annotation meta: may need new tag: - can't effectively monitor

Immaturity on Jane's part, I think. Both for being so picky about eating as to make it the pressing concern of all your relations, to refuse perfectly good arrowroot, and then to scour the meadows for your own.

Arrowroot is a food of low nutritional value that was sought after by people who had various food intolerances.

There are connections to racism as it relied on slavery for mass production and exportation and the obsession with 'purity' also has ideological similarities with reference to race.

http://www.digitalussouth.org/vegetable/vegetable.php?vegName=Arrow%20Root

https://janeaustensworld.com/tag/historical-food/

Here is a link to a post about the Romany of England during the regency. It says that to even have spoken with these people during the time was a crime and that might account for some of Harriet's fear. It also adds another dimension to the conflation of 'othering' of children, the poor, and racism.

https://janeaustensworld.com/tag/gypsies-in-regency-england/

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Referee #2

Evidence, reproducibility and clarity

Summary:

Cohen et al. presented a high-throughput approach to analyze protein-(putative) substrate interactions in yeast using BirA biotin ligase and its acceptor peptide AVI tag. Using this system, the authors identified the common and unique substrates of translocation pores, Sec61 and Ssh1. Interestingly, the differential substrates between Sec61 and Ssh1 seem to be explained by the degree of hydrophobicity in signal peptide sequences, which was also nicely demonstrated by an experiment showing that swapping the first three amino acids of substrate proteins is sufficient to convert the substrate specificity. While I appreciate that the approach is high-throughput and simple (does not require mass spectrometers), there are some technical comments to be addressed.

1. Why was BirA used to study transient interactions? Biotinylation through BirA is slow (that is why it takes several hours to label proximity proteins) and thus it may not be suitable for capturing transient interactions. Instead, TurboID would be more suitable as the biotinylation reaction is faster than BirA. A reasonable explanation using BirA is required.
2. One key question is whether biotinylated proteins identified by this method are substrates or proteins just proximal to Sec61 or Ssh1 due to close cellular localization (e.g. ER membrane) or same protein complex members. An experiment or analysis would be required to confirm that the proteins they identified are indeed potential substrates.
3. Along the same line, if proteins identified by this approach are bona fide substrates of Sec61 and Ssh1, proteins having signal peptides should be enriched in the candidate list of substrates. However, it does not look like that according to Figure 2A where the secretome proteins/total proteins ratio appears to be similar among the 4 categories (e.g., Ssh1 preferring, No preference, and Not interacting or excluded). The authors should comment on this.
4. Figures 1-2: They should comment on the reproducibility of the method. How many independent experiments were performed? If performed, how was reproducibility of results?
5. Figure 3: It is important to know the overlap of proteins commonly identified in both the interaction screening and protein localization assay. A Venn diagram that compares results between the two high-throughput assays would be useful.
6. Figure 4A (GO term): The authors mentioned that " the most consistent and repeating GO term group was those related to budding and polarity process. These include: "Establishment or maintenance of cell polarity"; "Development process involved in reproduction"; "Bipolar cellular bud site selection"; "Cell budding" and "Structural constituent of cell wall". Are protein sets in these functional categories similar or different? I am asking because GO enrichment analysis often provides apparently different functional categories but similar protein sets are included. 

Referees cross-commenting

The comments from reviewer #1 are reasonable and would further strengthen the quality of the paper.

Significance

The approach is high-throughput and simple (does not require mass spectrometers).

The differential substrates between Sec61 and Ssh1 seem to be explained by the degree of hydrophobicity in signal peptide sequences, which was also nicely demonstrated by an experiment showing that swapping the first three amino acids of substrate proteins is sufficient to convert the substrate specificity.

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Reply to the reviewers

Reviewer 1

Although this is an interesting, and generally well-performed study, it is primarily observational and there are few mechanistic insights provided into how MUC13 modulates barrier function. The authors propose a presumably direct interaction between MUC13 and PKC, which apparently sequesters PKC, preventing this kinase from triggering PKC-dependent increases in TJ barrier function; however, there is no evidence that a MUC13-PKC interaction occurs, that MUC13 is phosphorylated by PKC, or that phosphorylation of MUC13 has any impact on its function or overall barrier function. Thus, the hypothesis is not directly tested and all observations in this manuscript are generally correlative in nature.

While the MUC13 cytoplasmic tail contains a putative PKC-binding motif, we indeed do not show a direct interaction between MUC13 and a member of the PKC family in this manuscript. Unfortunately, we have so far not been able to successfully perform (co-)immunoprecipitation of MUC13 with our current anti-MUC13 antibodies.

To provide more insights into the possible MUC13-PKC interaction, we plan to perform several experiments.

• First, we will determine the expression levels of the different PKC isotypes (PKC alpha, beta, gamma, delta, epsilon, and zeta) in the HRT18 cell lines by western blot.
• Next, we will determine the localization of the relevant PKC isoforms and MUC13 by immunofluorescence microscopy. We are curious to see if we can find a colocalization between MUC13 and a PKC member on the lateral or apical membrane. If we can demonstrate a colocalization, we could follow up with a proximity ligation assay, but this would require the MUC13 antibody directed against the cytoplasmic tail (which only detects the lateral population) and might therefore be challenging.
• Furthermore, since PKC delta protein levels were upregulated in the total lysate of ∆MUC13 cells, we will test a PKC delta-specific inhibitor in the TEER assay.

  Consider quantifying all blots (Fig. 5C, Fig. 6B).

As suggested, we will quantify both blots.

Consider using dot-plots for all quantified data.

The graphs will be altered to include individual measurement points.

Reviewer 2

Fig2E showed two bands with different size in the two MUC13 WT control cell lines. They hypothesized that this could be the consequences of glycosylation different patterns. A sample with untransfected HRT18 might be included in the western blot panel. Additionally, what is the 100kDa band?

Mucin blots are notoriously difficult and these MUC13 blots are the result of a lot of trial and error. We repeated the Western Blot with original HRT18 cells, HRT18 original cell line, as well as the two CRISPR control cells used in the study (WT 1 and WT 2) and one of the full-length MUC13 knockout cells. The higher band was absent from the MUC13 knockout cells, but a small shift in the MUC13 band size can be noted in the WT 1 cells compared to the original and the WT 2 cell lines, possibly indicating a change in the glycosylation pattern. The 100 kDa band remains detectable in all cell lines including the ∆MUC13 cell line, therefore we consider this to be an aspecific background band of the MUC13 antibody. We will add a more extensive Western Blot analysis to the manuscript.

Did the transfection of the inducible GFP-MUC13 plasmid induce any decrease of Claudin1/3/4 in HRT18 or Caco2 cells? Same question regarding PKCdelta.

These are indeed interesting questions. We will perform these experiments with our MUC13-overexpression HRT18 cells.

Reviewer 3

Moreover, the authors should determine if MUC13∆CT localize to TJs, as suggested by the working model in Figure 7C. The subcellular localization of MUC3∆CT could give critical clues for its function, but Figure 2G fails to provide any information and the authors do not present any additional data concerning the localization of MUC13∆CT. Detection of MUC13 in membrane fractions of WT, MUC13∆CT and cells lacking the mucin domain could be a feasible strategy forward.

We will perform additional immunofluorescence experiments to determine the subcellular localization of MUC13-∆CT more accurately. However, detection of the extracellular domain by western blot, as suggested, is not possible due to the incompatibility of the extracellular MUC13-directed hybridoma antibody with the western blot technique. We currently do not have a suitable antibody that recognizes the ED and can be used for western blot.

The authors introduce an inducible MUC13-GFP fusion protein into WT and ∆MUC13 cells and show that it reverses the enhanced TEER upon MUC13 deletion. Unfortunately, the "Materials and Methods" section lacks adequate information on how this fusion protein was designed. Critical questions are the position of the GFP tag within MUC13, whether the fusion protein is correctly processed in HRT18 cells, and if it localizes to the apical or apico-lateral membrane domains? Figure 2H is of low magnification and fails to provide information on the subcellular localization of the MUC13-GFP fusion protein.

The materials and methods section will be adjusted to describe all the design details of the fusion protein. The GFP tag was added to the MUC13 C-terminus with a GGGS linker sequence in between. Processing of the fusion protein seems correct as we observed MUC13-GFP localization to both lateral and apical membranes and no access intracellular build up. As suggested by the reviewer, we will add more detailed immunofluorescence pictures to the manuscript.

Figures 6B-C suggest that PKCdelta levels increase in ∆MUC13 cells, which correlates with higher enrichment of Claudins in membrane fractions. The authors then inhibited PKCdelta and observed reduced recruitment of Claudins to membrane fractions. Since the family of Claudins are differentially regulated by phosphorylation (PMID: 29186552), the authors should investigate the TEER phenotype of WT, ∆MUC13 and MUC13∆CT upon PKC inhibition.

We must clarify that figures 6C-D are done using the PKC inhibitor targeting all conventional PKCs (alpha, beta, gamma) as well as delta (https://www.tocris.com/products/gf-109203x_0741). We recently obtained a PKCdelta-specific inhibitor which we will test in the TEER build-up experiments.

Moreover, the authors predict phosphorylation sites in MUC13CT and suggest a link between PKC and MUC13 (Figure. 6A), however no evidence is presented to support this hypothesis. The authors should either determine if PKC phosphorylates MUC13 and if this modification has implication on MUC13 localization and TJ function, or remove statements regarding MUC13 phosphorylation. The data provided suggest that PKC regulates TJ proteins independent of MUC13.

We will adjust the manuscript to put less emphasis on the putative PKC motifs in the MUC13 cytoplasmic tail. For further details on how we will proceed regarding the possible MUC13-PKC interaction see question 1 from reviewer #1.

Figure 5C. Quantification of at least 3 independent experiments is required.

These data will be added to the manuscript.

Figure 6B. Quantification of at least 3 independent experiments is required.

These data will be added to the manuscript.

Reviewer 4

OPTIONAL: MUC13 is expressed both, in the basolateral membranes and in the apical membrane of intestinal epithelial cells (IECs). Does the authors check the relevance of MUC13 in the formation of microvilli in IECs? Are microvilli different (microvilli staining, number of positive cells to microvilli, length, width or distribution of microvilli) in ΔMUC13 and in MUC13-ΔCT? How the glycocalyx looks like in these cells genetically modified for MUC13?

HRT18 cells do not seem to develop microvilli. However, we plan to stain these cells with a microvilli-specific antibody (ACTUB). The HRT18 cells express mostly MUC13 and relatively low levels of the larger TM mucin MUC1. To study changes in the glycocalyx, we will stain using a MAL-II antibody which targets α-2,3 sialic acids, which are abundantly present in mucins. In this way, we will determine any big changes in the total glycocalyx that may occur in response to the removal of MUC13.

In the figure 1D would be nice to represent the co-localization of MUC13 together with occluding in a graph in each Z-stack so you can visualize in which part of the cell is maximum colocalization of these both components.

These data will be provided.

In the figure 1E, would be great to compare between the two different MUC13 antibodies the apical fraction stained in HRT18 and Caco-2. Specially in the HRT18 cell line since the first antibody did not label apical MUC13 expression meanwhile the second antibody detects the apical expression in these cells. How much lateral lateral stain the C terminal antibody compare with the extracellular antibody for MUC13 and how much stain apically the C terminal antibody compare with the extracellular antibody? Would be nice to see some comparative results using the intensity by Z-stack and plotting in a graph.

This is a good suggestion as it is quite intriguing that both MUC13 antibodies seem to target (partially) different MUC13 populations. We will perform co-staining with both MUC13 antibodies to provide information on which MUC13 populations are detected by each antibody (apical vs lateral membrane).

Manuscript would be improved if in the figure 2H to compare within the same cell line the number of MUC13 positive cells in the WT, number of MUC13 positive cells in WT+pMUC13 and the number of MUC13 positive cells in the ΔMUC13+pMUC13

We will quantify the percentage of MUC13-GFP positive cells in both the WT and ΔMUC13 backgrounds by either microscopy or flow cytometry.

In figure 5C would be helpful to plot in a graph the normalized expression of each TJ protein and compare between the different cells used (WT, ΔMUC13 and MUC13-ΔCT) as you did in figure 5A

We will provide the quantification data of three independent experiments.

Description of the revisions that have already been incorporated in the transferred manuscript

Reviewer 1

In addition, this model does not explain why all kinase inhibitors tested reverse the increase in TER observed in deltaMUC13 cell lines. Does this reflect the lack of inhibitor specificity or the likelihood that many kinases are involved?

As stated in the manuscript, we think that MLCK, ROCK, and PKC are all essential for TER buildup in the ∆MUC13 cells. Because the roles of MLCK and ROCK are well established, we choose to follow up on the PKC results. We adjusted the text to clarify this point.

The authors do observe that there is an increase in expression of several tight junction-associated proteins, including the claudins, in deltaMUC13 cells. Affected CLDNs include 1, 2, 3, 4, 7, 12. (1) While it appears the authors are arguing that this increased claudin expression results in increased barrier function, they do not sufficiently highlight the well-known role that CLDN2 has in cation transport, and both CLDN-4 and -7 have also been implicated in paracellular ion flux (although this is apparently cell-type specific). These observations would seem to argue against a simple correlation between claudin expression and tight junction barrier function.

The reviewer is right about the different functions of claudins. Claudin-2, -4 and -7 have (potentially) pore-forming properties, while the other claudins restrict paracellular passage. It has been previously demonstrated that the magnitude of paracellular ion and water flux is reflected by the specific repertoire of claudin family members (Shashikanth et al., 2022). In this paper, overexpression of claudin-4 was shown to mobilize and affect polymeric strands of claudin-2, thus blocking its channel activity. Our mass spectrometry data demonstrated a striking increase in claudin-1, -2, -3, -4, -7, and -12 in the MUC13 knockout membranes compared to WT. We hypothesize that the claudin repertoire in the MUC13 knockout cells leads to a more restricted paracellular route (as observed in the TEER and tracer experiments). The pore-forming claudins may be subject to “interclaudin interference” therefore leading to restriction of the total paracellular ion and water flux. We have adjusted the text of the manuscript to clarify this point.

We attempted to investigate claudin-2 expression levels in isolated membranes by Western Blot but were unsuccessful as the antibody did not detect any protein while claudins-1 and -4 could be detected with the same method.

Furthermore, the authors should note the disconnect between paracellular ion flux mediated by claudins and the flux of markers such as dextrans and lucifer yellow, which can be dissociated from claudin function.

