between G4s and R-loops, the authors would probably obtain the same distribution pattern. To manipulate R-loop levels in vivo and test how this affects HEPG4-seq signals would have been helpful.
Single-molecule fluorescence studies have shown the existence of a positive feedback mechanism of G4 and R-loop formation during transcription (PMID: 32810236, 32636376), suggesting that G4s and Rloops could co-localize at the same molecule. Dhx9 is a versatile helicase capable of directly resolving R-loops and G4s or promoting R-loop formation (PMID: 21561811, 30341290, 29742442, 32541651, 35905379, 34316718). Although depletion of Dhx9 resulted in 6,171 Dhx9-bound co-localized G4s and R-loops with significantly altered levels of G4s or R-loops, only 276 of them (~4.5%) harbored altered G4s and R-loops, suggesting that the interacting G4s and R-loops are rare in living cells. Nowadays, the genome-wide co-occurrence of two factors are mainly obtained by bioinformatically intersection analysis. We agreed that the heterogenous distribution between cells will give false positive co-occurrence patterns. We will carefully discuss this point in the revised version. At the same time, we will make efforts to develop a new method to map the co-localized G4 and R-loop in the same molecule in the future study.
This study relies exclusively on Tn5-based mapping strategies. This is a problem as global changes in DNA accessibility might strongly skew the results. It is unclear at this stage whether the lack of DHX9, BLM, or WRN has an impact on DNA accessibility, which might underlie the differences that were observed. Moreover, Tn5 cleaves DNA at a nearby accessible site, which might be at an unknown distance away from the site of interest. The spatial accuracy of Tn5-based methods is therefore debatable, which is a problem when trying to demonstrate spatial co-occurrence. Alternative mapping methods would have been helpful.
In this study, we used the recombinant streptavidin monomer and anti-GP41 nanobody fusion protein (mSA-scFv) to specifically recognize hemin-G4-induced biotinylated G4 and then recruit the recombinant GP41-tagged Tn5 protein to these G4s sites. Similarly, the recombinant V5-tagged N-terminal hybrid-binding domain (HBD) of RNase H1 specifically recognizes R-loops and recruit the recombinant protein G-Tn5 (pG-Tn5) with the help of anti-V5 antibody. Therefore, the spatial distance of Tn5 to the target sites is well controlled and very short, and also the recruitment of Tn5 is specifically determined by the existence of G4s in HepG4-seq and R-loops in HBD-seq.
Reviewer #2 (Public Review):
Summary:
In this study, Liu et al. explore the interplay between G-quadruplexes (G4s) and R-loops. The authors developed novel techniques, HepG4-seq and HBD-seq, to capture and map these nucleic acid structures genome-wide in human HEK293 cells and mouse embryonic stem cells (mESCs). They identified dynamic, cell-type-specific distributions of co-localized G4s and R-loops, which predominantly localize at active promoters and enhancers of transcriptionally active genes. Furthermore, they assessed the role of helicase Dhx9 in regulating these structures and their impact on gene expression and cellular functions.
The manuscript provides a detailed catalogue of the genome-wide distribution of G4s and R-loops. However, the conceptual advance and the physiological relevance of the findings are not obvious. Overall, the impact of the work on the field is limited to the utility of the presented methods and datasets.
Strengths:
(1) The development and optimization of HepG4-seq and HBD-seq offer novel methods to map native G4s and R-loops.
(2) The study provides extensive data on the distribution of G4s and R-loops, highlighting their co-localization in human and mouse cells.
(3) The study consolidates the role of Dhx9 in modulating these structures and explores its impact on mESC self-renewal and differentiation.
We appreciate your valuable points.
Weaknesses:
(1) The specificity of the biotinylation process and potential off-target effects are not addressed. The authors should provide more data to validate the specificity of the G4-hemin.
The specificity of hemin-G4-induced peroxidase activity and self-biotinylation has been well demonstrated in previous studies (PMID: 19618960, 22106035, 28973477, 32329781). In the Fig.1A, we compared the hemin-G4-induced biotinylation levels in different conditions. Cells treated with hemin and Bio-An exhibited a robust fluorescence signal, while the absence of either hemin or Bio-An almost completely abolished the biotinylation signals, suggesting a specific and active biotinylation activity.
(2) Other methods exploring a catalytic dead RNAseH or the HBD to pull down R-loops have been described before. The superior quality of the presented methods in comparison to existing ones is not established. A clear comparison with other methods (BG4 CUT&Tag-seq, DRIP-seq, R-CHIP, etc) should be provided.
Thank you for the suggestions. We will include the comparisons in the revised version.
(3) Although the study demonstrates Dhx9's role in regulating co-localized G4s and R-loops, additional functional experiments (e.g., rescue experiments) are needed to confirm these findings.
Dhx9 has been demonstrate as a versatile helicase capable of directly resolving R-loops and G4s or promoting R-loop formation in previous studies (PMID: 21561811, 30341290, 29742442, 32541651, 35905379, 34316718). We believe that the current new dataset and previous studies are enough to support the capability of Dhx9 in regulating co-localized G4s and R-loops.
(4) The manuscript would benefit from a more detailed discussion of the broader implications of co-localized G4s and R-loops.
Thank you for the suggestions. We will include a more detailed discussion in the revised version.
(5) The manuscript lacks appropriate statistical analyses to support the major conclusions.
We apologized for this point. Whereas we have applied careful statistical analyses in this study, lacking of some statistical details make people hard to understand some conclusions. We will carefully add details of all statistical analysis.
(6) The discussion could be expanded to address potential limitations and alternative explanations for the results.
Thank you for the suggestions. We will include a more detailed discussion about this point in the revised version.
Reviewer #3 (Public Review):
Summary:
The authors developed and optimized the methods for detecting G4s and R-loops independent of BG4 and S9.6 antibody, and mapped genomic native G4s and R-loops by HepG4-seq and HBD-seq, revealing that co-localized G4s and R-loops participate in regulating transcription and affecting the self-renewal and differentiation capabilities of mESCs.
Strengths:
By utilizing the peroxidase activity of G4-hemin complex and combining proximity labeling technology, the authors developed HepG4-seq (high throughput sequencing of hemin-induced proximal labelled G4s), which can detect the dynamics of G4s in vivo. Meanwhile, the "GST-His6-2xHBD"-mediated CUT&Tag protocol (Wang et al., 2021) was optimized by replacing fusion protein and tag, the optimized HBD-seq avoids the generation of GST fusion protein aggregates and can reflect the genome-wide distribution of R-loops in vivo.
The authors employed HepG4-seq and HBD-seq to establish comprehensive maps of native co-localized G4s and R-loops in human HEK293 cells and mouse embryonic stem cells (mESCs). The data indicate that co-localized G4s and R-loops are dynamically altered in a cell type-dependent manner and are largely localized at active promoters and enhancers of transcriptionally active genes.
Combined with Dhx9 ChIP-seq and co-localized G4s and R-loops data in wild-type and dhx9KO mESCs, the authors confirm that the helicase Dhx9 is a direct and major regulator that regulates the formation and resolution of co-localized G4s and R-loops.
Depletion of Dhx9 impaired the self-renewal and differentiation capacities of mESCs by altering the transcription of co-localized G4s and R-loops-associated genes.
In conclusion, the authors provide an approach to studying the interplay between G4s and R-loops, shedding light on the important roles of co-localized G4s and R-loops in development and disease by regulating the transcription of related genes.
We appreciate your valuable points.
Weaknesses:
As we know, there are at least two structure data of S9.6 antibody very recently, and the questions about the specificity of the S9.6 antibody on RNA:DNA hybrids should be finished. The authors referred to (Hartono et al., 2018; Konig et al., 2017; Phillips et al., 2013) need to be updated, and the authors' bias against S9.6 antibodies needs also to be changed. However, as the authors had questioned the specificity of the S9.6 antibody, they should compare it in parallel with the data they have and the data generated by the widely used S9.6 antibody.
Thank you for the updating information about the structure data of S9.6 antibody. We politely disagree the specificity of the S9.6 antibody on RNA:DNA hybrids. The structural studies of S9.6 (PMID: 35347133, 35550870) used only one RNA:DNA hybrid to show the superior specificity of S9.6 on RNA:DNA hybrid than dsRNA and dsDNA. However, Fabian K. et al has reported that the binding affinities of S9.6 on RNA:DNA hybrid exhibits obvious sequence-dependent bias from null to nanomolar range (PMID: 28594954). We will include the comparison between S9.6-derived data and our HBD-seq data in the revised version.
Although HepG4-seq is an effective G4s detection technique, and the authors have also verified its reliability to some extent, given the strong link between ROS homeostasis and G4s formation, and hemin's affinity for different types of G4s, whether HepG4-seq reflects the dynamics of G4s in vivo more accurately than existing detection techniques still needs to be more carefully corroborated.
Thank you for pointing out this issue. In the in vitro hemin-G4 induced self-biotinylation assay, parallel G4s exhibit higher peroxidase activities than anti-parallel G4s. Thus, the dynamics of G4 conformation could affect the HepG4-seq signals (PMID: 32329781). In the future, people may need to combine HepG4-seq and BG4s-eq to carefully explain the endogenous G4s. We will carefully discuss this point in the revised version.
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Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
This paper by Beath et. al. identifies a potential regulatory role for proteins involved in cytoplasmic streaming and maintaining the grouping of paternal organelles: holding sperm contents in the fertilized embryos away from the oocyte meiotic spindle so that they don't get ejected into the polar body during meiotic chromosome segregation. The authors show that by time-lapse video, paternal mitochondria (used as a readout for sperm and its genome) is excluded from yolk granules and maternal mitochondria, even when moving long distances by cytoplasmic streaming. To understand how this exclusion is accomplished, they first show that it is independent of both internal packing and the engulfment of the paternal chromosomes by maternal endoplasmic reticulum creating an impermeable barrier. They then test whether the control of cytoplasmic steaming affects this exclusion by knocking down two microtubule motors, Katanin and kinesis I. They find that the ER ring, which is used as a proxy for paternal chromosomes, undergoes extensive displacement with these treatments during anaphase I and interacts with the meiotic spindle, supporting their hypothesis that the exclusion of paternal chromosomes is regulated by cytoplasmic streaming. Next, they test whether a regulator of maternal ER organization, ATX-2, disrupts sperm organization so that they can combine the double depletion of ATX-2 and KLP-7, presumably because klp-7 RNAi (unlike mei-1 RNAi) does not affect polar body extrusion and they can report on what happens to paternal chromosomes. They find that the knockdown of both ATX-2 and KLP-7 produces a higher incidence of what appears to be the capture of paternal chromosomes by the meiotic spindle (5/24 vs 1/25). However, this capture event appears to halt the cell cycle, preventing the authors from directly observing whether this would result in the paternal chromosomes being ejected into the polar body.
Strengths:
This is a useful, descriptive paper that highlights a potential challenge for embryos during fertilization: when fertilization results in the resumption of meiotic divisions, how are the paternal and maternal genomes kept apart so that the maternal genome can undergo chromosome segregation and polar body extrusion without endangering the paternal genome? In general, the experiments are well-executed and analyzed. In particular, the authors' use of multiple ways to knock down ATX-2 shows rigor.
Weaknesses:
The paper makes a case that this regulation may be important but the authors should do some additional work to make this case more convincing and accessible for those outside the field. In particular, some of the figures could include greater detail to support their conclusions, they could explain the rationale for some experiments better and they could perform some additional control experiments with their double depletion experiments to better support their interpretations. Also, the authors' inability to assess the functional biological consequences of the capture of the sperm genome by the oocyte spindle should be discussed, particularly in light of the cell cycle arrest that they observe.
These general comments are addressed in the more specific critiques below.
Reviewer #2 (Public Review):
Summary
In this manuscript, Beath et al. use primarily C. elegans zygotes to test the overarching hypothesis that cytoplasmic mechanisms exit to prevent interaction between paternal chromosomes and the meiotic spindle, which are present in a shared zygotic cytoplasm after fertilization. Previous work, much of which by this group, had characterized cytoplasmic streaming in the zygote and the behavior of paternal components shortly after fertilization, primarily the clustering of paternal mitochondria and membranous organelles around the paternal chromosomes. This work set out to identify the molecular mechanisms responsible for that clustering and test the specific hypothesis that the "paternal cloud" helps prevent the association of paternal chromosomes with the meiotic spindle.
Strengths
This work is a collection of technical achievements. The data are primarily 3- and 4-channel time-lapse images of zygotes shortly after fertilization, which were performed inside intact animals. There are many instances in which the experiments show extreme technical skill, such as tracking the paternal chromosomes over large displacements throughout the volume of the embryo. The authors employ a wide variety of fluorescent reporters to provide a remarkably clear picture of what is going on in the zygote. These reagents and the novel characterization of these stages that they provide will be widely beneficial to the community.
The data provide direct visualization of what had previously been a mostly hypothetical structure, the "paternal cloud," using simultaneous labeling of paternal DNA and mitochondria in combination with a variety of maternal proteins including maternal mitochondria, yolk granules, tubulin, and plasma membrane. Together, these images provided convincing evidence of the existence of this specified cytoplasmic domain. They go on to show that the knockdown of the ataxin-2 homolog ALX-2, a protein previously shown to affect ER dynamics, disrupted the paternal cloud, identifying a role for ER organization in this structure.
The authors then used the system to test the functional consequences of perturbing the cytoplasmic organization. Consistent with the paternal cloud being a stable structure, it stayed intact during large movements the authors generated using previously published knockdowns (of mei-1/katanin and kinesin-13/kpl-7) that increased cytoplasmic streaming. They used this data to document instances in which the paternal chromosomes were likely to have been attached to the spindle. They concluded with direct evidence of spindle fibers connecting to the paternal chromatin upon knockdown of ATX-2 in combination with increased cytoplasmic streaming, providing strong, direct support for their overarching hypothesis.
Weaknesses
While the data is convincing, the narrative of the paper could be streamlined to highlight the novelty of the experiments and better articulate the aims. For example, the cloud of paternal mitochondria and membranous organelles was previously shown, but Figures 1-2 largely reiterate that observation. The innovation seems to be that the combination of ER, yolk, and maternal mitochondrial markers makes the existence of a specified domain more concrete. There are also some instances where more description is needed to make the conclusions from the images clear.
These general comments are addressed in the more specific critiques below.
The manuscript intersperses what read like basic characterizations of fluorescent markers that, as written, can distract from the main story. The authors characterized the dynamics of ER organization throughout the substages of meiosis and the permeability of the envelope of ER that surrounds the paternal chromatin, but it could be more clearly established how the ability to visualize these structures allowed them to address their aims.
We have added the following after the initial description of ER morphology changes: (ER morphology was used to determine cell-cycle stages during live imaging reported below in Fig. 6.)
More background on what was previously known about ER organization in M-phase and the role of ataxin proteins specifically may help provide more continuity.
We have added references to transitions to ER sheets during mitotic M-phase in HeLa cells and Xenopus extracts.
Reviewer #3 (Public Review):
Summary:
This study by Beath et al. investigated the mechanisms by which sperm DNA is excluded from the meiotic spindle after fertilization. Time-lapse imaging revealed that sperm DNA is surrounded by paternal mitochondria and maternal ER that is permeable to proteins. By increasing cytoplasmic streaming using kinesin-13 or katanin RNAi, the authors demonstrated that limiting cytoplasmic streaming in the embryo is an important step that prevents the capture of sperm DNA by the oocyte meiotic spindle. Further experiments showed that the Ataxin-2 protein is required to hold paternal mitochondria together and close to the sperm DNA. Finally, double depletion of kinesin-13 and Ataxin-2 suggested an increased risk of meiotic spindle capture of sperm DNA.
Overall, this is an interesting finding that could provide a new understanding of how meiotic spindle capture of sperm DNA and its accidental expulsion into the polar body is prevented. However, some conceptual gaps need to be addressed and further experiments and improved data analyses would strengthen the paper.
- It would be helpful if the authors could discuss in good detail how they think maternal ER surrounds the sperm DNA
We have added 2 references to papers about nuclear envelope re-assembly from Shirin Bahmanyar’s lab and suggest the ER envelope is a halted intermediate in nuclear envelope reassembly.
and why is it not disrupted following Ataxin disruption.
We have been attempting to disrupt ER structures in the meiotic embryo for the last 5 years by depleting profilin, BiP, atlastin, ATX-2 and by optogenetically packing ER into a ball in the middle of the oocyte. None of these treatments prevent envelopment of the sperm DNA by maternal ER. None of these treatments remove ER from the spindle envelope and none remove ER from the plasma membrane. These treatments mostly result in “large aggregates” of ER that we have not examined by EM. Wild speculation: any disruption of the ER strong enough to prevent ER envelopment around chromatin would be sterile because the M to S transition in the mitotic zone of the germline would be blocked. Rapid depletion of ATX-2 to the extent shown by rigorous data in this manuscript does not prevent ER envelopment around chromatin. We chose not to speculate about the reasons for this because we do not know why.
- Since important phenotypes revealed in RNAi experiments (e.g. kinesin-13 and ataxin-2 double depletion) are not very robust, the authors should consider toning down their conclusions and revising some of their section headings. I appreciate that they are upfront about some limitations, but they do nonetheless make strong concluding sentences.
We have changed the discussion of the klp-7 atx-2 double depletion to: “The capture of the sperm DNA by the meiotic spindle in ATX-2 KLP-7 double depleted embryos suggests that the integrity of the exclusion zone around the sperm DNA might insulate the sperm DNA from spindle microtubules. However, a much larger number of klp-7(RNAi) singly depleted and atx-2(degron) singly depleted time-lapse sequences are needed to rigorously support this idea. “
- The discussion section could be improved further to present the authors' findings in the larger context of current knowledge in the field.
We have expanded the discussion as suggested.
- The authors previously demonstrated that F-actin prevents meiotic spindle capture of sperm DNA in this system. However, the current manuscript does not discuss how the katanin, kinesin-13 and Ataxin-2 mechanisms could work together with previously established functions of F-actin in this process.
We have added pfn-1(RNAi) to the discussion section.
- How can the authors exclude off-target effects in their RNAi depletion experiments? Can kinesin-13, katanin, and Ataxin phenotypes be rescued for instance?
For ataxin-2 phenotypes, two completely independent controls for off target effects are shown. GFP(RNAi) on a strain with and endogenous ATX-2::GFP tag vs GFP(RNAi) on a strain with no tag on the ATX-2. ATX-2::AID with or without auxin. For kinesin-13 and katanin, we did not do a rigorous control for off-target effects of RNAi. However, the effects of these depletions on cytoplasmic microtubules have been previously reported by others
- How are the authors able to determine if the paternal genome was actually captured by the spindle? Does lack of movement definitively suggest capture without using a spindle marker?
mKate::tubulin labels the spindle in each capture event. This can be seen in Video S3. for mei-1(RNAi) and Figure 9 for atx-2 klp-7 double depletions.
(1) Major issues:
The images provided are not convincing that mitochondria are entirely excluded from the regions with yolk granules from the images provided. Please provide insets of magnified images of the paternal mitochondria in Figure 1E to more clearly show the exclusion even when paternal mitochondria are streaming. Providing grayscale images, individual z-sections and/or some quantification of this data might also be more convincing to this reviewer.
We have modified Fig. 1 by adding single wavelength magnified insets to more clearly show that paternal mitochondria are in a “black hole” in the maternal yolk granules during cytoplasmic streaming.
Figure 2 -This figure can be retitled to highlight that the paternal organelle cloud is impermeable to mitochondria and conserved.
The legend has been re-titled as suggested.
Figure 3B, An image of the DNA within the ring of maternal ER especially since the maternal ER ring is used as a proxy for the paternal chromosomes in later figures would strengthen the authors' claims.
We have added a panel showing DAPI-stained DNA in the center of the ER ring and paternal mitochondria cloud.
Why is the faster time scale imaging significant? I think this could be more clearly set up in the paper. Perhaps rapid imaging of maternal mito-labeled kca-1(RNAi) embryos would better show the difference in time scale, with the expectation that the paternal cloud forms and persists while the ER invades.
We are not sure what the reviewer means. 5 sec time intervals were used throughout the paper. We are also not sure how kca-1(RNAi) would help. Movement of the entire oocyte into and out of the spermatheca is what limits the ability to keep a fusing sperm in focus. kca-1(RNAi) would prevent cytoplasmic streaming but not ovulation movements.
Figure 4 - The question about the permeability of the ER envelope seems to come out of nowhere as written. It isn't clear how it contributes to the larger story about preventing sperm incorporation in the spindle.
This section of the results is introduced with: “If the maternal ER envelope around sperm DNA was sealed and impermeable during meiosis, this could both prevent the sperm DNA from inducing ectopic spindle assembly and prevent the sperm DNA from interacting with meiotic spindle microtubules.”
The data in Figure 4 would probably not be expected to be in this paper based on the paper title. Maybe the title needs something about ER dynamics? "eg. ATX-2 but not an ER envelope" isolates the paternal chromatin?
In Figure 5, it seems that RNAi of klp-7 and Mei-1 had slightly different effects on short-axis displacement of the ER envelope (klp-7 affecting it more dramatically than mei-1) and slightly different effects on interaction with the meiotic spindle (capture vs streaming past the spindle). The authors mention in their discussion that the difference in the interaction with the meiotic spindle might reflect the effects that loss of Mei-1 may have on the spindle but could it also be a consequence of the differences in cytoplasmic streaming observed?
With our current data, the only statistically significant difference between cytoplasmic streaming of the sperm contents in mei-1(RNAi) vs klp-7(RNAi) is that excessive streaming persists longer into metaphase II in klp-7(RNAi). We have added a sentence describing this difference to the results. If differences in streaming were the cause of different capture frequencies, then klp-7(RNAi) would cause more capture events than mei-1(RNAi) but the opposite was observed. We have avoided too much discussion here because the frequency of capture events is too low to demonstrate statistically significant differences between mei-1(RNAi), klp-7(RNAi), and atx-2(degron) + klp-7(RNAi) without a very large increase in the number of time-lapse sequences.
Also, the authors should find a way to represent this interaction with the meiotic spindle in a quantitative or table form to allow the reader to observe some of the patterns they report more easily.
We have added a table to Fig. 9 that summarizes capture data.
Finally, can the authors report when they observe the closest association with the meiotic spindle: Does it correlate with the period of greatest displacement (AI) or are they unlinked?
The low frequency of capture events makes it difficult to test this rigorously.
Figure 6- 'Endogenously tagged ATX-2 was observed throughout oocytes and meiotic embryos without partial co-localization with ER.' How can the authors exclude co-localization with ER?
We have changed the wording to: “Endogenously tagged ATX-2 was observed throughout oocytes and meiotic embryos (Fig. 6A; Fig. S2). ATX-2 did not uniquely co-localize with ER (Fig. S2).“
The rationale for why the authors think that the integrity of sperm organelles is important to keep the genomes apart is not clear to this reviewer and needs to be explained better. Moving the discussion of the displacement experiments in Figure S3 from the end of the results section to the ATX-2 knockdown section would help accomplish this.
We have added the sentence: “The frequency of sperm capture by the meiotic spindle (Fig. 9D) was significantly higher than wild-type controls in klp-7(RNAi) atx-2(AID) double depleted embryos (p=0.011 Fisher’s exact test). Although the number of single mutant embryos analyzed was too low to demonstrate a significant difference between single and double mutant embryos, these results qualitatively support the hypothesis that limiting cytoplasmic streaming and maintaining the integrity of the ball of paternal mitochondria are both important for preventing capture events between the meiotic spindle and sperm DNA.”
It looks like, in the double knockdown of ATX-2 and KLP-7, the spread of paternal mitochondria is less affected than when only ATX-2 is depleted. What effect does this result have on the observation that the incidence of sperm capture appears to increase in the double depletion? What does displacement of the ER ring look like in the double depletion? Is it additive, consistent with their interpretation that both limiting cytoplasmic streaming and maintaining the integrity of the ball of paternal mitochondria is required to keep the genomes separate?
We cannot show a significant difference between single a double knockdowns without increasing n by alot. We did not analyze ER ring displacement in the double mutant.
Is the increased incidence of capture in the double-depleted embryos significant?
We have added the sentence: “The frequency of sperm capture by the meiotic spindle (Fig. 9D) was significantly higher than wild-type controls in klp-7(RNAi) atx-2(AID) double depleted embryos (p=0.011 Fisher’s exact test). Although the number of single mutant embryos analyzed was too low to demonstrate a significant difference between single and double mutant embryos, these results qualitatively support the hypothesis that limiting cytoplasmic streaming and maintaining the integrity of the ball of paternal mitochondria are both important for preventing capture events between the meiotic spindle and sperm DNA.”
What do the authors make of the cell cycle arrest observed when paternal chromosomes are captured? Is there an argument to be made that this arrest supports the idea that preventing this capture is actively regulated and therefore functionally important?
We chose not to discuss the mechanism of this arrest because considerably more work would be required to prove that it is not caused by a combination of imaging conditions and genotype. The low frequency of these capture + arrest events would make it very difficult to show that the arrest does not occur after depleting a checkpoint protein.
(2) Minor concerns:
Top of page 4: "streaming because depletion tubulin stops cytoplasmic streaming (7)" should be "streaming because depletion of tubulin stops cytoplasmic streaming (7)"
The ”of” has been inserted.
Page 6: "This result indicated that the volume of paternal mitochondria excludes maternal mitochondria and yolk granules but not maternal ER." The authors have only shown this for maternal mitochondria, not yolk granules.
We have deleted the mention of yolk granules here.
Page 7: "These results suggest that all maternal membranes are initially excluded from the sperm at fusion." Should be "These results show that maternal ER are initially excluded from the sperm at fusion. Since maternal mitochondria and yolk granules are excluded later, this suggests that all maternal membranes are initially excluded from the sperm at fusion."
We have changed this sentence as suggested.
It's not clear why the authors show other types of movement that might be quantified when cytoplasmic streaming is affected in Figure 5A and only quantify long-axis and short-axis displacement.
We have deleted the other types of movement from the schematic. Although these parameters were quantified, we did not include this data in the results so it would be confusing for the reader to have them in the schematic.
Bottom of page 7: Mention that the GFP::BAF-1 was maternally provided.
We have added “Maternally provided..”
Missing an Arrow on Figure 1A 9:20.
We removed the text citation to an arrow in Fig. 1A because we moved most of the description of the ER ring to Fig. 3 to address other reviewer suggestions.
Supplemental videos should be labeled appropriately to indicate what structures are labeled. It is currently difficult to understand what is being shown.
(3) Issues with the Discussion section:
"The simplest explanation is that cytoplasm does not mix during the 45 min from GVBD to pronucleus formation due to the high viscosity of cytoplasm." - Citation page 12.
We have changed the sentence to: “The simplest hypothesis is that maternal and paternal cytoplasm might not mix during the 45 min from GVBD to pronucleus formation due to the high viscosity of cytoplasm.”
"The higher frequency of capture of the sperm DNA by the meiotic spindle in ATX-2 KLP-7 double depleted embryos compared with either single depletion suggests that the integrity of the exclusion zone around the sperm DNA may insulate the sperm DNA from spindle microtubule" - Pages 12-13 reference the figures.
This sentence has been rewritten in response to other comments but the new sentence now references revised Fig. 9.
"ATX-2 is required to maintain the integrity of the ball of paternal mitochondria around the sperm DNA, but the mechanism is unknown." - Page 13 reference figure.
A reference to Figs 7 and 8 has been inserted.
" In control embryos, the sperm contents rarely came near the meiotic spindle in agreement with a previous study that found that male and female pronuclei rarely form next to each other (6). Streaming of the sperm contents was most commonly restricted to a jostling motion with little net displacement, circular streaming in the short axis of the embryo, or long axis streaming in which the sperm turned away from the spindle before the halfway point of the embryo. Depletion of MEI-1 or KLP-7 resulted in longer excursions of the sperm contents in the long axis of the embryo toward the spindle but frequent capture of the sperm by the spindle was only observed in mei-1(RNAi)." - Page 13, the corresponding figures need to be referenced for these sentences.
We have inserted figure references.
"In capture events observed after double depletion of ATX-2 and KLP-7, a bundle of microtubules was discernible extending from the spindle into the ER envelope surrounding the sperm DNA. Such bundles were not observed in mei-1(RNAi) capture events, likely because of the previously reported low density of microtubules in mei-1(RNAi) spindles (36, 37)." - Pages 13-14 references figures here.
We have inserted figure references.
"The higher frequency of capture of the sperm DNA by the meiotic spindle in ATX-2 KLP-7 double depleted embryos compared with either single depletion suggests that the integrity of the exclusion zone around the sperm DNA may insulate the sperm DNA from spindle microtubules." - This should be toned down since this phenotype is not robust.
We have changed this to: “The capture of the sperm DNA by the meiotic spindle in ATX-2 KLP-7 double depleted embryos suggests that the integrity of the exclusion zone around the sperm DNA might insulate the sperm DNA from spindle microtubules. However, a much larger number of klp-7(RNAi) singly depleted and atx-2(degron) singly depleted time-lapse sequences are needed to rigorously support this idea. “
ATX-2 depletion alters ER morphology but does not impact the maternal ER envelope - could the authors provide a potential explanation for this?
In the discussion, we cite papers showing that ATX-2 depletion affects many different cellular processes so the effect we see on paternal mitochondria might have nothing to do with the ER ring. We have been attempting to disrupt ER structures in the meiotic embryo for the last 5 years by depleting profilin, BiP, atlastin, ATX-2 and by optogenetically packing ER into a ball in the middle of the oocyte. None of these treatments prevent envelopment of the sperm DNA by maternal ER. None of these treatments remove ER from the spindle envelope and none remove ER from the plasma membrane. These treatments mostly result in “large aggregates” of ER that we have not examined by EM. Wild speculation: any disruption of the ER strong enough to prevent ER envelopment around chromatin would be sterile because the M to S transition in the mitotic zone of the germline would be blocked. Rapid depletion of ATX-2 to the extent shown by rigorous data in this manuscript does not prevent ER envelopment around chromatin. We chose not to speculate about the reasons for this because we do not know why.
It would be good to have representative images of what the altered spindle looks like in MEI-1-depleted oocytes.
The structure of MEI-1-depleted spindles has been described in the cited references.
"Depletion of MEI-1 or KLP-7 resulted in longer excursions of the sperm contents in the long axis of the embryo toward the spindle but frequent capture of the sperm by the spindle was only observed in mei-1(RNAi)" - It is intriguing that this does not happen in the double depletion experiments of kinesin-13 and ATX-2. The authors should perhaps discuss this.
This does happen in KLP-7 ATX-2 double depleted embryos as shown in Fig. 9.
(4) Missing citations:
"This analysis was restricted to embryos from anaphase I through anaphase II because our streaming data and that of Kimura 2020 indicate that the sperm contents have not moved significantly before anaphase I." - This needs an appropriate citation. Page 10.
We have inserted citations here.
" The simplest explanation is that cytoplasm does not mix during the 45 min from GVBD to pronucleus formation due to the high viscosity of cytoplasm." - Citation page 12. Not referencing figures in the discussion.
We have changed the sentence to: “The simplest hypothesis is that maternal and paternal cytoplasm might not mix during the 45 min from GVBD to pronucleus formation due to the high viscosity of cytoplasm.”
"The higher frequency of capture of the sperm DNA by the meiotic spindle in ATX-2 KLP-7 double depleted embryos compared with either single depletion suggests that the integrity of the exclusion zone around the sperm DNA may insulate the sperm DNA from spindle microtubule" - Pages 12-13 reference the figures.
A reference to the revised Fig. 9 has been inserted in the revised version of this sentence.
"ATX-2 is required to maintain the integrity of the ball of paternal mitochondria around the sperm DNA, but the mechanism is unknown."
References to Figs. 7 and 8 have been inserted.
Page 13 reference figure
" In control embryos, the sperm contents rarely came near the meiotic spindle in agreement with a previous study that found that male and female pronuclei rarely form next to each other (6). Streaming of the sperm contents was most commonly restricted to a jostling motion with little net displacement, circular streaming in the short axis of the embryo, or long axis streaming in which the sperm turned away from the spindle before the halfway point of the embryo. Depletion of MEI-1 or KLP-7 resulted in longer excursions of the sperm contents in the long axis of the embryo toward the spindle but frequent capture of the sperm by the spindle was only observed in mei-1(RNAi)." Page 13, the corresponding figures need to be referenced for these sentences.
We have inserted citations here.
"In capture events observed after double depletion of ATX-2 and KLP-7, a bundle of microtubules was discernible extending from the spindle into the ER envelope surrounding the sperm DNA. Such bundles were not observed in mei-1(RNAi) capture events, likely because of the previously reported low density of microtubules in mei-1(RNAi) spindles (36, 37)." Pages 13-14 references figures here.
We have inserted citations here.
(5) Referencing wrong figures in the text:
Figure 5 - In the figure legend there is a 5C but there is no 5C panel in the figure.
A C has been inserted in Fig. 5.
Figure 6A - "Dark holes were observed suggesting exclusion from the lumens of larger membranous organelles (Fig. 6A; Fig. S2)." Page 10.
6A has been changed to 6C.
Figure 6A is showing background autofluorescence in WT oocytes so I am not certain why it is cited here.
The Figure citation has been corrected to 6B, C.
Figure 8 - I could not find the supplemental data file with the individual mitochondria distance measurements.
We are including the Excel file with the revised submission.
The last sentence of the first paragraph should be re-worded to be more concise ". In C. elegans, the nucleus is positioned away from the site of future fertilization so that the meiosis I spindle assembles at the opposite end of the ellipsoid zygote from the site of fertilization (2-4). "
Every word of this sentence is important.
Last sentence second paragraph typo "These microtubules are thought to drive meiotic cytoplasmic streaming because depletion tubulin stops cytoplasmic streaming (7) and depletion of the microtubule-severing protein katanin by RNAi results in an increased mass of cortical microtubules and an increase in cytoplasmic streaming (8)." Pages 3-4.
“of” has been inserted.
(6) Typos in the introduction should be corrected:
Ataxin or kinesin-13 are not mentioned in the introduction but these are a big focus of the paper.
Gong et al 2024 written instead of number citation (page 5), no citation in References.
This has been corrected.
Supplemental videos should be labeled appropriately to indicate what structures are labeled. It is currently difficult to understand what is being shown.
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nisation des outils de configuration du CAP4000 Transition vers une nouvelle application web Auteur Joshua JOURDAM Date de publication 17 juillet 2024 Résumé au dos ou au début du mémoire synthèse carte de visite anglais / français ~15 lignes 3 à 5 mot clés Le renouvellement constant des technologies dans l’industrie est un phénomène de plus en plus marquant de nos jours. Les entreprises qui souhaitent rester compétitives sur le marché doivent s’adapter à ces changements et innover en permanence. Dans ce contexte, le présent projet a pour objectif de développer une nouvelle solution pour répondre aux besoins actuels des industriels. Le projet s’inscrit dans la conception et la réalisation d’une plateforme web permettant de faciliter la gestion des opérations de maintenance et de suivi des équipements SDEL Contrôle Commande. Mots clés Calculateur, Développement WEB, API REST, Authentification Table des matières 1 Environnement et Contexte 1.1 Entreprise, service et position 1.1.1 Vinci 1.1.2 Vinci Energies 1.1.3 Hiérarchie et Fonctionnement de l’Entreprise 1.1.4 SDEL Contrôle Commande 1.1.5 Le service Recherche et Développement 1.2 Contexte du projet 2 Problématique 3 Buts et Objectifs 3.1 Objectifs Stratégiques et Opérationnels 3.1.1 Sélectionner un Cadre de Développement Optimal 3.1.2 Préparer la Transition Technologique 3.1.3 Développer la Nouvelle Application Web 3.1.4 Objectif 4 : Développer les Compétences en Gestion de Projet et Techniques 4 Démarche 4.1 Démarche générale 4.2 Méthodologie, techniques et technologies 4.3 Analyse des risques 4.4 Acteurs 4.5 Lotissements 4.6 Planning prévisionnel 4.7 Planning effectif 4.7.1 Jalons 4.7.2 Livrables 4.8 Budget 5 Résultats 5.1 Evaluation des technologies du marché 5.2 Transition 5.2.1 OpenAPI 5.2.2 Authentification 5.2.3 POC supervision stage 5.3 Développement 5.3.1 Spécification de l’application 5.3.2 Fonctionnement de la solution 5.3.3 Architecture/Workspace (expliquer comment fonctionne un monorepo) 5.3.4 Bibliothèques (zod, react-hook-form, react-query, react-router, orval, react-testing-library, vitest) 5.3.5 Gestion des erreurs et des chargements 5.3.6 Authentification et autorisation 5.3.7 Application 5.3.8 Modules 5.3.9 Tests 5.3.10 Performances 5.3.11 Application 6 Conclusion 6.1 Bilan 7 Annexes 7.1 Références 7.2 Grille des compétences Acronymes HSP PRP REST API SDELCC JWT HTTP HTTPS HMAC WBS CSR SPA Remerciements Ce projet s’intègre dans le cadre de mon apprentissage au sein de l’entreprise SDEL Contrôle Commande. SDEL Contrôle Commande appartient à la filiale Energies du groupe VINCI. Grâce à son expertise technique, SDEL Contrôle commande propose son accompagnement auprès des gestionnaires de réseaux de transport et de distribution d’énergie. J’ai intégré l’entreprise en tant qu’apprenti ingénieur en informatique. J’ai été affecté au service Recherche et Développement, sous la responsabilité de Monsieur Sébastien BARRE, responsable du développement logiciel. Le service Recherche et Développement est en charge de la conception et du développement de calculateurs utilisés principalement dans le domaine de l’énergie notamment dans les postes de transformation du réseau électrique français. Il est également en charge de la maintenance des produits existants. Cette maintenance peut s’effectuer sur de longues périodes, de l’ordre de 20 ans. Le projet s’inscrit dans une dynamique globale qui vise à moderniser les logiciels et les outils que nos équipements embarquent. Cette modernisation à pour objectif de proposer des outils plus ergonomiques et de répondre à des contraintes de cybersécurité plus strictes. Le projet à pour objectif de développer une nouvelle application d’administration et de configuration des automates SDEL. IL se déroule sur la dernière année de ma formation d’ingénieur en apprentissage sur la période de Juin 2023 à août 2024. Ce rapport est découpé en 3 parties : Environnement et contexte : Dans un premier temps, je présenterai le contexte de mon entreprise, puis mon poste et mes rôles au sein de celle-ci. Je présenterai également le contexte, la problématique spécifique ainsi que les buts et objectif du projet. Mise en œuvre et analyse des résultats : Dans cette partie, j’aborderai la méthodologie de travail choisie et les outils utilisés pour assurer son bon déroulement. Je présenterai ensuite les résultats obtenus en évoquant les écarts avec les objectif établis. Bilan et perspectives : Enfin, je ferai un bilan et j’évoquerai les perspectives d’évolution du projet. Je présenterai également les compétences acquises et les apports de ce projet dans mon parcours de formation. Pour finir, je présenterai mes perspectives futures pour ma carrière professionnelle. 1 Environnement et Contexte développer contexte entreprise, Vinci et hiérarchie (energies, omexom), nos marchés (où) ce qu’il faut retenir de chaque chapitre (bullet list) 1.1 Entreprise, service et position 1.1.1 Vinci image/svg+xml Figure 1: Logo VINCI Vinci est une entreprise multinationale française spécialisée dans la construction et les concessions. Fondée en 1899 sous le nom de Société Générale d’Entreprises (SGE), elle est devenue Vinci en 2000. Vinci est l’une des plus grandes entreprises de construction et de concessions dans le monde, avec des activités diversifiées dans le domaine de la construction, des infrastructures, des services énergétiques et de la gestion des infrastructures. Secteurs d’activité : Construction : Vinci Construction est spécialisée dans le bâtiment, les travaux publics, le génie civil, les fondations et les infrastructures de transport. Concessions : Vinci Autoroutes et Vinci Airports gèrent des réseaux autoroutiers et des aéroports dans plusieurs pays. Énergie : Vinci Energies intervient dans les domaines des infrastructures d’énergie, des industries, des technologies de l’information, et de la transition énergétique. Immobilier : Vinci Immobilier est active dans le développement immobilier résidentiel, tertiaire et commercial. #mermaid-1{font-family:"trebuchet ms",verdana,arial,sans-serif;font-size:16px;fill:#ccc;}#mermaid-1 .error-icon{fill:#a44141;}#mermaid-1 .error-text{fill:#ddd;stroke:#ddd;}#mermaid-1 .edge-thickness-normal{stroke-width:2px;}#mermaid-1 .edge-thickness-thick{stroke-width:3.5px;}#mermaid-1 .edge-pattern-solid{stroke-dasharray:0;}#mermaid-1 .edge-pattern-dashed{stroke-dasharray:3;}#mermaid-1 .edge-pattern-dotted{stroke-dasharray:2;}#mermaid-1 .marker{fill:lightgrey;stroke:lightgrey;}#mermaid-1 .marker.cross{stroke:lightgrey;}#mermaid-1 svg{font-family:"trebuchet ms",verdana,arial,sans-serif;font-size:16px;}#mermaid-1 .edge{stroke-width:3;}#mermaid-1 .section--1 rect,#mermaid-1 .section--1 path,#mermaid-1 .section--1 circle,#mermaid-1 .section--1 polygon,#mermaid-1 .section--1 path{fill:#1f2020;}#mermaid-1 .section--1 text{fill:lightgrey;}#mermaid-1 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.edge-depth-10{stroke-width:-16;}#mermaid-1 .section-10 line{stroke:#fe9d63;stroke-width:3;}#mermaid-1 .disabled,#mermaid-1 .disabled circle,#mermaid-1 .disabled text{fill:lightgray;}#mermaid-1 .disabled text{fill:#efefef;}#mermaid-1 .section-root rect,#mermaid-1 .section-root path,#mermaid-1 .section-root circle,#mermaid-1 .section-root polygon{fill:hsl(180, 1.5873015873%, 48.3529411765%);}#mermaid-1 .section-root text{fill:#2c2c2c;}#mermaid-1 .icon-container{height:100%;display:flex;justify-content:center;align-items:center;}#mermaid-1 .edge{fill:none;}#mermaid-1 .mindmap-node-label{dy:1em;alignment-baseline:middle;text-anchor:middle;dominant-baseline:middle;text-align:center;}#mermaid-1 :root{--mermaid-font-family:"trebuchet ms",verdana,arial,sans-serif;}VINCIVinci EnergiesVinci ConstructionVinci AutoroutesVinci AirportsVinci Immobilier 1.1.2 Vinci Energies Vinci Energies, une filiale de Vinci, est spécialisée dans les services énergétiques et les technologies de l’information. Elle propose des solutions dans les domaines de l’énergie, des technologies de l’information, et des télécommunications. Ses principales activités incluent : Infrastructure Énergie : Gestion des réseaux électriques et des infrastructures de distribution d’énergie. Industrie : Optimisation des processus industriels et amélioration de l’efficacité énergétique. TIC (Technologies de l’Information et de la Communication) : Solutions pour les systèmes d’information et les télécommunications. Transition Énergétique et Environnementale : Développement de solutions pour une énergie plus durable et respectueuse de l’environnement. Vinci Energies, une division du groupe VINCI, regroupe plusieurs marques spécialisées dans divers domaines des services énergétiques et des technologies de l’information. Les cinq principales marques de Vinci Energies sont : Actemium : Spécialisée dans les solutions et les services pour les processus industriels, couvrant l’ensemble du cycle de vie des installations industrielles. Axians : Focalisée sur les technologies de l’information et de la communication (TIC), offrant des solutions pour les infrastructures IT, la cybersécurité, le cloud, les réseaux et la collaboration. Cegelec : Fournit des services et des solutions en ingénierie électrique et maintenance pour les infrastructures et les bâtiments. Omexom : Se concentre sur les infrastructures énergétiques, notamment les réseaux de transport et de distribution d’électricité, les énergies renouvelables et les systèmes de stockage d’énergie. VINCI Facilities : Offre des services de gestion et de maintenance des bâtiments, incluant des solutions de facility management intégrées pour optimiser les performances des installations. 1.1.3 Hiérarchie et Fonctionnement de l’Entreprise 1.1.3.1 Organisation Vinci est organisée en plusieurs divisions opérationnelles, chacune ayant une structure hiérarchique propre. La hiérarchie de Vinci et de ses filiales, comme Vinci Energies, est généralement structurée de la manière suivante : Conseil d’Administration : Organe suprême de la société, responsable de la stratégie globale et de la surveillance de la direction exécutive. Direction Générale : Composée du Président-Directeur Général (PDG) et d’autres membres de la direction exécutive, responsables de la mise en œuvre de la stratégie et de la gestion quotidienne de l’entreprise. Directeurs de Divisions/Branches : Chacun responsable d’une branche spécifique (par exemple, Vinci Construction, Vinci Energies). Directeurs de Filières/Entités : Supervisent des sous-divisions ou entités spécifiques au sein de chaque branche, telles que des régions géographiques ou des domaines spécialisés. Chefs de Projet et Managers Opérationnels : Responsables de la gestion quotidienne des projets et des équipes sur le terrain. Équipes Opérationnelles : Constituent les employés qui travaillent directement sur les projets, incluant ingénieurs, techniciens, ouvriers, et autres professionnels spécialisés. 1.1.3.2 Fonctionnement Décentralisation : Vinci privilégie une approche décentralisée, permettant à ses différentes divisions et filiales de bénéficier d’une grande autonomie. Cela favorise la réactivité et l’adaptabilité aux marchés locaux. Innovation : L’entreprise met l’accent sur l’innovation technologique et l’efficacité énergétique, soutenant les projets de recherche et développement pour anticiper les besoins futurs. Responsabilité Sociétale et Environnementale : Vinci est engagée dans une démarche de développement durable, visant à réduire son empreinte écologique et à améliorer ses performances environnementales. En résumé, Vinci est une entreprise diversifiée avec une structure hiérarchique bien définie, soutenant une approche décentralisée et innovante pour répondre aux besoins de ses marchés dans le domaine de la construction, des concessions, et des services énergétiques. 1.1.4 SDEL Contrôle Commande Figure 2: Entrée principale de SDEL Contrôle Commande SDEL Contrôle Commande appartient à la filiale Energies du groupe VINCI. Elle est composée de plusieurs marques, comme Omexom, Actemium et Axians. Chaque marque est spécialisée dans un domaine d’activité précis. Ainsi VINCI Energies offre une gamme complète de services et de solutions dans le domaine de l’énergie. SDEL Contrôle Commande est une entreprise mono-site basée à Saint-Aignan-Grandlieu. Au sein du réseau Omexom, SDEL Contrôle Commande intervient dans la gestion de projets clé en main, la conception, l’ingénierie, l’intégration, l’installation, la configuration, les essais, la mise en service et la maintenance de systèmes de contrôle commande de postes électriques et d’automatismes. Figure 3: Tranches SDEL Composée de plus de 300 salariés, elle bénéficie de plus de 50 années d’expérience dans le contrôle commande. Ainsi, grâce à son expertise technique, SDEL Contrôle commande propose son accompagnement auprès des gestionnaires de réseaux de transport et de distribution d’énergie. Nos clients majeurs sont RTE et Enedis. Nous proposons une offre sur mesure de produits à destination des postes du réseau électrique français. Nous fournissons également des systèmes de contrôle commande à Thales pour le pilotage de batteries marines et à la RATP pour la supervision du système de ventilation du métro parisien. RTE Enedis Thales RATP EDF Nos principaux concurrents sont Actia Telecom, SCLE, Eiffage Energie. Ils proposent une gamme de produits similaire sur le marché de la distribution et du transport de l’énergie. Quelques entreprises du groupe VINCI sont également en compétition directe avec SDEL Contrôle Commande sur certains appels d’offre. #fig-market-mermaid{font-family:"trebuchet ms",verdana,arial,sans-serif;font-size:16px;fill:#ccc;}#fig-market-mermaid .error-icon{fill:#a44141;}#fig-market-mermaid .error-text{fill:#ddd;stroke:#ddd;}#fig-market-mermaid .edge-thickness-normal{stroke-width:2px;}#fig-market-mermaid .edge-thickness-thick{stroke-width:3.5px;}#fig-market-mermaid .edge-pattern-solid{stroke-dasharray:0;}#fig-market-mermaid .edge-pattern-dashed{stroke-dasharray:3;}#fig-market-mermaid .edge-pattern-dotted{stroke-dasharray:2;}#fig-market-mermaid .marker{fill:lightgrey;stroke:lightgrey;}#fig-market-mermaid .marker.cross{stroke:lightgrey;}#fig-market-mermaid svg{font-family:"trebuchet ms",verdana,arial,sans-serif;font-size:16px;}#fig-market-mermaid .pieCircle{stroke:black;stroke-width:2px;opacity:0.7;}#fig-market-mermaid .pieOuterCircle{stroke:black;stroke-width:2px;fill:none;}#fig-market-mermaid .pieTitleText{text-anchor:middle;font-size:25px;fill:hsl(28.5714285714, 17.3553719008%, 86.2745098039%);font-family:"trebuchet ms",verdana,arial,sans-serif;}#fig-market-mermaid .slice{font-family:"trebuchet ms",verdana,arial,sans-serif;fill:#ccc;font-size:17px;}#fig-market-mermaid .legend text{fill:hsl(28.5714285714, 17.3553719008%, 86.2745098039%);font-family:"trebuchet ms",verdana,arial,sans-serif;font-size:17px;}#fig-market-mermaid :root{--mermaid-font-family:"trebuchet ms",verdana,arial,sans-serif;}85%10%4%1%EnergieDéfenseTransportAutres industries Figure 4: Répartition des marchés de SDEL Contrôle Commande #fig-organisation-mermaid{font-family:"trebuchet ms",verdana,arial,sans-serif;font-size:16px;fill:#ccc;}#fig-organisation-mermaid .error-icon{fill:#a44141;}#fig-organisation-mermaid .error-text{fill:#ddd;stroke:#ddd;}#fig-organisation-mermaid 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.icon-container{height:100%;display:flex;justify-content:center;align-items:center;}#fig-organisation-mermaid .edge{fill:none;}#fig-organisation-mermaid .mindmap-node-label{dy:1em;alignment-baseline:middle;text-anchor:middle;dominant-baseline:middle;text-align:center;}#fig-organisation-mermaid :root{--mermaid-font-family:"trebuchet ms",verdana,arial,sans-serif;}SDEL Contrôle CommandeRecherche etDéveloppementIngénierieInnovationGestion affairesStratégie IndustrielleBureau d 'étudesIntégrationLogistiqueChaîne achatsApprovisionnementEssaisMise en serviceTravauxInterventions Figure 5: Les services de SDEL Contrôle Commande 1.1.5 Le service Recherche et Développement SDEL Contrôle Commande propose des solutions techniques adaptées aux besoins de ses clients grâce à ses services Recherche et Développement, Ingénierie et Innovation. En plus de notre connaissance approfondie des différents constructeurs, notre expertise dans le domaine d’application nous permet de répondre aux besoins en ingénierie, dimensionnement, configuration et déploiement d’équipements de protection et de contrôle pour les réseaux électriques de transport et de distribution d’énergie. Le service Recherche et Développement est composé de 16 personnes. 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circle,#fig-software-team-mermaid .disabled text{fill:lightgray;}#fig-software-team-mermaid .disabled text{fill:#efefef;}#fig-software-team-mermaid .section-root rect,#fig-software-team-mermaid .section-root path,#fig-software-team-mermaid .section-root circle,#fig-software-team-mermaid .section-root polygon{fill:hsl(180, 1.5873015873%, 48.3529411765%);}#fig-software-team-mermaid .section-root text{fill:#2c2c2c;}#fig-software-team-mermaid .icon-container{height:100%;display:flex;justify-content:center;align-items:center;}#fig-software-team-mermaid .edge{fill:none;}#fig-software-team-mermaid .mindmap-node-label{dy:1em;alignment-baseline:middle;text-anchor:middle;dominant-baseline:middle;text-align:center;}#fig-software-team-mermaid :root{--mermaid-font-family:"trebuchet ms",verdana,arial,sans-serif;}BARRE SebastienChef de groupeIngénieurBAUDOUIN Jean LouisIHMTechnicienJANNIERE SylvainCAP4000 /IHMIngénieurCECILLON LucasCAP4000 /CybersécuritéApprentiDUPONT DavidIHMIngénieurHELARD FlorentCAP4000IngénieurMINIER BertrandYocto /CAP4000IngénieurJOURDAM JoshuaYocto /IHMApprenti Figure 6: Organigramme équipe logiciel Monsieur Sébastien BARRE, est responsable du développement logiciel dans le service Recherche et Développement. L’équipe logiciel travaille les applicatifs et le système d’exploitation des équipements que nous développons. Ces matériels sont destinés à être commercialisés via l’intégration dans les produits et services fournis par SDEL contrôle commande. Par exemple lors de la vente d’armoires de contrôle commande ou lors de l’installation d’un poste électrique. Figure 7: DigiBOX, calculateur SDELCC dédié aux applications des postes électriques Applications : Système de supervision de poste Passerelle de téléconduite Synoptique de poste local Consignateur d’état Concrètement -> embarqué, linux, yocto En tant qu’apprenti j’ai pour rôle de contribuer au développement de nos logiciels. Je suis aussi mobilisé pour tester et étudier l’intégration de nouvelles technologies sur les produits. Mon travail comprends l’étude, l’analyse de données, la création de prototypes, la mise en place de tests et l’assistance aux techniciens et aux ingénieurs dans leur travail. Je suis également amené à rédiger de la documentation et la communiquer les résultats de mes travaux. J’ai l’occasion de travailler sur des projets concrets et de développer mes compétences dans le domaine de l’informatique embarquée principalement. Avec ma montée en compétences au fur et à mesure de ma formation, je suis maintenant amené à travailler sur des projets plus complexes et à diriger le présent projet. 1.2 Contexte du projet Le CAP4000 est une base logicielle modulaire qui est utilisée par tous les équipements développés par le service Recherche et Développement. C’est une application qui fonctionne en permanence. Elle gère les principales fonctionnalités de nos produits en s’interfaçant avec différents composants tels que : Système d’exploitation (réseau, alimentation, processus …) Périphériques (affichage, cartes d’extensions, clé usb, …) Moteur d’automatisme Panneau frontal (leds, boutons, …) Nos équipements sont hautement configurables. Pour simplifier l’utilisation par nos client, l’administration des équipements doit pouvoir être effectuée à distance. Ces tâches sont réalisées grâce à aux outils de configuration historiques qui sont inclus dans une application de bureau windows. Figure 8: Utilitaire de configuration Depuis 2020 l’équipe logiciel travaille sur le remplacement de cette application. L’objectif est de moderniser nos outils pour simplifier et intégrer des contraintes de cybersécurité plus strictes dans les processus de gestion et de maintenance des équipements. Pour moderniser les principes d’accès aux ressources d’un calculateur, une API de type REST à été implémentée dans le logiciel CAP4000. L’objectif est de mettre à disposition un système de dialogue fiable et sécurisé avec un équipement dans le but de créer des outils basés sur les technologies Web pour les produits SDELCC. API (Interface de Programmation d’Application) Les API pour Application Programming Interface permettent à 2 ordinateur de communiquer entre eux. Imaginez cela comme l’utilisation d’un site web, mais au lieu de cliquer sur des boutons, vous écrivez du code pour demander explicitement des données à un serveur. Une API dite RESTful, suit un ensemble de règles et contraintes imposées par l’architecture REST (REpresentational State Transfer). Une API REST fonctionne sur le protocole HTTP (Hypertext Transfer Protocol). Elle mets à disposition des ressources (données) accessible par des URL uniques. Une requête permet d’accéder aux ressources. Chaque requête (GET, POST, PATCH, DELETE) respecte le principe CRUD (Create, Read, Update, Delete) et suit un format spécifique : méthode, URL, en-têtes (métadonnées) et corps (données). Un client effectue une requête sur le serveur via une URL, le serveur exécute du code (généralement accède à une base de données), formate les données dans une réponse avec un code d’état (indiquant le succès, une erreur client ou serveur). Les API REST sont stateless, ce qui signifie que chaque interaction est indépendante des précédentes, rendant les applications prévisibles et fiables. Les API de type REST sont devenues le standard de facto pour le développement d’API web depuis le début des années 2000. #fig-rest-api-flow-mermaid{font-family:"trebuchet ms",verdana,arial,sans-serif;font-size:16px;fill:#ccc;}#fig-rest-api-flow-mermaid .error-icon{fill:#a44141;}#fig-rest-api-flow-mermaid .error-text{fill:#ddd;stroke:#ddd;}#fig-rest-api-flow-mermaid .edge-thickness-normal{stroke-width:2px;}#fig-rest-api-flow-mermaid .edge-thickness-thick{stroke-width:3.5px;}#fig-rest-api-flow-mermaid .edge-pattern-solid{stroke-dasharray:0;}#fig-rest-api-flow-mermaid .edge-pattern-dashed{stroke-dasharray:3;}#fig-rest-api-flow-mermaid .edge-pattern-dotted{stroke-dasharray:2;}#fig-rest-api-flow-mermaid .marker{fill:lightgrey;stroke:lightgrey;}#fig-rest-api-flow-mermaid .marker.cross{stroke:lightgrey;}#fig-rest-api-flow-mermaid svg{font-family:"trebuchet ms",verdana,arial,sans-serif;font-size:16px;}#fig-rest-api-flow-mermaid .label{font-family:"trebuchet ms",verdana,arial,sans-serif;color:#ccc;}#fig-rest-api-flow-mermaid .cluster-label text{fill:#F9FFFE;}#fig-rest-api-flow-mermaid .cluster-label span,#fig-rest-api-flow-mermaid p{color:#F9FFFE;}#fig-rest-api-flow-mermaid .label text,#fig-rest-api-flow-mermaid span,#fig-rest-api-flow-mermaid p{fill:#ccc;color:#ccc;}#fig-rest-api-flow-mermaid .node rect,#fig-rest-api-flow-mermaid .node circle,#fig-rest-api-flow-mermaid .node ellipse,#fig-rest-api-flow-mermaid .node polygon,#fig-rest-api-flow-mermaid .node path{fill:#1f2020;stroke:#81B1DB;stroke-width:1px;}#fig-rest-api-flow-mermaid .flowchart-label text{text-anchor:middle;}#fig-rest-api-flow-mermaid .node .label{text-align:center;}#fig-rest-api-flow-mermaid .node.clickable{cursor:pointer;}#fig-rest-api-flow-mermaid .arrowheadPath{fill:lightgrey;}#fig-rest-api-flow-mermaid .edgePath .path{stroke:lightgrey;stroke-width:2.0px;}#fig-rest-api-flow-mermaid .flowchart-link{stroke:lightgrey;fill:none;}#fig-rest-api-flow-mermaid .edgeLabel{background-color:hsl(0, 0%, 34.4117647059%);text-align:center;}#fig-rest-api-flow-mermaid .edgeLabel rect{opacity:0.5;background-color:hsl(0, 0%, 34.4117647059%);fill:hsl(0, 0%, 34.4117647059%);}#fig-rest-api-flow-mermaid .cluster rect{fill:hsl(180, 1.5873015873%, 28.3529411765%);stroke:rgba(255, 255, 255, 0.25);stroke-width:1px;}#fig-rest-api-flow-mermaid .cluster text{fill:#F9FFFE;}#fig-rest-api-flow-mermaid .cluster span,#fig-rest-api-flow-mermaid p{color:#F9FFFE;}#fig-rest-api-flow-mermaid div.mermaidTooltip{position:absolute;text-align:center;max-width:200px;padding:2px;font-family:"trebuchet ms",verdana,arial,sans-serif;font-size:12px;background:hsl(20, 1.5873015873%, 12.3529411765%);border:1px solid rgba(255, 255, 255, 0.25);border-radius:2px;pointer-events:none;z-index:100;}#fig-rest-api-flow-mermaid .flowchartTitleText{text-anchor:middle;font-size:18px;fill:#ccc;}#fig-rest-api-flow-mermaid :root{--mermaid-font-family:"trebuchet ms",verdana,arial,sans-serif;}OdrinateurÉquipementNavigateurCAP4000VisiteRequêteGET/POST/PUT/DELETERéponseJSONLit et écritExecuteApplication webAPIrestModule XBase de donnéesProcéduresUtilisateur Figure 9: Principe d’utilisation de l’API REST du CAP4000 Cette API à pour principal objectif de permettre la configuration et la gestion des équipements à distance. Elle permet de récupérer des informations sur l’état de l’équipement et de ses composants. Elle permet également la modification la configuration de l’équipement et le déclenchement de procédures comme le redémarrage. Par exemple, il est possible de récupérer la version du logiciel installé sur l’équipement en exécutant la requête HTTP GET suivante : http://<ip-equipement>/api/v1/identification. identification { "CAP4000": { "IndiceValidation": 0, "Nom": "DigiBOX", "VersionCorrectif": 1, "VersionMajeure": 6, "VersionMineure": 0, "VersionProtocole": 2 }, "OS": { "Nom": "digibox-debug-os", "VersionCorrectif": 5, "VersionMajeure": 0, "VersionMineure": 4 }, "Produit": { "Nom": "digibox-debug", "VersionCorrectif": 1, "VersionMajeure": 2, "VersionMineure": 0 } } Une expérimentation d’application à été développée. Cette application est disponible pour deux plateformes : Windows et Web. Elle dialogue avec l’API REST du CAP4000. L’application a été développée avec le framework Qt. C’est un framework que nous utilisons déjà sur d’autres projets. Il a donc été choisi afin de capitaliser sur l’expertise du service. L’application est découpée en modules qui représentent une fonctionnalité dans l’interface (debug, configuration réseau, import de configuration, …). Qt (prononcé “cute”) Qt est un framework de développement d’applications multi-plateformes basé sur le language C++. Il permet de créer des logiciels avec une interface utilisateur graphique. Les applications peuvent être exécutées sur différents systèmes d’exploitation tels que Windows, macOS, Linux, etc., mais aussi dans un navigateur sans nécessiter de modifications majeures du code source. Pour fonctionner dans un navigateur, une application Qt doit être compilée au format WebAssembly. WebAssembly est un format binaire qui permet d’exécuter du code bas niveau de manière portable et sécurisée dans les navigateurs web modernes. Il est conçu pour compléter les langages de programmation traditionnels utilisés sur le web, tels que JavaScript, en offrant des performances plus élevées pour les applications web. Cette application expérimentale est destinée à être utilisée en interne par les collaborateurs de SDEL Contrôle Commande ainsi que certains clients qui souhaitent l’évaluer. Figure 10: Interface web du produit DigiBox (menu principal) On retrouve des fonctionnalités comme : Configuration des interfaces réseau Gestion des certificats État des cartes entrées/sorties Affichage des informations de débogage Gestion de l’alimentation Import de configuration … L’application gère les utilisateurs du système d’exploitation et les rôles du CAP4000. Ainsi, il est possible de restreindre l’accès à certaines fonctionnalités. Par exemple, un utilisateur avec le rôle “observateur” ne pourra pas accéder à la configuration réseau de l’équipement. L’architecture du cette solution peut être représentée par la pile technologique suivante : Table 1: Pile technologique Frontend API Backend Qt API REST CAP4000 Pile technologique D’abord c’est quoi ? Une pile technologique peut être découpée en trois catégories : Frontend La couche frontend inclus les outils requis pour construire une interface homme machine pour les utilisateurs finaux. Elle peut être développée pour fonctionner dans un navigateur internet ou sur un système d’exploitation (windows, linux, macos, android, ios, …). Backend La couche backend inclus un runtime (environnement d’exécution) serveur généralement accompagné d’une base de données. Elle permet de gérer les données et la logique métier de l’application (gestion des utilisateurs, des droits, fonctionnalités …). API La couche APIs permet de connecter le frontend et le backend (REST, GraphQL). Elle gère aussi l’intégration avec des services tiers (paiement, gestion des identités, messagerie, …) L’application web est accessible localement en accédant à un équipement via son adresse ip depuis un navigateur internet. Elle est compatible avec les navigateurs modernes (Chrome, Firefox, Edge, Safari, …). L’application est donc distribuée directement dans le système d’exploitation d’un équipement et ne nécessite aucune installation sur les postes de travail de nos clients. Chaque type d’équipement dispose de sa propre version de l’application intégrant plus ou moins de fonctionnalités. Dans la suite du rapport, nous allons présenter les différentes étapes de la réalisation de ce projet. Nous commencerons par présenter la problématique et les objectifs du projet. Nous détaillerons ensuite la méthodologie utilisée pour réaliser le projet. Enfin, nous présenterons les résultats obtenus et les perspectives pour la suite du projet. Parler des licenses libres / open sources https://www.diatem.net/les-licences-open-source/ 2 Problématique Aujourd’hui, nous souhaitons intégrer l’application web sur l’ensemble des produits que nous commercialisons. En informatique, les logiciels sont distribués sous plusieurs types de licenses. Les licenses open-sources permettent aux développeurs de les utiliser, de les modifier et de les redistribuer en suivant certaines règles. Il existe beaucoup de licences open-sources et chacune dispose de ses propres règles d’utilisation. Il est important de prendre en compte ces conditions avant de commercialiser un produit qui intègre un composant open-source. Le framework Qt est la propriété de The Qt Company. Il est distribué sous plusieurs licenses. Jusqu’ici nous avons utilisé la version open-source de ce logiciel pour commercialiser nos produits. Cependant cette version ne permet pas de distribuer une application au format WebAssembly sans également distribuer le code source de celle-ci. La direction de VINCI ne souhaite pas publier les sources de ses applications. Nous avons également écarté la possibilité de payer des licenses commerciales. La commercialisation des produits intégrant de l’application web sous sa forme actuelle n’est donc pas envisageable. Le présent projet vise à développer une nouvelle application en se basant sur une autre technologie. Nous souhaitons une interface graphique web reposant sur le dialogue avec un calculateur via l’API REST. Nous souhaitons utiliser un framework open source et entièrement gratuit, adapté aux besoins de l’embarqué. Ce projet permettra également d’explorer et monter en compétences sur les technologies web ainsi que consolider notre solution en utilisant des technologies pérennes qui autorisent la diffusion de nos applications sous licence propriétaire. Problématique Comment choisir judicieusement un framework open source pour le développement d’une nouvelle application web intégrée à l’ensemble de la gamme de produits, tout en respectant les contraintes de confidentialité imposées par la direction de l’entreprise et en garantissant la possibilité de diffuser les applications sous licence propriétaire ? Ce projet aura un impact sur les utilisateurs de l’application Qt. Comme cette application était encore en phase expérimentale, seuls les développeurs du service recherche et développement et les intervenants internes divers (test, bureau d’études, etc …) seront impactés. Nos client qui profitent déjà de l’application seront limités à l’utilisation sur la plateforme Windows uniquement. Lorsque la prochaine application sera développée, ils pourront bénéficier d’une mise à niveau vers la nouvelle version système de leur produit. L’application Qt continuera à être développée par Jean-Louis Baudoin. Un autre groupe de travail a réussi à reproduire le fonctionnement de l’application web en explorant des solutions alternatives au WebAssembly. Cela est rendu possible en installant l’application de bureau directement sur les calculateurs et partageant l’environnement de bureau grace aux technologies de type VNC. Cette solution, rapide à mettre en place, restera cependant temporaire en raison de ses faible performances et sera à terme définitivement remplacée définitivement lorsque la future application sera publiée. 3 Buts et Objectifs Choisir un framework Établir une liste de minimum 10 critères permettant la comparaison des frameworks Évaluer et tester au moins trois frameworks alternatifs en fonction la liste de critères Réaliser un prototype (POC) fonctionnel comprenant un menu ainsi que 3 modules Préparer la transition Mettre à niveau la spécification de l’API pour répondre au standard OpenAPI 3 Modifier la méthode d’authentification des requêtes pour simplifier l’implémentation de l’API dans la nouvelle application Changer le système d’authentification afin de garantir la sécurité de l’API Effectuer une semaine d’auto-formation sur le framework choisi Établir une liste ordonnée de modules à porter, à créer ou à supprimer comprenant au minimum les modules existants Développer la nouvelle application web Développer au moins 20 modules Atteindre des performances au moins équivalentes (dégradation maximale de 5%) à l’application actuelle Acquérir les compétences d’un ingénieur débutant Mettre en place une démarche de gestion de projet permettant d’atteindre les buts et objectifs fixés Fournir l’ensemble des livrables demandés par l’ESEO Avoir une note supérieure à 14 aux 3 évaluations PING Bien sûr, voici une proposition de structure alternative pour les objectifs, avec des formulations plus étoffées et professionnelles : 3.1 Objectifs Stratégiques et Opérationnels 3.1.1 Sélectionner un Cadre de Développement Optimal Identifier et choisir un framework adapté aux besoins spécifiques du projet. Élaborer une Liste de Critères de Sélection : Objectif : Développer une liste détaillée d’au moins 10 critères pertinents pour la comparaison des frameworks. Délai : 2 semaines. Description : Inclure des critères tels que la performance, la scalabilité, la facilité d’intégration, le support communautaire, la documentation, et la sécurité. Évaluer et Tester des Frameworks Alternatifs : Objectif : Évaluer au moins trois frameworks alternatifs en fonction de la liste de critères établie. Délai : 4 semaines. Description : Effectuer des tests pratiques pour chaque framework afin de vérifier leur conformité aux critères et documenter les résultats. Développer un Prototype Fonctionnel : Objectif : Réaliser un Proof of Concept (POC) comprenant un menu principal et trois modules fonctionnels. Délai : 6 semaines. Description : Utiliser le framework sélectionné pour développer un prototype démontrant les capacités du framework à répondre aux exigences du projet. 3.1.2 Préparer la Transition Technologique Assurer une transition fluide et sécurisée vers le nouveau framework. Mettre à Niveau la Spécification de l’API : Objectif : Conformer la spécification de l’API au standard OpenAPI 3. Délai : 2 semaines. Description : Revoir et modifier la spécification actuelle pour garantir la compatibilité et les bonnes pratiques. Modifier le Système d’Authentification : Objectif : Mettre en place un système d’authentification robuste pour garantir la sécurité de l’API. Délai : 3 semaines. Description : Intégrer des méthodes modernes d’authentification (par exemple, OAuth2) pour renforcer la sécurité et simplifier l’implémentation. Former l’Équipe sur le Nouveau Framework : Objectif : Effectuer une semaine d’auto-formation pour l’ensemble de l’équipe sur le framework sélectionné. Délai : 1 semaine. Description : Utiliser des ressources en ligne et des formations internes pour acquérir les compétences nécessaires. Établir une Liste de Modules à Migrer : Objectif : Créer une liste ordonnée des modules existants à porter, créer ou supprimer. Délai : 2 semaines. Description : Prioriser les modules en fonction de leur importance et de leur complexité, en incluant une évaluation des efforts requis pour chaque module. Minimum viable product : Liste modules 3.1.3 Développer la Nouvelle Application Web Concevoir et déployer une nouvelle application web performante et fonctionnelle. Développer les Modules Nécessaires : Objectif : Concevoir et développer au moins 20 modules fonctionnels pour la nouvelle application. Délai : 3 mois. Description : Chaque module doit être testé et validé selon les critères de qualité et de performance. Optimiser les Performances de l’Application : Objectif : Assurer que les performances de la nouvelle application ne se dégradent pas de plus de 5% par rapport à l’application actuelle. Délai : 1 mois. Description : Effectuer des tests de performance réguliers et optimiser le code et l’infrastructure en conséquence. 3.1.4 Objectif 4 : Développer les Compétences en Gestion de Projet et Techniques But : Acquérir et démontrer les compétences nécessaires pour réussir dans le cadre du projet. Mettre en Place une Démarche de Gestion de Projet : Objectif : Développer une approche structurée de gestion de projet pour atteindre les objectifs fixés. Délai : 1 semaine. Description : Utiliser des outils de gestion de projet (comme Jira ou Trello) pour suivre les tâches, les progrès et les délais. Fournir les Livrables Requis : Objectif : Produire et livrer tous les livrables exigés par l’ESEO. Délai : Selon les échéances établies. Description : Assurer la qualité et la complétude de tous les documents et livrables. Obtenir des Notes Élevées aux Évaluations PING : Objectif : Obtenir une note supérieure à 14/20 aux trois évaluations PING. Délai : Prochaine session d’évaluations. Description : Préparer et réviser les matières évaluées pour garantir une performance optimale. 4 Démarche Comment fonctionne le service R&D de base outils de gestion de projet Redmine Fiche de développement Notes Outils - Gestion de projet - Gestion de version - Environnement de développement - Produits de développement - Langages de programmation 4.1 Démarche générale La démarché générale du projet est définie par le présent document. Ce document défini les buts et objectif attendus. Il établis également un plan d’action pour les atteindre. Il mets en place un processus de communication pour garantir la circulation de l’information. Enfin, il identifie les risques et problèmes potentiels qui pourraient survenir et établi des solutions pour y faire face. 4.2 Méthodologie, techniques et technologies Le développement logiciel suit plusieurs étapes essentielles pour assurer la création et le bon fonctionnement d’un logiciel. Analyse des besoins : Identifier et définir les besoins des utilisateurs et les objectifs du logiciel. Les exigences fonctionnelles et non fonctionnelles sont spécifiées, ainsi que les contraintes du projet. Conception : Créer une architecture logicielle en se basant sur l’analyse des besoins. Cela implique la création de diagrammes, de schémas et de modèles qui servent de guide pour la réalisation du logiciel. Tests : Vérifier la qualité et la conformité du logiciel. Des tests unitaires, d’intégration et de validation sont réalisés pour détecter et corriger les éventuelles erreurs et bugs. Intégration : Assembler les différentes parties du logiciel en un ensemble fonctionnel et cohérent. Cela inclut l’ajout de fonctionnalités supplémentaires et l’optimisation des performances. Déploiement : Rendre le logiciel disponible aux utilisateurs finaux. Cela peut impliquer l’installation sur des serveurs, la distribution de fichiers d’installation ou la mise à disposition sur des plateformes en ligne. Maintenance : Maintenir le logiciel en état de fonctionnement. Les erreurs sont corrigées, des mises à jour sont effectuées, des nouvelles fonctionnalités peuvent être ajoutées et des améliorations sont apportées pour répondre aux besoins changeants des utilisateurs. Dans le cadre de ce projet, une approche de gestion de projet agile sera utilisée. Cette approche permettra une meilleure gestion des changements et des imprévus, tout en limitant l’effet tunnel. Méthodologie agile La méthodologie agile est une approche de gestion de projet qui se caractérise par sa flexibilité, sa collaboration continue avec les parties prenantes et sa capacité à s’adapter aux changements tout au long du cycle de développement. Les méthodologies agiles mettent l’accent sur la livraison itérative et incrémentale du produit, favorisant des cycles de développement courts et des retours fréquents des utilisateurs. L’agilité est souvent utilisée dans le développement logiciel, mais elle peut également être appliquée à d’autres domaines. Pour plus d’informations sur les méthodologies agiles, voir https://www.atlassian.com/fr/agile. La phase de développement sera découpée en sprints. Chaque période entreprise (2 à 4 semaines) intégrera un unique sprint. Cette segmentation permettra d’effectuer des contrôles réguliers de l’avancement et favorisera un dialogue continu. Sprint Un sprint en développement agile est un cycle de travail itératif et incrémental qui permet à une équipe de développer et de livrer des fonctionnalités de manière régulière, tout en restant flexible et adaptative aux changements et aux retours client. Un sprint intègre généralement les étapes suivantes : Planification des tâches en début du sprint Développement et test continu Revues et rétrospectives en fin de sprint Livraison logicielle potentielle Le projet utilisera un backlog pour recueillir, organiser et hiérarchiser l’ensemble des travaux à réaliser dans le cadre du projet. Chaque fonctionnalité à développer sera spécifiée en une user story et ajoutée comme ticket dans le backlog. Une user story est une technique de description des besoins du client du point de vue de ce dernier. L’objectif de chaque user story est de décrire une fonctionnalité du logiciel de manière simple et compréhensible, tout en se concentrant sur la valeur apportée à l’utilisateur final. Chaque user story pourra dépendre de plusieurs tâches de développements, qui seront rattachés à ce ticket. Au début de chaque sprint, le backlog devra être complété en ajoutant les tâches à traiter pour les trois semaines à venir. Si nécessaire, une modélisation de la fonctionnalité à implémenter pourra être réalisée pour répondre aux spécifications établies précédemment. Chaque sprint devra intégrer la spécification, le développement, les tests et la documentation d’une ou plusieurs user story. Un réunion sera effectué à la fin de chaque sprint afin de suivre l’état d’avancement et d’exercer un esprit critique. Le but de ces réunions sera de replacer les tickets qui n’ont pas pu être traités et d’effectuer un bilan de ce qui à marché et ce qui n’a pas fonctionné pour mieux organiser les sprints futurs. Ces réunions seront basés sur un unique document de suivi, qui sera mis à jour durant chaque sprint. L’utilisation d’UML sera privilégiée pour la modélisation des différents aspects du projet, tels que les cas d’utilisation, les diagrammes de classes, les diagrammes de séquence, etc. Cela permettra de décrire plus précisément les besoins du projet et de mieux visualiser les différentes parties impliquées. 4.3 Analyse des risques Table 2: SWOT (Strengths Weaknesses Opportunities Threats) Atouts Handicapes Interne Forces Maintenir la confidentialité du code source Economies de coûts à long terme Étendre et renforcer les compétences techniques de l’équipe de développement Faiblesses Coûteux en termes de temps et de ressources Peut ne pas répondre aux besoins Difficultés à apprendre un nouveau framework Externe Opportunités Nouvelles opportunités de développement pour l’entreprise Élargir son champ d’expertise Bénéficier de l’expertise de la communauté open source Menaces Coûts de licence prohibitifs ou des restrictions d’utilisation Difficulté à trouver une alternative qui soit compatible avec la cible embarquée Retards dans le développement en raison de l’apprentissage d’un nouveau framework Manque de compétences sur le nouveau framework et les technologies associées Établir un calendrier pour l’apprentissage et la mise en œuvre du nouveau framework Offrir une formation à l’équipe de développement pour aider à l’apprentissage du nouveau framework Mobiliser des ressources supplémentaires pour maintenir les délais Communauté du framework limitée Effectuer une recherche sur les communautés de développeurs pour identifier les frameworks les plus populaires Évaluer la taille de la communauté et la fréquence des mises à jour Évaluer la qualité de la documentation et des exemples Manque de ressources Augmenter l’équipe de développement pour combler les manques Étendre les délais du projet Réduire les fonctionnalités à développer Incompatibilité avec la cible embarquée Examiner les exigences de la cible embarquée et les spécifications de l’alternative Effectuer des tests de compatibilité pour vérifier si l’alternative répond aux exigences de la cible embarquée Résistance au changement Communiquer sur les avantages du nouveau framework choisi Mettre en place une formation pour les développeurs qui ne connaissent pas le nouveau framework Difficulté à trouver une alternative viable Effectuer une analyse des besoins pour identifier les caractéristiques essentielles que l’alternative doit posséder Effectuer une recherche sur les coûts des licences pour les différentes alternatives Quadrant chart risk analysis 4.4 Acteurs Table 3: Acteurs Acteur Rôle Description Joshua Jourdam Chef de projet, Développeur Fourni le livrable du projet. Conduit et pilote le projet. Anime les différentes réunions. Principal développeur. Sébastien Barré Sponsor du projet, Client Responsable global du projet et est un soutien pour le chef de projet. Prend les décisions importantes et arbitre entre deux choix, notamment en situation de crise. Détermine les attendus du projet et les exigences liées. Validera la conformité du livrable à ses attentes et exigences. Opérateurs, testeurs, développeurs Utilisateurs finaux Personnes qui vont utiliser le produit ou le service au quotidien. Exprime leur soutien ou leur mécontentement vis à vis du projet. Jean-Louis Baudoin Utilisateur clé Référent métier, développeur de l’application Qt. Sera le principal interlocuteur pour collecter des informations sur l’application actuelle. David Dupond Utilisateur clé Référent licenses, pourra valider la license d’utilisation du nouvel outil. Lucas Cecillon Utilisateur clé Référent cybersécurité, pourra être consulté sur les problématiques de sécurité de l’application et de l’API. Stagiaires Support Peuvent intervenir en renfort sur le projet, notamment lors des périodes estivales. 4.5 Lotissements %%| label: fig-work-breakdown-structure %%| fig-cap: WBS (Work Breakdown Structure) %%| file: ./graphics/wbs.mmd 4.6 Planning prévisionnel #fig-forecast-schedule-mermaid{font-family:"trebuchet ms",verdana,arial,sans-serif;font-size:16px;fill:#ccc;}#fig-forecast-schedule-mermaid .error-icon{fill:#a44141;}#fig-forecast-schedule-mermaid .error-text{fill:#ddd;stroke:#ddd;}#fig-forecast-schedule-mermaid .edge-thickness-normal{stroke-width:2px;}#fig-forecast-schedule-mermaid .edge-thickness-thick{stroke-width:3.5px;}#fig-forecast-schedule-mermaid .edge-pattern-solid{stroke-dasharray:0;}#fig-forecast-schedule-mermaid .edge-pattern-dashed{stroke-dasharray:3;}#fig-forecast-schedule-mermaid .edge-pattern-dotted{stroke-dasharray:2;}#fig-forecast-schedule-mermaid .marker{fill:lightgrey;stroke:lightgrey;}#fig-forecast-schedule-mermaid 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.activeCritText1,#fig-actual-schedule-mermaid .activeCritText2,#fig-actual-schedule-mermaid .activeCritText3{fill:hsl(28.5714285714, 17.3553719008%, 86.2745098039%)!important;}#fig-actual-schedule-mermaid .titleText{text-anchor:middle;font-size:18px;fill:#ccc;font-family:'trebuchet ms',verdana,arial,sans-serif;font-family:var(--mermaid-font-family);}#fig-actual-schedule-mermaid :root{--mermaid-font-family:"trebuchet ms",verdana,arial,sans-serif;} 01/06 01/07 01/08 01/09 01/10 01/11 01/12 01/01 01/02 01/03 01/04 01/05 01/06 01/07 01/08 01/09Réunion de lancement Recherche technologies Rapport avant projet Soutenance avant projet POC Spécification API Spécification fonctionelle Présentation des frameworks Présentation application React / Choix définitif Création du projet Sprint 1 Point authentification Authentification Point stratégie de tests Validation specification API Fiche de développement V1 Test déploiement sur cible Sprint 2 Sprint 3 Soutenance intermédiaire Sprint 4 Formation React Introduction plateforme de développementSprint 5 Rapport final Soutenance finale EvaluationPréparationDéveloppementEseo Figure 12: Diagramme de GANTT effectif 4.7.1 Jalons Réunion de lancement : Cadre le projet, enjeux, objectifs, finalité, jalons projet, risques identifiés, calendrier projet, … Réunion premier choix : Choix du framework pour commencer le POC Réunion de validation : Validation définitive du choix du framework, planification des étapes de développement Réunion en début de sprint : Tri, organisation, revue des tâches à réaliser Réunion de fin de sprint: Bilan, présentation des tâches réalisés, revue des spécification, replanification des tâches non réalisées, … Réunion de clôture : Fin du projet, assure une transition pour la maintenance et l’exploitation du projet 4.7.2 Livrables Document de comparaison des frameworks avec une évaluation quantitative de chaque critère, basée sur une analyse détaillée. Document de spécification, détaillant les fonctionnalités, les exigences système, les ressources requises et les performances attendues. Prototype (POC) fonctionnel de l’interface web, respectant toutes les spécifications documentées. Feuille de route pour la mise en place du framework, détaillant les étapes à suivre pour la pour le développement des fonctionnalités, les ressources requises et les délais. Documentation développeur qui comprends un guide de démarrage et les bonnes pratiques de développement. Documentation utilisateur qui comprends un guide d’utilisation et les bonnes pratiques d’utilisation. Rapports et soutenances de projet. 4.8 Budget La durée du projet PING est estimée à 500 heures minimum. Ce projet devrait nécessiter plus de ressources. Le temps total nécessaire à la réalisation du projet est difficilement quantifiable pour le moment. Étant donné que le projet est cadré pour une seule personne, le coût peut être calculé en utilisant le tarif horaire du salaire brut annuel moyen d’un ingénieur débutant. Cela représente environ 10 000 €. Des coûts d’intervention de développement externes supplémentaires ponctuels peuvent s’ajouter, mais ils sont plus difficiles à chiffrer. La mobilisation de certains membres de l’équipe logiciel lors des réunions peut également être prise en compte. 5 Résultats 5.1 Evaluation des technologies du marché La première phase du projet visait à trouver une technologie alternative au framework Qt pour développer des application pour la plateforme web. Pour cela, j’ai établi une liste de critères permettant d’évaluer chaque solution. Besoins développement Besoins fonctionnels Langage de programmation Communauté et support Proximité avec l’existant Date de sortie Documentation Évolutivité Licence Outils Patron de conception Plateformes Popularité Possibles freins J’ai identifié l’ensemble des technologies qui permettent de développer des application pour la plateforme Web. Ces technologies peuvent être regroupées en 2 catégories, natif et multi-plateforme. La première catégorie comprends l’ensemble des frameworks basés sur le langage JavaScript. La seconde réuni quand à elle des solutions plus diverses qui ce basent sur différent langages comme le C#, le Dart ou le C++. Ces technologies peuvent permettre de cibler plusieurs plateformes (web, bureau, mobile) avec une base de code unique. Ce premier découpage m’a amener à tester 5 solutions. Natif : React Vue Angular Multi-plateforme : Flutter Uno platform J’ai établi une procédure de test unique. L’objectif était de comprendre le fonctionnement basique et l’architecture des frameworks ainsi que les langages sur lesquels ils sont basés. Le test consistait à réaliser une page affichant des données reçues par l’API REST et un formulaire permettant de modifier le nom d’hôte de l’équipement. A partir de cette petite étude, j’ai conclu que les frameworks multi-plateformes sont des solution moins adaptés à notre besoin. Elle sont plus complexes et n’ont pas une intégration complète avec le fonctionnalités d’un navigateur web. Les solutions natives semblaient plus simples à utiliser. La prochaine étape consistait à réaliser un POC plus complet qui intègre les fonctionnalités de certains modules de l’application Qt. J’ai opté pour l’utilisation de React, le framework les plus largement utilisé. J’ai supervisé activement la période de stage de Romain LeDivenah, qui a pris en charge la réalisation de ce POC. Malgré mon statut de débutant, j’ai pu guider Romain dans la prise en main de React. Au cours du mois de supervision, l’objectif était de développer un prototype fonctionnel, répondant aux critères définis, comprenant un menu ainsi que trois modules distincts. 5.2 Transition 5.2.1 OpenAPI La spécification de l’API est définie dans un document word qui évolue au fur et à mesure de l’ajout de fonctionnalités. Cette documentation peut être améliorée. Il existe des outils spécialisés respectant les standards de l’industrie. Ils permettent de générer la documentation, la modélisation et du code a partir d’un fichier de description. J’ai souhaité intégrer la migration vers une spécification de notre API REST basée sur la norme OpenAPI 3 pour avoir a disposition une spécification qui suis des règles appliquées au marché actuel. Il existe de nombreux outil qui utilisent cette norme que je voulais également intégrer. Le stage de Romain LeDivenah m’a permis de travailler sur d’autres aspects en parallèle comme la spécification de l’api, et l’intégration d’outils. J’ai rédigé la spécification de l’API REST en suivant la norme OpenAPI 3.0.0. J’ai également mis en place l’outil Swagger UI pour mettre à disposition une documentation interactive de l’API à partir de cette spécification. J’ai aussi utilisé OpenAPI Generator pour générer un SDK client en JavaScript. Cet étape permettra de simplifier l’utilisation de l’API REST dans l’application à développer. Enfin le dernier outil que j’ai déployé est Spotlight Prism. C’est un serveur simulé HTTP open source qui permet d’émuler le comportement de notre API à partir d’un jeu d’exemple qui peut être défini dans la spécification. Cet outil permet de tester l’API sans avoir d’équipement à disposition ou de développer la partie graphique avant ou en parallèle de l’intégration d’une nouvelle fonctionnalité dans le CAP4000. Exemple de documentation générée avec Swagger UI 5.2.2 Authentification L’authentification de l’API est basée sur un secret partagé. Cette solution pouvait être utilisé avec l’application Qt car celle-ci était compilée en un format binaire. Cela présente cependant des problématiques majeures, particulièrement dans le contexte du langage JavaScript. Étant un langage interprété, le code source JavaScript est généralement envoyé au client, exposant ainsi le secret partagé au sein du code. Cette exposition représente une menace sérieuse pour la sécurité de l’API, car un utilisateur malveillant pourrait potentiellement accéder au code source, récupérer le secret partagé et compromettre l’authentification. L’utilisation du protocole HTTP (non sécurisé) pour communiquer avec l’API représente un risque supplémentaire. En effet, les données envoyées sur le réseau ne sont pas chiffrées, ce qui permet à un attaquant d’intercepter les requêtes et d’obtenir le secret partagé. La vulnérabilité de cette approche souligne la nécessité de stratégies plus sécurisées, telles que l’utilisation de méthodes d’authentification basées sur des jetons et l’utilisation du protocole HTTPS pour communiquer avec l’API. Lucas CECILLON, référent cybersécurité, a pu travailler sur cette partie en spécifiant et en implémentant un nouveau mécanisme d’authentification basé sur l’utilisation d’un jeton JWT et l’utilisation du protocole HTTPS. Ce mécanisme à également introduit d’autres problématiques comme la gestion des certificats utilisés pour chiffrer la connexion HTTPS sur un équipement. Le protocole HTTP est utilisé pour communiquer avec l’API REST. L’authentification est basée sur un secret partagé. Ce secret est stocké dans le code source de l’application Qt. L’authentification est effectuée avec plusieurs sécurités : Signature des requêtes avec un HMAC (basé sur le secret partagé) Timestamp pour éviter les attaques de rejeu Contrairement à l’IHM Web en QT utilisant WebAssembly (projet compilé puis exécuté directement par le navigateur), React envoie les sources au navigateur (JS, HTML, CSS) pour y être exécutées. Le secret est donc facilement interceptable et visible par n’importe qui. Par conséquent, il est essentiel de mettre en place une gestion plus sécurisée de la session utilisateur. Plusieurs solutions ont été envisagées pour sécuriser l’authentification : - JWT - Bearer - Session Cookie - Basic La solution mise en place s’axe autour de trois points : Utilisation du protocole HTTPS pour sécuriser les échanges Utilisation de JWT (JSON Web Token) pour l’authentification Gestion des certificats pour chiffrer les communications Suivant les recommandations de l’anssi 5.2.2.1 Mesures de protection SSL CSRF CSP CORS Protection des cookies HSTS XSS Rafraîchissement du token Cryptographie Rejeux 5.2.2.2 HTTPS Selon l’étude [DR01] réalisée, il est essentiel d’établir une communication entre le client et l’API en utilisant le protocole HTTPS (HTTP sécurisé avec TLS). Cela signifie que chaque appel à l’API doit obligatoirement être effectué via le port HTTPS. Par exemple : https://192.168.0.1:3001/api/v3/test. De la même manière, il est impératif que l’utilisateur ne puisse accéder à l’application Web qu’en utilisant le protocole HTTPS. Aucun accès en HTTP ne pourra être fait. Tout cela nécessite une gestion appropriée des certificats sur le calculateur afin de prévenir d’éventuels problèmes d’accès en cas de certificats corrompus ou expirés. 5.2.2.3 JWT Dorénavant, l’authentification des requêtes sera basée sur l’utilisation de jetons d’accès. Ces jetons seront générés par l’API et renvoyés une fois l’authentification effectuée. Par la suite, pour chaque requête jusqu’à la déconnexion du client, le jeton devra être inclus dans la demande envoyée à l’API. Avant de traiter une demande, l’API vérifiera systématiquement le contenu et l’intégrité du jeton de la manière suivante : • Est-il valide ? ◦ SHA256(header + « . » + payload) == signature • Est-il expiré ? ◦ Valeur « exp » • L’utilisateur a-t-il le droit d’effectuer cette requête ? ◦ Valeur « role » Selon l’étude [DR01] réalisée, l’API doit renvoyer le token dans un cookie sécurisé. Voici les paramètres à appliquer au cookie : • name : name (nom du cookie) • value : value (valeur du token) • domain : domain (nom de domaine du site, ou ip) • path : « / » (chemin du cookie) • sameSite : strict (politique de cloisonnement) • httpOnly : true (inaccessible côté client) • session : true (cookie de session) • secure : true (portée limitée aux canaux sécurisés) L’API doit spécifier le domaine du cookie en fonction de l’adresse IP à partir de laquelle elle a été sollicitée. 5.2.2.4 Certificats La mise en place d’une nouvelle version de l’IHM et d’API qui communiquent exclusivement via HTTPS soulève des questions concernant le gestion des certificats sur le calculateur. En effet, si l’utilisateur de l’IHM parvient à déposer sur le calculateur un couple de clé-privée/certificat corrompus, alors le serveur web ne sera pas joignable en HTTPS. Cela empechera toute configuration par le client, ce qui n’est pas souhaitable. Pour éviter cette situation, il est essentiel de mettre en œuvre une solution de gestion de la configuration TLS robuste, reposant sur trois piliers principaux : la génération automatique de certificats auto-signés de secours, la sécurisation de l’import des certificats et de leur utilisation. Flowchart fallback certificats 5.2.3 POC supervision stage 5.3 Développement 5.3.1 Spécification de l’application Figure 13: Redmine IHM Web CAP4000 Figure 14: User story : configuration des interfaces réseaux L’application Qt n’a pas de spécification propre. J’ai utilisé le logiciel Redmine pour créer un backlog de l’ensemble des fonctionnalités à développer. J’ai également utilisé ce logiciel pour créer des user stories qui décrivent les fonctionnalités à développer. Ces user stories sont utilisées pour définir les critères d’acceptation des fonctionnalités. Elles sont également utilisées pour suivre l’avancement du développement. Evolution spécification Avant / Après Comparaison Utilité Changements 5.3.2 Fonctionnement de la solution On garde le meme principe voir schema contexte Fonctionnement de React TODO 5.3.3 Architecture/Workspace (expliquer comment fonctionne un monorepo) CI/CD (commitlint, semantic versioning, changelog) Développement (branches, pull request) Comparaison SVN Git -> gitlab J’ai créé l’environnement du projet dans un “monorepo”. C’est un référentiel unique qui permet de contenir plusieurs projet. J’ai choisi cette approche car nous souhaitons développer une application par produit. Comme l’application Qt, le code sera découpé en modules qui pourront être intégrés ou non dans l’application d’un produit. J’ai également mis en place une démarche qualité du code et des méthodologies de développement. L’application adopte la norme semantic versioning pour gérer les versions des projets. J’ai préparé un changelog pour répertorier toutes le évolution de l’application. J’ai finalement intégré l’outil commitlint pour vérifier que les messages de commit suivent une convention de rédaction. Le projet est versionné avec l’outil de gestion de configuration Subversion. Le projet suivra une méthodologie de développement en branches. Chaque fonctionnalité sera développée dans une branche dédiée. Une fois la fonctionnalité terminée, la branche sera fusionnée dans la branche principale. 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.commit-merge{stroke:#1f2020;fill:#1f2020;}#mermaid-8 .commit-reverse{stroke:#1f2020;fill:#1f2020;stroke-width:3;}#mermaid-8 .commit-highlight-inner{stroke:#1f2020;fill:#1f2020;}#mermaid-8 .arrow{stroke-width:8;stroke-linecap:round;fill:none;}#mermaid-8 .gitTitleText{text-anchor:middle;font-size:18px;fill:#ccc;}#mermaid-8 :root{--mermaid-font-family:"trebuchet ms",verdana,arial,sans-serif;}mainfea-networkfix-log0-14645aa1-6fbbbf7V0.12-dfad1603-a9e8c90V0.25-dda00826-f304b18 5.3.4 Bibliothèques (zod, react-hook-form, react-query, react-router, orval, react-testing-library, vitest) 5.3.4.1 Routing Définition Modules Gestion “plug-in” multi-app 5.3.5 Gestion des erreurs et des chargements 5.3.6 Authentification et autorisation Utilisateurs et rôles principes Note Existant HTTP / Headers auth Problème Solutions HTTPS/JWT choix reauthentification flow dashboard lucas 5.3.6.1 RBAC 5.3.7 Application Primitives/Core Routing Navigation Layout Page d’accueil QtReact Empty Previous Next 5.3.8 Modules J’ai étudié l’application Qt pour comprendre son fonctionnement et son architecture. J’ai ensuite identifié les modules qui la composent et les fonctionnalités qu’ils offrent. J’ai regroupé certains modules qui partagent des fonctionnalités similaires. J’ai ensuite créé une liste permettant de prioriser les modules en fonction de leur importance. Cette liste est présentée dans le tableau ci-dessous. Table 4: Ordre de priorité des modules Priorité Module Qt Module React 0 IDENTIFICATION Shell REDEMARRAGE CALCULATEUR Shell DECONNEXION Shell 1 ETHERNET ADRESSES IP Réseau NODES CARTES ETAT DES CARTES Cartes ETAT DES E/S DATE/HEURE ETAT SYNCHRO Date et heure MODE SYNCHRO FUSEAU HORAIRE DATE / HEURE JOURNAL JOURNAL Journal RAZ DU JOURNAL 2 CONFIGURATION IMPORT CONFIGURATION Configuration EXPORT CONFIGURATION MOTS DE PASSE Utilisateurs CERT. EQUIPEMENT Certificats CERTIFICATS CA Autorités de certification 3 LISTE MNEMOS Mnémoniques SYS LOG SYSLOG SNMP SNMP 4 SERVEUR IEC 60870 IEC 61850 CLIENT IEC 61850 SERVEUR MODBUS MODBUS MAITRE MODBUS MODBUS ESCLAVE MQTT MQTT 5 FICHIER Fichier IMPRIMANTES Imprimantes DEBOGAGE Débogage 5.3.8.1 Réseau QtReact Previous Next Previous Next Le premier module sur lequel j’ai travaillé est le module réseau. Ce module permet de configurer les adresses IP des interfaces réseau de l’équipement. Il permet également de configurer les nœuds du réseau. Les nœuds sont des équipements distants qui peuvent être connectés à l’équipement principal. Ce module est essentiel pour la configuration de l’équipement et pour assurer la communication avec les autres équipements du réseau. HSR et PRP TODO : Expliquer HSR et PRP https://fr.belden.com/solutions/high-availability-seamless-redundancy 5.3.8.2 Journal QtReact Previous Next Previous Next 5.3.8.3 Date et heure QtReact Previous Next Previous Next 5.3.8.4 Cartes QtReact Previous Next Previous Next 5.3.8.5 Configuration QtReact Previous Next Previous Next 5.3.8.6 Utilisateurs QtReact Previous Next 5.3.8.7 Certificats QtReact Previous Next 5.3.8.8 Autorités de certification QtReact Empty Previous Next 5.3.8.9 Mnémoniques QtReact Previous Next 5.3.9 Tests 5.3.10 Performances Les performance des deux applications ont été évaluée avec l’outil lighthouse de chrome. C’est un outil automatisé open source permettant de mesurer la qualité des pages Web. Les rapports générés par cet outil permettent d’identifier les problèmes de performance, d’accessibilité et de compatibilité. Rapport application Qt Rapport application React Également, l’outil ne calcule pas correctement les temps de chargement initiaux au démarrage des application WebAssembly (Qt). Le temps de chargement de l’application Qt est d’environ 15 secondes tandis que le temps de chargement de l’application react est quasiment instantané (autour de 1 seconde). Finalement l’outil ne rends pas compte de l’expérience utilisateur. L’application React est plus fluide et plus réactive. L’intégration d’une couche de cache limite aussi le rechargement des données. L’interface de l’application Qt est plus simple mais ne permets pas de naviguer rapidement entre les pages. 5.3.11 Application 5.3.11.1 Sprint 1 Autoformation Développement de l’application Shell et layout Module réseau Recherche d’une suite de tests Intégration avec des bibliothèques pertinentes Routage et navigation : react-router Cache client : react-query 5.3.11.2 Sprint 2 Développement de l’application Module journal Module date et heure Module cartes Refactorisation des modules développés modules 1 à 4 Délégation de la gestion des formulaire Validation des données : zod Gestion des formulaires : react-hook-form Mise en place de la gestion multi-application Mise en place des principes d’authentification et d’autorisation avec la gestion multi-utilisateur Mise en place des tests de composants avec cypress Conformité Non régression 5.3.11.3 Sprint 3 Écriture des tests des modules 1 à 4 Test de déploiement sur cible avec un nouveau serveur web Problématiques liées au développement d’ihm Layout Front/back Authentification Echange de données Technologies Evolution rapide Cest quoi react ? fonctionnement => une seule responsabilité => affichage ecosystème très large, nécessité d’adopter d’autres bibliothèques pour étoffer les fonctionnalités et garantir la qualité du code 6 Conclusion En conclusion, le projet entamé en juin 2023, a permis de développer une application de configuration des automates SDEL plus ergonomique et sécurisée. Les nouvelles fonctionnalités et interfaces ont été conçues en collaboration avec les utilisateurs finaux. Les retours positifs attestent de l’efficacité de cette approche centrée utilisateur. Cette nouvelle application vient étoffer notre offre de services et renforce notre positionnement sur le marché de l’énergie qui nécessite l’intégration de contraintes de cybersécurité de plus en plus importantes au fils des années. La vigilance demeure de mise, et une gestion proactive post-implémentation est recommandée pour assurer une adaptation continue aux évolutions technologiques et aux nouvelles menaces. Ce projet constitue ainsi un jalon important dans notre trajectoire vers l’innovation et la pérennité de nos systèmes. Aujourd’hui, l’application est utilisée quotidiennement par les opérateurs de maintenance de nos clients et les équipes de test en interne. D’un point de vue personnel, ce projet vient clôturer ma formation d’ingénieur. Il marque un terme à mes études et m’a permis de mettre en pratique les connaissances acquises durant ces trois années d’apprentissage. Sur le plan technique et scientifique, le projet m’a permis de consolider mes compétences en informatique. J’ai pu découvrir de nouvelles technologies et approfondir mes connaissances en développement WEB. En termes de montée en compétences, j’ai constaté une nette amélioration de ma compréhension des applications WEB ainsi que les contraintes appliqués au domaine de l’embarqué et des réseaux privés. Du point de vue économique, le chiffrage du projet et la mise en place d’un feuille de route ont constitué une expérience pratique sur le fonctionnement et la nécessité des ces processus en entreprise. Cela m’a sensibilisé aux implications financières des choix effectués en tant que responsable et aiguillé ma vision vers une approche plus stratégique et pragmatique. Sur le plan organisationnel, la gestion du projet m’a confronté à certains défis en termes de coordination, de planification et de suivi des tâches. J’ai pu mettre en pratique les méthodes agiles apprises en cours. J’ai également pu progresser en autonomie. Au début parfois trop distant et au fur et à mesure de l’avancement du projet, j’ai amélioré la transmission d’informations vers les différentes parties du projet. Ces compétences organisationnelles acquises seront indéniablement bénéfiques dans ma future carrière professionnelle. Quant à mon projet professionnel, cette expérience a confirmé ma passion pour le développement logiciel et a éclairé les prochaines étapes de ma carrière. Mon objectif est de m’orienter vers le développement logiciel, en particulier dans le domaine WEB et fullstack. Pour finir, cette expérience a été formatrice et enrichissante à bien des égards. Elle a façonné mon identité professionnelle et renforcé ma détermination à exceller dans le domaine de l’informatique. Je suis prêt à relever de nouveaux défis et à contribuer de manière significative à des projets futurs. 6.1 Bilan Le projet a débuté par la mise en place de l’environnement de travail et l’apprentissage autonome des technologies, avec peu de références internes dans l’entreprise. Environ 600 à 700 heures ont été consacrées au projet, avec une moitié du projet déjà réalisée. La plupart des objectifs des premières phases du projet ont été atteints. L’authentification reste à valider lors du prochain sprint. Des refactorisations ont été nécessaires au fur et à mesure de l’apprentissage. Le projet a donc atteint des jalons significatifs, mais le chemin vers la finalisation nécessite encore des efforts substantiels. Il reste encore environ 600 heures de travail pour finir le développement des modules restant. 7 Annexes 7.1 Références 7.2 Grille des compétences 7.3 Acknowledgments I am grateful for the insightful comments offered by the anonymous peer reviewers at Books & Texts. The generosity and expertise of one and all have improved this study in innumerable ways and saved me from many errors; those that inevitably remain are entirely my own responsibility
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Summary:
Hiramatsu et al. investigated how cognate neurotransmitter receptors with antagonizing downstream effects localize within neurons when co-expressed. They focus on mapping the localization of the dopaminergic Dop1R1 and Dop2R receptors, which correspond to the mammalian D1- and D2-like dopamine receptors, which have opposing effects on intracellular cAMP levels, in neurons of the Drosophila mushroom body (MB). To visualize specific receptors in single neuron types within the crowded MB neuropil, the authors use existing dopamine receptor alleles tagged with 7 copies of split GFP to target reconstitution of GFP tags only in the neurons of interest as a read-out of receptor localization. The authors show that both Dop1R1 and Dop2R, with differing degrees, are enriched in axonal compartments of both the Kenyon Cells cholinergic presynaptic inputs and in different dopamine neurons (DANs), which project axons to the MB. Co-localization studies of dopamine receptors with the presynaptic marker Brp suggest that Dop1R1 and, to a larger extent Dop2R, localize in the proximity of release sites. This localization pattern in DANs suggests that Dop1R1 and Dop2R work in dual-feedback regulation as autoreceptors. Finally, they provide evidence that the balance of Dop1R1 and Dop2R in the axons of two different DAN populations is differentially modulated by starvation and that this regulation plays a role in regulating appetitive behaviors.
Strengths:
The authors use reconstitution of GFP fluorescence of split GFP tags knocked into the endogenous locus at the C-terminus of the dopamine receptors as a readout of dopamine receptor localization. This elegant approach preserves the endogenous transcriptional and post-transcriptional regulation of the receptor, which is essential for studies of protein localization.
The study focuses on mapping the localization of dopamine receptors in neurons of the mushroom body. This is an excellent choice of system to address the question posed in this study, as the neurons are well-studied, and their connections are carefully reconstructed in the mushroom body connectome. Furthermore, the role of this circuit in different behaviors and associative memory permits the linking of patterns of receptor localization to circuit function and resulting behavior. Because of these features, the authors can provide evidence that two antagonizing dopamine receptors can act as autoreceptors within the axonal compartment of MB innervating DANs. The differential regulation of the balance of the two receptors under starvation in two distinct DAN innervations provides evidence of the role that regulation of this balance can play in circuit function and behavioral output.
Weaknesses:
The approach of using endogenously tagged alleles to study localization is a strength of this study, but the authors do not provide sufficient evidence that the insertion of 7 copies of split GFP to the C terminus of the dopamine receptors does not interfere with the endogenous localization pattern or function. Both sets of tagged alleles (1X Venus and 7X split GFP tagged) were previously reported (Kondo et al., 2020), but only the 1X Venus tagged alleles were further functionally validated in assays of olfactory appetitive memory. Despite the smaller size of the 7X split-GFP array tag knocked into the same location as the 1X venus tag, the reconstitution of 7 copies of GFP at the C terminus of the dopamine receptor, might substantially increase the molecular bulk at this site, potentially impeding the function of the receptor more significantly than the smaller, single Venus tag. The data presented by Kondo et al. 2020, is insufficient to conclude that the two alleles are equivalent.
The authors' conclusion that the receptors localize to presynaptic sites is weak. The analysis of the colocalization of the active zone marker Brp whole-brain staining with dopamine receptors labeled in specific neurons is insufficient to conclude that the receptors are localized at presynaptic sites. Given the highly crowded neuropil environment, the data cannot differentiate between the receptor localization postsynaptic to a dopamine release site or at a presynaptic site within the same neuron. The known distribution of presynaptic sites within the neurons analyzed in the study provides evidence that the receptors are enriched in axonal compartments, but co-labeling of presynaptic sites and receptors in the same neuron or super-resolution methods are needed to provide evidence of receptor localization at active zones. The data presented in Figures 5K-5L provides compelling evidence that the receptors localize to neuronal varicosities in DANs where the receptors could play a role as autoreceptors.
Given the highly crowded environment of the mushroom body neuropil, the analysis of dopamine receptor localization in Kenyon cells is not conclusive. The data is sufficient to conclude that the receptors are preferentially localizing to the axonal compartment of Kenyon cells, but co-localization with brain-wide Brp active zone immunostaining is not sufficient to determine if the receptor localizes juxtaposed to dopaminergic release sites, in proximity of release sites in Kenyon cells, or both.
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www.biorxiv.org www.biorxiv.org
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Author response:
The following is the authors’ response to the original reviews.
eLife assessment
This study defines a fundamental aspect of protein kinase signalling in the protist parasite Toxoplasma gondii that is required for acute and chronic infections. The authors provide compelling evidence for the role of SPARK/SPARKEL kinases in regulating cAMP/cGMP signalling, although evidence linking the loss of these kinases to changes in the phosphoproteome is incomplete. Overall, this study will be of great interest to those who study Toxoplasma and related apicomplexan parasites.
We thank the reviewers for their thoughtful and positive evaluation of our work. Below, we have addressed all of the public reviews and recommendations for the authors in point-by-point responses. Additionally, we include with this resubmission RT-qPCR data where we observe no significant change in transcript levels for the relevant AGC kinases, supporting the hypothesis that SPARK/SPARKEL–regulation is post-translational.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
Herneisen et al characterise the Toxoplasma PDK1 orthologue SPARK and an associated protein SPARKEL in controlling important fate decisions in Toxoplasma. Over recent years this group and others have characterised the role of cAMP and cGMP signalling in negatively and positively regulating egress, motility, and invasion, respectively. This manuscript furthers this work by showing that SPARK and SPARKEL likely act upstream, or at least control the levels of the cAMP and cGMP-dependent kinases PKA and PKG, respectively, thus controlling the transition of intracellular replicating parasites into extracellular motile forms (and back again).
The authors use quantitative (phospho)proteomic techniques to elegantly demonstrate the upstream role of SPARK in controlling cAMP and cGMP pathways. They use sophisticated analysis techniques (at least for parasitology) to show the functional association between cGMP and cAMP signalling pathways. They therefore begin to unify our understanding of the complicated signalling pathways used by Toxoplasma to control key regulatory processes that control the activation and suppression of motility. The authors then use molecular and cellular assays on a range of generated transgenic lines to back up their observations made by quantitative proteomics that are clear in their design and approach.
The authors then extend their work by showing that SPARK/SPARKEL also control PKAc3 function. PKAc3 has previously been shown to negatively regulate differentiation into bradyzoite forms and this work backs up and extends this finding to show that SPARK also controls this. The authors conclude that SPARK could act as a central node of regulation of the asexual stage, keeping parasites in their lytic cell growth and preventing differentiation. Whether this is true is beyond the scope of this paper and will have to be determined at a later date.
Strengths:
This is an exceptional body of work. It is elegantly performed, with state-of-the-art proteomic methodologies carefully being applied to Toxoplasma. Observations from the proteomic datasets are masterfully backed up with validation using quantitative molecular and cellular biology assays.
The paper is carefully and concisely written and is not overreaching in its conclusions. This work and its analysis set a new benchmark for the use of proteomics and molecular genetics in apicomplexan parasites.
Weaknesses:
This reviewer did not identify any weaknesses.
Reviewer #2 (Public Review):
Summary:
The manuscript by Herneisen et al. examines the Toxoplasma SPARK kinase orthologous to mammalian PDK1 kinase. The extracellular signals trigger cascades of the second messengers and play a central role in the apicomplexan parasites' survival. In Toxoplasma, these cascades regulate active replication of the tachyzoites, which manifests as acute toxoplasmosis, or the development into drug-resilient bradyzoites characteristic of the chronic stage of the disease. This study focuses on the poorly understood signaling mechanisms acting upstream of such second messenger kinases as PKA and PKG. The authors showed that similar to PDK1, Toxoplasma SPARK appears to regulate several AGC kinases.
Strengths:
The study demonstrated a strong association of the SPARK kinase with an elongin-like SPARKEL factor and an uncharacterized AGC kinase. Using a set of standard assays, the authors determined the SPARK/SPARKEL role in parasite egress and invasion. Finally, the study presented evidence of the SPARK/SPARKEL involvement in the bradyzoite differentiation.
Weaknesses:
Although the study can potentially uncover essential sensing mechanisms operating in Toxoplasma, the evidence of the SPARK/SPARKEL mechanisms is weak. Specifically, due to incomplete data analysis, the SPARK/SPARKEL-dependent phosphoregulation of AGC kinases cannot be evaluated. The manuscript requires better organization and lacks guidance on the described experiments. Although the study is built on advanced genetics, at times, it is unnecessarily complicated, raising doubts rather than benefiting the study.
The evidence for the SPARK/SPARKEL interaction is demonstrated through diverse experimental approaches that are internally consistent. Five separate mass spectrometry experiments, with replicates and appropriate controls, with tags on either SPARK or SPARKEL, showed that SPARK and SPARKEL form a strong interaction (Figure 1A, 1D, 1E; Figure 1—figure supplement 1). Global mass spectrometry experiments assessing the impact of SPARK or SPARKEL depletion showed similar features (a reduction in PKG and PKA abundance and up-regulation of bradyzoite-associated proteins; Figure 3C–D). The phenotypes associated with SPARK and SPARKEL depletion phenocopy one another in all cell biological assays we tested (Figure 2A, 2D and PMID: 35484233; Figure 2E–J; Figure 4E–F; Figure 6A–B). Measuring the abundance of SPARK and SPARKEL in unenriched samples was challenging, but immunoblotting and proteomics suggest that depletion of one factor leads to down-regulation of the other (Figure 2B, 2C; Figure 3—figure supplement 1), which explains the genetic and cell biological phenocopying described above. We note that “further biochemical studies are required to discern the regulatory interactions between SPARK and SPARKEL” (first submission lines 590-591) and are beyond the scope of this work.
The evidence for SPARK/SPARKEL regulation of AGC kinase activity is demonstrated through diverse experimental approaches that are also internally consistent. PKA C1 and PKG abundance levels decrease in parasites depleted of SPARK/SPARKEL, as measured by mass spectrometry (Figure 3A and 3C) and cell-based assays for PKA C1/R (Figure 4D–F). Comparisons of the global SPARK-, PKA R-, PKG-, and PKA C3-depleted phosphoproteomes suggest that PKA and PKG activity is reduced upon SPARK depletion whereas the activity of an unrelated factor (PP1) is unaffected (Figure 4G–H, Figure 4—figure supplement 1, Figure 5D–E, Figure 7I–J). Parasites depleted of SPARK are hypersensitized to a PKG inhibitor (Figure 5B–C). SPARK, PKA, and PKG are proximal in cellulo (Figure 3I) and SPARK co-purifies with PKA C3 (Figure 7A). The kinetic-phase phenotypes associated with SPARK and SPARKEL depletion (PMID: 32379047, Figure 2A, 2D–2J) are consistent with reduced PKG activity (PMID: 28465425) and only develop after PKG has been depleted as shown by proteomics experiments (Figure 2E-J and Figure 3C). Other studies have shown that the effects of reduced PKG activity are dominant to reduced PKA C1 activity (PMID: 29030485). The replicative-phase phenotypes associated with SPARK and SPARKEL depletion are consistent with reduced PKA C3 activity (PMID: 27247232 and herein). Mechanistically, PKG and PKA C1 activity must be lower in SPARK-depleted parasites because the abundances of these kinases are lower (Figure 3A, 3C). The mechanism of regulation may be more complex in the case of PKA C3, as SPARK depletion did not cause a reduction in PKA C3 abundance as measured by cellular assays (Figure 7B–F), but PKA C3 activity decreased (Figure 7I–K). We concede that multiple mechanisms may lead to the reduction in PKA C1 and PKG abundances, such as decreased activation loop phosphorylation and autophosphorylation at other stabilizing sites or enhanced ubiquitin ligase activity leading to active degradation of the kinases; we have moved speculation regarding such mechanisms to the Discussion.
Although the reviewer commented that the manuscript “requires better organization” in the public review, no specific recommendations were provided to the authors. Therefore, we did not change the organization of the manuscript. We added an additional paragraph to the Discussion to reiterate key findings: “A prior study identified SPARK as a regulator of parasite invasion and egress following 24 hours of kinase depletion (Smith et al., 2022). Unexpectedly, we observed that three hours of SPARK or SPARKEL depletion were insufficient to impact T. gondii motility or calcium-dependent signaling, indicating that the phenotypes associated with SPARK and SPARKEL depletion develop over time. Quantitative proteomics revealed that PKA and PKG abundances began to decrease after more than three hours of SPARK depletion. Proximity labeling experiments also suggested that SPARK, PKA, and PKG are spatially associated within the parasite cell. We propose a model in which SPARK down-regulation coincides with reduced PKG and PKA activity due to diminished protein levels.” This work built upon genetic and proteomic approaches recently described by our group, which we cited in the text and extensive methods section. We added additional experimental detail where noted in the reviewer’s recommendations to the authors.
The study utilizes advanced genetics because biochemical tools for eukaryotic parasites are limited. For example, no antibodies for T. gondii SPARK, PKA subunits, or PKG exist; to say nothing of phosphosite-specific antibodies, which are common in the mammalian cell signaling field. Therefore, to measure the relationship between SPARK, SPARKEL, and PKA subunits, we had to generate strains in which multiple proteins were tagged with epitopes for downstream analysis. The genetic experiments included appropriate controls and were internally consistent with results obtained using orthogonal approaches, such as mass spectrometry.
Reviewer #3 (Public Review):
Summary:
This paper focuses on the roles of a toxoplasma protein (SPARKEL) with homology to an elongin C and the kinase SPARK that it interacts with. They demonstrate that the two proteins regulate the abundance of PKA and PKG, and that depletion of SPARKEL reduces invasion and egress (previously shown with SPARK), and that their loss also triggers spontaneous bradyzoite differentiation. The data are overall very convincing and will be of high interest to those who study Toxoplasma and related apicomplexan parasites.
Strengths:
The study is very well executed with appropriate controls. The manuscript is also very well and clearly written. Overall, the work clearly demonstrates that SPARK/SPARKEL regulate invasion and egress and that their loss triggers differentiation.
Weaknesses:
(1) The authors fail to discriminate between SPARK/SPARKEL acting as negative regulators of differentiation as a result of an active role in regulating stage-specific transcription/translation or as a consequence of a stress response activated when either is depleted
We demonstrate a novel function for SPARK and SPARKEL as negative regulators of differentiation. The pathways leading to differentiation are being actively studied. Up-regulation of a positive transcriptional regulator of chronic differentiation, BFD1, is sufficient to trigger differentiation in vitro in the absence of other stressful growth conditions (PMID: 31955846). SPARK or SPARKEL depletion results in up-regulation of proteins that are up-regulated upon BFD1 overexpression. Whether BFD1 overexpression or SPARK and SPARKEL depletion triggers cellular stress pathways is beyond the scope of the current work, which focused instead on the immediate effect of these pathways on AGC kinases. Study of the effect of the various kinases on the parasite phosphoproteome shows that the putative targets of PKA C3 are specifically downregulated upon SPARK knockdown, indicating PKA C3 activity is indeed decreased in the latter condition.
(2) The function of SPARKEL has not been addressed. In mammalian cells, Elongin C is part of an E3 ubiquitin ligase complex that regulates transcription and other processes. From what I can tell from the proteomic data, homologs of the Elongin B/C complex were not identified. This is an important issue as the authors find that PKG and PKA protein levels are reduced in the knockdown strains
Our experiments suggest that SPARK and SPARKEL form a complex, and down-regulation of one complex member leads to down-regulation of the other. Thus in all tested assays, knockdown of SPARK and SPARKEL phenocopy one another. Further biochemical and structural work will be required to determine the mechanism by which SPARKEL regulates SPARK.
Nearly all studies of the function of elongin C have been conducted in mammalian cells. Proteins with elongin C domains may serve alternative and unexplored functions in unicellular eukaryotes. We searched for the presence of Elongin A/B and known Elongin C complex members in the T. gondii genome and were unable to identify orthologs, explaining why these proteins were not identified in mass spectrometry experiments. Please see our response in Recommendations for the Authors, Reviewer 3 point 2.
Beyond the concerns raised by the review team, we have identified and corrected the following errors or omissions in the first submission of the manuscript:
- Line 176 of the first submission referred to a “peptide sequence match (PSM)”, which we have changed to “peptide-spectrum match”.
- We recolored and relabeled the lines in Figure 5A so that it is easier to match a specific peptide with a specific line; and also corrected a mislabeling.
- Figure 7B SPARK panel was incorrectly centered. The raw files can be viewed in Figure 7—source data 2.
- Figure 7—figure supplement 1D was missing an x-axis label.
- Line 1172 referred to “Supplementary File X”, which we corrected to “Supplementary File 3”.
- We have updated references to preprints that have since been published, including PMID: 38093015, 37933960, 37966241, and 37610220.
Editors comments:
The proteomics data reported in this study underpin the major findings and are very comprehensive. As noted in the reviews, it is strongly recommended that the authors normalize the levels of detected phosphopeptides against the levels of the parent protein in the different mutant lines in order to identify changes in protein phosphorylation that are linked to protein kinase activity rather than protein degradation. A focus on changes that occur at early time points following protein knock-down may also help to identify the main targets of each kinase.
Please see our response to Reviewer 2 Recommendations for the Authors, points 1 and 2.
Reviewer #1 (Recommendations For The Authors):
During my reading, I only found one small mistake. In Figure 7F, the x-axis is missing the word 'PKA'.
We have updated the x-axis to read “SPARK-AID/PKA C3-mNG (h. + IAA)”.
All information, code, and reagents are clearly explained.
Reviewer #2 (Recommendations For The Authors):
How the phosphoproteome was analyzed needs to be clarified. The normalization step, computing the ratio of the phosphopeptide to the protein (peptide) intensity, appears omitted. It is the most critical step of the analysis. The minor shifts between protein and phosphosite intensity seem negligible, as seen in Figure 4 AB. The significant changes can only be deduced by calculating this ratio. In the current state, the presented results are inconclusive. The manuscript contains overreaching and often unsupported statements because the data has not been appropriately filtered. Related to this topic, it is advisable to use well-accepted terminology and complete words when describing proteome and phosphoproteome. The interexchange of a "peptide" and a "phosphopeptide" in the text confuses and misleads.
To clarify the phosphoproteome analysis:
We cite a previous description of the phosphoproteomics sample preparation workflow (lines 1124-1125 of the first submission for example). Our quantitative phosphoproteomics experiments comprise two datasets generated from the same multiplexed samples. The samples were split at the point of phosphopeptide enrichment. Ninety-five percent of the samples were subjected to phosphopeptide enrichment (titanium dioxide followed by nickel affinity chromatography; “enriched samples”). Five percent of the samples were reserved as a reference for the non-enriched proteome (“non-enriched samples”). To clarify this point, we have added the sentences “Approximately 95% of the proteomics sample was used for phosphopeptide enrichment” and “The remaining 5% of the sample was not subjected to the phosphopeptide enrichment protocol” to the Methods sections, after describing the multiplexing steps.
The samples were fractionated separately and run separately on an LC-MS system, which is described in the Methods section, for example lines 1130-1149 of the first submission. Raw files of the phosphopeptide-enriched and unenriched samples were analyzed separately, which is described in the Methods section, for example lines 1151-1158 of the first submission. To clarify this point, we have added the sentence “Raw files of the phosphopeptide-enriched and unenriched samples were analyzed separately” to the Methods sections. Many of the search parameters and descriptions of normalization and protein abundances were described in lines 1085-1093 of the first submission in reference to the 24h SPARK depletion proteome. We added this information to the description of the SPARK depletion time course phosphoproteome data analysis: “The allowed mass tolerance for precursor and fragment ions was 10 ppm and 0.02 Da, respectively. False discovery was assessed using Percolator with a concatenated target/decoy strategy using a strict FDR of 0.01, relaxed FDR of 0.05, and maximum Delta CN of 0.05. Only unique peptide quantification values were used. Co-isolation and signal-to-noise thresholds were set to 50% and 10, respectively. Normalization was performed according to total peptide amount. In the case of the unenriched samples, protein abundances were calculated from summation of non-phosphopeptide abundances.”
We hope that this clarifies how the unenriched sample protein-level abundances were calculated. When we discuss “protein abundance”, we are referencing the unenriched sample summed non-phosphopeptide abundance. Our phosphoproteome analysis was based only on phosphopeptides, as our phosphopeptide enrichment resulted in 99% efficiency, and peptides lacking phosphorylation sites were filtered out before subsequent analyses. We used “peptide” and “phosphopeptide” interchangeably because the only peptide-level analysis performed was based on phosphopeptide abundances. We have changed any mention of “peptide” to “phosphopeptide” in the main text.
“The normalization step, computing the ratio of the phosphopeptide to the protein (peptide) intensity, appears omitted. It is the most critical step of the analysis.”:
Unlike common differential gene expression analysis pipelines, proteomics analysis pipelines are not settled. Many analyses do not perform peptide-to-parent-protein corrections; some normalize phosphopeptide abundances to parent protein abundances calculated from summing non-phosphopeptides or a combination of phosphopeptide and non-phosphopeptides on an ad hoc basis; some calculate global normalization factors based on regressions of protein and phosphopeptide abundances or other pairwise comparisons. A caveat of protein normalization of phosphopeptides is that it over-corrects cases in which protein abundance and phosphorylation are interdependent, as is the case for auto-phosphorylation and some activation loop phosphorylations (PMID: 37394063). We used the approach that retained the greatest complexity of the data, which is to not normalize abundances across different mass spectrometry experiments and discard information that was not in the overlap. We have updated Supplementary File 3.3 to include protein-level quantification values (from Supplementary File 3.2) if measured.
We clarified that the phosphopeptide abundances and protein-level abundances were derived from different datasets that were each internally normalized (globally centered by total peptide amount). Protein-level abundances were summed from non-phosphopeptide abundances. The calculated log2 changes are based on the globally centered data within each dataset. We analyzed the kinetic profiles of changing phosphopeptide abundances relative to a control using approaches similar to those described for several recent temporally resolved T. gondii phosphoproteomes (e.g. PMID: 37933960, 35976251, 36265000, 29141230) and as described in the Methods. The approach does not first correct for unenriched-sample parent protein abundance—in some applications, unenriched samples are not collected at all; instead, phosphopeptide ratios are median-normalized to non-phosphopeptide ratios (quantified due to inefficient phosphopeptide enrichment) and are individually tested against the null distribution of non-phosphopeptide ratios (e.g. PMID: 36265000, 29141230). We did not use this approach because our phosphopeptide enrichment was 99% efficient (18518 phosphopeptides of 18758 peptides with quantification values). In several cases using our approach, parent protein abundance is not quantified in the unenriched proteome dataset, but phosphopeptides are reliably quantified in the enriched proteome dataset. We note that phosphopeptide abundance changes can be difficult to interpret in such cases, e.g. in the first submission lines 178-186 and 193-194. We have added similar text to the results noting that in the case of PKA and PKG, both unenriched parent protein and enriched phosphopeptide abundances decreased (see below). We have also moved speculation about whether SPARK phosphorylates the activation loop of PKA and PKG, or whether the down-regulation of PKA and PKG arises from indirect effects, to the Discussion.
We have moved comparisons of protein and phosphopeptide abundances from the Results to the Discussion. We added the following sentences to the result section Clustering of phosphopeptide kinetics identifies seven response signatures: “Because non-phosphopeptide and phosphopeptide abundances were quantified in different mass spectrometry experiments, it is challenging to compare the rates of phosphopeptide and parent protein abundance changes, especially when phosphorylation status and protein stability are interconnected. In general, both PKA C1, PKA R, and PKG protein and phosphosite abundances decreased following SPARK depletion (Figure 3—figure supplement 1), as discussed further below. We also observed down-regulation of phosphosite and protein abundances of a MIF4G domain protein.” Figure 3—figure supplement 1E is a new panel that shows PKA C1, PKA R, and PKG phosphopeptide and parent protein abundances along with global changes in phosphopeptide and parent protein abundances in the cases which both were quantified. We changed lines 278-282 in the first submission to “The SPARK depletion time course phosphoproteome showed a reduction in the abundance of PKA C1 T190 and T341, which are located in the activation loop and C-terminal tail, respectively (Figure 4A). Several phosphosites residing in the N terminus of PKA R (e.g. S17, S27, and S94) also decreased following SPARK depletion (Figure 4B).” We changed lines 313-315 in the first submission to “The SPARK depletion time course phosphoproteome showed a reduction in the abundance of several phosphosites residing in the N terminus of PKG as well as T838, which corresponds to the activation loop (Figure 5A). By contrast, S105 did not greatly decrease, and S40 abundance slightly increased.”
The description of experiments should be more detailed. For example, the 3, 8, and 24 h treatments were used reversely; thus, they should be emphasized as time points before natural egress. Consequently, it seems that 3h treatment should be prioritized, given the SPARK/SPARKEL role in egress/invasion. Unexpectedly, the study draws more attention to a 24-hour treatment. If the AID-SPARK/SPARKEL is eliminated within 1h, parasites undoubtedly accumulate numerous secondary defects during a prolonged 23h deprivation. Since the SPARK pathway activates kinase/phosphatase cascades, the 24h data is likely overwhelmed with the consequences of the long-term complex degradation, making it a poor source of the putative SPARK substrates. Likewise, the downregulation of PKA observed in the 8 hours after SPARK depletion may be an indirect effect of the SPARK degradation. The direct effects and immediate substrates should be detectable within 2-3h of auxin treatment of the nearly egressing cultures.
The first submission described how parasites were harvested at 32 hours post-infection with 0, 3, 8, or 24 hours of IAA treatment (lines 157-160, 1097-1110, and Figure 3B). To reiterate this experimental detail, we have added “harvested 32 hours post-infection” to the sentence “...quantitative proteomics with tandem mass tag multiplexing that included samples with 0, 3, 8, and 24 hours of SPARK or SPARKEL depletion” and similarly in the figure legend. The time points are unrelated to natural egress because the experiment was terminated at 32 hours post-infection, which is earlier than the window typically used to study natural egress under these conditions (40-48 hours post-infection). We chose to terminate the experiment before natural egress to better localize phosphopeptide changes related to SPARK depletion. The phosphoproteome undergoes dramatic reorganization during egress due to the activity of myriad kinases and phosphatases (see PMID: 35976251, 37933960, and 36265000), which would have likely complicated the signal.
A pivotal result motivating time-course experiments and analysis was that SPARK/SPARKEL's role in egress and invasion emerges only after an extended depletion period (Figure 2E–J, first submission lines 126-145). The 24h depletion was used in the experimental system that first identified SPARK as a regulator of egress, which motivated our initial experiments, as stated in the first submission lines 126-144 and 149-151. We draw attention to the observation that SPARK and SPARKEL phenotypes develop over time in the first submission, lines 137-145. The role for SPARK/SPARKEL in egress/invasion does not manifest at 3h depletion; it manifests at 24h depletion. To ensure that this point is not overlooked by the reader, we have created a new heading in the Results section (SPARK and SPARKEL depletion phenotypes develop over time) for the paragraph that was previously lines 137-145. The remainder of the manuscript integrates data from proteomic, genetic, and cell-based assays across temporal dimensions to build a working model of how the phenotypes associated with SPARK depletion develop over time.
Underpinning this comment is an assumption that phosphopeptides that decrease the most rapidly following a kinase’s depletion are direct substrates, whereas phosphopeptides that decrease with slower kinetics are not. This is not always the case. Consider a kinase that phosphorylates sites on substrate A and substrate B. The site on substrate A is also the target of a phosphatase, whereas the site on substrate B is recalcitrant to phosphatase activity. If the kinase were inhibited, then the site on substrate A would be actively dephosphorylated. As measured by a phosphoproteomics experiment, the abundance of the substrate A phosphopeptide would drop rapidly due to the inactivity of the kinase and activity of the phosphatase. In the text, we called such sites “constitutively regulated” or dynamic—they are actively dephosphorylated and phosphorylated within a short timeframe. The phosphosite on substrate B is comparatively static; once it is phosphorylated by the kinase, it is unaffected by subsequent inhibition of the kinase. Only newly synthesized substrate B molecules would be affected by kinase inhibition. As measured by a phosphoproteomics experiment, the abundance of the substrate B phosphopeptide would drop more gradually after kinase inhibition, as the unphosphorylated peptide is found only on newly synthesized proteins that were not previously exposed to kinase activity. An example of the scenario described for substrate A would be that of yeast Cdk1 T14/Y15, which is phosphorylated by Wee1 and dephosphorylated by Cdc25 (e.g. PMID: 7880537). An example of the scenario described for substrate B would be that of the human PKA C activation loop T197, which is phosphorylated by PDK1 and is phosphatase-resistant under physiological conditions (e.g. PMID: 22493239, 15533936).
Both substrate A and B may be “direct” and functionally relevant targets of the kinase. Categorizing substrates as “immediate” is comparatively less informative in this context (although it may be relevant when studying fast, synchronized processes with high temporal resolution, such as induced Plasmodium spp. gametocyte activation or stimulation of T. gondii secretion). Furthermore, our earlier experiments had shown that the role for SPARK/SPARKEL in motility manifests after 3h depletion and is complete by 24h depletion. By this logic, we were most interested in the candidates showing differences at these time points. We conducted proximity labeling experiments to identify the overlap of proteins that exhibited SPARK-dependent decreases in the global proteomics and were also proximal to SPARK in space (first submission Figure 3I and lines 260-275), thus revealing a prioritized list of candidates, which included PKG and PKA. When technically feasible, we included a temporal dimension to follow-up experiments, rather than relying on a 24h terminal comparison (e.g. Figure 4E–H, Figure 5D–E, Figure 7D–F, Figure 7I–K; all first submission).
Fig2 (B and C). What antibodies had been used to detect tagged proteins? There is a concern regarding the use of multiple tags attached to the same protein to the point that it doubles the size of the studied protein. The switch of the mobility of the SPARK and SPARKEL on the WB due to a change in MW adds to the confusion. Furthermore, the study did not use all the fused epitopes (e.g., HA). At the same time, the same V5 tag was used to detect two factors in the same parasite. Although the controls are provided, it does not eliminate the possibility that the second band on the WB results from one protein degradation rather than the presence of two individual proteins. Different tags should be used to confirm the co-expression of two proteins. Panel E is missing the X-axis label.
Figure 2B was incorrectly labeled; the labels corresponding to SPARK and SPARKEL were switched. We corrected this error in the revised figures. The antibodies used were mouse monoclonal anti-V5 as described in the key resources table of the first submission. We added “V5” to Figure 2A and 2B. Regarding the effect of the tagging payload attached to the proteins, we have included in all assays a control relative to a parental strain (TIR1) without a tagging payload, and additionally included internal controls within tagged strains to calculate dependency of a phenotype on IAA treatment. The western blots in Figure 2B and 2C are from two different strains and experiments. The strains and experiments are described in the first submission main text (lines 113-124), the figure legend (lines 1847-1850), the key resources table, and the methods (lines 650-664, 872-891). A description of the SPARK-AID/SPARKEL-mNG strain was included in the key resources table but omitted in the methods. We therefore added the following section to the Methods:
“SPARKEL-V5-mNG-Ty/SPARK-V5-mAID-HA/RHΔku80Δhxgprt/TIR1
The HiT vector cutting unit gBlock for SPARKEL (P1) was cloned into the pALH193 HiT empty vector. The vector was linearized with BsaI and co-transfected with the pSS014 Cas9 expression plasmid into SPARK-V5-mAID-HA/RHΔku80Δhxgprt/TIR1 parasites. Clones were selected with 1 µM pyrimethamine and isolated via limiting dilution to generate the SPARKEL-V5-mNG-Ty/SPARK-V5-mAID-HA/RHΔku80Δhxgprt/TIR1 strain. Clones were verified by PCR amplification and sequencing of the junction between the 3′ end of SPARKEL (5’-GGGAGGCCACAACGGCGC-3’) and 5′ end of the protein tag (5’-gggggtcggtcatgttacgt-3’).”
To clarify the expected MW of each species, we have added the following text to the Methods:
“The expected molecular weight of SPARKEL-V5-HaloTag-mAID-Ty is 66 kDa, from the 42.7 kDa tagging payload and 23.3 kDa protein sequence. The expected molecular weight of SPARK-V5-mCherry-HA is 89.7 kDa, from the 31.9 kDa tagging payload and 57.8 kDa protein sequence. The expected molecular weight of SPARK-V5-mAID-HA is 71.3 kDa, from the 13.5 kDa tagging payload and 57.8 kDa protein sequence. The expected molecular weight of SPARKEL-V5-mNG-Ty is 55.2 kDa, from the 31.9 kDa tagging payload and 23.3 kDa protein sequence.”
SPARK and SPARKEL are lowly expressed, which may have been compounded by basal degradation due to the AID tag (see for example Figure 3—figure supplement 1D of the first submission). We attempted several immunoblot conditions and antibodies, and only the V5 antibody proved effective in recognizing these proteins above the limit of detection. For this reason, we included an additional single-tagged control in each immunoblot experiment. Uncropped images of the blots are included in the first submission as Figure 2—figure supplement 1D and E and as Figure 2 source data. We added the following statement to the results section of the text:
“However, SPARK and SPARKEL abundances are low and approach the limit of detection. We could only detect each protein by the V5 epitope. Although our experiments included single-tagged controls, we cannot formally eliminate the possibility that SPARK-AID yields degradation products that run at the expected molecular weight of SPARKEL. More sensitive methods, such as targeted mass spectrometry, may be required to measure the absolute abundance and stoichiometries of SPARK and SPARKEL.”
We added “h +IAA” to the x-axis of panel 2E.
Fig. 3. There is plentiful proteomic data on the factor-depleted parasites. Can it be used to confirm the co-degradation of the SPARK/SPARKEL complex components? This figure mainly includes quality control data that can be moved to Supplement. Did you detect SPARKEL in the TurboID experiment described in panel I? The plot shows only an AGC kinase.
SPARK and SPARKEL are lowly expressed, and we often do not detect SPARK or SPARKEL peptides with quantification values in complex samples (such as global depletion proteomes and phosphoproteomes; IPs and streptavidin pull-downs are comparatively less complex, with IPs being the least complex samples). We discussed this caveat in the first submission lines 178-186. To additionally clarify this point, we have added “We were unable to measure SPARK or SPARKEL abundances in this proteome” earlier in the text.
We consider the figure panels relevant to the discussion in the text.
SPARKEL was not quantified in the SPARK-TurboID experiment (Supplementary File 2). We have added “SPARKEL was not quantified in this experiment” to the text. “Not quantified” is a different outcome from “quantified but not enriched”. The interaction between SPARK and SPARKEL is supported by five other independent interaction experiments in which SPARKEL was quantified (Figure 1A, 1D, 1E; and Figure 1—figure supplement 1). The added insight from the SPARK proximity labeling experiments comes from integration with the global proteomics, which suggests that AGC kinases are in proximity to SPARK and exhibit SPARK-dependent stability and hence activity. The logic of the proximity labeling experiment is described in lines 258-275 of the first submission.
Fig. 6G is missing deltaBDF1 control for unbiased evaluation of the SPARK KD effect.
The logic of this experiment was to evaluate whether excess differentiation caused by SPARK and PKA C3 depletion (Figure 6A and 6B) was dependent on the BFD1 circuit. The ∆bfd1 phenotype is well-established under these experimental conditions: parasites lacking BFD1 do not differentiate under spontaneous or alkaline conditions (e.g. PMID: 31955846, 37081202, 37770433). Parasites lacking BFD1 do not differentiate when SPARK and PKA C3 are depleted, suggesting that differentiation caused by SPARK or PKA C3 depletion occurs through the BFD1 circuit. If differentiation caused by SPARK or PKA C3 depletion did not depend on the BFD1 circuit, we might have observed differentiation in the SPARK- and PKA C3-AID/∆bfd1 mutants.
To clarify this point, we have changed the first sentences of the last paragraph in the results section Depletion of SPARK, SPARKEL, or PKA C3 promotes chronic differentiation: “To assess whether excess differentiation caused by SPARK and PKA C3 depletion is dependent on a previously characterized transcriptional regulator of differentiation, BFD1 (Waldman et al., 2020), we knocked out the BFD1 CDS with a sortable dTomato cassette in the SPARK- and PKA C3-AID strains (Figure 6–figure supplement 1). The resulting SPARK- and PKA C3-AID/∆bfd1 mutants failed to undergo differentiation as measured by cyst wall staining (Figure 6G–H), suggesting that differentiation caused by depletion of these kinases depends on the BFD1 circuit.”
Lines 239-242. The logic behind the categories of "constitutively regulated sites" and "newly synthesized proteins dependent on SPARK activation" is odd. The former (3h treatment) represents the SPARK-specific events (even though it should be shortened to 1-2h), while an 8h treatment is already contaminated with secondary effects. Since Toxoplasma divides asynchronously, the "newly synthesized" proteins will be present at the time. Also, the protein phosphorylation does not always lead to substrate activation; it can be repressive, too.
We describe the logic in response to a comment above (substrate A vs. substrate B). It is correct that T. gondii divides asynchronously, with a cell cycle of approximately 8 hours, and 60% of parasites in G1 at a given time (PMID: 11420103). The proteomics experiments measure peptide and protein abundances at a population level. Newly synthesized proteins will be present at all time points; but the proportion of proteins synthesized after SPARK depletion relative to proteins synthesized before SPARK depletion will increase over time.
We moved lines 238-243 from the first submission to the Discussion.
It is accurate that phosphorylation does not always lead to substrate activation; it can also be repressive or not change substrate behavior. However, in the case of protein kinases, activation loop phosphorylation is highly correlated with activation (e.g. PMID: 15350212, 31521607).
Line 250-252: Because the SPARK degradation did not affect intracellular replication, SPARK is unlikely to affect cell cycle-specific phosphorylation.
To parallel the prior sentences describing different SPARK-dependent down-regulated clusters, we truncated this sentence to “The final cluster of depleted phosphopeptides, Cluster 4, only exhibits down-regulation at 8h of IAA treatment.”
SPARKEL depletion did not significantly affect intracellular replication under the time frames investigated here (approximately 25 hours post-invasion; Figure 2D). A prior study reported that SPARK depletion did not affect intracellular replication measured on a similar timescale (PMID: 35484233).
The opening sentence of the Discussion: Typically, we refer to the newly discovered proteins as the orthologs of the previously discovered counterparts and not the vice versa. Thus, calling Toxoplasma SPARK the ortholog of mammalian PDK1 would be more appropriate.
We changed the opening sentence of the Discussion to “SPARK is an ortholog of PDK1, which is considered a key regulator of AGC kinases”.
Reviewer #3 (Recommendations For The Authors):
(1) Authors should show alignment of SPARKEL with Elongin C. Are key residues conserved?
We have added an alignment of the SKP1/BTB/POZ domains of Homo sapiens elongin C, S. cerevisiae elongin C, and T. gondii SPARKEL as Figure 1—figure supplement 1B. This panel highlights elongin B interface, cullin binding sites, and target protein binding sites based on the human elongin C annotation. As discussed below, these interfaces may not be functionally conserved in T. gondii. Ultimately, future mechanistic and structural studies beyond the scope of the current work will be required to determine how SPARK and SPARKEL physically interact. The Discussion states, “further biochemical studies are required to discern the regulatory interactions between SPARK and SPARKEL” (lines 590-591).
(2) The failure to identify other Elongin B/C complex members should be addressed by direct IP analysis.
Indeed, elongin C has traditionally been characterized as a component of multisubunit complexes comprising Elongin A/B/C or Elongin BC/cullin/SOCS that regulate transcription or function as ubiquitin ligases, respectively (for a review, PMID: 22649776). We see two major issues when attempting to generalize these results to apicomplexan parasites. First, nearly all studies of the function of elongin C have been conducted in a single eukaryotic supergroup (the opisthokonts, including yeast and metazoans). The majority of eukaryotic diversity exists in other supergroups, including the SAR supergroup to which apicomplexans such as T. gondii belong (PMID: 31606140). Proteins with elongin C domains may serve alternative and unexplored functions in non-opisthokont unicellular eukaryotes. Second (in support of the first), we were unable to find orthologs of many of the opisthokont complex members in T. gondii, as systematically described below.
By BLAST, the most similar protein to SPARKEL in S. cerevisiae is ELC1 (YPL046C), with a BLAST E = 0.003. The next most similar protein was SCF ubiquitin ligase subunit SKP1 (YDR328C) with an E value of 0.62. ELC1 is 99 amino acids. The Elongin C (IPR039948) and SKP1/BTB/POZ superfamily domains (IPR011333) span most of this sequence. SPARKEL is 216 amino acids; the Elongin C and SKP1/BTB/POZ superfamily domains occupy the C-terminal half of the protein. The N-terminal domain of SPARKEL may be important for its function; however, future work is required to address this hypothesis.
Elongin B: Elongin B is not found universally amongst even opisthokonts; fungi and choanoflagellates lack obvious orthologs. The most similar T. gondii protein to human Elongin B (Q15370) by BLAST is TGME49_223125 (E = 0.017), an apicoplast ubiquitin-like protein PUBL (PMID: 28655825, 33053376). TGME49_223125 has a C-terminal ubiquitin-like domain (IPR000626) but no ELOB domain (IPR039049); indeed, no T. gondii protein has an ELOB domain that can be identified by sequence searching. Given the lack of similarity between EloB and TGME49_223125, as well as this protein’s possible red algal endosymbiont origin, we consider it an unlikely ortholog of EloB and topologically unlikely to interact with the SPARK/SPARKEL complex. We did not detect TGME49_223125 in SPARK or SPARKEL IPs (Supplementary File 1).
Elongin A: T. gondii appears to lack a human elongin A ortholog (Q14241) on the basis of sequence similarity. The most similar T. gondii protein to yeast Elongin A (O59671) by BLAST is TGME49_299230 (E = 0.022). Yeast EloA is 263 amino acids. TGME49_299230 is 1101 amino acids and does not have an EloA domain (IPR010684), suggesting it is not a true EloA ortholog.
Suppressor of cytokine signaling (SOCS): T. gondii appears to lack human SOCS1 or SOCS2 orthologs (O15524 and O14508) on the basis of sequence similarity. We were unable to identify T. gondii proteins with SOCS domains (PF07525, SM00253, SM00969, and SSF158235).
Von Hippel-Lindau tumor suppressor (VHL): T. gondii appears to lack a human VHL ortholog (P40337) on the basis of sequence similarity. We were unable to identify T. gondii proteins with VHL domains (IPR024048, IPR024053, PF01847, and SSF49468).
Cul-2/5: Cullins appeared early in the eukaryotic radiation (PMID: 21554755), and thus T. gondii possesses several. Since the ELC complex has been best characterized with human cullin-2 (Q13617) and cullin-5 (Q93034), we searched for orthologs of these proteins and identified TGME49_289310, TGME49_289310, and TGME49_316660. TGME49_289310 functionally resembles cullin-1 of the SCF complex (PMID: 31348812). None of these proteins were enriched in the SPARK or SPARKEL IPs (Supplementary Table 1).
Rbx1: We searched for human Rbx1 orthologs (P62877) and identified TGME49_213690, which functionally resembles Rbx1 of the SCF complex (PMID: 31348812); as well as several other RING proteins (TGME49_267520, TGME49_277740, TGME49_261990, and TGME49_232160) that were not found in the SPARK or SPARKEL IPs (Supplementary File 1).
Rbx2: We searched for human Rbx2 orthologs (Q9UBF6) and identified several RING proteins (TGME49_285190, TGME49_254700, TGME49_292340, TGME49_226740, TGME49_244610, and TGME49_304460) that were not found in the SPARK or SPARKEL IPs (Supplementary File 1). No T. gondii protein has an Rbx2 domain (cd16466) that can be identified by sequence searching.
In conclusion, we conducted “direct IP analysis” (Figure 1A, 1D; Figure 1-supplement 1A) of the SPARK and SPARKEL complex in the first submission of the manuscript. The observation that SPARK and SPARKEL form strong interactions was validated in cellulo via proximity labeling (Figure 1E; Figure 1-supplement 1B) in the first submission of the manuscript. These results are described together in the results section SPARK complexes with an elongin-like protein, SPARKEL (lines 75-110, first submission of manuscript). The failure to identify an interaction between SPARKEL and Elongin B/C complex members in T. gondii may be due to the observation that Elongin B and several ELC complex members do not exist in most eukaryotes, including T. gondii. We added the sentences “The function of proteins with Elongin C-like domains has not been widely investigated in unicellular eukaryotes” to the Results and “However, the SPARK and SPARKEL IPs and proximity experiments failed to identify obvious components of ubiquitin ligase complexes” to the Discussion.
(3) PKA and PKG half-lives should be measured as well as their transcript abundances.
The finding that PKA C1 and PKG protein abundances decreased upon SPARK/SPARKEL depletion was internally consistent across experiments. This down-regulation may be due to transcriptional, translational, or post-translational mechanisms. We measured PKG and PKA C1 transcript abundances in SPARK-AID and TIR1 parasites after 24 hours of IAA treatment using RT-qPCR. We did not detect significant differences in transcript levels of the queried kinases. These findings suggest that SPARK depletion leads to PKG and PKA down-regulation through post-transcriptional mechanisms. Translational control is normally enacted globally, for example through regulation of eukaryotic translation factors (PMID: 15459663). The rapid and specific down-regulation of PKG and PKA C1 would suggest that the kinase abundance levels are regulated by non-global translational mechanisms (e.g. mRNA-specific) or rather post-translational mechanisms.
Substantial additional work is required to determine protein half-lives in eukaryotic parasites. In our discussion of possible mechanisms and models, we were agnostic as to the cause of reduced PKG and PKA abundances upon SPARK depletion. We note in the discussion, “The cause for reduction of PKA C1 and PKG levels requires further study” (lines 541-542).
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Joint Public Review:
Ewing sarcoma is an aggressive pediatric cancer driven by the EWS-FLI oncogene. Ewing sarcoma cells are addicted to this chimeric transcription factor, which represents a strong therapeutic vulnerability. Unfortunately, targeting EWS-FLI has proven to be very difficult and better understanding how this chimeric transcription factor works is critical to achieving this goal. Towards this perspective, the group had previously identified a DBD-𝛼4 helix (DBD) in FLI that appears to be necessary to mediate EWS-FLI transcriptomic activity. Here, the authors used multi-omic approaches, including CUT&tag, RNAseq, and MicroC to investigate the impact of this DBD domain. Importantly, these experiments were performed in the A673 Ewing sarcoma model where endogenous EWS-FLI was silenced, and EWS-FLI-DBD proficient or deficient isoforms were re-expressed (isogenic context). The authors found that the DBD domain is key to mediate EWS-FLI cis activity (at msat) and to generate the formation of specific TADs. Furthermore, cells expressing DBD deficient EWS-FLI display very poor colony forming capacity, highlighting that targeting this domain may lead to therapeutic perspectives.
This new version of the study comprises as requested new data from an additional cell line. The new data has strengthened the manuscript. Nevertheless, some of the arguments of the authors pertaining to the limitations of immunoblots to assess stability of the DBD constructs or the poor reproducibility of the Micro C data remain problematic. While the effort to repeat MicroC in a different cell line is appreciated, the data are as heterogeneous as those in A673 and no real conclusion can be drawn. The authors should tone down their conclusions. If DBD has a strong effect on chromatin organization, it should be reproducible and detectable. The transcriptomic and cut and tag data are more consistent and provide robust evidence for their findings at these levels.
Concerning the issue of stability of the DBD and DBD+ constructs, a simple protein half-life assay (e.g. cycloheximide chase assay) could rule out any bias here and satisfactorily address the issue.
Suggestions:
The Reviewing Editor and a referee have considered the revised version and the responses of the referees. While the additional data included in the new version has consolidated many conclusions of the study, the MicroC data in the new cell line are also heterogeneous and as the authors argue, this may be an inherent limitation of the technique. In this situation, the best would be for the authors to avoid drawing robust conclusions from this data and to acknowledge its current limitations.
The referee and Reviewing Editor also felt that the arguments of the authors concerning a lack of firm conclusions on the stability of EWS-FLI1 under +/-DBD conditions could be better addressed. We would urge the authors to perform a cycloheximide chase type assay to assess protein half-life. These types of experiments are relatively simple to perform and should address this issue in a satisfactory manner.
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Author response:
The following is the authors’ response to the original reviews.
Reviewer #1 (Public Review):
Summary:
Ewing sarcoma is an aggressive pediatric cancer driven by the EWS-FLI oncogene. Ewing sarcoma cells are addicted to this chimeric transcription factor, which represents a strong therapeutic vulnerability. Unfortunately, targeting EWS-FLI has proven to be very difficult, and a better understanding of how this chimeric transcription factor works is critical to achieving this goal. Towards this perspective, the group had previously identified a DBD-𝛼𝛼4 helix (DBD) in FLI that appears to be necessary to mediate EWS-FLI transcriptomic activity. Here, the authors used multi-omic approaches, including CUT&tag, RNAseq, and MicroC to investigate the impact of this DBD domain. Importantly, these experiments were performed in the A673 Ewing sarcoma model where endogenous EWS-FLI was silenced, and EWS-FLI-DBD proficient or deficient isoforms were re-expressed (isogenic context). They found that the DBD domain is key to mediating EWS-FLI cis activity (at msat) and to generating the formation of specific TADs. Furthermore, cells expressing DBD-deficient EWS-FLI display very poor colony-forming capacity, highlighting that targeting this domain may lead to therapeutic perspectives.
We thank Reviewer 1 for their strong summary of Ewing sarcoma background and accurate description of our experimental approaches and findings.
Strengths:
The group has strong expertise in Ewing sarcoma genetics and epigenetics and also in using and analyzing this model (Theisen et al., 2019; Boone et al., 2021; Showpnil et al., 2022).
We thank the reviewer.
They aim at better understanding how EWS-FLI mediated its oncogenic activity, which is critical to eventually identifying novel therapies against this aggressive cancer.
We are happy to see that our overall aim was also appreciated by Reviewer 1.
They use the most recent state-of-the-art omics methods to investigate transcriptome, epigenetics, and genome conformation methods. In particular, Micro-C enables achieving up to 1kb resolved 3D chromatin structures, making it possible to investigate a large number of TADs and sub-TADs structures where EWS-FLI1 mediates its oncogenic activity.
We thank Reviewer 1 for their acknowledgement of our approaches and the resolution achieved with our Micro-C experiments.
They performed all their experiments in an Ewing sarcoma genetic background (A673 cells) which circumvents bias from previously reported approaches when working in non-orthologous cell models using similar approaches.
We agree with the reviewer about the importance of using model systems that accurately capture features of the disease being studied. As we have added an additional cell line in the revision we should note that this second model also represents a Ewing sarcoma genetic background while representing tumors expressing another oncogenic fusion found in this disease.
Weaknesses:
The main weakness comes from the poor reproducibility of Micro-C data . Indeed, it appears that the distances/clustering observed between replicates are typically similar or even larger than between biological conditions. For instance, in Figure 1B, I do not see any clustering when considering DBD1, DBD2, DBD+1, DBD+2.
Lanes 80-83: "KD replicates clustered together with DBD replicate 1 on both axes and with DBD replicate 2 on the y-axis. DBD+ replicates, on the other hand, clustered away from both KD and DBD replicates. These observations suggest that the global chromatin structure of DBD replicates is more similar to KD than DBD+ replicates."
When replacing DBD replicate 1 with DBD replicate 2, their statement would not be true anymore.
Additional replicates to clarify this aspect seem absolutely necessary since those data are paving the way for the entire manuscript.
These are valid concerns and we thank the reviewers for highlighting this limitation of poor clustering of Micro-C replicates on MDS plot. We account for this variability between different replicates when identifying differentially interacting regions. By using an adjusted p-value < 0.05, we aim to ensure that repeating the experiments we will discover the same differentially interacting regions with a false discovery rate of 5%.
We also would like to note that the replicates cluster much closely on PCA plot of RNA-seq data (Supplementary Figure 1C) and as well as on PCA plot of H3K27ac CUT&Tag data (Figure 4A). Notably, the RNA-seq result has now reproduced when performed with different sets of hands across multiple studies (Boone, et. al., 2021 and this report), as well as in a second cell line (as reported in this manuscript revision). These observations suggest that the cells of these replicates are functionally similar to each other at a population level. Chromatin organization detected by Micro-C is a highly heterogenous within cells of a population (Misteli, et. al., 2020). Moreover, despite increased resolution with Micro-C over Hi-C, the conventional sequencing depth that Micro-C is performed at makes resolving finer scale 3D interactions, particularly between enhancers and promoters, challenging (Goel, et. al., 2023). Thus biologically relevant interactions driving EWSR1::ETS transcriptional regulation through de novo enhancers may have relatively weak signal in Micro-C. Both the strength of the signal and the heterogeneous chromatin state present in bulk samples could affect the average signal leading to poor clustering replicates (Hafner and Boettiger, 2022).
Importantly, rather than add an additional replicate of a single cell line, we repeated our study in an additional cell line, TTC466, and largely reproduced our high-level findings for transcription, enhancer formation, and 3D chromatin. Specific limitations of the TTC466 study are addressed in the Discussion section (392-420). The reproduction of weak/moderate clustering in the MDS plot in both A673 and TTC466 cell lines suggests the α4 helix of EWSR1::ETS fusions are important for reshaping 3D chromatin. However, higher resolution analyses focused on specific EWSR1::ETS-bound loci are likely an important area of future study required to fully understand the role of the α4 helix in chromatin regulation in Ewing sarcoma.
Similarly:
- In Figure 1C, how would the result look when comparing DBD2/KD2/DBD+2? Same when comparing DBD 1 with KD1 and DBD+1. Would the difference go in the same direction?
This is a great point. We added distance decay plots of individual replicates in Supplementary Figure 2 and added discussion of these results in lines 88-89 of the text.
- Figure 1D-E. How would these plots look like when comparing each replicate to each other's? How much difference would be observed when comparing, for instance, DBD1/DBD2 ? or DBD1/DBD+1?
Unfortunately, separate replicates are required to conduct Differentially Interacting Region analysis as it determines statistically significant interactions. Therefore, we are unable to plot these analyses with individual replicates.
- Figure 2: again, how would these analyses look like when performing the analysis with only DBD1/DBD+1/KD1 or DBD2/DBD+2/KD?
This is a good suggestion. It is possible to do such analysis. However, we will lose resolution as such that we may not accurately detect TADs, especially smaller TADs. Therefore, we decided to combine the biological replicates.
Another major question is the stability of EWS-FLI DBD vs EWS-FLI DBD+ proteins. In the WB, FLAG intensities seem also higher (2/3 replicates) in DBD+ condition compared to the DBD condition (Figure S1B).
This is a valid concern with shRNA knock-down/rescue system and we regularly validate new constructs to ensure that they have similar expression levels as rescue with the wildtype fusion before proceeding to more exhaustive experimental workups. We would note that while we have not tested for differences in protein stability, for these constructs we largely see similar expression levels across multiple experiments, multiple cell lines, and multiple sets of hands. There may be some variations in expression level from experiment to experiment, but western blotting is a semiquantitative assay and it is also not possible to rule out that slight differences in band intensity may be a result of error in gel loading. For this reason, alongside western blotting for construct expression, we also validate construct function using RNA-seq and colony formation assays (as reported in this manuscript) and these show good agreement across biological replicates.
Indeed, it seems that they have more FLAG (i.e., EWS-FLI) peaks in the DBD+ condition compared to the DBD condition (Figure 2B).
We appreciate the comment since the legend of Figure 2B led to a misunderstanding. Figure 2B depicts the number of TADs detected in DBD and DBD+ conditions (height of the bar graphs) and the proportion of those TADs overlapped with FLAG, CTCF, both or neither peaks on y-axis. The number of FLAG peaks is actually lower in DBD+ as compared to DBD as shown in Figure 5A-B. We clarified our Figure 2 legend to accurately describe the various proportions (color coded section) of TADs bound by DBD/DBD+ FLAG and CTCF.
Would it be possible that DBD+ is just more expressed or more stable than DBD? The higher stability of the re-expressed DBD+ could also partially explain their results independently of the 3D conformational change. In other words, can they exclude that DBD+ and DBD binding are not related to their respective protein stability or their global re-expression levels?
It is possible that DBD+ protein is overexpressed or more stable than DBD. With our current set of data, we cannot conclusively exclude if binding by DBD and DBD+ are not related to their expression level or stability. We would note, as above, that western blots, RNA-seq, and agar assays have largely reproduced across experiments, hands, and cell lines and that western blot is an imperfect assay for assessing protein stability.
Surprisingly, WB FLI bands in DBD+ conditions are systematically (3/3 replicates) fainter than in DBD conditions (Figure S1B). How do the authors explain these opposite results between FLI and FALG in the WB?
This is an excellent observation that highlights one of the intricacies of studying EWSR1::FLI1 in our KD/rescue system. Often the limiting factor for an experiment is whether or not the KD condition maintains KD through a second viral transduction for rescue and selection. We have observed over many years of working with this system that rescue conditions which are fully functional (i.e. wildtype EWSR1::FLI1, DBD+, etc.) tend to maintain better KD of endogenous EWSR1::FLI1. Constructs that don’t rescue EWSR1::FLI1 function sometimes maintain KD to a lesser degree, though frequently to a functional degree (i.e. cells are not transformed and EWSR1::FLI1 transcriptional regulation is not rescued). We suspect this observation, also raised by Reviewer 1 is resulted from a potential selection of cells with more endogenous EWSR1::FLI1 escaping KD in in DBD conditions due to selective pressures during expansion in tissue culture.
We should note that the antibody used for detecting FLI recognizes residues that are deleted in
DBD and DBD+ constructs, such that the FLI1 blot in Supplementary Figure 1B does not detect either construct. It only detects endogenous EWSR1::FLI1 and the 3X-FLAG-EWSR1::FLI1 construct in the middle lane that runs at a slightly higher molecular weight. The FLAG antibody is the only antibody that detects all three rescue constructs.
Reviewer #2 (Public Review):
Summary:
The manuscript by Bayanjargal et al. entitled "The DBD-alpha4 helix of EWS::FLI is required for GGAA microsatellite binding that underlies genome regulation in Ewing sarcoma" reports on the critical role of a small alpha helix in the DNA binding domain (DBD) of the FLI1 portion of EWS::FLI1 that is critical for binding to repetitive stretches of GGAA-motifs, i.e. GGAA microsatellites, which serve as potent neoenhancers in Ewing sarcoma.
We thank Reviewer 2 for their succinct and accurate summary of our manuscript.
Strengths:
The paper is generally well-written, and easy to follow and the data presented are of high quality, welldescribed and underpin the conclusions of the authors. The report sheds new light on how EWS::FLI1 mechanistically binds to and activates GGAA microsatellite enhancers, which is of importance to the field.
We appreciate the reviewer’s assessment of our work.
Weaknesses:
While there are no major weaknesses in this paper, there are a few minor issues that the authors may wish to address before publication:
(1) While the official protein symbol for the gene EWSR1 is indeed EWS, the protein symbol for the gene FLI1 is identical, i.e. FLI1. The authors nominate the fusion oncoprotein EWS::FLI1 (even in the title) but it appears more adequate to use EWS::FLI1.
We appreciate the reviewer for bringing this to our attention. Indeed, the most recent guideline for fusion proteins nomenclature is to use the full gene symbols separated by double colons. Therefore, the accurate nomenclature is EWSR1::FLI1. We replaced instances of EWS::FLI with EWSR1::FLI1 and have used the EWSR1::ERG nomenclature in our revised manuscript.
(2) The used cell lines should be spelled according to their official nomenclature (e.g. A-673 instead of A673).
Corrected, thanks!
(3) It appears as if the vast majority of results were generated in a single Ewing sarcoma cell line (A-673) which is an atypical Ewing sarcoma cell line harboring an activating BRAF mutation and may be genomically quite unstable as compared to other Ewing sarcoma cell lines (Kasan et al. 2023 preprint at bioRxiv https://www.biorxiv.org/content/10.1101/2023.11.20.567802v1). Hence, it may be supportive for the paper to recapitulate/cross-validate a few key results in other Ewing sarcoma cell lines, e.g. by using EWS::ERG-positive cell lines. Perhaps the authors could make use of available published data.
We thank Reviewer 2 for this helpful comment. We replicated the experiments in TTC-466 cells containing EWSR1::ERG fusion and found that as for A-673 cells the DBD-α4 helix is important for transcriptional, enhancer, and 3D chromatin regulation (Supplementary Figures 9-18).
(4) Figure 6 and Supplementary Figure 5 are very interesting but focus on two selected target genes of the fusion (FCGRT and CCND1). It would be interesting to see whether these findings also extend to common EWS::ETS transcriptional signatures that have been reported. The authors could explore their data and map established consensus EWS::ETS signatures to investigate which other hubs might be affected at relevant target genes.
We expanded our analysis to other genes demonstrated to be regulated by EWSR1::FLI1 nucleated transcriptional hubs (Chong, et. al., 2018) and included NKX2-2 and GSTM4 gene regions in
Supplementary Figure 7-8 in A-673 cells. We also investigated the same gene regions of FCGRT, CCND1, NKX2-2, GSTM4 in TTC466 cells and report them in Supplementary Figures 14-17. For the purpose brevity, we decided to include the above examples. We may need to develop different tools to conduct further analysis to understand the gene regulatory networks driven by DBD and DBD+ in relation to hub formation. Although it is a great suggestion to map such network, this may be outside the scope of this manuscript. We thank the reviewer for bringing such a good point to our attention.
(5) Table 1 is a bit hard to read. In my opinion, it is not necessary to display P-values with up to 8 decimal positions. The gene symbols should be displayed in italic font.
Suggestions are adapted, thanks!
Reviewing Editor (Recommendations For The Authors):
We would draw the authors' attention to the following issues that would best benefit from additional revision.
As indicated by Referee 1, an important issue concerns the apparent poor reproducibility of Micro-C data. In Figure 1B, the clustering of the DBD1, DBD2, DBD+1, and DBD+2 is poor.
It appears that the distances/clustering observed between replicates are typically similar or even larger than between biological conditions. Lines 80-83: "KD replicates clustered together with DBD replicate 1 on both axes and with DBD replicate 2 on the y-axis. DBD+ replicates, on the other hand, clustered away from both KD and DBD replicates. If one replaced DBD replicate 1 with DBD replicate 2, this statement would no longer be true. The referees believe that it is important to fully account for these potential discrepancies. Most of the study is based on analyses of these data sets, so if there are issues with them it has repercussions on the entire study. We note however that in Figure 4A the clustering of the H3K27ac data is much more convincing. The referees also feel that it is important to show immunoblots of the expression of DBD and DBD+ levels in the experiments performed here. While this was previously shown in the Boone et al publication in 2021, it could be illustrated again here.
We thank the editors for concisely summarizing the main weaknesses of the paper and underscoring the importance of the Micro-C data in the rest of the paper. While the Editors note tighter clustering of the H3K27ac (Figure 4A), we would like to note that the replicates cluster much closely on PCA plot of RNA-seq data (Supplementary Figure 1C). Notably, the RNA-seq result has now reproduced when performed with different sets of hands across multiple studies (Boone, et. al., 2021 and this report), as well as in a second cell line (as reported in this manuscript revision). Though not as tight, the H3K27ac CUT&Tag also reproduces in TTC466 cells. Thus, we interpret these findings to indicate that our replicates are functionally similar to each other. As discussed above in the response to Reviewer 1 in more detail, there are several factors that could affect how these functional similarities are represented in Micro-C data. Micro-C is ultimately a readout of the chromatin organization in a heterogeneous population of cells (Misteli et al., 2020). Additionally, sequencing depth limitations in conventional Micro-C experiments limit the ability to faithfully assess the enhancer-promoter interactions that may be relevant for our model system (Goel, et. al., 2023). Thus, both the strength of the biologically relevant signal and the heterogeneous chromatin state present in bulk samples could affect the average signal and lead to poorly clustering replicates (Hafner and Boettiger, 2022).
To address these important concerns about rigor and reproducibility of the analyses, we repeated our study in an additional cell line, TTC466, and largely reproduced our high-level findings for transcription, enhancer formation, and 3D chromatin. These additional studies were not without their own limitations and these are addressed in the Discussion section (392-420). The reproduction of weak/moderate clustering in the MDS plot in both A673 and TTC466 cell lines suggests the α4 helix of EWSR1::ETS fusions are important for reshaping 3D chromatin. However, additional genomic analyses geared toward higher resolution at specific EWSR1::ETS-bound loci are likely an important area of future study required to fully understand the role of the α4 helix in chromatin regulation in Ewing sarcoma. Live cell imaging, as performed by Chong, et. al., 2018 and additional biochemical techniques may also be informative and are beyond the scope of this report.
With regards to concerns about construct expression, we have included immunoblots of the rescue constructs in both cell lines (Supplementary Figure 1B and 9A) and discussed Reviewer 1’s specific concerns in detail above.