We acknowledge that the flux of larger particles (the leak pathway) is not regulated by claudins (which regulates the pore pathway). We aimed to assess both the pore and the leak paracellular pathways, by using different techniques including TEER, small solutes (Lucifer Yellow CH), and larger molecules (4 and 70 kDa FITC-Dextrans). HRT18 wild type cells are already very restrictive to the pass of larger molecules (FITC-Dextrans) but are more permeable to smaller solutes such as Lucifer Yellow (400 Da). We observed that removal of the MUC13 cytoplasmic tail did not affect the TEER, but reduced the paracellular passage of Lucifer Yellow, demonstrating that manipulation of MUC13 can affect both the pore and leak pathways. We adjusted to text to include this point.

The increased expression of claudins in the nominally tail-minus MUC13 without a corresponding change in TER would again seem to argue against a simple correlation;

MUC13-dCT cells showed consistently increased levels of claudins-1 and -2, but not the other claudins. This claudin repertoire (with high claudins-1 and -2, but lower claudin-3, -4, -7, and -12) is apparently not enough to increase TEER. We think that this again reflects the importance of the total claudin composition for the control of the paracellular pathway.

Watch the use of decimal points instead of commas (lines 253 and 256).

Corrected.

Line 543: MilliQ is not a washing agent (or is it?). (Line 535) We use MilliQ as a final step before mounting the glass slides to remove any possible salt deposition that would affect the visualization by microscopy.

We have specified this in the text.

Line 553: TER is the product of total resistance times the area. The units are ohms times area.

Indeed, we have changed this mistake (line 545).

Line 630: Please provide the transfer conditions (voltage, amp, watts?) and transfer buffer when describing the Western blot protocol.

For immunoblotting of MUC13, protein lysates were transferred to 0.2 µm PVDF membranes using the Trans-Blot Turbo Transfer system (Biorad). The transfer was run using the protocol (High MW) which consisted in running for 10 min at 25 volts (V) and 1,3 amperes (A). These experimental data were added to the manuscript.

Reviewer 2

My main concern about this manuscript is that the authors analyzed MUC13 role in intestinal homeostasis and function using colorectal cancer cells. As helpful as cancer cells are, we should always be cautious about extrapolating roles in normal intestinal epithelium or IBD pathology. Obviously, these finding are also interesting in a cancer context. Using GEPIA (http://gepia.cancer-pku.cn/), I observed that MUC13 is overexpressed in colorectal cancer COAD-TCGA dataset (compared to normal colon from GTEX). Similar results were obtained previously by Gupta et al. (ref #10). I am aware that this would be difficult to confirm the main findings in a non-cancerous intestinal cell line but this limit (normal intestine using cancer cells) should be at least discussed in the manuscript.

We appreciate the reviewers’ comments and are aware of the downsides of using cancer-derived cell lines. We have performed the GEPIA analysis ourselves and have an ongoing project about the possible role of MUC13 in colorectal cancer progression. In a separate project, we are collaborating with the Gaultier Laboratory at the University of Virginia which has generated a MUC13 knockout mouse. This model will allow us to study the role of MUC13 in non-cancerous tissue. We recently received intestinal biopsies from these mice which will be stained with MUC13 and claudin antibodies to determine localization in healthy tissue. These experiments will reveal if MUC13 colocalizes with claudin on the lateral membrane in the healthy mouse intestinal tract. In future experiments, we will also address MUC13 localization and function in human intestinal organoids. We have adjusted the discussion to refer to the limitations of using cancer cell lines.

Massey et al (Micro 2021, PMC7014956) previously showed that MUC13 overexpression increased rigidity in PDAC cells and discussed involvement MUC13 link with EMT. MUC13-Her2 interaction was also associated with decrease of E-cadherin suggesting an EMT phenotype. This should be included in the discussion section.

The discussion has been adjusted to include the link with EMT.

The authors performed mass spectrometry analysis. Results are deposited on ProteomeXchange but are not yet publicly released. Among the 1189 membrane protein identified. Did the authors observed alteration of EMT proteins? (decrease of vimentin for example). In the discussion section (lane 347), the authors mentioned the relationship between other membrane bound mucins such as MUC1, MUC4, MUC16 or MUC17 and AJ/TJproteins. Did the authors observed any alteration of these mucin in the mass spectrometry data?

The mass spec analysis was performed on membrane fractions, therefore our dataset will not contain true cytosolic proteins. One of the key EMT proteins, Vimentin, is a cytosolic protein, and indeed it was not found in our dataset. Other EMT-related proteins are shown in the following table. TGF beta 1 was slightly decreased, while E-cadherin and Integrin beta 6 were slightly increased in the ∆MUC13 cells compared to WT cells.

Gene Name

Mean WT

Mean ∆MUC13

Mean MUC13-∆CT

TGFBI (TGB beta 1)

20,54

16,48

18,83

CDH1 (E-cadherin)

22,69

24,57

24,24

ITGB6 (Integrin beta 6)

18,86

21,74

19,19

Vimentin - Cytosolic

-

-

-

CDH2 (Cadherin-2, N-cadherin)

-

-

-

Mucins are large proteins comprised of densely O-glycosylated mucin domains, which makes them extremely challenging to study by mass spectrometry (MS) (Rangel-Angarita et al., 2021). We did not specifically employ mucin-directed technologies in this dataset, thus making the detection of mucins hard. No mucins other than MUC13 were detected. For MUC13, two peptides corresponding to the EGF-like domains in the extracellular domain, a region that is less densely glycosylated. We added a sentence to the description of the mass spec results to include the EMT proteins and other mucins.

Minor points:

Lane 126: HRT18 and Caco2 colon cancer cells instead of intestinal epithelial cells

Corrected.

Lane 181 and lane 514: add "full length" MUC13 DNA sequence

Corrected.

Lane 234: TEER was measured every 12h. How the authors did observed the largest increase at 42h? Was it 48h? Please clarify.

We aimed at measuring every 12 h, however the exact measurements were done at 18h, 24h, and 42 h post-infection. We have corrected this in the manuscript.

Reviewer 3

Line 43 and 46. "Enterocytes" should be replaced with "intestinal epithelial cells", since enterocytes are themselves a distinct subpopulation of IECs.

We have changed it in the manuscript.

Lines 58-60. References in support of the statements should be added.

We added a reference to this sentence.

Lines 188-190. Authors comment on "roundness" of different cell lines. If the parameter is critical for the manuscript, the authors should quantify this phenotype.

The parameter is not critical for the manuscript. We removed the sentence.

Figure 3A. Staining of cell lines should include panels showing localization of MUC13.

Co-staining of MUC13 with occludin in HRT18 cell lines can be found in figure 1D, and MUC13 with E-cadherin in supplementary figure 1.

Lines 323-327 and 390-392. Sentences on these lines contradict each other. The sentences should describe/discuss quantified data presented in Figure 6D.

The reviewer is right that we should be discussing the quantified data in 6D. We adjusted the sentence in line 323-327.

Proteomic data sets should be made publicly available on data depositories.

All proteomics raw data were deposited to the ProteomeXchange Consortium with the dataset identifier PXD029606.

Reviewer 4

OPTIONAL: In the figure 2E, is the extracellular antibody still detecting the MUC13-ΔCT?

No, unfortunately the antibody directed against the MUC13 ED is not compatible with western blot.

In the figure 2G, would be nice to comment possible reasons why the deletion in the first cell line of the MUC13-CT you can still detect with the extracellular antibody some lateral expression of MUC13 meanwhile in the second cell line, the same deletion (MUC13-CT) you cannot see any lateral MUC13 staining with the extracellular antibody.

Yes, this is indeed a puzzling finding, especially because the CRISPR deletion is the same in both cell lines. We will add a sentence about possible reduced stability of the MUC13 without CT domain that leads to a different outcome in both cell lines.

It would be nice that the results from Figure 3H are better explained since it is difficult to follow.

We adjusted the text to explain the experiment in more detail.

2. Description of analyses that authors prefer not to carry out

Reviewer 1

The authors may be overly reliant on TER measurements. Epithelial cells have two parallel resistive pathways: transcellular and paracellular. TER measure the contribution of both. Thus, an increase in TER could result from a decrease in transcellular ion transport. The authors need to measure transcellular ion flow or selectively measure the junctional resistance in a select set of experiments to rule this possibility out.

The reviewer is right that TEER is a sum of the resistance of the transcellular and paracellular pathways. However, due to the high resistance of cell membranes, the current predominantly travels via the paracellular route (Elbrecht et al., 2016). For this reason, TEER measurements are widely accepted techniques for the assessment of ions passage through the paracellular pathway (Shen et al., 2011).

Reviewer 3

Figure 1C. Caco2 and HRT18 cells exhibit distinct MUC13 expression patterns when probed with an antibody against the MUC13 CT; MUC13 localizes almost exclusively to lateral cell junction in HRT18 cells, while a higher portion of MUC13 is present on the apical surface of Caco2 cells. This observation has two possible explanations: 1) the two cell lines express distinct forms of MUC13, or 2) the two cell lines carry distinct machineries for anchoring MUC13 to apical versus apico-lateral membranes. Thus, The authors should take the opportunity to determine the impact of MUC13 deletion on TEER and TJ function in Caco2 cells. Proteomic analysis and functional assays in Caco2 cells may provide more a general mechanism for how MUC13 regulates TJ proteins.

Yes, this would be a great line of investigation. However, we aimed to knockout MUC13 in Caco-2 cell lines (with the same CRISPR/Cas9 protocol as the HRT18 cells) but were unable to obtain Caco-2 knockout clones. We think this might be a consequence of the poor capability of Caco-2 cells to grow as single colonies (a required step in the protocol). Another option is Caco-2 MUC13 knockout cells have reduced viability.

The authors generate cell lines that either lack MUC13 or express MUC13 lacking the cytoplasmic domain. Loss of MUC13 cells resulted in enhanced TEER and increased recruitment of TJ proteins to membrane fractions. MUC13∆CT cells show moderate recruitment of TJ proteins to membranes and no increase in TEER but inhibit paracellular diffusion of Luciferase Yellow across monolayers. Figure 3A suggests that Occludin redistributes to tricellular junctions in ∆MUC13 cells, whereas it is found more laterally in WT and MUC13∆CT cells. These finding suggest that full-length MUC13 interferes with TJ protein complexes. However the impact of the extracellular and intracellular (CT) domains is not fully elucidated. Does the O-glycosylated mucin domain interfere with the extracellular domains Occludin and Claudins? The authors should clarify the contribution of the mucin domain to the observed phenotype, for example by performing the described experiments in a cell line expressing MUC13 lacking the mucin domain.

Mucins are type I membrane proteins with the N-terminal part of the protein on the extracellular site. Therefore, a CRISPR method to specifically remove the glycosylated domain but leave the remainder of the protein in frame is challenging. An additional difficulty is that the ED contains a lot of repeats, complicating the design of specific guide RNAs. To specifically address the contribution of the glycosylated domain, we could complement the MUC13 knockout cell with a construct lacking the ED. However, this would not be comparable to the endogenous MUC13∆CT cell line presented in this manuscript. In future studies, we will strive to address the functions of the different MUC13 domains in more detail.

Figure 5A. Turnover of TJ proteins in membrane fractions occurs faster than over a period of 1-3 days (PMID: 18474622). The authors should determine TJ protein turnover over a period of minutes and hours.

We acknowledge the findings in this interesting paper concerning the continuous remodeling of tight junctions. However, the readout of our biotinylation assay is degradation and the timeframe of degradation turns out to be days and not hours. Within this timeframe remodeling is taking place but it cannot be captured in the total lysate.

Reviewer 4

OPTIONAL: The authors show that the probiotic Lactobacillus plantarum increase epithelial barrier independently of MUC13. Have the authors considered to use other probiotics as Lactobacillus paracasei (10.3389/fcimb.2015.00026), Akkermansia muciniphila (10.1038/emm.2017.282) or some metabolic products from intestinal microbiota as short-chain fatty acids (SCFAs) (10.3389/fphys.2021.650313) to check what is the role of MUC13 and if it is related with other microbe or microbiota metabolite?

Thank you for the suggestion. We have an ongoing project in which we investigate the impact of different probiotic bacteria and plan to investigate whether they have an impact on the epithelial barrier function in a MUC13-dependent manner. This study will lead to a separate publication.

OPTIONAL: The authors successfully delete MUC13 in IECs, both, full length and the cytosolic tail. Have the authors considered targeting the deletion of the PTS domain in MUC13? Could affect that something different from paracellular trafficking as the extracellular detection of microbes and microbial products?

Removal of a domain in the extracellular domain of MUC13 with CRISPR is challenging because mucins are type I membrane proteins, the repeats and possible frameshift, as described above.

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Referee #3

Evidence, reproducibility and clarity

Summary:

The authors describe a novel function for transmembrane mucin MUC13 in regulation of tight junctions (TJs) that create an impermeable cell monolayer that allows. paracellular diffusion of very small molecules. The authors use cultured intestinal epithelial cell monolayers. to demonstrate that MUC13 localizes to the apical aspects of IECs as well laterally to tight junctions. CRSIPR/Cas-mediated deletion of MUC13 increased transepithelial resistance (TEER) and reduced the extent of paracellular diffusion of <0.5 kDa molecules across the monolayer. Proteomic analysis revealed that specific TJ proteins are enriched in cell membrane fractions upon deletion of MUC13, while pharmacological inhibition of PKC involved in actomyosin contractility, resulted in loss of TJ proteins from cell membranes and TEER reduction. See major comments for a detailed discussion concerning the findings.

Major comments:

1. Figure 1C. Caco2 and HRT18 cells exhibit distinct MUC13 expression patterns when probed with an antibody against the MUC13 CT; MUC13 localizes almost exclusively to lateral cell junction in HRT18 cells, while a higher portion of MUC13 is present on the apical surface of Caco2 cells. This observation has two possible explanations: 1) the two cell lines express distinct forms of MUC13, or 2) the two cell lines carry distinct machineries for anchoring MUC13 to apical versus apico-lateral membranes. Thus, The authors should take the opportunity to determine the impact of MUC13 deletion on TEER and TJ function in Caco2 cells. Proteomic analysis and functional assays in Caco2 cells may provide more a general mechanism for how MUC13 regulates TJ proteins.
2. The authors generate cell lines that either lack MUC13 or express MUC13 lacking the cytoplasmic domain. Loss of MUC13 cells resulted in enhanced TEER and increased recruitment of TJ proteins to membrane fractions. MUC13∆CT cells show moderate recruitment of TJ proteins to membranes and no increase in TEER but inhibit paracellular diffusion of Luciferase Yellow across monolayers. Figure 3A suggests that Occludin redistributes to tricellular junctions in ∆MUC13 cells, whereas it is found more laterally in WT and MUC13∆CT cells. These finding suggest that full-length MUC13 interferes with TJ protein complexes. However the impact of the extracellular and intracellular (CT) domains is not fully elucidated. Does the O-glycosylated mucin domain interfere with the extracellular domains Occludin and Claudins? The authors should clarify the contribution of the mucin domain to the observed phenotype, for example by performing the described experiments in a cell line expressing MUC13 lacking the mucin domain. Moreover, the authors should determine if MUC13∆CT localize to TJs, as suggested by the working model in Figure 7C. The subcellular localization of MUC3∆CT could give critical clues for its function, but Figure 2G fails to provide any information and the authors do not present any additional data concerning the localization of MUC13∆CT. Detection of MUC13 in membrane fractions of WT, MUC13∆CT and cells lacking the mucin domain could be a feasible strategy forward.
3. The authors introduce an inducible MUC13-GFP fusion protein into WT and ∆MUC13 cells and show that it reverses the enhanced TEER upon MUC13 deletion. Unfortunately, the "Materials and Methods" section lacks adequate information on how this fusion protein was designed. Critical questions are the position of the GFP tag within MUC13, whether the fusion protein is correctly processed in HRT18 cells, and if it localizes to the apical or apico-lateral membrane domains? Figure 2H is of low magnification and fails to provide information on the subcellular localization of the MUC13-GFP fusion protein.
4. Figures 6B-C suggest that PKCdelta levels increase in ∆MUC13 cells, which correlates with higher enrichment of Claudins in membrane fractions. The authors then inhibited PKCdelta and observed reduced recruitment of Claudins to membrane fractions. Since the family of Claudins are differentially regulated by phosphorylation (PMID: 29186552), the authors should investigate the TEER phenotype of WT, ∆MUC13 and MUC13∆CT upon PKC inhibition. Moreover, the authors predict phosphorylation sites in MUC13CT and suggest a link between PKC and MUC13 (Figure. 6A), however no evidence is presented to support this hypothesis. The authors should either determine if PKC phosphorylates MUC13 and if this modification has implication on MUC13 localization and TJ function, or remove statements regarding MUC13 phosphorylation. The data provided suggest that PKC regulates TJ proteins independent of MUC13.

Minor comments:

1. Line 43 and 46. "Enterocytes" should be replaced with "intestinal epithelial cells", since enterocytes are themselves a distinct subpopulation of IECs.
2. Line 59. The authors should note that MUC13 does not have a canonical SEA domain that generates a cleaved heterodimer (PMID: 16369486).
3. Lines 58-60. References in support of the statements should be added.
4. Lines 188-190. Authors comment on "roundness" of different cell lines. If the parameter is critical for the manuscript, the authors should quantify this phenotype.
5. Figure 3A. Staining of cell lines should include panels showing localization of MUC13.
6. Figure 5A. Turnover of TJ proteins in membrane fractions occurs faster than over a period of 1-3 days (PMID: 18474622). The authors should determine TJ protein turnover over a period of minutes and hours.
7. Figure 5C. Quantification of at least 3 independent experiments is required.
8. Figure 6B. Quantification of at least 3 independent experiments is required.
9. Lines 323-327 and 390-392. Sentences on these lines contradict each other. The sentences should describe/discuss quantified data presented in Figure 6D.
10. Proteomic data sets should be made publicly available on data depositories.

Significance

Mucins participate in critical functions in the human intestine. Gel-forming mucins form the mucus layers that separate the gut microbiota from the underlying intestinal epithelial cells (IECs) (PMID: 18806221). Transmembrane mucins are instead anchored to the plasma membrane of various populations of IECs (PMID: 32169835; PMID: 28052300). Despite its discovery over 20 years ago, the functional role of MUC13 in the intestinal epithelium is still debated. MUC13 is expressed in human small intestine and colon under baseline conditions and is dysregulated during inflammation and tumorigenesis, as described by the authors. Thus, understanding how MUC13 expression and localization impact cell function is of great importance for elucidating its function in health and disease. Studies so far have identified transmembrane mucins as biophysical barriers against bacteria (PMID: 33596425) or facilitators of bacterial invasion (PMID: 33824202). The current manuscript can potentially offer novel conceptual insights into how transmembrane mucins govern the integrity of the epithelial monolayer that serves as a firewall between the multitude of microbes in the gut lumen and the immune system. Such insights have implication for both basic and clinical research on inflammatory bowel disease (IBD) and colorectal cancer (CRC). However, while the authors present convincing data that deletion of MUC13 enhances TEER and recruitment of TJ proteins, the study in its current form fail to provide mechanistic proof of how MUC13 impacts individual TJ proteins. Moreover, it is not clear if findings in a specific cultured cell line (HRT18) can be extrapolated to other frequently used intestinal cell lines (e.g. Caco2) and IECs in an in vivo setting. The latter is particularly important since the authors argue that their findings have important implication in intestinal inflammation and cancer.

restorasi gambar

Reviewer #1 (Public Review):

This paper investigates whether bistable rhodopsins can be used to manipulate GPCR signalling in zebrafish. As a first step, the authors compared the performance of bistable rhodopsins fused with a flag tag or with a fluorescent protein tag (TagCFP). Constructs were compared by expressing in HEK cells followed by calcium imaging with aequorin or cAMP monitoring with GloSensor. This showed that the protein with a smaller flag tag performed better. Then, a series of transgenic zebrafish lines were made, in which tagged rhodopsins were expressed in reticulospinal neurons or cardiomyocytes.

The data indicate that bistable rhodopsin can be used to manipulate Gq and Gi/o signalling in zebrafish. The Gq-coupled SpiRh1 was effective in manipulating reticulospinal neurons, as indicated by analysis of tail movements and calcium imaging of the neurons. Gi/o signalling could be manipulated by Opn3 from mosquitoes, TMT from pufferfish, and parapinopsin from lamprey, as shown by their effects on the heartbeat. Lamprey parapinopsin has the interesting property that it can be turned on and off by different wavelengths of light, and this was used to stop and restart the heart. Finally, the authors show that the cardiac effects are mediated by an inward-rectifier K+ channel, through the use of pharmacological inhibitors.

A strength of this paper is the testing of a range of bistable rhodopsins, with a total of 10 proteins tested. This provides a good resource for future experiments. A weakness is the failure to show that some experiments involved repeated sampling of the same animal. Figure 3 gives the impression that there are 48 independent datapoints. However, there are 8 animals, with 6 datapoints coming from each. Similarly, Figure 4 shows the data from 6 trials of 4 animals, not 24 independent animals. Repeated sampling should be reflected in the data presentation, and in the statistical analysis. Was there an effect of trial number, which is suggested in Figure 6?

Delta F/F refers to relative change, which should be (F-F0)/F0. This should be zero when t = 0. The values in Figure 3E, and 3F are ~ 1 when t = 0, however. Are these figures showing F/F0?

The authors' conclusions that the bistable rhodopsins are useful tools in the zebrafish system appear largely justified. This is consistent with findings from other organisms, including mouse (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097317/, https://www.sciencedirect.com/science/article/pii/S0896627321001616). The tools here are likely to find broad use by scientists who use the zebrafish as the experimental system for a variety of different areas.

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Reply to the reviewers

Reviewer 1.

Major point:

(1) The authors rely upon the redistribution of RNA to measure the inheritance of extant RNAs following cell cycle release. Blocking transcription nicely shows new synthesis is not required for this inheritance. This is also consistent with the idea any newly synthesized RNA would be 'dark,' or not EU labeled, but the transcription inhibitor experiments are critical controls and nicely done. As hinted at the end of their discussion, however, a lack of RNA localizing to G1 chromosomes could be formally attributable to differential RNA stability. Might altered RNA stability of NEAT1, MALAT1, or U2 also contribute to the observed altered localizations upon interphase reentry? The authors could use qPCR or measure RNA half-life to test this possibility. These data would nicely compliment the authors' existing FISH experiments and allow them to specifically argue for differential RNA localization.

We have addressed this point by measuring the stability of MALAT1, U2, and NEAT1 in G2 cells after transcription inhibition using RNA FISH. We find that U2 and MALAT1 exhibit very little RNA degradation after 2.5 hours of transcription inhibition, which is consistent with the reported half-lives for each of these transcripts (10 hours for MALAT1 and >24hrs for U2; PMC3337439). We conclude that differential RNA stability cannot account for differential RNA import observed for these two transcripts. In contrast, NEAT1 transcript is almost undetectable after 1.5 hours of transcription inhibition, which is also consistent with the reported half-life of this transcript (22406755, 3337439). Therefore, RNA degradation during mitosis could contribute to a lack of NEAT1 nuclear import in G1. We have included this new data in a modified Figure 2E (text p5 lines 154-166).

Minor Points:

(1) The authors examine published datasets identifying RNA associated with chromatin and state the reason why these data show little overlap is "primarily attributable to purification methodology." This statement seems speculative, and its basis seems unclear.

We have changed the wording of this section to remove unwarranted speculation (p4-5 lines 116-129).

(2) The SAF-A-AA experiments failed to reveal insight into mechanisms of RNA sorting, although they do suggest the AA construct functions as a gain-of-function due to a) increased RNA reincorporated into chromosomes b) dramatic increase of chromosome targeting of SAF-A. These effects make it difficult to interpret the SAF-A-AA data. Related to this point, the analysis of altered RNA distributions relative to SAF-A is underdeveloped. Because the authors only examined one lncRNA (MALAT1), the conclusion that “forced retention of SAF-A on mitotic chromatin does not lead to an increase in the nuclear inheritance of specific transcripts” seems like an overstatement.

We have reworded this conclusion about the role of SAF-A-AA on mitotic chromatin retention to more accurately reflect our findings (p6 line 197). (3) The authors find the U2 spliceosomal RNA is preferentially inherited. Might they speculate why this would be advantageous?

We have added a sentence to the discussion speculating about the importance of U2 inheritance (p8 line 269-271). (4) Optional: it would be exciting to test the significance of U2 RNA inheritance

We agree with the reviewer that this would be an exciting future direction to test. We envision that testing this idea rigorously would require the development of several new degron cell lines and is outside the scope of this study. (5) For Figure 1, please add statistics to figures and legend; add N=cells examined.

We have added a new supplemental Excel spreadsheet that contains the N of cells measured for each experiment and added statistics to figure legends and figures where tests were significant. (6) For Figure 2, single channel panel of U2 RNA should be added. Figure 2E seems to reproduce the same data shown in Figure 2D (right-most columns) shown with different axes.

We have added a single channel image of U2 to Figure 2 and replaced panel 2E with analysis of MALAT1, NEAT1, and U2 stability after transcription inhibition. (7) Figure 3, it is unclear why the authors selected MALAT1 for analysis, but not NEAT1 (or the single (unlabeled) antisense RNA also enriched in the SAF-A IP (figure 2C).

We examined MALAT1 in greater detail because it is the most abundant lncRNA bound by SAF-A and most robust RNA FISH probe. The unlabeled antisense transcript is hnRNPUas1 and was not detectable in DLD1 cells by RNA FISH. (8) Figure 4B, please add statistics to figure and legend.

For this experiment we prefer not to add statistics to the figure. This experiment was performed on a limited number of cells (21 and 8 respectively) and we do not believe that it is statistically appropriate to treat each cell as an independent N. The data confirms results in our previously published work (Sharp et al 2020) using live cell imaging. (9) Methods: in their description of the published lists of chromatin-bound RNAs, the authors should cite those works and provide a data availability statement with the associated GEO

We have cited these works in the text and methods sections and added GEO accession numbers associated with these studies. (p21 line 442).

Reviewer 2

Major comments:

The authors pose an interesting question -- how does nuclear RNA segregate following mitosis. In many ways, the results presented in this manuscript are rather preliminary. Key controls and validation are missing. Because of this, it is difficult to assess the validity of the main conclusions of the study. More specifically:

1. The main conclusion of the manuscript ("about half of nuclear RNA is inherited by G1 cells following division") is primarily dependent on the experiment described in Fig 1A-B. The authors labeled synchronized cells with EU and quantified nuclear signal after release from synchronization. However, key controls are missing. What is the synchronization efficiency of the RO3306 treatment? How many cells in their acquired fields of cells are in G2 vs in other cell cycle stages? Following their drug release, what percentage of the synchronized cells have undergone telophase? What is the potential error rate in identifying the cell cycle stage using their visual imaging analysis? Without these key controls, it is unclear how to interpret the data presented in Fig 1B.

One reason that nuclear inheritance has not been properly addressed in the literature is the difficulty in obtaining pure populations of cells synchronized in telophase or recently divided cells in early G1. There are no drugs available which can uniquely target these cell stages. In addition, the ability of human cells to all release perfectly synchronously from a drug-induced arrest can vary with cell type. For this reason we used a strategy employing synchronization methods designed to enrich cell populations for telophase or early G1 events, combined with single cell analysis of events with the distinct cytological features of each stage. Cells that have recently divided are extremely distinctive and easily identified using a combination of DAPI morphology to assess nuclear size and condensation state and the presence of Aurora-B/Midbody staining to indicate a recent cytokinesis. Our approach of using single cell analysis coupled with quantitative imaging therefore does not require a high efficiency of synchronization in cell populations. To gain confidence that our observations were reproducible we analyzed a large number of cells, performed multiple experimental replicates, and applied statistical tests to the data.

To clarify these important points we have added text to the descriptions of how these experiments were performed (p3 line 72) and added information about the number of biological replicates to all figure legends and number of cell analyzed in each experiment to Supplementary Table 1.

1. The use of transcriptional inhibitors in Fig 1 is really nice and is important for showing that it's not due to new transcription following mitosis. Well done!

2. One potential mechanism that could explain the observed 25% relocalized nuclear RNA is through passive diffusion. That is, a proportion of molecules that are randomly diffusing during mitosis get trapped inside the newly formed nuclear membrane in early G1. This would be considered noise, and not a specific process that actively relocalizes nuclear RNA back into the nucleus. However, the authors' assay does not have a measure of the noise in their system. One potential experiment that may help quantify this noise is to express GFP in their cells, perform the experiment described in Fig 1A, and quantify the nuclear signal after telophase. This quantification would be the lower bound of the random process. A similar experiment with GFP-NLS could be performed to assess the upper bound of the 'inherited' molecules after mitosis. Without this type of control to quantify noise/random diffusion levels, it is unclear how much of the 25% EU signal that the authors detect is specific to the process they are testing.