The referees also raise the issue of using an additional cell line to make a more general message. Although it would perhaps be asking too much to repeat the MicroC experiments, consolidation of the observations could be performed by focusing on specific loci such as FCGRT and CCND1 that were analyzed in this study. Could the authors use 4C-type experiments to reproduce the conclusions in an additional cell line? It would also be pertinent to consolidate the findings at these loci by 4C-type approaches even in the cell line used here. For the moment, all conclusions are based on the same set of data and a single technical approach.
We repeated the experiments in TTC466 cells and analyzed the data using same cut-offs used in A-673 cells. This allows us to compare between the two cell lines. We hope this new set of experiments and analyses address the reviewers’ concerns.
Reviewer #1 (Recommendations For The Authors):
All the data are performed in A673 cells. Knowing the transcriptomic and epigenetic heterogeneity of Ewing sarcoma cells, some of the experiments supporting their findings should be replicated in at least another Ewing sarcoma model.
Per our discussion above, we have replicated our experiments in an additional cell line model of Ewing sarcoma. Importantly, the TTC466 cell line used expresses the EWSR1::ERG fusion found in 10-15% of Ewing sarcoma cases.
Supplementary Figure 2B. Proportion of TAD boundaries bound by FLAG (i.e., EWS-FLI1) and CTCF. The number/proportion of FLAG (i.e., EWS-FLI) peaks observed at CTCF peak/TAD boundaries seems unexpectedly high. How do they explain this result since EWS-FLI peaks are rather intra-TAD to mediate their enhancer function?
In our previous study, we showed that EWSR1::FLI1 binding can be detected at boundaries of TADs (Showpnil, et. al., 2022). We think therefore it is likely that EWSR1::FLI1 binding is able to mediate enhancer function both inside TADs as well as at the borders of TADs and may, in some cases, function as an insulator between TADs.
For the >50kb loop analysis, what was the low-range threshold? Up to 15-20 kp, contact frequency interactions may be caused by PFA crosslink (did they use a 5kb threshold ?). Were those excluded from that analysis?
We acknowledge that we did not use a lower threshold to exclude those short-range loop interactions. In our previous study, we observed that EWSR1::FLI1 binding reduces long-range interactions in favor of short-range interactions (Showpnil, et. al., 2022) and wanted to be able to capture short-range loops in our analysis.
In Figure 2D, they observed that within TADs containing FLAG peaks at GGAA microsatellites, the intensity of the DBD+ FLAG peaks was higher compared to DBD FLAG peaks. How would this analysis look when considering the ETS FLAG peaks (i.e., EWS-FLI rather repressive peaks)? Could they compare TAD with GGAA msat vs TAD with ETS peaks?
We agree that this is an interesting observation. In our prior analyses we found no discernible relationship between EWSR1::FLI1 binding and changes in 3D chromatin associated with repression (Showpnil, et. al., Nucleic Acids Research, 2022). In contrast, EWSR1::FLI1-bound superenhancers had greater H3K27ac deposition when overlapping both a bound GGAA repeat and a non-microsatellite site. While there have been several additional reports about the relevance of EWSR1::FLI1 binding at nonmicrosatellite peaks, motifs at these loci have not yet been rigorously defined as GGAA repeats were by Johnson, et. al. in PLoS One, 2017. Each ETS factor binds different motifs containing the core 5’-GGAA-3’ with varying affinities depending on the flanking residues. There may be >100-fold difference in sequence-specific binding affinity for “high” vs. “low” affinity motifs. Better defining the types of ETS motifs bound by EWSR1::FLI1 and the functional changes associated with them thus represents an interesting area of future study.
Figure 1F: What is the biological meaning of these results (29.7, 39.5, and 54Mbp)? These distances are typically the size of a chromosome arm and clearly beyond classical chromatin loop/TAD structures in which EWS-FLI mediates its cis-activity.
We agree with referee here. This panel is now removed in our revised manuscript.
How do DBD, KD, and DBD+ conditions compare with WT parental cells in the omics data? (Figures 1B, 4A). Do DBD+ conditions overlap with WT conditions? It would be nice to have these analyses also for Micro-C and Cut&Tag data. To be acknowledged here, the transcriptome data showing this aspect in Figure S1C are very convincing.
This is a fair point. We were not able to obtain similar sequencing depth of wtEF Micro-C libraries to that of KD, DBD and DBD+ due to disproportional use of wtEF libraries in troubleshooting. Therefore, we decided to exclude wtEF condition from these analysis.
EWS-FLI cis-regulation at CCND1 also occurs through a much closer EWS-FLI peak (~-20kb msat upstream of CCND1 TSS) which was not taken into consideration. EWS-FLI peak intensity in both DBD and DBD+ at this msta seems similar. How would this fit into their model?
The referee is correct. The closest peak upstream of CCND1 TSS is about ~19kb away. We highlighted this peak with the dashed boxes near the CCND1 TSS (Supplementary Figure 6). Peak intensity of DBD+ FLAG is slightly higher compared to DBD. Nonetheless, we acknowledge that the difference is small. We suspect that the DBD-α4 helix is affecting binding dynamics at GGAA repeats, but these genomics approaches are not well suited to detect small, but significant, changes in binding affinity or dynamics. In this case a more biochemical approach may be needed. Even though, both protein can still bind the same microsatellites, it is possible that they might differ in their stability of binding or in the recruitment of additional proteins. These possibilities are discussed in the Discussion section (444-463).
For the Micro-C, they sequenced only 7 to 8 million reads per condition. This coverage seems particularly low, especially for their analyses using 1-5kb bins. How does this compare with other published Micro-C data? Can this explain the variability observed between replicates?
We apologize for the inconsistent verbiage of sequencing coverage that may have caused confusion. 7 to 8 million reads were used for shallow sequencing and QC analysis. Once a sample passed QC, we then sequenced 300 million reads per sample. 300M is now changed to 300 million to prevent a misunderstanding at line 598.
They mention:
"In our recent studies of EWS::FLI, we found a small alpha helix in the DNA binding domain DBD-𝛼𝛼4, to
be required for transcription and regulation by the fusion protein (Boone et al., 2021). Interestingly, this study did not find any change in chromatin accessibility (ATAC-Seq) and genome localization of EWS::FLI constructs (CUT&RUN) when DBD-𝛼𝛼4 helix was deleted leaving the mechanistic basis for the requirement of DBD-𝛼𝛼4 in transcription regulation unclear. "
And
"To assay the enhancer landscape, we collected H3K27ac CUT&Tag data from KD, DBD, and DBD+ cells. Principal component analysis of H3K27ac localization shows that the DBD replicates were clustered closer to the KD replicates while being in between the KD and the DBD+ replicates (Figure 4A), suggesting that DBD-𝛼𝛼4 helix is required to reshape the enhancer landscape."
But now H3K27ac CUT&Tag show strong differences which were not observed in ATAC seq. How to explain this discrepancy?
Though both H3K27ac and ATAC signal are associated with enhancers and promoters in euchromatin, they are not exactly measurements of the same thing. H3K4me2 is a mark more closely associated with ATAC signal than H3K27ac (Henikoff, et. al., 2020). Nonetheless, there are clear differences between the prior publication (Boone, et. al., 2021) and this work with regards to similar ATAC signal for each replicate and differences in H3K27ac. We suspect this may be related to a tighter association between H3K27ac and EWSR1::FLI1-mediated genome regulation and ATAC. Notably, there were very few differentially accessible regions between EWSR1::FLI1-depleted cells and conditions with EWSR1::FLI1 expression (either endogenous or wildtype rescue) using the A673 KD/Rescue system in Boone, et. al., 2021. In contrast, other A673 KD-rescue studies have reported differences in H3K27ac in EWSR1::FLI1 expressing conditions relative to EWSR1::FLI1-depleted conditions (Theisen, et. al., 2021). .
The authors mention:
"Our study thus uncovered a surprising role for FLI DBD in the process of hub formation which is usually attributed to the EWS low complexity domain."
Not sure this can be claimed, hubs are composed of many other factors that are not investigated here. Furthermore, promoter enhancer hubs/loops often include combined ETS and mSat chains to generate transcriptional hubs which have not been considered here. None of these points were discussed here.
We replaced “uncovered” with “suggest” in our revised manuscript at line 476.
What are the barcode patterns in Supp 5, are those frequently observed in their Micro-C data, likely mapping artifacts, do they have any impact on their analyses?
The barcode patterns in now Supplementary Figure 6 are blind spots in the hg19 genome assembly. Since they are few in numbers, we don’t expect these blind spots to impact our analysis.
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Reviewer #1 (Public Review):
Summary:
This research article by Nath et al. from the Lee Lab addresses how lipolysis under starvation is achieved by a transient receptor potential channel, TRPγ, in the neuroendocrine neurons to help animals survive prolonged starvation. Through a series of genetic analyses, the authors identify that TRPγ mutations specifically lead to a failure in lipolytic processes under starvation, thereby reducing animals' starvation resistance. The conclusion was confirmed through total triacylglycerol levels in the animals and lipid droplet staining in the fat bodies. This study highlights the importance of transient receptor potential (TRP) channels in the fly brain to modulate energy homeostasis and combat metabolic stress. While the data is compelling and the message is easy to follow, several aspects require further clarification to improve the interpretation of the research and its visibility in the field.
Strengths:
This study identifies the biological meaning of TRPγ in promoting lipolysis during starvation, advancing our knowledge about TRP channels and the neural mechanisms to combat metabolic stress. Furthermore, this study demonstrates the potential of the TRP channel as a target to develop new therapeutic strategies for human metabolic disorders by showing that metformin and AMPK pathways are involved in its function in lipid metabolisms during starvation in Drosophila.
Weaknesses:
Some key results that might strengthen their conclusions were left out for discussion or careful explanation (see below). If the authors could improve the writing to address their findings and connect their findings with conclusions, the research would be much more appreciated and have a higher impact in the field.
Here, I listed the major issues and suggestions for the authors to improve their manuscript:
(1) Are the increased lipid droplet size and the upregulated total TAG level measured in the starved or sated mutant in Figure 1? This information might be crucial for readers to understand the physiological function of TRP in lipid metabolism. In other words, clarifying whether the upregulated lipid storage is observed only in the starved trp mutant will advance our knowledge of TRPγ. If the increase of total TAG level is only observed in the starved animals, TRP in the Dh44 neurons might serve as a sensor for the starvation state required to promote lipolysis in starvation conditions. On the other hand, if the total TAG level increases in both starved and sated animals, activation of Dh44 through TRPγ might be involved in the lipid metabolism process after food ingestion.
(2) It is unclear how AMPK activation in Dh44 neurons reduces the total triacylglycerol (TAG) levels in the animals (Figure 3G). As AMPK is activated in response to metabolic stress, the result in Figure 3G might suggest that Dh44 neurons sense metabolic stress through AMPK activation to promote lipolysis in other tissues. Do Dh44 neurons become more active during starvation? Is activation of Dh44 neurons sufficient to activate AMPK in the Dh44 neurons without starvation? Is activation of AMPK in the Dh44 neurons required for Dh44 release and lipolysis during starvation? These answers would provide more insights into the conclusion in Lines 192-193.
(3) It is unclear how the lipolytic gene brummer is further downregulated in the trpγ mutant during starvation while brummer is upregulated in the control group (Figure 6A). This result implies that the trpγ mutant was able to sense the starvation state but responded abnormally by inhibiting the lipolytic process rather than promoting lipolysis, which makes it more susceptible to starvation (Figure 3B).
(4) There is an inconsistency of total TAG levels and the lipid droplet size observed in the Dh44 mutant but not in the Dh44-R2 mutant (Figures 7A and 7F). This inconsistency raises a possibility that the signaling pathway from Dh44 release to its receptor Dh44-R2 only accounts for part of the lipid metabolic process under starvation. Adding discussion to address this inconsistency may be helpful for readers to appreciate the finding.
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Reviewer #2 (Public Review):
Summary:
In this paper, the function of trpγ in lipid metabolism was investigated. The authors found that lipid accumulation levels were increased in trpγ mutants and remained high during starvation; the increased TAG levels in trpγ mutants were restored by the expression of active AMPK in DH44 neurons and oral administration of the anti-diabetic drug metformin. Furthermore, oral administration of lipase, TAG, and free fatty acids effectively restored the survival of trpγ mutants under starvation conditions. These results indicate that TRPv plays an important role in the maintenance of systemic lipid levels through the proper expression of lipase. Furthermore, authors have shown that this function is mediated by DH44R2. This study provides an interesting finding in that the neuropeptide DH44 released from the brain regulates lipid metabolism through a brain-gut axis, acting on the receptor DH44R2 presumably expressed in gut cells.
Strengths:
Using Drosophila genetics, careful analysis of which cells express trpγ regulates lipid metabolism is performed in this study. The study supports its conclusions from various angles, including not only TAG levels, but also fat droplet staining and survival rate under starved conditions, and oral administration of substances involved in lipid metabolism.
Weaknesses:
Lipid metabolism in the gut of DH44R2-expressing cells should be investigated for a better understanding of the mechanism. Fat accumulation in the gut is not mechanistically linked with fat accumulation in the fat body. The function of lipase in the gut (esp. R2 region) should be addressed, e.g. by manipulating gut-lipases such as magro or Lip3 in the gut in the contest of trpγ mutant. Also, it is not clarified which cell types in the gut DH44R2 is expressed. The study also mentioned only in the text that bmm expression in the gut cannot restore lipid droplet enlargement in the fat body, but this result might be presented as a figure.
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Reviewer #3 (Public Review):
In this manuscript, the authors demonstrated the significance of the TRPγ channel in regulating internal TAG levels. They found high TAG levels in TRPγ mutant, which was ascribed to a deficit in the lipolysis process due to the downregulation of brummer (bmm). It was notable that the expression of TRPγ in DH44+ PI neurons, but not dILP2+ neurons, in the brain restored the internal TAG levels and that the knockdown of TRPγ in DH44+ PI neurons resulted in an increase in TAG levels. These results suggested a non-cell autonomous effect of Dh44+PI neurons. Additionally, the expression of the TRPγ channel in Dh44 R2-expressing cells restored the internal TAG levels. The authors, however, did not provide an explanation of how TRPγ might function in both presynaptic and postsynaptic cells in the non-cell autonomous manner to regulate the TAG storage. The authors further determined the effect of TRPγ mutation on the size of lipid droplets (LD) and the lifespan and found that TRPγ mutation caused an increase in the size of LD and a decrease in the lifespan, which were reverted by feeding lipase and metformin. These were creative endeavors, I thought. The finding that DH44+ PI neurons have non-cell autonomous functions in regulating bodily metabolism (mainly sugar/lipid) in addition to directing sugar nutrient sensing and consumption is likely correct, but the paper has many loose ends. I would like to see a revision that includes more experiments to tighten up the findings and appropriate interpretations of the results.
(1) The authors need to provide interpretations or speculations as to how DH44+ PI neurons have non-cell autonomous functions in regulating the internal TAG stores, and how both presynaptic DH44 neurons and postsynaptic DH44 R2 neurons require TRPγ for lipid homeostasis.
(2) The expression of TRPγ solely in DH44 R2 neurons of TRPγ mutant flies restored the TAG phenotype, suggesting an important function mediated by TRPγ in DH44 R2 neurons. However, the authors did not document the endogenous expression of TRPγ in the DH44R2+ gut cells. This needs to be shown.
(3) While Dh44 mutant flies displayed normal internal TAG levels, Dh44R2 mutant flies exhibited elevated TAG levels (Figure 7A). This suggested that the lipolysis phenotype could be facilitated by a neuropeptide other than Dh44. Alternatively, a Dh44 neuropeptide-independent pathway could mediate the lipolysis. In either case, an additional result is needed to substantiate either one of the hypotheses.
(4) While the authors observed an increased area of fat body lipid droplets (LD) in Dh44 mutant flies (Figure 7F), they did not specify the particular region of the fat body chosen for measuring the LD area.
(5) The LD area only accounts for TAG levels in the fat body, whereas TAG can be found in many other body parts, including the R2 area as demonstrated in Figure 5A-D using Nile red staining. As such, measuring the total internal TAG levels would provide a more accurate representation of TAG levels than the average fat body LD area.
(6) In Figure 5F-I, the authors should perform the similar experiment with Dh44, Dh44R1, and Dh44R2 mutant flies.
(7) The representative image in Figure 6B does not correspond to the GFP quantification results shown in Figure 6C. In trpr1;bmm::GFP flies, the GFP signal appears stronger in starved conditions than in satiated conditions.
(8) In Figure 6H-I, fat body-specific expression of bmm reversed the increased LD area in TRPγ mutants. The authors also showed that Dh44+PI neuron-specific expression of bmm yielded a similar result. The authors need to provide an interpretation as to how bmm acts in the fat body or DH44 neurons to regulate this.
(9) The authors should explain why the DH44 R1 mutant did not represent similar results as the wild type.
(10) It would be good to have a schematic that represents the working model proposed in this manuscript.
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Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
The main goal of the authors was to study the testis-specific role of the protein FBXO24 in the formation and function of the ribonucleoprotein granules (membraneless electron-dense structures rich in RNAs and proteins).
We appreciate the summary comment of reviewer #1.
Strengths:
The wide variety of methods used to support their conclusions (including transgenic models)
We appreciate the positive comment of reviewer #1.
Weaknesses:
The lack of specific antibodies against FBXO24. Some of the experiments showing a specific phenotype are descriptive and lack of logical explanation about the possible mechanism (i.e. AR or the tail structure).
Because we could not obtain specific antibodies against FBXO24, we generated Fbxo24-FLAG transgenic mice, which can be used to show the interaction between FBXO24 and IPO5. For the mechanism of impaired acrosome reaction, we added some results and discussion as written in the response to the question (1) of reviewer #1 (public review). For the mechanism of abnormal flagellar structure, we added new results and fixed the manuscript as written in the response to the major comments of reviewer #3 (recommendations for the authors).
Questions:
The paper is excellent and employs a wide variety of methods to substantiate the conclusions. I have very few questions to ask:
(1) KO mice cannot undergo acrosome reaction (AR) even spontaneously. How do you account for this, given that no visible defects were observed in the acrosome?
One possibility is that Fbxo24 KO spermatozoa cannot undergo capacitation; however, it is difficult to analyze the capacitation status such as tyrosine phosphorylation because most Fbxo24 KO spermatozoa are not alive (Figure S3A). Other possibility is that AR-related proteins are affected in Fbxo24 KO spermatozoa. Therefore, we analyzed the amounts of AR-related proteins with mass spectrometry (Figure S3C). Although previous studies indicate that the assembly of the SNARE complex is a key event prior to AR [Hutt et al., 2005 (PMID: 15774481); Katafuchi et al., 2000 (PMID: 11066067); Schulz et al., 1997 (PMID: 9356173); Tomes et al., 2002 (PMID: 11884041)], no clear differences were detected for SNARE proteins (Figure S3C and D). PLCD4 that is important for AR [Fukami et al., 2001 (PMID: 11340203)) was also detected in Fbxo24 KO spermatozoa (Figure S3C). Although we could not find differences in the amounts of AR-related proteins, it is still possible that FER1L5, another AR-related protein [Morohoshi et al., 2023 (PMID: 36696506)] not detected in the mass spectrometry analyses, or AR-related proteins not yet identified are affected in Fbxo24 KO spermatozoa. We added these results and discussion (line 160-166 and 305-312).
(2) KO sperm are unable to migrate in the female tract, and, more intriguingly, they do not pass through the utero-tubal junction (UTJ). The levels of ADAM3 are normal, suggesting that the phenotype is influenced by other factors. The authors should investigate the levels of Ly6K since mice also exhibit the same phenotype but with normal levels of ADAM3.
We detected LY6K in Fbxo24 KO spermatozoa with immunoblotting, but no difference was found.
We added the results (Figure S3E and line 172–175).
(3) In Figure 4A, the authors assert that "RBGS Tg mice revealed that mitochondria were abnormally segmented in Fbxo24 KO spermatozoa." I am unable to discern this from the picture shown in that panel. Could you please provide a more detailed explanation or display the information more explicitly?
We are sorry for the ambiguous explanation on the morphology of sperm mitochondria sheath. Fbxo24 KO cauda epidydimal spermatozoa shows disorganized mitochondria sheath rather than “segmented”. We fixed the sentence (line 190-192) and added white arrowheads that indicate the disorganized regions (Figure 4A).
Reviewer #2 (Public Review):
Summary:
The manuscript by Kaneda et al "FBXO24 ensures male fertility by preventing abnormal accumulation of membraneless granules in sperm flagella" is a significant paper on the role of FBXO24 in murine male germ cell development and sperm ultrastructure and function. The body of experimental evidence that the authors present is extraordinarily strong in both breadth and depth. The authors investigate the protein's functions in male germ cells and sperm using a wide variety of approaches but focusing predominantly on their novel mouse model featuring deletion of the Fbxo24 gene and its product. Using this mouse, and a cross of it with another model that expresses reporters in the head and midpiece, they logically build from one experiment to the next. Together, their data show that this protein is involved in the regulation of membraneless electron-dense structures; loss of FBXO24 led to an accumulation of these materials and defects in the sperm flagellum and fertilizing ability. Interestingly, the authors found that several of the best-known components of electron-dense ribonucleoprotein granules that are found in the intermitochondrial cement and chromatoid body were not disrupted in the Fbxo24 knockout, suggesting that the electron-dense material and these structures are not all the same, and the biology is more complicated than some might have thought. They found evidence for the most changes in IPO5 and KPNB1, and biochemical evidence that FBXO24 and IPO5 could interact.
We appreciate the summary comment of reviewer #2.
Strengths:
The authors are to be commended for the thoroughness of their experimental approaches and the extent to which they investigated impacts on sperm function and potential biochemical mechanisms. Very briefly, they start by showing that the Fbxo24 message is present in spermatids and that the protein can interact with SKP1, in a way that is dependent on its F-box domain. This points toward a potential function in protein degradation. To test this, they next made the knockout mouse, validated it, and found the males to be sterile, although capable of plugging a female. Looking at the sperm, they identified a number of ultrastructural and morphological abnormalities, which they looked at in high resolution using TEM. They also cross their model with RBGS mice so that they have reporters in both the acrosome and mitochondria. The authors test a variety of sperm functions, including motility parameters, ability to fertilize by IVF, cumulus-free IVF, zona-free-IVF, and ICSI. They found that ICSI could rescue the knockout but not other assisted reproductive technologies. Defects in male fertility likely resulted from motility disruption and failure to get through the utero-tubal junction but defects in acrosome exocytosis also were noted. The authors performed thorough investigations including both targeted and unbiased approaches such as mass spectrometry. These enabled them to show that although the loss of the FBXO24 protein led to more RNA and elevated levels of some proteins, it did not change others that were previously identified in the electron-dense RNP material.
The manuscript will be highly significant in the field because the exact functions of the electron-dense RNP materials have remained somewhat elusive for decades. Much progress has been made in the past 15 years but this work shows that the situation is more complex than previously recognized. The results show critical impacts of protein degradation in the differentiation process that enables sperm to change from non-descript round cells into highly polarized and compartmentalized mature sperm, with an equally highly compartmentalized flagellum. This manuscript also sets a high bar for the field in terms of how thorough it is, which reveals wide-ranging impacts on processes such as mitochondrial compaction and arrangement in the midpiece, the correct building of the major cytoskeletal elements in the flagellum, etc.
We appreciate the positive comment of reviewer #2.
Weaknesses:
There are no real weaknesses in the manuscript that result from anything in the control of the authors. They attempted to rescue the knockout by expressing a FLAG-tagged Fbxo24 transgene, but that did not rescue the phenotype, either because of inappropriate levels/timing/location of expression, or because of interference by the tag. They also could not make anti-FBXO24 that worked for coimmunoprecipitation experiments, so relied on the FLAG epitope, an approach that successfully showed co-IP with IPO5 and SKP1.
We could not rescue the phenotype with Fbxo24-FLAG transgene, but different Fbxo24 mutant mice show the same phenotypes (Figure S6G). Further, another group showed that Fbxo24 KO mice exhibited abnormal mitochondrial coiling [Li et al., 2024 (PMID: 38470475)], confirming that
FBXO24 is involved in the mitochondrial sheath formation.
Reviewer #3 (Public Review):
Summary:
In this manuscript, the authors found that FBXO24, a testis-enriched F-box protein, is indispensable for male fertility. Fbxo24 KO mice exhibited malformed sperm flagellar and compromised sperm motility.
We appreciate the summary comment of reviewer #3.
Strengths:
The phenotype of Fbxo24 KO spermatozoa was well analyzed.
We appreciate the positive comment of reviewer #3.
Weaknesses:
The authors observed numerous membraneless electron-dense granules in the Fbxo24 KO spermatozoa. They also showed abnormal accumulation of two importins, IPO5 and KPNB1, in the Fbxo24 KO spermatozoa. However, the data presented in the manuscript do not support the conclusion that FBXO24 ensures male fertility by preventing the abnormal accumulation of membraneless granules in sperm flagella, as indicated in the manuscript title.
Fbxo24 KO mice showed abnormal accumulation of membraneless granules in sperm flagella and male infertility, suggesting that FBXO24 is involved in these processes, but there are no results that show the direct relationship as reviewer #3 mentioned. Therefore, we fixed the title.
Recommendations For The Authors:
Reviewer #2 (Recommendations For The Authors):
On page 4, lines 152-154, the authors introduce the RBGS mouse model and use it in their experiments.
However, they left out an obvious but helpful sentence that tells the reader that they crossed the Fbxo24-null mouse with the RBGS. As one continues reading it is clear, but best to avoid even slight confusion.
We revised the explanation in the result section (line 150-153).
Reviewer #3 (Recommendations For The Authors):
In this manuscript, the authors found that FBXO24, a testis-enriched F-box protein, is indispensable for male fertility. Fbxo24 KO mice exhibited malformed sperm flagellar and compromised sperm motility. The phenotype of Fbxo24 KO spermatozoa was well analyzed.
The authors observed numerous membraneless electron-dense granules in the Fbxo24 KO spermatozoa. They also showed abnormal accumulation of two importins, IPO5 and KPNB1, in the Fbxo24 KO spermatozoa. However, the data presented in the manuscript do not support the conclusion that FBXO24 ensures male fertility by preventing the abnormal accumulation of membraneless granules in sperm flagella, as indicated in the manuscript title.
Fbxo24 KO mice showed abnormal accumulation of membraneless granules in sperm flagella and male infertility, suggesting that FBXO24 is involved in these processes, but there are no results that show the direct relationship as reviewer #3 mentioned. Therefore, we fixed the title.
Major comments:
In the title, abstract, introduction, and some sections such as lines 275-276, the authors conclude that FBXO24 prevents the accumulation of importins and RNP granules during spermiogenesis. However, the provided data do not substantiate this claim. To provide conclusive evidence to support the current title, the authors need to present evidence supporting: 1) direct degradation of IPO5 and KPNB1 by FBXO24; 2) the direct requirement of IPO5 for the formation of the membraneless granules, and 3) infertility resulting from the presence of membraneless granules, rather than other issues such as abnormal ODF and AX.
(1) direct degradation of IPO5 and KPNB1 by FBXO24.
To examine if IPO5 can be degraded by FBXO24, we performed a ubiquitination assay using HEK293T cells. Ubiquitination of IPO5 was upregulated in the presence of WT FBXO24 but not with the mutant ΔF-box FBXO24, suggesting that IPO5 can be ubiquitinated by FBXO24. We did not examine the ubiquitination of KPNB1 because we failed to construct a plasmid vector expressing mouse KPNB1. We think that KPNB1 is not the substrate because we did not detect the interaction between FBXO24 and KPNB1 (Figure 5E). We added the results of the ubiquitination assay (Figure
5F and line 261-265) and mentioned it in the abstract (line 35).
(2) the direct requirement of IPO5 for the formation of the membraneless granules.
(3) infertility resulting from the presence of membraneless granules, rather than other issues such as abnormal ODF and AX.
We revealed that IPO5 aggregate under stress condition in COS7 cells (Figure 6C and D); however, we did not examine whether IPO5 is required for the formation of the membraneless granules. We consider that protein degradation systems such as PROTAC or Trim-Away to knockdown IPO5 at the protein level in Fbxo24 KO mice could be a good way to see if the membraneless granules are diminished and male fertility is rescued. However, it takes time to apply the degradation systems in vivo. Therefore, we would like to leave this rescue experiment for future studies. We fixed the title and abstract (line 37-38), and removed the last sentence of the introduction.
Also, the other group reported the analyses of Fbxo24 KO mice [Li et al., 2024 (PMID: 38470475)] right after we submitted our manuscript to the eLife. They reported not only disorganized flagellar structures but also abnormal head morphology, which may lead to male infertility. The differences from our study may be due to different mouse genetic backgrounds. We mentioned it in the discussion section (line 348-353).
Minor comments:
(1) The authors claimed a significant increase in the total amount of RNAs in Fbxo24 KO spermatozoa (lines 259-261), suggesting that the ...contain RNAs. More direct evidence supporting this claim should be provided.
We show that the amounts of IPO5 and KBNB1 increased in Fbxo24 KO spermatozoa (Figure 5A and B), both of which could be incorporated into RNP granules in COS7 cells (Figure 6C and D), supporting the idea that membraneless electron-dense structures may be RNP granules. However, because we did not show direct evidence that electron-dense structures contain RNAs, we removed the sentences (line 259-261 of the 1st submission manuscript).
(2) The author should provide an explanation for the absence of a FLAG band in the input Tg in Figure 5D and the larger size of the IPO5 band in the FLAG-IP group compared to the input. Similar observations are also noted in Figure 5E.
The FLAG band is weak because the protein amount is low. When we increase the contrast, we can see the FLAG band. We added an image with high contrast (Figure 5D). Sometimes, proteins run differently with SDS-PAGE after immunoprecipitation, likely due to varying protein composition in the sample. We explained it in the figure legend (line 868-869).
(3) In Line 526, clarify the procedure for sperm purification, and determine the potential for contamination from somatic cells.
We did not perform sperm purification, but when we observed spermatozoa obtained from cauda epididymis, we rarely observed either somatic cells or immature spermatogenic cells. We added pictures in Figure S7. Further, we added detailed explanation about how to collect spermatozoa from the epididymis (line 549-550).
(4) Define the Y-axis in Figure 2E, F, and G.
We have revised the figures.
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Reply to the reviewers
We thank the reviewers for their positive and constructive criticism. We answer their points one by one below.
Reviewer #1
1.) In the baf-1 G12T mutants the authors find reduced levels of lamin in hypodermal nuclei. It would be good to also examine the dynamics of lamin in the second tissue that was subjected to DamID (intestinal cells).
We provide a complete analysis of GFP::LMN-1 and EMR-1::mCh in control and baf-1(G12T) day 1 adults in intestine and hypodermis and at 20°C and 25°C. These data demonstrate that GFP::LMN-1 expression is reduced in baf-1(G12T) mutants in both tissue and at both temperatures. In contrast, for EMR-1::mCh a significant reduction was only observed in hypodermal nuclei at 20°C.
The effects on GFP::LMN-1 and EMR-1::mCh in the hypodermis 20°C were reported in Figure 2E-F in the original version of our manuscript. We have moved these data to the new Supplementary Figure S5 and represent instead the data obtained for hypodermis at 25°C in Figure 2E-F for consistency with the data represented in Figure 2A-D. Data on intestine for both markers and both temperatures are also included in the new Supplementary Figure S5.
We have modified the text as follows:
“To test the impact of baf-1(G12T) on LMN-1, EMR-1, and BAF-1 localization in vivo, we quantified these factors at the NE of hypodermal and intestinal cells. We observed a significantly lower median GFP::LMN-1 signal at the NE in baf-1(G12T) mutants in both tissues at 20°C and 25°C (Figure ____2E; Supplementary Figure S____5A-C). In contrast, accumulation of EMR-1 at the NE was unaffected by the baf-1(G12T) mutation in both tissues at 25°C and reduced in the hypodermis at 20°C (Figure ____2F; Supplementary Figure S____5D-F). In human NGPS cells, emerin was observed to be delocalized to the ER (Janssen et al., 2022; Puente et al., 2011), but we detected no increase in cytoplasmic EMR-1::mCh signal in the mutant, indicating that this NGPS phenotype is not present in the C. elegans model. In agreement with these microscopy data, analysis of whole-worm mRNA levels by quantitative RT-PCR also revealed a significant reduction in lmn-1 expression whereas emr-1 was unaffected (Supplementary Figure S4E-F).”
2.) The authors make a statement that EMR-1 expression was reduced in the baf-1 G12T mutant, but do not comment on LMN-1 expression. Can a statement on this be made by RT PCR?
Our gene expression analysis by RAPID determined a significant reduction in emr-1 expression in the intestine of baf-1(G12T) mutants, using a fold change of 2 as threshold. In contrast, expression of emr-1 in hypodermis as well as baf-1 and lmn-1 expression in both tissues were not significantly different between wild type and baf-1(G12T) mutants in our RAPID data.
We performed qRT-PCR on bulk mRNA to compare the expression of baf-1, emr-1 and lmn-1 in control versus baf-1(G12T) mutants. No differences were detected for baf-1 and emr-1 (new Supplementary Figure S4E-F). Considering that the qRT-PCR is on bulk mRNA, the emr-1 result is compatible with the RAPID data that suggest deregulation of emr-1 only in intestine and unaffected expression in the hypodermis. For baf-1 there is agreement between qRT-PCR and RAPID data from both tissues (no difference in the mutant). For lmn-1, the qRT-PCR analysis suggests a modest reduction (23%; not reaching the threshold applied in the RAPID analysis) in baf-1(G12T) mutants, which is concordant with the reduction observed in GFP::LMN-1 intensity in hypodermis and intestine by confocal microscopy (e.g. 14% reduction in median GFP::LMN-1 intensity in hypodermis at 25C; Figure 2E).
The discordance between RAPID and live imaging for emr-1/EMR-1::mCh (a reduction in the intestine or the hypodermis according to RAPID or live imaging, respectively) is not surprising. Although mRNA and protein levels in general correlate well, often, variation in transcription can only explain We have added these two sentences to the manuscript:
“In agreement with these microscopy data, analysis of whole-worm mRNA levels by quantitative RT-PCR also revealed a significant reduction in lmn-1 expression whereas emr-1 was unaffected (Supplementary Figure S4E-F).”
“As described above, the amount of endogenously tagged EMR-1::mCh at the NE of intestinal cells was normal in baf-1(G12T) mutants (Supplementary Figure S5F), suggesting a cellular capacity to buffer the downregulation of emr-1 transcription (Vogel & Marcotte, 2012).”
3.) The authors find few alterations in gene regulation of the loci which have different occupancy WT BAF-1 versus BAF-1 G12T. It was surprising to see the DamID and RNA polymerase DamID experiments be done with worms grown at 20°C, because the more penetrant phenotypes at the organismal level were observed at 25°C. Could this be the reason for the little change of chromatin occupancy of BAF-1 and BAF-1 G12T or few changes in gene expression? Would it make sense to examine the expression of some selected BAF-1 bound loci by single molecule Fish at 25°C and compare expression wt versus baf-1 G12T?
We performed the DamID experiments at 20°C to avoid potential artifacts and/or toxicity by higher expression levels of Dam fusion proteins (Greil, Moorman, & van Steensel, 2006; Schuster et al., 2010). We note that altered UV and tert-butyl hydroperoxide was observed at 20°C, indicating that the baf-1(G12T) allele affects physiology at several temperatures. The original version of our manuscript described the expression of fluorescently tagged LMN-1 and EMR-1 in the hypodermis at 20°C (Figure 2E-F). As described above, in the revised version, we report the expression in the intestine at 20°C and in both tissues at 25°C. For GFP::LMN-1, a similar reduction in the baf-1(G12T) mutant was observed at the two temperatures in both tissues, whereas for EMR-1::mCh a reduction was only seen in the hypodermis at 20°C. Taken together, we conclude that 20°C is a suitable temperature for the DamID experiments.
We appreciate the suggestion to study expression of genes bound by BAF-1 by smFISH. However, we anticipate that because the hypodermis is composed mostly of large syncytia covering the round body of the animal, smFISH would be difficult to quantify. Regarding loci with different occupancy of WT BAF-1 versus BAF-1(G12T), the emr-1 locus was bound in the intestine by Dam::BAF-1 but not by Dam::BAF-1(G12T) (Figure 6B). As mentioned above, we observed that emr-1 expression was reduced in intestine of baf-1(G12T) mutants, suggesting that BAF-1 binding has a positive effect of transcription of this locus.
4.) The finding that BAF-1 nuclear envelope localization remains unchanged in the mutant stems from detection of the inserted GFP epitope. Given that the tag has an influence on the BAF-1 G12 12T mutant viability, this statement should be phrased with more care. The tag could influence the turnover of the protein for example. Maybe Western blots comparing the signal of WT BAF-1 worms and BAF-1 G12T mutant worms would be instructive to compare the levels of the protein (at 20oC and at 25oC, day 1 adults and day 8 adults).
We performed Western blot experiments to address this. As controls, we included strains expressing equal amounts of GFP::BAF-1 and GFP::BAF-1(G12T) strains (Figure 3E and Supplementary Figure 7 in original manuscript reported equal expression of the two proteins). Surprisingly, the polyclonal anti-BAF-1 serum raised against recombinant, full-length wild type BAF-1 (Gorjanacz et al., 2007) has significantly lower affinity for mutant GFP::BAF-1(G12T) than for GFP::BAF-1, which precludes the evaluation of untagged proteins:
Figure 1. [png file provided to reviewers - not possible to include here for technical reasons] Western blot analyses with anti-BAF-1 serum (Gorjanacz et al, 2007). (A) Embryonic extracts. A band of the expected size is observed in wildtype embryos (*), but not in baf-1(G12T) embryos. (B) Extracts from young adults. A faint band of the expected size is observed in wildtype embryos (* in lane 1; longer exposure is shown below), whereas a more prominent band is present corresponding to endogenously tagged GFP::BAF-1 (** in lane 2). The intensity of the potential GFP::BAF-1(G12T) is reduced by >80% (lane 4; >90% reduction was observed in a second experiment).
We point out in the revised manuscript that the conclusion on equal BAF-1 and BAF-1(G12T) expression was based on endogenously tagged proteins: “Quantifying the intensity at the NE or in the nucleoplasm of hypodermal cells did not demonstrate any difference between endogenously GFP-tagged wild-type and mutant BAF-1 (Figure 3E). A small reduction in cytoplasmic signal was observed for BAF-1(G12T), however, no difference was detected in the ratio between nucleoplasmic/cytoplasmic signal (Figure 3E). Quantitative RT-PCR analysis of whole-worm RNA samples also indicated that baf-1 and baf-1(G12T) are expressed at identical levels (Supplementary Figure S4E-F).”
5.) Line 105: typo: remove "s"
Corrected.
6.) Line 154: A conclusion is missing for the fog-2 experiment.
We have modified the text as follows: “To test this possibility, we incubated baf-1(G12T) males with fog-2(q71) feminized worms that only produce oocytes and counted daily offspring. At 25°C, the fog-2(q71) allele prevents spermatogenesis specifically in XX hermaphrodites whereas X0 males are unaffected (Schedl & Kimble, 1988). We observed a reduction in brood size of approximately one third when sperm came from baf-1(G12T) males (Supplementary Figure S2B, C). Thus, we concluded that the baf-1(G12T) mutation has a negative impact on spermatogenesis. The male/female ratio in the progeny was ~1, suggesting that meiotic segregation of chromosomes was normal in baf-1(G12T) males.”
7). Would it make sense to discuss a possible influence of altered lamin binding to the nuclear envelope in the mutant in the context of the gene expression results?
We agree that this point is relevant, and we have added the following text to the Discussion: “At current, we can only speculate about how the NGPS mutation might affect gene expression. Proteomics analyses indicate that BAF interacts with several histones and transcription factors (Montes de Oca, Shoemaker, Gucek, Cole, & Wilson, 2009), and the differences between BAF-1 and BAF-1(G12T)’s chromatin binding profiles reported here might be accompanied by changes in the association of chromatin factors at the deregulated loci. A particularly interesting candidate is GCL-1/germ cell-less 1, a repressive factor involved in spermatogenesis (Holaska, Lee, Kowalski, & Wilson, 2003). Moreover, it is plausible that the diminished recruitment of LMN-1 to the NE in baf-1(G12T) mutants modifies its interaction with the genome and with chromatin factors.”
8). In a nutshell, the authors have established a convincing accessible model system for studying aging, ready for consecutive testing interventions to reduce the pace of premature aging.
We appreciate and share the opinion of the reviewer.
Reviewer #2
1). The value of this work is two-fold: First, it is a very robust characterization of NGPS worms. Second, this will be a very useful model for the study of NGPS. Overall, the study is well-designed, technically strong, and the results are carefully and thoughtfully interpreted, which is nicely exemplified by the discussion of the relatively small number of genes which are differentially bound by BAF1 and are also differentially expressed and the authors do a good job of not overinterpreting the data, but simply state them. The results are convincing and informative.
We thank the reviewer for her/his positive evaluation.
My only minor point that may make this paper marginally better is that it would be nice to have a paragraph in the Discussing elaborating on the potential and the limitations of using the worm model to understand human NGPS, for example, humans have multiple lamin proteins etc.
We agree with the reviewer and have added the following text to the Discussion: “We note that the simplicity of invertebrates also implies certain limitations. For instance, while both human and C. elegans genomes contain a single BAF gene, humans, but not C. elegans, express multiple lamin isoforms in tissue-specific ratios that regulate chromatin organization and nuclear mechanics (Swift et al., 2013). Thus, C. elegans is not suitable to explore potential differences in how wild type and NGPS BAF interacts differently with the various lamin isoforms.”
Reviewer #3
1). Overall, this manuscript strongly supports the major conclusion that this C. elegans line is a powerful model for human NGPS that complements a previously reported Drosophila model. Equally importantly, from the viewpoint of fundamental discovery, this manuscript also reports major advances in understanding how BAF influences gene expression at the molecular level.
We thank the reviewer for her/his positive evaluation.
2). DamID-Baf-1 access to chromatin was unaffected by the G12T mutation (Fig. S7), but they successfully identified subsets of genes 'occupied' by baf-1 in specific cell types, some of which were significantly affected in opposite ways by the NGPS mutation (Fig. 4, Fig. 5). However, these important new results are described too briefly, and discussion is inadequate. E.g., in hypodermal cells, the baf-1 G12T mutation dysregulated genes encoding proteins in five categories (ribosomal, proton transport, cuticle components, cell surface, lysine acetylation), by downregulating genes in three categories (ribosomal, proton transport, histone acetylation) and upregulating three other categories (cuticle components, cell surface, apical region). In intestinal cells, the mutation dysregulated genes in 8 categories (ribosomal, response to X-ray, proton transport, proteasome binding, mitochondrial protein import, endopeptidase activity, carboxy-lyase activity, ATP generation), by downregulating genes in 5 categories (ribosomal, proton transport, peptidase activity, NAD binding, metal cluster binding) and upregulating 3 categories (ribosomal, response to external stimulation, histone acetylation). Opposite results for "ribosomal genes" is confusing. Examples of genes in each affected category are shown in Fig. 6. To fully interpret this data, and address apparently-conflicting results, further analysis is needed to determine if any affected groups of genes have shared regulators. For example, Fig 5E shows "ribosomal protein genes" are both up- and down-regulated by the mutation. The authors should consider: (a) WHICH ribosomal genes are in each category, and (b) does either group of genes have known regulators that might be differentially affected by the baf-1 mutation? Similar consideration of other sets of differentially-affected genes might provide novel insight into specific chromatin-regulatory proteins (e.g., potential baf-1 partners; see next paragraph) affected by the NGPS mutation.
At first it may seem confusing that some ribosomal genes are downregulated while others are upregulated. However, the baf-1(G12T) mutant represents a disease situation and not a process of natural selection where one might expect “meaningful” groups of up- and down-regulated genes. We have looked closer at the individual deregulated ribosomal genes and found genes encoding structural components of large ribosomal subunits that are either upregulated (rpl-10, rpl-29, rpl-36) or downregulated (rpl-1, rpl-3, rpl-30) in the intestine. Although these opposite behaviors might seem confusing, we propose that they reflect deregulation of ribosome biosynthesis, which is in concordance with the observations in NGPS fibroblasts (Breusegem et al., 2022). We agree that it will be important to investigate how the NGPS mutation induces these oppositely directed effects on gene expression. We found a significant higher association of the 13 deregulated ribosomal genes to BAF-1(G12) than to BAF-1 in the intestine, but we believe it goes beyond the scope of this manuscript to focus on the underlying mechanisms.
3). The current manuscript is too strictly focused on establishing C. elegans as a model for NGPS, and neglects the novel discoveries. The authors did not consider or discuss HOW a baf-1 mutation might cause such complex gene expression outcomes- given that baf-1 binds dsDNA nonspecifically. One plausible molecular explanation is that the NGPS mutation might affect baf-1 interactions with: (a) transcription factors (Requiem, RBBP4, DDB1) or chromatin-regulators (PARP1; UV-regulated interactions with DDB2 and CUL4A) identified as BAF-associated in a proteomic study (Montes de Oca et al., 2009), or (b) histone modifiers such as SET/I2PP2A (blocks H3 dephosphorylation) or H3K9 methyltransferase 'G9a' (Montes de Oca et al., 2011), or (c) other regulators that control affected genes identified in this manuscript.
We agree that this point is very relevant, but at this point we do not have experimental support for any of these possibilities. As indicated in the response to Reviewer #2, we have added the following text to the Discussion: “At current, we can only speculate about how the NGPS mutation might affect gene expression. Proteomics analyses indicate that BAF interacts with several histones and transcription factors (Montes de Oca et al., 2009), and the differences between BAF-1 and BAF-1(G12T)’s chromatin binding profiles reported here might be accompanied by changes in the association of chromatin factors at the deregulated loci. A particularly interesting candidate is GCL-1/germ cell-less 1, a repressive factor involved in spermatogenesis (Holaska et al., 2003). Moreover, it is plausible that the diminished recruitment of LMN-1 to the NE in baf-1(G12T) mutants modifies its interaction with the genome and with chromatin factors.”
4). Figures 1, 2, 4, 5: the graphs in Fig 1A,B,D-F and Fig 2B,D and the colorscales in Fig 4F and Fig 5E are uninterpretable when printed in black-and-white. Please fix Figs 1 and 2 using black/light-gray/white/stippled for bar graphs, and black/light-gray/solid/dotted/dashed for line graphs. Fig 2B can be fixed by direct-labeling of class numbers within each bar (instead of 'color-coding' separately).
We thank the reviewer for this suggestion. We have modified the figures to enable better visualization when printed in BW.
5). Revise abstract lines 40-42 ("suggesting a direct relationship between BAF-1 binding [to what?] and gene expression") to reflect the deeper analysis.
We have rephrased this sentence, so it now reads: “Most genes deregulated by the baf-1(G12T) mutation were characterized by a change in BAF-1 association, suggesting a direct relation between association of a gene to BAF-1 and its expression.” However, we prefer to not extend into speculations in the abstract because of lack of experimental evidence.
6). Lines 132-155 (Figure 1): The impact on sperm production suggests the NGPS mutation might affect association with Germ cell-less (GCL), a transcription repressor that competes with BAF for binding to emerin in mammalian cells (Holaska et al., 2003 JBC).
This is indeed an interesting possibility and we have incorporated it into to Discussion (see answer to point 3 above).
7). Lines 151-154: Did not understand the fog-2 'feminized worm' experiments. Please briefly explain for non-worm experts.
Please see our response to Reviewer #1’s point 6.
8). Line 190: Clarify that nuclear shapes were categorized manually by single-blind observer.
We have amended the text: “Nuclei were manually classified by single-blind observer based on their morphology as previously described (Perez-Jimenez, Rodriguez-Palero, Rodenas, Askjaer, & Munoz, 2014), except that we introduced a fourth class to describe the most irregular nuclei (see Materials and Methods).”
9). Line 237-252: Abnormal chromosome segregation and postmitotic nuclear assembly in all gfp::baf-1(G12T) embryos is fully consistent (not 'presumably causative'; line 251) with the embryonic loss-of-function phenotype for baf-1 (Margalit et al., 2005, PNAS) and is consistent with mutational disruption of binding to lamin (Liu J et al., 2000, MBC) and/or LEM-domain proteins (Liu J, Lee KK et al., 2003, PNAS).
We thank the reviewer for pointing this out. We have added the following sentence: “These phenotypes are consistent with the effects of embryonic depletion of BAF-1 or LMN-1 (Liu et al., 2000; Margalit, Segura-Totten, Gruenbaum, & Wilson, 2005).”
10). Lines 530-533: Baf-1 localization (mobility) in intestinal cells is known to change profoundly in response to heat shock, caloric restriction or food deprivation (Bar et al., 2014, MBC). It would be worthwhile testing, in future, whether the NGPS mutation affects baf-1 localization in response to these stresses.
We appreciate this suggestion, and we agree with the reviewer that it would be important to test this in future studies.
Other changes:
Missing column in Table S3 added.
Mistake if column heading in Table S4 corrected.
Breusegem, S. Y., Houghton, J., Romero-Bueno, R., Fragoso-Luna, A., Kentistou, K. A., Ong, K. K., . . . Larrieu, D. (2022). A multiparametric anti-aging CRISPR screen uncovers a role for BAF in protein translation. bioRxiv. doi:10.1101/2022.10.07.509469
Gorjanacz, M., Klerkx, E. P., Galy, V., Santarella, R., Lopez-Iglesias, C., Askjaer, P., & Mattaj, I. W. (2007). Caenorhabditis elegans BAF-1 and its kinase VRK-1 participate directly in post-mitotic nuclear envelope assembly. Embo J, 26(1), 132-143. doi:10.1038/sj.emboj.7601470
Greil, F., Moorman, C., & van Steensel, B. (2006). DamID: mapping of in vivo protein-genome interactions using tethered DNA adenine methyltransferase. Methods Enzymol, 410, 342-359. doi:10.1016/S0076-6879(06)10016-6
Holaska, J. M., Lee, K. K., Kowalski, A. K., & Wilson, K. L. (2003). Transcriptional repressor germ cell-less (GCL) and barrier to autointegration factor (BAF) compete for binding to emerin in vitro. J Biol Chem, 278(9), 6969-6975.
Janssen, A., Marcelot, A., Breusegem, S., Legrand, P., Zinn-Justin, S., & Larrieu, D. (2022). The BAF A12T mutation disrupts lamin A/C interaction, impairing robust repair of nuclear envelope ruptures in Nestor-Guillermo progeria syndrome cells. Nucleic Acids Res. doi:10.1093/nar/gkac726
Liu, J., Rolef Ben-Shahar, T., Riemer, D., Treinin, M., Spann, P., Weber, K., . . . Gruenbaum, Y. (2000). Essential roles for Caenorhabditis elegans lamin gene in nuclear organization, cell cycle progression, and spatial organization of nuclear pore complexes. Mol Biol Cell, 11(11), 3937-3947.
Margalit, A., Segura-Totten, M., Gruenbaum, Y., & Wilson, K. L. (2005). Barrier-to-autointegration factor is required to segregate and enclose chromosomes within the nuclear envelope and assemble the nuclear lamina. Proc Natl Acad Sci U S A, 102(9), 3290-3295. doi:10.1073/pnas.0408364102
Montes de Oca, R., Shoemaker, C. J., Gucek, M., Cole, R. N., & Wilson, K. L. (2009). Barrier-to-autointegration factor proteome reveals chromatin-regulatory partners. PLoS ONE, 4(9), e7050. doi:10.1371/journal.pone.0007050
Perez-Jimenez, M. M., Rodriguez-Palero, M. J., Rodenas, E., Askjaer, P., & Munoz, M. J. (2014). Age-dependent changes of nuclear morphology are uncoupled from longevity in Caenorhabditis elegans IGF/insulin receptor daf-2 mutants. Biogerontology, 15(3), 279-288. doi:10.1007/s10522-014-9497-0
Puente, X. S., Quesada, V., Osorio, F. G., Cabanillas, R., Cadinanos, J., Fraile, J. M., . . . Lopez-Otin, C. (2011). Exome sequencing and functional analysis identifies BANF1 mutation as the cause of a hereditary progeroid syndrome. Am J Hum Genet, 88(5), 650-656. doi:10.1016/j.ajhg.2011.04.010
Schedl, T., & Kimble, J. (1988). fog-2, a germ-line-specific sex determination gene required for hermaphrodite spermatogenesis in Caenorhabditis elegans. Genetics, 119(1), 43-61. doi:10.1093/genetics/119.1.43
Schuster, E., McElwee, J. J., Tullet, J. M., Doonan, R., Matthijssens, F., Reece-Hoyes, J. S., . . . Gems, D. (2010). DamID in C. elegans reveals longevity-associated targets of DAF-16/FoxO. Mol Syst Biol, 6, 399. doi:10.1038/msb.2010.54
Swift, J., Ivanovska, I. L., Buxboim, A., Harada, T., Dingal, P. C., Pinter, J., . . . Discher, D. E. (2013). Nuclear lamin-A scales with tissue stiffness and enhances matrix-directed differentiation. Science, 341(6149), 1240104. doi:10.1126/science.1240104
Vogel, C., & Marcotte, E. M. (2012). Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat Rev Genet, 13(4), 227-232. doi:10.1038/nrg3185
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Referee #3
Evidence, reproducibility and clarity
The mechanisms of rare human progeria syndromes caused by mutations in nuclear lamina proteins (lamins or BANF1) are still poorly understood, mainly because these proteins are complicated: they interact and are structurally essential for mitosis and nuclear assembly; hence, disrupting either protein can (and often does) disrupt the other. Lamins and BANF1 also have multiple interwoven roles with other partners involved in 3D genome organization, chromatin regulation, and tissue-specific gene regulation during interphase. To focus on Nestor-Guillermo progeria syndrome (NGPS), caused by the homozygous A12T missense mutation in human BANF1, the authors inserted the corresponding G12T mutation in C. elegans baf-1. They tested potential phenotypes at multiple levels (molecular, transcriptional, cellular and organismal) extensively and rigorously, and did careful controls to determine whether BAF, a tiny (89-aa) protein, was disrupted by fusion to proteins such as GFP or TurboID. Animals carrying the G12T mutation exhibited reduced lifespan (Fig. 1, S1), lower responses to UV irradiation and heat-stress (Fig 7B, 7C), and revealed unexpected germline-specific defects in male worms (Fig. S2, S3), and altered gene expression in two tissues affected by human HGPS (Figs. 4 and 5). Overall, this manuscript strongly supports the major conclusion that this C. elegans line is a powerful model for human NGPS that complements a previously reported Drosophila model.
Equally importantly, from the viewpoint of fundamental discovery, this manuscript also reports major advances in understanding how BAF influences gene expression at the molecular level. Through careful attention to controls, and experimental design, the authors overcome many complications that make BAF difficult to study: its essential roles in mitosis and early embryogenesis, the 'tag'-sensitivity of endogenous BAF, and the absolute necessity to study BAF in native cell types. The authors carefully compared the impacts of tagging either baf-1 or lamin, and compared wildtype versus G12T-mutated baf-1 interactions with lamin and emerin (Fig. S5, S6, S8, S9; videos S1 and S2). DamID-Baf-1 access to chromatin was unaffected by the G12T mutation (Fig. S7), but they successfully identified subsets of genes 'occupied' by baf-1 in specific cell types, some of which were significantly affected in opposite ways by the NGPS mutation (Fig. 4, Fig. 5). However, these important new results are described too briefly, and discussion is inadequate. E.g., in hypodermal cells, the baf-1 G12T mutation dysregulated genes encoding proteins in five categories (ribosomal, proton transport, cuticle components, cell surface, lysine acetylation), by downregulating genes in three categories (ribosomal, proton transport, histone acetylation) and upregulating three other categories (cuticle components, cell surface, apical region). In intestinal cells, the mutation dysregulated genes in 8 categories (ribosomal, response to X-ray, proton transport, proteasome binding, mitochondrial protein import, endopeptidase activity, carboxy-lyase activity, ATP generation), by downregulating genes in 5 categories (ribosomal, proton transport, peptidase activity, NAD binding, metal cluster binding) and upregulating 3 categories (ribosomal, response to external stimulation, histone acetylation). Opposite results for "ribosomal genes" is confusing. Examples of genes in each affected category are shown in Fig. 6. To fully interpret this data, and address apparently-conflicting results, further analysis is needed to determine if any affected groups of genes have shared regulators. For example, Fig 5E shows "ribosomal protein genes" are both up- and down-regulated by the mutation. The authors should consider: (a) WHICH ribosomal genes are in each category, and (b) does either group of genes have known regulators that might be differentially affected by the baf-1 mutation? Similar consideration of other sets of differentially-affected genes might provide novel insight into specific chromatin-regulatory proteins (e.g., potential baf-1 partners; see next paragraph) affected by the NGPS mutation.
The current manuscript is too strictly focused on establishing C. elegans as a model for NGPS, and neglects the novel discoveries. The authors did not consider or discuss HOW a baf-1 mutation might cause such complex gene expression outcomes- given that baf-1 binds dsDNA nonspecifically. One plausible molecular explanation is that the NGPS mutation might affect baf-1 interactions with: (a) transcription factors (Requiem, RBBP4, DDB1) or chromatin-regulators (PARP1; UV-regulated interactions with DDB2 and CUL4A) identified as BAF-associated in a proteomic study (Montes de Oca et al., 2009), or (b) histone modifiers such as SET/I2PP2A (blocks H3 dephosphorylation) or H3K9 methyltransferase 'G9a' (Montes de Oca et al., 2011), or (c) other regulators that control affected genes identified in this manuscript.
Other clarifications and revisions to improve the manuscript:
Figures 1, 2, 4, 5: the graphs in Fig 1A,B,D-F and Fig 2B,D and the colorscales in Fig 4F and Fig 5E are uninterpretable when printed in black-and-white. Please fix Figs 1 and 2 using black/light-gray/white/stippled for bar graphs, and black/light-gray/solid/dotted/dashed for line graphs. Fig 2B can be fixed by direct-labeling of class numbers within each bar (instead of 'color-coding' separately).
Revise abstract lines 40-42 ("suggesting a direct relationship between BAF-1 binding [to what?] and gene expression") to reflect the deeper analysis.
Lines 132-155 (Figure 1): The impact on sperm production suggests the NGPS mutation might affect association with Germ cell-less (GCL), a transcription repressor that competes with BAF for binding to emerin in mammalian cells (Holaska et al., 2003 JBC). Lines 151-154: Did not understand the fog-2 'feminized worm' experiments. Please briefly explain for non-worm experts.
Line 190: Clarify that nuclear shapes were categorized manually by single-blind observer.
Line 237-252: Abnormal chromosome segregation and postmitotic nuclear assembly in all gfp::baf-1(G12T) embryos is fully consistent (not 'presumably causative'; line 251) with the embryonic loss-of-function phenotype for baf-1 (Margalit et al., 2005, PNAS) and is consistent with mutational disruption of binding to lamin (Liu J et al., 2000, MBC) and/or LEM-domain proteins (Liu J, Lee KK et al., 2003, PNAS).
Line 424: Agree that this new C. elegans model is important and strongly complements the Drosophila NGPS model.
Lines 463-464: Agree that future suppressor analysis in this C. elegans model will be powerfully informative.
Lines 530-533: Baf-1 localization (mobility) in intestinal cells is known to change profoundly in response to heat shock, caloric restriction or food deprivation (Bar et al., 2014, MBC). It would be worthwhile testing, in future, whether the NGPS mutation affects baf-1 localization in response to these stresses.
Referees cross-commenting
I agree with the comments from both other reviewers.
Significance
Overall, this manuscript strongly supports the major conclusion that this C. elegans line is a powerful model for human NGPS that complements a previously reported Drosophila model.
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Referee #1
Evidence, reproducibility and clarity
Summary:
Specific mutations in nuclear lamina proteins such as lamin A or BAF1 can cause premature aging syndromes (Huchinson Gilford progeria or Nestor Guillermo syndrome), which show age related deterioration of nuclear morphology as a hallmark and affected individuals have a severely shortened life span. In this study Romero-Bueno et al established an animal model system for the Nestor Guillermo syndrome, by generating C. elegans strains harboring homozygous baf-1::G12A mutations. They nicely recapitulate the expected cellular and organismal phenotypes: decreased life spans of the mutant animals and faster nuclear deterioration. In addition, the authors find reduced fertility in the mutant when BAF-1 was combined with a GFP tag and synthetic lethality when the baf-1::G12T mutant is introduced into strain carrying an epitope tagged Lamin allele. At the organismal level the authors report increased resistance to oxidative stress, but reduced thermotolerance and decreased UV resistance. By conducting tissue specific DamID together with tissue specific RNA polymerase DamID, the authors find that in the baf-1::G12T mutant the overall chromatin association of chromosome arms remains largely unchanged, however a few individual loci either lost or gained BAF-1 association. The authors report that loss of BAF-1 association with chromatin correlates with gene expression in some instances, however there was no strict uniform correlation. This is not surprising, because the changes in expression could be a secondary consequence of a BAF-1-mediated change of another locus or a consequence of altered lamin nucelar envelope association. The global pattern of BAF-1 and BAF-1 G12T binding to chromatin was very similar in both genotypes. The authors find unaltered localization of BAF-1 G 12T protein at the nuclear envelope, in contrast to reduced levels of lamin and emerin. Interestingly, BAF-1 is found on sperm, in contrast to the absence of other lamina proteins, like LMN-1 or Emerin.
Major comments:
- In the baf-1 G12T mutants the authors find reduced levels of lamin in hypodermal nuclei. It would be good to also examine the dynamics of lamin in the second tissue that was subjected to DamID (intestinal cells).
- The authors make a statement that EMR-1 expression was reduced in the baf-1 G12T mutant, but do not comment on LMN-1 expression. Can a statement on this be made by RT PCR?
- The authors find few alterations in gene regulation of the loci which have different occupancy WT BAF-1 versus BAF-1 G12T. It was surprising to see the DamID and RNA polymerase DamID experiments be done with worms grown at 20oC, because the more penetrant phenotypes at the organismal level were observed at 25oC. Could this be the reason for the little change of chromatin occupancy of BAF-1 and BAF-1 G12T or few changes in gene expression? Would it make sense to examine the expression of some selected BAF-1 bound loci by single molecule Fish at 25oC and compare expression wt versus baf-1 G12T?
Minor comments:
The finding that BAF-1 nuclear envelope localization remains unchanged in the mutant stems from detection of the inserted GFP epitope. Given that the tag has an influence on the BAF-1 G12 12T mutant viability, this statement should be phrased with more care. The tag could influence the turnover of the protein for example. Maybe Western blots comparing the signal of WT BAF-1 worms and BAF-1 G12T mutant worms would be instructive to compare the levels of the protein (at 20oC and at 25oC, day 1 adults and day 8 adults)
Line 105: typo: remove "s"
Line 154: A conclusion is missing for the fog-2 experiment would it make sense to discuss a possible influence of altered lamin binding to the nuclear envelope in the mutant in the context of the gene expression results?
Referees cross-commenting I also see this as a valuable study. I regretted a bit that the analysis was not done at the higher temperature when the authors saw the most prominent phenotypes--but I suppose the analysis is very expensive and time consuming.
Significance
Since a long time, it has remained a matter of debate whether the progeria T to G transition in BAF-1 reduces binding of BAF-1 to lamin or whether the mutation affects the binding of BAF-1 to chromatin and thereby alters chromatin organization. Conflicting results emerged from the studies of BAF1 mutants in tissue culture cells. For this reason, this study-conducted in the context of a whole animal-is very important: it allowed the author to do their experiments with cells with unaltered ploidy, expression from the endogenous promoters and in the context of defined tissues. A second conflicting finding concerned the localization of BAF-1 G 12 to T mutant protein at the nuclear envelope: some labs find it reduced at the nuclear envelope, others find unchanged amounts at the nuclear envelope. With this work the authors contributed novel and interesting findings to those ongoing discussions, they found both altered affinity of BAF-1 with chromatin (not on a global scale, but on a local scale) and reduced affinity to lamin.
Furthermore, this is one of the first studies mapping BAF-1 association with individual gene loci in a specific tissue and the authors showed that in a given tissue BAF-1 tends to be associated with not expressed genes. In a nutshell, the authors have established a convincing accessible model system for studying aging, ready for consecutive testing interventions to reduce the pace of premature aging. Strengths: convincing presentation of a novel genetic model system to study progeria, first study where BAF-1 bound loci were shown from the analysis of a tissue (there is a correlation of BAF-1 bound loci, which are not expressed in the examined tissue), introduction of an easy-to-handle model to search for compounds suitable for clinical intervention for progeria patients or anti-aging drugs. This study adds some clarity to conflicting views in the filed: the NGS mutation in BAF-1 both reduces the amount of lamin at the nuclear periphery and affects the affinity of BAF-1 to chromatin.
Limitations: the observed transcriptional changes in the mutant can be either a direct consequence of BAF-1 chromatin association or a consequence of an altered lamina since lamin is less stable at the nuclear envelope. The transcriptomic analysis was not conducted at the temperature at which penetrant phenotypes at the organismal level were observed.
Advance: Previous studies presented conflicting results about the nuclear envelope localization of BAF-1 G12T protein: this study clearly shows that the localization of the protein remains unaltered. This study also clearly demonstrates that there is less lamin at the nuclear envelope in the mutant, lending support to the in vitro findings that the mutant is compromised in Lamin binding.
Audience: The study will be of interest to anyone who studies the nuclear lamina, the nuclear envelope, progeria, aging and stress response of an organism. Beyond this a convincing powerful novel genetic system is being presented to study progeria, which is of interest to clinicians. It is also of interest for translational research, because the system can be used to screen for compounds, which could be useful for therapeutic intervention for progeria patients or for the identification of compounds that combat aging in general. Some of the presented synthetic effects with tagged strains open the opportunity to conduct genetic suppressor screens, which would be a wonderful entry point to collect more mechanistic insights in the phenomena of aging and stress response. This genetic system is an awesome starting point for further studies and advancements of elucidating the molecular mechanism of progeria by genetic screens.
Expertise: I am a C. elegans geneticist and appreciate that all the conflicting results from tissue culture studies can now be compared to an analysis in a more physiological setting and the context of a real tissue and a living animal. I am not really competent to judge the sensitivity of RAPID assays.
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Author response:
Reviewer #1 (Public Review):
This manuscript by Negi et al. investigates the effects of different ubiquitin and ubiquitin-like modifications on the stability of substrate proteins, seeking to provide mechanistic insights into known effects of these modifications on cellular protein abundance. The authors focus on comparative studies of two modifications, ubiquitin and FAT10 (a protein with two ubiquitin-like domains), on a panel of substrate proteins; prior work had established that FAT10-conjugated proteins had lower stability to proteosomal degradation than Ub-modified counterparts.
Strengths of the work include its integration of data across diverse approaches, including molecular dynamics simulations, solution NMR spectroscopy, and in vitro and cellular stability assays. From these, the authors provide provocative mechanistic insight into the lower stability of FAT10 on its own, and in FAT10-mediated destabilization of substrate proteins in computational and experimental findings. Notably, such destabilization impacts both the tag and tagged proteins, raising some provocative questions about mechanism. The data here are generally compelling, albeit with minor concerns on presentation in parts. Conclusions from this work will be interesting to scientists in several fields, particularly those interested in cellular proteostasis and in vitro protein design / long-range communication.
The most substantial weakness of this work from my perspective is the specificity of these destabilization effects. In particular, technical challenges of producing bona fide Ub- or FAT10-conjugated substrates with native linkages limits the ability to conduct in vitro studies on exactly the same molecules as being studied in cellular environments. Given some discussion in the manuscript about the importance of linkage location on the specificity of certain tag/substrate interactions, this raises an understandable but unfortunate caveat that needs to be considered more fully both in general and in light of data from other fields (e.g. single molecule pulling) showing site-dependence of comparable effects. I note that these concerns do not impact the caliber of the conclusions themselves, but perhaps suggest area for caution as to their potential impact at this time.
We thank the reviewer for positive assessment. The reviewer has pointed out the caveats regarding producing Ub- and Fat10-conjugated substrate, which we have now mentioned in the discussion in page 35 line 15.
Reviewer #2 (Public Review):
"Plasticity of the proteasome-targeting signal Fat10 enhances substrate degradation" is a nice study where the authors have shown the differences between two protein degradation tags namely, FAT10 and ubiquitin. Even though these tags are closely related in terms of folds, they have differential efficiency in degrading the substrates covalently attached to them. The authors have utilised extensive MD simulations combined with biophysics and cell biology to show the structural dynamics these tags provide for proteasomal degradation.
We thank the reviewer for positive assessment and suggestions to improve the manuscript quality.
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eLife assessment
This manuscript probes the ways in which a protein tag might influence the structure, dynamics and stability of a covalently-attached substrate protein. Such findings are of important significance to several fields, particularly in understanding how these influences control the abundance of proteins within a cell. The evidence provided to support the authors' conclusions are, however, incomplete and further control experiments are necessary to fully support the proposed model.
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Reviewer #1 (Public Review):
This manuscript by Negi et al. investigates the effects of different ubiquitin and ubiquitin-like modifications on the stability of substrate proteins, seeking to provide mechanistic insights into known effects of these modifications on cellular protein abundance. The authors focus on comparative studies of two modifications, ubiquitin and FAT10 (a protein with two ubiquitin-like domains), on a panel of substrate proteins; prior work had established that FAT10-conjugated proteins had lower stability to proteosomal degradation than Ub-modified counterparts.
Strengths of the work include its integration of data across diverse approaches, including molecular dynamics simulations, solution NMR spectroscopy, and in vitro and cellular stability assays. From these, the authors provide provocative mechanistic insight into the lower stability of FAT10 on its own, and in FAT10-mediated destabilization of substrate proteins in computational and experimental findings. Notably, such destabilization impacts both the tag and tagged proteins, raising some provocative questions about mechanism. The data here are generally compelling, albeit with minor concerns on presentation in parts. Conclusions from this work will be interesting to scientists in several fields, particularly those interested in cellular proteostasis and in vitro protein design / long-range communication.
The most substantial weakness of this work from my perspective is the specificity of these destabilization effects. In particular, technical challenges of producing bona fide Ub- or FAT10-conjugated substrates with native linkages limits the ability to conduct in vitro studies on exactly the same molecules as being studied in cellular environments. Given some discussion in the manuscript about the importance of linkage location on the specificity of certain tag/substrate interactions, this raises an understandable but unfortunate caveat that needs to be considered more fully both in general and in light of data from other fields (e.g. single molecule pulling) showing site-dependence of comparable effects. I note that these concerns do not impact the caliber of the conclusions themselves, but perhaps suggest area for caution as to their potential impact at this time.
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Joint Public Review:
The present study explored the principles that allow cells to maintain complex subcellular proteinaceous structures despite the limited lifetimes of the individual protein components. This is particularly critical in the case of neurons, where the size and protein composition of synapses define synaptic strength and encode memory.
PSD95 is an abundant synapse protein that acts as a scaffold in the recruitment of transmitter receptors and other signaling proteins and is required for proper memory formation. The authors used super-resolution microscopy to study PSD95 super-complexes isolated from the brains of mice expressing tagged PSD variants (Halo-Tag, mEos, GFP). Their results show compellingly that a large fraction (~25%) of super-complexes contains two PSD95 copies about 13 nm apart, that there is substantial turnover of PSD95 proteins in super-complexes over a period of seven days, and that ~5-20% of the super-complexes contain new and old PSD95 molecules. This percentage is higher in synaptic fractions as compared to total brain lysates, and highest in isocortex samples (~20%). These important findings support the notion put forward by Crick that sequential subunit replacement gives synaptic super-complexes long lifetimes and thus aids in memory maintenance. Overall, this is very interesting, providing key insights into how synaptic protein complexes are formed and maintained. On the other hand, the actual role of these PSD95 super-complexes in long-term memory storage remains unknown.
Strengths
(1) The study employed an appropriate and validated methodology.
(2) Large numbers of PSD95 super-complexes from three different mouse models were imaged and analyzed, providing adequately powered sample sizes.
(3) State-of-the-art super-resolution imaging techniques (PALM and MINFLUX) were used, providing a robust, high-quality, cross-validated analysis of PSD95 protein complexes that is useful for the community.
(4) The result that PSD95 proteins in dimeric complexes are on average 12.7 nm apart is useful and has implications for studies on the nanoscale organization of PSD95 at synapses.
(5) The finding that postsynaptic protein complexes can continue to exist while individual components are being renewed is important for our understanding of synapse maintenance and stability.
(6) The data on the turnover rate of PSD95 in super-complexes from different brain regions provide a first indication of potentially meaningful differences in the lifetime of super-complexes between brain regions.
Weaknesses
(1) The manuscript emphasizes the hypothesis that stable super-complexes, maintained through sequential replacement of subunits, might underlie the long-term storage of memory. While an interesting idea, this notion requires considerably more research. The presented experimental data are indeed consistent with this notion, but there is no evidence that these complexes are causally related to memory storage.
(2) Much of the presented work is performed on biochemically isolated protein complexes. The biochemical isolation procedures rely on physical disruption and detergents that are known to alter the composition and structure of complexes in certain cases. Thus, it remains unclear how the protein complexes described in this study relate to PSD95 complexes in intact synapses.
(3) Because not all GFP molecules mature and fold correctly in vitro and the PSD95-mEos mice used were heterozygous, the interpretation of the corresponding quantifications is not straightforward.
(4) It was not tested whether different numbers of PSD95 molecules per super-complex might contribute to different retention times of PSD95, e.g. in synaptic vs. total-forebrain super-complexes.
(5) The conclusion that the population of 'mixed' synapses is higher in the isocortex than in other brain regions is not supported by statistical analysis.
(6) The validity of conclusions regarding PSD95 degradation based on relative changes in the occurrence of SiR-Halo-positive puncta is limited.
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Author response:
The following is the authors’ response to the previous reviews.
Reviewer #1 (Public Review):
Key shortcomings include the unusual normalization strategies used for many experiments and the lack of quantification/statistical analyses for several experiments.
In the updated version of the paper, we have addressed all of this reviewer's criticisms. Most importantly, we have performed several additional experiments to address the concern that unusual normalization strategies were used in our paper and that quantification and statistical analyses were lacking for several experiments. We have now analyzed the full set of release conditions for Shh and engineered proteins from Disp-expressing n.t. control cells and Disp-/- cells both in the presence and absence of Scube2 (Figure 1A'-D', Figure 2E added to the paper, Figure 3B'-D', Figure 5C and Figure S2F-H). Previously, we had only quantified protein release from n.t. controls and Disp-/- cells in the presence but not in the absence of Scube2 under serum-depleted conditions. Quantifications of serum-free protein release and Shh release under conditions ranging from 0.05% FCS to 10% FCS were completely missing from the earlier versions of the manuscript, but have now been added to our paper. In addition, we have reanalyzed all of the data sets in the above figures, as well as Figures 2C and S1B, to address the issue of "unusual normalization strategies": unlike previous assays in which the highest amount of protein detected in the media was set to 100% and all other proteins in that experiment were expressed relative to that value, we now directly compare the relative amounts of cellular and corresponding solubilized proteins as a method to quantify release without the need for data normalization (Figs. 1A'-D', 2C,E, 3B'-D', E, 5C, Fig. S1B, S2F-H).
We have also repeated the qPCR analyses in C3H10T1/2 cells and now show that the same Shh/C25AShh activities can be observed when using another Shh responsive cell line, NIH3T3 cells (Fig. 4B, 6B, fig. S5B).
We would like to point out that if the criticism refers to the presentation of our RP-HPLC and SEC data, the normalization of the strongest eluted protein signal to 100% for all proteins tested is necessary to put their behavior in a clearer relationship. This is because only the relative positions of protein elution, and not their amounts, are important in these experiments.
The significance of the data provided is overstated because many of the presented experiments confirm/support previously published work.
To mitigate the first reviewer's comment that the significance of the data presented is overstated, we now clearly distinguish between our novel results and the known aspect of Hh release on lipoproteins throughout our paper. We now clearly describe what is new and important in our paper: First, contrary to the general perception in the field, Disp and Scube2 are not sufficient to solubilize Shh, casting doubt on the currently accepted model that Scube2 accepts dual-lipidated Shh from Disp and transports it to the receptor Ptch. Second, lipoproteins shift dual Shh processing to N-terminal peptide processing only to generate different soluble Hh forms with different activities (as shown in Figure 4C). Third, and again contrary to popular belief, this new release mode does not inactivate Shh, as we now show in two established cellular assays for Hh biofunction (Figures 4A-C, 5B'', 6B and S5C-G). Fourth, and most importantly, we show that spatiotemporally controlled, Disp-, Scube2- and HDL-mediated Shh release absolutely requires dual lipidation of the membrane-associated Shh precursor prior to its release. This finding (as shown in Figures 1 and S2) changes the interpretation of previously published in vivo data that have long been interpreted as evidence for the requirement of dual Shh lipidation for full receptor binding and activation.
The study provides a modest advance in our understanding of the complex issue of Shh membrane extraction.
Although we agree that our results integrate our novel observations into previously established concepts of Hh release and trafficking, we also hope that our data cast well-founded doubt on the current view that the issue of Hh release and trafficking is largely resolved by the model of Disp-mediated Shh hand-over to Scube2 and then to Ptch, which requires interactions with both Shh lipids. Our data show that this is clearly not the case in the presence of lipoproteins. Thus, the significance of our data is that models of Shh lipid-regulated signaling to Ptch obtained using the dual-lipidated Shh precursor prior to its Disp- and Scube2-mediated conversion into a delipidated or monolipidated, HDL-associated soluble ligand are likely to describe a non-physiological interaction. Instead, our work describes a highly bioactive soluble ligand with only one lipid still attached, which has not been described before in the literature. The in vivo endpoint analyses presented in Fig. S8 suggest that this new protein variant is likely to play an important role during development.
Reviewer #2 (Public Review):
The precise molecular identity (of the released Shh) remains to be defined.
We would like to respond that the direct comparison of soluble proteins and their well-defined double-lipidated precursors side-by-side in the same experiment, as shown in our paper, determines all relevant molecular changes in the Shh release process. Most importantly, we show by SDS-PAGE and RP-HPLC that HDL restricts Shh processing to the N-terminus and that the absence of HDL results in double processing of Shh during its release. We also show by SEC that the C-terminus binds the protein to HDL. In addition, the fly experiments confirm the requirement for N-terminal Hh processing, but not for processing of the C-terminal peptide, and suggest that the N-terminal Cardin-Weintraub sequence replaced by the functionally blocking tag represents the physiological cleavage site.
It would be important to demonstrate key findings in cells that secrete Shh endogenously.
We now confirm the key findings of our study in Panc1 cells that endogenously produce and secrete Shh: As shown in Fig. S1D, we find that soluble proteins are processed but retain the C-cholesterol, which we now directly confirm by RP-HPLC (Fig. S4F-H). The in vivo analyses shown in Fig. S8 suggest that the key finding - that N-terminal but not C-terminal Hh shedding is required for release - can be supported, at least in the fly: here, Hh variants impaired in their ability to be processed N-terminally strongly repress the endogenous protein, whereas the same protein impaired in its ability to be processed C-terminally does not.
The authors detect Shh variants that are expressed independently of Disp and Scube2 in secretion assays, but are excluded from interpretation as experimental artifacts.
We agree with the reviewer's criticism that the amounts of Shh released independently of Disp and Scube2 in secretion assays were not quantified and analyzed statistically to justify their proposed status as not physiologically relevant. We now show that these forms are indeed secretion artifacts (Fig. 3E and Fig. S2F-H show quantification of the lower electrophoretic mobility protein fraction (i.e., the "top" band representing the double-lipidated soluble protein fraction)) because this fraction is released independently of Disp and Scube2.
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Reviewer #1 (Public Review):
The study identifies the epigenetic reader SntB as a crucial transcriptional regulator of growth, development, and secondary metabolite synthesis in Aspergillus flavus, although the precise molecular mechanisms remain elusive. Using homologous recombination, researchers constructed sntB gene deletion (ΔsntB), complementary (Com-sntB), and HA tag-fused sntB (sntB-HA) strains. Results indicated that deletion of the sntB gene impaired mycelial growth, conidial production, sclerotia formation, aflatoxin synthesis, and host colonization compared to the wild type (WT). The defects in the ΔsntB strain were reversible in the Com-sntB strain.
Further experiments involving ChIP-seq and RNA-seq analyses of sntB-HA and WT, as well as ΔsntB and WT strains, highlighted SntB's significant role in the oxidative stress response. Analysis of the catalase-encoding catC gene, which was upregulated in the ΔsntB strain, and a secretory lipase gene, which was downregulated, underpinned the functional disruptions observed. Under oxidative stress induced by menadione sodium bisulfite (MSB), the deletion of sntB reduced catC expression significantly. Additionally, deleting the catC gene curtailed mycelial growth, conidial production, and sclerotia formation, but elevated reactive oxygen species (ROS) levels and aflatoxin production. The ΔcatC strain also showed reduced susceptibility to MSB and decreased aflatoxin production compared to the WT.
This study outlines a pathway by which SntB regulates fungal morphogenesis, mycotoxin synthesis, and virulence through a sequence of H3K36me3 modification to peroxisomes and lipid hydrolysis, impacting fungal virulence and mycotoxin biosynthesis.
The authors have achieved the majority of their aims at the beginning of the study, finding target genes, which led to catC mediated regulation of development, growth and aflatoxin metabolism. Overall most parts of the study are solid and clear.
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Author response:
The following is the authors’ response to the original reviews.
Reviewer 1:
(1) Peptides were synthesized with fluorescein isothiocyanate (FITC) and Tat tag, and then PEGylated with methoxy PEG Succinimidyl Succinate.
I have two concerns about the peptide design. First, FTIC was intended "for monitoring" (line 129), but was never used in the manuscript. Second, PEGylation targets the two lysine sidechains on the Tat, which would alter its penetration property.
We conducted an analysis of the cellular trafficking of FITC-tagged peptides following their permeabilization into cells.
Author response image 1.
However, we did not include it in the main text because it is a basic result.
(2) As can be seen in the figure above, after pegylation and permeabilization, the cells were stained with FITC. It appears that this does not affect the ability to penetrate into the cells.
(2) "Superdex 200 increase 10/300 GL column" (line 437) was used to isolate mono/di PEGylated PDZ and separate them from the residual PEG and PDZ peptide. "m-PEG-succinimidyl succinate with an average molecular weight of 5000 Da" (lines 133 and 134).
To my knowledge, the Superdex 200 increase 10/300 GL column is not suitable and is unlikely to produce traces shown in Figure 1B.
As Superdex 200 increase 10/300 GL featrues a fractionation range of 10,000 to 600,000 Da, we used it to fractionate PEGylated products including DiPEGylated PDZ (approx. 15 kDa) and MonoPEGylated PDZ (approx. 10 kDa) from residuals (PDZ and PEG), demonstrating successful isolation of PEGylated products (Figure 1C). Considering the molecular weights of PDZ and PEG are approximately 4.1 kDa and and 5.0 kDa, respectively, the late eluting peaks from SEC were likely to represent a mixed absorbance of PDZ and PEG at 215 nm.
However, as the reviewer pointed out, it could be unreasonable to annotate peaks representing PDZ and PEG, respectively, from mixed absorbance detected in a region (11-12 min) beyond the fractionation range.
In our revised manuscript, therefore, multiple peaks in the late eluting volume (11-12 min) were labeled as 'Residuals' all together. As a reference, the revised figure 1B includes a chromatogram of pure PDZ-WT under the same analytic condition.
Therefore, we changed Fig.1B to new results as followed:
(3) "the in vivo survival effect of LPS and PDZ co-administration was examined in mice. The pretreatment with WT PDZ peptide significantly increased survival and rescued compared to LPS only; these effects were not observed with the mut PDZ peptide (Figure 2a)." (lines 159-160).
Fig 2a is the weight curve only. The data is missing in the manuscript.
We added the survived curve into Fig. 2A as followed:
(4) Table 1, peptide treatment on ALT and AST appears minor.
In mice treated with LPS, levels of ALT and AGT in the blood are elevated, but these levels decrease upon treatment with WT PDZ. However, the use of mut PDZ does not result in significant changes. Figure 3A shows inflammatory cells within the central vein, yet no substantial hepatotoxicity is observed during the 5-day treatment with LPS. Normally, the ranges of ALT and AGT in C57BL6 mice are 16 ~ 200 U/L and 46 ~ 221 U/L, respectively, according to UCLA Diagnostic Labs. Therefore, the values in all experiments fall within these normal ranges. In summary, a 5-day treatment with LPS induces inflammation in the liver but is too short a duration to induce hepatotoxicity, resulting in lower values.
(5) MitoTraker Green FM shouldn't produce red images in Figure 6.
We changed new results (GREEN one) into Figs 6A and B as followed:
(6) Figure 5. Comparison of mRNA expression in PDZ-treated BEAS-2B cells. Needs a clearer and more detailed description both in the main text and figure legend. The current version is very hard to read.
We changed Fig. 5A to new one to understand much easier and added more detailed results and figure legend as followed:
Results Section in Figure 5:
“…we performed RNA sequencing analysis. The results of RNA-seq analysis showed the expression pattern of 24,424 genes according to each comparison combination, of which the results showed the similarity of 51 genes overlapping in 4 gene categories and the similarity between each comparison combination (Figure 5a). As a result, compared to the control group, it was confirmed that LPS alone, WT PDZ+LPS, and mut PDZ+LPS were all upregulated above the average value in each gene, and when LPS treatment alone was compared with WT PDZ+LPS, it was confirmed that they were averaged or downregulated. When comparing LPS treatment alone and mut PDZ+LPS, it was confirmed that about half of the genes were upregulated. Regarding the similarity between comparison combinations, the comparison combination with LPS…”
Figure 5 Legend Section:
“Figure 5. Comparison of mRNA expression in PDZ-treated BEAS-2B cells.
BEAS-2B cells were treated with wild-type PDZ or mutant PDZ peptide for 24 h and then incubated with LPS for 2 h, after which RNA sequencing analysis was performed. (a) The heat map shows the general regulation pattern of about 51 inflammation-related genes that are differentially expressed when WT PDZ and mut PDZ are treated with LPS, an inflammatory substance. All samples are RED = upregulated and BLUE = downregulated relative to the gene average. Each row represents a gene, and the columns represent the values of the control group treated only with LPS and the WT PDZ and mut PDZ groups with LPS. This was used by converting each log value into a fold change value. All genes were adjusted to have the same mean and standard deviation, the unit of change is the standard deviation from the mean, and the color value range of each row is the same. (b) Significant genes were selected using Gene category chat (Fold change value of 2.00 and normalized data (log2) value of 4.00). The above pie chart shows the distribution of four gene categories when comparing LPS versus control, WT PDZ+LPS/LPS, and mut PDZ+LPS/LPS. The bar graph below shows RED=upregulated, GREEN=downregulated for each gene category, and shows the number of upregulated and downregulated genes in each gene category. (c) The protein-protein interaction network constructed by the STRING database differentially displays commonly occurring genes by comparing WT PDZ+LPS/LPS, mut PDZ+LPS/LPS, and LPS. These nodes represent proteins associated with inflammation, and these connecting lines denote interactions between two proteins. Different line thicknesses indicate types of evidence used in predicting the associations.”
Reviewer 2:
(1) In this paper, the authors demonstrated the anti-inflammatory effect of PDZ peptide by inhibition of NF-kB signaling. Are there any results on the PDZ peptide-binding proteins (directly or indirectly) that can regulate LPS-induced inflammatory signaling pathway? Elucidation of the PDZ peptide-its binding partner protein and regulatory mechanisms will strengthen the author's hypothesis about the anti-inflammatory effects of PDZ peptide
As mentioned in the Discussion section, we believe it is crucial to identify proteins that directly interact with PDZ and regulate it. This direct interaction can modulate intracellular signaling pathways, so we plan to express GST-PDZ and induce binding with cellular lysates, then characterize it using the LC-Mass/Mass method. We intend to further research these findings and submit them for publication.
(2) The authors presented interesting insights into the therapeutic role of the PDZ motif peptide of ZO-1. PDZ domains are protein-protein interaction modules found in a variety of species. It has been thought that many cellular and biological functions, especially those involving signal transduction complexes, are affected by PDZ-mediated interactions. What is the rationale for selecting the core sequence that regulates inflammation among the PDZ motifs of ZO-1 shown in Figure 1A?
The rationale for selecting the core sequence that regulates inflammation among the PDZ motifs of ZO-1, as shown in Figure 1A, is grounded in the specific roles these motifs play in signal transduction pathways that are crucial for inflammatory processes. PDZ domains are recognized for their ability to function as scaffolding proteins that organize signal transduction complexes, crucial for modulating cellular and biological functions. The chosen core sequence is particularly important because it is conserved across ZO-1, ZO-2, and ZO-3, indicating a fundamental role in maintaining cellular integrity and signaling pathways. This conservation suggests that the sequence’s involvement in inflammatory regulation is not only significant in ZO-1 but also reflects a broader biological function across the ZO family.
(3) In Figure 3, the authors showed the representative images of IHC, please add the quantification analysis of Iba1 expression and PAS-positive cells using Image J or other software. To help understand the figure, an indication is needed to distinguish specifically stained cells (for example, a dotted line or an arrow).
We added the semi-quantitative results into Figs. 4d,e,f as followed:
Result section: “The specific physiological mechanism by which WT PDZ peptide decreases LPS-induced systemic inflammation in mice and the signal molecules involved remain unclear. These were confirmed by a semi-quantitative analysis of Iba-1 immunoreactivity and PAS staining in liver, kidney, and lung,respectively (Figures 4d, e, and f). To examine whether WT PDZ peptide can alter LPS-induced tissue damage in the kidney, cell toxicity assay was performed (Figure 3g). LPS induced cell damage in the kidney, however, WT PDZ peptide could significantly alleviate the toxicity, but mut PDZ peptide could not. Because cytotoxicity caused by LPS is frequently due to ROS production in the kidney (Su et al., 2023; Qiongyue et al., 2022), ROS production in the mitochondria was investigated in renal mitochondria cells harvested from kidney tissue (Figure 3h)....”
Figure legend section: “Indicated scale bars were 20 μm. (d,e,f) Semi-quantitative analysis of each are positive for Iba-1 in liver and kidney, and positive cells of PAS in lung, respectively. (g) After the kidneys were harvested, tissue lysates were used for MTT assay. (h) After...”
(4) In Figure 6G, H, the authors confirmed the change in expression of the M2 markers by PDZ peptide using the mouse monocyte cell line Raw264.7. It would be good to add an experiment on changes in M1 and M2 markers caused by PDZ peptides in human monocyte cells (for example, THP-1).
We thank you for your comments. To determine whether PDZ peptide regulates M1/M2 polarization in human monocytes, we examined changes in M1 and M2 gene expression in THP-1 cells. As a result, wild-type PDZ significantly suppressed the expression of M1 marker genes (hlL-1β, hIL-6, hIL-8, hTNF-ɑ), while increasing the expression of M2 marker genes (hlL-4, hIL-10, hMRC-1). However, mutant PDZ did not affect M1/M2 polarization. These results suggest that PDZ peptide can suppress inflammation by regulating M1/M2 polarization of human monocyte cells. These results are for the reviewer's reference only and will not be included in the main content.
Author response image 2.
Author response image 3.
Minor point:
The use of language is appropriate, with good writing skills. Nevertheless, a thorough proofread would eliminate small mistakes such as:
- line 254, " mut PDZ+LPS/LPS (45.75%) " → " mut PDZ+LPS/LPS (47.75%) "
- line 296, " Figure 6f " → " Figure 6h "
We changed these points into the manuscript.
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Reviewer #1 (Public Review):
Summary:
The manuscript by Zhou et al offers new high-resolution Cryo-EM structures of two human biotin-dependent enzymes: propionyl-CoA carboxylase (PCC) and methycrotonyl-CoA carboxylase (MCC). While X-ray crystal structures and Cryo-EM structures have previously been reported for bacterial and trypanosomal versions of MCC and for bacterial versions of PCC, this marks one of the first high resolution Cryo-EM structures of the human version of these enzymes. Using the biotin cofactor as an affinity tag, this team purified a group of four different human biotin-dependent carboxylases from cultured human Expi 293F (kidney) cells (PCC, MCC, acetyl-CoA carboxylase (ACC), and pyruvate carboxylase). Following further enrichment by size-exclusion chromatography, they were able to vitrify the sample and pick enough particles of MCC and PCC to separately refine the structures of both enzymes to relatively high average resolutions (the Cryo-EM structure of ACC also appears to have been determined from these same micrographs, though this is the subject of a separate publication). To determine the impact of substrate binding on the structure of these enzymes and to gain insights into substrate selectivity, they also separately incubated with propionyl-CoA and acetyl-CoA and vitrified the samples under active turnover conditions, yielding a set of cryo-EM structures for both MCC and PCC in the presence and absence of substrates and substrate analogues.
Strengths:
The manuscript has several strengths. It is clearly written, the figures are clear and the sample preparation methods appear to be well described. This study demonstrates that Cryo-EM is an ideal structural method to investigate the structure of these heterogeneous samples of large biotin-dependent enzymes. As a consequence, many new Cryo-EM structures of biotin-dependent enzymes are emerging, thanks to the natural inclusion of a built-in biotin affinity tag. While the authors report no major differences between the human and bacterial forms of these enzymes, it remains an important finding that they demonstrate how/if the structure of the human enzymes are or are not distinct from the bacterial enzymes. The MCC structures also provide evidence for a transition for BCCP-biotin from an exo-binding site to an endo-binding site in response to acetyl-CoA binding. This contributes to a growing number of biotin-dependent carboxylase structures that reveal BCCP-biotin binding at locations both inside (endo-) and outside (exo-) of the active site.
Weaknesses:
There are some minor weaknesses. Notably, there are not a lot of new insights coming from this paper. The structural comparisons between MCC and PCC have already been described in the literature and there were not a lot of significant changes (outside of the exo- to endo- transition) in the presence vs. absence of substrate analogues. There is not a great deal of depth of analysis in the discussion. For example, no new insights were gained with respect to the factors contributing to substrate selectivity (the factors contributing to selectivity for propionyl-CoA vs. acetyl-CoA in PCC). The authors state that the longer acyl group in propionyl-CoA may mediate stronger hydrophobic interactions that stabilize the alpha carbon of the acyl group at the proper position. This is not a particularly deep analysis and doesn't really require a cryo-EM structure to invoke. The authors did not take the opportunity to describe the specific interactions that may be responsible for the stronger hydrophobic interaction nor do they offer any plausible explanation for how these might account for an astounding difference in the selectivity for propionyl-CoA vs. acetyl-CoA. This suggests, perhaps, that these structures do not yet fully capture the proper conformational states. The authors also need to be careful with their over-interpretation of structure to invoke mechanisms of conformational change. A snapshot of the starting state (apo) and final state (ligand-bound) is insufficient to conclude *how* the enzyme transitioned between conformational states. I am constantly frustrated by structural reports in the biotin-dependent enzymes that invoke "induced conformational changes" with absolutely no experimental evidence to support such statements. Conformational changes that accompany ligand binding may occur through an induced conformational change or through conformational selection and structural snapshots of the starting point and the end point cannot offer any valid insight into which of these mechanisms is at play.
Some of these minor deficiencies aside, the overall aim of contributing new cryo-EM structures of the human MCC and PCC has been achieved. While I am not a cryo-EM expert, I see no flaws in the methodology or approach. While the contributions from these structures are somewhat incremental, it is nevertheless important to have these representative examples of the human enzymes and it is noteworthy to see a new example of the exo-binding site in a biotin-dependent enzyme.
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Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
In this study, Jellinger et al. performed engram-specific sequencing and identified genes that were selectively regulated in positive/negative engram populations. In addition, they performed chronic activation of the negative engram population over 3 months and observed several effects on fear/anxiety behavior and cellular events such as upregulation of glial cells and decreased GABA levels.
Strengths:
They provide useful engram-specific GSEA data and the main concept of the study, linking negative valence/memory encoding to cellular level outcomes including upregulation of glial cells, is interesting and valuable.
Weaknesses:
A number of experimental shortcomings make the conclusion of the study largely unsupported. In addition, the observed differences in behavioral experiments are rather small, inconsistent, and the interpretation of the differences is not compelling.
Major points for improvement:
(1) Lack of essential control experiments
With the current set of experiments, it is not certain that the DREADD system they used was potent and stable throughout the 3 months of manipulations. Basic confirmatory experiments (e.g., slice physiology at 1m vs. 3m) to show that the DREADD effects on these vHP are stable would be an essential bottom line to make these manipulation experiments convincing.
In previous work from our lab performing long-term activation of Gq DREADD receptors in the vHPC, we quantify the presence of Gq receptor expression over 3-, 6- and 9-month timepoints and show that there is no decrease in receptor expression, as measured via fluorescence intensity (Suthard et al., 2023). In this study, we also address that even if our manipulation is only working for 1 month, rather than 3 months, we are observing the long-term effects of this shorter-term stimulation. This is still relevant, and only changes how we interpret these findings, as shorter-term stimulation or disruption of neuronal activity can still have detrimental effects on behavior.
Furthermore, although the authors use the mCherry vector as a control, they did not have a vehicle/saline control for the hM3Dq AAV. Thus, the long-term effects such as the increase in glial cells could simply be due to the toxicity of DREADD expression, rather than an induced activity of these cells.
For chemogenetic studies, our experimental rationale utilized a standard approach in the field, which includes one of two control options: 1) active receptor vs. control vector + ligand or 2) active receptor + ligand or saline control. We chose the first option, as this more properly controls for the potential off-target effects of the ligand itself, as shown in other previous work (Xia et al., 2017). This is particularly important for studies using CNO, as many off-target effects have been noted as a limitation (Manvich et al., 2018). We chose to use DCZ as it is closely related to CNO and newer ligands, but comes with added benefits of high specificity, low off-target effects, high potency and brain penetrance (Nagai et al., 2020), but any potential off-target effects of DCZ are yet to be completely investigated as this ligand is very new.
Evidence of DREADD toxicity has been shown at high titer levels of AAV2/7- CamKIIα-hM4D(Gi)-mCherry in the hippocampus at 5 weeks, as the reviewer pointed out in their above comment (Goossens et al., 2021). Our viral strategy is targeted to a much smaller number of cells using AAV9-DIO-Flex-hM3Dq-mCherry at a lower titer, unlike expression within a much larger population of CaMKII+ excitatory neurons in this study. Additionally, visual comparison of their viral load and expression with ours shows much more intense expression that spans a larger area of the hippocampus (Goossens et al, 2021; Figure 1D), whereas ours is isolated to a smaller region of vHPC (see Figure 1B).
Further, we attempted to quantify a decrease in neuronal health (Yousef et al., 2017) resulting from DREADD expression via NeuN counts within multiple hippocampal subregions for the 6- and 14-month groups across active Gq receptor and mCherry conditions and did not observe significant decreases in NeuN as a result (Supplemental Figure 1). However, immunohistochemistry of an individual marker may not be sufficient to capture the entire health profile of an individual neuron and future work should consider other markers of cell death or inflammation, which we have added to the Limitations & Future Work section of our Discussion.
(2) Figure 1 and the rest of the study are disconnected
The authors used the cFos-tTA system to label positive/negative engram populations, while the TRAP2 system was used for the chronic activation experiments. Although both genetic tools are based on the same IEG Fos, the sensitivity of the tools needs to be validated. In particular, the sensitivity of the TRAP2 system can be arbitrarily altered by the amount of tamoxifen (or 4OHT) and the administration protocols. The authors should at least compare and show the percentage of labeled cells in both methods and discuss that the two experiments target (at least slightly) different populations. In addition, the use of TRAP2 for vHP is relatively new; the authors should confirm that this method actually captures negative engram populations by checking for reactivation of these cells during recall by overlap analysis of Fos staining or by artificial activation.
We thank the reviewer for their comments and opportunity to discuss the marked differences between TRAP2 and DOX systems. In particular, we agree that while both systems rely on the the Fos promoter to drive an effector of interest, their efficacy and temporal resolution vary substantially depending on genetic cell-type, brain region, temporal parameters of Dox or 4-OHT delivery, subject-by-subject metabolic variability, and threshold to Fos induction given the promoter sequences inherent to each system. For example, recent studies have reported the following:
- The TRAP2 line labels a subset of endogenously activeCA1 pyramidal cells (e.g. 5-18%) while the DOX system labels 20-40% of CA1 pyramidal cells (DeNardo et al, 2019; Monasterio et al, BioRxiv 2024 ).
- The temporal windows for each range from hours in TRAP2 to 24-48 hours for DOX (DeNardo et al, 2019; Denny et al, 2014; Liu & Ramirez et al, 2012).
- The efficacy of “tagging” a population of cells with TRAP2 vs with DOX will constrain the number of possible cells that may overlap with cFos upon re-exposure to a given experience (e.g. see the observed overlaps in vCA1 - BLA circuits (Kim & Cho, 2020), compared to vCA1 in general (Ortega-de San Luis et al, 2023) and valence-specific vCA1 populations (Shpokayte et al, 2022).
- Tagging vCA1 cells with both the TRAP2 and DOX systems are nonetheless sufficient to drive corresponding behaviors (e.g. vCA1 terminal stimulation drives behavioral changes with the DOX and TRAP2 system (Shpokayte et al, 2022) and vCA1 stimulation of an updated fear-linked ensemble drives light-induced freezing in a neutral context utilizing the TRAP2 and DOX systems (Ortega-de San Luis et al, 2023)).
Finally, and promisingly, as more studies continue to link the in vivo physiological dynamics of these cell populations tagged using each system (e.g. compare Pettit et al, 2022 with Tanaka et al, 2018) and correlating their activity to behavioral phenotypes, our field is in the prime position to uncover deeper principles governing hippocampus-mediated engrams in the brain. Together, we believe a more comprehensive understanding of these systems is fully warranted, especially in the service of further cataloging cellular similarities and differences within such tagged populations.
(3) Interpretation of the behavior data
In Figures 3a and b, the authors show that the experimental group showed higher anxiety based on time spent in the center/open area. However, there were no differences in distance traveled and center entries, which are often reduced in highly anxious mice. Thus, it is not clear what the exact effect of the manipulation is. The authors may want to visualize the trajectories of the mice's locomotion instead of just showing bar graphs.
Our findings show that our experimental group displays higher levels of anxiety-like behaviors as measured via time spent in center/open area, while there are no differences in distance traveled or center entries. For distance traveled, our interpretation is in line with complementary research (Jimenez et al, 2018; Kheirbek et al, 2013) that shows no changes in distance traveled/distance traveled in the center coupled with changes in anxiety levels as a result of manipulation within anxiety-related circuits. More broadly, any locomotion-related deficit could cause a change in distance traveled that is unrelated to anxiety-like behaviors alone. For example, a reduction in distance traveled could be coupled with a decrease in time spent in the center, but could also result only from motor or exploratory deficits. We hope that this explanation clarifies our interpretation of the open field and elevated plus maze findings in light of other literature.
In addition, the data shown in Figure 4b is somewhat surprising - the 14MO control showed more freezing than the 6MO control, which can be interpreted as "better memory in old". As this is highly counterintuitive, the authors may want to discuss this point. The authors stated that "Mice typically display increased freezing behavior as they age, so these effects during remote recall are expected" without any reference. This is nonsense, as just above in Figure 4a, older mice actually show less freezing than young mice. Overall, the behavioral effects are rather small and random. I would suggest that these data be interpreted more carefully.
In Figure 4B, we present our findings from remote recall and observe increased freezing levels in control mice with age, as mentioned by the reviewer, indicating increased memory. This is in line with previous work from Shoji & Miyakawa, 2019 which has been added as a reference for the quotation described above; we thank the reviewer for pointing this error out. As the reviewer has pointed out, above in Figure 4A, we measured freezing levels across all groups during contextual fear conditioning before the start of chronic stimulation, as this was the session we ‘tagged’ a negative memory in. Although it appears that there may be slightly lower levels of freezing in older (14-month old) mice, our findings do not determine statistical significance for difference between age group, only effects of time and subject which are expected as freezing increases within the session and animals display high levels of variability in freezing levels across many experiments (Figure 4A i-iii). We also find in previous work that control mice receiving 3-, 6- and 9-months of chronic DCZ stimulation in the vHPC with empty vector (mCherry) receptor show an increase in freezing with age (Suthard et al, 2023; Figure 2A ii).
(4) Lack of citation and discussion of relevant study
Khalaf et al. 2018 from Gräff lab showed that experimental activation of recall-induced populations leads to fear attenuation. Despite the differences in experimental details, the conceptual discrepancy should be discussed.
As mentioned by the reviewer, Khalaf et al. 2018 showed that experimental activation of recall-induced populations in the dentate gyrus leads to fear attenuation. Specifically, they pose that this fear attenuation occurs in these ensembles through updating or unlearning of the original memory trace via the engagement, rather than suppression, of an original traumatic experience. Despite the differences in experimental details with our current study and this work, we agree that the conceptual discrepancy should be discussed. First, one major difference is that we are reactivating an ensemble that was tagged during fear memory encoding, while Khalaf et al. are activating a remote recall-induced ensemble that was tagged one month after encoding. Although there is high overlap between the encoding and recall ensembles when mice are exposed to the conditioning context, these ensembles are not identical and may result in different behavioral phenotypes when chronically reactivated. Further, Khalaf et al rely on reactivation of the recall-induced ensemble during extinction to facilitate rapid fear attenuation. This differs from our current work, as their reactivation is occurring during the extinction process in the previously conditioned context, while we are reactivating chronically in the animal’s home cage over the course of a longer time period. It may be necessary that the memory is first reactivated, and thus, more liable to re-contextualization, in the original context compared to an unrelated homecage environment where there are presumably no related cues present. Importantly, this previous work tests the attenuation of fear shortly after an extinction process, while we are not traditionally extinguishing the context with aid of the memory reactivation. Finally, we are testing remote recall (3 months post-conditioning), while they are testing at a shorter time interval (28 days). In line with these ideas, future work may seek to tease out the mechanistic differences between recent and remote memory extinction both in terms of natural memory recall and chronically manipulated memory-bearing cells.
Reviewer #2 (Public Review):
Summary:
Jellinger, Suthard, et al. investigated the transcriptome of positive and negative valence engram cells in the ventral hippocampus, revealing anti- and pro-inflammatory signatures of these respective valences. The authors further reactivated the negative valence engram ensembles to assay the effects of chronic negative memory reactivation in young and old mice. This chronic re-activation resulted in differences in aspects of working memory, and fear memory, and caused morphological changes in glia. Such reactivation-associated changes are putatively linked to GABA changes and behavioral rumination.
Strengths:
Much of the content of this manuscript is of benefit to the community, such as the discovery of differential engram transcriptomes dependent on memory valence. The chronic activation of neurons, and the resultant effects on glial cells and behavior, also provide the community with important data. Laudable points of this manuscript include the comprehensiveness of behavioral experiments, as well as the cross-disciplinary approach.
Weaknesses:
There are several key claims made that are unsubstantiated by the data, particularly regarding the anthropomorphic framing of "rumination" on a mouse model and the role of GABA. The conclusions and inferences in these areas need to be carefully considered.
(1) There are many issues regarding the arguments for the behavioural data's human translation as "rumination." There is no definition of rumination provided in the manuscript, nor how rumination is similar/different to intrusive thoughts (which are psychologically distinct but used relatively interchangeably in the manuscript), nor how rumination could be modelled in the rodent. The authors mention that they are attempting to model rumination behaviours by chronically reactivating the negative engram ("To understand if our experimental model of negative rumination..."), but this occurs almost at the very end of the results section, and no concrete evidence from the literature is provided to attempt to link the behavioural results (decreased working memory, increased fear extinction times) to rumination-like behaviours. The arguments in the final paragraph of the Discussion section about human rumination appear to be unrelated to the data presented in the manuscript and contain some uncited statements. Finally, the rumination claims seem to be based largely upon a single data figure that needs to be further developed (Figure 6, see also point 2 below).
(2) The staining and analysis in Figure 6 are challenging to interpret, and require more evidence to substantiate the conclusions of these results. The histological images are zoomed out, and at this resolution, it appears that only the pyramidal cell layer is being stained. A GABA stain should also label the many sparsely spaced inhibitory interneurons existing across all hippocampal layers, yet this is not apparent here. Moreover, both example images in the treatment group appear to have lower overall fluorescence intensity in both DAPI and GABA. The analysis is also unclear: the authors mention "ROIs" used to measure normalized fluorescence intensity but do not specify what the ROI encapsulates. Presumably, the authors have segmented each DAPI-positive cell body and assessed fluorescence however, this is not explicated nor demonstrated, making the results difficult to interpret.
Based on the collective discussion from all reviewers on the completeness of our GABA quantification and its implications, we have decided to remove this figure and perform more substantive analysis of this E/I imbalance in future work.
(3) A smaller point, but more specific detail is needed for how genes were selected for GSEA analysis. As GSEA relies on genes to be specified a priori, to avoid a circular analysis, these genes need to be selected in a blind/unbiased manner to avoid biasing downstream results and conclusions. It's likely the authors have done this, but explicitly noting how genes were selected is an important context for this analysis.
As mentioned in our Methods section, gene sets were selected based on pre-existing biology and understanding of genes canonically involved in “neurodegeneration” such as those related to apoptotic pathways and neuroinflammation or “neuroprotection” such as brain-derived neurotrophic factor, to name a few. A limitation of this method is that we must avoid making strong claims about the actual function of these up- or down-regulated genes without performing proper knock-in or knock-out studies, but we hope that this provides an unbiased inventory for future experiments to perform causal manipulations.
Reviewer #3 (Public Review):
Summary:
The authors note that negative ruminations can lead to pathological brain states and mood/anxiety dysregulation. They test this idea by using mouse engram-tagging technology to label dentate gyrus ensembles activated during a negative experience (fear conditioning). They show that chronic chemogenetic activation of these ensembles leads to behavioral (increased anxiety, increased fear generalization, reduced fear extinction) and neural (increases in neuroinflammation, microglia, and astrocytes).
Strengths:
The question the authors ask here is an intriguing one, and the engram activation approach is a powerful way to address the question. Examination of a wide range of neural and behavioral dependent measures is also a strength.
Weaknesses:
The major weakness is that the authors have found a range of changes that are correlates of chronic negative engram reactivation. However, they do not manipulate these outcomes to test whether microglia, astrocytes, or neuroinflammation are causally linked to the dysregulated behaviors.
Recommendations For The Authors:
Reviewer #1 (Recommendations For The Authors):
- Figure 2c should include Month0, the BW before the start of the manipulation.
Regrettably, we do not have access to the Month 0 body weights at this time as this project changed hands over the course of the past year or so. This is an inherent limitation that we missed during analysis and we pose this as a limitation in the Results section after describing this finding. Therefore, it is possible that over the first month of stimulation (Month 0-1), there may have been a drop in body weight that rebounded by the first measurement at Month 1 that continued to increase normally through Months 2-3, as shown in our Figure 1. Thank you for this note.
- Figure 6a looks confusing - the background signal in the green channel is very different between control and experimental groups. Were representative images taken with different microscope settings?
The representative images were taken with the same microscope power settings, but were adjusted in brightness/contrast within FIJI for clarity in the Figure – we apologize that this was misleading in any way and thank the reviewer for their feedback. Further, based on the collective discussion from all reviewers on the completeness of our GABA quantification and its implications, we have decided to remove this figure and perform more substantive analysis of this E/I imbalance in future work.
- Typo mChe;try
This typo was fixed
- "During this contextual... mice in the 6- and 14- month groups..." Isn't it 3- and 11- month respectively at the time of fear conditioning? Throughout the manuscript, this point was written very confusingly.
Yes, we thank the reviewer for pointing this out. It has been corrected to 3- and 11-month old mice at the timing of fear conditioning and clarified throughout the manuscript where applicable.
- "GABAergic eYFP fluorescence" Where does the eYFP come from? The methods state that GABA quantification is based on IHC staining.
Based on the collective discussion from all reviewers on the completeness of our GABA quantification and its implications, we have decided to remove this figure and perform more substantive analysis of this
E/I imbalance in future work. We discuss this E/I balance not being directly assessed in the Limitations & Future Directions section of our Discussion, noting the importance of detailed quantification of both excitatory and inhibitory markers within the hippocampus.
Reviewer #2 (Recommendations For The Authors):
(1) There is a full methods section ("Analysis of RNA-seq data") that mostly describes RNA-seq analysis that seemingly does not appear in the paper. This section should be reviewed.
We have included this portion of the methods that explain the previous workflow from Shpokayte et al., 2022 where this dataset was generated and this has been noted in the “Analysis of RNA-seq data” section of the methods.
(2) Figure 6: GABA staining should be more critically analyzed, as discussed above, and validated with another GABA antibody for rigor. From the representative images provided in Figure 6, it looks possibly as though the hM3Dq images were simply not fully in the focal plane when being imaged or were over-washed, as DAPI staining also appears to be lower in these images.
Based on the collective discussion from all reviewers on the completeness of our GABA quantification and its implications, we have decided to remove this figure and perform more substantive analysis of this E/I imbalance in future work. Specifically, it will be necessary to rigorously investigate both excitatory and inhibitory markers within this region to ensure these claims are substantiated. Thank you for this suggestion.
(3) The first claim that human GABAergic interneurons cause rumination is uncited. (Page 19, first sentence beginning with: "Evidence from human studies suggests...").
Based on the collective discussion from all reviewers on the completeness of our GABA quantification and its implications, we have decided to remove this figure and perform more substantive analysis of this E/I imbalance in future work. Apologies for the lack of citation in-text, the proper citation for this finding is Schmitz et al, 2017.
(4) Gene names throughout the manuscript and figure are written in the wrong format for mice (eg: Page 13, second line: SPP1, TTR, and C1QB1 instead of Spp1, Ttr, C1qb1).
This was corrected throughout the manuscript.
(5) Tense on Page 15 third sentence of the second paragraph: "...spatial working memory was assessed...".
This was corrected throughout the manuscript.
(6) Supplemental Figure 1 would benefit from normalization of the NeuN+ cell counts. The inclusion of an excitatory and inhibitory neuron marker in this figure might benefit the argument that there is a change in the excitation/inhibition of the hippocampus - as the numbers of excitatory neurons outweigh the numbers of inhibitory neurons that would be assayed here.
In an effort to normalize the NeuN+ cell counts, for each of our ROIs (6-8 single tiles for each brain region (DG, vCA1, vSub) x 3-5 coronal slices = ~18 single tiles per mouse x 3-4 mice) we captured a 300 x 300 micrometer, single-tile z-stack at 20x magnification. These ROIs were matched for dimensions and brain regions across all groups for each hippocampal subregion quantified. We initially proposed to normalize these NeuN counts over DAPI, but because DAPI includes all nuclei (microglia, oligodendrocytes, astrocytes and neurons), we weren’t sure this was the most optimal tool. We do agree that further quantification of excitatory and inhibitory cell markers would be vital to more concrete interpretation of our findings and we have added this to our Limitations & Future Work section of the Discussion.
Reviewer #3 (Recommendations For The Authors):
(1) The DOX tagging window lacks temporal precision. I suggest the authors note this as a limitation.
We thank the reviewer for noting this, and we have added this limitation to the Methods section with the context of the 24-48 hour DOX window being longer than other methods like TRAP.
(2) Is there a homeostatic response to chronic engram stimulation? That is, is DCZ as effective in increasing neuronal excitability on day 90 as it is on day 1. This could be addressed with electrophysiology, or with IEG induction. Alternatively, the authors could refer to previous literature-- for example, Xia et al (2017) eLife-- that examined whether there was any blunting of the effects of DREADD ligands after sustained delivery via drinking water. There, of course, may be other papers as well.
As noted by the reviewer, it is important to determine if DCZ maintains its effects on neuronal excitability throughout the 3 month administration period. To address this, previous work has shown that CNO administration in drinking water over one month consistently inhibited hM4Di+ neurons without altering baseline neuronal excitability as measured by firing rate and potassium currents (Xia et al, 2017). Although this is only for one month, it is administered via the same oral route as our DCZ protocol and suggests that at least for that amount of time we are likely producing consistent effects. In our reply above to Reviewer #1’s comment, we also note that even if DCZ is only having an effect for one month, rather than 3 months, we are still observing enduring changes that resulted from this short-term disturbance.
(3) Please double check there is no group effect on weight in 6-month-old mice in Figure 2C.
Two-way RM ANOVA showed no main effect of Group within the 6-month-old control and hM3Dq groups.
Group: F(1,17) = 1.361, p=0.2594.
(4) The shock intensity is much higher than is typical for fear conditioning studies in mice. Why was this the case?
Yes, we do agree that this shock intensity is on the higher side of typical paradigms in mice, however, our lab has utilized 0.75mA to 1.5mA intensity foot shocks for contextual fear conditioning in the past (Suthard & Senne et al, 2023; 2024; Dorst & Senne et al, 2023; Grella et al., 2022; Finkelstein et al., 2022) and we maintained this protocol for internal consistency. However, it would be interesting to systematically investigate how differing intensities of foot shock, subsequent tagging of this ensemble and reactivation would uniquely impact behavioral state acutely and chronically in mice.
(5) Remote freezing is very low. The authors should comment on this-- perhaps repeated testing has led to some extinction?
A reviewer above suggested a similar phenomenon may be occuring, specifically fear attenuation as a result of chronic stimulation. They referenced previous work from Khalaf et al. 2018, where they reactivated a recall-induced ensemble, while we reactivated an ensemble tagged during encoding. We expand upon this work in light of our findings within the Limitations & Future Work section of our Discussion. However, we do appreciate the lower levels of freezing observed in remote recall and sought out other literature to understand the typical range of remote freezing levels. One thing that we note is that our remote recall is occurring 3 months after conditioning, which is much longer than typical 14-28 day protocols. However, we find that freezing levels at remote timepoints from 21-45 days results in contextual freezing levels of between 20-50% approximately (Kol et al., 2020), as well as 40-75% approximately in a variety of 28 day remote recall experiments (Lee et al., 2023). This information, together with our current experimental protocol demonstrates a wide range of remote freezing levels that may depend heavily on the foot shock intensity, duration of days after conditioning, and animal variability.
(6) "mice display increased freezing with age": please add a reference.
Apologies, we missed the citation for that claim and it has been added in-text and in the references list (Shoji & Miyakawa, 2019).
(7) Related to the low freezing levels for remote memory, why is generalization minimal? Many studies have shown that there is a time-dependent emergence of generalized fear, yet here this is not seen. Is it linked to extinction (as above)? Or genetic background?
Previous work has shown that rats receiving multiple foot shocks during conditioning displayed a time-dependent generalization of context memory, while those receiving less shocks did not (Poulos et al., 2016), as the reviewer noted in their comment. In our current study, we observe low levels of generalization in all of our groups compared to freezing levels displayed in the conditioned context at the remote timepoint, in opposition to this time-dependent enhancement of generalization. It is possible that the genetic background of our C57BL/6J mice compared to the Long-Evans rat strain in this previous work accounts for some of this difference. In addition, it is possible that the longer duration of time (3 months) compared to their remote timepoint (28 days) resulted in time-dependent decrease in generalization that decreases with greater durations of time from original conditioning. As noted above, it is indeed plausible that the reactivation of a contextual fear ensemble over time is attenuating freezing levels for both the original and similar contexts (Khalaf et al, 2018). We discuss the differences in our study and this 2018 work more comprehensively above.
(8) Morphological phenotypes of astrocytes/microglia. Would be great to do some transcriptomic profiling of microglia/astrocytes to couple with the morphological characterization (but appreciate this is beyond the scope of current work).
We thank the reviewer this suggestion, we agree that would be an incredibly informative future experiment and have added this to our Limitations & Future Experiments section of the Discussion.
(9) The authors could consider including a limitations section in their discussion which discusses potential future directions for this work:
- causal experiments.
- E/I balance is not assessed directly (interestingly, in this regard, expanded engrams are linked to increased generalization [e.g., Ramsaran et al 2023]).
Thank you for this suggestion, we have added a Limitations & Future Directions section to our Discussion and have expanded upon these suggested points.
(10) For Figure 10, consider adding an experimental design/timeline.
We are making the assumption that the reviewer meant Figure 1 instead of Figure 10 here, but note that there is a description of the viral expression duration (D0-D10), followed by an off Dox period of 48 hours (D10-D12), with subsequent engram tagging of a negative (foot shock) or positive (male-to-female exposure) on D12. In our experiments (Shpokayte et al., 2022), Dox was administered for 24 hours (D12-D13), which was followed by sacrificing the animal for cell suspension and sequencing of the positive and negative engram populations. This figure also shows the viral strategy for the Tet-tag system (Figure 1A), as well as representative viral expression in vHPC (Figure 1B). We are happy to add additional experimental design/timeline information to this figure that would be helpful to the reviewer.
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- Jun 2024
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Summary:
The paper sought to determine the number of myosin 10 molecules per cell and localized to filopodia, where they are known to be involved in formation, transport within, and dynamics of these important actin-based protrusions. The authors used a novel method to determine the number of molecules per cell. First, they expressed HALO tagged Myo10 in U20S cells and generated cell lysates of a certain number of cells and detected Myo10 after SDS-PAGE, with fluorescence and a stained free method. They used a purified HALO tagged standard protein to generate a standard curve which allowed for determining Myo10 concentration in cell lysates and thus an estimate of the number of Myo10 molecules per cell. They also examined the fluorescence intensity in fixed cell images to determine the average fluorescence intensity per Myo10 molecule, which allowed the number of Myo10 molecules per region of the cell to be determined. They found a relatively small fraction of Myo10 (6%) localizes to filopodia. There are hundreds of Myo10 in each filopodia, which suggests some filopodia have more Myo10 than actin binding sites. Thus, there may be crowding of Myo10 at the tips, which could impact transport, the morphology at the tips, and dynamics of the protrusions themselves. Overall, the study forms the basis for a novel technique to estimate the number of molecules per cell and their localization to actin-based structures. The implications are broad also for being able to understand the role of myosins in actin protrusions, which is important for cancer metastasis and wound healing.
Strengths:
The paper addresses an important fundamental biological question about how many molecular motors are localized to a specific cellular compartment and how that may relate to other aspects of the compartment such as the actin cytoskeleton and the membrane. The paper demonstrates a method of estimating the number of myosin molecules per cell using the fluorescently labeled HALO tag and SDS-PAGE analysis. There are several important conclusions from this work in that it estimates the number of Myo10 molecules localized to different regions of the filopodia and the minimum number required for filopodia formation. The authors also establish a correlation between number of Myo10 molecules filopodia localized and the number of filopodia in the cell. There is only a small % of Myo10 that tip localized relative to the total amount in the cell, suggesting Myo10 have to be activated to enter the filopodia compartment. The localization of Myo10 is log-normal, which suggests a clustering of Myo10 is a feature of this motor.
One of the main critiques of the manuscript was that the results were derived from experiments with overexpressed Myo10 and therefore are hard to extrapolate to physiological conditions. The authors counter this critique with the argument that their results provide insight into a system in which Myo10 is a limiting factor for controlling filopodia formation. They demonstrate that U20S cells do not express detectable levels of Myo10 (supplementary Figure 1E) and thus introducing Myo10 expression demonstrates how triggering Myo10 expression impacts filopodia. An example is given how melanoma cells often heavily upregulation Myo10.
In addition, the revised manuscript addresses the concerns about the method to quantitate the number of Myo10 molecules per cell and therefore puncta in the cell. The authors have now made a good faith effort to correct for incomplete labeling of the HALO tag (Figure 2A-C, supplementary Figure 2D-E). The authors also address the concerns about variability in transfection efficiency (Figure 1D-E).
A very interesting addition to the revised manuscript was the quantitation of the number of Myo10 molecules present during an initiation event when a newly formed filopodia just starts to elongate from the plasma membrane. They conclude that 100s of Myo10 molecules are present during an initiation event. They also examined other live cell imaging events in which growth occurs from a stable filopodia tip and correlated with elongation rates.
Weaknesses:
The authors acknowledge that a limitation of the study is that all of the experiments were performed with overexpressed Myo10. They address this limitation in the discussion but also provide important comparisons for how their work relates to physiological conditions, such as melanoma cells that only express large amounts of Myo10 when they are metastatic. Also, the speculation about how fascin can outcompete Myo10 should include a mechanism for how the physiological levels of fascin can complete with the overabundance of Myo10 (page 10, lines 401-408).
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Author response:
The following is the authors’ response to the original reviews.
eLife assessment
This valuable study reports on the packing of molecules in cellular compartments, such as actin-based protrusions. The study provides solid evidence for parameters that enable the building of a biophysical model of filopodia, which is required to gain a complete understanding of these important actin-based structures. Some areas of the manuscript require further clarification.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
The manuscript proposes an alternative method by SDS-PAGE calibration of Halo-Myo10 signals to quantify myosin molecules at specific subcellular locations, in this specific case filopodia, in epifluorescence datasets compared to the more laborious and troublesome single molecule approaches. Based on these preliminary estimates, the authors developed further their analysis and discussed different scenarios regarding myosin 10 working models to explain intracellular diffusion and targeting to filopodia.
Strengths:
Overall, the paper is elegantly written and the data analysis is appropriately presented.
Weaknesses:
While the methodology is intriguing in its descriptive potential and could be the beginning of an interesting story, a good portion of the paper is dedicated to the discussion of hypothetical working mechanisms to explain myosin diffusion, localization, and decoration of filopodial actin that is not accompanied by the mandatory gain/loss of function studies required to sustain these claims.
To be fair, the detailed mechanisms that we raise related to diffusion, localization, and decoration are based on extensive work by others. Many prior papers use domain deletions of Myo10 and fall in the category of gain/loss-of-function studies. It is true that we have not repeated those extensive studies, but it seems appropriate to connect with and cite their work where appropriate.
Reviewer #2 (Public Review):
Summary:
The paper sought to determine the number of myosin 10 molecules per cell and localized to filopodia, where they are known to be involved in formation, transport within, and dynamics of these important actin-based protrusions. The authors used a novel method to determine the number of molecules per cell. First, they expressed HALO tagged Myo10 in U20S cells and generated cell lysates of a certain number of cells and detected Myo10 after SDS-PAGE, with fluorescence and a stained free method. They used a purified HALO tagged standard protein to generate a standard curve which allowed for determining Myo10 concentration in cell lysates and thus an estimate of the number of Myo10 molecules per cell. They also examined the fluorescence intensity in fixed cell images to determine the average fluorescence intensity per Myo10 molecule, which allowed the number of Myo10 molecules per region of the cell to be determined. They found a relatively small fraction of Myo10 (6%) localizes to filopodia. There are hundreds of Myo10 in each filopodia, which suggests some filopodia have more Myo10 than actin binding sites. Thus, there may be crowding of Myo10 at the tips, which could impact transport, the morphology at the tips, and dynamics of the protrusions themselves. Overall, the study forms the basis for a novel technique to estimate the number of molecules per cell and their localization to actin-based structures. The implications are broad also for being able to understand the role of myosins in actin protrusions, which is important for cancer metastasis and wound healing.
Strengths:
The paper addresses an important fundamental biological question about how many molecular motors are localized to a specific cellular compartment and how that may relate to other aspects of the compartment such as the actin cytoskeleton and the membrane. The paper demonstrates a method of estimating the number of myosin molecules per cell using the fluorescently labeled HALO tag and SDS-PAGE analysis. There are several important conclusions from this work in that it estimates the number of Myo10 molecules localized to different regions of the filopodia and the minimum number required for filopodia formation. The authors also establish a correlation between number of Myo10 molecules filopodia localized and the number of filopodia in the cell. There is only a small % of Myo10 that tip localized relative to the total amount in the cell, suggesting Myo10 have to be activated to enter the filopodia compartment. The localization of Myo10 is log-normal, which suggest a clustering of Myo10 is a feature of this motor.
Weaknesses:
One main critique of this work is that the Myo10 was overexpressed. Thus, the amount in the cell body compared to the filopodia is difficult to compare to physiological conditions. The amount in the filopodia was relatively small - 100s of molecules per filopodia so this result is still interesting regardless of the overexpression. However, the overexpression should be addressed in the limitations.
This is a reasonable perspective and we now note this caveat in the Limitations section so that readers will take note. Our goal here was to understand a system in which Myo10 is the limiting reagent for filopodia, rather than a native system that expresses high Myo10 on its own. Because U2OS cells do not express detectable levels of Myo10 (see below), the natural perturbation here is overexpressing Myo10 to stimulate filopodial growth.
The authors have not addressed the potential for variability in transfection efficiency. The authors could examine the average fluorescence intensity per cell and if similar this may address this concern.
Indeed, cells are heterogenous and will naturally express different levels of Myo10 not only due to transfection efficiency, but also due to their state (cell cycle stage, motile behavior, and more). In fact, we measure the transfection efficiency of each bioreplicate and account for it in our calibration procedure. We also measure the fluorescence intensity per cell, which lets us calculate the total Myo10s per cell and the cell-to-cell variability. These Myo10 distributions across cells are shown in Fig. 1D-E.
We note here an error that we made in applying this transfection efficiency correction in the first submission. When we obtain the total Myo10 molecules by SDS-PAGE, we should divide by the total number of transfected cells. However, due to an operator precedence error, the transfection efficiency appeared in the numerator rather than the denominator. We have now corrected this error, which has the effect of increasing the number of molecules in all of our measurements. The effect of this correction has strengthened one of the paper’s main conclusions, that Myo10 is frequently overloaded at filopodial tips.
The SDS PAGE method of estimating the number of molecules is quite interesting. I really like this idea. However, I feel there are a few more things to consider. The fraction of HALO tag standard and Myo10 labeled with the HALO tagged ligand is not determined directly. It is suggested that since excess HALO tagged ligand was added we can assume nearly 100% labeling. If the HALO tag standard protein is purified it should be feasible to determine the fraction of HALO tagged standard that is labeled by examining the absorbance of the protein at 280 and fluorophore at its appropriate wavelength.
This is a fair point raised by the reviewer, and we have now measured a labeling efficiency of 90% in Supplementary Figure 2A-C. We have adjusted all values according to this labeling efficiency.
The fraction of HALO tagged Myo10 labeled may be more challenging to determine, since it is in a cell lysate, but there may be some potential approaches (e.g. mass spec, HPLC).
As noted, this value is considerably more challenging. Instead, we determined conditions under which labeling in cells is saturated. We have now stained with a concentration range for both fixed and live cell samples. Saturation occurs with ~0.5 μM HaloTag ligand-TMR in fixed/permeabilized cells and in live cells (Supplementary Figure 2D-E). This comparison of live cells vs. permeabilized cells allows us to say that the intact plasma membrane is not limiting labeling under these conditions.
In Figure 1B, the stain free gel bands look relatively clean. The Myo10 is from cell lysates so it is surprising that there are not more bands. I am not surprised that the bands in the TMR fluorescence gel are clean, and I agree the fluorescence is the best way to quantitate.
Figure 1B shows the focused view at high MW, and there is not much above Myo10. The full gel lanes shown in Supp. Fig. 1C show the expected number of bands from a cell lysate.
In Figure 3C, the number of Myo10 molecules needed to initiate a filopodium was estimated. I wonder if the authors could have looked at live cell movies to determine that these events started with a puncta of Myo10 at the edge of the cell, and then went on to form a filopodia that elongated from the cell. How was the number of Myo10 molecules that were involved in the initiation determined? Please clarify the assumptions in making this conclusion.
We thank the reviewer (and the other reviewers) for this excellent suggestion. We have now carried out these live cell experiments. These experiments were quite challenging, because we needed to collect snapshots of ~50 cells to measure the mean fluorescence intensity of transfected cells and then acquire movies of several cells for analysis. The U2OS cells were also highly temperature-sensitive and would retract their filopodia without objective heating.
We have now analyzed filopodial initiation events and measured considerably more Myo10 at the first signs of accumulation– in the 100s of molecules. The dimmer spots that we measured in the first draft were likely unrelated to filopodial initiation, and we have corrected the discussion on this point.
We now also track further growth from a stable filopodial tip (the phased-elongation mechanism from Ikebe and coworkers) and find approximately 500 molecules bud off in those events. We also track filopodial elongation rates as a function of Myo10 numbers. We have added additional live cell imaging sections that include these results.
It is stated in the discussion that the amount of Myo10 in the filopodia exceeds the number of actin binding sites. However, since Myo10 contains membrane binding motifs and has been shown to interact with the membrane it should be pointed that the excess Myo10 at the tips may be interacting with the membrane and not actin, which may prevent traffic jams.
This is also an excellent point to consider, and we have expanded the relevant discussion along these lines. We agree that the Myo10 at the filopodial tip is likely membrane-bound. We now estimate the 2D membrane area occupied by Myo10, and find that it reaches nearly full packing in many cases (under a number of assumptions that we spell out more fully in the manuscript).
Reviewer #3 (Public Review):
Summary:
The unconventional myosin Myo10 (aka myosin X) is essential for filopodia formation in a number of mammalian cells. There is a good deal of interest in its role in filopodia formation and function. The manuscript describes a careful, quantitative analysis of Myo10 molecules in U2OS cells, a widely used model for studying filopodia, how many are present in the cytosol versus filopodia and the distribution of filopodia and molecules along the cell edge. Rigorous quantification of Myo10 protein amounts in a cell and cellular compartment are critical for ultimately deciphering the cellular mechanism of Myo10 action as well as understand the molecular composition of a Myo10-generated filopodium.
Consistent with what is seen in images of Myo10 localization in many papers, the vast majority of Myo10 is in the cell body with only a small percentage (appr 5%) present in filopodia puncta. Interestingly, Myo10 is not uniformly distributed along the cell edge, but rather it is unevenly localized along the cell edge with one region preferentially extending filopodia, presumably via localized activation of Myo10 motors. Calculation of total molecules present in puncta based on measurement of puncta size and measured Halo-Myo10 signal intensity shows that the concentration of motor present can vary from 3 - 225 uM. Based on an estimation of available actin binding sites, it is possible that Myo10 can be present in excess over these binding sites.
Strengths:
The work represents an important first step towards defining the molecular stoichiometry of filopodial tip proteins. The observed range of Myo10 molecules at the tip suggests that it can accommodate a fairly wide range of Myo10 motors. There is great value in studies such as this and the approach taken by the authors gives one good confidence that the numbers obtained are in the right range.
Weaknesses:
One caveat (see below) is that these numbers are obtained for overexpressing cells and the relevance to native levels of Myo10 in a cell is unclear.
A similar concern was raised by Reviewer 2; please see above.
An interesting aspect of the work is quantification of the fraction of Myo10 molecules in the cytosol versus in filopodia tips showing that the vast majority of motors are inactive in the cytosol, as is seen in images of cells. This has implications for thinking about how cells maintain this large population in the off-state and what is the mechanism of motor activation. One question raised by this work is the distinction between cytosolic Myo10 and the population found at the ‘cell edge’ and the filopodia tip. The cortical population of Myo10 is partially activated, so to speak, as it is targeted to the cortex/membrane and presumably ready to go. Providing quantification of this population of motors, that one might think of as being in a waiting room, could provide additional insight into a potential step-by-step pathway where recruitment or binding to the cortical region/plasma membrane is not by itself sufficient for activation.
As mentioned in our response to Reviewer 2, we have now carried out quantitation in live cells to capture Myo10 transitions from cell body into filopodial movement. We attempted to identify this membrane-bound population of motors in our new live cell experiments but were unable to make convincing measurements. Notably, we see no noticeable enrichment of Myo10 at the cortex relative to the cytosol. Although we believe there is a membrane-bound waiting room (akin to the 3D-2D-1D mechanism of Molloy and Peckham), we suspect that the 2D population is diffusing too rapidly to be detected under our imaging conditions.
Specific comments:
(1) It is not obvious whether the analysis of numbers of Myo10 molecules in a cell that is ectopically overexpressing Myo10 is relevant for wild type cells. It would appear to be a significant excess based on the total protein stained blot shown in Fig S1E where a prominent band the size of tagged Myo10 seen in the transfected sample is almost absent in the WT control lane.
Even “wildtype” cells vary considerably in their Myo10 expression levels. For example, melanoma cells often heavily upregulate Myo10, while these U2OS cells produce nearly none (Supplementary Figure 1E). Thus, there is no single, widely acceptable target for Myo10 expression in wildtype cells.
Please note that the new Supplementary Figure 1E is a Myo10 Western blot, not total protein staining as before.
Ideally, and ultimately an important approach, would be to work with a cell line expressing endogenously tagged Myo10 via genome engineering. This can be complicated in transformed cells that often have chromosomal duplications.
Indeed, we chose U2OS cells for this work because they do not express detectable levels of Myo10, and thus we can avoid all of these complications. Here we can examine how Myo10 levels control filopodial production through ectopic expression.
However, even though there is an excess of Myo10 it would appear that activation is still under some type of control as the cytosolic pool is quite large and its localization to the cell edge is not uniform. But it is difficult to gauge whether the number of molecules in the filopodium is the same as would be seen in untransfected cells. Myo10 can readily walk up a filopodium and if excess numbers of this motor are activated they would accumulate in the tip in large numbers, possibly creating a bulge as and indeed it does appear that some tips are unusually large. Then how would that relate to the normal condition?
As noted above, the normal condition depends on the cellular system. However, endogenous Myo10 also accumulates in bulges at filopodial tips, so this is not a phenotype unique to Myo10 overexpression. For example, the images from Figure 1 of the Berg and Cheney (2002) citation show bulges from endogenous Myo10 in endothelial cells.
(2) Measurements of the localization of Myo10 focuses in large part on ‘Myo10 punctae’. While it seems reasonable to presume that these are filopodia tips, the authors should provide readers with a clear definition of a puncta. Is it only filopodia tips, which seems to be the case? Does it include initiation sites at the cell membrane that often appear as punctae?
We define puncta as any clusters/spots of Myo10 signal detected by segmentation, not limited to any location within the surface-attached filopodia. We exclude puncta that appear in the cell interior (~5 of which appear in Fig. 1A). These are likely dorsal filopodia, but there are few of these compared to the surface attached filopodia of U2OS cells. In Figure 2, “puncta” includes all Myo10 clusters along the filopodia shaft, though a majority happen to be tip-localized (please see Supplementary Figure 4B). We have edited the main text for clarification.
Along those lines, the position of dim punctae along the length of a filopodium is measured (Fig 3D). The findings suggest that a given filopodium can have more than one puncta which seems at odds if a puncta is a filopodia tip. How frequently is a filopodium with two puncta seen? It would be helpful if the authors provided an example image showing the dim puncta that are not present at the tip.
We have now provided an example image of dim puncta along filopodia in Supplementary Figure 4C.
(3) The concentration of actin available to Myo10 is calculated based on the deduction from Nagy et al (2010) that only 4/13 of the actin monomers in a helical turn are accessible to the Myo10 motor (discussion on pg 9; Fig S4). Subsequent work (Ropars et al, 2016) has shown that the heads of the antiparallel Myo10 dimer are flattened, but the neck is rather flexible, meaning that the motor can a variable reach (36 - 52 nm). Wouldn’t this mean that more actin could be accessible to the Myo10 motor than is calculated here?
Although we see why the reviewer might believe otherwise, the 4/13 fraction of accessible actin holds. This fraction is obtained from consideration of the fascin-actin bundle structure alone, independent of the reach of any particular myosin motor. Every repeating layer of 13 actin subunits (or 36 nm) has 4 accessible myosin binding-sites. The remaining 9 sites are rejected because a single myosin motor domain will have a steric clash with a neighboring actin filament in the bundle. A myosin with an exceptionally long reach might reach the next 13 subunit layer, but that layer also has only 4 binding sites. Thus, we can calculate the number of binding sites per unit length along the filopodium. This number would hold for a dimeric myosin with any reach, including myosin-5 or myosin-2.
(4) Quantification of numbers of Myo10 molecules in filopodial puncta (Fig 3C) leads the authors to conclude that ‘only ten or fewer Myo10 molecules are necessary for filopodia initiation’ (pg 7, top). While this is a reasonable based on the assumption that the formation of a puncta ultimately results from an initiation event, little is known about initiation events and without direct observation of coalescence of Myo10 at the cell edge that leads to formation of a filopodium, this seems rather speculative.
As noted above, we have now performed the necessary live cell imaging of filopodial nucleation events and have updated our conclusions accordingly.
Recommendations for the authors:
Reviewer #1 (Recommendations For The Authors):
I have made a series of comments that might help the authors improve their manuscript:
- A full calibration of the methodology would require testing a wider range of protein amounts, to exhaustively detect the dynamic range of the technique. The authors acknowledge in the discussion that “Furthermore, our estimates of molecules are predicated on the calibration curve of the Halo Standard Protein on the SDS-PAGE gels, which is likely the highest source of error on our molecule counts”. A good way of convincing a nasty reviewer is to provide a calibration with more than 3 reference points. At least this will help exclude from the analysis cells where Myo10 estimates are not in the linear regime of detection.
We completely agree with the reviewer’s suggestion to build a robust calibration curve. The SDS gel shown in Figure 1C originally contained 4 reference points, but the highest HaloTag standard protein point oversaturated the detector at the set exposure in the TMR channel and was omitted. We have now re-run the SDS gel to include a HaloTag standard protein curve comprising 5 points, alongside all three bioreplicates from the fixed cell experiments and all three bioreplicates from the live cell experiments (updated in Figure 1B-C). We had saved frozen lysates from the original fixed cell work, so we were able to reanalyze our data with the new set of standards. The Myo10 quantities are consistent, but with much tighter CIs from the standard curve.
- As already said this methodology is intriguing, however, a correlative validation with a conventional SMLM approach to address the bona-fide of the method would be ideal.
Unfortunately, single molecule approaches for validation are impractical for us. Due to the relatively high magnification of our TIRF microscope and the large spread area of the U2OS cells, single cells typically extend beyond the field of view. We acknowledge the benefits of SMLM quantitative techniques and other approaches cited in the introduction section. To avoid use of special tools/instruments, we offer our methodology, based off Pollard group’s quantitative Western blotting of GFP, as a simpler alternative accessible to anyone.
- TMR is a small ligand likely interacting also with Halo in its denatured state. However, to clear any doubts a parallel Native-PAGE investigation should be included, or if existing a specific reference should be provided.
Perhaps there is a misunderstanding here. One of the key advantages of the HaloTag labeling system is that the engineered dehalogenase is covalently modified by the ligand (the TMR-ligand is a suicide substrate). This means that the TMR remains bound even under denaturing conditions, which allows its detection in SDS-PAGE. Native gels are unnecessary here.
- Moreover, SDS-PAGE is run at alkaline pH, have the authors considered these points when designing the methodology? Fluorescence images were taken in PBS, which has a different pH. Could the authors, or the literature, exclude these aspects as potential pitfalls in the methodology? Also temperature is affecting fluorescence emission, but it is easier to control with certain tolerance in the room-temperature regime.
Our method does not compare fluorescence values that cross the experimental systems (SDS-PAGE vs. microscopy). Cellular proteins and HaloTag protein standards are compared in a single setting of SDS-PAGE to obtain the average number of Myo10s per transfected cell. Likewise, all measurements on intact (live or fixed) cells are conducted in that single setting to obtain average fluorescence per cell. Thus, there is no issue with the different buffers or temperatures affecting fluorescence emission.
- The authors should test their approach also with truncation variants of Myosin10 (for instance lacking the PH or motor domain). This is a classical approach that might prove the potential of the technique when altering the capacity of the protein to interact with a main binding partner. Also, treatments that induced filopodia formation might prove useful (i.e., hypotonic media induce filopodia formation in some fibroblast cell lines in our hands).
The reviewer raises interesting suggestions that we aim to address in future experiments, but truncation variants and environmental perturbations are beyond the focus of the current manuscript. Here, we report on the otherwise unperturbed state when we add exogenous full-length Myo10 to the U2OS cells. But indeed, experiments with Myo10 domain truncations, PI3K and PTEN inhibition, and cargo protein / activating cofactor knock-downs (among others) are on our drawing board.
- Most of the mechanisms hypothesized in the discussion are sound and plausible. However, the authors have chosen an experimental model where transient transfection of exogenous Myo10 in U2OS is performed. This approach poses two main and fundamental questions that are not resolved by the data provided:
A) how do different expression levels affect the Myo10 counting?
Our counting procedure does not assume uniform expression across a population of cells– quite the opposite, in fact. We directly measure Myo10 expression levels on a cell-by-cell basis with microscopy, once we know the number of molecules in our total pool (see the Methods for details). As an example of the final output, Figs. 1D and 1E show the total number of Myo10 molecules per cell for fixed and live cells, respectively.
B) how does endogenous and unlabeled Myo10 hamper the bonafide of counts? The authors claimed “U2OS cells express low levels of Myo10, so there is a small population of unlabeled endogenous Myo10 unaddressed by this paper”. As presented, the low levels of endogenous Myo10 sound an arbitrary parameter, and there are no data presented that can limit if not exclude this bias in the analysis. To produce data in a genetically modified cell line with Halo-tag on the endogenous protein will represent a much cleaner system. Alternatively, the authors should look for Myo10 KO cell lines where they can back-transfect their Halo-Tagged Myo10 construct in a more consistent framework, focusing on cells with low-to-mid levels of expression.
We agree, this is an important point to nail down (and is often neglected in the literature). We have now measured the endogenous Myo10 levels in U2OS cells by Western blotting and found that it is undetectable compared to our HaloTagged construct expression. Please see Supp. Fig 1E. Thus, for all intents and purposes, every Myo10 molecule in these experiments came from our expression plasmid. Accordingly, we have removed this caveat from the paper.
Minor points
- Figure 1B. To help the reader SDS-PAGE gels annotations should be clearer already from the figure.
We have updated the annotations for clarity.
- Methods should be organized in sessions. As it stands, it is hard for the reader to look for technical details.
We have expanded and added subsections to the Methods as requested.
- The good practice of indicating the gene and transcript entry numbers and the primer used to amplify and clone into the backbone vectors is getting lost in many papers. I would strongly encourage the authors to add this information to the methods.
We have included the gene entries to the methods and will include a full FASTA file of the coding sequence as supplementary information to avoid any ambiguity here.
The authors write “It is unclear how myosins navigate to the right place at the right time, but our results support an important interplay between Myo10 and the actin network.” It is a bit scholastic to say that Myo10 and actin have an important interplay, they are major binding partners. What is the new knowledge contained in this sentence?
Agreed– we have deleted the sentence in question.
Reviewer #2 (Recommendations For The Authors):
The authors should address all the weaknesses indicated in the public review.
There were a few other places that require clarification.
On page 4, the last paragraph. It is stated that the targeting of Myo10 was reported/proposed based on previous work (ref 31). The next few sentences are not referenced and thus likely refer to ref 31. The authors did not measure the parameters discussed in these sentences, so it is important to clarify that they are referring to previous work and not the current study.
Indeed, the next few sentences still refer to old reference 31, so we have now edited the paragraph for clarity.
On page 7, the reference to Figure 3A indicates that the trend of higher Myo10 correlating with more filopodia. However, the reference to Figure 3B indicates total intracellular Myo10 weakly correlates with more filopodia. However, the x-axis on Figure 3B is filopodia molecules not the intracellular Myo10. Please clarify.
We appreciate the reviewer for catching our mistake. Those plots are now in Fig. 2 and have been edited accordingly.
Reviewer #3 (Recommendations For The Authors):
The Discussion of results at the end of each section is rather brief and could be expanded on a bit more.
Before we were operating under the constraints of an eLife Short Report. We have now expanded the discussion for a full article.
The authors mention that actin filaments at the tips of filopodia could be frayed, citing Medalia et al, 2007 (ref 40). That paper describes an early cryoEM analysis of filopodia from the amoeba Dictyostelium. EM images of mammalian filopodia tips, e.g. Svitkina et al, 2003, JCB, do not show quite the same organization of actin as seen in the Dictyostelium filopodia tips. However, recent work from the Bershadsky lab, Li et al, 2023, presents a few cryoEM images of tips of left-bent filopodia that are tightly adhered to a substrate and there it looks like actin filaments become disorganized in tips, along with membrane bulging. The authors should consider expanding discussion of the filopodia tips to take into account what is known for mammalian filopodia.
We thank the reviewer for bringing these enlightening papers to our attention. We have now included these citations in the discussion.
Fig 1D - The x-axis is a bit odd, it goes from 0 then to 2.5e+06 with no indication of the bin size. Can this be re-labelled or the scale displayed a bit differently?
We have double-checked the axis breaks, which are large because the underlying values are large. We have also provided the bin size as requested for all histograms.
Fig 4A - What is the bin size for the histogram?
As above, we have now updated the figure legends (now in Fig. 3) to include the bin size.
Methods -
- Please provide an accession number for the Myo10 nucleotide sequence used for this work as there are at least two known isoforms.
Thank you for noting this. We are using the full-length, not the headless isoform. We have now updated the Methods accordingly.
- No mention is made of the SDS sample buffer used, was that also added to the sample?
We have now updated the Methods accordingly.
- How are samples boiled at 70 deg C? Do the authors actually mean ‘heated’?
Indeed. We have now corrected “boiled” to “heated.”
- Could the authors please briefly explain the connected component analysis used to identify filopodia?
We have now updated the Methods accordingly.
- The intensity of filopodia was determined by dividing tip intensity by the total bioreplicate sum of intensities then multiplying it by the total pool, if this reviewer understands correctly. It sounds like intensities are being averaged across a whole cell population instead of cell-by-cell. Is that correct? If so, can the authors please provide the underlying rationale for this? If not, then please better describe what was actually done.
We apologize for the confusion. Intensities are being averaged (summed) across a whole cell population, but importantly that step is only used to obtain a scale factor that converts the fluorescence signal at the microscope to the number of molecules. We then use that scale factor for all cells imaged in the bioreplicate, to both 1) find the total Myo10 in that cell, and 2) find the total amount of that Myo10 in any given location within that cell.
To further clarify, each bioreplicate has a known total number of Myo10 molecules associated with the number of cells loaded onto the SDS gel. From the SDS gel, we have an average number of Myo10 molecules per positively transfected cell. If 50 cell images are analyzed, then there is a Myo10 ‘total pool’ of (50 cells) * (average Myo10 molecules/cell). The fluorescence signal intensities in microscopy were summed for all cells within the bioreplicate (50 cells in this example). However, due to variation in expression, not every cell has the same signal intensity when imaged under the same conditions. It would be inaccurate to assume each cell contains the average Myo10 molecules/cell. Therefore, to get the number of molecules within a given Myo10 cell (or punctum), the summed cell (punctum) intensity was divided by the bioreplicate fluorescence signal intensity sum and multiplied by ‘total pool.’
- The authors quantify Myo10 protein amounts by western blotting using Halo tag fluorescence, a method that should provide good accuracy. The results depend on the transfection efficiency and it is rarely the case that it is 100%. The authors state that they use a ‘value correction for positively transfected cells’ (pg 11). It is likely that there was a range of expression levels in the cells, how was a cut-off for classifying a cell as non-expressing determined or set?
As described in the Methods, “microscopy was used to count the percentage of transfected cells from ~105-190 randomly surveyed cells per bioreplicate.” Cells were labeled and located with DAPI. If no TMR signal could be visually detected by microscopy, then the cell was deemed to be non-Myo10 expressing. We did not set a cutoff fluorescence value, as untransfected cells have no detectable signal. Please see Supplementary Figure 1F for examples.
- “In-house Python scripts” are used for image analysis. Will these be made publicly available?
Yes, we will package these up on GitHub.
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Author response:
The following is the authors’ response to the original reviews.
Reviewer #1 (Public Review):
Summary:
In this manuscript, Chowdhury and co-workers provide interesting data to support the role of G4-structures in promoting chromatin looping and long-range DNA interactions. The authors achieve this by artificially inserting a G4-containing sequence in an isolated region of the genome using CRISPR-Cas9 and comparing it to a control sequence that does not contain G4 structures. Based on the data provided, the authors can conclude that G4-insertion promotes long-range interactions (measured by Hi-C) and affects gene expression (measured by qPCR) as well as chromatin remodelling (measured by ChIP of specific histone markers).
Whilst the data presented is promising and partially supports the authors' conclusion, this reviewer feels that some key controls are missing to fully support the narrative. Specifically, validation of actual G4-formation in chromatin by ChIP-qPCR (at least) is essential to support the association between G4-formation and looping. Moreover, this study is limited to a genomic location and an individual G4-sequence used, so the findings reported cannot yet be considered to reflect a general mechanism/effect of G4-formation in chromatin looping.
Strengths:
This is the first attempt to connect genomics datasets of G4s and HiC with gene expression. The use of Cas9 to artificially insert a G4 is also very elegant.
Weaknesses:
Lack of controls, especially to validate G4-formation after insertion with Cas9. The work is limited to a single G4-sequence and a single G4-site, which limits the generalisation of the findings.
In the revised version we validated G4 formation inside cells at the insertion site using the reported G4-selective antibody BG4. Significant BG4 binding (by ChIP-qPCR) was clear in the G4-array insert, and not in the G4-mutated insert, supporting formation of G4s by the inserted G4-array (included as Figure S4).
To directly address the second point, we inserted the G4-sequence, or the mutated control, at a second relatively isolated locus (at the 10 millionth position on Chr12, denoted as 10M site in text). First, BG4 ChIP was done to confirm intracellular G4 formation by the inserted array. BG4 ChIP-qPCR binding was significant within the inserted region, and not in the negative control region (Figure S8), consistent with the 79M locus. Together these demonstrate intracellular G4 formation by inserted sequences at two different loci.
We next checked the state of chromatin of the G4-array inserted at the 10M locus, or its negative control. Histone marks H3K4Me1, H3K27Ac, H3K27Me3, H3K9me3 and H3K4Me3 were tested at the G4-array, or the negative control locus. Relative increase in the enhancer histone marks was evident, relative to the control sequence. This was largely similar to the 79M locus, supporting an enhancer-like state. Interestingly, here we further noted presence of the H3K27me3 histone mark. The presence of the H3K27Me3 repressor histone mark, along with H3K4Me1/H3K27Ac enhancer histone marks, support a poised enhancer-like status of the inserted G4 region, as has been observed earlier in other studies. Together, although data from the two distinct G4 insertion sites support the enhancer-like state, there are contextual differences likely due to the sequence/chromatin of the sites adjacent to the inserted sequence.
Effect of the 10M G4-insertion on activation of surrounding genes (10 Mb window), and not the G4-mutant insert, was evident for most genes. Consistent with the enhancer-like state of the G4-array insert; in line with the 79M G4-array insert.
These results have been added as the final section in the revised version, data is shown in Figure 7.
Reviewer #2 (Public Review):
Summary:
Roy et al. investigated the role of non-canonical DNA structures called G-quadruplexes (G4s) in long-range chromatin interactions and gene regulation. Introducing a G4 array into chromatin significantly increased the number of long-range interactions, both within the same chromosome (cis) and between different chromosomes (trans). G4s functioned as enhancer elements, recruiting p300 and boosting gene expression even 5 megabases away. The study proposes a mechanism where G4s directly influence 3D chromatin organization, facilitating communication between regulatory elements and genes.
Strength:
The findings are valuable for understanding the role of G4-DNA in 3D genome organization and gene transcription.
Weaknesses:
The study would benefit from more robust and comprehensive data, which would add depth and clarity.
(1) Lack of G4 Structure Confirmation: The absence of direct evidence for G4 formation within cells undermines the study's foundation. Relying solely on in vitro data and successful gene insertion is insufficient.
Using the reported G4-specific antibody, BG4, we performed BG4 ChIP-qPCR at the 79M locus. In addition, a second G4-insertion site was created and BG4 ChIP-qPCR was used to validate intracellular G4 formation. Briefed below, more details in the response above.
In the revised version we validated G4 formation inside cells at the insertion site using the reported G4-selective antibody BG4. Significant BG4 binding (by ChIP-qPCR) was clear in the G4-array insert, and not in the G4-mutated insert, supporting formation of G4s by the inserted G4-array (included as Figure S4).
Further, we inserted the G4-sequence, or the mutated control, at a second relatively isolated locus (at the 10 millionth position on Chr12, denoted as 10M site in text). First, BG4 ChIP was done to confirm intracellular G4 formation by the inserted array. BG4-ChIP-qPCR was significant within the G4-array inserted region, and not in the negative control region (Figure S8), consistent with the 79M locus. Together these demonstrate intracellular G4 formation by inserted sequences at two different loci. Added in revised text in the second and the final sections of results, data shown in Figures 7, S4 and S8.
(2) Alternative Explanations: The study does not sufficiently address alternative explanations for the observed results. The inserted sequences may not form G4s or other factors like G4-RNA hybrids may be involved.
As mentioned in response to the previous comment, we confirmed that the inserted sequence indeed forms G4s inside the cells. RNA-DNA hybrid G4s can form within R-loops with two or more tandem G-tracks (G-rich sequences) on the nascent RNA transcript as well as the non-template DNA strand (Fay et al., 2017, 28554731). A recent study has observed that R-loop-associated G4 formation can enhance chromatin looping by strengthening CTCF binding (Wulfridge et al., 2023, 37552993). As pointed out by the reviewer, the possibility of G4-RNA hybrids remains, we have mentioned this possibility for readers in the second last paragraph of the Discussion.
(3) Limited Data Depth and Clarity: ChIP-qPCR offers limited scope and considerable variation in some data makes conclusions difficult.
We noted variation with one of the primers in a few ChIP-qPCR experiments (in Figures 2 and 3D). The changes however were statistically significant across replicates, and consistent with the overall trend of the experiments (Figures 2, 3 and 4). Enhancer function, in addition to ChIP, was also confirmed using complementary assays like 3C and RNA expression.
(4) Statistical Significance and Interpretation: The study could be more careful in evaluating the statistical significance and magnitude of the effects to avoid overinterpreting the results.
We reconfirmed our statistical calculations from biological replicate experiments. We carefully looked at potential overinterpretations, and made appropriate changes in the manuscript (details of the changes given below in response to comment to authors).
Reviewer #3 (Public Review):
Summary:
This paper aims to demonstrate the role of G-quadruplex DNA structures in the establishment of chromosome loops. The authors introduced an array of G4s spanning 275 bp, naturally found within a very well-characterized promoter region of the hTERT promoter, in an ectopic region devoid of G-quadruplex and annotated gene. As a negative control, they used a mutant version of the same sequence in which G4 folding is impaired. Due to the complexity of the region, 3 G4s on the same strand and one on the opposite strand, 12 point mutations were made simultaneously (G to T and C to A). Analysis of the 3D genome organization shows that the WT array establishes more contact within the TAD and throughout the genome than the control array. Additionally, a slight enrichment of H3K4me1 and p300, both enhancer markers, was observed locally near the insertion site. The authors tested whether the expression of genes located either nearby or up to 5 Mb away was up-regulated based on this observation. They found that four genes were up-regulated from 1.5 to 3-fold. An increased interaction between the G4 array compared to the mutant was confirmed by the 3C assay. For in-depth analysis of the long-range changes, they also performed Hi-C experiments and showed a genome-wide increase in interactions of the WT array versus the mutated form.
Strengths:
The experiments were well-executed and the results indicate a statistical difference between the G4 array inserted cell line and the mutated modified cell line.
Weaknesses:
The control non-G4 sequence contains 12 point mutations, making it difficult to draw clear conclusions. These mutations not only alter the formation of G4, but also affect at least three Sp1 binding sites that have been shown to be essential for the function of the hTERT promoter, from which the sequence is derived. The strong intermingling of G4 and Sp1 binding sites makes it impossible to determine whether all the observations made are dependent on G4 or Sp1 binding. As a control, the authors used Locked Nucleic Acid probes to prevent the formation of G4. As for mutations, these probes also interfere with two Sp1 binding sites. Therefore, using this alternative method has the same drawback as point mutations. This major issue should be discussed in the paper. It is also possible that other unidentified transcription factor binding sites are affected in the presented point mutants.
Since the sequence we used to test the effects of G4 structure formation is highly G-rich, we had to introduce at least 12 mutations to be sure that a stable G4 structure would not form in the mutated control sequence. Sp1 has been reported to bind to G4 structures (Raiber et al., 2012). Therefore, Sp1 binding is likely to be associated with the G4-dependent enhancer functions observed here. We also appreciate that apart from Sp1, other unidentified transcription factor binding sites might be affected by the mutations we introduced. We have discussed these possibilities in the fourth paragraph of the Discussion section in the revised manuscript.
Reviewer #1 (Recommendations For The Authors):
Whilst the data presented is promising and partially supports the authors' conclusion, this reviewer feels that some key controls are missing to fully support the narrative used. Below are my main concerns:
(1) The main thing missing in the current manuscript is to validate the actual formation of G4 in chromatin context for the repeat inserted by CRISPR-Cas. Whilst I appreciate this will form promptly a G4 in vitro, to fully support the conclusions proposed the authors would need to demonstrate actual G4-formation in cells after insertion. This could be done by ChIP-qPCR using the G4-selective antibody BG4 for example. This is an essential piece of evidence to be added to link with confidence G4-formation to chromatin looping.
To address the concern regarding whether the inserted G4 sequence forms G4s in cells, as suggested, we used the G4-selective antibody BG4. PCR primers in the study were designed keeping multiple points in mind: Primers should not bind to any site of G/C alteration in the mutated control insert; either the forward/reverse primer is from the adjacent region for specificity; covers adjacent regions for studying any effects on chromatin; and, PCRs optimized keeping in mind the repeats within the inserted sequence. Given these, primer pairs R1-R4 were chosen for further work following optimizations (Figure 2, top panel). For BG4 ChIP-qPCR we used primer pairs R2, which covered >100 bases of the inserted G4-array, or the G4-mutated control. Significant BG4 binding was clear in the G4-array insert, and not in the G4-mutated insert, demonstrating formation of G4s by the inserted G4-array (Figure S4).
In response to comment #3 below, we inserted the G4-forming sequence (or its mutated control) at a second locus. This insertion was near the 10 millionth position of chromosome 12 (10M insertion locus in text). Here also, BG4 binding was significant within the G4-array inserted region, and not in the negative control region (Figure S8). Together these demonstrate G4 formation by the inserted sequence at two different loci.
(2) I found the LNA experiment very elegant. However, what would be the effect of LNA treatment on the control sequence that does not form G4s? This control is essential to disentangle the effect of LNA pairing to the sequence itself vs disrupting the G4-structure.
As per the reviewer’s suggestion, we performed a control experiment where we treated the G4-mutated insert (control) cells with the G4-disrupting LNA probes. The changes in the expression of the surrounding genes in this case were not significant, indicating that the effects observed in the G4-array insert cells were possibly due to disruption of the inserted G4 structures. This data is presented in Figure S5.
(3) The authors describe their work and present its conclusion as if this were a genome-wide study, whilst the work is focused on a specific genomic location, and the looping, along with the effect on histone acetylation and gene expression, is limited to this. The authors cannot conclude, therefore, that this is a generic effect and the discussion should be more focused on the specific G4s used and the genomic location investigated. Ideally, insertion of a different G4-forming sequence or of the same in a different genomic location is recommended to really claim a generic effect.
To address this we inserted the G4-array sequence, or the G4-mutated control sequence, at another relatively isolated locus – at the 10 millionth position of chromosome 12 – denoted as 10M. Using BG4 ChIP-qPCR intracellular G4 formation was confirmed. We observed that the enhancer-like features in terms of enhancer histone marks and increase in the expression of surrounding genes were largely reproduced at the 10M locus on G4 insertion (Figure 7). These results are added as the final section under Results.
Reviewer #2 (Recommendations For The Authors):
The study proposes a mechanism where G4s directly influence 3D chromatin organization, facilitating communication between regulatory elements and genes.
While the present manuscript presents an interesting hypothesis, it would benefit from enhanced novelty and more robust data. The study complements existing G4 research (e.g., PMID: 31177910). While the conclusions hold biological relevance, they largely reiterate established knowledge. Furthermore, the presented data appear preliminary and still lack depth and clarity.
Hou et al., 2019 (PMID: 31177910) showed presence of potential G4-forming sequences correlated with TAD boundaries, along with enrichment of architectural proteins and transcription factor binding sites. Also, other studies noted enrichment of potential G4-forming sequences at enhancers along with nucleosome depletion and higher transcription factor binding (Hou et al., 2021; Williams et al., 2020). These studies proposed the role of G4s in chromatin/TAD states based on analysis of potential G4-forming sequences using correlative bioinformatics analyses. Here we sought to directly test causality. Insertion of G4 sequence, and formation of intracellular G4s in an isolated, G4-depleted region resulted in altered characteristics of chromatin, and not in the negative control insertion that does not form G4s. These, in contrast to earlier studies, directly demonstrates the causal role of G4s as functional elements that impact local and distant chromatin.
Major concerns:
(1) Lack of G4 Structure Confirmation: Implement G4-specific antibodies or fluorescent probes to verify G4 structures inside the cells.
Detailed response given above. Briefly, in the revised version we validated G4 formation inside cells at the insertion site using the reported G4-selective antibody BG4. Significant BG4 binding (by ChIP-qPCR) was clear in the G4-array insert, and not in the G4-mutated insert, supporting formation of G4s by the inserted G4-array (included as Figure S4).
Further, we inserted the G4-sequence, or the mutated control, at a second relatively isolated locus (at the 10 millionth position on Chr12, denoted as 10M site in text). First, BG4 ChIP was done to confirm intracellular G4 formation by the inserted array. BG4 ChIP-qPCR binding was significant within the G4-array inserted region, and not in the negative control region (Figure S8), consistent with the 79M locus. Together these demonstrate intracellular G4 formation by inserted sequences at two different loci. Added in revised text in the second and the final sections of results, data shown in Figures 7, S4 and S8.
(2) Alternative Explanations: Explore the possibility that the sequences may not form G4s or that other factors like G4-RNA hybrids are involved.
Response provided in the public reviews section.
(3) Limited Data Depth and Clarity: ChIP-qPCR offers limited scope. Consider employing G4 ChIP-seq for genome-wide analysis of G4 association with histone modifications. Address inconsistencies in data like H3K27me3 variation and incomplete H3K9me3 data sets.
A recent study performed G4 CUT&Tag (Lyu et al., 2022, 34792172) and observed G4 formation at both active promoters and active and poised enhancers. We have discussed this in the sixth paragraph of the Discussion. The H3K27Me3 occupancy at the 79M locus insertions did not have any significant G4-dependent changes, however, at the second insertion site at the 10M locus (introduced in the revised manuscript, Figure 7) there was significant G4-dependent increase in H3K27Me3 occupancy along with the H3K4Me1 and H3K27Ac enhancer histone marks, indicating formation of a poised enhancer-like element.
We completed the H3K9me3 data sets for both insertion sites.
(4) Statistical Significance and Interpretation: Re-evaluate the statistical significance of results and interpret them in the context of relevant biological knowledge. Avoid overstating the impact of minor changes.
We revised several lines to avoid overstating results. Some of the changes are as below (changes underline/strikethrough)
- There was an a relatively modest increase in the recruitment of both p300 and a substantial increase in the recruitment of the more functionally active acetylated p300/CBP to the G4-array when compared against the mutated control.
- As expected, although modest, a decrease in the H3K4Me1 and H3K27Ac enhancer histone modifications was evident within the insert upon the LNAs treatment.
- Moreover, the enhancer marks were relatively reduced, although not markedly, when the inserted G4s were specifically disrupted.
(5) Unexplored Aspects: Investigate the relationship between G4 DNA and R-loops, and consider the role of CTCF and cohesin proteins in mediating long-range interactions. Integrate existing research to build a more comprehensive framework and draw more robust conclusions.
As mentioned in response to one of the earlier comments, a recent publication extensively studied the association between G4s, R-loops, and CTCF binding (Wulfridge et al., 2023). While, here we focused on the primary features of a potential enhancer, further work will be necessary to establish how G4s influence the coordinated action between cohesin and CTCF and consequent chromatin looping. We have described this for readers in the second last paragraph of the Discussion in the revised version.
Minor Concern:
(1) Enhancer Definition: The term "enhancer" requires specific criteria. Modify the section heading or provide evidence demonstrating the G4 sequence fulfills all conditions for being an enhancer, such as position independence and long-range effects.
Although we checked some of the primary features of a potential enhancer: Like expression of surrounding genes, enhancer histone marks, chromosomal looping interactions, and recruitment of transcriptional coactivators, further aspects may need to be validated. As suggested, in the revised manuscript the section heading has been modified to ‘Enhancer-like features emerged upon insertion of G4s.’
Reviewer #3 (Recommendations For The Authors):
In addition to the points in my public review, I would like to mention some less significant points.
The authors mention that "the array of G4-forming sequences used for insertion was previously reported to form stable G4s in human cells" (Lim et al., 2010; Monsen et al., 2020; Palumbo et al., 2009). However, upon reading the publications, I found that these observations were made in vitro. I may have missed something, but there are now several mappings of folded-G4 in human cells based on different approaches. It would be beneficial to investigate whether the hTERT promoter is a site of G-quadruplex formation in vivo. If confirmed, a similar analysis should be conducted on the 275 bp region inserted into the ectopic region to determine if it also has the ability to form a structured G4.