We appreciate the point that the reviewer has raised. To address this concern we examined the localization of the abundant mRNA b-actin. We examined the fraction of all b-actin FISH signal that is present in the nucleus in G2 and G1 cells following division. If a significant fraction of RNA is trapped in the reforming nucleus then we would have expected the fraction of b-actin in the G1 nucleus to increase. We observed that less b-actin RNA was present in the G1 nucleus, suggesting that passive entrapment of RNA is unlikely to be a mechanism of RNA inheritance. This is consistent with a lack of inheritance of MALAT1 and NEAT1 lncRNAs following mitosis. We have added these results to a new Supplemental Figure 2 and added text describing the results to the Results section of the manuscript (p4 lines 101-113). Additionally, this result is consistent with recent work showing that mitotic chromosomes condense through histone deacetylation and exclude negatively charged macromolecules (PMID: 35922507) and that chromosome clustering by Ki67 in early G1 phase excludes the cytoplasm from the new nucleus (PMID: 32879492). These references and ideas are now included in the results section of the manuscript.

Related to the comment 1 and 2, EU labeling for 3 hrs in G2 cells would label ALL transcribed RNA, which would include mature mRNAs that will be translated in the cytoplasm. That is, this method is not specific to labeling nuclear RNAs only. How much of their signal is from mRNAs that got trapped inside the newly formed nuclear membrane? One way to test this is to measure the nuclear EU signal at later time points following telophase. Presumably, the nuclear transport mechanism would lead to export of non-nuclear RNAs and only the retained nuclear RNAs would contribute to the signal.

Please see our response to point 3 with regard to entrapment. The laboratory that originally described EU RNA labeling demonstrated a 3 hour EU labeling period results in labeling nuclear RNA, and that longer labeling periods are required to visualize EU labeling of cytoplasmic RNAs after export (18840688). We have also observed in our previously published work that the 3 hour period labels nuclear RNA during interphase (33053167, 32035037). The nuclear EU signal reflects RNAs undergoing transcription, nuclear retained RNAs, and mature mRNAs prior to nuclear export.

To identify nuclear RNAs that could be relocalized following mitosis, the authors analyzed data from "two different studies using different methodologies and a total of three different cell lines". From this analysis, the authors "found very little overlap in the chromatin-bound RNAs identified in these studies (Fig 2A)". This analysis seems fraught with problems. What is the rationale for using these studies? How valid is it to compare results from different methodologies and from different cell lines from the DLD-1 cells used in this study?

We analyzed the data from these two studies because they were the only published studies that identified RNAs that were tightly linked to chromatin. We chose to compare the results from three different human cell lines because we sought to identify nuclear RNAs that were cell type-independent, so that we could analyze the transcripts behavior in DLD1 cells. In support of using these two studies all the RNAs that we analyzed were nuclear in our RNA FISH assays.

A known problem of assessing chromatin-bound RNAs is that the level of contamination from cytoplasmic RNAs is highly variable and highly dependent on the assay. Indeed some of the most common contaminants of nuclear RNA assays are sn-, and sno-RNAs, and these are the main classes of RNA that the authors identified as common among the three data sets. What validation was used to assess whether these are the common noise/contaminants in the data?

Our goal in using the two previously published studies was to identify cell type-independent nuclear RNAs that could be studied in detail using FISH. For validation in our study we performed RNA FISH on MALAT1, NEAT1, and U2. We found that each of these RNAs are highly enriched in the nucleus, consistent with previous publications. Since snRNAs function in splicing and snoRNA primarily function in the modification of tRNA and rRNA in the nucleolus it seems unlikely that these are contaminants of nuclear preparations. Each of the published studies performed their own validations of their purification and sequencing methodology. For the purpose of our work nuclear enrichment of a transcript by RNA FISH satisfied our requirements.

One experimental validation that can be performed is biochemical fractionation of EU labeled cells, which would allow for fractionating nuclear from cytoplasmic RNA. The same problems arise with the analysis shown in Fig 3C when comparing SAF-A RIP-seq with this merged list of chromatin bound RNAs.

In support of the nuclear enrichment of each of the transcripts that we examined RNA-FISH analysis demonstrated significant nuclear enrichment. Additionally, many previous studies have shown that each of these transcripts are enriched in the nucleus (U2: 11489914, 10021385, 7597053; NEAT1: 17270048; MALAT1: 12970751, 17270048). New text describing our use of these studies is present in the results section (p4-5 lines 117-129).

Throughout the manuscript, the authors pose their findings as "RNA inheritance" following mitosis. However, this terminology is misleading. In fact, unless RNAs are lost/kicked out of the cell as they divide, aren't all RNAs inherited following cell division since they are present in the new daughter cells? Instead, what the authors mean is that some nuclear RNAs retain their function following cell division by relocalizing back into the nucleus in the new G1 cells, whereas other nuclear RNAs are unable to relocalize into the nucleus, and then presumably turned over by degradation process. The authors should take better care of their terminology throughout the manuscript.

Thank you for pointing this out to us. As the reviewer stated most nuclear RNAs are removed from chromatin during mitosis. Only a subset are reimported into the nucleus. We have modified our wording to clearly state that we are discussing nuclear RNA inheritance by daughter cell nuclei rather than inheritance into daughter cells in general. These text changes can be found throughout the manuscript.

Minor comments: 1. In all of the figures showing quantification of nuclear EU/FISH signal, the colors (red v blue) are not described (not found in the legend or methods). Presumably they are biological replicates, but this should be clearly stated.

We have modified the plots and figure legends to more clearly explain what is plotted (See text in Figure Legends). 2. Is figure 2E the same data presented in Fig 2D but in different y-axis? If so, state clearly

We have removed the data in the previous version of Figure 2E and replaced it with new data examining stability of MALAT1, NEAT1, and U2 in response to Reviewer 1 (p5 lines 154-166).

Figure 3A. This experiment is using the SAF-A-AID-mCherry system. Therefore the label in Fig 3A should be SAF-A-KD (Knockdown) instead of KO (knockout)

We have corrected this in Figure 3. 4. Typo in Fig 4B y-axis. It should be "Chromatin-localized SAF-A" instead of "Chromain-localized SAF-A"

Thank you for pointing this out, we have corrected it. 5. The methods section indicate the "precise N or replicates in indicated figure legends" but none of the figure legends have the N values listed.

We have listed number of biological replicates in all figure legends and included a new Supplemental Table 1 that contains the number of cells measured for each experiment.

Reviewer 3

The authors investigate an interesting question focussed on whether nuclear RNA from the previous cell cycle is present in the subsequent G1. It turns out that this is more complex than expected with some classes of RNA being inherited whilst others are not. SAF-A or HNRNPU had been implicated in this process but the authors suggest that its role is limited.

Figure 1 In panel A the authors write on image SAF-A-mCh. What does this refer to?

We have added information to the Figure legends indicating that this refers to SAF-A-AID-mCherry knocked-in to the endogenous SAF-A locus (see Figure Legends).

Panel B and other panels can the authors present this data as a boxplot or distribution plot to get a better feel of the data distribution spread.

We have modified all the plots in the manuscript to the Superviolin form to provide a clearer depiction of experimental replicates, mean, and standard deviation.

Presumably labelled RNAs are naturally turned over. Have the authors considered that some loss of signal could be because of this?

We have addressed the stability of specific RNAs using RNA FISH. We find that U2 and MALAT1 show essentially no degradation during the time course of our experiments. This data has now been included in an updated Figure 2. We have also modified our text to address this point more clearly (Figure 2E and p5 lines 154-166).

Panel E, have the authors considered labelling RNA before RO3306 treatment? What effect would this have?

We have performed this experiment in RPE1 cells and the presence of RO3306 did not affect cytological detection of transcript labeling. We have not included this experiment in the manuscript because it is performed in a different cell line than we use for the remainder of these studies.

Shouls TI be added before RO3306 washout?

We added transcription inhibitors after RO washout and entry into mitosis because transcription is naturally suppressed during mitosis. We were concerned that transcriptional inhibition in late G2 could lead to failure to properly enter into M phase.

Also, it is unclear what the arrows are pointing at. In panel F there is a difference between the red and blue experiments. In the methods the authors say that inhibition was for either 1.5 or 2 h. Is this the source of the difference?

We have modified the figure legends to state clearly that different colors indicate biological replicate experiments (See Figure Legends). Figure 2 In panel A there are clear differences between the cell lines. Is it right to compare them? Particularly the GRID-seq vs diMARGI? B, how relevant is it focussing on the "42" overlapping RNAs? In my mind this is not very informative.

Our goal with this analysis was to identify cell type-independent chromatin bound RNAs to analyze in greater detail. Therefore, we analyzed three different cell lines because we planned to analyze transcript behavior in DLD1 cells, which were not included in either study. We have explained this rationale in greater detail in a revised version of the text (p4-5 lines 116-129).

D-E, at a glance it is not clear that E is an expanded view of D. It might be easier if the panels were at same height.

We have removed Panel E and replaced it with a new experiment examining the stability of NEAT1, MALAT1, and U2 after transcription inhibition (p5 lines 154-166). Figure 3 Is it correct to describe IAA treated degron cells as a KO? I also could not see a WB showing how complete SAF-A KD was.

We previously characterized these cell lines in great detail (Sharp et al. JCB 2020). We have now provided quantitative measurement of SAF-A-mCherry fluorescence after different times of auxin addition to provide a quantitative estimate of SAF-A depletion (Supplemental Figure 3C).

2 h treatment seems quite short, is this enough time to obtain sufficient knock down? How heterogenous is SAF-A KD in the cell population?

We examined SAF-A depletion by auxin addition at 2 hours and 24 hours and achieve comparable depletion levels. This data in now included in Supplementary Figure 3C. There is some heterogeneity in the KD as is evident in Figure S3C, but these cells are easily identifiable by the presence of SAF-A-AID-mCherry fluorescence.

Previous studies have shown that SAF-A does not like being tagged. How certain are the authors that these cells behave typically?

We have generated two different cell lines (DLD1 and RPE1) where a C-terminal tag is inserted into the both copies of the endogenous SAF-A gene. SAF-A is one of the common essential genes (https://depmap.org/portal/gene/HNRNPU?tab=overview), however each of our cell lines exhibits no growth defects. We have recently shown that C-terminally tagged SAF-A fully rescues SAF-A knockout phenotypes (Sharp et al. JCB. 2020). Additionally, we have also performed RNA-seq (not published) on RPE1, RPE1 with endogenously tagged SAF-A and RPE-1 depleted of SAF-A and rescued with WT SAF-A-GFP and observed no changes in gene expression or mRNA splicing. Based on these assays we are confident that C-terminally tagged SAF-A expressed at endogenous levels functions normally. Figure 4 I'm struggling with the heading, and wonder if this is not supported by the data. Similarly the final sentence "The highly dynamic exchange of SAF-A:RNA complex" does not really provide an explanation.

We have expanded the text in this section to explain this phenotype in greater detail (p7 lines 216-218).

https://peergos.net/#%7B%22secretLink%22:true%2c%22link%22:%22#6MDZhRRPT4ugkJuUfcR4HUBKWFaAUE9Lc5F8GiPr4gYNR2K3729dZfUirK3CUe/6MDZhRRPT4ugkJuUfccsrqELFsuKZiwACb3uN1JqNM2perh5qRRvLkqMu8Ak2S/2MHRVbXfR5Via4rQ8xM2WJGkzpxpEfGM4ypFCVzdwFQ1RZV3ipBFi3AsXS9Yiz8k9rDHmDkPGSxHvqry8i5SkrufTtWu5TG/5Pf7SvmJqyjVp3YfWj9CEoYztefHw9LUQY1FoL2tufSa8henP6b%22%2c%22open%22:true%2c%22filename%22:%22UCAN%20call%202022%2012%2020%201.html%22%7D

= - trail

• https://web.archive.org/web/20170809093734/https://www.cypherpunks.to/erights/history/actors/actor-induction.pdf

• http://erights.org/history/actors.html

• http://erights.org/history/index.html
• http://erights.org/index.html

From Chris "cdata" Joel @ Subconscious to Everyone 07:58 PM http://skyhunter.com/marcs/ewalnut.html From Alan Karp to Everyone 07:59 PM http://erights.org/

= Alan Karp

Object Oriented program and

Globally addressable objects

=- bible

From Chris "cdata" Joel @ Subconscious to Everyone 07:58 PM http://skyhunter.com/marcs/ewalnut.html From Alan Karp to Everyone 07:59 PM http://erights.org/

xxxx

asked in chat

From Me to Everyone 07:39 PM I do have one question  From Jess Martin to Everyone 07:40 PM @gyuri: if it doesn't get covered in this call, feel free ask in the fission Discord and tag me, as I have a feeling I was on the livestream of which you speak 🙂 From Blaine Cook to Everyone 07:40 PM 💯 From Me to Everyone 07:41 PM I reallu liked the idea of no signup needed to control wenbative identity. This may have implications to the way the whole webnative SDK based app are to be created/distributed and thought off. Any comments would be apprefiatd. This may not be the right forum, but it is live From Brooklyn Zelenka (@expede) to Everyone 07:42 PM Im checking in sorry folks gimme a minute From Me to Everyone 07:42 PM Yes will do.

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Reply to the reviewers

1. General Statements [optional]

We would like to thank the reviewers for taking time in reviewing and commenting on our paper. The comments were very constructive and conscientious, thanks to their expertise in the field. These comments and the revisions would surely make this paper a better and more robust finding in the field.

The comments were about clearer explanations, increasing the quality of the data and additional experiments for a stronger conclusion, all of which we are eager to accomplish. Now we have sorted out the problems and planned the experiments required in the revision, as detailed below.

2. Description of the planned revisions

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

Summary In this manuscript, Komori et al. examined the role of the LRRK2 substrate and regulator Rab29 in the lysosomal stress response. Briefly, in chloroquine (CQ)-treated HEK293 cells the authors observed an apparent LRRK2-independent increased in Rab29 phosphorylation which was accompanied by translocation of Rab29 to lysosomes. Intriguingly, the authors detected a similar increase in Rab29 phosphorylation when Rab29 was tethered to lysosomes in the absence of CQ treatment. Using mass spectrometry, mutagenesis and a phospho-specific anti-body, the authors mapped the CQ-induced phosphorylation site to S185 and demonstrated its independence from LRRK2. Next, the authors found that PKCa was the kinase responsible for S185 phosphorylation and lysosomal translocation of Rab29. Lastly, the authors showed that in addition to PKCa the lysosomal translocation of Rab29 was also regulated by LRRK2. Overall, Komori and colleagues provide interesting new insights into the phosphorylation-dependent regulation of Rab29. However, there are. Number of technical and conception concerns which should be addressed.

Major points 1) Figure 1F: the localization of Rab29 to lysosomes is not convincing at all. The authors should either provide more representative image examples or image the cells at a higher resolution. The authors should also confirm the CQ-induced lysosomal localization of Rab29 in a different cell type (e.g., HEK293).

We will replace Fig 1F pictures with slightly more magnified images with higher resolution. We will also include additional cell types (HEK293, and other cells that are predicted to express endogenous Rab29); Reviewer #2 also raised this point (see Reviewer #2 comment on Significance).

Moreover, the authors should show that prenylation of Rab29 is required for its CQ-induced phosphorylation.

We will test the effect of lovastatin, a HMG-CoA reductase inhibitor that causes the depletion of the prenylation precursor geranylgeranyl diphosphate from cells (Binnington et al., Glycobiology 2016, Gomez et al, J Cell Biol 2019), or 3-PEHPC, a GGTase II specific inhibitor that also causes the inhibition of Rab prenylation (Coxon FP et al, Bone 2005).

2) The rapalog-induced increase in Rab29 phosphorylation in Figure 2D is not convincing since there is at least 2-3-fold more Rab29 in FRB-LAMP1 expressing cells compared to their FRB-FIS1 counterparts. An independent loading control is also missing. This is a key experiment and should be properly controlled and quantified. In addition, can CQ treatment drive 2xFKBP GFP-Rab29 from mitochondria to lysosomes (in the presence of rapalog and FRB-Fis1)?

We will carefully examine another round of rapalog-induced phosphorylation of Rab29, with an independent loading control such as alpha-tubulin. The immunoblot analysis will be made against the intensity of non-p-Rab29. The response to the latter question was described in the section 4 below.

3) Figure 4A-C: Are these stable Rab29 expressing cells? If not, the quantification of "the size of largest lysosome in EACH cell" becomes very problematic. This analysis should be repeated with stable Rab29 variant cells in a background lacking endogenous Rab29. Furthermore, the LAMP1 signal is too dim to see any convincing colocalization (e.g., with WT) or the lack thereof (e.g., in the case of S185D).

The cells shown in Figure 4 are HEK293 cells transiently expressing Rab29, and the issue of quantification was described in the section 3 below. We agree that the signal of LAMP1 was dim, and it turned out that the confocal microscope we used had problems with the sensitivity of the red channels. We will be taking another round of these images with a new confocal microscope.

Lastly, the authors should corroborate their findings with an ultrastructural analysis since the electron microscopy would definitively be more suitable for this type of measurements.

We are planning to obtain electron microscopic images, according to this reviewer’s request. We plan to invite an expert in electron microscopy analysis as a co-author.

4) The lysosomal colocalization of Rab29 in Figure 5C is again not convincing. This analysis needs to be repeated with high resolution imaging.

Again, we will repeat this experiment with a new confocal microscope, with the hope that it would yield better images.

5) The authors need to show the level of LRRK2 depletion (Figure 6). Given the role of LRRK2 in driving lysosomal Rab29 translocation, the importance of the LRRK2 independent pS185 for this process remains unclear.

We will add the level of LRRK2 on its knockdown; we have experienced that LRRK2 knockdown usually occurs with more than 50% efficiency every time. The response to the latter comment was described in the section 3 below.

6) In general, the authors employ an alternative, biochemical assay (e.g., LysoIP) for the lysosomal translocation of Rab29. This would in particular help to clarify the effect of the Rab29 variants and LRRK2 inhibition.

We have previously shown that the overexpressed Rab29 (and LRRK2) is enriched in the lysosomal fraction from CQ-treated cells, which was performed using dextran-coated magnetite (Eguchi et al, PNAS 2018). Using the same biochemical method, we will show the enrichment of endogenous Rab29 in the lysosomal fraction.

Minor points

9) Figure 2C is lacking the control IF staining for mitochondria (to which 2xFKBP-GFP-Rab29 is assumed be recruited upon co-expression with FRB-FIS1).

We will stain the cells with MitoTracker to ensure that anchoring away of 2xFKBP-GFP-Rab29 by FRB-Fis1 results in mitochondrial localization.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

The data in the manuscript convincingly demonstrates that lysosomal overload by Chloroquine treatment induces Rab29 localisation to the lysosomes and that this membrane association is dependent on PKCalpha-dependent phosphorylation at Ser185.

We have a number of rather minor comments listed below:

Figure 2

The increasing levels of non-phosphorylated Rab29 over the indicated time course of AP21967 treatment in Figure 2B are concerning. First, could you provide an explanation for this clear increase in both non-p-Rab29 and p-Rab29 in the phostag but not the normal gel? Second, could all quantifications of p-Rab29 be made relative to the non-p-Rab29?

We will try another round of rapalog-induced phosphorylation of Rab29, with an independent loading control. The immunoblot analysis will be made against the intensity of non-p-Rab29. Reviewer #1 raised a similar concern on Figure 2D.

Figure 5

To further demonstrate that PKCalpha phosphorylates endogenous Rab29 at Ser185, we recommend reperforming the Go3983/PMA treatment in figure B with the anti-p-Ser185 antibody. It may be sufficient to perform the treatment only at 4 or 8 hours, simply to provide stronger evidence regarding the phosphorylation of endogenous Rab29.

We will give a try, although the anti-phosphorylated protein antibodies that we tried never worked for phos-tag SDS-PAGE. With the conventional western blot, we will be able to try this experiment.

It is not clear whether the activity of PMA in the assay is due to inhibition of PKCalpha. Are the effects ablated by PKCalpha KD

We will test the knockdown of PKCalpha, beta, gamma and delta by siRNAs to further narrow down the effects of PKC-dependent phosphorylation of Rab29.

Reviewer #2 (Significance (Required)):

These cell biology findings are important in the field as both Rab29 and LRRK2 are implicated in the pathogenesis of Parkinson disease. The phosphorilation of Ser185 of Rab29 by PKCalpha is novel and contributes to our understanding of Rab29 and LKRR2 regulation. One limitation of the study is that is conducted in only two cell types quite unrelated to the disease, so how general and disease relevant are the findings it is not clear. Most of the data are solid. There are two experiments whose results are difficult to interpret and a few controls missing. Also a few issues with quantifications, all of which is described in details above and will need to be fixed prior to publication. My expertise for this paper is in the cell biology of lysosomal function.

The issue that only two cell types were analyzed was also raised by reviewer #1, so we will examine additional cell types, especially those that are predicted to express endogenous Rab29. Our responses to other issues raised are described elsewhere. Thank you for these insightful comments.

3. Description of the revisions that have already been incorporated in the transferred manuscript

Figure 4A-C: Are these stable Rab29 expressing cells? If not, the quantification of "the size of largest lysosome in EACH cell" becomes very problematic. This analysis should be repeated with stable Rab29 variant cells in a background lacking endogenous Rab29. (Reviewer #1)

As described in the section 2 above, the cells shown in Figure 4 are HEK293 cells transiently expressing Rab29. We are sorry that the description “the size of largest lysosome in each cell” was misleading. As we analyzed only cells overexpressing GFP-Rab29 that were marked with GFP fluorescence, we believe that transient expression should not be a problem. To avoid any misunderstandings, we have described in Figure 4 legends that only lysosomes in Rab29-positive cells (and all cells expressing Rab29) were included in the analysis of the largest lysosome of each cell.

Regarding the effect of endogenous Rab29 in Figure 4 experiments, Reviewer #2 similarly raised the issue on whether Rab29 phosphomimetics are acting as dominant active, preventing lysosomal enlargement. On this point, we have previously reported that knockdown of endogenous Rab29 causes the enhancement of lysosomal enlargement upon CQ treatment (Figure 5I,J of Eguchi et al, PNAS 2018), suggesting that the lysosome-deflating effect by phosphomimetics is a dominant active effect rather than dominant negative suppressing endogenous Rab29. This point is considered significant, and thus has been explained in the results section (page 7, lines 168-171).

Along similar lines: why not all cells in Figure 5E and Figure 5G show Rab29- and LRRK2-positive structures? How do the authors know which of these phenotypes is the prevalent one? (Reviewer #1)

As for the ratio of cells with Rab29- and LRRK2-positive structures, it seems reasonable given that different cells have different levels of exposure to lysosomal stress and that the response is transient and does not occur simultaneously. The ratio of these positive cells may also vary depending on the cell culture conditions. Since Rab29- and LRRK2-positive structures are rarely seen in control cells, we think this would be a meaningful phenotype even if only 20-30% of cells show such structures. The result that the ratio of localization changes is not 100% is now noted in the results section explaining Figure 1G (page 4-5, lines 108-110) where the immunocytochemical data first appears.

Given the role of LRRK2 in driving lysosomal Rab29 translocation, the importance of the LRRK2 independent pS185 for this process remains unclear. (Reviewer #1)

Our data suggested that Rab29 is stabilized on lysosomes only when LRRK2-mediated phosphorylation and S185 phosphorylation both occur on Rab29 molecule (as shown in Figure 7 scheme), so we believe there is no contradiction. We have now described more clearly about this notion at the end of the results section (page 9, lines 235-236).

It is not clear what the authors mean by "lysosomal overload stress". Since mature lysosomal incoming pathways such as autophagy or endocytosis are disrupted by CQ, it is difficult to picture an overload. Maybe rephrasing would help to clarify this. (Reviewer #1)

Chloroquine (CQ) is known as a lysosomotropic agent that accumulates within acidic organelles due to its cationic and amphiphilic nature, causing lysosome overload and osmotic pressure elevation, and this is what we call “lysosomal overload stress”. The well-known effects of CQ to disrupt lysosomal incoming pathways are ultimately caused by the above consequences. Also, we have previously reported that lysosomal recruitment of LRRK2 is caused by CQ but not by bafilomycin A1, the latter being an inducer of lysosomal pH elevation, or by vacuolin-1 that enlarges lysosomes without inducing lysosomal overload/pH elevation (Eguchi et al, PNAS 2018), and further found that not only CQ but also other lysosomotropic agents commonly induced LRRK2 recruitment (Kuwahara et al, Neurobiol Dis 2020). We thus have described the effect of CQ as “overload”. However, it is true that we have not provided a clear explanation for readers, so we have added some notes for lysosomal overload stress in the introduction section (page 3, lines 69-71).

Which cell type is used for the IF analysis in Figure 2C? This information is in general quite sparse. The authors should clearly state the cell type for each experiment/Figure. (Reviewer #1)

We have added cell type information that was missing in several places in the manuscript. We are very sorry for the inconveniences. For clarification, HEK293 cells were used in Figure 2C.

Are the images in figure 1F representative? i.e. does Rab29 always colocalise to such enlarged lysosomes upon CQ treatment and does CQ treatment always drastically alter the cellular distribution of Rab29? (Reviewer #2)

The images in Figure 1F are representative of when Rab29 is recruited, but it is not seen in all cells, and the ratio of recruitment (~80%) is shown in Figure 1G. Reviewer #1 also asked why Rab29 recruitment is not seen in all cells, and we gave the same answer above. It may be reasonable to speculate that different cells have different levels of exposure to lysosomal stress and that the response is transient and does not occur simultaneously. The ratio of these positive cells may also vary depending on the cell culture conditions. For the readers’ clarity, we have added that the ratio of localization change of Rab29 is not 100% and is comparable to that of LRRK2 previously reported (page 4-5, lines 108-110).

Considering that the "forced localisation technique" induces a non-physiological colocalization of non-endogenous Rab29 to lysosomes, it may be an overestimation to conclude just from these data that phosphorylation of Rab29 occurs on the lysosomal surface. This is also quite in contrast with the later finding that phosphorylation by PKCalpha promotes lysosome localization of Rab29. It seems more reasonable to conclude that Rab29 can be phosphorylated when localised at the lysosomes (as opposed to other organelles such as mitochondria). If the authors feel strongly about this point they might need to find a less non-physiological assay. (Reviewer #2)

Yes, it could be an overestimation, and as we do not have better means to conduct a less non-physiological assay, we have modified the description from “occurred on the lysosomal surface” to “could occur on the lysosomal surface” (page 5, line 112 (subtitle) and line 128).

Regarding the comparison with the later finding that phosphorylation by PKCalpha promotes lysosome localization of Rab29, these data (Figure 2 and 5) could be explained with a single speculation: phosphorylation of Rab29 on lysosomal membranes could retain Rab29 on the membranes for a longer time. It is not easy to decipher which comes first, association with membranes or phosphorylation of Rab29, in a physiological assay, but considering reports that show PKCalpha activation happens on membranes (Prevostel et al., J Cell Sci 2000), at least the data favor our conclusion over the idea of PKCalpha phosphorylating Rab29 in the cytoplasm and then promoting lysosomal localization. This point is now clearly described in the discussion (page 10, lines 248-251).

It is not clear how the Rab29 phosphomimetics are acting as dominant active preventing lysosomal enlargement. Authors should speculate or repeat the experiments in absence of endogenous Rab29 to clarify the matter. (Reviewer #2)

A similar concern about the effect of endogenous Rab29 was also raised by Reviewer #1 (see above). We have previously reported that knockdown of endogenous Rab29 causes the enhancement of lysosomal enlargement upon CQ treatment (Figure 5I,J of Eguchi et al, PNAS 2018), suggesting that the lysosome-deflating effect by phosphomimetics is a dominant active effect rather than dominant negative suppressing endogenous Rab29. This point is considered important and thus has been explained in the results section (page 7, lines 168-171).

Overall, there is some missing information regarding repeats for Western blots, such as those in figure 3C, 3D and 3E. Please add indications about repeats in the figure legend or methods. (Reviewer #2)

We have added the repeat information to each figure legend where it was missing. We are very sorry for the inconveniences.

The model in figure 7 however seems to suggest that Rab29 associates to lysosomal membranes independently, and is then stabilised at the membranes by LRRK2 and PKCalpha - a point which is not directly supported by the data. (Reviewer #2)

As noted earlier, we consider that phosphorylation of Rab29 on lysosomal membranes could retain Rab29 on the membranes for a longer time, given the present data and previous reports that phosphorylation of Rab29 is more likely to happen on the lysosomal membrane than in the cytosol. Also, as inhibition of either of the two phosphorylations ends up in disperse Rab29 localization, we have made this figure as a model of what is plausible right now. This explanation is now added in the discussion (page 10, lines 248-251).