We performed BG4 ChIP to confirm in vivo G4 formation by the inserted G4-array as suggested (Figures S4, S8). Detail response given above. Briefly, in the revised version we validated G4 formation inside cells at the insertion site using the reported G4-selective antibody BG4. Significant BG4 binding (by ChIP-qPCR) was clear in the G4-array insert, and not in the G4-mutated insert, supporting formation of G4s by the inserted G4-array (included as Figure S4).
Further, we inserted the G4-sequence, or the mutated control, at a second relatively isolated locus (at the 10 millionth position on Chr12, denoted as 10M site in text). First, BG4 ChIP was done to confirm intracellular G4 formation by the inserted array. BG4-ChIP-qPCR was significant within the inserted region, and not in the negative control region (Figure S8). Consistent with the 79M locus. Together these demonstrate intracellular G4 formation by inserted sequences at two different loci. Added in revised text in the second and the final sections of results, data shown in Figures 7, S4 and S8.
The inserted sequence originates from a well-characterized promoter. The authors suggest that placing it in an ectopic position creates an enhancer-like region, based on the observation of increased levels of H3K27Ac and H3K4me1 on the WT array. To provide a control that it is not a promoter, it would be useful to also analyze a specific mark of promoter activity, such as H3K4me3.
As suggested by reviewer, we also analysed the H3K4Me3 promoter activation mark at both the 79M and 10M (introduced in the revised manuscript, Figure 7) insertion loci. We did not observe any significant G4-dependent changes in the recruitment of H3K4Me3 (Figures 2, 7).
In the discussion, the authors mention "it was proposed that inter-molecular G4 formation between distant stretches of Gs may lead to DNA looping". To investigate this further, it would be worthwhile to examine whether the promoter regions of activated genes (PAWR, PPP1R12A, NAV3, and SLC6A15) contain potentially forming G-quadruplexes (pG4). Additionally, sites that establish more contact with the G4 array described in Figure 6F could be analyzed for enrichment in pG4.
Thank you for pointing this out. We found promoters of the four genes (PAWR, PPP1R12A, NAV3, and SLC6A15) harbour potential G4-forming sequences (pG4s). Also as suggested, we analysed the contact regions in Fig 6F, along with the whole locus, for pG4s. Relative enrichment in pG4 was seen, particularly within the significantly enhanced interacting regions, which at times spreads beyond the interacting regions also. This is shown in the lower panel of Figure 6F in the revised version. We have described this in Discussion for readers.
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Comment by onewheeljoe:
For example, we might simply ask that each participant refrain from using hashtags as a final thought because that is a form of sarcasm or punchline that can be misconstrued or shut down honest debate or agreeable disagreement.
We could ask respondents to reply to any comment that they read twice because of tone to use "ouch" as a tag or a textual response. The offending respondent could respond with "oops" in order to preserve good will in an exchange of ideas.
Finally, the first part of a flash mob might occur here, in the page notes, where norms could be quickly negotiated and agreed upon with a form of protocol.
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Reviewer #1 (Public Review):
Summary:
Guo, Hue et al. focused on understanding the epigenetic activity and functional dependencies for two different fusions found in infantile rhabdomyosarcoma, VGLL2::NCOA2, and TEAD1::NCOA2. They use a variety of models and methods; specifically, ectopic expression of the fusions in human 293T cells to perform RNAseq (both fusions), CUT&RUN (VGLL2::NCOA2), and BioID mass spec (both fusions). These data identify that the VGLL2::NCOA2 fusion has peaks that are enriched for TEAD motifs. Further, CPB/p300 CUT&RUN support an enrichment of binding sites and three TEAD targets in VGLL2::NCOA2 and TEAD1::NCOA2 expressing cells. They also functionally evaluated genetic and chemical dependencies (TEAD inhibition), and found this was only effective for the VGLL2::NCOA2 fusion, and not for TEAD1::NCOA2. Using complementary biochemical approaches they suggest (with other supporting data) that the fusions regulate TEAD transcriptional outputs via a YAP/TAZ independent mechanism. Further, they expand into a C2C12 myoblast model and show that TEAD1::NCOA2 is transforming in colony formation assays and in mouse allografts. This is consistent with previously published strategies using VGLL2::NCOA2. Importantly, they show that a CBP/p300 (a binding partner found in their BioID mass spec) small molecule inhibitor suppresses tumor formation using this mouse allograft model, that the tumors are less proliferative, and have a reduction in transcriptional of three TEAD target genes. Generally, the data is interesting and suggests new biology for these fusion-oncogenes. However, the choice of 293T for the majority of the transcriptional, epigenetic, and proteomic studies makes the findings difficult to interpret in the context of the human disease, and the rationale for the choice of an epithelial-like kidney cell line is not discussed. Further, details are missing from the figures, figure legends, and methods that make the data difficult to interpret, and should be added to improve the reader's understanding. Overall, the breadth of methods used in this study, and the comparison of the two fusion-oncogene's biology is of interest to the fusion-oncogene, pediatric sarcoma, and epigenetic therapeutic targeting fields.
Strengths:
(1) Multiple experimental approaches were used to understand the biology of the fusion-oncogenes, including genomic, proteomic, chemical, and genetic inhibition. These approaches identify potential new mechanisms of convergent fusion-oncogene activity, around TEAD transcriptional targeting (that is YAP/TAZ independent) and reveal CBP/p300 as a functional dependency.
(2) Complementary models were used, including cell-based assays and mouse allograft models to show the dependency on CBP/P300.
(3) Co-IPs were clear and convincing and showed direct interaction of the fusion-oncogene with ectopic and endogenous TEAD1/pan-TEAD, but not YAP/TAZ.
(4) Potential to follow-up on additional targets/mechanisms of tumorigenesis. For example, in the BioID proteomics screen, a unique VGLL2::NCOA2 and TEAD::NCOA2 interactor is P53, which also is an enriched pathway in Figure 4C in the p300 CUT&RUN peaks in the VGLL2::NCOA2 and TEAD1::NCOA2 expressing cells - is this indicative of the toxicity of the fusion-oncogenes or do you think this informs potential mechanisms for transformation.
Weaknesses:
(1) The rationale for performing genomics, transcriptional, and proteomics work in 293T cells is not discussed. Further, there are no functional readouts mentioned in the 293T cells with expression of the fusion-oncogenes. Did these cells have any phenotypes associated with fusion-oncogene expression (proliferation differences, morphological changes, colony formation capacity)? Further, how similar are the gene expression signatures from RNA-seq to rhabdomyosarcoma? This would help the reader interpret how similar these cell models are to human disease.
(2) TEAD1::NCOA2 fusion-oncogene model was not credentialed past H&E, and expression of Desmin. Is the transcriptional signature in C2C12 or 293T similar to a rhabdomyosarcoma gene signature?
(3) For the fusion-oncogenes, did the HA, FLAG, or V5 tag impact fusion-oncogene activity? Was the tag on the 3' or 5' of the fusion? This was not discussed in the methods.
(4) Generally, the lack of details in the figures, figure legends, and methods make the data difficult to interpret. A few examples are below:
a. Individual data points are not shown for figure bar plots (how many technical or biological replicates are present and how many times was the experiment repeated?).<br /> b. What exons were included in the fusion-oncogenes from VGLL2 and NCOA2 or TEAD1 and NCOA2?<br /> c. For how long were the colony formation experiments performed? Two weeks?<br /> d. In Figure 2D, what concentration of CP1 was used and for how long?<br /> e. How was A485 resuspended for cell culture and mouse experiments, what is the percentage of DMSO?<br /> f. How many replicates were done for RNA-seq, CUT&RUN, and ATACseq experiments?
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Reply to the reviewers
Reviewer #1 (Evidence, reproducibility and clarity (Required):
The majority of the conclusions are well supported by strong experimental evidence. The only area where that is not fully the case is the role of Pak1 as a downstream effector of FoxG1-FoxO6 and its effects on macropinocytosis. To further strengthen this claim, the authors should demonstrate that ablation of Pak1 can rescue the functional consequences of forced FoxO6 expression and whether overexpression of Pak1 rescues quiescence exit in FoxO6 knockout. Thank you to the reviewer for these helpful suggestions. To investigate the effects of Pak1 ablation, and therefore more directly the link between FOXG1 and FoxO6 and macropinocytosis, we tested the published Pak1 inhibitor IPA-3. Unfortunately, to distinguish the role of Pak1 in quiescence exit and macropinocytosis, we would need a dosage of IPA-3 that is efficacious but does not affect cell proliferation. It was not possible to optimise such a dosage (a dosage of 10uM is shown to be efficacious at inhibiting Pak1 (Verma et al, 2020; Wong et al, 2013) however even at 2.5uM we see significant cell death in our cells. Indeed, this is potentially due to pleiotropic roles for Pak1.
Also, it is not feasible to overexpress Pak1 in the FoxO6 KO cells with inducible FOXG1. To ensure we are investigating quiescence exit this would need to be in an inducible manner; however, re-transfecting cells using the PiggyBac system would potentially alter FOXG1 transgene levels by excising the existing transgene.
As shown in Figure S3, we do not observe clear vacuole formation in F6 (FOXG1-inducible) cells upon Dox addition. As detailed in the discussion, we hypothesise that FoxO6-induced macropinocytosis could represent a stalled state, with other pathways downstream of FOXG1 necessary to be activated concomitantly to ensure cell cycle re-entry, e.g., through increased pinocytic flux that cannot be assessed within our experimental timeframes. Indeed, active Pak1 has been found to modulate pinocytic cycling, enhancing both FITC-dextran uptake and efflux (Dharmawardhane et al, 2000). We therefore would not hypothesise that high Pak1 levels alone would be sufficient to drive quiescence exit.
Alternatively, the macropinocytosis observed may be a metabolic stress response because of the hyperactivation of signalling pathways upon FoxO6 overexpression. Hyperactivation of Ras signalling, canonical Wnt and PI3K signalling have all been shown to play roles in inducing macropinocytosis (Overmeyer et al, 2008; Tejeda-Muñoz et al, 2019; Recouvreux & Commisso, 2017).
We believe the observed macropinocytosis phenotype upon Foxo6 overexpression, and the changes in Pak1 expression upon Foxo6 loss or FOXG1 induction provide interesting insights into the function of this underexplored FoxO family member. However, currently we are unable to demonstrate a direct link between these processes and have therefore modified the text to reflect this (see lines 292-4, 330-3, 365-8).
- The manuscript stresses the role of NSC quiescence exit in GBM and demonstrates that FoxG1 KO reduces FoxO6 levels in a murine GBM cell line but a BMP4-mediated quiescence and dox-induced FoxG1 over-expression or an abolishment of cell cycle re-entry thereof by reduced FoxO6 levels in the case of FoxG1 KO is lacking. But this would significantly substantiate the relevance of the findings. *
Mouse GBM cells have elevated levels of FoxG1 and have been shown to be refractory to BMP4-mediated quiescence entry, maintaining colony formation following BMP treatment (Bulstrode et al, 2017). It is therefore challenging to specifically investigate cell cycle re-entry/ quiescence exit using these mouse GBM cells, or indeed any GBM cell line due to their inability to respond fully to BMP cues (Caren et al, 2015). It has also been shown by Bulstrode et al, 2017 that Foxg1 null mouse neural stem cells show an increased propensity to exit cycle in response to BMP treatment, and reduced colony formation on return to EGF/FGF-2 growth factors. FOXG1 null cell lines therefore show a reduced response to BMP cues, making it difficult to explore quiescence exit per se.To navigate this, instead we investigated Dox-induced FOXG1 overexpression in FoxO6 WT and KO mouse NS cells, which display similar quiescence characteristics upon BMP treatment (Figure 4).
- In the introduction and discussion, FoxO6 is mentioned for its oncogenic roles in various cancers but no reference to GBM specifically is cited. It feels like a missed opportunity to not show evidence of this in the IENS cell line that has reduced levels of FoxO6; is there an effect in their proliferative capacity? What are the expression levels of Pak1 following FoxG1 KO in IENS cells? *
Thank you for the helpful suggestion. It is indeed true the literature on FoxO6 in GBM is lacking, explaining the absence of citations on this. On investigation of expression of the proliferation marker Ki67 in these cells we found no significant difference in expression, now shown in Figure 1H. This is in fitting with previous findings of our lab (Bulstrode et al, 2017) which show that FOXG1 is dispensable for the maintenance of continued NSC or GSC proliferation in vitro. We investigated the expression levels of Pak1 following FOXG1 KO in IENS and found a decrease in both KO lines compared to parental cells (updated Figure 6F).
As explained in our discussion, these data suggest that Foxg1/FoxO6/Pak1 are not functionally important in sustaining GSC/NSC proliferation, as shown by the lack of proliferation defects upon Foxg1 or FoxO6 deletion (Bulstrode et al, 2017), but impact regulatory transitions, as cells prepare to exit quiescence into the proliferative radial-glia like state.
*Minor comments *
- Fig1A shows 4 and 2-fold respectively for the two mouse NSC lines, not 17 and 4-fold increase as written on manuscript, please adjust accordingly.
The qRT-PCR data are presented as log2(fold change) or - ddCt, where this value equals zero for the calibrator sample, as indicated in the figure legends and axes. The data are presented in this way to enable accurate visualisation of up- and down-regulation of gene expression. Data are stated as ‘fold increase’ in the text for ease of reading, which we have clarified in the text and figure legends (e.g. lines 154 and 176).
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- Fig2G manuscript reports a 235-fold upregulation, but graph looks more like a 7 or 8-fold as shown on Fig1A for the F6 NSC line. I would recommend checking the fold changes reported throughout the paper. *
See previous comment above. The qRT-PCR data are presented as log2(fold change) or - ddCt, where this value equals zero for the calibrator, as indicated in the figure legends and axes. The data are presented in this way to enable accurate visualisation of up- and down-regulation of gene expression. Data are stated as ‘fold increase’ in the text for ease of reading, which we have clarified in the text and figure legends (e.g. lines 154 and 176).
- The manuscript describes the increase of FOXG1 after BMP4-induced cell cycle exit as compared to non-BMP4 treated cells (p.8 first paragraph), but I am wondering if this expression is rather compared to dox negative and not vs BMP4 negative treatment. *
Data are presented relative to the non-BMP treated (EGF/FGF-2) control throughout the manuscript for consistency. This is to enable changes in expression between -Dox and +Dox to be visualised throughout the quiescence-exit time course relative to the initial starting population in EGF/FGF-2 growth media, prior to BMP treatment.
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- In Fig2G it is interesting that FoxO6 is upregulated in BMP4 treated throughout the experiment with highest values at day10 post treatment. At the same time, non-BMP4 treated cells keep decreasing their FoxO6 levels dramatically but there is no mention or reference to this effect.*
In Figure 2G, all cells have been treated with BMP4, prior to return to growth media (EGF/FGF) with or without Dox. It is true that in the +Dox condition with FOXG1 induction, FoxO6 levels continue to increase up to Day 10, perhaps reflective of the expansion of a highly proliferative radial glia-like population.
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- Fig2 would benefit from a western blot like Fig1D where FoxG1 and FoxO6-HA protein levels are also shown in dox-treated comparing BMP4-treated vs non-treated. *
Due to the lack of specific FoxO6 antibodies and the absence of a FoxO6-HA tag in this cell line, it is not possible to perform protein analysis of FoxO6 levels in this figure as for Figure 1D.
- The colonies in Fig3E should be quantified, as their ability to form neurospheres seems somewhat compromised upon FoxO6 KO. Fig3B and 3F could perhaps be consolidated into one panel in the interest of space and presentation. *
Good suggestion. We have now consolidated Fig 3B and 3F into one panel (now Figure 3F) as suggested by the reviewer. We performed additional replicates for Figure 3E to quantify the colony formation efficiency. This showed a small but insignificant decrease in colony forming ability in the KO cells (Figure 3E). Importantly the FoxO6 null cells do form colonies, and our results show that FoxO6 is not essential for proliferation or colony formation of NSCs in EGF/FGF-2 – this therefore does not account for the complete loss in colony formation we see the in the FoxO6 KO cells upon FOXG1 induction.
- Fig4A shows vs "parental" non-BMP on y axis but wouldn't this show fold change of dox+ parental vs parental. The authors should clarify this. *
All samples in Figure 4A are compared to parental cells in EGF/FGF-2, i.e. non-BMP treated, as the calibrator sample where log2(fold change) equals zero. We chose to set a single calibrator sample for all data (parental and FoxO6 KO cells included) to allow us to compare changes in FOXG1 transgene across the entire experiment.
- Perhaps the authors can add a non-BMP4 treated count of % FOXG1 positive cells to Fig4C for reference. *
As shown in Figure 4A, both parental and FoxO6 KO cells show similar, i.e. negligible, FOXG1 transgene expression without Dox, compared to the parental non-BMP4 treated control, therefore negligible FOXG1-V5 positive cells are seen by ICC. We have edited Figure 4A to include a non-BMP treated and BMP-treated control to show the negligible FOXG1-V5 expression by qPCR as controls.
- The sentence mentioning Fig5D for the first time (p.10 third paragraph) needs rephrasing for clarity and should also call out Fig5C for the mCherry expression live cell imaging data where appropriate. Fig5D does not appear to be live imaging as implied by the text. If vacuole formation is observed already as early as 10-11h after Dox induction, then it should be shown somewhere in Fig5. Vacuole formation is shown with a higher magnification image inset only in the 22h timepoint image. I think Fig5E should be more substantiated with some sort of quantification, e.g. % of vacuoles positive for EEA1 and/or LAMP1. *
We apologise for this. The first reference to Figure 5D one line 234 should refer to Figure 5C, this has now been corrected in the text. Vacuoles are visible in Figure 5C panel 10 h 30 min, however, to make this clearer we have also supplied an accompanying movie of the live imaging (Movie 1). The imaging in Fig 5E has not been quantified as this imaging was performed with the purpose of confirming the vacuole structures seen are not simply enlarged lysosomes, due to their similarity in appearance to those published elsewhere (Ramosaj et al, 2021; Leeman et al, 2018). Instead, we have provided Western blotting data in Figure S5E to support this conclusion that there is no clear increase in EEA1 or LAMP1 (early endosomal or lysosomal) expression upon FoxO6-HA induction.
*- Could the authors comment on the lack of proliferative advantage of the FoxO6 overexpression. FigS3 shows Edu staining, but there is no proliferation assay in either Fig5 or S3. What would be the effect of FoxO6 overexpression on BMP4-mediated quiescence with or without FoxG1 over-expression? *
Induction of FoxO6-HA overexpression does not provide a proliferative advantage to the cells. Looking at individual cells, those with high FoxO6-HA levels seem to associate with EdU negativity. In Figure S3 we provide quantitative EdU incorporation assay as a proliferation assay (quantification of the number of cells cycling, therefore incorporating EdU, within a 24h pulse period). Quantification of the EdU staining in Figure S3G is provided in Figure S3H. We have now clarified this in the text on page 11, lines 263-4.
Unfortunately, due to transgene overexpression using the PiggyBac transposon method, it is not feasible to overexpress FoxO6 and FOXG1 in the same cell line, as re-transfecting cells using the PiggyBac system would potentially alter FOXG1 transgene levels and make results difficult to interpret. Given the association of vacuolated cells with EdU negativity, we predict that FoxO6 overexpression would not give an advantage for quiescence exit. Indeed, BMP-treated cells with FoxO6 overexpression show a decrease in EdU positivity, as shown in Figure S3H. As discussed in the text, we hypothesise that cells with FoxO6 overexpression are in a stalled state, potentially due to signalling hyperactivation. While this may not be physiological, it gives us clues as to the function and downstream targets of FoxO6, which remain uncharacterised.
*- Can the authors clarify if there is a proliferation change in F6 cells in Fig6F as in Fig2F? Fig6F shows Pak1 is already upregulated in quiescent NSCs, what are the expression levels of Pak1 in FoxO6 -/- ANS4 cells upon FoxG1-mediated quiescence exit as shown in Fig4? Is there a particular reason why the F6 cell line data is shown only up to day2 post Dox-induction rather than d4 or d10? For consistency with the rest of similar experimental data this timeline should be extended. Does Pak1 remain elevated, plateaus or keeps reducing further post day2? *
The data is (previous) Figure 6F is the same assay and cell line as presented in Figure 2, but at an early timepoint (Day 2) during the quiescence exit assay. We have provided in the panel qRT-PCR analysis of Ki67 to show that cells begin to show increased proliferation at this timepoint. Due to our hypothesis that Pak1 is required at an early transition point, we decided to analyse this expression at an earlier timepoint than Figure 2. We have also repeated this at D10 (data below), showing Pak1 levels continue to increase with time, along with FoxO6 and the proliferative marker Ki67. Due to technical issues with variable FOXG1 transgene levels we were unable to analyse Pak1 expression levels in FoxO6+/- ANS4 cells upon FOXG1-mediated quiescence exit.
*15 . Reviewer #1 (Significance (Required)): *
The study provides a conceptual advance for exit from stem cell quiescence. There is strong evidence provided for murine neural stem cells, but the link to GBM cancer stem cells is less developed (but perhaps this is the subject of a separate manuscript).
While FoxG1 is a known regulator of neurodevelopment and glioblastoma, the functions of FoxO6 have not been studied in the context of neural stem cells. In my view, this study should be of high interest to audiences in both neurodevelopment and cancer research. * Expertise: glioblastoma, cancer stem cells, neurodevelopment *
We have edited the text and title to clarify that neural stem cells are used here as a model for GSCs with high levels of FOXG1 (e.g. lines 36 and 69).
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
*Major comments: *
-The choice of NSCs as a main experimental model to understand the effects of FoxG1 and FoxO6 is not fully justified. The authors had previously shown that FoxG1 is expressed at very low levels in NSCs (Fig. 1A in Bulstrode et al. 2017). FoxO6 also seems to be barely expressed in NSCs (Fig. 1 of the current manuscript) and, in addition, its levels seem to go further down as cells exit quiescence (-Dox line in Fig. 2H). Therefore, these two genes do not seem to play an important role in the normal exit from quiescence of NSCs, with FoxO6 only affecting FoxG1 overexpression-induced exit from quiescence. * * *If the aim is to mimic a GBM-like state by FoxG1 overexpression, this should be made much clearer in the text, including title and abstract. In that case, the authors should also show a direct comparison of the levels of FoxG1 in GBM and upon Dox-induced overexpression in NSCs. *
We agree with this criticism and suggestion to fix this. It is indeed our aim to mimic a GBM-like state by inducing FOXG1 overexpression and we should have made that more explicit. All experiments are performed in the context of high FOXG1 level. Like Foxg1, FoxO6’s homeostatic roles may be subtle in adulthood, and mostly involved in neural plasticity (Yu et al, 2019). This is in keeping with our finding that basal FoxO6 levels are low in adult NSCs and not required for sustained proliferation but are important for cell state transitions. If the FoxO6 levels activated by elevated FOXG1 represent an acquired dependency of GBM, there may be a therapeutic window to target this pathway. However, given the poorly understood roles of FoxO6, further work is needed to determine its specific value as a therapeutic target. We have modified the title and the text to make this clearer. This is also stated in the first paragraph of the results section on page 7 (line 148).
We have provided below a Western Blot (Bulstrode, 2016) in which FOXG1 levels in F6 cells induced with Dox (1000 ng/ml the dosage used) with the GBM cell lines G7 and G144, and the normal NS cell line U5. This shows that the FOXG1 levels induced are significantly higher than found in normal neural stem cells (mouse or human). This model has been previously used and published in Bulstrode et al, 2017, upon which this manuscript expands.
*-While the authors state that they aim to study NSC quiescence, they use a protocol that is closer to modelling astrocytic differentiation. In fact, in their previous work, they use this very same protocol (removal of growth factors and addition of BMP) to study the role of FoxG1 and Sox2 on astrocyte de-differentiation (Bulstrode et al. 2017). While there is arguably no perfect in vitro model of NSC quiescence, the current standard in the field is treatment with both BMP and FGF for 48 to 72 hours (e.g.: Mira et al., 2010, Martynoga et al., 2013, Knobloch et al., 2017, Leeman et al., 2020). BMP alone is regarded as a pro-astrocytic differentiation cue, and 24 hours might not be enough for NSCs to fully commit to either differentiation or quiescence. Therefore, either the claims in the paper are changed to match the astrocytic differentiation model, or a standard quiescence protocol should be used throughout to confirm the findings also apply to the exit from quiescence of NSCs. *
We agree with the reviewer that there is indeed no perfect in vitro model of NSC quiescence and thank the reviewer for this useful discussion. Coincident with this project, this was an active area of research from our laboratory as explored by Marques-Torrejon et al, 2021 (Nature Comms). After 24 h BMP4 treatment, we found that adult mouse NS cells: exit cell cycle, are growth factor unresponsive, obtain an astrocytic morphology, upregulate astrocytic markers such as Gfap and Aqp4, and downregulate radial glia/NS cell markers such as Nestin and Olig2 (Figure 3).
We therefore initially viewed them as terminally differentiated. However, the exact state of these cells is difficult to define due to the lack of definitive markers and transcriptional differences that can distinguish terminally differentiated GFAP-expressing astrocytes from quiescent type B SVZ NS cells (which also express GFAP) (Bulstrode et al, 2017; Doetsch et al, 1999; Codega et al, 2014). Findings from our laboratory later suggested some NS cell markers are maintained following BMP4 treatment and these cells can be forced back into cycle with combined Wnt/EGF signalling, or FGF/BMP signalling (Marques-Torrejon et al 2021). This suggests in vitro NS cells may lie along a continuous spectrum of states from dormant quiescent, activated quiescent (primed for cell cycle re-entry) to actively proliferating, similar to that observed in vivo in the mouse SVZ (Dulken et al, 2017). Indeed, after 24 h BMP4 treatment, we observe a minimal level of colony formation in no Dox controls following 10 days of exposure to the growth factors EGF/FGF-2 (Figure 2D-F).
These non-cycling BMP4-induced astrocytic cells might therefore be better viewed as dormant quiescent NSCs, hence our reference as quiescent NSCs. The assay conditions used in this manuscript differ to those of Marques-Torrejon et al, in terms of density and length of BMP4 treatment; it is therefore likely that our BMP-treated cells are at different stages along the continuum between dormancy and primed quiescent states. Importantly, regardless of the exact cell type induced by 24 h BMP4 treatment, we have considered the changes induced by FOXG1 overexpression, in comparison to the effect of NS cell media alone.
*-The FoxO6-induced vacuole formation in NSCs is a very interesting finding. However, so far it was only observed upon FoxO6 overexpression. To claim vacuolization is required for quiescence exit, the authors should show whether this phenomenon is also observed upon normal exit from quiescence and FoxG1-induced reactivation of NSCs. From the author's own data, Pak1 (which induces vacuolization) is unlikely to reactivate NSCs, as its expression is highest in BMP-treated cells (Figure 6F). The authors should show whether some vacuolization is present at these stage in NSCs and if not, discuss the possible interplay between Pak1 and FoxO6 in vacuole formation and quiescence exit. *
As detailed in the discussion, we hypothesise that FoxO6- induced macropinocytosis could represent a stalled state, with other pathways downstream of FOXG1 necessary to be activated concomitantly to ensure cell cycle re-entry, e.g., through increased pinocytic flux that cannot be assessed within our experimental timeframes. Indeed, active Pak1 has been found to modulate pinocytic cycling, enhancing both FITC-dextran uptake and efflux (Dharmawardhane et al, 2000). Alternatively, the macropinocytosis observed may be a metabolic stress response because of hyperactivation of signalling pathways upon FoxO6 overexpression Hyperactivation of Ras signalling, canonical Wnt and PI3K signalling have all been shown to play roles in inducing macropinocytosis (Overmeyer et al, 2008; Tejeda-Muñoz et al, 2019; Recouvreux & Commisso, 2017).
We do not see clear evidence of vacuoles in FOXG1-induced reactivation of NSCs – this supports that the macropinocytosis seen upon FoxO6 overexpression is a stalled state or due to hyperactivation. While this may not be physical, it gives us clues as to the function and downstream targets of FoxO6, which remain uncharacterised (such as a link of FoxO6 and FOXG1 with Pak1-related pathways). Demonstrating a requirement for vacuolisation in quiescence exit is outwidth this manuscript and therefore we are careful not to claim this. We have modified the text to clarify this.
As the reviewer noted, it is interesting that Pak1 is highest in BMP-treated cells; it seems that BMP signalling itself is triggering elevated Pak1 levels, likely as cells undergo extensive cell shape changes during the transition from proliferation to quiescence. However, in EGF/FGF-2, Pak1 levels decrease, and our data suggests that FOXG1/FoxO6 are required to increase or maintain Pak1, potentially to again enable the cell shape/metabolic changes required on quiescence exit. We have added to the text to expand upon this observation on page 14 (lines 330-333). -Finally, the data on the regulation of Pak1 expression by FoxO6 is insufficient to draw any strong conclusions. Downregulation of Pak1 in FoxO6 cells is not enough evidence to claim a direct regulation. The authors should show whether Pak1 levels are increased after FoxO6 overexpression and whether FoxG1 is downregulated in FoxO6 KO NSCs (indirectly affecting Pak1 expression).
We have performed qRT-PCR analysis of Foxg1 expression in FoxO6 KO NSCs and see no consistent difference in expression, indicating this is not indirectly affecting Pak1 expression (see below, 1). We have also investigated Pak1 levels upon FoxO6 overexpression, over a time course following Dox addition (see below, 2). Interestingly, when FoxO6 is overexpressed, Pak1 is not clearly upregulated at any time-point. It may be that as Pak1 is already expressed in the -Dox controls, due to its roles in a variety of cellular functions, that the levels are saturated already. It is clear that Pak1 expression decreases upon FoxO6 loss in EGF/FGF (without coincident Foxg1 downregulation) and in F6 cells, higher FOXG1 correlates with higher Pak1 in EGF/FGF. Together with the induction of macropinocytosis upon FoxO6 overexpression, these data provide interesting insights into the potential pathways downstream of Foxo6 in controlling quiescence exit, directly or indirectly related to Pak1 signalling. We have modified the text to reflect this on page 14 (lines 330-333).
Minor comments: * Please state in the main text that NSCs are derived from the SVZ. *
This has been added to the text on page 7 (line 149) and is in the methods ‘Cell Culture’ section.
Reviewer #2 (Significance (Required)):
As I said before, I find this work tackles a very important question, how is the exit from quiescence controlled in NSCs. This manuscript will be of interest to researchers in the fields of adult stem cell biology and adult neurogenesis. While my expertise lies mostly on NSC biology, this work is of potential great interest for the cancer field, particularly for brain cancer research. Elucidating the mechanisms GBM cells use to exit quiescence is crucial in order to avoid the relapse of this aggressive form of brain cancer. To increase the relevance of the work to the cancer community, some of the key findings should be reproduced with GBM cells. It would be particularly important to show whether Pak1 induced vacuolization and macropinocytosis can be observed in GBM cells.
As detailed in the discussion, we hypothesise that FoxO6- induced macropinocytosis could represent a stalled state, with other pathways downstream of FOXG1 necessary to be activated concomitantly to ensure cell cycle re-entry, e.g., through increased pinocytic flux that cannot be assessed within our experimental timeframes. Alternatively, the macropinocytosis observed may be a metabolic stress response because of hyperactivation of signalling pathways upon FoxO6 overexpression Hyperactivation of Ras signalling, canonical Wnt and PI3K signalling have all been shown to play roles in inducing macropinocytosis (Overmeyer et al, 2008; Tejeda-Muñoz et al, 2019; Recouvreux & Commisso, 2017). We do not see clear evidence of vacuoles in FOXG1-indued reactivation of NSCs– this supports that the macropinocytosis seen upon FoxO6 overexpression is a stalled state or due to hyperactivation. We do not therefore think macropinocytosis per se would be observed in quiescence exit of GBM cells – indeed a normal form of macropinocytosis-induced cell death called methuosis has been observed in GBM cells with hyperactivated Ras signalling (Overmeyer et al, 2008). However, this phenotype still gives us clues as to the function of FoxO6 in quiescence exit in GSCs and the downstream signalling pathways it may regulate, such as Pak1-related signalling (discussed on lines 330-3 and 366-9).
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
Summary: * The overall objective of the paper is to investigate the mechanisms by which co-option of the activity of developmental master lineage regulators by cancer cells allows them to gain fitness. To answer this question, they focus on FOXG1. This TF acts during the specification of the telecephalon. Its expression can be increased in Glioblastoma (GBM) and, more importantly for the paper, FOXG1 has previously been shown to promote exit from quiescence of glioblastoma stem cells (GSCs) and non-transformed neural stem cells (NSCs). In a previous screen, the authors identified FoxO6 as a potential direct target gene of FOXG1. In this paper, they showed that with the gain of expression for FOXG1 in NSCs and loss of FOXG1 in GSCs, FoxO6 is increased or decreased, respectively. Loss of FoxO6 in NSCs does not alter their cell cycle or cell shape and specification. Yet, loss of FoxO6 in NSCs blocks FOXG1-mediated exit from quiescence. To understand the mechanisms, they decided to overexpress FoxO6 in NSCs and demonstrated that the cells undergo macropinocytosis, a process by which cells can engulf large amount of nutriments from the external medium. It remains to be determined whether this macropinocytosis occurs in cells overexpressing FOXG1 and GSCs. The authors provide a first answer by showing that overexpression of FOXG1 induces not only FoxO6 but also the expression of PAK1, one of the key kinases that regulates the membrane engulfment of macropinocytosis in NSCs. In GSC lines, the decrease of FOXO6 decreases PAK1 levels. *
Major comments: * The paper describes interesting and convincing results (number of cell lines, repeated experiments seems sufficient) but it is difficult to reconcile them all in a single model, and this diminishes the impact of the study. Epistatic interactions between FoxG1, FoxO6, PAK1 and macropinocytosis are not always studied in the same cell models. Whether FOXG1-induced exit from quiescence of NSCs is dependent on a FOXG1-->FOXO6-->PAK1-->Macropinocytosis axis remains to be demonstrated. Also does such an axis operate in tumor cells remains to be fully assessed? In particular, if FoxO6 overexpression in NSCs can induce macropinocytosis, is this cellular process induced by FoxO6 downstream of FOXG1 activity during NSC quiescence exit? Is PAK1 a relay of FoxO6? Experiments looking at macropinocytosis and the involvement of PAK1 in the cell models of Figure 4 will definitely help to bridge the different results all together. *
We thank the reviewer for this useful insight and discussion for future work.
To directly investigate the effects of Pak1 ablation, and therefore more directly the link between FOXG1 and FoxO6 and macropinocytosis, we tested the published Pak1 inhibitor IPA-3. Unfortunately, to distinguish the role of Pak1 in quiescence exit and macropinocytosis, we would need a dosage of IPA-3 that is efficacious but does not affect cell proliferation. It was not possible to optimise such a dosage (a dosage of 10uM is shown to be efficacious at inhibiting Pak1 (Verma et al, 2020; Wong et al, 2013) however even at 2.5uM we see significant cell death in our cells. Indeed, this is potentially due to the variety of cellular functions Pak1 is involved in. Conversely, it is not feasible to overexpress Pak1 in the FoxO6 KO cells with inducible FOXG1. To ensure we are investigating quiescence exit this would need to be in an inducible manner; however, re-transfecting cells using the PiggyBac system would potentially alter FOXG1 transgene levels (through excision of the existing transgene) and therefore make results difficult to interpret.
We hypothesise that FoxO6- induced macropinocytosis could represent a stalled state, with other pathways downstream of FOXG1 necessary to be activated concomitantly to ensure cell cycle re-entry, e.g., through increased pinocytic flux that cannot be assessed within our experimental timeframes (as detailed in the text discussion). Alternatively, the macropinocytosis observed may be a metabolic stress response because of hyperactivation of signalling pathways upon FoxO6 overexpression Hyperactivation of Ras signalling, canonical Wnt and PI3K signalling have all been shown to play roles in inducing macropinocytosis (Overmeyer et al, 2008; Tejeda-Muñoz et al, 2019; Recouvreux & Commisso, 2017). We do not see clear evidence of vacuoles in FOXG1-induced reactivation of NSCs– this supports that the macropinocytosis seen upon FoxO6 overexpression is a stalled state or due to hyperactivation and therefore not a physiological process in quiescence exit. We do not therefore think macropinocytosis per se would be observed in quiescence exit of GBM cells – indeed a normal form of macropinocytosis-induced cell death called methuosis has been observed in GBM cells with hyperactivated Ras signalling (Overmeyer et al, 2008).
However, we believe the observed macropinocytosis phenotype upon Foxo6 overexpression, and the changes in Pak1 expression upon Foxo6 loss or FOXG1 induction provide interesting insights into the function of this underexplored FoxO family member, in GSCs and the downstream signalling pathways it may control, such as Pak1-related signalling. We have modified the text to reflect the limitations of our current data and discuss this (lines 330-3 and 366-9).
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www.reddit.com www.reddit.comMemes?1
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This might be a weird question, but does anyone keep memes in your ZK? I'm realizing I download a lot of memes that I particularly appreciate -- but then I usually can't fnd them again if I want them. Anyone have a method for this?
I only have a few very specific memes indexed in my box: https://boffosocko.com/tag/zettelkasten-memes/ and a few more at https://hypothes.is/users/chrisaldrich?q=zettelkasten+meme
Historically, Aby Warburg had a large image-based zettelkasten for his work on art which predated Richard Dawkins' conception of meme, but I think qualifies. See: https://boffosocko.com/tag/aby-warburg/ or his Bilderatlas Mnemosyne project: https://warburg.sas.ac.uk/archive/bilderatlas-mnemosyne
It's digital in nature, but Shawn Gilmore has a large collection of images of string walls, Anacapa charts, walls and floors littered with paperwork by obsessives, etc. for his cultural research. It also includes some popular memes. https://www.vaultofculture.com/nst
replyy to u/a2jc4life at https://www.reddit.com/r/Zettelkasten/comments/1ddhn9n/memes/
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www.biorxiv.org www.biorxiv.org
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Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
In this manuscript, Eaton et al. examine the regulation of transcription directionality using a powerful genomic approach (more about the methodology below). Their data challenge the notion that the polyadenylation signal-reading Cleavage and Polyadenylation (CPA) complex is responsible for controlling promoter directionality by terminating antisense transcription. Namely, depletion of the required CPA factor RBBP6 has little effect on antisense transcription measured by POINT. They find instead that initiation is intrinsically preferential in the sense direction and additionally maintained by the activities of an alternative processing complex called Integrator, together with the kinase CDK9. In the presence of CDK9 activity, depletion of Integrator endoribonuclease INTS11 leads to globally increased transcription in the antisense direction, and minor effects in the sense direction. However, CDK9 inhibition reveals that sense transcription is also sensitive to INS11 depletion. The authors suggest that CDK9 activity is stronger in the sense direction, preventing INTS11-mediated premature termination of sense transcrpts.
Strengths:
The combination of acute depletion of the studied factors using degron approaches (important to limit possible secondary effects), together with novel and very sensitive nascent transcriptomics methods POINT and sPOINT is very powerful. The applied spike-in normalization means the analysis is more rigorous than most. Using this methodology allowed the authors to revisit the interesting question of how promoter/transcription directionality is determined.
The data quality appears very good and the fact that both global analysis as well as numerous gene-specific examples are shown makes it convincing.
The manuscript is well written and hence a pleasure to read.
We appreciate this positive assessment.
Weaknesses:
I am slightly worried about the reproducibility of the data - it is unclear to me from the manuscript if and which experiments were performed in replicate (lack of table with genomic experiments and GEO access, mentioned in more detail in below recommendations to authors), and the methods could be more detailed.
All sequencing data was deposited with GEO. Multiple biological replicates were performed for each sequencing experiment. Bigwig files are presented as a table in the GEO submissions. This data has now been made public.
A separate discussion section would be useful, particularly since the data provided challenge some concepts in the field. How do the authors interpret U1 data from the Dreyfuss lab in light of their results? How about the known PAS-density directionality bias (more PAS present in antisense direction than in sense) - could the differential PAS density be still relevant to transcription directionality?
As suggested, we have expanded our discussion to relate our findings to existing data. We think the results from the Dreyfuss lab are very important and highlight the role of U1 snRNA in enforcing transcriptional elongation. It does this in part by shielding PAS sequences. Recent work from our lab also shows that U1 snRNA opposes the Restrictor complex and PNUTS, which otherwise suppress transcription (Estell et al., Mol Cell 2023). Most recently, the Adelman lab has demonstrated that U1 snRNA generally enhances transcription elongation (Mimoso and Adelman., Mol Cell 2023). Our work does not challenge and is not inconsistent with these studies.
The role of U1 in opposing PAS-dependent termination inspired the idea that antisense transcriptional termination may utilise PASs. This was because such regions are rich in AAUAAA and comparatively poor in U1 binding sites. However, our RBBP6 depletion and POINT-seq data suggest that PAS-dependent termination is uncommon in the antisense direction. As such, other mechanisms suppress antisense transcription and influence promoter directionality. In our paper, we propose a major role for the Integrator complex.
We do not completely rule out antisense PAS activity and discuss the prior work that identified polyadenylated antisense transcripts. Nevertheless, this was detected by oligo-dT primed RT-PCR/Northern blotting, which cannot determine the fraction of non-polyadenylated RNA that could result from PAS-independent termination (e.g. by Integrator). To do that requires an analysis of total nascent transcription as achieved by our POINT-seq. Based on these experiments, Integrator depletion has a greater impact on antisense transcription than RBBP6 depletion.
I find that the provided evidence for promoter directionality to be for the most part due to preferential initiation in the sense direction should be stressed more. This is in my eyes the strongest effect and is somehow brushed under the rug.
We agree that this is an important finding and incorporated it into the title and abstract. As the reviewer recommends, we now highlight it further in the new discussion.
References 12-17 report an effect of Integrator on 5' of protein-coding genes, while data in Figure 2 appears contradictory. Then, experiments in Figure 4 show a global effect of INST11 depletion on promoter-proximal sense transcription. In my opinion, data from the 2.5h time-point of depletion should be shown alongside 1.5h in Figure 2 so that it is clear that the authors found an effect similar to the above references. I find the current presentation somehow misleading.
We are grateful for this suggestion and present new analyses demonstrating that our experiment in Figure 2 concurs with previous findings (Supplemental Figures 2A and B). Our original heatmap (Figure 2E) shows a very strong and general antisense effect of INTS11 loss. On the same scale, the effects in the sense direction are not as apparent, which is also the case using metaplots. New supplemental figure 2A now shows sense transcription from this experiment in isolation and on a lower scale, demonstrating that a subset of genes shows promoter-proximal increases in transcription following INTS11 depletion. This is smaller and less general than the antisense effect but consistent with previous findings. Indeed, our new analysis in supplemental figure 2B shows that affected protein-coding genes are lowly expressed, in line with Hu et al., Mol Cell 2023. This explains why a sense effect is not as apparent by metaplot, for which highly expressed genes contribute the most signal.
As a result of our analyses, we are confident that the apparently larger effect at the 2.5hr timepoint (Figure 4) that we initially reported is due to experimental variability and not greater effects of extended INTS11 depletion. Overlaying the 1.5h and 2.5h datasets (Supplemental Figure 4B) revealed a similar number of affected protein-coding genes with a strong (83%) overlap between the affected genes. To support this, we performed qPCR on four affected protein-coding transcripts which revealed no significant difference in the level of INTS11 effect after 2.5h vs 1.5h (Supplemental Figure 4C).
We now present data for merged replicates in Figures 2 and 4 which reveal very similar average profiles for -INTS11 vs +INTS11 at both timepoints. Overall, we believe that we have resolved this discrepancy by showing that it amounts to experimental variability and because the most acutely affected protein-coding genes are lowly expressed. As detailed above, we show this in multiple ways (and validate by qPCR) We have revised the text accordingly and removed our original speculation that differences reflected the timeframe of INTS11 loss.
Conclusion/assessment:
This important work substantially advances our understanding of the mechanisms governing the directionality of human promoters. The evidence supporting the claims of the authors is compelling, with among others the use of advanced nascent transcriptomics including spike-in normalization controls and acute protein depletion using degron approaches.
In my opinion, the authors' conclusions are in general well supported.
Not only the manuscript but also the data generated will be useful to the wide community of researchers studying transcriptional regulation. Also, the POINT-derived novel sPOINT method described here is very valuable and can positively impact work in the field.
We are grateful for the reviewers' positive assessment of our study.
Reviewer #2 (Public Review):
Summary:
Eaton and colleagues use targeted protein degradation coupled with nascent transcription mapping to highlight a role for the integrator component INST11 in terminating antisense transcription. They find that upon inhibition of CDK9, INST11 can terminate both antisense and sense transcription - leading to a model whereby INST11 can terminate antisense transcription and the activity of CDK9 protects sense transcription from INST11-mediated termination. They further develop a new method called sPOINT which selectively amplifies nascent 5' capped RNAs and find that transcription initiation is more efficient in the sense direction than in the antisense direction. This is an excellent paper that uses elegant experimental design and innovative technologies to uncover a novel regulatory step in the control of transcriptional directionality.
Strengths:
One of the major strengths of this work is that the authors endogenously tag two of their proteins of interest - RBBP6 and INST11. This tag allows them to rapidly degrade these proteins - increasing the likelihood that any effects they see are primary effects of protein depletion rather than secondary effects. Another strength of this work is that the authors immunoprecipitate RNAPII and sequence extracted full-length RNA (POINT-seq) allowing them to map nascent transcription. A technical advance from this work is the development of sPOINT which allows the selective amplification of 5' capped RNAs < 150 nucleotides, allowing the direction of transcription initiation to be resolved.
We appreciate this positive assessment.
Weaknesses:
While the authors provide strong evidence that INST11 and CDK9 play important roles in determining promoter directionality, their data suggests that when INST11 is degraded and CDK9 is inhibited there remains a bias in favour of sense transcription (Figures 4B and C). This suggests that there are other unknown factors that promote sense transcription over antisense transcription and future work could look to identify these.
We agree that other (so far, unknown) factors promote sense transcription over antisense, which was demonstrated by our short POINT. We have provided an expanded discussion on this in the revision. In our opinion, demonstrating that sense transcription is driven by preferential initiation in that direction is a key finding and we agree that the identification of the underlying mechanism constitutes an interesting avenue for future study.
Reviewer #3 (Public Review):
Summary:
Using a protein degradation approach, Eaton et al show that INST11 can terminate the sense and anti-sense transcription but higher activity of CDK9 in the sense direction protects it from INS11-dependent termination. They developed sPOINT-seq that detects nascent 5'-capped RNA. The technique allowed them to reveal robust transcription initiation of sense-RNA as compared to anti-sense.
Strengths:
The strength of the paper is the acute degradation of proteins, eliminating the off-target effects. Further, the paper uses elegant approaches such as POINT and sPOINT-seq to measure nascent RNA and 5'-capped short RNA. Together, the combination of these three allowed the authors to make clean interpretations of data.
We appreciate this positive assessment.
Weaknesses:
While the manuscript is well written, the details on the panel are not sufficient. The methods could be elaborated to aid understanding. Additional discussion on how the authors' findings contradict the existing model of anti-sense transcription termination should be added.
We have added more detail to the figure panels, which we hope will help readers to navigate the paper more easily. Specifically, the assay employed for each experiment is indicated in each figure panel. As requested, we provide a new and separate discussion section in the revision.
Recommendations for the authors:
Reviewer #1 (Recommendations For The Authors):
Congratulations on this important piece of work!
Some specific suggestions.
MAJOR
-The data are not available (Accession "GSE243266" is currently private and is scheduled to be released on Sep 01, 2026.) This should be corrected and as a minimum, the raw sequencing files as well as the spike-in scaled bigwig files should be provided in GEO.
We have made the data public. Raw and bigwig files are provided as part of the GEO upload.
MINOR
- It would be useful for readers if you could include catalog numbers of the reagents used in the study.
We have included this information in our revision.
- A table in experimental procedures summarizing the genomic experiments performed in this study as well as published ones reanalyzed here would be helpful.
This is now provided as part of the resources table.
- It would be easier for reviewers to evaluate the manuscript if the figure legends were included together with the figures on one page. This is now allowed by most journals.
We have used this formatting in the revision.
- Providing some captions for the results sections would be helpful.
We have included subheadings as suggested.
Reviewer #2 (Recommendations For The Authors):
Generally, I would suggest writing the experiment-type above panels where it is not immediately obvious what they are so a reader can appreciate the figures without referencing the legend. E.g. write POINT-seq on Figure 1B just to make it obvious to someone looking at the figures what methodology they are looking at. Likewise, you could write RNAPII ChIP-seq for Supplementary Figures 3D and 3E.
We have carried out this recommendation.
Can a y-axis be indicated on POINT-seq genome browser tracks? This could make them easier to interpret.
Y-axis scales are provided as RPKM as stated in the figure legends.
The authors could address/speculate in the text why there is less POINT-seq signal for the antisense transcript in the treatment condition in Figure 1B? Or could consider including a different example locus where this is not the case for clarity.
Acute depletion of poly(A) factors (like RBBP6) results in a strong read-through beyond the poly(A) signal of protein-coding genes as Figure 1 shows. However, it also causes a reduction in transcription levels, which can be seen in the figure and is correctly noted by the reviewer in this comment. We see this with other poly(A) factor depletions (e.g. CPSF73 and CPSF30 – Eaton et al., 2020 and Estell et al., 2021) and other labs have observed this too (e.g for CPSF73-dTAG depletion (Cugusi et al., Mol Cell 2022)). Plausible reasons include a limited pool of free RNAPII due to impaired transcriptional termination or limited nucleotide availability due to their incorporation within long read-through transcripts. For these reasons, we have retained the example in Figure 1B as a typical representation of the effect. Moreover, the heatmap in Figure 1D fairly represents the spectrum of effects following RBBP6 loss – highlighting the strong read-through beyond poly(A) signals and the marginal antisense effects.
"The established effect of INTS11 at snRNAs was detected in our POINT-seq data and demonstrates the efficacy of this approach (Figure 2B)." The authors could explain this point more clearly in the text and describe the data - e.g. As expected, depletion of INTS11 leads to increased POINT-seq signal at the 3' end of snRNAs, consistent with defects in transcriptional termination. This is highlighted by the RNU5A-1 and RNU5B-1 loci (Figure 2B).
We agree and have added more context to clarify this.
I would suggest adjusting the scale of the heatmap in Figure 2E - I think it would be easier to interpret if the value of 0 was white - with >0 a gradient of orange and <0 a gradient of blue (as is done in Figure 1C). I think making this change would make the point as written in the text clearer i.e. "heatmap analysis demonstrates the dominant impact of INTS11 on antisense versus sense transcription at most promoters (Figure 2E)." I'm assuming most of the sense transcription would be white (more clearly unchanging) when the scale is adjusted.
We agree and have done this. The reviewer is correct that most sense transcription is unchanged by INTS11 loss. However, as we alluded to in the original submission, a subset of transcripts shows a promoter-proximal increase after INTS11 depletion. We have expanded the analyses of this effect (see responses to other comments) but stress that it is neither as general nor as large as the antisense effect.
The authors make the point that there is mildly increased transcription over the 5' end of some genes upon INST11 depletion and show a track (Supplementary Fig 2A). It is not immediately obvious from the presentation of the meta-analysis in Figure 2D how generalisable this statement is. Perhaps the size of the panel or thickness of the lines in Figure 2D could be adjusted so that the peak of the control (in blue) could be seen. Perhaps an arrow indicating the peak could be added? I'm assuming the peak at the TSS is slightly lower in the control compared to INST11 depletion based on the authors' statement.
We have provided multiple new analyses of this data to highlight where there are promoter-proximal effects of INTS11 loss in the sense direction. Please see our response to the public review of reviewer 1 and new supplemental figures 2A, 2B, 4A and 4B which highlight the sense transcription increased in the absence of INTS11.
The authors label Figure 4 "Promoters lose their directionality when CDK9 is inhibited" - but in INST11 depleted cells treated with CDK9i they find that there still is a bias towards sense transcription. Suggested edit "Some promoter directionality is lost when CDK9 is inhibited" or similar.
We agree and have made this change.
The authors conclude that INTS11-mediated effects are the result of perturbation of the catalytic activities of Integrator, the authors should perform rescue experiments with the catalytically dead E203Q-INTS11 mutant.
This is a very good suggestion and something we had intended to pursue. However, as we will describe below (and shown in Supplemental Figure 4G), there were confounding issues with this experiment.
The E203Q mutant of INTS11 is widely used in the literature to test for catalytic functions of INTS11. However, we have found that this mutation impairs the ability of INTS11 to bind other Integrator modules in cells. Based on co-immunoprecipitation of flag-tagged WT and E203Q derivatives, INTS1 (backbone module), 10 (tail module), and 8 (phosphatase module) all show reduced binding to E203Q vs. WT. Because E203Q INTS11 is defective in forming Integrator complexes, rescue experiments might not fully distinguish the effects of INTS11 activity from those caused by defects in complex assembly. While this may at first seem unexpected, in the analogous 3’ end processing complex, catalytic mutants of CPSF73 (which is highly related to INTS11) negatively affect its interaction with other complex members (Kolev and Steitz, EMBO Reports 2005).
We hypothesise that INTS11 activity is most likely involved in attenuating promoter-proximal transcription, but we cannot formally rule out other explanations and discuss this in our revision. Regardless of how INTS11 attenuates transcription, our main conclusion is on its requirement to terminate antisense transcription whether this involves its cleavage activity or not.
The authors suggest that CDK9 modulates INTS11 activity/assembly and suggest this may be related to SPT5. Is there an effect of CDK9 inhibition on the snRNA's highlighted in Figure 2B?
We believe that snRNAs are different from protein-coding genes concerning CDK9 function. Shona Murphy’s lab previously showed that, unlike protein-coding genes, snRNA transcription is insensitive to CDK9 inhibition, and that snRNA processing is impaired by CDK9 inhibition (Medlin et al., EMBO 2003 and EMBO 2005). We reproduce these findings by metaanalysis of 15 highly expressed and well-separated snRNAs and by qRT-PCR of unprocessed RNU1-1, RNU5A-1 and RNU7-1 snRNA following CDK9 inhibition. We observe snRNA read-through by POINT-seq following INTS11 loss whether CDK9 is inhibited or not (left panel, below). Note the higher TES proximal signal in CDK9i conditions, which likely reflects the accumulation of unprocessed snRNA as validated by qPCR for three example snRNAs (right panel, below).
Author response image 1.
For Figure 4, would similar results be observed using inhibitors targeting other transcriptional CDKs such as CDK7,12/13?
In response to this suggestion, we analysed four selected protein-coding transcripts (the same 4 that we used to validate the CDK9i results) by qRT-PCR in a background of CDK7 inhibition using the THZ2 compound (new Supplemental Figure 4E). THZ2 suppresses transcription from these genes as expected. Interestingly, expression is restored by co-depleting Integrator, recapitulating our findings with CDK9 inhibition. As CDK7 is the CDK-activating kinase for CDK9, its inhibition will also inhibit CDK9 so THZ2 may simply hit this pathway upstream of where CDK9 inhibitors. Second, CDK7 may independently shield transcription from INTS11. We allude to both interesting possibilities.
What happens to the phosphorylation state of anti-sense engaged RNAPII when INTS11 is acutely depleted and/or CDK9 is inhibited? This could be measured by including Ser5 and Ser2 antibodies in the sPOINT-seq assay and complemented with Western Blot analysis.
We have performed the western blot for Ser5 and Ser2 phosphorylation as suggested. Both signals are mildly enhanced by INTS11 loss, which is consistent with generally increased transcription. Ser2p is strongly reduced by CDK9 inhibition, which is consistent with the loss of nascent transcription in this condition. Interestingly, both modifications are partly recovered when INTS11 is depleted in conjunction with CDK9 inhibition. This is consistent with the effects that we see on POINT-seq and shows that the recovered transcription is associated with some phosphorylation of RNAPII CTD. This presumably reflects the action(s) of kinases that can act redundantly with CDK9.
We have not performed POINT-seq with Ser5p and Ser2p antibodies under these various conditions. Our rationale is that our existing data uses an antibody that captures all RNAPII (regardless of its phosphorylation status), which we feel most comprehensively assays transcription in either direction. Moreover, the lab of Fei Chen (Hu et al., Mol Cell 2023) recently published Ser5p and Ser2p ChIP-seq following INTS11 loss. By ChIP-seq, they observe a bigger increase in antisense RNAPII occupancy vs. sense providing independent and orthogonal support for our POINT-seq data. Interestingly, this antisense increase is not paralleled by proportional increases in Ser5p or Ser2p signals. This suggests that the unattenuated antisense transcription resulting from INTS11 loss does not have high Ser5p or Ser2p. Since CDK7 and 9 are major Ser5 and 2 kinases, this supports our model that their activity is less prevalent for antisense transcription. We now discuss these data in our revision.
The HIV reporter RNA experiments should be performed with the CDK9 inhibitor added to the experimental conditions. Presumably CDK9 inhibition would result in no upregulation of the reporter upon addition of TAT and/or dTAG. Perhaps the amount of TAT should be reduced to still have a dynamic window in which changes can be detected. It is possible that reporter activation is simply at a maximum. Can anti-sense transcription be measured from the reporter?
We have performed the requested CDK9 inhibitor experiment to confirm that TAT-activated transcription from the HIV promoter is CDK9-dependent (new supplemental figure 4F). Consistent with previous literature on HIV transcription, CDK9 inhibition attenuates TAT-activated transcription. Importantly, and in line with our other experiments, depletion of INTS11 results in significant restoration of transcription from the HIV promoter when CDK9 is inhibited. Thus, TAT-activated transcription is CDK9-dependent and, as for endogenous genes, CDK9 prevents attenuation by INTS11.
While TAT-activated transcription is high, we do not think that the plasmid is saturated. When considering this question, we revisited previous experiments using this system to study RNA processing (Dye et al., Mol Cell 1999, Cell 2001, Mol Cell 2006). In these cases, mutations in splice sites or polyadenylation sites have a strong effect on RNA processing and transcription around HIV reporter plasmids. Effects on transcription and RNA processing are; therefore, apparent in the appropriate context. In contrast, we find that the complete elimination of INTS11 has no impact on RNA output from the HIV reporter. Our original experiment assessing the impact of INTS11 loss in +TAT conditions used total RNA. One possibility is that this allows non-nascent RNA to accumulate which might confound our interpretation of INTS11 effects on ongoing transcription. However, the new experiment described in the paragraph above was performed on chromatin-associated (nascent) RNA to rule this out. This again shows no impact of INTS11 loss on HIV promoter-derived transcription in the presence of TAT.
To our knowledge, antisense transcription is not routinely assayed from plasmids. They generally employ very strong promoters (e.g. CMV, HIV) to drive sense transcription. Crucially, their circular nature means that RNAPII going around the plasmid could interfere with antisense transcription coming the other way which does not happen in a linear genomic context. This is why we restricted our use of plasmids to looking at the effects of stimulated CDK9 recruitment (via TAT) on transcription rather than promoter directionality.
The authors should clearly state how many replicates were performed for the genomics experiments. Ideally, a signal should be quantified and compared statistically rather than relying on average profiles only.
We have stated the replicate numbers for sequencing experiments in the relevant figure legends. All sequencing experiments were performed in at least two biological replicates, but often three. In addition, we validated their key conclusions by qPCR or with orthogonal sequencing approaches.
Reviewer #3 (Recommendations For The Authors):
The authors provide strong evidence in support of their claims.
ChIP-seq of pol2S5 and S2 upon INST11 and CDK9 inhibition will strengthen the observation that transcription in the sense direction is more efficient.
We view the analysis of total RNAPII as the most unbiased way of establishing how much RNAPII is going one way or the other. Importantly, ChIP-seq was very recently performed for Ser2p and Ser5p RNAPII derivatives in the lab of Fei Chen (Hu et al., Mol Cell 2023). Their data shows that loss of INTS11 increases the occupancy of total RNAPII in the antisense direction more than in the sense direction, which is consistent with our finding. Interestingly, the increased antisense RNAPII was not paralleled with an increase in Ser2p or Ser5p. This suggests that, following INTS11 loss, the unattenuated antisense transcription is not associated with full/normal Ser2p or Ser5p. These modifications are normally established by CDK7 and 9; therefore, this published ChIP-seq suggests that they are not fully active on antisense transcription when INTS11 is lost. This supports our overall model that CDK9 (and potentially CDK7 as suggested for a small number of genes in new Supplemental Figure 4E) is more active in the sense direction to prevent INTS11-dependent attenuation. We now discuss these data in our revision.
In Supplementary Figure 2, the eRNA expression increases upon INST11 degradation, I wonder if the effects of this will be appreciated on cognate promoters? Can the authors test some enhancer:promoter pairs?
We noticed that some genes (e.g. MYC) that are regulated by enhancers show reduced transcription in the absence of INTS11. Whilst this could suggest a correlation, the transcription of other genes (e.g. ACTB and GAPDH) is also reduced by INTS11 loss although they are not regulated by enhancers. A detailed and extensive analysis would be required to establish any link between INTS11-regulated enhancer transcription and the transcription of genes from their cognate promoters. We agree that this would be interesting, but it seems beyond the scope of our short report on promoter directionality.
Line 111, meta plot was done of 1316 genes. Details on this number should be provided. Overall, the details of methods and analysis need improvement. The layout of panels and labelling on graphs can be improved.
We have now explained the 1316 gene set. In essence, these are the genes separated from an expressed neighbour by at least 10kb. This distance was selected because depletion of RBBP6 induces extensive read-through transcription beyond the polyadenylation site of protein-coding genes. To avoid including genes affected by transcriptional read-through from nearby transcription units we selected those with a 10kb gap between them. This was the only selection criteria so is unlikely to induce any unintended biases. Finally, we have added more information to the figure panels and their legends, which we hope will make our manuscript more accessible.
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Reviewer #2 (Public Review):
Summary:
Eaton and colleagues use targeted protein degradation coupled with nascent transcription mapping to highlight a role for the integrator component INST11 in terminating antisense transcription. They find that upon inhibition of CDK9, INST11 can terminate both antisense and sense transcription - leading to a model whereby INST11 can terminate antisense transcription and the activity of CDK9 protects sense transcription from INST11-mediated termination. They further develop a new method called sPOINT which selectively amplifies nascent 5' capped RNAs and find that transcription initiation is more efficient in the sense direction than in the antisense direction. This is an excellent paper which uses elegant experimental design and innovative technologies to uncover a novel regulatory step in the control of transcriptional directionality.
Strengths:
One of the major strengths of this work is that the authors endogenously tag two of their proteins of interest - RBBP6 and INST11. This tag allows them to rapidly degrade these proteins - increasing the likelihood that any effects they see are primary effects of protein depletion rather than secondary effects. Another strength of this work is that the authors immunoprecipitate RNAPII and sequence extracted full length RNA (POINT-seq) allowing them to map nascent transcription. A technical advance from this work is the development of sPOINT which allows the selective amplification of 5' capped RNAs < 150 nucleotides, allowing the direction of transcription initiation to be resolved.
Weaknesses:
While the authors provide strong evidence that INST11 and CDK9 play important roles in determining promoter directionality, their data suggests that when INST11 is degraded and CDK9 is inhibited there remains a bias in favour of sense transcription (Figure 4B and C). This suggests that there are other unknown factors that promote sense transcription over antisense transcription and future work could look to identify these.
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Reply to the reviewers
We would like to thank all reviewers for their detailed and constructive feedback, which substantially helped improve the manuscript. We apologise for the time taken for the revisions, which was partially due to the first author (successfully) writing and defending her PhD thesis in the same time frame. We would like to point out already here that, based on reviewers' feedback, main figure 6 is completely redone and the conclusions of this figure have changed substantially. We no longer suggest RNA chaperoning activity (it was identified as being due to the high concentration of TEV protease, in a control suggested by the reviewers). Instead, our refined assay conditions with lower TEV protease concentration identified ribonuclease activity of membrane-bound full-length 2C, which is consistent with a publication from 2022 (PMID: 35947700).
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
Evidence, reproducibility, and clarity
Summary:
In this study by Shankar and colleagues, the authors aim to understand the structure and function of the enterovirus 2C protein, a putative viral helicase with AAA+ ATPase activity. Using poliovirus (as a model enterovirus) 2C, the author's propose the protein contains two amphipathic helices (AH1 and AH2) at the N-terminus that are divided by a conserved glycine. Using purified MBP-tagged 2C and N-terminal 2C truncations, their data suggests AH1 is primarily responsible for clustering at membranes, whilst AH2 is the main mediator of 2C oligmerisation and membrane binding. Furthermore, 2C was suggested to be able to recruit RNA to membranes, with a preference for dsRNA, and the author's data implies that the helicase activity of 2C is ATP-independent. Instead, the ATP activity appears to be required for 2C hexamer formation or chaperone activity. The manuscript is generally well written /presented and the author's present very interesting data which raises several questions, some of which require additional experimentation to help support the author's conclusions. Specific comments are as follows.
We thanks the reviewer for the overall positive assessment, as well as the specific comments below.
Major Comments:
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The authors use four main constructs throughout the paper: full-length 2C, 2C with deletion of AH1 (ΔAH1), 2C with both AH1 and AH2 deleted (ΔMBP) and 2C with an extended N-terminal deletion. From this, the author's draw conclusions on the function of both AH1 and AH2. One of the author's main conclusions is that AH2 is the main mediator of 2C membrane association (e.g., in line 169). However, is it possible to conclude the relative importance of AH1 vs AH2 without testing a construct containing the deletion of AH2 only (ΔAH2)? This should be generated and used alongside this data to fully define the relative importance of AH1 and AH2 in these assay and remove the possibility that the deletion of AH1 changes the structure and/or function of AH2, which could also result in the observed differences.
This was a very good suggestion. We expressed and purified the ΔAH2 protein requested by the reviewer and characterized its oligomeric state as well as its membrane binding. It turns out, as suspected, that the ΔAH2 protein behaves very similarly to the ΔMBD protein (i.e. it does not form higher order oligomers and does not bind membranes). The changes in the manuscript due to this addition are many but can primarily be found in main figures 2-3 and their associated supplementary figures.
Previous structural predictions of 2C do not appear to have two separate AHs at the N-terminus. Are the AH1 and AH2 structures predicted to be formed in the context of the entire 2C protein, 2BC precursors and polyprotein? Are there structural approaches that could provide experimental evidence for two separate AH at the N-terminus?
This is a good point. Previous predictions were not that detailed, partially since they were done in the pre-alphafold era. Unfortunately, we cannot think of a tractable experimental method that could verify the split nature of the amphipathic helix in the only context that would matter: the protein bound to a membrane. A long-term goal would be in situ structures of full-length 2C on membranes using cryo-electron tomography, but our current sample and data sets are not sufficient for this. We added a mention of the long-term need for experimental structures of full-length 2C on lines 315-318 in the discussion.
Why are the 2C dimers (lines 137-138) not apparent on the mass photometry data presented (figure 2)?
Different constructs were measured by mas photometry and SEC-MALS. Also, the required concentration is 100-1000x lower for mass photometry which will affect a dynamic equilibrium in case the same construct were measured by the two methods.
It appeared that binding of ΔMBD-2C was better when POPS is in the membrane (line 174). What is the explanation for this and was this finding significant?
Well spotted. It may mean that 2C has a second, lower affinity membrane-binding site which is charge-dependent somewhere outside the MBD. We now added a mention of this in the discussion, lines 321-323.
From the author's data on lipid drop clustering they conclude ΔAH1 is more effective for clustering, however, the ΔAH1 construct produces pentamers not hexamers (from Figure 2). Is formation of hexamers related to or required for membrane clustering?
ΔAH1 is LESS effective at clustering, not more. As for the mention of pentamers in the original submission: we now think this was an unfortunate choice of words. The mass photometry data for 2C(ΔAH1) could more parsimoniously be interpreted as a mix of hexamers and other (unknown to us) smaller oligomers such as trimers. We have removed all mentions of pentamers.
The replicon data presented in Figure 7 should include a replication-defective control (e.g., polymerase mutant), in order to compare how defective in replication ΔAH1 and ΔMBP deletions are compared to a fully-defective construct. Likewise, deletion of ΔAH1 in this construct is likely to affect processing of the viral polyprotein where several previous studies with picornaviruses have demonstrated that the residues in the P2'-P4' positions can change cleavage efficiency (e.g., PMID: 2542331), or the structure of 2C, leading to the reduction of replication.
Thanks for these good comments. We made the polymerase-dead (GDD-to-GAA) replicon and remeasured it side by side with the 2C replicons. It has a similar luciferase activity indicating that no replication takes place in the 2C deletion replicons. This is shown in the new figure 7. As for the possibility or processing defects, we mentioned this in the original discussion and have now cited the reference suggested by the reviewer in this context (line 324).
How does the author's model of ATPase-independent helicase activity and an APT-dependent required RNA chaperone activity fit with 2 step model for RNA binding and ATPase activity suggested by Yeager et al (PMID: 36399514)?
Acting upon comments from other reviewers, we completely redid the "helicase assay" in the revised manuscript. It turns out that the ATP-independent unwinding activity in the original submission was an artefact of the assay conditions (specifically, of the TEV protease at the higher concentration we used in the old assay). In our improved assay we neither see helicase activity nor ATP-independent RNA chaperoning activity.
Optional major comments that would increase the significance of the work:
All of the optional comments below are exceptionally interesting. But given the long time needed for the several major changes to this manuscript (e.g. the ΔAH2 protein characterization and reoptimisation of the helicase assay) we believe it is more sensible to address them in future studies, for which the 2C reconstitution system can be used.
The preference for dsRNA over ssRNA appears to be quite small (Figure 5d). In the context of a viral infection where ssRNA is likely to outnumber dsRNA at different times during infection is this preference physiologically relevant? In relation to this, what size stretch of dsRNA is required for preference, and could this correspond to cis-acting RNA structural elements, dsRNA as it escapes 3D polymerase or as part of the RF and RI forms (PMID: 9343205)? What is the proposed mechanism of how dsRNA outcompetes membrane tethering of 2C? OPTIONAL The author's study has been conducted in the absence of other viral non-structural proteins. What is the physiological importance of the observations, such as membrane interaction/clustering or RNA binding when presented in the context of the other replication machinery. OPTIONAL Do 2C monomers, dimers and hexamers have different functions in viral replication perhaps at different stages of replication and which of these forms are relevant during viral infection or can they all be detected during infection? Can any suggested separate functional arrangements be separated by genetic complementation experiments? OPTIONAL
Minor comments:
-
The author's appear to interchange between naming/nomenclature of the constructs which makes it confusing to follow (for example, ΔMBD is the same as 2C(41-329) likewise, 2C(Δ115) is sometimes called 2C(116-329)). It would be much easier to follow if the naming of constructs was consistent throughout (unless I am misunderstanding some subtlety in the difference between such constructs).
Thanks very much for spotting this. We have fixed it.
The author's suggest a pentamer arrangement for the ΔAH1 construct, however in the mass photometry data (figure 2D), a hexamer is indicated with the arrow. It would be helpful to change the label to indicate the size of the pentamer where this is being generated, not the hexamer.
As mentioned above, we think the "pentamer" designation of the original manuscript was unfortunate. It is more parsimonious to interpret this as a mix of states, hexamer and undefined snaller.
In most figures, data for full-length 2C, ΔAH1 and ΔMBP is shown. However data for ΔMBP is missing in Figure 4. Using ΔMBP may demonstrate even lower clustering, hinting that AH2 is also involved in this process.
Thanks for this comment. In our view, it can be derived from figure 3 (which shows lack of binding to PC/PE membranes) that the ΔMBD construct would not cluster membranes under the conditions of the assay (clustering requires concomitant binding to two membranes). We now describe our rationale for this on lines 220-222. However, we did include the ΔMBD protein in the new negative staining TEM supplementary figure where it and ΔAH2 show no signs of clustering (figure S10).
I think it would be better for normalise the data in the flotation experiments such that the percentage of 2C in the upper faction is presented as relative to the amount of lipid in the upper fraction (presented in Figure S4).
The change suggested by the reviewer would make it impossible to show the important no-liposome control (leftmost bar in Fig. 3C) in the same plot as the other measurements. We believe that would unnecessarily complicate the figure. Thus, we opted to keep the measurement that are normalised by lipid fluorescence in the supplementary figure. Instead, we now added another mention of this supplementary figure in the legend to main figure 3.
At several places (e.g., lines 232 and 272) the author's refer to "realistic systems". I think the term "physiologically relevant" might be more appropriate.
Agreed and changed throughout.
Line 237: I think "y" is a typo and should read "by".
Thanks. This text was reworked due to the major changes to figure 6.
Reviewer #1 (Significance (Required)):
Significance
I have limited expertise with structural biology but specialise my research on positive-sense RNA virus replication, structure and function. This research is of interest to a broad audience of researchers investigating many positive-sense RNA viruses, which extends beyond the viral family studied here. The work utilises novel techniques to begin to understand the specific roles of 2C in poliovirus replication. The author's data add important incremental new insight into recent studies on viral helicase proteins as referenced in the study, however, a key limitation is understanding the importance/relevance of their observations during a viral infection.
We thanks the reviewer for this positive and nuanced appraisal of our work.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
The authors present an alternative assay system to investigate picornavirus 2C, a protein that is tricky to analyze biochemically in its full length form because of an amphipathic helix at the N-terminus. Poliovirus 2C is expressed with an N-terminal MBP tag, a 50kD protein that helps with solubility as is commonly used for 2C investigations. A difference here is that liposomes are included to mimic membranes for 2C attachment. The key findings are that 2C induces clustering of of liposomes, that double stranded RNA binding by 2C impacts this clustering effect and that a free N-terminus (after cleavage of MBP by TEV protease) is needed for RNA binding and an ATP independent (ie non helicase) RNA duplex separation activity.
Major:
In the floatation assays in figure 3 the authors use a system where MBP-2C is fluorophore-labeled with ATTO488 on exposed cysteines. Poliovirus and other enterovirus 2C has a very well characterized zinc finger domain that has cysteines coordinating a zinc ion. Mutation experiments previously showed that these cysteines are necessary for viral replication and 2C stability. Have the authors controlled for disruption of the zinc finger domain by the labelling of cysteines with ATT0488 and checked if the protein remains folded?
We completely agree with the reviewer and apologise for the omission in the original submission. We have now included a Zn content measurement, which shows unchanged levels between labelled and unlabelled 2C protein (Figure S7). Also, we now in the revised manuscript explicitly describe our original reasoning for labelling on native cysteines: the presence of two cysteines which are not necessary for viral replication and which are more solvent exposed-exposed (and thus more likely to be labelled) in the crystal structure of the soluble fragment of 2C (lines 176-181).
In the analysis of the amphipathic helix, did the authors include membranes in their structural predictions o just the free helix? How does inclusion of membranes impact the predictions? In the predictions in Figure D, only 2 of 4 show a kink and there doesn't seem to be a correlation between those that predict a kink or not and whether the hydrophobic side is aligned in Figure S1.
Unfortunately, predicting a protein structure with the interacting membrane is beyond what is currently doable with protein prediction methods (one would have to combine protein structure predictions with molecular dynamics simulations including a membrane). Based on general principles of protein structure, it is likely that there is some flexibility around G17. Thus there may not be a single "kink angle" for any given virus, but we believe that the presence of the kink (and offset hydrophobic surfaces) for a number of viruses lends credibility and robustness to the observation. We added some descriptions of this thinking on lines 126-127.
Based on previous structures of 2C from different viruses the N-terminal amphipathic helix containing region is predicted to localize on one face of the predicted hexametric structure tethering 2C to the membrane. How does the authors hypothesized model explain 2C dependent clustering? is there evidence that 2C hexamers can oligomerize further into dodecamers for example, maintaining separate faces to enable N-terminal interaction with different membranes? What is the distance between the liposomes in figure 4 at the points of density attributed to 2C? How does this compare to the size of 2C determined in previous structural studies? Is it consistent with one hexamer/2 hexamers sitting on top of one another?
These are very interesting questions but we believe it is prudent to limit our speculation at this point. Eventually, we hope that larger data sets of cryo-electron tomography, coupled to subtomogram averaging, may provide a more definitive answer. What we managed to do with our current cryo-electron tomography data set is to estimate the volume of individual protein densities, and from the volume calculate an estimated molecular mass of the individual complexes seen in the tomograms. This correlates very well with 2C hexamers (new figure 4D).
In the Discussion lines 278-285 the authors suggest that having MBP attached may reflect the polyprotein condition. Can they make a construct with MBP-2B2C to examine interaction with liposomes and assess 2C function?
This is a highly relevant question, but the biochemistry of 2BC is even more challenging than 2C, and we are unfortunately nowhere near being able to work with purified 2BC at the moment.
Discussion lines 293-296, the possibility of two different populations of 2C, binding RNA or membranes cannot be excluded, there is much more 2C around late in infection that present in early infection- the model in figure 8 doesn't acknowledge/capture this.
We have changed the model figure such that more 2C is seen later, and the clustering function is also seen late in infection. The original discussion text referred to (which is unchanged) talks about a "preferential role in RNA replication and particle assembly at later time points" specifically for this reason. We hope the new figure 8 is better at conveying this message.
Discussion lines 313-317, the authors don't reference a study where a mutant of foot-and-mouth disease virus 2C lacking the n-terminal amphipathic helix that could bind but not hydrolyze ATP, hexamerized in the presence of RNA that seems pertinent here (PMID: 20507978).
Thanks for the suggestion. However, after the extensive changes we made to the revised to figure 6 based on excellent reviewer comments (essentially: the RNA chaperoning activity turned out to be an artefact, the improved assay shows no sign of RNA unwinding but instead of 2C-mediated ribonuclease activity), these sentence of the original discussion lost most of their context and we opted to remove them.
Some evidence of MBP-2C cleavage by TEV in the different assays used should be presented as this is a major focus of discussion and currently no gels show TEV cleavage is happening.
Thanks for the suggestion - we agree. We now show these in the new supplementary figures S5 and S12.
Reviewer #2 (Significance (Required)):
The work presents an additional methodology to investigate a a protein that has previously been difficult to study. The authors acknowledge that there is still a lot of 2C biology that remains to be discovered.
Thanks, we agree.
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
The manuscript provides insights into the role of the N-terminus in membrane binding and its importance in the various functions of 2C.
Major issues
Line 103-119. Is this novel? I thought people had done a lot of bioinformatic analysis of PV 2C (especially Wimmer) who also did mutational work to analyse the importance of various amino acids in the N-terminal helix. I feel like the paper in general, and this section in particular, underplays the large body of work that has been done on the amphipathic helix by various groups.
We apologise if our original manuscript didn't sufficiently acknowledge previous work in the field. In the first sentence of the mentioned paragraph (now lines 112-113) , we did however cite several papers that have previously addressed the amphipathic nature of the N-terminus of 2C. We have now added two more references along the same line, and changed the wording in a way that we hope better bring across that the amphipathic nature per se has been studies before. We would be happy to add more specific references if the reviewer has any suggestions. However, the rest of our analysis IS indeed novel for the following reasons: (i) we show that the amphipathic region is not a simple, single amphipathic helix, but instead has a conserved glycine (helix breaker/destabiliser residue) and two distinct amphipathic stretches before and after this region, (ii) we use alphafold2 (not available at the time of the earlier work) to provide the first reliable structural models of the membrane-binding domain. These models consistently, across several enterovirus 2C proteins, reveal that the hydrophobic surfaces of the first and second amphipathic regions, on either side of the conserved glycine 17, are offset from one another. This lends additional credibility to the distinct nature of these regions which have not previously been identified as such and which we also show in the biochemical assays to be functionally distinct. We have now also added a clarification to the Discussion that the N-terminus of 2C had previously been identified as its membrane-binding domain and we cite references for this. We hope that these changes will sufficiently acknowledge earlier work in the field while clearly pointing out the advance that our paper makes.
Line 132. Did you validate your column with known MW standards? The peak for full length and deltaAH1 look fairly standard for 2C, in that you have a mixture of species. Not sure you can say it is a hexamer when it is such a broad peak. C doesn't really help you too much since the counts at 400 (pentamer) and 480 (hexamer) are almost the same with quite large error bars. Like most people that have worked with 2C I think the best you can say is that you are making some kind of oligomerized 2C that includes hexamer, pentamer, etc. Why no dimer for MBP-2C and MBP-2C(delta AH1) when compared to the other constructs?
We did not calibrate the gel filtration column since the outcome would anyway be a more crude estimate of molecular mass than the mass photometry and SEC-MALS measurements. But we do agree with the reviewer on the broad mass photometry peaks. To address this experimentally, we compared the existing MBP-2C spectra to new recordings on apoferritin, a highly stable homomultimeric protein complex of a similar mass to aa MBP-2C hexamer. The apoferritin mass estimate is overlayed with the full-length MBP-2C in the new figure 2D and the corresponding supplementary figure S3. This indeed shows that the MBP-2C peak is broader, i.e. consistent with a mix of species which are predominantly but not only hexamers. We describe and discuss this on lines 145-149. As for the mention of pentamers in the original submission: we now think this was an unfortunate choice of words. The mass photometry data for 2C(ΔAH1) could more parsimoniously be interpreted as a mix of hexamers and other (unknown to us) smaller oligomers such as trimers. We have removed all mentions of pentamers.
Line 143. Does your data show that there are two amphipathic helices? Bioinformatics suggests it but your experiments just show the importance of the two areas in oligomerization, not that it is forming two helices.
We agree that the choice of words was not idea and have now changed it to "structure predictions indicate" (lines 162).
Figure S2. Your preps are still relatively dirty, which isn't ideal for biochemical assays. Especially lane 3, where you are looking at 50-60% purity. I don't want you to re-run experiments but I think you need to comment on the purity of the protein you are working with. Also I don't like that you removed the top and bottom of the SDS-PAGE. How much protein never entered the gel. Is there a big fat band at 20 kDa? You need to have the full gel here. Did you measure 260 nm of the preps as well to see if you had bound RNA to the 2C?
Thanks for the comment, we agree that our original submission lacked detail in the description of the protein purification. This is now addressed with the new figure S2 which shows size exclusion chromatograms of the fluorophore-labelled proteins (same chromatograms as in figure 2) and the corresponding uncropped gels imaged both in the stain-free channel (showing all proteins) and in the fluorescence channel. The A260/A280 ratio measured for all proteins shows that they are free of nucleic acids at the point of imaging. The protein preps are not 100% homogeneous but we do believe that they are more than 50-60% pure.
Lines 170. Wasn't this done in the recent "An Amphipathic Alpha-Helix Domain from Poliovirus 2C Protein Tubulate Lipid Vesicles"? I don't see it referenced. What is novel about the current work when compared to that paper? Any differences?
Thanks for pointing this out. The referenced study worked with a synthesized, isolated peptide corresponding to AH2 (i.e. not with full protein). An amphipathic peptide outside the context of its protein cannot be expected to recapitulate the properties of the entire protein, e.g. since it is not spatially constrained in how it interactis with membranes. As one example (relating to the title of that paper) we don't see full-length 2C protein tubulating membranes the way the isolated peptide does. As for the reviewer's question about novelty, the paper mentioned does not identify the split nature of the amphipathic region, does not consider the role of AH1, does not characterise the membrane-binding properties of full-length 2C with respect to liposome membrane composition and size, does not identify and characterise the membrane clustering properties of 2C, nor its interactions with nucleic acid when bound to a membrane. However, we do agree that we should have cited the paper in our manuscript. We now cite it in the discussion, lines 320-321.
I'm surprised by the lack of electron microscopy (negative stain mostly) of both the oligomerized 2C and the various liposomes. I know the Carlson group is a microscopy group so why the lack of validation using electron microscopy of the various DLS experiments? I know you did cryo-ET for one of the constructs but I think negative stain electron microscopy of other constructs would be useful.
Thanks for the suggestion. As suggested, we have now expanded the analysis with negative staining EM of several more constructs studied by DLS. It can be found in the new supplementary figure S10.
Figure 4C. What evidence is there that this is 2C apart from you added it to the liposomes? It also comes back to the relative impurity of your protein prep. Could this be E.coli contamination?
Thanks for this comment. We have now added a new supplementary figure (S5) showing SDS-PAGE gels of the reactions used for flotation and DLS assays - which are identical to the cryo-ET samples. In addition, we estimated the molecular mass of the individual, putative 2C desities in the cryo-electron tomograms by measuring their volume. This analysis, which can be found in the new figure 4D, shows that the estimated mass of individual protein densities is consistent with a hexamer of full-length 2C. In addition, we mention in the discussion the long-term need to determine high-resolution structures of membrane-bound 2C using cryo-ET and subtomogram averaging (lines 315-318).
Figure 8. Is this model supported by the data in this paper? Your cryo-ET says that 2C is there but that isn't supported by any other data. How is the dsRNA protected from the innate immune system in this model? is it just sat out in the cytosol? How is the nascent ssRNA packeged into the capsid? Is there competition between the dsRNA and capsid for 2C binding (which your model suggests)? I know it sounds like I am being overly critical of the model but in my opinion there are still too many unanswered questions in the field to come up with a half decent model.
Thanks for this comment. We are the first to agree that our understanding of the roles of 2C is far from complete! We should have been more clear that the model figure represents some of the roles of 2C identified to date, and does not claim to be complete. However we do feel that a model figure serves a purpose of putting our findings into a context, and also providing testable hypotheses for future research . As for the question, some of the roles of 2C shown in the model figure (in particular, particle assembly) are rather supported but earlier work of ourselves and others. We have now produced a new model figure and changed the figure legend to better reflect the incompleteness of the current understanding, and the origin of the different parts of the model figure. In addition, we extended the final paragraph of the discussion (which lists still-unknown aspects of 2C) with the reviewer's mention of dsRNA shielding from innate immunity (lines 374-375). The other aspects mentioned by the reviewer as not yet fully understood are already mentioned in that paragraph.
Minor issues
Lines 43-45: I feel like you underplay the success of the poliovirus vaccination program. Approximately 30 of WPV1 in 2022 and the full eradication of WPV2 and 3. Vaccine derived polio is still an issue but even that is relatively low compared to where the world was in the 1950s.
We agree that the previous wording was not ideal. We replaced it and added another recent reference - related to the type 2 vaccine switch (lines 47-49).
Line 66. I agree there are 11 individual proteins but I feel like this leaves out the fact that some of the uncleaved precursors appear to have some functions, for example 2BC.
Good point. We have now added a mention of 2BC and the fact that it has distinct functions to the introduction (lines 70-71). 2BC is also mentioned in the legend of the model figure (figure 8).
Line 56: LD needs to be defined.
Well spotted thanks. Since the abbreviation was not used anywhere else we opted to spell it out instead (line 59).
Line 75. I think you have misrepresented Xia et al here. They clearly say that in their study that they show helicase and chaperone activity. I never managed to repeat that work but you should still report what they claim. One major thing is that they used insect expressed protein, whereas most people (including myself and in the paper under review) use E.coli expressed protein. Do post translational modifications play an important role in function?
You are right that the reference to their paper for this statement was incorrect. We have now made this part of the introduction more explicit (lines 82-83) and we also in the new discussion mention the possibility of e.g. post-translational modifications affecting 2C helicase activity, under reference to Xia et al (lines 359-361)
Line 103. Need to make it clear here it is poliovirus 2C.
Thanks, we added it (line 112).
Line 135. I assume you mean kDa instead of uM?
It should actually be μM. It is the solution concentration at which the assay was performed. We added some words to clarify this (line 154).
Figure 3. What do you mean by "Only 2C"? Is that MBP-2C? Maybe I am reading the data wrong but adding TEV does nothing? How do you know TEV is removing the MBP? It looks like MBP-2C binds to the liposomes just the same as cleaved MBP-2C. I see in line 165 you acknowledge this. Could an alternative conclusion for line 168 be that MBP isn't being cleaved off but that AH2 is too small to be exposed in that construct? Did you do that construct without MBP being cleaved? I think you need to confirm that MBP is being cleaved off.
Thanks for spotting this mistake. It should indeed be MBP-2C (in the absence of liposomes). We corrected figure 3. Also, in response to this comment and similar ones, we have now added a new supplementary figure showing SDS-PAGE gels of the reaction loaded onto flotation assays and DLS (figure S5). It shows that MBP-2C is cleaved.
Line 184. Is there a reason you use the 2019 paper as a reference instead of the far earlier Bienz et al papers? I'd suggest they are the seminal papers on 2C membrane association. Once again how is this work different from the recent "An Amphipathic Alpha-Helix Domain from Poliovirus 2C Protein Tubulate Lipid Vesicles" paper?
See our response above of the paper mentioned here (which we have now cited). As for why we cite the 2019 paper here: our statement pertains specifically to the contact sites between lipid droplets and replication organelles, not to the membrane binding of 2C per se. We have now added a more general mention of membrane remodelling by non-structural proteins in the introduction, where we cite on of the Bienz papers (lines 75-77).
Figure 5D. So only 1-3% of RNA is found in the upper fraction? Is that significant enough to say that dsRNA was recruited significantly more than ssRNA? How confident are you in your quantification of the starting amounts of RNA?
We agree that the fraction is low, however, the fluorescence signal is very clearly above background. We are thus confident in the measurement. The low percentage at the end of the experiment likely has a simple physico-chemical explanation: in a dynamic equilibrium in a density gradient, whatever RNA dissociates during the run will migrate away from the 2C-vesicle fraction and not be able to rebind. We still tried to address this concern by a complementary experiment where we used fluorescence anisotropy to measure binding of RNA to 2C on vesicles. While the measurements showed the same tendency, they curves were not clean enough to be published, which we think is due to the complex system with 2C bound to vesicles and clusters of vesicles. Still, in view of the relatively low percentage of measured recruitment we opted to adjust the paper title and the title of figure 5 (including the subheading related to figure 5) to put less emphasis on the dsRNA recruitment.
Line 223. Any idea why the MBP needs to be cleaved off? Clearly the MDB is accessible or it would not bind to the liposomes.
Since we have no data directly supporting this we prefer not to speculate in the paper. But one guess would be that the NTD of 2C, as implicated by previous publications, has a dual role in membrane binding and RNA binding. It may be that it can bind membrane while conjugated to MBP, but needs MBP to be removed in order to simultaneously bind membrane and RNA.
Line 237: missing "b" in "by"
Thanks. This paragraph was rewritten in the light of the changes to figure 6.
Figure 6. I don't fully understand the results here. Earlier you showed that the delta MBD didn't really bind SUV. So presumably it isn't really membrane bound. Why does it have similar activity to full-length MBP in your helicase assay if membrane is important? Did you do SUV and TEV protease only control?
We are very grateful to this reviewer (and others) for pointing out the need for a TEV control. When performing the control, we found that the TEV protease, at the high concentrations initially used, surprisingly had an artefactual RNA chaperone-like effect on its own. We then proceeded to titrate down the TEV protease concentration to the point where it no longer interfered. At this TEV protease concentration, although 2C was substantially cleaved (see the new supplementary figure S12), we could no longer detect an RNA chaperone activity. Thus, the contents of the new figure 6, and its conclusions, have been substantially changed. We now focused our attention on the remaining effect that 2C has on RNA: single-strand ribonuclease activity. These experiments were all conducted in the presence of RNase inhibitors, and the presence of Mg2+-dependent ribonuclease activity parallels a recent publication that found this for truncated 2C from hepatitis A and several enteroviruses.
Line 257: "staring"?
Thanks, corrected. A staring glycine would indeed be something strange.
Line 336. Need to change the u to mu.
Thanks, corrected.
Any discussion on your observation in Figure 1D that EV71 and CVB3 don't appear to have AH1 and AH2 or do you think that the domains are conserved across the different viruses?
Thanks for bringing this up. Based on this and a comment from another reviewer, we have now clarified our thinking around this. Since the glycine will introduce some flexibility between AH1 and AH2, we cannot say from the single alphafold predictions that this is THE kink angle. The presence of the kink in the predictions of several MBDs lends more credibility to the robustness of the observation, but most importantly the hydrophobic surfaces in AH1 and AH2 are non-aligned for ALL sequences we looked at. This is now described on lines 126-128.
Table 1 (and possibly elsewhere): an apostrophe is not the prime symbol. 5' compared to 5′.
Thanks, we corrected this throughout.
Line 702 "and" should be "an".
Thanks, corrected.
I couldn't open one of the movies (140844_0_supp_2820374_a2g272.avi).
Sorry to hear this, we will check the movie again.
Reviewer #3 (Significance (Required)):
Overall I liked the paper and is worth publishing. One of the issues in the 2C field is the difficulty in making pure 2C and carrying out in vitro assays that correlate with what is observed in the natural infection. I think this paper suffers from similar struggles with a 2C preparation that doesn't appear that pure. I think it also suffers from not having 2C from a wild-type infection. I don't think that it is feasible to get that kind of 2C but by once again using a recombinant protein from E.coli we are left with another manuscript that provides conflicting evidence of the functions of 2C without a definitive answer. The experiments are well done, although are missing some controls and the manuscript is laid out in a logical manner and is relatively easy to follow.
We thanks the reviewer for these comments. We believe that we have now provided better information regarding the purification of the recombinant 2C protein, and we do think that the controls present in the original manuscript and the revised manuscript alleviate the concerns about lack of specificity. Of course, isolating 2C vesicles from wildtype infection would be another interesting way of approaching its function, but such an approach would come with its own set of challenges related e.g. to the presence of confounding host factors.
Reviewer #4 (Evidence, reproducibility and clarity (Required)):
This is an interesting manuscript that reports the development of an in vitro membrane assay for probing the biochemical functions of the enterovirus 2C protein. The technique is interesting because it can be applied to 2C proteins from other members of the picornavirus family, an important group of mammalian pathogens. It has the capacity to probe different functions (e.g. membrane clustering, ATPase activity, RNA-binding and manipulation activities).
Overall, the manuscript is well written and gives a clear account of the work undertaken. It adds insight to previous studies of enteroviral (and picornaviral) 2C proteins, providing confirmation of some earlier work in a more physiological context and some new insights, particularly into the membrane and RNA binding aspects of 2C.
That said, there are a number of places where some amendment of the claims made is required to provide a more precise statement of the findings of this work. These are listed below.
We thank the reviewer for this positive feedback on our work, as well as for the specific comments below.
Line 21 (Abstract) - The authors claim to have shown that a conserved glycine divides the N-terminal membrane-binding domain into 2 helices. I would suggest instead what they have produced are computational predictions that this is the case - some way short of an experimental demonstration. Sequence analysis predicts helical secondary structure in the N-terminus and indeed Alphafold2 also predicts a helical structure, but these predictions require experimental verification. The authors should therefore rewrite sections that claim to have shown the presence of 2 helices. In doing so, they should perhaps also comment on the fact that Alphafold2 does not predict 2 helices in this region for all enteroviruses (see Fig 1D). Moreover, the sequence analysis in Fig. S1 shows the presence of two Lys residues in the segment 17-38; it would be interesting for the reader to have these indicated in the figures showing the Alphafold2 prediction - do they in any way interrupt the hydrophobic face of the predicted helix?
Thanks very much for this comment, which is in line with what other reviewers also wrote. We agree, and changed the abstract sentence. We have also rewritten the manuscripts in several places to address the limits of structure predictions and the eventual need for an experimental structure of full-length membrane-bound 2C (lines 126-128 and 315-318).
Line 82 (Introduction) - The authors write that the membrane binding domain (MBD) of poliovirus has been shown to mediate hexamerisation, citing Adams et al (2009) - reference 43. However, that is not what this paper shows. Rather it provides evidence of aggregation of an MBP-2C fusion protein into forms that ranged from tetramer to octamer, but no evidence that these aggregates assume functional forms (e.g. the presumed hexameric ring structure characteristic of the AAA+ ATPase family to which 2C belongs). As far as I am aware the first demonstration of hexameric ring formation by a picornaviral 2C protein was for the 2C of foot-and-mouth disease virus (see Sweeney et al, JBC, 2010). Although this is not an enterovirus, this finding was later confirmed for Echovirus 30 (ref 51). I should declare an interest here: the Sweeney paper is from my lab. I will leave it to the editor and the authors to determine how to write a more precise account of the early observations of hexamerisation in picornaviral and enteroviral 2C proteins.
Thanks very much for this insightful comment. As a response to this and other similar comments, we are much more cautious about our wording in the revised manuscript (see also response to comment below. In the part of the introduction discussed here (now lines 89-91) we now use the original wording of the Adams paper ("oligomerization"). In the context of that new text we didn't feel that Sweeney et al paper was a suitable reference, but we now cite it in the later mention of 2C's oligomeric/hexameric state in the first part of the Results (lines 137-138 ).
Line 132 - the authors used mass photometry to investigate oligomeric forms of their MBP-2C constructs and state that for the full length 2C protein "the high-mass peak closely corresponds to a hexamer". While it is true that the peak shown in Fig 2C aligns with the expected MW for an MBP-2C hexamer, the peak is very broad, indicative of the presence of other oligomeric states with lower and higher numbers of monomers. This should be commented on. Indeed, the finding seems to echo the early findings of Adams et al (ref 43) with poliovirus MBP-2C.
Thanks for this comment, which was also made by another reviewer. We cite here what we replied to that reviewer
...we do agree with the reviewer on the broad mass photometry peaks. To address this experimentally, we compared the existing MBP-2C spectra to new recordings on apoferritin, a highly stable homomultimeric protein complex of a similar mass to aa MBP-2C hexamer. The apoferritin mass estimate is overlayed with the full-length MBP-2C in the new figure 2D and the corresponding supplementary figure S3. This indeed shows that the MBP-2C peak is broader, i.e. consistent with a mix of species which are predominantly but not only hexamers. We describe and discuss this on lines 145-149.
Line 143 - for the reasons given above, this summary paragraph represents too strong a statement of what has been observed.
We agree, and changed the paragraph. It now only refers to "oligomerization" (lines 162-164).
Line 197 - I note that the authors did not test the membrane clustering capabilities of the 2C(41-329) construct. Although the 2C(deltaAH1) construct had already shown a significant loss of activity, the shorter construct could still have been a useful control. I don't think it is necessary for this experiment to be done, but if the authors have a rationale for not performing the experiment, perhaps they could include it in a revised manuscript.
Thanks for the suggestion. The rationale is that a protein that doesn't bind a membrane in the first place will also not cluster them (an action that requires binding TWO membranes). We now describe our reasoning on lines 220-222. Nevertheless, we did test these constructs in the new supplementary figure showing negative staining TEM (figure S10).
Line 223 - typo. I think you mean MBD.
Thanks! Corrected (now line 257).
Line 215 - the authors observed that the presence of ssDNA reduced membrane clustering and conclude that "nucleic acid binding partially outcompetes membrane tethering activity". Two things: (1) although I agree is it likely that this effect is due to binding of DNA to 2C, binding has not been demonstrated experimentally so the authors should be more careful in how they describe their result; (2) there is no data presented to show that RNA binding reduces membrane tethering so at best I think the conclusion has to be that the data are consistent with the notion that DNA binding reduces membrane tethering. It would of course be interesting to see the effects of RNA and I'm curious to know why the assay was not performed.
Thanks for the comment. The honest answer is that previous publications (primarily Yeager et al, NAR 2022) convinced us that the outcome should be near-identical with DNA, so we chose DNA oligos because they are cheaper and easier to work with. But we agree with the reviewer that RNA is of course more relevant. We now present a comparison at 5 μM of ssDNA and ssRNA, which in fact shows a slightly stronger effect on membrane clustering by RNA (figure 5C). In the light of this additional experiment, we feel that some of the text changes suggested by the reviewer may no longer be necessary.
Line 237 - typo: by, not y
Thanks. In the light of the extensive changes to figure 6 this text was removed.
Line 284 - the authors claim that 2C may only bind RNA after the N-terminus is liberated from 2B in infected cells, since cleavage of the MBP tag from their construct was needed for 2C to bind RNA in their in vitro assay. However, this does not automatically follow given the large structural differences between MBP and 2B and the fact that the authors have not tested the RNA binding capacity of a 2BC fusion protein. Their claim here is too strong and should be re-written.
We agree, and have added a discussion along the lines suggested by the reviewer (line 330-332).
Line 293 - The authors speculate that RNA binding might cause a shift between the membrane clustering activities and the role of the protein in RNA replication. However, since they have not shown that RNA binding reduces membrane clustering, this is too speculative.
In our revised manuscript we have studied the effect of RNA on membrane binding, thus we feel that this text is relevant in the context of the extended experiments.
Line 299-317 - within this discussion is the assumption that in their assay system enterovirus 2C adopts the ring-like hexameric structure typical of AAA+ ATPases. While I agree this may well be the case, it has not been demonstrated in this study so the authors should make clear they are making this assumption. The same applies to the legend of Fig 8.
This part of the discussion was extensively rewritten after our changes to figure 6. We now only refer to "hexamer" once in the corresponding part of the discussion, where we talk about structural models of hexamers produced by other groups who have crystallised fragments of 2C. There we believe we should refer to hexamers to accurately cite their work.
We are not sure what the reviewer is referring to when it comes to the legend for figure 8: the original legend had no reference to the oligomeric state of 2C. We have substantially changed figure 8 and its legend and the new figure and legend make no references to hexamers/oligomers.
Line 302 - the authors claim to have shown that 2C is 'selective' for dsRNA. I think at best they have shown a preference for binding dsRNA over ssRNA.
We changed the wording (line 349). We have also changed the title of the paper where we removed "double-stranded".
Line 313 - The sentence starting "A recent study..." needs a reference.
The revised discussion no longer contains this sentence.
Line 332 - the full sequence of the synthetic gene used in this study should be made available (e.g. as supplementary information or a deposited sequence with an accession number). This is a critical point before the paper can be published.
We will of course submit the sequences as supplementary data. Thanks for the reminder.
Line 362 - the authors should describe the likely points of attachment of fluorophores and comment on how this labelling might affect 2C function.
Thanks for the comment. In response to this and a similar comment from another reviewer, we discuss the likely conjugation site of the fluorophore (lines 175-181), and also (due to the proximity to the Zn finger) provide a new measurement showing that equal amounts of Zn can be detected in the labelled and unlabelled protein (figure S7).
Line 372 - Is a single protein standard (BSA) sufficient to calibrate the SEC-MALS system?
Yes, it is the recommended procedure (note that SEC-MALS is only dependent on scattering, not elution volumes etc).
Reviewer #4 (Significance (Required)):
As stated above this is an interesting study that presents findings from a novel assay. It will be of interest to picornavirologists and the wider community interested in the mechanisms of AAA+ ATPases.
We thanks the reviewer for this positive appraisal of our work.
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Referee #4
Evidence, reproducibility and clarity
This is an interesting manuscript that reports the development of an in vitro membrane assay for probing the biochemical functions of the enterovirus 2C protein. The technique is interesting because it can be applied to 2C proteins from other members of the picornavirus family, an important group of mammalian pathogens. It has the capacity to probe different functions (e.g. membrane clustering, ATPase activity, RNA-binding and manipulation activities).
Overall, the manuscript is well written and gives a clear account of the work undertaken. It adds insight to previous studies of enteroviral (and picornaviral) 2C proteins, providing confirmation of some earlier work in a more physiological context and some new insights, particularly into the membrane and RNA binding aspects of 2C.
That said, there are a number of places where some amendment of the claims made is required to provide a more precise statement of the findings of this work. These are listed below.
Line 21 (Abstract) - The authors claim to have shown that a conserved glycine divides the N-terminal membrane-binding domain into 2 helices. I would suggest instead what they have produced are computational predictions that this is the case - some way short of an experimental demonstration. Sequence analysis predicts helical secondary structure in the N-terminus and indeed Alphafold2 also predicts a helical structure, but these predictions require experimental verification. The authors should therefore rewrite sections that claim to have shown the presence of 2 helices. In doing so, they should perhaps also comment on the fact that Alphafold2 does not predict 2 helices in this region for all enteroviruses (see Fig 1D). Moreover, the sequence analysis in Fig. S1 shows the presence of two Lys residues in the segment 17-38; it would be interesting for the reader to have these indicated in the figures showing the Alphafold2 prediction - do they in any way interrupt the hydrophobic face of the predicted helix?
Line 82 (Introduction) - The authors write that the membrane binding domain (MBD) of poliovirus has been shown to mediate hexamerisation, citing Adams et al (2009) - reference 43. However, that is not what this paper shows. Rather it provides evidence of aggregation of an MBP-2C fusion protein into forms that ranged from tetramer to octamer, but no evidence that these aggregates assume functional forms (e.g. the presumed hexameric ring structure characteristic of the AAA+ ATPase family to which 2C belongs). As far as I am aware the first demonstration of hexameric ring formation by a picornaviral 2C protein was for the 2C of foot-and-mouth disease virus (see Sweeney et al, JBC, 2010). Although this is not an enterovirus, this finding was later confirmed for Echovirus 30 (ref 51). I should declare an interest here: the Sweeney paper is from my lab. I will leave it to the editor and the authors to determine how to write a more precise account of the early observations of hexamerisation in picornaviral and enteroviral 2C proteins. Line 132 - the authors used mass photometry to investigate oligomeric forms of their MBP-2C constructs and state that for the full length 2C protein "the high-mass peak closely corresponds to a hexamer". While it is true that the peak shown in Fig 2C aligns with the expected MW for an MBP-2C hexamer, the peak is very broad, indicative of the presence of other oligomeric states with lower and higher numbers of monomers. This should be commented on. Indeed, the finding seems to echo the early findings of Adams et al (ref 43) with poliovirus MBP-2C.
Line 143 - for the reasons given above, this summary paragraph represents too strong a statement of what has been observed.
Line 197 - I note that the authors did not test the membrane clustering capabilities of the 2C(41-329) construct. Although the 2C(deltaAH1) construct had already shown a significant loss of activity, the shorter construct could still have been a useful control. I don't think it is necessary for this experiment to be done, but if the authors have a rationale for not performing the experiment, perhaps they could include it in a revised manuscript.
Line 223 - typo. I think you mean MBD.
Line 215 - the authors observed that the presence of ssDNA reduced membrane clustering and conclude that "nucleic acid binding partially outcompetes membrane tethering activity". Two things: (1) although I agree is it likely that this effect is due to binding of DNA to 2C, binding has not been demonstrated experimentally so the authors should be more careful in how they describe their result; (2) there is no data presented to show that RNA binding reduces membrane tethering so at best I think the conclusion has to be that the data are consistent with the notion that DNA binding reduces membrane tethering. It would of course be interesting to see the effects of RNA and I'm curious to know why the assay was not performed.
Line 237 - typo: by, not y
Line 284 - the authors claim that 2C may only bind RNA after the N-terminus is liberated from 2B in infected cells, since cleavage of the MBP tag from their construct was needed for 2C to bind RNA in their in vitro assay. However, this does not automatically follow given the large structural differences between MBP and 2B and the fact that the authors have not tested the RNA binding capacity of a 2BC fusion protein. Their claim here is too strong and should be re-written.
Line 293 - The authors speculate that RNA binding might cause a shift between the membrane clustering activities and the role of the protein in RNA replication. However, since they have not shown that RNA binding reduces membrane clustering, this is too speculative.
Line 299-317 - within this discussion is the assumption that in their assay system enterovirus 2C adopts the ring-like hexameric structure typical of AAA+ ATPases. While I agree this may well be the case, it has not been demonstrated in this study so the authors should make clear they are making this assumption. The same applies to the legend of Fig 8.
Line 302 - the authors claim to have shown that 2C is 'selective' for dsRNA. I think at best they have shown a preference for binding dsRNA over ssRNA.
Line 313 - The sentence starting "A recent study..." needs a reference.
Line 332 - the full sequence of the synthetic gene used in this study should be made available (e.g. as supplementary information or a deposited sequence with an accession number). This is a critical point before the paper can be published.
Line 362 - the authors should describe the likely points of attachment of fluorophores and comment on how this labelling might affect 2C function.
Line 372 - Is a single protein standard (BSA) sufficient to calibrate the SEC-MALS system?
Significance
As stated above this is an interesting study that presents findings from a novel assay. It will be of interest to picornavirologists and the wider community interested in the mechanisms of AAA+ ATPases.
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Referee #2
Evidence, reproducibility and clarity
The authors present an alternative assay system to investigate picornavirus 2C, a protein that is tricky to analyze biochemically in its full length form because of an amphipathic helix at the N-terminus. Poliovirus 2C is expressed with an N-terminal MBP tag, a 50kD protein that helps with solubility as is commonly used for 2C investigations. A difference here is that liposomes are included to mimic membranes for 2C attachment. The key findings are that 2C induces clustering of of liposomes, that double stranded RNA binding by 2C impacts this clustering effect and that a free N-terminus (after cleavage of MBP by TEV protease) is needed for RNA binding and an ATP independent (ie non helicase) RNA duplex separation activity.
Major:
In the floatation assays in figure 3 the authors use a system where MBP-2C is fluorophore-labeled with ATTO488 on exposed cysteines. Poliovirus and other enterovirus 2C has a very well characterized zinc finger domain that has cysteines coordinating a zinc ion. Mutation experiments previously showed that these cysteines are necessary for viral replication and 2C stability. Have the authors controlled for disruption of the zinc finger domain by the labelling of cysteines with ATT0488 and checked if the protein remains folded?
In the analysis of the amphipathic helix, did the authors include membranes in their structural predictions o just the free helix? How does inclusion of membranes impact the predictions? In the predictions in Figure D, only 2 of 4 show a kink and there doesn't seem to be a correlation between those that predict a kink or not and whether the hydrophobic side is aligned in Figure S1.
Based on previous structures of 2C from different viruses the N-terminal amphipathic helix containing region is predicted to localize on one face of the predicted hexametric structure tethering 2C to the membrane. How does the authors hypothesized model explain 2C dependent clustering? is there evidence that 2C hexamers can oligomerize further into dodecamers for example, maintaining separate faces to enable N-terminal interaction with different membranes? What is the distance between the liposomes in figure 4 at the points of density attributed to 2C? How does this compare to the size of 2C determined in previous structural studies? Is it consistent with one hexamer/2 hexamers sitting on top of one another?
In the Discussion lines 278-285 the authors suggest that having MBP attached may reflect the polyprotein condition. Can they make a construct with MBP-2B2C to examine interaction with liposomes and assess 2C function?
Discussion lines 293-296, the possibility of two different populations of 2C, binding RNA or membranes cannot be excluded, there is much more 2C around late in infection that present in early infection- the model in figure 8 doesn't acknowledge/capture this.
Discussion lines 313-317, the authors don't reference a study where a mutant of foot-and-mouth disease virus 2C lacking the n-terminal amphipathic helix that could bind but not hydrolyze ATP, hexamerized in the presence of RNA that seems pertinent here (PMID: 20507978).
Some evidence of MBP-2C cleavage by TEV in the different assays used should be presented as this is a major focus of discussion and currently no gels show TEV cleavage is happening.
Significance
The work presents an additional methodology to investigate a a protein that has previously been difficult to study. The authors acknowledge that there is still a lot of 2C biology that remains to be discovered.
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Reply to the reviewers
1. General Statements [optional]
We thank all the reviewers for their constructive and critical comments. We provide a point-by-point response to the reviewers' comments, as detailed below. By responding to them, we believe that our revised manuscript will significantly improve so that it will be of interest for researchers in the field of cell biology, signaling pathways, physiology and nutrition.
Reply to the reviewers
Reviewer #1 (Evidence, reproducibility and clarity):
Summary: The manuscript by Yusuke Toyoda and co-workers describes that the phosphorylation of the a-arrestin Aly3 downstream of TORC2 and GAD8 (AKT) negatively regulates endocytosis of the hexose transporter Ght5 in S.pombe under glucose limiting growth conditions.
To arrive at these conclusions, the researchers define a set of redundant c-terminal phosphorylation sites in Aly3 that are downstream by GAD8. Phosphorylation of these sites reduces Ght5 ubiquitination and endocytosis. For ubiquitination, Aly3 interacts with the ubiquitin ligases Pub1/3.
We thank the reviewer for his/her time and reporting advantages and issues of this study.
Major points:
Figure 3B: it would be interesting to compare Aly3 migration pattern (and hence potential phosphorylation) under glucose replete or limiting growth conditions. Can the authors provide direct evidence that Aly3 phosphorylation changes in response to glucose availability? Also please explain the 'smear' in lanes aly3(4th Ala), aly3(4th Ala, A584S), aly3(4th Ala, A586T).
While it is an interesting possibility that the Aly3 migration pattern changes in response to glucose concentrations in medium, we think that this is unlikely and that examining this possibility is beyond the scope of this study. Because a phospho-proteomics study reported by Dr. Paul Nurse's lab showed Tor1-dependent phosphorylation of Aly3 at S584 under high glucose (2%) conditions (Mak et al, EMBO J, 2021), the Aly3 phosphorylation (migration) pattern is likely to be constant regardless of glucose conditions. Glucose conditions affect the mRNA and protein levels of Ght5, but supposedly not its endocytosis to vacuoles (Saitoh et al, Mol Biol Cell, 2015; Toyoda et al, J Cell Sci, 2021).
As for the smear in Aly3(4th A), Aly3(4th A;A584S), Aly3(4th A; A586T), we suspect that some posttranslational modification occurs on these mutant Aly3 proteins, but the identity of the modification is unclear. We did not mention the smear signals in the original manuscript, because the presence or absence of the smear did not necessarily correlate with cell proliferation in low glucose and thus vacuolar localization of Ght5, which is the main topic of this study. In the revised manuscript, we will mention this point more clearly.
Figure 4: Ght5 localization should be analyzed + / - thiamine and in media with different glucose levels. Also, a co-localization with a vacuolar marker (FM4-64) would be nice (but not necessary). Ideally, the authors should add WB analysis of Ght5 turnover to complement the imaging data. Also, would it be possible to measure directly the effects on glucose uptake (using eg: 2-NBDG).
In this revision, we plan to observe Ght5 localization under the conditions indicated by the reviewer (+/- thiamine and high/low glucose levels) to unambiguously show that the vacuolar localization of Ght5 occurs in a manner dependent solely on expression of the mutant Aly3 protein.
We thank the reviewer for the suggestion of co-staining with FM4-64. Indeed, because we previously reported that the cytoplasmic Ght5 signals were surrounded by FM4-64 signals in the TORC2-deficient tor1Δ mutant cells (Toyoda et al, J Cell Sci, 2021), the cytoplasmic Ght5-GFP signals in Figure 4 are very likely to co-localize with vacuoles. We will modify the text to clarify this point.
As suggested, we plan to add Western blot analysis of Ght5 turnover in Aly3-expressing cells, to complement the imaging data (Figure 4) in the revised manuscript. Persistent appearance of GFP in Western blot would be a good support for vacuolar transport of Ght5-GFP.
While regulation of glucose uptake is an important issue, measurement of Ght5-dependent glucose uptake using 2-NBDG was very difficult in our hands. Another reviewer (Reviewer #2) also mentioned the difficulty of this measurement in the Referees cross-commenting section.
Figure 5: Given the localization of Ght5 shown in Figure 4, I'm surprised that it is possible in to detect full length Ght5, and its ubiquitination in the phospho-mutants of Aly3. I expected that the majority of Ght5 would be constitutively degraded, and that one would need to prevent endocytosis and/or vacuolar degradation to detect full length Ght5 and ubiquitination. Please explain the discrepancy. Also it seems that the quantification in B was performed on a single experiment.
As the aim of Figure 5 is to compare the ubiquitinated species of Ght5 among the samples expressing different species of Aly3, the loading amount of each sample was adjusted so that the abundance of immunoprecipitated Ght5 is same across them. Therefore, as the reviewer points out, before the adjustment, abundance of the full-length Ght5 might be different in these samples. In the revised manuscript, we will add explanation on this point; why the anti-GFP blot of Figure 5A has the similar intensities in those samples.
In the revised manuscript, we will add two additional replicates of the same experiment as Figure 5 in Supplementary material to show reproducibility of the result.
Figure 6: Which PPxY motif of Aly3 is used for interaction with Pub1/3 and does their interaction depend on (de)phosphorylation?
In the revised manuscript, we will discuss that "both PY motifs of Aly3 might be required for full interaction with Pub1/3," by citing the following published knowledge:
(a) Mutation of both PPxY motif of budding yeast Rod1 and Rog3 (Aly3 homologs) diminished their interaction with the ubiquitin ligase Rsp5 (Andoh et al, FEBS Lett, 2002).
(b) Mutating either one of two PPxY motifs of budding yeast Cvs7/Art1 greatly decreased interaction with WW domain, and mutating both abolished the interaction (Lin et al, Cell, 2008).
Our preliminary results indicated that Pub3 interacted with Aly3, Aly3(4th A) and phospho-mimetic Aly3(4th D), and thus suggested that the Aly3-Pub1/3 interaction does not depend on the phosphorylation status of Aly3. Consistently, budding yeast Rod1 reportedly interacts with Rsp5 regardless of its phosphorylation status (e.g. Becuwe et al, J Cell Biol, 2012). While we have partially mentioned this point in the original manuscript (L499-503), we will discuss this point more clearly in the revised manuscript.
Reviewer #1 (Significance):
The results are well presented and clear cut (with few exceptions, please see major points). They provide further evidence that metabolic cues instruct the phosphorylation of a-arrestins. Phosphorylation then negatively regulates a-arrestin function in selective endocytosis and is essential to adjust nutrient uptake across the plasma membrane to the given biological context.
We thank the reviewer for finding significance of our study. We believe that adding new results of the requested experiments and responding to the raised comments will clarify the significance of our revised manuscript.
Reviewer #2 (Evidence, reproducibility and clarity):
**Summary / background. This paper focuses on the regulation of endocytosis of the hexose transporter, Ght5, in S. pombe by nutrient limitation through the arrestin-like protein Aly3. Ght5 is induced when glucose is limiting and is required for growth and proliferation in these conditions. ght5+ encodes the only high-affinity glc transporter from fission yeast. ght5+ is induced in low glucose conditions at the transcriptional level and is translocated to the plasma membrane to allow glc import. Ght5 is targeted to the vacuole in conditions of N limitation. Mutations in the TORC2 pathway lead to the same process, thus preventing growth on low glucose medium, as shown in the gad8ts mutant, mutated for the Gad8 kinase acting downstream of TORC2. Previously, the authors demonstrated that the vacuolar delivery of Ght5 in the gad8ts mutant is suppressed by mutation of the arrestin-like protein Aly3. Arrestin-like proteins are in charge of recognising and ubiquitinating plasma membrane proteins to direct their vacuolar targeting by the endocytosis pathway. This suggested that Aly3 is hyperactive in TORC2 mutants, and accordingly, Ght5 ubiquitination was increased in gad8ts.
**Overall statement This study aims at deepening our understanding of the regulation of endocytosis by signalling pathways through arrestin-like proteins. Ght5 is a nice model to study a physiological regulation, and the authors have a great set of tools at hand. However, I think the conclusions are not always rigorous and the conclusions are sometimes far-reaching. The main problem is that much of the conclusions concern a potential phosphorylation of Aly3 which is not experimentally addressed. An additional issue is the fact that they look at Ght5 ubiquitination by co-immunoprecipitation in native conditions (or at least, it seems to me) which cannot be conclusive. Overall, I think some experiments should be performed to address (at least) these 2 points before the manuscript can be published, see detailed comments below.
We thank the reviewer for pointing both advantages and issues of our manuscript.
We admit that phosphorylation of Aly3 was not experimentally shown in our manuscript, although its phosphorylation has already been shown in phospho-proteomic studies by other groups. For this issue, we plan to add an experiment and modify the text, as explained below.
The other major issue raised by this reviewer is that detection of Ght5 ubiquitination by immunoprecipitation in a native condition cannot be conclusive. Although we noticed that many studies perform affinity purification after denaturing and precipitating proteins with TCA or acetone to detect ubiquitination of the affinity-purified protein (e.g. Lin et al, Cell, 2008), we disagree with this opinion of the reviewer #2. In a review article describing methods to study ubiquitination by immunoblotting (Emmerich and Cohen, Biochem Biophys Res Comm, 2015), affinity purification of the protein of interest in a native condition is mentioned as one major choice. Moreover, a denaturing condition was not applicable to detect ubiquitinated Ght5 because the Ght5 protein that is once denatured and precipitated with TCA cannot be re-solubilized for immune-purification and -blotting. As the reviewer points out, a pitfall of detection of ubiquitinated Ght5 in a native condition is the presence of co-immunoprecipitated proteins. In our previous study (Toyoda et al, J Cell Sci, 2021), we purified GFP-tagged Ght5 and showed that a 110 kDa band detected in an anti-Ub immunoblot was also recognized by an anti-GFP antibody, confirming that the detected 110 kDa band corresponded to an ubiquitinated species of Ght5, but not a co-immunoprecipitated protein. Similarly, in the revised manuscript, we will add a panel of high-contrast (over-exposed) anti-GFP immunoblot, in which the indicated 110 kDa band was clearly detected by an anti-GFP antibody, in Figure 5A.
We appreciate these issues raised by the reviewer #2. By responding to them, we believe that conclusions of our study will be more rigorous and undoubtful in the revised manuscript.
**Major statements and criticism.
*Fig 1. Based on the hypothesis that TORC2-mediated phosphorylation regulate Ght5 endocytosis, the authors first considered a possible phosphorylation of Ght5. They mutagenised 11 **possible** phosphorylation sites on the Ct of Ght5, but none affected the growth on low glucose in the absence of thiamine, suggesting that they don't contribute to the observed TORC2-mediated regulation. However, I disagree with the statement that "phosphorylation of Ght5 is dispensable for cell proliferation in low glucose", given that the authors do not show 1- that Ght5 is phosphorylated and 2-that this is abolished by these mutations. They should either provide data on this or tone down and say that these residues are not involved in the regulation, without implying phosphorylation which is not proven.
Although we did not experimentally test whether these 11 residues of Ght5 was phosphorylated in our hand, these residues have been shown to be phosphorylated in phospho-proteomics studies by other groups (Kettenbach et al, Mol Cell Proteomics, 2015; Swaffer et al, Cell Rep, 2018; Tay et al, Cell Rep, 2019; Halova et al, Open Biol, 2021; Mak et al, EMBO J, 2021). In the revised manuscript, we plan to be more precise by replacing this conclusion with the following statement: "11 Ser/Thr residues of Ght5, which are reportedly phosphorylated, are not essential for cell proliferation in low glucose."
In the presence of Thiamine (Supp fig 1), it seems that the ST/A mutant grows better in low glucose, and this is not explained nor commented. Since the transporter is not expressed, could the authors provide an explanation to this? If the promoter is leaky and some ght5-ST/A is expressed, it may be more stable and allow better growth than the WT, which would tend to indicate that impairing phosphorylation prevents endocytosis (which is classical for many transporters, see the body of work on CK1-mediated phosphorylation of transporters). Have the authors tried to decrease glc concentration lower than 0.14% in the absence of thiamine to see if this also true when the transporters is strongly expressed? (OPTIONAL)
Improved growth of Ght5(ST11A)-expressing cells in the presence of thiamine was mentioned in the legend of Supplementary Figure 1A. In the revised manuscript, we will mention this observation also in the main text for better description of the results.
Adding thiamine to medium does not completely shut off transcription from the nmt1 promoter but allows some transcription, as previously reported (Maundrell, J Biol Chem, 1990; Forsburg, Nuc Acid Res, 1993). In the revised manuscript, we will mention this "leakiness" of the nmt1 promoter and, by citing the suggested studies, will discuss a possibility that the ST11A mutations might prevent endocytosis of Ght5 and consequently promote cell proliferation in low glucose conditions.
We found that, in the absence of thiamine, cells expressing ght5+ and ght5(ST11A) proliferated to the comparable extent on medium containing 0.08% glucose. This result will be added to the revised manuscript.
*Fig 2. The authors then follow the hypothesis that TORC2 exerts its Ght5-dependent regulation through the phosphorylation of Aly3. They mutagenised 18 **possible** phosphorylation sites on Aly3. This led to a strong defect in growth in low-glc medium. Mutation of the possible Gad8 site (S460) did not recapitulate this phenotype, suggesting that it is not sufficient, however, mutations of 4 ST residues in a CT cluster (582-586) mimicked the full 18ST/A mutation, suggesting these are the important residues for Ght5 endocytosis.
We thank the reviewer for appreciating the results in Fig. 2. As we explain below, we plan to perform an additional experiment to show that the Aly3 C-terminus is phosphorylated. With this result, our model will gain another experimental support.
*Fig 3A. Further dissection did not allow to pinpoint this regulation to a specific residue, beyond the dispensability of the T586 residue. Fig 3B. The authors look at the effects of mutation of Aly3 on these sites at the protein level. They had to develop an antibody because HA-epitope tagging did not lead to a functional protein (Supp fig 2). Whereas I agree that the mutations causing a phenotype lead to a change in the migration pattern, I disagree with the statement that "This observation indicated that slower migrating bands were phosphorylated species of Aly3" (p.9 l.271). First, lack of phosphorylation usually causes a slower mobility on gel, which is not clear to spot here. Second, a smear appears on top of the mutated proteins (eg. 4th Ala) which is possibly caused by another modification. There are many precedents in the literature about arrestins being ubiquitinated when they are not phosphorylated (see the work on Bul1, Rod1, Csr2 in baker's yeast from various labs). My gut feeling is that lack of phosphorylation unleashes Aly3 ubiquitination leading to change in pattern. All in all, it is impossible to state about the phosphorylation of a protein without addressing its phosphorylation properly by phosphatase treatment + change in migration, or MS/MS. Thus, whereas the data looks promising, this hypothesis that Aly3 is phosphorylated at the indicated sites is not properly demonstrated.
We disagree with the reviewer's opinion that a lack of phosphorylation usually causes slower mobility on gel. There are many examples in which phosphorylation causes slower mobility on gel, including budding yeast Rod1 (Alvaro et al, Genetics, 2016), and mammalian TXNIP (Wu et al, Mol Cell, 2013). In the revised manuscript, we will cite these reports to support our interpretation that the slower migrating bands are likely phosphorylated species of Aly3 (L270-271).
Smear-like signals in Aly3(4th Ala), Aly3(4th A;A584S) and Aly3(4th A;A586T) might result from some modification, but identity of the modification is unknown. As the reviewer #2 mentioned, phosphorylation on Aly3 might negatively regulate another modification. The precedent studies revealed that budding yeast Rod1 and Rog3 arrestins tend to be ubiquitinated in snf1/AMPK-deficient cells (Becuwe et al, J Cell Biol, 2012; O'Donnell et al, Mol Cell Biol, 2015), and that Bul1 arrestin is dephosphorylated and ubiquitinated in budding yeast cells deficient in Npr1 kinase (Merhi and Andre, Mol Cell Biol, 2012). Also, budding yeast Csr2 arrestin is deubiquitinated and phosphorylated upon glucose replenishment, while non-phosphorylated Csr2 is ubiquitinated and activated by Rsp5 (Hovsepian et al, J Cell Biol, 2012). While the smear-like signals are interesting, we noticed that the smear-like signals did not necessarily correlate with cell proliferation defects in low glucose. We therefore think that clarifying the identity of the smear-like signals is beyond the scope of this study. We will discuss the smear-like signals only briefly in the revised manuscript, and would address this issue in our future work, hopefully.
While the 4 S/T residues at the C-terminus of Aly3 as well as the other 14 S/T residues have been already shown to be phosphorylated in the precedent studies (Kettenbach et al, Mol Cell Proteomics, 2015; Tay et al, Cell Rep, 2019; Halova et al, Open Biol, 2021), we will confirm that the slower migrating Aly3 is indeed phosphorylated by phosphatase treatment in the revised manuscript. This planned experiment will further strengthen our study and support our conclusion and model.
*Fig 4. The authors now look at the functional consequences of these mutations on ALy3 on Ght5 localisation. The data clearly shows that mutation of the 4 identified S/T residues (Aly3-4th A) causes aberrant localisation of the transporter to the vacuole, likely to cause the observed growth defect on low glucose. There is a nice correlation between the vacuolar localisation and growth in low-glucose for the various aly3 mutants. (A final proof could be to express this in the context of an endocytic mutant, which should restore membrane localisation and suppress the aly3-4thA phenotype - OPTIONAL). However, I still disagree with the statement that "These results indicate that phosphorylation of Aly3 at the C-terminal 582nd, 584th, and/or 585th serine residues is required for cell-surface localization of Ght5." given that phosphorylation was not properly demonstrated.
While phosphorylation of the 582nd, 584th and/or 585th serine residues of Aly3 is not experimentally demonstrated in our hands, they have been shown to be phosphorylated in phospho-proteomics studies by other groups (Kettenbach et al, Mol Cell Proteomics, 2015; Tay et al, Cell Rep, 2019; Halova et al, Open Biol, 2021; Mak et al, EMBO J, 2021). Among them, the 584th serine residue (S584) was reported to be phosphorylated in a TORC2-dependent manner (Mak et al, EMBO J, 2021), consistent with our model. To explicitly demonstrate that S584 is phosphorylated, we plan to make a strain expressing a mutant Aly3 protein in which all the possible phosphorylation sites except S584 are replaced with alanine, namely Aly3(ST17A;S584). Hopefully, we can properly show the phosphorylation of S584 by measuring the mobility of the Aly3(ST17A;S584) on gel with/without phosphatase treatment or gad8 mutation.
We thank the reviewer for suggestion of the experiment using an endocytic mutant. Previously we reported that vacuolar localization of Ght5 in gad8 mutant cells was suppressed by mutations in not only aly3 but also genes encoding ESCRT complexes (Toyoda et al, J Cell Sci, 2021). We therefore think that in cells expressing Aly3(ST18A) or Aly3(4th Ala), Ght5 is subject to endocytosis and ensuing selective transport to vacuoles via endosome-localized ESCRT complexes. We will discuss this point in the revised manuscript.
*Fig 5. Here, the authors question the role of Aly3 mutations on Ght5 ubiquitination. They immunoprecipitate Ght5 and address its ubiquitination status in various Aly3 mutants. The data is encouraging for a role in Aly3 phosphorylation (?) in the negative control of Ght5 ubiquitination. My main problem with this experiment is that it seems that Ght5 immunoprecipitations were made in non-denaturing conditions, which leads to the question of what is the anti-ubiquitin revealing here (Ght5 or a co-immunoprecipitated protein, for example Aly3 itself, or the Pub ligases, or an unknown protein). It seems that this protocol was previously used in their previous paper, but I stand by my conclusion that ubiquitination of a given protein can only be looked in denaturing conditions. The experiments should be repeated in buffers classical for the study of protein ubiquitination to be able to conclude unambiguously that we are looking at Ght5 ubiquitination itself, especially in the absence of a non-ubiquitinable form of Ght5 as a negative control. Could the authors comment on the fact that S-A or S-D mutations display the same phenotype regarding the possible Ght5 ubiquitination?
As mentioned above, immunoprecipitation of Ght5 in denaturating conditions is not feasible. Ght5 can be affinity-purified only in a non-denaturing condition. In addition, affinity purification in a native condition is considered as a major choice to examine its ubiquitination according to a literature by Emmerich and Cohen (Emmerich and Cohen, Biochem Biophys Res Comm, 2015). A drawback of native condition is, as the reviewer points out, that the affinity-purified fraction might include non-bait (non-Ght5) proteins. The 110 kDa band indicated by an arrow in Fig. 5A was confirmed to be Ght5, not a non-bait protein, as a band at the identical position was detected in the immunoblot with anti-GFP antibody. Because this band in the anti-GFP immunoblot was too faint to be visible in Fig. 5A of the original manuscript, we will add an additional panel showing the contrast-enhanced anti-GFP immunoblot in which the 110 kDa band is clearly visible.
As for the result that "S-A or S-D mutations display the same phenotype regarding the possible Ght5 ubiquitination," we are afraid that the reviewer #2 misunderstood the labels of the samples. We apologize for confusing notational system of the sample name. Full description of samples is as follows; In Aly3(4th A), all of S582, S584, S585 and T586 are replaced with A; In Aly3(4th A;A584S), S582, S585 and T586 are replaced with A, whereas S584 remains intact; In Aly3(4th A;A584D), S582, S585 and T586 are replaced with A, and S584 is replaced with phospho-mimetic D. Because cells expressing Aly3(4th A;A584S) and Aly3(4th A;A584D) exhibited similarly low levels of Ght5 ubiquitination, we speculated that phosphorylation at S584 of Aly3 negatively regulates ubiquitination of Ght5.
In the revised manuscript, we plan to add a table showing amino acid sequence of each species of Aly3 (just like Figure 3A) to avoid confusion.
*Fig 6. The authors want to document the model whereby Aly3 may interact with some of the Nedd4 ligases (Pub1/2/3) to mediate its Ght5-ubiquitination function. They actually use the Aly3-4thA mutant, it should have been better with the WT protein. But the results indicate a clear interaction with at least Pub1 and Pub3. By the way, are the Pub1/2/3 fusions functional? Nedd4 proteins are notoriously affected in their function by C-terminal tagging and are usually tagged at their N-terminus (See Dunn et al. J Cell Biol 2004).
We plan to test whether Pub1-myc is functional by comparing proliferation of the Pub1-myc-expressing strain and pub1Δ strain, as pub1Δ cells reportedly show proliferation defects at a high temperature (Tamai and Shimoda, J Cell Sci, 2002). As deletion of pub2 or pub3 reportedly exhibited no obvious defects (Tamai and Shimoda, J Cell Sci, 2002; Hayles et al, Open Biol, 2013), it is not easy to assess functionality of the myc-tagged genes.
Please note that C-terminally tagged Pub1/2/3 proteins have been widely used in studies with fission yeast. Both Pub1-HA and non-tagged Pub1 were reported to be ubiquitinated (Nefsky and Beach, EMBO J, 1996; Strachan et al, J Cell Sci, 2023). Pub1-GFP, which complemented the high temperature sensitivity of pub1Δ, localized to cell surface and cytoplasmic bodies (Tamai and Shimoda, J Cell Sci, 2002). Pub2-GFP, overexpression of which arrested cell growth just like overexpression of non-tagged Pub2, localized to cell surface, and consistently Pub2-HA was detected in membrane-enriched pellet fractions after ultracentrifugation (Tamai and Shimoda, J Cell Sci, 2002). They also reported ubiquitin conjugation of the HECT domain of Pub2 fused with myc epitope at its C-terminus. Pub3-GFP localized to cell surface (Matsuyama et al, Nat Biotech, 2006).
Regardless of functionality of the myc-tagged Pub1/2/3, we believe that results of this experiment (Figure 6) support our model, because the aim of this experiment, which is to identify the HECT-type and WW-domain containing ubiquitin ligase(s) that interact with Aly3, is irrelevant to functionality of the myc-tagged Pub proteins.
*Fig 7. The authors want to provide genetic interaction between the Pub ligases and the growth defects in low glc due to alterations in Ght5 trafficking. It is unclear how the gad8ts pub1∆ mutant was generated since it doesn't seem to grow on regular glc concentration (Supp fig 5), could the authors provide some information about this? It is also not clear whether it can be stated thatches mutant is "more sensitive" to glc depletion because of the low level of growth to begin with (even at 3%). Altogether, the data show that deletion of pub3+ is able to suppress the growth defect of the gad8ts mutant on low glc medium, suggesting it is the relevant ligase for Ght5 endocytosis. This is confirmed by microscopy observations of Ght5 localisation. However, I would again tone down the main conclusion, which I feel is far-reaching: "Combined with physical interaction data, these results strongly suggest that Aly3 recruits Pub3, but not Pub2, for ubiquitination of Ght5." Work on Rsp5 in baker's yeast has shown that Rsp5 function goes beyond cargo ubiquitination, including ubiquitination of arrestins (which is often required for their function as mentioned in the introduction) or other endocytic proteins (epsins, amphyphysin etc). I agree that the data are compatible with this model but there are other possible explanations. Anything that would block endocytosis would supposedly suppress the gad8ts phenotype.
gad8ts pub1Δ was produced at 26 {degree sign}C, a permissive temperature of the gad8ts mutant. While this is described in the Methods section of the original manuscript, we will mention this more clearly in the Results section of the revised manuscript.
We did not conclude low glucose sensitivity of gad8ts pub1Δ cells in the indicated part (L376-377). Rather, we compared proliferation of gad8ts single mutant and pub1Δ single mutant cells in low glucose, and we found that the pub1Δ single mutant exhibited the higher sensitivity. In the revised manuscript we will correct the text to clarify that we compared proliferation of two single mutants (but not gad8ts pub1Δ mutant).
We agree with the opinion that the recruited Pub3 may ubiquitinate proteins other than Ght5. In the revised manuscript, we will correct our conclusion of the Figure 7 experiment (L388-390), not to limit the possible ubiquitination target(s) to Ght5.
In a genetic screen, we found that mutations in aly3+ and genes encoding ESCRT complexes suppressed low-glucose sensitivity and vacuolar transport of Ght5 of gad8ts mutant cells (Toyoda et al, J Cell Sci, 2021). This finding appears consistent with the reviewer's opinion that blocking endocytosis would supposedly suppress the gad8ts phenotype. We will mention this point in the revised manuscript.
*Discussion Some analogy with the regulation of the Bul arrestins by TORC1/Npr1 and PP2A/Sit4 could be mentioned (Mehri et al. 2012), at the discretion of the authors. The possibility that phosphorylation may neutralise a basic patch on Aly3 Ct, possibly involved in electrostatic interactions with Ght5 is very interesting. Regarding the effect of the mutations on Aly3 localisation (p.15 l.498), did the authors tag Aly3 with GFP? There are examples where proteins tagged with HA are not functional whereas tagging with GFP does not alter their function (eg. Rod1, Laussel et al. 2022) - and here Supp Fig 2 only relates to HA-tagging. Proof of a change in Aly3 localisation upon mutation would definitely be a plus (OPTIONAL).
We thank the reviewer for the suggestion of a reference. In the revised manuscript, we will cite the indicated report in the corresponding part for an additional support of TORC1-mediated control of Aly3 (de)phosphorylation.
While examining localization of Aly3 by GFP-tagging is interesting, we do not believe that it is necessary in this study. We would like to produce Aly3-GFP and to examine its functionality and localization in our future study. We thank the reviewer's insightful suggestion.
**Minor comments.
*Introduction: - I believe the text corresponding to the work on TXNIP is incorrect (p.5 l.127). TXNIP is degraded after its phosphorylation, not "rectracted" from the surface.
In the revised manuscript, we will correct the text accordingly.
- For the sake of completion, the authors could add other references concerning the regulation of Rod1 in budding yeast such as Becuwe et al. 2012 J Cell Biol and O'Donnell et al. 2015 Mol Cell Biol, in addition to Llopis-Torregrosa et al. 2016.
In the revised manuscript, we will add the suggested references and correct the text in the corresponding part of the Introduction (L123-138).
- Other examples of the requirement for arrestin ubiquitination beyond Art1 (p.5 l.136-137) are listed in the ref cited: Kahlhofer et al. 2021.
We will cite the indicated review to navigate readers for more examples of arrestin ubiquitination (and transporter ubiquitination).
*Figures: In general, I think it would be clearer if the authors showed on the figures that the background strain in which the XXX gene is added (or its mutant forms) is a xxx∆ strain.
We will modify the figures to clearly show the genetic background of the strains used.
**Referees cross-commenting**
Cross review of Reviewer 1 - *I don't believe that the authors "define a set of redundant c-terminal phosphorylation sites in Aly3", because phosphorylation is not proven. *I thinks the points raised for Fig 3B are valid but the authors should focus on making their story conclusive before expanding to other data (except for the explanation of the smear, see my review). Also, I don't think 2NBDG actually works to measure Glc uptake. * same for Fig 6 - not sure the interaction site mapping between Aly3 and Pubs would bring much value since there are more urgent things to do to make the story solid.
As mentioned above, we will experimentally show phosphorylation of the Aly3 C-terminus in the revised manuscript. Such experiments would make our story more solid and conclusive. We truly appreciate the comments and suggestions.
We agree with the comments on difficulty of measuring glucose uptake using 2-NBDG. In fact, we tried and failed measuring Ght5-mediated glucose uptake using 2-NBDG.
Cros review of Reviewer 3 - we have many overlaps, so briefly : *I agree that the bibliography is incomplete (mentioned in my review) *I agree that there is no demonstration of the phospho-status of Aly3, and it is a problem *I agree that the results can be better quantified, esp. in the light of the points raised by this referee concerning the variability of expression of ST18A Other specific comments : *I agree that the statement that dephosphorylation activates alpha-arresting should be toned down - this was observed in several instances but there are examples of arrestin-mediated endocytosis which does not require their prior dephosphorylation. *I fully agree that efforts could be made regarding the classification/nomenclature of arrestins in S. pombe, this had escaped my attention
As detailed in the individual point raised by the reviewers, we will add the suggested references and accordingly correct the text in the revised manuscript.
In addition to experimentally showing Aly3 phosphorylation, we will quantify the immunoblot result.
Our statement that dephosphorylation activates alpha-arrestins might be too generalized. We will mention reports in which arrestin-mediated endocytosis does not require prior dephosphorylation (e.g. O'Donnell et al, Mol Biol Cell, 2010; Gournas et al, Mol Biol Cell, 2017; Savocco et al, PLoS Biol, 2019), and modify the text precisely.
Reviewer #2 (Significance):
*strengths and limitations This study aims at deepening our understanding of the regulation of endocytosis by signalling pathways through arrestin-like proteins in S. pombe. Ght5 is a nice model to study a physiological regulation, and the authors have a great set of tools at hand, including the discovery of Aly3 as the main arrestin for this regulation, and a signalling pathway (TORC2/Gad8) acting upstream. The main question is now to understand at the mechanistic level how TORC2 signaling impinges on the regulation of this arrestin.
Overall, the authors nicely demonstrate that C-terminal Ser/Thr residues are crucial for the function of Aly3 in Ght5 endocytosis. They propose a model whereby Aly3 phosphorylation by an unknownn kinase inhibits its function on Ght5 ubiquitination, which would favour its endocytosis. However, I think the conclusions are not always rigorous and the conclusions are sometimes far-reaching. The main problem is that much of the conclusions concern a potential phosphorylation of Aly3 which is not experimentally addressed. An additional issue is the fact that they look at Ght5 ubiquitination by co-immunoprecipitation in native conditions (or at least, it seems to me) which cannot be conclusive. Overall, I think some experiments should be performed to address (at least) these 2 points before the manuscript can be published, see detailed comments above.
*Advance
This study, if completed carefully, would provide among the first examples of mapping of phosphorylation sites on arrestins, which are usually phosphorylated at many sites and are thus difficult to study. Few studies went down to this level in this respect (see Ivshov et al. eLife 2020). There are no changes in paradigms or new conceptual insights, but this work is a nice example of the conservation of these regulatory mechanisms.
We appreciate that this study is highly evaluated by this reviewer. We understand the main problems raised by the reviewer, and as we detailed above, we plan to perform an experiment and make explanation to respond to the problems. With the raised issues answered, we believe that conclusions of the revised manuscript will be more rigorous.
Our study reveals mechanisms regulating vacuolar transport of the Ght5 hexose transporter via the TORC2 pathway in fission yeast. The serine residues at the Aly3 C-terminus (582nd, 584th and 585th serine residues), which are probably phosphorylated in a manner dependent on the TORC2 pathway, are required for sustained Ght5 localization to cell surface and cellular adaptation to low glucose. To our knowledge, there is no such study, and thus we think that this study is novel. By responding to the reviewers' comments and adding new data as explained above, the revised manuscript will be able to present novelty of our study more clearly. Comparison of our study in fission yeast to related studies in other model organisms may reveal the conservation and diversity of these regulatory mechanisms.
*Audience Should be of interest for people studying basic research in the field of cell biology, signalling pathways, transporter regulation by physiology. Reviewer background is on the regulation of transporter endocytosis by signalling pathways and arrestin-like proteins.
Reviewer #3 (Evidence, reproducibility and clarity): (Authors' response in blue)
In this manuscript, the authors work to address how phospho-regulation of a-arrestin Aly3 in S. pombe regulates the glucose transporter Ght5. The authors use a series of phospho-mutants in Aly3 and assess function of these mutants using growth assays and localization of Ght5. My main concerns with the manuscript are that 1) there is a lack of appreciation for the similar work that has been done in S. cerevisiae to define a-arrestin phospho-regulation, which is evidenced by the severe lack of referencing throughout the document, 2) the sites mutated on Aly3 are not demonstrated to change phospho-status of Aly3 and so all interpretations of these mutants need to be better contextualized and 3) almost none of the findings are quantified (imaging or immunoblots) making it difficult to assess the rigor of the outcomes. More detailed comments are provided below.
We thank the reviewer for thorough reading of the manuscript and the detailed comments. As explained below, we will respond to the points raised by the reviewer and accordingly modify the manuscript.
Minor Comments
Immunoblotting or immunostaining to define the levels and localization of phospho-mutants - In Figure 1, an immunoblot or immunostaining to define the abundance/localization of WT Ght5 vs its ST11A mutant would be appreciated. It is very difficult to know if ST11A is as functional as WT or not without an assessment of the levels and localization of the WT and mutant proteins to accompany the spot assays. Perhaps a version of Ght5 that is a phospho-mimetic would be more useful here as well since that version should not be dephosphorylated and then presumably would be internalized and not allow for growth on low glucose medium.
We plan to add fluorescence microscopy data of WT Ght5 and Ght5(ST11A) in the revised manuscript, to compare the localization and abundance of these two Ght5 species. In our preliminary observation, those of two Ght5 species seemed to be indistinguishable.
We'd like to emphasize that the primary aim of this study is to reveal mechanisms regulating Ght5 localization and consequently ensuring cell proliferation in low glucose. While analyzing a phospho-mimetic Ght5 mutant (e.g. Ght5(ST11D)) is interesting in terms of understanding of the nature of Ght5, we believe that such an analysis is out of the scope on this study. As Ght5(ST11A)-expressing cells proliferated comparably to Ght5(WT)-expressing cells and WT and ST11A Ght5 indistinguishably localize on the cell surface, phosphorylation of the ST residues of Ght5 is not likely to be the primary mechanism regulating Ght5 localization and function. We would like to assess a phospho-mimetic Ght5 mutant protein in our future studies.
For the Aly3 mutants where the abundance of Aly3 appears lower via immunoblotting (i.e., 4thA-A582S or S582A) how is the near perfect functional readout explained when the levels of the protein are much lower than WT? For the ST18A mutant, this is a particularly important point since the authors indicate on lines 194-197 that based on the functional data for ST18A, some of these ST residues are needed for phospho-regulation of Aly3. However, in Figure 3B the authors clearly show that there is very little ST18A protein in cells, and so these mutations have impacted Aly3 stability, which may or may not be linked to its phospho-status. The authors should be upfront about this finding on lines 194-197 and should not present this phospho-model as the only reason for why ST18A may not be functional. On lines 265-276 for the authors indicate that ST18A is expressed equivalently to WT Aly3, which is just not the case in Figure 3B. Perhaps quantification of replicate data would help clarify this issue. Further, if the authors wish to conclude that the upper MW bands in Figure 3B are due to phosphorylation, perhaps they should perform phosphatase treatments of their extracts to collapse these bands. However, most certainly the overall abundance of the single band for ST18A is reduced compared to the total bands of WT Aly3.
We disagree with the opinion that the levels of the mutant Aly3 are much lower than WT. For semi-quantitative measurement of the protein abundance, 2-fold dilution series of the WT Aly3 sample were loaded in the leftmost 3 lanes of Figure 3B. Although the levels of Aly3(4th A;A582S), Aly3(S582A) and Aly3(ST18A) were lower than that of WT Aly3, those are 50% or more of the WT, judging from the intensities of the serially-diluted WT samples. To clearly show that the expression of these Aly3 proteins is within comparable levels, we plan to add a column chart of the quantified expression levels and to mention abundances of the Aly3 proteins more quantitatively in the revised text. We do not think that replicate data (of Western blots as in Figure 3B) helps clarify this issue, because nmt1 promoter-driven gene transcription is induced with a small variation (Forsburg, Nuc Acid Res, 1993). We will cite this report and mention this point in the revised text.
We are afraid that this reviewer seems to consider that Aly3(ST18A) is not functional, but it is not a case and we do not intend to claim so. While deletion of aly3 did not interfere with cell proliferation in low glucose (see vector controls in Figures 2B, 2C and 3A, -Thiamine), expression of the ST18A mutant clearly hinders cell proliferation in low glucose, indicating that the ST18A performs dominant negative function to inhibit cell proliferation. That is, even though the expression level and/or stability of the ST18A is reduced, it is still sufficiently abundant to perform the dominant negative function. We propose the phospho-model not due to dysfunctionality of ST18A, but its dominant negative functionality. The 18 S/T residues of Aly3, which are shown to be phosphorylated in precedent phospho-proteomics studies, seem to be required to down-regulate Aly3's function to inhibit cell proliferation in low glucose. We apologize for this confusion, and we will modify the text and figures to clarify these points in the revised manuscripts.
To obtain an experimental support for our description that the slower migrating bands in Figure 3B are due to phosphorylation, we plan to perform a phosphatase treatment experiment as suggested.
Figure 2A - how do the phosphorylation sites identified in Aly3 compare to those identified in Rod1 from S. cerevisiae? See PMID 26920760 or SGD for more information. I am confused as to why the Aly3 protein has an arrowhead at the C-terminus. What does this denote?
We will mention reported phosphorylation sites of Aly3 and budding yeast Rod1/Art4 in the revised manuscript, by referring to the indicated report and database. It should be noted that similarity between amino acid sequences of Aly3 and S. cerevisiae Rod1 is not so high and limited in Arrestin-N and -C domains. The C-terminal half of Aly3, in which most of the potential phosphorylation sites are found, is not similar to Rod1. Thus, these sites are unlikely to be conserved between them.
An arrowhead indicates the direction of transcription (from N to C-terminus). We will describe it explicitly in the revised figure legend.
Figure 2 - The WT and Aly3-ST18A are expressed in S. pombe from a non-endogenous locus under the control of the Nmt1 promoter. However, are these mutants present in cells that contain WT copies of Aly3 at other genomic loci? If so, this would surely muddy the interpretations of these data as a- and b-arrestins are capable of multimerizing and the effect of multimerization on their activities can vary.
As mentioned in L188, an aly3 deletion mutant strain (aly3Δ) was used as a host, and thus all strains harboring an nmt1-driven aly3 gene lack the endogenous aly3 gene. We will add an illustration clearly showing that the host strain lacks the endogenous aly3+ gene and modify the legend of Figure 2.
Functional readouts for Aly3 using Ght5 localization - The reduced surface levels of Ght5 does correspond to the spot assay growth in low glucose for the various Aly3 mutants used. However, it would be useful if these assays incorporated an endocytosis inhibitor to help prevent the activities of these Aly3 plasmids to see if the transporter is retained at the PM. At the end of these mutational analyses, the authors conclude that phosphorylation of Aly3 at any of 3 sites is required for Ght5 trafficking to the vacuole in low glucose, however no experiment is done to demonstrate that these sites are phosphorylated residues. A phosphatase assay would be useful to help demonstrate that the modifications in 3B really are phosphorylation and a quantification of the phosphorylated bands in these WBs would also be useful to solidify the statement made on lines 306-309.
We thank the reviewer for suggestion of the experiment using an endocytosis inhibitor. Previously we reported that vacuolar localization of Ght5 in gad8ts mutant cells was suppressed by mutations in not only aly3 but also genes encoding ESCRT complexes (Toyoda et al, J Cell Sci, 2021). We therefore think that, in cells expressing Aly3(ST18A) or Aly3(4th Ala), Ght5 is subject to endocytosis and subsequent selective transport to vacuoles via ESCRT complexes. We will mention these previous findings in the revised manuscript.
As mentioned in responses to the comments above and other reviewer's, we will perform a phosphatase treatment experiment and its quantification in the revised manuscript. Here, we'd like to emphasize that these 3 sites have been shown to be phosphorylated in phospho-proteomic studies by other researchers (Kettenbach et al, Mol Cell Proteomics, 2015; Tay et al, Cell Rep, 2019; Halova et al, Open Biol, 2021; Mak et al, EMBO J, 2021), although we do not show it directly in this study.
Phosphorylation assessments - in general, it would be good to not only build the non-phosphorylatable versions of Aly3 but also the phospho-mimetic forms.
We produced a phospho-mimetic mutant Aly3 (i.e. Aly3(4th A;A584D)), and showed the result in Figure 5A; cells expressing Aly3(4th A;A584D) exhibited a low ubiquitination of Ght5, similarly to Aly3(WT)- and Aly3(4th A;A584S)-expressing cells. According to our experiences, replacing S/T with D/E does not necessarily mimic phosphorylation. Thus, we do not believe that systematic production of phospho-mimetic Aly3 mutants would help achieve the aim of this study.
Pub1, 2, and 3 - It would be helpful if the authors indicated what genes Pubs 1-3 correspond to in S. cerevisiae, where Rsp5 is the predominant Ub ligase interacting with a-arrestins. Is there no ortholog of Rsp5 in S. pombe?
Pub1, Pub2 and Pub3 are regarded as orthologs of budding yeast Rsp5, according to the fission yeast database PomBase. We will perform a homology search for these E3 proteins, and based on the result, we will add a description in the revised manuscript.
Pub-Aly3 interactions - could the authors please comment on the reason why so very little Aly3 is copurified with Pub1 or Pub2? Can any clear conclusion be drawn about pub2 given how very little Pub2 is present in the IPs? Based on my understanding of these data I do not think that this can be cleanly interpreted. What is is the identity of the ~50kDa MW band in Figure 6 in the upper MYC detection panel?
We do not have an accurate answer for the result that a small amount of Aly3 is copurified with Pub1 or Pub3. The Pub1/3-Aly3 interaction may be weak or transient. We will discuss this point in the revised manuscript.
Regarding whether Aly3 interacts with Pub2, we agree with the reviewer. As described in the Results (L360-362), we could not conclude anything about Aly3-Pub2 interaction by this immunoprecipitation experiment alone. On the other hand, the genetic interaction experiment (Figure 7A) suggests that pub2+ is not involved in defects caused by the gad8ts mutation (while pub3+ and aly3+ are). By this experiment, we think that Pub2 is not a partner of Aly3.
In the revised manuscript, we will describe that Pub2 is not a partner of Aly3 in a paragraph describing the Figure 7A experiment.
Because the 50 kDa band found in the IP fraction of all the samples appears even in "beads only" (Figure 6), those are supposedly derived from mouse IgG dissociated from the beads used for immunoprecipitation. We will mention this in the legend of Figure 6.
Phosphorylation and ubiquitination of a-arrestins - The paragraph from lines 123-138 is very superficial in addressing what is known about phosphorylation and ubiquitination of a-arrestins. The way this section is written, it feels misleading to the reader as it omits many of the details for regulation that would help place the current study in context. The discussion of Rod1 phosphorylation by AMPK for example, which is directly relevant to this study, is underdeveloped. I would recommend splitting this into two paragraphs and providing a more in depth, and accurate, view of the literature on this topic, with a focus on the regulation that is relevant for the ortholog of Aly3 in S. cerevisiae. For example, Rod1 phosphorylation by AMPK is greatly expanded upon in the following papers (PMID 22249293 and 25547292) and AMPK regulation of C-tail phosphorylation of a-arrestins is defined further in PMID 26920760. These references are each particularly important to compare with the current findings presented in this manuscript. Torc2 regulation ofa-arrestins is also reviewed in PMID 36149412 and references therein should be considered.
Because the primary aim of this study is to reveal mechanisms regulating Ght5 localization in fission yeast, but not to dissect modification and regulation of α-arrestins, we decided not to get into the details of phosphorylation and ubiquitination of α-arrestins. Furthermore, although budding yeast Rod1 and Rog3 are found to be downstream of the TORC2-Ypk1 signaling in the context of internalization of the Ste2 pheromone receptor, it is not clear whether TORC2-Ypk1 signaling also regulate α-arrestin-mediated internalization of hexose transporters in budding yeast. For these reasons, we focused on limited literatures essential for interpretation of the results and omitted many references describing the details of α-arrestin regulation. However, as this reviewer commented, we realize that our decision makes the discussion superficial and misleading to the reader. We sincerely apologize for this inconvenience.
In the revised manuscript, we will reorganize the paragraphs in the discussion and include the suggested references. Regarding budding yeast Rod1, we will cite the study reporting Ypk1-mediated phosphorylation on Rod1 in mating pheromone response via regulation of Ste2 endocytosis (Alvaro et al, Genetics, 2016). We will also mention other reports (Becuwe et al, J Cell Biol, 2012; O'Donnell et al, Mol Cell Biol, 2015) about AMPK-dependent phosphorylation of Rod1 in the corresponding part (e.g. L129-130). In addition, we will mention that Aly2, Rod1 and Rog3 α-arrestins were found downstream of the TORC2-Ypk1 signaling (Muir et al, eLife, 2014; Thorner, Biochem J, 2022).
As a further detailed example, there is far more work done on ubiquitination of a-arrestins in S. cerevisiae than the single citation provided by the authors on line 137. The way this section is written it feels misleading. Considerable effort has been spent on defining how mono- and poly-ubiquitination regulate a-arrestins and the authors should consider the data provided in the following citations and revise the two sentences they provide in this introduction to better reflect the breadth of our understanding rather than simply indicate that the 'mechanisms that regulate functions of a-arrestisn are not fully understood'. (PMIDs 23824189; 22249293; 17028178; 28298493)
Ubiquitination of α-arrestin itself is not the topic of this study, and physiological consequences of ubiquitination of Aly3 remain unknown. Because of these reasons, we did not describe the details of ubiquitination of α-arrestins in the original manuscript. However, we never intend to mislead the reader, and thus to avoid it, we will revise the indicated sentences and cite the suggested literatures (O'Donnell et al, J Biol Chem, 2013; Becuwe et al, J Cell Biol, 2012; Kee et al, J Biol Chem, 2006; Ho et al, Mol Biol Cell, 2017) in the revised manuscript.
Context of the findings and lack of citations - The referencing in this manuscript is very poor as many of the key papers that report analogous findings in the budding yeast Saccharomyces cerevisiae are not cited. This oversight in citing the appropriate literature must be remedied before this manuscript can be considered further for publication. Examples of these omissions occur at the following places:
We will modify the text and carefully cite more literatures describing analogous finding in budding yeast and other organisms in the revised manuscript. We appreciate the insightful suggestions by this reviewer. It should be noted, however, that it is not evident whether budding yeast Rod1 and Rog3 are orthologous to fission yeast Aly3. Although Rod1 and Aly3 share overlapping roles, amino acid sequence similarity of them is not high and limited only in domains which are generally conserved among α-arrestin-family proteins.
Line 90 - The Puca and Brou citations is one example of this but the first examples come from Daniela Rotin's work looking at Rsp5 interactions in budding yeast, which is where the association between HECT-domain Ub ligases and a-arrestins is also documented by Scott Emr and Hugh Pelham's labs. Here are some PMID numbers to improve the citations of this section (PMID 17551511; 18976803; 19912579) and each of these references long predates the Puca and Brou publication.
In the revised manuscript, we will improve the citations by including the suggested studies (Gupta et al, Mol Syst Biol, 2007; Lin et al, Cell, 2008; Nikko and Pelham, Traffic, 2009).
Lines 123-126 - Phosphorylation can also increase vacuole-dependent degradation of alpha-arrestins as demonstrated in PMID 35454122. The interaction with 14-3-3 proteins that is driven by phosphorylation of a-arrestins was first demonstrated by the Leon group in PMID 22249293). Lines 129-132 - Here again the Leon reference that helps demonstrate the 14-3-3 inhibition of Rod1 is lacking (PMID 22249293).
We will cite the suggested studies in description of these topics (Bowman et al, Biomolecules, 2022; Becuwe et al, J Cell Biol, 2012).
Lines 130-132 - Please include references for the statement that dephosphorylation activates a-arrestin activity. There are no citations on this statement and there are many to choose from and I would urge the authors to cite the primary literature on these points.
We will cite studies for the statement "Conversely, dephosphorylation is thought to activate α-arrestins and to promote selective endocytosis of transporter proteins" (L130-132).
These are just a few examples from the Introduction, but the Discussion is similarly wrought with issues in referencing and framing the experimental results within the context of the larger field, including what is known about Rod1/Rog3 regulation in S. cerevisiae. For example, the Llopis-Torregrosa et al reference and statement on lines 508-510 is incorrect. There are other phosphorylation sites defined in the C-terminus of Rod1, as described in Alvaro et al. PMID: 26920760.
We will carefully correct Discussion by citing the suggested references (e.g. Alvaro et al, Genetics, 2016) and framing the obtained results within the context of the larger field.
Of note, a combination of α-arrestin, upstream kinase(s) and distinct phosphorylation sites appears to determine the target transporter (Kahlhofer et al, Biol Cell, 2021; Thorner, Biochem J, 2022), and it has not been explicitly proved that TORC2-Ypk1 signaling also regulate α-arrestin-mediated internalization of hexose transporters in budding yeast. For these reasons, we stated "S. cerevisiae Rod1 and Rog3 are phosphorylated solely by Snf1p/AMPK" in the context of internalization of hexose transporters. We will also discuss this point in the revised manuscript.
Minor Comments Clarification needed - Lines 107-121 - The relationship between the S. pombe arrestins and those in other organisms is somewhat unclear. Frist, all the arrestins in humans and S. cerevisiae can be sorted into the alpha, beta and Vps26 classes. However, the authors indicate that the S. pombe genome has 11 arrestin-like proteins but only 4 of these are a-arrestins. What classes do the other 7 arrestins belong to? It would be appreciated if this point was clarified.
To our knowledge, fission yeast arrestins are not well classified yet. We will perform a phylogenetic tree analysis to classify them, and modify the description of the indicated part accordingly. We will also cite our previous report (Toyoda et al, J Cell Sci, 2021), in which the overall protein structure and domains of 11 fission yeast arrestin-like proteins were reported.
Next, for the 4 a-arrestins identified in S. pombe the authors indicate that Aly3 is the homolog of Rod1/Art4 and Rog3/Art7 from S. cerevisiae. What is the relationship of Rod1 in S. pombe to Rod1 in S. cerevisiae? Are these also homologs? You can see how the nomenclature is confusing and, given the functional overlap of S. cerevisiae Rod1/Rog3 proteins it is important to know if Aly3 is the only version of these a-arrestins or if there is an additional counterpart in S. pombe. This point becomes somewhat more confusing when on lines 134-136 the authors talk about Arn1/Any1 as an arrestin related protein in S. pombe yet this protein was not included on the list of a-arrestins in the preceding section. What class of arrestin is this protein?
According to PomBase, both Aly3 and Rod1 are assigned as the orthologue of budding yeast Rod1 and Rog3. However, as mentioned in responses above, it is unclear whether Aly3 is really orthologous to budding yeast Rod1/Rod3. In the revised manuscript, we will perform a homology search for these 4 proteins, and add information on how much these arrestins share homology.
Arn1/Any1 is regarded as a β-arrestin (Nakase et al, J Cell Sci, 2013). We will also mention this in the revised manuscript.
Alpha-arrestin homology - On lines 127-129 the authors indicate that TXNIP is the mammalian homolog of Aly3. To my knowledge, there are no evolutionary analyses that can draw these lines of homology between the a-arrestins in humans and those in yeasts. It would be appreciated if the authors could cite the work that leads to this conclusion or revise the sentence to more accurately reflect what is known on this topic. It certainly appears that, given their functional overlap in regulating glucose transporters, Txnip and Rod1/Rog3 in humans and S. cerevisiae are functionally connected. I urge the authors to use more caution when describing this protein family.
Among human α-arrestins, ARRDC2 (22%) but not TXNIP (20%) has the highest amino acid identity to Aly3 (Toyoda et al, J Cell Sci, 2021). However, as TXNIP has been reported to regulate endocytosis of hexose transporters, GLUT1 and 4 (Wu et al, Mol Cell, 2013; Waldhart et al, Cell Rep, 2017), we think that TXNIP and Aly3 share physiological roles. We will revise the sentence (L127-129) more accurately.
Text editing - The text could use editing as there are awkward and grammatically incorrect sentences in several places. Here are a few examples to help the authors:
Please note that the original manuscript is edited by a professional editor, who is a native English (American) speaker and has edited thousands of research papers, before initial submission. We will ask an editor to check the revised draft again before submission.
Lines 57-60 - the protein is not expressed over the entire cell surface, but is localized to the entire cell surface.
We will correct this wording.
Lines 80-83 - this sentence is very confusing
We will correct this part by changing the phrase "Unlike TORC1," into a clause.
Line 86 - Is there more than one gene encoding Aly3 in S. pombe?
No, there is only one gene encoding Aly3. We will correct this part so as to avoid being misunderstood.
Line 88, 109, - these sentences need to start with a capitol so either capitalize the A in arrestin or write out Alpha with a capitol A.
We will correct the sentence as suggested.
Lines 145-148 - unclear as written
We will clarify the meaning of the sentence by changing the voice.
Line 224 - why are these amino acids being referred to as hydroxylated? Perhaps hydroxyl-containing amino acids or 18 amino acids with hydroxyl side chains would be better choices?
We will correct the word as suggested.
Line 300 - very confusing sentence structure
We will correct this part by simplifying the structure of the sentence.
And elsewhere....
We will carefully check the revised text before submission.
Reviewer #3 (Significance):
The authors provide some information as to the residues needed in the Aly3 C-tail for Ght5 trafficking in S. Pombe. These results are not places in the context of similar phosphor-regulatory work done for a-arrestins in S. cerevisiae, and this is needed for appreciation of the significance of the study.
Overall, it appears that the model put forth is very similar to the one already proposed in S. cerevisiae where phosphorylation impedes a-arrestin-mediated trafficking of glucose transporters. It is interesting to see this similarity hold in S. Pombe, but it does not dramatically alter our appreciation of a-arrestin biology.
The significance of the findings are somewhat underscored by the fact that very little quantification of data are presented, making the rigor of the work difficult to assess.
We thank the reviewer for careful reading and evaluation of our study. As the reviewer states, the results are not placed in the context of similar phospho-regulatory works done for α-arrestins in S. cerevisiae. This may partly come from the fact that it remains unclear whether internalization of hexose transporters is regulated by TORC2-dependent phosphorylation in S. cerevisiae. We believe that our study is novel and significant for this reason. By performing the additional experiments/quantification and revising the text as suggested by the reviewers, the manuscript will be further strengthened, and we will be able to clearly conclude that TORC2-dependent phosphorylation of Aly3 regulates localization of the Ght5 hexose transporter and cellular responses to glucose shortage stress.
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Referee #2
Evidence, reproducibility and clarity
Summary/background.
This paper focuses on the regulation of endocytosis of the hexose transporter, Ght5, in S. pombe by nutrient limitation through the arrestin-like protein Aly3. Ght5 is induced when glucose is limiting and is required for growth and proliferation in these conditions. ght5+ encodes the only high-affinity glc transporter from fission yeast. ght5+ is induced in low glucose conditions at the transcriptional level and is translocated to the plasma membrane to allow glc import. Ght5 is targeted to the vacuole in conditions of N limitation. Mutations in the TORC2 pathway lead to the same process, thus preventing growth on low glucose medium, as shown in the gad8ts mutant, mutated for the Gad8 kinase acting downstream of TORC2. Previously, the authors demonstrated that the vacuolar delivery of Ght5 in the gad8ts mutant is suppressed by mutation of the arrestin-like protein Aly3. Arrestin-like proteins are in charge of recognising and ubiquitinating plasma membrane proteins to direct their vacuolar targeting by the endocytosis pathway. This suggested that Aly3 is hyperactive in TORC2 mutants, and accordingly, Ght5 ubiquitination was increased in gad8ts.
Overall statement
This study aims at deepening our understanding of the regulation of endocytosis by signalling pathways through arrestin-like proteins. Ght5 is a nice model to study a physiological regulation, and the authors have a great set of tools at hand. However, I think the conclusions are not always rigorous and the conclusions are sometimes far-reaching. The main problem is that much of the conclusions concern a potential phosphorylation of Aly3 which is not experimentally addressed. An additional issue is the fact that they look at Ght5 ubiquitination by co-immunoprecipitation in native conditions (or at least, it seems to me) which cannot be conclusive. Overall, I think some experiments should be performed to address (at least) these 2 points before the manuscript can be published, see detailed comments below.
Major statements and criticism.