English proofreading should be improved: "CQ was treated to HEK293" (page 4), "As we assumed that this phosphorylation is independent of LRRK2" as an opening line (page 5) (Reviewer #2)

Thank you for pointing out these incorrect wordings. They were corrected.

4. Description of analyses that authors prefer not to carry out

In addition, can CQ treatment drive 2xFKBP GFP-Rab29 from mitochondria to lysosomes (in the presence of rapalog and FRB-Fis1)? (Reviewer #1)

We do not think that a comparison between the affinities of FKBP-rapalog-FRB and Rab29-[unknown factor that directs Rab29 to lysosomes] is necessary, as the former has a Kd in the single digit nM range (Banaszynski et al, JACS 2005), whereas the latter (based on estimations from related PPIs) is estimated to be in the μM range, which shows a much weaker affinity than the former (McGrath et al, Small GTPases 2019). Furthermore, even if Rab29 appears to have migrated from mitochondria to lysosomes as a result of this experiment, one cannot rule out the possibility that a small portion of the mitochondrial membrane was incorporated into the lysosomal membrane that was enlarged by CQ treatment.

Molecular weight markes should be provided for all immunoblot experiments. (Reviewer #1)

The immunoblot pictures without molecular weight markers in our paper are all Phos-tag SDS-PAGE blot analyses. Phos-tag SDS-PAGE results in band shifts of phosphorylated proteins, and writing in markers would be misleading. Moreover, previous representative studies heavily using Phos-tag (e.g., Kinoshita et al, Proteomics 2011, Ito et al, Biochemical Journal 2016) also did not show the molecular weight markers. Here we performed phos-tag SDS-PAGE analysis only to find differences in the phosphorylation state of Rab proteins.

The use of the quantification ratio of cells with Rab29-positive lysosomes in figure 1G might be slightly misleading as it does not allow the reader to understand to what extent Rab29 localisation at lysosomes upon CQ treatment. We recommend using a simpler quantification, such as by measuring the average colocalisation of Rab29 and LAMP1 per cell. (Reviewer #2)

For figure 5D and 5F, As with figure 1G, we recommend using a more straightforward and impartial method of quantification such as simply measuring the colocalisation of Rab29 with LAMP1. (Reviewer #2)

Popular colocalization analyses using Pearson’s or Mander’s coefficients would be a good choice if the amounts of Rab29 varied greatly between lysosomes. However, this may not apply in this case; the amount of Rab29 or LRRK2 on each lysosome is considered to saturate quickly and a relatively low amount of them may not be detected on immunofluorescence observations, whereas the probability of finding these structures has been shown to exhibit a moderate sigmoid curve (as seen in Figure 1E or 2H of Eguchi et al., PNAS 2018). Therefore, the amount of Rab29 or LRRK2 could be approximated to a Bernoulli distribution in terms of colocalization with lysosomes, and this is the reason why we chose to quantify “the ratio of cells with Rab29-positive lysosomes”.

We recommend using a more transparent and simple quantification method, such as average size of lysosomes per cell. (Reviewer #2)

As one can see in the inset of Figure 4B, unenlarged lysosomes are unfortunately too small for the quantification of their size, much less tell two small lysosomes apart in our experimental settings and laboratory resources, so we decided to analyze the largest lysosome in each cell as a representative of the cells to minimize measurement errors. This measurement only includes GFP-Rab29 positive cells, and by comparing against CQ-untreated cells we intended to increase the validity of this analysis. This quantification method was also used in our previous report (Eguchi et al, PNAS 2018).

Reviewer #1 (Public Review):

In this study, the protein composition of exocytotic sites in dopaminergic neurons is investigated. While extensive data are available for both glutamatergic and GABA-ergic synapses, it is far less clear which of the known proteins (particularly proteins localized to the active zone) are also required for dopamine release, and whether proteins are involved that are not found in "classical" synapses. The approach used here uses proximity ligation to tag proteins close to synaptic release sites by using three presynaptic proteins (ELKS, RIM, and the beta4-subunit of the voltage-gated calcium channel) as "baits". Fusion proteins containing BirA were selectively expressed in striatal dopaminergic neurons, followed by in-vivo biotin labelling, isolation of biotinylated proteins and proteomics, using proteins labelled after expression of a soluble BirA-construct in dopaminergic neurons as reference. As controls, the same experiments were performed in KO-mouse lines in which the presynaptic scaffolding protein RIM or the calcium sensor synaptotagmin 1 were selectively deleted in dopaminergic neurons. To control for specificity, the proteomes were compared with those obtained by expressing a soluble BirA construct. The authors found selective enrichments of synaptic and other proteins that were disrupted in RIM but not Syt1 KO animals, with some overlap between the different baits, thus providing a novel and useful dataset to better understand the composition of dopaminergic release sites.

Technically, the work is clearly state-of-the-art, cutting-edge, and of high quality, and I have no suggestions for experimental improvements. On the other hand, the data also show the limitations of the approach, and I suggest that the authors discuss these limitations in more detail. The problem is that there is very likely to be a lot of non-specific noise (for multiple reasons) and thus the enriched proteins certainly represent candidates for the interactome in the presynaptic network, but without further corroboration it cannot be claimed that as a whole they all belong to the proteome of the release site.

Donwell Abbey is fiction, perhaps based on the real-life Claremont Park in Surrey, Highbury as Kenneth Smith evidences in his essay. However, Austen did not make up the popularity of strawberry season. Berry-picking could start as early as May reach its peak in July and and end in September (Eat the Seasons UK has a chart to follow). According to Austen's chronology, it is the "middle of June" in this segment and, as Mr. Knightley assures Mrs. Elton, the strawberries are already "ripening fast". Joanne Major's essay "Strawberries and cream: A Wimbledon tradition with a hong history" provides a brief history of British strawberry fanaticism paired with images that illustrate just how long the berry has remained a British summer staple. Why does Austen contrast "strawberries" with "cabbage-beds" then? The Royal Horticultural Society answers that cabbages can be harvested year round. Together with potatoes they make up the latter part of another common British staple "bubble and squeak". Even the mundanity of cabbages, Austen tells us, might "tempt" Mrs. Elton in her current state of restlessness.

Donwell Abbey is fiction, perhaps based on the real-life Claremont Park in Surrey, Highbury as Kenneth Smith evidences in his essay. However, Austen did not make up the popularity of strawberry season. Berry-picking could start as early as May reach its peak in July and and end in September (Eat the Seasons UK has a chart to follow). According to Austen's chronology, it is the "middle of June" in this segment and, as Mr. Knightley assures Mrs. Elton, the strawberries are already "ripening fast". Joanne Major's essay "Strawberries and cream: A Wimbledon tradition with a hong history" provides a brief history of British strawberry fanaticism paired with images that illustrate just how long the berry has remained a British summer staple. Why does Austen contrast "strawberries" with "cabbage-beds" then? The Royal Horticultural Society answers that cabbages can be harvested year round. Together with potatoes they make up the latter part of another common British staple "bubble and squeak". Even the mundanity of cabbages, Austen tells us, might "tempt" Mrs. Elton in her current state of restlessness.

一般使用在template上，不支持x-transition

https://lukechandler.wordpress.com/tag/standing-stone/

annotation meta: may need new tag: - developer use case - more complicated to express than they need to be.

annotation meta: may need new tag: the runaround?

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Reply to the reviewers

Reviewer 1

This paper identifies a role for the hereditary spastic paraplegia protein spatacsin in lysosome morphology, positioning and dynamics, and undertakes detailed mechanistic studies to try to identify the mechanism for this effect. In doing so the paper elucidates further mechanistic information about the properties of two other hereditary spastic paraplegia proteins, spastizin and AP5Z1. The work is done in mammalian cells and uses a combination of over-expression, depletion and biochemical studies. The main findings are:

1. The authors present evidence that spatacsin is an ER-localised protein.
2. Murine embryonic fibroblasts lacking spatacsin have a reduced number of tubular lysosomes and the remaining lysosomes are less motile. In general, a relationship between tubular lysosome morphology and lysosome motility, often in association with the endoplasmic reticulum (ER), is demonstrated. These tubular lysosomes are catalytically active and acidic.
3. In terms of mechanism of this effect, by combining a yeast-two hybrid and siRNA phenotypic screen, the authors identify a number of spatacsin-interacting proteins that also regulate lysosomal tubulation. The most important of these for the purposes of this paper is UBR4, an E3 ubiquitin ligase.
4. The authors show that spatacsin and UBR4 promote degradation of AP5Z1, and that this property required the ability of spatacsin to interact with UBR4. Somewhat surprisingly, as AP5Z1 is a coat protein, this degradation appeared to occur within the lumen of the lysosome - the authors speculate how this could be in the discussion.
5. The authors then demonstrate that AP5Z1 and spastizin, both hereditary spastic paraplegia proteins, compete for binding with spatacsin.
6. The relationship between spatacsin, spastizin, AP5Z1 and motor proteins in then examined. There is a known interaction between spastizin and KIF13A and expression of a dominant negative KIF13A protein reduced lysosomal tubulation. The authors then demonstrate an interaction between AP5Z1 and the p150Glued dynein/dynactin complex member, then showed that expression of a dominant negative p150Glued protein reduced lysosomal tubulation.
7. Finally, that authors demonstrate the relevance of these findings to neurons, the target cells of hereditary spastic paraplegia, by showing that lysosomal tubulation and axonal transport are reduced in mouse neurons lacking spastacsin, and that depletion of UBR4 or AP5Z1 affected these as expected from the experiments above.

Major comments:

Overall I believe that the key conclusions of this paper are generally convincing and that the work is of high quality. However, I do have some reservations:

1. The localisation of spatacsin on the ER. It is always difficult to be convinced about colocalization of a diffuse punctate marker and the ER. From the STED experiments in figure 1, while it definitely seems that there is some spatacsin on the ER, there also appears to be some spatacsin puncta that are not. I'd like to know if these puncta represent lysosome-associated spatacsin. This is important for interpretation of the subsequent experiments (see point 3 below). I also think quantification of these co-localisation will increase confidence in the results. In addition, a caveat of the immunofluorescence studies is that they use over-expressed spatacsin. I appreciate that there are no good antibodies to endogenous spatacsin, but I don't think this limitation is sufficiently acknowledged. As the claim of ER-localisation is critical for the proposed mechanistic model, and in the absence of experiments with endogenously tagged spatacsin, this makes the biochemical fractionation studies of figure 1C very important. To make these more convincing I would prefer to see additional control markers to verify the separation of lysosomal and ER compartments - e.g. lamp1, lamp2, an ER tubular marker such as a REEP5 or a reticulon.

Authors response : We agree with the reviewer that the localization of spatacsin is critical, and we appreciate the knowledge of the reviewer concerning the lack of good antibodies to endogenous spatacsin. We better acknowledged this limitation in our revised manucript (p. 5 and p. 15). We performed extra experiments to convincingly show that spatacsin is indeed localized at the ER. First, we performed 3-color STED experiments to visualize in the same cell spatacsin, the ER and lysosomes. The preliminary data seem to indicate that some spatacsin is associated with lysosomes at ER-lysosomes contact site. We plan to add quantifications of colocalization between spatacsin and ER staining at STED resolution to better support the fact that spatacsin is a protein of the ER.

Moreover, as requested, we have performed a western blot with Lamp2 and REEP5 antibodies on the ER- and lysosome-enriched fractions (New Figure 1B). This western blot shows that a significant proportion of Lamp2 is present in the ER-enriched fraction, which may be explained by the strong association of ER with late endosomes and lysosomes. Yet the lysosome-enriched fractions that contained no ER markers do not present spatacsin staining, suggesting that spatacsin is either in the ER or in lysosomes associated with the ER that are not positive for cathepsin D. We reformulated the text of Figure 1 according to the new included data (p. 5-6).

The authors generally do a good job of quantifying their results. However, this is lacking for the biochemical experiments (immunoblotting and IP) in figures 4 and 5, and I would prefer to see these quantified (the quantification should include data from repeat experiments so that we can judge the reproducibility of the results).

Authors response : We agree that our presentation did not indicate that the western blots were repeated several times. We have added quantifications for the western blots present in Figures 4 and 5.

On page 10, referring to the proximity ligation results, the authors comment: "This suggests that the spatacsin-spastizin interaction occurs at contact sites between the ER and lysosomes to allow spastizin recruitment to lysosomes". I'm not sure this statement is fully supported, as mentioned at point 1 above it is possible that some steady state spatacsin is at lysosomes. To fully support this, we'd need to see the PLA signal also convincingly co-localise with an ER marker.

Authors response : We will perform extra PLA experiment to indeed show that the spots where spatacsin and spastizin colocalize with an ER marker. This data will be added in Figure 5.

In figure 6C and D the effect of spastizin on lysosomal tubulation and dynamics is investigated. Wartmannin treatment is used to do this, as it is known to remove spastizin from lysosomes. However, this is a very indirect manipulation that could have many other consequences and it would be better to demonstrate this directly by showing the effect of depletion of spastizin on lysosomal morphology/dynamics. I also think the role of AP5Z1 in tubulation/dynamics would be better supported with additional experiments to deplete the protein - at present only over-expression is examined.

Authors response: *We added new data to answer this comment. Downregulation of spastizin using siRNA led to lower number of tubular lysosomes and decreased the proportion of dynamic lysosomes, showing that spastizin is required to regulate lysosome motility (Figure 6B-6C Supplementary Figure 7B). We have also added new data regarding downregulation of AP5Z1 (Figure 6A-6C-Supplementary 7A). Both overexpression and downregulation of AP5Z1 using siRNA decreased the number of tubular lysosomes and decreased the proportion of dynamic lysosomes (Figure 6A-6C-Supplementary Figure 6C-D). *

This observation suggests that the levels of AP5Z1 must be tightly regulated to control lysosome motility. We added discussion about this point as well (p.12-13).

While the experiments showing that over-expression of dominant negative forms of KIF13A and p150Glued affect lysosomal tubulation/dynamics provide good circumstantial evidence that spatacsin influences these lysosomal properties via its interactions with spastizin and AP5Z1 (which bind to these motor proteins), the authors have not shown that the interaction of the motor proteins with spastizin and AP5Z1 is required for this ability to regulate lysosome tubulation/dynamics. This means that the model presented in figure 7 is not fully supported by the data. If the authors have been able to map the binding regions for these interactions then perhaps this could be investigated with rescue experiments, although I appreciate that this is potentially a major piece of work and perhaps outside the scope of this paper. An alternative would be that the authors acknowledged this part of the model as somewhat speculative.

Authors response : We agree with the reviewer that our data do not show that KIF13A and p150Glued interact directly with spastizin and AP5Z1 to regulate lysosome dynamics. It has previously been shown that the adaptor complex AP2 interacts with p150glued via the ear domain of AP2 b subunit (Kononenko et al, 2017). It is therefore likely that the interaction of adaptor complex 5 with p150-Glued also occurs via AP5B1 subunit, and thus interaction of AP5Z1 with p150 glued would be indirect. *We discussed this point carefully (p.16). *

*Regarding the interaction of Spastizin with KIF13A, it was identified by yeast-two hybrid screen and validated by GST-pulldown (Sagona et al, 2010). This showed that KIF13A interacts with the C-terminal domain of Spastizin, and we discussed this point. To confirm that KIF13A interaction with spastizin is required to promote its role in tubular lysosome formation and dynamics, we can perform an experiment where we downregulate endogenous mouse spastizin using siRNA and express either full length human spastizin to rescue the effect of the siRNA, or overexpress a human spastizin lacking its C-terminal domain required for the interaction with KIF13A (where we would expect no rescue). This would strengthen our conclusion on the role of KIF13A in link with spastizin to regulate the formation and dynamics of tubular lysosomes. We could add these data in Figure 6 (or Supplementary Figure 7). *

• Are the experiments adequately replicated and statistical analysis adequate?

In general I am not convinced that the statistical tests are applied rigorously in this paper. Most experiments are done three times, but the "n" used for statistical testing is typically chosen as, e.g. the number of cells, number of lysosomes, rather than number of biological repeat experiments. This means that inter-experimental variability is not rigorously taken into account. A more rigorous practice would be to use the mean measures for each of three biological repeats and apply the statistical tests to the three means, so n=3 if three repeats were done. Superplots would be a nice way to graphically display these data.

Authors response : We agree with the comments of the reviewer regarding data presentation. We have therefore changed the presentation of all graphs of the manuscript using superplots that allow us to show all the points that were analyzed as well as the mean value for each biological replicate, and performed statistical analyses by comparing the biological replicates as proposed in Lord et al, JCB 2020 (10.1083/jcb.202001064).

Minor comments:

1. In supplementary figure 3D I cannot honestly say that I see the smaller band.

Authors response : We agree that this western blot is not clear. We will provide a new western blot.

When first called out, I expected supplementary tables 1 and 2 to show the list of interactors with wild-type spatacsin and spatacsind32-34 respectively, but this is not what they show.

Author response : We have added two supplementary data tables (Now Supplementary Tables 1 and 2) to give the list of interactors of wild-type C-terminal domain of spatacsin and spatacsinD32-34, respectively.

Supplementary Tables 3 and 4 now refer to the analysis of the downregulation experiments by respectively the neural network method and the tubular lysosome detection method.

The experiments in Figure 4A are a little problematic in the way that they are called out. The first call refers to just a small subset of the data in the figure, and the figure is then called out at various points later in the paper. This is quite confusing. Is there any way this could be simplified?

Authors response :We agree with the reviewer that Figure 4A was called at various points of the manuscript. This was to avoid duplicating data into two separate figures. However, we have modified the presentation of Figure 4 and Figure 5. We have included new Figure 4C to show that downregulation of UBR4 prevents the degradation of AP5Z1 upon overexpression of Spatacsin-GFP, but also in basal conditions in wild-type fibroblasts. The co-IP that was originally presented in Figure 4A has now been moved into Supplementary Figure 6A.

The section on page 10: "Spatacsin also interacts with spastizin, and is required to recruit spastizin to lysosomes (Hirst et al., 2021). ........ We hypothesized that spatacsin interaction with spastizin was required for spastizin localization to lysosomes." Is odd, as the authors seem to be hypothesising an observation that they have just said has already been demonstrated.

Authors response : We agree that these sentences were odd. We have rephrased the paragraph (p. 11).

Can the authors explain why there is so little interaction between wild-type KIF13A and spastizin?

Authors response : The interaction domain of spastizin with KIF13A is close to the motor domain according to the two-hybrid data published by Sagona et al (2010). The dominant negative construct of KIF13A that is devoid of the motor domain (KIF13A-ST) may thus facilitate access of spastizin to binding domain. We have commented on this point in the text (p.13).

In figure 6G p150Glued signal is also present in the control IP lane, which casts doubt on the specificity of the interaction. Could the authors generate a cleaner result?

Authors response : We have repeated the experiment 3 times, always with some p150Glued signal present in the control IP. Of note, as stated in the method section, we have increased the concentration of NaCl in the washing of this co-IP to decrease non-specific binding of p150glued to control beads, but we could not get cleaner results so far. We will try to get cleaner western blot to illustrate Figure 6G.

I would be interested to see how AP5Z1 expression differs between neurons with and without spatacsin- we would expect similar results to those shown in the MEFS.

*Authors response : We have not checked the levels of AP5Z1 in neurons with and without spatacsin yet. However, the complete knockout of spatacsin strongly modifies the levels of its partners. We previously showed that spastizin levels are decreased by >90% in Spg11 knockout brain (Branchu et al, 2017). Furthermore, the levels of AP5Z1 have been shown to be decreased by ~50% in fibroblasts of SPG11 and SPG15 patients (Hirst et al, 2015). *

*Our work shows that spatacsin promotes the degradation of AP5Z1 by lysosomes. It is possible that other degradation mechanism(s) may exist and could explain the lower levels of AP5Z1 in knockout cells. We discussed this point (p.15). *

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

In this study Pierga et al. report that SPG11 (spatacsin) is an ER-resident protein involved in the regulation of ER-lysosome contact sites (in particular tubular lysosomes) and subsequent faster motility of tubular lysosomes, as well in the degradation of AP5Z1 (SPG48), which forms a heterotrimeric complex with SPG15 (spastizin) and SPG11. This complex has been localized by several groups on the cytoplasmic side of LAMP-1-positive lysosomes. In addition, mutations in SPG11, SPG15, and SPG48 patients share various clinical features and were supported by biochemical/cell biological data from Spg11 and Spg15 KO mouse models and cultured cells both from patients and mice, respectively, demonstrating e.g. accumulation of autolysosome storage material, defects in the autophagic lysosome reformation process, and the loss of cortical motoneurons and Purkinje cells.

Major concerns:

i) Fig. 1, 2, 3: major disadvantage of this study is the analysis of overexpressed proteins (SPG11-V5, GFP-Sec61, and Lamp1-mCherry) which might contribute to the observed strong expression of SPG11-V5 in the ER/ER-enriched fraction. The results should be compared with the endogenous expressed proteins.

Authors response :* As stated by reviewer 1, there are no good antibodies to endogenous spatacsin, and therefore we have to rely on expression of tagged spatacsin to study its localization by immunohistochemistry. For the colocalization with the ER, we stained the latter by GFP-Sec61 that is a widely used marker for this compartment. To confirm our results, we plan to try to perform new STED imaging with REEP5 antibody to stain the ER, and Lamp1 antibody to label lysosomes, avoiding overexpression of proteins to label the subcellular compartments. Furthermore, as it is not possible to localize endogenous spatacsin by immunostaining, we addressed its localization by biochemical fractionation and western blots comparing wild-type and Spg11 knockout samples. *

For Figure 2, the data presented were indeed obtained using transfection of Lamp1-mCherry. However, we confirmed our observation of Figure 2A using alternative staining of lysosomes (Lysotracker or loading of lysosomes with Texas-Red Dextran). We therefore think that our data presented in figure 2 are valid, and that the effect we observed on tubular lysosomes was not affected by expression of Lamp1-mCherry.

In Figure 3, the lysosome were labelled with Texas-Red Dextran, and thus all the data presented in figure 3 do not rely on overexpression.

In Fig. 1C the lack of the mature Cathepsin D form which is proteolytically generated only in lysosomes from the higher molecular mass precursor is misleading and should be related to presence of lysosomal membrane proteins.

Authors response: As requested, we have performed a western blot to show the lysosomal membrane protein Lamp2 on the ER- and lysosome-enriched fractions (Figure 1B). This western blot shows that a significant proportion of Lamp2 is actually present in the ER-enriched fraction, which may be explained by the strong association of ER with late endosomes and lysosomes previously described (Friedman et al, 2013). Yet the lysosome-enriched fractions that contained no ER markers do not present spatacsin staining, suggesting that spatacsin is either in the ER or in lysosomes associated with the ER. We reformulated the text of Figure 1 according to the new included data (p 5-6). The 3-colours STED experiment that we plan to perform to answer reviewer 1 comments will help discriminate between these possibilities.

Fig. 1D: the TEM image shows only a single lysosome and proposed ER contact zones in wt-MEFs without comparison with Spg11 KO MEFs (only in the quantification). Without double immunogold labeling of SPG11 (and their lack on SPG11 KO cell lysosomes) and known ER contact-site proteins this image and the conclusion are insufficient.

Authors response : We have added an image of a lysosome taken from a knockout fibroblast (Figure 1E). As stated above there are no good antibodies to spatacsin for immunostaining, so it will not be possible to perform double immunogold labelling. This prevents us from claiming that spatacsin is a protein enriched at contact site. We therefore modulated our result section and discussion accordingly (p.5-6 and p.16).

ii) The rationale for the selection of the deleted Spg11 region D32-34 is not clear. What are the symptoms of this Spg11 knock-in mouse? A more detailed description of the phenotype is required Is the phenotype including the accumulation of LC3-positive material similar to the phenotype of the SPG11 KO mouse which has been published by Varga et al.(2015) and Branchu et al. (2017) ? If not, is the new mechanisms reported here not so important?

Author response : We have added new data (Supplementary Figure 3E-F) showing motor and cognitive impairment in mice expressing truncating spatacsin, although the motor dysfunction is slightly less marked than in Spg11 knockout animals. We also checked for accumulation of autophagy markers. We did not use LC3, but p62 that labels substrates to be degraded by autophagy. We observed accumulation of p62 in Spg11 knockout and in Spg11D32-34/D32-34 mouse neurons (Supplementary Figure 3G). These data support the functional importance of the domain encoded by exons 32 to 34 of Spg11. We commented on this in the text (p.9).

iii) p8/Fig. 3F/Suppl.Fig.3F- the most important part of the manuscript: what are the parameters of lysosomal staining in images that were used to identify genes important for lysosome tubulation by the neural network?

Authors response : For screening in Figure 3, lysosomes were stained by loading fibroblasts with Texas-Red Dextran overnight, followed by a wash of at least 4 hours. The neural network was first trained to discriminate between control and Spg11-/- fibroblasts, using any parameters of the lysosomal staining, not necessarily lysosome tubulation. This is a completely unsupervised and unbiased method, but one of its drawbacks is that we do not know which parameters were used by the network to discriminate between control and Spg11-/- fibroblasts. Therefore, we validated the classification performed by the neural network on a data set independent from the training set before using it for the screening. We rephrased the paragraph to make it clearer (p.9).

I cannot understand how the authors predict the probability of the cell to be considered as an Spg11 KO fibroblast (why not as an Spg11 D32-34 knock-in fibroblast?) as the basis for the selection of interaction candidates.

Author response : The neural network was trained on sets of images obtained from wild-type and Spg11 KO fibroblasts, which were expected to represent extreme lysosomal phenotypes linked to spatacsin function. We could therefore predict the probability of cells to be considered as Spg11 KO, not as Spg11 *D32-34 fibroblasts. We clarified this in the text (p9). *

A simple statement that the neural network approach identified those genes is too weak and requires more convincing experimental data. It has to be shown at least for the 8 positive genes in both approaches how the siRNA treatments of these genes phenocopied the lysosomal changes and of course the effect of the downregulation on the protein level of their products both in wild-type control and Spg11 D32-34 knock-in MEF. The Suppl. Fig.3F is completely unclear. How were the Y2H interaction partner validated? Did the authors use the identified 8 interaction candidates as full length bait to demonstrate the interaction with the Spg11 exons 32-34 ?

Author response : The purpose of the siRNA screen was to quickly identify putative candidates important for the regulation of lysosome dynamics. We identified 8 candidates possibly implicated in lysosomes dynamics based on the two analysis methods. We have added in Supplementary Figure 4 C-D the effect of both siRNA on lysosomal function by the two methods of analysis compared to the effect of siSPG11. However, here we aimed to identify candidates and we do not claim that every one of these eight proteins were indeed implicated in the regulation of lysosome dynamics. We corrected the text, accordingly, stating that the products of the 8 identified genes are good candidates to regulate lysosomal function (p.10). We validated the role of one of the identified candidates, UBR4, and we showed that the UBR4 siRNA indeed downregulates the protein level (Figure 4C). We only validated the interaction of spatacsin Cter with UBR4 by co-immunoprecipitation (Figure 4B).

*For the 7 remaining candidates, full characterization would indeed be required to validate their role and elucidate their mechanisms of action, but this is out of the scope of this manuscript. *

p8/Fig.3F: the genes identified in both approaches have to be listed in the Fig. 3F-Table.

Authors response : We have added in new Figure 3F the list of the 8 candidate genes that could contribute to regulate lysosome function.

The GO process- ubiquitin-dependent protein catabolic process is neither positive for the neural network nor for the directed analysis but positive for both analyses? Please explain. Similarly, the GO process proteolysis involved in cellular protein catabolic process -is not positive for the neural network analysis but again positive for both analyses.

Authors response : We agree with the reviewer that Table 3F in its older version could be a bit confusing. GO analysis is based on “enrichment” of biological processes within a list of proteins. As we did not have the same number of proteins in the 3 analyses provided in original Table 3F, we got variability in the identified biological processes. To simplify, we have therefore chosen to present only the GO analysis for the 8 candidates that were most likely implicated in lysosomal dynamics according to our two analyses of the siRNA screen which is the most relevant for our study (new Figure 3G).

For Fig. 3G the mutant ubiquitin-K0 staining in wild-type MEF cells has to be shown as well as for the Spg11 ki/KO MEFs (+ quantification of the respective data)

Authors response : As stated by Reviewer 4, the expression of lysine-null ubiquitin may impact many different cellular pathways. We therefore removed this part of the data in order to simplify the manuscript (p.10)

iv) The interpretation of the Y2H-interactome analysis by the authors is hard to follow. They searched with the exon 32-34 cDNA for binding partner, selected 3 degradative GO processes and showed by overexpression of a mutant Ub-K0 plasmid in wild-type MEFs a decreased number of tubular lysosomes, as well as their dynamics (without showing the control data in Spg11 KO or ki-MEFs). Thus, poly-ub of proteins should be in some way responsible for a lysosomal phenotype of Spg11ki MEFs.