- Fig 1. Based on the hypothesis that TORC2-mediated phosphorylation regulate Ght5 endocytosis, the authors first considered a possible phosphorylation of Ght5. They mutagenised 11 possible phosphorylation sites on the Ct of Ght5, but none affected the growth on low glucose in the absence of thiamine, suggesting that they don't contribute to the observed TORC2-mediated regulation. However, I disagree with the statement that "phosphorylation of Ght5 is dispensable for cell proliferation in low glucose", given that the authors do not show 1- that Ght5 is phosphorylated and 2-that this is abolished by these mutations. They should either provide data on this or tone down and say that these residues are not involved in the regulation, without implying phosphorylation which is not proven. In the presence of Thiamine (Supp fig 1), it seems that the ST/A mutant grows better in low glucose, and this is not explained nor commented. Since the transporter is not expressed, could the authors provide an explanation to this? If the promoter is leaky and some ght5-ST/A is expressed, it may be more stable and allow better growth than the WT, which would tend to indicate that impairing phosphorylation prevents endocytosis (which is classical for many transporters, see the body of work on CK1-mediated phosphorylation of transporters). Have the authors tried to decrease glc concentration lower than 0.14% in the absence of thiamine to see if this also true when the transporters is strongly expressed? (OPTIONAL)
- Fig 2. The authors then follow the hypothesis that TORC2 exerts its Ght5-dependent regulation through the phosphorylation of Aly3. They mutagenised 18 possible phosphorylation sites on Aly3. This led to a strong defect in growth in low-glc medium. Mutation of the possible Gad8 site (S460) did not recapitulate this phenotype, suggesting that it is not sufficient, however, mutations of 4 ST residues in a CT cluster (582-586) mimicked the full 18ST/A mutation, suggesting these are the important residues for Ght5 endocytosis.
- Fig 3A. Further dissection did not allow to pinpoint this regulation to a specific residue, beyond the dispensability of the T586 residue. Fig 3B. The authors look at the effects of mutation of Aly3 on these sites at the protein level. They had to develop an antibody because HA-epitope tagging did not lead to a functional protein (Supp fig 2). Whereas I agree that the mutations causing a phenotype lead to a change in the migration pattern, I disagree with the statement that "This observation indicated that slower migrating bands were phosphorylated species of Aly3" (p.9 l.271). First, lack of phosphorylation usually causes a slower mobility on gel, which is not clear to spot here. Second, a smear appears on top of the mutated proteins (eg. 4th Ala) which is possibly caused by another modification. There are many precedents in the literature about arrestins being ubiquitinated when they are not phosphorylated (see the work on Bul1, Rod1, Csr2 in baker's yeast from various labs). My gut feeling is that lack of phosphorylation unleashes Aly3 ubiquitination leading to change in pattern. All in all, it is impossible to state about the phosphorylation of a protein without addressing its phosphorylation properly by phosphatase treatment + change in migration, or MS/MS. Thus, whereas the data looks promising, this hypothesis that Aly3 is phosphorylated at the indicated sites is not properly demonstrated.
- Fig 4. The authors now look at the functional consequences of these mutations on ALy3 on Ght5 localisation. The data clearly shows that mutation of the 4 identified S/T residues (Aly3-4th A) causes aberrant localisation of the transporter to the vacuole, likely to cause the observed growth defect on low glucose. There is a nice correlation between the vacuolar localisation and growth in low-glucose for the various aly3 mutants. (A final proof could be to express this in the context of an endocytic mutant, which should restore membrane localisation and suppress the aly3-4thA phenotype - OPTIONAL). However, I still disagree with the statement that "These results indicate that phosphorylation of Aly3 at the C-terminal 582nd, 584th, and/or 585th serine residues is required for cell-surface localization of Ght5." given that phosphorylation was not properly demonstrated.
- Fig 5. Here, the authors question the role of Aly3 mutations on Ght5 ubiquitination. They immunoprecipitate Ght5 and address its ubiquitination status in various Aly3 mutants. The data is encouraging for a role in Aly3 phosphorylation (?) in the negative control of Ght5 ubiquitination. My main problem with this experiment is that it seems that Ght5 immunoprecipitations were made in non-denaturing conditions, which leads to the question of what is the anti-ubiquitin revealing here (Ght5 or a co-immunoprecipitated protein, for example Aly3 itself, or the Pub ligases, or an unknown protein). It seems that this protocol was previously used in their previous paper, but I stand by my conclusion that ubiquitination of a given protein can only be looked in denaturing conditions. The experiments should be repeated in buffers classical for the study of protein ubiquitination to be able to conclude unambiguously that we are looking at Ght5 ubiquitination itself, especially in the absence of a non-ubiquitinable form of Ght5 as a negative control. Could the authors comment on the fact that S-A or S-D mutations display the same phenotype regarding the possible Ght5 ubiquitination?
- Fig 6. The authors want to document the model whereby Aly3 may interact with some of the Nedd4 ligases (Pub1/2/3) to mediate its Ght5-ubiquitination function. They actually use the Aly3-4thA mutant, it should have been better with the WT protein. But the results indicate a clear interaction with at least Pub1 and Pub3. By the way, are the Pub1/2/3 fusions functional? Nedd4 proteins are notoriously affected in their function by C-terminal tagging and are usually tagged at their N-terminus (See Dunn et al. J Cell Biol 2004).
- Fig 7. The authors want to provide genetic interaction between the Pub ligases and the growth defects in low glc due to alterations in Ght5 trafficking. It is unclear how the gad8ts pub1∆ mutant was generated since it doesn't seem to grow on regular glc concentration (Supp fig 5), could the authors provide some information about this? It is also not clear whether it can be stated thatches mutant is "more sensitive" to glc depletion because of the low level of growth to begin with (even at 3%). Altogether, the data show that deletion of pub3+ is able to suppress the growth defect of the gad8ts mutant on low glc medium, suggesting it is the relevant ligase for Ght5 endocytosis. This is confirmed by microscopy observations of Ght5 localisation. However, I would again tone down the main conclusion, which I feel is far-reaching: "Combined with physical interaction data, these results strongly suggest that Aly3 recruits Pub3, but not Pub2, for ubiquitination of Ght5." Work on Rsp5 in baker's yeast has shown that Rsp5 function goes beyond cargo ubiquitination, including ubiquitination of arrestins (which is often required for their function as mentioned in the introduction) or other endocytic proteins (epsins, amphyphysin etc). I agree that the data are compatible with this model but there are other possible explanations. Anything that would block endocytosis would supposedly suppress the gad8ts phenotype.
Discussion
Some analogy with the regulation of the Bul arrestins by TORC1/Npr1 and PP2A/Sit4 could be mentioned (Mehri et al. 2012), at the discretion of the authors. The possibility that phosphorylation may neutralise a basic patch on Aly3 Ct, possibly involved in electrostatic interactions with Ght5 is very interesting. Regarding the effect of the mutations on Aly3 localisation (p.15 l.498), did the authors tag Aly3 with GFP? There are examples where proteins tagged with HA are not functional whereas tagging with GFP does not alter their function (eg. Rod1, Laussel et al. 2022) - and here Supp Fig 2 only relates to HA-tagging. Proof of a change in Aly3 localisation upon mutation would definitely be a plus (OPTIONAL).
Minor comments.
Introduction:
- I believe the text corresponding to the work on TXNIP is incorrect (p.5 l.127). TXNIP is degraded after its phosphorylation, not "rectracted" from the surface.
- For the sake of completion, the authors could add other references concerning the regulation of Rod1 in budding yeast such as Becuwe et al. 2012 J Cell Biol and O'Donnell et al. 2015 Mol Cell Biol, in addition to Llopis-Torregrosa et al. 2016.
- Other examples of the requirement for arrestin ubiquitination beyond Art1 (p.5 l.136-137) are listed in the ref cited: Kahlhofer et al. 2021.
Figures: In general, I think it would be clearer if the authors showed on the figures that the background strain in which the XXX gene is added (or its mutant forms) is a xxx∆ strain.
Referees cross-commenting
Cross review of Reviewer 1
- I don't believe that the authors "define a set of redundant c-terminal phosphorylation sites in Aly3", because phosphorylation is not proven.
- I thinks the points raised for Fig 3B are valid but the authors should focus on making their story conclusive before expanding to other data (except for the explanation of the smear, see my review). Also, I don't think 2NBDG actually works to measure Glc uptake.
- same for Fig 6 - not sure the interaction site mapping between Aly3 and Pubs would bring much value since there are more urgent things to do to make the story solid.
Cros review of Reviewer 3 - we have many overlaps, so briefly :
- I agree that the bibliography is incomplete (mentioned in my review)
- I agree that there is no demonstration of the phospho-status of Aly3, and it is a problem
- I agree that the results can be better quantified, esp. in the light of the points raised by this referee concerning the variability of expression of ST18A
Other specific comments :
- I agree that the statement that dephosphorylation activates alpha-arresting should be toned down - this was observed in several instances but there are examples of arrestin-mediated endocytosis which does not require their prior dephosphorylation.
- I fully agree that efforts could be made regarding the classification/nomenclature of arrestins in S. pombe, this had escaped my attention
Significance
strengths and limitations
This study aims at deepening our understanding of the regulation of endocytosis by signalling pathways through arrestin-like proteins in S. pombe. Ght5 is a nice model to study a physiological regulation, and the authors have a great set of tools at hand, including the discovery of Aly3 as the main arrestin for this regulation, and a signalling pathway (TORC2/Gad8) acting upstream. The main question is now to understand at the mechanistic level how TORC2 signaling impinges on the regulation of this arrestin.
Overall, the authors nicely demonstrate that C-terminal Ser/Thr residues are crucial for the function of Aly3 in Ght5 endocytosis. They propose a model whereby Aly3 phosphorylation by an unknownn kinase inhibits its function on Ght5 ubiquitination, which would favour its endocytosis. However, I think the conclusions are not always rigorous and the conclusions are sometimes far-reaching. The main problem is that much of the conclusions concern a potential phosphorylation of Aly3 which is not experimentally addressed. An additional issue is the fact that they look at Ght5 ubiquitination by co-immunoprecipitation in native conditions (or at least, it seems to me) which cannot be conclusive. Overall, I think some experiments should be performed to address (at least) these 2 points before the manuscript can be published, see detailed comments above.
Advance
This study, if completed carefully, would provide among the first examples of mapping of phosphorylation sites on arrestins, which are usually phosphorylated at many sites and are thus difficult to study. Few studies went down to this level in this respect (see Ivshov et al. eLife 2020). There are no changes in paradigms or new conceptual insights, but this work is a nice example of the conservation of these regulatory mechanisms.
Audience
Should be of interest for people studying basic research in the field of cell biology, signalling pathways, transporter regulation by physiology. Reviewer background is on the regulation of transporter endocytosis by signalling pathways and arrestin-like proteins.
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Author response:
The following is the authors’ response to the previous reviews.
Public Reviews:
Reviewer #2 (Public Review):
Although the study by Xiaolin Yu et al is largely limited to in vitro data, the results of this study convincingly improve our current understanding of leukocyte migration.
(1) The conclusions of the paper are mostly supported by the data and in the revised manuscript clarification is provided concerning the exact CCL5 forms (without or with a fluorescent label or His-tag) and amounts/concentrations that were used in the individual experiments. This is important since it is known that modification of CCL5 at the N-terminus affects the interactions of CCL5 with the GPCRs CCR1, CCR3 and CCR5 and random labeling using monosuccinimidyl esters (as done by the authors with Cy-3) is targeting lysines. The revised manuscript more clearly indicates for each individual experiment which form is used. However, a discussion on the potential effects of the modifications on CCL5 in the results and discussion sections is still missing.
Many thanks for the reviewer's suggestion. We fully agree it is important to clarify the potential issue of Cy3 labeling, and believe it is more suitable in the Materials and Methods section (line 312-314).
(2) In general, authors used high concentrations of CCL5 in their experiments. In their reply to the comments they indicate that at lower CCL5 concentrations no LLPS is detected. This is important information since it may indicate the need for chemokine oligomerization for LLPS. This info should be added to the manuscript and comparison with for instance the obligate monomer CCL7 and another chemokine such as CXCL4 that easily forms oligomers may clarify whether LLPS is controlled by oligomerization.
We are pleased by the help of the reviewers and accordingly inserted a brief discussion as suggested (line 240-246).
(3) Statistical analyses have been improved in the revised manuscript.
Thanks to the reviewer for his/her comment.
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maggieappleton.com maggieappleton.com
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the right knowledge to make a full-stack app
Worth considering Brooks's distinction of essential versus incidental complexity. It's especially worth considering the instances where the "incidental" part comes from being incidental to the fact that if it were easier, there it would make a lot of people unhappy for reasons that I call "the consultant effect".
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Reviewer #1 (Public Review):
The study identifies the epigenetic reader SntB as a crucial transcriptional regulator of growth, development, and secondary metabolite synthesis in Aspergillus flavus, although the precise molecular mechanisms remain elusive. Using homologous recombination, researchers constructed sntB gene deletion (ΔsntB), complementary (Com-sntB), and HA tag-fused sntB (sntB-HA) strains. Results indicated that deletion of the sntB gene impaired mycelial growth, conidial production, sclerotia formation, aflatoxin synthesis, and host colonization compared to the wild type (WT). The defects in the ΔsntB strain were reversible in the Com-sntB strain.
Further experiments involving ChIP-seq and RNA-seq analyses of sntB-HA and WT, as well as ΔsntB and WT strains, highlighted SntB's significant role in the oxidative stress response. Analysis of the catalase-encoding catC gene, which was upregulated in the ΔsntB strain, and a secretory lipase gene, which was downregulated, underpinned the functional disruptions observed. Under oxidative stress induced by menadione sodium bisulfite (MSB), the deletion of sntB reduced catC expression significantly. Additionally, deleting the catC gene curtailed mycelial growth, conidial production, and sclerotia formation, but elevated reactive oxygen species (ROS) levels and aflatoxin production. The ΔcatC strain also showed reduced susceptibility to MSB and decreased aflatoxin production compared to the WT.
This study outlines a pathway by which SntB regulates fungal morphogenesis, mycotoxin synthesis, and virulence through a sequence of H3K36me3 modification to peroxisomes and lipid hydrolysis, impacting fungal virulence and mycotoxin biosynthesis.
The authors have achieved majority of their aims at the beginning of the study, finding target genes, which led to catC mediated regulation of development, growth and aflatoxin metabolism. Overall most parts of the study is solid and clear.
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Reviewer #1 (Public Review):
Summary:
In this manuscript by Beardslee and Schmitz, the authors undertook a screen for potential degrons - short peptide sequences at the C-terminus that would target the toxin VapC for degradation. The authors randomly mutagenized 5 amino acids appended to the C-terminus of VapC and transformed this library into E. coli to look for surviving cells when the VapC gene was expressed. The authors found an enrichment for tags ending Ala-Ala, and found that this enrichment was dependent on the presence of the ClpXP protease, since this sequence was not similarly enriched in a mutant lacking this protease. Moreover, the authors identify the sequence FKLVA as the tag with the highest fold enrichment in the screen and confirm that GFP tagged with this sequence is degraded by ClpXP with similar kinetics to GFP tagged with the ssrA-derived tag.
Strengths:
This study has two major implications for understanding the nature of degrons in E. coli. First, peptides ending Ala-Ala, and especially degrons resembling the ssrA degron are likely the most degradation-promoting sequences in E. coli. Second, these findings suggest that ClpXP is the most central protease, at least for this particular protein with a randomized C-terminus under the particular conditions of this screen. It is also notable that the ribosome quality control protein RqcH tags truncated proteins with an alanine tag in a template-free manner when the large ribosomal subunit is obstructed. Although E. coli doesn't encode RqcH, the utility of alanine-tagging for protein degradation likely extends to other organisms.
Weaknesses:
The authors remark and show that mutations that inactivate the VapC protein are enriched potentially more than the proteolysis tags. This is a limitation of the study and the authors have done well to describe this as it will inform future screens. Perhaps using a protein with more intermediate toxicity in future screens would help to prioritize C-terminal mutations instead of toxin-inactivating mutations.
For clarity, the authors should explain why the NNK structure of the random codons was used. Why is it important that the codon end with a G or T?
Authors state on page 7 that by determining enrichment of individual tags they can rank the relative Km for proteolysis of the individual tags. This statement is not accurate since the tag could variously impact its association with any of the proteases in the cell. Since Km is specific to each particular protease, these can't be ranked in vivo when all proteases are present.
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Reviewer #2 (Public Review):
Summary:
The authors studied the sequence determinants of C-terminal tags that govern protein degradation in bacteria. They introduce a new strategy to determine degron sequences: Detox (Degron Enrichment by toxin). This unbiased approach links degron efficiency to cell growth as degrons are C-terminally fused to the toxin VapC, which inhibits protein translation. Selecting for bacterial growth and thus toxin degradation enabled the identification of potent degron derived from a randomized library of pentapeptides. Remarkably, most degrons show sequence similarity to the SsrA-tag, which is fused to incomplete polypeptides at stalled ribosomes by the tmRNA-tagging system. These findings underline the extraordinary efficiency of the SsrA-tag and the ClpXP protease in removing incomplete polypeptides and demonstrate that most proteins are spared from degradation by harboring different C-termini. The introduced method will be highly useful to determine degron sequences in other positions and other bacterial species.
Strengths:
The work introduces an innovative and powerful strategy to identify degron sequences in bacteria. The study is well-controlled and results have been thoroughly analyzed. It will now become important to broaden the technology, making it also accessible for more complex degrons.
Weaknesses:
The approach is efficient in identifying strong degron sequences that are predominantly recognized by the ClpXP protease. The sequence specificity of other proteolytic systems, however, is not efficiently addressed, pointing to a potential limitation of this technology. The GS-rich linker sequence connecting the degron and the toxin might also impact proteolysis and thus outcome.
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Author response:
The following is the authors’ response to the original reviews.
Key Considerations:
There seem to be two inconsistencies related to some results depicted in Figures 1, 2, 3 and 5.
Firstly, Figure 1 shows the effect on C_Las infection (_C_Las+) compared to the control (_C_Las-), where results show an increase of TAG, Glycogen, lipid droplet size, oviposition period, and fecundity. In Figures 2, 3, and 5, the authors establish the involvement of the genes _DcAKH, DcAKHR, and miR34 in this process, by showing that by preventing the function of these three factors the effects of _C_Las+ are lost. However, while Figure 1 shows the increase of TAG and lipid droplet size in _C_Las+, Figures 2, 3, and 5 do not show a significant elevation in TAG when comparing _C_Las- and _C_Las+.
Secondly, in addition to the absence of statistical difference in TAG and lipid droplet size observed in Figure 1, Figures 2, 3, and 5 show an increase in TAG and lipid droplet size after ds_DcAKH_ (Figure 2), ds_DcAKHR_ (Figure 3) and agomiR34 (Figure 5) treatments. Considering that AKH, AKHR, and miR34 are important factors to _C_Las-induce increase in TAG and lipid droplet size, one might expect a reduction in TAG and lipid droplet size when _C_Las+ insects are silenced for these factors, contrary to the observed results.
Thanks for your excellent suggestion. Lipid droplets are cellular organelles responsible for storing lipids within cells, playing a crucial role in fat metabolism and energy homeostasis. The formation and breakdown of lipid droplets involve a complex interplay of genes and enzymes, including DGAT (for synthesis), ATGL and HSL (for breakdown). In C_Las-negative _D. citri, there is a delicate balance between creasing and breaking down of lipid droplets. The enlargement of lipid droplet size following C_Las infection may result from a significantly higher synthesis rate compared to breakdown, as more energy is required during early ovarian development. The hormone AKH, a key player in fat metabolism, primarily stimulates fat breakdown. Therefore, when _DcAKH and DcAKHR are silenced without affecting fat synthesis, there is no enhancement of fat breakdown; instead, there is an accumulation of lipid droplets, resulting in their enlargement. This suggests that _C_Las infection affects both the breakdown and synthesis of lipid droplets, while AKH and AKHR primarily impact the breakdown, leading to similar outcomes. However, the underlying physiological mechanisms warrant further in-depth exploration.
Reviewer #1 (Recommendations For The Authors):
(1) Line 25: change "In addition" to "Additionally".
Thanks for your wonderful suggestion. We have changed “In addition” to “Additionally” in our revised manuscript (Line 26).
(2) Lines 60-72: Have there been any previous reports on the interaction between host AKH hormones and microorganisms in insects or animals? If yes, please add more background.
Thanks for your wonderful suggestion. We have added the interactions between host AKH hormones and microorganisms in insects (Line 74-81).
(3) Lines 82-95: add the following reference about the miR-275 of Diaphorina citri in the background. Nian, X., Luo, Y., He, X., Wu, S., Li, J., Wang, D., Holford, P., Beattie, G. A. C., Cen, Y., Zhang, S., & He, Y. (2024). Infection with 'Candidatus Liberibacter asiaticus' improves the fecundity of Diaphorina citri aiding its proliferation: A win-win strategy. Molecular Ecology, 33, e17214.
Thanks for your wonderful suggestion. We have added the sentence “in D. citri-C_Las interaction, _C_Las hijacks the JH signaling pathway and host miR-275 that targets the _vitellogenin receptor (DcVgR) to improve D. citri fecundity, while simultaneously increasing the replication of C_Las itself, suggesting a mutualistic interaction in _D. citri ovaries with _C_Las” in our revised manuscript (Line 97-100).
(4) In the figures of Nile red staining, the digit of the scale bar should be added.
Thanks for your wonderful suggestion. We have added the digit of the scale bar for Nile red staining in the Figure 1C, 2E, 3E, 5C.
(5) In Figures 2G-H, 3G-H, 5E-F, the presentation of data should be consistent with Figure 1D-E.
Thanks for your wonderful suggestion. We have changed figure 1D-E in our revised manuscript.
(6) In the discussion part, more information should be added about miR-275 and DcVgR from the above reference.
Thanks for your wonderful suggestion. We have added the information “In D. citri-C_Las interaction, _C_Las operates host hormone signaling and miRNA to mediate the mutualistic interaction between _D. citri fecundity and its replication” in Line 350-353.
(7) For the primer specific, please add the melting curves for qPCR primers of DcAKH, DcAKHR, Dcβ-ACT, U6, and miR-34 in the supplementary material.
Thanks for your wonderful suggestion. We have added the melting curves for qPCR primers of DcAKH, DcAKHR, Dcβ-ACT, U6 and miR-34 in the supplementary material of Figure S6.
(8) Line 476: Dcβ-ACT was indicated as a gene and should be Italic.
Thanks for your wonderful suggestion. We have changed “DcβACT” to “Dcβ-ACT” in our revised manuscript (Line 491).
(9) Reference style should be consistent and correct. Like [5], [10], [37], [47].
Thanks for your wonderful suggestion. We have revised them in our revised manuscript.
Reviewer #2 (Recommendations For The Authors):
(1) In order to better engage readers, I suggest emphasizing the "enhanced fecundity" in the title. A suggestion for the revised title is: Adipokinetic hormone signaling mediates the enhanced fecundity of Diaphorina citri infected by 'Candidatus Liberibacter asiaticus'.
Thanks for your wonderful suggestion. We have changed the title to “Adipokinetic hormone signaling mediates the enhanced fecundity of Diaphorina citri infected by 'Candidatus Liberibacter asiaticus'” in our revised manuscript.
(2) For the abstract, in lines 14-15, please change the first sentence to "Diaphorina citri serves as the primary vector for 'Candidatus Liberibacter asiaticus' (C_Las), the bacterium associated with the severe Asian form of huanglongbing." In line 18, delete "present". In line 19, change "increased" to "increasing". In line 21, change "triacylglycerol accumulation" to "the accumulation of triacylglycerol". In line 33, change "in _D. citri ovaries with C_Las" to "between _C_Las and _D. citri ovaries".
Thanks for your wonderful suggestion. We have revised them following your suggestion in our revised manuscript, including changed “Diaphorina citri is the primary vector of the bacterium, ‘Candidatus Liberibacter asiaticus’ (C_Las) associated with the severe Asian form of huanglongbing” to “_Diaphorina citri serves as the primary vector for 'Candidatus Liberibacter asiaticus' (C_Las), the bacterium associated with the severe Asian form of huanglongbing” in Line 15-16; deleted "present" in Line 19; changed "increased" to "increasing" in Line 20; changed "triacylglycerol accumulation" to "the accumulation of triacylglycerol" in Line 22; changed "in _D. citri ovaries with C_Las" to "between _C_Las and _D. citri ovaries" in Line 34.
(3) In lines 57-59, change "How D. citri maintains a balance between lipid metabolism and increased fecundity after infection with C_Las is not known." to "However, the mechanism of how _D. citri maintains a balance between lipid metabolism and increased fecundity after infection with _C_Las remains unknown.".
Thanks for your wonderful suggestion. We have changed " How D. citri maintains a balance between lipid metabolism and increased fecundity after infection with C_Las is not known" to "However, the mechanism of how _D. citri maintains a balance between lipid metabolism and increased fecundity after infection with _C_Las remains unknown" in our revised manuscript (Line 58-60).
(4) In Figure 1, "n.s" should be changed to "n.s.", "n.s." should be added in 13 DAE of Figure 1A, and the specific numerical value of the scale bar should be indicated on Figures 1C, 2E, 3E, and 5C.
Thanks for your wonderful suggestion. We have revised them in our revised manuscript.
(5) In all the figure legends, the "**P < 0.01,***P < 0.001" should be changed to "**p < 0.01,***p < 0.001".
Thanks for your wonderful suggestion. We have revised them in our revised manuscript.
(6) In Figures 1D-E, the preoviposition period and oviposition period were presented using a box diagram, but in other figures (including Figure 2G-H, Figure 3G-H, Figure 5E-F) these were shown using a column chart. Please keep the method of presentation consistent.
Thanks for your wonderful suggestion. We have revised the figure 1D-E in our revised manuscript.
(7) For discussion, in line 333, change "Increasing numbers" to "An increasing number". In line 334, change "vertically transmitted" to "transmitted vertically".
Thanks for your wonderful suggestion. We have changed "Increasing numbers" to "An increasing number" in Line 345; changed "vertically transmitted" to "transmitted vertically" in Line 346 in our revised manuscript.
(8) In lines 338-342, change "There are few studies on the mechanisms underlying vector-bacteria interactions. However, Singh and Linksvayer (2020) [38] found that Wolbachia-infected colonies of Monomorium pharaonis had increased colony-level growth, accelerated colony reproduction, and shortened colony life cycles compared to those that were uninfected." to "Although there is limited research on the mechanisms underlying vectorbacteria interactions, Singh and Linksvayer (2020) [38] found that Wolbachia_infected colonies of _Monomorium pharaonis exhibited increased colony-level growth, accelerated colony reproduction, and shortened colony life cycles compared to uninfected colonies.".
Thanks for your wonderful suggestion. We have revised it in our revised manuscript (Line 350-355) .
(9) In line 370, delete "present". In lines 386-387, change "More and more miRNAs have been reported to be involved in the metabolic processes of insects including reproduction." to "There is increasing evidence implicating miRNAs in the metabolic processes of insects, particularly in relation to reproduction.".
Thanks for your wonderful suggestion. We have revised them in our revised manuscript, including deleted "present" in Line 383 and changed "More and more miRNAs have been reported to be involved in the metabolic processes of insects including reproduction" to "There is increasing evidence implicating miRNAs in the metabolic processes of insects, particularly in relation to reproduction" in Line 399-400.
(10) In line 423, change "After infection with C_Las, _D. citri are more fecund than their uninfected counterparts." to "Upon infection with C_Las, _D. citri exhibits enhanced fecundity compared to uninfected individuals.". In lines 424-425 and 439-440, change "the more offspring of D. citri, the more C_Las in the field" to "the increased offspring of _D. citri contributes to a higher presence of _C_Las in the field.". In Line 429, change " information" to "insights".
Thanks for your wonderful suggestion. We have revised them in our revised manuscript, including changed "After infection with C_Las, _D. citri are more fecund than their uninfected counterparts" to "Upon infection with C_Las, _D. citri exhibits enhanced fecundity compared to uninfected individuals" in Line 436-437; changed "the more offspring of D. citri, the more C_Las in the field" to "the increased offspring of _D. citri contributes to a higher presence of _C_Las in the field" in Line 438-439; changed "information" to "insights" in Line 443.
(11) In lines 446-447, change "The _C_Las-infected lemon plants and psyllids were monitored to detect _C_Las infection monthly using the quantitative polymerase chain reaction (qPCR)" to "Monthly monitoring of the _C_Las infection in both the lemon plants and psyllids was conducted using quantitative polymerase chain reaction (qPCR)".
Thanks for your wonderful suggestion. We have revised it in our revised manuscript (Line 460-461).
(12) In lines 452-458, how did the authors identify homologous sequences of AKH and AKHR for phylogenetic tree analysis and alignment of the amino acid sequences? From NCBI or other databases? The methodological details should be added.
Thanks for your wonderful suggestion. We have added the methodological details in our revised manuscript (Line 469-470).
(13) In line 476, Dcβ-ACT should be italic.
Thanks for your wonderful suggestion. We have changed “DcβACT” to italic in our revised manuscript (Line 491).
(14) In line 538, the manufacturer should be provided for Nile Red.
Thanks for your wonderful suggestion. We have provided the manufacturer of Nile Red in our revised manuscript (Line 553).
(15) Does miR-34 have any other target genes? If yes, whether they have any function in the fecundity improvement of D. citri after infected by CLas.
Thanks for your insightful suggestion. In addition to DcAKHR, we predicted three other genes have binding sites in 3’UTR with miR-34, including Innexin, T-box transcription factor TBX1, and fatty acid synthase. Despite this, the mRNA expression levels of all three genes remained unchanged between _C_Las-negative and _C_Las-postive females. Therefore, we believe that these genes are not implicated in the fecundity improvement.
(16) The reference format should be unified. Please revise references 10, 28, 43, 47, and 53.
Thanks for your wonderful suggestion. We have revised them in the revised manuscript.
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Reviewer #1 (Public Review):
Summary:
This manuscript by Shea and Villeda furnishes the field with a valuable scRNAseq data set detailing microglial aging in the mouse hippocampus. They provide clear evidence that changes in microglial attributes begin in mid-life, well before time points when mice are traditionally considered to be "aging." It also adds to a growing body of data in the field demonstrating that there is substantial heterogeneity in microglial responses to aging. Using in vitro experiments and transgenic manipulations in mice, the authors show that transforming growth factor beta (TGFb1)-based signaling can potently impact microglial state, consistent with previous findings in the field. They also demonstrate that manipulation of microglial TGFb1-based signaling can impact hippocampus-dependent behaviors.
Limitations of the study lie primarily in reaching too far with interpretations of the data. The authors argue that changes in microglial transcriptome during midlife represent a type of "checkpoint," after which microglial aging can progress along distinct trajectories depending on the status of TGFb1 signaling. They also posit that a specific intermediate "stress response" state in midlife is mechanistically linked to a translational burst that drives the subsequent progression of microglia to an "inflammatory state." Unequivocal data to support these causal links is lacking, however. similarly, key additional experiments would be needed to demonstrate that TGFb1 signaling and microglial progression through these identified intermediate states are causally linked to cognitive decline.
Guidance for readers along with study strengths and caveats:
The present manuscript provides valuable strengthening and expansion to a growing body of data showing prominent changes in the microglial state during aging. Microarray(1), bulkRNAseq(2-5), scRNAseq(6,7), snRNAseq(8,9), and spatial transcriptomic(10) approaches have been leveraged to map changes in microglial transcriptome during aging in rodents, non-human primates, and humans. A number of these studies include the hippocampus (1,8,9,11) and have highlighted variation across brain regions in microglial transcriptomic changes during aging (1,11). They have also revealed differences across sex (7) as well as increased cell-to-cell heterogeneity (6-10), consistent with the idea that individual microglia can follow distinct aging trajectories. Several of these studies revealed that changes in microglial attributes begin in middle age (1,7,11), supporting similar observations from studies that did not use omics (12-14). The present manuscript utilizes scRNAseq of hippocampal microglia at adulthood (6mo), middle age (12mo), late middle age (18mo) and aging (24mo) to show that aging-induced changes in microglia begin in middle age and that microglia exhibit ample phenotypic heterogeneity during the progression of aging.
To gain further insight into the dynamics of microglial aging in the hippocampus, the authors used a bioinformatics method known as "pseudotime" or "trajectory inference" to understand how cells may progress through different functional states, as defined by cellular transcriptome (15,16). These bioinformatics approaches can reveal key patterns in scRNAseq / snRNAseq datasets and, in the present study, the authors conclude that a "stress response" module characterized by expression of TGFb1 represents a key "checkpoint" in microglial aging in midlife, after which the cells can move along distinct transcriptional trajectories as aging progresses. This is an intriguing possibility. However, pseudotime analyses need to be validated via additional bioinformatics as well as follow-up experiments. Indeed, Heumos et al, in their Nature Genetics "Expert Guidelines" Review, emphasize that "inferred trajectories might not necessarily have biological meaning." They recommend that "when the expected topology is unknown, trajectories and downstream hypotheses should be confirmed by multiple trajectory inference methods using different underlying assumptions."(15) Numerous algorithms are available for trajectory inference (e.g. Monocle, PAGA, Sligshot, RaceID/StemID, among many others) and their performance and suitability depends on the individual dataset and nature of the trajectories that are to be inferred. It is recommended to use dynGuidelines(16) for the selection of optimal pseudotime analysis methods. In the present manuscript, the authors do not provide any justification for their use of Monocle 3 over other trajectory inference approaches, nor do they employ a secondary trajectory inference method to confirm observations made with Monocle 3. Finally, follow-up validation experiments that the authors carry out have their own limitations and caveats (see below). Hence, while the microglial aging trajectories identified by this study are intriguing, they remain hypothetical trajectories that need to be proven with additional follow-up experiments.
To follow up on the idea that TGFb1 signaling in microglia plays a key role in determining microglial aging trajectories, the authors use RNAscope to show that TGFb1 levels in microglia peak in middle age. They also treat primary LPS-activated microglia with TGFb1 and show that this restores expression of microglial homeostatic gene expression and dampens expression of stress response and, potentially, inflammatory genes. Finally, they utilize transgenic approaches to delete TGFb1 from microglia around 8-10mo of age and scRNAseq to show that homeostatic signatures are lost and inflammatory signatures are gained. Hence, findings in this study support the idea that TGFb1 can strongly regulate microglial phenotype. Loss of TGFb1 signaling to microglia in adulthood has already been shown to cause decreased microglial morphological complexity and upregulation of genes typically associated with microglial responses to CNS insults(17-19). TGFb1 signaling to microglia has also been implicated in microglial responses to disease and manipulations to increase this signaling can improve disease progression in some cases(19). In this light, the findings in the present study are largely confirmatory of previous findings in the literature. They also fall short of unequivocally demonstrating that TGFb1 signaling acts as a "checkpoint" for determining subsequent microglial aging trajectory. To show this clearly, one would need to perturb TGFb1 signaling around 12mo of age and carry out sequencing (bulkRNAseq or scRNAseq) of microglia at 18mo and 24mo. Such experiments could directly demonstrate whether the whole microglial population has been diverted to the TGFb1-low aging trajectory (that progresses through a translational burst state to an inflammation state as proposed). Future development of tools to tag TGFb1 high or low microglia could also enable fate tracing type experiments to directly show whether the TGFb1 state in middle age predicts cell state at later phases of aging.
The present study would also like to draw links between features of microglial aging in the hippocampus and a decline in hippocampal-dependent cognition during aging. To this end, they carry out behavioral testing in 8-10mo old mice that have undergone microglial-specific TGFb1 deletion and find deficits in novel object recognition and contextual fear conditioning. While this provides compelling evidence that TGFb1 signaling in microglia can impact hippocampus-dependent cognition in midlife, it does not demonstrate that this signaling accelerates or modulates cognitive decline (see below). Age-associated cognitive decline refers to cognitive deficits that emerge as a result of the normative brain aging process(20-21). For a cognitive deficit to be considered age-associated cognitive decline, it must be shown that the cognitive operation under study was intact at some point earlier in the adult lifespan. This requires longitudinal study designs that determine whether a manipulation impacts the relationship between brain status and cognition as animals age (22-24). Alternatively, cross-sectional studies with adequate sample sizes can be used to sample the variability in cognitive outcomes at different points of the adult lifespan(22-24) and show that this is altered by a particular manipulation. For this specific study, one would ideally demonstrate that hippocampal-based learning/memory was intact at some point in the lifespan of mice with microglial TGFb1 KO but that this manipulation accelerated or exacerbated the emergence of deficits in hippocampal-dependent learning/memory during aging. In the absence of these types of data, the authors should tone down their claims that they have identified a cellular and molecular mechanism that contributes to cognitive decline.
A final point of clarification for the reader pertains to the mining of previously generated data sets within this study. The language in the results section, methods, and figure legends causes confusion about which experiments were actually carried out in this study versus previous studies. Some of the language makes it sound as though parabiosis experiments and experiments using mouse models of Alzheimer's Disease were carried out in this study. However, parabiosis and AD mouse model experiments were executed in previous studies (25,26), and in the present study, RNAseq datasets were accessed for targeted data mining. It is fantastic to see further mining of datasets that already exist in the field. However, descriptions in the results and methods sections need to make it crystal clear that this is what was done.
References:
(1) Grabert, K. et al. Microglial brain region-dependent diversity and selective regional sensitivities to aging. Nat. Neurosci. (2016). doi:10.1038/nn.4222<br /> (2) Hickman, S. E. et al. The microglial sensome revealed by direct RNA sequencing. Nat. Neurosci. (2013). doi:10.1038/nn.3554<br /> (3) Deczkowska, A. et al. Mef2C restrains microglial inflammatory response and is lost in brain ageing in an IFN-I-dependent manner. Nat. Commun. (2017). doi:10.1038/s41467-017-00769-0<br /> (4) O'Neil, S. M., Witcher, K. G., McKim, D. B. & Godbout, J. P. Forced turnover of aged microglia induces an intermediate phenotype but does not rebalance CNS environmental cues driving priming to immune challenge. Acta Neuropathol. Commun. (2018). doi:10.1186/s40478-018-0636-8<br /> (5) Olah, M. et al. A transcriptomic atlas of aged human microglia. Nat. Commun. (2018). doi:10.1038/s41467-018-02926-5<br /> (6) Hammond, T. R. et al. Single-Cell RNA Sequencing of Microglia throughout the Mouse Lifespan and in the Injured Brain Reveals Complex Cell-State Changes. Immunity 50, 253-271 (2019).<br /> (7) Li, X. et al. Transcriptional and epigenetic decoding of the microglial aging process. Nat. aging 3, 1288-1311 (2023).<br /> (8) Zhang, H. et al. Single-nucleus transcriptomic landscape of primate hippocampal aging. Protein Cell 12, 695-716 (2021).<br /> (9) Su, Y. et al. A single-cell transcriptome atlas of glial diversity in the human hippocampus across the postnatal lifespan. Cell Stem Cell 29, 1594-1610.e8 (2022).<br /> (10) Allen, W. E., Blosser, T. R., Sullivan, Z. A., Dulac, C. & Zhuang, X. Molecular and spatial signatures of mouse brain aging at single-cell resolution. Cell 186, 194-208.e18 (2023).<br /> (11) Soreq, L. et al. Major Shifts in Glial Regional Identity Are a Transcriptional Hallmark of Human Brain Aging. Cell Rep. 18, 557-570 (2017).<br /> (12) Hefendehl, J. K. et al. Homeostatic and injury-induced microglia behavior in the aging brain. Aging Cell (2014). doi:10.1111/acel.12149<br /> (13) Nikodemova, M. et al. Microglial numbers attain adult levels after undergoing a rapid decrease in cell number in the third postnatal week. J. Neuroimmunol. 0, 280-288 (2015).<br /> (14) Moca, E. N. et al. Microglia Drive Pockets of Neuroinflammation in Middle Age. J. Neurosci. 42, 3896-3918 (2022).<br /> (15) Heumos, L. et al. Best practices for single-cell analysis across modalities. Nat. Rev. Genet. 24, 550-572 (2023).<br /> (16) Saelens, W., Cannoodt, R., Todorov, H. & Saeys, Y. A comparison of single-cell trajectory inference methods: towards more accurate and robust tools. (2018). doi:10.1101/276907<br /> (17) Zöller, T. et al. Silencing of TGFβ signalling in microglia results in impaired homeostasis. Nat. Commun. 9, (2018).<br /> (18) Bedolla, A. et al. Microglia-derived TGF-β1 ligand maintains microglia homeostasis via autocrine mechanism and is critical for normal cognitive function in adult mouse brain. bioRxiv Prepr. Serv. Biol. (2023). doi:10.1101/2023.07.05.547814<br /> (19) Spittau, B., Dokalis, N. & Prinz, M. The Role of TGFβ Signaling in Microglia Maturation and Activation. Trends Immunol. 41, 836-848 (2020).<br /> (20) L. Nyberg, M. Lövdén, K. Riklund, U. Lindenberger, L. Bäckman, Memory aging and brain maintenance. Trends Cogn. Sci. 16, 292-305 (2012).<br /> (21) L. Luo, F. I. M. Craik, Aging and memory: A cognitive approach. Can. J. Psychiatry 53, 346-353 (2008).<br /> (22) Y. Stern, M. Albert, C. Barnes, R. Cabeza, A. Pascual-Leone, P. Rapp.<br /> A framework for concepts of reserve and resilience in aging. Neurobiol. Aging, 124 (2022), pp. 100-103, 10.1016/j.neurobiolaging.2022.10.015<br /> (23) Y. Stern, C.A. Barnes, C. Grady, R.N. Jones, N. Raz. Brain reserve, cognitive reserve, compensation, and maintenance: operationalization, validity, and mechanisms of cognitive resilience. Neurobiol. Aging, 83 (2019), pp. 124-129, 10.1016/j.neurobiolaging.2019.03.022<br /> (24) R. Cabeza, M. Albert, S. Belleville, F.I.M. Craik, A. Duarte, C.L. Grady, U. Lindenberger, L. Nyberg, D.C. Park, P.A. Reuter-Lorenz, M.D. Rugg, J. Steffener, M.N. Rajah. Maintenance, reserve and compensation: the cognitive neuroscience of healthy ageing. Nat. Rev. Neurosci., 19 (11) (2018), Article 11, 10.1038/s41583-018-0068-2<br /> (25) Palovics, R. et al molecular hallmarks of heterochronic parabiosis at single-cell resolution. Nature 603, 309-314 (2022)<br /> (26) Sala Frigerio, C. et al. The major risk factors for Alzheimer's Disease: age, sex, and genes modulate the microglial response to Abeta plaques. Cell Rep, 27, 1293-1306 (2019)
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Reviewer #1 (Public Review):
Summary:
In this manuscript, "PAbFold: Linear Antibody Epitope Prediction using AlphaFold2", the authors generate a python wrapper for the screening of antibody-peptide interactions using AlphaFold, and test the performance of AlphaFold on 3 antibody-peptide complexes. In line with previous observations regarding the ability of AlphaFold to predict antibody structures and antigen binding, the results are mixed. While the authors are able to use AlphaFold to identify and experimentally validate a previously characterized broad binding epitope with impressive precision, they are unable to consistently identify the proper binding registers for their control [Myc-tag, HA-tag] peptides. Further, it appears that the reproducibility and generality of these results are low, with new versions of AlphaFold negatively impacting the predictive power. However, if this reproducibility issue is solved, and the test set is greatly increased, this manuscript could contribute strongly towards our ability to predict antibody-antigen interactions.
Strengths:
Due to the high significance, but difficulty, of the prediction of antibody-antigen interactions, any attempts to break down these predictions into more tractable problems should be applauded. The authors' approach of focusing on linear epitopes (peptides) is clever, reducing some of the complexities inherent to antibody binding. Further, the ability of AlphaFold to narrow down a previously broadly identified experimental epitope is impressive. The subsequent experimental validation of this more precisely identified epitope makes for a nice data point in the assessment of AlphaFold's ability to predict antibody-antigen interactions.
Weaknesses:
Without a larger set of test antibody-peptide interactions, it is unclear whether or not AlphaFold can precisely identify the binding register of a given antibody to a given peptide antigen. Even within the small test set of 3 antibody-peptide complexes, performance is variable and depends upon the scFv scaffold used for unclear reasons. Lastly, the apparent poor reproducibility is concerning, and it is not clear why the results should rely so strongly on which multi-sequence alignment (MSA) version is used, when neither the antibody CDR loops nor the peptide are likely to strongly rely on these MSAs for contact prediction.
Major Point-by-Point Comments:
(1) The central concern for this manuscript is the apparent lack of reproducibility. The way the authors discuss the issue (lines 523-554) it sounds as though they are unable to reproduce their initial results (which are reported in the main text), even when previous versions of AlphaFold2 are used. If this is the case, it does not seem that AlphaFold can be a reliable tool for predicting antibody-peptide interactions.
(2) Aside from the fundamental issue of reproducibility, the number of validating tests is insufficient to assess the ability of AlphaFold to predict antibody-peptide interactions. Given the authors' use of AlphaFold to identify antibody binding to a linear epitope within a whole protein (in the mBG17:SARS-Cov-2 nucleocapsid protein interaction), they should expand their test set well beyond Myc- and HA-tags using antibody-antigen interactions from existing large structural databases.
(3) As discussed in lines 358-361, the authors are unsure if their primary control tests (antibody binding to Myc-tag and HA-tag) are included in the training data. Lines 324-330 suggest that even if the peptides are not included in the AlphaFold training data because they contain fewer than 10 amino acids, the antibody structures may very well be included, with an obvious "void" that would be best filled by a peptide. The authors must confirm that their tests are not included in the AlphaFold training data, or re-run the analysis with these templates removed.
(4) The ability of AlphaFold to refine the linear epitope of antibody mBG17 is quite impressive and robust to the reproducibility issues the authors have run into. However, Figure 4 seems to suggest that the target epitope adopts an alpha-helical structure. This may be why the score is so high and the prediction is so robust. It would be very useful to see along with the pLDDT by residue plots a structure prediction by residue plot. This would help to see if the high confidence pLDDT is coming more from confidence in the docking of the peptide or confidence in the structure of the peptide.
(5) Related to the above comment, pLDDT is insufficient as a metric for assessing antibody-antigen interactions. There is a chance (as is nicely shown in Figure S3C) that AlphaFold can be confident and wrong. Here we see two orange-yellow dots (fairly high confidence) that place the peptide COM far from the true binding region. While running the recommended larger validation above, the authors should also include a peptide RMSD or COM distance metric, to show that the peptide identity is confident, and the peptide placement is roughly correct. These predictions are not nearly as valuable if AlphaFold is getting the right answer for the wrong reasons (i.e. high pLDDT but peptide binding to a non-CDR loop region). Eventual users of the software will likely want to make point mutations or perturb the binding regions identified by the structural predictions (as the authors do in Figure 4).
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Author response:
Reviewer #1 (Public Review):
This manuscript presents an exciting new method for separating insulin secretory granules using insulator-based dielectrophoresis (iDEP) of immunolabeled vesicles. The method has the advantage of being able to separate vesicles by subtle biophysical differences that do not need to be known by the experimenter, and hence could in principle be used to separate any type of organelle in an unbiased way. Any individual organelle ("particle") will have a characteristic ratio of electrokinetic to dielectrophoretic mobilities (EKMr) that will determine where it migrates in the presence of an electric field. Particles with different EKMr will migrate differently and thus can be separated. The present manuscript is primarily a methods paper to show the feasibility of the iDEP technique applied to insulin vesicles. Experiments are performed on cultured cells in low or high glucose, with the conclusion that there are several distinct subpopulations of insulin vesicles in both conditions, but that the distributions in the two conditions are different. As it is already known that glucose induces release of mature insulin vesicles and stimulates new vesicle biosynthesis and maturation, this finding is not necessarily new, but is intended as a proof of principle experiment to show that the technique works. This is a promising new technology based on solid theory that has the possibility to transform the study of insulin vesicle subpopulations, itself an emerging field. The technique development is a major strength of the paper. Also, cellular fractionation and iDEP experiments are performed well, and it is clear that the distribution of vesicle populations is different in the low and high glucose conditions. However, more work is needed to characterize the vesicle populations being separated, leaving open the possibility that the separated populations are not only insulin vesicles, but might consist of other compartments as well. It is also unclear whether the populations might represent immature and mature vesicles, distinct pools of mature vesicles such as the readily releasable pool and the reserve pool, or vesicles of different age. Without a better characterization of these populations, it is not possible to assess how well the iDEP technique is doing what is claimed.
Major comments:
1) There is no attempt to relate the separated populations of vesicles to known subpopulations of insulin vesicles such as immature and mature vesicles, or the more recently characterized Syt9 and Syt7 vesicle subpopulations that differ in protein and lipid composition (Kreutzberger et al. 2020). Given that it is unclear exactly what populations of vesicles will be immunolabeled (see point #2 below), it is also possible that some of the "subpopulations" are other compartments being separated in addition to insulin vesicles. It will be important to examine other markers on these separated populations or to perform EM to show that they look like insulin vesicles.
We thank the reviewer for this comment and have added the following to the discussion:
“The intensity peaks we observed at specific EKMr values likely correspond to some of the previously described insulin vesicle subpopulations34,54-57. Larger particles are expected to have a smaller EKMr value compared to smaller particles50. Subpopulations containing larger insulin vesicles, such as a mature pool34,54, synaptotagmin IX-positive vesicles57, or docked vesicles near the plasma membrane34 may have lower EKMr values than smaller immature vesicles. Additionally, phosphatidylcholine lipids increase the zeta potential of tristearoylglycerol crystals58. This effect may extend to insulin vesicle subpopulations containing more phosphatidylcholine, such as young insulin vesicles55 which could lead to higher EKMr values. Taken together, these two properties may be used to predict the EKMr values of known insulin vesicle subpopulations. For example, insulin vesicles with EKMr values of 1-2×109 V/m2 (Fig. 4C) may represent a synaptotagmin IX-positive subpopulation due to their larger radii and depletion under glucose stimulation. Additionally, young insulin vesicles may have EKMr values between 5 and 7.5×109 V/m2 (Fig. 4C) due to higher amounts of phosphatidylcholine present in this subpopulation55. In this EKMr range, we observed a higher intensity for glucose-treated cells which may suggest biosynthesis of new vesicles. Immature insulin vesicles are likely to have higher EKMr values due to their smaller size34, such as an EKMr value between 1.5-1.6×1010 V/m2 (Fig. 4C). Here we demonstrated the capabilities of DC-iDEP to separate insulin vesicle subpopulations in an unbiased manner. Future experiments using chemical probes to label subpopulations will be useful to accurately define the EKMr values associated with specific subpopulations.” pages 7-8, lines 176-191
Furthermore, we have conducted additional experiments using a modified INS-1 cell line with a GFP-tagged C-peptide (hPro-CpepSfGFP, GRINCH cells RRID:CVCL_WH61) in order to visualize a more complete population of insulin vesicles. By using this cell line, we have performed confocal microscopy, transmission electron microscopy, and cryo-electron microscopy experiments, demonstrating that the isolated vesicles resemble insulin vesicles and contain GFP-tagged C-peptide (Fig. 1-S3). While we acknowledge that further investigation using a more detailed labeling strategy of known insulin vesicle populations with DC-iDEP would be informative, we believe it is beyond the scope of our initial proof-of-concept experiments.
The following text was added to the results section to describe our additional microscopy analysis:
“To verify that the insulin vesicles were intact prior to DC-iDEP, we imaged a modified INS-1E cell line that contains a human insulin and green fluorescent protein-tagged C peptide (hPro-CpepSfGFP).49 This GFP tag allowed for quick visual verification of intact vesicles using fluorescence confocal microscopy. We observed distinct puncta rather than a diffuse GFP signal which indicated that the vesicles were intact and not ruptured. Further analysis of isolated vesicles was done using EM. We observed intact vesicles with the expected size and shape using both transmission electron microscopy (TEM) and cryo-electron microscopy (cryo-EM) (Fig. 1—figure supplement 3).” Page 5, lines 104 – 109.
2) An antibody to synaptotagmin V is used to immunolabel vesicles, but there has been confusion between synaptotagmins V and IX in the literature and it isn't clear what exactly is being recognized by this antibody (this reviewer actually thinks it is Syt 9). If it is indeed recognizing Syt 9, it might already be labeling a restricted population of insulin vesicles (Kreutzberger et al. 2020). The specificity of this antibody should be clarified. Furthermore, Figure 2 is not convincing at showing that this synaptotagmin antibody specifically labels insulin vesicles nor is there convincing colocalization of this synaptotagmin antibody with insulin vesicles. In the image shown, several cells show very weak or no staining of both insulin and the synaptotagmin. The highlighted cell appears to show insulin mainly in a perinuclear structure (probably the Golgi) rather than in mature vesicles (which should be punctate), and insulin is not particularly well-colocalized with the synaptotagmin. Other cells in the image appear to have even less colocalization of insulin and synaptotagmin, and there is no quantification of colocalization. It seems possible that this antibody is recognizing other compartments in the cell, which would change the interpretation of the populations measured in the iDEP experiments. It would also be good to perform synaptotagmin staining under glucose-stimulating conditions, in case this alters the localization.
We thank the reviewer for bringing this issue to our attention. The antibody originally used in Figure 2 recognizes the 386 aa isoform of synaptotagmin, which is called Syt 9 in the paper mentioned above (Kreutzberger et al. 2020). We have edited our manuscript to label this antibody as “Synaptotagmin IX” to match the existing literature. This antibody, therefore, likely labels only a subset of insulin vesicles. We believe that populations measured in the iDEP experiments consist solely of insulin vesicles, as supported by Western blot and dynamic light scattering results (Fig. 1—figure supplement 2B-C), as well as EM images (Fig. 1—figure supplement 3). Even with a subset of insulin vesicles, these results show the potential of this method, as iDEP analysis reveals heterogeneity within the population of Syt 9-positive insulin vesicles. We have replaced the original immunofluorescence images in Figure 2 with images that are more representative of INS-1E cells. We recognize that immuno-labeling did not yield perfect co-localization, which was expected. However, these experiments do provide valuable insights into the promise of using DC-iDEP for more in-depth separation analysis. Future work will use a modified INS-1 cell line or mouse model with a GFP-tagged C-peptide (hPro-CpepSfGFP, GRINCH cells RRID:CVCL_WH61) in order to visualize a less restricted set of insulin vesicles, avoiding the limitations associated with antibodies confined to a specific insulin vesicle subpopulation.
3) The EKMr values of the vesicle populations between the low and high glucose conditions don't seem to precisely match. It is unclear if this just a technical limitation in comparing between experiments or instead suggests that glucose stimulation does not just change the proportion of vesicles in the subpopulations (i.e. the relative fluorescent intensities measured), but rather the nature of the subpopulations (i.e. they have distinct biophysical characteristics). This again gets to the issue of what these vesicle subpopulations represent. If glucose stimulation is simply converting immature to mature vesicles, one might expect it to change the proportion of vesicles, but not the biophysical properties of each subpopulation.
We thank the reviewer for this question. We agree that glucose likely shifts the proportion of vesicles within a specific EKMr value rather than impacting the overall biophysical characteristics of all vesicles. We have performed new statistical analysis as suggested and rewritten this section to better explain the differences between conditions.
“Visual inspection of the collected data revealed generally similar patterns of vesicles collected at specific EKMr values (Fig. 4). However, at 1200 V we achieved adequate separation of vesicle populations to discern unique populations of vesicles from cells treated with glucose compared to no treatment. Using a two-way ANOVA, we found a statistically significant interaction between the effect of treatment on vesicles collected at each EKMr value for data collected only at 1200 V [F (8, 45) = 3.61, p= 0.003]. A Bonferroni post hoc test revealed a significant difference in the intensity or quantity of vesicles collected between treated and untreated samples at 1.10x109 V/m2 (p=0.0249), 5.35x109 V/m2 (p=0.0469), 7.45x109 V/m2 (p=0.0369). These differences reflect a shift in the populations of insulin vesicles upon glucose stimulation.” Page 7, lines 158-165
We have also now directly addressed the potential identities of the different populations in the discussion section. This was addressed in major comment #1 and on page 7 lines, 176-191 of the manuscript.
4) The title of the paper promises "isolation" of insulin vesicles, but the manuscript only presents separation and no isolation of the separated populations. Isolation of the separated populations is important to be able to better define what these populations are (see point #1 above). Isolation is also critical if this is to be a valuable technique in the future. Yet the paper is unclear on whether it is actually technically feasible to isolate the populations separated by iDEP. In line 367, it states "this method provides a mechanism for the isolation and concentration of fractions which show the largest difference between the two population patterns for further bioanalysis (imaging, proteomics, lipidomics, etc.)." However, in line 361 it says "developing the capability to port the collected individual boluses will enable downstream analyses such as mass spectrometry or electron microscopy," suggesting that true isolation of these populations is not yet feasible. This should be clarified.
We thank the reviewer for pointing this out. We have modified the text and title to put more focus on our ability to separate vesicles rather than isolate. We agree that the isolation and further biophysical characterization of these subpopulations will be critical to understanding them. However, this capability is still in development. We have made the following change to clarify that a way to isolate these subpopulations once iDEP-assisted separation has occurred is currently being developed.
Title: “Insulator-based dielectrophoresis-assisted separation of insulin secretory vesicles”
“this method serves as a stepping stone towards isolation and concentration of fractions which show the largest difference between the two population patterns for further bioanalysis…” page 9, line 230-232.
Reviewer #2 (Public Review):
This manuscript used DC-iDEP, a technology previously used on other organelle preparations to isolate insulin secretory granules from INS1 cells based on differences in dielectrophoretic and electrokinetic properties of synaptotagmin V positive insulin granules.
The major motivation presented for this work is to provide a methodology to allow for more sensitive isolation of subpopulations of granules allowing better understanding of the biochemical composition of these populations. This manuscript clearly demonstrates the ability of this technology to separate these subpopulations which will allow for future biochemical characterizations of insulin granules in future studies.
After proving these subpopulations can be observed, this method was then utilized to show there are shifts in these subpopulations when granules are isolated from glucose stimulated cells. Overall the method of isolation is novel and could provide a tool for further characterization of purified secretory granules.
The observation of glucose stimulation causing shifts in subpopulations is unsurprising. Glucose stimulation could cause a depletion of insulin and other secretory content from a subset of granules. It would be expected that this loss of content would cause a shift in electrochemical properties of the granules, but this is a nice confirmation that the isolation method has the sensitivity to delineate these changes.
Major comments:
1) It is unclear what Synaptotagmin isoform is being looked at. Synaptotagmin V and IX have been repetitively interchanged in the literature. See note in syt IX section of "Moghadam and Jackson 2013 Front. Endocrinology" or read "Fukuda and Sagi- Eisenberg Calcium Bind Proteins 2008".
The 386 aa. isoform that is abundant in PC12 cells has been robustly observed in INS1 cells in multiple studies and has been frequently referred to as syt IX. The sequence the antibody was raised against should be determined from the company where this was purchased and then this should be mapped to to which isoform of Synaptotagmin by sequence and clarified in the text.
We thank the reviewer for this comment. The supplier (Thermo Fisher Scientific) calls this antibody “Synaptotagmin V.” As it recognizes the 386 aa synaptotagmin isoform, we have changed references to this antibody to call it “Synaptotagmin IX” to match the existing literature.
2) Immunofluorescence of insulin and syt V is confusing. The example images do not appear to show robust punctate structures that are characteristic of secretory granules (in both the insulin and syt V stain).
We appreciate the reviewer bringing this point to our attention. We agree that the immunofluorescence images in Figure 2 are not representative of typical INS-1E cells and have replaced the original image for Figure 2 with new images that show punctate structures that are more characteristic of secretory granules. These images also have better colocalization of insulin and synaptotagmin V (now labeled synaptotagmin IX) than the original image, with Pearson’s R values of 0.66 and 0.64.
3) In the discussion it says, "Finally, this method provides a mechanism for the isolation and concentration of fractions which show the largest difference between the two population patterns for further bioanalysis (imaging, proteomics, lipidomics, etc.) that otherwise would not be possible given the low-abundance components of these subpopulations."
It would help to elaborate more on the yield and concentrations of isolated granules. This would give a better sense of what level of biochemical characterization could be performed on sub- populations of granules.
We thank the reviewer for this comment. This line has been changed to clarify the current capabilities of iDEP, as subpopulations cannot presently be removed from the channel.
“this method serves as a stepping stone towards isolation and concentration of fractions which show the largest difference between the two population patterns for further bioanalysis…” page 9 line 230-232.
Once it is possible to isolate subpopulations from the channel, we expect to obtain sufficient sample for further characterization. We anticipate that biophysical characterization such as imaging will be highly feasible, and small-scale proteomics could also be possible. However, currently we have not measured the concentration of isolated vesicles due to complications in the isolation steps. If the quantity of isolated subpopulations proves inadequate for proteomic analysis, we plan to scale up our cell culture to generate enough insulin vesicles for further biochemical characterization. However, these experiments are out of scope for our current work, so we removed details on this idea in the Introduction and Discussion.
Reviewer #3 (Public Review):
The manuscript from Barekatain et al. is investigating heterogeneity within the population of insulin vesicles from an insulinoma cell line (INS-1E) in response to glucose stimulation. Prevailing dogma in the beta-cell field suggests that there are distinct pools of mature insulin granules, such as ready-releasable and a reserve pool, which contribute to distinct phases of insulin release in response to glucose stimulation. Whether these pools (and others) are distinct in protein/lipid composition or other aspects is not known, but has been suggested. In this manuscript, the authors use density gradient sedimentation to enrich for insulin vesicles, noting the existence of a number of co-purifying contaminants (ER and mitochondrial markers). Following immunolabeling with synaptotagmin V and fluorescent-conjugated secondary antibodies, insulin vesicles were applied to a microfluidic device and separated by dielectrophoretic and electrokinetic forces following an applied voltage. The equilibrium between these opposing forces was used to physically separate insulin granules. Here some differences were observed in the insulin (Syt V positive) granule populations, when isolated from cells that were either non-stimulated or stimulated with glucose, which has been suggested previously by other studies as noted by the authors; however in the current manuscript, the inclusion of a number of control experiments may provide a better context for what the data reveal about these changes.
The major strength of the paper is in the use of the novel, highly sophisticated methodology to examine physical attributes of insulin granules and thus begin to provide some insight into the existence of distinct insulin granule populations within a beta-cell -these include insulin granules that are maturing, membrane- docked (i.e. readily releasable), in reserve, newly-synthesized, aged, etc. Whether physical differences exist between these various granule pools is not known. In this capacity, the technical abilities of the current manuscript may begin to offer some insight into whether these perceived distinctions are physical.
The major weakness of the manuscript is that the study falls short in terms of linking the biology to the sophisticated changes observed and primarily focuses on differences in response to glucose. Without knowing what the various populations of granules are, it is challenging to understand what the changes in response to glucose mean.
Specific concerns are as follows:
1) There is confusion on what the DC-iDEP separation between stimulated and stimulated cells reveals. Do these changes reflect maturation state of granules, nascent vs. old granules? Ready- releasable vs. reserve pool? The comments in the text seem to offer all possibilities.
We thank the reviewer for this comment. Additional experiments will be useful to concretely define the physical nature of these subpopulations. Our primary goal in this study is to assess the utility of DC-iDEP in reproducibly separating these subpopulations. Our current results reflect variations in the amounts of subpopulations described in the literature and/or in currently uncharacterized subpopulations. As addressed in Reviewer #1 question #1, we have added to the discussion to review these possibilities (Page 7-8, lines 176-191).
2) It is unclear what we can infer regarding the physical changes of granules between the stimulated states of the cells. Without an understanding of the magnitude of the effect, it is unclear how biologically significant these changes are. For example, what degree of lipid or protein remodeling would be necessary to give a similar change?
We thank the reviewer for this question. Separation by iDEP is sufficiently sensitive to distinguish particles with minimal differences between them. For example, we could successfully separate wild type GFP from a point mutation variant of GFP. We anticipate that this method is capable of distinguishing vesicles with greater physical differences between them resulting in more distinct EKMr values. However, significant future experiments are likely necessary to determine the extent of lipid and protein remodeling between each subpopulation to define the biological significance of each subpopulation.
3) The reliance on a single vesicle marker, Syt V, is concerning given that granule remodeling is the focus.
We appreciate the reviewer’s concern. The current manuscript focuses on synaptotagmin V (IX)-positive insulin vesicles. The results of these experiments demonstrate the capabilities of iDEP to reveal heterogeneity in a seemingly similar set of particles. In future experiments we plan to use the modified INS-1 cell line with a GFP-tagged C-peptide (hPro-CpepSfGFP, GRINCH cells RRID:CVCL_WH61). All insulin vesicles from this cell line contain GFP-tagged C-peptide, and therefore would allow for the detection of a more complete set of insulin vesicles. The results from the current manuscript provide the proof-of-concept validation that this method is promising for understanding vesicle remodeling in more detail in the future.
4) Additional confirmation that the isolated vesicles are in fact insulin granules would be helpful. As noted, granules were gradient enriched, but did carry contaminants. Note that the microscopy image provided does not provide any real validation for this marker.
Further confirmation that the immune-isolated vesicles are in fact insulin granules should be included. EM with immunogold labeling post-SytV enrichment would be a potential methodology to confirm.
We thank the reviewer for this comment. We have performed new immunofluorescence imaging to demonstrate the overlap of insulin and synaptotagmin (Fig 2). Additionally, we have performed microscopy experiments with a modified INS-1 cell line with a GFP-tagged C-peptide (hPro-CpepSfGFP, GRINCH cells RRID:CVCL_WH61) in order to provide evidence of these granules’ identity. Fluorescence microscopy revealed that the isolated granules contain GFP-tagged C-peptide (Fig. 1—figure supplement 3A), while transmission electron microscopy and cryo-electron microscopy confirmed that these vesicles have radii within the correct range to be considered insulin vesicles (Fig 1—figure supplement 3B-C). We added the following text in the results section to describe the new results included:
“To verify that the insulin vesicles were intact prior to DC-iDEP, we imaged a modified INS-1E cell line that contains a human insulin and green fluorescent protein-tagged C peptide (hPro-CpepSfGFP).49 This GFP tag allowed for quick visual verification of intact vesicles using fluorescence confocal microscopy. We observed distinct puncta rather than a diffuse GFP signal which indicated that the vesicles were intact and not ruptured. Further analysis of isolated vesicles was done using EM. We observed intact vesicles with the expected size and shape using both transmission electron microscopy (TEM) and cryo-electron microscopy (cryo-EM) (Fig. 1—figure supplement 3). Page 5, lines 104 – 109.
5) It would be useful to understand if the observed effects are specific to the INS-1E cell line or are a more universal effect of glucose on beta-cells.
We agree with the reviewer that it would be interesting to study these effects in primary beta cells. While we expect to see similar results in these cells, there may be differences in the population variations or EKMr values. However, working with beta cells is currently beyond the scope of this study, as our primary focus is on validating this approach.
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Author response:
Reviewer #1 (Public Review):
Authors propose a mechanism where actin polymerization in the dendritic shaft plays a key role in trapping AMPAR vesicles around the stimulated site, promoting the preferential insertion of AMPAR into the potentiated synapse. This dendritic mechanism is novel and may be important for phenomena. Authors also developed a sophisticated method to observe the endogenous behavior of AMPAR using the HITI system.
However, there are some major issues that need to be addressed to support the authors' claims. Also, overall, it is hard to follow. It could be better written.
We thank the reviewer for carefully reading our text and for the helpful recommendations. We have performed additional experiments and analysis to address the raised issues (detailed below). In addition, we have streamlined and shortened the text to improve its clarity and focus on the biological story.
Reviewer #2 (Public Review):
In this study, Wong and colleagues investigate mechanisms leading to input-specificity of LTP. They focus on the trafficking of AMPA receptors as the surface accumulation of AMPARs is one of the key features of potentiated synapses. They employ an elegant strategy to label endogenous GluA1 with a HaloTag using CRISPR-based technology and succeed to find targeting site which does not interfere with receptor's trafficking or function. This allowed them to visualize and track single receptors in endosomes as well as at the plasma membrane of primary rat hippocampal neurons. They develop and extend particle tracking and molecule counting algorithms to analyze active transport and diffusion of AMPARs and, as expected find that neuronal activation leads to increased surface expression of labelled AMPARs. Interestingly, they also observe a strong decrease in long-range motion of AMPAR-containing vesicles upon induction of chemical LTP. From this point, the manuscript focuses on explaining this observation. The authors switch from a global activation protocol to glutamate uncaging to induce LTP at individual synapses. Also, in these settings, they measure the reduction in mobile vesicle fraction within about 30 µm long dendritic segment containing the activated spine. In search of an explanation, they investigate activity-dependent actin polymerization as a possible confinement factor that could change the motility of organelles in dendrites. Their hypotheses is based on pre-existing literature demonstrating the role of F-actin in trapping and stalling dendritic endolysosomes as well similar role of F-actin in non-neuronal cells. Indeed, the authors convincingly show that pharmacological depolymerization or stabilization of F-actin bidirectionally impacts the trafficking behavior of AMPAR-containing vesicles in the dendritic shaft. To directly visualize effects of structural LTP at individual synapses on dendritic actin cytoskeleton, they employ a F-actin-binding probe Tractin. Here they find that cLTP results in the formation of dendritic F-actin fibers and bundles arranged in a network. The spatial extent of such a network correlates with an area where AMPAR vesicles exhibit decreased motility. Although this makes sense, I have some concerns about these experiments.
Tractin has been previously published as F-actin marker but like several other binding probes (i.e. lifeact), it affects F-actin structure and dynamics. The large number of F-actin bundles is not very typical for dendrites of hippocampal neurons and might be an artifact of Tractin overexpression. It is difficult to judge whether this is a case because there is no comparison with the endogenous situation where F-actin is labelled directly. The final series of experiments focus on the role of processive myosins in stalling and exocytosis of AMPAR vesicles. To address this point, the authors employ a mixture of three different myosin inhibitors and show that although myosins are not responsible for increased vesicle confinement they facilitate exocytosis of AMPARs. What I find somewhat missing are data and examples of AMPAR trafficking into dendritic spines. Also here, stronger experimental support could benefit the conclusions.
Overall, the authors achieved the aims of their study. They demonstrated that synapse-specific potentiation results in signaling which triggers actin polymerization in dendritic shaft beneath the activated input. This leads to trapping and accumulation of AMPAR-containing endosomes which then have higher probability to be delivered and secreted at activated dendritic spines. In addition to conceptual advance of this work, several state-of-the-art labeling and analysis techniques where developed in this project and they will likely be used by other groups.
We thank the reviewer for raising these important issues with regards to the use of tractin as a marker for actin polymerization. We have performed additional experiments (detailed below) using phalloidin and also dominant negative inhibitors of myosin Va, Vb, and VI in order to strengthen our conclusions. We find that inducing synaptic activity with cLTP increases phalloidin labeling and the appearance of F-actin fibers. Moreover, inhibition of myosin Va and Vb (but not VI) using their dominant negative c-terminal domains recapitulates the effects of pharmacological inhibition on both the motion states and directional bias of GluA1-HT vesicles in response to cLTP.
With regards to AMPAR trafficking into spines, we and others have found that GluA1-containing vesicles rarely enter dendritic spines (see response to Reviewer #2, comment 3). Furthermore, exocytic events occur largely at extrasynaptic sites, such as on the dendritic shaft (Figure 5-video 1-3; Lin et al., 2007; Makino et al., 2009; Patterson et al., 2010). Consequently, we believe vesicles are concentrated proximal to synaptic activity in the dendritic shaft rather than in the dendritic spine itself, creating a larger reservoir of intracellular AMPARs that can exocytose during synaptic activity. Others have demonstrated that surface bound AMPARs diffuse across the cell membrane into stimulated synapses where they are captured (Choquet and Opazo, 2022).
We also thank the reviewers for acknowledging the conceptual and technical advances in this work.
Reviewer #3 (Public Review):
Wong et al. developed a new versatile approach with a robust signal to track protein dynamics by inserting a tag into the endogenous loci and different properties of fluorescent dyes for conjugation. Using this approach, the authors monitor the trafficking of Fluorescent dye and Halo-tagged GluA1 with time-lapse imaging and found that neuronal stimulation induces GluA1 accumulation surrounding stimulated synapses on dendritic shafts and actin polymerization at synapses and dendrites. Furthermore, combining with pharmacological manipulations of actin polymerization or myosin activity, the authors found that actin polymerization facilitates exocytosis of GluA1 near activated synapses. The new approach may provide broad impacts upon appropriate control experiments, and the practical application of this approach to GluA1 trafficking upon neuronal activation is significant. However, there are several weaknesses, including confirmation of activity of the tagged receptors and receptor specificity mimicking endogenous LTP machinery. If the receptor tagged by the new robust approach reflects endogenous machinery, this approach will provide a big opportunity to the community as a versatile method to visualize a protein not visualized previously.
Although we use methods previously demonstrated to stimulate LTP, we do not ourselves demonstrate LTP using electrophysiological methods, and consequently we have changed the text to focus on synaptic plasticity (specifically structural plasticity). Furthermore, we confirm the activity of HaloTag knock-in receptors by expressing GluA1-HT and GluA1-HT-SEP in HEK293T cells and performing whole-cell patch clamp experiments. We find that GluA1-HT and GluA1-HT-SEP responds to glutamate in a similar manner to untagged GluA1.
We also thank the reviewer for acknowledging the novelty of our strategy.
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Reply to the reviewers
Reply to reviewers
First, we would like to extend our gratitude to all reviewers for their supportive and enthusiastic feedback, which acknowledges our study as an interesting, well-executed, and well-documented contribution to the field. We are also pleased that the novelty and significance of our work have been recognized and appreciated.
As highlighted by reviewers 2, 3, and 4, our research represents a substantial advancement in understanding the mechanisms that coordinate the development of different cell types. Our findings have broader implications for developmental biology. We also thank the reviewers for their valuable insights, which have significantly improved the overall readability of our manuscript. We have carefully considered all minor corrections and text modifications they had suggested and made amendments accordingly.
The reviewers proposed several complementary experiments to enhance and clarify our points. We have conducted most of these experiments, with one exception (detailed below), and incorporated the corresponding results into this revised version of the manuscript.
Additionally, reviewers agreed that higher resolution images depicting the interactions between tendon and myoblast membranes would strengthen our manuscript. In response, we are pleased to present new high-resolution images of Ama::EGFP localization with respect to tendon and muscle cells, obtained using Zeiss Airyscan technology. We also provide new images using newly generated flies that allow simultaneous observation of both myoblast and tendon membranes.
We believe these modifications substantially enhance the quality and interest of our results, as already highlighted by the reviewers.
__Referees cross-commenting: __
All reviewers agreed* that "this is an interesting study that is well done and well documented. I agree with reviewer 1 that the study would further benefit from better imaging of the cellular extensions of tendons and myoblasts to see how both cell types interact." *
Reply: We agree with this point. To address it, we analyzed leg discs from Sr-Gal4>UAS-myrGFP line (labelling tendon membranes) crossed with a newly generated line R32D05::CD4TdTomato (myoblast specific expression of membrane tagged Tomato protein). Using confocal Zeiss Airy Scan technology, we generated high resolution images for which both tendon cell extensions and myoblast membranes are simultaneously visualized. These images are included in the new Figure 2 (O, P and O', P'). To be noticed: as we also provide new high resolution images of Ama::EGFP and Nrt localizations (Fig. 2 M, N and M', N'), we removed images of zoom in of 5h APF leg disc.
REVIEWER 1
Moucaud et al carried out single cell sequencing on myoblasts from the developing drosophila leg muscles, focusing on gene expressions overlapping with tendon and muscle cells. This study proposes that neuronal cell adhesion molecules Ama and Nrt interact in myoblast and tendon adhesion to support tendon and in proliferation of muscle progenitors. This study traces Ama and Nrt expression with various drosophila mutant strains and provides evidence to support its claims using single cell sequencing, immuno-fluoresence and in situ hybridisation. *The authors report novel markers to study the interactions between muscle and tendon progenitors in the Drosophila leg provide convincing evidence of their functions in muscle and muscle and tendon formation. *
- The authors report novel markers to study the interactions between muscle and tendon progenitors in the Drosophila leg provide convincing evidence of their functions in muscle and muscle and tendon formation. *
__ Reply:__ We are grateful to the Reviewer 1 for his/her supportive comments on the quality of our work.
Page 2 "cell types*..." might be worth including other cell types such as vascular/endothelial if listing all cell types in the limb, as the sentence is suggesting. *
__ Reply__: "blood vessels" have been added as components of the limb musculoskeletal system.
Reviewer's comment: The authors discuss the interactions between the myoblasts and tendon cells but do not show any cellular resolution of the interaction between the cells and the secreted adhesion proteins. It would enhance the manuscript if the authors could show high resolution images of these cellular interactions with the secreted protein in vivo.
__ Reply__: see reply to referees cross-commenting about newly generated high-resolution images shown in Fig. 2.
Lots of examples of definite article (the) missing throughout the text.
Reply: The text has been edited and missing articles added
Second line of Abstract does not flow: Ama encodes secreted proteins to "Ama encodes a secreted protein"
__ Reply__ the correction has been made accordingly
2nd para Intro- this para is essentially discussing vertebrate limb muscle/tendon precursors, although includes a non-vertebrate citation. It could be helpful to (briefly) compare/contrast the non-vertebrate vs vertebrate literature on this topic.
__ Reply__: Indeed, this paragraph is primarily focused on the development of the musculoskeletal system in vertebrates. The comparison (from a molecular standpoint) with the muscle system of the Drosophila leg appears in the following paragraph. For clarity, we have included a brief, more general description (end of second paragraph) about the muscle/tendon system in Drosophila to highlight certain divergences between vertebrate and invertebrate systems and to introduce the subsequent paragraph.
"in limb of chick embryo add "the limb"
__ Reply:__ the correction has been made accordingly
p6 because these two antibodies were raised in rabbit, as the Twist antibody, needs some additional explanatory text.
__ Reply__: We have modified the text to give a more accurate explanation: "Because these two antibodies were raised in rabbit, as was the Twist antibody, we could not use this latter to visualize the myoblasts"
P9 discussion creeping into results section-with some speculation on Ama forming homophilic adhesions which has not been experimentally tested.
__ Reply:__ Because we chose to submit this work as a short format paper, Results and Discussion sections are indeed combined. However, we agree that homophilic adhesion properties of Ama have been shown only in cell culture and not tested in physiological context. To clarify this point, we have modified the corresponding part of the text and only suggest that Ama could directly bind to membranes through its putative GPI modification as proposed by Seeger et al.
Ama depletion affects both viability and the proliferation rate of leg disc myoblasts (in a Nrt-independent way) Does it have similar role in tendon precursors? Could the authors provide any evidence of apoptosis given proposed role of Ama in glial cells?
__ Reply: __As asked by Reviewer 1, we have tested these two points and included the results in suppl figure 3 (A-C). As expected, the proliferation rate of tendon cells is not affected as we have previously showed that tendon cells are post-mitotic cells (Laurichesse et al. 2021). Moreover, we now show that Ama depletion does not lead to apoptosis of tendon cells. See Supp. Figure 3 (A-C), the main text has also been modified accordingly.
REVIEWER 2:
In this well-written, comprehensive, and interesting manuscript, the authors study the molecular circuitry that supports the coordinated activity of tendon cells and myoblasts during development. As the authors themselves point out in the introduction, the assembly of tissues within the musculoskeletal system provides a particularly attractive system in which to study how different cell types coordinate their behaviours to form higher-order structures. Using single-cell transcriptomics, the authors first identify the cell adhesion molecule Ama and transmembrane protein Nrt as enriched in Drosophila myoblasts and tendon cells. Their transcriptomic data suggest that Nrt is specifically expressed in the tendon cells while Ama is expressed in both. They support these data with a variety of in situ, antibody, and endogenous stainings. Using a series of genetic manipulations, they then convincingly show that Ama controls the total number of myoblasts during the larval stages: Ama knockdown is associated with both decreased proliferation and increased apoptosis of myoblasts. Ama's role in regulating myoblast number is shown to be independent of Nrt and likely under the control of the FGF/RTK pathway. Finally, the authors show that the loss of either Nrt or Ama activity is associated with a loss of adhesion between myoblasts and tendon cells and with the stunted growth of the long tendon. Thus, their data point to Ama playing dual roles in muscle development by regulating both myoblast number and cell adhesion.
* I very much enjoyed reading the paper, which I think makes an important contribution to our understanding of both the developing musculature and inter-cell-type coordination during development more broadly. I have only a handful of grammatical errors to point out.*
__Reply: __We appreciate these enthusiastic and supportive comments, and we would like to thank the Reviewer for highlighting the broader contribution of our work to the understanding of the mechanisms of coordination between different cell types.
*- Grammar: 'This prompted us to use Drosophila model to search' should read 'This prompted us to use the Drosophila model to search' - Grammar: '...identify Neurotactin (Nrt) and its binding partner, Amalgam (Ama) as candidates...' should read '...identify Neurotactin (Nrt) and its binding partner, Amalgam (Ama), as candidates...' - Grammar: 'As tendon precursors in leg disc' should read 'As tendon precursors in the leg disc'. - Grammar : '...we performed a series of in situ hybridization...' should read '...we performed a series of in situ hybridizations...' - Grammar: 'Because these two antibodies were raised in rabbit, as the Twist antibody' should read 'Because these two antibodies were raised in rabbit, as was the Twist antibody' - Grammar: 'Statistical analysis reveals an increase myoblast total number when overexpressing an activated ERK' should read 'Statistical analysis reveals an increase in the total number of myoblasts when overexpressing an activated ERK' - Grammar: The following section header needs rephrasing: 'Ama, potential downstream effector of FGF pathway in the regulation of myoblast number'. Maybe 'Ama is a potential downstream effector of the FGF pathway in the regulation of myoblast number' or Ama: a potential downstream effector of the FGF pathway in the regulation of myoblast number. - Grammar: 'whereas its reduction (UAS-StyRNAi) lead to more myoblasts' should read 'whereas its reduction (UAS-StyRNAi) leads to more myoblasts' - For clarity 'The expression of the constitutively active form of ERK could rescue the phenotype of Ama depletion in glial cells (Ariss et al. 2020)' might read better as 'Previous work has shown that the expression of the constitutively active form of ERK can rescue the phenotype of Ama depletion in glial cells (Ariss et al. 2020). Therefore, we tried...' - Grammar: 'showed a significant higher number of myoblasts compared' should read 'showed a significantly higher number of myoblasts compared' - Grammar: 'Another, not exclusive, possibility' should read Another, non-mutually exclusive, possibility'. - Grammar: 'We measured the length of the tilt relatively to the length' should read '. We measured the length of the tilt relative to the length' *
Reply: All the modifications suggested above by Reviewer 2 are now included in the text.
REVIEWER 3:
*Myoblast and tendon precursors stem from different developmental origins. Hence, they need to find each other to build a functional muscle-skeleton. How they do so is an exciting biological problem, not only for this reviewer who is working on Drosophila muscle development, too. As we currently understand little about how myoblasts communicate with tendons during development, I find this manuscript a generally interesting contribution unravelling a new mechanism of cell-cell communication between these two cell types. It proposes a role for 2 interesting proteins that are little studied. Furthermore, Drosophila leg muscle-tendon development is complex and results in an intricate final architecture. Thus, a better understanding of its molecular mechanisms of development is exciting to this reviewer and to the muscle and tendon fields. *
Reply: We express our gratitude to Reviewer 3 for his/her keen interest in our work and for emphasizing its significance within the field of developmental biology.
*While some Ama mRNA expression in myoblasts was confirmed with in situ hybridisation, it was also shown that Ama mRNA is expressed in other sources including tendon precursors. As the interesting AmaGFP protein overlapping with the developing tendon cells is found at some distance from the myoblasts, the source for this Ama protein population is not entirely clear. To identify if it is secreted from myoblasts I suggest to stain for Ama-GFP in the muscle-specific Ama knock-down discs at 5h APF. This could use the late knock-down condition. *
__ Reply:__ In Suppl Fig.2 in a close-up view of the femur region, we show that at 5h APF Ama is transcribed in addition to myoblasts also in the developing tilt tendon. This tendon associated Ama expression is specific as it is detected after myoblast specific Ama knockdown. Thus, at 5h APF, the Ama-GFP signal detected at the interface of muscle and tendon precursors could in part correspond to Ama secreted by the tilt tendon cells. However, we also observed clear Ama-GFP signal at the interface of myoblasts and tendon precursors at 0h APF when Ama is not yet transcriptionally activated in tilt tendon precursors (not shown). Thus, we are confident that the myoblasts are the main source of secreted Ama protein that ensure close proximity of myoblast and tendon precursor cells. A view supported by the loss of myoblast-tendon cell proximity in myoblast-specific Ama knockdown. However, to clarify this point, we immunostained myoblast-specific Ama knock-down discs for the Ama protein in at 5h APF as suggested. As stated in the text, we were concerned that GFP tag could influence the life-time of the Ama protein, as GFP itself is pretty stable. This is why we used anti-Ama antibody kindly provided by Dr. Silman to determine whether myoblast-specific Ama knockdown (using R32D05-Gal4 driver) would completely abolish Ama protein at 5h APF. We indeed observed a strong reduction of Ama protein at this stage indicating that the contribution of Ama protein from tendon cells is minimal (but cannot be completely excluded), with myoblasts remaining the major source at this stage. This new result is now presented in Suppl Fig. 2M-P. This result is also in accordance with our new result showing that tendon-specific AmaKD has no effect on tendon growth (see reply to the comment below regarding tendon length). In light of this new result, we have modified the text accordingly in the corresponding paragraph (p5-6).
Generally, it might be useful to move the part of Figure 2 that shows the Ama-GFP Nrt co-staining to the later part in the text that addresses the interaction of both cell types and keep the autonomous Ama role in muscle for the start of paper only.
__ Reply: __We have indeed debated extensively about this possibility before submitting this work. While such a presentation would have some logical coherence, it also has the disadvantage of having to resume, at least partially, the expression of Ama, leading to certain redundancies. Additionally, we chose to begin with a comparison of the new myoblast transcriptomic data with pre-established tendon data to highlight the presence of ligand-receptor pairs. In this context, it seemed to us more pertinent to present the expression patterns of Ama and Nrt together in the initial figures.
To quantify the interaction of the myoblast cell membranes and the tendon cells better it would be useful to combine sr>CAAXmCherry with a myoblast membrane maker (possibly Him-CD8-GFP or use R15B03-Gal4 with R79D08-lexA). This could also improve the "mean distance" measurements. As currently presented, it is not so clear how the mean distance was measured. It could be helpful to indicate some examples in zoom-in vies on Figure 5. Does a distance of 4 µm in wild type mean that the myoblast is not touching the tendon precursors, or is only the myoblast nucleus that is Twi positive at this distance?
__ Reply: We are grateful to this reviewer for its relevant suggestion. Thus, as stated above (referees cross-commenting), we provide new high-resolution images with labelled membranes of both tendon cells and myoblasts (fig 2 O-P). As shown here, myoblast membranes are very closed to each other, and nuclei occupy an important part of myoblast volumes. So, we found more accurate to use the myoblast nucleus (stained with Twist antibody) to detect individual myoblasts using Imaris Spot function rather than myoblast membranes. We also believe that the distances between the center of myoblast nuclei and the tendon surface are representative of the distance between these two cell types as nucleus myoblast occupies most of the cell volume. We addressed this point in the new Suppl. Fig.5. __Regarding the distance of 4____ µm: As mentioned in the original text, the 4 µm distance represents the average distance between myoblasts and the tendon surface in wild type discs. We do not perceive this distance as indicative of a threshold distinguishing myoblasts that interact physically with tendons from those that do not. We rather use this mean distance to quantify the distribution of myoblasts around the tendon and their dispersion/mis-distribution in Ama and Nrt knockdown leg discs. To clarify this point, we have modified the corresponding paragraph: "This result indicates that AmaKD leads to myoblasts mis-distribution around the tilt, suggesting that the reduction of Ama level could affect myoblast-tendon adhesion".
For a better understanding of how the mean distance was measured, we added a new Supplementary Figure 5 (rather than a zoom-in in the main figure as suggested by this reviewer), with a corresponding description of how this distance was measured in addition to the explanations in the material and method section.
Is the tendon elongation phenotype seen after Ama RNAi in muscle and in Nrt mutants due to the fact that myoblasts are further away from tendons or is it an Ama/Nrt role that is autonomous to tendons? This could be tested by assaying tendon elongation after tendon-specific Ama knock-down as shown in Figure S2.
__ Reply: __As asked by this reviewer, we have performed this experiment using Sr-Gal4 driver to induce tendon-specific Ama knockdown and assessed tendon elongation using R79D08-lexA>lexAop-GFP marker. Overall statistical analysis is now included in Fig 5F and G graphs. This analysis shows that tendon-specific Ama knockdown does not affect tendon elongation. This is in concordance with the fact that Ama knockdown in myoblasts leads to tendon defects similar to that of Nrt loss of function in tendon clearly indicating that the observed phenotypes are due to Ama's role in myoblasts. This does not exclude an additional subsequent Ama function in growing tendon precursors in later development.
Minor : Is Figure 2Q a zoom-in from Figure 2P? If yes, it would be helpful to indicate the rough position of it in the lower magnification image.
Reply: Figure 2Q was not a zoom-in from Figure 2P in the previous version of the paper. As stated above Fig. 2 has now been modified.
Minor page 6 - w[1118] is with small "w".
Reply: modifications have been made accordingly in main and figure texts.
REVIEWER 4:
*The manuscript is well-organized, with clear descriptions of methods and results. The use of transcriptomic datasets and gene expression analyses provides insights into the molecular mechanisms underlying the interaction between muscle and tendon precursors. *
*The immunostaining and in situ hybridization experiments well illustrate the expression patterns of Ama and Nrt in muscle and tendon cells during leg disc development in Drosophila. *
*The functional analyses, including knockdown experiments, support the conclusion that Ama plays a crucial role in maintaining the pool of leg muscle precursor cells and coordinating tendon and muscle precursor growth. *
The manuscript significantly enhances our understanding of cell-cell interactions in the musculoskeletal system of Drosophila. The findings have broader implications for the field of developmental biology. In general, this manuscript provides valuable insights into the molecular processes governing leg muscle and tendon development.
Reply: We are indebted to Reviewer 4 for highlighting that our manuscript is well-organized and well-illustrated. We are also grateful to Reviewer 4 for highlighting the valuable insights of our work.
some aspects in the manuscript, for example how Ama regulates myoblast number and its interaction with the FGFR pathway, could be further explored or clarified.
__ Reply:__ Regarding Ama's contribution for maintaining the myoblast pool through its interaction with the FGF pathway, we demonstrate here that, contrary to what has been proposed for glial cells, Ama acts downstream of this pathway, although we emphasize that there is a synergistic effect with the MAPK pathway inhibitor, Sprouty. These findings thus reveal complex and variable regulatory mechanisms between Ama and the FGF pathway that would require specific investigation, the entirety of which appears challenging to integrate into this same publication.
the organization of the abstract could be improved to provide a clearer and more comprehensive overview of the study. The abstract currently lacks a structured presentation of essential components such as methods, results, and conclusions. It would greatly benefit from a more systematic arrangement.
__ Reply:__ We have made modifications to propose a more structured abstract.
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openbooks.lib.msu.edu openbooks.lib.msu.edu
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TAG ENDS OF OVERHEARD CONVERSATIONS
I don't have time to proof this entire play, but hopefully someone else already has or will do so? I've been comparing it to the Dial publication, but probably better to look at Sara Crangle's edited version, reprinted in the Essays and Stories of Mina Loy. This is also the authoritative addition of Sacred Prostitute.
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chssachetan.wordpress.com chssachetan.wordpress.com
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ENRON –THE POWER TO DO IT ALL, CHS’ Indranet Journal, Vol 3, No 2-4,1994
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Herman Rodrigues, who produced the Indranet journal for many years
indranet
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the journal Indranet
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en.wikipedia.org en.wikipedia.org
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Contents move to sidebar hide (Top) 1Text 2Printing history 3The production process: Das Werk der Bücher Toggle The production process: Das Werk der Bücher subsection 3.1Pages 3.2Ink 3.3Type 3.4Type style 3.5Rubrication, illumination and binding 4Early owners 5Influence on later Bibles 6Forgeries 7Surviving copies Toggle Surviving copies subsection 7.1Substantially complete copies 8Recent history 9See also 10General bibliography 11References 12External links Toggle the table of contents Gutenberg Bible 48 languages العربية閩南語 / Bân-lâm-gúБеларускаяБеларуская (тарашкевіца)БългарскиCatalàČeštinaCymraegDanskDeutschEestiΕλληνικάEspañolEsperantoEstremeñuEuskaraفارسیFrançaisFrysk한국어Հայերենहिन्दीHrvatskiBahasa IndonesiaInterlinguaItalianoעבריתქართულიLatviešuМакедонскиമലയാളംमराठीNederlands日本語Norsk bokmålPolskiPortuguêsРусскийSimple EnglishSlovenčinaСрпски / srpskiSuomiSvenskaதமிழ்TürkçeУкраїнськаاردو中文 Edit links ArticleTalk English ReadEditView history Tools Tools move to sidebar hide Actions ReadEditView history General What links hereRelated changesUpload fileSpecial pagesPermanent linkPage informationCite this pageGet shortened URLDownload QR codeWikidata item Expand allEdit interlanguage links Print/export Download as PDFPrintable version In other projects Wikimedia Commons From Wikipedia, the free encyclopedia Earliest major book printed in Europe The copy of the Gutenberg Bible held at the Richelieu - Bibliothèques, musée, galeries. The Gutenberg Bible, also known as the 42-line Bible, the Mazarin Bible or the B42, was the earliest major book printed in Europe using mass-produced metal movable type. It marked the start of the "Gutenberg Revolution" and the age of printed books in the West. The book is valued and revered for its high aesthetic and artistic qualities[1] and its historical significance. The Gutenberg Bible is an edition of the Latin Vulgate printed in the 1450s by Johannes Gutenberg in Mainz, in present-day Germany. Forty-nine copies (or substantial portions of copies) have survived. They are thought to be among the world's most valuable books, although no complete copy has been sold since 1978.[2][3] In March 1455, the future Pope Pius II wrote that he had seen pages from the Gutenberg Bible displayed in Frankfurt to promote the edition, and that either 158 or 180 copies had been printed. The 36-line Bible, said to be the second printed Bible, is also sometimes referred to as a Gutenberg Bible, but may be the work of another printer.[4] Text[edit] Gutenberg Bible in the Beinecke Rare Book & Manuscript Library at Yale University in New Haven, Connecticut The Gutenberg Bible, an edition of the Vulgate, contains the Latin version of the Hebrew Old Testament and the Greek New Testament. It is mainly the work of St Jerome who began his work on the translation in AD 380, with emendations from the Parisian Bible tradition, and further divergences.[5] Printing history[edit] Gutenberg Bible of the New York Public Library; purchased by James Lenox in 1847, it was the first Gutenberg Bible to be acquired by a United States citizen. While it is unlikely that any of Gutenberg's early publications would bear his name, the initial expense of press equipment and materials and of the work to be done before the Bible was ready for sale suggests that he may have started with more lucrative texts, including several religious documents, a German poem, and some editions of Aelius Donatus's Ars Minor, a popular Latin grammar school book.[6][7][8] Preparation of the Bible probably began soon after 1450, and the first finished copies were available in 1454 or 1455.[9] It is not known exactly how long the Bible took to print. The first precisely datable printing is Gutenberg's 31-line Indulgence which certainly existed by 22 October 1454.[10] Gutenberg made three significant changes during the printing process.[11] Spine of the Lenox copy Some time later, after more sheets had been printed, the number of lines per page was increased from 40 to 42, presumably to save paper. Therefore, pages 1 to 9 and pages 256 to 265, presumably the first ones printed, have 40 lines each. Page 10 has 41, and from there on the 42 lines appear. The increase in line number was achieved by decreasing the interline spacing, rather than increasing the printed area of the page. Finally, the print run was increased, necessitating resetting those pages which had already been printed. The new sheets were all reset to 42 lines per page. Consequently, there are two distinct settings in folios 1–32 and 129–158 of volume I and folios 1–16 and 162 of volume II.[11][12] The most reliable information about the Bible's date comes from a letter. In March 1455, the future Pope Pius II wrote that he had seen pages from the Gutenberg Bible, being displayed to promote the edition, in Frankfurt.[13] It is not known how many copies were printed, with the 1455 letter citing sources for both 158 and 180 copies. Scholars today think that examination of surviving copies suggests that somewhere between 160 and 185 copies were printed, with about three-quarters on paper and the others on vellum.[14][15] The production process: Das Werk der Bücher[edit] A vellum copy of the Gutenberg Bible owned by the U.S. Library of Congress, on display at the Thomas Jefferson Building in Washington, D.C. In a legal paper, written after completion of the Bible, Johannes Gutenberg refers to the process as Das Werk der Bücher ("the work of the books"). He had introduced the printing press to Europe and created the technology to make printing with movable types finally efficient enough to facilitate the mass production of entire books.[16] Many book-lovers have commented on the high standards achieved in the production of the Gutenberg Bible, some describing it as one of the most beautiful books ever printed. The quality of both the ink and other materials and the printing itself have been noted.[1] Pages[edit] First page of the first volume: the epistle of St Jerome to Paulinus from the University of Texas copy. The page has 40 lines. The paper size is 'double folio', with two pages printed on each side (four pages per sheet). After printing the paper was folded once to the size of a single page. Typically, five of these folded sheets (ten leaves, or twenty printed pages) were combined to a single physical section, called a quinternion, that could then be bound into a book. Some sections, however, had as few as four leaves or as many as twelve leaves.[17] Gutenberg Bible on display at the U.S. Library of Congress The 42-line Bible was printed on the size of paper known as 'Royal'.[18] A full sheet of Royal paper measures 42 cm × 60 cm (17 in × 24 in) and a single untrimmed folio leaf measures 42 cm × 30 cm (17 in × 12 in).[19] There have been attempts to claim that the book was printed on larger paper measuring 44.5 cm × 30.7 cm (17.5 in × 12.1 in),[20] but this assertion is contradicted by the dimensions of existing copies. For example, the leaves of the copy in the Bodleian Library, Oxford, measure 40 cm × 28.6 cm (15.7 in × 11.3 in).[21] This is typical of other folio Bibles printed on Royal paper in the fifteenth century.[22] Most fifteenth-century printing papers have a width-to-height ratio of 1:1.4 (e.g. 30:42 cm) which, mathematically, is a ratio of 1 to the square root of 2 or, simply, 2 {\textstyle {\sqrt {2}}} . Many suggest that this ratio was chosen to match the so-called Golden Ratio, 1 + 5 2 {\textstyle {\tfrac {1+{\sqrt {5}}}{2}}} , of 1:1.6; in fact the ratios are, plainly, not at all similar (equating to a difference of about 12 per cent). The ratio of 1:1.4 was a long established one for medieval paper sizes.[23] A single complete copy of the Gutenberg Bible has 1,288 pages (4×322 = 1288) (usually bound in two volumes); with four pages per folio-sheet, 322 sheets of paper are required per copy.[24] The Bible's paper consists of linen fibers and is thought to have been imported from Caselle in Piedmont, Italy based on the watermarks present throughout the volume.[25] Ink
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If a Tree Falls in the Forest, and There's No One Around to Hear It, Does It Make a Sound?
The age-old question of whether a falling tree makes a sound when there's no one around to hear it exploits the tension between perception and reality. This article explores possible answers and their consequences.
By Jack Maden | September 2022
If a tree falls in the forest, and there's no one around to hear it, does it make a sound? Well, if by 'sound' we mean vibrating air, then yes, when the tree falls, it vibrates the air around it.
However, if by 'sound' we mean the conscious noise we hear when our sensory apparatus interacts with the vibrating air, then if no one is around to hear the tree when it falls, there'd be no sensory apparatus for the vibrating air to interact with, and thus no conscious noise would be heard.
So, the answer to this age-old question seems to be simple: it depends on how we define 'sound'. If we define it as 'vibrating air', the falling tree makes a sound. If we define it as a conscious experience, the lonesome falling tree does not make a sound.
There, problem solved.
The point of asking this question, however, is not so that it can be answered quickly and put aside.
Rather, its point is to draw out the rather strange tension between our two very different definitions of the word 'sound'.
On the one hand, we classify sound as a mechanistic process that exists without us, 'out there' in the world. On the other, we regard it as a private conscious experience, its existence entirely dependent on us.
And when you dwell on this latter definition, you realize it doesn't just extend to sounds. Everything we experience --- everything we see, hear, smell, touch, taste --- all of it depends on our sensory apparatus, on us. Without us, our experiences would not exist.
As the great 16th-century astronomer Galileo Galilei put it:
Tastes, odors, colors, and so on... reside only in consciousness. If the living creature were removed, all these qualities would be wiped away and annihilated.
Take away our senses, and the world of our experience would be replaced by a colorless, soundless, odorless, tasteless nothingness. Without us, what remains?
The reason our original question --- When a tree falls in the forest, and there's no one around to hear it, does it make a sound? --- is such a teaser, is because it hits on a deeper question. Namely:
If there was no conscious life, would the physical universe exist?
Our kneejerk reaction to this question might be, 'of course it would'. But let's think about it again: if there was nothing conscious, then nothing would be experienced. There would be nothing resembling anything we call 'existence'. No colors, no sounds, no smells, no tastes, no touch, no sense of time, no sense of space.
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Is consciousness more fundamental than matter?
Reflecting on this strange state of affairs, numerous great thinkers have concluded that consciousness must be more fundamental than the 'stuff' that consciousness experiences.
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For instance, in his 1710 work, A Treatise Concerning the Principles of Human Knowledge, the philosopher George Berkeley discusses the absurdity of a world existing independently of our conscious minds:
It is indeed an opinion strangely prevailing amongst people that houses, mountains, rivers, and in a word all sensible objects, have an existence natural or real, distinct from their being perceived by the understanding... for what are the forementioned objects but things we perceive by sense? And what do we perceive besides our own ideas or sensations? And is it not plainly repugnant that any one of these or any combination of them should exist unperceived?
On this view, it is absurd to say a lonesome falling tree makes a sound. For Berkeley, it is absurd to say the tree, without a conscious mind there perceiving it, even exists. (You can learn more about his mind-bending arguments for this position in our short explainer piece on Berkeley's subjective idealism, his theory that the world is in our minds).
But to conclude this brief reflection on the tension between perception and reality, consider a comment from the Nobel Prize-winning quantum physicist Max Planck in a 1931 interview (italics added):
I regard consciousness as fundamental. I regard matter as derivative from consciousness. We cannot get behind consciousness. Everything that we talk about, everything that we regard as existing, postulates consciousness.
What do you think? Can we get behind consciousness?
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https://www.poetryfoundation.org/poems/44272/the-road-not-taken
The Road Not Taken
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BY ROBERT FROST
Two roads diverged in a yellow wood,
And sorry I could not travel both
And be one traveler, long I stood
And looked down one as far as I could
To where it bent in the undergrowth;
Then took the other, as just as fair,
And having perhaps the better claim,
Because it was grassy and wanted wear;
Though as for that the passing there
Had worn them really about the same,
And both that morning equally lay
In leaves no step had trodden black.
Oh, I kept the first for another day!
Yet knowing how way leads on to way,
I doubted if I should ever come back.
I shall be telling this with a sigh
Somewhere ages and ages hence:
Two roads diverged in a wood, and I---
I took the one less traveled by,
And that has made all the difference.
n/a
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In his renowned essay,“Battle of the Books” (1698), Jonathan Swift celebrated these texts asmore excellent than moderns realized—and he bequeathed a phraseto describe the honey of the ancients that Matthew Arnold wouldlater make infamous: “sweetness and light.”
note the "honey of the ancients" description here with a tangential nod to the commonplace tradition
see: <br /> - https://hypothes.is/a/mCsl9voQEeuP3t8jNOyAvw<br /> - https://hypothes.is/users/chrisaldrich?q=tag%3A%22jonathan+swift%22+tag%3A%22commonplace+books%22
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Author response:
The following is the authors’ response to the original reviews.
Reviewer #1 (Recommendations For The Authors):
Major concerns:
(1) It is not clear about the biological significance of the inhibitory effects of human Abeta42 on gammasecretase activity. As the authors mentioned in the Discussion, it is plausible that Abeta42 may concentrate up to microM level in endosomes. However, subsets of FAD mutations in APP and presenilin 1 and 2 increase Abeta42/Abeta40 ratio and lead to Abeta42 deposition in brain. APP knock-in mice NLF and NLGF also develop Abeta42 deposition in age-dependent manner, although they produce more human Abeta42 than human Abeta40.
If the production of Abeta42 is attenuated, which results in less Abeta42 deposition in brain. So, it is unlikely that human Abeta42 interferes gamma-secretase activity in physiological conditions. This reviewer has an impression that inhibition of gamma-secretase by human Abeta42 is an interesting artifact in high Abeta42 concentration. If the authors disagree with this reviewer's comment, this manuscript needs more discussion in this point of view.
We thank the Reviewer for raising this key conceptual point, we acknowledge that it was insufficiently discussed in the original manuscript. In response to this point, we introduced the following paragraph in the discussion section of the revised manuscript:
“From a mechanistic standpoint, the competitive nature of the Aβ42-mediated inhibition implies
that it is partial, reversible, and regulated by the relative concentrations of the Aβ42 peptide (inhibitor) and the endogenous substrates (Figure 10C and 10D). The model that we put forward is that cellular uptake, as well as endosomal production of Aβ, result in increased intracellular concentration of Aβ42, facilitating γ-secretase inhibition and leading to the buildup of APP-CTFs (and γ-secretase substrates in general). As Aβ42 levels fall, the augmented concentration of substrates shifts the equilibrium towards their processing and subsequent Aβ production. As Aβ42 levels rise again, the equilibrium is shifted back towards inhibition. This cyclic inhibitory mechanism will translate into pulses of (partial) γsecretase inhibition, which will alter γ-secretase mediated-signaling (arising from increased CTF levels at the membrane or decreased release of soluble intracellular domains from substrates). These alterations may affect the dynamics of systems oscillating in the brain, such as NOTCH signaling, implicated in memory formation, and potentially others (related to e.g. cadherins, p75 or neuregulins). It is worth noting that oscillations in γ-secretase activity induced by treatment with a γ-secretase inhibitor semagacestat have been proposed to have contributed to the cognitive alterations observed in semagacestat treated patients in the failed Phase-3 IDENTITY clinical trial (7) and that semagacestat, like Aβ42, acts as a high affinity competitor of substrates (85).
The convergence of Aβ42 and tau at the synapse has been proposed to underlie synaptic dysfunction in AD (86-89), and recent assessment of APP-CTF levels in synaptosome-enriched fractions from healthy control, SAD and FAD brains (temporal cortices) has shown that APP fragments concentrate at higher levels in the synapse in AD-affected than in control individuals (90). Our analysis adds that endogenous Aβ42 concentrates in synaptosomes derived from end-stage AD brains to reach ~10 nM, a concentration that in CM from human neurons inhibits γ-secretase in PC12 cells (Figure 7). Furthermore, the restricted localization of Aβ in endolysosomal vesicles, within synaptosomes, likely increases the local peptide concentration to the levels that inhibit γ-secretase-mediated processing of substrates in this compartment. In addition, we argue that the deposition of Aβ42 in plaques may be preceded a critical increase in the levels of Aβ present in endosomes and the cyclical inhibition of γsecretase activity that we propose. Under this view, reductions in γ-secretase activity may be a (transient) downstream consequence of increases in Aβ due to failed clearance, as represented by plaque deposition, contributing to AD pathogenesis.“
We have also added figures 10C and 10D, presented here for convenience.
Author response image 1.
(2) It is not clear whether the FRET-based assay in living cells really reflects gamma-secretase activity.
This reviewer thinks that the authors need at least biochemical data, such as levels of Abeta.
We have established a novel, HiBiT tag based assay reporting on the global γ-secretase activity in cells, using as a proxy the total levels of secreted HiBiT-tagged Aβ peptides. The assay and findings are presented in the revised manuscript as follows:
In the result section, in the “Aβ42 treatment leads to the accumulation of APP C-terminal fragments in neuronal cell lines and human neuron” subsection:
“The increments in the APP-CTF/FL ratio suggested that Aβ42 (partially) inhibits the global γ-
secretase activity. To further investigate this, we measured the direct products of the γ-secretase mediated proteolysis of APP. Since the detection of the endogenous Aβ products via standard ELISA methods was precluded by the presence of exogenous human Aβ42 (treatment), we used an N-terminally tagged version of APPC99 and quantified the amount of total secreted Aβ, which is a proxy for the global γsecretase activity. Briefly, we overexpressed human APPC99 N-terminally tagged with a short 11 amino acid long HiBiT tag in human embryonic kidney (HEK) cells, treated these cultures with human Aβ42 or p3 17-42 peptides at 1 μM or DAPT (GSI) at 10 µM, and determined total HiBiT-Aβ levels in conditioned media (CM). DAPT was considered to result in full γ-secretase inhibition, and hence the values recorded in DAPT treated conditions were used for the background subtraction. We found a ~50% reduction in luminescence signal, directly linked to HiBiT-Aβ levels, in CM of cells treated with human Aβ42 and no effect of p3 peptide treatment, relative to the DMSO control (Figure 3D). The observed reduction in the total Aβ products is consistent with the partial inhibition of γ -secretase by Aβ42.”
In Methods:
“Analysis of γ-secretase substrate proteolysis in cultured cells using secreted HiBiT-Aβ or -Aβ-like peptide levels as a proxy for the global γ-secretase endopeptidase activity
HEK293 stably expressing APP-CTF (C99) or a NOTCH1-based substrate (similar in size as
APP- C99) both N-terminally tagged with the HiBiT tag were plated at the density of 10000 cells per 96-well, and 24h after plating treated with Aβ or p3 peptides diluted in OPTIMEM (Thermo Fisher Scientific) supplemented with 5% FBS (Gibco). Conditioned media was collected and subjected to analysis using Nano-Glo® HiBiT Extracellular Detection System (Promega). Briefly, 50 µl of the medium was mixed with 50 µl of the reaction mixture containing LgBiT Protein (1:100) and Nano-Glo HiBiT Extracellular Substrate (1:50) in Nano-Glo HiBiT Extracellular Buffer, and the reaction was incubated for 10 minutes at room temperature. Luminescence signal corresponding to the amount of the extracellular HiBiT-Aβ or -Aβ-like peptides was measured using victor plate reader with default luminescence measurement settings.”
As the direct substrate of γ -secretase was used in this analysis, the observed reduction (~50%) in the levels of N-terminally-tagged (HiBiT) Aβ peptides in the presence of 1 µM Aβ42, relative to control conditions, demonstrates a selective inhibition of γ-secretase by Aβ42 (not by the p3). These data complement the FRET-based findings presented in Figure 5.
(3) Processing of APP-CTF in living cells is not only the cleavage by gamma-secretase. This reviewer thinks that the authors need at least biochemical data, such as levels of Abeta in Figures 4, 5 and 7.
We tried to measure the levels of Aβ peptides secreted by cells into the culture medium directly by ELISA (using different protocols) or MS (using established methods, as reported in Koch et al, 2023), but exogenous Aβ42 (treatment) present at relatively high levels interfered with the readout and rendered the analysis inconclusive.
However, we were successful in the determination of total secreted (HiBiT-tagged) Aβ peptides from the HiBiT tagged APP-C99 substrate, as indicated in the previous point. The quantification of the levels of these peptides showed that Aβ42 treatment resulted in ~50% reduction in the γ -secretase mediated processing of the tagged substrate.
In addition, we would like to highlight that our analysis of the contribution of other APP-CTF degradation pathways, using cycloheximide-based assays in the constant presence of γ-secretase inhibitor, failed to reveal significant differences between Aβ42 treated cells and controls (Figure 6B & C). The lack of a significant impact of Aβ42 on the half-life of APP-CTFs under the conditions of γsecretase inhibition maintained by inhibitor treatment is consistent with the proposed Aβ42-mediated inhibitory mechanism.
(4) Similar to comment #3. Processing of Pancad-CTF and p75 in living cells may be not only the cleavage by gamma-secretase. This reviewer thinks that the authors need at least biochemical data, such as levels of ICDs in Figures 6C and E.
To address this comment we have now performed additional experiments where we measured Nterminal Aβ-like peptides derived from NOTCH1-based substrate using the HiBiT-based assay. These experiments showed a reduction in the aforementioned peptides in the cells treated with Aβ42 relative to the vehicle control, and hence further confirmed the inhibitory action of Aβ42. These new data have been included as Figure 8D in the revised manuscript and described as follow:
Finally, we measured the direct N-terminal products generated by γ-secretase proteolysis from a HiBiT-tagged NOTCH1-based substrate, an estimate of the global γ-secretase activity. We quantified the Aβ-like peptides secreted by HEK 293 cells stably expressing this HiBiT-tagged substrate upon treatment with 1 µM Aβ1-42, p3 17-42 peptide or DAPT (GSI) (Figure 8D). DAPT treatment was considered to result in a complete γ-secretase inhibition, and hence the values recorded in the DAPT condition were used for background subtraction. A ~20% significant reduction in the amount of secreted
N-terminal HiBiT-tagged peptides derived from the NOTCH1-based substrates in cells treated with Aβ1-
42 supports the inhibitory action of Aβ1-42 on γ-secretase mediated proteolysis.
Minor concerns:
(1) Murine Abeta42 may be converted to murine Abeta38 easily, compared to human Abeta42. This may be a reason why murine Abeta42 exhibits no inhibitory effect on gamma-secretase activity.
In order to address this question, we performed additional experiments where we assessed the processing of murine Aβ42 into Aβ38. Analogous to human Aβ42, the murine Aβ42 peptide was not processed to Aβ38 in the assay conditions. These new data have been integrated in the manuscript and added as a Supplementary figure 1B.
(2) It is curious to know the levels of C99 and C83 in cells in supplementary figure 3.
The conditions used in these assays were analogous to the conditions used in the figure 3 (i.e. treatment with Aβ peptides at 1 µM concentrations). Such conditions were associated with profound and consistent APP-CTF accumulation in this model system.
Reviewer #2 (Recommendations For The Authors):
In the current study, the authors show that Aβs with low affinity for γ-secretase, but when present at relatively high concentrations, can compete with the longer, higher affinity APPC99 substrate for binding and processing. They also performed kinetic analyses and demonstrate that human Aβ1-42 inhibits γ-secretase-mediated processing of APP C99 and other substrates. Interestingly, neither murine Aβ1-42 nor human p3 (17-42 amino acids in Aβ) peptides exerted inhibition under similar conditions. The authors also show that human Aβ1-42-mediated inhibition of γ-secretase activity results in the accumulation of unprocessed, which leads to p75-dependent activation of caspase 3 in basal forebrain cholinergic neurons (BFCNs) and PC12 cells.
These analyses demonstrate that, as seen for γ-secretase inhibitors, Aβ1-42 potentiates this marker of apoptosis. However, these are no any in vivo data to support the physiological significance of the current finding. The author should show in APP KO mice whether gamma-secretase enzymatic activity is elevated or not, and putting back Aβ42 peptide will abolish these in vivo effects.
The findings presented in this manuscript form the basis for further in vitro and in vivo research to investigate the mechanisms of inhibition and its contribution to brain pathophysiology. Here, we used well-controlled model systems to investigate a novel mechanism of Aβ42 toxicity. Multiple mechanisms regulate the local concentration of Aβ42 in vivo, making the dissection of the biochemical mechanisms of the inhibition more complex. Nevertheless, beyond the scope of this report, we consider these very reasonable comments as a motivation for further research activities.
The experimental concentrations for Aβ42 peptide in the assay are too high, which are far beyond the physiological concentrations or pathological levels. The artificial observations are not supported by any in vivo experimental evidence.
It is correct that in the majority of the experiments we used low μM concentrations of Aβ42. However, we would like to note that we have also performed experiments where conditioned medium collected from human APP.Swe expressing neurons was used as a source of Aβ. In these experiments total Aβ concentration was in low nM range (0.5-1 nM) (Figure 7). Treatment with this conditioned medium led to the increase APP-CTF levels, supporting that low nM concentrations of Aβ are sufficient for partial inhibition of γ-secretase.
In addition, we highlight that analyses of the brains of the AD affected individuals have shown that APPCTFs accumulate in both sporadic and genetic forms of the disease (Pera et al. 2013, Vaillant-Beuchot et al. 2021); and recently, Ferrer-Raventós et al. 2023 have revealed a correlation between APP-CTFs and Aβ levels at the synapse (Ferrer-Raventós et al. 2023). We therefore assessed the concentration of Aβ42 in synaptosomes derived from frontal cortices of post-mortem AD and age-matched non-demented (ND) control individuals. Our findings and conclusions are included in the revised version as follows:
In the results section:
“We next investigated the levels of Aβ42 in synaptosomes derived from frontal cortices of post-mortem AD and age-matched non-demented (ND) control individuals (Figure 10B). Towards this, we prepared synaptosomes from frozen brain tissues using Percoll gradient procedure (62, 63). Intact synaptosomes were spun to obtain a pellet which was resuspended in minimum amount of PBS, allowing us to estimate the volume containing the resuspended synaptosome sample. This is likely an overestimate of the actual synaptosome volume. Finally, synaptosomes were lysed in RIPA buffer and Aβ peptide concentrations measured using ELISA (MSD). We observed that the concentration of Aβ42 in the synaptosomes from (end-stage) AD tissues was significantly higher (10.7 nM) than those isolated from non-demented tissues (0.7 nM), p<0.0005***. These data provide evidence for accumulation at nM concentrations of endogenous Aβ42 in synaptosomes in end-stage AD brains. Given that we measured Aβ42 concentration in synaptosomes, we speculate that even higher concentrations of this peptide may be present in the endolysosome vesicle system, and therein inhibit the endogenous processing of APP-CTF at the synapse. Of note treatment of PC12 cells with conditioned medium containing even lower amounts of Aβ (low nanomolar range (0.5-1 nM)) resulted in the accumulation of APP-CTFs.”
In the discussion:
“The convergence of Aβ42 and tau at the synapse has been proposed to underlie synaptic dysfunction in AD (86-89), and recent assessment of APP-CTF levels in synaptosome-enriched fractions from healthy control, SAD and FAD brains (temporal cortices) has shown that APP fragments concentrate at higher levels in the synapse in AD-affected than in control individuals (90). Our analysis adds that endogenous Aβ42 concentrates in synaptosomes derived from end-stage AD brains to reach ~10 nM, a concentration that in CM from human neurons inhibits γ-secretase in PC12 cells (Figure 7). Furthermore, the restricted localization of Aβ in endolysosomal vesicles, within synaptosomes, likely increases the local peptide concentration to the levels that inhibit γ-secretase-mediated processing of substrates in this compartment. In addition, we argue that the deposition of Aβ42 in plaques may be preceded by a critical increase in the levels of Aβ present in endosomes and the cyclical inhibition of γ-secretase activity that we propose. Under this view, reductions in γ-secretase activity may be a (transient) downstream consequence of increases in Aβ due to failed clearance, as represented by plaque deposition, contributing to AD pathogenesis. ”
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“Tag! You’re it!”
Tubbo knows exactly what to do to bring out Ranboo's genuine self
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Author response:
The following is the authors’ response to the original reviews.
eLife assessment
The authors present evidence suggesting that MDA5 can substitute as a sensor for triphosphate RNA in a species that naturally lacks RIG-I. The key findings are potentially important for our understanding of the evolution of innate immune responses, but the evidence is incomplete, as additional biochemical and functional experiments are needed to unambiguously assign MDA5 as a bona fide sensor of triphosphate RNA in this model. This also leaves the title as overstating its case.
We would like to thank the editorial team for these positive comments on our manuscript and the constructive suggestions to improve our manuscript. According to the suggestions and valuable comments of the referees, we have added substantial amounts of new data and analysis to substantiate our claims, and the manuscript, including the title, has been carefully revised to better reflect our conclusions. We are now happy to send you our revised manuscript, we hope the modified manuscript addresses your and the reviewers’ concerns satisfactorily and is suitable for publication in eLife now.
Reviewer #1 (Public Review):
This study offers valuable insights into host-virus interactions, emphasizing the adaptability of the immune system. Readers should recognize the significance of MDA5 in potentially replacing RIG-I and the adversarial strategy employed by 5'ppp-RNA SCRV in degrading MDA5 mediated by m6A modification in different species, further indicating that m6A is a conservational process in the antiviral immune response.
However, caution is warranted in extrapolating these findings universally, given the dynamic nature of host-virus dynamics. The study provides a snapshot into the complexity of these interactions, but further research is needed to validate and extend these insights, considering potential variations across viral species and environmental contexts.
We concur with the viewpoint that virus-host coevolution complicates the derivation of universal conclusions. To address this challenge, incorporated additional experiments and data based on the suggestions of the reviewers. These experiments were carried out across diverse models, including two distinct vertebrate species (M. miiuy and G. gallus), two different viruses (SCRV and VSV), and the synthesis of corresponding 5’ppp-RNA probes. We believe that these supplementary data bolster the evidence supporting the immune replacement role of MDA5 in the recognition of 5'ppp-RNA in RIG-I deficient species (Figure 1C-1E, Figure 2O and 2P, Figure 4). Moreover, we have duly incorporated references in both the introduction and discussion sections to further support our conclusion that MDA5 in T. belangeri, a mammal lacking RIG-I, possesses the ability to detect RNA viruses posed as RIG-I agonists (doi: 10.1073/pnas.1604939113). Lastly, meticulous revisions have been undertaken in the manuscript, including adjustments to the title, to ensure harmonization with our research outcomes.
Reviewer#2 (Public Review):
This manuscript by Geng et al. aims to demonstrate that MDA5 compensates for the loss of RIG-I in certain species, such as teleost fish miiuy croaker. The authors use siniperca cheats rhabdovirus (SCRV) and poly(I:C) to demonstrate that these RNA ligands induce an IFN response in an MDA5-dependent manner in M. miiuy derived cells. Furthermore, they show that MDA5 requires its RD domain to directly bind to SCRV RNA and to induce an IFN response. They use in vitro synthesized RNA with a 5'triphosphate (or lacking a 5'triphosphate as a control) to demonstrate that MDA5 can directly bind to 5'-triphosphorylated RNA. The second part of the paper is devoted to m6A modification of MDA5 transcripts by SCRV as an immune evasion strategy. The authors demonstrate that the modification of MDA5 with m6A is increased upon infection and that this causes increased decay of MDA5 and consequently a decreased IFN response.
The key message of this paper, i.e. MDA5 can sense 5'-triphosphorylated RNA and thereby compensate for the loss of RIG-I, is novel and interesting, yet there is insufficient evidence provided to prove this hypothesis. Most importantly, it is crucial to test the capacity of in vitro synthesized 5'-triphosphorylated RNA to induce an IFN response in MDA5-sufficient and -deficient cells. In addition, a number of important controls are missing, as detailed below.
To further support the notion that MDA5 is capable of detecting 5'ppp-RNA in species lacking RIG-I, we conducted additional experiments. Initially, we isolated the RNA from SCRV and VSV viruses. Subsequently, we synthesized 5'ppp-RNA probes that corresponded to the genome termini of SCRV and VSV in vitro. Then, these RNAs were treated with Calf intestinal phosphatase (CIAP) to generate dephosphorylated derivatives. Next, we separately tested the activation ability of various RNAs on IRF3 dimer and IFN response in MKC (M. miiuy kidney cell line) and DF-1 (G. gallus fibroblast cell line) cells, and determined that the immune activation ability of SCRV/VSV viruses depends on their triphosphate structure (Figure 1C-1E, Figure 4C and 4J). In addition, the knockdown of MDA5 inhibited the immune response mediated by SCRV RNA (Figure 2P and 2Q). Finally, we incorporated essential experimental controls (Figure 4B and 4I). We think that the inclusion of these supplementary experimental data significantly enhances the credibility and further substantiates our hypothesis.
The authors describe an interaction between MDA5 and STING which, if true, is very interesting. However, the functional implications of this interaction are not further investigated in the manuscript. Is STING required to relay signaling downstream of MDA5?
To better explore the role of STING in MDA5 signal transduction, we constructed a STING expression plasmid and synthesized specific siRNA targeting STING. Next, we found that co-expression of STING and MDA5 significantly enhance MDA5-mediated IFN-1 response during SCRV virus infection (Figure 2N). Conversely, silencing of STING expression restored the MDA5-mediated IFN-1 response (Figure 2O). These findings provide important evidence for the critical involvement of STING in the immune signaling cascade mediated by MDA5 in response to 5'ppp-RNA viruses.
The second part of the paper is quite distinct from the first part. The fact that MDA5 is an interferon-stimulated gene is not mentioned and complicates the analyses (i.e. is there truly more m6A modification of MDA5 on a per molecule basis, or is there simply more total MDA5 and therefore more total m6A modification of MDA5).
For the experimental data analysis in Figure 5E and 5F, we first compared the m6A-IP group to the input group, and then normalized the control group (IgG group of 5E and Mock group of 5F) to a value of “1”. Given the observed variability in MDA5 expression levels within the input group of Mock and SCRV virus-infected cells, our analysis represents the actual m6A content of each MDA5 molecule. To enhance clarity, we have updated the label on the Y-axis in Figure 5E and 5F.
Finally, it should be pointed out that several figures require additional labels, markings, or information in the figure itself or in the accompanying legend to increase the overall clarity of the manuscript. There are frequently details missing from figures that make them difficult to interpret and not self-explanatory. These details are sometimes not even found in the legend, only in the materials and methods section. The manuscript also requires extensive language editing by the editorial team or the authors.
We acknowledge the valuable feedback from the reviewer and have made significant improvements to our manuscript based on the recommendations provided in the "Recommendation for the authors" section. Furthermore, we have conducted a thorough review of the entire article, resulting in substantial enhancements to the format, clarity, and overall readability of our manuscript.
Reviewer#3 (Public Review):
Summary: In this manuscript, the authors investigated the interaction between the pattern recognition receptor MDA5 and 5'ppp-RNA in a teleost fish called Miiuy croaker. They claimed that MDA5 can replace RIG-I in sensing 5'ppp-RNA of Siniperca cheats rhabdovirus (SCRV) in the absence of RIG-I in Miiuy croaker. The recognition of MDA5 to 5'ppp-RNA was also observed in the chicken (Gallus gallus), a bird species that lacks RIG-I. Additionally, they reported that the function of MDA5 can be impaired through m6A-mediated methylation and degradation of MDA5 mRNA by the METTL3/14-YTHDF2/3 regulatory network in Miiuy croaker under SCRV infection. This impairment weakens the innate antiviral immunity of fish and promotes the immune evasion of SCRV.
Strengths:<br /> These findings provide insights into the adaptation and functional diversity of innate antiviral activity in vertebrates.
Weaknesses:<br /> However, there are some major and minor concerns that need to be further addressed. Addressing these concerns will help the authors improve the quality of their manuscript.One significant issue with the manuscript is that the authors claim to be investigating the role of MDA5 as a substitute for RIG-I in recognizing 5'ppp-RNA, but their study extends beyond this specific scenario. Based on my understanding, it appears that sections 2.2, 2.3, 2.5, 2.6, and 2.7 do not strictly adhere to this particular scenario. Instead, these sections tend to investigate the functional involvement of Miiuy croaker MDA5 in the innate immune response to viral infection. Furthermore, the majority of the data is focused on Miiuy croaker MDA5, with only a limited and insufficient study on chicken MDA5. Consequently, the authors cannot make broad claims that their research represents events in all RIG-I deficient species, considering the limited scope of the species studied.
We agree with the reviewer's perspective that functional analysis of MDA5 in M. miiuy may not adequately represent all species lacking RIG-I. To address this concern, we have incorporated additional experimental data utilizing different model systems, including two different vertebrate species (M. miiuy and G. gallus), two distinct viruses (SCRV and VSV), and the synthesis of two corresponding 5’ppp-RNA probes. While the functional characterization of G. gallus MDA5 remains relatively limited compared to M. miiuy, our current experimental findings provide support for two key observations. Firstly, the triphosphate structure of the VSV virus is pivotal in activating the innate immune response in G. gallus against the virus (Figure 1D and 4J). Secondly, G. gallus MDA5 can recognize 5’ppp-RNA (Figure 4I, 4K and 4L). Consequently, although we cannot definitively establish the immune surrogate function of MDA5 in all RIG-I-deficient species, our research data further substantiates this hypothesis. Moreover, we have adopted a more cautious attitude in summarizing our experimental conclusions, thereby enhancing the rigor of our manuscript language.
The current title of the article does not align well with its actual content. It is recommended that the focus of the research be redirected to the recognition function and molecular mechanism of MDA5 in the absence of RIG-I concerning 5'ppp-RNA. This can be achieved through bolstering experimental analysis in the fields of biochemistry and molecular biology, as well as enhancing theoretical research on the molecular evolution of MDA5. It is advisable to decrease or eliminate content related to m6A modification.
Following the reviewer's recommendations, we have revised the title to emphasize that our main research focus is a teleost fish devoid of RIG-I. Furthermore, we have conducted additional molecular experiments to further elucidate the 5'ppp-RNA recognition function of MDA5 in RIG-I-deficient species. In an attempt to analyze the potential molecular evolution of MDA5 resulting from RIG-I deficiency, we collected MDA5 coding sequences from diverse vertebrates. However, due to multiple independent loss events of RIG-I in fish, fish with or without RIG-I genes in the phylogenetic tree cannot be effectively clustered separately, making it extremely difficult to perform this aspect of analysis. Consequently, we have regrettably opted to forgo the molecular evolution analysis of MDA5.
Our article topic is to reveal an antagonistic phenomenon between fish receptor and RNA viruses. The MDA5 of RIG-I-lost fish has evolved the ability to recognize 5’ppp-RNA virus and mediate IFN response to resist SCRV infection. Conversely, the m6A methylation mechanism endows the SCRV virus with a means to weaken the immune capacity of MDA5. Therefore, we believe that the latter part is an important part of the arms race between the virus and its host, and should be retained.
Additionally, the main body of the writing contains several aspects that lack rigor and tend to exaggerate, necessitating significant improvement.
We appreciate the reviewer’s comment and have improved the manuscript addressing the points raised in the “Recommendation for the authors”. We have added corresponding experiments to strengthen the verification of the conclusions, and in addition, we are more cautious in summarizing the language of the conclusions.
Recommendations for the authors:
Reviewer #1 (Recommendations For The Authors):
(1) The evidential foundation within the Result 1 section appears somewhat tenuous.
Firstly, the author derives conclusions regarding the phenomenon of RIG-I loss in lower vertebrates by referencing external literature and conducting bioinformatics analyses. It is pertinent to inquire whether the author considered fortifying these findings through additional WB/PCR experiments, particularly for evaluating RIG-I expression levels across diverse vertebrates, encompassing both lower and higher orders.
Firstly, the species we analyzed are mostly model species with excellent genomic sequence information in the database. Secondly, the RIG-I protein sequences (at least some domain sequences) are relatively conserved in vertebrates. Therefore, the credibility of evaluating the existence of RIG-I in these species through homology comparison is high. Therefore, we do not intend to conduct additional PCR/WB experiments to confirm this.
Additionally, following the identification of RIG-I loss, the author postulates MDA5 as a substitute of RIG-I, grounding this speculation in the analysis of MDA5 and LGP2 protein structures. It is imperative to address whether the author could enhance the manuscript by supplying expression data for MDA5 and LGP2 across different vertebrates and elucidating further why MDA5 is posited as the compensatory mechanism for RIGI loss.
Like MDA5, LGP2 is also an interferon-stimulating gene, so they both likely exhibit high sensitivity to viral infections. Therefore, we think that comparing the expression data of these two genes is difficult to evaluate their function. In mammals, the regulatory mechanisms of LGP2 to RIG-I and MDA5 were complicated and ambiguous. To evaluate the potential function of LGP2 in M. miiuy, we further constructed LGP2 plasmid and synthesized siRNA targeting LGP2. Then, our results indicate that mmiLGP2 can enhance the antiviral immune response mediated by mmiMDA5 (Figure 1H and 1I), further indicating the regulatory role of mmiLGP2 in RLR signaling, rather than acting as a compensatory receptor for RIG-I.
Also, is it conceivable that other receptors contribute to this compensatory effect in lower vertebrates?
5’ triphosphate short blunt-end double-strand RNA is the ligand of RIG-I as contained in the panhandle of negative-strand viral genomes. We mainly focus on the immune recognition and compensatory effects of other receptors on RIG-I loss, and MDA5, as the protein with the most similar structure, first attracted our attention. In addition, IFIT proteins have been reported to recognize triphosphate single-stranded RNA (doi: 10.1038/nature11783). However, we used SCRV and VSV RNA as viral models, both of which have negative stranded genomes and meet the ligand standards of RIG-I, rather than IFIT. Therefore, we excluded the IFIT protein from our research scope.
(2) The article exclusively employs a singular type of 5'PPP-RNA virus and one specific lower vertebrate species, thereby potentially compromising the robustness of the assertion that this phenomenon is prevalent in lower vertebrates. To bolster this claim, could the author consider incorporating data from an alternative 5'PPP-RNA virus and a different lower vertebrate species?
To address this concern, we have incorporated additional experimental data utilizing different model systems, including two different vertebrate species (M. miiuy and G. gallus) and two distinct viruses (SCRV and VSV). While the functional characterization of G. gallus MDA5 remains relatively limited compared to M. miiuy, our current experimental findings provide support for two key observations. Firstly, the triphosphate structure of the VSV virus is pivotal in activating the innate immune response in G. gallus against the virus (Figure 1D and 4J). Secondly, G. gallus MDA5 can recognize 5’ppp-RNA (Figure 4I, 4K and 4L). Consequently, these experimental results further confirmed the conservatism of this immune compensation mechanism.
(3) A nuanced consideration of the statement in Result 5 is warranted. Examination of the results under SCRV infection conditions suggests dynamic fluctuations in MDA5 expression levels, challenging the veracity of the statement implying "increased expression", which contradicts the proposed working model of this article.
Because MDA5 acts as a receptor and plays a recognition immune role in the early stages of virus infection, the expression of MDA5 in the early stage of SCRV infection rapidly increases. In the later stage of infection, the expression of MDA5 may gradually decrease again due to the negative feedback mechanism in the host body to prevent excessive inflammation. However, compared to the uninfected group, the expression of MDA5 was significantly increased in the SCRV-infected group, so we believe that the term "increased expression" is not a problem. In addition, the m6A mechanism can weaken the function of MDA5, but it still cannot prevent the overall increase of MDA5 expression, which is not contradictory to the working model in this article.
Additionally, the alterations in m6A levels in miiuy croaker under SCRV infection conditions warrant clarification. Could the author employ m6A dot blotting to supplement the findings related to total m6A levels?
Our previous studies (doi: 10.4049/jimmunol.2200618) have suggested that the total m6A level is increased after SCRV infection in miiuy croaker. We cited this conclusion in the discussion of our manuscript.
(4) It would be beneficial if the editors could assist the author in enhancing the language of the manuscript.
We have carefully checked the full article and modified it with Grammarly tools, and we believe that the grammar, format, and readability of our articles have been greatly improved.
Reviewer #2 (Recommendations For The Authors):
Figure 1
(1) Figure 1B - some clarification needs to be added about this figure in the text. It is unclear what the main point is that the authors would like to convey.
What we want to emphasize is that some species with RIG-I, such as zebrafish, have also experienced RIG-I loss events, but have undergone whole genome replication events before the loss, thus preserving a copy of RIG-I. This indicates that loss events of RIG-I are very common in vertebrates and do not occur randomly. We have elaborated on this point in the results and discussion.
(2) Figure 1C - is not very informative other than showing Mm MDA5 and LGP2 side-by-side. It would be more useful to show a comparison of human RIG-I/MDA5 alongside Mm and Gg MDA5. Are there any conserved/shared key residues between hRIG-I/hMDA5 versus mmMDA5?
Homologous proteins are often known to adopt the same or similar structure and function. We have added human RIG-I domain information to this figure (Figure 1F). By comparing the domain information of human RIG-I with M. miiuy MDA5 and LGP2, M. miiuy MDA5 has a similar structure to human RIG-I, making it most likely to compensate for the missing RIG-I. While M. miiuy LGP2 lacks the CARD domain, which is crucial for signal transduction, so we will shift our focus to M. miiuy MDA5. In addition, we collected protein sequences of MDA5 and RIG-I from various vertebrates to identify key residues evolved in recognizing 5'ppp-RNA by M. miiuy MDA5. However, unfortunately, no potential residues were found during the comparison process.
Figure 2
(1) Figure 2B - It would be important to demonstrate MDA5-Flag expression by immunoblot and compare MDA5-Flag overexpression to endogenous MDA5 expression using the anti-MDA5 antibody from panel 2A. If IF is used, more cells need to be visible in the field.
After transfecting the MDA5 plasmid into MKC, endogenous MDA5 expression was detected using MDA5 antibodies. The results showed a significant increase in MDA5 protein levels, indicating that MDA5 antibodies can specifically recognize MDA5 protein. In addition, we retained the original immunofluorescence images to better demonstrate the subcellular localization of MDA5.
(2) Figure 2C - The 1:1 stoichiometry of MDA5:MAVS (in the absence of any stimulus) is quite surprising. How does the interaction between MDA5 and MAVS change upon stimulation with an RNA ligand (SCRV, poly(I:C))?
We do not believe that the actual stoichiometry between MDA5 and MAVS is what you described as 1:1. In fact, the proportion of proteins in the complex depends on many factors in the experimental results with Co-IP. Firstly, the MDA5 plasmid in this study has a 3 × Flag tag, while the MAVS only has a 1x Myc tag, which makes the antibody more sensitive for detecting MDA5-Flag. In addition, the Co-IP results are also affected by multiple factors such as the type of antibody and the number of recoveries, making it difficult to estimate the actual ratio of MDA5 to MAVS. Based on the above reasons and the fact that the detection of the interaction strength between MDA5 and MAVS after infection seems to be off-topic, we did not continue to explore this point.
(3) Figure 2D - The interaction between MDA5 and STING is a very interesting finding but is not elaborated on in the paper (even though the interaction between MDA5 and STING is mentioned in the abstract). The manuscript would be strengthened if the interaction between MDA5 and STING is further investigated. For example, does the IFN response that is reported in panels 2E to 2H require the presence of STING? Does mmMDA5 signal via STING in response to a DNA ligand?
We appreciate the referee's suggestion to study the mutual influence between MDA5 and STING. We found that co-expression of STING and MDA5 can enhance MDA5-mediated IFN-1 response during SCRV virus infection, while knocking down STING can restore MDA5-mediated IFN-1 (Figure 2N and 2O). This indicates that STING plays an important signaling role in the immune response of MDA5 to RNA viruses. We understand the importance of cGAS/STING pathways in identifying exogenous DNA, so exploring the MDA5 pathway for DNA ligand recognition is an interesting and meaningful perspective. But this seems to be detached from the theme of our article, so we didn't continue to explore this point.
(4) Figures 2F and 2H - the authors demonstrate that SCRV induces a type I IFN response in an MDA5-dependent manner. While SCRV is a single-stranded negative-sense RNA virus that contains 5'ppp-RNA, it cannot be excluded that MDA5 is activated here in response to a double-stranded RNA intermediate of viral origin or even a host-derived RNA whose expression or modification is altered during infection. To demonstrate in an unambiguous manner that MDA5 senses 5'ppp-RNA, it is crucial to use the in vitro synthesized 5'ppp-RNA (and its dephosphorylated derivative as a control) from Fig. 4 in these experiments.
We transfected 5 'ppp SCRV and 5' ppp VSV (and their dephosphorylated derivatives) synthesized in vitro into MKC cells and DF-1 cells, respectively. The results showed that 5’ppp-RNAs significantly promoted the formation of IRF3 dimers, while their dephosphorylated derivatives did not (Figure 4C and 4J). In addition, we extracted virus RNA from the SCRV and VSV viruses and dephosphorylated them with Calf intestinal phosphatase (CIAP). These RNAs were transfected into MKC and DF-1 cells and found that the immune response mediated by virus RNAs was much higher than the dephosphorylated form (Figure 1C-1E). The above results indicate that the immune response activated by SCRV and VSV is indeed dependent on their triphosphate structure. Finally, the IRF3 dimer and IFN induction activated by SCRV RNA can be inhibited by si-MDA5 (Figure 2P and 2Q), further demonstrating the involvement of MDA5 in the immune response mediated by 5’ppp-RNA ligands.
(5) In mice and humans, MDA5 is known to collaborate with LGP2 to jointly induce an IFN response. Does M.miiuy express LGP2? If so, it would be informative to include a siRNA targeting LGP2 in the experiments in panel F. In mammals, LGP2 potentiates the response via MDA5 while it may inhibit RIG-I activation.
M.miiuy express LGP2. We constructed an LGP2 plasmid and synthesized si-LGP2 to investigate the impact of LGP2 on MDA5-mediated immune processes (Figure 1G-1I). The results showed that LGP2 can enhance the IFN response mediated by MDA5 during SCRV virus infection, similar to that in mammals.
(6) Minor comment - Is the poly(I:C) used in this figure high or low molecular weight poly(I:C)? HMW poly(I:C) preferentially stimulates MDA5, while LMW poly(I:C) preferentially stimulates RIG-I.
We used poly(I:C)-HMW as a positive control for activating MDA5. We have modified the relevant information in Figure 2 and its legend.
Figure 3
(1) Figure 3F/G - The normalization in this Figure is difficult to interpret. It would be better to split Figure 3G into 4 separate graphs and include the mock-infected cells alongside the infected samples (as done in Figure 2).
To better demonstrate the function of the RD domain of MDA5 in M. miiuy, we have changed the experimental plan, as shown in figure 3F. We detected the induction of antiviral factors by overexpression of MDA5 and MDA5-△RD under poly (I:C)-HMW stimulation. This can indicate that the RD domain of MDA5 has a conserved function in the recognition of poly(I:C)-HMW in M. miiuy, and can serve as a positive control for the recognition of SCRV virus by the RD domain.
Figure 4
(1) Figure 4B - A number of important controls are missing. Was the immunoprecipitation of RNA successful? This could be shown by running a fraction of the immunoprecipitated material on an RNA gel and/or by showing that the input RNA was depleted after IP. In addition, a control IP (Streptavidin beads without biotinylated RNA) is missing to ensure that MDA5 does not stick non-specifically to the Streptavidin resin.
We appreciate the referee's suggestions. We rerun this experiment and added a non-biomarker RNA IP control group, and the results showed that MDA5 did not adsorb non-specific onto the beads (Figure 4B). In addition, based on the referee's suggestion, we tested the consumption of RNA before and after immunoprecipitation, and the results showed that biotin-labeled RNA, rather than non-biotin-labeled RNA, could be adsorbed by beads, indicating the success of RNA precipitation. However, we think that this is not necessary for the final presentation of the experimental results, so we did not show this in the figure.
(2) Figure 4B - It is unclear why there is such a large molecular weight difference between endogenous MDA5 and MDA5-Flag (110 kDa versus 130/140 kDa). Why is there less MDA5-Flag retrieved than endogenous MDA5?
After careful analysis, we believe that the significant difference in molecular weight between endogenous MDA5 and MDA5 Flag may be due to three reasons. Firstly, MDA5 flag has a 3× Flag tag. Secondly, as shown in the primer table, we constructed MDA5 between the NotI and XbaI cleavage sites in the pcDNA3.1 vector, which are located at the posterior position in the vector. This means that the Flag tag has a certain distance from the starting codon of MDA5, and these sequences on the vector can also be translated and increase the molecular weight of the exogenous MDA5 protein. Finally, in order to facilitate the amplification of the primers, the F-terminal primers of MDA5 contain a small portion of the 3'UTR sequence (excluding the stop codon). These above reasons may have led to significant differences in molecular weight. In addition, in order to supplement important experimental controls, we have conducted a new RNA pull-down experiment as shown in Figure 4B.
(3) Minor point: Figure 4B - please clarify in the figure whether RNA or protein is immunoprecipitated and via which tags.
We have conducted a new RNA pull-down experiment as shown in Fig 4B, and we have clearly labeled the relevant information in the figure.
(4) Figure 4E - the fraction of MDA5 that binds 5'ppp-RNA seems incredibly minor. And why is this experiment done using 5'OH-RNA as a competitor, rather than simply incubating MDA5 and 5'OH-RNA together and demonstrating that these do not form a complex?
The proportion of MDA5 combined with 5’ppp-RNA is influenced by many conditions, including the concentration and purity of the probe and purified protein. In addition, the dosage ratio between the RNA probe and MDA5 protein in the EMSA experiment can also have a significant impact on the results. Therefore, it is not possible to accurately determine the actual binding force between MDA5 and RNA. In the EMSA experimental program, both cold probes (5’ppp-RNA) and mutated cold probes (5’OH-RNA and 5’pppGG-RNA) are crucial for demonstrating the specific binding between MDA5 and 5’ppp-RNA, as they can exclude false positive errors caused by factors such as the presence of biotin in the purified MDA5 protein itself.
(5) Figure 4B/4C/4F - These experiments would be strengthened by including an MDA5 mutant that cannot bind to RNA. These mutants are well-described in mammals. If these residues are conserved, it is straightforward to generate this mutant.
As shown in Figure 3, the MDA5 of M. miiuy has an RD domain that can recognize the SCRV virus. We constructed MDA5-△RD mutant plasmids with 6x His-tags and purified them for EMSA experiments (Figure 4E). The experimental results further indicate that MDA5, rather than MDA5-△RD, can bind to 5’ppp-SCRV (Figure 4G). This further confirms the crucial role of the RD domain in recognizing the 5'ppp-RNA virus.
(6) Minor point: Figure 4E: please clarify in which lanes MDA5 has been added.
Thank you for the referee's suggestion. We have synthesized new 5'ppp-RNA probes (5’ppp-SCRV and their dephosphate derivatives) and rerun this experiment, and relevant information has been added in the Figure (Figure 4F).
Figure 5
(1) Figure 5C - As MDA5 is an interferon-stimulated gene (as shown in panel G/H/I)) the increased MDA5 expression could simply explain the increase in the amount of m6A-MDA5 that is immunoprecipitated after infection. Could this figure be improved by doing a fold change between input vs m6A-IP OR uninfected vs SCRV-infected conditions? This would reveal whether the modification of MDA5 with m6A is really increased after infection.
As shown in Figure 5F below, our data indicates that the proportion of m6A-modified MDA5 does indeed increase after SCRV infection, rather than solely due to the increased expression of MDA5 itself.
(2) Figure. 5E/F - The y-axis is unclear: relative MDA5 m6A levels. Relative to what? Input? Mock infected?
For experiments in Figure 5E/F, we first compared the m6A-IP group with the input group, and then normalized the control group (IgG group of 5E and Mock group of 5F) to “1”. We have replaced the Y-axis name with a clearer one (Figure 5E and 5F).
(3) General comment - It is not mentioned in the text that MDA5 is an interferon-stimulated gene. This would account for the increase in expression (qPCR) after viral infection or poly(I:C) transfection, hence there is no novelty in this finding. In addition, the authors suggest that MDA5 increases at the protein level (by immunoblot) but the increase on these blots is not convincing (figure 5H/5I).
We understand that the increase in expression of MDA5 as an interferon-stimulated gene after viral infection is a common phenomenon. We present this to further validate the m6A sequencing transcriptome data, and to demonstrate that although m6A modification interferes with MDA5 expression during viral infection, it cannot prevent the increase of mRNA level of MDA5. In addition, we rerun the experiment and the results showed that the expression of MDA5 protein can indeed be specifically activated by the SCRV virus and poly(I:C)-HMW.
Figure 6
(1) Figure 6E - What was the MOI of the virus used in this experiment? It is not mentioned in the figure legend.
MOI=5, we have added this point in the figure legend.
Figure 7
(1) Figure 7J - This graphic is somewhat misleading and should be altered to better reflect the conclusions that are drawn in the manuscript. The graphic suggests that MAVS and STING interact, but this is not demonstrated in the paper. In addition, the paper does not demonstrate whether MAVS or STING (or both) are needed downstream of MDA5 to relay signalling. Finally, please draw an arrow from type I IFNs to increased expression of MDA5 to illustrate that MDA5 is an ISG.
Thank you for the referee's suggestion. We have revised the images to more accurately match the conclusions of the manuscript (Figure 7J). Firstly, we have separated the STING protein from the MAVS protein. Secondly, arrows have been used to indicate that MDA5 is an IFN-stimulated gene. Finally, as we have added relevant experiments to demonstrate the importance of MITA protein in the signaling process of MDA5-activated IFN response. In addition, the function of MAVS binding to MDA5 protein and promoting its signal transduction is very conserved, and there is a good research background even in fish with RIG-I deficiency (10.1016/j.dci.2021.104235). Therefore, in Figure 7J, we still chose to bind MAVS to MDA5 protein and use it as a downstream signal transducer of MDA5.
Discussion<br /> (1) There is very little discussion about METTL and YTHDF proteins in the discussion despite the fact that the last 2 figures are entirely devoted to these proteins.
Based on the referee's suggestion, we have added relevant content about METTL and YTHDF proteins in the discussion. In addition, the basic mechanism and function of METTL and YTHDF proteins were briefly described in the introduction.
Reviewer #3 (Recommendations For The Authors):
Please refer to the specific suggestions and recommendations. They include proposals for experimental additions, improved methodologies, and suggestions to resolve writing-related concerns.
Major concerns
(1) I suggest changing the article title to "Functional Replacement of RIG-I with MDA5 in Fish Miiuy Croaker", or a similar title, to make it more focused and closely aligned with the content of the article.
Following the reviewer's recommendations, we have revised the title to emphasize our primary research subject is a teleost fish that lacks RIG-I. In addition, we have changed “5’ppp-RNA” to “5’ppp-RNA virus” to emphasize the interaction between the virus and the receptor. We believe that the revised title is more in line with the content of the article.
(2) Due to the inherent limitations in genome sequencing, assembly, and annotation for the Miiuy croaker, comprehensive annotation of immune-related genes remains incomplete. To address this critical gap, it is recommended that authors establish experimental protocols, such as Fluorescence In Situ Hybridization (FISH), to confirm the absence of RIG-I in the Miiuy croaker. They should simultaneously employ MDA5 probes as a positive control for validation purposes.
The miiuy croaker has good genomic information at the chromosomal level (doi: 10.1016/j.aaf.2021.06.001). In addition, studies have shown that RIG-I is absent in the orders of Perciformes (doi: 10.1016/j.fsirep.2021.100012), while miiuy croaker belongs to the order Perciformes, so it does indeed lose the RIG-I gene. Therefore, we do not intend to use FISH technology to prove this.
(3) Similarly, it is recommended that the authors first provide evidence of the presence of 5'ppp at the 5' terminus of the genome RNA of SCRV, as demonstrated in the study by Goubau et al. (doi: 10.1038/nature13590, Supplementary figure 1). This evidence is crucial before drawing conclusions about the compensatory role of MDA5 in recognizing 5'ppp RNA viruses, using SCRV as the viral model.
As suggested by the referee, we extracted SCRV RNA from SCRV virus particles and assessed the 5’-phosphate-dependence of stimulation by SCRV RNA. Calf intestinal phosphatase (CIAP) treatment substantially reduced the stimulatory activity of SCRV RNA in MKC cells of M. miiuy (Figure 1C and 1E). In addition, similar results were obtained by transfecting VSV-RNA isolated from VSV virus into DF-1 cells of G. gallus (Figure 1D). The above evidences confirm the presence of triphosphate molecular features between SCRV and VSV viruses, and indicating that birds and fish lacking RIG-I have other receptors that can recognize 5’ppp-RNA.
(4) The 62-nucleotide (nt) 5'ppp-RNA utilized in this study was obtained from Vesicular Stomatitis Virus (VSV). In order to provide direct evidence, it is necessary to include a 62-nt 5'ppp-RNA that is directly derived from SCRV itself.
We adopted this suggestion and synthesized a 67-nucleotide 5’ppp-SCRV RNA probe. We found that 5’ppp-SCRV activates dimerization of IRF3 and binds to MDA5 of M. miiuy in a 5’-triphosphate-dependent manner (Figure 4A-4F).
(5) Given that RNAs with uncapped diphosphate (PP) groups at the 5′ end also activate RIG-I, similar to RNAs with 5′-PPP moieties, and the 5′-terminal nucleotide must remain unmethylated at its 2′-O position to allow RNA recognition by RIG-I, it is necessary for the authors to conduct additional experiments to supplement and validate these two distinguishing features of RIG-I in RNA recognition. This will provide more reliable evidence for the replacement of RIG-I by MDA5 in RNA recognition.
Thank you for the reviewer's professional suggestions. We understand that exploring the combination of 5’pp-RNA and 2′-O-methylated RNA with MDA5 can further demonstrate the alternative function of MDA5. But we think that the use of 5’ppp-RNA and their dephosphorylation derivatives can fully demonstrate that the MDA5 of M. miiuy and G. gallus have evolved to recognize 5’triphosphate structure like human RIG-I. Therefore, we do not intend to conduct any additional experiments
(6) In section 2.3, the authors assert that Miiuy croaker recognizes SCRV through its RD domain. This claim is supported by their data showing that cells overexpressed with the MDA5 ΔRD mutant lost the ability to inhibit SCRV replication. As a result, the authors draw the conclusion that "these findings provide evidence that MDA5 may recognize 5'-triphosphate-dependent RNA (5'ppp-RNA) through its RD domain." However, to strengthen their argument, the authors should first demonstrate that during SCRV infection, MDA5-mediated antiviral immune response is indeed initiated by recognizing the 5'ppp part of the SCRV RNA, rather than the double-strand part (which can exist in ssRNA virus) of the viral RNA, as this is naturally a ligand for MDA5. Additionally, the authors should treat the isolated SCRV RNA with CIP to remove the phosphate group and examine the binding of MDA5 with SCRV RNA before and after treatment. They should also transfect CIP-treated or untreated SCRV RNA into MDA5 knockdown and wild-type MKC cells to investigate the induction of antiviral signaling and levels of viral replication. Finally, the authors should verify the binding ability of the mutants with isolated SCRV RNA, with or without CIP treatment, to determine which domain of MDA5 is responsible for SCRV 5'ppp-RNA recognition.
We understand the reviewer's concern that MDA5 may be identified by binding to dsRNA in the SCRV virus. Based on the reviewer's suggestion, we extracted SCRV RNA and obtained its dephosphorylated RNA using Calf intestinal phosphatase (CIAP). Next, we transfected them into MDA5-knockdown and wild-type MKC cells, and detected the dimerization of IRF3 and IFN reaction. The results indicate that SCRV RNA does indeed activate immunity in a triphosphate-dependent manner, and knockdown of MDA5 prevents immune activation of SCRV RNA (Figure 1C and 1E, Figure 2P and 2Q). Finally, we synthesized a 5'ppp-SCRV RNA probe and demonstrated that MDA5 binds to 5'ppp-SCRV through the RD domain (Figure 4E-4G). We believe that these results can better demonstrate that MDA5 recognizes 5’ppp-RNA through its RD domain and addresses the concerns of the reviewers.
(7) Similarly, merely presenting Co-IP data demonstrating the interaction between Miiuy croaker MDA5 and STING in overexpressed EPC cells does not justify the claim that "in vertebrates lacking RIG-I, MDA5 can utilize STING to facilitate signal transduction in the antiviral response". This is because interactions observed through overexpression may not accurately reflect the events occurring during viral infection or their actual antiviral functions. To provide more robust evidence, it is essential to conduct functional experiments after STING knockout (or at least knockdown). Furthermore, it is important to note that Miiuy Croaker alone cannot adequately represent all "vertebrates lacking RIG-I".
We found that co-expression of STING and MDA5 can enhance MDA5-mediated IFN-1 response during SCRV virus infection, while knocking down STING can restore MDA5-mediated IFN-1 response (Figure 2N and 2O). This indicates that STING plays an important signaling role in the immune response of MDA5 to RNA viruses. In addition, loss of RIG-I is a common phenomenon in vertebrates, and STING of birds such as chickens (doi: 10.4049/jimmunol.1500638) and mammalian tree shrews (doi: 10.1073/pnas.1604939113) can also bind to MDA5, indicating that STING can indeed play a crucial role in MDA5 signaling in species with RIG-I deficiency. We have added this section to our discussion and elaborated on our observations in more cautious language.
(8) In the manuscript, a series of experiments were conducted using an antibody (Beyotime Cat# AF7164) against endogenous MDA5. The corresponding immunogen for this MDA5 antibody is a recombinant fusion protein containing amino acids 1-205 of human IFIH1/MDA5 (NP_071451.2). However, the amino acid sequences of IFIH1/MDA5 differ substantially between humans and Miiuy croaker, which could introduce errors in the results. Therefore, it is essential to employ antibodies specifically designed for targeting Miiuy croaker's own MDA5 in the experiments.
As shown in Figure 2B, endogenous MDA5 antibodies can detect the MDA5 portion that is forcibly overexpressed by plasmids, suggesting that the MDA5 antibody can indeed specifically recognize the MDA5 protein of M. miiuy.
(9) It is recommended to investigate the phosphorylation of IRF3 in order to confirm the downstream signaling pathway during viral infection when MDA5 is knocked down or overexpressed.
Due to the lack of available phosphorylation antibodies for fish IRF3, we used IRF3 dimer experiments to detect downstream signaling (Figure 1C and 1D, Figure 2P, Figure 4C and 4J).
(10) The use of poly I:C as a mimic for dsRNA to investigate MDA5's recognition of 5'ppp-RNA in hosts lacking RIG-I, as well as the examination of the regulatory role of MDA5 m6A methylation upon activation by 5'ppp-RNA, may be inappropriate. Poly I:C does not possess 5'ppp, and while it has been identified as a ligand for MDA5 in various studies, MDA5 cannot serve as a substitute for RIG-I in recognizing poly (I:C). Therefore, the authors should utilize 5'ppp-dsRNA as the mimic and include the corresponding 5'ppp-dsRNA control without a 5'triphosphate as the negative control (both available from InvivoGen). This approach will specifically elucidate the mechanisms involved when MDA5 functions similarly to RIG-I in the recognition of 5'ppp-RNA.
In our study, we used poly(I:C)-HMW, a known dsRNA mimetic that can be preferentially recognized by MDA5 rather than RIG-I, as a positive control for activating MDA5. What we want to demonstrate is that, like poly(I:C)-HMW (positive control), SCRV can also promote MDA5-mediated IFN immunity, further indicating the important role of MDA5 in 5’ppp-RNA virus invasion. We have clearly labeled the type of poly(I:C) in the figures and legends to avoid misunderstandings for readers.
(11) In Figure 2, Figure 3, and Figure 6, the appearance of virus plaques is not readily apparent, and it is necessary to replace these images with clearer photographs. It appears that MKC or MPC cells are not appropriate for conducting plaque assays. To accurately assess viral proliferation, the authors should measure key indicators throughout the process, such as the production of positive-strand RNAs (+RNAs), replication intermediates (RF), and transcription of subgenomic RNAs. This approach is preferable to solely measuring the M and G protein genes from the virus genome as positive results can still be observed in contaminated cells.
As pointed out by the reviewer, we also think that the virus plaque images in Figure 2K and Figure 3D are not clear enough, so we have replaced them with new clear images (Figure 2J and Figure 3D). But we think that other images can clearly display the proliferation of the SCRV virus, so we did not replace them. In addition, the primers we currently use do measure +RNA, so the replication level of the SCRV virus can be accurately evaluated without being affected by virus contamination. Because the regions where the two pairs of primers are located belong to the SCRV-M and SCRV-G protein genes, we label them as SCRV-M and SCRV-G to distinguish between the two pairs of genes. To avoid reader misunderstanding, we have modified the Y-axis label in the figures (Figure 2I and 2K, Figure 3E, Figure 6E and 6O).
(12) There is a substantial disparity in the molecular size of M. miiuy MDA5 between endogenous and exogenously expressed proteins, as shown in Figure 2A and 2C-D. Please provide clarification.
Please refer to the response to Reviewer 2's question regarding Figure 4B above.
(13) The manuscript incorporates the evolutionary perspective, but lacks specific evolutionary analysis. Thus, it is essential to include relevant analysis to comprehend the evolutionary dynamics and positive selection on MDA5 and LGP2 in the absence of RIG-I in Miiuy croaker. This can be achieved through theoretical calculations using appropriate algorithms, such as the branch models and branch-site models based on the maximum-likelihood method implemented in the phylogenetic analysis by maximum likelihood (PAML) package.
In fact, we have analyzed the molecular evolution of MDA5 and LGP2. Unfortunately, even when analyzing only the MDA5/LGP2 CDS sequences in fish, we found that the topologies of gene trees of MDA5/LGP2 were largely consistent with the species tree. Thus, species with or without RIG-I in the gene trees cannot effectively separate clusters, making it extremely difficult to analyze the molecular evolution of MDA5/LGP2 caused by RIG-I deficiency. Consequently, we gave up this aspect of analysis.
(14) If the narrative regarding m6A methylation goes beyond the activation of MDA5 through recognition of 5'ppp-RNA and represents a regulatory mechanism for all MDA5 activation events, it is not relevant to the theme of "An arms race under RIG-I loss: 5'ppp-RNA and its alternative recognition receptor MDA5." Therefore, all investigations in this paper should focus solely on events when MDA5 recognizes 5'ppp-RNA. Any data associated with the broader regulatory mechanisms and m6A methylation of MDA5 should be excluded from this manuscript and instead be included in a separate study dedicated to exploring this specific topic.
Our theme aims to showcase RNA viruses, rather than an interaction between 5'ppp-RNA and host virus receptors, which our current topic cannot accurately express. Therefore, we made two main changes: firstly, we limited the study species to M. miiuy, although some studies on the functional substitution of MDA5 for RIG-I involved birds. Secondly, change “5’ppp-RNA” to “5’ppp-RNA virus”. We believe that the revised title is more in line with our current research contents.
(15) The running title appears to be hastily done.
We modified it to “MDA5 recognizes 5’ppp-RNA virus in species lacking RIG-I”.
(16) There are many descriptions that are not strongly related to the main theme of the article in the introduction section, making it lengthy and fragmented. Please focus on the research background of RIG-I and MDA5, including their structures, functions, and regulatory mechanisms, as well as the research progress on the compensatory effect of MDA5 in the absence of RIG-I and its evolutionary adaptation mechanism in other species.
Based on the suggestions of the reviewers, we have removed some of the less relevant content in the introduction and added research progress on the compensatory effect of MDA5 in the evolutionary adaptation mechanism of tree shrews in the absence of RIG-I.
(17) Lines 149-156 in the "Results" section include content that resembles an "Introduction" It is important to avoid duplicating information in the results section. Therefore, the authors are encouraged to revise this paragraph to ensure conciseness in the article.
We have streamlined this section to enhance the article's conciseness and clarity.
(18) In the "Results" section, at line 177, the authors assert, "As depicted in Figure 1F-1H," which should be corrected to Figure 2F-2H. Furthermore, the y-axis of the two figures on the right-hand side of Figure 2H represents the ISG15 genes. At line 182, "as demonstrated in Figure 1I-1L," should be revised as "as illustrated in Figure 2I-2L". The authors demonstrated a lack of attention to detail.
Thank you to the reviewer for pointing out our errors, and we have made the necessary corrections.
(19) In lines 197-198, the authors stated that "MDA5-ΔRD showed an inability to interact with SCRV." However, Figure 3D did not reveal any significant difference, thus it is advisable to repeat this experiment at least once.
We have replaced this virus spot image with a new one (Figure 3D).
(20) In lines 200-201 of the "2.3 RD domain is required for MDA5 to recognize SCRV" section, the authors report that the expression of antiviral genes was induced by the overexpression of both MDA5 and MDA5-ΔRD, even in the absence of infection (Figure 3F). Why does the expression of antiviral genes increase in the absence of viral RNA stimulation? Please provide a reasonable explanation.
In the absence of viral infection, overexpression of viral receptor proteins may still transmit erroneous signaling, affecting the body's immunity. We speculate that due to the preservation of the CARD domain by MDA5 and MDA5-ΔRD, they can still induce the expression of antiviral factors without ligands, although this induction effect is much smaller than that of viral infection. However, in order to better demonstrate the function of the RD domain of MDA5 in M. miiuy, we have changed the experimental plan, as shown in the figure 3F. We detected the induction of antiviral factors by overexpression of MDA5 and MDA5-△RD under poly (I:C)-HMW stimulation. This can indicate that the RD domain has a conserved function in the recognition of poly(I:C)-HMW in M. miiuy, and can serve as a positive control for the recognition of SCRV virus invasion by the RD domain of MDA5.
(21) Please provide the GeneBank accession number of M. miiuy MDA5.
The GeneBank accession number of M. miiuy MDA5 was added in the section 4.5 plasmids construction.
(22) The content of lines 228-233 in the "Results" section bears resemblance to that of the "Introduction." To ensure the avoidance of information duplication, it is recommended to remove this paragraph from the results section.
This section has been streamlined.
(23) The bands of mmiMDA5 in the 5'ppp-RNA and dsRNA lanes in Figure 4B are weak and almost unobservable. Please replace them with clear images.
We have rerun this experiment and replaced the images (Figure 4B).
(24) In Figure 5G and at line 253, there are only results presented for the SCRV infection group, while no results are shown for the control group. This raises the question of why the control group results are missing. It is necessary to provide a reasonable explanation or correction for this issue.
The "0 h" infection time point of the SCRV virus is the control group, and we have replaced it with a more intuitive image (Figure 5G).
(25) In Figure 7C, it would be necessary to include the western blot result of YTHDF protein expression in order to verify the efficiency of YTHDF siRNA.
In fact, we have attempted to detect the endogenous expression of YTHDF protein using available commercial antibodies. Unfortunately, only the YTHDF2 antibody can specifically recognize the endogenous protein expression of YTHDF2 in M. miiuy. In addition, the knockdown effect of si-YTHDF2 has been validated by YTHDF2 antibody (doi: 10.4049/jimmunol.2200618).
(26) In line 422 of the "4.3 Cell culture and treatment" section, the paragraph raises a question regarding the nature of Miiuy croaker kidney cells (MKCs) and spleen cells (MPCs) - whether they are cell lines or freshly isolated cells (or primary cultures) derived from kidney and spleen tissues. If these cells are indeed cell lines, it is requested to provide detailed information about the sources and properties of the cells (such as whether they are epithelial cells or other mixed cell types) and the generations of propagation. Alternatively, if the cells were freshly isolated or primary cultures obtained from fish, the method for cell isolation should be provided. The source and stability of cells are extremely important for ensuring the repeatability and reliability of experimental outcomes.
M. miiuy kidney cells (MKCs) and spleen cells (MPCs) are cell lines derived from the kidney and spleen tissues of M. miiuy, with passages ranging from 20 to 40 times. These details have been incorporated into section 4.3.
(27) There are many inaccurate descriptions in the text, which employ concepts that are too broad. These descriptions need to be narrowed down to specific species or objects. Here are a few examples, along with the necessary revisions. Other similar instances should also be revised accordingly. For instance, in line 119, "fish MDA5" should be changed to "Miiuy croaker MDA5." Similarly, in line 166, "fish MDA5-mediated signaling pathway" should be changed to "Miiuy croaker MDA5-mediated signaling pathway." In line 174, "fish MDA5" should be revised to "Miiuy croaker MDA5." Additionally, in line 185, "antiviral responses of teleost" should be changed to "antiviral responses of Miiuy croaker." In line 197, "interact with SCRV" should be revised to "interact with 5'ppp-RNA of SCRV." In line 337, "loss of RIG-I in the vertebrate" should be modified to "loss of RIG-I in Miiuy croaker and chicken." Similarly, in line 338, "MDA5 of fish" should be changed to "MDA5 of Miiuy croaker." Lastly, in line 348, "RIG-I deficient vertebrates" should be revised to "RIG-I deficient Miichthys miiuy and Gallus gallus."
Thank you for the reviewer's suggestions. We have made revisions to these inaccurate descriptions and reviewed the entire manuscript to address similar statements with broad concepts.
(28) Finally, it should be noted that a similar discovery has already been reported in tree shrews (Ling Xu, et al., Proc Natl Acad Sci., 2016, 113(39):10950-10955). This article shares similarities with that research report, therefore it is necessary to discuss in detail the relationship between the two in the discussion and compare and analyze the evolutionary patterns of MDA5 from it.
Based on the reviewer's suggestions, we have compared the similarities and differences between these two reports during the discussion and analyzed the evolutionary dynamics of MDA5 in these vertebrates lacking RIG-I.
Minor concerns:
Thank you to the reviewer for their meticulous examination to our manuscript, we have made revisions to the following suggestions.
(1) At line 120, the sentence "SCRV(one 5'ppp-RNA virus)" should have a space between "SCRV" and "(one 5'ppp-RNA virus)". Please make this correction.
Corrected.
(2) At lines 147-148, the sentence "However, the downstream gene of TOPORSa is missing a RIG-I" is not accurate and needs modification.
We have modified this sentence.
(3) At line 184, "findings indicate" should be corrected to "findings indicated".
Corrected.
(4) At line 189, "a 5'ppp-RNA virus" should be deleted and the text seems redundant.
Deleted.
(5) At line 198, "replication. (Figure 3C-3E)", please remove the punctuation between "replication" and "(Figure 3C-3E)".
Corrected.
(6) At line 416 in "Materials and methods" section, "4.2 Sample and challenge" should be corrected to "4.2 Fish and challenge".
Corrected.
(7) At line 419, the authors state that "The experimental procedure for SCRV infection was performed as described", please briefly describe the SCRV infection method and the infectious dose.
Based on the reviewer's suggestions, we have added relevant descriptions of SCRV infection in section 4.2.
(8) There are several formatting issues in the "Materials and Methods" section. For instance, in line 424, there is no space between the number and letter in "100 μg/ml" and "26 ℃" should be corrected to "26℃". Additionally, in line 430, "Cells" should be corrected to "cells".
Corrected.
(9) At line 446, "50 ng/ul" and "100 mU/ul" should be corrected to "50 ng/μl" and "100 mU/μl".
Corrected.
(10) At line 459, "primers 1)" should be corrected to "primers".
Corrected.
(11) At lines 461-464, the description "For protein purification, MDA5 plasmids with 6× His tag was constructed based on pcDNA3" seems to be no direct logical connection between protein purification and the plasmid construction. Please make the necessary corrections.
Corrected.
(12) At line 548, "cytoplasmic" should be corrected to "Cytoplasmic".
Corrected.
(13) At line 549, "5× 107" should be corrected to "5 × 107".
Corrected.
(14) At line 557, "MgCl2" should be corrected to "MgCl2".
Corrected.
(15) At line 558, "6 %" should be corrected to "6%".
Corrected.
(16) At line 565, "50μg" should be corrected to "50 μg".
Corrected.
(17) At line 571, "300{plus minus}50 bp." should be corrected to "300 {plus minus} 50 bp."
Corrected.
(18) At lines 592-593, the sentence "After several incubations, the m6A level was quantified colorimetrically at a wavelength of 450 nm" does not read smoothly, please improve it.
Revised.
(19) At line 786, "MDA5 recognize" should be corrected to "MDA5 recognized".
Corrected.
(20) At lines 788 and 798, "Pulldown" should be corrected to "Pull-down".
Corrected.
(21) At lines 790 and 796, "bluestaining" should be corrected to "blue staining".
Deleted.
(22) At line 825, "SCRV and infection" should be corrected to "SCRV infection".
Corrected.
(23) At lines 826-827, "SCRV (H) and poly(I:C) (I) infection" should be corrected to "SCRV infection (H) and poly(I:C) stimulation (I)".
Corrected.
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Reply to the reviewers
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
The authors report a mass spectrometry (MS)-based interactomics technique, time-resolved interactome profiling (TRIP), which allows for tracking temporal changes in the interactome of protein of interest. To show that TRIP can successfully deconvolute interactomes over time, they pulsed thyroid cells with homopropargylglycine (Hpg), immunoprecipitated the Hpg incorporated thyroglobulin (Tg) and its interacting proteins at different time points, and subjected the samples to tandem mass tag (TMT)-based quantitative MS analysis. The MS results show that WT and variant Tg proteins indeed associate with different proteostasis network factors in a differential manner over the course of time. In addition, they utilized an siRNA-based luciferase fusion assay to evaluate whether silencing each proteostasis network component changes the levels of Tg in both lysate and media. From the combination of the TRIP and siRNA-based assays, they found many hits, including hits implicated in protein degradation, VCP and TEX264, which they validated with multiple experiments.
I am overall quite positive and think this is an important study. But there are some meaningful points to consider.
Our Response: We thank Reviewer #1 for their positive outlook on our manuscript and their constructive feedback. We have addressed the comments below.
Significant comments:
Reviewer #1, Comment #1: Oonly two replicates of the main data (the TRIP-MS experiments) for this paper is problematic. Especially since the manuscript is supposed to be demonstrating and validating the new technique. Consistent with this concern, the relative enrichment profiles for some of the results were surprising. For instance, interaction with CCDC47 was tapering off but then at 3 h it suddenly reaches the maximum level of engagement. Is this a real finding or the variability in the method? Impossible to tell with two replicates. Presenting heat maps based on biological duplicates is also very problematic. It masks the error, which is large as can be seen in some of the panels showing individual proteins. In my view, triplicates and a clear understanding of the error in the technique should be required.
Our Response: The TRIP datasets for WT Tg contains 5 biological replicates, while the A2234D and C1264R Tg contains 6 biological replicates. Two replicates are typically included in a TMTpro 16plex mass spectrometry run, and each analysis consists of 3 MS runs. We apologize that the number of replicates and layout of the MS runs was not clearly explained. Data for individual replicates is found in Dataset EV1, Dataset EV3, and a newly added Table EV3 delineates the sample layout across the TMT channels and MS runs. We clarified the text as follows:
"Subsequently, two sets of TRIP time course samples (0, 0.5, 1, 1.5, 2, and 3 hr) could be pooled using the 16plex TMTpro and analyzed by LC-MS/MS (Fig 2A). In total, 5 biological replicates were analyzed for WT and 6 biological replicates were analyzed for A2234D and C1264R, respectively (Table EV3)."
Reviewer #1, Comment #2: The same concern arises for the high-throughput siRNA screen, which was performed only in duplicate for WT and A2234D.
Our Response: While the initial screen was performed in duplicate for WT and A2234D, which is common for larger screens due to resource constraints, we would like to direct the reviewer to the fact that we followed up on observed hits using thyroid cell lines with many more replicates. Furthermore, most hits came from the C1264R Tg variant, which had three replicates in the initial screen. Hits were also extensively followed-up.
Reviewer #1, Comment #3: *There are issues with some of the immunoprecipitation experiments: In Figure 1C, a negative control for FLAG IP is missing. *
*-In Figure 2B, I am curious why the band (Hpg -, chase time 0 h) is so faint for the first WB (IB for FLAG) - is Hpg treatment indeed leading to much more Tg present at 0 h? If so, that is a concern. *
-Also, a negative control must be included (either plain cells or cells expressing fluorescent protein or a different epitope-tagged WT Tg).
-In this same figure, I am puzzled why the bands for 1.5-3 timepoints in Biotin PD elution, probed for Rhodamine, are very faint especially considering that in Figure 1D, the corresponding bands, which are 4 h after the pulse, look fine. It seems like the IP failed here?
Our Response: In Fig 2B, we have updated this figure with higher-quality images that are more representative of the results found when performing this experiment. Furthermore, to address the missing negative controls in Fig. 1C, we have added a separate figure (Fig EV2) where (-) FLAG-tagged Tg is included in this panel. We updated the text as follows:
"Furthermore, the C-terminal FLAG-tag and Hpg labeling are necessary for this two-stage enrichment strategy, and DSP crosslinking is necessary to capture these interactions after stringent wash steps (Fig 1D, Fig EV2)."
Regarding the Biotin PD rhodamine/TAMRA signal in Fig 2B: The blots in this figure panel represent the time-resolved Tg fractions from cell lysate, corresponding only to intracellular thyroglobulin. The decrease in band intensity for 1.5-3 hr time points is expected due to continued secretion and/or degradation dynamics taking place that decrease the intracellular population of labeled thyroglobulin that is able to be captured. For comparison, please note the C1264R panel (Fig 2C), where the rhodamine/TAMRA signal in the Biotin PD elutions is more stable compared to WT, indicating the cellular retention of C1264R while WT Tg is efficiently secreted and the signal is lost more rapidly. Fig 1D contains samples derived from a 4 hr Hpg pulse (without chase), explaining why the overall fluorescent Tg signal is more intense.
Suggestion to consider:
Reviewer #1, Comment #4: This manuscript, supported by the title and abstract, mainly focuses on the presentation of the development and application of TRIP, which is highly significant. The story becomes less coherent and harder to follow as significant amounts of text/figures are dedicated to siRNA-based high throughput screening and follow-up. In addition, although the discovery of TEX264 as one of the hits is very interesting and exciting, TEX264 apparently was not a hit in the TRIP experiment and is pretty distracting from the main point of the paper highlighted in the abstract and title, therefore. The siRNA-based assay and follow-up studies could be a separate scientific story of their own. Especially considering my concerns on the number of replicates for both the TRIP and siRNA-based assay, it could be beneficial to actually split the manuscript into two and conduct more replicates of the -omic work, which should corroborate the exciting discoveries the authors have made.
Our Response: We have edited the manuscript to hopefully provide a more cohesive presentation of all data, findings, and conclusions within the paper. Given the generally positive outlook on the manuscript from other reviewers and our responses to significant comments from Reviewer #1 we opted to keep the manuscript as a single piece and address all reviewer comments.
Minor comments:
Reviewer #1, Comment #5: Throughout the manuscript, the authors have not defined what FT is; presumably it means FLAG tag.
Our Response: Reviewer #1 is correct in FT corresponding to FLAG tag. We have now edited the manuscript text to clarify this as follows:
"Thyroglobulin was chosen as model secretory client protein, and we generated isogenic Fischer rat thyroid cells (FRT) cells that stably expressed FLAG-tagged Tg (Tg-FT), including WT or mutant variants (A2234D and C1264R)."
Reviewer #1, Comment #6: The authors might discuss their rationale for choosing 0-3 hrs for their TRIP studies. That includes any relevant information about the half-life of WT versus variant Tg, whether the Hpg pulse time is short enough to avoid missing key features of the temporal interactome, and discussion of what would happen if the TRIP were performed at prolonged time points (e.g. 6-10 h).
Our Response: Apologies that we omitted this important point, which is indeed related to the secretion and degradation half-life. We edited the manuscript text to discuss the rationale for 0-3 hr, length of the Hpg pulse and the impact on capturing interactions, and performing TRIP at prolonged time points as follows:
"Our previous study indicated that ~70% of WT Tg-FT was secreted after 4 hours, while approximately 50% of A2234D and 15% of C1264R was degraded after the same time period (Wright et al, 2021). Therefore, we reasoned that a 3-hr chase period would be a enought time to capture the majority of Tg interactions throughout processing, secretion, cellular retention, and degradation, while still being able to capture an appreciable amount of sample for analysis."
We explain the labeling timeline and limitations further in the discussion:
"To address this, we utilized a labeling time of 1 hr which allows us to generate a large enough labeled population of Tg-FT for TRIP analysis, but some early interactions are likely missed within the TRIP workflow. In the case of mutant Tg, performing the TRIP analysis for much longer chase periods (6-8 hrs) may provide insightful details to the iterative binding process of PN components that is thought to facilitate protein retention within the secretory pathway."
Reviewer #1, Comment #7: Lines 68-69: the two citations should probably come one sentence earlier (at least Coscia et al 2020 is a structure paper).
Our Response: We agree. We have edited the manuscript as follows to correct this:
"In earlier work, we mapped the interactome of the secreted thyroid prohormone thyroglobulin (Tg) comparing the WT protein to secretion-defective mutations implicated in congenital hypothyroidism (CH) (Wright et al, 2021). Tg is a heavily post-translationally modified, 330 kDa prohormone that is necessary to produce triiodothyronine (T3) and thyroxine (T4) thyroid specific hormones (Citterio et al, 2019; Coscia et al, 2020). Tg biogenesis relies extensively on distinct interactions with the PN to facilitate folding and eventual secretion."
Reviewer #1, Comment #8: Line 91: "(Figure 1A)" should follow the sentence "To develop the time-resolved..." to help readers better understand the system.
Our Response: __We agree. We have edited the manuscript to add the Fig 1A reference. Furthermore, we redesigned the schematic in Fig 1A to better explain the experimental system. (see also __Reviewer #2, comment 10)
"To develop the time-resolved interactome profiling method, we envisioned a two-stage enrichment strategy utilizing epitope-tagged immunoprecipitation coupled with pulsed biorthogonal unnatural amino acid labeling and functionalization (Fig 1A). Cells can be pulse labeled with homopropargylglycine (Hpg) to synchronize newly synthesized populations of protein. After pulsed labeling with Hpg, samples can then be collected across time points throughout a chase period (Fig 1A, Box 1) (Kiick et al, 2001; Beatty et al, 2006). The Hpg alkyne incorporated into the newly synthesized population of protein can be conjugated to biotin using copper-catalyzed alkyne-azide cycloaddition (CuAAC) (Fig 1A, Box 2). Subsequently, the first stage of the enrichment strategy can take place where the client protein of interest is globally captured and enriched using epitope-tagged immunoprecipitation, followed by elution (Fig 1A, Box 3)."
Reviewer #1, Comment #9: Line 101: Fisher should be Fischer
Our Response: Thank you. We have edited the manuscript text to correct this.
Reviewer #1, Comment #10: Line 131: Should be 1.5 hrs instead of 2 hrs.
Our Response: We edited this point (see below in comment #11)
Reviewer #1, Comment #11: Lines 135-136: I do not agree with the claim that HSPA5 profile looked similar for MS and WB. I do not see a peak for HSPA5 at 2 hrs in Figure 2D.
Our Response: We replaced the mass spectrometry quantification in Fig 2D, E with the scaled, relative enrichments. This provides a more meaningful comparison, as all interactions are scaled in the same way. Unfortunately, it is still difficult to directly compare the Western blot results in Fig. 2B-C to the mass spectrometry quantifications in Fig 2D-E because the WB intensities are not normalized to the Tg bait protein amounts, which is changing over time. At 2-3hrs time points, little WT Tg is pulled down as most of it is secreted. Therefore, the HSPA5 interactions are no longer detectable by Western blot. On the other hand, MS is much more sensitive to capture the interactions. We modified the text as follows:
"For C1264R, interactions with HSPA5 were highly abundant at the 0 hr time point and remained mostly steady throughout the first 1.5 hours (Fig 2C). A similar temporal profile was also observed for HSP90B1. Additionally, interactions with PDIA4 were detectable for C1264R and were found to gradually increase throughout the first 1.5 hr of the chase period, before rapidly declining (Fig 2C). We noticed similar temporal profiles for PDIA4 and HSPA5 to our western blot analysis, when measured via TMTpro LC-MS/MS as further outlined below (Fig 2D-E). In particular, the HSPA5 WT Tg interaction declined within the first hours, yet for C1264R Tg, the HSPA5 interactions remained mostly steady over the 3-hour chase period. (Fig 2E)."
Reviewer #1, Comment #12: Line 186: The cited paper Shurtleff et al 2018 is missing in the reference list.
Our Response: Thank you. We have corrected this in the citation management system and it is now available in the reference list.
Reviewer #1, Comment #13: Line 188: I disagree with the authors' claim here because, at least for CCDC47, interactions with C1264R seem to come back at the 3 hr time point.
Our Response: We have removed the discussion of EMC and PAT complex components from the text. The implications of these interactions for Tg biogenesis remain unclear and were therefore a distraction from the discussion of other core proteostasis network components pertinent to Tg processing. Nonetheless, the full dataset - including these interactions - remains available to readers in Appendix Fig S1 for further perusal.
Reviewer #1, Comment #14: Line 203: I am not sure if P4HA1 can be included in the examples for showing distinct patterns for mutants compared to the WT according to their data in Figure 3H.
Our Response: We agree. We have edited the text to remove the discussion of prolyl hydroxylation and isomerization family members and elected to discuss the new clustering analysis and the robustness of the TRIP method in more detail. The full TRIP data is nonetheless available to interested readers in Appendix Fig S1.
Reviewer #1, Comment #15: Line 216: The authors should add citations about the functions of STT3A and STT3B proteins.
Our Response: We've edited the manuscript text to include a reference to the primary literature for STT3A and STT3B functions, as follows:
"Previously, we showed that A2234D and C1264R differ in interactions with N glycosylation components, particularly the oligosaccharyltransferase (OST) complex. Efficient A2234D degradation required both STT3A and STT3B isoforms of the OST, which mediate co-translational or post-translational N-glycosylation, respectively (Kelleher et al, 2003; Cherepanova & Gilmore, 2016)."
Reviewer #1, Comment #16: Lines 248-251, "We found that interactions with these components...": this sentence should refer to Figure 3 - Figure Supplement 3 instead of Figure 3L and S4.
Our Response: Thank you. This section of the manuscript was significantly rewritten and the figure references updated.
Reviewer #1, Comment #17: Lines 258-260, "Another striking observation was that the temporal profile of EMC interactions for C1264R correlated with RTN3, PGRMC1, CTSB, and CTSD interactions.": Please provide more evidence to support the potential correlation between different interaction profiles. Or the authors should move this sentence to the discussion section as it sounds speculative. This highlights the issue of only having duplicates, as well.
Our Response: We agree that this point was highly speculative and we removed discussion of the EMC interactions.
To further investigate the correlation of interaction profiles across the dataset, we performed unbiased k-means clustering. This led to the identification of 7 and 6 unique clusters of interactors for WT and C1264R Tg-FT, respectively. These data are represented in Fig 3F and Fig EV5. Unique clusters highlight similar temporal interaction profiles for Tg-FT interactors, and provide a quantitative representation of correlative interactions that take place during Tg-FT processing.
"To assess temporal interaction changes in an unbiased fashion and identify protein groups exhibiting comparative behavior, we carried out k-means clustering of the temporal profiles for WT and C1264R. This analysis revealed a large divergence in the interaction profiles. For WT Tg, only one cluster exhibited steadily decreasing interactions (cluster 4), while others increased with time, or showed peaks at intermediate times (Fig 3F, Fig EV5A). On the other hand, C1264R largely exhibited clusters with decreasing interactions over time (Fig 3F, Fig EV5B). Cluster 2 for WT with biomodal interactions at early and late time points contains many Hsp70/90 chaperoning components. For C1264R Tg, many Hsp70/90 chaperoning components and disulfide/redox-processing components are instead part of cluster 2', which exhibited an initial rise in interactions strength before plateauing (Fig 3F, Fig EV5A,B). This divergent temporal engagement between WT Tg and the destabilized C1264R mutant is aligned with the patterns observed in the manual grouping (Fig 3B,C), highlighting that the unbiased temporal clustering can reveal broader patterns in the reorganization of the proteostasis dynamics."
One of the clusters of the C1264R Tg interactions contained autophagy interactors along with glycosylation components. We therefore postulate that this could point to a coordination of these processes. We discuss this new point in the updated manuscript:
"In the k-means clustered profiles, autophagy interactions largely group together in the same cluster, showing stronger interactions at earlier time points. In the same cluster are glycosylation components (UGGT1 and STT3B, MLEC), further supporting a possible coordination for C1264R Tg between lectin-dependent protein quality control and targeting to autophagy (Fig EV5B,C)."
Reviewer #1, Comment #18: Line 340: As written, should cite more than one paper
Our Response: Thank you. We reworded the manuscript to correct this, as follows:
"The discovery of several protein degradation components as hits for rescuing mutant Tg secretion may suggest that the blockage of degradation pathways can broadly rescue the secretion of A2234D and C1264R mutant Tg, a phenomenon similarly found for destabilized CFTR implicated in the protein folding disease cystic fibrosis (Vij et al, 2006; Pankow et al, 2015; McDonald et al, 2022)."
Reviewer #1, Comment #19: Line 371: Should be Figure 4 - figure supplement 2
Our Response: We edited the manuscript to correct this error.
Reviewer #1, Comment #20: Line 1231: "Zhang et al 2018" needs to be removed
Our Response: We have removed this citation.
Reviewer #1, Comment #21: Line 1286: FRTR should be FRT
Our Response: Thank you. We have corrected this within the text.
Reviewer #1, Comment #22: Figure 3E: Color used to highlight the three proteins (CCDC47, EMC1, EMC4) should match the color used in Figure 3 - Figure Supplement 3
Our Response: __We have edited Figure 3 to remove the section related to membrane protein biogenesis. This data is still available in __Appendix Fig S1 with consistent color coding.
Reviewer #1, Comment #23: Figure 4A: The bottom figure where lysate signal is inversely proportional to time is misleading because the authors are assessing steady-state level of proteins in this assay.
__Our Response: __We agree. We updated the schematic in __Fig 4A __to better explain the workflow and differentiate the steady-state protein level being measured within the lysate.
Reviewer #1, Comment #24: Figure 4 - Figure Supplement 1 caption: in (C), (F) should be (B). (K) should be (G) and I am not sure what the authors mean when they refer to (J) in caption of (G).
Our Response: We have corrected this lettering mistake to match the figure properly. Please note that this figure is now Fig EV6, and it includes some new and reorganized panels.
Reviewer #1, Comment #25: Figure 5 caption for (C and D): Need to specify the time that the samples were collected (8 hrs), as it seems different from A and B according to the main text.
Our Response: We have specified the collection time within the caption for these data in Fig 5C __and __5D.
Reviewer #1, Comment #26: Figure 5 - Figure Supplement 1: Data for HERPUD1 and P3H1 should be included.
Our Response: We have now included data to confirm the knockdown for HERPUD1 and LEPRE1 (P3H1) in Fig EV7F-G.
Reviewer #1, Comment #27: Figure 5 - Figure Supplement 2B: Please mention in the caption how degradation is defined.
Our Response: We have updated the Fig EV7H caption to include how "degradation" is defined within these experiments:
"% Degradation is defined as . Where is the fraction of Tg-FT detected in the lysate at a given timepoint n, and is the fraction of Tg-FT detected in the media at a given timepoint n."
Reviewer #1 (Significance (Required)):
Reviewer #1, Comment #28: This manuscript is highly significant because the authors (1) designed and validated a new methodology for time-resolved interactomics study, (2) presented the dynamic changes in Tg interactome for WT and variants, and (3) discovered how proteins implicated in degradation pathways (e.g. VCP, TEX264, RTN3) can change the secretion profile of WT and mutant Tg proteins. With TRIP, the authors demonstrated that they could obtain valuable data that were previously not captured from steady-state interactomics studies (Wright et al. 2021; Figure 3M and Figure 3 - Figure supplement 4D-4I). Furthermore, the authors treated cells with VCP inhibitors and performed both 35S pulse-chase analyses and TRIP. These experiments provide valuable information to the field by (1) presenting a new method to rescue Tg secretion defect, and (2) demonstrating a broader applicability of TRIP. If the major comments above can be addressed I believe this is a tremendous contribution to the field.
Our Response: We thank Reviewer #1 for their review comments and praise for the work presented within this manuscript.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
Reviewer #2: In the manuscript 'Time-Resolved Interactome Profiling Deconvolutes Secretory Protein Quality Control Dynamics' Wright et al. developed an approach for time-resolved protein protein interaction mapping relying on pulsed unnatural amino acid incorporation, protein cross linking, sequential affinity purification, and quantitative mass spectrometry named time-resolved interactome profiling (TRIP). The authors applied the TRIP method to compare the interactions of the secreted thyroid prohormone thyroglobulin (Tg) comparing the WT protein to secretion-defective mutations implicated in congenital hypothyroidism. They further employed an RNA interference screening platform (1) to investigate if (1) interactors identified via TRIP are functionally relevant for Tg protein quality control and (2) to identify factors that can rescue mutant Tg secretion. The screen was initially performed in HEK293 cells, but selected hits with a phenotype in HEK cells were then followed up in Fisher rat thyroid cells. Further functional validation was performed by pharmacologic inhibition of VCP, a hit from the RNAi screen with an effect on Tg lysate abundance and Tg secretion. While the authors present a comprehensive study including identification of protein-protein interactions using proteomics followed up by an RNA interference screen for functional validation, major comments need to be addressed for both the proteomics as well as the functional genomics aspects of the study (see comments below).
Our response: Thank you to reviewer 2 for their constructive feedback. We addressed all comments in detail below.
Major comments:
Reviewer #2, Comment #1: The authors describe a new method for quantitative, temporal interaction mapping. The protocol involves two enrichment steps as well as several reactions including cross-linking of the samples as well as functionalization of the unnatural amino acids. Given all these steps, the authors should rigorously characterize the quantitative reproducibility of the experiment when performed in independent biological replicates. This is important because in the final quantitative MS experiment, the authors only use two biological replicates, which is too low especially for such an involved sample preparation procedure, which would expect to have a high variability between replicates. Given the low number of replicates and the unknown reproducibility of the quantification for this protocol, it is questionable at this point how reliable the quantification over the time course is.
__Our Response: __We apologize that the number of replicates and robustness of the analysis was not entirely clear in our manuscript. We thank the reviewer for the feedback, as this is important point to clarify. We included several additional analyses to further explain the robustness and quantitative reproducibility of our results:
- We clarified the number of replicates For quantitative MS experiments five biological replicates were analyzed for WT, while six biological replicates were analyzed for A2234D and C1264R Tg-FT, respectively not two as mistakenly presumed by Reviewer #2. These data are available in Dataset EV1 and Table EV3. There is only one place where two biological replicates are included, C1264R Tg-FT FRT cells treated with ML-240 treatment for TRIP analysis. We have further clarified the number of biological replicates within the manuscript text as follows (see also reviewer #1, comment 1):
"Subsequently, two sets of TRIP time course samples (0, 0.5, 1, 1.5, 2, and 3 hr) could be pooled using the 16plex TMTpro and analyzed by LC-MS/MS (Fig 2A). In total, 5 biological replicates were analyzed for WT and 6 biological replicates were analyzed for A2234D and C1264R, respectively (Table EV3)."
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We displayed the reproducibility of TRIP time profiles for several individual proteins in Fig EV3 __and in __Fig 3K (VCP). We included shading to indicate the standard error of the mean (SEM) for the individual protein time courses to provide further assessment of the quantitative reproducibility. We updated the text as follows: "To benchmark the TRIP methodology, we chose to monitor a set of well-validated Tg interactors and compare the time-resolved PN interactome changes to our previously published steady-state interactomics dataset (Wright et al, 2021). Previously, we found that CALR, CANX, ERP29 (PDIA9), ERP44, and P4HB interactions with mutants A2234D or C1264R Tg exhibited little to no change when compared to WT under steady state conditions (Fig EV4A). However, in our TRIP dataset we were able to uncover distinct temporal changes in engagement that were previously masked within the steady-state data. Our time-resolved data deconvolutes these aggregate measurements, revealing prolonged CALR, ERP29, and P4HB engagements for both A2234D and C1264R Tg mutants compared to WT (Fig EV4B-F). We found that these measurements for key interactors and PN pathways exhibited robust reproducibility, as exemplified by the standard error of the mean for the TRIP data (Fig EV4B-I, Appendix Figure S1B)."
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For full transparency, we also include the SEM of all TRIP profiles in the heatmap in Appendix Fig S1B.
- Furthermore, we included 25-75% quartile ranges for the pathway aggregated time courses (Fig 3B,C,J,K) and the k-means hierarchical clustering analysis (Fig 3F, Fig EV5). Especially these clustering data allow for the visualization and analysis of temporal protein interactions that are correlated with one another, while the accompanying quartile ranges provide further context for the reproducibility of these measurements and cluster profiles (see __Reviewer #1, Comment 17 __above for further explanation about the k-means clustering).
Reviewer #2, Comment #2: Compared to the previous dataset published last year, the authors discover an overlap in interactors, but also a huge discrepancy, with 96 previously identified interactors not detected in the current study, but 198 additional interactors identified. How do the authors explain the big differences between these datasets?
__Our Response: __We can only speculate here but this difference in overlapping interactors may stem from several different factors, including but not limited to cell line, instrumentation, LC-MS/MS methodology, and sample processing workflows. Our previous dataset was published using transiently transfected HEK293 cell lines expressed FLAG-tagged constructs of Tg. The HEK293 cell line makes for a robust cell line used throughout several biological investigations, but it is not representative of the native cellular environment in which Tg is expressed. Moreover, transiently transfected cells can lead to high protein expression that may not always represent what is found within the native cellular environment and proteome. Here, we used Fischer rat thyroid (FRT) cells engineered to stably express FLAG-tagged constructs of Tg. This cell line model should more accurately represent the native cellular environment Tg is expressed as it is exclusively found within thyroid tissue. Our previous dataset was collected across two different instruments with similar LC-MS/MS methodology. Here, this dataset was collected on a single instrument after performing further method optimization from our methodology used to acquire the first dataset. In line with our LC-MS/MS methodology development, the sample processing workflows here are quite different. Our previous dataset utilized 6plex TMT labeling with globally immunoprecipitated samples from various Tg constructs. Global immunoprecipitation of Tg leads to much larger protein sample amounts than the TRIP methodology presented here, which we coupled with 16plex TMTpro labeling. This is also one of the reasons we chose to deploy a booster/carrier channel within our experimental labeling schemes.
Reviewer #2, Comment #3: For the temporal interaction analysis the authors describe differences in the temporal profiles of selected interactions comparing wt and mutant, however no statistical analysis is performed comparing wt and mutant interaction profiles across the time course. Furthermore the variability between the replicates for the temporal profiles is not shown and some of the temporal profiles appear to be noisy. A more rigorous statistical analysis should be performed including additional biological replicates to evaluate the changes over the time course, especially as the temporal interaction analysis is the novelty of this study.
Our Response: Please also see our response to Reviewer #2, comment 1 above. We previously presented an analysis of the variability of the TRIP measurements (SEM) (now in Appendix Fig S1B). We have since provided further statistical analysis found in the updated Fig 2B,C,J, which include 25-75% quartile ranges for respective proteostasis network pathways. We also included SEM for the time profiles of individual interactors in Fig EV4.
To assess the divergence in time profiles in an unbiased way, we added a k-means hierarchical clustering analysis (Fig 3F, Fig. EV5). These clustering data allow for the visualization and analysis of temporal protein interaction profiles that are similar to one another and how groups of interactors shift between different clusters for WT Tg and the C1264R mutant.
Reviewer #2, Comment #4: To functionally validate interactors derived from the TRIP analysis as well as to identify factors that can rescue mutant Tg secretion the authors developed an RNA interference screen. There are a number of aspects that need to be addressed/clarified for this part of the study.
Our Response: We have added some clarifying changes to the text and the figure panels associated with the siRNA screening and follow-up experiments on the trafficking and degradation factors that rescue Tg secretion. We have addressed other comments from Reviewers #3 and #4 related to these portions of the paper and hope that Reviewer #2 finds them satisfactory.
Reviewer #2, Comment #5: While the authors validate the stable cell lines expressing the nanoluciferase tagged Tg and the linearity of luminescence signal in lysate and media carefully, they do not validate their platform in combination with the RNAi knockdown strategy. The authors should select genes as positive controls that are expected to modulate Tg secretion and demonstrate that the knockout of these positive controls indeed results in changes in Tg secretion in their system.
Our Response: This is an excellent suggestion and certainly something we would have done given any prior knowledge on known control genes that would positively or negatively regulate Tg secretion. The purpose for developing the siRNA screening platform was to investigate and hopefully discover genes that are able to positively or negatively regulate Tg processing. We have done so to the best of our ability, identifying for example NAPA which positively regulates WT Tg secretion, as seen by the decrease in WT Tg secretion when treated with NAPA siRNA. Conversely, we found that VCP may negatively regulate C1264R Tg secretion, as discovered by the increase in secretion with VCP siRNA or ML-240 treatment. We included a standard "TOX" siRNA control, which we knew would likely negatively affect WT Tg secretion and this was indeed the case. As we stated within the manuscript:
"This is the first study to broadly investigate the functional implications of Tg in-teractors and other PQC network components on Tg processing."
Reviewer #2, Comment #6: For the screen the authors select 167 Tg interactors and PN (Proteostasis network) related factors. This statement is very vague and the authors should clarify which genes were knocked down and which criteria were applied to narrow down the list of interactors and to select PN factors. The authors should therefore provide a supplementary table including all genes included in the screen, their source (were this derived from the initial study by Wright et al, from the current study or compiled from prior knowledge about PN), as well as their results from the screen based on luminescence in media and lysate. It is unclear how many of the selected factors are actually coming from the TRIP analysis.
Our Response: The list of genes included within the siRNA screen, as well as the results were previously included, and are now included in Appendix Fig S2. We have further provided the information requested by Reviewer #2 within Dataset EV5 indicating whether a gene was included in the siRNA screen due to its identification within our previous proteomics dataset (Wright et al, 2021.), the proteomics dataset presented here, or based upon primary literature. We added a comment in the text:
"Moreover, we were interested in identifying factors whose modulation may act to rescue mutant Tg secretion. HEK293 cells were engineered to stably express nanoluciferase-tagged Tg constructs (Tg-NLuc) and screened against 167 Tg interactors and related PN components (see Dataset EV5 for the list of genes)."
Reviewer #2, Comment #7: Only a small number of the 167 selected genes shows an effect on Tg abundance/secretion. How do the authors explain this result? Would we not expect that Tg interactors, especially those from the TRIP method which interact with the newly synthesized are more enriched for functionally relevant genes.
Our Response: The proteostasis network contains genes and proteins of high redundancy in structure and function, and many single-gene knockdowns are likely insufficient to have a large impact on Tg abundance or secretion. In fact, these results are in line with what we would have expected when designing these experiments. Our goal here was to identify the key players that control Tg protein quality control.
We explain the proteostasis network redundancy in the manuscript:
"The functional implications of protein-protein interactions can be difficult to deduce, especially in the case of PQC mechanisms containing several layers of redundancy across stress response pathways, paralogs, and multiple unique proteins sharing similar functions (Wright & Plate, 2021; Bludau & Aebersold, 2020; Karagöz et al, 2019; Braakman & Hebert, 2013)."
Reviewer #2, Comment #8: The authors initially performed the screen in HEK293 cells and as a second step wanted to validate the hits from the HEK cells in more relevant Fisher rat thyroid cells. Indeed they could show that knockdown of NAPA increased WT TG in lysate and decreased WT Tg secretion. Furthermore, they further validated genes to modulate mutant Tg lysate and media abundance. The authors should perform a rescue experiment to demonstrate that the observed phenotype can be reversed through re-introduction of NAPA.
Our Response: We have now performed the requested NAPA complementation experiments and provided the data within Fig EV 7I. Overexpression of a human, siRNA-resistant NAPA construct partially reversed the increase in WT Tg lysate retention. These results further support the identification of NAPA as a pro-trafficking factor for WT Tg. We updated the manuscript text to include these data as follows:
"To understand if these results were directly attributable to NAPA function, we performed complementation experiments where FRT cells treated with NAPA siRNAs were co-transfected with a human NAPA plasmid. WT Tg lysate abundance decreased when NAPA expression was complemented, confirming that the observed retention phenotype could be attributed to NAPA silencing (Fig EV7I). These results established that NAPA acts as a pro-secretion factor for WT Tg."
Reviewer #2, Comment #9: One hit from this analysis was the ER-phagy receptor TEX264, while TEX264 was not identified in the TRIP data, is selectively increased the C1264R secretion, but not wt and the other Tg mutant. Following Co-IP data however revealed some interaction between the C1264R and to a lesser extent the A2234D mutant. How do the authors explain that TEX264 was missed in the TRIP dataset?
Our Response: The TRIP samples are of much lower protein abundance compared to globally purified samples used for the Co-IP analysis. While the interaction is seen with the globally purified Co-IP samples, this interaction is likely much more difficult to capture with the low abundance, time-resolved samples that are acquired through the TRIP workflow, especially if this interaction is transient or requires the coordination of other accessory proteins as has been detailed in the literature and discussed within the manuscript presented here:
"While A2234D and C1264R Tg were preferentially enriched with TEX264 compared to WT, it remains unclear what other accessory proteins may be necessary for the recognition of TEX264 clients (Chino et al, 2019; An et al, 2019). Furthermore, TEX264 function in both protein degradation and DNA damage repair further complicates siRNA-based investigations (Fielden et al., 2022). Further investigation is needed to fully elucidate 1) if Tg degradation takes place via ER-phagy and 2) by which mechanisms this targeting is mediated."
Minor comments:
Reviewer #2, Comment #10: The workflow needs to be described clearer. For example, it should be better explained why the authors selected a two-stage enrichment strategy, I assume that the first based on the Flag affinity tag is to purify the protein of interest and the second step based on the incorporation and functionalization of the unnatural amino acids to enrich for the newly synthesized fraction at specific time points after protein synthesis? These are critical steps for the method but the rationals are not well explained, neither in the text nor the figures captures all these steps of the method very clearly, which makes it really difficult for the reader to understand the individual steps of the method. Moreover, the structures in Figure 1 workflow are not clearly labeled, so that it is confusing which part represents which protein/molecule.
Our Response: Thank you for this feedback. We have updated Fig 1 to provide more detail to provide more clarity for the readers. Furthermore, we have edited the text to more clearly describe the workflow:
"To develop the time-resolved interactome profiling method, we envisioned a two-stage enrichment strategy utilizing epitope-tagged immunoprecipitation coupled with pulsed biorthogonal unnatural amino acid labeling and functionalization (Fig 1A). Cells can be pulse labeled with homopropargylglycine (Hpg) to synchronize newly synthesized populations of protein. After pulsed labeling with Hpg, samples can then be collected across time points throughout a chase period (Fig 1A, Box 1) (Kiick et al, 2001; Beatty et al, 2006). The Hpg alkyne incorporated into the newly synthesized population of protein can be conjugated to biotin using copper-catalyzed alkyne-azide cycloaddition (CuAAC) (Fig 1A, Box 2). Subsequently, the first stage of the enrichment strategy can take place where the client protein of interest is globally captured and enriched using epitope-tagged immunoprecipitation, followed by elution (Fig 1A, Box 3). The second enrichment step can then utilize a biotin-streptavidin pulldown to capture the Hpg pulse-labeled, and CuAAC conjugated population, enriching samples into time-resolved fractions (Fig 1A, Box 4) (Li et al, 2020; Thompson et al, 2019)."
Reviewer #2, Comment #11: Except for the general workflow shown in Figure 1, a more detailed workflow showing the experimental steps, such as the sample fractions with the following steps could be added so that the design of the method is clearer. Also the style of the workflows including Figure 1, Figure 2A, and Figure 3A are different. It would be helpful to make them the same style and make the Figure 2A as a zoom in or more detailed illustration on part of Figure 1.
Our Response: Thank you for this feedback. In addition to updating Fig 1, we also expanded Fig 2A to more clearly outline the experimental steps in the TRIP workflow. Assuming the term "style" used here is in reference to color pallets and figure schematics used, these have been updated to ensure they are agreeable aesthetically across manuscript figures.
Reviewer #2, Comment #12: A summary of proteomics results of time course labeling after all enrichment steps, including the total number of identified proteins at different conditions and control would be helpful for having an overview impression on the proteomics results
Our Response: __We have included an updated __Dataset EV1 that provides a summary of proteomics data included which runs given proteins were identified in, % of TMT channels quantified, % of Hpg Pulse channels quantified, and generally number of proteins quantified across runs for each construct.
Reviewer #2, Comment #13: In Figure 2B, the WB for PDIA4 in the Biotin PD elution is missing. Why was the PDIA4 interaction missing for the time course analysis, but the interaction was captured in the initial test for Wt Tg (Figure 1D). Additionally, in this panel the Rhodamine Probe Gel shows inconsistencies at the time points 1.5 - 3h. Does this mean that the labeling did not work well for these conditions? As we would expect a consistent Rhodamine Probe signal at every time point.
Our Response: Please also see our response to Reviewer #1, comments 3 & 11. Fig 1D features continuous Hpg labeling for 4 hours to ensure that most intracellular Tg is labeled for this proof-of-concept experiment for the two-stage enrichment strategy. Fig 2B features a shorter 60 minute pulse of Hpg labeling, prior to the full chase period and two-stage enrichment strategy. PDIA4 interactions were detectable throughout Fig 1D because those measurements captured a larger population of labeled Tg, whereas in Fig 2B Tg bait protein amounts were much smaller after the two-stage enrichment procedure to capture the time-synchronized population.
The Rhodamine/TAMRA Probe Gel in Fig 2B does not have inconsistencies in Tg abundance, but highlights the fact that pulse labeled WT Tg is being secreted or degraded in FRT cells. As you would expect as time continues during the chase period, intracellular WT Tg signal decreases as secretion and degradation take place. Constant Rhodamine/TAMRA probe signal would not be expected here. Consistent with this, the C1264R Tg signal remains more stable for the intial time course. This is expected as the C1264R Tg variant is retained intracellular undergoing increased interactions the proteostasis network. We have removed the PDIA4 panel for WT Tg because there was no signal above the detection limit. This is now explained as follows:
"For WT Tg, interactions with HSPA5 peaked within the first 30 minutes of the chase period and rapidly declined, in line with previous observations, but PDIA4 interactions were not detectable by western blot analysis (Fig 2B) (Menon et al, 2007; Kim & Arvan, 1995)."
Reviewer #2, Comment #14: In Figure 2, why was there no WB results for the A2234D? In Figure 2D and 2E, at which time point are the changes significant compared to WT?
Our Response: We did not perform the WB experiments with A2234D. We used WT and C1264R Tg in our proof of concept experiments via WB and decided to move forward with analyzing A2234D Tg by LC-MS/MS. Please see our response above to Reviewer #2, comment 3 for information on the statistical analysis.
Reviewer #2, Comment #15: All figure legends should indicate how many biological replicates were performed for each experiment represented in the figure.
Our Response: We have updated the figure captions to include this information where applicable.
Reviewer #2, Comment #16: The heatmaps shown in Figure 3, Figure 3 - Figure Supplement 3, and Figure 7 are in the current form incomprehensible. The heatmaps depict the relative enrichment vs the control sample, which was scaled between 1 and -1. The color coding with 5 different colors from 1 to -1 is very confusing and should be changed to just two colors, one for positive and one for negative relative enrichment. I would also suggest changing the visualization of the heatmap showing the wt and mutants side by side, instead of stacked on top of each other for each individual protein.
Our Response: Thank you for this feedback, and we apologize for the confusion. We adjusted our data analysis approach by removing previous negative enrichment values. As these served only as "background" within the dataset, they did not carry much meaning. The TRIP enrichment is now scaled from 0 to 1, where a value of 1 represents the time point at which the enrichment is greatest, while 0 represents the background intensity in the (-) Hpg control sample. The associated figures have been updated accordingly, and we feel they are now more comprehensible and aesthetically pleasing.
We opted to keep the Viridis color scheme in the heatmap to allow for more nuanced differentiation of the enrichment values.
Reviewer #2, Comment #17: The data analysis method for generating relative enrichment shown in the heatmap is not explained. This should be described in the method section for a better understanding of the data analysis.
Our Response: We have edited the methods section as follows to better explain the analysis:
"For time resolved analysis, data were processed in R with custom scripts. Briefly, TMT abundances across chase samples were normalized to Tg TMT abundance as described previously and compared to (-) Hpg samples for enrichment analysis (Wright et al, 2021). For relative enrichment analysis, the means of log2 interaction differences were scaled to values from 0 to 1, where a value of 1 represented the time point at which the enrichment reached the maximum, and 0 represented the background intensity in the (-) Hpg channel. Negative log2 enrichment values were set to 0 as the enrichment fell below the background."
Reviewer #2, Comment #18: There are no legends of flowcharts in Figure 2A and Figure 3A and it is difficult to understand which are the key components in the complex and what are the differences among different periods of labeling.
Our Response: We have now consolidated Fig 2A and Fig 3A into a single panel found in Fig 2A, which is significantly reorganized to better explain the TRIP workflow. The caption has additionally been updated to highlight key steps within the workflow with numbering to allow readers to follow and visualize the steps more easily. The figure caption now reads as follows:
"(A) Workflow for TRIP protocol utilizing western blot or mass spectrometric analysis of time-resolved interactomes. (1) Cells are pulse-labeled with Hpg (200μM final concentration) for 1 hr, chased in regular media for specified time points, and cross-linked with DSP (0.5mM) for 10 minutes to capture transient proteoastasis network interactions; (2) Lysates are functionalized with a TAMRA-Azide-PEG-Desthiobiotin probe using copper CuAAC Click reaction; (3) Lysates undergo the first stage of the enrichment strategy where the Tg-FT is globally captured and enriched using immunoprecipitation; (4) Eluted Tg-FT populations from the global immunoprecipitation undergo biotin-streptavidin pulldown to capture the pulse Hpg-labeled, and CuAAC conjugated population of Tg-FT, enriching samples into time-resolved fractions; (5) Time-resolved fraction may then undergo western blot analysis or (6) quantitative liquid chromatography - tandem mass spectrometry (LC-MS/MS) analysis with tandem mass tag (TMTpro) multiplexing or analysis. The (-) Hpg control channel is used to identify enriched interactors and a (-) Biotin pulldown channel to act as a booster (or carrier)."
Reviewer #2, Comment #19: Why did only one of the VCP inhibitors (ML-240) exhibit a phenotype in Tg abundance and secretion, but not the other VCP inhibitors?
Our Response: Please also see our response to Reviewer #3, comment 2 below. This could be due to a number of reasons, but we added a brief discussion on the mechanisms of action for the inhibitors that may at least partially explain the differences in phenotype seen with the VCP inhibitors. We updated the text as follows:
"ML-240 and CB-5083 are ATP-competitive inhibitors that preferentially target the D2 domain of VCP subunits, whereas NMS-873 is a non-ATP-competitive allosteric inhibitor which binds at the D1-D2 interface of VCP subunits (Chou et al, 2013, 2014; Anderson et al, 2015; le Moigne et al, 2017; Tang et al, 2019). ML-240 and NMS-873 have been shown to decrease both proteasomal degradation and autophagy, in line with VCP playing a role in both processes (Chou et al, 2013, 2014; Her et al, 2016). Conversely, while CB-5083 is known to decrease proteasomal degradation it has been shown to increase autophagy. (Anderson et al, 2015; le Moigne et al, 2017; Tang et al, 2019)."
Reviewer #2 (Significance (Required)):
Reviewer #2, Comment #20: __The authors __describe a novel and elegant method to map time resolved protein interactions of newly synthesized proteins, which allows monitoring of proteins regulating protein quality control.
Authors describe it as a general method, however, they only demonstrate the applicability to one protein and do not systematically evaluate the quantitative nature of their approach by determining quantitative reproducibility, which would be necessary to be able to claim that this is a method with broad applicability.
Given my expertise in quantitative proteomics, I can mainly comment on the technological aspects of the proteomics part of the manuscript, but do not feel qualified to evaluate the significance of this study in terms of novel biology. Nevertheless, it feels that there is a stronger emphasis on the biology in the current form of the manuscript which will raise interest of scientists with a focus on protein quality control and Tg biology.
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
Provide a short summary of the findings and key conclusions (including methodology and model system(s) where appropriate). Please place your comments about significance in section 2.
In this manuscript, the authors describe their efforts to develop a methodology for determining time-resolved protein-protein interactions using quantitative mass spectrometry. With TRIP (time-resolved interactome profiling), they combine a pulsed bio-orthogonal unnatural amino acid labelling (homopropargylglycine, Hpg), CuAAC conjugation and biotin-streptavidin pulldowns to enrich at different timepoints and time-resolve by combining TMT labelling and LC-MS/MS (Figure 1). This technique is then applied to the maturation of the secreted WT and mutant thyroglobulin (Tg-WT, Tg-C1264R, Tg-A2234D) expressed in HEK293 and rat thyroid cells (FRT) and linked to hyperthyroidism. There, they identify a collection of ER resident proteins involved in protein folding/processing (e.g. chaperones, redox, glycans, hydroxylation) as well as degradation (e.g. autophagy, ERAD/proteasomes) (Fig. 2). Here the authors effectively use pulse-labelled form of TRIPs to highlight the different interactions formed with Tg-WT vs. Tg-mutants during biogenesis and secretion (or retention). The analysis found ~200 new interactions compared to previous studies along with about 40% of those identified previously. Differences in interactions were observed for mutants, which shown extended interaction with chaperones and redox processing pathways. While many interactions appeared as might be expected, the identification of membrane protein processing elements (e.g. EMC, PAT) was puzzling and raised some questions about the specificity within the protocol. Mutants enriched for CANX CALR and UGGT, suggesting prolonged association with glyco-processing factors. Interaction of C1264R with the ER-phagy factors CCPG1 and RTN3 was greater than WT. The authors note that their interaction correlated with that of EMC1 & 4, but it is not clear why that might be.
With interactors in hand, the authors complemented the TRIP protocol with siRNA KD of identified factors, to investigate any changes to secreted vs intracellular Tg upon loss. KD of NAPA (a-SNAP) and LMAN1 increased WT lysate (intracellular) Tg but not mutants. NAPA also reduced Tg-WT secretion. In contrast, KD of NAPA increased A2234D secretion while LEPRE1 increased C1264R (but not A2234D or WT), suggesting mutants have differential processing paths and requirements. KD of VCP increased secretion of both mutants. Some ER-phagy receptors were found among interactors (e.g. RTN3 in Tg-C1264R only) but often their KD had no impact on secretion (CCPG1, SEC62, FAM134B). NAMA observations were recapitulated in thyroid derived cell line (FRT). KD of TEX264 and VCP increased Tg-C1264 secretion while RTN3 KD in FRTs decreased Tg-C1264 secretion. This was in contrast to data from HEK293s for reasons that are not clear. Co-IP with TEX264 enriched for all Tg forms but more so for C1264R and A2234D - motivating the authors to propose selective targeting of Tg to TEX264 and the consideration of ER-phagy as a "major" degradative pathway during Tg processing.
Given the observations with siRNAs to VCP, the authors next use a selection of VCP inhibitors to ask whether secretion can be rescued upon pharmacological impairment of the AAA ATPase. They observed that ML-240, but interestingly not the more conventionally used CB-5083 or NMS-873, increased secretion of Tg-C1264R but not lysate. Inhibitors increased lysate but decreased the secreted fraction for Tg-WT (Fig 7). Finally, the authors used TRIP again in ML-240 treated Tg-C1264R expressing cells to look for changes to interactome with treatment - observed decreases to glycan and chaperone interactions, CANX and UGGT1, decreased interaction with DNAJB11 and C10, like that of WT. There was no apparent change to the UPR, although activation was not directly measured.
Major comments:
Reviewer #3, Comment #1: __Are the key conclusions convincing? __The TRIP methodology appears to be quite robust and should be a powerful strategy for this field and others going forward. The drawback will be the length of pulse required will limit the number/type of proteins to be monitored to ones with longer t1/2's. There were interesting interactions found with Tg and the mutants linked to hyperthyroidism, but cut and dry differences did not appear as obvious, even though strong "trends" appear to be present. The path from identifying interactors in a time-resolved manner to then following them up with targeted KD does provides some clarity, which is important.
Our Response: We thank Reviewer #3 for their time in reviewing our manuscript and providing this positive feedback. We have enhanced our analysis of the TRIP data to more clearly highlight difference in time profiles between WT and mutant variants. Please see our response to Reviewer #2, comment 1 & 3. We also highlight the limitations of the time resolution in the discussion (see also Reviewer #2, comment 6):
"To address this, we utilized a labeling time of 1 hr which allows us to generate a large enough labeled population of Tg-FT for TRIP analysis, but some early interactions are likely missed within the TRIP workflow. In the case of mutant Tg, performing the TRIP analysis for much longer chase periods (6-8 hrs) may provide insightful details to the iterative binding process of PN components that is thought to facilitate protein retention within the secretory pathway."
We have addressed all further comments below.
__Reviewer #3, Comment #2: __Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether? The data regarding VCP silencing and pharmacological impairment appear clear but leave some questions outstanding in this reviewer's opinion. The lack of effect with the 2 highly selective inhibitors suggests that the underlying mechanism for switching fate of intracellularly retained Tg-C1264R towards secreted forms is not at all clear. ML-240 is an early derivative of DBeQ and reportedly impairs both ERAD and autophagic pathways, similarly to DBeQ. The differences between the VCP inhibitors' mechanism of action were not discussed, but perhaps should be elaborated upon, particularly in the matter of how ERAD and ER-phagy pathways might be being differentially affected. At the risk of asking for too many additional experiments, this reviewer would just prefer to see this fleshed out in a bit more detail.
Our response: We agree with Reviewer #3 that the underlying mechanism for switching fate of the intracellular retained Tg-C1264R towards secreted forms remains unclear. We have added additional text to discuss further the details surrounding the inhibitors used and the general manner in which ERAD and ER-phagy pathways can be affected. This added text reads as follows:
"ML-240 and CB-5083 are ATP-competitive inhibitors that preferentially target the D2 domain of VCP subunits, whereas NMS-873 is a non-ATP-competitive allosteric inhibitor which binds at the D1-D2 interface of VCP subunits (Chou et al, 2013, 2014; Anderson et al, 2015; le Moigne et al, 2017; Tang et al, 2019). ML-240 and NMS-873 have been shown to decrease both proteasomal degradation and autophagy, in line with VCP playing a role in both processes (Chou et al, 2013, 2014; Her et al, 2016). Conversely, while CB-5083 is known to decrease proteasomal degradation it has been shown to increase autophagy. (Anderson et al, 2015; le Moigne et al, 2017; Tang et al, 2019)."
"As we discovered that pharmacological VCP inhibition with ML-240 can rescue C1264R Tg secretion yet is detrimental for WT Tg processing, it is unclear whether VCP may exhibit distinct functions for WT and mutant Tg PQC. Finally, as ML-240 is shown to block both the proteasomal and autophagic functions of VCP it is unclear which of these pathways may be playing a role in the rescue of C1264R, or detrimental WT processing (Chou et al, 2013, 2014)."
__Reviewer #3, Comment #3: __Q1. The degree (if any) of Tg-C1264 aggregation during and/or detergent solubility do not appear to have been considered as a potential source of the increase in released secreted material (Figure 4, 5). Do Tg mutants partition into RIPA-insoluble fractions at all? That is to say.. is the total population of synthesized Tg being considered? A full accounting? Could the authors address this and if biochemical extraction data (via urea or high SDS) is available, include it to answer this concern.
Our response: The transient aggregation of Tg has been investigated in some detail previously (Kim et al, 1992, 1993). The transient aggregates have the ability to partition into RIPA-insoluble fractions. Of note, these aggregates are shown to be made up, at least in part, of mixed disulfide linkages requiring reducing agent to fully resolubilize. With that being said, these aggregates represent a minority of the overall Tg population. In our prior manuscript (Wright, et al. 2021), we quantified the RIPA-insoluble fraction found in the pellet (see Supplemental Info Fig. 5). As the majority of Tg remains soluble during processing it should be able to be captured via our TRIP methodology. That is to say, we are capturing most of the Tg that is available for analysis while understanding that some smaller population of Tg remains in RIPA-insoluble fractions.
__Reviewer #3, Comment #4: __Q2. Along the same lines, what does Tg-WT and mutant expression look like by microscopy? Is Tg-WT uniformly distributed while Tg-mutants appear in puncta... more aggregated - perhaps reflecting the increased engagement of chaperones and redox machinery? Changes in the pattern of Tg-C1264R mutant (e.g. w/ VCP KD or inhibition) would add additional support for the authors interpretation of improved secretion. If this data is at hand, including it might be worth consideration.
Our response: Thank you for this suggestion. The subcellular localization of Tg and any changes from proteostasis modulation is an ongoing area of follow up work in our lab. We have some preliminary results that the localization for WT and C1264R Tg indeed differs. However, given that this manuscript is already dense in information, we opted to reserve this data for a future manuscript where we plan to further elucidate the targeting mechanism of mutant Tg to VCP or TEX264. We direct the reviewer to work published by Zhang et al, 2022,(https://doi.org/10.1016/j.jbc.2022.102066) showing a staunch difference of WT vs mutant Tg in the localization from intracellular to a secreted population in rat tissue. While most all WT Tg is found in the follicular lumen (secreted), mutant Tg heavily co-localizes with the ER resident chaperone BiP. While this paper does not go into detail on the differences in subcellular localization, it further highlights the drastic changes in Tg processing and how these manifest in distinct differences in localization within tissue.
__Reviewer #3, Comment #5: __Q3. Does the level of Tg mutant expression in the FRT clones impact the profiles obtained by TRIP? (Figure 3). This is a question of gauging the relative saturation of QC machinery and how that might impact profiles from TRIP. Were clones expressing at different levels tested? Perhaps a brief discussion of this.
Our response: We do not foresee an impact from level of Tg expression on the profiles obtained by TRIP. We were able to identify distinct profiles because we processed the data and normalized it based on the relative Tg amount. For example, while WT and A2234D Tg are expressed at similar levels intracellularly, we were able to identify distinct differences in the interaction profiles across the two constructs. When developing FRT clones, we selected those that were expressed at similar levels and, therefore, did not have the capability to directly test differences, if any, in observed profiles that may be the result of different expression levels of the same Tg construct. Furthermore, Tg can make up 50% of all protein content within thyroid tissue (Di Jeso & Arvan, 2016). As such, thyroid cells are adept at maintaining the balance of QC machinery to process thyroid. Therefore, we do not anticipate that the amount of Tg expressed in TRIP experiments would have a significant impact on the profiles that we were able to observe.
__Reviewer #3, Comment #6: __Q4. For Figure 3, the hour-long labelling period seems a bit long, compared with 3 hr of chase. Perhaps this reviewer missed this but how long does Tg take to mature and/or mutants to misfold and degrade? Is there any possibility to shorten this so that the profiles of labelled Tg could be more synchronized? If not, perhaps this could just be discussed.
Our response: While the 1-hour labeling period may seem long, we had to balance the labeling time to 1) label a large enough population of Tg for it to remain detectible throughout the chase period, and 2) keep the chase period long enough to capture the large majority of Tg processing. In our hands we found that by 4 hours WT Tg was ~63% secreted, with ~25% retained intracellular (Fig EV7H). Conversely, we found that C1264R remains very stable over this period with most protein being retaining intracellularly and little degradation taking place (Fig EV9A). Hence, we opted for the overall ~4 hour total for sample processing (1 Hr pulse labeling + 3 hour chase period for time point collections). Literature suggest that WT Tg takes ~2 hours to be processed within the ER and reach the medial golgi. This is exemplified by the EndoH resistant population that appears at this ~2 hour time point (Menon et al. JBC. 2007). Please also see our response to Reviewer #1, comment 6. We updated the text as follows:
"We pulse labeled WT Tg FRT cells with Hpg for 1 hr, followed by a 3 hr chase in regular media capturing time points in 30-minute intervals and analyzing via western blot or TMTpro LC-MS/MS (Fig 2A). Our previous study indicated that ~70% of WT Tg-FT was secreted after 4 hours, while approximately 50% of A2234D and 15% of C1264R was degraded after the same time period (Wright et al, 2021). Therefore, we reasoned that a 3-hr chase period would be a enought time to capture the majority of Tg interactions throughout processing, secretion, cellular retention, and degradation, while still being able to capture an appreciable amount of sample for analysis."
We anticipate that this labeling period can be decreased with future iterations of this methodology. This will also be bolstered by the continued improvements that come about within quantitative proteomics in increased instrument sensitivity and improved sample preparation methods that have the ability to decrease sample loss.
We explain the labeling timeline and limitations further in the discussion:
"To address this, we utilized a labeling time of 1 hr which allows us to generate a large enough labeled population of Tg-FT for TRIP analysis, but some early interactions are likely missed within the TRIP workflow. In the case of mutant Tg, performing the TRIP analysis for much longer chase periods (6-8 hrs) may provide insightful details to the iterative binding process of PN components that is thought to facilitate protein retention within the secretory pathway."
__Reviewer #3, Comment #7: __Q5. It is curious that only ML-240 and not other well characterized inhibitors of VCP/p97, has an effect, as both are used far more often than ML-240. The authors do not really address this in detail but does it suggest that the ML-240 effect on VCP/p97 could be affecting different pathways, given the nature of this compound. Is this compound acting on Tg-C1264R maturation at the level of translation or post-translationally? If the latter, through what means?
Our Response: We thank Reviewer #3 for appreciating this surprising finding. We were similarly curious as to how, or why ML-240 was able to elicit this effect compared to other VCP inhibitors. We elaborated in the manuscript text on these compounds and on how the ERAD and ERphagy pathways, utilizing VCP, may be differentially regulated (See response to__ Reviewer #3, Comment 2__). While speculative, we believe that ML-240 acts on C1264R Tg maturation post-translationally. This is given by the fact that ML-240 does not seem to affect the translational velocity of C1264R Tg, as Fig EV9A shows similar levels of 35S-labeled C1264R in DMSO or ML-240 treated cells. It may be the case that acute treatment with ML-240 alters the folding vs degradation balance of the ER proteostasis network in such a way that some population of C1264R that is usually degraded is able to be secreted. Another Tg mutation G2320R was shown to be degraded via the proteasome in PLCCL3 thyrocytes, as MG-132 treatment slowed mutant Tg degradation (Menon et al. JBC. 2007), although G2320R degradation was not be exclusively proteasomal. The L2284P Tg mutation exemplified similar results to G2340R where MG-132 slowed degradation. Furthermore, L2284P Tg was not affected by autophagic/lysosomal inhibitors chloroquine and E64 (Tokunaga et al. JBC. 2000), suggesting ERAD more exclusively degrades L2284P. It is unclear which degradation pathway, ERAD or ER-phagy, may be the predominate pathway for C1264R Tg degradation. Furthermore, we do not exclude the possibility that both may be at play and affected by treatment with ML-240.
We utilized our HEK293 Tg-NLuc cells and screened other proteasomal and lysosomal inhibitors bafilomycin and bortezomib. Neither of these compounds were able to rescue A2234D or C1264R secretion, highlighting that the effect is specific to ML-240 treatment. This new data is now shown in __Fig EV10A,B __and described in the text:
"To understand whether this rescue in secretion was uniquely linked to VCP inhibition or could be more broadly attributed to blocking Tg degradation, we tested the proteasomal inhibitor bortezomib, and lysosomal inhibitor bafilomycin. Bafilomycin increased WT Tg lysate abundance, and bortezomib significantly increased A2234D lysate abundance, consistent with a role of these degradation processes in Tg PQC (Fig EV10A). When monitoring Tg-NLuc media abundance, neither bafilomycin nor bortezomib significantly altered WT, A2234D, or C1264R abundance (Fig. EV10B). confirming that general inhibition of proteasomal or lysosomal degradation does with rescue mutant Tg secretion."
__Reviewer #3, Comment #8: __Q6. Continuing from Q5.. At what point and where is VCP/p97 able to affect mutant Tg processing? In line 317, the authors seem to correlate increased VCP association with mutants to their increased secretion. It is not clear how this would result, as engagement with VCP would be in a compartment different to that which supports trafficking and secretion. Could the authors expand on how this might come about. This is also relevant to the ML-240 data in Figure 7. Moreover, VCP is associated with ERAD (as is HerpUD1) rather than ER-phagy and at least in the siRNA raw data, there are also effects from Derlin3 and FAF2 KDs.. both ERAD factors. Some clarity here would be appreciated.
Our Response: This line of discussion in the text was meant to suggest that, since VCP showed a higher enrichment for mutant Tg, particularly C1264R, it would make sense that inhibiting VCP would have a larger effect on mutant Tg processing as compared to WT Tg. As we saw with the siRNA screening data, suppression of VCP resulted in increased C1264R secretion, while not affecting WT Tg processing. This passage was not intended to suggest that increased VCP association with mutant Tg found within the TRIP dataset was the reason for rescued secretion. These are two different sets of experiments and environments in which these data are captured. We were simply looking for the opportunity to bridge the findings from the two sets of experiments to a single discussion point. Of note, we understand that VCP is associated with ERAD and acts to regulate autophagy. Given that core autophagy machinery is relevant for both bulk autophagy and ER-phagy, we did not want to rule out the fact that VCP inhibition via ML-240 could affect autophagic flux in these experiments (Chou et al. Chemmedchem. 2013; Khaminets et al. Nature. 2015; Hill et al. Nat. Chem. Bio. 2021.)
It is great that the reviewer also noted that DERL3 and FAF2 knockdown increased C1264R Tg secretion. Since these ERAD factors did not reach the defined threshold in the screen, we did not include further discussion, but this data remains available in Appendix Fig S3. We have updated the manuscript text to clarify the previous points we aimed to make. The text now reads as follows:
"VCP silencing exclusively affecting mutant Tg corroborates our TRIP dataset, and suggest a more prominent role for VCP in mutant Tg PQC compared to WT. VCP interactions were sparse for WT Tg while they remained more steady throughout the chase period for the mutants (Fig 3H,K)."
__Reviewer #3, Comment #9: __Q7. There does not appear to be a direct demonstration of Tg-C1264R turnover by ER-phagy (via TEX264). Given the inconsistency with it not being detected by TRIP, while another receptor RTN3 was, but has not impact on Tg-C1264R secretion, perhaps including that data would go some way to demonstrating a fate of ER-phagy (at least partly) for this mutant.
Our response: We performed follow-up experiments to test interactions with Tg and the wider panel of ER-phagy receptors. We transiently expressed FLAG-tagged CCPG1, RTN3L, and TEX264 in HEK293 cells stably expressing Tg-NLuc and performed FLAG IPs followed by western blot analysis. We found that WT and C1264R Tg were enriched, albeit modestly, in the RTN3L Co-IP compared to control samples expressing GFP. Additionally, we found that WT, A2234D, and C1264R Tg were all enriched with CCPG1 compared to control samples expressing GFP. CCPG1 was found to be a C1264R Tg interactor within our mass spectrometry datasets, along with RTN3. We have now integrated these data into the manuscript as Fig EV8, and updated the manuscript text as follows:
"Additionally, we monitored Tg enrichment with ER-phagy receptors CCPG1 and RTN3 via Western blot as both were found to be C1264R Tg interactors within our TRIP dataset. RTN3L is found to be the only RTN3 isoform involved in ER turnover via ER-phagy (Grumati et al, 2017). WT and C1264R Tg-NLuc were modestly enriched with RTN3L compared to control samples expressing GFP. Conversely, we found that all Tg variants exhibited modest interactions with CCPG1 compared to control samples expressing GFP, although less than with TEX264 (Fig EV8).
Together, these data suggest that TEX264, CCPG1, or RTN3L engage with Tg during processing, and CH-associated Tg mutants may be selectively targeted to TEX264. Furthermore, ER-phagy may be considered as a degradative pathway in Tg processing, as other studies have mainly focused on Tg degradation through ERAD (Tokunaga et al, 2000; Menon et al, 2007)."
Whether the TEX246 recruitment of mutant Tg leads to degradation remains to be tested. When we monitored C1264R Tg degradation by pulse-chase assay (Fig. EV9A), only a small fraction (
__Reviewer #3, Comment #10: __Q9. The authors provide data that the UPR was not induced by ML-240 at 3hrs (10µM) (Figure 7, supplemental 1). This is in stark contrast to the results of Chou et al (2013) which the authors reference, reporting that ML-240 induced ATF4 and CHOP by 2 hrs at concentrations lower than used here (albeit a different cell type). While not exclusively UPR, could the authors address the potential activation of the integrated stress response (eIF2a phosphorylation, ATF4 and CHOP) in the FRT cells due to ML-240 treatment? If present, is there some link that could this provide an explanation for increased Tg-C1264R secretion? [Basal PERK/UPR activation with mutants.]
Our Response: Thank you for bringing up this important point. As the reviewer acknowledges, the difference in UPR activation could stem from the different cell lines. Additionally, we measured activation via qPCR, whereas Chou et al. measured via immunoblot. We would like to point out that while we did not observe the upregulation of HSPA5 or ASNS (markers of ATF6 and PERK/ISR activation, respectively) in the presence of short ML-240 treatment (2-3 hr), we did observe the upregulation of DNAJB9 (a marker of IRE1/XBP1s activation).
To address Reviewer #3's point, we performed further experiments monitoring the potential activation of the ISR in FRT cells due to ML-240 treatment. We treated C1264R Tg-FT FRT cells with ML-240 (10μM) for 2 hours, and monitored eIF2a phosphorylation via immunoblot. Indeed, we observed that ML-240 induced eIF2a phosphorylation compared to cells treated with DMSO. Tunicamycin (1mg/mL) was used a positive control, and showed similar results to ML-240. We have integrated these results into the manuscript, available in Fig EV10C.
However, we would like to point out that all of these markers represent signs of early UPR inductions. Importantly, our results that HSPA5 transcript levels are not induced suggest that there is only very modest upregulation of ER chaperone levels occurring. Typically, the ER proteostasis network remodeling requires a longer time than the acute 2-4 hr treatment with ML-240. We have updated the manuscript text as follows:
"Finally, we monitored activation of the unfolded protein response (UPR) in the presence of ML-240 in FRT cells expressing C1264R Tg-FT. Phosphorylation of eIF2a, an activation marker for the PERK arm of the UPR, was induced within 2 hr of ML-240 treatment (Fig EV10C). We further investigated the induction of UPR targets via qRT-PC. HSPA5 and ASNS transcripts, markers of ATF6 and PERK UPR activation respectively, remained unchanged or slightly decreased after 3 hr treatment with ML-240 in C1264R Tg cells (Fig EV10D). Only DNAJB9 transcript expression showed a significant increase in both WT Tg and C2164R Tg FRT cells (Fig EV10D). Moreover, ML-240 did not significantly alter cell viability after 3 hr, as measured by propidium iodide staining (Fig EV10E). Overall, these results highlight that the short ML-240 treatment induces early UPR markers, but the selective rescue of C1264R Tg secretion via ML-240 treatment is unlikely the results of global remodeling of the ER PN due to UPR activation."
__Reviewer #3, Comment #11: __Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments. Any of the suggested experiments above all use reagents reported in the manuscript and so would presumably incur minimal cost and hopefully time. This reviewer is sympathetic to time and financial constraints and so discussion of the issue could suffice.
Our response: We have addressed follow-up experiments whenever possible or provided further discussion details where applicable. We are appreciative of Reviewer #3's sympathy for the time and financial constraints that go into this work and addressing manuscript revisions. Unfortunately, the 1st and 2nd authors both left the lab immediately after the reviews were received. Hence, many of the experiments had to be addressed by other lab members joining the project, which took considerably longer than anticipated. We apologize for the long delay with our revisions.
__Reviewer #3, Comment #12: __Are the data and the methods presented in such a way that they can be reproduced? Yes. The methodology is explained in detail.
Our Response: Thank you.
__Reviewer #3, Comment #13: __Are the experiments adequately replicated and statistical analysis adequate? Yes. Relevant information is either in the figure legends or is provided in the source data.
Our Response: Thank you.
Minor comments:
__Reviewer #3, Comment #14: __Are prior studies referenced appropriately? The references are generally appropriate, with a few exceptions of more general references used
Our Response: Thank you.
__Reviewer #3, Comment #15: __Are the text and figures clear and accurate? The text is clearly written, and the figures are clear.
Our Response: Thank you.
__Reviewer #3, Comment #16: __Do you have suggestions that would help the authors improve the presentation of their data and conclusions? A summary figure comparing the changing profiles of WT and C1264R and the factors implicated for them could be helpful.
Our Response: We opted not to include a summary figure because the paper and figures area already dense in information.
__Reviewer #3, Comment #17: __Perhaps include common nomenclature for proteins as well (e.g. HSP5A - BiP, HSP90B1 - Grp94, etc..)
Our Response: We updated the manuscript throughout to reference common nomenclature or other protein names where applicable at their first mention.
__Reviewer #3, Comment #18: __Line 317 - our is misspelled
Our Response: Thank you. We have made this correction.
__Reviewer #3, Comment #19: __Figure 4 - Supplemental Figure 1 - Legend has text referring to panels J and K, but Figure only goes up to F.
Our Response: Thank you. This was an error in references to Figure panel lettering and we have since corrected this. Please note that this Figure is now Fig EV6.
Reviewer #3 (Significance (Required)):
__Reviewer #3, Comment #20: __
-
Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.
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Place the work in the context of the existing literature (provide references, where appropriate).
Protein-protein interactions are often used to illustrate complexes and functionality, but these provide only snapshots, rather than "movies". There are many datasets out there exploring P-P interactions, but most if not all lack any temporal resolution for the interactions they report. The TRIP method described approaches this from the dynamic perspective - identifying the transient interactions formed by folding nascent chains with proteins that aid in their maturation and trafficking, or degradation. This represents an important technical advance in our ability to dynamically monitor protein interactions. The use of Tg mutants is valuable and perhaps this will lead to new perspectives on how to rescue it or other pathophysiological mutants with loss of function phenotypes.
- State what audience might be interested in and influenced by the reported findings.
This work should appeal to a broad audience within cell biology, particularly as the TRIP technique is attempting to address a fundamental question - what interactions form during the biogenesis/lifetime of a protein. Moreover, the effort to try to understand the different interactions formed with pathologically relevant mutant proteins as a strategy to try to rescue functionality, is a valuable exercise of this approach.
- Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.
ER quality control
Our Response: We thank reviewer #3 for this positive endorsement.
Reviewer #4 (Evidence, reproducibility and clarity (Required)):
Summary
In this manuscript, Wright et al. developed an approach (termed TRIP) that allowed to map the temporal changes in the interaction landscape of a newly synthesized protein of interest. Using their TRIP approach, the authors found that the extensive interactions of thyroglobulin (Tg) with the proteostasis network (PN) during its passage through the secretory pathway were profoundly altered in response to disease-causing mutations (e.g. C1264R). The authors cross-validated their findings with a focus RNAi screen monitoring the cellular and secreted abundance of Tg variants upon deletion of PN components. In subsequent experiments the authors focused on two hits, VCP and TEX264, for which they confirmed their inhibitory effect on the secretion of Tg C1264R. Importantly, the authors found that TEX264 increasingly interacts with the Tg mutant and that pharmacological inhibition of VCP yielded the same phenotype than depletion of VCP. Overall, Wright and colleagues__ established an elegant method to map protein interaction in a time-resolved manner and demonstrated its value by the analysis of disease-related Tg mutants__. Hence, this work has the potential to serve as a rich resource for Tg-related research and as a powerful new tool to examine protein interactions. However, several concerns remain.
Our response: Thank you to reviewer #4 for their valuable feedback and positive assessment. We addressed all comments in detail below.
Major points:
__Reviewer #4, Comment #1: __Overall, the TRIP workflow is quite difficult to understand at a first glance - even for a reader with a background in proteomics, biochemistry and cell biology. The authors may want to improve the description of the TRIP methodology and explain in more detail what the individual components and steps are good for. Along the same line, from the main text and the figure legend it was not clear that Tg was actually Flag-tagged. However, without this information it is difficult to follow the workflow. While Figure 1A is certainly helpful, the bulky graphics are deflecting the reader's attention. A more schematic version might be more informative.
Our Response: Thank you for this feedback, which was also mirrored by Reviewer #2 (comment 10). We have made significant updates to clarify Fig 1 to provide more detail and eliminate some of unnecessary bulky graphics. We also expanded the schematic for the TRIP workflow in Fig 2A and we aligned all symbols used. Furthermore, we have edited the text to describe the workflow more clearly:
"To develop the time-resolved interactome profiling method, we envisioned a two-stage enrichment strategy utilizing epitope-tagged immunoprecipitation coupled with pulsed biorthogonal unnatural amino acid labeling and functionalization (Fig 1A). Cells can be pulse labeled with homopropargylglycine (Hpg) to synchronize newly synthesized populations of protein. After pulsed labeling with Hpg, samples can then be collected across time points throughout a chase period (Fig 1A, Box 1) (Kiick et al, 2001; Beatty et al, 2006). The Hpg alkyne incorporated into the newly synthesized population of protein can be conjugated to biotin using copper-catalyzed alkyne-azide cycloaddition (CuAAC) (Fig 1A, Box 2). Subsequently, the first stage of the enrichment strategy can take place where the client protein of interest is globally captured and enriched using epitope-tagged immunoprecipitation, followed by elution (Fig 1A, Box 3). The second enrichment step can then utilize a biotin-streptavidin pulldown to capture the Hpg pulse-labeled, and CuAAC conjugated population, enriching samples into time-resolved fractions (Fig 1A, Box 4) (Li et al, 2020; Thompson et al, 2019)."
Additionally, we have improved text to very clearly state that for the TRIP experiments Tg is FLAG-tagged and this epitope tag is required for the two-stage enrichment strategy. As one small example:
"Thyroglobulin was chosen as the model secretory client protein. We generated isogenic Fischer rat thyroid cells (FRT) cells that stably expressed FLAG-tagged Tg (Tg-FT), including WT or mutant variants (A2234D and C1264R) (Fig EV1)"
"Furthermore, the C-terminal FLAG-tag and Hpg labeling are necessary for this two-stage enrichment strategy, and DSP crosslinking is necessary to capture these interactions after stringent wash steps (Fig 1D, Fig EV2)."
__Reviewer #4, Comment #2: __To what extend do the difference in protein abundance between Tg WT and Tg C1264R contribute to the increase binding of their interactors (e.g., HSP5 and PDIA4). The authors should perform a TRIP coupled immunoblot analysis where WT and Mutant are loaded side-by-side on the SDS-PAGE.
Our Response: As Reviewer #3 (comment 5) had a similar inquiry, we provide the same response as listed above:
We do not foresee an impact from level of Tg expression on the profiles obtained by TRIP. We were able to identify distinct profiles because we processed the data and normalized it based on the relative Tg amount. For example, while WT and A2234D Tg are expressed at similar levels intracellularly, we ere able to identify distinct differences in the interaction profiles across the two constructs. When developing FRT clones, we selected those that were expressed at similar levels and, therefore, did not have the capability to directly test differences, if any, in observed profiles that may be the result of different expression levels of the same Tg construct. Furthermore, Tg can make up 50% of all protein content within thyroid tissue (Di Jeso & Arvan, 2016). As such, thyroid cells are adept at maintaining the balance of QC machinery to process thyroid. Therefore, we do not anticipate that the amount of Tg expressed in TRIP experiments would have a significant impact on the profiles that we were able to observe.
__Reviewer #4, Comment #3: __While the RNAi screen was done with pooled siRNA, it is not clear what was used for the RNAi validation experiments shown in Figure 5. This should be done by individual siRNA and not the same pooled reagents as used for the screen.
Our Response: Similarly, pooled siRNAs were initially utilized for the data shown in Figure 5. The RNAi screen utilized siRNAs optimized for human cells, where as those found for Figure 5 were for rat cells. For the revisions, we performed control experiments with individual siRNAs, which are now shown in Fig EV7J,K. While we did not find that any one single siRNA recapitulated the full phenotype, we did find that several single siRNAs for VCP and TEX264 at least partially restored the observed phenotype of increased C1264R Tg secretion. This result is expected given that we reasoned the siRNAs are likely providing an additive effect contributing to the observed phenotypes. We provided these single siRNA control experiments in Fig EV7J,K, and updated the manuscript text as follows:
"Several individual VCP and TEX264 siRNAs were able to partially recapitulate these increased secretion phenotype on C1264R Tg-FT, confirming that the effect is mediated by the respective gene silencing (Fig EV7J,K)."
Reviewer #4, Comment #4: __In Figure 5A it is not clear which band was used to quantify the effect of NAPA reduction. Also, this analysis lacks normalization to an unrelated protein or loading control. Moreover, the authors should also examine the effect of the siRNA targets shown in Figure 5C for Tg WT and not only the mutant.__
Our Response: The uppermost band in Fig 5A was used for quantification. We added a red asterisk similar to that found in Fig 5C to denote this lower back in the lysate panel(s) as a non-specific background band found within the Western blot. These data are the result of immunoprecipitations of both cell lysate and medium content, as such there is no applicable loading control that can be used within the western blots. For experiments, cell amounts were normalized by seeding and subsequently culturing the same amount of cells, as denoted within the Materials and Methods - FRT siRNA validation studies section of the manuscript. Furthermore, there are no loading controls that are easily utilized for analyzing cell culture medium. We have further clarified the Fig 5 caption to provide clearer experimental detail:
"(A and B) Western blot analysis (A) and quantification (B) of WT Tg-FT secretion from FRT cells transfected with select siRNAs hits from initial screening data set. Red asterisk denotes a non-specific background band within the western blot. Cells were transfected with 25nM siRNAs for 36 hrs, media exchanged and conditions for 4 hrs, Tg-FT was immunoprecipitated from lysate and media samples, and Tg-FT amounts were analyzed via immunoblotting. N = 6.
(C and D) Western blot analysis (C) and quantification (D) of C1264R Tg-FT secretion from FRT cells transfected with select siRNA hits from the initial screening data set. Red asterisk denotes a non-specific background band within the western blot. Cells were transfected with 25nM siRNAs for 36 hrs, media exchanged and conditions for 8 hrs, Tg-FT was immunoprecipitated from lysate and media samples, and Tg-FT amounts were analyzed via immunoblotting. All statistical testing performed using an unpaired student's t-test with Welch's correction. *pFinally, as the siRNA targets shown in Fig 5C were shown to be hits exclusively for C1264R Tg-FT we did not believe it was necessary to follow-up on these with WT Tg-FT. Similarly, we did not follow-up on hits that were exclusive to WT Tg-FT with C1264R and A2234D Tg-FT.
__Reviewer #4, Comment #5: __The authors should also test for the binding of RTN3 to Tg WT and mutant - in particular in comparison to TEX264. This would be important in the context that only RTN3 but not TEX264 was detected in the TRIP approach. Do the authors also detect VCP and LC3B in their pulldowns?
Our response: Please also see Reviewer #3, comment 9, who made a similar point.
We performed follow-up experiments to test interactions with Tg and the wider panel of ER-phagy receptors. We transiently expressed FLAG-tagged CCPG1, RTN3L, and TEX264 in HEK293 cells stably expressing Tg-NLuc and performed FLAG IPs followed by western blot analysis. We found that WT and C1264R Tg were enriched, albeit modestly, in the RTN3L Co-IP compared to control samples expressing GFP. Additionally, we found that WT, A2234D, and C1264R Tg were all enriched with CCPG1 compared to control samples expressing GFP. CCPG1 was found to be a C1264R Tg interactor within our mass spectrometry datasets, along with RTN3. We have now integrated these data into the manuscript as Fig EV8, and updated the manuscript text as follows:
"Additionally, we monitored Tg enrichment with ER-phagy receptors CCPG1 and RTN3 via Western blot as both were found to be C1264R Tg interactors within our TRIP dataset. RTN3L is found to be the only RTN3 isoform involved in ER turnover via ER-phagy (Grumati et al, 2017). WT and C1264R Tg-NLuc were modestly enriched with RTN3L compared to control samples expressing GFP. Conversely, we found that all Tg variants exhibited modest interactions with CCPG1 compared to control samples expressing GFP, although less than with TEX264 (Fig EV8).
Together, these data suggest that TEX264, CCPG1, or RTN3L engage with Tg during processing, and CH-associated Tg mutants may be selectively targeted to TEX264. Furthermore, ER-phagy may be considered as a degradative pathway in Tg processing, as other studies have mainly focused on Tg degradation through ERAD (Tokunaga et al, 2000; Menon et al, 2007)."
Regarding VCP, we can detect it routinely in our AP-MS experiment as presented previously (Wright et al. 2021), and here in Fig 3, Appendix Fig S1. However, we have not been able to detect interactions via western blot, which may be attributed to the increased sensitivity that LC-MS offers. We have not probed for LC3 interactions via western blot as we did not detect it by LC-MS either, but we identified several lysosomal and other autophagy-related components previously (Wright et al. 2021), and here shown in Appendix Fig S1 and Fig EV5C.
__Reviewer #4, Comment #6: __The effect of TEX264 depletion on Tg secretion should be confirmed by TEX263 KO experiments. Do the authors observe a similar increase in secreted Tg C1264R in BafA1- or SAR405-treated cells? Moreover, the authors should show that Tg C1264R is actually delivered to lysosomes using biochemical assays such as LysoIP or colocalization experiments.
Our response: To address this concern, we generated stable TEX264 knockout FRT cell lines by CRISPR, and probed several clones for their impact on Tg secretion. We found that TEX264 knockout did not recapitulate the increase in C1264R Tg secretion observed with transient siRNA knockout. While disappointing, these results are not necessarily surprising, considering that prolonged TEX264 knockout may lead the cell to adapt compensation mechanisms by modulating other proteostasis factors and/or autophagy machinery.
We performed experiments utilizing the autophagy inhibitor Bafilomycin A1, and have now included these results with the manuscript available in Fig EV10A,B. We found that BafA1 treatment led to the accumulation of WT Tg in the lysate but not for the C1264R Tg. We updated the manuscript text to accompany these data as follows:
"To understand whether this rescue in secretion was uniquely linked to VCP inhibition or could be more broadly attributed to blocking Tg degradation, we tested the proteasomal inhibitor bortezomib, and lysosomal inhibitor bafilomycin. Bafilomycin increased WT Tg lysate abundance, and bortezomib significantly increased A2234D lysate abundance, consistent with a role of these degradation processes in Tg PQC (Fig EV10A). When monitoring Tg-NLuc media abundance, neither bafilomycin nor bortezomib significantly altered WT, A2234D, or C1264R abundance (Fig. EV10B). confirming that general inhibition of proteasomal or lysosomal degradation does with rescue mutant Tg secretion."
These results raise the possibility that the mutant Tg interaction with TEX264 may not lead to active autophagic degradation of mutant Tg. This is also consistent with the slow degradation of C1264R Tg observed in the pulse-chase experiment in Fig EV9A. Whether the TEX246 recruitment of mutant Tg leads to degradation or assumes an alternative function, for example, intracellular sequestration, remains to be tested. Importantly, we have refrained from making claims in the manuscript that C1264R Tg is delivered to the lysosome but have presented data showing that it interacts with ER-phagy-related components and have further speculated on the possibility how autophagy could play a role in Tg processing.
Thank you for the LysoIP suggestion. Ongoing work in the lab is addressing this question and experiments suggested by the reviewer, but this is better reserved for a follow-up manuscript.
__Reviewer #4, Comment #7: __Figure 7A and 7C lack loading controls. The quantification shown in Figure 7B and 7D should be normalized to this control. Since VCP activity is often coupled to the of the proteasome, the authors should check whether blocking the proteasome yields a similar effect than ML-240.
Our Response: Like Fig 5A discussed above (Reviewer #4, comment 4), these data are the result of immunoprecipitations from cell lysate and medium. As a result, there is not applicable loading control that can be used within the western blots. For experiments, cell amounts were normalized by seeding and subsequently culturing the same amount of cells, as denoted within the Materials and Methods - FRT siRNA validation studies section of the manuscript and Material and Methods - VCP pharmacological inhibition studies.
Regarding the effect of proteasome inhibition, we tested whether bortezomib treatment can increase C1264R Tg secretion. We found that bortezomib led to a small but significant increase in A2234D Tg accumulation in the lysate, but did not increase secretion of Tg for WT or any of the mutant variants. This new data is shown in Fig EV10A,B. We updated the text as follow:
"To understand whether this rescue in secretion was uniquely linked to VCP inhibition or could be more broadly attributed to blocking Tg degradation, we tested the proteasomal inhibitor bortezomib, and lysosomal inhibitor bafilomycin. Bafilomycin increased WT Tg lysate abundance, and bortezomib significantly increased A2234D lysate abundance, consistent with a role of these degradation processes in Tg PQC (Fig EV10A). When monitoring Tg-NLuc media abundance, neither bafilomycin nor bortezomib significantly altered WT, A2234D, or C1264R abundance (Fig. EV10B). confirming that general inhibition of proteasomal or lysosomal degradation does with rescue mutant Tg secretion."
__Reviewer #4, Comment #8: __With regard to Figure 7 - Figure supplement 1: The authors should monitor the effect of ML-240 on Tg secretion such that WT and C1264R mutants are directly compared (side-by-side on the same immunoblot). Otherwise, it is difficult to claim that ML-240 rescues the secretion of the mutant.
Our response: The reviewer is referring to the S35 pulse-chase experiments now shown in Fig EV9. We would like to clarify that these images are not immunoblots but autoradiographs. Even though the samples for WT and C1264R Tg were loaded onto separate gels, the gels were imaged at the same time and are therefore directly comparable. Regardless, the more meaningful information that can be gleaned from these experiments are the absolute rates of protein secretion and degradation and how they change in response to ML-240 treatment. The scale in the quantifications (0 - 100%) is the same and corresponds to the total amount of WT or C1264R Tg that is labeled with 35S during the 30 min pulse. Importantly, we found that C1264R Tg-FT secretion is significantly increased in the presence of ML-240, changing from
__Reviewer #4, Comment #9: __How did ML-240 affect the ER-phagy components (in particular RTN3) in the TRIP analysis of Tg C1264R (Figure 7G-L)?
Our response: This is a great discussion point raised by reviewer #4. We have updated the manuscript text to discuss in more detail changes in interactions with degradation components, especially with proteasomal degradation machinery (Fig 7M,N). The manuscript text now reads as follows:
"The most striking interaction changes occurred with proteasomal degradation components, which remained steady until 1.5 hr, but then abruptly declined with ML-240 treatment at later time points (Fig 7M,N). This decline tracks with changes to the glycan processing machinery, highlighting that the coordination between N-glycosylation and diverting Tg away from ERAD may be a key to the rescue mechanism."
Minor points:
__Reviewer #4, Comment #10: __The candidate labeling in Figure 3 - Figure supplement 2 and 3 is too small und unreadable. The authors should provide a higher resolution of these figures or increase the font.
Our response: These figures are now in the Appendix and we have edited this figure to provide higher resolution.
Reviewer #4 (Significance (Required)):
Please see above
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Referee #2
Evidence, reproducibility and clarity
In the manuscript 'Time-Resolved Interactome Profiling Deconvolutes Secretory Protein Quality Control Dynamics' Wright et al. developed an approach for time-resolved protein protein interaction mapping relying on pulsed unnatural amino acid incorporation, protein cross linking, sequential affinity purification, and quantitative mass spectrometry named time-resolved interactome profiling (TRIP). The authors applied the TRIP method to compare the interactions of the secreted thyroid prohormone thyroglobulin (Tg) comparing the WT protein to secretion-defective mutations implicated in congenital hypothyroidism. They further employed an RNA interference screening platform (1) to investigate if (1) interactors identified via TRIP are functionally relevant for Tg protein quality control and (2) to identify factors that can rescue mutant Tg secretion. The screen was initially performed in HEK293 cells, but selected hits with a phenotype in HEK cells were then followed up in Fisher rat thyroid cells. Further functional validation was performed by pharmacologic inhibition of VCP, a hit from the RNAi screen with an effect on Tg lysate abundance and Tg secretion. While the authors present a comprehensive study including identification of protein-protein interactions using proteomics followed up by an RNA interference screen for functional validation, major comments need to be addressed for both the proteomics as well as the functional genomics aspects of the study (see comments below).
Major comments:
- The authors describe a new method for quantitative, temporal interaction mapping. The protocol involves two enrichment steps as well as several reactions including cross-linking of the samples as well as functionalization of the unnatural amino acids. Given all these steps, the authors should rigorously characterize the quantitative reproducibility of the experiment when performed in independent biological replicates. This is important because in the final quantitative MS experiment, the authors only use two biological replicates, which is too low especially for such an involved sample preparation procedure, which would expect to have a high variability between replicates. Given the low number of replicates and the unknown reproducibility of the quantification for this protocol, it is questionable at this point how reliable the quantification over the time course is.
- Compared to the previous dataset published last year, the authors discover an overlap in interactors, but also a huge discrepancy, with 96 previously identified interactors not detected in the current study, but 198 additional interactors identified. How do the authors explain the big differences between these datasets?
- For the temporal interaction analysis the authors describe differences in the temporal profiles of selected interactions comparing wt and mutant, however no statistical analysis is performed comparing wt and mutant interaction profiles across the time course. Furthermore the variability between the replicates for the temporal profiles is not shown and some of the temporal profiles appear to be noisy. A more rigorous statistical analysis should be performed including additional biological replicates to evaluate the changes over the time course, especially as the temporal interaction analysis is the novelty of this study.
- To functionally validate interactors derived from the TRIP analysis as well as to identify factors that can rescue mutant Tg secretion the authors developed an RNA interference screen. There are a number of aspects that need to be addressed/clarified for this part of the study.
- While the authors validate the stable cell lines expressing the nanoluciferase tagged Tg and the linearity of luminescence signal in lysate and media carefully, they do not validate their platform in combination with the RNAi knockdown strategy. The authors should select genes as positive controls that are expected to modulate Tg secretion and demonstrate that the knockout of these positive controls indeed results in changes in Tg secretion in their system.
- For the screen the authors select 167 Tg interactors and PN (Proteostasis network) related factors. This statement is very vague and the authors should clarify which genes were knocked down and which criteria were applied to narrow down the list of interactors and to select PN factors. The authors should therefore provide a supplementary table including all genes included in the screen, their source (were this derived from the initial study by Wright et al, from the current study or compiled from prior knowledge about PN), as well as their results from the screen based on luminescence in media and lysate. It is unclear how many of the selected factors are actually coming from the TRIP analysis.
- Only a small number of the 167 selected genes shows an effect on Tg abundance/secretion. How do the authors explain this result? Would we not expect that Tg interactors, especially those from the TRIP method which interact with the newly synthesized are more enriched for functionally relevant genes.
- The authors initially performed the screen in HEK293 cells and as a second step wanted to validate the hits from the HEK cells in more relevant Fisher rat thyroid cells. Indeed they could show that knockdown of NAPA increased WT TG in lysate and decreased WT Tg secretion. Furthermore, they further validated genes to modulate mutant Tg lysate and media abundance. The authors should perform a rescue experiment to demonstrate that the observed phenotype can be reversed through re-introduction of NAPA.
- One hit from this analysis was the ER-phagy receptor TEX264, while TEX264 was not identified in the TRIP data, is selectively increased the C1264R secretion, but not wt and the other Tg mutant. Following Co-IP data however revealed some interaction between the C1264R and to a lesser extent the A2234D mutant. How do the authors explain that TEX264 was missed in the TRIP dataset?
Minor comments:
- The workflow needs to be described clearer. For example, it should be better explained why the authors selected a two stage enrichment strategy, I assume that the first based on the Flag affinity tag is to purify the protein of interest and the second step based on the incorporation and functionalization of the unnatural amino acids to enrich for the newly synthesized fraction at specific time points after protein synthesis? These are critical steps for the method but the rationals are not well explained, neither in the text nor the figures captures all these steps of the method very clearly, which makes it really difficult for the reader to understand the individual steps of the method. Moreover, the structures in Figure 1 workflow are not clearly labeled, so that it is confusing which part represents which protein/molecule.
- Except for the general workflow shown in Figure 1, a more detailed workflow showing the experimental steps, such as the sample fractions with the following steps could be added so that the design of the method is clearer. Also the style of the workflows including Figure 1, Figure 2A, and Figure 3A are different. It would be helpful to make them the same style and make the Figure 2A as a zoom in or more detailed illustration on part of Figure 1.
- A summary of proteomics results of time course labeling after all enrichment steps, including the total number of identified proteins at different conditions and control would be helpful for having an overview impression on the proteomics results
- In Figure 2B, the WB for PDIA4 in the Biotin PD elution is missing. Why was the PDIA4 interaction missing for the time course analysis, but the interaction was captured in the initial test for Wt Tg (Figure 1D). Additionally, in this panel the Rhodamine Probe Gel shows inconsistencies at the time points 1.5 - 3h. Does this mean that the labeling did not work well for these conditions? As we would expect a consistent Rhodamine Probe signal at every time point.
- In Figure 2, why was there no WB results for the A2234D? In Figure 2D and 2E, at which time point are the changes significant compared to WT?
- All figure legends should indicate how many biological replicates were performed for each experiment represented in the figure.
- The heatmaps shown in Figure 3, Figure 3 - Figure Supplement 3, and Figure 7 are in the current form incomprehensible. The heatmaps depict the relative enrichment vs the control sample, which was scaled between 1 and -1. The color coding with 5 different colors from 1 to -1 is very confusing and should be changed to just two colors, one for positive and one for negative relative enrichment. I would also suggest changing the visualization of the heatmap showing the wt and mutants side by side, instead of stacked on top of each other for each individual protein.
- The data analysis method for generating relative enrichment shown in the heatmap is not explained. This should be described in the method section for a better understanding of the data analysis. There are no legends of flowcharts in Figure 2A and Figure 3A and it is difficult to understand which are the key components in the complex and what are the differences among different periods of labeling.
- Why did only one of the VCP inhibitors (ML-240) exhibit a phenotype in Tg abundance and secretion, but not the other VCP inhibitors?
Significance
The authors describe a novel and elegant method to map time resolved protein interactions of newly synthesized proteins, which allows monitoring of proteins regulating protein quality control. Authors describe it as a general method, however, they only demonstrate the applicability to one protein and do not systematically evaluate the quantitative nature of their approach by determining quantitative reproducibility, which would be necessary to be able to claim that this is a method with broad applicability.
Given my expertise in quantitative proteomics, I can mainly comment on the technological aspects of the proteomics part of the manuscript, but do not feel qualified to evaluate the significance of this study in terms of novel biology. Nevertheless, it feels that there is a stronger emphasis on the biology in the current form of the manuscript which will raise interest of scientists with a focus on protein quality control and Tg biology.
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Referee #1
Evidence, reproducibility and clarity
The authors report a mass spectrometry (MS)-based interactomics technique, time-resolved interactome profiling (TRIP), which allows for tracking temporal changes in the interactome of protein of interest. To show that TRIP can successfully deconvolute interactomes over time, they pulsed thyroid cells with homopropargylglycine (Hpg), immunoprecipitated the Hpg incorporated thyroglobulin (Tg) and its interacting proteins at different time points, and subjected the samples to tandem mass tag (TMT)-based quantitative MS analysis. The MS results show that WT and variant Tg proteins indeed associate with different proteostasis network factors in a differential manner over the course of time. In addition, they utilized an siRNA-based luciferase fusion assay to evaluate whether silencing each proteostasis network component changes the levels of Tg in both lysate and media. From the combination of the TRIP and siRNA-based assays, they found many hits, including hits implicated in protein degradation, VCP and TEX264, which they validated with multiple experiments.
I am overall quite positive and think this is an important study. But there are some meaningful points to consider.
Significant comments:
- Only two replicates of the main data (the TRIP-MS experiments) for this paper is problematic. Especially since the manuscript is supposed to be demonstrating and validating the new technique. Consistent with this concern, the relative enrichment profiles for some of the results were surprising. For instance, interaction with CCDC47 was tapering off but then at 3 h it suddenly reaches the maximum level of engagement. Is this a real finding or the variability in the method? Impossible to tell with two replicates. Presenting heat maps based on biological duplicates is also very problematic. It masks the error, which is large as can be seen in some of the panels showing individual proteins. In my view, triplicates and a clear understanding of the error in the technique should be required.
- The same concern arises for the high-throughput siRNA screen, which was performed only in duplicate for WT and A2234D.
- There are issues with some of the immunoprecipitation experiments: In Figure 1C, a negative control for FLAG IP is missing. In Figure 2B, I am curious why the band (Hpg -, chase time 0 h) is so faint for the first WB (IB for FLAG) - is Hpg treatment indeed leading to much more Tg present at 0 h? If so, that is a concern. Also, a negative control must be included (either plain cells or cells expressing fluorescent protein or a different epitope-tagged WT Tg). In this same figure, I am puzzled why the bands for 1.5-3 timepoints in Biotin PD elution, probed for Rhodamine, are very faint especially considering that in Figure 1D, the corresponding bands, which are 4 h after the pulse, look fine. It seems like the IP failed here?
Suggestion to consider:
This manuscript, supported by the title and abstract, mainly focuses on the presentation of the development and application of TRIP, which is highly significant. The story becomes less coherent and harder to follow as significant amounts of text/figures are dedicated to siRNA-based high throughput screening and follow-up. In addition, although the discovery of TEX264 as one of the hits is very interesting and exciting, TEX264 apparently was not a hit in the TRIP experiment and is pretty distracting from the main point of the paper highlighted in the abstract and title, therefore. The siRNA-based assay and follow-up studies could be a separate scientific story of their own. Especially considering my concerns on the number of replicates for both the TRIP and siRNA-based assay, it could be beneficial to actually split the manuscript into two and conduct more replicates of the -omic work, which should corroborate the exciting discoveries the authors have made.
Minor comments:
Throughout the manuscript, the authors have not defined what FT is; presumably it means FLAG tag.
The authors might discuss their rationale for choosing 0-3 hrs for their TRIP studies. That includes any relevant information about the half-life of WT versus variant Tg, whether the Hpg pulse time is short enough to avoid missing key features of the temporal interactome, and discussion of what would happen if the TRIP were performed at prolonged time points (e.g. 6-10 h).
Lines 68-69: the two citations should probably come one sentence earlier (at least Coscia et al 2020 is a structure paper).
Line 91: "(Figure 1A)" should follow the sentence "To develop the time-resolved..." to help readers better understand the system.
Line 101: Fisher should be Fischer
Line 131: Should be 1.5 hrs instead of 2 hrs.
Lines 135-136: I do not agree with the claim that HSPA5 profile looked similar for MS and WB. I do not see a peak for HSPA5 at 2 hrs in Figure 2D.
Line 186: The cited paper Shurtleff et al 2018 is missing in the reference list.
Line 188: I disagree with the authors' claim here because, at least for CCDC47, interactions with C1264R seem to come back at the 3 hr time point.
Line 203: I am not sure if P4HA1 can be included in the examples for showing distinct patterns for mutants compared to the WT according to their data in Figure 3H.
Line 216: The authors should add citations about the functions of STT3A and STT3B proteins.
Lines 248-251, "We found that interactions with these components...": this sentence should refer to Figure 3 - Figure Supplement 3 instead of Figure 3L and S4.
Lines 258-260, "Another striking observation was that the temporal profile of EMC interactions for C1264R correlated with RTN3, PGRMC1, CTSB, and CTSD interactions.": Please provide more evidence to support the potential correlation between different interaction profiles. Or the authors should move this sentence to the discussion section as it sounds speculative. This highlights the issue of only having duplicates, as well.
Line 340: As written, should cite more than one paper
Line 371: Should be Figure 4 - figure supplement 2
Line 1231: "Zhang et al 2018" needs to be removed
Line 1286: FRTR should be FRT
Figure 3E: Color used to highlight the three proteins (CCDC47, EMC1, EMC4) should match the color used in Figure 3 - Figure Supplement 3
Figure 4A: The bottom figure where lysate signal is inversely proportional to time is misleading because the authors are assessing steady-state level of proteins in this assay.
Figure 4 - Figure Supplement 1 caption: in (C), (F) should be (B). (K) should be (G) and I am not sure what the authors mean when they refer to (J) in caption of (G).
Figure 5 caption for (C and D): Need to specify the time that the samples were collected (8 hrs), as it seems different from A and B according to the main text.
Figure 5 - Figure Supplement 1: Data for HERPUD1 and P3H1 should be included.
Figure 5 - Figure Supplement 2B: Please mention in the caption how degradation is defined.
Significance
This manuscript is highly significant because the authors (1) designed and validated a new methodology for time-resolved interactomics study, (2) presented the dynamic changes in Tg interactome for WT and variants, and (3) discovered how proteins implicated in degradation pathways (e.g. VCP, TEX264, RTN3) can change the secretion profile of WT and mutant Tg proteins. With TRIP, the authors demonstrated that they could obtain valuable data that were previously not captured from steady-state interactomics studies (Wright et al. 2021; Figure 3M and Figure 3 - Figure supplement 4D-4I). Furthermore, the authors treated cells with VCP inhibitors and performed both 35S pulse-chase analyses and TRIP. These experiments provide valuable information to the field by (1) presenting a new method to rescue Tg secretion defect, and (2) demonstrating a broader applicability of TRIP. If the major comments above can be addressed I believe this is a tremendous contribution to the field.
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Reply to the reviewers
Compared to our initial submission to Review Commons, we have addressed all the reviewers' comments. We have extensively re-written the manuscript to make it clearer to a larger audience. In particular, we have transferred Figure EV1 to Figure 1 with more complete panels and included a scheme (Figure EV3) on the steps of D2R internalization which we measure with live cell imaging. We have added a new paragraph to the start of the Discussion to summarize our main conclusions and reordered the discussion on the possible mechanisms of membrane PUFA enrichment on D2R endocytosis. All the changes in the text are in red for easier comparison with the previous version.
As suggested by reviewer 1, we have performed additional experiments to test the specificity of the effects of PUFA treatments on D2R endocytosis, reinforcing the results shown in Figure 4 using feeding assays. We show with live cell TIRF imaging and the ppH assay that TfR-SEP endocytosis is not affected (Figure EV5) and that SEP-β2AR endocytosis and βarr2-mCherry recruitment to the plasma membrane are not affected (Figure EV6).
Reviewer #1
Evidence, reproducibility and clarity
*The manuscript, using different live and fixed cell trafficking assays, demonstrates that incorporation of poly-unsaturated, but not saturated, free fatty acids in the membrane phospholipids reduce agonist induced internalization of the D2 dopamine receptor but not the adrenergic beta2 receptors or the transferrin receptor. Pulsed pH (ppH) live microscopy further demonstrated that the reduced internalization by incorporation of free fatty acid was accompanied by a blunted recruitment of Beta-arrestin for the D2R.
I believe said claims put forward in the manuscript are overall well supported by the data and as such I do not believe that further experiments are necessarily needed to uphold these key claims. Also, the methodology is satisfactorily reported, and statistics are robust, although two-way Anova like used in Fig 1 seems appropriate for Fig 2 and 3*
We thank the reviewer for his/her positive assessment of our work. We have checked the statistical tests used for all our measures. For Figure 2 and 3 (now 3 and 4) we test for only one factor (PUFA treatment or not) so we ran ordinary one-way ANOVA using Graphpad Prism.
That said, I suggest that the fixed cell internalization experiments (Fig 2 and 3), which relate the effect on the D2R to B2AR and transferrin are revised. This is important since this is relevant to judge whether the effect is a general or a selective molecular mechanism since this is the one of the three assay which this comparison relies on. Alternatively, I suggest omitting this data and include the B2AR in the Live DERET assay and both B2AR and TfR in the ppH assay. Specifically, my concerns with the fixed cell internalization are: • The analysis is based on counting the number of endosomes, which is not necessarily equivalent to the number of receptors internalized
The number of puncta, as well as their fluorescence, is reported by the analysis program (written in Matlab2021 and available upon request). We chose to show number of puncta because they reflect more directly the number of labelled endosomes (in Figures 3 and 4). As shown in the figure below, we found slight but significant differences between groups for FLAG-D2R (88.6 % and 87.6 % of average fluorescence in DHA and DPA treated cells compared to control cells), (panel A), and no differences for FLAG-β2AR (panel B). We find a significant decrease in puncta fluorescence for transferrin uptake in cells incubated with DHA (but not DPA) relative to control cells (panel C). However, because we did not detect differences in the number of puncta or in the frequency and amplitude of endocytic vesicle creation events (see below), we still conclude that enrichment with exogenous PUFAs does not affect clathrin mediated endocytosis.
In conclusion, the most robust measure of endocytosis for this assay is the number of detected puncta per cell rather than their fluorescence.
- The analysis relies on fully effective stripping of the surface pool of receptors - i.e clustered surface receptors not stripped by the protocol will be assessed as internalized. It is often very difficult to obtain full efficiency of the Flag-tag stripping and this is somewhat expression dependent. • The protocol for the constitutive and agonist induced internalization is different and yet shown on the same absolute graph. Although I take it the microscope gain setting are unaltered between the constitutive and agonist induced internalization I don't believe the quantification can be directly related. This is confusing at the very least. More critically however, the membrane signal from the non-stripped condition of constitutive internalization will likely fully shield internalized receptors in the Rab4 membrane proximal recycling pathway leading to under-estimation of the in the constitutive endocytosis. I believe this methodological limitation underlies the massive relative difference in the constitutive endocytosis between panel 2A,B and 2C,D. For comparison, by a quantitative dual color FACS endocytosis assay, we have previously demonstrated the ligand endocytosis a ~4 fold increased over constitutive (in concert with Fig 2A,B here) (Schmidt et al 20XX). Importantly, high relative variability by this methodology could well shield an actual effect of incorporation of FFAs on the constitutive endocytosis. We thank the reviewer for pointing this difference in the protocol. As a matter of fact, we have not used acid stripping in all the conditions used for the uptake assays (Figures 3 and 4). We apologize for the confusion and we have clarified this point in the Methods section. In early experiments we compared conditions with or without stripping but we concluded from these experiments that indeed, the stripping was not complete. Moreover, we noticed early on that many cells treated with DHA or DPA did not have any detectable cluster (13 cells out of 58 quantified cells treated with DHA after addition of QPL, 12/56 cells treated with DPA, 0/68 for cells treated with vehicle). Stripping the antibody would have made these cells undetectable, biasing the analysis. Therefore, to make our results more consistent we decided to use non-stripping conditions. To detect endosomes specifically, we used a segmentation tool developed earlier (see Rosendale et al.* 2019). This tool is based on wavelet transforms which recognizes dot-like structures. In addition, we excluded from the cell mask the labelled plasma membrane by a mask erosion.
We agree the design of experiments was not aimed at comparing the effect of PUFA treatment on low levels of constitutive D2R endocytosis. This would require more sensitive assays and be addressed in subsequent studies.
'Optional' Also, it would be informative to see the ppH Beta-arrestin experiments with the B2AR to assess, whether the putative discrepancy between D2R and B2AR is upstream or downstream of the blunted Beta-arrestin recruitment. To the same point, it would be very informative to assess how the incorporation of the free fatty acids affect receptor signalling, which would also help relate the effect of incorporation of the FFA's in the phospholipids to previous experiment using short term incubation with FFA's
We have now performed live imaging experiments in HEK293 cells expressing SEP-β2AR, GRK2 and βarr2-mCherry and stimulated with isoproterenol (Figure EV6). We show that the clustering of SEP-β2AR, of βarr2-mCherry, as well as endocytosis, are not affected by treatments with DHA or DPA. In this study, we focused on the early trafficking steps of D2R internalization. It will be interesting in a future study to address its consequences on G protein dependent and independent signaling. Moreover, and for good measure, we performed experiments to assess TfR-SEP endocytosis with the ppH assay. Again, we found no difference between cells treated or not with PUFAs (Figure EV5)
*References overall seem appropriate although Schmidt et al would be relevant for reference of the constitutive vs agonist induced endocytosis of D2R and B2AR. *
We have now cited Schmidt et al. 2020 doi 10.1111/bcpt.13274 in the discussion with the following sentences: "D2R also shows constitutive endocytosis (Schmidt et al, 2020) which may be modulated by PUFAs although we did not detect any significant difference in our measures (see Figure 3) which were aimed at detecting high levels of internalization induced by agonists. Further work will be required to specifically examine the effect of PUFAs on constitutive GPCR internalization."
Overall, the figures are well composed and convey the messages fairly well. Specific point that would strengthen the rigor include: • Chosing actual representative pictures of the quantitative data in Fig 2 and 3 (e.g. hard to see 25 endocytic events in Fig 2A constitutive endo, EtOH)
We apologize for the confusion. We employ a normalization procedure to account for cell size. In addition, all numbers have been normalized to the condition stimulated with agonist with no PUFA treatment). In fact, we detect in unstimulated cells very few puncta (on average 0.6, range 0-5) compared to 27.3 clusters (range 2-87) in cells stimulated with QPL.
- Showing actual p values for the statistical comparisons* For easier reading, we have kept the stars convention for the figures but added two tables with all statistical tests and the p values for both main figures and EV figures.
Moreover, for ease of reading the figures (without consulting the legend repeatedly) it would be very helpful to headline individual panel with what the experiments assesses. Figure 1a and 1b for example can't be distinguished at all before reading the figure legend. Also, y-axis could be more informative on what I measured rather than just giving the unit.
We have added titles to panels (in particular for Figure 2A,B which correspond to former Figure 1A,B) and we have given new titles to Y axes to make them clearer. We hope that the reading of our figures will now be easier.
Finally, the figure presentation and description of S1 is very hard to follow. I cannot really make out what is assessed in the different panels.
We have changed substantially Figure EV1 (now Figure 1) with new presentation of data: all 4 conditions (control, treated with DHA, DPA or BA) systematically presented in the same graph, and clearer titles for the parameter displayed on the Y axes. We hope that this figure is now easier to follow.
Significance
*The strength of the manuscript is the use and validation of incorporation of FFA's in the plasma membrane, which more closely mimics the physiological situation than brief application of FFAs as often done. Is addition, the blunted recruitment of beta-arrestin as assessed by the ppH protocol is quite intriguing mechanistically. The limitation are the relative narrow focus on the D2 receptor (and not multiple GPCRs) that does not really speak to as or assess the physiological, pathophysiological or therapeutic role of the observations (except from referring the relation between FFAs and disease). Also, despite the putative role of Beta-arrestin recruitment in the process, the actual causation in the process is not clear. This shortcoming is underscored by the putative effect on the constitutive internalization described above.
My specific expertise for assessing the paper is within general trafficking processes (including the trafficking methodology applied), trafficking of GPCRs and function of the dopamine system including the role of D2 receptors.*
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Reviewer #2 (Evidence, reproducibility and clarity (Required)):
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The only conclusion that I was able to understand from the study was that enrichment of cell membranes with polyunsaturated fatty acids specifically inhibited agonist-induced internalization of D2 receptors. However, I think that the experiments used to conclude that PUFAs do not alter D2R clustering but reduce the recruitment of β-arrestin2 and D2R endocytosis need some clarification (i.e. data depicted in Fig. 2-5). This lack of clarity might be due to the fact I am not familiar enough with the employed technologies or to the unclear writing style of the paper. There was an overuse of acronyms, initialisms and abbreviations, which are difficult to understand for researchers outside of the specific lipid field. I think that the manuscript should be written in a way to be legible also for researchers not working in the immediate filed.
The paper was not written in a manner that a general audience of cell biologists or those interested in GPCR biology could understand and judge. It is indeed interesting that polyunsaturated fatty acids specifically inhibit D2R internalization in HEK293 cells, and it could be significant. But, it is difficult to judge the significance of the observation without more in vivo data.
I would suggest the following. Remove all acronyms and abbreviations. Significantly, expand the Materials and Methods section, either in the manuscript or in the Supplemental section. I suggest clearly explaining each construct used, and the function of each module in the construct, with diagrams. In addition, provide a comprehensive step by step description of each experimental protocol, providing the reader with the rationale for each step in the protocol with explanatory diagrams. The authors should also more clearly explain the rationale and logic that was utilized to make the conclusions that they did from the depicted observations. Only then can a broader audience determine if the authors' conclusions are justified.
We thank the reviewer for his/her comments. Indeed, our main message was that two types of PUFAs (DHA and DPA) specifically alter D2R endocytosis by reducing the recruitment of β-arrestin2 without changing D2R clustering at the plasma membrane. We are sorry that our writing was not clear enough. We also found out that in the last steps of the submission to Review Commons, the first paragraph of the Discussion was inadvertently erased. This made our main conclusions, summarized in this first paragraph, less clear. We have now put back this important paragraph. Moreover, we have extensively rewritten the manuscript thriving to make it as clear as possible to a large audience. We have reduced the use of acronyms to keep only the most used ones [e.g. PUFA (used 99 times), DHA (37 times), GPCR (34 times), D2R (126 times), GRK (17 times)] and made them consistent throughout the manuscript. Following the reviewer's suggestion, we have also added a scheme of the steps following D2R activation by agonist leading to its internalization (Figure EV3).
We understand that the reviewer implies by "in vivo data" results obtained in the brain of animals. As written in the Introduction and in the Discussion, the current work follows up on a recently published manuscripts by a subset of the authors, namely (i) Ducrocq et al. 2020 (doi 10.1016/j.cmet.2020.02.012) in which we show that deficits in motivation in animals deprived in ω3-PUFAs can be restored specifically by conditional expression of a fatty acid desaturase from c. elegans (FAT1) that allows restoring PUFA levels specifically in D2R-expressing striatal projection neurons (which mediate the so-called indirect pathway), and (ii) Jobin et al. 2023 (doi: 10.1038/s41380-022-01928-6) which combines in cellulo (HEK 293 cells) and in vivo data to show that PUFAs affects the ligand binding of the dopamine D2 receptor and its signaling in a lipid context that reflects patient lipid profiles regarding poly-unsaturation levels.
Reviewer #2 (Significance (Required)):
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In summary, I will reiterate that the reported experiments need to be much better explained to make the study understandable to a broader audience and for that audience to determine whether the conclusions are justified.
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Reviewer #3 (Evidence, reproducibility and clarity (Required)):
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Summary:
The authors investigate the role of lipid polyunsaturation in endocytic uptake of the dopamine D2 receptor (D2R). To modulate the degree of unsaturation in live cell plasma membranes, the authors incubate cell lines with pure fatty acid that is metabolized and incorporated into the cellular membranes. To quantify the internalization of D2R in these live cells, the authors utilized quantitative fluorescence assays such as DERET and endosome analysis to determine the degree and rate of D2R internalization in the presence of two model agonists - dopamine and quinpirole. The authors conclude that when the PUFA content of the plasma membrane is increased (i.e., via ω3 or ω6 fatty acids), both the quantity and rate of D2R internalization decrease substantially. The authors confirmed that these phenomena are specific to D2R as caveolar endocytosis and clathrin-mediated endocytosis were unaffected when these same experimental techniques were utilized for β2 adrenergic receptor and transferrin. Additionally, the authors conclude that the clustering ability of D2R is unaffected by lipid unsaturation but that the ability of D2R clusters to interact with β-arrestin2 is inhibited in the presence of excess PUFA. Based on these findings, the authors propose several hypothetical mechanisms for lipid-D2R interactions on the plasma membrane, which will likely be the scope of future work.
Overall, this is a highly thorough and rigorous body of work that convincingly illustrates the connection between PUFA levels and D2R activity. However, I do not agree with the authors' conclusions pertaining to how their results should be interpreted in the context of fatty acid-related disorders. Additionally, this manuscript could benefit from some reorganization which would present the work more clearly. Please see the comments below.
We thank the reviewer for the positive appreciation of our work, qualified as a "thorough and rigorous body of work that convincingly illustrates the connection between PUFA levels and D2R activity". We will address the specific points raised by the reviewer with our answers below.
Comments:
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- A recurring motivation for this study that is brought up by the authors is that dietary deficiency of ω3 fatty acids is tied to D2R dysfunction. This would indicate that PUFA reduction in the plasma membrane results in D2R dysfunction. However, the experiments emphasized in this manuscript investigate the condition where PUFA content is INCREASED in the plasma membrane and D2R function is compromised. It seems inappropriate for the authors to cite dietary deficiency of ω3 as a motivation when they experimentally test a condition that is tied to ω3 surplus.* Regarding the general comment of the reviewer, we agree that direct conclusion cannot be drawn on the etiology of psychiatric disorders by looking at the effect of membrane fatty acid levels on D2R in HEK 293 cells. Nevertheless, we mention in the Introduction the intriguing occurrence of low PUFA levels in psychiatric disorders as starting point to look at D2R as an important target for psychoactive drugs prescribed for these disorders. In the Discussion, we propose that manipulating fatty acid levels might potentiate the efficacy of D2R ligands used as treatments. We felt raising these aspects was not putting too much emphasis on psychiatric disorders. However, in accordance with the reviewer's comment, we toned down these descriptions in the revised manuscript.
The goal of increasing the levels of fatty acids at the membrane in HEK 293, the most widely used cellular system to study GPCR trafficking, was to try to emulate the levels of lipids in brain cells. Indeed, the levels of PUFAs in our culture conditions are much lower (~8 %, Figure 1B) than in brain extracts (~30 %). Therefore, the "control" condition in HEK 293 cells would correspond to PUFA deficiency while after our enrichment protocol these levels are closer to those found in brain cells. Our results could therefore be interpreted as endocytosis of D2R being augmented under membrane PUFA decrease. Importantly, increased receptor internalization often correlates with decreased signaling. Therefore, membrane PUFA enrichment in our conditions would rather potentiate D2R signaling.
- Following up on the first comment, the authors' results seem to indicate that excess ω3's are detrimental to D2R function. This result would be at odds with the conventional view that ω3's are essential and that excessive ω3 may not be harmful. The authors should rationalize their findings in the context of what is known about excess dietary ω3.*
The Reviewer is right that the conventional view is that excessive ω3 PUFA may not be harmful. However, this rather applies to dietary consumption, which might have limited effect to brain fatty acid contents since their accretion is highly regulated. Moreover, the majority of studies looking at ω3 supplementation have been performed in young adults and the effects on the developing brain - as it might be happening in pathological conditions in which D2R is involved - remain poorly understood. Furthermore, as mentioned above, blunted internalization of D2R under membrane PUFA enrichment is not an indication of "detrimental" to D2R function. Nor do we argue that membrane enrichment corresponds to excess PUFAs.
- I would argue that the control experiments with saturated fatty acids (i.e., Behenic Acid in figure 1), represent a scenario mimicking ω3 deficiency as the enrichment of Behenic Acid causes an overall reduction in PUFAs (Figure EV1C - an increase in SFA must correspond to a decrease in PUFA). These Behenic acid results are the only experiments presented by the authors that mimic a scenario resembling ω3 deficiency and the results show that the D2R internalization is unaffected (Figure 1G-H). Therefore, I would further argue that if anything, the authors results suggest that ω3 deficiency is NOT correlated to D2R internalization. Again, the authors must rationalize these findings in the context of what is known about dietary intake of ω3's.*
The Reviewer must refer to the fact that nutrients rich in SFAs are usually poor in PUFAs and vice-versa. Based on our lipidomic analysis, we now present in Figure 1B the effect of treatments (DHA, DPA, BA) on the levels of PUFAs (Figure 1B) and saturated fatty acids (Figure 1C). In cells treated with behenic acid (BA), PUFA levels are not significantly changed relative to control, untreated cells, while saturated fatty acid levels are increased. BA was used here to determine whether the effects observed with PUFAs was related to the enrichment in unsaturations or due to carbon chain length (C22). It is not the case because BA treatment, unlike DHA or DPA treatment, does not affect D2R endocytosis (Figure 2G,H).
- It's not clear why the authors decided to include an ω6 fatty acid in this study. The authors built up a detailed rationale for investigating ω3's as they are dietarily essential and tied to disease when deficient. To my knowledge, ω6's are considered much less beneficial than ω3's in a dietary sense. The inclusion of an ω6 almost seems coerced as the ω6-related results don't provide any interesting additional insights. It would benefit the manuscript if the authors provided some additional discussion explaining why ω6's are being investigated in addition to ω3's. *
We agree that we could have made the rationale clearer. The goal in comparing ω3-DHA and ω6-DPA was to assess whether the position of the first unsaturation (n-3 vs n-6), with the same carbon chain length (C22) might differentially impact D2R endocytosis.
- In Figure EV1D, the AHA and DPA percentages each increase by ~6%. The corresponding Figure EV1B indicates that the overall PUFA% in the plasma membrane also increases by 6%. This makes sense as the total change in PUFA content is consistent with the amount of AHA or DPA being internalized to cells. However, this consistency was not observed with BA and SFAs. In Figure EV1E, the BA percentage increases only ~1% while the total SFA percentage in Figure EV1C increases by ~6%. How can something undergoing a 1% change (relative to total lipid content) result in a 6% overall change in SFA content?*
The reviewer is correct: the level of SFAs is increased by 5.2% (34.5 % of total FAs in control cells to 39.7 % in BA treated cells), more than the increase in BA alone (1.18% from 0.35 % to 1.53 %). A close look at our lipidomics data showed that many of the 10 saturated fatty acids quantified are enhanced. In particular, the two most abundant ones, palmitic acid (16:0) and stearic acid (18:0) are increased, from 21.37 % to 22.28 % and 8.47 % to 11.17%, respectively. The reasons for these apparent discrepancies may involve lipid metabolic pathways which convert the rare and long BA into more common and shorter SFAs to preserve lipid contents and thus membrane properties.
- In Figure 4, the discussion of kinetics does not make sense. How exactly are kinetics being monitored in this figure? (Recruitment kinetics are discussed in panels D and G)*
We wanted to convey the impression that the time to reach the peak βarr2-mCherry recruitment was shorter in PUFA-treated cells than in control cells. However, after analyzing the kinetics in individual cells, we did not find a statistically significant difference in the time to maximum fluorescence. Therefore, we removed this reference to the kinetics of recruitment.
We now write: " However, treatment with DHA or DPA significantly decreased peak βarr2-mCherry fluorescence (Figure 5F-G).."
- In Figure 5, What is the purpose of panel D? Would it be more helpful to include additional, overlaid "cumulative N" plots for scenarios in which PUFAs were enriched? This would work well in conjunction with panel F.*
The purpose of this panel is to show the kinetics of increase in the frequency of endocytic vesicle formation upon agonist addition, and the decrease in frequency when the agonist is removed. We have now added examples of cells treated with DHA and DPA of similar surface for direct comparison with control (EtOH) cells.
- For the readers who are new to this area or unfamiliar with the assays used, Figure 1 is not intuitive and initially difficult to interpret. It would greatly benefit the flow of the manuscript if Figures EV1A-C and EV2A were included in the main text and "Normalized R" was clearly defined in the main text, prior to discussion of Figure 1.*
We have now transferred Figure EV1 as Figure 1. We have adapted the scheme of the DERET assay and its legend (now in Figure EV1A) to make it clearer. We did not put in Figure 2 because this figure is already very big. We have changed "Normalized R" to "Ratio 620/520) (% max)" to be clearer and more consistent with the scheme.
Reviewer #3 (Significance (Required)):
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General assessment: The work, for the most part, is rigorous and scientifically sound. The authors utilize impressive, quantitative assays to expand our understanding of protein-lipid interactions. However, the authors need to improve their discussion of the actual physiological conditions that correspond to their experimental results.
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Advance: This work may fill a gap in our understanding of disorders related to the dopamine D2 receptor. However, some of the results may be at odds with what is currently known/understood about dietary ω3 fatty acids.
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Audience: This work will be of broad interest to researchers in the biophysics field, with particular emphasis on researchers who study protein and membrane biophysics. This work will also be of interest to researchers who study membrane molecular biology.
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Reviewer Expertise: quantitative fluorescence spectroscopy and microscopy; membrane biophysics; protein-lipid interactions
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Referee #1
Evidence, reproducibility and clarity
The manuscript, using different live and fixed cell trafficking assays, demonstrates that incorporation of poly-unsaturated, but not saturated, free fatty acids in the membrane phospholipids reduce agonist induced internalization of the D2 dopamine receptor but not the adrenergic beta2 receptors or the transferrin receptor. Pulsed pH (ppH) live microscopy further demonstrated that the reduced internalization by incorporation of free fatty acid was accompanied by a blunted recruitment of Beta-arrestin for the D2R.
I believe said claims put forward in the manuscript are overall well supported by the data and as such I do not believe that further experiments are necessarily needed to uphold these key claims. Also, the methodology is satisfactorily reported, and statistics are robust, although two-way Anova like used in Fig 1 seems appropriate for Fig 2 and 3
That said, I suggest that the fixed cell internalization experiments (Fig 2 and 3), which relate the effect on the D2R to B2AR and transferrin are revised. This is important since this is relevant to judge whether the effect is a general or a selective molecular mechanism since this is the one of the three assay which this comparison relies on. Alternatively, I suggest omitting this data and include the B2AR in the Live DERET assay and both B2AR and TfR in the ppH assay. Specifically, my concerns with the fixed cell internalization are:
- The analysis is based on counting the number of endosomes, which is not necessarily equivalent to the number of receptors internalized
- The analysis relies on fully effective stripping of the surface pool of receptors - i.e clustered surface receptors not stripped by the protocol will be assessed as internalized. It is often very difficult to obtain full efficiency of the Flag-tag stripping and this is somewhat expression dependent.
- The protocol for the constitutive and agonist induced internalization is different and yet shown on the same absolute graph. Although I take it the microscope gain setting are unaltered between the constitutive and agonist induced internalization I don't believe the quantification can be directly related. This is confusing at the very least. More critically however, the membrane signal from the non-stripped condition of constitutive internalization will likely fully shield internalized receptors in the Rab4 membrane proximal recycling pathway leading to under-estimation of the in the constitutive endocytosis. I believe this methodological limitation underlies the massive relative difference in the constitutive endocytosis between panel 2A,B and 2C,D. For comparison, by a quantitative dual color FACS endocytosis assay, we have previously demonstrated the ligand endocytosis a ~4 fold increased over constitutive (in concert with Fig 2A,B here) (Schmidt et al 20XX). Importantly, high relative variability by this methodology could well shield an actual effect of incorporation of FFAs on the constitutive endocytosis.
'Optional' Also, it would be informative to see the ppH Beta-arrestin experiments with the B2AR to assess, whether the putative discrepancy between D2R and B2AR is upstream or downstream of the blunted Beta-arrestin recruitment. To the same point, it would be very informative to assess how the incorporation of the free fatty acids affect receptor signalling, which would also help relate the effect of incorporation of the FFA's in the phospholipids to previous experiment using short term incubation with FFA's
References overall seem appropriate although Schmidt et al would be relevant for reference of the constitutive vs agonist induced endocytosis of D2R and B2AR. Overall, the figures are well composed and convey the messages fairly well. Specific point that would strengthen the rigor include:
- Chosing actual representative pictures of the qunatiative data in Fig 2 and 3 (e.g. har to see 25 endocytic events in Fig 2A constitutive endo, EtOH)
- Showing actual p values for the statistical comparisions
Moreover, for ease of reading the figures (without consulting the legend repeatedly) it would be very helpful to headline individual panel with what the experiments assesses. Figure 1a and 1b for example can't be distinguished at all before reading the figure legend. Also, y-axis could be more informative on what I measured rather than just giving the unit.
Finally, the figure presentation and description of S1 is very hard to follow. I cannot really make out what is assessed in the different panels.
Significance
The strength of the manuscript is the use and validation of incorporation of FFA's in the plasma membrane, which more closely mimics the physiological situation than brief application of FFAs as often done. Is addition, the blunted recruitment of beta-arrestin as assessed by the ppH protocol is quite intriguing mechanistically. The limitation are the relative narrow focus on the D2 receptor (and not multiple GPCRs) that does not really speak to as or assess the physiological, pathophysiological or therapeutic role of the observations (except from referring the relation between FFAs and disease). Also, despite the putative role of Beta-arrestin recruitment in the process, the actual causation in the process is not clear. This shortcoming is underscored by the putative effect on the constitutive internalization described above.
My specific expertise for assessing the paper is within general trafficking processes (including the trafficking methodology applied), trafficking of GPCRs and function of the dopamine system including the role of D2 receptors.
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Reply to the reviewers
Compared to our initial submission to Review Commons, we have addressed all the reviewers' comments. We have extensively re-written the manuscript to make it clearer to a larger audience. In particular, we have transferred Figure EV1 to Figure 1 with more complete panels and included a scheme (Figure EV3) on the steps of D2R internalization which we measure with live cell imaging. We have added a new paragraph to the start of the Discussion to summarize our main conclusions and reordered the discussion on the possible mechanisms of membrane PUFA enrichment on D2R endocytosis. All the changes in the text are in red for easier comparison with the previous version.
As suggested by reviewer 1, we have performed additional experiments to test the specificity of the effects of PUFA treatments on D2R endocytosis, reinforcing the results shown in Figure 4 using feeding assays. We show with live cell TIRF imaging and the ppH assay that TfR-SEP endocytosis is not affected (Figure EV5) and that SEP-β2AR endocytosis and βarr2-mCherry recruitment to the plasma membrane are not affected (Figure EV6).
Reviewer #1
Evidence, reproducibility and clarity
*The manuscript, using different live and fixed cell trafficking assays, demonstrates that incorporation of poly-unsaturated, but not saturated, free fatty acids in the membrane phospholipids reduce agonist induced internalization of the D2 dopamine receptor but not the adrenergic beta2 receptors or the transferrin receptor. Pulsed pH (ppH) live microscopy further demonstrated that the reduced internalization by incorporation of free fatty acid was accompanied by a blunted recruitment of Beta-arrestin for the D2R.
I believe said claims put forward in the manuscript are overall well supported by the data and as such I do not believe that further experiments are necessarily needed to uphold these key claims. Also, the methodology is satisfactorily reported, and statistics are robust, although two-way Anova like used in Fig 1 seems appropriate for Fig 2 and 3*
We thank the reviewer for his/her positive assessment of our work. We have checked the statistical tests used for all our measures. For Figure 2 and 3 (now 3 and 4) we test for only one factor (PUFA treatment or not) so we ran ordinary one-way ANOVA using Graphpad Prism.
That said, I suggest that the fixed cell internalization experiments (Fig 2 and 3), which relate the effect on the D2R to B2AR and transferrin are revised. This is important since this is relevant to judge whether the effect is a general or a selective molecular mechanism since this is the one of the three assay which this comparison relies on. Alternatively, I suggest omitting this data and include the B2AR in the Live DERET assay and both B2AR and TfR in the ppH assay. Specifically, my concerns with the fixed cell internalization are: • The analysis is based on counting the number of endosomes, which is not necessarily equivalent to the number of receptors internalized
The number of puncta, as well as their fluorescence, is reported by the analysis program (written in Matlab2021 and available upon request). We chose to show number of puncta because they reflect more directly the number of labelled endosomes (in Figures 3 and 4). As shown in the figure below, we found slight but significant differences between groups for FLAG-D2R (88.6 % and 87.6 % of average fluorescence in DHA and DPA treated cells compared to control cells), (panel A), and no differences for FLAG-β2AR (panel B). We find a significant decrease in puncta fluorescence for transferrin uptake in cells incubated with DHA (but not DPA) relative to control cells (panel C). However, because we did not detect differences in the number of puncta or in the frequency and amplitude of endocytic vesicle creation events (see below), we still conclude that enrichment with exogenous PUFAs does not affect clathrin mediated endocytosis.
In conclusion, the most robust measure of endocytosis for this assay is the number of detected puncta per cell rather than their fluorescence.
- The analysis relies on fully effective stripping of the surface pool of receptors - i.e clustered surface receptors not stripped by the protocol will be assessed as internalized. It is often very difficult to obtain full efficiency of the Flag-tag stripping and this is somewhat expression dependent. • The protocol for the constitutive and agonist induced internalization is different and yet shown on the same absolute graph. Although I take it the microscope gain setting are unaltered between the constitutive and agonist induced internalization I don't believe the quantification can be directly related. This is confusing at the very least. More critically however, the membrane signal from the non-stripped condition of constitutive internalization will likely fully shield internalized receptors in the Rab4 membrane proximal recycling pathway leading to under-estimation of the in the constitutive endocytosis. I believe this methodological limitation underlies the massive relative difference in the constitutive endocytosis between panel 2A,B and 2C,D. For comparison, by a quantitative dual color FACS endocytosis assay, we have previously demonstrated the ligand endocytosis a ~4 fold increased over constitutive (in concert with Fig 2A,B here) (Schmidt et al 20XX). Importantly, high relative variability by this methodology could well shield an actual effect of incorporation of FFAs on the constitutive endocytosis. We thank the reviewer for pointing this difference in the protocol. As a matter of fact, we have not used acid stripping in all the conditions used for the uptake assays (Figures 3 and 4). We apologize for the confusion and we have clarified this point in the Methods section. In early experiments we compared conditions with or without stripping but we concluded from these experiments that indeed, the stripping was not complete. Moreover, we noticed early on that many cells treated with DHA or DPA did not have any detectable cluster (13 cells out of 58 quantified cells treated with DHA after addition of QPL, 12/56 cells treated with DPA, 0/68 for cells treated with vehicle). Stripping the antibody would have made these cells undetectable, biasing the analysis. Therefore, to make our results more consistent we decided to use non-stripping conditions. To detect endosomes specifically, we used a segmentation tool developed earlier (see Rosendale et al.* 2019). This tool is based on wavelet transforms which recognizes dot-like structures. In addition, we excluded from the cell mask the labelled plasma membrane by a mask erosion.
We agree the design of experiments was not aimed at comparing the effect of PUFA treatment on low levels of constitutive D2R endocytosis. This would require more sensitive assays and be addressed in subsequent studies.
'Optional' Also, it would be informative to see the ppH Beta-arrestin experiments with the B2AR to assess, whether the putative discrepancy between D2R and B2AR is upstream or downstream of the blunted Beta-arrestin recruitment. To the same point, it would be very informative to assess how the incorporation of the free fatty acids affect receptor signalling, which would also help relate the effect of incorporation of the FFA's in the phospholipids to previous experiment using short term incubation with FFA's
We have now performed live imaging experiments in HEK293 cells expressing SEP-β2AR, GRK2 and βarr2-mCherry and stimulated with isoproterenol (Figure EV6). We show that the clustering of SEP-β2AR, of βarr2-mCherry, as well as endocytosis, are not affected by treatments with DHA or DPA. In this study, we focused on the early trafficking steps of D2R internalization. It will be interesting in a future study to address its consequences on G protein dependent and independent signaling. Moreover, and for good measure, we performed experiments to assess TfR-SEP endocytosis with the ppH assay. Again, we found no difference between cells treated or not with PUFAs (Figure EV5)
*References overall seem appropriate although Schmidt et al would be relevant for reference of the constitutive vs agonist induced endocytosis of D2R and B2AR. *
We have now cited Schmidt et al. 2020 doi 10.1111/bcpt.13274 in the discussion with the following sentences: "D2R also shows constitutive endocytosis (Schmidt et al, 2020) which may be modulated by PUFAs although we did not detect any significant difference in our measures (see Figure 3) which were aimed at detecting high levels of internalization induced by agonists. Further work will be required to specifically examine the effect of PUFAs on constitutive GPCR internalization."
Overall, the figures are well composed and convey the messages fairly well. Specific point that would strengthen the rigor include: • Chosing actual representative pictures of the quantitative data in Fig 2 and 3 (e.g. hard to see 25 endocytic events in Fig 2A constitutive endo, EtOH)
We apologize for the confusion. We employ a normalization procedure to account for cell size. In addition, all numbers have been normalized to the condition stimulated with agonist with no PUFA treatment). In fact, we detect in unstimulated cells very few puncta (on average 0.6, range 0-5) compared to 27.3 clusters (range 2-87) in cells stimulated with QPL.
- Showing actual p values for the statistical comparisons* For easier reading, we have kept the stars convention for the figures but added two tables with all statistical tests and the p values for both main figures and EV figures.
Moreover, for ease of reading the figures (without consulting the legend repeatedly) it would be very helpful to headline individual panel with what the experiments assesses. Figure 1a and 1b for example can't be distinguished at all before reading the figure legend. Also, y-axis could be more informative on what I measured rather than just giving the unit.
We have added titles to panels (in particular for Figure 2A,B which correspond to former Figure 1A,B) and we have given new titles to Y axes to make them clearer. We hope that the reading of our figures will now be easier.
Finally, the figure presentation and description of S1 is very hard to follow. I cannot really make out what is assessed in the different panels.
We have changed substantially Figure EV1 (now Figure 1) with new presentation of data: all 4 conditions (control, treated with DHA, DPA or BA) systematically presented in the same graph, and clearer titles for the parameter displayed on the Y axes. We hope that this figure is now easier to follow.
Significance
*The strength of the manuscript is the use and validation of incorporation of FFA's in the plasma membrane, which more closely mimics the physiological situation than brief application of FFAs as often done. Is addition, the blunted recruitment of beta-arrestin as assessed by the ppH protocol is quite intriguing mechanistically. The limitation are the relative narrow focus on the D2 receptor (and not multiple GPCRs) that does not really speak to as or assess the physiological, pathophysiological or therapeutic role of the observations (except from referring the relation between FFAs and disease). Also, despite the putative role of Beta-arrestin recruitment in the process, the actual causation in the process is not clear. This shortcoming is underscored by the putative effect on the constitutive internalization described above.
My specific expertise for assessing the paper is within general trafficking processes (including the trafficking methodology applied), trafficking of GPCRs and function of the dopamine system including the role of D2 receptors.*
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Reviewer #2 (Evidence, reproducibility and clarity (Required)):
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The only conclusion that I was able to understand from the study was that enrichment of cell membranes with polyunsaturated fatty acids specifically inhibited agonist-induced internalization of D2 receptors. However, I think that the experiments used to conclude that PUFAs do not alter D2R clustering but reduce the recruitment of β-arrestin2 and D2R endocytosis need some clarification (i.e. data depicted in Fig. 2-5). This lack of clarity might be due to the fact I am not familiar enough with the employed technologies or to the unclear writing style of the paper. There was an overuse of acronyms, initialisms and abbreviations, which are difficult to understand for researchers outside of the specific lipid field. I think that the manuscript should be written in a way to be legible also for researchers not working in the immediate filed.
The paper was not written in a manner that a general audience of cell biologists or those interested in GPCR biology could understand and judge. It is indeed interesting that polyunsaturated fatty acids specifically inhibit D2R internalization in HEK293 cells, and it could be significant. But, it is difficult to judge the significance of the observation without more in vivo data.
I would suggest the following. Remove all acronyms and abbreviations. Significantly, expand the Materials and Methods section, either in the manuscript or in the Supplemental section. I suggest clearly explaining each construct used, and the function of each module in the construct, with diagrams. In addition, provide a comprehensive step by step description of each experimental protocol, providing the reader with the rationale for each step in the protocol with explanatory diagrams. The authors should also more clearly explain the rationale and logic that was utilized to make the conclusions that they did from the depicted observations. Only then can a broader audience determine if the authors' conclusions are justified.
We thank the reviewer for his/her comments. Indeed, our main message was that two types of PUFAs (DHA and DPA) specifically alter D2R endocytosis by reducing the recruitment of β-arrestin2 without changing D2R clustering at the plasma membrane. We are sorry that our writing was not clear enough. We also found out that in the last steps of the submission to Review Commons, the first paragraph of the Discussion was inadvertently erased. This made our main conclusions, summarized in this first paragraph, less clear. We have now put back this important paragraph. Moreover, we have extensively rewritten the manuscript thriving to make it as clear as possible to a large audience. We have reduced the use of acronyms to keep only the most used ones [e.g. PUFA (used 99 times), DHA (37 times), GPCR (34 times), D2R (126 times), GRK (17 times)] and made them consistent throughout the manuscript. Following the reviewer's suggestion, we have also added a scheme of the steps following D2R activation by agonist leading to its internalization (Figure EV3).
We understand that the reviewer implies by "in vivo data" results obtained in the brain of animals. As written in the Introduction and in the Discussion, the current work follows up on a recently published manuscripts by a subset of the authors, namely (i) Ducrocq et al. 2020 (doi 10.1016/j.cmet.2020.02.012) in which we show that deficits in motivation in animals deprived in ω3-PUFAs can be restored specifically by conditional expression of a fatty acid desaturase from c. elegans (FAT1) that allows restoring PUFA levels specifically in D2R-expressing striatal projection neurons (which mediate the so-called indirect pathway), and (ii) Jobin et al. 2023 (doi: 10.1038/s41380-022-01928-6) which combines in cellulo (HEK 293 cells) and in vivo data to show that PUFAs affects the ligand binding of the dopamine D2 receptor and its signaling in a lipid context that reflects patient lipid profiles regarding poly-unsaturation levels.
Reviewer #2 (Significance (Required)):
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In summary, I will reiterate that the reported experiments need to be much better explained to make the study understandable to a broader audience and for that audience to determine whether the conclusions are justified.
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Reviewer #3 (Evidence, reproducibility and clarity (Required)):
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Summary:
The authors investigate the role of lipid polyunsaturation in endocytic uptake of the dopamine D2 receptor (D2R). To modulate the degree of unsaturation in live cell plasma membranes, the authors incubate cell lines with pure fatty acid that is metabolized and incorporated into the cellular membranes. To quantify the internalization of D2R in these live cells, the authors utilized quantitative fluorescence assays such as DERET and endosome analysis to determine the degree and rate of D2R internalization in the presence of two model agonists - dopamine and quinpirole. The authors conclude that when the PUFA content of the plasma membrane is increased (i.e., via ω3 or ω6 fatty acids), both the quantity and rate of D2R internalization decrease substantially. The authors confirmed that these phenomena are specific to D2R as caveolar endocytosis and clathrin-mediated endocytosis were unaffected when these same experimental techniques were utilized for β2 adrenergic receptor and transferrin. Additionally, the authors conclude that the clustering ability of D2R is unaffected by lipid unsaturation but that the ability of D2R clusters to interact with β-arrestin2 is inhibited in the presence of excess PUFA. Based on these findings, the authors propose several hypothetical mechanisms for lipid-D2R interactions on the plasma membrane, which will likely be the scope of future work.
Overall, this is a highly thorough and rigorous body of work that convincingly illustrates the connection between PUFA levels and D2R activity. However, I do not agree with the authors' conclusions pertaining to how their results should be interpreted in the context of fatty acid-related disorders. Additionally, this manuscript could benefit from some reorganization which would present the work more clearly. Please see the comments below.
We thank the reviewer for the positive appreciation of our work, qualified as a "thorough and rigorous body of work that convincingly illustrates the connection between PUFA levels and D2R activity". We will address the specific points raised by the reviewer with our answers below.
Comments:
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- A recurring motivation for this study that is brought up by the authors is that dietary deficiency of ω3 fatty acids is tied to D2R dysfunction. This would indicate that PUFA reduction in the plasma membrane results in D2R dysfunction. However, the experiments emphasized in this manuscript investigate the condition where PUFA content is INCREASED in the plasma membrane and D2R function is compromised. It seems inappropriate for the authors to cite dietary deficiency of ω3 as a motivation when they experimentally test a condition that is tied to ω3 surplus.* Regarding the general comment of the reviewer, we agree that direct conclusion cannot be drawn on the etiology of psychiatric disorders by looking at the effect of membrane fatty acid levels on D2R in HEK 293 cells. Nevertheless, we mention in the Introduction the intriguing occurrence of low PUFA levels in psychiatric disorders as starting point to look at D2R as an important target for psychoactive drugs prescribed for these disorders. In the Discussion, we propose that manipulating fatty acid levels might potentiate the efficacy of D2R ligands used as treatments. We felt raising these aspects was not putting too much emphasis on psychiatric disorders. However, in accordance with the reviewer's comment, we toned down these descriptions in the revised manuscript.
The goal of increasing the levels of fatty acids at the membrane in HEK 293, the most widely used cellular system to study GPCR trafficking, was to try to emulate the levels of lipids in brain cells. Indeed, the levels of PUFAs in our culture conditions are much lower (~8 %, Figure 1B) than in brain extracts (~30 %). Therefore, the "control" condition in HEK 293 cells would correspond to PUFA deficiency while after our enrichment protocol these levels are closer to those found in brain cells. Our results could therefore be interpreted as endocytosis of D2R being augmented under membrane PUFA decrease. Importantly, increased receptor internalization often correlates with decreased signaling. Therefore, membrane PUFA enrichment in our conditions would rather potentiate D2R signaling.
- Following up on the first comment, the authors' results seem to indicate that excess ω3's are detrimental to D2R function. This result would be at odds with the conventional view that ω3's are essential and that excessive ω3 may not be harmful. The authors should rationalize their findings in the context of what is known about excess dietary ω3.*
The Reviewer is right that the conventional view is that excessive ω3 PUFA may not be harmful. However, this rather applies to dietary consumption, which might have limited effect to brain fatty acid contents since their accretion is highly regulated. Moreover, the majority of studies looking at ω3 supplementation have been performed in young adults and the effects on the developing brain - as it might be happening in pathological conditions in which D2R is involved - remain poorly understood. Furthermore, as mentioned above, blunted internalization of D2R under membrane PUFA enrichment is not an indication of "detrimental" to D2R function. Nor do we argue that membrane enrichment corresponds to excess PUFAs.
- I would argue that the control experiments with saturated fatty acids (i.e., Behenic Acid in figure 1), represent a scenario mimicking ω3 deficiency as the enrichment of Behenic Acid causes an overall reduction in PUFAs (Figure EV1C - an increase in SFA must correspond to a decrease in PUFA). These Behenic acid results are the only experiments presented by the authors that mimic a scenario resembling ω3 deficiency and the results show that the D2R internalization is unaffected (Figure 1G-H). Therefore, I would further argue that if anything, the authors results suggest that ω3 deficiency is NOT correlated to D2R internalization. Again, the authors must rationalize these findings in the context of what is known about dietary intake of ω3's.*
The Reviewer must refer to the fact that nutrients rich in SFAs are usually poor in PUFAs and vice-versa. Based on our lipidomic analysis, we now present in Figure 1B the effect of treatments (DHA, DPA, BA) on the levels of PUFAs (Figure 1B) and saturated fatty acids (Figure 1C). In cells treated with behenic acid (BA), PUFA levels are not significantly changed relative to control, untreated cells, while saturated fatty acid levels are increased. BA was used here to determine whether the effects observed with PUFAs was related to the enrichment in unsaturations or due to carbon chain length (C22). It is not the case because BA treatment, unlike DHA or DPA treatment, does not affect D2R endocytosis (Figure 2G,H).
- It's not clear why the authors decided to include an ω6 fatty acid in this study. The authors built up a detailed rationale for investigating ω3's as they are dietarily essential and tied to disease when deficient. To my knowledge, ω6's are considered much less beneficial than ω3's in a dietary sense. The inclusion of an ω6 almost seems coerced as the ω6-related results don't provide any interesting additional insights. It would benefit the manuscript if the authors provided some additional discussion explaining why ω6's are being investigated in addition to ω3's. *
We agree that we could have made the rationale clearer. The goal in comparing ω3-DHA and ω6-DPA was to assess whether the position of the first unsaturation (n-3 vs n-6), with the same carbon chain length (C22) might differentially impact D2R endocytosis.
- In Figure EV1D, the AHA and DPA percentages each increase by ~6%. The corresponding Figure EV1B indicates that the overall PUFA% in the plasma membrane also increases by 6%. This makes sense as the total change in PUFA content is consistent with the amount of AHA or DPA being internalized to cells. However, this consistency was not observed with BA and SFAs. In Figure EV1E, the BA percentage increases only ~1% while the total SFA percentage in Figure EV1C increases by ~6%. How can something undergoing a 1% change (relative to total lipid content) result in a 6% overall change in SFA content?*
The reviewer is correct: the level of SFAs is increased by 5.2% (34.5 % of total FAs in control cells to 39.7 % in BA treated cells), more than the increase in BA alone (1.18% from 0.35 % to 1.53 %). A close look at our lipidomics data showed that many of the 10 saturated fatty acids quantified are enhanced. In particular, the two most abundant ones, palmitic acid (16:0) and stearic acid (18:0) are increased, from 21.37 % to 22.28 % and 8.47 % to 11.17%, respectively. The reasons for these apparent discrepancies may involve lipid metabolic pathways which convert the rare and long BA into more common and shorter SFAs to preserve lipid contents and thus membrane properties.
- In Figure 4, the discussion of kinetics does not make sense. How exactly are kinetics being monitored in this figure? (Recruitment kinetics are discussed in panels D and G)*
We wanted to convey the impression that the time to reach the peak βarr2-mCherry recruitment was shorter in PUFA-treated cells than in control cells. However, after analyzing the kinetics in individual cells, we did not find a statistically significant difference in the time to maximum fluorescence. Therefore, we removed this reference to the kinetics of recruitment.
We now write: " However, treatment with DHA or DPA significantly decreased peak βarr2-mCherry fluorescence (Figure 5F-G).."
- In Figure 5, What is the purpose of panel D? Would it be more helpful to include additional, overlaid "cumulative N" plots for scenarios in which PUFAs were enriched? This would work well in conjunction with panel F.*
The purpose of this panel is to show the kinetics of increase in the frequency of endocytic vesicle formation upon agonist addition, and the decrease in frequency when the agonist is removed. We have now added examples of cells treated with DHA and DPA of similar surface for direct comparison with control (EtOH) cells.
- For the readers who are new to this area or unfamiliar with the assays used, Figure 1 is not intuitive and initially difficult to interpret. It would greatly benefit the flow of the manuscript if Figures EV1A-C and EV2A were included in the main text and "Normalized R" was clearly defined in the main text, prior to discussion of Figure 1.*
We have now transferred Figure EV1 as Figure 1. We have adapted the scheme of the DERET assay and its legend (now in Figure EV1A) to make it clearer. We did not put in Figure 2 because this figure is already very big. We have changed "Normalized R" to "Ratio 620/520) (% max)" to be clearer and more consistent with the scheme.
Reviewer #3 (Significance (Required)):
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General assessment: The work, for the most part, is rigorous and scientifically sound. The authors utilize impressive, quantitative assays to expand our understanding of protein-lipid interactions. However, the authors need to improve their discussion of the actual physiological conditions that correspond to their experimental results.
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Advance: This work may fill a gap in our understanding of disorders related to the dopamine D2 receptor. However, some of the results may be at odds with what is currently known/understood about dietary ω3 fatty acids.
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Audience: This work will be of broad interest to researchers in the biophysics field, with particular emphasis on researchers who study protein and membrane biophysics. This work will also be of interest to researchers who study membrane molecular biology.
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Reviewer Expertise: quantitative fluorescence spectroscopy and microscopy; membrane biophysics; protein-lipid interactions
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Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
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Referee #1
Evidence, reproducibility and clarity
The manuscript, using different live and fixed cell trafficking assays, demonstrates that incorporation of poly-unsaturated, but not saturated, free fatty acids in the membrane phospholipids reduce agonist induced internalization of the D2 dopamine receptor but not the adrenergic beta2 receptors or the transferrin receptor. Pulsed pH (ppH) live microscopy further demonstrated that the reduced internalization by incorporation of free fatty acid was accompanied by a blunted recruitment of Beta-arrestin for the D2R.
I believe said claims put forward in the manuscript are overall well supported by the data and as such I do not believe that further experiments are necessarily needed to uphold these key claims. Also, the methodology is satisfactorily reported, and statistics are robust, although two-way Anova like used in Fig 1 seems appropriate for Fig 2 and 3
That said, I suggest that the fixed cell internalization experiments (Fig 2 and 3), which relate the effect on the D2R to B2AR and transferrin are revised. This is important since this is relevant to judge whether the effect is a general or a selective molecular mechanism since this is the one of the three assay which this comparison relies on. Alternatively, I suggest omitting this data and include the B2AR in the Live DERET assay and both B2AR and TfR in the ppH assay. Specifically, my concerns with the fixed cell internalization are:
- The analysis is based on counting the number of endosomes, which is not necessarily equivalent to the number of receptors internalized
- The analysis relies on fully effective stripping of the surface pool of receptors - i.e clustered surface receptors not stripped by the protocol will be assessed as internalized. It is often very difficult to obtain full efficiency of the Flag-tag stripping and this is somewhat expression dependent.
- The protocol for the constitutive and agonist induced internalization is different and yet shown on the same absolute graph. Although I take it the microscope gain setting are unaltered between the constitutive and agonist induced internalization I don't believe the quantification can be directly related. This is confusing at the very least. More critically however, the membrane signal from the non-stripped condition of constitutive internalization will likely fully shield internalized receptors in the Rab4 membrane proximal recycling pathway leading to under-estimation of the in the constitutive endocytosis. I believe this methodological limitation underlies the massive relative difference in the constitutive endocytosis between panel 2A,B and 2C,D. For comparison, by a quantitative dual color FACS endocytosis assay, we have previously demonstrated the ligand endocytosis a ~4 fold increased over constitutive (in concert with Fig 2A,B here) (Schmidt et al 20XX). Importantly, high relative variability by this methodology could well shield an actual effect of incorporation of FFAs on the constitutive endocytosis.
'Optional' Also, it would be informative to see the ppH Beta-arrestin experiments with the B2AR to assess, whether the putative discrepancy between D2R and B2AR is upstream or downstream of the blunted Beta-arrestin recruitment. To the same point, it would be very informative to assess how the incorporation of the free fatty acids affect receptor signalling, which would also help relate the effect of incorporation of the FFA's in the phospholipids to previous experiment using short term incubation with FFA's
References overall seem appropriate although Schmidt et al would be relevant for reference of the constitutive vs agonist induced endocytosis of D2R and B2AR. Overall, the figures are well composed and convey the messages fairly well. Specific point that would strengthen the rigor include:
- Chosing actual representative pictures of the qunatiative data in Fig 2 and 3 (e.g. har to see 25 endocytic events in Fig 2A constitutive endo, EtOH)
- Showing actual p values for the statistical comparisions
Moreover, for ease of reading the figures (without consulting the legend repeatedly) it would be very helpful to headline individual panel with what the experiments assesses. Figure 1a and 1b for example can't be distinguished at all before reading the figure legend. Also, y-axis could be more informative on what I measured rather than just giving the unit.
Finally, the figure presentation and description of S1 is very hard to follow. I cannot really make out what is assessed in the different panels.
Significance
The strength of the manuscript is the use and validation of incorporation of FFA's in the plasma membrane, which more closely mimics the physiological situation than brief application of FFAs as often done. Is addition, the blunted recruitment of beta-arrestin as assessed by the ppH protocol is quite intriguing mechanistically. The limitation are the relative narrow focus on the D2 receptor (and not multiple GPCRs) that does not really speak to as or assess the physiological, pathophysiological or therapeutic role of the observations (except from referring the relation between FFAs and disease). Also, despite the putative role of Beta-arrestin recruitment in the process, the actual causation in the process is not clear. This shortcoming is underscored by the putative effect on the constitutive internalization described above.
My specific expertise for assessing the paper is within general trafficking processes (including the trafficking methodology applied), trafficking of GPCRs and function of the dopamine system including the role of D2 receptors.
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others argue that it's not an interpreted language and that it's actually a compiled language
Sounds cool
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JavaScript is an interpreted language
This is cool as well as sick!
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Reviewer #1 (Public Review):
Summary:
This paper reports the finding that less fat accumulates in C. elegans that are feeding on Comamonas aquatica DA1877 (DA) vs the standard lab diet of Escherichia coli OP50 (OP50). While these bacteria are likely to be different in many ways, the authors found that fat accumulation phenotype depends on the vitamin B12 content of the bacterial diet and the involvement of B12 in the methionine cycle, affecting SAMS-1 and phosphatidylcholine (PC) synthesis. They report that low PC levels activate SREBP-1 (SBP-1 in C. elegans) and that an important target of SBP-1 is the delta 9 desaturase FAT-7. Finally, they describe a role for ASM-3, an acid sphingomyelinase, in influencing PC synthesis and fat accumulation in the worm.
Strengths:
This is a comprehensive story about how a dietary change affects fat accumulation in C. elegans. Their experimental evidence is convincing. The most novel aspect of this paper is that the coelomecyte expression of asm-3 contributes to PC/TAG homeostasis in C. elegans, which most likely occurs through the production of phosphocholine by the enzymatic breakdown of sphingomyelin by ASM-3. The phosphocholine will provide precursors for phosphatidylcholine (PC) synthesis, contributing to the PC synthesis pathway.
Weaknesses:
In the way the story is presented, the authors tend to imply that they discovered the pathways of B12, PC, SBP-1, and FAT-7, ignoring some important studies describing the relationship between PC synthesis and TAG accumulation in both the mammalian lipid metabolism field (liver) as well as in C. elegans. Many previous studies with similar results are not cited appropriately. Thus, the pathways reported in the paper are not new, and in this sense, the work is mostly confirmatory.
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Reviewer #3 (Public Review):
Summary:
The authors presented data that linked vitamin B12, S-adenosyl methionine (SAM), and phosphatidylcholine (PC) synthesis to lipid homeostasis in C. elegans. They confirmed mechanisms previously shown by other labs, including the regulation of FAT-7 expression by SBP-1, and the targeting of SEIP-1 by PC levels. The authors also attempted to link the synthesis of phospho-choline by the ASM-3 sphingomyelinase to PC synthesis and lipid homeostasis. However, the relative contribution of phospho-choline by ASM-3 versus the canonical Kennedy pathway was not elucidated. Therefore, the significance of the ASM-3-dependent mechanism to PC synthesis requires further investigation.
Strengths:
The authors used a wide range of biochemical and cell biological methods to measure fatty acid composition, neutral lipid levels, and lipid droplet dynamics in C. elegans. The quality of the data is generally high.
Weaknesses:
Data interpretation and the construction of the working model did not seem to take into account the two well-established pathways for PC synthesis. The Kennedy pathway generates PC from phospho-choline and DAG via a cytidine-based intermediate. The second PC synthesis pathway entails the methylation of PE by PEMT, with the donor methyl groups provided by the vitamin B12-dependent 1-carbon cycle. The authors' model seemed to overlook part of the Kennedy pathway that involves choline kinase (and not ASM-3) as the canonical enzyme that generates phospho-choline. The authors also did not explicitly consider DAG as a precursor of triacylglycerol (TAG), which was directly or indirectly measured as a readout of organismal fat content in the paper. Therefore, alternative models should be entertained. For example, the proposed genetic and dietary effects on lipid homeostasis could stem from the competition for a limiting pool of precursors that were shared by PC and TAG synthesis. PC itself may not have a deterministic role, as depicted by the authors' model. Finally, the claim that "coelomocytes regulate diets-induced lipid homeostasis through asm-3" was not well supported. In the absence of quantitative analysis of phospho-choline in mutants, it was unclear how much ASM-3 contributed to the overall phospho-choline, and ultimately PC level. The proposed inter-tissue regulation of PC synthesis also requires coelomocytes-specific knock-down/depletion of asm-3 for verification.
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stackoverflow.com stackoverflow.com
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I can confirm that this is still actual for Rails 7 - jpEg converts to jpg and your production fails.
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Reviewer #3 (Public Review):
Summary:
The work by Kalita et al. reports regulation of RecB expression by Hfq protein in E.coli cell. RecBCD is an essential complex for DNA repair and chromosome maintenance. The expression level needs to be regulated at low level under regular growth conditions but upregulated upon DNA damage. Through quantitative imaging, the authors demonstrate that recB mRNAs and proteins are expressed at low level under regular conditions. While the mRNA copy number demonstrates high noise level due to stochastic gene expression, the protein level is maintained at a lower noise level compared to expected value. Upon DNA damage, the authors claim that the recB mRNA concentration is decreased, however RecB protein level is compensated by higher translation efficiency. Through analyzing CLASH data on Hfq, they identified two Hfq binding sites on RecB polycistronic mRNA, one of which is localized at the ribosome binding site (RBS). Through measuring RecB mRNA and protein level in the ∆hfq cell, the authors conclude that binding of Hfq to the RBS region of recB mRNA suppresses translation of recB mRNA. This conclusion is further supported by the same measurement in the presence of Hfq sequestrator, the sRNA ChiX, and the deletion of the Hfq binding region on the mRNA.
Strengths:
(1) The manuscript is well-written and easy to understand.<br /> (2) While there are reported cases of Hfq regulating translation of bound mRNAs, its effect on reducing translation noise is relatively new.<br /> (3) The imaging and analysis are carefully performed with necessary controls.
Weaknesses:
The major weaknesses include a lack of mechanistic depth, and part of the conclusions are not fully supported by the data.
(1) Mechanistically, it is still unclear why upon DNA damage, translation level of recB mRNA increases, which makes the story less complete. The authors mention in the Discussion that a moderate (30%) decrease in Hfq protein was observed in previous study, which may explain the loss of translation repression on recB. However, given that this mRNA exists in very low copy number (a few per cell) and that Hfq copy number is on the order of a few hundred to a few thousand, it's unclear how 30% decrease in the protein level should resides a significant change in its regulation of recB mRNA.<br /> (2) Based on the experiment and the model, Hfq regulates translation of recB gene through binding to the RBS of the upstream ptrA gene through translation coupling. In this case, one would expect that the behavior of ptrA gene expression and its response to Hfq regulation would be quite similar to recB. Performing the same measurement on ptrA gene expression in the presence and absence of Hfq would strengthen the conclusion and model.<br /> (3) The authors agree that they cannot exclude the possibility of sRNA being involved in the translation regulation. However, this can be tested by performing the imaging experiments in the presence of Hfq proximal face mutations, which largely disrupt binding of sRNAs.<br /> (4) The data on construct with a long region of Hfq binding site on recB mRNA deleted is less convincing. There is no control to show that removing this sequence region itself has no effect on translation, and the effect is solely due to the lack of Hfq binding. A better experiment would be using a Hfq distal face mutant that is deficient in binding to the ARN motifs.<br /> (5) Ln 249-251: The authors claim that the stability of recB mRNA is not changed in ∆hfq simply based on the steady-state mRNA level. To claim so, the lifetime needs to be measured in the absence of Hfq.<br /> (6) What's the labeling efficiency of Halo-tag? If not 100% labeled, is it considered in the protein number quantification? Is the protein copy number quantification through imaging calibrated by an independent method? Does Halo tag affect the protein translation or degradation?<br /> (7) Upper panel of Fig S8a is redundant as in Fig 5B. Seems that Fig S8d is not described in the text.
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Author response:
Reviewer #1 (Public Review):
Summary:
In this study the authors use an elegant set of single-molecule experiments to assess the transcriptional and post-transcriptional regulation of RecB. The question stems from a previous observation from the same lab, that RecB protein levels are low and not induced under DNA damage. The authors first show that recB transcript levels are low and have a short half-life. They further show that RecB levels are likely regulated via translational control. They provide evidence for low noise in RecB protein levels across cells and show that the translation of the mRNA increases under double-strand break conditions. Authors identify Hfq binding sites in the recbcd [recBCD] operon and show that Hfq regulates the levels of RecB protein without changing the mRNA levels. They suggest that RecB translation is directly controlled by Hfq binding to mRNA, as mutating one of the binding sites has a direct effect on RecB protein levels.
Strengths:
The implication of Hfq in regulation of RecB translation is important and suggests mechanisms of cellular response to DNA damage that are beyond the canonically studied mechanisms (such as transcriptional regulation by LexA). Data are clearly presented and the writing is direct and easy to follow. Overall, the study is well-designed and provides novel insights into the regulation of RecB, that is part of the complex required to process break ends.
Weaknesses:
Some key findings need additional support/ clarifications to strengthen the conclusions. These are suggested to the authors.
Reviewer #2 (Public Review):
Summary:
The authors carry out a careful and rigorous quantitative analysis of RecB transcript and protein levels at baseline and in response to DNA damage. Using single-molecule FISH and Halo-tagging in order to achieve sensitive measurements, they provide evidence that enhanced RecB protein levels in response to DNA damage are achieved through a post-transcriptional mechanism mediated by the La-like RNA binding protein, Hhq1 [Sm-like RNA binding protein, Hfq]. In terms of biological relevance, the authors suggest that this mechanism provides a way to control the optimum level of RecB expression as both deletion and over-expression are deleterious. In addition, the proposed mechanism provides a new framework for understanding how transcriptional noise can be suppressed at the protein level.
Strengths:
Strengths of the manuscript include the rigorous approaches and orthogonal evidence to support the core conclusions, for example, the evidence that altering either Hhq1 [Hfq] or its recognition sequence on the RNA similarly enhance the protein to RNA ratio of RecB. The writing is clear and the experiments are well-controlled. The modeling approaches provide essential context to interpret the data, particularly given the small numbers of molecules per cell. The interpretations are careful and well supported.
Weaknesses:
The authors make a compelling case for the biological need to exquisitely control RecB levels, which they suggest is achieved by the pathway they have uncovered and described in this work. However, this conclusion is largely inferred as the authors only investigate the effect on cell survival in response to (high levels of) DNA damage and in response to two perturbations - genetic knock-out or over-expression, both of which are likely more dramatic than the range of expression levels observed in unstimulated and DNA damage conditions.
In the discussion, we proposed that the post-transcriptional regulation of recB that we have uncovered could be involved in keeping RecB levels within an optimal range. We agree that testing the phenotypic impact of small changes in RecB levels would add additional strength to this suggestion. However, this is experimentally very challenging because of the low copy number of RecB molecules, which makes it difficult to slightly alter RecB levels in a controlled and homogeneous (across cells) manner. Developing the synthetic biology tools necessary for such an experiment is beyond the scope of this article. In the manuscript, we will clarify the limits of our interpretation of the role of the uncovered regulation.
Reviewer #3 (Public Review):
Summary:
The work by Kalita et al. reports regulation of RecB expression by Hfq protein in E.coli cell. RecBCD is an essential complex for DNA repair and chromosome maintenance. The expression level needs to be regulated at low level under regular growth conditions but upregulated upon DNA damage. Through quantitative imaging, the authors demonstrate that recB mRNAs and proteins are expressed at low level under regular conditions. While the mRNA copy number demonstrates high noise level due to stochastic gene expression, the protein level is maintained at a lower noise level compared to expected value. Upon DNA damage, the authors claim that the recB mRNA level is not significantly affected, but RecB protein level increases due to a higher translation efficiency. [Upon DNA damage, the authors claim that the recB mRNA concentration is decreased, however RecB protein level is compensated by higher translation efficiency]. Through analyzing CLASH data on Hfq, they identified two Hfq binding sites on RecB polycistronic mRNA, one of which is localized at the ribosome binding site (RBS). Through measuring RecB mRNA and protein level in the ∆hfq cell, the authors conclude that binding of Hfq to the RBS region of recB mRNA suppresses translation of recB mRNA. This conclusion is further supported by the same measurement in the presence of Hfq sequestrator, the sRNA ChiX, and the deletion of the Hfq binding region on the mRNA.
Strengths:
(1) The manuscript is well-written and easy to understand.
(2) While there are reported cases of Hfq regulating translation of bound mRNAs, its effect on reducing translation noise is relatively new.
(3) The imaging and analysis are carefully performed with necessary controls.
Weaknesses:
The major weaknesses include a lack of mechanistic depth, and part of the conclusions are not fully supported by the data.
(1) Mechanistically, it is still unclear why upon DNA damage, translation level of recB mRNA increases, which makes the story less complete. The authors mention in the Discussion that a moderate (30%) decrease in Hfq protein was observed in previous study, which may explain the loss of translation repression on recB. However, given that this mRNA exists in very low copy number (a few per cell) and that Hfq copy number is on the order of a few hundred to a few thousand, it's unclear how 30% decrease in the protein level should resides a significant change in its regulation of recB mRNA.
While Hfq is a highly abundant protein, it has many mRNA and sRNA targets, some of which are also present in large amounts (DOI: 10.1046/j.1365-2958.2003.03734.x). As recently shown, the competition among the targets over Hfq proteins results in unequal (across various targets) outcomes, where the targets with higher Hfq affinity have an advantage over the ones with less efficient binding (DOI: 10.1016/j.celrep.2020.02.016). In line with these findings, we reason that upon DNA damage, a moderate decrease in the Hfq protein abundance (30%) can lead to a similar competition among Hfq targets where high-affinity targets outcompete low- affinity ones as well as low-abundant ones (such as recB mRNAs). Therefore, we hypothesise that the regulation of low abundant targets of Hfq by moderate perturbations of Hfq protein level is a potential explanation for the change in RecB translation that we have observed. We will expand this part of the discussion to explain our reasoning in a more explicit and coherent way.
(2) Based on the experiment and the model, Hfq regulates translation of recB gene through binding to the RBS of the upstream ptrA gene through translation coupling. In this case, one would expect that the behavior of ptrA gene expression and its response to Hfq regulation would be quite similar to recB. Performing the same measurement on ptrA gene expression in the presence and absence of Hfq would strengthen the conclusion and model
Indeed, based on our model, we expect PtrA expression to be regulated by Hfq in a similar manner to RecB. However, the product encoded by the ptrA gene, Protease III, (i) has been poorly characterised; (ii) unlike RecB, is located in the periplasm (DOI: 10.1128/jb.149.3.1027-1033.1982); and (iii) is not involved in any DNA repair pathway. Therefore, analysing PtrA expression would take us away from the key questions of our study.
(3) The authors agree that they cannot exclude the possibility of sRNA being involved in the translation regulation. However, this can be tested by performing the imaging experiments in the presence of Hfq proximal face mutations, which largely disrupt binding of sRNAs.
(4) The data on construct with a long region of Hfq binding site on recB mRNA deleted is less convincing. There is no control to show that removing this sequence region itself has no effect on translation, and the effect is solely due to the lack of Hfq binding. A better experiment would be using a Hfq distal face mutant that is deficient in binding to the ARN motifs.
We thank the referee for these suggestions. We have performed the requested experiments, and the quantification of RecB abundance in the presence of Hfq proteins mutated in the proximal and distal face will be added to the revised version of the manuscript.
(5) Ln 249-251: The authors claim that the stability of recB mRNA is not changed in ∆hfq simply based on the steady-state mRNA level. To claim so, the lifetime needs to be measured in the absence of Hfq.
We agree that this statement is not fully supported by our data and will address this issue in the revised version.
(6) What's the labeling efficiency of Halo-tag? If not 100% labeled, is it considered in the protein number quantification? Is the protein copy number quantification through imaging calibrated by an independent method? Does Halo tag affect the protein translation or degradation?
Our previous study (DOI: 10.1038/s41598-019-44278-0) described a detailed characterisation of the HaloTag labelling technique for quantifying low-copy proteins in single E. coli cells.
In that study, we used RecB-HaloTag as an example of a low-copy number protein. We showed a complete quantitative agreement of RecB detection between two fully independent methods: HaloTag-based labelling with cell fixation and RecB-sfGFP combined with a microfluidic device that lowers protein diffusion in the bacterial cytoplasm. This second method has previously been validated for protein quantification (DOI: 10.1038/ncomms11641) and provides detection of 80-90% of the labelled protein. Additionally, in our protocol, immediate chemical fixation of cells after the labelling and quick washing steps ensure that new, unlabelled RecB proteins are not produced. We, therefore, conclude that our approach to RecB detection is highly reliable and sufficient for comparing RecB production in different conditions and mutants.
The RecB-HaloTag construct has been designed for minimal impact on RecB production and function. The HaloTag is translationally fused to RecB in a loop positioned after the serine present at position 47 where it is unlikely to interfere with (i) the formation of RecBCD complex (based on RecBCD structure, DOI: 10.1038/nature02988), (ii) the initiation of translation (as it is far away from the 5’UTR and the beginning of the open reading frame) and (iii) conventional C-terminal-associated mechanisms of protein degradation (DOI: 10.15252/msb.20199208). In our manuscript, we showed that the RecB-HaloTag degradation rate is similar to the dilution rate due to bacterial growth. This is in line with a recent study on unlabelled proteins, which shows that RecB’s lifetime is set by the cellular growth rate (https://doi.org/10.1101/2022.08.01.502339) and indicates that the HaloTag fusion is not affecting RecB stability.
Furthermore, we have demonstrated (DOI: 10.1038/s41598-019-44278-0) that (i) bacterial growth is not affected by replacing the native RecB with RecB-HaloTag, (ii) RecB-HaloTag is fully functional upon DNA damage, and (iii) no proteolytic processing of the RecB-HaloTag is detected by Western blot.
These results suggest that RecB expression and functionality are unlikely to be affected by the translational HaloTag insertion at Ser-47 in RecB. In the revised version of the manuscript, we will add information about the construct and discuss the reliability of the quantification.
(7) Upper panel of Fig S8a is redundant as in Fig 5B. Seems that Fig S8d is not described in the text.
Indeed, the data in the upper panel in Fig S8a was repeated (from Fig 5B) for visual purposes to facilitate comparison with the panel below. We will modify the figure legend to indicate this repetition clearly.
In Fig S8d, we confirmed the functionality of the Hfq protein expressed from the pQE-Hfq plasmid in our experimental conditions, which was not described in the text. We will include this clarification in the updated manuscript.
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In Südwestfrankreich wurden Anfan Oktober mit über 35° die höchsten Oktobertemperaturen der Messgeschichte festgestellt. An einem Tag wurden in 350 Städten Temperaturrekorde gebrochen. Vorangegangen waren Rekordtemperaturen im September. https://www.liberation.fr/environnement/climat/355-degres-dans-le-tarn-le-record-de-chaleur-pour-un-mois-doctobre-deja-battu-20231002_NJ6VFMGT4VDB5NL3JOISU7SDCY/?redirected=1
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Der italienische Konzern Eni beginnt mit der Öl- und Gasforderung vor der Elfenbeinküste. Bei der Behauptung, es handele sich um das erste emissionsfreie Förderprojekt, werden die Emissionen durch Verbrennung der Produkte nicht berücksichtigt. Geplant ist eine Steigerung der Produktion bis auf täglich 150.000 Barrel Öl und ca. 5,6 Millionen Kubikmeter Gas. Das Erdgas wird über eine Pipeline an die Elfenbeinküste geliefert.
Zu Eni: https://hypothes.is/search?q=tag%3A%22actor%3A%20Eni%22
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20 reiche Länder planen bis 2050 neue Öl- und Gas-Projekte, die zusammen weitere 173 Gigatonnen CO<sub>2</sub>-Emissionen verursachen werden, wenn es nicht gelingt sie zu stoppen. Oil Change International hat einen Bericht über den Anteil der verschiedenen Staaten an den Expansionsplänen veröffentlicht. Mit einem Drittel entfällt der Hauptanteil auf die USA.
Mehr zur fossilen Expansion: https://hypothes.is/search?q=tag%3A%22process%3A%20fossil%20development%22
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Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
In their manuscript, Yu et al. describe the chemotactic gradient formation for CCL5 bound to - i.e. released from - glycosaminoglycans. The authors provide evidence for phase separation as the driving mechanism behind chemotactic gradient formation. A conclusion towards a general principle behind the finding cannot be drawn since the work focuses on one chemokine only, which is particularly prone to glycan-induced oligomerisation.
Strengths:
The principle of phase separation as a driving force behind and thus as an analytical tool for investigating protein interactions with strongly charged biomolecules was originally introduced for protein-nucleic acid interactions. Yu et al. have applied this in their work for the first time for chemokine-heparan sulfate interactions. This opens a novel way to investigate chemokine-glycosaminoglycan interactions in general.
Response: Thanks for the encouragement of the reviewer.
Weaknesses:
As mentioned above, one of the weaknesses of the current work is the exemplification of the phase separation principle by applying it only to CCL5-heparan sulfate interactions. CCL5 is known to form higher oligomers/aggregates in the presence of glycosaminoglycans, much more than other chemokines. It would therefore have been very interesting to see, if similar results in vitro, in situ, and in vivo could have been obtained by other chemokines of the same class (e.g. CCL2) or another class (like CXCL8).
Response: We share the reviewer’s opinion that to investigate more molecules/cytokines that interact with heparan sulfate in the system should be of interesting. We expect that researchers in the field will adapt the concept to continue the studies on additional molecules. Nevertheless, our earlier study has demonstrated that bFGF was enriched to its receptor and triggered signaling transduction through phase separation with heparan sulfate (PMID: 35236856; doi: 10.1038/s41467-022-28765-z), which supports the concept that phase separation with heparan sulfate on the cell surface may be a common mechanism for heparan sulfate binding proteins. The comment of the reviewer that phase separation is related to oligomerization is demonstrated in (Figure 1—figure supplement 2C and D), showing that the more easily aggregated mutant, A22K-CCL5, does not undergo phase separation.
In addition, the authors have used variously labelled CCL5 (like with the organic dye Cy3 or with EGFP) for various reasons (detection and immobilisation). In the view of this reviewer, it would have been necessary to show that all the labelled chemokines yield identical/similar molecular characteristics as the unlabelled wildtype chemokine (such as heparan sulfate binding and chemotaxis). It is well known that labelling proteins either by chemical tags or by fusion to GFPs can lead to manifestly different molecular and functional characteristics.
Response: We agree with the reviewer that labeling may lead to altered property of a protein, thus, we have compared chemotactic activity of CCL5 and CCL5-EGFP (Figure 2—figure supplement 1). To further verify this, we performed additional experiment to compare chemotactic activity between CCL5 and Cy3-CCL5 (see Author response image 1). For the convenience of readers, we have combined the original Figure 2—figure supplement 1 with the new data (Figure R1), which replaced original Figure 2—figure supplement 1.
Author response image 1.
Chemotactic function of CCL5-EGFP and CCL5-Cy3. Cy3-Labeled CCL5 has similar activity as CCL5, 50 nM CCL5 or CCL5-Cy3 were added to the lower chamber of the Transwell. THP-1 cells were added to upper chambers. Data are mean ± s.d. n=3. P values were determined by unpaired two-tailed t-tests. NS, Not Significant.
Reviewer #2 (Public Review):
Although the study by Xiaolin Yu et al is largely limited to in vitro data, the results of this study convincingly improve our current understanding of leukocyte migration.
(1) The conclusions of the paper are mostly supported by the data although some clarification is warranted concerning the exact CCL5 forms (without or with a fluorescent label or His-tag) and amounts/concentrations that were used in the individual experiments. This is important since it is known that modification of CCL5 at the N-terminus affects the interactions of CCL5 with the GPCRs CCR1, CCR3, and CCR5 and random labeling using monosuccinimidyl esters (as done by the authors with Cy-3) is targeting lysines. Since lysines are important for the GAG-binding properties of CCL5, knowledge of the number and location of the Cy-3 labels on CCL5 is important information for the interpretation of the experimental results with the fluorescently labeled CCL5. Was the His-tag attached to the N- or C-terminus of CCL5? Indicate this for each individual experiment and consider/discuss also potential effects of the modifications on CCL5 in the results and discussion sections.
Response: We agree with the reviewer that labeling may lead to altered property of a protein, thus, we have compared chemotactic activity of CCL5 and CCL5-EGFP (Figure 2—figure supplement 1). To further verify this, we performed additional experiment to compare chemotactic activity between CCL5 and Cy3-CCL5 (see Author response image 1). For the convenience of readers, we have combined the original Figure 2—figure supplement 1 with the new data (Author response image 1), which replaced original Figure 2—figure supplement 1.
The His-tag is attached to the C-terminus of CCL5, in consideration of the potential impact on the N-terminus.
(2) In general, the authors appear to use high concentrations of CCL5 in their experiments. The reason for this is not clear. Is it because of the effects of the labels on the activity of the protein? In most biological tests (e.g. chemotaxis assays), unmodified CCL5 is active already at low nM concentrations.
Response: We agree with the reviewer that the CCL5 concentrations used in our experiments were higher than reported chemotaxis assays and also higher than physiological levels in normal human plasma. In fact, we have performed experiments with lower concentration of CCL5, where the effect of LLPS was not seen though the chemotactic activity of the cytokine was detected. Thus, LLPS-associated chemotactic activity may represent a scenario of acute inflammatory condition when the inflammatory cytokines can increase significantly.
(3) For the statistical analyses of the results, the authors use t-tests. Was it confirmed that data follow a normal distribution prior to using the t-test? If not a non-parametric test should be used and it may affect the conclusions of some experiments.
Response: We thank the reviewer for pointing out this issue. As shown in Author response table 1, The Shapiro-Wilk normality test showed that only two control groups (CCL5 and 44AANA47-CCL5+CHO K1) in Figure 3 did not conform to the normal distribution. The error was caused by using microculture to count and calculate when there were very few cells in the microculture. For these two groups, we re-counted 100 μL culture medium to calculate the number of cells. The results were consistent with the positive distribution and significantly different from the experimental group (Author response image 3). The original data for the number of cells chemoattractant by 500 nM CCL5 was revised from 0, 247, 247 to 247, 123, 370 and 500 nM 44AANA47 +CHO-K1 was revised from 1111, 1111, 98 to 740, 494, 617. The revised data does not affect the conclusion.
Author response table 1.
Table R1 Shapiro-Wilk test results of statistical data in the manuscript
Author response image 3.
Quantification of THP-1collected from the lower chamber. Data are mean ± s.d. n=3. P values were determined by unpaired two-tailed t-tests.
Recommendations for the authors:
Reviewer #1:
See the weaknesses section of the Public Review. In addition, the authors should discuss the X-ray structure of CCL5 in complex with a heparin disaccharide in comparison with their docked structure of CCL5 and a heparin tetrasaccharide.
Response: Our study, in fact, is strongly influenced by the report (Shaw, Johnson et al., 2004) that heparin disaccharide interaction with CCL5, which is highlighted in the text (page5, line100-102).
Reviewer #2:
(1) Clearly indicate in the results section and figure legends (also for the supplementary figures) which form and concentration of CCL5 is used.
Response: The relevant missing information is indicated across the manuscript.
(2) Clearly indicate which GAG was used. Was it heparin or heparan sulfate and what was the length (e.g. average molecular mass if known) or source (company?)?
Response: Relevant information is added in the section “Materials and Methods.
(3) Line 181: What do you mean exactly with "tiny amounts"?
Response: “tiny amounts” means 400 transfected cells. This is described in the section of Materials and Methods. It is now also indicated in the text and legend to the figure.
(4) Lines 216-217: This is a very general statement without a link to the presented data. No combination of chemokines is used, in vivo testing is limited (and I agree very difficult). You may consider deleting this sentence (certainly as an opening sentence for the Discussion).
Response: We appreciate very much for the thoughtful suggestion of the reviewer. This sentence is deleted in the revised manuscript.
(5) Why was 5h used for the in vitro chemotaxis assay? This is extremely long for an assay with THP-1 cells.
Response: We apologize for the unclear description. The 5 hr includes 1 hr pre- incubation of CCL5 with the cells enable to form phase separation. After transferring the cells into the upper chamber, the actual chemotactic assay was 4 hr. This is clarified in the Materials and Methods section and the legend to each figure.
(6) Define "Sec" in Sec-CCL5-EGFP and "Dil" in the legend of Figure 4.
Response: The Sec-CCL5-EGFP should be “CCL5-EGFP’’, which has now been corrected. Dil is a cell membrane red fluorescent probe, which is now defined.
(7) Why are different cell concentrations used in the experiment described in Figure 5?
Response: The samples were from three volunteers who exhibited substantially different concentrations of cells in the blood. The experiment was designed using same amount of blood, so we did not normalize the number of the cell used for the experiment. Regardless of the difference in cell numbers, all three samples showed the same trend.
(8) Check the text for some typos: examples are on line 83 "ratio of CCL5"; line 142 "established cell lines"; line 196 "peripheral blood mononuclear cells"; line 224 "to mediate"; line 226 "bind"; line 247 "to form a gradient"; line 248 "of the glycocalyx"; line 343 and 346 "tetrasaccharide"; line 409-410 "wild-type"; line 543 "on the surface of CHO-K1 and CHO-677"; line 568 "white".
Response: Thanks for the careful reading. The typo errors are corrected and Manuscript was carefully read by colleagues.
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Reviewer #2 (Public Review):
Although the study by Xiaolin Yu et al is largely limited to in vitro data, the results of this study convincingly improve our current understanding of leukocyte migration.
(1) The conclusions of the paper are mostly supported by the data and in the revised manuscript clarification is provided concerning the exact CCL5 forms (without or with a fluorescent label or His-tag) and amounts/concentrations that were used in the individual experiments. This is important since it is known that modification of CCL5 at the N-terminus affects the interactions of CCL5 with the GPCRs CCR1, CCR3 and CCR5 and random labeling using monosuccinimidyl esters (as done by the authors with Cy-3) is targeting lysines. The revised manuscript more clearly indicates for each individual experiment which form is used. However, a discussion on the potential effects of the modifications on CCL5 in the results and discussion sections is still missing.<br /> (2) In general, authors used high concentrations of CCL5 in their experiments. In their reply to the comments they indicate that at lower CCL5 concentrations no LLPS is detected. This is important information since it may indicate the need for chemokine oligomerization for LLPS. This info should be added to the manuscript and comparison with for instance the obligate monomer CCL7 and another chemokine such as CXCL4 that easily forms oligomers may clarify whether LLPS is controlled by oligomerization.<br /> (3) Statistical analyses have been improved in the revised manuscript.
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Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.
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Reply to the reviewers
We would like to thank the three reviewers for their time and effort, the constructive criticism, and suggestions to improve the quality of the manuscript. Below, we address the points raised by providing further clarifications or revising the manuscript as indicated.
__Reviewer #1 (Evidence, reproducibility and clarity (Required)): __
This study investigates mitochondrial and apicoplast division and distribution during the life cycle of Plasmodium falciparum. Utilizing the MitoRed reporter line for fluorescent mitochondrial marking and employing high-resolution 3D imaging techniques, including FIB-SEM, the research unveils the dynamics of these essential organelles across various stages of the parasite's development. The authors' work marks a significant step forward in understanding the cellular biology of Plasmodium falciparum, offering novel insights into the dynamics of mitochondrial and apicoplast division. By addressing the additional comments and incorporating recent findings and clarifications, the research not only underscores the complexity of these processes but also situates the study within the continuum of apicomplexan parasite research.
Major comments: • Suitability of Reporter Line for Oocyst Development: The conclusion regarding the limitations of the MitoRed line for oocyst development stages prompts a discussion on alternative approaches, such as mito trackers, to validate observations in these stages. In the current state, it is difficult to conclude whether the data presented are only true for this specific transgenic line.
We agree with the reviewer that the lack of MitoRed salivary gland sporozoites indeed hints to a developmental issue and therefore interpretation of mitochondrial morphology in oocyst stages should be done carefully. Although we would like to verify these observations with a wild-type line, there are several complications with using a MitoTracker staining. Firstly, a general staining procedure will also highlight the much larger and more abundant host mitochondria thus complicating both the actual imaging and interpretation of the data. Secondly, our own data presented in this manuscript demonstrated that MitoTracker stainings of blood-stage parasites should be considered with great care and it remains to be tested whether mosquito-stage parasite viability and mitochondrial morphology remain unaffected. Thirdly, mosquito experiments are time intensive and costly and we lack the time and funding to expand on this part of the work. We therefore decided to move the oocyst data to the supplement and added additional qualifiers for interpretation to the text.
Line 578: “Although these mitochondrial observations should be interpreted with care since oocysts did not form salivary gland populating sporozoites and might therefore not be representing healthy oocysts, in P. berghei liver-stage schizonts, a very similar mitochondrial organization was observed in sub-compartments created by large membrane invaginations.”
To conclude, we think it is important to be open about the limitations of the MitoRed line and discuss this in the paper to provide a balanced view for others that might want to use this line in the future. At the same time, we think that the observation of the mitochondrial organization centers and the great similarity with mitochondrial organization in liver- and blood-stage schizonts offers tentative support for a biologically relevant phenotype and gives new insights that we would like to share in this manuscript, provided that they are interpreted with care.
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Analysis of Mitochondrion and Apicoplast Association with CPs: Could the author elaborate on how their statistical power and image data support assertions of random association between organelles and CPs (line 438-439) and the dynamic nature of Mito-CP interactions (line 504)? In addition, could the authors comment/discuss their findings regarding the distance between Mito-Api compared to the one reported in Figure S2 of Sun et al. preprint: bioRxiv 2022.09.14.508031; doi: https://doi.org/10.1101/2022.09.14.508031
We would like to clarify the point that the reviewer raises. Although we indeed observed that the distances between the CP-mito are significantly smaller compared to CP-apicoplast in schizont 1 in Figure 7, we do not think that there is interaction between the mitochondrion and CPs. In schizont 3-6, the apicoplast shows close apposition with CPs over the complete length of the apicoplast/with all apicoplast fragments and the distances between CPs and apicoplast range from 0-150 nm, therefore we think there is CP-apicoplast interaction. The distance between CPs and mitochondrion is much larger in all schizonts with an average of 500-600 nm, except for schizont 6 where the CP-mito distances become smaller due to the alignment of the mitochondrion with the apicoplast. Still the CP-mito distance is significantly bigger in schizont 6 compared to CP-apicoplast. Therefore, we do not think there are mito-CP interactions in any of the schizont stages. To clarify this in the text, we added the following sentences:
Line 483: “Although the distances between the mitochondrion and CPs (average 616 nm, SD 235 nm) in this early schizont are significantly smaller than the apicoplast-CPs distances (average 1350 nm, SD 260 nm), there is no direct interaction between the mitochondrion and CPs since the smallest CP-mitochondrion distance measured is 332 nm. The significant difference can be explained by the fact that the apicoplast is located in the center of the parasite, while the mitochondrion is larger and stretched throughout the whole cell leading to coincidental closer proximity to the peripheral CPs.”
We have also added extra comparisons of CP-apicoplast and CP-mitochondrion distances to the text to support this (Line 483-503).
We thank the reviewer for their suggestion of comparison with the data from Sun et al. The EM tomography data in that paper are indeed of much higher resolution and hint at physical interaction between the membranes of the mitochondrion and apicoplast. We have added the following sentences to the discussion:
Line 612: “EM tomography data from Sun et al. show there are hints of connecting structures between the mitochondrion and apicoplast in areas where the distance between the organelles is very small and similar to the distance between the inner and outer membranes of the organelles themselves in merozoites, suggesting physical link between the organelles.”
• Incorporation of Recent Findings into Schematic Models: I recommend the authors modify their current model in Figure 8 to reflect on recent findings on CP outer domain contact with the parasite plasma membrane (PPM) post-mitosis as demonstrated by Liffner et al. PMID: 38108809.
We agree with the reviewer that the data from Liffner et al. suggest contact of the outer CP with the PPM, however, we think ExM data should be interpreted with some care. Contact sites are strictly defined as an area where membranes of two organelles are in close proximity to each other, while there is no membrane fusion, there are tethering forces (protein-lipid or protein-protein interaction), and fulfill a specific function (PMID:30894536). The ExM data do not have the resolution to define the CP-PPM appositions as contact sites. Although we indeed see closeness of the CPs and the PPM in our FIB-SEM data, we do not see evidence of a physical contact between the two. Therefore, for this proposed model, we would keep the focus on the division and segregation of the two endosymbiotic organelles.
Minor comments: • Reference to WHO Report: The manuscript cites malaria incidence and mortality data from an older WHO report. Given the availability of the 2022 WHO reports, authors should update the text and citation (line 36).
Changed accordingly.
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Clarification of Host: The term "its mitochondrion" (line 42) should be specified as "human mitochondrion" to clearly distinguish between the two different hosts.
We changed “The malaria parasite harbors a unique mitochondrion that differs greatly from its host mitochondrion” to “The malaria parasite harbors a unique mitochondrion that differs greatly from the human mitochondrion”.
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Terminology of Parasite Development Stages: The usage of "schizogony" to describe division processes in liver and mosquito stages could be misleading due to the distinct process of endopolygeny nuclear-like division observed during sporogony (line 56; PMID: 31805442). I would recommend the authors use a more general language, such as cell division.
Changed accordingly.
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Prior Research on CP and Apicoplast Association: The observation of centriolar plaques (CPs) associating with the apicoplast (line 91) has precedents in the study of other apicomplexan parasites, such as Sarcosystis (PMID: 16079283). Acknowledging and discussing these findings would contextualize the current study within the broader range of the most commonly studied apicomplexan parasites.
We thank the reviewer for this suggestion and added the following sentence and citation to the discussion:
Line 646: ”In other apicomplexan parasites, such as Toxoplasma gondii and Sarcocystis neurona, centrosomes have also been indicated to be involved in apicoplast organization and distribution during cell division.”
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Depth of Imaging Data: Could the authors indicate the width of their z-stack, for instance, in Figure 1? I would also suggest the authors use hours of post-infection (h.p.i) for clarity (lines 234-254) to aid comprehension by a broader audience as they do later in the manuscript.
As suggested we added the depth and interval ranges of the Z-stacks are added to the legends of Figures 1, 2, 3, and 5.
It is common practice to describe the oocyst stages by days instead of hours post infection (of the mosquito; also referred to as days after feeding) as the development takes ~2 weeks. Later in the manuscript, we refer to the development of asexual blood stages, a ~48h cycle, which is commonly referred to by hours post invasion (of the red blood cell). Sticking to common practices in the field, we have decided leave the time indications used unaltered.
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Visualization of Mitochondrial Structures: Suggestions to include or reference images of bulbous mitochondrial structures (line 445) directly in the main text or within key figures (e.g., Figure 6) would help the reader understand what and where are these bulbous structures.
Arrows are added to Figure 6 to indicate bulins.
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Organelle Communication and Division Mechanisms: The discussion of bulbous invagination structures (buildings) (line 469) and their role in organelle division is interesting; could it be also for organelle communication or storage? Can the authors expand the discussion about it?
We have indeed wondered and discussed possible functions of these bulins extensively. While roles in organelle communication or storage are other interesting theories that also crossed our minds, the timing of appearance, the precise location of the bulins at the entrance of developing merozoites at the stage where bulins are most abundant, and their morphological features together to us strongly suggest a link to (mitochondrial) fission, via membrane remodeling and/or the distribution of certain components, such as mitochondrial DNA, proteins, or protein complexes. We would like to keep the focus of the paper at mitochondrial and apicoplast fission and as such we discuss various observations within this context. Discussing all our observations within the wider context of Plasmodium biology would be lead to overly long and unfocused paper and hence we would like to leave these discussions for other manuscripts with a different focus.
Reviewer #1 (Significance (Required)):
The study is a significant contribution to the field of parasitology, particularly in understanding the cellular biology of Plasmodium falciparum. The development of the MitoRed reporter line is a notable advancement, allowing for the real-time visualization of mitochondrial dynamics. This tool could be invaluable for future studies exploring parasite biology's intricacies and identifying new antimalarial drug targets. Furthermore, while the study provides detailed insights into the division and distribution of mitochondria and apicoplasts, the molecular mechanisms underlying these processes remain to be fully elucidated. Specifically, the role of specific proteins in mediating these divisions and the potential interplay between mitochondrial and apicoplast dynamics during parasite development warrant further investigation.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
During its development and growth, the human malaria parasite P. falciparum needs to guarantee that cellular organelles, including the mitochondrion and the apicoplast, will be divided and segregated correctly into the daughter parasites. However, the details and mechanisms of these processes are not clear. Here, authors provide a description of mitochondrial replication and segregation in P. falciparum schizonts, gametocytes and oocysts. They generated a reporter cell line by attaching mScarlet red fluorescent protein to the mitochondrial heat shock protein 70-3 and used high-resolution 3D-imaging and focused ion beam scanning electron microscopy to study mitochondrion dynamics in the asexual, gametocytes and mosquito stages. The authors found that in schizonts, the mitochondrion forms a cartwheel structure at the end of early segmentation stage with full division occurring only at a late stage of schizogony. Apicoplast division happens after nuclear division but is complete before nuclear division is completed. Authors also found apicoplast but not mitochondrion is associated with centriolar plaque (analogue of centrosome in P. falciparum) during the schizogony. At the end, authors proposed their model of nuclei, mitochondrial and apicoplast division in the asexual stage schizogony. This well-written manuscript provides insights on mitochondrion and apicoplast fission in P. falciparum blood stage schizogony and mitochondrion dynamic in the blood, gametocytes and mosquito stages. Questions and suggestions are below:
Major comments The marker line forms mature oocysts but does not produce salivary gland sporozoites. This phenotype needs to be explained more clearly. Are sporozoites produced in the midgut, are they released into the hemocoel?
For clarity, we have expanded our explanation of this phenotype and indicated the limitations of the tool in lines 250-259:
“While several free sporozoites were observed in dissected midguts and salivary glands on day 16 (data not shown), we never observed an oocyst containing fully mature sporozoites with a divided mitochondrion or an infected salivary gland on day 16 and 21 after infection. This indicates that sporozoites are produced and released into the hemocoel, however, they have a health defect that prevents them from infecting the salivary glands. Possibly the mitochondrial marker or the integration in the SIL7 locus causes issues for sporozoite development. We conclude that the MitoRed line is a great tool for mitochondrial visualization in asexual blood stages, gametocytes stages, and mosquito stages up until late oocysts (Supplemental Information S1) but that for studies later in the life cycle other tools need to be developed and tested.”
Does introduction of an exogenous copy of HSP70 influence total HSP70 expression in the parasite, and can this cause the observed defect in sporozoite production? Did authors try to tag the endogenous HSP70 to see if it's a suitable reporter?
For clarity, as we describe in the paper (e.g. lines 113-117) we did not express an additional copy of HSP70-3 but merely fused its promoter region and mitochondrial targeting sequence without any further functional domains to mScarlet. This is a strategy that has been employed with great success to study mitochondrial biology in all life-cycle stages of P. berghei (PMID:29669282). While we cannot formally exclude that the use of a second copy of the HSP70-3 promoter could somehow influence the expression of the endogenous copy, it seems rather unlikely. A plethora of promoters of a wide variety of genes have been used for transgenic expression of e.g. drug cassettes and other fluorescent markers in a multitude of studies and to the best of our knowledge there are no reports of this ever interfering with endogenous expression levels. Although we think it would be interesting to know what exactly causes the defective sporozoite production, this information will not add to our understanding of mitochondrial dynamics in mosquito stages and hence beyond the scope of this study (see also our responses to the previous comment and the first comment of reviewer 1).
Did authors compare the growth of the reporter parasite line to wild-type in gametocytes and oocysts?
Typically, conversion rates of gametocyte inductions are highly variable even within the same experiment. MitoRed gametocytes have been induced in at least five independent experiments. Although we have not performed a direct quantification of gametocyte conversion or growth rates between MitoRed and NF54 WT parasites, stage V male and female MitoRed gametocytes developed normally demonstrating no morphological aberrations in each of these experiments within the expected 12-day time frame, similarly as WT parasites, assessed by light microscopy. As we found no indications for a developmental phenotype deviating from what is commonly observed for wild-type parasites as is shown in supplemental figure S3. We have added comparison of exflagellation events in MitoRed vs WT parasites to figure S4, showing no significant difference and indicating formation of healthy male gametes. Normal healthy of MitoRed gametocytes is further supported by the fact that these parasites infect mosquitos.
A direct comparison of the growth of MitoRed with WT in oocyst stages is challenging, since infections can show high variance. In addition, these experiments are very costly and time intensive. As we focused our work on blood-stage development and because there are limitations in the use of MitoRed when studying subsequent mosquito- and liver-stage development as discussed above and in the manuscript, we decided not to invest our limited resources for a direct comparison with WT, reserving such a comparison for future transgenic lines that present no obvious developmental defects.
In figure 1A and Methods, are all MitoTracker stains incubated at 100 nM for 30 minutes? Did authors try to optimize the conditions to improve quality Mitotracker staining can be improved?
Indeed, all MitoTracker stains were performed at 100 nM, except for the Rhodamin123 used for life imaging. In the past, we have performed several pilot experiments to optimize staining conditions of which 100nM for 30 min most consistently resulted in sufficiently bright yet specific signals. Notably, this is the MitoTracker concentration that is described most frequently in other papers. The use of a lower concentration might indeed improve the mitochondrial morphology in MitoTracker stained parasites, however, for the scope of this paper we wanted to compare our new mitochondrial marker with the most commonly used MitoTracker staining conditions. Combined with the fact that MitoTrackers are toxic at low concentrations, we preferred to step away from MitoTracker when looking at mitochondrial division, to ensure we are looking at biologically relevant mitochondria.
In figure 1B, can authors replace the figures for the first ring? The parasite does not seem healthy and the scale bar is shorter than the others. Can authors define DIC in the legend?
Change accordingly.
In figure 8, it looks like some apicoplasts are not associated with the CP, contrary to what is stated in the text, for eg the one at the 7 o'clock position in stage 3.
It is indeed difficult to find an angle of visualization that shows clearly that all CPs associate with the apicoplast, a common challenge when trying to visualize 3D data in a 2D space. However, in the 3D animated movies that are provided with the manuscript, the reader can observe this association more clearly, as the organelles rotate slowly so that all angles can be observed. We therefore think that these movies are indispensable to demonstrate and clarify things that are difficult to extract from still, non-rotating image.
The Discussion should mention the failure in generating sporozoites from this reporter line Can authors discuss the SIL7 locus as the site of integration, in the context of potential effect of its disruption on sporozoite production.
In the discussion, we briefly mention the limitation of the use of MitoRed. We have now also added a reference to the more extensive discussion of this phenotype in the supplemental information and included an additional sentence in the results section to indicate the limitations. As indicated in response to previous comments, we think it is important to discuss these limitations as well as present the observations we made during oocyst development but to compartmentalize these to an extended, supplementary section. This allows us to keep the focus on fission during blood-stage schizogony and not make the discussion overly lengthy.
Authors should explain criteria for identifying organelles in FIB-SEM images eg mitochondria, apicoplast etc.
We added to following sentence to clarify how we identified the mitochondrion and apicoplast in the FIB-SEM images (lines 387-389):
"The mitochondrion and apicoplast can be recognized by their tubular shape in addition to the double membrane of the mitochondrion and the thicker appearance of the four membranes of the apicoplast.”
FIB-SEM images show other prominent organelles in these images (dense granules? hemozoin crystals?). It would be helpful for reader orientation and greater appreciation of the work if these organelles were marked as well.
We agree with the reviewer it would be an interesting addition to visualize other organelles, such as e.g. dense granules, rhoptries, and IMC, to learn more about general organellar biology of the parasite. However, segmentation of these organelles requires the training of a new deep learning model and/or the manual segmentation of +400 image slices per parasite. This is unfortunately not feasible for us. However, the dataset is going to be available online and we encourage researchers to revisit and reuse the dataset for their own research questions.
Minor comments The format of blood, mosquito and liver stage is not consistent. Eg. in line 17, 22, 56 and 65. Some has a dash line while some doesn't.
We use hyphens (dashes are longer and used between clauses/sentences) as appropriate. That is, when we use “blood-stage” as a compound adjective as in “the blood-stage parasites are” but not when using “stages” as the noun as “the blood stages are”. We have double-checked the entire manuscript once more to ensure correct hyphenation throughout.
In line 36, numbers of cases and death by malaria are by estimation.
Changed accordingly
Can authors define Plasmodium falciparum as P. falciparum in line 37?
It is common practice to write the full name of a species at first mention in the main body of a manuscript (not including the abstract).
The sentence in line 57-59 is confusing. At the end of schizogony, the daughter merozoite/sporozoite has one mitochondrion but it's multiple in the parasite.
We adapted the sentence so it will be clearer to the reader that the parasite has a single mitochondrion that divides into multiple fragments during cell division:
“During P. falciparum cell division, the single parasite mitochondrion needs to be properly divided and distributed among the daughter cells.”
Can authors specify which mitochondrial dyes are toxic in line 76?
We have included the following sentence to clarify:
“However, eight of these dyes were tested in a drug screen all showing IC50 values below 1mM with three, Mito Red, DiOC6, and Rhodamine B being highly active against P. falciparum with IC50 values below 30 nM14,15.”
In line 115, can authors indicate the Gene ID for PfNF54? Can authors define the reported parasite line as MitoRed here instead of line 125?
Although we indeed used NF54 as the parental strain for the MitoRed line, we think the 3D7 gene ID is more useful in this context. The 3D7 genome is used as the reference genome by the entire field and it is much better annotated than the NF54 genome. Furthermore, the genomes are not all too different to start with, as 3D7 is a subclone of the NF54 line.
In line 134 and 540, use punctate instead of 'punctuated'?
Changed accordingly.
In line 161 to 163, can authors also cite ref 19?
Reference 19 (now 20) is cited in line 163 precluding the need for an additional citation in the next sentence.
In line 174, pH change can also trigger gametocytes activation.
Changed accordingly.
In Figure S4, please indicate the percentage of parasites having close apposition of mitochondrion to axonemes.
When we revisited our images to check what percentage of parasites have close appositions of the mitochondrion and the axonemes, we found that in all exflagellating parasites that were analyzed there is close apposition or overlap between the mitochondrial and the tubulin signal. We changed the text to reflect this:
Line 189: “We found close apposition of the dispersed mitochondria to the axonemal tubulin in all 19 exflagellating males that were analyzed (Figure S4B, S4C).”
Line 237 to 239, please clarify why authors think there is one fragment in mitochondrial.
We have added the following sentence to clarify:
Line 239: “Segmentation of the fluorescent signal based on manual thresholding indicated that the mitochondrion consisted of one continuous structure.”
In line 259, the ookinete stage is II to IV.
Stage indications have been corrected.
In line 281, please define RBC.
Changed accordingly.
In figure 5A, please provide a scale bar for the original and reconstructed image. Should the unit of fragment volume be um3 but not um?
We have added scale bars to the original fluorescent images and the unit has been changed to mm3. Unfortunately, it is not really appropriate to provide a 2D scale bar with a 3D image, since this will not take the depth of your image into account, unless an orthographic projection is used. Objects that are more to the front are visualized slightly bigger than things in the back and therefore a scale bar would not help for interpreting the size of the depicted objects.
Can author do a statistical analysis in Fig 5B and 5C to show the stage at which the majority of nuclei and mitochondria divide?
Changed accordingly.
In figure 5D, the labels on Y axis are not the same size.
The two different sizes were used intentionally to show clearly it is a logarithmic instead of a linear scale.
In figure 6, what's the green black color organelle in the first column (like the organelle showing up as 4 in the first one, at 1/2/6/8 o'clock)? Can authors provide annotations of organelles using arrows at least in the supplementary?
We have added annotations of the RBC, food vacuole, rhoptries, parasite membrane and parasitophorous vacuole membrane to the micrograph images in Figure 6 and the Table S3.
In line 717, the font of ul is not consistent with others like line 691.
Changed accordingly
In line 731, 37 {degree sign}C.
Changed accordingly
Reviewer #2 (Significance (Required)):
The mitochondria of human malaria parasite Plasmodium falciparum differs from the host's and is an intriguing drug target. During the asexual blood stage replication, parasite mitochondrial elongates to form a branched network and undergoes rapid fissions to be distributed properly imto daughter merozoites. However, the details of these processes are unknown. In this study, authors use confocal microscopy and FIB-SEM to describe the dynamics of mitochondrial division in the asexual schizont stage, gametocytes and oocysts.
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
Summary The authors developed a new reporter parasite line that can facilitates the study of mitochondria cell biology in sexual and asexual stages of Plasmodium falciparum. This strategy gets around the need for antibodies or MitoTracker, that could be toxic in some parasite stages. The authors further provided new insights into how mitochondria divide and interacts with both apicoplast and centriolar plaques (CPs) using informative and cutting-edge imaging. The study showed that mitochondria get segregated during cellular division in a cartwheel model and aligns with the apicoplast. Finally, they highlight a potential unique association between CPs and apicoplast in the later stages of schizogony that might contributes to apicoplast segregation.
Major comments: 1. The authors should provide a positive control in the form of another mitochondrial marker to validate that the signal provided by the fluorescent parasite is specific to mitochondria. They could try to tag a well-known mitochondria protein in the reported cell line and compare the signal using antibody stain.
Although we agree with the reviewer that a co-localization of the mitochondrial marker with a tagged mitochondrial protein would verify the mitochondrial localization of the marker, we do think that the co-localization with MitoTracker (Figure 1 and Figure S2) is a good validation method. MitoTracker is a widely used and accepted mitochondrial dye to stain mitochondria in Plasmodium species and other eukaryotes. We believe that the co-localization of our mitochondrial marker with several MitoTracker dyes is enough to prove mitochondrial localization.
There should be more rigour in the observations: the authors should provide quantification of how many parasites/fields were analysed and the percentage of observations described in Figure 2. Was this data consistent in different parasites/experiments? How many times were the experiment repeated?
To provide more rigor we have included a more detailed description of the number of experiments, the number of parasites imaged, and the percentage of parasites with the described observation:
Line 159: “For each stage, between 11-19 parasites were imaged over two independent experiments and described observations were consistent over all analyzed parasites.”
Line 181: “While this particular activation experiment was performed on a gametocyte culture that did not exflagellate for unclear reasons, it was repeated twice, and very similar results were found in exflagellating males (n=19) (Figure 2C).”
Line 189: “We found close apposition of the dispersed mitochondria to the axonemal tubulin in all 19 exflagellating males that were analyzed (Figure S4).”
More rigour is required also in the analysis of oocyst: what was the criteria to define 'large oocysts' (lines 241-242)? How many oocysts were analysed?
We have added estimated diameters of the oocyst to provide more defined criteria:
Line 238: “At day 7, small oocysts (~10 mm diameter) were observed with a branched mitochondrial network stretched out throughout the cell (Figure 3C).”
Line 241: “Day 10 oocysts were much larger (~35 mm diameter) and the mitochondrial mesh-like network appeared more organized, also localizing to areas directly below the oocyst wall (Figure 3D).”
Line 243: “Some large oocysts (~70 mm diameter) showed a highly organized mitochondrial network, where mitochondrial branches were organized in a radial fashion around a central organizational point (Figure 3E, S5A).”
Line 247: “Some smaller oocysts (~35 mm diameter) at day 13 showed structures that looked like beginning MOCs (Figure S5B).”
Finally figure 5 also lacks rigour: How were the fragments quantified? How many times were the experiment repeated? Is there any statistical difference in different parasite stages? To clarify how mitochondrial fragments were quantified, we added the following sentences to the materials and methods section:
Line 765: “3D visualization and quantifications were done in Arivis 4D Vision software. For mitochondrial measurements, threshold-based segmentation was used. For nuclei, blob-finder function was used for segmentation. Number of segmented objects and volume of objects was determined by Arivis software.”
The experiment was repeated twice, and the second independent experiment, which shows the same mitochondrial division stages, is added to the supplement (Figure S7). We added the following sentence to the text for clarification (Line 310):
“These mitochondrial division stages were confirmed in a second, independent 3D imaging experiment (Figure S7).”
Statistical analysis between different parasite stages was performed and added to Figure 5.
Minor comments: 1. Error bars in Fig S1. should be in a different colour from the line graph (eg. black or white).
Changing the color of the error bars made the figure less clear to interpret, due to their small size. We therefore decided to leave the image unaltered.
Scale bar in Fig 2D is missing.
As indicated in response to reviewer 2, unfortunately, it is not really appropriate to provide a 2D scale bar with a 3D image, since this will not take the depth of your image into account. That is, things that are more to the front are visualized slightly bigger than things in the back and therefore a scale bar would not help for interpreting the size of the depicted objects.
In Fig 4. a square dotted line should be placed to represent the GAP45 crop area.
Changed accordingly.
In Table S3 the authors should provide a colour legend and highlight mitochondria in the micrographs.
Color legend and annotations of RBC, food vacuole, rhoptries, parasite membrane and parasitophorous vacuole membrane have been added to the table.
Lines 282-286. The authors should try to hypothesize why MitoRed does not work for live imaging during schizogony
Despite several attempts to improve imaging conditions to prevent this, including, reduced laser power, increase time interval, better temperature control, and gassing of the imaging chamber with low oxygen mixed gas, parasites remained unhealthy. In the discussion, we hypothesize that the mitochondrial marker might cause parasites to be unhealthy due to phototoxicity.
In Fig. 6B parasite is misspelled
Changed accordingly.
Reviewer #3 (Significance (Required)):
Significance
The current paper provides a significant advance in the study of mitochondria cell biology in P. falciparum. The authors used a new strategy for mitochondria visualization that works well in most of parasite stages, enabling them to described in detail mitochondria and apicoplast division that can be used as guideline for future work. The limitation of this study, is a lack of mechanisms that might explain the reported observations, which leaves the discussion somewhat speculative.
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Referee #3
Evidence, reproducibility and clarity
Summary
The authors developed a new reporter parasite line that can facilitates the study of mitochondria cell biology in sexual and asexual stages of Plasmodium falciparum. This strategy gets around the need for antibodies or MitoTracker, that could be toxic in some parasite stages. The authors further provided new insights into how mitochondria divide and interacts with both apicoplast and centriolar plaques (CPs) using informative and cutting-edge imaging. The study showed that mitochondria get segregated during cellular division in a cartwheel model and aligns with the apicoplast. Finally, they highlight a potential unique association between CPs and apicoplast in the later stages of schizogony that might contributes to apicoplast segregation.
Major comments:
- The authors should provide a positive control in the form of another mitochondrial marker to validate that the signal provided by the fluorescent parasite is specific to mitochondria. They could try to tag a well-known mitochondria protein in the reported cell line and compare the signal using antibody stain.
- There should be more rigour in the observations: the authors should provide quantification of how many parasites/fields were analysed and the percentage of observations described in Figure 2. Was this data consistent in different parasites/experiments? How many times were the experiment repeated?
- More rigour is required also in the analysis of oocyst: what was the criteria to define 'large oocysts' (lines 241-242)? How many oocysts were analysed?
- Finally figure 5 also lacks rigour: How were the fragments quantified? How many times were the experiment repeated? Is there any statistical difference in different parasite stages?
Minor comments:
- Error bars in Fig S1. should be in a different colour from the line graph (eg. black or white).
- Scale bar in Fig 2D is missing.
- In Fig 4. a square dotted line should be placed to represent the GAP45 crop area.
- In Table S3 the authors should provide a colour legend and highlight mitochondria in the micrographs.
- Lines 282-286. The authors should try to hypothesize why MitoRed does not work for live imaging during schizogony
- In Fig. 6B parasite is misspelled
Significance
The current paper provides a significant advance in the study of mitochondria cell biology in P. falciparum. The authors used a new strategy for mitochondria visualization that works well in most of parasite stages, enabling them to described in detail mitochondria and apicoplast division that can be used as guideline for future work.
The limitation of this study, is a lack of mechanisms that might explain the reported observations, which leaves the discussion somewhat speculative.
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Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
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Referee #2
Evidence, reproducibility and clarity
During its development and growth, the human malaria parasite P. falciparum needs to guarantee that cellular organelles, including the mitochondrion and the apicoplast, will be divided and segregated correctly into the daughter parasites. However, the details and mechanisms of these processes are not clear. Here, authors provide a description of mitochondrial replication and segregation in P. falciparum schizonts, gametocytes and oocysts. They generated a reporter cell line by attaching mScarlet red fluorescent protein to the mitochondrial heat shock protein 70-3 and used high-resolution 3D-imaging and focused ion beam scanning electron microscopy to study mitochondrion dynamics in the asexual, gametocytes and mosquito stages. The authors found that in schizonts, the mitochondrion forms a cartwheel structure at the end of early segmentation stage with full division occurring only at a late stage of schizogony. Apicoplast division happens after nuclear division but is complete before nuclear division is completed. Authors also found apicoplast but not mitochondrion is associated with centriolar plaque (analogue of centrosome in P. falciparum) during the schizogony. At the end, authors proposed their model of nuclei, mitochondrial and apicoplast division in the asexual stage schizogony. This well-written manuscript provides insights on mitochondrion and apicoplast fission in P. falciparum blood stage schizogony and mitochondrion dynamic in the blood, gametocytes and mosquito stages. Questions and suggestions are below:
Major comments
The marker line forms mature oocysts but does not produce salivary gland sporozoites. This phenotype needs to be explained more clearly. Are sporozoites produced in the midgut, are they released into the hemocoel?
Does introduction of an exogenous copy of HSP70 influence total HSP70 expression in the parasite, and can this cause the observed defect in sporozoite production? Did authors try to tag the endogenous HSP70 to see if it's a suitable reporter?
Did authors compare the growth of the reporter parasite line to wild-type in gametocytes and oocysts? In figure 1A and Methods, are all MitoTracker stains incubated at 100 nM for 30 minutes? Did authors try to optimize the conditions to improve quality Mitotracker staining can be improved? In figure 1B, can authors replace the figures for the first ring? The parasite does not seem healthy and the scale bar is shorter than the others. Can authors define DIC in the legend? In figure 8, it looks like some apicoplasts are not associated with the CP, contrary to what is stated in the text, for eg the one at the 7 o'clock position in stage 3. The Discussion should mention the failure in generating sporozoites from this reporter line Can authors discuss the SIL7 locus as the site of integration, in the context of potential effect of its disruption on sporozoite production. Authors should explain criteria for identifying organelles in FIB-SEM images eg mitochondria, apicoplast etc. FIB-SEM images show other prominent organelles in these images (dense granules? hemozoin crystals?). It would be helpful for reader orientation and greater appreciation of the work if these organelles were marked as well.
Minor comments
The format of blood, mosquito and liver stage is not consistent. Eg. in line 17, 22, 56 and 65. Some has a dash line while some doesn't. In line 36, numbers of cases and death by malaria are by estimation. Can authors define Plasmodium falciparum as P. falciparum in line 37? The sentence in line 57-59 is confusing. At the end of schizogony, the daughter merozoite/sporozoite has one mitochondrion but it's multiple in the parasite. Can authors specify which mitochondrial dyes are toxic in line 76? In line 115, can authors indicate the Gene ID for PfNF54? Can authors define the reported parasite line as MitoRed here instead of line 125? In line 134 and 540, use punctate instead of 'punctuated'? In line 161 to 163, can authors also cite ref 19? In line 174, pH change can also trigger gametocytes activation. In Figure S4, please indicate the percentage of parasites having close apposition of mitochondrion to axonemes. Line 237 to 239, please clarify why authors think there is one fragment in mitochondrial. In line 259, the ookinete stage is II to IV. In line 281, please define RBC. In figure 5A, please provide a scale bar for the original and reconstructed image. Should the unit of fragment volume be um3 but not um? Can author do a statistical analysis in Fig 5B and 5C to show the stage at which the majority of nuclei and mitochondria divide? In figure 5D, the labels on Y axis are not the same size. In figure 6, what's the green black color organelle in the first column (like the organelle showing up as 4 in the first one, at 1/2/6/8 o'clock)? Can authors provide annotations of organelles using arrows at least in the supplementary? In line 717, the font of ul is not consistent with others like line 691. In line 731, 37 {degree sign}C.
Significance
The mitochondria of human malaria parasite Plasmodium falciparum differs from the host's and is an intriguing drug target. During the asexual blood stage replication, parasite mitochondrial elongates to form a branched network and undergoes rapid fissions to be distributed properly imto daughter merozoites. However, the details of these processes are unknown. In this study, authors use confocal microscopy and FIB-SEM to describe the dynamics of mitochondrial division in the asexual schizont stage, gametocytes and oocysts.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This manuscript describes some biochemical experiments on the crucial virulence factor EsxA (ESAT-6) of Mycobacterium tuberculosis. EsxA is secreted via the ESX-1 secretion system. Although this system is recognized to be crucial for virulence the actual mechanisms employed by the ESX-1 substrates are still mostly unknown. The EsxA substrate is attracting most attention as the central player in virulence, especially phagosomal membrane disruption. EsxA is secreted as a dimer together with EsxB. The authors show that EsxA is also able to form homodimers and even tetramers, albeit at very low pH (below 5). Furthermore addition of a nanobody that specifically binds EsxA is blocking intracellular survival, also if the nanobody is produced in the cytosol of the infected macrophages.
Strengths:
Decent biochemical characterization of EsxA and identification of a new and interesting tool to study the function of EsxA (nanobody). Well written.
Weaknesses:
The findings are not critically evaluated using extra experiments or controls.<br /> For instance, tetrameric EsxA in itself is interesting and could reveal how EsxA works. But one would say that this is a starting point to make small point mutations that specifically affect tetramer formation and then evaluate what the effect is on phagosomal membrane lysis. Also one would like to see experiments to indicate whether these structures can be produced under in vitro conditions, especially because it seems that this mainly happens when the pH is lower than 5, which is not normally happening in phagosomes that are loaded with M. tuberculosis.<br /> Also the fact that the addition of the nanobody, either directly to the bacteria or produced in the cytosol of macrophages is interesting, but again the starting point for further experimentation. As a control one would like to se the effect on an Esx-1 secretion mutant. Furthermore, does cytososlic production or direct addition of the nanobody affect phagosomal escape? What happens if an EsxA mutant is produced that does not bind the nanobody?<br /> Finally, it is a bit strange that the authors use a non-native version of esxA that has not only an additional His-tag but also an additional 12 amino acids, which makes the protein in total almost 20% bigger. Of course these additions do not have to alter the characteristics, but they might. On the other hand they easily discard the natural acetylation of EsxA by mycobacteria itself (proven for M. marinum) as not relevant for the function because it might not happen in (the close homologue) M. tuberculosis.
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www.reddit.com www.reddit.com
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where do I start?
reply to u/rocklover7 at https://www.reddit.com/r/typewriters/comments/1cnljgm/where_do_i_start/
The best thing you could do is to take a moment at the library or bookshop and pick up a copy of Polt, Richard. The Typewriter Revolution: A Typist’s Companion for the 21st Century. 1st ed. Woodstock, VT: Countryman Press, 2015.
He looks at typewriters from a writers' writer perspective which I'm sure you'll appreciate. He's got experience with a wide variety of machines as well as a large collection himself. He goes over all of the common/popular (and solid machines) in a variety of sizes and formats to help you figure out which one you might like to start out with. He also covers some of the common problems and repairs that regularly pop up. The book is really a "best of" list of typewriter material from the past 15+ years of this reddit forum and material from the "typosphere" of which he's been not only an active member, but literal ring-leader. The vast majority of the questions which appear on a weekly basis here are discussed and addressed in his book, along with some emphasis on writerly concerns and practice which most beginners here wouldn't be asking. Even reading 3 or 4 of the 8 chapters which are rife with images will give you a solid crash course for exactly the sorts of typewriter (and writing) advice you're searching for.
Definitely DO NOT pick up a new machine off of Amazon. They're even worse than some of the late 70s/early 80s machines. Instead, for beginners (and for the value) I'd recommend looking at Remingtons (Quiet-Riter), Royals (Quiet De Luxe), or Smith-Coronas (Clipper, Silent, Super) from roughly 1948-1958 which is generally the peak of U.S. typewriter manufacturing as well as for features. These were all built like tanks and are usually still in very good condition, even when they're in bad condition. I've provided links to some of these models in the typewriter database, so you have an idea visually of what to look out for.
If desperate, and you live in an area where machines are priced starting over $50 or you're more price sensitive (making eBay, Facebook Marketplace or Craigslist less appealing), you can find some of these every day listed at shopgoodwill.com starting at $10. Even with heaving bidding on auctions, these usually don't go over $35 (except for some of the Smith-Coronas). I've even seen them (sadly) not move at all for $10. This would give you an incredibly solid and inexpensive machine to tinker on, and will most likely work for you out of the box (as long as it's got a ribbon.) You'll end up with a solid machine to start off on while you search for your dream machine. It'll also give you some experience cleaning up and maintaining one. Of the seven machines I've gotten this way and paid an average of about $30-35 each (all in with shipping, tax, etc.) All but one were all immediately usable and only needed moderate cleaning that one could do at home with a cloth, dish soap, a toothbrush and maybe some canned air. Two of the seven were in near mint condition and didn't need any work at all. Tag/garage sales are also inexpensive options that usually allow you test out a machine, but it requires some shoe leather and lots of patience. If you've got a favorite author you love and trust, you might try searching out their machines: https://site.xavier.edu/polt/typewriters/typers.html
If there are any type-ins in your local area, try to go so you can not only meet others, but it might give you a chance to see and try out the machines of others to see what might suit you best.
Happiness and best wishes on your search!
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karammdskin.com karammdskin.com
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THE TRIFECTA The Path to Great Skin is Simple
We need to incorporate the brand value prop into this tag and message
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Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.
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Reply to the reviewers
Reply to reviewer comments
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We extend our gratitude to the reviewers for their time and valuable feedback on our manuscript. We especially appreciate the insightful suggestions that have significantly contributed to refining our work and elucidating our findings. With the revisions made to the text and the inclusion of new experimental data, we believe our manuscript now effectively addresses all reviewer comments. We eagerly await your evaluation of our revised submission.
Small ARF-like GTPases play fundamental roles in dynamic signaling processes linked with vesicular trafficking in eukaryotes. Despite of their evolutionary conservation, there is little known about the ARF-like GTPase functions in plants. Our manuscript reports the biochemical and cell biological characterization of the small ARF-like GTPase TTN5 from the model plant Arabidopsis thaliana*. Fundamental investigations like ours are mostly lacking for ARF and ARL GTPases in Arabidopsis. *
We employed fluorescence-based enzymatic assays suited to uncover different types of the very rapid GTPase activities for TTN5. The experimental findings are now illustrated in a more comprehensive modified Figure 2 and in the form of a summary of the GTPase activities for TTN5 and its mutant variants in the NEW Figure 7A in the Discussion part. Taken together, we found that TTN5 is a non-classical GTPase based on its enzymatic kinetics. The reviewers appreciated these findings and highlighted them as being „impressive in vitro biochemical characterization" and "major conceptual advance". Since such experiments are "uncommon" for being conducted with plant GTPases, reviewers regarded this analysis as "useful addition to the plant community in general". The significance of these findings is given by the circumstance that „the ARF-like proteins are poorly addressed in Arabidopsis while they could reveal completely different function than the canonical known ARF proteins". Reviewers saw here clearly a "strength" of the manuscript.
With regard to the cell biological investigation and initial assessment of cell physiological roles of TTN5, we now provide requested additional evidence. First of all, we provide NEW data on the localization of TTN5 by immunolocalization using a complementing HA3-TTN5 construct, supporting our initial suggestions that TTN5 may be associated with vesicles and processes of the endomembrane system. The previous preprint version had left the reviewers „less convinced" of cell biological data due to the lack of complementation of our YFP-TTN5 construct, lack of Western blot data and the low resolution of microscopic images. We fully agree that these points were of concern and needed to be addressed. We have therefore intensively worked on these „weaknesses" and present now a more detailed whole-mount immunostaining series with the complementing HA3-TTN5 transgenic line (NEW Figure 4, NEW Figure 3P), Western blot data (NEW Supplementary Figures S7C and D), and we will provide all original images upon publication of our manuscript at BioImage Archives which will provide the high quality for re-analysis. BioImage Archives is an online storage for biological image data associated with a peer-reviewed publication. This way, readers will be able to inspect each image in detail. The immunolocalization data are of particular importance as they indicate that HA3-TTN5 can be associated with punctate vesicle structures and BFA bodies as seen with YFP studies of YFP-TTN5 seedlings. We have re-phrased very carefully and emphasized those localization patterns which are backed up by immunostaining and YFP fluorescence detection of YFP-TTN5 signals. To improve the comprehension, the findings are summarized in a schematic overview in NEW Figure 7B of the Discussion. We have also addressed all other comments related to the cell biological experiments to "provide the substantial improvement" that had been requested. We emphasize that we found two cell physiological phenotypes for the TTN5T30N mutant. YFP-TTN5T30N confers phenotypes, which are differing mobility of the fluorescent vesicles in the epidermis of hypocotyls (see Video material and NEW Supplementary Video Material S1M-O), and a root growth phenotype of transgenic HA3-TTN5T30N seedlings (NEW Figure 3O). We explain the cell physiological phenotypes in relation to enzymatic GTPase data. These findings convince us of the validity of the YFP-TTN5 analysis indicative of TTN5 localization.
*We are deeply thankful to the reviewers for judging our manuscript as "generally well written", "important" and "of interest to a wide range of plant scientists" and "for scientists working in the trafficking field" as it "holds significance" and will form the basis for future functional studies of TTN5. *
We prepared very carefully our revised manuscript in which we address all reviewer comments one by one. Please find our revision and our detailed rebuttal to all reviewer comments below. Changes in the revised version are highlighted by yellow and green color. In the "revised version with highlighted changes".
With these adjustments, we hope that our peer-reviewed study will receive a positive response.
We are looking forward to your evaluation of our revised manuscript and thank you in advance,
Sincerely
Petra Bauer and Inga Mohr on behalf of all authors
*
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__Reviewer #1 (Evidence, reproducibility and clarity (Required)): __
The manuscript from Mohr and collaborators reports the characterization of an ARF-like GTPase of Arabidopsis. Small GTPases of the ARF family play crucial role in intracellular trafficking and plant physiology. The ARF-like proteins are poorly addressed in Arabidopsis while they could reveal completely different function than the canonical known ARF proteins. Thus, the aim of the study is important and could be of interest to a wide range of plant scientists. I am impressed by the biochemical characterization of the TTN5 protein and its mutated versions, this is clearly a very nice point of the paper and allows for proper interpretations of the other results. However, I was much less convinced on the cell biology part of this manuscript and aside from the subcellular localization of the TTN5 I think the paper would benefit from a more functional angle. Below are my comments to improve the manuscript:
1- In the different pictures and movies, TTN5 is quite clearly appearing as a typical ER-like pattern. The pattern of localization further extends to dotty-like structures and structures labeled only at the periphery of the structure, with a depletion of fluorescence inside the structure. These observations raise several points. First, the ER pattern is never mentioned in the manuscript while I think it can be clearly observed. Given that the YFP-TTN5 construct is not functional (the mutant phenotype is not rescued) the ER-localization could be due to the retention at the ER due to quality control. The HA-TTN5 construct is functional but to me its localization shows a quite different pattern from the YFP version, I do not see the ER for example or the periphery-labeled structures. In this case, it will be a crucial point to perform co-localization experiments between HA-TTN5 and organelles markers to confirm that the functional TTN5 construct is labeling the Golgi and MVBs, as does the non-functional one. I am also quite sure that a co-localization between YFP-TTN5 and HA-TTN5 will not completely match... The ER is contacting so many organelles that the localization of YFP-TTN5 might not reflects the real location of the protein.
__Our response: __
At first, we like to state that specific detection of intracellular localization of plant proteins in plant cells is generally technically very difficult, when the protein abundance is not overly high. In this revised version, we extended immunostaining analysis to different membrane compartments, including now immunostaining of complementing HA3-TTN5 in the absence and presence of BFA, along with immunodetection of ARF1 and FM4-64 labeling in roots (NEW Figure 3P, NEW Figure 4A, B). In the revised version, we focus the analysis and conclusions on the fluorescence patterns that overlap between YFP-TTN5 detection and HA3-TTN5 immunodetection. With this, we can be most confident about subcellular TTN5 localization. Please find this NEW text in the Result section (starting Line 323):
„For a more detailed investigation of HA3-TTN5 subcellular localization, we then performed co-immunofluorescence staining with an Alexa 488-labeled antibody recognizing the Golgi and TGN marker ARF1, while detecting HA3-TTN5 with an Alexa 555-labeled antibody (Robinson et al. 2011, Singh et al. 2018) (Figure 4A). ARF1-Alexa 488 staining was clearly visible in punctate structures representing presumably Golgi stacks (Figure 4A, Alexa 488), as previously reported (Singh et al. 2018). Similar structures were obtained for HA3-TTN5-Alexa 555 staining (Figure 4A, Alexa 555). But surprisingly, colocalization analysis demonstrated that the HA3-TTN5-labeled structures were mostly not colocalizing and thus distinct from the ARF1-labeled ones (Figure 4A). Yet the HA3-TTN5- and ARF1-labeled structures were in close proximity to each other (Figure 4A). We hypothesized that the HA3-TTN5 structures can be connected to intracellular trafficking steps. To test this, we performed brefeldin A (BFA) treatment, a commonly used tool in cell biology for preventing dynamic membrane trafficking events and vesicle transport involving the Golgi. BFA is a fungal macrocyclic lactone that leads to a loss of cis-cisternae and accumulation of Golgi stacks, known as BFA-induced compartments, up to the fusion of the Golgi with the ER (Ritzenthaler et al. 2002, Wang et al. 2016). For a better identification of BFA bodies, we additionally used the dye FM4-64, which can emit fluorescence in a lipophilic membrane environment. FM4-64 marks the plasma membrane in the first minutes following application to the cell, then may be endocytosed and in the presence of BFA become accumulated in BFA bodies (Bolte et al. 2004). We observed BFA bodies positive for both, HA3-TTN5-Alexa 488 and FM4-64 signals (Figure 4B). Similar patterns were observed for YFP-TTN5-derived signals in YFP-TTN5-expressing roots (Figure 4C). Hence, HA3-TTN5 and YFP-TTN5 can be present in similar subcellular membrane compartments."
We did not find evidence that HA3-TTN5 can localize at the ER using whole-mount immunostaining (NEW Figure 3P; NEW Figure 4A, B). Hence, we are careful with describing that fluorescence at the ER, as seen in the YFP-TTN5 line (Figure 3M, N) reflects TTN5 localization. We therefore do not focus the text on the ER pattern in the Result section (starting Line 295):
„Additionally, YFP signals were also detected in a net-like pattern typical for ER localization (Figure 3M, N). (...) We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."
*And we discuss in the Discussion section (starting Line 552): *
„We based the TTN5 localization data on tagging approaches with two different detection methods to enhance reliability of specific protein detection. Even though YFP-TTN5 did not complement the embryo-lethality of a ttn5 loss of function mutant, we made several observations that suggest YFP-TTN5 signals to be meaningful at various membrane sites. We do not know why YFP-TTN5 does not complement. There could be differences in TTN5 levels and interactions in some cell types, which were hindering specifically YFP-TTN5 but not HA3-TTN5. (...) Though constitutively driven, the YFP-TTN5 expression may be delayed or insufficient at the early embryonic stages resulting in the lack of embryo-lethal complementation. On the other hand, the very fast nucleotide exchange activity may be hindered by the presence of a large YFP-tag in comparison with the small HA3-tag which is able to rescue the embryo-lethality. The lack of complementation represents a challenge for the localization of small GTPases with rapid nucleotide exchange in plants. Despite of these limitations, we made relevant observations in our data that made us believe that YFP signals in YFP-TTN5-expressing cells at membrane sites can be meaningful."
2- What are the structures with TTN5 fluorescence depleted at the center that appear in control conditions? They look different from the Golgi labeled by Man1 but similar to MVBs upon wortmannin treatment, except that in control conditions MVBs never appear like this. Are they related to any kind of vacuolar structures that would be involved in quality control-induced degradation of non-functional proteins?
Our response:
The reviewer certainly refers to fluorescence images from N. benthamiana leaf epidermal cells where different circularly shaped structures are visible. In these respective structures, the fluorescent circles are depleted from fluorescence in the center, e.g. in Figure 5C, YFP- fluorescent signals in TTN5T30N transformed leaf discs. We suspect that these structures can be of vacuolar origin as described for similar fluorescent rings in Tichá et al., 2020 for ANNI-GFP (reference in manuscript). The reviewer certainly does not refer to swollen MVBs that are seen following wortmannin treatment, as in Figure 5N-P, which look similar in their shape but are larger in size. Please note that we always included the control conditions, namely the images recorded before the wortmannin treatment, so that we were able to investigate the changes induced by wortmannin. Hence, we can clearly say that the structures with depleted fluorescence in the center as in Figure 5C are not wortmannin-induced swollen MVBs.To make these points clear to the reader, we added an explanation into the text (Line 385-388):
„We also observed YFP fluorescence signals in the form of circularly shaped ring structures with a fluorescence-depleted center. These structures can be of vacuolar origin as described for similar fluorescent rings in Tichá et al. (2020) for ANNI-GFP."
3- The fluorescence at nucleus could be due to a proportion of YFP-TTN5 that is degraded and released free-GFP, a western-blot of the membrane fraction vs the cytosolic fraction could help solving this issue.
Our response:
In an α-GFP Western blot using YFP-TTN5 Arabidopsis seedlings, we detected besides the expected and strong 48 kDa YFP-TTN5 band, three additional weak bands ranging between 26 to 35 kDa (NEW Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins expressed from aberrant transcripts. α-HA Western blot controls performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size (Supplementary Figure S7D). We must therefore be cautious about nuclear TTN5 localization and we rephrased the text carefully (starting Line 300):
„We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."
4- It is not so easy to conclude from the co-localization experiments. The confocal pictures are not always of high quality, some of them appear blurry. The Golgi localization looks convincing, but the BFA experiments are not that clear. The MVB localization is pretty convincing but the images are blurry. An issue is the quantification of the co-localizations. Several methods were employed but they do not provide consistent results. As for the object-based co-localization method, the authors employ in the text co-localization result either base on the % of YFP-labeled structures or the % of mCherry/mRFP-labeled structures, but the results are not going always in the same direction. For example, the proportion of YFP-TTN5 that co-localize with MVBs is not so different between WT and mutated version but the proportion of MVBs that co-localize with TTN5 is largely increased in the Q70L mutant. Thus it is quite difficult to interpret homogenously and in an unbiased way these results. Moreover, the results coming from the centroid-based method were presented in a table rather than a graph, I think here the authors wanted to hide the huge standard deviation of these results, what is the statistical meaning of these results?
Our response:
First of all, we like to point out that, as explained above, the BFA experiments are now more clear. We performed additional BFA treatment coupled with immunostaining using HA3-TTN5-expressing Arabidopsis seedlings and coupled with fluorescence analysis using YFP-TTN5-expressing Arabidopsis plants. In both experiments, we observed the typical BFA bodies very clearly (NEW Figure 4B, C).
Second, we like to insist that we performed colocalization very carefully and quantified the data in three different manners. We like to state that there is no general standardized procedure that best suits the idea of a colocalization pattern. Results of colocalization are represented in stem diagrams and table format, including statistical analysis. Colocalization was carried out with the ImageJ plugin JACoP for Pearson's and Overlap coefficients and based on the centroid method. The plotted Pearson's and Overlap coefficients are presented in bar diagrams in Supplementary Figure S8A and C, including statistics. The obtained values by the centroid method are represented in table format in Supplementary Figure S8B and D, which *can be considered a standard method (see Ivanov et al., 2014). *
Colocalization of two different fluorescence signals was performed for the two channels in a specific chosen region of interest (indicating in % the overlapping signal versus the sum of signal for each channel). The differences between the YFP/mRFP and mRFP/YFP ratios indicate that a higher percentage of ARA7-RFP signal is colocalizing with YFP-TTN5Q70L signal than with the TTN5WT or the TTN5T30N mutant form signals, while the YFP signals have a similar overlap with ARA7-positive structures. This is not a contradiction. Presumably this answers well the questions on colocalization.
Please note that upon acceptance for publication, we will upload all original colocalization data to BioImage Archive. Hence, the high-quality data can be reanalyzed by readers.
5- The use of FM4-64 to address the vacuolar trafficking is a hazardous, FM4-64 allows the tracking of endocytosis but does not say anything on vacuolar degradation targeting and even less on the potential function of TTN5 in endosomal vacuolar targeting. Similarly, TTN5, even if localized at the Golgi, is not necessarily function in Golgi-trafficking. __Our response: __
*Perhaps our previous description was misleading. Thank you for pointing this out. We reformulated the text and modified the schematic representation of FM4-64 in NEW Figure 6A: *
"(A), Schematic representation of progressive stages of FM4-64 localization and internalization in a cell. FM4-64 is a lipophilic substance. After infiltration, it first localizes in the plasma membrane, at later stages it localizes to intracellular vesicles and membrane compartments. This localization pattern reflects the endocytosis process (Bolte et al. 2004)."
6- The manuscript lacks in its present shape of functional evidences for a role of TTN5 in any trafficking steps. I understand that the KO mutant is lethal but what are the phenotypes of the Q70L and T30N mutant plants? What is the seedling phenotype, how are the Golgi and MVBs looking like in these mutants? Do the Q70L or T30N mutants perturbed the trafficking of any cargos?
__Our response: __
*We agree fully that functional evidences are interesting to assign roles for TTN5 in trafficking steps. A phenotype associated with TTN5T30N and TTN5Q70L is clearly meaningful. *
First of all, we like to emphasize that it is incorrect that the manuscript lacks functional evidences for a role of TTN5 and the two mutants. In fact, the manuscript even highlights several functional activities that are meaningful in a cellular context. These include different types of kinetic GTPase enzyme activities, subcellular localization in planta and association with different endomembrane compartments and subcellular processes such as endocytosis. We surely agree that future research can focus even more on cell physiological aspects and the physiological functions in plants to examine the proposed roles of TTN5 in intracellular trafficking steps. For such studies, our findings are the fundamental basis.
Concerning the aspect of colocalization of the mutants with the markers we show in Figure 5C, D and G, H that YFP-TTN5T30N- and YFP-TTN5Q70L-related signals colocalize with the Golgi marker GmMan1-mCherry. Figure 5K, L and O, P show that YFP-TTN5T30N and YFP-TTN5Q70L-related signals can colocalize with the MVB marker, and this may affect relevant vesicle trafficking processes and plasma membrane protein regulation involved in root cell elongation.
*At present, we have not yet investigated perturbed cargo trafficking. These aspects are certainly interesting but require extensive work and testing of appropriate physiological conditions and appropriate cargo targets. We discuss future perspectives in the Discussion. We agree that such functional information is of great importance, but needs to be clarified in future studies. *
__Reviewer #1 (Significance (Required)): __
In conclusion, I think this manuscript is a good biochemical description of an ARF-like protein but it would need to be strengthen on the cell biology and functional sides. Nonetheless, provided these limitations fixed, this manuscript would advance our knowledge of small GTPases in plants. The major conceptual advance of that study is to provide a non-canonical behavior of the active/inactive cycle dynamics for a small-GTPase. Of course this dynamic probably has an impact on TTN5 function and involvement in trafficking, although this remains to be fully demonstrated. Provided a substantial amount of additional experiments to support the claims of that study, this study could be of general interest for scientist working in the trafficking field.
__Our response: __
We thank reviewer 1 for the very fruitful comments. We hope that with the additional experiments, NEW Figures and NEW Supplementary Figures as well as our changes in the text, all comments by the reviewer have been addressed.
__Reviewer #2 (Evidence, reproducibility and clarity (Required)): __
The manuscript by Mohr and colleagues characterizes the Arabidopsis predicted small GTPase TITAN5 in both biochemical and cell biology contexts using in vitro and in planta techniques. In the first half of the manuscript, the authors use in vitro nucleotide exchange assays to characterise the GTPase activity and nucleotide binding properties of TITAN5 and two mutant variants of it. The in vitro data they produce indicates that TITAN5 does indeed have general GTPase and nucleotide binding capability that would be expected for a protein predicted to be a small GTPase. Interestingly, the authors show that TITAN5 favors a GTP-bound form, which is different to many other characterized GTPases that favor GDP-binding. The authors follow their biochemical characterisation of TITAN with in planta experiments characterizing TITAN5 and its mutant variants association with the plant endomembrane system, both by stable expression in Arabidopsis and transient expression in N.benthamiana.
The strength of this manuscript is in its in vitro biochemical characterisation of TITAN5 and variants. I am not an expert on in vitro GTPase characterisation and so cannot comment specifically on the assays they have used, but generally speaking this appears to have been well done, and the authors are to be commended for it. In vitro characterisation of plant small GTPases is uncommon, and much of our knowledge is inferred for work on animal or yeast GTPases, so this will be a useful addition to the plant community in general, especially as TITAN5 is an essential gene. The in planta data that follows is sadly not as compelling as the biochemical data, and suffers from several weaknesses. I would encourage the authors to consider trying to improve the quality of the in planta data in general. If improved and then combined with the biochemical aspects of the paper, this has the potential to make a nice addition to plant small GTPase and endomembrane literature.
The manuscript is generally well written and includes the relevant literature.
Major issues:
- The authors make use of a p35s: YFP-TTN5 construct (and its mutant variants) both stably in Arabidopsis and transiently in N.benthamiana. I know from personal experience that expressing small GTPases from non-endogenous promoters and in transient expression systems can give very different results to when working from endogenous promoters/using immunolocalization in stable expression systems. Strong over-expression could for example explain why the authors see high 'cytosolic' levels of YFP-TTN5. It is therefore questionable how much of the in planta localisation data presented using p35S and expression in tobacco is of true relevance to the biological function of TITAN5. The authors do present some immunolocalization data of HA3-TTN5 in Arabidopsis, but this is fairly limited and it is very difficult in its current form to use this to identify whether the data from YFP-TTN5 in Arabidopsis and tobacco can be corroborated. I would encourage the authors to consider expanding the immunolocalization data they present to validate their findings in tobacco. __Our response: __
We are aware that endogenous promoters may be preferred over 35S promoter. However, the two types of lines we generated with endogenous promoter did both not show fluorescent signals so that we could unfortunately not use them (not shown). Besides 35S promoter-mediated expression we were also investigating inducible expression vectors for fluorescence imaging in N. benthamiana (not shown). Both inducible and constitutive expression showed very similar expression patterns so that we chose characterizing in detail the 35S::YFP-TTN5 fluorescence in both N. bethamiana*and Arabidopsis. *
We have expanded immunolocalization using the HA3-TTN5 line and compare it now along with YFP fluorescence signal in YFP-TTN5 seedlings (NEW Figure 3P; NEW Figure 4).
„For a more detailed investigation of HA3-TTN5 subcellular localization, we then performed co-immunofluorescence staining with an Alexa 488-labeled antibody recognizing the Golgi and TGN marker ARF1, while detecting HA3-TTN5 with an Alexa 555-labeled antibody (Robinson et al. 2011, Singh et al. 2018) (Figure 4A). ARF1-Alexa 488 staining was clearly visible in punctate structures representing presumably Golgi stacks (Figure 4A, Alexa 488), as previously reported (Singh et al. 2018). Similar structures were obtained for HA3-TTN5-Alexa 555 staining (Figure 4A, Alexa 555). But surprisingly, colocalization analysis demonstrated that the HA3-TTN5-labeled structures were mostly not colocalizing and thus distinct from the ARF1-labeled ones (Figure 4A). Yet the HA3-TTN5- and ARF1-labeled structures were in close proximity to each other (Figure 4A). We hypothesized that the HA3-TTN5 structures can be connected to intracellular trafficking steps. To test this, we performed brefeldin A (BFA) treatment, a commonly used tool in cell biology for preventing dynamic membrane trafficking events and vesicle transport involving the Golgi. BFA is a fungal macrocyclic lactone that leads to a loss of cis-cisternae and accumulation of Golgi stacks, known as BFA-induced compartments, up to the fusion of the Golgi with the ER (Ritzenthaler et al. 2002, Wang et al. 2016). For a better identification of BFA bodies, we additionally used the dye FM4-64, which can emit fluorescence in a lipophilic membrane environment. FM4-64 marks the plasma membrane in the first minutes following application to the cell, then may be endocytosed and in the presence of BFA become accumulated in BFA bodies (Bolte et al. 2004). We observed BFA bodies positive for both, HA3-TTN5-Alexa 488 and FM4-64 signals (Figure 4B). Similar patterns were observed for YFP-TTN5-derived signals in YFP-TTN5-expressing roots (Figure 4C). Hence, HA3-TTN5 and YFP-TTN5 can be present in similar subcellular membrane compartments."
- *
Many of the confocal images presented are of poor quality, particularly those from N.benthamiana.
Our response:
All confocal images are of high quality in their original format. To make them accessible, we will upload all raw data to BioImage Archive upon acceptance of the manuscript.
The authors in some places see YFP-TTN5 in cell nuclei. This could be a result of YFP-cleavage rather than genuine nuclear localisation of YFP-TTN5, but the authors do not present western blots to check for this.
__Our response: __
As described in our response to reviewer 1, comment 3, Fluorescence signals were detected within the nuclei of root cells of YFP-TTN5 plants, while immunostaining signals of HA3-TTN5 were not detected in the nucleus. In an α-GFP Western blot using YFP-TTN5 Arabidopsis seedlings, we detected besides the expected and strong 48 kDa YFP-TTN5 band, three additional weak bands ranging between 26 to 35 kDa (NEW Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins expressed from aberrant transcripts. α-HA Western blot controls performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size (Supplementary Figure S7D). We must therefore be cautious about nuclear TTN5 localization and we rephrased the text carefully (starting Line 300):
- *
„We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."
That YFP-TTN5 fails to rescue the ttn5 mutant indicates that YFP-tagged TTN5 may not be functional. If the authors cannot corroborate the YFP-TTN5 localisation pattern with that of HA3-TTN5 via immunolocalization, then the fact that YFP-TTN5 may not be functional calls into question the biological relevance of YFP-TTN5's localisation pattern.
__Our response: __
This refers to your comment 1, please check this comment for a detailed response. Please also see our answer to reviewer 1, comment 1.
At first, we like to state that specific detection of intracellular localization of plant proteins in plant cells is generally technically very difficult, when the protein abundance is not overly high. In this revised version, we extended immunostaining analysis to different membrane compartments, including now immunostaining of complementing HA3-TTN5 in the absence and presence of BFA, along with immunodetection of ARF1 and FM4-64 labeling in roots (NEW Figure 3P, NEW Figure 4A, B). In the revised version, we focus the analysis and conclusions on the fluorescence patterns that overlap between YFP-TTN5 detection and HA3-TTN5 immunodetection. With this, we can be most confident about subcellular TTN5 localization. Please find this NEW text in the Result section (starting Line 323):
„For a more detailed investigation of HA3-TTN5 subcellular localization, we then performed co-immunofluorescence staining with an Alexa 488-labeled antibody recognizing the Golgi and TGN marker ARF1, while detecting HA3-TTN5 with an Alexa 555-labeled antibody (Robinson et al. 2011, Singh et al. 2018) (Figure 4A). ARF1-Alexa 488 staining was clearly visible in punctate structures representing presumably Golgi stacks (Figure 4A, Alexa 488), as previously reported (Singh et al. 2018). Similar structures were obtained for HA3-TTN5-Alexa 555 staining (Figure 4A, Alexa 555). But surprisingly, colocalization analysis demonstrated that the HA3-TTN5-labeled structures were mostly not colocalizing and thus distinct from the ARF1-labeled ones (Figure 4A). Yet the HA3-TTN5- and ARF1-labeled structures were in close proximity to each other (Figure 4A). We hypothesized that the HA3-TTN5 structures can be connected to intracellular trafficking steps. To test this, we performed brefeldin A (BFA) treatment, a commonly used tool in cell biology for preventing dynamic membrane trafficking events and vesicle transport involving the Golgi. BFA is a fungal macrocyclic lactone that leads to a loss of cis-cisternae and accumulation of Golgi stacks, known as BFA-induced compartments, up to the fusion of the Golgi with the ER (Ritzenthaler et al. 2002, Wang et al. 2016). For a better identification of BFA bodies, we additionally used the dye FM4-64, which can emit fluorescence in a lipophilic membrane environment. FM4-64 marks the plasma membrane in the first minutes following application to the cell, then may be endocytosed and in the presence of BFA become accumulated in BFA bodies (Bolte et al. 2004). We observed BFA bodies positive for both, HA3-TTN5-Alexa 488 and FM4-64 signals (Figure 4B). Similar patterns were observed for YFP-TTN5-derived signals in YFP-TTN5-expressing roots (Figure 4C). Hence, HA3-TTN5 and YFP-TTN5 can be present in similar subcellular membrane compartments."
We did not find evidence that HA3-TTN5 can localize at the ER using whole-mount immunostaining (NEW Figure 3P; NEW Figure 4A, B). Hence, we are careful with describing that fluorescence at the ER, as seen in the YFP-TTN5 line (Figure 3M, N) reflects TTN5 localization. We therefore do not focus the text on the ER pattern in the Result section (starting Line 295):
„Additionally, YFP signals were also detected in a net-like pattern typical for ER localization (Figure 3M, N). (...) We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."
*And we discuss in the Discussion section (starting Line 552): *
„We based the TTN5 localization data on tagging approaches with two different detection methods to enhance reliability of specific protein detection. Even though YFP-TTN5 did not complement the embryo-lethality of a ttn5 loss of function mutant, we made several observations that suggest YFP-TTN5 signals to be meaningful at various membrane sites. We do not know why YFP-TTN5 does not complement. There could be differences in TTN5 levels and interactions in some cell types, which were hindering specifically YFP-TTN5 but not HA3-TTN5. (...) Though constitutively driven, the YFP-TTN5 expression may be delayed or insufficient at the early embryonic stages resulting in the lack of embryo-lethal complementation. On the other hand, the very fast nucleotide exchange activity may be hindered by the presence of a large YFP-tag in comparison with the small HA3-tag which is able to rescue the embryo-lethality. The lack of complementation represents a challenge for the localization of small GTPases with rapid nucleotide exchange in plants. Despite of these limitations, we made relevant observations in our data that made us believe that YFP signals in YFP-TTN5-expressing cells at membrane sites can be meaningful."
- *
Without a cell wall label/dye, the plasmolysis data presented in Figure 5 is hard to visualize.
__Our response: __
Figure 6E-G (previously Fig. 5) show the results of plasmolysis experiments with YFP-TTN5 and the two mutant variant constructs. It is clearly possible to observe plasmolysis when focusing on the Hechtian strands. Hechtian strands are formed due to the retraction of the protoplast as a result of the osmotic pressure by the added mannitol solution. Hechtian strands consist of PM which remained in contact with the cell wall, visible as thin filamental structures. We stained the PM and the Hechtian strands by the PM dye FM4-64. This is similary done in Yoneda et al., 2020. We could detect in the YFP-TTN5-transformed cells, colocalization with the YFP channels and the PM dye in filamental structures between two neighbouring FM4-64-labelled PMs. Although an additional labeling of the cell wall may further indicate plasmolysis, it is not needed here.
Please consider that we will upload all original image data to BioImage Archive so that a detailed re-investigation of the images can be done.
- *
__Minor issues: __
In some of the presented N.benthamiana images, it looks like YFP-TTN5 may be partially ER-localised. However, co-localisation with an ER marker is not presented.
Our response:
*Referring to our response to comments 1 and 3 of reviewer 2 and to comment 1 of reviewer 1: *
We did not find evidence that HA3-TTN5 can localize at the ER using whole-mount immunostaining (NEW Figure 3P; NEW Figure 4A, B). Hence, we are careful with describing that fluorescence at the ER, as seen in the YFP-TTN5 line (Figure 3M, N) reflects TTN5 localization. We therefore do not focus the text on the ER pattern in the Result section (starting Line 295):
„Additionally, YFP signals were also detected in a net-like pattern typical for ER localization (Figure 3M, N). (...) We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."
*And we discuss in the Discussion section (starting Line 552): *
„We based the TTN5 localization data on tagging approaches with two different detection methods to enhance reliability of specific protein detection. Even though YFP-TTN5 did not complement the embryo-lethality of a ttn5 loss of function mutant, we made several observations that suggest YFP-TTN5 signals to be meaningful at various membrane sites. We do not know why YFP-TTN5 does not complement. There could be differences in TTN5 levels and interactions in some cell types, which were hindering specifically YFP-TTN5 but not HA3-TTN5. (...) Though constitutively driven, the YFP-TTN5 expression may be delayed or insufficient at the early embryonic stages resulting in the lack of embryo-lethal complementation. On the other hand, the very fast nucleotide exchange activity may be hindered by the presence of a large YFP-tag in comparison with the small HA3-tag which is able to rescue the embryo-lethality. The lack of complementation represents a challenge for the localization of small GTPases with rapid nucleotide exchange in plants. Despite of these limitations, we made relevant observations in our data that made us believe that YFP signals in YFP-TTN5-expressing cells at membrane sites can be meaningful."
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There is some inconsistency within the N.benthamiana images. For example, compare Figure 4C of YFP-TTN5T30N to Figure 4O of YFP-TTN5T30N. Figure 4O is presented as being significant because wortmannin-induced swollen ARA7 compartments are labelled by YFP-TTN5T30N. However, structures very similar to these can already been seen in Figure 4C, which is apparently an unrelated experiment. This, to my mind, is likely a result of the very different expression levels between different cells that can be produced by transient expression in N.benthamiana.
__Our response: __
Former Figure 4 is now Figure 5. As detailed in our response to comment 2 of reviewer 1:
The reviewer certainly refers to fluorescence images from N. benthamiana leaf epidermal cells where different circularly shaped structures are visible. In these respective structures, the fluorescent circles are depleted from fluorescence in the center, e.g. in Figure 5C, YFP- fluorescent signals in TTN5T30N transformed leaf discs. We suspect that these structures can be of vacuolar origin as described for similar fluorescent rings in Tichá et al., 2020 for ANNI-GFP (reference in manuscript). The reviewer certainly does not refer to swollen MVBs that are seen following wortmannin treatment, as in Figure 5N-P, which look similar in their shape but are larger in size. Please note that we always included the control conditions, namely the images recorded before the wortmannin treatment, so that we were able to investigate the changes induced by wortmannin. Hence, we can clearly say that the structures with depleted fluorescence in the center as in Figure 5C are not wortmannin-induced swollen MVBs.To make these points clear to the reader, we added an explanation into the text (Line 385-388):
„We also observed YFP fluorescence signals in the form of circularly shaped ring structures with a fluorescence-depleted center. These structures can be of vacuolar origin as described for similar fluorescent rings in Tichá et al. (2020) for ANNI-GFP."
**Referees cross-commenting**
It sems that all of the reviewers have converged on the conclusion that the in planta characterisation of TTN5 is insufficient to be of substantial interest to the field, highlighting the fact that major improvements are required to strengthen this part of the manuscript and increase its relevance.
__Reviewer #2 (Significance (Required)): __
General assessment: the strengths of this work are in its in vitro characterisation of TITAN5, however, the in planta characterisation lacks depth.
Significance: the in vitro characterisation of TITAN5 is commendable as such work is lacking for plant GTPases. However, the significance of the work would be boosted substantially by better in planta characterisation, which is where most the most broad interest will lie.
My expertise: my expertise is in in planta characterisation of small GTPases and their interactors.
__Our response: __
We thank the reviewer for the kind evaluation of our manuscript. We are confident that the changes in the text and NEW Figures and NEW Supplementary Figures will be convincing to consider our work.
__Reviewer #3 (Evidence, reproducibility and clarity (Required)): __
Summary: Cellular traffic is an important and well-studied biological process in animal and plant systems. While components involved in transport are known the mechanism by which these components control activity or destination remains to be studied. A critical step in regulating traffic is proper budding and tethering of vesicles. A critical component in determining this step is a family proteins with GTPase activity, which act as switches facilitating vesicle interaction between proteins, or cytoskeleton. The current manuscript by Mohr and colleagues have characterized a small GTPase TITAN5 (TTN5) and identified two residues Gln70 and Thr30 in the protein which they propose to have functional roles. The authors catalogue the localization, GTP hydrolytic activity, and discuss putative functions of TTN5 and the mutants.
__Major comments: __
The core of the manuscript, which is descriptive characterization of TTN5, lies in reliably demonstrating putative roles. While the GTP hydrolysis rates are well-quantified (though the claims need to be toned down), the microscopy data especially the association of TTN5 with different endomembrane compartments is not convincing due to the quality (low resolution) of the figures submitted. The manuscript text is difficult to navigate due to repetition and inconsistency in the order that the mutants are referred. I am requesting additional experiments which should be feasible considering the authors have all the materials required to perform the experiments and obtain high-quality images which support their claims.
In general the figure quality needs to be improved for all microscopy images. I would suggest that the authors highlight 1-2 individual cells to make their point and use the current images as supplementary to establish a broader spread. __Our response: __
*We have worked substantially on the text and figures to make the content well comprehensive. The mutants are referred to in a consistent manner in the text and figures. We have addressed requested experiments. *
As we pointed out in the cover letter and our responses to reviewers 1 and 2, we will upload all raw image data to BioImage Archive upon acceptance of the manuscript so that they can be re-examined without any reduction of resolution. Furthermore, we have conducted new experiments on immunolocalization of HA3-TTN5 (NEW Figure 3P, NEW Figure 4A, B). The text has been improved in several places (see highlighted changes in the manuscript and as detailed in the responses to reviewer 1. We think, this addresses well the reviewers' concerns.
Fig. S1 lacks clarity. __Our response: __
Supplementary Figure S1 shows TTN5 gene expression in different organs and growing stages as revealed by transcriptomic data, made available through the AtGenExpress eFB tool of the Bio-Analytic Resource for Plant Biology (BAR). The figure visualizes that TTN5 is ubiquitously expressed in different plant organs and tissues, e.g. the epidermis layers that we investigated here, and throughout development including embryo development. In accordance with the embryo-lethal phenotype, this highlights well that TTN5* is needed throughout for plant growth and it emphasizes that our investigation of TTN5 localization in epidermis cells is valid. *
We have added a better description to the figure legend. We now also mention the respective publications from which the transcriptome data-sets are derived. The modified figure legend is:
"Supplementary Figure S1. Visualization of TTN5 gene expression levels during plant development based on transcriptome data. Expression levels in (A), different types of aerial organs at different developmental stages; from left to right and bottom to top are represented different seed and plant growth stages, flower development stages, different leaves, vegetative to inflorescence shoot apex, embryo and silique development stages; (B), seedling root tissues based on single cell analysis represented in form of a uniform manifold approximation and projection plot; (C), successive stages of embryo development. As shown in (A) to (C), TTN5 is ubiquitously expressed in these different plant organs and tissues. In particular, it should be noted that TTN5 transcripts were detectable in the epidermis cell layer of roots that we used for localization of tagged TTN5 protein in this study. In accordance with the embryo-lethal phenotype, the ubiquitous expression of TTN5 highlights its importance for plant growth. Original data were derived from (Nakabayashi et al. 2005, Schmid et al. 2005) (A); (Ryu et al. 2019) (B); (Waese et al. 2017) (C). Gene expression levels are indicated by local maximum color code, ranging from the minimum (no expression) in yellow to the maximum (highest expression) in red."
For the supplementary videos, it is difficult to determine if punctate structures are moving or is it cytoplasmic streaming? Could this be done with a co-localized marker? Considering that such markers have been used later in Fig. 4? __Our response: __
We had detected movement of YFP fluorescent structures in all analyzed YFP-TTN5 plant parts except the root tip. Movement of fluorescence signals in YFP-TTN5T30N seedlings was slowed in hypocotyl epidermis cells. To answer the reviewer comment, we added three NEW supplemental videos (NEW Supplementary Video Material S1M-O) generated with all the three YFP-TTN5 constructs imaged over time in N. benthamiana leaf epidermal cells upon colocalization with the cis-Golgi marker GmMan1-mCherry as requested by the reviewer. In these NEW videos, some of *the YFP fluorescent spots seem to move together with the Golgi stacks. GmMan1 is described with a stop-and-go directed movement mediated by the actino-myosin system (Nebenführ 1999) and similarly it might be the case for YFP-TTN5 signals based on the colocalization. *
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It would be good if the speed of movement is quantified, if the authors want to retain the current claims in results and the discussion. __Our response: __
*We describe a difference in the movement of YFP fluorescent signal for the YFP-TTN5T30N variant in the hypocotyl compared to YFP-TTN5 and YFP-TTN5Q70L. In hypocotyl cells, we could observe a slowed down or arrested movement specifically of YFP-TTN5T30N fluorescent structures, and we describe this in the Results section (Line 278-291). *
"Interestingly, the mobility of these punctate structures differed within the cells when the mutant YFP-TTN5T30N was observed in hypocotyl epidermis cells, but not in the leaf epidermis cells (Supplementary Video Material S1E, compare with S1B) nor was it the case for the YFP-TTN5Q70L mutant (Supplementary Video Material S1F, compare with S1E)."
*The slowed movement in the YFP-TTN5T30N mutant is well visible even without quantification. We checked that the manuscript text does not contain overstatements in this regard. *
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Fig.2 I am not sure what the unit / scale is in Fig. 2D/E if each parameter (Kon, Koff, and Kd) are individually plotted? Could the authors please clarify/simplify this panel?
__Our response: __
We presented kinetics for nucleotide association (kon) and dissociation (koff) and the dissociation constant (Kd) in a bar diagram for each nucleotide, mdGDP (Figure 2D) and mGppNHp (Figure 2E). We modified and relabeled the bar diagram representation. It should be now very clear which are the parameters and units. Please see also the other modified figures (NEW modified Figure 2A-H). We also modified the legend of Figure 2D and E:
"(D-E), Kinetics of association and dissociation of fluorescent nucleotides mdGDP (D) or mGppNHp (E) with TTN5 proteins (WT, TTN5T30N, TTN5Q70L) are illustrated as bar charts. The association of mdGDP (0.1 µM) or mGppNHp (0.1 µM) with increasing concentration of TTN5WT, TTN5T30N and TTN5Q70L was measured using a stopped-flow device (see A, B; data see Supplementary Figure S3A-F, S4A-E). Association rate constants (kon in µM-1s-1) were determined from the plot of increasing observed rate constants (kobs in s-1) against the corresponding concentrations of the TTN5 proteins. Intrinsic dissociation rates (koff in s-1) were determined by rapidly mixing 0.1 µM mdGDP-bound or mGppNHp-bound TTN5 proteins with the excess amount of unlabeled GDP (see A, C, data see Supplementary Figure S3G-I, S4F-H). The nucleotide affinity (dissociation constant or Kd in µM) of the corresponding TTN5 proteins was calculated by dividing koff by kon. When mixing mGppNHp with nucleotide-free TTN5T30N, no binding was observed (n.b.o.) under these experimental conditions."
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Are panels D and E representing values for mdGDP and GppNHP? This is not very clear from the figure legend.
__Our response: __
Yes, Figure 2D and E represent the kon, koff and Kd values for mdGDP (Figure 2D) and mGppNHP (Figure 2E). As detailed in our previous response to comment 2a, we modified figure and figure legend to make the representation more clear.
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Fig. 3 Same comments as in para above - improve resolution fo images, concentrate on a few selected cells, if required use an inset figure to zoom-in to specific compartments. Our response:
As detailed in our responses to reviewers 1 and 2, we will upload all original image data to BioImage Archive upon acceptance of the manuscript, so that a detailed investigation of all our images is possible without any reduction of resolution.
Please provide the non-fluorescent channel images to understand cell topography __Our response: __
*We presented our microscopic images with the respective fluorescent channel and for colocalization with an additional merge. We did not present brightfield images as the cell topography was already well visible by fluorescent signal close to the PM. Therefore, brightfield images would not provide any benefit. Since we will upload all original data to BioImage Archive for a detailed investigation of all our images, the data can be obtained if needed. *
Is the nuclear localization seen in transient expression (panel L-N) an artefact? If so, this needs to be mentioned in the text. Our response:
As explained in our responses to reviewers 1 and 2, fluorescence signals were detected within the nuclei of root cells of YFP-TTN5 plants, while immunostaining signals of HA3-TTN5 were not detected in the nucleus.
In an α-GFP Western blot using YFP-TTN5 Arabidopsis seedlings, we detected besides the expected and strong 48 kDa YFP-TTN5 band, three additional weak bands ranging between 26 to 35 kDa (NEW Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins expressed from aberrant transcripts. α-HA Western blot controls performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size (Supplementary Figure S7D). We must therefore be cautious about nuclear TTN5 localization and we rephrased the text carefully (starting Line 300):
„We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."
Fig. 4 - In addition to the points made for Fig. 3 The authors should consider reducing gain/exposure to improve image clarity. Especially for the punctate structures, which are difficult to observe in TTN5, likely because of the cytoplasmic localization as well.
__Our response: __
Thank you for this comment. We record image z-stacks and represent in single z-planes. Reducing the gain to decrease the cytoplasmic signal does not increase the clarity of the punctate structures as the signal strength will become weak.. As mentioned above, we will upload all original image data to BioImage Archive for a detailed investigation of all our images without any reduction of resolution.
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Reducing Agrobacterial load could be considered. OD of 0.4 is a bit much, 0.1 or even 0.05 could be tried. If available try expression in N. tabaccum, which is more amenable to microscopy. However, this is OPTIONAL, benthamiana should suffice. __Our response: __
Thank you for the suggestion. We are routinely using N. benthamiana leaf infiltration. When setting up this method at first, we did not observe different localization results by using different ODs of bacterial cultures. Hence, an OD600 of 0.4 is routinely used in our institute. This value is comparable with the literature although some literature reports even higher OD values for infiltration (Norkunas et al., 2018; Drapal et al., 2021; Zhang et al., 2020, Davis et al., 2020; Stephenson et al., 2018).
A standard norm now is to establish the level of colocalization is by quantifying a pearson's or Mander's correlation. Which I believe has been done in the text, I didn't find a plot representing the same? Could the data (which the authors already have) be plotted alongwith "n" as a table or graph? __Our response: __
*Please check our response to reviewer 1, comment 4. *
We like to insist that we performed colocalization very carefully and quantified the data in three different manners. We like to state that there is no general standardized procedure that best suits the idea of a colocalization pattern. Results of colocalization are represented in stem diagrams and table format, including statistical analysis. Colocalization was carried out with the ImageJ plugin JACoP for Pearson's and Overlap coefficients and based on the centroid method. The plotted Pearson's and Overlap coefficients are presented in bar diagrams in Supplementary Figure S8A and C, including statistics. The obtained values by the centroid method are represented in table format in Supplementary Figure S8B and D, which *can be considered a standard method (see Ivanov et al., 2014). *
Colocalization of two different fluorescence signals was performed for the two channels in a specific chosen region of interest (indicating in % the overlapping signal versus the sum of signal for each channel). The differences between the YFP/mRFP and mRFP/YFP ratios indicate that a higher percentage of ARA7-RFP signal is colocalizing with YFP-TTN5Q70L signal than with the TTN5WT or the TTN5T30N mutant form signals, while the YFP signals have a similar overlap with ARA7-positive structures. This is not a contradiction. Presumably this answers well the questions on colocalization.
Please note that upon acceptance for publication, we will upload all original colocalization data to BioImage Archive. Hence, the high-quality data can be reanalyzed by readers.
The cartoons for the action of chemicals are useful, but need a bit more clarity. Our response:
The schematic explanations of pharmacological treatments and expected outcomes are useful to readers. For a better understanding, we added additional explaining sentences to the figure legends (Figure 5E, M; Figure 6A). We also modified Figure 6A and the corresponding legend.
"(E), Schematic representation of GmMan1 localization at the ER upon brefeldin A (BFA) treatment. BFA blocks ARF-GEF proteins which leads to a loss of Golgi cis-cisternae and the formation of BFA-induced compartments due to an accumulation of Golgi stacks up to a redistribution of the Golgi to the ER by fusion of the Golgi with the ER (Renna and Brandizzi 2020)."
"(M), Schematic representation of ARA7 localization in swollen MVBs upon wortmannin treatment. Wortmannin inhibits phosphatidylinositol-3-kinase (PI3K) function leading to the fusion of TGN/EE to swollen MVBs (Renna and Brandizzi 2020)."
"(A), Schematic representation of progressive stages of FM4-64 localization and internalization in a cell. FM4-64 is a lipophilic substance. After infiltration, it first localizes in the plasma membrane, at later stages it localizes to intracellular vesicles and membrane compartments. This localization pattern reflects the endocytosis process (Bolte et al. 2004)."
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Fig. 5 does the Q70L mutant show reduced endocytosis ?
__Our response: __
We have not investigated this question. As detailed in our response to reviewer 1, *we like to emphasize that we agree fully that functional evidences are interesting to assign role for TTN5 in trafficking steps. A phenotype associated with TTN5T30N and TTN5Q70L would be clearly meaningful. *
Concerning the aspect of colocalization of the mutants with the markers we show in Figure 5C, D and G, H that YFP-TTN5T30N- and YFP-TTN5Q70L-related signals colocalize with the Golgi marker GmMan1-mCherry. Figure 5K, L and O, P show that YFP-TTN5T30N and YFP-TTN5Q70L-related signals can colocalize with the MVB marker, and this may affect relevant vesicle trafficking processes and plasma membrane protein regulation involved in root cell elongation.
*At present, we have not yet investigated perturbed cargo trafficking. These aspects are certainly interesting but require extensive work and testing of appropriate physiological conditions and appropriate cargo targets. We discuss future perspectives in the Discussion. We agree that such functional information is of great importance, but needs to be clarified in future studies. *
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The main text needs to be organized in a way that a reader can separate what is the hypothesis/assumption from actual results and conclusions (see lines #143-149).
Our response:
*Thank you for this comment. We reformulated text throughout the manuscript. *
The text is repeated in multiple places, while I understand that this is not plagiarism, the repetitiveness makes it difficult to read and understand the text. I highlight a couple of examples here, but please check the whole text thoroughly and edit/delete as necessary. a. Lines #124-125 with Lines #149-151 Lines #140-143
__Our response: __
*We checked the text and removed unnecessary repetitions. *
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*
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Could the authors elaborate on whether there are plan homologs of TTN5? Also, have other ARF/ARLs been compared to TTN5 beyond HsARF1? *
Our response:
Phylogenetic trees of the ARF family in Arabidopsis in comparison to human ARF family were already published by Vernoud et al. (2003). In this phylogenetic tree ARF, ARL and SAR proteins of Arabidopsis are compared with the members in humans and S. cervisiae. It is difficult to deduce whether the proteins are homologs or orthologs. In this setting, an ortholog of TTN5 may be HsARL2 followed by HsARL3. In Figure 1A we represented some human GTPases as closely related in sequence to TTN5, these are HsARL2, HsARF1 and AtARF1 since they are the best studied ARF GTPases. HRAS is a well-known member of the RAS superfamily which we used for kinetic comparison in Figure 2. We additionally compared published kinetics of RAC1, HsARF3, *CDC42, RHOA, ARF6, RAD, GEM, and RAS GTPases. *
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On a related note, a major problem I have with these kinetic values is the assumption of significance or not. For eg. Line#180 the values represent and 2 and 6-fold increase, if these numbers do not matter can a significance threshold be applied so as to understand how much fold-change is appreciable?
Our response:
The kinetics of TTN5 and its two mutant variants can be compared with those of other studied GTPases. To provide a basis for the statements about differences in GTPase activities, we modified the text and added respective references in the text for comparisons of fold changes.
The new text is now as follows Line 175-231):
„ We next measured the dissociation (koff) of mdGDP and mGppNHp from the TTN5 proteins in the presence of excess amounts of GDP and GppNHp, respectively (Figure 2C) and found interesting differences (Figure 2D, E; Supplementary Figures S3G-I, S4F-H). First, TTN5WT showed a koff value (0.012 s-1 for mGDP) (Figure 2D; Supplementary Figure S3G), which was 100-fold faster than those obtained for classical small GTPases, including RAC1 (Haeusler et al. 2006)and HRAS (Gremer et al. 2011), but very similar to the koff value of HsARF3 (Fasano et al. 2022). Second, the koffvalues for mGDP and mGppNHp, respectively, were in a similar range between TTN5WT (0.012 s-1 mGDP and 0.001 s-1mGppNHp) and TTN5Q70L (0.025 s-1 mGDP and 0.006 s-1 mGppNHp), respectively, but the koff values differed 10-fold between the two nucleotides mGDP and mGppNHp in TTN5WT (koff = 0.012 s-1 versus koff = 0.001 s-1; Figure 2D, E; Supplementary Figure S3G, I, S4F, H). Thus, mGDP dissociated from proteins 10-fold faster than mGppNHp. Third, the mGDP dissociation from TTN5T30N (koff = 0.149 s-1) was 12.5-fold faster than that of TTN5WT and 37-fold faster than the mGppNHp dissociation of TTN5T30N (koff = 0.004 s-1) (Figure 2D, E; Supplementary Figure S3H, S4G). Mutants of CDC42, RAC1, RHOA, ARF6, RAD, GEM and RAS GTPases, equivalent to TTN5T30N, display decreased nucleotide binding affinity and therefore tend to remain in a nucleotide-free state in a complex with their cognate GEFs (Erickson et al. 1997, Ghosh et al. 1999, Radhakrishna et al. 1999, Jung and Rösner 2002, Kuemmerle and Zhou 2002, Wittmann et al. 2003, Nassar et al. 2010, Huang et al. 2013, Chang and Colecraft 2015, Fisher et al. 2020, Shirazi et al. 2020). Since TTN5T30N exhibits fast guanine nucleotide dissociation, these results suggest that TTN5T30N may also act in either a dominant-negative or fast-cycling manner as reported for other GTPase mutants (Fiegen et al. 2004, Wang et al. 2005, Fidyk et al. 2006, Klein et al. 2006, Soh and Low 2008, Sugawara et al. 2019, Aspenström 2020).
The dissociation constant (Kd) is calculated from the ratio koff/kon, which inversely indicates the affinity of the interaction between proteins and nucleotides (the higher Kd, the lower affinity). Interestingly, TTN5WT binds mGppNHp (Kd = 0.029 µM) 10-fold tighter than mGDP (Kd = 0.267 µM), a difference, which was not observed for TTN5Q70L (Kd for mGppNHp = 0.026 µM, Kd for mGDP = 0.061 µM) (Figure 2D, E). The lower affinity of TTN5WT for mdGDP compared to mGppNHp brings us one step closer to the hypothesis that classifies TTN5 as a non-classical GTPase with a tendency to accumulate in the active (GTP-bound) state (Jaiswal et al. 2013). The Kd value for the mGDP interaction with TTN5T30N was 11.5-fold higher (3.091 µM) than for TTN5WT, suggesting that this mutant exhibited faster nucleotide exchange and lower affinity for nucleotides than TTN5WT. Similar as other GTPases with a T30N exchange, TTN5T30Nmay behave in a dominant-negative manner in signal transduction (Vanoni et al. 1999).
To get hints on the functionalities of TTN5 during the complete GTPase cycle, it was crucial to determine its ability to hydrolyze GTP. Accordingly, the catalytic rate of the intrinsic GTP hydrolysis reaction, defined as kcat, was determined by incubating 100 µM GTP-bound TTN5 proteins at 25{degree sign}C and analyzing the samples at various time points using a reversed-phase HPLC column (Figure 2F; Supplementary Figure S5). The determined kcat values were quite remarkable in two respects (Figure 2G). First, all three TTN5 proteins, TTN5WT, TTN5T30N and TTN5Q70L, showed quite similar kcatvalues (0.0015 s-1, 0.0012 s-1, 0.0007 s-1; Figure 2G; Supplementary Figure S5). The GTP hydrolysis activity of TTN5Q70L was quite high (0.0007 s-1). This was unexpected because, as with most other GTPases, the glutamine mutations at the corresponding position drastic impair hydrolysis, resulting in a constitutively active GTPase in cells (Hodge et al. 2020, Matsumoto et al. 2021). Second, the kcat value of TTN5WT (0.0015 s-1) although quite low as compared to other GTPases (Jian et al. 2012, Esposito et al. 2019), was 8-fold lower than the determined koff value for mGDP dissociation (0.012 s-1) (Figure 2E). This means that a fast intrinsic GDP/GTP exchange versus a slow GTP hydrolysis can have drastic effects on TTN5 activity in resting cells, since TTN5 can accumulate in its GTP-bound form, unlike the classical GTPase (Jaiswal et al. 2013). To investigate this scenario, we pulled down GST-TTN5 protein from bacterial lysates in the presence of an excess amount of GppNHp in the buffer using glutathione beads and measured the nucleotide-bound form of GST-TTN5 using HPLC. As shown in Figure 2H, isolated GST-TTN5 increasingly bonds GppNHp, indicating that the bound nucleotide is rapidly exchanged for free nucleotide (in this case GppNHp). This is not the case for classical GTPases, which remain in their inactive GDP-bound forms under the same experimental conditions (Walsh et al. 2019, Hodge et al. 2020)."
Another issue with the kinetic measurements is the significance levels. Line #198-201. The three proteins are claimed to have similar values and in the nnext line, the Q70L mutant is claimed to be high.
Our response:
Please see our response and changes in the text according in our response to the previous comment 9. We have provided extra explanations and references to clarify why the kinetic behavior of TTN5 is unusual in several respects (Line 215-220).
„First, all three TTN5 proteins, TTN5WT, TTN5T30N and TTN5Q70L, showed quite similar kcat values (0.0015 s-1, 0.0012 s-1, 0.0007 s-1; Figure 2G; Supplementary Figure S5). The GTP hydrolysis activity of TTN5Q70L was quite high (0.0007 s-1). This was unexpected because, as with most other GTPases, the glutamine mutations at the corresponding position drastic impair hydrolysis, resulting in a constitutively active GTPase in cells (Hodge et al. 2020, Matsumoto et al. 2021)."
Provide data for conclusion in line#214-215
Our response:
We agree that a reference should be added after this sentence to make this sentence clearer (Line 228-231).
"As shown in Figure 2H, isolated GST-TTN5 increasingly bonds GppNHp, indicating that the bound nucleotide is rapidly exchanged for free nucleotide (in this case GppNHp). This is not the case for classical GTPases, which remain in their inactive GDP-bound forms under the same experimental conditions (Walsh et al. 2019, Hodge et al. 2020)."
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How were the mutants studied here identified? random mutation or was it directed based on qualified assumptions?
__Our response: __
We used the T30N and the Q70L point mutations as such types of mutants had been reported to confer specific phenotypes in these well-conserved amino acid positions in multiple other small GTPases (Erickson et al. 1997, Ghosh et al. 1999, Radhakrishna et al. 1999, Jung and Rösner 2002, Kuemmerle and Zhou 2002, Wittmann et al. 2003, Nassar et al. 2010, Huang et al. 2013, Chang and Colecraft 2015, Fisher et al. 2020, Shirazi et al. 2020). In particular, these positions affect the interaction between small GTPases and their respective guanine nucleotide exchange factor (GEF; T30N) or on GTP hydrolysis (Q70L). We introduced the mutants and described their potential effect on the GTPase cycle in the introduction and cited exemplary literature. Please see also our response to comment 6 and the proposed text changes (Line 142-151).
Could more simplification be provided for deifitinition of Kon/Koff values. And can these values be compared between mutants directly?
__Our response: __
*We introduce kon and koff in the modified Figure 2D, E, and they are described in the figure legends. Moreover, we present the data for calculations in Supplementary Figures S3, 4, where again we define the values in the respective figure legends. *
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Data provided are not convincing to claim that both the mutant forms have lower association with the Golgi.
__Our response: __
*Our conclusion is that both YFP-TTN5 and YFP-TTN5Q70L fluorescence signals tend to colocalize more with the Golgi-marker signals compared to YFP-TTN5T30N signals as deduced from the centroid-based colocalization method (Line 404-405). *
"Hence, the GTPase-active TTN5 forms are likely more present at cis-Golgi stacks compared to TTN5T30N."
The Pearson coefficients of all three YFP-TTN5 constructs were nearly identical, but we could identify differences in overlapping centers between the YFP and mCherry channel. 48 % of the GmMan1-mCherry fluorescent cis-Golgi stacks were overlapping with signal of YFP-TTN5Q70L, while for YFP-TTN5T30N an overlap of only 31 % was detected. This means that less cis*-Golgi stacks colocalized with signals in the YFP-TTN5T30N mutant than in YFP-TTN5Q70L, which is the statement in our manuscript. *
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IN general the Authors should strongly consider the claims made in the manuscript. For eg. "This study lays the foundation for studying the functional relationships of this small GTPase" (line 125) is unqualified as this is true for every protein ever studied and published. Considering that TTN was not isolated/identified in this study for the first time this claim doesn't stand.
__Our response: __
*We reformulated the sentence (Line 123-124). *
"This study paves the way towards future investigation of the cellular and physiological contexts in which this small GTPase is functional."
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Line #185 - "characterestics of a dominant-negative...." What is this based on? From the text it is not clear what are the paremeters. Considering that no complementation phenotypes have been presented, this is a far-fetched claim Our response:
Small GTPases in general are a well studied protein family and the here used mutations T30N and Q70L are conserved amino acids and commonly used for the characterization of the Ras superfamily members. We added explaining sentences with references to the text. The characteristics referred to in the above paragraph is based on the kinetic study.
We modified the text as follows (Line 186-197 ):
„Third, the mGDP dissociation from TTN5T30N (koff = 0.149 s-1) was 12.5-fold faster than that of TTN5WT and 37-fold faster than the mGppNHp dissociation of TTN5T30N (koff = 0.004 s-1) (Figure 2D, E; Supplementary Figure S3H, S4G). Mutants of CDC42, RAC1, RHOA, ARF6, RAD, GEM and RAS GTPases, equivalent to TTN5T30N, display decreased nucleotide binding affinity and therefore tend to remain in a nucleotide-free state in a complex with their cognate GEFs (Erickson et al. 1997, Ghosh et al. 1999, Radhakrishna et al. 1999, Jung and Rösner 2002, Kuemmerle and Zhou 2002, Wittmann et al. 2003, Nassar et al. 2010, Huang et al. 2013, Chang and Colecraft 2015, Fisher et al. 2020, Shirazi et al. 2020). Since TTN5T30N exhibits fast guanine nucleotide dissociation, these results suggest that TTN5T30N may also act in either a dominant-negative or fast-cycling manner as reported for other GTPase mutants (Fiegen et al. 2004, Wang et al. 2005, Fidyk et al. 2006, Klein et al. 2006, Soh and Low 2008, Sugawara et al. 2019, Aspenström 2020)."
The claims in Line #224-227 are exaggerated. Please tone down or delete __Our response: __
*We rephrased the sentence (Line 240-243). *
"Therefore, we propose that TTN5 exhibits the typical functions of a small GTPase based on in vitro biochemical activity studies, including guanine nucleotide association and dissociation, but emphasizes its divergence among the ARF GTPases by its kinetics."
Line#488-489 - This conclusion is not really supported. At best Authors can claim that TTN5 is associated with trafficking components, but the functional relevance of this association is not determined. Our response:
*We toned down our statement (Line 604-608). *
„The colocalization of FM4-64-labeled endocytosed vesicles with fluorescence in YFP-TTN5-expressing cells may indicate that TTN5 is involved in endocytosis and the possible degradation pathway into the vacuole. Our data on colocalization with the different markers support the hypothesis that TTN5 may have functions in vesicle trafficking."
__Minor comments: __
Line #95 - " This rolein vesicle....." - please clarify which role? Our response:
We rephrased the sentence (Line 96-99).
„These roles of ARF1 and SAR1 in COPI and II vesicle formation within the endomembrane system are well conserved in eukaryotes which raises the question of whether other plant ARF members are also involved in functioning of the endomembrane system."
Line #168 - "we did not observed" please change to "not able to measure/quantify" __Our response: __
*We changed the text accordingly (Line 169-171). *
„A remarkable observation was that we were not able to monitor the kinetics of mGppNHp association with TTN5T30N but observed its dissociation (koff = 0.026 s-1; Figure 2E)."
Line#179 - ARF# is human for Arabidopsis?
Our response:
*The study of Fasano et al., 2022 is based on human ARF3 and we added the information to the text (Line 180-181) *
"(...) very similar to the koff value of HsARF3 (Fasano et al. 2022)."
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Line #181 - compared to what is the 10-fold difference?
__Our response: __
The 10-fold difference is between the nucleotides mGDP and mGppNHp, for both TTN5WT and TTN5Q70L. We added the information on specific nucleotides to this sentence for a better understanding (Line 181-185).
„Second, the koff values for mGDP and mGppNHp, respectively, were in a similar range between TTN5WT (0.012 s-1mGDP and 0.001 s-1 mGppNHp) and TTN5Q70L (0.025 s-1 mGDP and 0.006 s-1 mGppNHp), respectively, but the koffvalues differed 10-fold between the two nucleotides mGDP and mGppNHp in TTN5WT (koff = 0.012 s-1 versus koff = 0.001 s-1; Figure 2D, E; Supplementary Figure S3G, I, S4F, H)."
Lines #314-323 - are diffciult to understand, consider reframing. Same goes for the conclusion following these lines.
__Our response: __
We added an explanation to these sentences for a better understanding (Line 392-405).
„We performed an additional object-based analysis to compare overlapping YFP fluorescence signals in YFP-TTN5-expressing leaves with GmMan1-mCherry signals (YFP/mCherry ratio) and vice versa (mCherry/YFP ratio). We detected 24 % overlapping YFP- fluorescence signals for TTN5 with Golgi stacks, while in YFP-TTN5T30N and YFP-TTN5Q70L-expressing leaves, signals only shared 16 and 15 % overlap with GmMan1-mCherry-positive Golgi stacks (Supplementary Figure S8B). Some YFP-signals did not colocalize with the GmMan1 marker. This effect appeared more prominent in leaves expressing YFP-TTN5T30N and less for YFP-TTN5Q70L, compared to YFP-TTN5 (Figure 5B-D). Indeed, we identified 48 % GmMan1-mCherry signal overlapping with YFP-positive structures in YFP-TTN5Q70L leaves, whereas 43 and only 31 % were present with YFP fluorescence signals in YFP-TTN5 and YFP-TTN5T30N-expressing leaves, respectively (Supplementary Figure S8B), indicating a smaller amount of GmMan1-positive Golgi stacks colocalizing with YFP signals for YFP-TTN5T30N. Hence, the GTPase-active TTN5 forms are likely more present at cis-Golgi stacks compared to TTN5T30N."
Authors might consider a longer BFA treatment (3-4h) to see more clearer ER-Golgi fusion (BFA bodies)
__Our response: __
We perforned addtional BFA treatments for HA3-TTN5-expressing Arabidopsis seedlings followed by whole-mount immunostaining and for YFP-TTN5-expressing Arabidopsis lines. In both experiments we could obtain the typical BFA bodies. We included the NEW data in NEW Figure 4B, C
**Referees cross-commenting**
I agree with both my co-reviewers that the manuscript needs substantial improvement in its cell biology based experiments and conclusions thereof. I think the concensus of all reviewers points to weakness in the in-planta experiments which needs to be addressed to understand and characterize TTN5, which is the main goal of the manuscript.
Reviewer #3 (Significance (Required)):
Significance: The manuscript has general significance in understanding the role of small GTPases which are understudied. Although the manuscript does not advance the field of either intracellular trafficking or organization it holds significance in attempting to characterize proteins involved, which is a prerequisite for further functional studies.
__Our response: __
Thank you for your detailed analysis of our manuscript and positive assessment. Our study is an advance in the plant vesicle trafficking field.
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Reply to the reviewers
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
Summary: In this paper, Dresselhaus et al (2023) investigate the possibility that known cargoes of extracellular vesicles (EVs) released at the Drosophila neuromuscular junction have cell-autonomous functions rather than functions specifically conferred as a condition of their release in EVs, in vivo. To do so, authors focus their studies on use of Tsg101-KD, a mutant of the ESCRT-I machinery, of the ESCRT EV biogenesis pathway, and are able to show that for some endogenously-expressed, fluorescently-tagged cargoes, fluorescence intensity in the pre-synaptic compartment is significantly elevated (Syt4 and Evi) and the postsynaptic intensity in the muscle is significantly decreased (Syt4, Evi, APP, and Nrg).
We note that throughout our study, we detected endogenous Nrg with a well-characterized monoclonal antibody, not a fluorescent tag. We and others previously demonstrated that endogenous Nrg detected by this antibody is trafficked from neurons into EVs, using the same pathways as other EV cargoes such as Syt4, APP and Evi (Blanchette et al., 2022; Enneking et al., 2013; Walsh et al., 2021). Thus, the EV trafficking phenotypes in our study are consistent across fluorescently tagged cargo (endogenous knockin for Syt4 and GAL4/UAS-driven for APP and Evi), as well as for untagged, endogenous Nrg, thus controlling for effects of either overexpression or tagging.
These findings suggest that these cargoes become trapped in the endosomal system (colocalizing with early, late, and recycling endosomal compartments), rather than undergoing secretion in EVs targeting post-synaptic muscle and glia as usual. This phenotype is recapitulated for select cargoes using mutants of both early and late components of ESCRT pathway machinery. They further characterize the Tsg101 mutant, demonstrating co-occurrence of an autophagic flux defect, but as the cargo phenotype is present without induction of the autophagic flux defect for their Hrs mutants, authors suggest the overlapping role of Tsg101 in autophagy is independent of its role in the ESCRT pathway/ EV secretion. Subsequently, they use previously defined functional phenotypes of the Evi (number of active zones, number of boutons, number of developmentally-arrested ghost boutons) and Syt-4 (number of transient ghost boutons and mEJPs) cargoes to show a minimal dependence on cargo delivery via ESCRT-derived EVs for these cargoes to carry out their synaptic growth and plasticity functions in vivo. However, it should be notes that for Evi/ Wg cargo, there is a slight increase in developmentally-arrested ghost boutons suggesting the cargo may not be entirely independent of EV-mediated cargo delivery. Finally, authors express an anti-GFP proteasome-directed nanobody using motor neuron or muscle-specific drivers and find that Syt4-GFP cargo doesn't enter muscle cytoplasm as fluorescence is maintained and cargo is not degraded by the muscle proteasome. While authors suggest this as evidence of EV-mediated transfer for cargo proteostasis, it is not explicitly shown that Syt4 cargo is, in fact, trafficked and degraded by the lysosome or hypothesized how Syt4 function or post-synaptic localization may be carried out independently of EVs.
We have added new data showing that Syt4 is taken up by glial and muscle phagocytosis (Fig. 7), and included in the discussion several possible interpretations for how Syt4 activity is carried out independently of its traffic into EVs. Indeed we believe it is more likely to function in the presynaptic neuron rather than the postsynaptic muscle.
Major comments:
R1.1 It is difficult to evaluate the findings of this study without knowing the extent of ESCRT pathway impairment. Please provide data quantifying the degree of knockdown/ mutant expression for each ESCRT component (i.e., western blot)
To address the reviewer’s request to specifically measure the degree of knockdown in the RNAi lines, we tested all available reagents. Unfortunately no Drosophila Tsg101 antibody exists and we did not receive a reply to our requests for a Shrub antibody. An Hrs antibody exists, but we found that none of three available Hrs RNAi lines depleted Hrs signal, or caused a phenotype similar to the HrsD28 point mutant, suggesting that they are not effective at knocking down the protein. Therefore, we were unable to specifically measure the level of depletion in motor neurons for RNAi of Tsg101, Shrub, or Hrs.
However, we can make a strong argument that our knockdowns were sufficiently effective to answer the questions in our study. We used RNAi as only one of several complementary tools to manipulate ESCRT function (i.e. we also used loss-of-function mutants (HrsD28/Deficiency) and dominant negative mutants (Vps4DN)). These mutants caused a comparable and severe loss of EVs to RNAi (Fig 2): therefore the extent of depletion in the RNAi experiments was sufficient to cause a similarly severe phenotype as genomic or DN mutations, meeting the definition of a bona fide loss-of-function. We also know, since we used these complementary strategies, that the phenotypes we observe are very unlikely to be due to off-target effects of the RNAi.
More importantly, what is directly relevant for our subsequent functional experiments is to know the extent of EV depletion, which we have explicitly measured throughout the paper. It is unclear what additional insights would be gained by knowing whether the strong Tsg101 and Shrub RNAi phenotypes are due to incomplete versus complete knockdown, given that we do measure the extent of EV depletion under these conditions. Further, we note that tsg101 null mutants die as first instar larvae (Moberg et al., 2005), raising the possibility that a more complete knockdown in neurons would be lethal early in development and make our study impossible. Indeed HrsD28 is an early stop that preserves the VHS and FYVE domains but truncates the C-terminal ⅔ of the protein. Its (occasional) survival to third instar indicates that it may be a severe hypomorph rather than a null.
We have added a sentence in the text (p12 line 21-25) to clarify that we do not know the exact extent of knockdown for our RNAi experiments, but that by genetic definitions, they meet the criteria of a loss-of-function manipulation.
R1.2 Loss of ESCRT machinery likely disrupts the release of small EVs to a significant extent; however, the authors do not show that EV release is entirely lost, only that 1) cargoes are backed up in the endosomal system due to endosomal dysfunction and 2) fluorescence of cargoes in the postsynaptic compartment is diminished. To claim that ESCRT-derived EVs with the relevant cargoes are lost, the authors should perform immunogold labelling with TEM. This would provide direct evidence that the cargoes examined here are packaged in ILVs, and that the ILVs are of a size (~50-150nm) consistent with exosomes (which should really be referred to as small extracellular vesicles (sEVs) per the minimal information for studies of extracellular vesicles (MISEV 2018 [https://doi.org/10.1080/20013078.2018.1535750]) Additionally, EM would show the loss of cargo packaging and provide information about where these cargoes localize in the presence of ESCRT mutants/loss-of-function.
EM (including some limited immunoEM) studies requested by Reviewer 1 have previously been performed in this system by us and by the Budnik and Verstreken labs (Koles et al., 2012; Korkut et al., 2009; Korkut et al., 2013; Lauwers et al., 2018; Walsh et al., 2021). MVBs at the NMJ contain ~50-100 nm ILVs, and can often be seen proximal to or fusing with the plasma membrane. Mutants such as Hsp90 that block this fusion also block EV release, arguing that these MVBs are the source of EV (Lauwers et al., 2018). By immunoEM, the EV cargo Evi localizes to MVBs (Koles et al., 2012). ~50-200 nm structures containing immunogold against Evi were also observed in the subsynaptic reticulum between the neuron and the muscle, as well as in membrane compartments in the muscle cytoplasm (Koles et al., 2012; Korkut et al., 2009). Thus, the criteria requested by the reviewer have previously been established in this system.
In response to the reviewer’s request to show that these structures are altered in ESCRT mutants, we attempted immunoEM experiments in the Tsg101KD condition. However, similar to the previously published results (Koles et al., 2012; Korkut et al., 2009), immunoEM in thick tissue such as Drosophila larval fillets is quite challenging, and we found it very difficult to retain immunogenicity together with excellent fixation and preservation of membrane structures, such that we could rigorously measure compartment morphology and size. Even if we did achieve good structural preservation, exosomes are ambiguous in complex membrane-rich tissues, since cross-sections through the extensively infolded muscle membrane (e.g. see Fig 3B) are very similar in size to EVs.
As an alternative and more robust approach, we used STED microscopy, with a resolution of ~50nm, where we could conduct a rigorous and properly powered study of directly labeled EV cargoes (New data in Fig. S1). We show that postsynaptic Nrg and APP-GFP are found in structures with a mean diameter of ~125 nm, consistent with small EVs or exosomes, and these are strongly depleted in the Tsg101KD animals (to similar levels as antibody background far from the site of EV accumulation), as expected. Note that we are able to detect particles significantly smaller than 125 nm in the distribution, suggesting that the resolution of our system is sufficient to measure EV width.
We also note that several of these cargoes are detected via an intracellular tag (Syt4, APP, Evi) or antibody against an intracellular domain (Nrg), so by topology they must be membrane-bound in the EVs rather than cleaved from the cell surface. We and others have previously shown that this postsynaptic signal is entirely derived from the presynaptic neuron, by using neuronal UAS-expression of a tagged protein, by neuronal RNAi of the endogenous gene, or by the tissue-specific tagging approach in the current manuscript (Fig. S4). We have also previously shown that these puncta contain the tetraspanin Sunglasses (CG12143/Tsp42Ej), which is an EV marker (Walsh et al., 2021). We have added new data to our manuscript (Fig. S1A) to show that neuronally-derived tetraspanin EVs are depleted in upon Tsg101KD. Therefore, the reviewer’s point “2) fluorescence of cargoes in the postsynaptic compartment is diminished.” is the most direct and sensitive test of trans-synaptic cargo transfer, and is the precise parameter that we are trying to manipulate to test the functions of this transfer.
We believe that light microscopy showing loss of presynaptically-derived cargoes in the postsynaptic region is the best and most direct argument for loss of EV secretion, compared to the ambiguity of EM. It is also exactly the method that led to the proposal for the signaling function of EVs in previous work, which our current manuscript is revisiting. We are now using improved tests of that original hypothesis by examining it in light of additional membrane trafficking mutants (and finding that it no longer holds up). Overall, given the preponderance of evidence from the preceding literature and our studies indicating that (1) these cargoes are indeed in EVs and (2) we see a strong enough depletion of transsynaptic transfer to challenge the hypothesis that EVs serve signaling functions (see R1.3 response below), we are reluctant to spend more time attempting immunoEM which is not likely to resolve membrane structures.
To address the point of EV terminology used in our manuscript, we think it is very unlikely that the postsynaptic structures are not exosomes. The criteria defined by MISEV for exosomes is that they are endosomally-derived from MVBs, ideally with the EV “caught in the act of release” upon fusion with the plasma membrane. As noted above, cargoes such as Syt4 and Evi are observed by immunoEM in MVBs, and these can be found in the process of fusing with the plasma membrane (i.e. caught in the act of release) (Koles et al., 2012; Korkut et al., 2009; Korkut et al., 2013; Lauwers et al., 2018). Mutants that block MVB fusion also block EV release at the NMJ (Lauwers et al., 2018). These EVs require ESCRT for their formation and are trapped in endosomes rather than the plasma membrane upon ESCRT depletion (this study). They depend on multiple components of the endosomal system (Rab GTPases, retromer) for their formation (Koles et al., 2012; Walsh et al., 2021). Taken together, it seems to us that there is sufficient data to argue that these are exosomes. However, as the reviewers requested, we have called them EVs in the revised paper (and only suggest they are exosomes in the discussion).
R1.3 Other biogenesis pathways utilize multivesicular bodies to generate EVs, most prominently the nSMase2/ceramide synthesis pathway (which operates in an ESCRT-independent manner). It is possible that this pathway compensates when there are defects in the canonical ESCRT pathway. Thus, it is imperative for the authors to show that the cargo secretion no longer occurs in the presence of ESCRT mutations/loss-of-function. The authors should also use nSMase2 pathway mutants to see if the phenotypes in cargo trafficking (i.e., pre/ post-synaptic protein levels) are recapitulated.
The reviewer asked us to show that cargo secretion does not occur in the ESCRT mutants. We reiterate that at the limits of detection of our assay, we see a very strong depletion of secretion__, and that EV cargo levels are not distinguishable from background (__Figure S1). Perhaps Reviewer 1’s concern is that since it would never be possible to show that we have depleted EVs completely (i.e. below the level of detection of our assays), that it is not possible to challenge the hypothesis that EV traffic is required for the proposed signaling functions of EVs. Indeed, they mention in their overall assessment “as it is unknown if minor sources of cargo+ EVs are sufficient in maintaining functional phenotype”. We do have some information on this, as described in the manuscript (p3 lines 41-43; p7 lines 25-31; p11 lines 27-30) and as follows: The critical argument against this concern is that other trafficking mutants with residual levels of EVs (rab11 or nwk) do show loss of signaling function (Blanchette et al., 2022; Korkut et al., 2013). Therefore residual EVs, even at the lower level of detection of our assay, are not enough to support signaling. The main difference is that in nwk and rab11 mutants the levels of the cargo in the donor presynaptic neuron are also strongly depleted, unlike in the ESCRT mutants. This strongly suggests that the cargoes are signaling from the presynaptic compartment, rather than in EVs. We have added the nwk mutant to show this baseline in Figure 2A,D. Similarly, our new results showing that hrs mutants retain Wg signaling while Tsg101 mutants do not, despite a similar degree of EV depletion (new data with more cargoes in Figure 2A-F), argues that residual EVs do not account for the lack of disruption of signaling. Finally, we have been transparent in our discussion that trace amounts of EVs could still exist, including by alternative pathways, but are unlikely to provide function (p11 lines 25-33).
We agree that it might be an interesting future mechanistic direction to ask if the SMase pathway works with or in parallel to the ESCRT pathway (both have been suggested in the literature). However, we do not believe that this is essential for the current work: The SMase pathway is unlikely to be “compensating”, since EVs are already very strongly depleted with ESCRT disruption alone. We also note that SMase depletion may also affect other trafficking pathways (Back et al., 2018; Choezom and Gross, 2022; Niekamp et al., 2022), and therefore might not provide any clarifying information if it did disrupt signaling. In summary, we believe the depletion we see in single ESCRT mutants is sufficient to (1) establish the role of ESCRT in EV traffic in this system, and (2) test the role of transsynaptic transfer in signaling functions of cargoes.
R1.4 The authors' findings support that cargo trafficking is affected by widespread endosomal dysfunction but doesn't cleanly prove that 1) synaptic sEV release is lost and 2) that cargo-specific sEVs are lost. As previously mentioned, loss of cargo+ ILVs in MVEs by TEM could demonstrate this, but another useful approach would be to include in vitro Drosophila primary neuronal culture/ EV isolation and mass spec/proteomic characterization studies as proof of concept. According to widely agreed upon guidelines in the EV field, the authors should directly characterize their EV population to show 1) the appropriate size distribution associated with exosomes/sEVs, 2) the presence of traditional EV markers (i.e., tetraspanins), 3) changes in overall EV count by ESCRT mutants, and 4) decreased levels of cargo(es) of interest in the presence of ESCRT mutants/loss-of-function. In vitro experiments would be particularly helpful for quantifying the degree of loss of cargo-specific EVs with each ESCRT mutant. These experiments could also investigate the possibility that cargoes are secreted in nSMase2/ Ceramide-derived EVs, by showing that EV cargo levels are unaffected in nSMase mutants.
Our data already show loss of cargo-specific EVs, defined by puncta of several independent specific cargoes in the extraneuronal space and postsynaptic muscle. To further substantiate this, we have directly characterized our EV population and shown a distribution of ~125 nm extraneuronal structures containing the transmembrane cargoes Nrg and APP (by STED) as well as Evi, Syt4 and the EV marker tetraspanin (by confocal microscopy). This addresses the (1) size distribution, (2) EV marker and (3) count criteria. All these markers (cargoes and tetraspanins) are severely depleted from the postsynaptic area in the ESCRT mutants, satisfying the (4) decreased levels criteria. As noted above, we and others have repeatedly demonstrated that these postsynaptic puncta are derived from neurons, and since we are detecting the intracellular domain in all cases, must be membrane-bound. Others have previously shown by EM that several of these markers are surrounded by membrane and derived from neuronal MVBs (see R1.2). Note that we do not believe that ESCRT mutants must necessarily cleanly show enlarged endosomes without ILVs or a class E vps compartment - instead stalled endosomes appear to be targeted for autophagy in heterogeneous intermediates (Fig 3).
We do not believe that turning to a heterologous system (e.g. cultured primary Drosophila neurons, which do not even form functional synapses) is usefully translatable to results in neurons in vivo. Data from our lab and many other systems has shown that EV biogenesis and release pathways are highly cell-type specific (p9 lines 8-12), and also differ in different regions of neurons (eg synapses vs soma) (Blanchette and Rodal, 2020). Further, keeping the experimental setup of the original for EV signaling hypothesis is a prerequisite for our improved tests of this hypothesis. We do note that APP, Evi and Syt4 have been demonstrated by us and others to be released from Drosophila S2 cells in EVs defined by differential centrifugation, sucrose gradient buoyancy, electron microscopy and mass spectrometry (Koles et al., 2012; Korkut et al., 2009; Korkut et al., 2013; Walsh et al., 2021). However even if we did measure the precise change in EV number and cargoes upon ESCRT manipulation in these heterologous cells, it would not allow us to conclude that the same quantitative change was happening in the motor neurons of interest in vivo, which is the information we need to conduct our tests of cargo signaling function. All we would learn is whether ESCRT was required in that cell type, which would not be informative for our study.
We appreciate that EV researchers working in cell culture systems often use a set of approaches including bulk isolation, EM, and mass spectrometry. Our system does not allow for these approaches, but provides complementary strengths of single EV characterization, in vivo relevance with functional assays, and a wealth of genetic tools. MISEV itself states that it does not provide a set of agreed-upon rules that can be applied generically to any experiment. We agree with the MISEV statement that we should use the best available assays for the system under investigation.
R1.5 During functional tests of Evi+ motor neurons lacking generation of Evi+ EVs, there is a slight defect observed, namely the increased formation of developmentally arrested ghost boutons when Evi secretion in sEVs is lost. As mentioned, Evi is a transporter of Wg and it is possible for Wg to be transmitted between cells via normal diffusion. Thus, some basal levels of Wg may be reaching the muscle when its transfer via sEVs is abolished, and these basal levels may be sufficient to phenocopy the WT in the number of active zones and boutons. Is it possible that this element of Evi/ Wg function is dose-dependent and thus reliant on the extra Evi/ Wg transferred via sEVs? If possible, the authors should use a Wnt-signaling pathway reporter (i.e., fluorescently tagged Beta-Catenin) to measure the levels of Wnt signaling activity in the muscle when Evi/Wg+ EVs are present vs. abolished. If the degree of Wnt signaling (readout would be intensity of fluorescent reporter) is decreased without Evi+ sEVs, there may be a dose-dependent response. Otherwise, please more clearly disclose the partial loss of Evi function without Evi+ sEVs or state the intact function of Evi without sEVs as speculative.
We agree that Wg is likely to be reaching the muscle in the absence of Evi exosomes via conventional secretory mechanisms, and have conducted new experiments to test this hypothesis (Fig. 5). In Drosophila muscles, Wg does not signal via a conventional b-catenin pathway. Instead, neuronally-derived Wg activates cleavage of its receptor Fz2, resulting in translocation of a Fz2 C-terminal fragment into the nucleus (Mathew et al., 2005; Mosca and Schwarz, 2010). We did attempt to directly measure Wg (using antibodies or knockins) and though we were able to detect a specific presynaptic signal, the background noise throughout the postsynaptic muscle was too high for a sensible quantification. In response to the reviewer’s question and also R2.6), we collaborated with the laboratory of Timothy Mosca to test Fz2 nuclear import in Tsg101 and Hrs mutants (new Figure 5F-G). Strikingly, we found that Hrs mutants, despite being extremely sickly, have normal nuclear import of Frizzled. We also confirmed that Hrs mutants have dramatically depleted levels of all EV cargoes examined, including Evi (Figure 2A-F). On the other hand we found that Tsg101 knockdowns have dramatically reduced Wg signaling (and a concomitant defect in postsynaptic development). We do not rule out (but think it is unlikely) that very small amounts of EVs could be present in hrs but not tsg101 mutants. A more parsimonious interpretation is that additional membrane trafficking defects in the Tsg101 mutants (which are beyond the scope of this study to explore in detail) block an alternative mode of Wg release, perhaps conventional secretion. The fact that Hrs mutants, despite showing similar depletion of Evi EVs, do not have a signaling defect strongly argues that EV release per se is not required for Wg signaling.
R1.6 To support the authors' hypothesis that Syt4 transmission via EVs is a proteostatic mechanism, the authors should determine whether Syt4 cargo localizes to lysosomal compartments in muscle, glia, or both. Otherwise, the proteostatic degradation of Syt4 via EVs is speculative.
Our data suggest that EVs serve as one of several parallel proteostatic mechanisms for presynaptic cargoes. We have added new data to the manuscript to emphasize the advance our work makes in our understanding of these mechanisms, and have emphasized this in the discussion on p 11-12, lines 46-5).
- Degradation of neuronally derived EVs in glia and muscles. Previous work has shown that EV cargoes such as Evi can be found in compartments in the muscle cytoplasm, and that a-HRP-positive puncta are taken up and degraded by glial and muscle phagocytosis (Fuentes-Medel et al., 2009). These a-HRP-positive structures, despite colocalizing with EV cargoes Syt4, Nrg and APP (Walsh et al., 2021), were not previously connected to EVs. We have added new data showing that muscle or glial-specific RNAi of the phagocytic receptor Draper leads to the accumulation of EVs containing Syt4 (new Figure 7G-H)). Together with our finding (Figure 7A-F) that Syt4 is not significantly detected in the muscle cytoplasm, these results indicate that the main destination for transynaptic transfer is phagocytosis by the recipient cell. We have not been able to convincingly detect EV cargoes in the endolysosomal system of muscles, even in mutants disrupting lysosomal traffic, likely because the small number of EVs released by neurons (even over days of development) are drastically diluted in the much larger muscle cell.
- Compensatory endosomophagy in the neuron. __When EV release is blocked in Hrs or Tsg101 mutants, we observe an induction of autophagy in the neuron (__Figure 3B, E-G). However, in the absence of ESCRT manipulation, autophagy mutants do not accumulate EVs (Figure 3C,D. S2H-I). This suggests that autophagy is a compensatory mechanism that is induced in the absence of EV release.
- Retrograde transport to cell bodies: We previously found that disruption of neuronal dynactin leads to accumulation EV cargoes in presynaptic terminals (Blanchette et al., 2022), suggesting that retrograde transport is a mechanism for removal of these cargoes from synapses. Interestingly, EV release is not increased in these conditions, indicating that the retrogradely transported compartment represents a late endosome without ILVs, or an MVB that cannot fuse with the plasma membrane.
R1.7 Please discuss alternate modes of cargo transfer from the presynaptic compartment to the postsynaptic compartment that may be utilized when EV-mediated transfer is abolished (i.e., cytonemes or tunneling nanotubules).
We have added these possibilities to the discussion (p11 line 31), though we note that we do not observe any such structures, or indeed any Syt4 in the muscle cytoplasm, and there is no current evidence for such transsynaptic structures in this system. Conventional secretion of Wg into the extracellular space and signaling through its transmembrane receptor Frizzled2 can account for Wg signaling in the absence of exosomes.
R1.8 OPTIONAL: Investigate the mechanism of Syt4+ sEV fusion with the postsynaptic compartment (direct fusion with the plasma membrane, receptor-mediated fusion, endocytosis and unpacking, or endocytosis and degradation).
We note that the Budnik lab has already shown that HRP-positive EVs released by NMJs are taken up by glia and muscles (Fuentes-Medel et al., 2009), and we have added data showing that this also applies for Syt4 (Fig. 7). Our data are not consistent with Syt4 fusing with recipient cell membranes or entering the muscle cytoplasm. Further investigation of this mechanism is beyond the scope of this project.
Given that several fundamental questions have yet to be answered regarding the biogenesis pathways and machinery utilized for EV-mediated cargo secretion, and the necessity for further TEM studies and/or work with primary cultures to characterize ILVs and EVs, >6 months is estimated to perform the necessary experiments that may require learning/ optimizing new systems.
Minor comments:
R1.9 Please clarify the choice of using Tsg101 KD in place of mutants of other ESCRT machinery (i.e., Hrs). Especially as when the Tsg101 mutant was characterized, you found major defects in autophagic flux that were not present for HrsD28/Df.
Tsg101 RNAi was selected since it provides a neuron-autonomous knockdown, eliminating the complications of mutant effects in other tissues. These animals are also relatively healthy as third instar larvae compared to genomic mutants tsg1012 (L1 lethal) and HrsD28 or motor-neuron driven Vps4DN (where L3 larvae are rare). This made it easier to recover enough larvae to properly power experiments, and alleviated concerns that general sickness is contributing to the phenotype (though note that neuronal Tsg101KD does result in pupal lethality). Finally, we were unable to effectively knock down Hrs by RNAi (see R1.1). To extend our studies beyond Tsg101, we have included additional experiments in the revised manuscript showing that HrsD28 animals, despite being quite unhealthy, still retain Syt4-dependent functional plasticity (See R2.5 and R3.4) and Wg signaling.
R1.10 Please clarify why the specific method in experiment in Fig. 4E-J was chosen. As Syt4 is a transmembrane protein, is likely undergoes degradation via the lysosome, like other membrane-bound proteins. Is it known whether the proteasome-directed nanobody is sufficient to pull Syt4 from membrane-bound compartments to undergo degradation in the proteasome? Would it make more sense to use a lysosome-directed nanobody?
The GFP tag on Syt4 is cytosolic rather than lumenal. Our data show that when we express the proteosome-directed nanobody presynaptically, it efficiently degrades membrane-associated Syt4-GFP (Fig. 7B). Therefore we expect that this tool should be similarly effective on membrane-associated Syt4-GFP if it were exposed to the muscle cytoplasm. We have confirmed that it is effective in the muscle against DLG-GFP (Fig. S5A)
R1.11 Please provide further methodological information regarding the sample preparation for live imaging of axons to generate kymographs found in Fig. S3.
Additional details have been provided on p14 lines 10-24 and p15 lines 31-37.
R1.12 In Figure 1I and 1J, include representative image and quantification of Syt4-GFP pre- and post-synaptic intensity for HrsD28/Df for consistency with ShrubKD and Vps4DN in Figure 1K-P.
We generated and tested HrsD28; Syt4-GFP (Fig 2A,D), and HrsD28; Evi-GFP strains (Fig 2B-E). All EV cargoes exhibited a dramatic post-synaptic depletion in Hrs mutants, similar to the other ESCRT manipulations.
R1.13 In Figure 2H, please provide a cell type marker or HRP mask with a merged image for image clarity.
This image shows neuronal cell bodies in the ventral ganglion, which are densely packed relative to each other. The cell type specificity is provided by the motor neuron driver. We did not use a cell type marker or individually mask cells for analysis, but instead quantified intensity over the whole field of view. We can manually trace cell bodies in this image if requested, but it would not represent our ROI for analysis.
R1.14 In Figure 4B, please provide quantification for the differences between 1) WT Mock and Tsg101 MOCK and 2) WT Stim and Tsg101KD Stim to show that upon stimulation, WT and Tsg101 undergo the same increase in the number of ghost boutons/ NMJ in Muscle 4.
We have added these statistical comparisons to the graph (Fig. 6B)
R1.15 In Figure 3 G and H, use consistent scale bars to compare between temperatures.
We have removed the Shrub data at 20º as it did not provide additional insight to the manuscript.
Reviewer #1 (Significance (Required)):
General assessment (Strengths):
-Use of Drosophila NMJ model system consistent with others in the field and exceptional harnessing of genetic tools for mutations across the ESCRT pathway (-0, -I, -III, etc.) -Identification of ESCRT pathway mutants that do not deplete pre-synaptic cargo levels but generate endosomal dysfunction, indicative of a possible decrease in secretion of cargoes via EVs -Implementing functional characterization of Evi/ Wg and Syt4 cargoes, consistent with previous work in the field; highly reproducible
-Sufficiently thorough investigation of the cross-regulation of autophagy and EV biogenesis by Tsg101
General assessment (Weaknesses):
-Lack of investigation of known ESCRT-independent pathways/ genes involved in the generation of sEVs (i.e., nSMase2/ Ceramide) especially as it is unknown if minor sources of cargo+ EVs are sufficient in maintaining functional phenotype
See R1.3 for comments on this point
-Lack of sEV characterization and validation of EVs derived from mutant
We have added STED data to measure EV size, and described the challenges in EV membrane measurements by EM in the in vivo system.
-Does not show the loss of cargoes of interest on EVs from mutants other than through back-up of cargoes in the presynaptic endocytic pathway (Rab7, Rab5, Rab11)
We strongly disagree with this comment. We have explicitly measured the loss of numerous cargoes in postsynaptic structures that have been rigorously established to be EVs in this and previous publications. Our findings are not limited to back-up of presynaptic structures.
-Lack of rigorous investigation of the claim that Evi and Syt4 are released via EVs for proteostatic means is missing. Authors should demonstrate the degradation of EV cargoes by recipient cells (either muscle OR glia)
We have added new data and discussion on multiple and compensatory proteostatic pathways.
-If EV-mediated cargo transfer is not required, authors should investigate alternate modes of cargo transfer more rigorously (i.e., diffusion of Wg, suggest/ test hypotheses for mechanism of Syt4 function or transfer).
We have included discussion of alternate modes of transfer for Wg (i.e. conventional secretion). By contrast, for Syt4 we believe it is acting in the donor cell without transfer, and have included alternate interpretations of the previous literature that had suggested its function in muscles.
Advance: -Compared with other recent in vivo studies of EVs where donor EVs are loaded with a cargo, such as Cre, which uniquely identifies recipient cells through Cre recombination-mediated expression of a fluorescent reporter (Zomer et al 2015, Cell), this study relies on the readout of fluorescently tagged cargo in the recipient cells to represent transfer via EVs. While numerous studies in the Drosophila field focus on the same small set of known EV cargoes at the NMJ (Koles et al., 2012; Gross et al., 2012; Korkut et al., 2013; Korkut et al., 2009; Walsh et al., 2021), there is a noticeable lack of EV characterization based on MISEV (i.e. TEM of EVs, size distribution, enrichment of well-known EV markers [https://doi.org/10.1080/20013078.2018.1535750]) that would significantly strengthen the work and make it more widely accepted in the EV field.
As mentioned above, many of these criteria (including EV size and enrichment of known EV markers) are already established in the previous literature for this system. As requested, we have also added similar data to our revised manuscript.
-In this study, the use of ESCRT machinery mutants is proven as a new technical method in delineating the role of EV cargoes in cell-autonomous versus EV-dependent functions. This is the first study, to my knowledge, that has leveraged mutants from both early and late ESCRT complexes for the study of EVs in Drosophila. Additionally, the finding that some cargoes may be able to carry out their signaling functions, independent of transfer via EVs, provides key mechanistic insight into one possible role of EVs as proteostatic shuttles for cargo. This work also begins to address a fundamental question in the field, which is to delineate roles that EVs actually carry out in physiological conditions, compared to the many roles that have been shown possible in vitro.
We appreciate the reviewer’s insight into the impact of our work.
Audience: -Basic research (endosomal biology, ESCRT pathway, cell signaling, neurodevelopment)
-Specialized (Drosophila, Neurobiology; Extracellular Vesicles)
-This article will be of interest to basic scientists in the field of endosomal trafficking and extracellular vesicle biology as well as though studying the nervous system in Drosophila melanogaster. As the field of extracellular vesicle biology has broad implications in the spread of pathogenic cargoes in cancer and neurodegenerative disease, the basic biology associated with EVs has some translational relevance.
Expertise (Keywords):
-ESCRT and nSMase2 EV biogenesis pathways
-EV characterization in vitro/ live imaging studies
-EV release and uptake
-Neuronal and glial cell biology
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
This manuscript addresses the role of exosome secretion in neuromuscular junction development in Drosophila, a system that has been proposed to depend on exosomes. In particular, delivery of Wingless via exosomes has been proposed to promote structural organization of the synapse. Previously, however, the studies that proposed this model targeted the cargoes themselves, rather than targeting exosome biogenesis or secretion. In this new study, exosome biogenesis is targeted via knockdown of the ESCRT components Hrs, TSG101, and Chmp4. The authors find that some previously ascribed functions are not inhibited by these knockdowns. In particular, formation of active zones, as defined by BRP-positive puncta (total and per micrometer), and total bouton numbers. It does look like there is a partial defect in BRP-positive puncta per micrometer, but it is not significant. For ghost bouton formation, there is a similar increase in evi-mutant and ESCRT-KD NMJs (with some subtle differences depending on abdominal segment and temperature). They also examine the role of Syt4, which has been proposed to be transferred from nerve to muscle cells at the junction and to regulate mEJP frequency after stimulation. They found no difference in mEJP frequency after stimulation between WT and TSG101-KD animals, although they did not have a positive control with inhibition of Syt4. They did do an elegant experiment to demonstrate that most of extracellularly transferred Syt4 does not reach the muscle cytoplasm. Overall, it is an interesting paper, mostly well controlled and rigorous, and well-written. It is an important contribution to the EV and NMJ fields. The data should provoke reconsideration of some of the functions that were previously ascribed to exosome transfer at the NMJ. However, I do think that there are some overly strong statements and the functions of the exosomes at the synapse were quite narrowly examined. For example, the title of the paper is pretty strong and the abstract does not say which functions were or were not affected by TSG101 KD. There are also a couple of experiments that would enhance the manuscript. Some specific suggestions are below:
R2.1 Title: "ESCRT disruption provides evidence against signaling functions for synaptic exosomes" seems a bit broad -- only evi/Wg and Syt4 functions were examined at NMJ synapses, not all signaling functions of all exosomes at all synapses. Something like, "ESCRT disruption provides evidence against signaling functions for exosome-carried evi/Wg and Syt4 at the neuromuscular junction" seems a bit more reasonable.
We are open to changing the title to: “ESCRT disruption provides evidence against transsynaptic signaling functions for some extracellular vesicle cargoes” though we prefer to leave it as is since “provides evidence against” is already fairly understated.
__ __R2.2 Abstract: the description of the actual data is very little, just one sentence saying that "many" of the signaling functions are retained with ESCRT depletion. I think a bit more focus on the actual data is warranted.
We have edited the abstract to include more detail on the signaling phenotypes.
__
__R2.3 Results section:
Fig 3: What does A2 and A3 mean for the graphs in c,d,e, g, h? Please specify in figure legend.
We have described in the figure legends that A2 and A3 refer to specific abdominal segments in the larvae.
R2.4 The sentence "Further, active zones in Tsg101KD appeared morphologically normal by TEM (Fig.2B)." is confusing to me. What do you mean by that? Are you referring to the following two sentences about feathery DLG and SSR? But the feathery DLG I presume is in Fig 3, where that staining is. And I also don't know what feathery DLG means -- it should be pointed out in the appropriate image.
Presynaptic active zones are defined by an electron-dense T-shaped pedestal at sites of synaptic vesicle release, and can be seen in the TEM in what is now Figure 3B, marked as AZ. We have also labeled AZ by immunofluorescence (Fig. 5A) and they appear normal.
By contrast, Dlg primarily labels the postsynaptic apparatus associated with the infoldings of the muscle membrane. In control animals, Dlg immunostaining is relatively tightly and smoothly clustered within ~1µm of the presynaptic neuron. By contrast, in Evi mutants, there are wisps of Dlg-positive structures extending from the bouton periphery. We have added arrows in what is now Fig. 5C to indicate the feathery structures.
R2.5 Fig 4 addresses Syt4 function. However, there is no positive control inhibiting Syt4 to see if there is a change. Just comparison of WT and TSG101. It seems like this positive control is in order.
We have added the positive control (Fig. 6E-F) reproducing the previously reported result that Syt4 mutants lack the high-frequency stimulation-induced increase in mEPSP frequency (HFMR). We have also added new data on HrsD28 genomic mutants. Despite the fact that few of these larvae survive and they are quite unhealthy, they still exhibit robust HFMR, similar to the Tsg101KD larvae, strongly supporting our hypothesis.
R2.6 Discussion: I think some discussion of what ghost boutons are and what the possible significance is of the evi and ESCRT mutant phenotype of enhanced ghost bouton formation
We have added more discussion on the ghost bouton phenotype (p11 lines 5-14), especially in light of our new findings that Hrs and Tsg101 mutants may distinguish alternative modes of Wg secretion (see R1.5)
R2.7 Also, in the Discussion, it is mentioned that Wg probably gets secreted in the ESCRT mutants -- presumably this accounts for the discrepancy between evi mutants and the ESCRT mutants. An experiment to actually test this would greatly enhance the manuscript.
We have added this experiment as addressed in R1.5
Reviewer #2 (Significance (Required)):
Overall, it is an interesting paper, mostly well controlled and rigorous, and well-written. It is an important contribution to the EV and NMJ fields. The data should provoke reconsideration of some of the functions that were previously ascribed to exosome transfer at the NMJ. However, I do think that there are some overly strong statements and the functions of the exosomes at the synapse were quite narrowly examined. For example, the title of the paper is pretty strong and the abstract does not say which functions were or were not affected by TSG101 KD.
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
Dresselhaus et al. investigates signaling functions for synaptic exosomes at the Drosophila NMJ. Exosomes are widely seen in vivo and in vitro. They are clearly sufficient to induce signaling responses in vitro, but whether they normally fulfill signaling functions in vivo has not been rigorously addressed. The authors make use of several mutants that block exosome release to test whether exosome release is important for two distinct signaling pathways: the Evi/Wg pathway and the Syt4 signaling pathway. Both pathways have been implicated in neuron to muscle signaling. Surprisingly, the authors find scant evidence that exosome release is required for either pathway. They convincingly show that knockdown of Tsg101 (an ESCRT-I component) does not phenocopy many synaptic phenotypes of either wg or syt4. Instead, they propose that in vivo, exosomes may serve as a proteostatic mechanism, as a mechanism for the neuron to dispose of unwanted/damaged proteins.
Specific comments are below:
R3.1 Loss of Tsg101 has been linked to upregulated MAPK stress signaling pathways and autophagy. Thus, it's possible that activating such compensatory mechanisms in Tsg101 knockdown animals could mask phenotypes associated with specific loss of EV cargoes such as Wg or Syt4. Indeed, the authors demonstrate that loss of Tsg101 and Hrs have very different effects on synaptic autophagy. To provide additional evidence that Wg or Syt4 signaling is independent of EV release, it would be good to check for wg/syt4 phenocopy in additional ESCRT complex mutants. I understand they did a bit with Shrub knockdown at low temperature in Figure 3, but the temperature-dependence of the ghost bouton phenotype clouds the interpretation. Could the authors try a motorneuron driver with a more restricted phenotype to overcome the lethality issues, or alternatively use one of their other ESCRT component mutants? This is obviously the central claim of the manuscript, and it would be strengthened by carrying out phenotypic analysis in mutants other than the Tsg101 RNAi line.
As noted for R2.5, we have added HFMR experiments for the HrsD28 genomic mutant, and found that despite being very unhealthy, they exhibit robust HFMR similar to Tsg101KD. We also confirmed dramatic depletion of Syt4 EVs in the HrsD28 mutant. Thus, the preserved Syt4 signaling function in ESCRT mutants with depleted EV Syt4 is not restricted to Tsg101, and does not depend on the co-occurring autophagy phenotype.
R3.2 In Figure 1, the authors show that neuronal Tsg101 RNAi dramatically reduces "postsynaptic" levels of exosome cargoes at the L3 stage to argue that exosome release is blocked in this mutant. While this seems very likely at the L3 stage, it is unclear when Tsg101 levels are reduced and thus when exosome release is impaired in this background. This is important because we don't know when these signaling pathways act. For example, it is possible that the critical period for Wg and Syt4 signaling is during the L1 stage, and that Tsg101 knockdown is incomplete at that stage. It is important to assay exosome release at earlier larval stage, particularly when RNAi is the method used to reduce gene function.
We have conducted this experiment. We noted accumulation of cargoes in Tsg101KD L1 larvae, indicating that the RNAi is effective early in development. However, we do not find many EVs in either wild-type or Tsg101KD first instar larvae (red is a-HRP, green is Syt4-GFP). This argues that it is unlikely that EV-mediated signaling has a critical period earlier in development. It is likely that the accumulation of EVs that we observe trapped in the muscle membrane reticulum in third instar larvae were laid down over days or hours of development. We do not propose to include these data in the manuscript unless the editors and reviewers prefer that we do so.
R3.3 If the Syt4 and Evi exosomes do not serve major signaling roles and are in fact neuronal waste, it seems likely they are phagocytosed by glia. Are levels of non-neuronal Syt4/Evi levels increased when glial phagocytosis in blocked (eg in draper mutants)?
As mentioned above, the Budnik lab previously showed that uptake and degradation of postsynaptic a-HRP-positive structures depends on glial and muscle phagocytosis.a-HRP recognizes a number of neuronally-derived glycoproteins (Snow et al., 1987). Though the Budnik lab had not previously linked these structures to EVs, we do know that they very strongly colocalize with known EV cargoes and depend on the exact same membrane traffic machinery for release, arguing that some a-HRP antigen proteins are also EV cargoes (Blanchette et al., 2022). To close this loop. we have added data showing that Syt4-positive EVs also depend on Draper for their clearance (Fig 7).
R3.4 For the HFMR experiment, it would be good to see the syt4-dependent phenotype as a positive control.__ __
As mentioned for R2.5, we have added the Syt4 positive control (Figure 6E,F), which fails to show HFMR as expected.
.__ __R3.5 In the abstract, the authors state that, "the cargoes are likely to function cell autonomously in the motorneuron". Isn't it alternatively possible that these proteins (wg in particular) could signal to the muscle in a non-exosome dependent pathway?
Yes, we believe that Wg is likely released by another mechanism (perhaps conventional secretion). As noted for R1.5 and R2.6, we have added new data in Fig. 5 showing that Frizzled nuclear import IS NOT disrupted in Hrs mutants, despite dramatic loss of Evi EVs. Interestingly Frizzled nuclear import (and postsynaptic development) IS altered in neuronal Tsg101KD larvae, which disrupt additional membrane trafficking pathways beyond EV release (see Fig. 3). This is particularly interesting in light of the normal Syt4 signaling in Tsg101KD larvae, and supports the hypothesis that Syt4 can function without leaving the neuron, while Wg must be released, albeit not via Hrs-dependent EV formation. Another (less parsimonious) interpretation is that very small amounts of Wg release in the Hrs mutant are sufficient to promote Frizzled nuclear import.
Reviewer #3 (Significance (Required)):
This is an important paper that is well-organized and logically presented. It makes a clear and largely compelling case against major signaling roles for exosomes at this synapse. The authors should be commended for publishing this work, which demands a re-evaluation of proposed key roles for exosomes at the fly NMJ. Given the intense interest in exosomes in neurobiology, this paper will be of great interest to neuronal cell biologists working across systems.
We thank the reviewer for their appreciation of the impact of our work on the field.
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Long post on 'how to' tag with a set of rules. Not a word on why to tag as a personal practice. Retrieval is key, and not just retrieval but retrieval in contexts. Not merely descriptive but mostly associative. That there is e.g. a #longtail of tags only used once is also a piece of information itself. E.g. when finding the starting point for a new branch of exploration. I find that [[Tags are valuable as pivots 20070815104800]]. The mostly used tags (unavoidable if you use a limited set as suggested in rule 2) become useless because they no longer demarcate a manageble chunck of material.
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Reviewer #1 (Public Review):
Summary:
The manuscript by Jang et al. describes the application of new methods to measure the localization of GTP-binding signaling proteins (G proteins) on different membrane structures in a model mammalian cell line (HEK293). G proteins mediate signaling by receptors found at the cell surface (GPCRs), with evidence from the last 15 years suggesting that GPCRs can induce G-protein mediated signaling from different membrane structures within the cell, with variation in signal localization leading to different cellular outcomes. While it has been clearly shown that different GPCRs efficiently traffic to various intracellular compartments, it is less clear whether G proteins traffic in the same manner, and whether GPCR trafficking facilitates "passenger" G protein trafficking. This question was a blind spot in the burgeoning field of GPCR localized signaling in need of careful study, and the results obtained will serve as an important guidepost for further work in this field. The extent to which G proteins localize to different membranes within the cell is the main experimental question tested in this manuscript. This question is pursued through two distinct methods, both relying on genetic modification of the G-beta subunit with a tag. In one method, G-beta is modified with a small fragment of the fluorescent protein mNG, which combines with the larger mNG fragment to form a fully functional fluorescent protein to facilitate protein trafficking by fluorescent microscopy. This approach was combined with the expression of fluorescent proteins directed to various intracellular compartments (different types of endosomes, lysosome, endoplasmic reticulum, Golgi, mitochondria) to look for colocalization of G-beta with these markers. These experiments showed compelling evidence that G-beta co-localizes with markers at the plasma membrane and the lysosome, with weak or absent co-localization for other markers. A second method for measuring localization relied on fusing G-beta with a small fragment from a miniature luciferase (HiBit) that combines with a larger luciferase fragment (LgBit) to form an active luciferase enzyme. Localization of G-beta (and luciferase signal) was measured using a method known as bystander BRET, which relies on the expression of a fluorescent protein BRET acceptor in different cellular compartments. Results using bystander BRET supported findings from fluorescence microscopy experiments. These methods for tracking G protein localization were also used to probe other questions. The activation of GPCRs from different classes had virtually no impact on the localization of G-beta, suggesting that GPCR activation does not result in the shuttling of G proteins through the endosomal pathway with activated receptors.
Strengths:
The question probed in this study is quite important and, in my opinion, understudied by the pharmacology community. The results presented here are an important call to be cognizant of the localization of GPCR coupling partners in different cellular compartments. Abundant reports of endosomal GPCR signaling need to consider how the impact of lower G protein abundance on endosomal membranes will affect the signaling responses under study.
The work presented is carefully executed, with seemingly high levels of technical rigor. These studies benefit from probing the experimental questions at hand using two different methods of measurement (fluorescent microscopy and bystander BRET). The observation that both methods arrive at the same (or a very similar) answer inspires confidence about the validity of these findings.
Weaknesses:
The rationale for fusing G-beta with either mNG2(11) or SmBit could benefit from some expansion. I understand the speculation that using the smallest tag possible may have the smallest impact on protein performance and localization, but plenty of researchers have fused proteins with whole fluorescent proteins to provide conclusions that have been confirmed by other methods. Many studies even use G proteins fused with fluorescent proteins or luciferases. Is there an important advantage to tagging G-beta with small tags? Is there evidence that G proteins with full-size protein tags behave aberrantly? If the studies presented here would not have been possible without these CRISPR-based tagging approaches, it would be helpful to provide more context to make this clearer. Perhaps one factor would be interference from newly synthesized G proteins-fluorescent protein fusions en route to the plasma membrane (in the ER and Golgi).
As noted by the authors, they do not demonstrate that the tagged G-beta is predominantly found within heterotrimeric G protein complexes. If there is substantial free G-beta, then many of the conclusions need to be reconsidered. Perhaps a comparison of immunoprecipitated tagged G beta vs immunoprecipitated supernatant, with blotting for other G protein subunits would be informative.
Additional context and questions:
(1) There exists some evidence that certain GPCRs can form enduring complexes with G-beta-gamma (Pubmed: 23297229, 27499021). That would seem to offer a mechanism that would enable receptor-mediated transport of G protein subunits. It would be helpful for the authors to place the findings of this manuscript in the context of these previous findings since they seem somewhat contradictory.
(2) There is some evidence that GaS undergoes measurable dissociation from the plasma membrane upon activation (see the mechanism of the assay in Pubmed: 35302493). It seems possible that G-alpha (and in particular GaS) might behave differently than the G-beta subunit studied here. This is not entirely clear from the discussion as it now stands.
(3) The authors say "The presence of mNG-b1 on late endosomes suggested that some G proteins may be degraded by lysosomes". The mechanism of lysosomal degradation by proteins on the outside of the lysosome is not clear. It would be helpful for the authors to clarify.
(4) Although the authors do a good job of assessing G protein dilution in endosomal membranes, it is unclear how this behavior compares to the measurement of other lipid-anchored proteins using the same approach. Is the dilution of G proteins what we would expect for any lipid-anchored protein at the inner leaflet of the plasma membrane?
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Reviewer #3 (Public Review):
Summary:
This article addresses an important and interesting question concerning intracellular localization and dynamics of endogenous G proteins. The fate and trafficking of G protein-coupled receptors (GPCRs) have been extensively studied but so far little is known about the trafficking routes of their partner G proteins that are known to dissociate from their respective receptors upon activation of the signaling pathway. The authors utilize modern cell biology tools including genome editing and bystander bioluminescence resonance energy transfer (BRET) to probe intracellular localization of G proteins in various membrane compartments in steady state and also upon receptor activation. Data presented in this manuscript shows that while G proteins are mostly present on the plasma membrane, they can be also detected in endosomal compartments, especially in late endosomes and lysosomes. This distribution, according to data presented in this study, seems not to be affected by receptor activation. These findings will have implications in further studies addressing GPCR signaling mechanisms from intracellular compartments.
Strengths:
The methods used in this study are adequate for the question asked. Especially, the use of genome-edited cells (for the addition of the tag on one of the G proteins) is a great choice to prevent the effects of overexpression. Moreover, the use of bystander BRET allowed authors to probe the intracellular localization of G proteins in a very high-throughput fashion. By combining imaging and BRET authors convincingly show that G proteins are very low abundant on early endosomes (also ER, mitochondria, and medial Golgi), however seem to accumulate on membranes of late endosomal compartments.
Weaknesses:
While the authors provide a novel dataset, many questions regarding G protein trafficking remain open. For example, it is not entirely clear which pathway is utilized to traffic G proteins from the plasma membrane to intracellular compartments. Additionally, future studies should also address the dynamics of G protein trafficking, for example by tracking them over multiple time points.
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Reviewer #2 (Public Review):
Summary:
Watanabe, Takashi, et al. investigated the use of the Golden Gate dual-expression vector system to enhance the modern standard for rapid screening of recombinant monoclonal antibodies. The presented data builds upon modern techniques that currently use multiple expression vectors to express heavy and light chain pairs. In a single vector, they express the linked heavy and light chain variable genes with a membrane-bound Ig which allows for rapid and more affordable cell-based screening. The final validation of H1 and H2 strain influenza screening resulted in 81 "H1+", 48 "H2+", and 9 "cross" reactive clones. The kinetics of some of the soluble antibodies were tested via SPR and validated with a competitive inhibition with classical well-characterized neutralizing clones.
Strengths:
In this study, Watanabe, Takashi, et al. further develop and refine the methodologies for the discovery of monoclonal antibodies. They elegantly merge newer technologies to speed up turnaround time and reduce the cost of antibody discovery. Their data supports the feasibility of their technique.
This study will have an impact on pandemic preparedness and antibody-based therapies.
Weaknesses:
A His tagged antigen was used for immunization and H1-his was used in all assays. Either the removal of His specific clones needs to be done before selection, or a different tag needs to be used in the subsequent assays.
This assay doesn't directly test the neutralization of influenza but rather equates viral clearance to competitive inhibition. The results would be strengthened with the demonstration of a functional antibody in vivo with viral clearance.
Limitations of this new technique are as follows: there is a significant loss of cells during FACs, transfection and cloning efficiency are critical to success, and well-based systems limit the number of possible clones (as the author discussed in the conclusions). Early enrichment of the B cells could improve efficiency, such as selection for memory B cells.
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Author response:
The following is the authors’ response to the original reviews.
Reviewer #3 (Public Review):
Summary:
It has been proposed in the literature, that the ATP release channel Panx1 can be activated in various ways, including by tyrosine phosphorylation of the Panx1 protein. The present study reexamines the commercial antibodies used previously in support of the phosphorylation hypothesis and the presented data indicate that the antibodies may recognize proteins unrelated to Panx1. Consequently, the authors caution about the use and interpretation of results obtained with these antibodies.
Strengths:
The manuscript by Ruan et al. addresses an important issue in Panx1 research, i.e. the activation of the channel formed by Panx1 via protein phosphorylation. If the authors' conclusions are correct, the previous claims for Panx1 phosphorylation on the basis of the commercial anti-phospho-Panx1 antibodies would be in question.
This is a very detailed and comprehensive analysis making use of state-of-the-art techniques, including mass spectrometry and phos-tag gel electrophoresis.
In general, the study is well-controlled as relating to negative controls.
The value of this manuscript is, that it could spawn new, more function-oriented studies on the activation of Panx1 channels.
Weaknesses:
Although the manuscript addresses an important issue, the activation of the ATP-release channel Panx1 by protein phosphorylation, the data provided do not support the firm conclusion that such activation does not exist. The failure to reproduce published data obtained with commercial anti-phospho Panx1 antibodies can only be of limited interest for a subfield.
(1) The title claiming that "Panx1 is NOT phosphorylated..." is not justified by the failure to reproduce previously published data obtained with these antibodies. If, as claimed, the antibodies do not recognize Panx1, their failure cannot be used to exclude tyrosine phosphorylation of the Panx1 protein. There is no positive control for the antibodies.
The full title of our manuscript is “Human Pannexin 1 Channel is NOT Phosphorylated by Src Tyrosine Kinase at Tyr199 and Tyr309”. The major conclusion of our manuscript shall not be extended to the claim that “Panx1 is NOT phosphorylated”. This is by no means our conclusion. In fact, the LC-MS/MS data from both ours and others have shown that PANX1 is phosphorylated at both serine and tyrosine sites1. However, we provided solid evidence that Tyr199 and Tyr309 of human PANX1 are not effective substrate of the Src kinase.
We did provide several positive controls for the antibodies in our study. We showed that the anti-PANX1 and anti-Src antibodies unambiguously recognized PANX1 and Src, respectively (Figure 3A), and that a pan-specific phosphotyrosine antibody (P-Tyr-100) unambiguously recognized phosphorylated Src (Figure 3A)—as expected—but did not recognize PANX1. In addition, we demonstrated that the two antibodies in question (anti-PANX1-pY198 and anti-PANX1-pY308) did produce signals in our western blot analysis, but we provided compelling evidence that the bands produced by these antibodies do not correspond to PANX1 (Figure 2B).
(2) The authors claim that exogenous SRC expression does not phosphorylate Y198. DeLalio et al. 2019 show that Panx1 is constitutively phosphorylated at Y198, so an effect of exogenous SRC expression is not necessarily expected.
We have unambiguously identified peptide fragments containing non-phosphorylated Y198 in our LC-MS/MS experiment, none corresponds to a phosphorylated Y198. Therefore, our LC-MS/MS data doesn’t support the notion that Panx1 is constitutively phosphorylated at Y198.
(3) The authors argue that the GFP tag of Panx1at the COOH terminus does not interfere with folding since the COOH modified (thrombin cleavage site) Panx1 folds properly, forming an amorphous glob in the cryo-EM structure. However, they do not show that the COOH-modified Panx1 folds properly. It may not, because functional data strongly suggest that the terminal cysteine dives deep into the pore. For example, the terminal cysteine, C426, can form a disulfide bond with an engineered cysteine at position F54 (Sandilos et al. 2012).
Our manuscript included results of using a non-GFP tagged PANX1 construct (Figure 2-figure supplement 1). We didn’t notice any difference for PANX1 phosphorylation between GFP-tagged and non-GFP-tagged PANX1. Therefore, the folding of the C-terminal tail of PANX1 doesn’t affect the conclusion of our study.
(4) The authors dismiss the additional arguments for tyrosine phosphorylation of Panx1 given by the various previous studies on Panx1 phosphorylation. These studies did not, as implied, solely rely on the commercial anti-phospho-Panx1 antibodies, but also presented a wealth of independent supporting data. Contrary to the authors' assertion, in the previous papers the pY198 and pY308 antibodies recognized two protein bands in the size range of glycosylated and partial glycosylated Panx1.
We didn’t dismiss additional arguments for the Src-dependent PANX1 regulation. In fact, in the discussion of our manuscript, we acknowledged the fact that Src may still be involved in PANX1 regulation, but probably through indirect mechanisms. In the two previous studies2,3, it’s unclear if the multimeric bands detected by pY198/pY308 antibodies correspond to glycosylated PANX1 or not, as the authors did not overlay the protein markers with their blots. In particular, the migration pattern of PANX1 changes across different western blot images from DeLalio et al2. It’s also worth noting that none of these “independent supporting data” in the two previous studies provided direct evidence that Src can phosphorylate pY198/pY308.
(5) A phosphorylation step triggering channel activity of Panx1 would be expected to occur exclusively on proteins embedded in the plasma membrane. The membrane-bound fraction is small in relation to the total protein, which is particularly true for exogenously expressed proteins. Thus, any phosphorylated protein may escape detection when total protein is analyzed. Furthermore, to be of functional consequence, only a small fraction of the channels present in the plasma membrane need to be in the open state. Consequently, only a fraction of the Panx1 protein in the plasma membrane may need to be phosphorylated. Even the high resolution of mass spectroscopy may not be sufficient to detect phosphorylated Panx1 in the absence of enrichment processes.
We agree with the reviewer that only plasma membrane-residing Panx1 phosphorylation is functionally relevant. Interestingly, however, previous studies actually analyzed total protein from cell lysate and concluded that PANX1 is phosphorylated at Y198 and Y3082,3. This has motivated our analysis, in which we found that the phosphorylation events cannot be detected when using whole cell lysate. Therefore, we have also conducted an electrophysiology experiment by comparing conditions with/without active Src kinase (Figure 7). Our result indicates that PANX1 current is not affected by the presence of Src. This result suggests that even if there might be minor Src kinase phosphorylation beyond detection limit of western blot or mass spectrometry, they may not be functionally significant as well.
(6) In the electrophysiology experiments described in Figure 7, there is no evidence that the GFP-tagged Panx1 is in the plasma membrane. Instead, the image in Figure 7a shows prominent fluorescence in the cytoplasm. In addition, there is no evidence that the CBX-sensitive currents in 7b are mediated by Panx1-GFP and are not endogenous Panx1. Previous literature suggests that the hPanx1 protein needs to be cleaved (Chiu et al. 2014) or mutated at the amino terminus (Michalski et al 2018) to see voltage-activated currents, so it is not clear that the currents represent hPANX1 voltage-activated currents.
Our previous analysis has already shown that endogenous current of non-transfected cells is not sensitive to CBX4. Therefore, the CBX-sensitive current in cells overexpressed PANX1 is from PANX1-GFP. It should be noted that when protein is overexpressed, it tends to accumulate at different intracellular membranes during protein synthesis/maturation. However, this doesn’t affect a portion of the protein to be trafficked to the plasma membrane. In the paper from Michalski et al 2018, it was shown that WT human/mouse PANX1 displayed voltage-dependent activation5. Although the current is relatively small, it is clearly distinguishable from non-transfected HEK and CHO cells. This voltage-dependent activation is also sensitive to CBX, consistent with our measurement (Figure 7)4. When GS is introduced at the N-terminus, the voltage-dependent activation of human/mouse PANX1 is significantly boosted, likely due to the altered NTH conformation resulting from the N-terminal extension.
Recommendations for the authors:
Reviewer #3 (Recommendations For The Authors):
Literature quotes are still problematic. Why are secondary papers quoted instead of the original work? At least quote reviews by authors who published the original findings.
We appreciate the reviewer pointing this out. We have carefully checked our references and made sure that the original literature is cited.
Why does wtPanx1 run close to the 37 kD marker (Figure 2 supplement 1) instead of close to 50 kD as shown in the previous papers using the pY198 and pY308 antibodies?
It is a common observation that membrane proteins migration in SDS-PAGE gel doesn’t correlate with their formula molecular weight, also known as “gel shifting”6–8. The molecular mechanism of this phenomenon remains complex. Therefore, simply relying on protein molecular standard could not unambiguously identify PANX1 protein band. This is an issue for identifying PANX1 band, especially in light of the fact that some antibodies may not be very specific (see Figure 6B). In our experiment, we have correlated the in-gel fluorescence and western blot signal which allowed us to determine the protein band corresponding to PANX1. It is worth noting that in Figure S3 of DeLalio 2019, the PANX1 is detected at 37 kDa2. However, in many other panels of the paper, PANX1 is detected at close to 50 kDa (for example, Figure S2B).
Figure 6, supplement 1: why are there oligomers observed in the absence of crosslinking? Why is there no shift in the size of the "oligomers" in response to glycosidase F?
It is common to observe multimeric membrane proteins, including PANX1, forming oligomeric bands in SDS-PAGE gels, likely because they are not fully denatured or disassembled. PANX1 also contains several free cysteines, which may non-specifically crosslink subunits. There is actually a small shift for the 75 kDa band (dimer) in Figure 6, supplement 1. For higher molecular weight bands, this small shift may not be apparent due to the limited resolution of the gel.
A positive control for the antibodies used is missing. The authors argue that such controls are not available, since these commercial antibodies are "proprietary".
We did provide several positive controls for the antibodies in our study. We showed that the anti-PANX1 and anti-Src antibodies unambiguously recognized PANX1 and Src, respectively (Figure 3A), and that a pan-specific phosphotyrosine antibody (P-Tyr-100) unambiguously recognized phosphorylated Src (Figure 3A)—as expected—but did not recognize PANX1. In addition, we demonstrated that the two antibodies in question (anti-PANX1-pY198 and anti-PANX1-pY308) did produce signals in our western blot analysis, but we provided compelling evidence that the bands produced by these antibodies do not correspond to PANX1 (Figure 2B).
Unfortunately, the epitopes that Millipore Sigma used to generate anti-PANX1-pY198 and anti-PANX1-pY308 are not available. The description of the immunogen from Millipore Sigma website states that “A linear peptide corresponding to 12 amino acids surrounding phospho-Tyr198 of murine Pannexin-1” and “A linear peptide corresponding to 13 amino acids surrounding phosphotyrosine 308 of rat pannexin-1”. However, these immunogen peptides are not available for us to purchase.
References
(1) Nouri-Nejad, D. et al. Pannexin 1 mutation found in melanoma tumor reduces phosphorylation, glycosylation, and trafficking of the channel-forming protein. Mol Biol Cell 32, (2021).
(2) DeLalio, L. J. et al. Constitutive SRC-mediated phosphorylation of pannexin 1 at tyrosine 198 occurs at the plasma membrane. Journal of Biological Chemistry 294, (2019).
(3) Weilinger, N. L. et al. Metabotropic NMDA receptor signaling couples Src family kinases to pannexin-1 during excitotoxicity. Nat Neurosci 19, (2016).
(4) Ruan, Z., Orozco, I. J., Du, J. & Lü, W. Structures of human pannexin 1 reveal ion pathways and mechanism of gating. Nature 584, (2020).
(5) Michalski, K., Henze, E., Nguyen, P., Lynch, P. & Kawate, T. The weak voltage dependence of pannexin 1 channels can be tuned by N-terminal modifications. Journal of General Physiology 150, (2018).
(6) Rath, A., Cunningham, F. & Deber, C. M. Acrylamide concentration determines the direction and magnitude of helical membrane protein gel shifts. Proc Natl Acad Sci U S A 110, (2013).
(7) Rath, A. & Deber, C. M. Correction factors for membrane protein molecular weight readouts on sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Anal Biochem 434, (2013).
(8) Rath, A., Glibowicka, M., Nadeau, V. G., Chen, G. & Deber, C. M. Detergent binding explains anomalous SDS-PAGE migration of membrane proteins. Proc Natl Acad Sci U S A 106, (2009).
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Reviewer #3 (Public Review):
The manuscript by Ruan et al. addresses an important issue in Panx1 research, i.e. the activation of the channel formed by Panx1 via protein phosphorylation. If the authors' conclusions are correct, the previous claims for Panx1 phosphorylation on the basis of the commercial anti-phospho-Panx1 antibodies would be in question.
This is a very detailed and comprehensive analysis making use of state-of-the-art techniques, including mass spectrometry and phos-tag gel electrophoresis.
In general, the study is well-controlled as relating to negative controls.
The value of this manuscript is, that it could spawn new, more function-oriented studies on the activation of Panx1 channels.
The weaknesses identified previously are reproduced below:
Weaknesses:
Although the manuscript addresses an important issue, the activation of the ATP-release channel Panx1 by protein phosphorylation, the data provided do not support the firm conclusion that such activation does not exist. The failure to reproduce published data obtained with commercial anti-phospho Panx1 antibodies can only be of limited interest for a subfield.
(1) The title claiming that "Panx1 is NOT phosphorylated..." is not justified by the failure to reproduce previously published data obtained with these antibodies. If, as claimed, the antibodies do not recognize Panx1, their failure cannot be used to exclude tyrosine phosphorylation of the Panx1 protein. There is no positive control for the antibodies.
(2) The authors claim that exogenous SRC expression does not phosphorylate Y198. DeLalio et al. 2019 show that Panx1 is constitutively phosphorylated at Y198, so an effect of exogenous SRC expression is not necessarily expected.
(3) The authors argue that the GFP tag of Panx1at the COOH terminus does not interfere with folding since the COOH modified (thrombin cleavage site) Panx1 folds properly, forming an amorphous glob in the cryo-EM structure. However, they do not show that the COOH-modified Panx1 folds properly. It may not, because functional data strongly suggest that the terminal cysteine dives deep into the pore. For example, the terminal cysteine, C426, can form a disulfide bond with an engineered cysteine at position F54 (Sandilos et al. 2012).
(4) The authors dismiss the additional arguments for tyrosine phosphorylation of Panx1 given by the various previous studies on Panx1 phosphorylation. These studies did not, as implied, solely rely on the commercial anti-phospho-Panx1 antibodies, but also presented a wealth of independent supporting data. Contrary to the authors' assertion, in the previous papers the pY198 and pY308 antibodies recognized two protein bands in the size range of glycosylated and partial glycosylated Panx1.
(5) A phosphorylation step triggering channel activity of Panx1 would be expected to occur exclusively on proteins embedded in the plasma membrane. The membrane-bound fraction is small in relation to the total protein, which is particularly true for exogenously expressed proteins. Thus, any phosphorylated protein may escape detection when total protein is analyzed. Furthermore, to be of functional consequence, only a small fraction of the channels present in the plasma membrane need to be in the open state. Consequently, only a fraction of the Panx1 protein in the plasma membrane may need to be phosphorylated. Even the high resolution of mass spectroscopy may not be sufficient to detect phosphorylated Panx1 in the absence of enrichment processes.
(6) In the electrophysiology experiments described in Figure 7, there is no evidence that the GFP-tagged Panx1 is in the plasma membrane. Instead, the image in Figure 7a shows prominent fluorescence in the cytoplasm. In addition, there is no evidence that the CBX-sensitive currents in 7b are mediated by Panx1-GFP and are not endogenous Panx1. Previous literature suggests that the hPanx1 protein needs to be cleaved (Chiu et al. 2014) or mutated at the amino terminus (Michalski et al 2018) to see voltage-activated currents, so it is not clear that the currents represent hPANX1 voltage-activated currents.
Note from the editors: The authors provided a rebuttal to the latest review, but no additional data, so we encourage readers to read the concerns and the author responses.
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Reviewer #2 (Public Review):
Summary:
This manuscript combines live yeast cell imaging and other genomic approaches to study how transcription factor (TF) condensates might help organize and enhance the transcription of the target genes in the methionine starvation response pathway. The authors show that the TFs in this response can form phase-separated condensates through their intrinsically disordered regions (IDRs), and mediate the spatial clustering of the related endogenous genes as well as reporter inserted near the endogenous target loci.
Strengths:
This work uses rigorous experimental approaches, such as imaging of endogenously labeled TFs, determining expression and clustering of endogenous target genes, and reporter integration near the endogenous target loci. The importance of TFs is shown by rapid degradation. Single-cell data are combined with genomic sequencing-based assays. Control loci engineered in the same way are usually included. Some of these controls are very helpful in showing the pathway-specific effect of the TF condensates in enhancing transcription.
Weaknesses:
Perhaps the biggest weakness of this work is that the role of IDR and phase separation in mediating the target gene clustering is unclear. This is an important question. TF IDRs may have many functions including mediating phase separation and binding to other transcriptional molecules (not limited to proteins and may even include RNAs). The effect of IDR deletion on reduced Fano number in cells could come from reduced binding with other molecules. This should be tested on phase separation of the purified protein after IDR deletion. Also, the authors have not shown IDR deletion affects the clustering of the target genes, so IDR deletion may affect the binding of other molecules (not the general transcription machinery) that are specifically important for target gene transcription. If the self-association of the IDR is the main driving force of the clustering and target gene transcription enhancement, can one replace this IDR with totally unrelated IDRs that have been shown to mediate phase separation in non-transcription systems and still see the gene clustering and transcription enhancement effects? This work has all the setup to test this hypothesis.
The Met4 protein was tagged with MBP but Met 32 was not. MBP tag is well known to enhance protein solubility and prevent phase separation. This made the comparison of their in vitro phase behavior very different and led the authors to think that maybe Met32 is the scaffold in the co-condensates. If MBP was necessary to increase yield and solubility during expression and purification, it should be cleaved (a protease cleavage site should be engineered) to allow phase separation in vitro.
Are ATG36 and LDS2 also supposed to be induced by -met? This should be explained clearly. The signals are high at -met.
Figure 6B, the Met4-GFP seems to form condensates at all three loci without a very obvious difference, though 6C shows a difference. 6C is from only one picture each. The authors should probably quantify the signals from a large number of randomly selected pictures (cells) and do statistics.
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- Apr 2024
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Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
During the last decades, extensive studies (mostly neglected by the authors), using in vitro and in vivo models, have elucidated the five-step mechanism of intoxication of botulinum neurotoxins (BoNTs). The binding domain (H chain) of all serotypes of BoNTs binds polysialogangliosides and the luminal domain of a synaptic vesicle protein (which varies among serotypes). When bound to the synaptic membrane of neurons, BoNTs are rapidly internalized by synaptic vesicles (SVs) via endocytosis. Subsequently, the catalytic domain (L chain) translocates, a process triggered by the acidification of these organelles. Following translocation, the disulfide bridge connecting the H chain with the L chain is reduced by the thioredoxin reductase/thioredoxin system, and it is refolded by the chaperone Hsp90 on SV's surface. Once released into the cytosol, the L chains of different serotypes cleave distinct peptide bonds of specific SNARE proteins, thereby disrupting neurotransmission. In this study, Yeo et al. extensively revise the neuronal intoxication model, suggesting that BoNT/A follows a more complex intracellular route than previously thought. The authors propose that upon internalization, BoNT/A-containing endosomes are retro-axonally trafficked to the soma. At the level of the neuronal soma, this serotype then traffics to the endoplasmic reticulum (ER) via the Golgi apparatus. The ER SEC61 translocon complex facilitates the translocation of BoNT/A's LC from the ER lumen into the cytosol, where the thioredoxin reductase/thioredoxin system and HSP complexes release and refold the catalytic L chain. Subsequently, the L chain diffuses and cleaves SNAP25 first in the soma before reaching neurites and synapses. Strengths:
I appreciate the authors' efforts to confirm that the newly established methods somehow recapitulate aspects of the BoNTs mechanism of action, such as toxin binding and uptake occurring at the level of active synapses. Furthermore, even though I consider the SNAPR approach inadequate, the genome-wide RNAi screen has been well executed and thoroughly analyzed. It includes well-established positive and negative controls, making it a comprehensive resource not only for scientists working in the field of botulinum neurotoxins but also for cell biologists studying endocytosis more broadly. Weaknesses:
I have several concerns about the authors' main conclusions, primarily due to the lack of essential controls and validation for the newly developed methods used to assess toxin cleavage and trafficking into neurons. Furthermore, there is a significant discrepancy between the proposed intoxication model and existing studies conducted in more physiological settings. In my opinion, the authors have omitted over 20 years of work done in several labs worldwide (Montecucco, Montal, Schiavo, Rummel, Binz, etc.). I want to emphasize that I support changes in biological dogma only when these changes are supported by compelling experimental evidence, which I could not find in the present manuscript.
We thank the reviewer for his reading and comments and for pointing out the discrepancy between our proposed model and the existing model. However, we respectfully disagree with the phrase of “extensive studies have elucidated the five-steps mechanism of intoxication…”. This sentence and the following imply that the model is well-established and demonstrated. It also highlights how the reviewer is convinced about this previous model.
We contest this model for theoretical reasons and contest the strength of evidences that support it. We previously included references to previous work showing that the model is also being challenged by others. In light of the reviewer’s comments, we incluced more references in the introduction and we also explicit our main theoretical concern in the introduction:
“Arguably, the main problem of the model is its failure to propose a thermodynamically consistent explanation for the directional translocation of a polypeptidic chain across a biologial membrane. Other known instances of polypeptide membrane translocation such as the co-translational translocation into the ER indicate that it is an unfavorable process, which consumes significant energy (Alder and Theg 2003). ”
We also added the following text in the Discussion to address with the reviewer’s concerns: “Our study contradicts the long-established model of BoNT intoxication, which is described in several reviews specifically dedicated to the subject 1–4. In short, these reviews support the notion that BoNT are molecular machines able to mediate their own translocation across membranes; this notion has convinced some cell biologists interested in toxins and retrograde traffic, who describe BoNT mode of translocation in their reviews 5,6.
But is this notion well supported by data? A careful examination of the primary literature reveals that early studies indeed report that BonTs form ion channels at low pH values 7,8. These studies have been extended by the use of patch-clamp 9,10. These works and others lead to various suppositions on how the toxin forms a channel and translocate the LC 1,11 .
However, only a single study claims to reconstitute in vitro the translocation of BonT LC across membranes 12. In this paper, the authors report using a system of artificial membranes separating two aqueous compartments. They load the toxin in the cis compartment and measure the protease activity in the trans compartment after incubation. However, when the experimental conditions described are actually converted in terms of molarity, it appears that the cis compartment was loaded at 10e-8M BonT and that the reported translocated protease activity is equivalent to 10e-17 M (Figure 3D, 12). Thus, in this experiment, about 1 LC molecule in 100 millions has crossed the membrane. Such extremely low transfert rate does not tally with the extreme efficiency of intoxication in vivo, even while taking into account the difference between artificial and biological membranes.
In sum, a careful analysis of the primary literature indicate that while there is ample evidence that BoNTs have the ability to affect membranes and possibly create ion channels, there is actually no credible evidence that these channels mediate translocation of the LC. As mentioned earlier, it is not clear how such a self-translocation mechanism would function thermodynamically. By contrast, our model proposes a mechanism without a thermodynamic problem, is consistent with current knowledge about other protein toxins, such as PE, Shiga and Ricin, and can help explain previously puzzling features of BonT effects. It is worth noting that a similar self-translocation model was proposed for other protein toxins such as Pseudomonas exotoxin, which have similar molecular organisation as BonT (68). However, it has since been demonstrated that the PE toxins require cellular machinery, in particular in the ER, for intoxication (21,69,70).”
Reviewer #2 (Public Review):
Summary:
The study by Yeo and co-authors addresses a long-lasting issue about botulinum neurotoxin (BoNT) intoxication. The current view is that the toxin binds to its receptors at the axon terminus by its HCc domain and is internalized in recycled neuromediator vesicles just after the release of the neuromediators. Then, the HCn domain assists the translocation of the catalytic light chain (LC) of the toxin through the membrane of these endocytic vesicles into the cytosol of the axon terminus. There, the LC cleaves its SNARE substrate and blocks neurosecretion. However, other views involving kinetic aspects of intoxication suggest that the toxin follows the retrograde axonal transport up to the nerve cell body and then back to the nerve terminus before cleaving its substrate.
In the current study, the authors claim that the BoNT/A (isotype A of BoNT) not only progresses to the cell body but once there, follows the retrograde transport trafficking pathway in a retromer-dependent fashion, through the Golgi apparatus, until reaching the endoplasmic reticulum. Next, the LC dissociates from the HC (a process not studied here) and uses the translocon Sec61 machinery to retro-translocate into the cytosol. Only then, does the LC traffic back to the nerve terminus following the anterograde axonal transport. Once there, LC cleaves its SNARE substrate (SNAP25 in the case of BoTN/A) and blocks neurosecretion.
To reach their conclusion, Yeo and co-authors use a combination of engineered tools: a cell line able to differentiate into neurons (ReNcell VN), a reporter dual fluorescent protein derived from SNAP25, the substrate of BoNT/A (called SNAPR), the use of either native BoNT/A or a toxin to which three fragment 11 of the reporter fluorescent protein Neon Green (mNG) are fused to the N-terminus of the LC (BoNT/A-mNG11x3), and finally ReNcell VN transfected with mNG1-10 (a protein consisting of the first 10 beta strands of the mNG).
SNAPR is stably expressed all over in the ReNcell VN. SNAPR is yellow (red and green) when intact and becomes red only when cleaved by BoNT/A LC, the green tip being degraded by the cell. When the LC of BoNT/A-mNG11x3 reaches the cytosol in ReNcell VN transfected by mNG1-10, the complete mNG is reconstituted and emits a green fluorescence.
In the first experiment, the authors show that the catalytic activity of the LC appears first in the cell body of neurons where SNAPR is cleaved first. This phenomenon starts 24 hours after intoxication and progresses along the axon towards the nerve terminus during an additional 24 hours. In a second experiment, the authors intoxicate the ReNcell VN transfected by mNG1-10 using the BoNT/A-mNG11x3. The fluorescence appears also first in the soma of neurons, then diffuses in the neurites in 48 hours. The conclusion of these two experiments is that translocation occurs first in the cell body and that the LC diffuses in the cytosol of the axon in an anterograde fashion.
In the second part of the study, the authors perform a siRNA screen to identify regulators of BoNT/A intoxication. Their aim is to identify genes involved in intracellular trafficking of the toxin and translocation of the LC. Interestingly, they found positive and negative regulators of intoxication. Regulators could be regrouped according to the sequential events of intoxication.
Genes affecting binding to the cell-surface receptor (SV2) and internalization. Genes involved in intracellular trafficking. Genes involved in translocation such as reduction of the disulfide bond linking the LC to the HC and refolding in the cytosol. Genes involved in signaling such as tyrosine kinases and phosphatases. All these groups of genes may be consistent with the current view of BoNT intoxication within the nerve terminus. However, two sets of genes were particularly significant to reach the main conclusion of the work and definitely constitute an original finding important to the field. One set of genes consists of those of the retromer, and the other relates to the Sec61 translocon. This should indicate that once endocytosed, the BoNT traffics from the endosomes to the Golgi apparatus, and then to the ER. Ultimately, the LC should translocate from the ER lumen to the cytosol using the Sec61 translocon. The authors further control that the SV2 receptor for the BoNT/A traffics along the axon in a retromer-dependent fashion and that BoNT/A-mNG11x3 traverses the Golgi apparatus by fusing the mNG1-10 to a Golgi resident protein.
Strengths:
The findings in this work are convincing. The experiments are carefully done and are properly controlled. In the first part of the study, both the activity of the LC is monitored together with the physical presence of the toxin. In the second part of the work, the most relevant genes that came out of the siRNA screen are checked individually in the ReNcell VN / BoNT/A reporter system to confirm their role in BoNT/A trafficking and retro-translocation.
These findings are important to the fields of toxinology and medical treatment of neuromuscular diseases by BoNTs. They may explain some aspects of intoxication such as slow symptom onset, aggravation, and appearance of central effects.
Weaknesses:
The findings antagonize the current view of the intoxication pathway that is sustained by a vast amount of observations. The findings are certainly valid, but their generalization as the sole mechanism of BoNT intoxication should be tempered. These observations are restricted to one particular neuronal model and engineered protein tools. Other models such as isolated nerve/muscle preparations display nerve terminus paralysis within minutes rather than days. Also, the tetanus neurotoxin (TeNT), whose mechanism of action involving axonal transport to the posterior ganglia in the spinal cord is well described, takes between 5 and 15 days. It is thus possible that different intoxication mechanisms co-exist for BoNTs or even vary depending on the type of neurons.
Although the siRNA experiments are convincing, it would be nice to reach the same observations with drugs affecting the endocytic to Golgi to ER transport (such as Retro-2, golgicide or brefeldin A) and the Sec61 retrotranslocation (such as mycolactone). Then, it would be nice to check other neuronal systems for the same observations.
We thank the reviewer for the careful reading and comments of our manuscript. The reference to “a vast amount of observation” is a similar argument to the Reviewer 1 and used to suggest that our study may not be applicable as a general mechanism.
We respectfully disagree as described above and posit on the contrary that the model we propose is much more likely to be general than the model presented in current reviews for the several reasons cited (see added text in Introduction and Discussion). While we agree that more work is needed to confirm the proposed mechanisms of BonT translocation in other models, these experiments fall outside the perimeter of our study.
The fact that nerve/muscle preparations of BonT activity have relatively fast kinetics does not pose a contradiction to our model. Our model reveals primarily the requirement for trafficking to the ER membranes. This ER targeting requires trafficking through the Golgi complex, in turn explaining the requirement for trafficking to the soma of neurons in the experimental system we used. However, in neuronal cells in vivo, Golgi bodies can be found along the lenght of the axon, thus BonT may not always require trafficking to the soma of the affected cells. The time required for intoxication could thus vary greatly depending on the neuronal structural organisation.
TenT is proposed to transfer from excitatory neurons into inhibitory neurons before exerting its action. While the detailed mechanism of this fascinating mechanism remain to be explored, it clearly falls beyond the purview of this manuscript.
Regarding the use of drugs, we agree that it would be a nice addition; unfortunately we are unable to perform such experiments at this stage. Setting up a large scale siRNA screen for BonT mechanism of action is challenging as it requires a special facility with controlled access and police authorisation (in Singapore) given the high toxicity of this molecule. Unfortunately, the authorisations have now lapsed.
Reviewer #3 (Public Review): Summary:
The manuscript by Yao et al. investigates the intracellular trafficking of Botulinum neurotoxin A (BoNT/A), a potent toxin used in clinical and cosmetic applications. Contrary to the prevailing understanding of BoNT/A translocation into the cytosol, the study suggests a retrograde migration from the synapse to the soma-localized Golgi in neurons. Using a genome-wide siRNA screen in genetically engineered neurons, the researchers identified over three hundred genes involved in this process. The study employs organelle-specific split-mNG complementation, revealing that BoNT/A traffics through the Golgi in a retromer-dependent manner before moving to the endoplasmic reticulum (ER). The Sec61 complex is implicated in the retro-translocation of BoNT/A from the ER to the cytosol. Overall, the research challenges the conventional model of BoNT/A translocation, uncovering a complex route from synapse to cytosol for efficient intoxication. The findings are based on a comprehensive approach, including the introduction of a fluorescent reporter for BoNT/A catalytic activity and genetic manipulations in neuronal cell lines. The conclusions highlight the importance of retrograde trafficking and the involvement of specific genes and cellular processes in BoNT/A intoxication.
Strengths:
The major part of the experiments are convincing. They are well-controlled and the interpretation of their results is balanced and sensitive.
Weaknesses:
To my opinion, the main weakness of the paper is in the interpretation of the data equating loss of tGFP signal (when using the Red SNAPR assay) with proteolytic cleavage by the toxin. Indeed, the first step for loss of tGFP signal by degradation of the cleaved part is the actual cleavage. However, this needs to be degraded (by the proteasome, I presume), a process that could in principle be affected (in speed or extent) by the toxin.
We thank the reviewer for his comments and careful reading of our manuscript.
Regarding the read-out of the assay, we agree that the assay could be sensitive to alteration in the protein degradation pathway. We have added the following sentence in the Discussion to take it into account:
“As noted by one reviewer, the assay may be sensitive to perturbation in the general rate of protein degradation, a consideration to keep in mind when evaluating the results of large scale screens.”
While this may be valid for some hits in the general list, it is important to note that the main hits have been shown to affect toxin trafficking by an independent, orthogonal assay based on the split GFP reconstitution.
Recommendations to authors:
Reviewer #1 (Recommendations For The Authors):
(1) To assess the activity of BoNT/A in neurons, Yeo et al. have generated a neuronal stem line referred to as SNAPR. This cell line stably expresses a chimeric reporter protein that consists of SNAP25 flanked at its N-terminus with a tagRFPT and at its C-terminus with a tagGFP. After exposure to BoNT/A, SNAP25 is cleaved and, the C-terminal tGFP-containing moiety is rapidly degraded. I have many doubts about the validity of the described method. Indeed, BoNT/A activity is analysed in an indirect way by quantifying the degradation of the GFP moiety generated after toxin cleavage (Fig. 2). In this regard, the authors should consider that their approach is dependent, not only on the toxin's metalloprotease activity but also on the functionality of the proteasome in neurons. Therefore, considering the current dataset, it is impossible to rule out the possibility that the progression of GFP signal loss from the soma to the neurite terminals may be attributed to the different proteasome activity in these compartments. Is it conceivable that the GFP fragment generated upon toxin cleavage degrades more rapidly in the soma in comparison to axonal terminals? This alternative explanation could challenge the conclusion drawn in Fig. 2.
The reviewer’s alternative explanation disregards the experiments performed with the split-GFP complementation approach, which indicate translocation in the soma first. The split GFP reporter is not dependent on the proteasome activity. It also disregard the genetic data implicating many genes involved in membrane retrograde traffic, which are also not consistent with the hypothesis of the reviewer. These genes depletions not only affect SNAPR degradation but also BoNT/A-mNG11 trafficking: thus, their effect cannot be attributed to an completely hypothetical spatial heterogeneous distribution of the proteasome.
For this reason, I strongly suggest using a more physiological approach that does not depend on proteasomal degradation or on the expression of the sensor in neurons. The authors should consider performing a time course experiment following intoxication and staining BoNT/A-cleaved SNAP25 by using specific antibodies (see Antonucci F. et al., Journal of Neuroscience, 2008 or Rheaume C. et al., Toxins 2015).
For the above reason, we do not agree with the pressing importance of confirming by a third method using specific antibodies; especially considering that BonT is very difficult to detect in cells when incubated at physiological levels. By the way, the cited paper, by Antonucci F; et al. documents long distance retrograde traffic of BonT/A, which is in line with our data.
An alternative approach could involve the use of microfluidic devices that physically separate axons from cell bodies. Such a separation will allow us to test the authors' primary conclusion that SNAP25 is initially cleaved in the soma. The suggested experiments will also rule out potential overexpression artifacts that could influence the authors' conclusions when using the newly developed SNAPR approach. Without these additional experiments, the authors' main conclusion that SNAP25 is cleaved first in the neuronal soma rather than at the nerve terminal is inadequate.
As discussed above we disagree about the doubts raised by the reviewer: we present three types of evidences (SNAPR, split GFP and genetic hits) and they all point in the same direction. Thus, we respectfully doubt that a fourth approach would convince this reviewer. To note, we have attempted to use microfluidics devices as suggested by the reviewer, however, the Ren-VM neurons were not able to extend axons long enough across the device.
(2) To detect BoNT/A translocation into the cytosol, the authors have used a complementation assay by intoxicating ReNcell VM cell expressing a cytosolic HA-tagged split monomeric NeonGreen (Cyt-mNG1-10) with an engineered BoNT/A, where the catalytic domain (LC) was fused to mNG1-11. When drawing conclusions regarding the detection of cytosolic LC in the neuronal soma, the authors should highlight the limitations of this assay and explicitly describe them to the readers. Firstly, the authors need to investigate whether the addition of mNG1-11 to the LC affects the translocation process itself (by comparing with a WT, not tagged, LC).
Additionally, from the data shown in Fig. 2C, it is evident that the Cyt-mNG1-10 is predominantly expressed in the cytosol and less detected in neurites. This raises the question of whether there might be a bias for the cell soma in this assay. To address this important concern, I suggest quantifying MFI per cell (Fig. 2D) taking into consideration the amount of HA-tagged Cyt-mNG1-10. Furthermore, I strongly suggest targeting mNG1-10 to synapses and performing a similar time course experiment to observe when LC translocation occurs at nerve terminals. Alternative experiments, to prove that BoNT/A requires retrograde trafficking before it can translocate, may be done to repeat the experiments shown in Fig. 2D in the presence of inhibitors (or by KD some of the hits identified as microtubule stabilizers) that should interfere with BoNT/A trafficking to the neuronal somata. Without these additional experiments, the authors' main conclusion that the BoNT/A catalytic domain is first detected in the neuronal soma rather than at the nerve terminal is very preliminary.
Similarly as for the SNAPR assay, the reviewer is raising the level of doubt to very high levels. We respect his thoroughness and eagerness to question the new model. However, we note that a similar level of scrutiny does not apply to the prevalent competitive model. Indeed, the data supporting the self-translocation model is based on a single in vitro experiment published in one panel as we have explain din the discussion (see above).
(3) In the genome-wide RNAi screening, rather than solely assessing SV2 surface levels, it would have been beneficial to directly investigate BoNT/A binding to the neuronal membrane. For instance, this could have been achieved by using a GFP-tagged HC domain of BoNT/A. At present, the authors cannot exclude the possibility that among the 135 hits that did not affect SV2 levels, some might still inhibit BoNT/A binding to the neuronal surface. These concerns, already exemplified by B4CALT4 (which is known to be involved in the synthesis of GT1b), should be explicitly addressed in the main text.
We agree with the reviewer that perturbation of binding of BonT is possible. We added the following text:
“Network analysis reveals regulators of signaling, membrane trafficking and thioreductase redox state involved in BoNT/A intoxication
Among the positive regulators of the screen, 135 hits did not influence significantly surface SV2 levels and are thus likely to function in post-endocytic processes (Supplementary Table 2). However, we cannot formerly exclude that they could affect binding of BonT to the cell surface independently of SV2.”
(4) The authors should clearly state which reagents they have tried to use in order to explain the challenges they faced when directly testing the trafficking of BoNT/A. The accumulation of Dendra-SV2 bulbous structures at the neurite tips in VPS35-depleted cells could be interpreted as a sign of neuronal stress/death. Have the authors investigated other proteins that do not undergo retro-axonal trafficking in a retromer-dependent manner? This control is essential. In this regard, the use of a GFP-tagged HC domain of BoNT/A could prove to be quite helpful.
We tried multiple commercially available antibodies against BonT but we could not get a very good signal. The postdoc in charge of this project has now gone to greener pastures and we are not in the capacity to provide the details corresponding to these antibodies. We di dnot observe significant cell death after VPS-35 knockdown at the time of the experiment, however longe rterm treatment might result in toxicity indeed.
(5) Considering my concerns related to the SNAPR system and the complementation assay to study SNAP25 cleavage and BoNT/A trafficking, I suggest validating some of their major hits (ex. VPS34 and Sec61) by performing WB or IF analysis to examine the cleavage of endogenous SNAP25. Furthermore, the authors should test VPS35 depletion in the context of the experiments performed in Fig. 6G-H, by validating that this protein is essential for BoNT/A retrograde trafficking.
The reviewer concerns are well noted but as discussed above, the two systems we used are completely orthogonal. Thus, for the reviewer’s concerns to be valid, it would have to be two completely independent artefacts giving rise to the same result. The alternative explanation is that BonT/A translocates in the soma. The Ockham razor principle dictates that the simplest explanation is the likeliest.
(6) The introduction and the discussion section of this paper completely disregard more than 20 years of research conducted by several labs worldwide (Montecucco, Montal, Schiavo, Rummel, Binz, etc). The authors should make an effort to contextualize their data within the framework of these studies and address the significant discrepancies between their proposed intoxication model and existing research that clearly demonstrates BoNTs translocating upon the endocytic retrieval of SVs at presynaptic sites. Nevertheless, even assuming that the model proposed by the authors is accurate, numerous questions emerge. One such question is: How can the authors explain the exceptional toxicity of botulinum neurotoxin in an ex vivo neuromuscular junction preparation devoid of neuronal cell bodies (see Cesare Montecucco and Andreas Rummel's seminal studies)?
Please see above in the answer to public reviews.
(7) Scale bars should be added to all representative pictures.
This has been done. Thank you for the thorough reading of our manuscript.
Reviewer #2(Recommendations For The Authors):*
(1) The title overstates the results. It may be indicated "in differenciated ReNcell VM".
Title changed to: “Botulinum toxin intoxication requires retrograde transport and membrane translocation at the ER in RenVM neurons”
(2) In the provided manuscript there are two Figure 2 and no Figure 3. This made the reading and understanding extremely difficult and should be corrected. As a result, the Figure legends do not fit the numbering. There are also discrepancies between some Figure panels (A, B, C, etc), the text, and the Legends. All this needs to be carefully checked.
We apologize for the confusion as the manuscript as followed multiple rounds of revisions. We have carefully verified labels and legends.
(3) The BoNT/A-mNG11x3 may introduce some bias that could be discussed. Would these additional peptides block LC translocation from synaptic vesicles in the nerve termini? In addition, the mNG peptides that are unfolded before complementation may direct LC towards Sec61. These aspects should be discussed.
The comment would be valid if BoNT/A-mNG11x3 was the only approach used in the paper, however the SNAPR reporter is used with native BonT and shows data consistent with the split GFP approach.
(4) In the Figure about SV2 (Fig 3 or 4): The authors did not locate SV2. The cells seem not to have the same differentiated phenotype as in Figure 1 and Figure 2/3A.
We apologized above for the mislabeling. It is not clear what is the question here.
(5) The authors should check whether BoNT/A wt cleaves the endogeneous SNAP25 by western blot for instance in the original ReNcell VN before SNAPR engineering. This should be compared with wt SNAP25 cleavage by the BoNT/A-LC-mNG.
It is likely that BoNT/A-LC-mNG11 should have similar activity as it is only adding a small peptide at the end of the LC. At any rate, it is not clear why this is so important since both molecules translocate in the cytosol, with the same kinetics and in the same subcellular locale.
(6) Perhaps I did not understand. How can the authors exclude that what is observed is the kinetic overproduction of the reporter substrate SNAPR?
The authors could use SLO toxin (PNAS 98, 3185-3190, 2001) to permeabilize the cells all along their body and axon to introduce BoNT/A or LC (wt) and observe synchronized SNAPR cleavage throughout the cells.
The concept mentioned here is not very clear to us. The reviewer is proposing that the SNAPR is produced much more efficiently at the tips of the neurites and thus its cleavage takes longer to be detected and is apparent first in the soma?? With all due respect, this is a strange hypothesis, at odds with what we know of protein dynamics in the neurons (i.e. most proteins are largely made in the soma and transported or diffuse into the neurites).
Again, the two orthogonal approaches: split GFP and SNAPR reporter use different constructs and methods, yet converge on similar results. Perhaps, the incredulity of the reviewer might be more productively directed at the current data “demonstrating” the translocation of LC in the synaptic button?
(7) The authors could also use an essay on neurotransmitter release monitoring by electrophysiology measurements to check the functional consequences of the kinetic diffusion of LC activity along the axon. Can the authors exclude that some toxin molecules translocate from the endocytic vesicles and block neurotransmission within minutes or a few hours?
It is well established that inhibition of neurotransmission does not occur within minutes in vivo and in vitro, but rather within hours or even days. This kinetic delay is experienced by many patients and is one of the key argument against the current model of self-translocation at the synaptic vesicle level.
Minor remarks
Thank you for pointing out all these.
(1) Please check typos. There are many. Check space before the parenthesis, between numbers and h (hours), reference style etc.
Thank you. We have reviewed the text and try to eliminate all these instances.
(2) Line 90: The C of HC should be capitalized.
Fixed
(3) Line 107: add space between "neurons(Donato".
Fixed
(4) Line 109: space "72 h".
Fixed
(5) Line 115: a word is missing ? ...to show retro-axonal... ? Please clarify this sentence.
Fixed
(6) Figure 1E: does nm refer to nM (nanomolar)? Please correct. No mention of panel F.
Fixed
(7) Line 161: do you mean ~16 µm/h? Please correct.
Fixed
(8) Line 168, words are missing.
Fixed, thank you
We verified that Cyt-mNG1-10 was expressed using the HA tag, the expression was homogeneously distributed in differentiated neurons and we observed no GFP signal (Figure2C).
(9) Line 171: Isn't mNG 11 the eleventh beta strand of the neon green fluorescent protein, not alpha helix? Otherwise, can the authors confirm it acquires the shape of an alpha helix? Same at line 326.
We have corrected the mistake; thanks for pointing it out.
(10) Figure 2 is doubled. The legend of Fig 2 refers to Figure 3. There is no legend for Figure 2. Then, some figures are shifted in their numbering.
Fixed
(11) The fluorescence in the cell body must appear before the fluorescence in the axon due to higher volume. Please discuss.
The fluorescence progresses in the neurites extensions in a centripetal fashion. The volume of the neurite near the cell body is not significantly different from the end of the neurite. Thus the fluorescence data is consistent with translocation in soma and not with an effect due to higher volume in the soma.
(12) Figure 2D, right: the term intoxication is improper for this experiment. Rather, it is the presence of the BoNT/A-mNG11 that is detected. I believe the authors should be particularly careful about the use of terms: intoxication means blockade of neurosecretion, SNAPR cleavage means activity etc.
While the reviewer is correct that it is the presence of BoNT/A-mNG11 that is detected, it remains that it is an active toxin, so the neurons are effectively intoxicated; as they are when we use the wild type toxin. We do not imply that we are measuring intoxication, but simply that the neurons are put into contact with a toxin.
(13) Line 196: Should we read TXNRD1 is required for BoNT/A LC translocation? TXNRD1 in the current model of translocation is located in the cytoplasm and is supposed to play a role in the cleavage of the disulfide bond linking LC to HC. In the model proposed by this study, LC is translocated through the Sec61 translocon. In this case, I would assume that the protein disulfide isomerase (PDI) in the endoplasmic reticulum would reduce the LC-HC disulfide bond. In that case, TXNRD1 would not be required anymore. Please discuss.
Why should we assume that a PDI is involved in the reduction of the LC-HC disulfide bond? In our previous studies on A-B toxins (PE and Ricin), different reduction systems seemed to be at play. There is no conceptual imperative to assume reduction in the ER because the Sec61 translocon is implicated. Reduction might occur on the cytosolic side by TXNRD1 or the effect of this reductase could be indirect.
(14) The legend of Figure 4 (in principle Figure 5?) is not matching with the panels and panel entries are missing (Figure 4F in particular).
Fixed
(15) Figure 6 panels E and H, please match colors with legend (grey and another color).
Not clear
(16) Please indicate BoNT/A construct concentrations in all Figure legends.
Done
(17) Line 416: isn't SV2 also involved in epilepsy?
Yes it is.
(18) Line 433: as above, shouldn't the disulfide bond linking LC to HC be cleaved by PDI in the ER in this model (as for other translocating bacterial toxins) rather than by thioredoxin reductases in the cytoplasm? Please discuss.
See above
(19) Identification of vATPase in the screen could be consistent with the endocytic vesicle acidification model of translocation.
Yes
(20) Did the authors add KCl in screening controls without toxins? This should be detailed in the Materials and Methods. Could there be a KCl effect on the cells? KCl exposure for 48 hours may be highly stressful for cells. The KCl exposure should last only several minutes for toxin entry.
We did not observe significant cell detah with the cell culture conditions used. Cell viability was controlled at multiple stages using nuclei number for instance
Reviewer #3 (Recommendations For The Authors):
Main comments: (1) In Figure 1B: could you devise a means to prevent proteosomal degradation of the tGFP cleaved part to assess whether this is formed?
We have also used a FRET assay after tintoxication and obtained similar results
(2) Line 152: Where it reads "was not surprising", maybe I missed something, but to me, this is indeed surprising. If the toxin is rapidly internalized and translocated (therefore, it is able to cleave SNAP25), the fact that tGFP requires 48 hours to be degraded seems surprising to me. Or does it mean that the toxin also slows down the degradation of the tGFP fragment? So, how can you differentiate between the effect being on cleavage of the fragment or in tGFP degradation?
The reviewer is correct, the “not” was a typo due to re-writting; the long delay between adding the toxin and observing cleavage was suprising indeed. Our interpretation is that it is trafficking that takes time, indeed, the split-GFP data kinetics indicates that the toxin takes about 48h to fill up the entire cytosol (Fig. 2D).
(3) Regarding the effect of Sec61G knockdown, is it possible that the observed effects are indirect and not due to the translocon being directly responsible for translocating the protein?
As discussed in the last part of the results,Sec61 knock-down results in block of intoxication, but does not prevent BonT from reaching the lumen of the ER (Figure 6G,H). Thus, Sec61 is “is instrumental to the translocation of BoNT/A LC into the neuronal cytosol at the soma.”
Minor comments:
(1) Fig. 3E: in the legend I think one of the NT3+ should be NT3-.
Yes, thanks for spotting it
(2) Would you consider adding Figure S4 as a main figure?
Thanks for the suggestion
(3) Please, check that all microscopy image panels have scale bars.
Done
(4) Figure 6B (bottom panes): why does it seem that there is a lot of mNeonGreen positive signal in regions that are not positive for HA? Shouldn't complementation keep HA in the complemented protein.
Our assumption i sthat there is an excess of receptor protein (HA tag) over reconstituted protein (GFP protein) given the relatively low concentration of toxin being internalized and translocated Refs: (1) Pirazzini M, Azarnia Tehran D, Leka O, Zanetti G, Rossetto O, Montecucco C. On the translocation of botulinum and tetanus neurotoxins across the membrane of acidic intracellular compartments. Biochim Biophys Acta. 2016 Mar;1858(3):467–474. PMID: 26307528
(2) Pirazzini M, Rossetto O, Eleopra R, Montecucco C. Botulinum Neurotoxins: Biology, Pharmacology, and Toxicology. Pharmacol Rev. 2017 Apr;69(2):200–235. PMCID: PMC5394922
(3) Dong M, Masuyer G, Stenmark P. Botulinum and Tetanus Neurotoxins. Annu Rev Biochem. Annual Reviews; 2019 Jun 20;88(1):811–837.
(4) Rossetto O, Pirazzini M, Fabris F, Montecucco C. Botulinum Neurotoxins: Mechanism of Action. Handb Exp Pharmacol. 2021;263:35–47. PMCID: 6671090
(5) Williams JM, Tsai B. Intracellular trafficking of bacterial toxins. Curr Opin Cell Biol. 2016 Aug;41:51–56. PMCID: PMC4983527
(6) Mesquita FS, van der Goot FG, Sergeeva OA. Mammalian membrane trafficking as seen through the lens of bacterial toxins. Cell Microbiol. 2020 Apr;22(4):e13167. PMCID: PMC7154709
(7) Hoch DH, Romero-Mira M, Ehrlich BE, Finkelstein A, DasGupta BR, Simpson LL. Channels formed by botulinum, tetanus, and diphtheria toxins in planar lipid bilayers: relevance to translocation of proteins across membranes. Proc Natl Acad Sci U S A. 1985 Mar;82(6):1692–1696. PMCID: PMC397338
(8) Donovan JJ, Middlebrook JL. Ion-conducting channels produced by botulinum toxin in planar lipid membranes. Biochemistry. 1986 May 20;25(10):2872–2876. PMID: 2424493
(9) Fischer A, Montal M. Single molecule detection of intermediates during botulinum neurotoxin translocation across membranes. Proc Natl Acad Sci U S A. 2007 Jun 19;104(25):10447–10452. PMCID: PMC1965533
(10) Fischer A, Nakai Y, Eubanks LM, Clancy CM, Tepp WH, Pellett S, Dickerson TJ, Johnson EA, Janda KD, Montal M. Bimodal modulation of the botulinum neurotoxin protein-conducting channel. Proc Natl Acad Sci U S A. 2009 Feb 3;106(5):1330–1335. PMCID: PMC2635780
(11) Fischer A, Montal M. Crucial role of the disulfide bridge between botulinum neurotoxin light and heavy chains in protease translocation across membranes. J Biol Chem. 2007Oct 5;282(40):29604–29611. PMID: 17666397
(12) Koriazova LK, Montal M. Translocation of botulinum neurotoxin light chain protease through the heavy chain channel. Nature structural biology. 2003. p. 13–18. PMID: 12459720
(13) Moreau D, Kumar P, Wang SC, Chaumet A, Chew SY, Chevalley H, Bard F.Genome-wide RNAi screens identify genes required for Ricin and PE intoxications. Dev Cell. 2011 Aug 16;21(2):231–244. PMID: 21782526
(14) Bassik MC, Kampmann M, Lebbink RJ, Wang S, Hein MY, Poser I, Weibezahn J, Horlbeck MA, Chen S, Mann M, Hyman AA, Leproust EM, McManus MT, Weissman JS. A systematic mammalian genetic interaction map reveals pathways underlying ricin susceptibility. Cell. 2013 Feb 14;152(4):909–922. PMCID: PMC3652613
(15) Tian S, Muneeruddin K, Choi MY, Tao L, Bhuiyan RH, Ohmi Y, Furukawa K, Furukawa K, Boland S, Shaffer SA, Adam RM, Dong M. Genome-wide CRISPR screens for Shiga toxins and ricin reveal Golgi proteins critical for glycosylation. PLoS Biol. 2018 Nov;16(11):e2006951. PMCID: PMC6258472
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BBC highly critical of Humane AI Pin, just like [[Humane AI Pin review not even close]] I noted earlier. Explicitly ties this to the expectations of [[rabbit — home]] too, which is a similar device. Issue here is I think similar to other devices like voice devices in your home. Not smart enough at the edge, too generic to be of use as [[small band AI personal assistant]] leading to using it for at most 2 or 3 very basic things (weather forecast, time, start playlist usually, and at home perhaps switching on a light), that don't justify the price tag .
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Author response:
The following is the authors’ response to the original reviews.
Reviewer #1:
I will summarize my comments and suggestions below.
(1) Abstract:
"Non-catalytic (pseudo)kinase signaling mechanisms have been described in metazoans, but information is scarce for plants." To the best of my understanding EFR is an active protein kinase in vitro and in vivo and cannot be considered a pseudokinase. Consider rephrasing.
We rephrased to: “Non-catalytic signaling mechanisms of protein kinase domains have been described in metazoans, but information is scarce for plants.”
(2) Page 4: It should be noted, that while membrane associated Rap-RiD systems have been used in planta to activate receptor kinase intracellular domains by promoting interaction with a co-receptor kinase domain, this system does not resemble the actual activation mechanism in the plasma membrane. This would be worth discussing when introducing the system. For example, the first substrates of the RK signaling complex may also be membrane associated and not freely diffuse in solution, which may be important for enzyme-substrate interaction.
We inserted on page 4: “The RiD system was previously applied in planta, maintaining membrane-association by N-terminal myristoylation (Kim et al., 2021). For the in vitro experiments, the myristoylation sites were excluded to facilitate the production of recombinant protein.”
(3) Page 4 and Fig 1: The catalytic Asp in BRI1 is D1027 and not D1009 (https://pubmed.ncbi.nlm.nih.gov/21289069/). Please check and prepare the correct mutant protein if needed.
We clarified this in the text by stating that we mutated the HRD-aspartate to asparagine in all our catalytic-dead mutants: “Kinase-dead variants with the catalytic residue (HRD-aspartate) replaced by asparagine (EFRD849N and BRI1D1009N), had distinct effects […]”. D1027 in BRI1 is the DFG-Asp, which was not mutated in our study.
(4) Page 4 and Fig 1: Is BIK1 a known component of the BR signaling pathway and a direct BRI1 substrate? Or in other words how specific is the trans-phosphorylation assay? In my opinion, a more suitable substrate for BRI1/BAK1 would be BSK1 or BSK3 (for example https://pubmed.ncbi.nlm.nih.gov/30615605/).
Kinase-dead BIK1 is a reported substrate of BRI1. We clarified this in the results section by inserting: “BIK1 was chosen as it is reported substrate of both, EFR/BAK1 and BRI1/BAK1 complexes (Lin et al., 2013).”
(5) Fig. 1B Why is BIK1 D202N partially phosphorylated in the absence of Rap? I would suggest to add control lanes showing BRI1, EFR, FLS2, BAK1 and BIK1 in isolation. Given that a nice in vitro activation system with purified components is available, why not compare the different enzyme kinetics rather than band intensities at only 1 enzyme : substrate ratio?
BIK1 D202N is partially phosphorylated due to the presence of active BAK1 that is capable of transphosphorylating BIK1 D202N as it has been reported in a previous study: (DOI: 10.1038/s41586-018-0471-x).
(6) Page 4 and Fig 1: Is the kinase dead variant of EFR indeed kinase dead? I could still see a decent autorad signal for this mutant when expressed in E. coli (Fig 1 A in Bender et al., 2021; https://pubmed.ncbi.nlm.nih.gov/34531323/)? If this mutant is not completely inactive, could this change the interpretation of the experiments performed with the mutant protein in vitro and in planta in the current manuscript? In my opinion, it could be possible that a partially active EFR mutant can be further activated by BAK1, and in turn can phosphorylate BIK1 D202N. The differences in autorad signal for BRI1D1009?N and EFRD849N is very small, and the entire mechanism hinges on this difference.
We would like to emphasize that the mechanism hinges on the difference between non-dimerized and dimerized kinase domains in the in vitro kinase assay. BRI1 D1009N fails to enhance BIK1 D202N trans-phosphorylation compared to the non-dimerized sample, while EFR D849N is still capable of enhancing BIK1 transphosphorylation upon dimerization as indicated by quantification of autorads (Figure 1B/C). We have also addressed this point in a section on the limitations of our study.
(7) Fig 1B. "Our findings therefore support the hypothesis that EFR increases BIK1 phosphorylation by allosterically activating the BAK1 kinase domain." To the best of my understanding presence of wild-type EFR in the EFR-BAK1 signaling complex leads to much better phosphorylation of BIK1D202N when compared to the EFRD849N mutant. How does that support the allosteric mechanism? By assuming that the D849N mutant is in an inactive conformation and fully catalytically inactive (see above)? Again, I think the data could also be interpreted in such a way that the small difference in autorad signal for BIK1 between BRI1 inactive (but see above) and ERF inactive are due to EFR not being completely kinase dead (see above), rather than EFR being an allosteric regulator. To clarify this point I would suggest to a) perform quantitative auto- and trans-(generic substrate) phosphorylation assays with wt and D849N EFR to derive enzyme kinetic parameters, to (2) include the EFRD849 mutant in the HDX analysis and (3) to generate transgenic lines for EFRD489N/F761H/Y836F // EFRD489N/F761H/SSAA and compare them to the existing lines in Fig. 3.
Mutations of proteins, especially those that require conformational plasticity for their function can have pleiotropic effects as the mutation may affect the conformational plasticity and consequently catalytic and non-catalytic functions that depend on the conformational plasticity. In such cases, it is difficult to fully untangle catalytic and non-catalytic functions. Coming back to EFR D849N, the D849N mutation may also impact the non-catalytic function by altering the conformational plasticity, explaining the difference observed in EFR vs EFR D849N. As you rightly suggested, HDX would be a way to address this but would still not clarify whether catalytic activity contributes to activation. We instead attempted to produce analog sensitive EFR variants for in vivo characterization of EFR-targeted catalytic inhibition. Unfortunately, we failed in producing an analog-sensitive variant for which we could show ATP-analog binding. To address your concern, we inserted a section on limitations of the study.
(8) Fig. 2B,C, supplement 3 C,D. Has it been assessed if the different EFR versions were expressed to similar protein levels and still localized to the PM?
Localization of the mutant receptors has not been explicitly evaluated by confocal microscopy. However, the selected mutation EFRF761H is shown to accumulate in stable Arabidopsis lines (Figure 3 – Supplement 1C) and BAK1 could be coIPed by all EFR variants upon elf18-treatment (Figure 3 B), indicating plasma membrane localization.
(9) How the active-like conformation of EFR is in turn activating BAK1 is poorly characterized, but appears to be the main step in the activation of the receptor complex. Extending the HDX analyses to resting and Rap-activated receptor complexes could be a first step to address this question. I tried to come up with an experimental plan to test if indeed the kinase activity of BAK1 and not of EFR is essential for signal propagation, but this is a complex issue. You would need to be able to mimic an activated form of EFR (which you can), to make sure its inactive (possibly, see above) and likewise to engineer a catalytically inactive form of BAK1 in an active-like state (difficult). As such a decisive experiment is difficult to implement, I would suggest to discuss different possible interpretations of the existing data and alternative scenarios in the discussion section of the manuscript.
We addressed your concern whether BAK1 kinase activity is essential for signaling propagation by pairing EFRF761H and BAK1D416N (Figure 4 Supplement 2 C) which fails to induce signaling. In this case, EFRF761H is in its activated conformation but cannot activate downstream signaling. We also attempted to address your concern by an in vitro kinase assay by pairing EFR and BAK1D416N and using a range of concentrations of the substrate BIK1D202N. We observed that catalytic activity of BAK1 but not EFR was essential for BIK1 phosphorylation. However, this experiment does not address whether activated EFR can efficiently propagate signaling in the absence of BAK1 catalytic activity. In the limitations of the study section, we now discuss the catalytic importance of EFR for signaling activation.
Author response image 1.
BIK1 trans-phosphorylation depends on BAK1 catalytic activity. Increasing concentrations of BIK1 D202N were used as substrate for Rap-induced dimers of EFR-BAK1, EFR D849N-BAK1, and EFR-BAK1 D416N respectively. BIK1 trans-phosphorylation depended on the catalytic activity of BAK1. Proteins were purified from E. coli λPP cells. Three experiments yielded similar results of which a representative is shown here.
Reviewer #2:
All of my suggestions are minor.
Figure 1B, I think it would be more useful to readers to explain the amino acid in the D-N change, rather than just call it D-to-N? Also, please label the bands on the stained gel; the shift on FKBP-BRI1 and FKBP-EFR are noticeable on the Coomassie stain.
We implemented your suggestions.
Figure 1-Supplement 1. There is still a signal in pS612 BAK1 (it states 'also failed to induce BAK1 S612 phosphorylation' in the text, which is not quite correct). Also, could mention the gel shift seen in BAK1, which appears absent in Y836F.
We corrected the text which now states: “To test whether the requirement for Y836 phosphorylation is similar, we immunoprecipitated EFR-GFP and EFRY836F-GFP from mock- or elf18-treated seedlings and probed co-immunoprecipitated BAK1 for S612 phosphorylation. EFRY836F also obstructed the induction of BAK1 S612 phosphorylation (Figure 1 – Supplement 1), indicating that EFRY836F and EFRSSAA impair receptor complex activation.” The gel shift of BAK1 you pointed out was not observed in replications and thus we prefer not to comment on it.
Figure 2 and 3 are full of a, b, c,d's, which I don't understand. Sorry
We used uppercase letters to indicate subpanels and lowercase letters to indicate the results of the statistical testing. In the figure caption, we have clarified that the lowercase letters refer to statistical comparisons.
Figure 2 A. If each point on the x-axis is one amino acid, I think it would again be useful to name the amino acids that the gold or purple or blue colored lines extend through.
Each point stands for a peptide which are sorted by position of their starting amino acid from N-terminus to C-terminus. We now added plots of HDX for individual peptides that correspond to the highlighted region in subpanel A.
Figure Supplement 1 is very small for what it is trying to show, even on the printed page. If this residue were to be phosphorylated, what would happen to the H-bond?
We suppose that VIa-Tyr phosphorylation would break the H-bond and causes displacement of the aC-b4 loop. Recent studies, published after our submission, highlight the importance of this loop for substrate coordination and ATP binding. Thus, phosphorylation of VIa-Tyr and displacing this loop may render the kinase rather unproductive. We have expanded the discussion to include this point.
Figure 2B: Tyr 836 is not present in any of the alignments in Figure 2A. This should be rectified, because the text talks about the similarity to Tyr 156 in PKA.
We have adjusted the alignments such that they now contain the VIa-Tyr residues of EFR and PKA.
Figure 4D. Is there any particular reason that these Blots are so hard to compare or FKBP and BAK1?
We assume it is referred to Figure 4 – Supplement 2 D. FKBP-EFR and FRB-BAK1 both are approximately the size of RubisCo, the most abundant protein in plant protein samples and which overlay the FKBP- and FRB-tagged kinase. Thus, it is difficult to detect these proteins.
Reviewer #3:
(1) The paper reporting the allosteric activation mechanism of EGFR should be cited.
Will be included.
(2)The authors showed that "Rap addition increased BIK1 D202N phosphorylation when the BRI1 or EFR kinase domains were dimerized with BAK1, but no such effect was observed with FLS2". Please explain why FLS2 failed to enhance BIK1 transphosphorylation by Rap treatment?
Even though BIK1 is a reported downstream signaling component of FLS2/BAK1, it might be not the most relevant downstream signaling component and rather related RLCKs, like PBL1, might be better substrates for dimerized FLS2/BAK1. We haven’t tested this, however. Alternatively, the purified FLS2 kinase domain might be labile and quickly unfolds even though it was kept on ice until the start of the assay, or the N-terminal FKBP-tag may disrupt function. As the reason for our observation is not clear, we have removed FLS2 in vitro dimerization experiments from the manuscript.
(3) Based solely on the data presented in Figure 1, it can be concluded that EFR's kinase activity is not required to facilitate BIK1 transphosphorylation. Therefore, the title of Figure 1, "EFR Allosterically Activates BAK1," may be inappropriate.
We have changed the figure title to: “EFR facilitates BIK1 trans-phosphorylation by BAK1 non-catalytically.”
(4) In Figure 1- Supplement 1, I could not find any bands in anti-GFP and anti-BAK1 pS612 of input. Please redo it.
Indeed, we could not detect protein in the input samples of this experiment. BAK1 S612 phosphorylation is an activation mark and not necessarily expected to be abundant enough for detection in input samples. EFR-GFP, however, is usually detected in input samples and is reported in Macho et al. 2014 from which manuscript these lines come. Why EFR-GFP is not detected in this set of experiments is unclear but, in our opinion, does not detract from the conclusions drawn since similar amounts of EFR-GFP are pulled-down across all samples.
(5) For Figure 2A, please mark the structure represented by each color directly in the figure.
We have made the suggested change.
(6) Please modify "EFRF761/Y836F and EFRF761H/SSAA restore BIK1 trans-phosphorylation" to "EFRF761H/Y836F and EFRF761H/SSAA restore BIK1 trans-phosphorylation".
Thank you for spotting this. We changed it.
(7) The HDX-MS analysis demonstrated that the EFR (Y836F) mutation inhibits the formation of the active-like conformation. Conversely, the EFR (F761H) mutation serves as a potent intragenic suppressor, significantly stabilizing the active-like conformation. Confirming through HDX-MS conformational testing that the EFR (Y836F F761H) double mutation does not hinder the formation of the active-like EFR kinase conformation would greatly strengthen the conclusions of the article.
Response: We agree that this is beneficial, and we attempted to do it but failed to produce enough protein for HDX-MS analysis. We stated this now in an extra section of the paper (“Limitations of the study”).
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www.makeuseof.com www.makeuseof.com
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How to RDP From Windows to Linux
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social-media-ethics-automation.github.io social-media-ethics-automation.github.io
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How do you think attribution should work when copying and reusing content on social media (like if you post a meme or gif on social media)? When is it ok to not cite sources for content? When should sources be cited, and how should they be cited?
I believe attribution is a must for any usage of any content that is created by other people because without crediting those creators, it will demotivate those people when the person using their work gains more views or money. When the sources need to be cited, it should be as simple as tagging (putting the creator tag) on the post.
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www.theguardian.com www.theguardian.com
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Der Bericht des Copernikus Climate Change Service über 2023 ist lact Direktor Carlo Buontempo "ein dramatisches Zeugnis dafür, wie weit weil wir uns von dem Klima entfernt haben, in dem sich die menschliche Zivilisation entwickelt hat". Viele Kimaforschende waren davon überrascht, wie deutlich die Temperaturrekorde des Jahres 2023 über denen der vorangegangenen Jahre lagen.Auch Zahl und Ausmaß von Extremwetterereignissen übertrafen die Erwartungen. https://www.theguardian.com/environment/2024/jan/09/2023-record-world-hottest-climate-fossil-fuel
Mehr zu den Copernicus-Daten für 2023: https://hypothes.is/search?q=tag%3A%22Global%20Climate%20Highlights%202023%22
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www.derstandard.de www.derstandard.de
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Das Europäische Klima-Bebachtungsprogramm Copernicus hat die wichtigsten Daten zum Jahr 2023 zusammengefasst. Im heissesten Jahr seit Beginn der Aufzeichnungen war es im Durchschnitt 1,48° wärmer als in der vorindustriellen Zeit. Jeder einzelne Tag war mindestens 1° wärmer. Eine Vielzahl von Extremwetterereignissen sind auf die Rekordtemperaturen zurückzuführen. https://www.derstandard.at/story/3000000202321/2023-war-es-waermer-als-in-den-vergangenen-100000-jahren
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www.biorxiv.org www.biorxiv.org
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Author response:
The following is the authors’ response to the original reviews.
Reviewer #1 (Recommendations For The Authors):
Specific comments to improve the quality of the work:
(1) The choice of subunits to tag are really not ideal. In the available structures of the human proteasome, The C-terminus of Rpn3/PSMD3 points directly toward the ATPase pore and is likely to disrupt the structure and/or dynamics of the proteasome during proteolysis (see comments regarding controls for functionality below). Similarly, the C-terminal tail of Rpt1/PSMC2 has a key role in the opening of the 20S core particle gate for substrate translocation and processing (see 2018 Nature Communications, 9:1360 and 2018 Cell Reports 24:1301-1315), and Alpha3/PSMA4 can be substituted by a second copy of Alpha4/PSMA7 in some conditions (although tagging Alpha3/PSMA4 would admittedly provide a picture of the canonical proteasome interactome while actively excluding the interactome of the non-canonical proteasomes that form via replacement of Alpha3/PSMA4). Comparison of these cell lines with lines harboring tags on subunits that are commonly used for tagging in the field because of a lack of impacts, such as the N-terminus of Rpn1/PSMD2, the C-terminus of Rpn11/PSMD14, and the C-terminus of Beta4/PSMB2 would help instill confidence that the interactome reported largely arises from mature, functional proteasomes rather than subcomplexes, defective proteasomes, or other species that may occur due to tagging at these positions.
We thank the reviewer for pointing this out. The original purpose of our strategy was to establish proximity labeling of proteasomes to enable applications both in cell culture and in vivo. The choice of PSMA4 and PSMC2 was dictated by previous successful tagging with GFP in mammalian cells (Salomons et al., Exp Cell Res 2010)(Bingol and Schuman, Nature 2006). However, the choice of C-terminal PSMC2 might have been not optimal. HEK293 cells overexpressing PSMC2-BirA show slower growth and the BioID data retrieve higher enrichment of assembly factors suggesting slower assembly of this fusion protein in proteasome. Although we did not observe a negative impact on overall proteasome activity and PSMC2-BirA was (at least in part) incorporated into fully assembled proteasomes as indicated by enrichment of 20S proteins.We apologize for not making it clear that we labeled the N-terminus of PSMD3/Rpn3 and not the C-terminus (Figure 1a and S1a). Therefore, we included in Figure S1a of the revised manuscript structures of the proteasome where the tagged subunit termini are highlighted: C-terminus for PSMA4 and PSMC2 and N-terminus for PSMD3. Additionally, we would like to point out that, differently from PSMC2-BirA, cells expressing BirA-PSMD3 did not show slower growth, and BioID data showed a more homogenous enrichment of both 19S and 20S proteins, as compared to PSMC2-BirA (Figure 1D and 1E). However, the overall level of enrichment of proteasome subunits was not comparable to PSMA4-BirA and, therefore, we opted for focusing the rest of the manuscript on this construct.
In support of this point, the data provided in Figure 1E in which the change in the abundances of each proteasome subunit in the tagged line vs. the BirA control line demonstrates substantial enrichment of the subcomplexes of the proteasome that are tagged in each case; this effect may represent the known feedback-mediated upregulation of new proteasome subunit synthesis that occurs when proteasomal proteolysis is impaired, or alternatively, the accumulation of subcomplexes containing the tagged subunit that cannot readily incorporate into mature proteasomes. Acknowledging this limitation in the text would be valuable to readers who are less familiar with the proteasome.
We would like to clarify that the data shown in Figure 1E do not represent whole proteome data, but rather log2 fold changes vs. BirA* control calculated on streptavidin enrichment samples. The differences in the enrichment of the various subcomplexes between cell lines derives from the fact that the effect size of the enrichment depends on both protein abundance in the isolated complexes, but also on the efficiency of biotinylation. The latter will be higher for proteins located in closer proximity to the bait. A similar observation was pointed out in a recent publication (PMID:36410438) that compared BioID and Co-IP for the same bait. When a component of the nuclear pore complex (Nup158) was analyzed by BioID only the more proximal proteins were enriched as compared to the whole complex in Co-IP data (Author response image 1):
Author response image 1.
Proteins identified in the NUP158 BioID or pulldown experiments are filled in red or light red for significance intervals A or B, respectively. The bait protein NUP158 is filled in yellow. Proteins enriched in the pulldown falling outside the SigA/B cutoff are filled in gray. NPC, nuclear pore complex. SigA, significant class A; SigB, significant class B. Reproduced from Figure 6 of PMID: 36410438.
However, we would like to point out that despite quantitative differences between different proteasome subunits, both 19S and 20S proteins were found to be strongly enriched (typically >2 fold) in all the constructs compared to BirA* control line (Figure 1E). This indicates that at least a fraction of all the tagged subunits are incorporated into fully assembled proteasomes.
Regarding the upregulation of proteasome subunits as a consequence of proteasome dysfunction, we did not find evidence of this, at least in the case of PSMA4. The immunoblot shown in Figure 2A and its quantification in S3A indicate no increased abundance of endogenous PSMA4 upon tetracycline induction of PSMA4-BirA*.
(2) The use of myc as a substrate of the proteasome for demonstration that proteolysis is unaffected is perhaps not ideal. Myc is known to be degraded via both ubiquitin-dependent and ubiquitin-independent mechanisms, such that disruption of one means of degradation (e.g., ubiquitin-dependent degradation) via a given tag could potentially be compensated by another. A good example of this is that the C-terminal tagging of PSMC2/Rpt1 is likely to disrupt interaction between the core particle and the regulatory particle (as suggested in Fig. 1D); this may free up the core particle for ubiquitin-independent degradation of myc.
Aside from using specific reporters for ubiquitin-dependent vs. independent degradation or a larger panel of known substrates, analysis of the abundance of K48-ubiquitinated proteins in the control vs. tag lines would provide additional evidence as to whether or not proteolysis is generally perturbed in the tag lines.
We thank the reviewer for this suggestion. We have included an immunoblot analysis showing that the levels of K48 ubiquitylation (Figure S3d) are not affected by the expression of tagged PSMA4.
(3) On pg. 8 near the bottom, the authors accidentally refer to ARMC6 as ARMC1 in one instance.
We have corrected the mistake.
(4) On pg. 10, the authors explain that they analyzed the interactome for all major mouse organs except the brain; although they explain in the discussion section why the brain was excluded, including this explanation on pg. 10 here instead of in the discussion might be a better place to discuss this.
We moved the explanation from the discussion to the results part.
Reviewer #2 (Recommendations For The Authors):
(1) Perhaps the authors can quantify the fraction of unassembled PSMA4-BirA* from the SEC experiment (Fig. 2b) to give the readers a feeling for how large a problem this could be.
The percentages based on Area Under the Curve calculations have been added to Figure S3b.
(2) Do the authors observe any difference in the enrichment scores between proteins that are known to interact with the proteasome vs proteins that the authors can justify as "interactors of interactors" vs the completely new potential interactors? This could be an interesting way to show that the potential new interactors are not simply because of poor false positive rate calibration, but that they behave in the same way as the other populations.
We thank the reviewer for this suggestion. We analyzed the enrichment scores for 20S proteasome subunits, known PIPs, first neighbors and the remaining enriched proteins. The remaining proteins (potential new interactors) have very similar scores as the first neighbors of known interactors. This plot has been added to Figure S3g.
(3) Did the authors try to train a logistic model for the miniTurbo experiments, like it was done for the BirA* experiments? Perhaps combining the results of both experiments would yield higher confidence on the proteasome interactors.
Following the reviewers suggestion, we applied the classifier on the dataset of the comparison between miniTurbo and PSMA-miniTurbo. We found a clear separation between the FPR and the TPR with 136 protein groups enriched in PSMA-miniTurbo. We have added the classifier and corresponding ROC curve to Figure S4f and S4g.
75 protein groups were found to be enriched for both PSMA4-BirA* and PSMA4-miniTurbo (Author response image 2), including the proteasome core particles, regulatory particles, known interactors and potential new interactors. As we focused more on the identification of substrates with PSMA4-miniTurbo, we did not pursue these overlapping protein groups further, but rather used the comparison to the mouse model to identify potential new interactors.
Author response image 2.
Overlap between ProteasomeID enriched proteins (fpr<0.05) between PSMA4-BirA* and PSMA4-miniTurbo.
(4) Perhaps this is already known, but did the authors check if MG132 affect proteasome assembly? The authors could for example repeat their SEC experiments in the presence of MG132.
We thank the reviewer for the suggestion, however to our knowledge there are no reports that MG132 has an effect on the assembly of the proteasome. MG132 is one of the most used proteasome inhibitors in basic research and as such has been extensively characterized in the last 3 decades. The small peptide aldehyde acts as a substrate analogue and binds directly to the active site of the protease PSMB5/β5. We therefore think it is unlikely that MG132 is interfering with the assembly of the proteasome.
(5) Minor comment: at the bottom of page 8, the authors probably mean ARMC6 and not ARMC1.
We have corrected the mistake.
(6) It would be interesting to expand the analysis of the already acquired in vivo data to try to identify tissue-specific proteasome interactors. Can the authors draw a four-way Venn diagram with the interactors of each tissue?
We thank the reviewer for this suggestion. We have generated an UpSet plot showing the overlap of ProteasomeID enriched proteins in the four tissues that gave us meaningful results (Author response image 3). In order to investigate whether the observed differences in ProteasomeID enriched proteins could be meaningful in terms of proteasome biology, we have highlighted proteins belonging to the UPS that show tissue specific enrichments. We found proteasome activators such as PSME1/PA28alpha and PSME2/PA28beta to enrich preferentially in kidney and liver, respectively, as well as multiple deubiquitinases to enrich preferentially in the heart. These differences might be related to the specific cellular composition of the different tissues, e.g., number of immune cells present, or the tissue-specific interaction of proteasomes with enzymes involved in the ubiquitin cycle. Given the rather preliminary nature of these findings, we have opted for not including this figure in the main manuscript, but rather include it only in this rebuttal letter.
Author response image 3.
Upset plot showing overlap between ProteasomeID enriched proteins in different mouse organs.
Reviewer #3 (Recommendations For The Authors):
(1) In the first paragraph of the Introduction, the authors link cellular senescence caused by partial proteasome inhibition with the efficacy of proteasome inhibitors in cancer therapy. Although this is an interesting hypothesis, I am not aware of any direct evidence for this; rather, I believe the efficacy of bortezomib/carfilzomib in haematological malignancies is most commonly attributed to these cells having adapted to high levels of proteotoxic stress (e.g., chronic unfolded protein response activation). I would suggest rephrasing this sentence.
We thank the reviewer for the comment and have amended the introduction.
(2) For the initial validation experiments (e.g., Fig. 1B), have the authors checked what level of Streptavidin signal is obtained with "+ bio, - tet" ? Although I accept that the induction of PSMA4-BirA* upon doxycycline addition is clear from the anti-Flag blots, it would still be informative to ascertain what level of background labelling is obtained without induction (but in the presence of exogenous biotin).
We tested four different conditions +/- tet and +/- biotin (24h) in PSMA4-BirA* cell lines (Author response image 4). As expected, biotinylation was most pronounced when tet and biotin were added. When biotin was omitted, streptavidin signal was the lowest regardless of the addition of tet. Compared to the -biotin conditions, a slight increase of streptavidin signal could be observed when biotin was added but tet was not added. This could be either due to the promoter leaking (PMID: 12869186) or traces of tetracycline in the FBS we used, as we did not specifically use tet-free FBS for our experiments.
Author response image 4.
Streptavidin-HRP immunoblot following induction of BirA fusion proteins with tetracycline (+tet) and supplementation of biotin (+bio). For the sample used as expression control tetracycline was omitted (-tet). To test background biotinylation, biotin supplementation was omitted (-bio). Immunoblot against BirA and PSMA was used to verify induction of fusion proteins, while GAPDH was used as loading control.
(3) For the proteasome structure models in Fig. 1D, a scale bar would be useful to inform the reader of the expected 10 nm labelling radius (as the authors have done later, in Fig. 2D).
We have added 10 nm scale bars to Figure 1d.
(4) In the "Identification of proteasome substrates by ProteasomeID" Results subsection, I believe there is a typo where the authors refer to ARMC1 instead of ARMC6.
We have corrected the mistake.
(5) I think Fig. S5 was one of the most compelling in the manuscript. Given the interest in confirming on-target efficacy of targeted degradation modalities, as well as identifying potential off-target effects early-on in development, I would consider promoting this out of the supplement.
We thank the reviewer for the comment and share the excitement about using ProteasomeID for targeted degradation screening. We have moved the data on PROTACs (Figure S5) into a new main Figure 5.
In addition, in relation to the comment of this reviewer regarding the detection of endogenous substrates, we have now included validation for one more hit emerging from our analysis (TIGD5) and included the results in Figure 4f, 4g and S4j.
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Reviewer #3 (Public Review):
Summary:
Bartolome et al. present ProteasomeID, a novel method to identify components, interactors, and (potentially) substrates of the proteasome in cell lines and mouse models. As a major protein degradation machine that is highly conserved across eukaryotes, the proteasome has historically been assumed to be relatively homogeneous across biological scales (with few notable exceptions, e.g., immunoproteasomes and thymoproteasomes). However, a growing body of evidence suggests that there is some degree of heterogeneity in the composition of proteasomes across cell tissues, and can be highly dynamic in response to physiologic and pathologic stimuli. This work provides a methodological framework for investigating such sources of variation. The authors start by adapting the increasingly popular biotin ligation strategy for labelling proteins coming into close proximity with one of three different subunits of the proteasome, before proceeding with PSMA4 for further development and analysis based on their preliminary labelling data. In a series of well-constructed and convincing validation experiments, the authors go on to show that the tagged PSMA4 construct can be incorporated into functional proteasomes, and is able to label a broad set of known proteasome components and interacting proteins in HEK293T cells. They also attempt to identify novel proteasomal degradation substrates with ProteasomeID; while this was convincing for known substrates with particularly short half-lives, the results for substrates with longer half-lives were less clear. One of the most compelling results was from a similar experiment to confirm proteasomal degradation induced by a BRD-targeting PROTAC, which I think is likely to be of keen interest to the targeted degradation community. Finally, the authors establish a ProteasomeID mouse model, and demonstrate its utility across several tissues.
Strengths:
(1) ProteasomeID itself is an important step forward for researchers with an interest in protein turnover across biological scales (e.g., in sub-cellular compartments, in cells, in tissues, and whole organisms). I especially see interest from two communities: those studying fundamental proteostasis in physiological and pathologic processes (e.g., ageing; tissue-specific protein aggregation diseases), and those developing targeted protein degradation modalities (e.g., PROTACs; molecular glues). All the datasets generated and deposited here are likely to provide a rich resource to both. The HEK293T cell line data are a valuable proof-of-concept to allow expansion into more biologically-relevant cell culture settings; however, I envision the greatest innovation here to be the mouse model. For example, in the targeted protein degradation space, two major hurdles in early-stage pre-clinical development are (i) evaluation of degradation efficacy across disease-relevant tissues, and (ii) toxicity and safety implications caused by off-target degradation, e.g., of newly-identified molecular glues and/or in particularly-sensitive tissues. The ProteasomeID mouse allows early in vivo assessment of both these questions. The results of the BRD PROTAC experiment in 293T cells provides an excellent in vitro proof-of-concept for this approach.
(2) The mass-spectrometry-based proteomics workflows used and presented throughout the manuscript are robust, rigorous, and convincing. For example, the algorithm the authors use for defining enrichment score cut-offs are logical and based on rational models, rather than on arbitrary cut-offs that are common for similar proteomics studies. The construction (and subsequent validation) of both BirA*- and miniTurbo- tagged PSMA4 variants also increases the utility of the method, allowing researchers to choose the variant with the labelling time-scale required for their particular research question.
(3) The optimised BioID and TurboID protocol the authors develop (summarised in Fig. S2A) and validate (Fig. S2B-D) is likely to be of broad interest to cell and molecular biologists beyond the protein degradation field, given that proximity labelling is a current gold-standard in global protein:protein interaction profiling.
Limitations:
I think the authors do an excellent job in highlighting the limitations of ProteasomeID throughout the Results and Discussion. I do have some specific comments that might provide additional context for the reader.
(1) The authors do a good job in showing that a substantial proportion of PSMA4-BirA* is incorporated into functional proteasome particles; however, it is not immediately clear to me how much background (false-positive IDs) might be contributed by the ~40 % of PSMA4-BirA* that is not incorporated into the mature core particle (based on the BirA* SEC-MS traces in Fig. 2b and S3b, i.e., the large peak ~ fraction 20). Are there any bands lower down in the native gel shown in Fig. 2c, i.e., corresponding to lower molecular weight complexes or monomeric PSMA4-BirA*? The enrichment of proteasome assembly factors in all the ProteasomeID experiments might suggest the presence of assembly intermediates, which might themselves become substrates for proteasomal degradation (as has been shown for other incompletely-assembled protein complexes, e.g., the ribosome, TRiC/CCT).
(2) Although the authors attempt to show that BirA* tagging of PSMA4 does not interfere with proteasome activity (Fig. 2e-f), I think the experimental evidence for this is incomplete. They show that the overall chymotrypsin-like activity (attributable to PSMB5) in cells expressing PSMA4-BirA* is not markedly reduced compared with control BirA*-expressing cells. However, they do not show that the activity of the specific proteasome sub-population that contains PSMA4-BirA* is unaffected (e.g., by purifying this sub-population via the Flag tag). The proteasome activity of the sub-population of wild-type proteasome complexes that do not contain the PSMA4-BirA* (~50%, based on the earlier immunoblots) could account for the entire chymotrypsin-like activity-especially in the context of HEK293T cells, where steady-state proteasome levels are unlikely to be limiting. It would also be useful to assess any changes in tryspin- and caspase- like activities, especially as tagging of PSMA4 could conceivably interfere with the activity of some PSMB subunits, but not others.
(3) I was left slightly unsure as to the general utility of ProteasomeID for identifying novel proteasomal substrates in homeostatic conditions--especially for proteins with longer half-lives. The cycloheximide chases in Fig. 4g/S4j are clear for MYC and TIGD5 (which have short half-lives), but are not so clear for ARMC6 and BRAT1: the reduction in the bands are modest, and might have been clearer with longer "chase" time-points. Furthermore, classifying candidates based on enrichment following proteasome inhibition with MG-132 have the potential to lead to a high number of false positives. ProteasomeID's utility in identifying potential substrates in more targeted settings (e.g., molecular glues, off-target PROTAC substrates) is far more apparent.
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Author response:
The following is the authors’ response to the original reviews.
Reviewer #1 (Public Review):
In this study, the authors examined the role of IBTK, a substrate-binding adaptor of the CRL3 ubiquitin ligase complex, in modulating the activity of the eiF4F translation initiation complex. They find that IBTK mediates the non-degradative ubiquitination of eiF4A1, promotes cap-dependent translational initiation, nascent protein synthesis, oncogene expression, and tumor cell growth. Correspondingly, phosphorylation of IBTK by mTORC1/ S6K1 increases eIF4A1 ubiquitination and sustains oncogenic translation.
Strengths:
This study utilizes multiple biochemical, proteomic, functional, and cell biology assays to substantiate their results. Importantly, the work nominates IBTK as a unique substrate of mTORC1, and further validates eiF4A1 (a crucial subunit of the ei44F complex) as a promising therapeutic target in cancer. Since IBTK interacts broadly with multiple members of the translational initial complex - it will be interesting to examine its role in eiF2alpha-mediated ER stress as well as eiF3-mediated translation. Additionally, since IBTK exerts pro-survival effects in multiple cell types, it will be of relevance to characterize the role of IBTK in mediating increased mTORC1 mediated translation in other tumor types, thus potentially impacting their treatment with eiF4F inhibitors.
Limitations/Weaknesses:
The findings are mostly well supported by data, but some areas need clarification and could potentially be enhanced with further experiments:
(1) Since eiF4A1 appears to function downstream of IBTK1, can the effects of IBTK1 KO/KD in reducing puromycin incorporation (in Fig 3A), cap-dependent luciferase reporter activity (Fig 3G), reduced oncogene expression (Fig 4A) or 2D growth/ invasion assays (Fig 4) be overcome or bypassed by overexpressing eiF4A1? These could potentially be tested in future studies.
We appreciate the reviewer for bringing up this crucial point. As per the reviewer's suggestion, we conducted experiments where we overexpressed Myc-eIF4A1 in IBTK-KO SiHa cells. Our findings indicate that increasing levels of eIF4A1 through ectopic overexpression is unable to reverse the decrease in puromycin incorporation (Fig. S3C) and protein expression of eIF4A1 targets caused by IBTK ablation (Fig. S4E). These results clearly demonstrate that IBTK ablation-induced eIF4A1 dysfunctions cannot be rescued by simply elevating eIF4A1 protein levels. Given the above results are negative, the impacts of eIF4A1 overexpression on the 2D growth/invasion capacities of IBTK-KO cells were not further examined. We sincerely appreciate the reviewer's understanding regarding this matter.
(2) The decrease in nascent protein synthesis in puromycin incorporation assays in Figure 3A suggest that the effects of IBTK KO are comparable to and additive with silvesterol. It would be of interest to examine whether silvesterol decreases nascent protein synthesis or increases stress granules in the IBTK KO cells stably expressing IBTK as well.
We appreciate the reviewer for bringing up this crucial point. We have showed that silvestrol treatment still decreased nascent protein synthesis in IBTK-KO cells overexpressing FLAG-IBTK as well (Fig. S3B).
(3) The data presented in Figure 5 regarding the role of mTORC1 in IBTK- mediated eiF4A1 ubiquitination needs further clarification on several points:
- It is not clear if the experiments in Figure 5F with Phos-tag gels are using the FLAG-IBTK deletion mutant or the peptide containing the mTOR sites as it is mentioned on line 517, page 19 "To do so, we generated an IBTK deletion mutant (900-1150 aa) spanning the potential mTORC1-regulated phosphorylation sites" This needs further clarification.
We appreciate the reviewer for bringing up this crucial point. The IBTK deletion mutant used in Fig. 5F is FLAG-IBTK900-1150aa. We have annotated it with smaller font size in the panel (red box) in Author response image 1.
Author response image 1.
- It may be of benefit to repeat the Phos tag experiments with full-length FLAG- IBTK and/or endogenous IBTK with molecular weight markers indicating the size of migrated bands.
We appreciate the reviewer for bringing up this crucial point. We attempted to perform Phos-tag assays to detect the overexpressed full-length FLAG-IBTK or endogenous IBTK. However, we encountered difficulties in successfully transferring the full-length FLAG-IBTK or endogenous IBTK onto the nitrocellulose membrane during Phos-tag WB analysis. This is likely due to the limitations of this technique. Based on our experience, phos-tag gel is less efficient in detecting protein motility shifts with large molecular weights. As the molecular weight of IBTK protein is approximately 160 kDa, it falls within this category. Considering these technical constraints, we did not include Phos-tag assay results for full-length IBTK in our study. We sincerely appreciate the reviewer's understanding regarding this matter.
The binding of Phos-tag to phosphorylated proteins induces a mobility shift during gel electrophoresis or protein separation techniques. This shift allows for the visualization and quantification of phosphorylated proteins separately from non-phosphorylated proteins. It's important to note that these mobility shifts indicate phosphorylation status, rather than actual molecular weights. pre- stained protein markers are typically used as a reference to assess the efficiency of protein transfer onto the membrane [Ref: 1]. Considering the aforementioned reasons, we did not add molecular weights to the WB images.
Reference [1]. FUJIFILM Wako Pure Chemical Corporation, https://www.wako- chemicals.de/media/pdf/c7/5e/20/FUJIFILM-Wako_Phos-tag-R.pdf
- Additionally, torin or Lambda phosphatase treatment may be used to confirm the specificity of the band in separate experiments.
We appreciate the reviewer for bringing up this crucial point. Torin1 is a synthetic mTOR inhibitor by preventing the binding of ATP to mTOR, leading to the inactivation of both mTORC1 and mTORC2, whereas rapamycin primarily targets mTORC1 activity and may inhibit mTORC2 in certain cell types after a prolonged treatment. We have identified that the predominant mediator of IBTK phosphorylation is the mTORC1/S6K1 complex. Therefore, in this context, we think that rapamycin is sufficient to inactivate the mTORC1/S6K1 pathway. As shown in Fig. 5F, the phosphorylated IBTK900-1150aa was markedly decreased while the non-phosphorylated form was simultaneously increased in rapamycin- treated cells. As per the reviewer's suggestion, we treated FLAG-IBTK900-1150aa overexpressed cells with lambda phosphatase. As shown in Fig. 5G, lambda phosphatase treatment completely abolished the mobility shifts of phosphorylated FLAG-IBTK900-1150aa. Additionally, the lowest band displayed an abundant accumulation of the non-phosphorylated form of FLAG-IBTK900-1150aa. These findings confirm that the mobility shifts observed in WB analysis correspond to the phosphorylated forms of FLAG-IBTK900-1150aa.
- Phos-tag gels with the IBTK CRISPR KO line would also help confirm that the non-phosphorylated band is indeed IBTK.
We appreciate the reviewer for bringing up this crucial point. As we state above, we performed Phos-tag assays to detect the mobility shifts of phosphorylated FLAG-IBTK900-1150aa. Anti-FLAG antibody, but not the anti-IBTK antibody was used for WB detection. This antibody does not exhibit cross-reactivity with endogenous IBTK.
- It is unclear why the lower, phosphorylated bands seem to be increasing (rather than decreasing) with AA starvation/ Rapa in Fig 5H.
We appreciate the reviewer for bringing up this crucial point. We think the panel the reviewer mentioned is Fig. 5F. According to the principle of Phos-tag assays, proteins with higher phosphorylation levels have slower migration rates on SDS-PAGE, while proteins with lower phosphorylation levels have faster migration rates.
As shown in Author response image 2, the green box indicates the most phosphorylated forms of FLAG-IBTK900-1150aa, the red box indicates the moderately phosphorylated forms of FLAG-IBTK900-1150aa, and the yellow box indicates the non-phosphorylated forms of FLAG-IBTK900-1150aa. AA starvation or Rapamycin treatment reduced the hyperphosphorylated forms of FLAG-IBTK900-1150aa (green box), while simultaneously increasing the hypophosphorylated (red box) and non- phosphorylated (yellow box) forms of FLAG-IBTK900-1150aa. Thus, we conclude that AA starvation or Rapamycin treatment leads to a marked decrease in the phosphorylation levels of FLAG-IBTK900-1150aa.
Author response image 2.
Reviewer #2 (Public Review):
Summary:
This study by Sun et al. identifies a novel role for IBTK in promoting cancer protein translation, through regulation of the translational helicase eIF4A1. Using a multifaceted approach, the authors demonstrate that IBTK interacts with and ubiquitinates eIF4A1 in a non-degradative manner, enhancing its activation downstream of mTORC1/S6K1 signaling. This represents a significant advance in elucidating the complex layers of dysregulated translational control in cancer.
Strengths:
A major strength of this work is the convincing biochemical evidence for a direct regulatory relationship between IBTK and eIF4A1. The authors utilize affinity purification and proximity labeling methods to comprehensively map the IBTK interactome, identifying eIF4A1 as a top hit. Importantly, they validate this interaction and the specificity for eIF4A1 over other eIF4 isoforms by co- immunoprecipitation in multiple cell lines. Building on this, they demonstrate that IBTK catalyzes non-degradative ubiquitination of eIF4A1 both in cells and in vitro through the E3 ligase activity of the CRL3-IBTK complex. Mapping IBTK phosphorylation sites and showing mTORC1/S6K1-dependent regulation provides mechanistic insight. The reduction in global translation and eIF4A1- dependent oncoproteins upon IBTK loss, along with clinical data linking IBTK to poor prognosis, support the functional importance.
Weaknesses:
While these data compellingly establish IBTK as a binding partner and modifier of eIF4A1, a remaining weakness is the lack of direct measurements showing IBTK regulates eIF4A1 helicase activity and translation of target mRNAs. While the effects of IBTK knockout/overexpression on bulk protein synthesis are shown, the expression of multiple eIF4A1 target oncogenes remains unchanged.
Summary:
Overall, this study significantly advances our understanding of how aberrant mTORC1/S6K1 signaling promotes cancer pathogenic translation via IBTK and eIF4A1. The proteomic, biochemical, and phosphorylation mapping approaches established here provide a blueprint for interrogating IBTK function. These data should galvanize future efforts to target the mTORC1/S6K1-IBTK-eIF4A1 axis as an avenue for cancer therapy, particularly in combination with eIF4A inhibitors.
Reviewer #1 (Recommendations For The Authors):
(1) Certain references should be provided for clarity. For e.g.,: Page 15, line 418 " The C-terminal glycine glycine (GG) amino acid residues are essential for Ub conjugation to targeted proteins".
We appreciate the reviewer for bringing up this crucial point. We have taken two fundamental review papers (PMID: 22524316, 9759494) on the ubiquitin system as references in this sentence.
(2) Please describe the properties of the ΔBTB mutant on page 15 when first describing it. What motifs does it lack and has it been described before in functional studies?
We appreciate the reviewer for bringing up this crucial point. We added a sentence to describe the properties of the ΔBTB mutant. This mutant lacks the BTB1 and BTB2 domains (deletion of aa 554–871), which have been previously demonstrated to be essential for binding to CUL3. The original reference has been added to the revised manuscript.
(3) In Figure 2G how do the authors explain the fact that co-expression of the Ub K-ALLR mutant, which is unable to form polyubiquitin chains, formed only a moderate reduction in IBTK-mediated eIF4A1 ubiquitination?
We appreciate the reviewer for bringing up this crucial point. The Ub K-ALLR mutant can indeed conjugate to substrate proteins, but it cannot form chains due to its absence of lysine residues, resulting in mono-ubiquitination. Multi- mono-ubiquitination refers to the attachment of single ubiquitin molecules to multiple lysine residues on a substrate protein. It's worth noting that a poly- ubiquitinated protein and a multi-mono-ubiquitinated protein appear strikingly similar in Western blot. Our findings demonstrated that the co-expression of the Ub K-ALL-R mutant resulted in only a modest reduction in IBTK-mediated eIF4A1 ubiquitination (Fig. 2G), and that eIF4A1 was ubiquitinated at twelve lysine residues when co-expressed with IBTK (Fig. S2F). As such, we conclude that the CRL3IBTK complex primarily catalyzes multi-mono-ubiquitination on eIF4A1. .
(4) In Figure 5, The identity of the seven sites in the IBTK 7ST A mutants should be specified.
We appreciate the reviewer for bringing up this crucial point. We have specified the seven mutation sites in the IBTK-7ST A mutant (Fig. 6A).
(5) In Figure 5, the rationale for generating antibodies only to S990/992/993, as opposed to the other mTORC1/S6K motifs should be specified.
We appreciate the reviewer for bringing up this crucial point. Upon demonstrating that IBTK can be phosphorylated—with evidence from positive Phos-tag and in vitro phosphorylation assays—we sought to directly detect changes in the phosphorylation levels using an antibody specific to IBTK phosphorylation. However, the expense of generating seven phosphorylation- specific antibodies for each site is significant. Recognizing that S990/992/993 are three adjacent sites, we deemed it appropriate to generate a single antibody to recognize the phospho-S990/992/993 epitope. Moreover, out of the seven phosphorylation sites, S992 perfectly matches the consensus motif for S6K1 phosphorylation (RXRXXS). Utilizing this antibody allowed us to observe a substantial decrease in the phosphorylation levels of these three adjacent Ser residues in IBTK following either AA deprivation or Rapamycin treatment (Fig. 5L). We have specified these points in the manuscript.
Reviewer #2 (Recommendations For The Authors):
The following suggestions would strengthen the study:
(1) Directly examine the effects of IBTK modulation (knockdown/knockout/ overexpression) on eIF4A1 helicase activity.
We appreciate the reviewer for bringing up this crucial point. We agree with the reviewer's suggestion that evaluating IBTK's influence on eIF4A1 helicase activity directly would enhance the strength of our conclusion. However, the current eIF4A1 helicase assays, as described in previous publications [Ref: 1, 2], can only be conducted using in vitro purified recombinant proteins. For instance, it is feasible to assess the varying levels of helicase activity exhibited by recombinant wild-type or mutant EIF4A1 proteins [Ref: 2]. Importantly, there is currently no reported methodology for evaluating the helicase activity of EIF4A1 in vivo, as mentioned by the reviewer in gene knockdown, knockout, or overexpression cellular contexts. Therefore, we have not performed these assays and we sincerely appreciate the reviewer's understanding in this regard. We sincerely appreciate the reviewer's understanding regarding this matter.
Reference:
[1] Chu J, Galicia-Vázquez G, Cencic R, Mills JR, Katigbak A, Porco JA, Pelletier J. CRISPR-mediated drug-target validation reveals selective pharmacological inhibition of the RNA helicase, eIF4A. Cell reports. 2016 Jun 14;15(11):2340-7.
[2] Chu J, Galicia-Vázquez G, Cencic R, Mills JR, Katigbak A, Porco JA, Pelletier J. CRISPR-mediated drug-target validation reveals selective pharmacological inhibition of the RNA helicase, eIF4A. Cell reports. 2016 Jun 14;15(11):2340-7.
(2) Justify why the expression of some but not all eIF4A1 target oncogenes is affected in IBTK-depleted/overexpressing cells. This is important if IBTK should be considered as a therapeutic target. The authors should consider which of the eIF4A1 targets are most impacted by IBTK KO. This would provide a more focused therapeutic approach in the future.
We appreciate the reviewer for bringing up this crucial point. As the reviewer has pointed out, we assessed the protein levels of ten reported eIF4A1 target genes across three cancer cell lines (Fig.4, Fig. S4A, C). We observed that IBTK depletion led to a substantial reduction in the protein levels of most eIF4A1- regulated oncogenes upon IBTK depletion, although there were some exceptions. For instance, IBTK KO in H1299 cells exerted minimal influence on the protein levels of ROCK1 (Fig. S4A). Several possible explanations might account for this observation: firstly, given that our list of eIF4A1 target genes collected from previous studies conducted using distinct cell lines, it is not unexpected for different lines to exhibit subtle differences in regulation of eIF4A1 target genes. Secondly, as a CRL3 adaptor, IBTK potentially performs other biological functions via ubiquitination of specific substrates; dysregulation of these could buffer the impact of IBTK KO on the protein expression of some eIF4A1 target genes. We added these comments to the Discussion section of the revised manuscript.
(3) Expand mTOR manipulation experiments (inhibition, Raptor knockout, activation) and evaluate impacts on IBTK phosphorylation, eIF4A1 ubiquitination, and translation.
The mTORC1 signaling pathway is constitutively active under normal culture conditions. In order to inhibit mTORC1 activation, we employed several approaches including AA starvation, Rapamycin treatment, or Raptor knockout. Our results have demonstrated that both AA starvation and rapamycin treatment led to a reduction in eIF4A1 ubiquitination (Fig. 5M). Moreover, we have included new findings in the revised manuscript, which highlight that Raptor knockout specifically decreases eIF4A1 ubiquitination (Fig. 5N). It is worth mentioning that the impacts of mTOR inhibition or activation on protein translation have been extensively investigated and documented in numerous studies. Therefore, in our study, we did not feel it necessary to examine these treatments further.
(4) Although not absolutely necessary, it would be nice to see if some of these findings are true in other cancer cell types.
We appreciate the reviewer for bringing up this crucial point. We concur with the reviewer's suggestion that including data from other cancer cell types would enhance the strength of our conclusion. While the majority of our data is derived from two cervical cancer cell lines, we have corroborated certain key findings— such as the impact of IBTK on eIF4A1 and its target gene expression—in H1299 cells (human lung cancer) (Fig. 2C, Fig. S4A, B) and in CT26 cells (murine colon adenocarcinoma) (Fig. S4C, D). Additionally, we demonstrated that IBTK promotes IFN-γ-induced PD-L1 expression and tumor immune escape in both the H1299 and CT26 cells (Fig. S6A-K).
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Reviewer #1 (Public Review):
In this study, the authors examined the role of IBTK, a substrate-binding adaptor of the CRL3 ubiquitin ligase complex, in modulating the activity of the eiF4F translation initiation complex. They find that IBTK mediates the non-degradative ubiquitination of eiF4A1, promotes cap-dependent translational initiation, nascent protein synthesis, oncogene expression, and tumor cell growth. Correspondingly, phosphorylation of IBTK by mTORC1/ S6K1 increases eIF4A1 ubiquitination and sustains oncogenic translation.
Strengths:
This study utilizes multiple biochemical, proteomic, functional and cell biology assays to substantiate their results. Importantly, the work nominates IBTK as a unique substrate of mTORC1, and further validates eiF4A1 ( a crucial subunit of the ei44F complex) as a promising therapeutic target in cancer. Since IBTK interacts broadly with multiple members of the translational initial complex- it will be interesting to examine its role in eiF2alpha-mediated ER stress as well as eiF3-mediated translation. Additionally, since IBTK exerts pro-survival effects in multiple cell types, it will be of relevance to characterize the role of IBTK in mediating increased mTORC1 mediated translation in other tumor types, thus potentially impacting their treatment with eiF4F inhibitors.
Limitations/Weaknesses:
The findings are mostly well supported by data, but some areas need clarification and could potentially be enhanced with further experiments:
(1) Since eiF4A1 appears to function downstream of IBTK1, can the effects of IBTK1 KO/KD in reducing puromycin incorporation ( in Fig 3A), cap-dependent luciferase reporter activity (Fig 3G), reduced oncogene expression ( Fig 4A) or 2D growth/ invasion assays (Fig 4) be overcome or bypassed by overexpressing eiF4A1? These could potentially be tested in future studies. <br /> (2) The decrease in nascent protein synthesis in puromycin incorporation assays in Figure 3A suggests that the effects of IBTK KO are comparable to and additive with silvesterol. It would be of interest to examine whether silvesterol decreases nascent protein synthesis or increases stress granules in the IBTK KO cells stably expressing IBTK as well. <br /> (3) The data presented in Figure 5 regarding the role of mTORC1 in IBTK-mediated eiF4A1 ubiquitination needs further clarification on several points:<br /> - It is not clear if the experiments in Figure 5F with Phos-tag gels are using the FLAG-IBTK deletion mutant or the peptide containing the mTOR sites as it is mentioned on line 517, page 19 "To do so, we generated an IBTK deletion mutant (900-1150 aa) spanning the potential mTORC1-regulated phosphorylation sites" This needs further clarification.<br /> -It may be of benefit to repeat the Phos tag experiments with full length FLAG-IBTK and/or endogenous IBTK with molecular weight markers indicating size of migrated bands.<br /> -Additionally, torin or Lambda phosphatase treatment may be used to confirm the specificity of the band in separate experiments.<br /> -Phos-tag gels with the IBTK CRISPR KO line would also help confirm that the non-phosphorylated band is indeed IBTK. <br /> -It is unclear why the lower, phosphorylated bands seem to be increasing ( rather than decreasing) with AA starvation/ Rapa in Fig 5H.
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Reviewer #2 (Public Review):
Summary:
In this manuscript, Wang and co-workets employ single molecule light microscopy (SMLM) to detect Nipah virus Fusion protein (NiV-F) in the surface of cells. They corroborate that these glycoproteins form microclusters (previously seen and characterized together with the NiV-G and Nipah Matrix protein by Liu and co-workers (2018) also with super-resolution light microscopy). Also seen by Liu and coworkers the authors show that the level of expression of NiV-F does not alter the identity of these microclusters nor endosomal cleavage. Moreover, mutations and the transmembrane domain or the hexamer-of-trimer interface seem to have a mild effect on the size of the clusters that the authors quantified. Importantly, it has also been shown that these particles tend to cluster in Nipah VLPs.
Strengths:
The authors have tried to perform SMLM in single VLPs and have shown partially the importance of NiV-F clustering.
Weaknesses:
The labelling strategy for the NiV-F is not sufficiently explained. The use of a FLAG tag in the extracellular domain should be validated and compared with the unlabelled WT NiV-F when expressed in functional pseudoviruses (for example HIV-1 based particles decorated with NiV-F). This experiment should also be carried out for both infection and fusion (including BlaM-Vpr as a readout for fusion). I would also suggest to run a time-of-addition BlaM experiment to understand how this particular labelling strategy affects single virion fusion as compared to the the WT. It would also be very important to compare the FLAG labelling approach with recent advances in the field (for instance incorporating noncanonical amino acids (ncAAs) into NiV-F by amber stop-codon suppression, followed by click chemistry).
The correlation between the existence of microclusters of a particular size and their functionality is missing. Only cell-cell fusion assays are shown in supplementary figures and clearly, single virus entry and fusion cannot be compared with the biophysics of cell-cell fusion. Not only the environment is completely different, membrane curvature and the number of NiV-F drastically varies also. Therefore, specific fusion assays (either single virus tracking and/or time-of-addition BlaM kinetics with functional pseudoviruses) are needed to substantiate this claim.
The authors also claim they could not characterize the number of NiV-F particles per cluster. Another technique such as number and brightness (Digman et al., 2008) could support current SMLM data and identify the number of single molecules per cluster. Also, this technology does not require complex microscopy apparatus. I suggest they perform either confocal fluorescence fluctuation spectroscopy or TIRF-based nandb to validate the clusters and identify how many molecule are present in these clusters. Also, it is not clear how many cells the authors employ for their statistics (at least 30-50 cells should be employed and not consider the number of events blinking events). I hope the authors are not considering only a single cell to run their stats... The differences between the mutants and the NiV-F is minor even if their statistical analyses give a difference (they should average the number and size of the clusters per cell for a total of 30-50 cells with experiments performed at least in three different cells following the same protocol). They should also compare the level of expression (with the number of molecules per cell provided by number and brightness) with the total number of clusters. Overall, it seems that the authors have only evaluated a very low number of cells.
The same applies to the VLP assay. I assume the authors have only taken VLPs expressing both NiV-M and NiV-F (and NiV-G). But even if this is not clearly stated I would urge the authors to show how many viruses were compared per condition (normally I would expect 300 particles per condition coming from three independent experiments). As a negative control to evaluate the cluster effect I would mix the different conditions. Clearly you have clusters with all conditions and the differences in clustering depending on each condition are minimal. Therefore you need to increase the n for all experiments.
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Author response:
The following is the authors’ response to the current reviews.
We sincerely appreciate the reviewer’s dedication to evaluating our manuscript and raising essential considerations regarding the classification of the migration behavior we described. While the reviewer suggests that this behavior aligns with the concept of itinerancy, we contend that it represents a distinct phenomenon, albeit with similarities, as both involve the non-breeding movements of birds. We acknowledge that our manuscript did not adequately address this distinction and have considered the reviewer’s feedback. In our response, we clarify the difference between the described phenomenon and itinerancy. Our revised manuscript will include a new section in the Discussion to address this issue comprehensively.
In the first part of the review, the reviewer emphasizes that the pattern we are describing is consistent with itinerancy. Regardless of the terminology used, we want to highlight the existence of two different types of migratory behavior, both of which involve movement in non-breeding areas.
The first type, called itinerancy, was first described by Moreau in 1972 in “The Palaearctic-African Bird Migration Systems.” As noted by the reviewer, this behavior involves an alternation of stopovers and movements between different short-term non-breeding residency areas. They usually occur in response to food scarcity in one part of the non-breeding range, causing birds to move to another part of the same range. These movements typically cover distances of 10 to 100 kilometers but are neither continuous nor directional. Moreau (1972) defined itinerancy as prolonged stopovers, normally lasting several months, primarily in tropical regions. He noted observations of certain species disappearing from his study areas in sub-Saharan Africa in December and others appearing, suggesting they may have multiple home ranges during the non-breeding season. Subsequent research, as mentioned by the reviewer, has confirmed itinerancy in many species, particularly among Palaearctic-African migrants in sub-Saharan Africa. In particular, the Montagu’s Harrier has been extensively studied in this regard. The reviewer rightly points out that our study does not include recent findings on this species. In our revised version, we will include references to recent studies, such as those by Trierweiler et al. (2013, Journal of Animal Ecology, 82:107-120) and Schlaich et al. (2023, Ardea, 111:321-342), which show that Montagu’s Harrier has an average of 3-4 home ranges separated by approximately 200 kilometers. These studies suggest that the species spends approximately 1.5 months at each site, with the most extended period typically observed at the last site before migrating to the breeding grounds.
In the second type, birds undertake a post-breeding migration, arrive in their non-breeding range, and then gradually move in a particular direction throughout the season. This continuous directional movement covers considerable distances and continues throughout the non-breeding period. In our study, this movement covered about 1000 km, comparable to the total migration distance of Rough-legged Buzzards of about 1500 km. As observed in our research, these movements are influenced by external factors such as snow cover. In such cases, the progression of snow cover in a south-westerly direction during winter can prevent birds from finding food, forcing them to continue migrating in the same direction. In essence, this movement represents a prolonged phase of the migration process but at a slower pace. Similar behavior has been documented in buzzards, as reported by Strandberg et al. (2009, Ibis 151:200-206). Although several transmitters in their study stopped working in mid-winter, the authors observed a phenomenon they termed ‘prolonged autumn migration.’
In the second part of the review, the reviewer questions the need to distinguish between the two behaviors we have discussed. However, we believe these behaviors differ in their structure (with the first being intermittent and often non-directional, whereas the second is continuous and directional) and in their causes (with the first being driven by seasonal food resource cycles and the second by advancing snow cover). We therefore argue that it is worth distinguishing between them. To differentiate these forms of non-breeding movement, we propose to use ‘itinerancy’ for the first type, as described initially by Moreau in 1972, and introduce a separate term for the second behavior. Although ‘slow directional itinerancy’ could be considered, we find it too cumbersome.
Moreover, ‘itinerancy’ in the literature refers not only to non-breeding movements but also to the use of different nesting sites, e.g., Lislevand et al. (2020, Journal of Avian Biology: e02595), reinforcing its association with movements between multiple sites within habitats. We, therefore, propose that the second behavior be given a distinct name. We acknowledge the reviewer’s point that we did not adequately address this distinction in the Discussion and plan to include a separate section in our paper’s revised version. In the third part of his review, the reviewer suggests an alternative title. Another reviewer, Dr Theunis Piersma, suggested the current title during the first round of reviewing, and we have chosen his version.
In the fourth part of the review, the reviewer questions whether it is appropriate to discuss the conservation aspect of this study. This type of non-breeding movement raises concerns about accurately determining non-breeding ranges and population dynamics for species that exhibit this behavior. We believe that accurate determination of range and population dynamics is critical to conservation efforts. While this may be less important for species breeding in Europe and migrating to Africa, for which monitoring breeding territories is more feasible, it’s essential for Arctic and sub-Arctic breeding species. Large-scale surveys in these regions have historically been challenging and have become even more so with the end of Arctic cooperation following Russia’s war with Ukraine (Koivurova, Shibata, 2023). For North America and Europe, non-breeding abundance is typically estimated once per season in mid-winter. In North America, these are the so-called Christmas counts (which take place once at the end of December), and in Europe, they are the IWC counts mentioned by the reviewer (as follows from their official website - “The IWC requires a single count at each site, which should be repeated each year. The exact dates vary slightly from region to region, but take place in January or February”). Because of such a single count in mid-winter, non-breeding habitats occupied in autumn and spring will be listed as ‘uncommon’ at best, while south-western habitats where birds are only present in mid-winter will be listed as ‘common.’ However, the situation will be reversed if we consider the time birds spend in these habitats.
The reviewer also highlights the introduction’s unconventional structure and information redundancy at the beginning. We have chosen this structure and provided basic explanations to improve readability for a wider audience, given eLife’s readership. At the same time, we will certainly take the reviewers’ feedback into account in the revised version. We plan to include the references to modern itinerancy research mentioned above and to add a section on itinerancy to the Discussion.
We appreciate the reviewer’s input and sincerely thank them for their time and effort in reviewing our paper. While we may not fully agree on the classification of the behavior we describe, we value the opportunity to engage in discussion and believe that presenting arguments and counterarguments to the reader is beneficial to scientific progress.
The following is the authors’ response to the original reviews.
Reviewer #1 (Recommendations For The Authors):
I much enjoyed reading this manuscript, that is, once I understood what it is about. Titles like "Conserving bird populations in the Anthropocene: the significance of non-breeding movements" are a claim to so-called relevance, they have NOTHING to do with the content of the paper, so once I understood that this paper was about the "Quick quick slow: the foxtrot migration of rough-legged buzzards is a response to habitat and snow" (an alternative title), it was becoming very interesting. So the start of the abstract as well as the introduction is very tedious, as clearly much trouble is taken here to establish reputability. In my eyes this is unnecessary: eLife should be interested in publishing such a wonderful description of such a wonderful migrant in a study that comes to grips with limiting factors on a continental scale!
We sincerely appreciate your time and effort in reviewing our manuscript. Thank you for your appreciation of our study.
We agree that the focus of the article should be changed from conservation to migration patterns. We have rewritten the Introduction and Discussion as suggested. We have added the application of this pattern including conservation at the end of the Discussion by completely changing Figure 5. We have also changed the title to the suggested one.
Not sure that the first paragraph statements that seek to downplay what we know about wintering vs breeding areas are valid (although I see what purpose they serve). Migratory shorebirds have extensively been studied in the nonbreeding areas, for example, including movement aspects (see, as just one example, Verhoeven, M.A., Loonstra, A.H.J., McBride, A.D., Both, C., Senner, N.R. & Piersma, T. (2020) Migration route, stopping sites, and non breeding destinations of adult Black tailed Godwits breeding in southwest Fryslân, The Netherlands. Journal of Ornithology 162, 61-76) and there are very impressive studies on the winter biology of migrants across large scale (for example in Zwarts' Living on the Edge book on the Sahel wetlands). Think also about geese and swans and about seabirds!
We have rewritten the first paragraph and it now talks about patterns of migratory behavior. We have also rewritten the second paragraph, now it is devoted to studies of movements in the non-breeding period. We explain how our pattern differs from those already studied and give references to the papers you mentioned.
Directional movements in nonbreeding areas as a function of food (in this case locusts) have really beautifully been described by Almut Schlaich et al in JAnimEcol for Montagu's harriers.
We have added Montagu's harrier example in the second paragraph of the Introduction and the Discussion. We have added a reference to Schlaich and to Garcia and Arroyo, who suggested that Montagu's harriers have long directional migrations during the non-breeding period.
Once the paper starts talking buzzards, and the analyses of the wonderful data, all is fine. It is a very competent analysis with a description of a cool pattern.
Thank you for your appreciation of our study. We hope the revised version is better and clearer.
However, i would say that it is all a question of spatial scale. The buzzards here respond to changes in food availability, but there is not an animal that doesn't. The question is how far they have to move for an adequate response: in some birds movements of 100s of meters may be enough, and then anything to the scale of rough-legged buzzards.
In the new version of the manuscript, we emphasize that this is a large distance (about 1000 km), comparable to the distance of the fall and spring migrations (about 1400 km) in lines 70-72 of the Introduction and 379-383 of the Discussion.
And actually, several of the shorebirds I know best also do a foxtrot, such as red knots and bar-tailed godwits moulting in the Wadden Sea, then spending a few months in the UK estuaries, before returning to the Wadden Sea before the long migrations to Arctic breeding grounds. The publication of the rough-legged buzzard story may help researchers to summarize patterns such as this too. Mu problem with this paper is the framing. A story on the how and why of these continental movements in response to snow and other habitat features would be a grand contribution. Drop Anthropocene, and rethink whether foxtrot should be introduced as a hypothesis or a summary of cool descriptions. I prefer the latter, and recommend eLife to go with that too, rather than encourage "disconnected frames that seek 'respectability'" Good luck, theunis piersma
We thank the reviewer again for his valuable comments and suggestions. We have changed the framing to the suggested one and removed the Anthropocene from the article.
Reviewer #2 (Recommendations For The Authors):
We sincerely appreciate the time and effort you have taken to review our manuscript. We have carefully considered all of your comments, including both public and author comments, and provided detailed responses to each of them below. In addition, we would like to address the most important public comments.
We agree with the suggestion to shift the focus of the article from conservation to migration patterns. Accordingly, we have rewritten both the Introduction and Discussion sections to focus on migration behavior rather than conservation.
However, we respectfully disagree with the suggestion that the migration patterns we describe are synonymous with itinerancy. We acknowledge that our original presentation may have been unclear and may have hindered full understanding. In the revised version, we provide a detailed analysis of migratory behavior in the Introduction that describes how our pattern differs from itinerancy. We also revisit this distinction in the Discussion section. We have also carefully revised Figure 1 to improve clarity and avoid potential misunderstandings.
Regarding the applicability of the described migration pattern, we acknowledge that the Rough-legged Buzzard is not listed as an endangered species. However, we believe that our findings have practical implications. We have moved our discussion of this issue to the end of the Discussion section and have completely revised Figure 5. While the overall population of Rough-legged Buzzards is not declining, certain regions within its range are experiencing declines. We show that this decline does not warrant listing the species as endangered. Instead, it may represent a redistribution within the non-breeding range - a shift in range dynamics. We use the example of the Rough-legged Buzzard to illustrate this concept and emphasize the importance of considering such dynamics when assessing the conservation status of species in the future.
We also acknowledge that the hypothesis of this form of behavior has been proposed previously for Montagu's Harrier, and we have included this information in the revised manuscript. In addition, we agree that the focus on the Anthropocene is unnecessary in this context and have therefore removed it.
We believe that these revisions significantly improve the clarity and robustness of the manuscript, and we are grateful for your insightful comments and suggestions.
As a general comment, please note that including line numbers (as it is the standard in any manuscript submission) would facilitate reviewers providing more detailed comments on the text.
We apologize for this oversight and have added line numbers to our revised manuscript.
Dataset: unclear what is the frequency of GPS transmissions. Furthermore, information on relative tag mass for the tracked individuals should be reported.
We have included this information in our manuscript (L 157-163). We also refer to the study in which this dataset was first used and described in detail (L 164).
Data pre-processing: more details are needed here. What data have been removed if the bird died? The entire track of the individual? Only the data classified in the last section of the track? The section also reports on an 'iterative procedure' for annotating tracks, which is only vaguely described. A piecewise regression is mentioned, but no details are provided, not even on what is the dependent variable (I assume it should be latitude?).
Regarding the deaths. We only removed the data when the bird was already dead. We have corrected the text to make this clear (L 170).
Regarding the iterative procedure. We have added a detailed description on lines 175-188.
Data analysis: several potential issues here:
(1) Unclear why sex was not included in all mixed models. I think it should be included.
Our dataset contains 35 females and eight males. This ratio does not allow us to include sex in all models and adequately assess the influence of this factor. At the same time, because adult females disperse farther than males in some raptor species, we conducted a separate analysis of the dependence of migration distance on sex (Table S8) and found no evidence for this in our species. We have written a separate paragraph about this. This paragraph can be found on lines 356-360 of the new manuscript.
(2) Unclear what is the rationale of describing habitat use during migration; is it only to show that it is a largely unsuitable habitat for the species? But is a formal analysis required then? Wouldn't be enough to simply describe this?
Habitat use and snow cover determine the two main phases (quick and slow) of the pattern we describe. We believe that habitat analysis is appropriate in this case and that a simple description would be uninformative and would not support our conclusions.
(3) Analysis of snow cover: such a 'what if' analysis is fine but it seems to be a rather indirect assessment of the effect of snow cover on movement patterns. Can a more direct test be envisaged relating e.g. daily movement patterns to concomitant snow cover? This should be rather straightforward. The effectiveness of this method rests on among-year differences in snow cover and timing of snowfall. A further possibility would be to demonstrate habitat selection within the entire non-breeding home range of an individual in relation snow cover. Such an analysis would imply associating presence-absence of snow to every location within the non-breeding range and testing whether the proportion of locations with snow is lower than the proportion of snow of random locations within the entire non-breeding home range (95% KDE) for every individual (e.g. by setting a 1/10 ratio presence to random locations).
The proposed analysis will provide an opportunity to assess whether the Rough-legged Buzzard selects areas with the lowest snow cover, but will not provide an opportunity to follow the dynamics and will therefore give a misleading overall picture. This is especially true in the spring months. In March-April, Rough-legged Buzzards move northeast and are in an area that is not the most open to snow. At this time, areas to the southwest are more open to snow (this can be seen in Figure 4b). If we perform the proposed analysis, the control points for this period would be both to the north (where there is more snow) and to the south (where there is less snow) from the real locations, and the result would be that there is no difference in snow cover.
A step-selection analysis could be used, as we did in our previous work (Curk et al 2020 Sci Rep) with the same Rough-legged Buzzard (but during migration, not winter). But this would only give us a qualitative idea, not a quantitative one - that Rough-legged Buzzards move from snow (in the fall) and follow snowmelt progression (in the spring).
At the same time, our analysis gives a complete picture of snow cover dynamics in different parts of the non-breeding range. This allows us to see that if Rough-legged Buzzards remained at their fall migration endpoint without moving southwest, they would encounter 14.4% more snow cover (99.5% vs. 85.1%). Although this difference may seem small (14.4%), it holds significance for rodent-hunting birds, distinguishing between complete and patchy snow cover. Simultaneously, if Rough-legged Buzzards immediately flew to the southwest and stayed there throughout winter, they would experience 25.7% less snow cover (57.3% vs. 31.6%). Despite a greater difference than in the first case, it doesn't compel them to adopt this strategy, as it represents the difference between various degrees of landscape openness from snow cover.
We write about this in the new manuscript on lines 385-394.
Results: it is unclear whether the reported dispersion measures are SDs or SEs. Please provide details.
For the date and coordinates of the start and end of the different phases of migration, we specified the mean, sd, and sample size. We wrote this in line 277. For the values of the parameters of the different phases of the migration (duration, distance, speed, and direction), we used the mean, the standard error of the mean, and the confidence interval (obtained using the ‘emmeans’ package). We have indicated this in lines 302-303 and the caption of Table 1 (L 315) and Figure 2 (L 293-294). For the values of habitat and snow cover experienced by the Rough-legged Buzzards, we used the mean and the error of the mean. We reported this on lines 322 and 337 and in Figures 3 (L 332-333) and 4 (L 355-356).
Discussion: in general, it should be reshaped taking into account the comments. It is overlong, speculative and quite naive in several passages. Entire sections can be safely removed (I think it can be reduced by half without any loss of information). I provide some examples of the issues I have spotted below. For instance, the entire paragraph starting with 'Understanding....' is not clear to me. What do you mean by 'prohibited management' options? Without examples, this seems a rather general text, based on unclear premises when related to the specific of this study. Some statements are vague, derive from unsubstantiated claims, and unclear. E.g. "Despite their scarcity in these habitats, forests appear to hold significant importance for Rough-legged buzzards for nocturnal safety". I could not find any day-night analysis showing that they actually roost in forests during nighttime. Being a tundra species, it may well be possible that rough-legged buzzards perceive forests as very dangerous habitats and that they prefer instead to roost in open habitats. Analysing habitat use during day and night during the non-breeding period may be of help to clarify this. Furthermore, considering the fast migration periods, what is the flight speed during day and night above forests? Do these birds also migrate at night or do they roost during the night? Perhaps a figure visualizing day and night track segments could be of help (or an analysis of day vs. night flight speed) (there are several R packages to annotate tracks in relation to day and night). This is an example of another problematic statement: "The progression of snow cover in the wintering range of Rough-legged buzzards plays a significant role in their winter migration pattern." The manuscript does not contain any clear demonstration of this, as I wrote in my previous comments. Without such evidence, you must considerably tone down such assertions. But since providing a direct link is certainly possible, I think that additional analyses would clearly strengthen your take-home message.
The paragraph starting with "The quantification of environmental changes that could prove fatal to bird species presents yet another challenge for conservation efforts in an era of rapid global change." is quite odd. Take the following statement "For instance, the presence of small patches of woodland in the winter range might appear crucial to the survival of the Rough-legged buzzard. Elimination of these seemingly minor elements of vegetation cover through management actions could have dire consequences for the species.". It is based on the assumption that minor vegetation elements play a key role in the ecology of the species, without any evidence supporting this. Does it have any sense? I could safely say exactly the opposite and I would believe it might even be more substantiated.
We agree with these comments.
We have completely rewritten this section. As suggested, we have shortened it by removing statements that were not supported by the research. We have completely removed the statements about "prohibited management". We have also removed the statement that "forests appear to be of significant importance to Rough-legged buzzards for nocturnal safety" and everything associated with that statement, e.g. the statement about "small elements of vegetation cover", etc. We do believe that this statement is true in substance, but we also agree that it is not supported by the results and requires separate analysis. At the same time, we believe that this is a topic for a separate study and would be redundant here. Therefore, we leave it for a separate publication.
Conclusion paragraph: I believe this severely overstates the conservation importance of this study. That the results have "crucial implications for conservation efforts in the Anthropocene, where rapidly changing environmental factors can severely impact bird migration" seems completely untenable to me. What is the evidence for such crucial implications? For instance, these results may suggest that climate change, because global warming is predicted to reduce snow cover in the non-breeding areas, might well be beneficial for populations of this species, by reducing non-breeding energy expenditure and improving non-breeding survival. I think statements like these are simply not necessary, and that the study should be more focused on the actual results and evidence provided.
We have completely rewritten this section. We removed the reference to the Anthropocene and focused on migratory behavior and migration patterns.
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drive.google.com drive.google.com
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整体翻译: - 句子:(An meinem freien Tag, komm schon mit, sie machen mir einen knackigen frischen Fruchtsalat!) - 翻译:(在我休息日,快跟我一起来,他们给我准备了一份清脆新鲜的水果沙拉!)
单词分解与翻译: - An: (在),介词,表示某个时间点或位置。 - meinem: (我的),代词,第一格的属格形式,中性单数。 - freien: (休息的),形容词,表示没有工作或任务的。 - Tag: (日子),名词,指一天的时间段。 - komm: (来),动词 "kommen" (来) 的第二人称单数现在时态。 - schon: (已经),副词,用于表示事情早已发生或已经存在。 - mit: (一起),介词,表示与某人或某物一同。 - sie: (他们),代词,第三人称代词,复数形式。 - machen: (准备),动词,表示进行某种制作或准备。 - mir: (给我),代词,第一格的与格形式,表示动作的接受者是说话人自己。 - einen: (一份),不定冠词,宾格形式,表示单数形式。 - knackigen: (清脆的),形容词,表示脆弱或有咬劲的。 - frischen: (新鲜的),形容词,表示新鲜或未经过长时间保存的。 - Fruchtsalat: (水果沙拉),名词,指由水果切片或拌合而成的沙拉。
所以整句的意思是:(在我休息日,快跟我一起来,他们给我准备了一份清脆新鲜的水果沙拉!) 这句话表示说话人在休息日邀请对方一同前往,他们为说话人准备了一份清脆新鲜的水果沙拉。使用"An meinem freien Tag"强调了休息日的重要性和愉快的氛围。
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整体翻译: - 句子:(Oh, heute ist mein einziger freier Tag der Woche!) - 翻译:(哦,今天是我一周中唯一的休息日!)
单词分解与翻译: - Oh: (哦),感叹词,表示惊讶、兴奋或失望等情绪。 - heute: (今天),副词,表示时间上的 "今天"。 - ist: (是),助动词 "sein" (是) 的第三人称单数现在时态。 - mein: (我的),代词,第一人称所有格,表示某物属于说话者。 - einziger: (唯一的),形容词,表示仅有一个或独一无二的。 - freier: (休息的),形容词,表示没有工作或任务的。 - Tag: (日,天),名词,表示一天或时间段。 - der: (的),冠词,用于表示性别或格的名称。 - Woche: (周,星期),名词,表示一周或时间段。
所以整个句子的意思是:(哦,今天是我一周中唯一的休息日!) 这句话表达了说话者对今天是周中唯一的休息日的感叹和惊喜。使用"Oh"表示情绪的表达,"heute"表示时间上的 "今天","ist"表示 "是","mein einziger freier Tag"表示唯一的休息日,"der Woche"表示在一周中。
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整体翻译: - 句子:(Heute ist Sonntag, der einzige Tag, an dem ich ausschlafen darf, doch nicht kann, weil es viel zu heiß ist!) - 翻译:(今天是星期日,是我唯一可以睡懒觉的日子,但我不能,因为天气太热了!)
单词分解与翻译: - Heute: (今天),副词,表示指示或强调目前的时间点。 - ist: (是),动词 "sein" (是) 的第三人称单数现在时态。 - Sonntag: (星期日),名词,表示一周中的第七天,通常被视为休息日。 - der: (这个),定冠词,阳性形式,单数。 - einzige: (唯一的),形容词,表示只有一个或没有其他的。 - Tag: (日子,天),名词,表示时间的单位,通常指一天。 - an dem: (在这一天),介词 "an" (在...上) 和代词 "dem" (这个) 的组合,用于表示具体的日期或时间点。 - ich: (我),代词,第一人称主格。 - ausschlafen: (睡懒觉),动词,表示延长睡眠或在早晨继续睡觉以恢复精力。 - darf: (可以),助动词 "dürfen" (可以) 的第一人称单数现在时态,表示允许或有权做某事。 - doch: (但是),连词,用于引出相反或对比的情况。 - nicht: (不),副词,表示否定。 - kann: (能,可以),动词 "können" (能,可以) 的第一人称单数现在时态。 - weil: (因为),从属连词,表示原因或解释。 - es: (它),代词,用于指代前文中的某个事物或情况。 - viel zu: (太...了),表示程度过高或超过正常范围。 - heiß: (热),形容词,表示温度高或气温高。 - ist: (是),动词 "sein" (是) 的第三人称单数现在时态。
所以整句的意思是:(今天是星期日,是我唯一可以睡懒觉的日子,但我不能,因为天气太热了!) 这句话描述了今天是星期日,通常是休息和放松的日子,但由于天气过热,说话人无法享受到睡懒觉的乐趣。使用"doch"和"nicht"表达了对比和失望的情绪。
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Author response:
The following is the authors’ response to the original reviews.
eLife assessment
This study presents useful findings regarding the role of formin-like 2 in mouse oocyte meiosis. The submitted data are supported by incomplete analyses, and in some cases, the conclusions are overstated. If these concerns are addressed, this paper would be of interest to reproductive biologists.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
The presented study focuses on the role of formin-like 2 (FMNL2) in oocyte meiosis. The authors assessed FMNL2 expression and localization in different meiotic stages and subsequently, by using siRNA, investigated the role of FMNL2 in spindle migration, polar body extrusion, and distribution of mitochondria and endoplasmic reticulum (ER) in mouse oocytes.
Strengths:
Novelty in assessing the role of formin-like 2 in oocyte meiosis.
Weaknesses:
Methods are not properly described.
Overstating presented data.
It is not clear what statistical tests were used.
My main concern is that there are missing important details of how particular experiments and analyses were done. The material and methods section are not written in the way that presented experiments could be repeated - it is missing basic information (e.g., used mouse strain, timepoints of oocytes harvest for particular experiments, used culture media, image acquisition parameters, etc.). Some of the presented data are overstated and incorrectly interpreted. It is not clear to me how the analysis of ER and mitochondria distribution was done, which is an important part of the presented data interpretation. I'm also missing important information about the timing of particular stages of assessed oocytes because the localization of both ER and mitochondria differs at different stages of oocyte meiosis. The data interpretation needs to be justified by proper analysis based on valid parameters, as there is considerable variability in the ER and mitochondria structure and localization across oocytes based on their overall quality and stage.
Thank you for your comment. We regret the oversight of omitting critical information in the manuscript. In the revised manuscript, we have included essential details such as mouse strains, culture media, stages of oocyte and statistical methods in the materials and methods section. Please find our details responses in the “Recommendations for the authors” part.
Reviewer #2 (Public Review):
Summary:
This research involves conducting experiments to determine the role of Fmnl2 during oocyte meiosis I.
Strengths:
Identifying the role of Fmnl2 during oocyte meiosis I is significant.
Weaknesses:
The quantitative analysis and the used approach to perturb FMNL2 function are currently incomplete and would benefit from more confirmatory approaches and rigorous analysis.
(1) Most of the results are expected. The new finding here is that FMNL2 regulates cytoplasmic F-actin in mouse oocytes, which is also expected given the role of FMNL2 in other cell types. Given that FMNL2 regulates cytoplasmic F-actin, it is very expected to see all the observed phenotypes. It is already established that F-actin is required for spindle migration to the oocyte cortex, extruding a small polar body and normal organelle distribution and functions.
Thank you for your comment. In the recent decade, Arp2/3 complex (Nat Cell Biol 2011), Formin2 (Nat Cell Biol 2002, Nat Commun 2020), and Spire (Curr Biol 2011) were reported to be 3 key factors to involve into this process. These factors regulate actin filaments in different ways. However, how they cross with each other for the subcellular events were still fully clear. Our current study identified that FMNL2 played a critical role in coordinating these molecules for actin assembly in oocytes. Our findings demonstrate that FMNL2 interacts with both the Arp2/3 complex and Formin2 to facilitate actin-based meiotic spindle migration. Additionally, we discovered a novel role for FMNL2 in determining the distribution and function of the endoplasmic reticulum and mitochondria, which may in turn influence meiotic spindle migration in oocytes. Our results not only uncover the novel functions of FMNL2-mediated actin for organelle distribution, but also extend our understanding of the molecular basis for the unique meiotic spindle migration in oocyte meiosis.
(2) The authors used Fmnl2 cRNA to rescue the effect of siRNA-mediated knockdown of Fmnl2. It is not clear how this works. It is expected that the siRNA will also target the exogenous cRNA construct (which should have the same sequence as endogenous Fmnl2) especially when both of them were injected at the same time. Is this construct mutated to be resistant to the siRNA?
Thank you for your question. We regret any misunderstanding that may have been caused by the inappropriate description in our manuscript. In the rescue experiments, we initially injected FMNL2 siRNA into oocytes, followed by the microinjection of FMNL2 mRNA 18-20 hours later. After conducting our previous experiments, we have verified through Western blotting that endogenous FMNL2 is effectively suppressed 18-20 hours following the microinjection of FMNL2 siRNA. Additionally, we observed a significant increase in exogenous FMNL2 protein expression 2 hours after the injection of FMNL2 mRNA. We believe that the exogenous FMNL2 could compensate the decrease by FMNL2 knockdown, and this approach was adopted in many oocyte studies.
(3) The authors used only one approach to knockdown FMNL2 which is by siRNA. Using an additional approach to inhibit FMNL2 would be beneficial to confirm that the effect of siRNA-mediated knockdown of FMNL2 is specific.
Thank you for your question. Yes, the specificity is always the concern for siRNA or morpholino microinjection due to the off-target issue. Due to the limitation we could not generate the knock out model, and there are no known inhibitors with specific targeting capabilities for FMNL2. To solve this, we performed the rescue study with exogenous mRNA to confirm the effective knock down of FMNL2. These measures provide reassurance regarding the credibility of the experimental outcomes, and this is also the general way to avoid the off-target of siRNA or morpholino.
Reviewer #3 (Public Review):
Summary:
The authors focus on the role of formin-like protein 2 in the mouse oocyte, which could play an important role in actin filament dynamics. The cytoskeleton is known to influence a number of cellular processes from transcription to cytokinesis. The results show that downregulation of FMNL2 affects spindle migration with resulting abnormalities in cytokinesis in oocyte meiosis I.
Weaknesses:
The overall description of methods and figures is overall dismissively poor. The description of the sample types and number of replicate experiments is impossible to interpret throughout, and the quantitative analysis methods are not adequately described. The number of data points presented is unconvincing and unlikely to support the conclusions. On the basis of the data presented, the conclusions appear to be preliminary, overstated, and therefore unconvincing.
Thank you for your comment. We regret the oversight of omitting critical information in the manuscript. In the revised manuscript, we have incorporated your suggestions for modification, particularly regarding the Materials and Methods section. Please see the detailed revision and responses in the “Recommendations for the authors” part.
Recommendations for the authors:
Reviewer #1 (Recommendations for The Authors):
My main concern is that there are missing important details of how particular experiments and analyses were done. The material and methods section is not written in the way that presented experiments could be repeated - it is missing basic information (e.g., used mouse strain, timepoints of oocytes harvest for particular experiments, used culture media, image acquisition parameters, etc.). Some of the presented data are overstated and incorrectly interpreted. It is not clear to me how the analysis of ER and mitochondria distribution was done, which is an important part of the presented data interpretation. I'm also missing important information about the timing of particular stages of assessed oocytes because the localization of both ER and mitochondria differs at different stages of oocyte meiosis. The data interpretation needs to be justified by proper analysis based on valid parameters, as there is considerable variability in the ER and mitochondria structure and localization across oocytes based on their overall quality and stage. My specific comments are listed below.
(1) Information about statistical tests that were used needs to be provided for all quantification experiments.
Thank you for your suggestion. Based on your suggestions, we revised the statistical analysis description in the Materials and Methods section. Additionally, we also included a description of the statistical methods in the legends of the relevant result figures.
(2) I recommend replacing the plunger plots, used in most quantification data, with alternatives allowing evaluation of the distribution of the data (dot plots, box plots, whisker plots).
Thank you for your suggestion. Following your suggestion, we replaced the plunger plots in Fig 2C, D, H, I and Fig3 B, C with dot plots.
(3) Can the authors provide information about particular time points when were individual oocyte stages (GVBD, meiosis I, and meiosis II) harvested/used for immunofluorescence protein detection, western blotting, microinjection, and ER and mitochondria staining? Were the time points always the same in all presented experiments and experimental vs control group? If not, this needs to be clarified.
Thank you for your suggestion. We used oocytes in the metaphase I (MI) stage for the statistical analysis of spindle migration, actin filament aggregation, endoplasmic reticulum localization, and mitochondrial localization. In the Western blot analysis, GV stage oocytes were utilized to evaluate the efficiency of knockdown and rescue experiments. The protein expression levels of Arp2, Formin2, INF2, Cofilin, Grp78, and Chop in different treatment groups were detected using MI-stage oocytes. In the revised version, we provided all the detailed information about the stages.
(4) Figure 1B: Can the authors comment on why there is a missing representative image of MII oocyte FMBL2-Ab? I recommend including this in the figure to have a complete view of comparing overexpressed and endogenous FMNL2 localization in oocyte meiosis.
Thank you for your suggestion. In the revised manuscript, we added immunostaining images of FMNL2 antibody in MII stage oocytes.
(5) Figure 1C: The figure legend says, "FMNL2 and actin overlapped in cortex and spindle surrounding". In MI oocytes, there is usually no accumulated actin signal around the spindle, which is also true in the presented images, so there cannot be overlapping with the FMNL2 signal. The interpretation should be changed.
We apologize for this inappropriate description that was used, and we deleted this sentence.
(6) Figure 2B: What were the parameters of the "large" and "normal" polar bodies for performing the analysis?
Thank you for your question. In order to assess the size of the polar body, we conducted a comparison between the diameter of the polar body and that of the oocyte. If the diameter of the polar body was found to be less than 1/3 of the oocyte's diameter, we categorized it as normal-sized polar body. Conversely, if the polar body's diameter exceeded 1/3 of the oocyte's diameter, we categorized it as a large polar body. We have included these details in the Results section of the manuscript.
(7) Figure 2F: Can the authors comment on what can be the second band in the rescue group?
Thank you for your question. In the rescue experiment, we microinjected exogenous FMNL2-EGFP mRNA into the oocytes. As a result, compared to endogenous FMNL2, the protein size increased due to the addition of the EGFP tag, approximately 27 kDa. Hence, in the Western blot bands of the rescue group, the upper band represents the expression of exogenous FMNL2-EGFP, while the lower band corresponds to the expression of endogenous FMNL2. We have provided annotations in the revised Figure 2F to clarify this.
(8) Can the authors comment on the variability of PBE between 2C and 2H in the FMNL2-KD groups? In panel C, the PBE in the KD group was 59.5 {plus minus} 2.82%; in panel H, the PBE in the KD group was 48.34 {plus minus} 4.2%, and in the rescue group, the PBE was 62.62 {plus minus} 3.6%. The rescue group has a similar PBE rate as the KD group in panel C. How consistent was the FMNL2 knockdown across individual replicates? Can the authors provide more details on how the rescue experiment was performed?
Thank you for your question. We believe that the difference in PBE observed in Figure 2C and 2H of the FMNL2-KD group was due to the microinjection times and the duration of in vitro arrest. The results shown in Figure 2C depict the outcome of a single injection of FMNL2 siRNA into GV stage oocytes, followed by 18 hours of in vitro arrest; the results shown in Figure 2H contain a subsequent additional injection of FMNL2-EGFP mRNA with another 2 hours of arrest. The two rounds of microinjection and the extended period of in vitro arrest both affect oocyte maturation rates.
(9). Figure 2J and K: What groups were compared together? The used statistic needs to be properly described.
Thank you for your question. The FMNL2-KD, FMNL3-KD, and FMNL2+3-KD groups were all compared to the Control group, therefore, t-test was used for analysis. We have provided explanations in the revised manuscript.
(10) Figure 4B and C: Can the authors provide representative images without oversaturated actine signal?
Thank you for your question. For the analysis of oocyte F-actin, the F-actin are divided into cortex actin and cytoplasmic actin. Due to the contrast during imaging, the strong cortex actin signals affected the detection of cytoplasmic actin, therefore, it is necessary to increase the scanning index, which will cause the overexpose the cortex actin signal. This is for the better observation of the cytoplasmic signals.
(11) Figure 4G + 5H: Can the authors comment on why they used as a housekeeping gene actin instead of tubulin, which was used in the rest of the WB experiments?
Thank you for your question. In most of the western blot experiments conducted in this study, we used tubulin as a housekeeping gene. However, due to the supply of antibodies by delivery period, we had GAPDH and actin as well for some experiments. These housekeeping genes were all valid for the study.
(12) Based on what parameters was ER considered normally or abnormally distributed, and what stages of oocytes were assessed?
Thank you for your question. In this study, we employed oocytes at the MI stage for the analysis of ER localization. In the MI stage, the ER localized around the spindle, which is regarded as the typical localization pattern. The ER displayed a dispersed distribution throughout the cytoplasm or clustered were categorized as aberrant positioning. We included relevant descriptions in the revised version of the manuscript.
(13) Figure 5H: As a housekeeping gene was used actin - the quantification is labeled as a Grp78 to tubulin ratio.
Thank you for pointing out the error. This is a label mistake and we corrected it.
(14) Information about how JC-1 staining was done needs to be provided.
Thank you for your carefully reading. We included a description of JC1 staining in the Materials and Methods section.
(15). Line 231-232: "As shown in Figure 4A" - the text doesn't correspond to the figure.
Thank you for pointing out the error. We revised this mistake in the revised manuscript by correcting "Fig3A" to "Fig4A."
(16) Line 265: there is probably a missing word "Formin2".
Thank you and we corrected the error and made the necessary changes in the revised manuscript.
Reviewer #2 (Recommendations for The Authors):
(1) Quantification and analysis:
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Fig. 3B: The rate of spindle migration should be quantified based on the distance from the spindle to the cortex. Also, the orientation of the spindle (Z-position) needs to be taken into consideration.
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Fig. 5C, D: It is unclear how the rate of ER distribution was calculated.
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Western blot: In many experiments (such as Fig. 5H), the bands are saturated which will prevent accurate intensity measurements and quantifications.
For spindle migration, we specifically focused on spindles exhibiting a distinctive spindle-like shape with clear bipolarity to eliminate any statistical discrepancies potentially caused by variations in Z-axis alignment. Our criterion for determining successful migration was based on the contact between the spindle pole and the cortical region of the oocyte. Therefore, we think that the rate is better to reflect the phenotype than the distance.
For the examination of ER localization, Reviewer 1 also raised this issue. We utilized oocytes at the MI stage in this study. The ER localized around the spindle in MI stage. The ER displayed a dispersed distribution throughout the cytoplasm or clustered were categorized as aberrant positioning. We included relevant descriptions in the revised version of the manuscript.
For the bands of the western blot results, during the experimental procedure we typically capture multiple images at different exposure levels (3-5 images). In the revised manuscript, we have replaced the inappropriate images with more suitable ones.
(2) Given that all Immunoprecipitation experiments in this manuscript were performed on the whole ovary which contains more somatic cells than oocytes, the results do not necessarily reflect meiotic oocytes. Please consider this possibility during the interpretation.
Thank you for your suggestion. Yes, we agree with you. In the revised manuscript, we made appropriate modifications to the relevant descriptions.
(3) 351-365: The conclusion that Arp2/3 compensates for the decreased formin 2 in FMNL2 knockdown oocytes is a bit unconvincing. 1- In mouse oocytes, it is already known that Arp2/3 and formin 2 regulate different pools of F-actin nucleation. 2- The authors found an increase in Arp2/3 in FMNL2 knockdown oocytes compared to control oocytes without any change in cortical F-actin. Given that Arp2/3 is primarily promoting cortical F-actin, it is expected to see an increase in cortical F-actin in FMNL2 knockdown oocytes, which was not the case.
Thank you for your question. Yes, previous studies showed that formin2 localizes to the cytoplasm of oocytes and accumulates around the spindle, which facilitate cytoplasmic actin assembly. While Arp2/3 is primarily responsible for actin assembly at the cortex region of oocytes. In invasive cells, FMNL2 is mainly localized in the leading edge of the cell, lamellipodia and filopodia tips, to improve cell migration ability by actin-based manner (Curr Biol 2012). We showed that FMNL2 localized both at spindle periphery and cortex, but depletion of FMNL2 did not affect cortex actin intensity. We think that FMNL2 and Arp2/3 both contribute to the cortex actin dynamics, when FMNL2 decreased, ARP2 increased to compensate for this, which maintained the cortex actin level. In the revised manuscript, we have made modifications to avoid excessive extrapolation from our results, ensuring that our conclusions are presented in a more objective manner.
(4) Lines 195-197: The spindle is initially formed soon after the GVBD, so there is no spindle during GVBD. Also, I can't see oocytes at anaphase I or telophase I in this figure. Please revise.
Thank you for your suggestion. We apologize for the inappropriate descriptions that were used. In the revised manuscript, we have made modifications to the respective descriptions in the Results part.
(5) Fig. 2E: It seems that the control oocyte is abnormal with mild cytokinesis defects. Please replace or delete it since this information is already included in Fig. 3A.
Thank you for your suggestion. Based on our observations, during the extrusion of the first polar body in oocytes, there is a temporary occurrence of cellular morphological fragmentation due to cortical reorganization (11h in control oocyte from Fig 2E). However, after the extrusion of the first polar body, the oocyte morphology returns to normal. Figure 2E illustrates the meiotic division process of oocytes, while Figure 3A primarily focuses on the process of oocyte spindle migration. We think that it is better to retain both to present our results.
Reviewer #3 (Recommendations for The Authors):
In the case of the observed phenotype, the stage of GV is important. The phenotypes presented also occur in meiotic or developmentally incompetent oocytes. In addition, the images of GV oocytes appear as NSN, which also show the KD phenotype in Figs. 2 and 3.
Thank you for your concern. As the oocyte grows, the proportion of SN-type oocytes gradually increases. When the oocyte diameter reaches 70-80 μm, the proportion of SN oocytes is approximately 52.7% (Mol Reprod Dev. 1995). In our study, both the control and knockdown groups collected oocytes with a diameter of around 80 μm, which is considered as fully-grown oocytes, predominantly in the SN phase. Since the collection period and size of the oocytes were consistent, we can sure that the observed differences between the control and knockdown groups in phenotype analysis could be solid and reliable.
MII is absent in Fig. 1B.
In the revised manuscript, we added immunostaining images of FMNL2 in MII stage oocytes.
The result of KD is not convincing. Also, discuss whether the heterozygous effect of Fmnl2 deletion affects reproductive fitness.
Thank you for your concern. In our investigation, limited to the setup of knock out model, we employed siRNA to knockdown FMNL2 expression, to avoid the risk of off-target, we performed rescue experiment with exogenous mRNA, which we believe that it could solve this issue. When designing siRNA sequences, we ensured their specificity for binding to FMNL2 mRNA only, and we assessed the levels of FMNL2 and FMNL3 mRNA in oocytes after injection of FMNL2 siRNA. The results showed that, compared to the control group, the expression of FMNL2 mRNA decreased by approximately 70% after 18 hours of FMNL2 siRNA injection, while the level of FMNL3 mRNA was not decreased.
Fig. 2F rescue experiment with double bands. What bands are seen here? Did the authors inject tagged or untagged FMNL2? Or does endogenous FMNL2 appear higher in the sample after KD?
Thank you for your question. In the rescue experiment, we microinjected exogenous FMNL2-EGFP mRNA into the oocytes. As a result, compared to endogenous FMNL2, the protein size increased due to the addition of the EGFP tag, approximately 27 kDa. Hence, in the Western blot bands of the rescue group, the upper band represents the expression of exogenous FMNL2-EGFP, while the lower band corresponds to the expression of endogenous FMNL2. We provided annotations in the revised Figure 2F to clarify this.
Variability in mitochondria and ER distribution patterns is also known in healthy and developing oocytes, although the authors described only a single phenotype.
Thank you for your concern. Yes, mitochondria and ER show dynamic localization in different stage of oocyte maturation. However, in this study we employed oocyte MI stage for the analysis of ER and mitochondria localization, and in MI stage, both the ER and mitochondria localize around the spindle. This pattern is considered as the normal localization. Several studies showed that dispersed or clustered localization contributed to maturation defects. We included relevant descriptions in the revised manuscript.
What exactly is meant by input in the IP experiments? Why is the target missing in the input sample?
Thank you for your question. We subjected the input samples to electrophoresis on a single channel, all the analyzed proteins demonstrated normal expression, thereby confirming the viability of the input sample. However, upon simultaneous exposure with the IP samples, we observed a lack of clear signal for certain proteins in the input group. This phenomenon is due to the excessive signal intensity resulting from protein enrichment in the IP group, which caused the low exposure of proteins in input group.
Explain the rationale for using, actin or tubulin as loading or normalization controls in the study focusing on the cytoskeleton.
Thank you for your question. Actin and tubulin are both widely used as the control due to their stable expression. For actin, there are α-actin and β-actin isoforms. Formins and Arp2/3 complex regulate the polymerization of α-actin and β-actin to form F-actin, not isoform expression. In our study F-actin (the functional type) was examined. While α-tubulin and β-tubulin are two subtypes of tubulin, and they interact with each other to form stable α/β-tubulin heterodimers. The changes of cytoskeleton dynamics could not change the expression of α/β-tubulin. Therefore, β-actin and α-tubulin could be used as normalization controls.
Fig. 6E shows only , but the legend says *.
Thank you for pointing out the error. We correct the mistake in the revised manuscript.
Spindle positioning appears to differ between control and KD. Does this affect the quantification of Fig. 6F? Adequate nomenclature should be used here.
Thank you for your question. Yes, spindle positioning was affected by FMNL2 depletion. However, central spindle or cortex spindle all belong to MI stage, and JC1 is not related with the stage difference. To avoid misunderstanding we replaced the representative images and corresponding description in Figure 6F.
The description of the methods and legends should be significantly improved.
Thank you for your suggestion. Reviewer 1 and 2 also raised the similar concern. We enriched the description of methods and legends in the revised manuscript.
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Reviewer #3 (Public Review):
Summary:
How short-term isolation acts on the brain to promote social behavior remains incompletely understood. The authors found that social interactions after a period of acute isolation increased investigation promoted mounting, and increased the production of ultrasonic vocalizations (USVs). This was true for females during same-sex interactions as well as for males interacting with females. Concomitant with these increased behavioral readouts, cFos expression in the preoptic area of the hypothalamus (POA) was found to increase selectively in single-housed females. Chemogenetic silencing of these POA neurons attenuated all three behavioral measures in socially isolated females. Surprisingly, ablation of the same POA neurons decreased mounting duration without impacting social investigation or USV production. While optogenetic activation was sufficient to evoke USV production, it did not affect either mounting or social investigation. In males, chemogenetic silencing of POA neurons decreased mounting but not other behaviors. Together, these data point towards a role of POA neurons in mediating social behaviors after acute isolation but the exact nature of that control appears to depend on the choice of perturbation method, sex, and social context in complex ways that are hard to parse. This study is an essential first step; additional experiments will be needed to explain the apparent discrepancy between the various circuit perturbation results and to gain a more comprehensive understanding of the role of POA in social isolation.
Strengths:
The goal of understanding the neural circuit mechanisms underlying acute social isolation is clearly important and topical. Using a state-of-the-art technique to tag specific neurons that were active during certain behavioral epochs, the authors managed to identify the POA as a critical circuit locus for the effects of social isolation. The experimental design is perfectly reasonable and the quality of the data is good. The control experiments (Figures 2B-D) showing that chemogenetic inactivation of other hypothalamic regions (AH and VMH) do not affect social behavior is indeed quite satisfying and points towards a specific role of POA within the hypothalamus. Using a combination of behavioral assays, activity-dependent neural tagging, and circuit manipulation techniques, the authors present convincing evidence for the role of the preoptic area of the hypothalamus in mediating certain behaviors following social isolation. These data are likely to be a valuable resource for understanding how hypothalamic circuits adjust to the challenges of social isolation.
Weaknesses:
While the authors should be commended for performing and reporting multiple circuit perturbation experiments (e.g., chemogenetics, ablation), the conflicting effects on behavior are hard to interpret without additional experiments. For example, chemogenetic silencing of the POA neurons (using DREADDs) attenuated all three behavioral measures but the ablation of the same POA neurons (using CASPACE) decreased mounting duration without impacting social investigation or USV production. Similarly, optogenetic activation of POA neurons was sufficient to generate USV production as reported in earlier studies but mounting or social investigation remained unaffected. Do these discrepancies arise due to the efficiency differences between DREADD-mediated silencing vs. Casp3 ablation? Or does the chemogenetic result reflect off-manifold effects on downstream circuitry whereas a more permanent ablation strategy allows other brain regions to compensate due to redundancy? It is important to resolve whether these arise due to technical reasons or whether these reflect the underlying (perhaps messy) logic of neural circuitry. Therefore, while it is clear that POA neurons likely contribute to multiple behavioral readouts of social isolation, understanding their exact roles in any greater detail will require further experiments.
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Author response:
Public Reviews:
Reviewer #1 (Public Review):
Summary:
In their manuscript entitled 'The domesticated transposon protein L1TD1 associates with its ancestor L1 ORF1p to promote LINE-1 retrotransposition', Kavaklıoğlu and colleagues delve into the role of L1TD1, an RNA binding protein (RBP) derived from a LINE1 transposon. L1TD1 proves crucial for maintaining pluripotency in embryonic stem cells and is linked to cancer progression in germ cell tumors, yet its precise molecular function remains elusive. Here, the authors uncover an intriguing interaction between L1TD1 and its ancestral LINE-1 retrotransposon.
The authors delete the DNA methyltransferase DNMT1 in a haploid human cell line (HAP1), inducing widespread DNA hypo-methylation. This hypomethylation prompts abnormal expression of L1TD1. To scrutinize L1TD1's function in a DNMT1 knock-out setting, the authors create DNMT1/L1TD1 double knock-out cell lines (DKO). Curiously, while the loss of global DNA methylation doesn't impede proliferation, additional depletion of L1TD1 leads to DNA damage and apoptosis.
To unravel the molecular mechanism underpinning L1TD1's protective role in the absence of DNA methylation, the authors dissect L1TD1 complexes in terms of protein and RNA composition. They unveil an association with the LINE-1 transposon protein L1-ORF1 and LINE-1 transcripts, among others.
Surprisingly, the authors note fewer LINE-1 retro-transposition events in DKO cells than in DNMT1 KO alone.
Strengths:
The authors present compelling data suggesting the interplay of a transposon-derived human RNA binding protein with its ancestral transposable element. Their findings spur interesting questions for cancer types, where LINE1 and L1TD1 are aberrantly expressed.
Weaknesses:
Suggestions for refinement:
The initial experiment, inducing global hypo-methylation by eliminating DNMT1 in HAP1 cells, is intriguing and warrants a more detailed description. How many genes experience misregulation or aberrant expression? What phenotypic changes occur in these cells?
The transcriptome analysis of DNMT1 KO cells showed hundreds of deregulated genes upon DNMT1 ablation. As expected, the majority were up-regulated and gene ontology analysis revealed that among the strongest up-regulated genes were gene clusters with functions in “regulation of transcription from RNA polymerase II promoter” and “cell differentiation” and genes encoding proteins with KRAB domains. In addition, the de novo methyltransferases DNMT3A and DNMT3B were up-regulated in DNMT1 KO cells suggesting the set-up of compensatory mechanisms in these cells. We will include this data set in the revised version of the manuscript.
Why did the authors focus on L1TD1? Providing some of this data would be helpful to understand the rationale behind the thorough analysis of L1TD1.
We have previously discovered that conditional deletion of the maintenance DNA methyltransferase DNMT1 in the murine epidermis results not only in the up-regulation of mobile elements, such as IAPs but also the induced expression of L1TD1 ((Beck et al, 2021), Suppl. Table 1 and Author response image 1). Similary, L1TD1 expression was induced by treatment of primary human keratinocytes or squamous cell carcinoma cells with the DNMT inhibitor aza-deoxycytidine (Author response image 2 and 3). These finding are in accordance with the observation that inhibition of DNA methyltransferase activity by azadeoxycytidine in human non-small cell lung cancer cells (NSCLCs) results in upregulation of L1TD1 (Altenberger et al, 2017). Our interest in L1TD1 was further fueled by reports on a potential function of L1TD1 as prognostic tumor marker. We will include this information in the revised manuscript.
Author response image 1.
RT-qPCR of L1TD1 expression in cultured murine control and Dnmt1 Δ/Δker keratinocytes. mRNA levels of L1td1 were analyzed in keratinocytes isolated at P5 from conditional Dnmt1 knockout mice (Beck et al., 2021). Hprt expression was used for normalization of mRNA levels and wildtype control was set to 1. Data represent means ±s.d. with n=4. **P < 0.01 (paired t-test).
RT-qPCR analysis of L1TD1 expression in primary human keratinocytes. Cells were treated with 5-aza-2-deoxycidine for 24 hours or 48 hours, with PBS for 48 hours or were left untreated. 18S rRNA expression was used for normalization of mRNA levels and PBS control was set to 1. Data represent means ±s.d. with n=3. **P < 0.01 (paired t-test).
Author response image 3.
Induced L1TD1 expression upon DNMT inhibition in squamous cell carcinoma cell lines SCC9 and SCCO12. Cells were treated with 5-aza-2-deoxycidine for 24 hours, 48 hours or 6 days. (A) Western blot analysis of L1TD1 protein levels using beta-actin as loading control. (B) Indirect immunofluorescence microscopy analysis of L1TD1 expression in SCC9 cells. Nuclear DNA was stained with DAPI. Scale bar: 10 µm. (C) RT-qPCR analysis of L1TD1 expression in primary human keratinocytes. Cells were treated with 5-aza-2deoxycidine for 24 hours or 48 hours, with PBS for 48 hours or were left untreated. 18S rRNA expression was used for normalization of mRNA levels and PBS control was set to 1. Data represent means ±s.d. with n=3. P < 0.05, *P < 0.01 (paired t-test).
The finding that L1TD1/DNMT1 DKO cells exhibit increased apoptosis and DNA damage but decreased L1 retro-transposition is unexpected. Considering the DNA damage associated with retro-transposition and the DNA damage and apoptosis observed in L1TD1/DNMT1 DKO cells, one would anticipate the opposite outcome. Could it be that the observation of fewer transposition-positive colonies stems from the demise of the most transposition-positive colonies? Further exploration of this phenomenon would be intriguing.
This is an important point and we were aware of this potential problem. Therefore, we calibrated the retrotransposition assay by transfection with a blasticidin resistance gene vector to take into account potential differences in cell viability and blasticidin sensitivity. Thus, the observed reduction in L1 retrotransposition efficiency is not an indirect effect of reduced cell viability.
Based on previous studies with hESCs, it is likely that, in addition to its role in retrotransposition, L1TD1 has additional functions in the regulation of cell proliferation and differentiation. L1TD1 might therefore attenuate the effect of DNMT1 loss in KO cells generating an intermediate phenotype (as pointed out by Reviewer 2) and simultaneous loss of both L1TD1 and DNMT1 results in more pronounced effects on cell viability.
Reviewer #2 (Public Review):
In this study, Kavaklıoğlu et al. investigated and presented evidence for the role of domesticated transposon protein L1TD1 in enabling its ancestral relative, L1 ORF1p, to retrotranspose in HAP1 human tumor cells. The authors provided insight into the molecular function of L1TD1 and shed some clarifying light on previous studies that showed somewhat contradictory outcomes surrounding L1TD1 expression. Here, L1TD1 expression was correlated with L1 activation in a hypomethylation-dependent manner, due to DNMT1 deletion in the HAP1 cell line. The authors then identified L1TD1-associated RNAs using RIP-Seq, which displays a disconnect between transcript and protein abundance (via Tandem Mass Tag multiplex mass spectrometry analysis). The one exception was for L1TD1 itself, which is consistent with a model in which the RNA transcripts associated with L1TD1 are not directly regulated at the translation level. Instead, the authors found the L1TD1 protein associated with L1-RNPs, and this interaction is associated with increased L1 retrotransposition, at least in the contexts of HAP1 cells. Overall, these results support a model in which L1TD1 is restrained by DNA methylation, but in the absence of this repressive mark, L1TD1 is expressed and collaborates with L1 ORF1p (either directly or through interaction with L1 RNA, which remains unclear based on current results), leads to enhances L1 retrotransposition. These results establish the feasibility of this relationship existing in vivo in either development, disease, or both.
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Reviewer #2 (Public Review):
In this study, Kavaklıoğlu et al. investigated and presented evidence for the role of domesticated transposon protein L1TD1 in enabling its ancestral relative, L1 ORF1p, to retrotranspose in HAP1 human tumor cells. The authors provided insight into the molecular function of L1TD1 and shed some clarifying light on previous studies that showed somewhat contradictory outcomes surrounding L1TD1 expression. Here, L1TD1 expression was correlated with L1 activation in a hypomethylation-dependent manner, due to DNMT1 deletion in the HAP1 cell line. The authors then identified L1TD1-associated RNAs using RIP-Seq, which displays a disconnect between transcript and protein abundance (via Tandem Mass Tag multiplex mass spectrometry analysis). The one exception was for L1TD1 itself, which is consistent with a model in which the RNA transcripts associated with L1TD1 are not directly regulated at the translation level. Instead, the authors found the L1TD1 protein associated with L1-RNPs, and this interaction is associated with increased L1 retrotransposition, at least in the contexts of HAP1 cells. Overall, these results support a model in which L1TD1 is restrained by DNA methylation, but in the absence of this repressive mark, L1TD1 is expressed and collaborates with L1 ORF1p (either directly or through interaction with L1 RNA, which remains unclear based on current results), leads to enhances L1 retrotransposition. These results establish the feasibility of this relationship existing in vivo in either development, disease, or both.
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Reviewer #2 (Public Review):
The first portion of the manuscript centered on identifying and confirming the ATHB2 microprotein (ATHB2miP), which constitutes the core message of this study. Overall, I find no issue with the selection criteria employed for identifying alternative microprotein mRNA transcripts. However, I do have some queries that I hope the authors can address for clarity.
(1) Upon reviewing the supplemental dataset where the authors listed the 377 unique novel miPs, along with those specifically in WL or shade treatments, I sought to comprehend the rationale behind focusing on ATHB2. Have the authors examined the shade response of all 377 potential microprotein candidates? Readers may be intrigued to learn how many of these candidates exhibit induction or repression under shade conditions, and whether such changes correlate positively or negatively with alterations in the full-length TSSs in response to shade. Essentially, I aim to discern the prevalence of microprotein production during shade responses and any shared characteristics among these microprotein transcripts. This inquiry also aims to uncover the existence of a common mechanism regulating microprotein transcription.
(2) To confirm that ATHB2miP stems from an independent transcription event, the authors sequenced full-length cDNAs using PacBio isoseq. However, I find the information regarding isoseq missing from the manuscript. My assumption is that the full-length cDNAs were reverse transcribed from mRNAs isolated from whole seedlings, where mature mRNAs in the cytoplasm predominate, making it challenging to evaluate whether a specific mRNA undergoes post-transcriptional processing. One approach to confirming ATHB2miP as a product of independent transcription involves examining nascent mRNA produced in the nucleus. The authors may need to isolate nascent mRNAs associated with RNA Polymerase II in the nucleus from seedlings treated with shade for 45 min, and then perform reverse transcription and PacBio isoseq.
(3) The authors noted the identification of two potential start codons, TTG and CTG, in the alternative TSS of ATHB2 using TISpredictor. Yet, it's imperative to identify the actual translation initiation site and the full-length sequence of ATHB2miP. I suggest the authors fuse an epitope tag (e.g., 3xFLAG) to the C-terminus of ATHB2 (utilizing the genomic sequence of ATHB2) and generate transgenic lines to be treated with shade to induce ATHB2miP-3xFLAG production. Affinity purification (anti-FLAG beads) and mass spectrometry can then identify the actual start site of ATHB2miP. This step is crucial, as the current ATHB2miP used may not be the exact sequence, and any observed phenotype could be artifacts arising from these lines.
(4) My confusion arose when analyzing the results in Figures 1E - G. The authors didn't specify whether these plants were subjected to shade treatment. What are the sequences within the second intron and third exon excluded from pATHB2control::GUS that promote transcription and translation? Have the authors examined the sequence features? This information is pivotal and related to the above question #1 because it may tell us whether the sequence feature is shared by other miP candidates.
The latter part of the manuscript focused on the functional characterization of ATHB2miP. The approaches adopted by the authors resemble those used in studying antimorphic (dominant negative) alleles. However, I have several concerns regarding the approaches and conclusions.
(5) Firstly, as mentioned in question #3, the authors did not map the actual translation initiation site of ATHB2miP. Therefore, all constructs involving ATHB2miP, such as eGFP-ATHB2miP, BD-ATHB2miP, and mCherry-ATHB2miP in Figure 2, and 35S::miP in Figures 3-5, may contain extra amino acids in the N-terminus, given that epitope tags were all added to the N terminus. These additional amino acids could potentially impact the behavior of ATHB2miP and lead to artifacts. Identifying the translation initiation site in ATHB2miP would facilitate the development of tools to disrupt ATHB2miP expression without affecting full-length ATHB2 expression. For instance, if the "CTG" before the leucine zipper domain is confirmed as the translation initiation site, mutating it to another Leu codon (e.g., TTA) could generate transgenic lines using the genomic sequence of ATHB2, including this mutation, to evaluate the impact of losing ATHB2miP on shade responses.
(6) Another concern pertains to the 35S::miP line utilized in Figures 3-5. The authors only presented results from one 35S::miP line, raising the possibility of T-DNA insertion disrupting an endogenous gene in the transgenic plant genome. It is essential to clarify how many individual T1 plants were generated and how many of them showed the same phenotype as the line used in the manuscript. Additionally, the use of the constitutive CaMV35S promoter could generate artifacts akin to neomorphic mutations. For example, the authors identified Cluster 1 genes that were only induced in 35S::miP, but not in t-athb2 or WT plants (Figure 3B); moreover, they found an overrepresentation of genes involved in root development in this cluster. This observation correlated well with the root phenotype of 35S::miP under the proximity shade (Figure 4D), in which the short-root phenotype was only observed in lines expressing 35S::miP. These data could be artifacts due to the constitutive expression of ATHB2miP in roots but didn't necessarily reflect the natural function of ATHB2miP.
(7) Furthermore, I seek clarification regarding the rationale behind employing different shade conditions, including deep shade, canopy shade, and proximity shade, and the significance of treating plants with these conditions. The results were challenging to interpret, and I have reservations about some statements made. The authors claimed that ATHB2 acts as a growth repressor in deep shade but a growth promoter in the canopy and proximity shade (Lines 366-368). However, it appears that regardless of the shade conditions, most mutant and transgenic lines were not significantly different from WT (Figure 4C). Additionally, the definition of proximity shade in this manuscript (R:FR = 0.06) differs from that in Roig-Villanova & Martinez-Garcia (Front. Plant Sci., 2016; R:FR, 0.5-0.3). Clarity on this disparity would be appreciated.
(8) In Figure 5, no statistical analyses were presented in Figure 5C. It remains unclear whether the differences observed are statistically significant. Moreover, the values appear quite similar among all three genotypes. Even if statistically significant, do these minor differences in Fe concentrations significantly impact plant physiology? Additionally, some statements related to Figure 5 do not align with the data presented. For instance, claims about longer hypocotyls in t-athb2, athb2∆, and atbh2∆LZ mutants compared to wild type under shade conditions on high iron media (lines 453-455) were not supported by the data in Figure 5D. Similarly, statements about the differences between mutants (lines 458-460) were not substantiated by the data.
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staging.theirstory.io staging.theirstory.io
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tickets. That we've logged so far. These ones in the inbox that look a little bit more bare are just drafts which are you know, somewhere where you can you can you can capture all the information about an issue. But it's not yet been formalized into an actual GitHub issue. Now we'll start with that. You know, if you came in here and you'd wanted just to log some issue or some idea, even you can just start t
2 comments on the same text
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KWoCurr 1 point2 points3 points 5 hours ago (0 children)I actually do use Dewey!
I'm with you on some of this, but let me play devil's advocate for a moment, so that we might hew closer to the question u/atomicnotes has posed:
If a Dewey Decimal Number is equivalent to a topic heading or subject, then what is the difference between using these subject/category/tag headings and forgoing the work of translating into a DC number (a task which is far less straightforward for those without a library science). If there is a onto to one and onto correspondence there should mathematically be no difference.
And how does one treat insightful material on geometry (516), for example, which comes from a book classified about political science (320-329)?
In a similar vein, why not use Otlet's Universal Decimal Classification which more easily allows for the admixture of topics as well as time periods?
Separately, I'll echo your valuable statement:
"I think everyone stumbles into a system of their own. I suspect the best practice here is the one that works for you!"
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Reply to the reviewers
We thank all reviewers for their thorough assessment and constructive comments. We are glad that the reviewers appreciate that our findings are of interest to the nuclear transport field and that our extension of the use of the RITE methodology can be a valuable tool for the further characterization of NPCs that differ in composition and potentially function. In response to the reviewers’ comments, we have revised the text to incorporate their suggestions and improve overall readability and clarity. Furthermore, we propose to perform a set of additional experiments to address the reviewers’ most important critiques. Below we list our response with the reviewer comments reprinted in dark grey and our response in blue for easier orientation. We have added numbering of the comments for easier orientation.
Many of the comments made by the reviewers have already been implemented, additional points will be addressed in a revised version of the manuscript as detailed below.
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
The authors extended the existing recombination-induced tag exchange (RITE) technology to show that they can image a subset of NPCs, improving signal-to-noise ratios for live cell imaging in yeast, and to track the stability or dynamics of specific nuclear pore proteins across multiple cell divisions. Further, the authors use this technology to show that the nuclear basket proteins Mlp1, Mlp2 and Pml39 are stably associated with "old NPCs" through multiple cell cycles. The authors show that the presence of Mlp1 in these "old NPCs" correlates with exclusion of Mlp1-positive NPCs from the nucleolar territory. A surprising result is that basket-less NPCs can be excluded from the non-nucleolar region, an observation that correlates with the presence of Nup2 on the NPC regardless of maturation state of the NPC. In support of the proposal that retention of NPCs via Mlp1 and Nup2 in non-nucleolar regions, simulation data is presented to suggest that basket-less NPCs diffuse faster in the plane of the nuclear envelope.
However, there are some points that do need addressing:
Major Points 1. Taking into account that the Nup2 result in Figure 4B forms the basis for one half of the proposed model in Figure 6 regarding the exclusion of NPCs from the nucleolar region of the NE, there is a relatively small amount of data in support of this finding and this proposed model. For example, the only data for Nup2 in the manuscript is a column chart in Figure 4B with no supporting fluorescence microscopy examples for any Nup2 deletion. Further, the Nup60 deletion mutant will have zero basket-containing NPCs, whereas the Nup2 deletion will be a mixture of basket-containing and basket-less NPCs. The only support for the localization of basket-containing NPCs in the Nup2 deletion mutant is through a reference "Since Mlp1-positive NPCs remain excluded from the nucleolar territory in nup2Δ cells (Galy et al., 2004), the homogenous distribution observed in this mutant must be caused predominantly by the redistribution of Mlp-negative NPCs into the nucleolar territory."
We have already added fluorescent images of the nup2d strain to figure 4A in the preliminary revision.
In addition, we will repeat the experiment from Galy et al. 2004 to test whether Mlp-positive NPCs are excluded from nucleoli in our hands as well.
Furthermore, we propose to carry out more experiments to pinpoint which domains of Nup2 contribute to nucleolar exclusion, which will provide more insight into the mechanism behind this effect. We propose to do this by analyzing NPC localization in mutants expressing truncations of Nup2 with deletions for individual domains as their only copy of Nup2. Regardless of whether we find a single domain of Nup2 responsible of a combinatorial action, this experiment will indicate a potential molecular mechanism for nucleolar exclusion.
- The authors could consider utilizing this opportunity to discuss their technological innovations in the context of the prior work of Onischenko et al., 2020. This work is referenced for the statement "RITE can be used to distinguish between old and new NPCs" Page 2, Line 43. However, it is not referenced for the statement "We constructed a RITE-cassette that allows the switch from a GFP-labelled protein to a new protein that is not fluorescently labelled (RITE(GFP-to-dark))" despite Onischenko et al., 2020 having already constructed a RITE-cassette for the GFP-to-dark transition. The authors could consider taking this opportunity to instead focus on their innovative approach to apply this technology to decrease the number of fluorescently-tagged NPCs by dilution across multiple cell divisions and to interpret this finding as a measure of the stability of nuclear pore proteins within the broader NPC.
We apologize for this imprecise citation. We have modified the text to indicate that our RITE cassette was previously used in two publications. It now reads: “We used a RITE-cassette that allows the switch from a GFP-labelled protein to a new protein that is not fluorescently labelled (RITE(GFP-to-dark)) (Onischenko et al., 2020, Kralt et al., 2022). “
- The authors could also consider taking this opportunity to discuss their results in the context of the Saccharomyces cerevisiae nuclear pore complex structures published e.g. in Kim et al., 2018, Akey et al., 2022, Akey et al., 2023 in which the arrangement of proteins in the nuclear basket is presented, and also work from the Kohler lab (Mészáros et al., 2015) on how the basket proteins are anchored to the NPC. There is additional literature that also might help provide some perspective to the findings in the current manuscript, such as the observation that a lesser amount of Mlp2 to Mlp1 observed is consistent with prior work (e.g. Kim et al., 2018) and that intranuclear Mlp1 foci are also formed after Mlp1 overexpression (Strambio-de-Castillia et al., 1999).
Following the reviewer’s suggestion, we extended our discussion of basket Nup stoichiometry and organization in the discussion section including several of the citations mentioned. At this point, we did not see a good way to incorporate discussion about the nuclear Mlp1 foci formed after Mlp1 overexpression. However, this observation is in line with the foci formed in cells lacking Nup60, suggesting that Mlp1 that cannot be incorporated into NPCs forms nuclear foci.
Minor Points 1. What is the "lag time" of the doRITE switching? Do the authors believe that it is comparable to the approximate 1-hour timeframe following beta-estradiol induction as shown previously in Chen et al. Nucleic Acids Research, Volume 28, Issue 24, 15 December 2000, Page e108, https://doi.org/10.1093/nar/28.24.e108
Our data (e.g. newRITE, Figure S3B) suggest that the switch occurs on a similar timeframe at
- The authors could consider a brief explanation of radial position (um) for the benefit of the reader, in Figures 1E (right panel) and 2B (right panel), perhaps using a diagram to make it easier to understand the X-axis (um).
To address this, we have now included a diagram and refer to it in the figure legend.
- In Figure 1G, would the authors consider changing the vertical axis title and the figure legend wording from "mean number of NPCs per cell" to "mean labeled NPC # per cell" to reflect that what is being characterized are the remaining GFP-bearing NPCs over time?
Thank you for spotting this inaccuracy. We have changed the label to “mean # of labeled NPCs per cell”.
- In Figure 2C, the magenta-labeled protein in the micrographs is not described in the figure or the legend.
As requested, a description has been added in figure and legend.
- In Figure S2A, there is an arrow indicating a Nup159 focus, but this is not described in the figure legend, as is done in Figure 2C.
A description has been added to the legend.
- In Figure S3C, the figure legend does not match the figure. Was this supposed to be designed like Figure 3C and is missing part of the figure? Or is the legend a typographical error?
We apologize for this error and thank the reviewer for spotting it. The legend has been corrected.
- In Figure S4B, the spontaneously recombined RITE (GFP-to-dark) Nup133-V5 appears in the western blot as equally abundant to pre-recombined Nup133-V5-GFP. In the figure legend, this is explained as cells grown in synthetic media without selection to eliminate cells that have lost their resistance marker from the population. In Cheng et al. Nucleic Acids Res. 2000 Dec 15; 28(24): e108, Cre-EBD was not active in the absence of B-estradiol, despite galactose-induced Cre-EBD overexpression. Would the authors be able to comment further on the Cre-Lox RITE system in the manuscript?
We note that also in the cited publication, cells are grown in the presence of selection to select (as stated in this publication) “against pre-excision events that occur because of low but measurable basal expression of the recombinase”. Although the authors report that spontaneous recombination is reduced with the b-estradiol inducible system (compared to pGAL expression control of the recombinase only), they show negligible spontaneous recombination only within a two-hour time window. Indeed, we also observe low levels of uninduced recombination on a short timeframe, but occasional events can become significant in longer incubation times (e.g. overnight growth) in the absence of selection. It should be noted that in our system, Cre expression is continuously high (TDH3-promoter) and not controlled by an inducible GAL promoter. We have added the information about the promoter controlling Cre-expression in the methods section.
- In Figure 6, the authors may want to consider inverting the flow of the cartoon model to start from the wild type condition and apply the deletion mutations at each step to "arrive" at the mutant conditions, rather than starting with mutant conditions and "adding back" proteins.
Following the suggestions of the reviewer, we have modified our model to more clearly represent the contributions of the different basket components.
Reviewer #1 (Significance (Required)):
Recent work has drawn attention to the fact that not all NPCs are structurally or functionally the same, even within a single cell. In this light, the work here from Zsok et al. is an important demonstration of the kind of methodologies that can shed light on the stability and functions of different subpopulations of NPCs. Altogether, these data are used to support an interesting and topical model for Nup2 and nuclear-basket driven retention of NPCs in non-nucleolar regions of the nuclear envelope.
We thank the reviewer for this positive assessment of our work.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
In this study, Zsok et al. develop innovative methods to examine the dynamics of individual nuclear pore complexes (NPCs) at the nuclear envelope of budding yeast. The underlying premise is that with the emergence of biochemically distinct NPCs that co-exist in the same cell, there is a need to develop tools to functionally isolate and study them. For example, there is a pool of NPCs that lack the nuclear basket over the nucleolus. Although the nature of this exclusion has been investigated in the past, the authors take advantage of a modification of recombination induced tag exchange (RITE), the slow turnover of scaffold nups, the closed mitosis of budding yeast, and extensive high quality time lapse microscopy to ultimately monitor the dynamics of individual NPCs over the nucleolus. By leveraging genetic knockout approaches and auxin-induced degradation with sophisticated quantitative and rigorous analyses, the authors conclude that there may be two mechanisms dependent on nuclear basket proteins that impact nucleolar exclusion. They also incorporate some computational simulations to help support their conclusions. Overall, the data are of the highest quality and are rigorously quantified, the manuscript is well written, accessible, and scholarly - the conclusions are thus on solid footing.
We thank the reviewer for this assessment.
Reviewer #2 (Significance (Required)):
I have no concerns about the data or the conclusions in this manuscript. However, the significance is not overly clear as there is no major conceptual advance put forward, nor is there any new function suggested for the NPCs over nucleoli. As NPCs are immobile in metazoans, the significance may also be limited to a specialized audience.
We respectfully disagree with this assessment. It is becoming increasingly clear that NPC variants are also present in other model systems. We characterize the interaction between conserved nuclear components, the NPC, the nucleolus and chromatin. While the specific architecture of the nucleus varies between species, many of these interactions are conserved. For example, Nup50, the homologue of Nup2, interacts with chromatin also in other systems including mammalian cells and thus may contribute to regulating the interplay between the nuclear basket and adjoining chromatin. Furthermore, our work demonstrates the use of a novel approach in the application of RITE that can be useful for other researchers in the field of NPC biology and beyond. For example, doRITE could be applied to study the properties of aged NPCs in the context of young cells. In the revised manuscript, we attempt to better highlight and discuss the conceptual advances of our manuscript.
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
The manuscript of Zsok et al. describes the role of nuclear basket proteins in the distribution and mobility of nuclear pore complexes in budding yeast. In particular, the authors showed that the doRITE approach can be used for the analysis of stable and dynamically associated NUPs. Moreover, it can distinguish individual NUPs and follow the inheritance of individual NPCs from mother to daughter cells. The author's findings highlight that Mlp1, Mlp2, and Pml39 are stably associated with the nuclear pore; deletion of Mlp1-Mlp2 and Nup60 leads to the higher NPC density in the nucleolar territory; and NPCs exhibit increased mobility in the absence of the nuclear basket components.
The manuscript contains most figures supporting the data, and data supports the conclusions. However, authors need to include better explanations for figures in the text and figure legends. Lack of detailed explanation can pose challenges for non-experts. In addition, the authors jump over figures and shuffle them through the manuscript, which disrupts the flow and coherence of the manuscript.
We thank the reviewer for pointing this out. We have modified the figure legends throughout the manuscript in an attempt to make them more accessible to the reader. In addition, we will revise the figure order and text as suggested to improve the flow of the manuscript.
Major comments: 1) The nuclear basket contains Nup1, Nup2, Nup60, Mlp1, and Mlp2 in yeast. Nup60 works as a seed for Mlp1/Mlp2 and Nup2 recruitment and plays a key role in the assembly of nuclear pore basket scaffold (PMID: 35148185). Logically, the authors focused primarily on Nup60 in the current manuscript. However, NUP153 has another ortholog of yeast - Nup1, which has not been studied in this work. I recommend adjusting the title of the manuscript to: Nup60 and Mlp1/Mlp2 regulate the distribution and mobility of nuclear pore complexes in budding yeast. I also suggest discussing why work on Nup1 was not included/performed in the manuscript.
We have changed the title to “Nuclear basket proteins regulate the distribution and mobility of nuclear pore complexes in budding yeast”. We think that this better captures the essence of our manuscript than listing all four proteins (Mlp1/2, Nup60 and Nup2) in the title.
We initially focused on the network that is involved in Mlp1/2 interaction at the NPC. However, we agree that it would be interesting to test, whether Nup1 plays a role in the analyzed processes as well. Since Nup1 is essential in our yeast background, we will use auxin-inducible degradation of Nup1 to test its involvement in NPC distribution.
2) Figure 2B: I suggest choosing a more representative image for Pml39. It looks not like a stable component but rather dynamic as NUP60 or Gle1 based on figure showed in Figure 2B.
Due to its lower copy number, Pml39 is much more difficult to visualize than the other Nups. To guide the reader, we have now added arrow heads to point to remaining Pml39 foci at the 14 hour timepoint. The 11 hour time point most clearly show that Pml39 is less dynamic than other Nups such as Nup116, Nup60 or Gle1. At this time point, clear dots for Pml39 can be detected, while e.g. Nup116 in the same figure exhibits a more distributed signal and the signal for Nup60 and Gle1 is no longer visible. We will describe this more clearly in our revised manuscript as well.
3) Depletion of AID-tagged proteins needs to be supported by Western blot analysis with protein-specific antibodies, and PCR results should be included in supplementary data to demonstrate the homozygosity of the strains.
The correct genomic tagging of the depleted proteins by AID was confirmed by PCR. We will include this PCR analysis in the supplemental data. Please note that we are working with haploid yeast cells. Therefore, all strains only carry a single copy of the genes. Unfortunately, we do not have protein-specific antibodies against the depleted proteins. However, the Mlp1-mislocalization phenotype demonstrates that depletion of Nup60 is successful and the depletion strain for PolII depletion was used and characterized previously (PMID: 31753862, PMID: 36220102).
4) Figure 5B: Snapshots of images from the movie are required. There are no images, only quantifications.
We have replaced the supplemental movie with a movie showing the detection by Trackmate as well as overlaid tracks. As requested, a snapshot of this movie was inserted in figure 5B. We have also moved the example tracks from the supplement to the main figure. Furthermore, we will deposit the tracking dataset in the ETH Research Collection to make it available to the community.
5) Description of figure legends is more technical than supporting/explaining the figure. For example, below my suggestions for Figure 1D. Please, consider more detailed explanation for other figures. (D) Left: Schematic of the RITE cassette. NUP of interest is tagged with V5 tag and eGFP fluorescent protein where LoxP sites flank eGFP. Before the beta-estradiol-induced recombination, the old NPCs are marked with eGFP signal, whereas new NPCs lack an eGFP signal after the recombination. ORF: open reading frame; V5: V5-tag; loxP: loxP recombination site; eGFP: enhanced green fluorescent protein. Right: doRITE assay schematic of stable or dynamic Nup behavior over cell divisions in yeast after the recombination.
We have modified the figure legends throughout the manuscript to make them more explanatory and helpful for the reader.
In addition, I recommend highlighting the result in the title of the figures. Please, re-consider titles for Figure S3.
We have revised the title for Figure S3 to state a result. It now reads: “Mlp1 truncations localize preferentially to non-nucleolar NPCs.”
Minor: i) P.1 Line 31. Extra period symbol before the "(Figure 1A)".
Fixed
ii) P.2 Line 10. Inconsistent writing of PML39 and MLP1. Both genes are capitalized. The same for P.4 Line 16. In some cases all letters are capitalized in other only the first one.
We are following the official yeast gene nomenclature by spelling gene names in italicized capitals and protein names with only the first letter capitalized. We are sorry that this can be confusing for readers more familiar with other model systems but we adhere to the accepted yeast nomenclature standards.
iii) P.2 Line 18-22. The sentence is too long and hard to read. I recommend splitting it into two sentences.
We agree and have fixed this.
iv) P.2-3 Line 46-47. The sentence is unclear. Suggestion: We expected that successive cell divisions would dilute the signal of labelled and stably associated with the NPC nucleoporins. By contrast, ...
We have modified the sentence to read: “When tagging a Nup that stably associates with the NPC, we expected that successive cell divisions would dilute labelled NPCs by inheritance to both mother and daughter cells leading to a low density of labelled NPCs. By contrast,…”
v) P.4 Line 17-21. Please, consider adding extra information and clarifying lines 19-21. For example, in Line 19 Figure 2B you can add that the reader needs to compare row 1 and row 4.
Thank you, we have fixed this as suggested.
vi) P. 5 Line 15. When a number begins a sentence, that number should always be spelled out. You can pe-phrase the sentence to avoid it. Also, I recommend adding an explanation/hypothesis of why new NPCs are less frequently detected in nucleolar territory.
We have formatted the text. Interestingly, new NPCs are more frequently detected in the nucleolar territory. We have reformulated this section to make it clearer, also in response to the next comment.
vii) P.5 Line 17-22. I recommend re-phrasing these two sentences. Logically, it is clear that Mlp1/Mlp2 loss mimics "old NPCs" to look more like "new NPCs", and for that reason, they are more frequently included in the nucleolar territory, but it is not clear when you read these two sentences from the first time.
We have reformulated this section to make it clearer.
viii) P6. Line 16. No figure supporting data on graph (Figure 3B).
We have added fluorescent images of the nup2d strain to figure 4A.
ix) P.7 Line 10-13. The sentence is unclear.
We have shortened the sentence and moved part of the content to the discussion in the next paragraph.
x) P.13,14 etc. If 0h timepoint has been used for normalization, why is it present on the graph?
The 0h timepoint is shown for comparison and to illustrate the standard deviation in the data.
xi) P.15. Line 32-33. There is no image here. Potentially wrong description of the figure.
Thank you for spotting this. This was fixed.
xii) Figures: - Inconsistent labeling of figures. For example, Fig.1, Fig.1S, Figure 2 etc.
Thank you, this has been corrected.
- Inconsistent labeling of figures. For example, Fig.1 G "mean number of NPCs per cell" - no capitalization of the first letter. Fig.1S "Fraction in population" is capitalize d. In general, titles of axis should be capitalized.
Thank you for spotting this. This was fixed.
Suggestions for Figure 1D and Figure 6 are attached as a separate file.
We thank the reviewer for their suggestions to improve these figures. We have taken their recommendation and revised the figures accordingly (see also response to reviewer 1, minor point 8).
Reviewer #3 (Significance (Required)):
Zsok et al. used the recombination-induced tag exchange (RITE) approach, which is an interesting and powerful method to follow individual NUPs over time with respect to their localization and abundance. This approach has been used before in PMID: 36515990 to distinguish pre-existing and newly synthesized Nup2 populations and has been extended to other basket NUPs in this work. Using this method, the authors support the earlier data on basket nucleoporins and highlight new insights on how basket nucleoporins regulate NPCs distribution and mobility. Overall, the manuscript provides new details on the stability of nucleoporins in yeast and how these data align with the mass spectrometry and FRAP data performed earlier in other studies. The limitation of this study is the absence of data on Nup1. It was unclear why these data were not present. Additional data can be included on the dynamics of Pml39, for example, using the FRAP method. The dynamic of Pml39 at the pore was shown only using the doRITE method.
As suggested, we propose to test whether Nup1 influences NPC organization (see also above). Unfortunately, we are not able to provide orthologous data for the dynamics of Pml39. As we have discussed in the manuscript, FRAP is not suitable for the analysis of the dynamics of most nucleoporins in yeast due to the high lateral mobility of NPCs in the nuclear envelope and has previously generated misleading results for Mlp1. Furthermore, the low expression levels of Pml39 will make it difficult to obtain reliable FRAP curves for this protein. We therefore do not think that adding FRAP experiments with Pml39 will provide valuable insight.
However, in addition to the Pml39 doRITE result itself, our observation that the Pml39-dependent pool of Mlp1 exhibits stable association with the NPC supports the interpretation of Pml39 as a stable protein as well.
In general, this study represents a unique research study of basic research on nuclear pore proteins that will be of general interest to the nuclear transport field.
Field of expertise: nuclear-cytoplasmic transport, nuclear pore, inducible protein degradation. I do not have sufficient expertise in ExTrack.
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Referee #3
Evidence, reproducibility and clarity
The manuscript of Zsok et al. describes the role of nuclear basket proteins in the distribution and mobility of nuclear pore complexes in budding yeast. In particular, the authors showed that the doRITE approach can be used for the analysis of stable and dynamically associated NUPs. Moreover, it can distinguish individual NUPs and follow the inheritance of individual NPCs from mother to daughter cells. The author's findings highlight that Mlp1, Mlp2, and Pml39 are stably associated with the nuclear pore; deletion of Mlp1-Mlp2 and Nup60 leads to the higher NPC density in the nucleolar territory; and NPCs exhibit increased mobility in the absence of the nuclear basket components.
The manuscript contains most figures supporting the data, and data supports the conclusions. However, authors need to include better explanations for figures in the text and figure legends. Lack of detailed explanation can pose challenges for non-experts. In addition, the authors jump over figures and shuffle them through the manuscript, which disrupts the flow and coherence of the manuscript.
Major comments:
- The nuclear basket contains Nup1, Nup2, Nup60, Mlp1, and Mlp2 in yeast. Nup60 works as a seed for Mlp1/Mlp2 and Nup2 recruitment and plays a key role in the assembly of nuclear pore basket scaffold (PMID: 35148185). Logically, the authors focused primarily on Nup60 in the current manuscript. However, NUP153 has another ortholog of yeast - Nup1, which has not been studied in this work. I recommend adjusting the title of the manuscript to: Nup60 and Mlp1/Mlp2 regulate the distribution and mobility of nuclear pore complexes in budding yeast. I also suggest discussing why work on Nup1 was not included/performed in the manuscript.
- Figure 2B: I suggest choosing a more representative image for Pml39. It looks not like a stable component but rather dynamic as NUP60 or Gle1 based on figure showed in Figure 2B.
- Depletion of AID-tagged proteins needs to be supported by Western blot analysis with protein-specific antibodies, and PCR results should be included in supplementary data to demonstrate the homozygosity of the strains.
- Figure 5B: Snapshots of images from the movie are required. There are no images, only quantifications.
- Description of figure legends is more technical than supporting/explaining the figure. For example, below my suggestions for Figure 1D. Please, consider more detailed explanation for other figures. (D) Left: Schematic of the RITE cassette. NUP of interest is tagged with V5 tag and eGFP fluorescent protein where LoxP sites flank eGFP. Before the beta-estradiol-induced recombination, the old NPCs are marked with eGFP signal, whereas new NPCs lack an eGFP signal after the recombination. ORF: open reading frame; V5: V5-tag; loxP: loxP recombination site; eGFP: enhanced green fluorescent protein. Right: doRITE assay schematic of stable or dynamic Nup behavior over cell divisions in yeast after the recombination.
In addition, I recommend highlighting the result in the title of the figures. Please, re-consider titles for Figure S3.
Minor:
P.1 Line 31. Extra period symbol before the "(Figure 1A)".
P.2 Line 10. Inconsistent writing of PML39 and MLP1. Both genes are capitalized. The same for P.4 Line 16. In some cases all letters are capitalized in other only the first one.
P.2 Line 18-22. The sentence is too long and hard to read. I recommend splitting it into two sentences.
P.2-3 Line 46-47. The sentence is unclear. Suggestion: We expected that successive cell divisions would dilute the signal of labelled and stably associated with the NPC nucleoporins. By contrast, ...
P.4 Line 17-21. Please, consider adding extra information and clarifying lines 19-21. For example, in Line 19 Figure 2B you can add that the reader needs to compare row 1 and row 4.
P. 5 Line 15. When a number begins a sentence, that number should always be spelled out. You can pe-phrase the sentence to avoid it. Also, I recommend adding an explanation/hypothesis of why new NPCs are less frequently detected in nucleolar territory.
P.5 Line 17-22. I recommend re-phrasing these two sentences. Logically, it is clear that Mlp1/Mlp2 loss mimics "old NPCs" to look more like "new NPCs", and for that reason, they are more frequently included in the nucleolar territory, but it is not clear when you read these two sentences from the first time.
P6. Line 16. No figure supporting data on graph (Figure 3B).
P.7 Line 10-13. The sentence is unclear.
P.13,14 etc. If 0h timepoint has been used for normalization, why is it present on the graph?
P.15. Line 32-33. There is no image here. Potentially wrong description of the figure.
Figures:
- Inconsistent labeling of figures. For example, Fig.1, Fig.1S, Figure 2 etc.
- Inconsistent labeling of figures. For example, Fig.1 G "mean number of NPCs per cell" - no capitalization of the first letter. Fig.1S "Fraction in population" is capitalized. In general, titles of axis should be capitalized.
Suggestions for Figure 1D and Figure 6 are attached as a separate file.
Significance
Zsok et al. used the recombination-induced tag exchange (RITE) approach, which is an interesting and powerful method to follow individual NUPs over time with respect to their localization and abundance. This approach has been used before in PMID: 36515990 to distinguish pre-existing and newly synthesized Nup2 populations and has been extended to other basket NUPs in this work. Using this method, the authors support the earlier data on basket nucleoporins and highlight new insights on how basket nucleoporins regulate NPCs distribution and mobility. Overall, the manuscript provides new details on the stability of nucleoporins in yeast and how these data align with the mass spectrometry and FRAP data performed earlier in other studies. The limitation of this study is the absence of data on Nup1. It was unclear why these data were not present. Additional data can be included on the dynamics of Pml39, for example, using the FRAP method. The dynamic of Pml39 at the pore was shown only using the doRITE method.
In general, this study represents a unique research study of basic research on nuclear pore proteins that will be of general interest to the nuclear transport field.
Field of expertise: nuclear-cytoplasmic transport, nuclear pore, inducible protein degradation. I do not have sufficient expertise in ExTrack.
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Referee #2
Evidence, reproducibility and clarity
In this study, Zsok et al. develop innovative methods to examine the dynamics of individual nuclear pore complexes (NPCs) at the nuclear envelope of budding yeast. The underlying premise is that with the emergence of biochemically distinct NPCs that co-exist in the same cell, there is a need to develop tools to functionally isolate and study them. For example, there is a pool of NPCs that lack the nuclear basket over the nucleolus. Although the nature of this exclusion has been investigated in the past, the authors take advantage of a modification of recombination induced tag exchange (RITE), the slow turnover of scaffold nups, the closed mitosis of budding yeast, and extensive high quality time lapse microscopy to ultimately monitor the dynamics of individual NPCs over the nucleolus. By leveraging genetic knockout approaches and auxin-induced degradation with sophisticated quantitative and rigorous analyses, the authors conclude that there may be two mechanisms dependent on nuclear basket proteins that impact nucleolar exclusion. They also incorporate some computational simulations to help support their conclusions. Overall, the data are of the highest quality and are rigorously quantified, the manuscript is well written, accessible, and scholarly - the conclusions are thus on solid footing.
Significance
I have no concerns about the data or the conclusions in this manuscript. However, the significance is not overly clear as there is no major conceptual advance put forward, nor is there any new function suggested for the NPCs over nucleoli. As NPCs are immobile in metazoans, the significance may also be limited to a specialized audience.
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Referee #1
Evidence, reproducibility and clarity
The authors extended the existing recombination-induced tag exchange (RITE) technology to show that they can image a subset of NPCs, improving signal-to-noise ratios for live cell imaging in yeast, and to track the stability or dynamics of specific nuclear pore proteins across multiple cell divisions. Further, the authors use this technology to show that the nuclear basket proteins Mlp1, Mlp2 and Pml39 are stably associated with "old NPCs" through multiple cell cycles. The authors show that the presence of Mlp1 in these "old NPCs" correlates with exclusion of Mlp1-positive NPCs from the nucleolar territory. A surprising result is that basket-less NPCs can be excluded from the non-nucleolar region, an observation that correlates with the presence of Nup2 on the NPC regardless of maturation state of the NPC. In support of the proposal that retention of NPCs via Mlp1 and Nup2 in non-nucleolar regions, simulation data is presented to suggest that basket-less NPCs diffuse faster in the plane of the nuclear envelope.
However, there are some points that do need addressing:
Major Points
- Taking into account that the Nup2 result in Figure 4B forms the basis for one half of the proposed model in Figure 6 regarding the exclusion of NPCs from the nucleolar region of the NE, there is a relatively small amount of data in support of this finding and this proposed model. For example, the only data for Nup2 in the manuscript is a column chart in Figure 4B with no supporting fluorescence microscopy examples for any Nup2 deletion. Further, the Nup60 deletion mutant will have zero basket-containing NPCs, whereas the Nup2 deletion will be a mixture of basket-containing and basket-less NPCs. The only support for the localization of basket-containing NPCs in the Nup2 deletion mutant is through a reference "Since Mlp1-positive NPCs remain excluded from the nucleolar territory in nup2Δ cells (Galy et al., 2004), the homogenous distribution observed in this mutant must be caused predominantly by the redistribution of Mlp-negative NPCs into the nucleolar territory."
- The authors could consider utilizing this opportunity to discuss their technological innovations in the context of the prior work of Onischenko et al., 2020. This work is referenced for the statement "RITE can be used to distinguish between old and new NPCs" Page 2, Line 43. However, it is not referenced for the statement "We constructed a RITE-cassette that allows the switch from a GFP-labelled protein to a new protein that is not fluorescently labelled (RITE(GFP-to-dark))" despite Onischenko et al., 2020 having already constructed a RITE-cassette for the GFP-to-dark transition. The authors could consider taking this opportunity to instead focus on their innovative approach to apply this technology to decrease the number of fluorescently-tagged NPCs by dilution across multiple cell divisions and to interpret this finding as a measure of the stability of nuclear pore proteins within the broader NPC.
- The authors could also consider taking this opportunity to discuss their results in the context of the Saccharomyces cerevisiae nuclear pore complex structures published e.g. in Kim et al., 2018, Akey et al., 2022, Akey et al., 2023 in which the arrangement of proteins in the nuclear basket is presented, and also work from the Kohler lab (Mészáros et al., 2015) on how the basket proteins are anchored to the NPC. There is additional literature that also might help provide some perspective to the findings in the current manuscript, such as the observation that a lesser amount of Mlp2 to Mlp1 observed is consistent with prior work (e.g. Kim et al., 2018) and that intranuclear Mlp1 foci are also formed after Mlp1 overexpression (Strambio-de-Castillia et al., 1999).
Minor Points
- What is the "lag time" of the doRITE switching? Do the authors believe that it is comparable to the approximate 1-hour timeframe following beta-estradiol induction as shown previously in Chen et al. Nucleic Acids Research, Volume 28, Issue 24, 15 December 2000, Page e108, https://doi.org/10.1093/nar/28.24.e108
- The authors could consider a brief explanation of radial position (um) for the benefit of the reader, in Figures 1E (right panel) and 2B (right panel), perhaps using a diagram to make it easier to understand the X-axis (um).
- In Figure 1G, would the authors consider changing the vertical axis title and the figure legend wording from "mean number of NPCs per cell" to "mean labeled NPC # per cell" to reflect that what is being characterized are the remaining GFP-bearing NPCs over time?
- In Figure 2C, the magenta-labeled protein in the micrographs is not described in the figure or the legend.
- In Figure S2A, there is an arrow indicating a Nup159 focus, but this is not described in the figure legend, as is done in Figure 2C.
- In Figure S3C, the figure legend does not match the figure. Was this supposed to be designed like Figure 3C and is missing part of the figure? Or is the legend a typographical error?
- In Figure S4B, the spontaneously recombined RITE (GFP-to-dark) Nup133-V5 appears in the western blot as equally abundant to pre-recombined Nup133-V5-GFP. In the figure legend, this is explained as cells grown in synthetic media without selection to eliminate cells that have lost their resistance marker from the population. In Cheng et al. Nucleic Acids Res. 2000 Dec 15; 28(24): e108, Cre-EBD was not active in the absence of B-estradiol, despite galactose-induced Cre-EBD overexpression. Would the authors be able to comment further on the Cre-Lox RITE system in the manuscript?
- In Figure 6, the authors may want to consider inverting the flow of the cartoon model to start from the wild type condition and apply the deletion mutations at each step to "arrive" at the mutant conditions, rather than starting with mutant conditions and "adding back" proteins.
Significance
Recent work has drawn attention to the fact that not all NPCs are structurally or functionally the same, even within a single cell. In this light, the work here from Zsok et al. is an important demonstration of the kind of methodologies that can shed light on the stability and functions of different subpopulations of NPCs. Altogether, these data are used to support an interesting and topical model for Nup2 and nuclear-basket driven retention of NPCs in non-nucleolar regions of the nuclear envelope.
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inst-fs-iad-prod.inscloudgate.net inst-fs-iad-prod.inscloudgate.netJoyful1
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“Close your mouth, señora,” Luzia said gently as she gathered her skirts.“You look like you’re waiting for someone to push a cake into it.”
tag team fr
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Referee #4
Evidence, reproducibility and clarity
Summary:
In this work, Zemlianski and colleagues exploit S. pombe mutations responsible for catastrophic mitoses, in particular those leading to a cut / cut-like phenotypes, whereby cytokinesis takes place without proper DNA segregation, trapping DNA molecules by septum formation in between the two separating cells. The work builds on the team's previous observation that these defects can be alleviated when cells are grown in a nitrogen-rich medium, and motivate their efforts to understand this better. The manuscript is written in a concise, neat and informative manner, and the results are presented clearly, with consistence in the format and the style all along. The analyses appear to have been, in general, conducted under the best standards. The findings are important and the data are of good quality. I have, however, important concerns that will be detailed below, and which, as I hope will be made clear, question the pertinence of including "TOR signaling" in the title, and making a distinction between "good" and "poor" nitrogen sources in the abstract.
Major comments:
Results
The conclusion that the phenotype is suppressed by "good" but not "poor" nitrogen sources is not sufficiently supported. First, this interpretation is based on comparing only two or three sources of each type; Second, the "good" source glutamate needed to be raised for it to have a significant effect; 3) there is a strange datum, as Glu 100 mM in Graph 1D looks exactly the same as Glu 50 mM in Graph 1E, I guess there is a mistake in the plotting; 4) and, more important, the fact that the authors had the nice initiative of reproducing their YES medium experiments for every graph led to the inevitable fact that slightly different values were obtained every time, which is normal. While the values yield very similar data for panels 1B, 1C and even 1D, the frequency of catastrophic mitoses for the cbf11 mutant in YES in panel 1E is much lower than in panel Figure 1B, for example. This has the consequence of making the suppression obtained when adding 'poor' sources, such as proline or uracil, non-significantly different. Thus, the authors conclude that 'poor' nitrogen sources are not good at suppressing the phenotype. I suggest that the authors pool all their YES data (they will have 12 repeats of their experiment) and plot, in a single graph, all the other treatments. By performing the analyses again, using the appropriate statistical test for that, perhaps they will have a surprise. After which, the question is, is it so important to put the emphasis on whether the source is good or poor? The incontestable observation is that, in general, there is clear trend of suppression of the phenotype.
In Figure 2, images should be shown as an example of what was seen, what was quantified, how the "decrease in nuclear cross-section area" looked like indeed.
Also, important for Figure 2, the authors used the nuclear cross-section area as a readout for nuclear envelope expansion versus shrinkage. For that, they did not use a fluorescent marker for the nuclear envelope that is continuous, but a nucleoporin (Cut11-GFP). In my experience, nucleoporins being discontinuously distributed throughout the nuclear envelope, the area encompassed by the signal may be underestimated in the event of a strong nuclear envelope deformation, as I have tried to illustrate in the scheme below: I WILL SEND THE SCHEME BY MAIL TO THE EDITOR, AS I CANNOT COPY-PASTE IT IN THE SYSTEM BOX Given that the photos from which the data were retrieved have not been shown, I cannot at present judge whether the use of a nuclear envelope marker providing continuous signals is absolutely necessary or not, and whether this consideration will affect (or not at all) the conclusions.
The authors do not seem to comment or pay any attention to a very crucial result they obtain: the addition of ammonium to the WT strain has the effect of also restricting the nuclear cross-section area. They indeed say in their text "we did not observe any differences between cultures grown with or without ammonium supplementation (Fig.2)". I guess they refer here to the cbf11 mutant, in which case the sentence is true (although unfair to the WT). But by neglecting that the supplementation with ammonium had the power of reducing the cross-section area of WT nuclei, they are misled (or misleading) in their interpretation. The same, although milder, is true for Figure 5C, where the addition of ammonium to the WT culture does not alter the median value of prophase + metaphase duration, however has the virtue of very much rendering sharp (less scattered) the population of values, suggesting that the accuracy / control of the process is enhanced. What does this mean? I think it should be carefully thought about and considered as a whole.
In the same line as above, the authors omit the RNA-seq analysis concerning the treatment of the WT with ammonium (Figure 3). This is very important to understand the standpoint of what this treatment elicits. It would also help unravel the observations I mentioned above that the authors did not assess in their descriptions. Also regarding Figure 3, it is completely obscure why the authors decided to show the genes on the right axis, and not others. Knowing how vast the lipid pathways are, there are likely many other hits that could be relevant. A particular thought goes for the proteins in charge of filling lipid droplets, such as sterol- and fatty acid-esterifying enzymes. Unless a very justified reason is provided, the choice at present seems arbitrary and it would be better to show a more unbiased data representation.
In the same vein, related to the effect of ammonium onto the WT, in Figure S1 (I want to congratulate the authors for showing their 3 experimental replicates), the results very neatly show that ammonium supplementation to the WT leads to a neat and reproducible increase in TAG, a fact on which the authors do not comment. In the mutant, irrespective of ammonium presence or absence, a huge increase in squalene and steryl esters (SE) are seen. I think the work would benefit from actually quantifying the intensity of these bands and thus materializing this in the form of values. TAG, squalene and SE are all neutral lipids, and are all stored within LD to prevent lipotoxicity if accumulated in the endoplasmic reticulum. While ammonium elicits strong TAG accumulation in the WT, this is not the case in the mutant, likely because the massive occupation of LD storage capacity is overwhelmed with squalene and SE. Could this have something to do with the suppression they are studying?
In the section of results where the authors comment the TLC analysis, they write "suggesting failed coordination between sterol and TAG lipid metabolism pathway". As it stands, the sentence is rather devoid of real meaning and may be even misleading, when considering what I wrote before.
My biggest concern has to do with the very last part, when they explore the implications of TOR:
- First, all the data presented in the two concerned panels of Figure 7 (B and C) and of Figure S3 lack the values obtained for the single mutants with which cbf11 was combined. This is not acceptable from a genetic point of view, and may prevent us from having important information. For example: if the authors were right that Tor2/TORC1 is ensuring successful progression through closed mitosis (last sentence of results), then one would predict that the tor2-S allele leads to an increase, already per se, of the frequency of catastrophic mitoses. However, at present, I cannot check that.
- the authors turn to use a ∆ssp2 mutant to "increase Tor2 activity". However, this is a pleiotropic strategy, as AMP-kinase is the major sensor and responder to energy depletion, frequently triggered by glucose shortage, thus I am not sure the effects associated to its absence can be unequivocally be ascribed to a Tor2 raise.
- there is a counterintuitive observation: rapamycin, which mimics nitrogen shortage, has the same effect than ammonium supplementation. This is strangely bypassed in the discussion, where the authors wrote "we showed increased mitotic fidelity in cbf11 cells when the stress-response branch of the TOR network was suppressed, either by ablation of Tor1/TORC2 or by boosting the activity of the pro-growth Tor2/TORC1 branch. These data are in agreement with previous findings that Tor2/TORC1 inhibition mimics nitrogen starvation".
- last, and irrespective of what was said above, the authors conclude that the phenotype suppression is due to "a role for Tor2/TORC1 in ensuring successful progression through mitosis". If, as stated by the authors, Tor1/TORC2 absence not only abrogates Tor1/TORC2 activity, but it simultaneously raises Tor2/TORC1 activity, and if reciprocally Tor2/TORC1 increased activity concurs with Tor1/TORC2 attenuation, it cannot therefore be discerned if the suppression is due to Tor2/TORC1 raise or to Tor1/TORC2 dampening.
Discussion
The authors invoke that TOR controls lipin, despite what they go on to dismiss the link between TOR and lipids by saying "we did not observe any major changes in phospholipid composition when cells were grown in ammonium-supplemented YES medium compared to plain YES (Figure S2)", with this reinforcing their conclusion that ammonium does not suppress lipid-related cut mutants through directly correcting lipid metabolism defects. While I agree with that reasoning, I invoke again that they nevertheless neglected the clear change observed in their three replicates (Figure S2) that ammonium addition to WT cells strongly increases the amount of TAG (esterified fatty acids). Since lipin activity promotes DAG formation, which then leads to TAG accumulation, this aspect should not be neglected.
The emphasis on TOR, which expands several paragraphs of the Discussion, should be revisited if the evidence provided for this part of the data is not reinforced.
To finish, if I may provide some personal thoughts that may be useful for the authors, I would first remind that TAG storage prevents the channeling of phosphatidic acid towards novel phospholipid synthesis thus antagonizes NE expansion, which agrees with their neglected observation for the WT in Figure 2A. The antagonization of NE expansion can be achieved through autophagy (DOI 10.1038/s41467-023-39172-3; DOI 10.1177/25152564231157706), and indeed rapamycin addition (a very potent inducer of autophagy) also suppressed the cut phenotype (Figure 7A). What is more, in S. cerevisiae, autophagy has been shown as important to transition through mitosis conveniently and to prevent mitotic aberrations (DOI 10.1371/journal.pgen.1003245), and to impose a "genome instability" intolerance threshold by restricting NE expansion (DOI 10.1177/25152564231157706). In the first mentioned work, the authors proposed that autophagy may help raising aminoacid levels, which could assist cell cycle progression. This would have the virtue of reconciling the otherwise counterintuitive observation of the authors that rapamycin, which mimics nitrogen shortage, has the same effect than ammonium supplementation. It could be that ammonium supplementation mimics the downstream signal of a complex cascade initiated by actual aminoacid shortage, known to elicit autophagy-like processes (thus explaining why TAG raise, why the NE does not expand), and may culminate with launching a program for more accurate mitosis and genome segregation. In further support, TORC1 inhibition (as elicited by +rapamycin) is a central node that integrates multiple cues, not only nitrogen availability, but also carbon shortage (DOI 10.1016/j.molcel.2017.05.027), and even genetic instability cues (DOI 10.1016/j.celrep.2014.08.053), perhaps helping unravel why ammonium (via TOR) suppresses very diverse cut mutants, irrespective of whether they stem from lipid or chromatid cohesion deficiencies. These previous works should be considered by the authors.
Minor
There was no speculation about why the suppressions are partial.
Reference 15, cited in the text, is absent from the references list.
An explanation of which statistical tests were chosen and why they were chosen would be necessary.
In particular, for the analyses performed for Figure 5, one-way ANOVA should be applied instead of several t-tests.
A small section in M&M about how data in general was acquired, quantified, plotted and analyzed would be appropriate.
In the discussion, the sentence "this could mean that the signaling of availability of a good nitrogen source is by itself more important for mitotic fidelity than the actual physical presence of the nutrients" is a rather void sentence. Because, from the point of view of how a cell "works", the signal is important for the basic reason that it is supposed to represent the actual real cue eliciting it.
In the second part of Results, when the phenotype of cbf11 mutants concerning LD is mentioned, the authors said "aberrant LD content". It would be good if they can mention already at this stage which type of aberration this was: more LD? less LD? bigger? smaller?
What is the difference between the two SE bands in Figure S2? What exactly does SE-1 and SE-2 mean?
In Figure 2, the two graphs, presented side by side, would be more easily comparable if they could be plotted with the same y-axis scale.
In Figure 1A, it would be useful for non-specialists of this phenotype and non-pombe readers to show a control of how it looks to be "normal".
Referees cross-commenting
Overall, there is a striking consensus on the need to either address experimentally or remove the emphasis put on the TOR/mitotic fidelity connection, and of clarifying the counter-intuitive notions associated to the results obtained with rapamycin. Also, the need for revisiting / improving / justifying the means by which nuclear envelope deformation is assessed has been raised at least twice. I therefore guess that the common guidelines for improving this manuscript are clearly established.
Significance
In view of all of the above, my feeling is that the authors have put the accent on the TOR message, which is weak, while they have less put the accent on very strong and elegant findings they do: The authors discover that the suppression of cut(-like) mutant phenotype by addition of NH4 is not due to a correction in lipid metabolism defects, suggesting that the effect is indirect. In support, cut-like mutants whose molecular defect stems from lipid-unrelated defects are also suppressed by ammonium addition. What is more, the authors refine the type of cut-like mutants susceptible of being "corrected" by ammonium addition, finding a "novel definition of cuts" that invoke a temporal rule. This important observation has relevant implications:
- the long-standing interpretation (commented by the authors) that lipid-related cut mutants are defective because of insufficient synthesis of lipids to be able to grow their nuclear envelope membranes seems now inappropriate in light of their data;
- this has the immediate implication that perhaps the importance of nitrogen supplementation for accurate mitosis is no longer a fact that may apply only to (yeast) organisms performing closed mitosis, which may broaden the implications of their finding substantially;
- the nature of the temporal ruler they discover that makes defects appearing early susceptible of being suppressed by nitrogen supplementation deserves analysis in further works, thus opening an immediate perspective.
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按照文本解析格式提供翻译,德语句子 "willst du denn deinen freien Tag nicht mit uns verbringen" 可以翻译成:
你难道不想和我们一起度过你的休息日吗?
单词分解与翻译: - willst : 动词“wollen”的第二人称单数现在时态,意为“想要”。 - du : (你),代词,第二人称单数主格形式。 - denn : (难道),副词,常用来加强语气,表达惊讶、疑问或期待。 - deinen : (你的),形容词性物主代词,这里是“dein”的第四格形式,表示所属关系,意指“你的”。 - freien : (自由的、空闲的),形容词,这里修饰后面的名词“Tag”,表示“休息日”、“空闲的一天”。 - Tag : (天、日),名词,单数形式,这里特指休息或空闲的时间。 - nicht : (不),否定副词。 - mit : (和...一起),介词。 - uns : (我们),代词,第一人称复数宾格形式。 - verbringen : (度过、共度时光),动词,原形为“verbringen”,此处意为一起度过一段时间。
整个句子意思是询问对方是否不愿意在休息日与说话人及其他人共同度过这一天。
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整体翻译: 想到爸爸独自度过他的休息日,我感到很伤心。
单词翻译:
- Ich:我(主格,第一人称单数代词)
- war:是(动词sein的一般过去时第一人称单数变位,这里表示过去的状态)
- traurig:伤心的(形容词,表示情绪低落或悲伤)
- bei:在……时/因为(介词,这里表示某种情境或原因)
- dem:这个(定冠词der的第三格形式,用来限定后面的名词)
- Gedanken:想法、念头(名词,指思想或思考的内容)
- dass:引导从句,相当于英语中的"that",在这里引出原因状语从句
- mein:我的(形容词性物主代词,单数第一格,表示所属关系)
- Pops:爸爸、爹地(非正式口语中的称呼,此处指父亲)
- seinen:他的(形容词性物主代词,单数第四格,指代父亲的)
- freien:空闲的、自由的(形容词,修饰后面的名词Tag,表示“休息日”)
- Tag:天、日子(名词,这里特指休息日或者空闲时间)
- ganz:完全地、整个地(副词,强调后面的动作状态)
- allein:独自、单独(副词,表示一个人没有陪伴)
- verbringt:度过、花费(动词verbringen的一般现在时第三人称单数变位,表示正在发生的或习惯性的动作)
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firstmonday.org firstmonday.org
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With the easy-to-use language of HTML, the ubiquity of TCP/IP that connected computers all over the globe and the well-understood domain name system for buying names, anyone could easily set-up their own Web site to share knowledge about any subject of their choosing, and thus the Web soon took off as the first truly decentralized system for global knowledge sharing. The Web’s decentralized nature, which allowed anyone to contribute and link to anyone else, made it a “permission-less” platform for knowledge. The decentralized innovation also applied to the core functionality of the Web as developers added new tags, such as the image tag by Netscape, and a constant stream of innovation has characterized the Web ever since its inception. Of course, it helped that CERN was committed to providing the core technology for free and the permission-less innovation was managed by a consensus-run global standards process for HTML, HTTP and URIs at the Internet Engineering Task Force (IETF) and Berners-Lee’s own World Wide Web Consortium (W3C). Still, the Web was not completely decentralized, as the domain name system itself, on which URIs depend, was centralized and requires the licensing of domain names — although once one has bought a single domain name one may host many different Web sites. As regards the decentralization of knowledge, the Web was viewed not as the end, but the beginning: Berners-Lee and others began hoping that eventually it would evolve into a truly universal information space for the sharing of knowledge that went beyond hypertext.
happy beginnings...
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整体翻译: - Oh, ist das wieder ein wundervoller Tag.<br /> (哦,今天又是美好的一天。)
单词分解与翻译: - Oh: (哦),这是一个感叹词,用于表达惊讶、喜悦或其他强烈的情绪。 - ist: (是),这是动词 "sein" (是) 的第三人称单数现在时态,用于表示某人的状态或存在。 - das: (这,那个),这是一个指示代词,用于指代特定的事物或概念。 - wieder: (又),这是一个副词,用于表示重复或再次发生的动作或事件。 - ein: (一个),这是一个不定冠词,用于名词之前,表示一个或多个未确定的对象。 - wundervoller: (美好的),这是一个形容词,用于形容令人愉悦或令人惊叹的事物。 - Tag: (天),这是一个名词,指一天的时间或日期。
所以整个句子意思是:(哦,今天又是美好的一天。) 这句话表达了说话人对当前一天的积极感受,表明他们认为这是一个愉快或令人满意的日子。
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Reply to the reviewers
We would like to express our gratitude to the reviewers for their comments, which helped us to improve the quality of our manuscript. Below are the responses to each comment. We hope that these responses will satisfy the reviewers.
Reviewer #1
Evidence, reproducibility and clarity
Summary: The nonsense-mediated mRNA decay (NMD) is and RNA quality pathway that eliminates mRNAs containing premature termination codons. Its mechanism has been studied for several decades but despite enormous progress we still don't have a satisfactory model that would explain most of the published observations. In particular, the mechanism has been proposed to differ substantially between yeast and metazoa. Yeast Nmd4 protein was previously shown to be involved in NMD, to interact with UPF1 and exhibit similarities with metazoan SMG6 and SMG5/7, that are normally believed to be specific for metazoan NMD (Dehecq et al., EMBO J, 2018). Barbarin-Bocahu et al now describe the crystal structure of the complex between the yeast UPF1 RNA helicase and Nmd4. Importantly, the authors show that interaction is required for NMD activity and increases the ATPase activity of UPF1. Barbarin-Bocahu et al equally show that this interaction and its role in NMD is conserved in the human UPF1-SMG6 complex, thus providing additional novel evidence for universal conservation of the NMD mechanism in eukaryotes. The manuscript carefully combines biochemistry, biophysics with functional in vivo studies. In my opinion, all the experiments are very well executed, generally convincing and interpretations appear correct, so the manuscript is certainly suitable for publication. I have included some suggestions below that I believe could strengthen the manuscript and enhance our confidence in the findings.
We are grateful for the useful suggestions that have enabled us to improve our manuscript.
Major comments:*
*Page 7 - "Since the D1353A mutation completely abolishes the enzymatic activity of SMG6 (34), this strongly suggests that the PIN domain of Nmd4 is not endowed with endonucleolytic activity. " Could/was the endonucleolytic activity of NMD4 be tested?
We agree with this important point. Our statement is based on previous site directed mutagenesis experiments on the PIN domain of human SMG6 (Galvan et al; 2006; EMBO Journal; PMID : 17053788 / Eberle et al; 2008; Nat. Struct. Mol. Biol.; PMID : 19060897), which showed that D1353 is the critical residue of SMG6 active site involved in the endonuclease enzymatic activity. Given that in yeast Nmd4 proteins, the corresponding residue is hydrophobic (Leu112 in S. cerevisiae Nmd4 and Phe114 in Kluyveromyces lactis Nmd4) and therefore cannot participate directly in catalysis, we assume that yeast Nmd4 proteins have no endonucleolytic activity.
Furthermore, despite decades of research in this field, no endonucleolytic activity has been described as being involved in the NMD pathway of S. cerevisiae (the model system in which the NMD mechanism was discovered in the 1970's), whereas it has been well characterized in the NMD pathway of metazoans for more than twenty years (Gatfield and Izaurralde; Nature; 2004; PMID : 15175755 / Huntzinger et al; RNA; 2008; PMID : 18974281 / Eberle et al; Nat. Struct. Mol. Biol.; 2009; PMID : 19060897 / Lykke-Andersen et al; Genes Dev.; 2014; PMID : 25403180). Our attempts to demonstrate an endonucleolytic activity of purified Nmd4 in vitro were not successful. This negative result could be due to many reasons, including loss of enzymatic activity in the tested buffer, the absence of an important cofactor or the choice of the tested RNA. For these reasons, we prefer not to include this type of negative result in the current manuscript.
We hope that, on the basis of the above informations, the reviewer will agree that further substantial efforts to demonstrate a hypothetical endonucleolytic activity of Nmd4 are unlikely to be fruitful. Moreover, we believe that even if yeast Nmd4 turns out to behave as an endonuclease, this fact does not change the main message of the manuscript.
Page 10 - The two proteins bind RNA with reasonable affinity. The complex binds polyU RNA with Kd of 0.44 μM . The authors suggest, based on structure superpositions, that RNA fragments bound to the PIN domain and Upf1-HD have opposite orientations. But since they have the complex ready to crystallize, did they attempt to determine the structure with of the complex with RNA? The complex is quite small (~100 kDa with RNA) but it could be even visible by cryo-EM. I don't insist that such a structure needs to be included but it might perhaps be easy to do and would surely strengthen the story. If it is too difficult, it could at least be mentioned that it was tried?
We agree that it would be interesting to determine the crystal structure of the complex with a short RNA fragment. Unfortunately, despite extensive efforts, we could not obtain crystals of the complex in the presence of RNA. This is probably due to the large movements of the RecA2 and 1B domains relative to the RecA1 domain observed in former studies upon RNA binding to Upf1. We have mentioned that we tried to crystallize this complex in the absence or the presence of a short oligonucleotide in our revised manuscript.
As far as single-particle cryo-EM is concerned, we are aware that recent advances in this field should make it possible to determine the structure of the Nmd4-Upf1-RNA complex, but we do not yet have the necessary expertise in this technique. Despite the interesting information that such a structure could provide, we therefore consider that this would require a very significant investment and that it is beyond the scope of this manuscript.
I think it is important to demonstrate that the structure-based mutants don't significantly impact the overall structure of the proteins (e.g. glycine residues are mutated within helices). At least gel filtration profiles with gels of the WT and mutated proteins should be shown in SI.
Thank you very much for highlighting this point. We fully agree that it is important to demonstrate that the Upf1 and Nmd4 mutants used in the in vitro experiments (pull-down and ATPase assays) are not affected in their overall folding. As suggested by the reviewer, we have included gel filtration chromatograms for WT and mutant proteins (Figures S2A for Upf1-HD proteins and S2B for His6-ZZ-Nmd4 proteins). These chromatograms clearly show that the different mutants behave very similarly to the WT proteins during purification, demonstrating that the overall structures of the mutants are very similar to those of the wild-type proteins. We have also included the Coomassie blue stained SDS-PAGE analysis of the proteins present in the main peak to show the purity of the final proteins.
Perhaps the main finding of this manuscript is the conservation of the UPF1-Nmd4 interaction in human UPF1-SMG6. But the interaction is only demonstrated by co-IP with ectopically expressed human proteins in human cells that contain all the other human proteins as well. It would probably be more convincing to demonstrated the interaction in pull-downs with purified proteins as done for the yeast complex.
Thank you for highlighting what we consider to be one of the most interesting findings presented in our manuscript. We agree that pull-down experiments using pure protein fragments expressed in E. coli would have been ideal to further confirm our co-IP results and to validate that mutations do not affect the overall structure of SMG6. Unfortunately, despite considerable efforts, we were unable to express sufficient quantities of the SMG6-[207-580] fragment or shorter versions as soluble proteins in E. coli. Indeed, Elena Conti's laboratory had the same experience according to a statement in a paper on SMG6 (Chakrabarti et al; 2014 Nucleic Acids Research; PMID: 25013172), indicating that this region protein is very difficult to work with. As we have not yet set up protein over-expression techniques in human cells or baculovirus-infected insect cells in our laboratory, we have not been able to try these expression systems to express these SMG6 domains. These are the reasons why we decided to demonstrate this interaction by co-IP experiment using ectopically expressed tagged proteins in human cells and all appropriate controls.
In addition, using purified proteins would enable testing whether the mutations in SMG6 don't affect the overall structure of the mutants compared to the WT.
We agree that this is an important issue. Several bioinformatics tools, including AlphaFold2 (identifier: AF-Q86US8-F1), predict that the human SMG6-[207-580] fragment is largely unstructured (see panel A of figure below). Furthermore, the pLDDT values or confidence scores for this region in the AlphaFold2 model are very low (below 50), indicating that the structure of this region is poorly predicted (see panel B of figure below). Therefore, biophysical techniques to assess that the overall structure of this fragment is not affected by the introduced mutations are very limited. However, we did not observe reduced levels of SMG6 mutants compared with WT in human cells expressing these variants (Fig. 4B and S4), so we believe that these mutants behave similarly to the wild-type fragment, as is often postulated by scientists for in cellulo studies. Furthermore, if these mutants drastically affect the overall structure of SMG6, we would expect NMD to be strongly affected, resulting in a notable accumulation of NMD RNA substrates in our in cellulo experiments when the effect of the double mutant (M2) is compared to that of the SMG6 WT protein (Fig. 4C). This was not the case. On the basis of all these elements, we assume that the overall structure of the SMG6 protein is not affected by these mutations.
Figure for reviewing purpose : Model of the three-dimensional structure of human SMG6 protein generated by AlphaFold2.
A. Model of human SMG6 protein (green) with the region 207-580 used in our study colored in red.
B. Model of human SMG6 protein (green) colored according to the pLDDT values. Orange : pLDDT 90.
Since the detected similarity to Nmd4 is only in a region covering residues 440-470, why is the tested construct much larger (207-580) including extra, large disordered regions.
For in cellulo studies, it has previously been shown that the SMG6-[207-580] fragment is expressed as a stable protein in human cells and is responsible for the phospho-independent interaction between UPF1 and SMG6 (Chakrabarti et al; 2014; Nucleic Acids Research; PMID: 25013172). As our aim was not to reduce this SMG6 region to a shorter peptide but to conduct an amino acid-level analysis by site-directed mutagenesis, we decided to perform our experiments using the same SMG6 domain as Conti's laboratory and to mutate conserved residues on this fragment.
Finally, the most convincing way to show and characterize the human UPF1-SMG6 interaction would be an X-ray structure. It might be feasible to crystallize human UPF1 HD domain with a SMG6 peptide. Or at least an Alphafold model could be included? I had a quick try just with the Colabfold and using the HD domain and the SMG6 peptide, Alphafold can predict convincingly the binding of the region around W456 and in some models even around R448. I think that this would strengthen the conclusions in this part of the manuscript.
We agree that determination of the crystal structure of human UPF1 HD linked to this region of SMG6 protein interaction would have further supported our conclusions on the conservation of UPF1-Nmd4 interaction in human UPF1-SMG6. However, due to the SMG6 expression problems mentioned above, we were unable to reconstitute the human complex in vitro, which precluded crystallization assays.
Based on this suggestion, we generated a model of human UPF1-HD bound to the 421-480 region of human SMG6 using AlphaFold2 Colabfold. Of the various models proposed (25 in total), most are very similar and show that the side chains of R448 and W456 of SMG6 bind to regions of human UPF1 corresponding to the region of the yeast protein that interacts with R210 and W216 of Nmd4. This model is consistent with our hypothesis and we have decided to include it in the revised manuscript as suggested (Fig. EV6). We thank the reviewer for this constructive comment.
We have added the following text to mention this model : « Based on this observation, we generated a model of the complex between human UPF1-HD and the region 421-480 of SMG6 using AlphaFold2 software (1,2). In this model, the SMG6 fragment binds to the same region of UPF1-HD as the Nmd4 « arm » (Fig. EV6). In particular, the R448 and W456 side chains of SMG6 match almost perfectly with R210 and W216 side chains of S. cerevisiae Nmd4, suggesting that this conserved region from SMG6 is involved in the interaction between the SMG6 and UPF1-HD proteins. »
Does the SMG6 addition also increases the ATPase activity of UPF1?
This is a very good point and we agree that the results of such an experiment may have further supported our conclusions about the conservation of the Upf1-Nmd4 interaction in human UPF1-SMG6. Unfortunately, due to the SMG6 protein expression problems mentioned above, we could not perform these in vitro experiments.
Minor comments: Examples of electron density omit maps of the key interaction interfaces should be shown in Supplementary Information for the reader to be able to judge the crystallography data quality.
Following this suggestion, we have added two panels showing electron density omit maps of residues at the interface in Fig. S1. We hope that this will convince the reader of the quality of our crystallographic data. We have also added the following sentence to the main text : « The overall quality of the electron density map allowed us to unambiguously identify the residues of the two proteins involved in the formation of the complex (Fig. S1A-B). »
I suggest to add the Kd values to ITC panels for clarity in main and EV figures.
We have taken this suggestion into account for figures 2A and EV5.
On page 10: What experiment is this referring to : "This is in agreement with our ITC experiments (carried out in the absence of a non-hydrolyzable ATP analog), which revealed no major synergistic effect between the two proteins for RNA binding." Results in EV4A? Or some other not shown data? The results in EV4A do show an increase in RNA binding when both proteins are in a complex.
Thank you for your comment. We realize that this sentence was not clear. We refer to the ITC data for the interaction of Upf1-HD, Nmd4 or the complex with RNA (Fig. EV5A). These data show a 2.3-fold increase in the affinity of Upf1 for RNA in the presence of Nmd4, which we consider to be a notable effect but not a major one. Based on the second reviewer's comments that our comparison between Nob1 and the PIN domain of Nmd4 is not convincing, we have decided to delete this speculative section, which did not address an important point in our current study. We will address this point using more direct and sophisticated methods in future work.
On page 16, "organsms" should be" organisms"
Typo corrected.
In certain figure legends the panel labels (A,B,C..) are missing (e.g. Fig 3, EV1, EV5).
We apologize for this problem ,which was due to a conversion problem when preparing the PDF file of the submitted article. This problem has now been corrected.
The PIN domain structure was solved only to determine the structure of the complex? I only found it mentioned in the methods and no other mention of this structure in the main text. Maybe one sentence could be added to the results to explain why this structure was solved and how it compares to the complex structure.
We agree that we forgot to explain why we solved the structure of the PIN domain of Nmd4. The point was to help in the determination of the structure of the complex. We have added the following sentence to the main text to explain this point: « We also determined the 1.8 Å resolution crystal structure of the PIN domain of Nmd4 (residues 1 to 167) to help us determine the structure of the Nmd4/Upf1-HD complex. As this structure is virtually identical to the structure of the PIN domain of Nmd4 in the complex (rmsd of 0.5 Å over 163 C𝛼 atoms between the two structures), we will only describe the structure of this domain in the Upf1-Nmd4 complex. »
Significance
This is a important study, providing detailed insight into the function on Nmd4, SMG6 and UPF1 NMD. The results also point towards a conserved mechanism on NMD between yeast and human. I would like to highlight the quality of the experiments. This study will be of great interest to people working on NMD but also more broadly to scientists working on RNA, helicases and structural biologists.
We are very grateful for the reviewer's comments about the broad interest and overall quality of our work.
Reviewer #2
Evidence, reproducibility and clarity
In this study, the authors solved the crystal structure of the UPF1 helicase domain in complex with Nmd4. Through the structure and biochemical studies, they uncovered a region responsible for Nmd4 binding to UPF1, also important for their function in NMD. In the end, the authors also extended their findings to the human SMG6, proposing a conserved mechanism for Nmd4 and SMG6.
The mechanism of UPF1 functioning during NMD is a long-existing question. For decades, people have been trying to find out the roles of all the NMD factors during this process. This study visualized the first direct connection between UPF1 and the putative SMG6 homolog, Nmd4. Undoubtedly, it will aid our understanding of how the whole process works.
One of the limitations of this study is the conservation between Nmd4 and SMG6. Although they both have a PIN domain, Nmd4 is inactive while SMG6 is active. During NMD, SMG6 is thought to work to cut the mRNA, thus promoting the degradation of the non-functional mRNA. Therefore, Nmd4 and SMG6 may only share a similar binding mode with UPF1, however, they do not share similar functions. This study might only apply to yeast study.
We respectfully disagree with this comment. The role of SMG6 in NMD cannot be attributed solely to the endonuclease activity of the SMG6 PIN domain alone. Indeed, recruitment of the SMG6 PIN domain alone to an mRNA is not sufficient to destabilize it (Nicholson et al; 2014; Nucleic Acids Research; PMID: 25053839). This clearly indicates that other regions of SMG6 are critical for NMD. In our manuscript, we unveil the conservation of the Upf1-Nmd4 interaction in human UPF1-SMG6 (and probably more generally in metazoans) and show that this interaction plays a role in the optimal removal of NMD substrates. We strongly believe that our results are not only applicable to the study of yeast, but will fuel future studies in human cells aimed at describing the mechanistic details of the human NMD pathway.
comments: the study write in a very clear way, and most of the experiments are clear and sound. I do not have any major comments. I only have a few minor comments, listed below:
We are very grateful for the reviewer's comments about the overall quality of our manuscript and of the experimental work.
1:The authors also solved the PIN domain of the SMG6. This is a result worth showing in the main figure.
In our study, we did not solve the structure of the human SMG6 PIN domain. This was done by Dr. Conti's group in 2006 (Galvan et al; 2006; EMBO Journal; PMID : 17053788). This is the reason why we do not include this in the main figure. However, we have solved the crystal structure of Nmd4 PIN domain alone to help us determine the structure of the complex. Since it is very similar to the structure of the Nmd4 PIN domain in the complex with Upf1, we do not describe this structure in details. Following up the suggestion from another reviewer, we have included the following sentence mentioning that we have also determined the structure of Nmd4 PIN domain in the main text : « We also determined the 1.8 Å resolution crystal structure of the PIN domain of Nmd4 (residues 1 to 167) to help us determine the structure of the Nmd4/Upf1-HD complex. As this structure is virtually identical to the structure of the PIN domain of Nmd4 in the complex (rmsd of 0.5 Å over 163 C𝛼 atoms between the two structures), we will only describe the structure of this domain in the Upf1-Nmd4 complex. »
2:It would be easier to read if the authors could add all the binding constants directly into the ITC panels.
We have taken this suggestion into account for figures 2A and EV5.
3:I am confused with His6-ZZ. Is ZZ a protein tag?
The ZZ protein is a tag consisting of a tandem of the Z-domain from Staphylococcus aureus protein A. This domain binds to the Fc region of IgG and has been shown to improve expression levels and stability of recombinant proteins. In our case, it proved crucial to obtain mg amounts of the yeast Nmd4 protein and to enhance considerably its stability. We have added the following sentence in the « Materials and methods » section of the manuscript : « The ZZ-tag consists in a tandem of the Z-domain from Staphylococcus aureus protein A and was used as an enhancer of protein expression and stability. »
4:The comparison between Nob1 and the PIN domain of Nmd4 is not convincing for me. Since the PIN domain is not required for the binding between Nmd4 and UPF1, the conformation of the PIN domain could be a result of the crystal packing. Thus, it is still possible that Nmd4 and UPF1 bind to the same RNA. To this end, I challenge the conclusion the authors have made on the mRNA binding part.
We agree with your comment. Since this comparison is purely speculative and is not a major focus of our study, we decided to remove this section. We will address this point using more direct and sophisticated methods in future work aimed at elucidating this aspect.
5: "Showing that Nmd4 stabilizes Upf1-HD on RNA in the absence of ATP and that Upf1 is the main RNA binding factor in the Nmd4/Upf1-HD complex." As mentioned above, I don't think one can make the conclusion UPF1 is the main RNA binding factor; there shouldn't be a main and minor. Meanwhile, what will happen if you add ATP in? Or AMPPNP? Or ADP?
We agree with your comment that our current data do not allow to conclude precisely about the role of Upf1 as major RNA binding factor. We have replaced this sentence by the following one : « Whether this increase in affinity is due to a synergistic effect between both proteins or to an allosteric stimulation of one partner on the RNA binding property of the second partner remains to be clarified. ».
Regarding the role of the nucleotides on RNA binding properties of the Upf1 helicase domain or the complex, we faced precipitation problems when mixing high concentrations Upf1 and nucleotides for ITC experiments, making difficult to determine Kd values for the interaction between Upf1 and RNA in the presence of nucleotides. However, in a previous study (Dehecq et al; 2018; EMBO J; PMID : 30275269), we observed that AMPPNP did not affect the amount of Nmd4 and Upf1-HD co-precipitated by an RNA oligonucleotide, indicating that nucleotide does not significantly affect the interaction of the complex with RNA.
6: "But also that a physical interaction between Upf1-HD and the PIN domain exists in vitro, although we were unable to detect it using our various interaction assays." This also confused me, since one cannot detect the interaction in any assay, how could you be so confident there is a physical interaction? Have you tested assays which are good for weak binding?
We understand that this sentence may be confusing. The tests we have used to determine whether there is a physical interaction between the PIN domain of Nmd4 and Upf1-HD are ITC and pull-down. These are excellent methods for detecting stable interactions with dissociation constants (Kd) in the nanomolar to tens of micromolar range. These two methods did not indicate any direct interaction between the PIN domain of Nmd4 and Upf1-HD. However, we observed that the PIN domain of Nmd4 stimulates the ATPase activity of Upf1-HD to the same extent as the « arm » of Nmd4. This is an indirect indication that the Nmd4 PIN may interact with Upf1-HD, otherwise a stimulatory effect would not be expected. Our radioactivity-based ATPase assay is very sensitive, allowing the detection of a stimulatory effect due to a transient interaction between the PIN domain of Nmd4 and Upf1-HD, which, as indicated above, could not be detected with the interaction assays used. We would also like to point out that in our ATPase conditions, Upf1-HD (0.156 µM) is incubated with a 20-fold molar excess (3.12 µM) of its partners (Nmd4-FL, Nmd4 « arm » or Nmd4 PIN). Such an excess cannot be used in our interaction tests. This could explain the stimulatory effect detected for the PIN domain of Nmd4 in our ATPase assay.
We have clarified this section by adding the following sentences: « We were unable to detect such an interaction using our different interaction assays (pull-down and ITC), which are optimal for studying interactions with dissociation constants (Kd) in the nanoM to tens of microM range. We therefore assume that a transient low-affinity interaction (high Kd value not detected by our binding assays) exists between Upf1-HD and PIN Nmd4 and can only be detected by highly sensitive assays such as our radioactivity-based ATPase assay, which was performed with a 20-fold molar excess of PIN Nmd4 domain over Upf1-HD. »
7: Figure 4B should be done in the context of the full length of SMG6 and UPF1.
**Referees cross-commenting**
*This session contains comments from both Rev1 and Rev2*
Rev1:
There seems to be a contradiction in comments on Figure 4B. I agree with Reviewer 2 that using FL proteins will be informative to see whether the FL proteins indeed interact (or not in the case of the mutants).
If one wants to use this experiment to map the interacting regions, then I think that the UPF1 HD domain and the short conserved region of SMG6 should be used. The long fragment SMG6 207-580 is not ideal for either. The short constructs would be more suited for a pull-down experiments (like done for the yeast proteins).
Rev2
Response to reviewer #1, It is necessary to use the full-length protein (FL protein) to map the interface unless they have pre-existing information to support mapping down to short fragments.
In addition, performing further structural work would be beyond the scope of this study. Given the additional time and effort required, I do not recommend doing so for this study.
Rev1:
As I said, I agree with using the FL proteins. The pre-existing information supporting the mapping comes from sequence alignments with the yeast structure and the mutagenesis. This is further confirmed by Alphafold modeling which in my opinion should be included. As I mentioned in my review, I don't insist on further structural work
Thank you very much for this comment and the discussions between reviewers, which show that we didn't explain our experimental strategy clearly. Human UPF1 has been shown to interact with SMG6 in both phospho-dependent and phospho-independent modes. In our manuscript, we focus on characterizing the phospho-independent interaction. For this reason, we cannot perform this experiment using the full-length version of SMG6 and UPF1, otherwise the effects of our point mutants on the UPF1-SMG6 interaction could be masked by the phospho-dependent interaction occurring between domain 14.3.3 of SMG6 and the C-terminus of Upf1. To circumvent this problem, we were inspired by former in cellulo studies, which have shown that the SMG6-[207-580] fragment is expressed as a stable protein in human cells and is responsible for the phospho-independent interaction between UPF1 and SMG6 (Chakrabarti et al; 2014; Nucleic Acids Research; PMID: 25013172). Similarly, the helicase domain of UPF1 was found to be sufficient for this phospho-independent interaction with human SMG6 (Nicholson et al; 2014; Nucleic Acids Research; PMID: 25053839). These are the reasons why we decided to use this protein domains in our in cellulo studies to test the effect of our point mutants on the interaction. As indicated above in an answer to one comment to reviewer #1, as our aim was not to reduce this SMG6 region to a shorter peptide but to conduct an amino acid-level analysis by site-directed mutagenesis, this is also why we decided to perform our experiments using the same SMG6 domain as Conti's laboratory and to mutate conserved residues on this fragment. We have also included the AlphaFold2 model of the complex between human UPF1 and SMG6 in our revised version.
To clarify this point, we have amended the relevant section as follows: « To determine whether this motif might be involved in the interaction between SMG6 and UPF1-HD proteins, we ectopically expressed the region comprising residues 207-580 of human SMG6 fused to a C-terminal HA tag (SMG6-[207-580]-HA) and human UPF1-HD (residues 295-921 fused to a C-terminal Flag tag; UPF1-HD-Flag) in human HEK293T cells, as these regions have previously been shown to be responsible for the phosphorylation-independent interaction between these two proteins. Compared to the full-length UPF1 and SMG6 proteins, these constructs also preclude our findings of any interference from the phosphorylation-dependent interaction occurring between the C-terminus of UPF1 and the 14-3-3 domain of SMG6. »
8: "The NMD mechanism not only targets mRNAs but also small nucleolar RNAs (snoRNAs) and long noncoding RNAs (lncRNAs) harboring bona fide stop codons but in a specific context such as short upstream open reading frame (uORF), long 3'-UTRs, low translational efficiency or exon-exon junction located downstream of a stop codon." "First, for mRNAs with long 3'-UTRs, the 3'-faux UTR model posits that a long 3 spatial distance between a stop codon and the mRNA poly(A) tail destabilizes NMD substrates by preventing the interaction between the eRF1-eRF3 translation termination complex bound to the A- site of a ribosome recognizing a stop codon and the poly(A)-binding protein (Pab1 or PABP in S. cerevisiae and human, respectively)." These are difficult to read.
Thank you for this suggestion to improve the clarity of our manuscript. We have tried to make these sentences easier to read as follow:
« The NMD mechanism also targets mRNAs, small nucleolar RNAs (snoRNAs) and long noncoding RNAs (lncRNAs) carrying normal stop codons located in a specific context (short upstream open reading frame or uORF, long 3'-UTRs, low translational efficiency or exon-exon junction located downstream of a stop codon (3-11)). »
« The first model, the 3'-faux UTR model posits that for mRNAs with long 3'-UTRs, a long spatial distance between a stop codon and the mRNA poly(A) tail destabilizes NMD substrates. Indeed, it would prevent the physical interaction between the eRF1-eRF3 translation termination complex recognizing a stop codon in the A-site of the ribosome and the poly(A)-binding protein (Pab1 or PABP in S. cerevisiae and human, respectively) bound to the 3' poly(A) tail (12-14). »
9: please add the Ramachandran plot values.
Thank you for pointing out this omission. These values have been included in Table EV1.
__Significance __
NMD is one of the major topics in the field of gene translational regulation research. this study will be of interest to a broad audience. i am an expert in the structure study in translation. However, I have limited experience in the in vivo study of NMD substrates.
We are very grateful for the reviewer's comments about the broad interest and the overall quality of our work.
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Referee #2
Evidence, reproducibility and clarity
In this study, the authors solved the crystal structure of the UPF1 helicase domain in complex with Nmd4. Through the structure and biochemical studies, they uncovered a region responsible for Nmd4 binding to UPF1, also important for their function in NMD. In the end, the authors also extended their findings to the human SMG6, proposing a conserved mechanism for Nmd4 and SMG6.
The mechanism of UPF1 functioning during NMD is a long-existing question. For decades, people have been trying to find out the roles of all the NMD factors during this process. This study visualized the first direct connection between UPF1 and the putative SMG6 homolog, Nmd4. Undoubtedly, it will aid our understanding of how the whole process works.
One of the limitations of this study is the conservation between Nmd4 and SMG6. Although they both have a PIN domain, Nmd4 is inactive while SMG6 is active. During NMD, SMG6 is thought to work to cut the mRNA, thus promoting the degradation of the non-functional mRNA. Therefore, Nmd4 and SMG6 may only share a similar binding mode with UPF1, however, they do not share similar functions. This study might only apply to yeast study.
comments: the study write in a very clear way, and most of the experiments are clear and sound. I do not have any major comments. I only have a few minor comments, listed below:
1:The authors also solved the PIN domain of the SMG6. This is a result worth showing in the main figure.
2:It would be easier to read if the authors could add all the binding constants directly into the ITC panels.
3:I am confused with His6-ZZ. Is ZZ a protein tag?
4:The comparison between Nob1 and the PIN domain of Nmd4 is not convincing for me. Since the PIN domain is not required for the binding between Nmd4 and UPF1, the conformation of the PIN domain could be a result of the crystal packing. Thus, it is still possible that Nmd4 and UPF1 bind to the same RNA. To this end, I challenge the conclusion the authors have made on the mRNA binding part.
5: "Showing that Nmd4 stabilizes Upf1-HD on RNA in the absence of ATP and that Upf1 is the main RNA binding factor in the Nmd4/Upf1-HD complex." As mentioned above, I don't think one can make the conclusion UPF1 is the main RNA binding factor; there shouldn't be a main and minor. Meanwhile, what will happen if you add ATP in? Or AMPPNP? Or ADP?
6: "But also that a physical interaction between Upf1-HD and the PIN domain exists in vitro, although we were unable to detect it using our various interaction assays." This also confused me, since one cannot detect the interaction in any assay, how could you be so confident there is a physical interaction? Have you tested assays which are good for weak binding?
7: Figure 4B should be done in the context of the full length of SMG6 and UPF1.
8: "The NMD mechanism not only targets mRNAs but also small nucleolar RNAs (snoRNAs) and long noncoding RNAs (lncRNAs) harboring bona fide stop codons but in a specific context such as short upstream open reading frame (uORF), long 3'-UTRs, low translational efficiency or exon-exon junction located downstream of a stop codon." "First, for mRNAs with long 3'-UTRs, the 3'-faux UTR model posits that a long 3 spatial distance between a stop codon and the mRNA poly(A) tail destabilizes NMD substrates by preventing the interaction between the eRF1-eRF3 translation termination complex bound to the A- site of a ribosome recognizing a stop codon and the poly(A)-binding protein (Pab1 or PABP in S. cerevisiae and human, respectively)." These are difficult to read.
9: please add the Ramachandran plot values.
Significance
NMD is one of the major topics in the field of gene translational regulation research. this study will be of interest to a broad audience. i am an expert in the structure study in translation. However, I have limited experience in the in vivo study of NMD substrates.
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Local file Local file
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We quote because we are afraid to-change words, lest there be a change in meaning.
Quotations are easier to collect than writing things out in one's own words, not only because it requires no work, but we may be afraid of changing the original meaning by changing the original words or by collapsing the context and divorcing the words from their original environment.
Perhaps some may be afraid that the words sound "right" and they have a sense of understanding of them, but they don't quite have a full grasp of the situation. Of course this may be remedied by the reader or listener not only by putting heard stories into their own words and providing additional concrete illustrative examples of the concepts. These exercises are meant to ensure that one has properly heard/read and understood a concept. Psychologists call this paraphrasing or repetition the "echo effect" (others might say parroting or mirroring) and have found that it can help to build understanding, connection, and likeability between people. Great leaders who do this will be sure to make sure that credit for the original ideas goes to the originator and not to themselves simply because they repeated it, especially in group settings where their words may have more primacy amidst their underlings.
(I can't find it at the moment, but there's a name/tag for this in my notes? looping?)
Beyond this, can one place the idea into a more clear language than the original? Add some poetry perhaps? Make the concept into a concrete meme to make it more memorable?
Journalists like to quote because it gives primacy of voice to the speaker and provides the reader with the sense that they're getting the original from which they might make up their own minds. It also provides a veneer of vérité to their reportage.
Link this back to Terrence's comedy: https://hypothes.is/a/xe15ZKPGEe6NJkeL77Ji4Q
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what little indexing is attempted can only 14be described as an unsystematic effort. The catchword methodof the catalogue has been bodily transplanted to indexing,which makes it very difficult to control our indexed informationproperly, and limits our supply of information to that whichwill fall in with the catchword method
Catchwords (broad or even narrow topics) can be useful, but one should expand beyond these short words to full phrases or even sentences/paragraphs which contain atomic (or perhaps molecular) ideas that can be linked.
We could reframe the atomic as simple catchwords, and make molecular ideas combinations of these smaller atoms which form larger and fuller thoughts which can be linked and remixed with others.
Dennis Duncan (2022) touches on this in his book on Indexing when he looks at indexes which contained portions of their fuller text which were later removed and thereby collapsing context. Having these pieces added back in gave a fuller picture of ideas within an index. Connect this idea with his historical examples.
Great indexes go beyond the catchword to incorporate full ideas with additional context. To some extent this is what Luhmann was doing at larger scale compared to his commonplacing brethren who were operating far more closely to the catchword (tag) level. (Fortunately they held the context in their heads and were thus able to overcome some of the otherwise inherent problems.)
The development of all of this historically seems to follow the principle of small pieces loosely joined.
Tags
- shifts in meaning
- repetition
- journalism
- small pieces loosely joined
- Julius Kaiser
- atomic ideas
- quote
- testing understanding
- writing to test understanding
- context collapse
- sententiae
- echo effect
- molecular notes
- quot homines tot sententiae
- open questions
- parroting
- echolalia
- paraphrasing
- idea links
- catchwords
- indexing
- quotations
- semantic shift
- catchword method
Annotators
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Author Response
The following is the authors’ response to the original reviews.
eLife assessment
This study, utilizing CITE-Seq to explore CML, is considered a useful contribution to our understanding of treatment response. However, the reviewers express concern about the incomplete evidence due to the small sample size and recommend addressing these limitations. Strengthening the study with additional patient samples and validation measures would enhance its significance.
We thank the editors for the assessment of our manuscript. In view of the comments of the three reviewers, we have increased the number of CML patient samples analyzed to confirm all the major findings included in the manuscript. In total, more than 80 patient samples across different approaches have now been analyzed and incorporated in the revised manuscript.
To the best of our knowledge, this is the first single cell multiomics report in CML and differs substantially from the recent single cell omics-based reports where single modalities were measured one at a time (Krishnan et al., 2023; Patel et al., 2022). Thus, the sc-multiomic investigation of LSCs and HSCs from the same patient addresses a major gap in the field towards managing efficacy and toxicity of TKI treatment by enumerating CD26+CD35- LSCs and CD26-CD35+ HSCs burden and their ratio at diagnosis vs. 3 months of therapy. The findings suggest design of a simpler and cheaper FACS assay to simultaneously stratify CML patients for TKI efficacy as well as hematologic toxicity.
Reviewer 1:
Summary:
This manuscript by Warfvinge et al. reports the results of CITE-seq to generate singlecell multi-omics maps from BM CD34+ and CD34+CD38- cells from nine CML patients at diagnosis. Patients were retrospectively stratified by molecular response after 12 months of TKI therapy using European Leukemia Net (ELN) recommendations. They demonstrate heterogeneity of stem and progenitor cell composition at diagnosis, and show that compared to optimal responders, patients with treatment failure after 12 months of therapy demonstrate increased frequency of molecularly defined primitive cells at diagnosis. These results were validated by deconvolution of an independent previously published dataset of bulk transcriptomes from 59 CML patients. They further applied a BCR-ABL-associated gene signature to classify primitive Lin-CD34+CD38- stem cells as BCR:ABL+ and BCR:ABL-. They identified variability in the ratio of leukemic to non-leukemic primitive cells between patients, showed differences in the expression of cell surface markers, and determined that a combination of CD26 and CD35 cell surface markers could be used to prospectively isolate the two populations. The relative proportion of CD26-CD35+ (BCR:ABL-) primitive stem cells was higher in optimal responders compared to treatment failures, both at diagnosis and following 3 months of TKI therapy.
Strengths:
The studies are carefully conducted and the results are very clearly presented. The data generated will be a valuable resource for further studies. The strengths of this study are the application of single-cell multi-omics using CITE-Seq to study individual variations in stem and progenitor clusters at diagnosis that are associated with good versus poor outcomes in response to TKI treatment. These results were confirmed by deconvolution of a historical bulk RNAseq data set. Moreover, they are also consistent with a recent report from Krishnan et al. and are a useful confirmation of those results. The major new contribution of this study is the use of gene expression profiles to distinguish BCRABL+ and BCR-ABL- populations within CML primitive stem cell clusters and then applying antibody-derived tag (ADT) data to define molecularly identified BCR:ABL+ and BCR-ABL- primitive cells by expression of surface markers. This approach allowed them to show an association between the ratio of BCR-ABL+ vs BCR-ABL- primitive cells and TKI response and study dynamic changes in these populations following short-term TKI treatment.
Weaknesses:
One of the limitations of the study is the small number of samples employed, which is insufficient to make associations with outcomes with confidence. Although the authors discuss the potential heterogeneity of primitive stem, they do not directly address the heterogeneity of hematopoietic potential or response to TKI treatment in the results presented. Another limitation is that the BCR-ABL + versus BCR-ABL- status of cells was not confirmed by direct sequencing for BCR-ABL. The BCR-ABL status of cells sorted based on CD26 and CD35 was evaluated in only two samples. We also note that the surface markers identified were previously reported by the same authors using different single-cell approaches, which limits the novelty of the findings. It will be important to determine whether the GEP and surface markers identified here are able to distinguish BCR-ABL+ and BCR-ABL- primitive stem cells later in the course of TKI treatment. Finally, although the authors do describe differential gene expression between CML and normal, BCR:ABL+ and BCR:ABL-, primitive stem cells they have not as yet taken the opportunity to use these findings to address questions regarding biological mechanisms related to CML LSC that impact on TKI response and outcomes.
Reviewer #1 (Recommendations For The Authors):
Minor comment: Fig 4 legend -E and F should be C and D.
We thank the reviewer for positive assessment of our work. Here, we highlight the updates in the revised manuscript considering the feedback received.
Minor comment: Fig 4 legend -E and F should be C and D.
We have edited the revised manuscript accordingly
One of the limitations of the study is the small number of samples employed, which is insufficient to make associations with outcomes with confidence.
Although we performed CITE-seq for 9 CML patient samples at diagnosis, we extended our investigations to include additional samples (e.g., largescale deconvolution analysis of samples, Fig 3 C-E, qPCR for BCR::ABL1 status, Fig. 6A, and the ratio between CD35+ and CD26+ populations at diagnosis and during TKI therapy, Fig. 6C-D) as described in the manuscript.
In comparison to a scRNA-seq, multiomic CITE-seq involves preparation and sequencing of separate libraries corresponding to RNA and ADTs thereby being even more resource demanding limiting our capacity to process an extensive number of patient samples. To confirm our findings in a larger cohort we have therefore adopted a computational deconvolution approach, CIBERSORT to analyze a larger number of independent samples (n=59). This reflects a growing, sustainable trend to study larger number of patients in face of still prohibitively expensive but potentially insightful scomics approaches (For example, please see Zeng et al, A cellular hierarchy framework for understanding heterogeneity and predicting drug response in acute myeloid leukemia, Nature Medicine, 2022).
However, in view of the comment, we have now substantially increased the number of analyzed patients in the revised manuscript. These include increased number of patient samples to investigate the ratio between CD35 and CD26 marked populations at diagnosis, and 3 months of TKI therapy (from n=8 to n=12 with now 6 optimal responders and 5 treatment failure at diagnosis and after TKI therapy), qPCR for BCR::ABL1 expression status at diagnosis (from n=3 to n=9) , and followed up the BCR::ABL1 expression in three additional samples after TKI therapy. Moreover, we examined the CD26 and CD35 marked populations for expression of GAS2, one of our top candidate LSC signature genes in three additional samples at diagnosis and at 3m follow up. Thus, >80 patient samples across different approaches have been analyzed to strengthen all major conclusions of the study.
We emphasize that we were cautious in generalizing the observation obtained from any one approach and sought to confirm any major finding using at least one complementary method. As an example, although CITE-seq (n=9) showed altered frequency of all cell clusters between optimal and poor responders (Fig. 3B), we refrained from generalizing because our independent large-scale computational deconvolution analysis (n=59) only substantiated the altered proportion of primitive and myeloid cell clusters (Fig. 3E).
Although the authors discuss the potential heterogeneity of primitive stem, they do not directly address the heterogeneity of hematopoietic potential or response to TKI treatment in the results presented.
Thanks for noting the discussion on heterogeneity of the primitive stem cells. As described in the original manuscript, the figure 6 D-E showed a relationship between heterogeneity and TKI therapy response. The results showed that CD35+/CD26+ ratio within the HSC fraction associated with this therapy response. We have now increased the number of patient samples analyzed and present the updated results in the revised manuscript (now figure 6 C-D). These observations set the stage for assessing whether long term therapy outcome can also be influenced by heterogeneity at diagnosis.
We have shown the hematopoietic potential of HSCs marked by CD35 expression in an independent parallel study and therefore only mentioned it concisely in the current manuscript. A combination of scRNA-seq, scATAC-seq and cell surface proteomics showed CD35+ cells at the apex of healthy human hematopoiesis, containing an HSCspecific epigenetic signature and molecular program, as well as possessing self-renewal capacity and multilineage reconstitution in vivo and vitro. The preprint is available as Sommarin et al. ‘Single-cell multiomics reveals distinct cell states at the top of the human hematopoietic hierarchy’, Biorxiv; https://www.biorxiv.org/content/10.1101/2021.04.01.437998v2.full
We also note that the surface markers identified were previously reported by the same authors using different single-cell approaches, which limits the novelty of the findings.
Our current manuscript is indeed a continuation of and builds onto our previous paper (Warfvinge R et al. Blood, 2017). In contrast to our previous report which was limited to examination of only 96 genes per cell, CITE-seq allowed us to examine the molecular program of cells using unbiased global gene expression profiling. Finally, although CD26 appears, once again as a reliable marker of BCR::ABL1+ primitive cells, CD35 emerges as a novel and previously undescribed marker of BCR::ABL1- residual stem cells. A combination of CD35 and CD26 allowed us to efficiently distinguish between the two populations housed within the Lin-34+38/low stem cell immunophenotype.
Another limitation is that the BCR-ABL + versus BCR-ABL- status of cells was not confirmed by direct sequencing for BCR-ABL. The BCR-ABL status of cells sorted based on CD26 and CD35 was evaluated in only two samples
Single cell detection of fusion transcripts is challenging with low detection sensitivity in single cell RNA-seq as has been noted previously (Krishnan et al. Blood, 2023, Giustacchini et al. Nature Medicine, 2017, Rodriguez-Meira et al. Molecular Cell, 2019). However, this is likely to change with the inclusion of targetspecific probes in scRNA-seq library preparation protocols. Nonetheless, in view of the comment, we have included more patient samples (from the previous n=3 to current n=10 (including TKI treated samples) for direct assessment of BCR-ABL1 status by qPCR analysis; the updated results are included in the revised manuscript (Figure 6A).
It will be important to determine whether the GEP and surface markers identified here are able to distinguish BCR-ABL+ and BCR-ABL- primitive stem cells later in the course of TKI treatment.
We performed qPCR to check for BCR::ABL1 status, and the level of GAS2, one of the top genes expressed in CML cells within CD26+ and CD35+ cells at diagnosis and following 3 months of TKI therapy. The results showed that while CD26+ are BCR::ABL1+, the CD35+ cells are BCR::ABL1- at both time points. Moreover, the expression of LSC-specific gene, GAS2 was specific to BCR::ABL1+ CD26+ cells at both diagnosis as well as following 3 months of TKI therapy. The new results are presented in figure 6B in the revised manuscript.
Finally, although the authors do describe differential gene expression between CML and normal, BCR:ABL+ and BCR:ABL-, primitive stem cells they have not as yet taken the opportunity to use these findings to address questions regarding biological mechanisms related to CML LSC that impact on TKI response and outcomes.
We agree with the reviewer that our major focus here was to characterize the cellular heterogeneity coupled to treatment outcome and therefore we did not delve deep into the molecular mechanisms underlying TKI response. However, in response to this comment, as mentioned above, we noted that one of the top genes in BCR::ABL1 cells (Fig. 4 C; right; in red), GAS2 (Growth Specific Arrest 2) was expressed at both diagnosis and TKI therapy within CD26+ cells relative to CD35+ cells (updated figure 6B). Interestingly, GAS2 was also detected in CML LSCs in a recent scRNA-seq study (Krishnan et al. Blood, 2023) suggesting GAS2 upregulation could be a consistent molecular feature of CML cells. GAS2 has been previously noted as deregulated in CML (Janssen JJ et al. Leukemia, 2005, Radich J et al, PNAS, 2006), control of cell cycle, apoptosis, and response to Imatinib (Zhou et al. PLoS One, 2014). Future investigations are warranted to assess whether GAS2 could play a role in the outcome of long-term TKI therapy.
Reviewer 2:
Summary:
The authors use single-cell "multi-comics" to study clonal heterogeneity in chronic myeloid leukemia (CML) and its impact on treatment response and resistance. Their main results suggest 1) Cell compartments and gene expression signatures both shared in CML cells (versus normal), yet 2) some heterogeneity of multiomic mapping correlated with ELN treatment response; 3) further definition of s unique combination of CD26 and CD35 surface markers associated with gene expression defined BCR::ABL1+ LSCs and BCR::ABL1- HSCs. The manuscript is well-written, and the method and figures are clear and informative. The results fit the expanding view of cancer and its therapy as a complex Darwinian exercise of clonal heterogeneity and the selective pressures of treatments.
Strengths:
Cutting-edge technology by one of the expert groups of single-cell 'comics.
Weaknesses:
Very small sample sizes, without a validation set. The obvious main problem with the study is that an enormous amount of results and conjecture arise from a very small data set: only nine cases for the treatment response section (three in each of the ELN categories), only two normal marrows, and only two patient cases for the division kinetic studies. Thus, it is very difficult to know the "noise" in the system - the stability of clusters and gene expression and the normal variation one might expect, versus patterns that may be reproducibly study artifact, effects of gene expression from freezing-thawing, time on the bench, antibody labeling, etc. This is not so much a criticism as a statement of reality: these elegant experiments are difficult, timeconsuming, and very expensive. Thus in the Discussion, it would be helpful for the authors to just frankly lay out these limitations for the reader to consider. Also in the Discussion, it would be interesting for the authors to consider what's next: what type of validation would be needed to make these studies translatable to the clinic? Is there a clever way to use these data to design a faster/cheaper assay?
We thank the reviewer for appraisal of our manuscript. We take the opportunity to point out the updates in the revised manuscript in view of the comments.
Very small sample sizes, without a validation set. The obvious main problem with the study is that an enormous amount of results and conjecture arise from a very small data set: only nine cases for the treatment response section (three in each of the ELN categories), only two normal marrows, and only two patient cases for the division kinetic studies.
As the reviewer has noted the single cell omics experiments remain resource demanding thereby placing a limitation on the number of patients analyzed. As described above in response to the comments from reviewer 1, multiomic CITE-seq allows extraction of two modalities in comparison to a typical scRNA-seq, however, this also makes it even more limited in the number of samples processed in a sustainable way. This was one of the motivations to analyze a larger number of independent samples (n=59) while benefiting from the insights gained from CITE-seq (n=9). Furthermore, by analyzing CD34+ cells from bone marrow and peripheral blood of CML patients, including both responders and non-responders after one year of Imatinib therapy, we were able to significantly diversity the patient pool, which was lacking in our CITE-seq patient pool. As mentioned above, this reflects a growing trend to analyze larger number of patients while anchoring the analysis on prohibitively expensive but potentially insightful sc-omics approaches (For example, please see Zeng et al, A cellular hierarchy framework for understanding heterogeneity and predicting drug response in acute myeloid leukemia, Nature Medicine, 2022).
As emphasized above, we frequently sought to confirm the findings from one approach using a complementary method and independent samples. For example, although CITE-seq (n=9) showed altered frequency of all cell clusters between optimal and poor responders (Fig. 3B), we refrained from generalizing because an independent largescale computational deconvolution analysis (n=59) only substantiated the altered proportion of primitive and myeloid clusters.
In view of the comment, we have now increased the number of patients analyzed during the revision process. These include increased numbers to investigate the ratio between CD35+ and CD26+ populations at diagnosis, as well as 3 months of TKI therapy, qPCR for BCR::ABL1, and patients examined for GAS2, one of the top genes expressed in CML cells (see response to reviewer 1 for details). Altogether, >80 patient samples across different approaches were analyzed to strengthen the conclusions.
During the revision, we have analyzed cells from 8 CML patients for cell cycle using gene activity scores. This is in addition to the cell division kinetics data reported previously are now together described in the supplementary figures 9C-F.
It is very difficult to know the "noise" in the system - the stability of clusters and gene expression and the normal variation one might expect, versus patterns that may be reproducibly study artifact, effects of gene expression from freezing-thawing, time on the bench, antibody labeling, etc. This is not so much a criticism as a statement of reality: these elegant experiments are difficult, time-consuming, and very expensive. Thus in the Discussion, it would be helpful for the authors to just frankly lay out these limitations for the reader to consider.
We agree with the reviewer that sc-omics approaches can be noisy despite continuing efforts to denoise single cell datasets through both experimental and bioinformatic innovations. Therefore, we have updated the discussion as recommended by the reviewer (paragraph 5 in the discussion).
We also note that CITE-seq, in contrast to scRNA-seq alone provides dual features: surface marker/protein as well as RNA for annotating the same cluster. In our manuscript, for example, cell clusters in UMAP for normal BM; Fig 1B were described using both surface markers (Fig. 1C) and RNA (Fig. 1D) making the cluster identity robust. To further elaborate this approach, a new supplementary figure 1C shows annotations of clusters using both RNA and surface markers.
To potentially address the issue of stability of clusters and gene expression, we compared the marker genes for major clusters from nBM from this study (supplementary table 4, Warfvinge et al.) with those described recently in a scRNA-seq study by Krishnan et al. supplementary table 8, Blood, 2023 using Cell Radar, a tool that identifies and visualizes which hematopoietic cell types are enriched within a given gene set (description: https://github.com/KarlssonG/cellradar
Direct link: https://karlssong.github.io/cellradar/). To compare, we used our in-house gene list for the major clusters as well as mapped the same number of top marker genes based on log2FC from corresponding cluster from Krishnan et al. as inputs to Cell Radar. The Cell Radar plot outputs are shown below.
Author response image 1.
This approach showed broad similarities across clusters from this study with their counterparts from the other study suggesting the cluster identities reported here are likely to be robust. Please note these figures are for reviewer response only and not included in the final manuscript.
Also in the Discussion, it would be interesting for the authors to consider what's next: what type of validation would be needed to make these studies translatable to the clinic? Is there a clever way to use these data to design a faster/cheaper assay?
Our findings on CD26+ and CD35+ surface markers to enrich BCR::ABL1+ and BCR::ABL1- cells suggest a simpler, faster and cheaper FACS panel can possibly quantify leukemic and non-leukemic stem cells in CML patients. We anticipate that future investigations, clinical studies might examine whether CD26CD35+ cells could be plausible candidates for restoring normal hematopoiesis once the TKI therapy diminishes the leukemic load, and whether patients with low counts of CD35+ cells at diagnosis have a relatively higher chance of developing hematologic toxicity such as cytopenia during therapy.
We briefly mentioned this possibility in the discussion; however, we have now moved it to another paragraph to highlight the same. Please see paragraph 5 in the revised manuscript.
Reviewer 3:
Summary:
In this study, Warfvinge and colleagues use CITE-seq to interrogate how CML stem cells change between diagnosis and after one year of TKI therapy. This provides important insight into why some CML patients are "optimal responders" to TKI therapy while others experience treatment failure. CITE-seq in CML patients revealed several important findings. First, substantial cellular heterogeneity was observed at diagnosis, suggesting that this is a hallmark of CML. Further, patients who experienced treatment failure demonstrated increased numbers of primitive cells at diagnosis compared to optimal responders. This finding was validated in a bulk gene expression dataset from 59 CML patients, in which it was shown that the proportion of primitive cells versus lineage-primed cells correlates to treatment outcome. Even more importantly, because CITE-seq quantifies cell surface protein in addition to gene expression data, the authors were able to identify that BCR/ABL+ and BCR/ABL- CML stem cells express distinct cell surface markers (CD26+/CD35- and CD26-/CD35+, respectively). In optimal responders, BCR/ABL- CD26-/CD35+ CML stem cells were predominant, while the opposite was true in patients with treatment failure. Together, these findings represent a critical step forward for the CML field and may allow more informed development of CML therapies, as well as the ability to predict patient outcomes prior to treatment.
Strengths:
This is an important, beautifully written, well-referenced study that represents a fundamental advance in the CML field. The data are clean and compelling, demonstrating convincingly that optimal responders and patients with treatment failure display significant differences in the proportion of primitive cells at diagnosis, and the ratio of BCR-ABL+ versus negative LSCs. The finding that BCR/ABL+ versus negative LSCs display distinct surface markers is also key and will allow for a more detailed interrogation of these cell populations at a molecular level.
Weaknesses:
CITE-seq was performed in only 9 CML patient samples and 2 healthy donors. Additional samples would greatly strengthen the very interesting and notable findings.
Reviewer #3 (Recommendations For The Authors):
My only recommendation is to bolster findings with additional CML and healthy donor samples.
CITE-seq was performed in only 9 CML patient samples and 2 healthy donors. Additional samples would greatly strengthen the very interesting and notable findings.
We thank the reviewer for the positive assessment of our manuscript. As mentioned in response to comments from reviewer 1 and 2, CITE-seq remains an reource consuming single cell method potentially limiting the number of patients to be analyzed. However, during the revision process, we have increased the number of patient material analyzed for other assays; these include increased number to investigate the ratio between CD35+ and CD26+ populations at diagnosis, and 3 months of TKI therapy, qPCR for BCR::ABL1, and patients examined for GAS2, one of the top genes expressed in CML cells. Thus, >80 patient samples across different assays have been analyzed to strengthen the conclusions. (Please see comment to reviewer 1 for more details)
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Reviewer #1 (Public Review):
Summary:
This manuscript by Warfvinge et al. reports the results of CITE-seq to generate single-cell multi-omics maps from BM CD34+ and CD34+CD38- cells from nine CML patients at diagnosis. Patients were retrospectively stratified by molecular response after 12 months of TKI therapy using European Leukemia Net (ELN) recommendations. They demonstrate heterogeneity of stem and progenitor cell composition at diagnosis, and show that compared to optimal responders, patients with treatment failure after 12 months of therapy demonstrate increased frequency of molecularly defined primitive cells at diagnosis. These results were validated by deconvolution of an independent previously published dataset of bulk transcriptomes from 59 CML patients. They further applied a BCR-ABL-associated gene signature to classify primitive Lin-CD34+CD38- stem cells as BCR:ABL+ and BCR:ABL-. They identified variability in the ratio of leukemic to non-leukemic primitive cells between patients, showed differences in expression of cell surface markers and determined that a combination of CD26 and CD35 cell surface markers could be used to prospectively isolate the two populations. The relative proportion of CD26-CD35+ (BCR:ABL-) primitive stem cells was higher in optimal responders compared to treatment failures, both at diagnosis and following 3 months of TKI therapy.
Strengths:
The studies are carefully conducted and the results are very clearly presented. The data generated will be a valuable resource for further studies. The strengths of this study are the application of single-cell multi-omics using CITE-Seq to study individual variations in stem and progenitor clusters at diagnosis that are associated with good versus poor outcomes in response to TKI treatment. These results were confirmed by deconvolution of a historical bulk RNAseq data set. Moreover, they are also consistent with a recent report from Krishnan et al. and are a useful confirmation of those results. The major new contribution of this study is the use of gene expression profiles to distinguish BCR-ABL+ and BCR-ABL- populations within CML primitive stem cell clusters and then applying antibody-derived tag (ADT) data to define molecularly identified BCR:ABL+ and BCR-ABL- primitive cells by expression of surface markers. This approach allowed them to show an association between the ratio of BCR-ABL+ vs BCR-ABL- primitive cells and TKI response and study dynamic changes in these populations following short-term TKI treatment.
Weaknesses:
The number of samples studied by CITE-Seq is limited. However, the authors have confirmed their key observations in additional samples. The BCR-ABL+ versus BCR-ABL- status of cells was not confirmed by direct sequencing for BCR-ABL. However, we recognize that the methodologies to perform these analyses on single cells is still evolving and the authors have shown that CD26 and CD35 expression can consistently identify BCR-ABL+ versus BCR-ABL- cells. It will be of interest to learn whether the GEP and surface markers identified here can distinguish BCR-ABL+ primitive stem cells later in the course of TKI treatment.
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Reply to the reviewers
1. Point-by-point description of the revisions
Reviewer #1:
Evidence, reproducibility and clarity (Required):
In this manuscript Czajkowski et al explore the role of the doublecortin-family kinase ZYG-8 during meiosis in C. elegans Oocytes. First by studying available temperature-sensitive mutants and then by generating their own strain expressing ZYG-8 amenable to auxin-inducible degradation, they establish that defects in ZYG-8 lead to defects in spindle assembly, such as the formation of multipolar spindles, and spindle maintenance, in which spindles elongate, fall apart, and deform in meiosis. Based on these observations the authors conclude that ZYG-8 depletion leads to excessive outward force. As the lab had previously found that the motor protein KLP-18 generates outside directed forces in meiosis, Czajkowski et al initially speculate that ZYG-8 might regulate KLP-18. KLP-18 depletion generally leads to the formation of monopolar spindles in meiosis. Intriguingly, when the authors co-deplete ZYG-8 they find that in some cases bipolarity was reestablished. This led to the hypothesis that yet another kinesin, BMK-1, the homolog of the mammalian EG-5, could provide redundant outward directed forces to KLP-18. The authors then study the effect of ZYG-8 and KLP-18 co-depletion in a BMK-1 mutant background strain and observe that bipolarity is no longer reestablished under these conditions, suggesting that BMK-1 generates additional outward directed forces. The authors also conclude that ZYG-8 inhibits BMK-1. To follow up on this Czajkowski et al generate a ZYG-8 line that carries a mutation in the kinase domain, which should inhibit its kinase activity. This line shows similar effects in terms of spindle elongation but reduced impact on spindle integrity, reflected in minor effects on the number of spindle poles and spindle angle. The authors conclude that ZYG-8's kinase activity is required for the function of ZYG-8 in meiosis and mitosis. Overall, the paper is well written, and the data is presented very clearly and reproducible. The experiments are adequately replicated, and statistical analysis are adequate. *The observations are very interesting. However, the authors could provide some additional insight into the function of ZYG-8. This paper is strongly focused on motor generated forces within the spindle and tries to place ZYG-8 within this context, but there is compelling evidence from other studies that ZYG-8 also affects microtubule dynamics, which would have implications for spindle assembly and structure. The paper would strongly benefit from the authors exploring this role of ZYG-8 in the context of meiosis further. If the authors feel that this would extend beyond the scope of this paper, I would suggest that the authors rephrase some of their introduction and discussion to reflect the possibility that changes in microtubule growth and nucleation rates could explain some of the phenotypes (think of katanin) and effects and that therefore it can not necessarily be concluded that BMK-1 is inhibited by ZYG-8. *
We thank the reviewer for these positive comments on our manuscript and on the rigor of our data. We also thank them for the excellent suggestion to explore a potential role for microtubule dynamics. As detailed below in response to the specific points, we performed new experiments to explore this possibility, and found via FRAP analysis that there were substantial changes in microtubule dynamics upon ZYG-8 depletion. We have therefore added these new data and have re-written major parts of the manuscript to incorporate a discussion of microtubule dynamics throughout the paper (introduction, results, model, discussion). Our data now support two roles for ZYG-8 in regulating acentrosomal spindle assembly and stability - one in modulating microtubule dynamics and the other in tuning forces (either directly or indirectly). We are grateful to the reviewer for motivating us to do these experiments, as they have added a whole new angle to the manuscript and have greatly increased its impact, as we now have a fuller understanding of how ZYG-8 contributes to oocyte meiosis.
Major points:
*1.) Zyg-8, as well as the mammalian homolog DCLK-1, has been reported to play an important role for microtubule dynamics. While the introduction mentions its previously shown role in meiosis and mitosis, it is totally lacking any background on the effect on microtubule dynamics. The authors mention these findings in the discussion, but it would be helpful to incorporate this in the introduction as well. As an example, Goenczy et al 2001 demonstrated that ZYG-8 is involved in spindle positioning but also showed its ability to bind microtubules and promote microtubule assembly. Interestingly, like the authors here, Goenczy et al concluded that while the kinase domain contributes to, it is not essential ZYG-8's function. Also, Srayko et al 2005 (PMID 16054029) demonstrated that ZYG-8 depletion led to reduced microtubule growth rates and increased nucleation rates in C. elegans mitotic embryos. And in mammalian cells DCLK-1 was shown to increase microtubule nucleation rate and decrease catastrophe rate, leading to a net stabilization of microtubules (Moores et al 2006, PMID: 16957770). It would be great if the authors could add to the introduction that ZYG-8 has been suggested to affect microtubule dynamics. *
We agree that this is a great idea. As the reviewer suggested, we decided to explore the possibility that ZYG-8 impacts microtubule dynamics within the oocyte spindle. We depleted ZYG-8 and performed FRAP experiments to determine if there were effects on microtubule turnover. We found that loss of ZYG-8 caused a dramatic decrease in the spindle's ability to recover tubulin, both at the spindle center and at the spindle poles (shown in a new Figure 7). We made substantial changes to the manuscript when adding these new data - the manuscript now discusses ZYG-8's role in modulating microtubule dynamics in the introduction, results, discussion, and model (Figure 9), and we added all of the references suggested by the reviewer. We think that the manuscript is greatly improved due to these additions and changes.
*2a.) The authors initially study two different ts alleles, or484ts and b235ts. The experiments clearly show a significant increase in spindle length in both strains. However, the or484 strain had been previously studied (McNally et al 2016, PMID: 27335123), and only minor effects on spindle length were reported (8.5µm in wt metaphase and 10µm in zyg-8 (or484)). How do the authors explain these differences in ZYG-8 phenotype. Even though the ZYG-8 phenotype is consistent throughout this paper it would be good to explain why the authors observe spindle elongation, fragmentation and spindle bending in contrast to previous observations. *
The reviewer is correct that McNally et.al. (2016) noted only minor effects on spindle length and did not report observing spindle bending or pole defects. However, the images presented in their paper of spindles in the zyg-8(or484) mutant (in Figure 8B) only showed spindles after they had already shrunk in preparation for anaphase; it is possible that these spindles had pole or midspindle defects prior to this shrinking, and that the authors did not note those phenotypes because their analysis focused on anaphase. In contrast, since the goal of our study focused on how ZYG-8 impacts spindle assembly and maintenance, we looked carefully at spindle morphology and quantified a larger number of metaphase spindles (in their study, only 12 metaphase spindles were measured, since metaphase was not the focus of their manuscript). Recently (after we submitted our manuscript), another study from the McNally lab was published, where they did note metaphase defects following ZYG-8 inhibition (though they did not describe the defects in detail or explore why they happened). We now mention and cite this new paper (Li et.al., 2023) in our manuscript, to show that our findings are consistent with the work of others in the field.
*2b.) As a general note, it would be helpful if the authors could indicate if the spindles are in meiosis I or II. The only time where this is specifically mentioned is in Video 7, showing a Meiosis II spindle, which makes me assume all other data is in Meiosis I. Adding this to the figures would also help to distinguish if some of the images, i.e. Figure 1B, show multipolar spindles due to failed polar body extrusion. If this is the case then the quantification of number of poles should maybe reflect different possibilities, such as fragmented poles vs. multiple poles because two spindles form around dispersed chromatin masses. *
We agree that it is a good idea to clarify this issue. For all of our experiments, we analyzed both MI and MII spindles. However, there were no noticeable differences in phenotype between MI and MII spindles for any of our mutant/depletion conditions - we observed bent spindles, elongated spindles, and extra poles in both MI and MII following ZYG-8 inhibition. Therefore, for the quantifications presented in the manuscript (spindle length, spindle angle, number of poles), we pooled our MI and MII data. We have now added this information to the manuscript for clarity (lines 97-99 and 139-141). In addition, we have added new images to Figure 1B that show examples of MII spindles (both at the permissive and restrictive temperature), to show that the phenotypes are indistinguishable between MI and MII.
We agree with the reviewer that one of the spindles in the original Figure 1B looked like it could have resulted from failed polar body extrusion (the chromosomes appeared to be in two masses, something we did not originally notice, so theoretically each mass could have organized its own spindle). To determine if this was the case, we looked closely at the chromosomes in this image; we confirmed that there were only 6 chromosomes, and that all were bivalents (these can be distinguished from MII chromosomes based on size). Therefore, this spindle was not multipolar due to an issue with polar body extrusion. However, to prevent future confusion, we picked a different representative spindle (where the bivalents we not grouped into two masses), and we added a new column to the figure that shows the DNA channel in grayscale (so it is easier to see and count the chromosomes). We also now note in the materials and methods how we were able to distinguish between MI and MII in our experiments (chromosome count, size, presence of polar bodies), so that it is clear that none of our phenotypes result from failed polar body extrusion (lines 600-603).
*3) The authors generate a line that carries a mutation leading to a kinase dead version of ZYG-8. It would be great if the authors could further test if this version is truly kinase dead. What is interesting is that the kinase dead version the authors create has less effect on the numbers of pole than the zyg-8 (b235)ts strain, which carries a mutation in a less conserved kinase region. Overall, it seems that the phenotypes are very similar, independent on mutations in the microtubule binding area, kinase area or after AID. This could of course be due to all regions being important, i.e. microtubule binding is required for localizing kinase-activity. Generating mutant versions of the target proteins, for example here BMK-1, that can not be phosphorylated or are constitutively active as well as assessment of changes in protein phosphorylation levels in the kinase dead strain would be helpful to provide deeper insight into potential regulation of proteins by ZYG-8. *
We agree that it would be ideal to test whether the D604N mutant is truly kinase dead. However, in the interest of time, we ask to be allowed to skip that experiment. The analogous residue has been mutated in mammalian ZYG-8 (DCLK1), and has been shown to cause DCLK1 to be kinase dead in vitro; this is a highly conserved aspartic acid in the central part of the catalytic domain, so we infer that the mutation we made in ZYG-8 should be kinase dead as well. However, since we did not test this directly, we softened our language in the manuscript, explaining that we "infer" that it is kinase dead rather than stating definitively that it is. With regard to the zyg-8(b235)ts mutant having a stronger phenotype, we think that it is possible that this mutation destabilizes a larger portion of the protein (rather than just affecting the catalytic activity), since the phenotypes in this mutant are similar to depletion of the protein in the ZYG-8 AID strain. Therefore, we think that our D604N mutant reveals new information about the role of kinase activity, since it is a more specific mutation that should likely only affect catalytic activity and not the rest of the protein (based on the previous work on DCLK1).
While we appreciate the suggestion from the reviewer to generate mutant versions of potential target proteins, we ask that this be considered beyond the scope of the study. Now that we know that ZYG-8 not only affects forces within the spindle (maybe BMK-1) but also microtubule dynamics, there are many potential targets - it would require a lot of work to figure out what the relevant targets are. Instead of exploring this experimentally in this manuscript, we added a new section to the discussion where we speculate on what some of these targets could be, to motivate future studies.
*4a) The authors state that "BMK-1 provides redundant outward force to KLP18". Redundancy usually suggests that one protein can take over the function of another one when the other is not there. In these scenarios a phenotype is often only visible when both proteins are depleted as each can take over the function of the other one. Here however the situation seems slightly different, as depletion of BMK-1 has no phenotype while depletion of KLP-18 leads to monopolar spindles. If BMK-1 would normally provide outward directed forces, would this not be visible in KLP-18 depleted oocytes if they were truly redundant? I assume the authors hypothesize that ZYG-8 inhibits BMK-1 and thus it can not generate outward directed forces. In this case, do the authors envision that ZYG-8 inhibits BMK-1 prior to or in metaphase or only in anaphase or throughout meiosis? Do they speculate, that BMK-1 is inhibited in anaphase and only active in metaphase? *
The reviewer makes an excellent point - we agree that we should not use the word "redundant" in this context, so we have removed this phrasing from the manuscript. We hypothesize that BMK-1 can provide outward forces during spindle assembly but is not capable of providing as much force as KLP-18 (the primary force-generating motor). We infer this based on our experiments where we co-deplete KLP-18 and ZYG-8 (using long-term depletion). Although BMK-1 is presumably activated under these conditions, it is not able to restore spindle bipolarity (there are outward forces generated, which results in minus ends being found at the periphery of the monopolar spindle, but spindles are not bipolar).
Therefore, BMK-1 is not able to fully replace the function of KLP-18 during spindle assembly. Interestingly, our experiments imply that BMK-1 can better substitute for KLP-18 later on (when ZYG-8 is inhibited); when we remove ZYG-8 from formed monopolar spindles, bipolarity can be restored (an activity dependent on BMK-1). These findings suggest that ZYG-8 plays a more important role in suppressing BMK-1 activity after the spindle forms, to prevent spindle overelongation in metaphase. We have edited the manuscript to better explain these points.
*4b) In addition, Figure S4 somewhat argues against a role for ZYG-8 in regulating BMK-1. ZYG-8 depletion supposedly leads to increased outward forces due to loss of BMK-1 inhibition, thus co-depletion of ZYG-8 with BMK-1 should rescue the increased spindle size at least to some extent, however neither increase in spindle length nor increase in additional spindle pole formation are prevented by co-depletion of BMK-1 suggesting that BMK-1 is not generating the forces leading to spindle length increase. Thus, arguing that after all ZYG-8 does not regulate BMK-1. This should be discussed further in the paper and the authors should consider changing the title. At this point the provided evidence that ZYG-8 is regulating motor activity is not strong enough to make this claim. *
The reviewer is correct that Figure S4 shows that the effects of depleting ZYG-8 on bipolar spindles (spindle elongation and pole/midspindle defects) cannot solely be explained by a role for ZYG-8 in regulating BMK-1 - this was the point that we were trying to make when we included this data in the original manuscript. However, we previously did not know what this other role could be, and therefore we only speculated on other potential roles in the discussion. Now that we have done FRAP experiments and have found that ZYG-8 also affects microtubule dynamics in the oocyte spindle, we now have a better explanation for the data presented in Figure S4 - it makes sense that deleting BMK-1 would not rescue the effects of ZYG-8 depletion, since we have evidence that ZYG-8 also regulates microtubule dynamics. We now clearly explain this in the revised manuscript and we have changed the title to make it clear that ZYG-8 plays multiple roles in oocytes.
*5) The authors are proposing that ZYG-8 regulates/ inhibits BMK-1, however convincing evidence for an inhibition is not provided in my opinion and the effect of ZYG-8 on BMK-1 could be indirect. To make a compelling argument for a regulation of BMK-1 the authors would have to investigate if ZYG-8 interacts and/ or phosphorylates BMK-1 (see 7) and if this affects its dynamics. In addition, given the reported role of ZYG-8 on microtubule dynamics it would be very important that the authors consider studying the effect of ZYG-8 degradation on microtubule dynamics. Tracking of EBP-2 would be good, however this is very difficult to do inside meiotic spindles due to their small size. In addition, the authors could maybe consider some FRAP experiments, which could provide insights into microtubule dynamics and motions, which could be indicative of outward directed forces/ sliding. *
We thank the reviewer for these comments as they motivated us to explore a role for ZYG-8 in modulating microtubule dynamics. The reviewer is correct that tracking EBP-2 in the very small meiotic spindle is not possible due to technical limitations, so we took the suggestion to perform FRAP. These experiments revealed that microtubule turnover in the spindle is greatly slowed following ZYG-8 depletion, suggesting a global stabilization of microtubules (data presented in a new Figure 7). This change in dynamics could contribute to the observed spindle phenotypes, which we now explain in detail in the manuscript. Given these new findings, we also now note that the effects we see on BMK-1 activity could be indirect (i.e. maybe increasing the stability of microtubules allows motors to exert excess forces). We now clearly discuss these various possibilities in the discussion.
Summary: Additional requested experiments:
- Interaction/ phosphorylation of BMK-1 by ZYG-8, i.e. changes of BMK-1 phosphorylation in absence of ZYG-8, BMK-1 mutations that may prevent phosphorylation by ZYG-8.
- Assessment of microtubule dynamics (EBP-2, FRAP, length in monopolar spindles...)
- Kinase activity of the kinase dead ZYG-8 strain (OPTIONAL) We assessed the role of ZYG-8 in microtubule dynamics (bullet point #2). Because this new analysis revealed that ZYG-8 plays multiple roles in the spindle, we decided not to further investigate whether ZYG-8 phosphorylates BMK-1, since the manuscript now no longer argues that this is ZYG-8's major function. We also did not assess the kinase activity of the D604N mutant since this has been done previously for DCLK1, and instead we softened the language in manuscript when describing this mutant.
Minor points:
*1) In Figure 4C it seems that the ZYG-8 AID line as well as the zyg-8 (or848)ts already have a phenotype (increased ASPM-1 foci) in absence of auxin/ at the permissive temperature. Does this suggest that the ZYG-8 AID as well as the zyg-8 (or848) strains are after all slightly defective (even if Figure 1, S1 and S2 argue otherwise) and thus more responsive to the loss of KLP-18? *
The reviewer is correct that the ZYG-8 AID strain (without auxin) and zyg-8(or848)ts strain (at the permissive temperature) are slightly defective in the klp-18(RNAi) monopolar spindle assay. To more rigorously determine whether these strains were also defective in other assays, we generated new graphs comparing the spindle lengths and angles of the two temperature sensitive strains at the permissive temperature to wild-type (N2) worms. These data are now shown in Figure S1 (new panels F and G). A comparison of our ZYG-8 AID strain to a control strain (both in the absence of auxin) are shown in Figure S2 (panels C and D). In this analysis, there wasn't a significant difference for either of these comparisons (i.e. the spindle lengths and angles were all equivalent). We do not know why these strains appear to be slightly defective in the monopolar spindle assay, though perhaps this assay is more sensitive and can detect very mild defects in protein function.
*2) The authors observe that in preformed monopolar spindles degradation of ZYG-8 can sometimes restore bipolarity. This observation is very interesting but why do the authors not observe a similar phenotype in long-term ZYG-8 AID; klp-18 (RNAi) or zyg-8(or484)ts; klp-18(RNAi). In the latter conditions bipolarity does not seem to occur at all. Do the authors think this is due to differences in timing of events? *
We thank the reviewer for highlighting this point. We do think that our data suggest that ZYG-8 plays a more important role maintaining the spindle that it does in spindle formation; we have now more clearly explained this in the manuscript (detailing the differences in phenotypes we observe when we deplete ZYG-8 prior to spindle assembly or after the spindle has already formed, lines 180-189 and 227-231). To emphasize this point further, we have also included a graph in Figure S3G that directly compares the number of poles per spindle in long-term auxin treated spindles to short-term auxin treated spindles (with and without metaphase arrest).
*3) Based on the Cavin-Meza 2022 paper it looks like depletion of KLP-18 in a BMK-1 mutant background does not look different from klp-18 (RNAi) alone. However, looking at Video 8, it looks like spindles "shrink" in absence of KLP-18 and BMK-1. Or is this due to any effects from the ZYG-8 AID strain? This can also be seen in Video 9. *
The reviewer highlights a fair point that was not clearly explained in our manuscript. In normal monopolar anaphase, chromosomes move in towards the center pole as the spindle gets smaller (C. elegans oocyte spindles shrink in both bipolar and monopolar anaphase); this was previously described in Muscat et.al. 2015, and, as the reviewer noted, in Cavin-Meza et.al. 2022 (in a strain with the bmk-1 mutation). We see this same monopolar anaphase behavior in the ZYG-8 AID strain (Figure 6). We have now better explained normal monopolar anaphase progression and we have cited the Muscat et.al. paper in the relevant sections of the manuscript (lines 221-223 and 714-717).
*4) Line 311: " ZYG-8 loads onto the spindle along with BMK-1, and functions to inhibit BMK-1 from over elongating microtubules during metaphase." Maybe this sentence could be re-phrased as it currently sounds like BMK-1 elongates (polymerizes) microtubules. *
In re-writing the manuscript and emphasizing that there are multiple for ZYG-8 (in addition to regulating forces within the spindle), we removed this sentence.
*5) Line 313: "Intriguingly, in C. elegans oocytes and mitotically-dividing embryos, BMK-1 inhibition causes faster spindle elongation during anaphase, suggesting that BMK-1 normally functions as a brake to slow spindle elongation (Saunders et al., 2007; Laband et al., 2017). Further, ZYG-8 has been shown to be required for spindle elongation during anaphase B (McNally et al., 2016). Our findings may provide an explanation for this phenotype, since if ZYG-8 inhibits BMK-1 as we propose, then following ZYG-8 depletion, BMK-1 could be hyperactive, slowing anaphase B spindle elongation." This paragraph could be modified for better clarity. It is not clear how the findings of the authors, BMK-1 provides outward force but is normally inhibited by ZYG-8, align with the last sentence saying "following zyg-8 depletion, BMK-1 could be hyperactive slowing anaphase B spindle elongation", should it not increase elongation according to the authors observations? *
In re-writing the manuscript to incorporate our new data showing that ZYG-8 plays a role in modulating microtubule dynamics, we also re-wrote this discussion so that there would be less emphasis on the potential connection between ZYG-8 and BMK-1. In making these edits to expand the focus of the manuscript, we removed this section of the discussion.
Reviewer #1 (Significance (Required)): *In this manuscript Czajkowski et al explore the role of the doublecortin-family kinase ZYG-8 during meiosis in C. elegans Oocytes. The authors conclude that BMK-1 generates outward directed force, redundant to forces generated by KLP-18, and that ZYG-8 inhibits BMK-1. The authors conclude that ZYG-8's kinase activity is required for the function of ZYG-8 in meiosis and mitosis. This research is interesting and provides some novel insight into the role of ZYG-8. In particular the observed spindle elongation and subsequent spindle fragmentation are novel and had not yet been reported. Also, the observation that degradation of ZYG-8 in monopolar klp-18(RNAi) spindles can restore bipolarity is novel and interesting, as well as the observation that this is somewhat dependent on the presence of BMK-1. This will be of interest to a broad audience and provides some new insight into the role of importance of ZYG-8 and BMK-1. The limitation of the study is the interpretation of the results and the lack of solid evidence that the observed phenotypes are due to ZYG-8 regulation motor activity, as the title claims. To support this some more experiments would be required. In addition, ZYG-8 has been reported to affect microtubule dynamics, which can certainly affect the action of motors on microtubules. This line of research is not explored in the paper but would certainly add to its value.
Field of expertise: Research in cell division *
We thank the reviewer for their positive comments on the impact and novelty of our findings. We hope that the additional experiments we performed and the revisions we made to the text thoroughly address the reviewer's concerns and that they deem the revised manuscript ready for publication.
Reviewer #2 (Evidence, reproducibility and clarity (Required)): *In this manuscript, the authors explore the requirement for doublecortin kinase Zyg8 in C elegans oocytes. Oocytes build meiotic spindles in the absence of centrosomes, and therefore unique regulation occurs during this process. Therefore, how spindles are built and its later stability are an area of active investigation in the field. Using mutant alleles of Zyg8 and auxin-induced degron alleles, the authors demonstrate that this kinase is required to negatively regulate outward pole forces through BMK1 kinesin and that it has other functions to still explore. Overall, I find that this study takes an elegant genetic approach to tackling this important question in oocyte biology. I have some comments to consider for making the MS clear to a reader. *
We thank the reviewer for these positive comments on our approach and the importance of our research question. We have attempted to address all of the reviewer's suggestions and we think that they increase the clarity of the manuscript.
Major Comments:
*1.) Although I like the graphs describing the altered angles of the spindles, it falls short in fully assessing the phenotype in a meaningful statistical way. Could the authors also graph the data to show statistical significance in the angles between conditions? Perhaps by grouping them into angle ranges and performing an Anova test? This is important in Figure 2E where it is not obvious that there is a difference. *
The reviewer makes a good point - we have now addressed this concern by performing ANOVA tests to compare conditions on each of the angle graphs. Results of these tests have been reported in the corresponding figure legends. This analysis has confirmed all of the statements we made in the original manuscript. In Figure 1D and S1D, spindle angles were significantly different in the zyg-8 temperature sensitive mutants at the restrictive temperature, and in Figure 2, the angles were significantly different between the "minus auxin" and "plus auxin" conditions. This differs from Figure 7, where there was no significant difference in spindle angle between control spindles and kinase dead mutant spindles (p-value >0.1).
*2.) The authors do not discuss the significance of the altered spindle angles which I think is an interesting phenotype. Would this be a problem upon Anaphase onset? What is known about spindle angle and aneuploidy or cell viability? Has this phenotype been described before in oocytes or somatic cells? Does depletion of other kinesin motors cause this? *
The reviewer brings up a good point that warrants more discussion in the manuscript. We agree that the angled spindles are an interesting phenotype; we believe that they could be a result of the spindle elongating to a point where the spindle center becomes weakened, suggesting that the severity of the angle is representative of the severity of spindle elongation. Alternatively, the angled spindles could be a result of the loss of spindle stability factors, such as the doublecortin domain of ZYG-8. This domain is known to have microtubule binding activity; this could be required to maintain stable crosslinked microtubules in the spindle center, such that when ZYG-8 is depleted, the spindle more easily comes apart as the spindle elongates. We now discuss these possibilities in the revised manuscript.
To the reviewer's second point, we did not examine anaphase outcomes in our manuscript. However, this was recently explored by another lab (in a study that was published after we submitted our manuscript). This study showed that spindles lacking ZYG-8 were able to initiate anaphase and segregate chromosomes (McNally et.al., 2023, https://doi.org/10.1371/journal.pgen.1011090). Perhaps when the spindle shrinks at anaphase onset, the spindle is able to reorganize and largely correct the angle defect, enabling bi-directional chromosome segregation. Interestingly, however, McNally et.al. did report conditions under which spindle bending in anaphase resulted in polar body extrusion errors. The authors reported that BMK-1, which is known to act as a brake to prevent spindle oveelongation in anaphase, is required to prevent bent spindles during anaphase by resisting the forces of cortical myosin on the spindle. Thus, there is precedence for the idea that spindle needs to remain straight throughout anaphase, to ensure proper chromosome segregation.
*3.) How is embryo spindle positioning determined? It is not clear from the images that there is a defect so I'm not sure what to look for. Is there a way to quantify this? *
In the original manuscript, spindle positioning within the embryo was determined qualitatively by eye, which we agree was not a precise measure. To address the reviewer's comment, we re-analyzed our images and assessed the position of the spindle within each embryo quantitatively - these data are now shown in Figure 8H and Figure S2B. Spindle position was quantified by analyzing images using Imaris software. The center of the spindle was set by creating a Surface of the DNA signal, and finding the center of that signal. The cell center was determined by measuring the length of the embryo along the long axis and the width of the embryo along the short axis, and setting the center as the halfway point of the total length and width of the embryo. Distance from spindle center to cell center was then measured and graphed. This quantification confirmed the claims we made in our original manuscript - both auxin-treated ZYG-8 AID spindles and ZYG-8 kinase-dead mitotic spindles were significantly mispositioned. The details of how we performed this quantification have been added to the materials and methods.
*4.) In Figure 1, it appears that there are 2 spindles. Are these MI and MII spindles or ectopic spindles? How do the authors know which one to measure? *
We thank the reviewer for pointing this out. Reviewer 1 had a similar comment, and we now understand that using that image was misleading, as it looked like as if were two separate MII spindles formed following a failed polar body extrusion event. We have gone through all of our images to stage the oocytes by looking at their chromosome morphology (i.e., to distinguish MI and MII) - the image in question had 6 bivalents and was therefore in Meiosis I; we think that this was a single spindle where the chromosomes happened to cluster into two masses. However, to prevent further confusion, we have replaced this image with a different representative image. In spindles like this with multiple poles, we measure the dominant axis of the spindle (if there are multiple poles, we pick the most prominent ones for the angle measurement). For additional details please see our response to Reviewer 1 major point #2b.
*5.) The authors show depletion of Zyg8 by western (long) and loss of Gfp (long and short), but don't do so for the acute treatment. I'm guessing this is because the Gfp tag is taken by the spindle marker. The authors should either demonstrate or explain how they know that the acute depletion is effective in removing Zyg8 protein. *
The reviewer makes a valid point. However, we are unable to see ZYG-8 depletion via acute auxin treatment using live imaging, as ZYG-8 localization is too dim and diffuse to see on the spindle using our typical live imaging parameters (we attempted to do this in a version of the ZYG-8 AID strain that has mCherry::tubulin and GFP::ZYG-8, so that there was no other spindle protein tagged with GFP). To see any GFP::ZYG-8 signal, we had to increase the laser power and exposure time well above what we typically use for live imaging - in doing this, we noticed that there was a limit to how high we could go before the cell began dying during the imaging time course, evident by a lack of chromosome movement, lack of tubulin turnover, and a general increase in tubulin signal throughout the cytoplasm. We do believe that ZYG-8 is being depleted using acute auxin treatment, however, as we see spindle defects very quickly upon dissection of the oocytes into auxin - we just unfortunately don't have a good way of quantifying this given these technical limitations. We have now added information to the materials and methods noting that we cannot see GFP::ZYG-8 under our live imaging conditions (lines 552-561), so that the reader better understands this caveat.
*6.) In video 2, the chromosome signal is dimmer in the auxin treatment compared to video 1. Why is this? Is it just an experimental artifact or is there something significant about this? If it is because of video choice, consider replacing this one. *
We thank the reviewer for their keen observations. The chromosome signal being dimmer in the auxin treatment is an experimental artifact - the brightness of the signal can vary depending on how far the spindle is from the slide (this can vary from video to video, and can also change over the time course of one video if the spindle moves during filming). Because of this, movies taken at the same intensity and exposure conditions may appear to have varying levels of brightness. So that readers of the manuscript can better see the chromosomes in this video, we have brightened the chromosome channel in this movie and noted this in the materials and methods (lines 549-551).
7.) Please consider color palette changes for color-blind readership.
We agree that it is important to present data in a way that can be appreciated by color-blind readers. Although we would prefer not to have to alter every image in our paper at this point, we have provided all important individual channels in grey scale. We are also planning to adopt a change in color palette for future papers.
Reviewer #2 (Significance (Required)):
*The strengths of this manuscript include use of multiple genetic approaches to establish temporal requirements of ZYG8 and which pathway it is acting through. Additionally, the videos and images make the phenotypes clear to evaluate. A minor limitation is that we don't know if the ZYG8 and BMK1 genetic interaction is a direct phosphorylation or not. This MS is an advancement to the field of spindle building and stability, and is particularly relevant to human oocyte quality and fertility. Previous work has shown that human oocyte spindles are highly unstable, but it is challenging to dissect genetic interactions and to conduct mechanistic studies in human oocytes. Therefore, the work here, although conducted in a nematode, can shed light on mechanism as to why human oocyte spindles are unstable and associated with high aneuploidy rates. Based on my expertise in mammalian oocyte biology, I am confident that work presented here will be of high interest to people in the field of meiotic spindle building, aneuploidy and fertility. It also will have broader interest to folks in the areas of kinesin biology, general microtubule and spindle biology. *
We thank the reviewer for these positive comments on the strength of our data and the significance of our findings reported in our original manuscript. We think that the improvements that we have made in response to suggestions from all three reviewers has further increased this impact.
Reviewer #3 (Evidence, reproducibility and clarity (Required)):
*Summary: The focus of this paper is the function of a relatively understudied (at least in meiosis) kinase in acentrosomal spindle assembly (Zyg-8, or DCLK1 in mammals) in C. elegans oocytes. The authors use existing ts alleles and a newly generated GFP-Auxin fusion protein, and find that the ts alleles and auxin degron have similar phenotypes. They also examine the interaction with two related kinesins, KLP-18 and BMK-1 in order to investigate the mechanism behind the zyg-8 mutant phenotype. One can probably debate the significance and focus of their conclusions (force balance on the spindle). However, this is an important study because its the first on the meiotic function of a ZYG-8 kinase, and it may open the way to further studies of this kinase and how it regulates multiple kinesins and meiotic spindle assembly. *
We thank the reviewer for these positive comments and for pointing out the potential future impacts of our work. In revising the manuscript, we have broadened the focus of the manuscript - we no longer solely focus on force balance within the spindle. Thus, our revisions have substantially increased the significance and impact of our work, since the manuscript is no longer narrowly focused.
Major points:
*1.) The main concern is the focus that the main defect in zyg-8 depleted oocytes is on outward forces (eg line 134, 277, but many other places in Results and Discussion). The arguments in favor (eg line 269-271) are reasonable. However, these data are not conclusive, and do not rule out regulation of other motor activities, such as bundling, depolymerization or chromosome movement. These are complex phenotypes, and a kinase could have multiple targets and there are often multiple interpretations. This is briefly alluded to in line 372-373 but the authors could do more. Spindle length changes could be caused by different rates of depolymerization or polymerization at the poles or chromosomes. Its not clear how poleward force regulation explains the multiple pole phenotype, although a lack of central spindle integrity could do that. In most of the Results and Discussion, it is not clearly stated on what structures these outward forces are acting. Are these forces effecting kinetochore associated microtubules, or antiparallel overlap microtubules? What do the authors mean by proper force balance? Figure 8 suggests the defect is associated with the amount of overlap and force among antiparallel microtubules - that the forces effected are from the sliding of these microtubules. *
We agree that our original manuscript was too narrowly focused on the idea of force balance and that we did not discuss other potential roles for ZYG-8 in enough detail (except for briefly in our discussion). In response to both this comment and to a suggestion by Reviewer #1, we decided to investigate a potential role for ZYG-8 in modulating microtubule dynamics (which could be another explanation for some of the phenotypes we observed). We performed FRAP to measure the rate of tubulin turnover within the spindle near the center and at the poles. Interestingly, these experiments revealed that loss of ZYG-8 slows the rate of tubulin turnover, suggesting a general stabilization of microtubules. Thus, we have re-written our manuscript to clearly explain that ZYG-8 plays multiple roles in oocyte spindles - with these changes throughout the manuscript (in the introduction, results, and discussion), the paper is now no longer focused primarily on forces. We hypothesize in the discussion that the phenotypes we observe could be a combination of the effects on microtubule dynamics and spindle forces; if microtubules become more stable and motors produce excess outward forces, this may cause stress on the spindle structure that could cause the midspindle to bend and the poles to split (lines 379-382). We also now more clearly explain that the effect ZYG-8 has on spindle forces could be either direct or indirect (e.g., ZYG-8 could directly regulate motors or, by affecting the microtubule tracks themselves, it could affect their ability to exert forces). As for which population of microtubules are affected, we hypothesize that the excess forces act primarily on overlapping antiparallel microtubules (these microtubules run laterally alongside chromosomes in this system), as is represented in the model figure (Figure 9); we attempted to more clearly explain this in the re-written manuscript.
*2.) Based on differences between the long term and short term knockdown phenotypes, the authors suggest ZYG-8 is more important for spindle maintenance. For example, in line 299 the authors note that there is a more severe phenotypes with zyg-8 removed from pre-formed spindles. The authors could improve the presentation of this to allow the reader to appreciate this observation. The data is spread between Figures 2 and 3 without a direct comparison of the data. One solution would be to graph the data (eg # of poles) together in one graph and indicate if there is statistical significance. In the Discussion, the authors could refer to specific figure panels. *
The reviewer is correct that our data suggests that ZYG-8 is more important for spindle maintenance than it is for assembly. As suggested, we made a graph that includes all the pole data from Figures 2 and 3 (long-term auxin, short-term auxin, and metaphase-arrested short-term auxin) - this is now shown in Figure S3D. This makes it easier for the reader to compare these data and appreciate this point. In addition, we added text to the results section, to more clearly explain our rationale for thinking that ZYG-8 plays a more prominent role in spindle maintenance than in assembly (lines 180-189 and 227-231).
*3.) What is the practical difference between acute and short term depletion. Does acute show weaker phenotypes because there is more residual protein? Unfortunately, the effectiveness of Auxin treatment does not appear to be measured for acute or short term. If the acute depletion adds little to Figure 3, or is not much different than long term, then its not clear what it adds to the paper. Later, in Figure 6, why is only short term and acute analyzed. In general, the authors need to provide better rationale for the different auxin conditions, particularly acute and short term (eg. line 135). If they don't add anything, they should consider not presenting them because readers may get confused by the different conditions, why they were done, and what is learned from each one. *
The reviewer brings up a fair point that we agree requires clarification. Descriptions of the different types of auxin experiments is provided in Figure 1A. Long-term AID depletes proteins overnight, so the protein of interest is already missing from the oocyte when the spindle begins to form - this allows us to assess whether the protein is required for spindle assembly. However, to determine if a protein is required to stabilize pre-formed spindles, we need to remove the protein quickly after the spindle forms (using either acute or short-term AID). Acute AID is performed by dissecting oocytes directly into auxin-containing media; this allows us to watch what happens to the spindle live, as the protein is being depleted. However, one limitation is that we can only film for a short time before the oocytes begin to die (oocytes become unhappy with extended light exposure, so we cut off the videos after 15 minutes or so, to ensure that we are not filming past the point where they begin to arrest or die). Therefore, to assess what happens to spindles beyond this point, we perform short-term auxin treatment, where whole worms are soaked in auxin containing solution for 30-45 minutes and then the oocytes are dissected for immunofluorescence; this technique allows us to look at what happens to the spindle after more extended protein depletion (since we are not limited to the 10-15 minute window of filming). We have now clarified this in the manuscript by adding these details to the materials and methods. Unfortunately, it is not technically possible to quantify the extent of protein depletion in acute AID via western blotting since we would not be able to easily collect enough dissected oocytes to make a protein sample. (It is also technically challenging to quantify this via imaging; see our response to Reviewer #2, point #5). However, we assume that we are depleting ZYG-8 since we see dramatic spindle defects immediately upon dissection into auxin.
Minor points:
*3.) I am a little confused about imaging for GFP::tubulin in auxin experiments. Doesn't the ZYG-8 protein also have GFP? Should this be visible in controls? Is it measurable in the experiments? *
The reviewer is correct that the ZYG-8 protein is also tagged with GFP in the GFP::tubulin; mCherry::histone live imaging experiments. However, we found that the GFP::ZYG-8 signal is undetectable using the live imaging conditions we are using. We determined this by analyzing a version of the ZYG-8 AID strain in which tubulin was tagged with mCherry (and thus the only GFP-tagged protein was ZYG-8). Using the same live imaging parameters we use for our movies of GFP::tubulin (same exposure time, laser power, etc), we did not detect any GFP::ZYG-8. We have now added this information to the materials and methods (lines 552-561) to clarify these points for the reader, to prevent further confusion.
*4.) It is nice that the authors validated the results in an emb-30 background with unarrested oocytes. The authors note that the wild-type oocytes undergo anaphase (line 150). The images seem to suggest the auxin treated oocytes do not. Can the authors comment on anaphase in the depletion experiments. Even better, would be to comment on the accuracy of chromosome alignment and segregation. If zyg-8 mutant oocytes complete meiosis, is there any aneuploidy? These are important questions because otherwise the defects in zyg-8 mutants have less significance. *
We thank the reviewer for their comment. Previous work on ZYG-8 in C. elegans examined a role for ZYG-8 in anaphase and showed that this protein is required for anaphase B spindle elongation (McNally et.al. 2016); because this was known when we launched our study, we purposely did not extensively study ZYG-8 in anaphase and instead focused on understanding how ZYG-8 contributes to spindle formation and stability. Our fixed imaging long-term AID experiments revealed that spindles were able to go through anaphase and segregate chromosomes bidirectionally despite the metaphase spindle phenotypes, consistent with this previous work (McNally et.al. 2016) and with another recent paper from the same lab (McNally et.al. 2023). However, we did not examine whether there were chromosome segregation errors. Given that anaphase is not the focus of our paper, we ask that this be deemed beyond the scope of our study.
5.) Later, in line 184, the authors indicate that zyg-8 bipolar spindles "segregate chromosomes". Which images show anaphase I? As noted above, a limitation of these studies is not knowing the outcome of meiosis in these Zyg-8 depletions.
We agree that in the original manuscript it was difficult to see that chromosomes were segregating bidirectionally in our movies and in the still timepoint images presented in Figure 5. Therefore, we brightened the chromosome channel in the relevant videos to make it easier to see the segregating chromosomes. Video 6 shows an oocyte in Meiosis II, as the first polar body can be seen near the spindle in this movie. At 2 minutes, the monopolar spindle becomes bipolar and begins to shrink as it goes into anaphase. Chromosomes begin to move apart and then the spindle elongates. At 11 minutes, you can see that the chromosomes have segregated bidirectionally. Thus, when monopolar spindles reorganize into bipolar spindles under these conditions, they can drive bidirectional chromosome segregation. We did not assess the fidelity of chromosome segregation under these conditions (i.e., whether chromosomes segregated accurately), as the question we were trying to answer in this experiment was whether outward forces sufficient to re-establish bipolarity could be activated upon ZYG-8 depletion (as explained above in response to point #4, we focused our study on trying to understand the effects of ZYG-8 depletion on the spindle, rather than on anaphase). We agree that analyzing anaphase outcomes would be interesting, but we ask that it be considered beyond the scope of this study.
*6.) Line 206 suggests that ZYG-8 inhibits BMK-1. Is a simple explanation that BMK-1 is required for the bipolar spindles observed in the klp-18 zyg-8 AID oocytes? *
Yes, the reviewer is correct that BMK-1 is required for the generation of bipolar spindles in the klp-18(RNAi) ZYG-8 AID conditions. In the original manuscript we extrapolated this result to propose that ZYG-8 regulates BMK-1. However, this comment, as well as feedback from the other reviewers and our new experiments (showing that ZYG-8 also modulates microtubule dynamics) has made us re-think the way we discuss this result, as we now agree that it does not prove this regulation (it is only suggestive). Therefore, in the revised manuscript, we no longer definitely claim that ZYG-8 regulates BMK-1 - we have switched to softer language (stating that ZYG-8 "may regulate" BMK-1, etc.). In the results section we now describe our conclusions as follows: "These data demonstrate that BMK-1 produces the outward forces that are activated upon ZYG-8 and KLP-18 co-depletion and raise the possibility that ZYG-8 regulates BMK-1 either directly or indirectly" (lines 250-252).
*7.) Given that many mitotic and meiotic kinases are localized to specific regions or domains of the spindle, there is only limited discussion of the ZYG-8 localization pattern. Does the ZYG-8 localization pattern provide any insights into its mechanism of promoting spindle assembly? *
The reviewer makes a good point - while we did report ZYG-8 localization, the discussion on the importance of its localization pattern was limited. To address this, we now remind readers in the discussion that ZYG-8 and BMK-1 co-localize throughout meiosis, consistent with the possibility that ZYG-8 could regulate BMK-1. Notably, this localization pattern is also consistent with the observation that ZYG-8 modulates microtubule dynamics across the spindle; this is now also noted in the discussion (lines 358-361).
*8.) Line 96-97 - how much is the ZYG-8 depletion? *
To address this question, we have quantified the amount of ZYG-8 protein in our ZYG-8 AID strain in control, long-term, and short-term auxin treated conditions. The western blot was quantified by comparing the raw intensity of the bands and subtracting the background signal. Short-term auxin depletion resulted in an ~63% reduction in ZYG-8 GFP signal, and long-term depletion resulted in an ~93% reduction in ZYG-8 GFP signal. This has now been reported in the manuscript on lines 785-786.
*9.) Line 140: the authors say spindle length could not be measured, but perhaps it makes more sense to measure half spindle (chromosome to spindle pole). The images do give the impression that the chromosome to pole distance is shorter. *
While we liked this idea and tried to perform these measurements, it turned out to be difficult in practice, since the spindle length measurements are obtained by finding the distance from pole (center of the ASPM-1 staining) to center of the chromosome signal. If you look carefully at our images you will notice that the chromosomes lose alignment following short-term AID; therefore, the chromosomes do not form one mass, which made it very difficult to determine an accurate "center" of the DNA signal. Additionally, in most cases the poles are disrupted such that ASPM-1 is found in many separate masses and/or is diffusely localized around the periphery of the spindle. Because of this, we unfortunately felt that these measurements would not be very accurate and would be hard to interpret.
*10.) Don't see the point of lines 323-330. Could be deleted? *
In revising our manuscript, we have rephrased these lines in an attempt to provide more context. Because DCLK1 has been shown to be upregulated in a wide variety of cancers, there are ongoing efforts to find chemical inhibitors that specifically block the kinase activity of this protein to be used as cancer therapeutics. However, no one has previously shown that the kinase activity of DCLK1 is important for its in vivo function (in any organism). Therefore, we were trying to make the point that, since we demonstrated that kinase activity is important for the functions of a DCLK1 family member in vivo, this suggests that these kinase inhibitors may in fact be beneficial in knocking down DCLK1 activity.
11.) Figure 1: Because ts alleles could have a defective phenotype at "permissive" temperature, a wild-type control should be included. This data does appear in a later figure.
The reviewer is correct that this data does appear in a later figure, but we agree this direct comparison would provide clarity to the reader. To address this comment, we compared the spindle lengths and angles of the two temperature-sensitive (TS) strains (at both the permissive and restrictive temperatures) to wild-type (N2) worms - these data have been added to Figure S1 (new panels F and G). The spindle lengths of both TS strains at the permissive temperature did not significantly differ from wild-type spindle lengths (p>0.1), while both TS strains at the restrictive temperature were significantly different than wild-type (p0.1), but there was a significant difference between wild-type spindles and the TS mutants at the restrictive temperature (doublecortin domain mutant (p Reviewer #3 (Significance (Required)): The strengths of this paper are the novelty of studying Zyg-8. It also addresses important questions regarding acentrosmal spindle assembly in oocytes. The weakness is mostly in the limited interpretation of results and not enough consideration of alternative interpretations. Related to this, the authors only test the force balance hypothesis with the knockout of two related kinesins. They don't experimentally investigate other mechanisms for the zyg-8 phenotype. This research should be of broad interest to anyone interested in oocyte spindle assembly, and also in a more specialized way to those who study kinases or Zyg-8 homologs in other cell types or organisms.
We thank the reviewer for these positive comments on the strengths and novelty of our manuscript. We also appreciate the constructive suggestions of all three reviewers, which motivated us to perform new experiments that revealed additional functions for ZYG-8 - these revisions have greatly improved the manuscript and have broadened its impact.
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Referee #2
Evidence, reproducibility and clarity
In this manuscript, the authors explore the requirement for doublecortin kinase Zyg8 in C elegans oocytes. Oocytes build meiotic spindles in the absence of centrosomes, and therefore unique regulation occurs during this process. Therefore, how spindles are built and its later stability are an area of active investigation in the field. Using mutant alleles of Zyg8 and auxin-induced degron alleles, the authors demonstrate that this kinase is required to negatively regulate outward pole forces through BMK1 kinesin and that it has other functions to still explore. Overall, I find that this study takes an elegant genetic approach to tackling this important question in oocyte biology. I have some comments to consider for making the MS clear to a reader.
Major Comments:
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Although I like the graphs describing the altered angles of the spindles, it falls short in fully assessing the phenotype in a meaningful statistical way. Could the authors also graph the data to show statistical significance in the angles between conditions? Perhaps by grouping them into angle ranges and performing an Anova test? This is important in Figure 2E where it is not obvious that there is a difference.
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The authors do not discuss the significance of the altered spindle angles which I think is an interesting phenotype. Would this be a problem upon Anaphase onset? What is known about spindle angle and aneuploidy or cell viability? Has this phenotype been described before in oocytes or somatic cells? Does depletion of other kinesin motors cause this?
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How is embryo spindle positioning determined? It is not clear from the images that there is a defect so I'm not sure what to look for. Is there a way to quantify this?
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In Figure 1, it appears that there are 2 spindles. Are these MI and MII spindles or ectopic spindles? How do the authors know which one to measure?
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The authors show depletion of Zyg8 by western (long) and loss of Gfp (long and short), but don't do so for the acute treatment. I'm guessing this is because the Gfp tag is taken by the spindle marker. The authors should either demonstrate or explain how they know that the acute depletion is effective in removing Zyg8 protein.
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In video 2, the chromosome signal is dimmer in the auxin treatment compared to video 1. Why is this? Is it just an experimental artifact or is there something significant about this? If it is because of video choice, consider replacing this one.
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Please consider color palette changes for color-blind readership.
Significance
The strengths of this manuscript include use of multiple genetic approaches to establish temporal requirements of ZYG8 and which pathway it is acting through. Additionally, the videos and images make the phenotypes clear to evaluate. A minor limitation is that we don't know if the ZYG8 and BMK1 genetic interaction is a direct phosphorylation or not.
This MS is an advancement to the field of spindle building and stability, and is particularly relevant to human oocyte quality and fertility. Previous work has shown that human oocyte spindles are highly unstable, but it is challenging to dissect genetic interactions and to conduct mechanistic studies in human oocytes. Therefore, the work here, although conducted in a nematode, can shed light on mechanism as to why human oocyte spindles are unstable and associated with high aneuploidy rates.
Based on my expertise in mammalian oocyte biology, I am confident that work presented here will be of high interest to people in the field of meiotic spindle building, aneuploidy and fertility. It also will have broader interest to folks in the areas of kinesin biology, general microtubule and spindle biology.
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Reviewer #1 (Public Review):
Summary:
In this work, Odenwald and colleagues show that mutant biotin ligases used to perform proximity-dependent biotin identification (TurboID) can be used to amplify signal in fluorescence microscopy and to label phase-separated compartments that are refractory to many immunofluorescence approaches. Using the parasite Trypanosoma brucei, they show that fluorescent methods such as expansion microscopy and CLEM, which require bright signals for optimal detection, benefit from the elevated signal provided by TurboID fusion proteins when coupled with labeled streptavidin. Moreover, they show that phase-separated compartments, where many antibody epitopes are occluded due to limited diffusion and potential sequestration, are labeled reliably with biotin deposited by a TurboID fusion protein that localizes within the compartment. They show successful labeling of the nucleolus, likely phase-separated portions of the nuclear pore, and stress granules. Lastly, they use a panel of nuclear pore-TurboID fusion proteins to map the regions of the T. brucei nuclear pore that appear to be phase-separated by comparing antibody labeling of the protein, which is susceptible to blocking, to the degree of biotin deposition detected by streptavidin, which is not.
Strengths:
Overall, this study shows that TurboID labelling and fluorescent streptavidin can be used to boost signal compared to conventional immunofluorescence in a manner similar to tyramide amplification, but without having to use antibodies. TurboID could prove to be a viable general strategy for labeling phase-separated structures in cells, and perhaps as a means of identifying these structures, which could also be useful.
Weaknesses:
However, I think that this work would benefit from additional controls to address if the improved detection that is being observed is due to the increased affinity and smaller size of streptavidin/biotin compared to IgGs, or if it has to do with the increased amount of binding epitope (biotin) being deposited compared to the number of available antibody epitopes. I also think that using the biotinylation signal produced by the TurboID fusion to track the location of the fusion protein and/or binding partners in cells comes with significant caveats that are not well addressed here, mostly due to the inability to discern which proteins are contributing to the observed biotin signal.
To dissect the contributions of the TurboID fusion to elevating signal, anti-biotin antibodies could be used to determine if the abundance of the biotin being deposited by the TurboID is what is increasing detection, or if streptavidin is essential for this. Alternatively, HaloTag or CLIP tagging could be used to see if diffusion of a small molecule tag other than biotin can overcome the labeling issue in phase-separated compartments. There are Halo-biotin substrates available that would allow the conjugation of 1 biotin per fusion protein, which would allow the authors to dissect the relative contributions of the high affinity of streptavidin from the increased amount of biotin that the TurboID introduces.
The idea of using the biotin signal from the TurboID fusion as a means to track the changing localization of the fusion protein or the location of interacting partners is an attractive idea, but the lack of certainty about what proteins are carrying the biotin signal makes it very difficult to make clear statements. For example, in the case of TurboID-PABP2, the appearance of a biotin signal at the cell posterior is proposed to be ALPH1, part of the mRNA decapping complex. However, because we are tracking biotin localization and biotin is being deposited on a variety of proteins, it is not formally possible to say that the posterior signal is ALPH1 or any other part of the decapping complex. For example, the posterior labeling could represent a localization of PABP2 that is not seen without the additional signal intensity provided by the TurboID fusion. There are also many cytoskeletal components present at the cell posterior that could be being biotinylated, not just the decapping complex. Similar arguments can be made for the localization data pertaining to MLP2 and NUP65/75. I would argue that the TurboID labeling allows you to enhance signal on structures, such as the NUPs, and effectively label compartments, but you lack the capacity to know precisely which proteins are being labeled.
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