Now they went to AP5Z1, the second binding partner of SPG11, which is reduced in its abundance upon overexpression of Spg11-GFP. I would expect to do the respective control experiment to show that in the absence of SPG11 or in the knock-in cells the amount of AP5Z1 has to increase. However, in the studies by the Huebner group by deletion of Spg11 or the other binding partner Spg15, no increase of AP5Z1 protein levels has been observed. The authors have to comment on this discrepancy.

*Authors response : We agree that this is an important point to discuss, and we failed to do it in our first version. *

*The complete knockout of spatacsin strongly modifies the levels of its partners. We previously showed that spastizin levels are decreased by >90% in Spg11 knockout (Branchu 2017). Furthermore, the levels of AP5Z1 have been shown to be decreased by ~50% in fibroblasts of SPG11 and SPG15 patients (Hirst et al, 2015). *

Our work shows that spatacsin promotes the degradation of AP5Z1 by lysosomes. It is possible that other degradation mechanism may exist, and could explain the lower levels of AP5Z1 in knockout cells. Furthermore, it was proposed that AP5Z1 stability may depend on the presence of spatacsin and spastizin (Hirst et al., 2013)*. Therefore spatacsin may contribute to tightly regulate AP5Z1 levels by contributing both to its stability, and to its degradation. We have carefully discussed this point (p.16). Furthermore, the experiments requested by reviewer 2 in point (vi) that we are planning to perform will help clarify the mechanisms of AP5Z1 degradation both in presence and absence of spatacsin. *

Then the authors found that the selected interaction partner of the exon 32-34 sequence, UBR4, does not bind to the Spg11-GFP construct lacking the domain encoded by exons 32-34 but to the C-terminal domain of Spg11-GFP. Unfortunately, all these IP-experiments were shown as cut and paste figures, preventing the direct comparison between the input and the IP protein amounts (since the information is missing what percentage of the input and the IP has been loaded per lane, the evaluation and significance of these Co-IPs are unclear).

Authors response : We have added in the Figure legend the fact that the input represents 5% of lysate added to the immunoprecipitation assays

v) p9: AP5 (Z1) is a cytoplasmic protein and can be localized on the cytoplasmic surface of lysosomes. How should the GFP-mcherry-AP5Z1 protein enter the lumen of lysosomes justifying the quenching of the GFP signal? A positive control has to be included in the experiment shown in Fig. 4E demonstrating the effect of MG132 under identical conditions of a protein substrate for proteasomal degradation.

Authors response :* We agree this is an important control. We plan to add a control showing accumulation of ubiquitin in lysates upon MG132 treatment to show it was indeed effective. *

vi) Fig. 5A: In contrast to GFP-mcherry-AP5Z1, spastizin-GFP is localized at the cytoplasmic surface of lysosomes (co-staining with LAMP1-mcherry) in wild-type MEFs. In regard to the incomplete data commented under "minor points Fig.4/Suppl.Fig.4", I suggest to perform a simple control experiment with overexpressed GFP-spastizin and mCherry-AP5Z1 in wild-type MEFs (at the best also in Spg11 KO MEF) with and without bafA treatment, which will clearly demonstrate whether single components of the trimeric Spg11, spastizin-AP5Z1 complex are degraded independently of each other in lysosomes.

*Authors response : As stated above, we will perform this control experiment, and will add the data in Figure 5 in future revision. This will help clarify the mechanism of degradation of AP5Z1 and spastizin both in presence and absence of spatacsin. Discussion of this point will also help to clarify the point iv raised by reviewer #2. *

vii) why did the authors neither mention nor discuss the described role of SPG11 in autophago-lysosome reformation (ALR)?

*Authors response : We did not discuss ALR in our first version as we did not investigate autophagic conditions. However, due to the well-described role of spatacsin in ALR, we agree that we should discuss ALR in our manuscript, and we added a paragraph (p.15). *

Minor points

• Figure 1 A, B, D, and G: ER-lysosome contact sites. The quantification of the co-localization of spatacsin-V5 with the ER marker protein GFP-Sec61b has to be given.

Authors response :* We plan to add quantification data performed on STED images showing localization of Spatacsin-GFP together with ER and lysosomal markers. This data will be added in Figure 1. *

Moreover, the authors analyzed overexpressed tagged-proteins only. The results should be compared with the endogenous proteins.

Authors response :* As stated above, there are no good antibodies to endogenous spatacsin for immunostaining. We will add new STED images with antibodies against endogenous Reep5 and Lamp1 to label the ER and lysosomes together with overexpressed spatacsin. Regarding endogenous spatacsin, we could only investigate its localization by subcellular fractionation and western blots comparing wild-type and Spg11 knockout samples. We added biochemical data suggesting that spatacsin is enriched either in the ER or in lysosome membrane associated with the ER. These data have been added in Figure 1 and in text (p.5) and we added a paragraph in discussion regarding spatacsin subcellular localization (p.15). *

p8/Figure 3: what does the 'analysis of trained neural networks' mean?

Authors response : We did not analyzed the trained neural network, but we used this trained neural network to perform image analysis. We clarified the text (p.10).

Figure 4: what happens with the other AP5 subunits?

Authors response : This is a very interesting question. We will test whether overexpression of spatacsin-GFP induces a degradation of some other AP5 subunit, provided we get specific antibody. We will add the data in Figure 4A.

Fig.4F/Suppl.Fig4: live images of GFP-mcherry-AP5Z1 + lysotracker staining have to be shown both for wild-type MEFs with and without bafilomycin A treatment(as in Fig.4F), and in Spg11 KO and Ki MEFs +/- bafA.

Authors response : We will add these data in Figure 4 (WT Mefs +/- Baf A) and in Supplementary Figure 5 (Spg11KO and SPG11D32-34 Mefs +/- Baf).

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

This manuscript highlights an interesting localization of spatacsin in the endoplasmic reticulum (ER)-lysosomes contact sites. In addition, it implicates spatacsin in regulating tubular dynamic lysosomes. Mechanistically, the authors propose that spatacsin interacts with UBR4 to promote the autophagic degradation of its binding partner AP5Z1 at the lysosomes. In turn, this would also regulate the amount of spastizin at the lysosomes, which is known to interact with anterograde motors. The authors further show that AP5Z1 interacts with p150Glued. Thus, the balance between AP5Z1 and spastizin at the lysosomes would determine lysosomal trafficking directionality.

Major Comments

1. Several crucial results of the manuscript are based on quantifications performed on immunofluorescence stainings. Data points in graphs show individual cells or individual lysosomes and the authors apply statistical tests on replicates that cannot be considered biologically independent, since they come from the same experiment or even the same cell. It is recommended to show superplots where both the individual data and the average of each independent experiment is indicated as recommended by Lord et al. (J Cell Biol 2020 219 (6): e202001064.). Statistics should be performed only on independent biological replicates.

Authors response : We agree with the comments of the reviewer regarding data presentation. We have therefore changed the presentation of all graphs of the manuscript using superplots that allow us to show all the points that were analyzed as well as the mean value for each biological replicate, and performed statistical analyses by comparing the biological replicates as proposed in Lord et al, JCB 2020 (10.1083/jcb.202001064).

The authors have used yeast two-hybrid to search for spatacsin interactors. Although in the manuscript they refer to supplementary tables that should show these interactors, the available Tables are confusing and refer to the following downregulation experiments.

Author response : We have added two supplementary data tables (Now Supplementary Tables 1 and 2) to give the list of interactors of wild-type C-terminal domain of spatacsin and spatacsinD32-34, respectively.

Supplementary Tables 3 and 4 now refer to the analysis of the downregulation experiments by respectively the neural network method and the tubular lysosome detection method.

An experiment to demonstrate that endogenous UBR4 and spatacsin interact by co-immunoprecipitation would be crucial.

Authors response : We agree with the reviewer that it would be important to test whether endogenous spatacsin and UBR4 are interacting by co-immunoprecipitation. So far we have not managed to immunoprecipitate either endogenous spatacsin or endogenous UBR4 with the antibodies we tested, which prevents us to test the interactions of endogenous proteins by co-immunoprecipitation. We are not sure we can provide this result.

Several important experiments to unravel the mechanistic role of spatacsin (Figure 4 and 5) are performed upon overexpression. This is a major limitation of the study and the authors should address it as much as possible. Western blots and immunoprecipitations are shown that appear to have been performed only once and have no quantification. As an example, in Fig 4A the difference in levels of AP5Z1 upon spatacsin overexpression or UBR4 downregulation are very minor. I would be very careful in drawing big conclusions, without additional repetitions and additional experiments in an endogenous setting.

*Authors response : We agree that a lot of our experiments used overexpression. We have now added to the manuscript new data obtained in MEFs where we downregulated spastizin or AP5Z1 (Figure 6). They confirm the role of spastizin in the regulation of lysosome dynamics. Furthermore, our new data show that levels of AP5Z1 must be tightly regulated as both overexpression and downregulation of AP5Z1 affects lysosome dynamics (p.12). We also discussed these data carefully (p.16 ). *

Furthermore, we agree that our presentation did not indicate that the western blots were repeated several times. We have now added quantifications for the western blots presented in Figures 4 and 5. Furthermore, we have also added the data showing that downregulation of UBR4 led to higher levels of AP5Z1 in control fibroblasts (Figure 4C).

The authors suggest a model by which UBR4 recruited by spatacsin is involved in autophagic degradation of AP5Z1. The data shown do not support this conclusion. First, in Figure 4A downregulation of UBR4 does not increase levels of AP5Z1 above the control in lane 1, but only when spatacsin is overexpressed. The effect of downregulation of UBR4 in wilt-type cells on AP5Z1 should be investigated. Secondly, there is no experiment directly proving that the stability of AP5Z1 depends on UBR4.

Authors response : We have added new western blots (and quantification) in Figure 4C showing that downregulation of UBR4 increased levels of AP5Z1 in control conditions. The fact that downregulation of UBR4 increased levels of AP5Z1 in control conditions suggests that UBR4 contributes to regulating the levels of AP5Z1. However, we do not show whether UBR4 directly promotes the degradation of UBR4, which has been added in the discussion (p15). To test whether UBR4 affects the stability of AP5Z1, we will monitor whether downregulation of UBR4 by siRNA increases the half-life of AP5Z1. These data will be added on Figure 4.

The authors suggest that the interaction of spatacsin with spastizin or AP5Z1 are in competition. This is an interesting hypothesis, however to conclusively demonstrate this, pull-down experiments in KO cells and not upon extreme overexpression should be performed.

Authors response : We agree that testing the interaction of spatacsin with its partners in SPG15 KO or AP5Z1 KO fibroblasts would be a very good control of our hypothesis. However, we previously showed that the levels of AP5Z1 are lower in SPG15 KO than in control fibroblasts (Hirst et al, 2015), which introduces a bias in the analysis. We therefore plan to concentrate on AP5Z1 fibroblasts and investigate whether interaction of spatacsin with spastizin is modified in these cells. An alternative would be to monitor the effect of siRNA downregulating AP5Z1 on the interaction between spatacsin and spastizin. We will add these data in Figure 5.

Minor comments

1. In figure 1G and 1H the overlapping area between lysosomes and ER is quantified. Considering that the ER occupies a large portion of the field a 90{degree sign} flipped control for both WT and KO would be important to sort out random colocalization. In this direction, it would be also essential to show that the total amount of lysosomes is not different in WT and KO, especially because in figure 1A the lysosomes in WT and KO seem to be different not just in shape but also in number and size. A different number or size of lysosomes affects this analysis.

Authors response :* We added quantifications in Supplementary Figure 1F showing that 90° flipped controls are indeed not capturing the same proportion of contacts between the ER and lysosomes. We also added quantifications in Supplementary Figure 1D-E showing that the average size of lysosomes and the number of lysosomes per unit area are similar in control and Spg11 KO fibroblasts and mentioned it in the text (p.6). If the lysosomal staining appears different in Spg11 KO fibroblasts it is because lysosomes are clustered around the nucleus, an observation that we reported previously (Boutry et al, 2019). *

In the second chapter of the Results, the authors state: "we observed by live imaging a higher number of lysosomes with tubular shape in Spg11+/+ compared to Spg11-/- cells", however the number of elongated lysosomes is quantified per area. Why the number of elongated lysosomes is not quantified over the total amount of lysosomes?

Authors response : The point raised by the reviewer is a fair point. The purpose of our analysis was to compare the number of lysosomes with tubular shape in control and Spg11 KO cells. As the number of lysosomes per unit area is invariant between control and Spg11 KO cells as shown in new data included in Supplementary Figure 1D, normalization to total number of lysosomes or to cell surface reflects the same difference in phenotype.

The In the fourth chapter of the Results, the authors state:" In wild-type MEFs, mCherry was colocalized with lysosomes. In contrast, GFP that is sensitive to pH was poorly colocalized with lysosomes, suggesting that AP5Z1 was mainly inside the acidic subcellular compartment (Figure 4F)." If the aim of the authors is to shown that AP5Z1 is mainly into the lysosome, the amount AP5Z1-mcherry inside and outside the lysosome need to be compared, with a proper statistical analysis. There is also a lot of GFP signal in the cytosol. Why is that?

*Authors response : We agree with the reviewer, we will add quantification of the proportion of AP5Z1-mCherry inside lysosomes on Supplementary Figure 5. *

Regarding the GFP-AP5Z1 signal in the cytosol, AP5Z1 has no transmembrane domain and may thus exist as a cytosolic protein. Since GFP is quenched in the acidic environment of lysosomes, the GFP fluorescence of the mCherry-GFP-AP5Z1 protein is outside lysosomes, and it appears partly cytosolic. Of note, there is also some cytosolic mCherry signal that is less visible due to the high level of mCherry fluorescence in lysosomes. We will clarify this point with the quantification of the proportion of mCherry signal compared to GFP inside the lysosomes and add it in Figure 4.

construct used in the paper is a C-terminal tagged version of spatacsin. The authors should consider to test an N-terminal tagged construct at least for the localization experiments.

Authors response : We added an immunostaining image of Spatacsin with an N-terminal tag (Supplementary Figure 1B) and mentioned it in the text (p.6). As spatacsin with a C-terminal tag, it presents a diffuse distribution that poorly co-localizes with lysosomes.

Figure 5C: a negative control and the quantification are missing.

Authors response : A non-transfected cell is present on Figure 5C, visible thanks to the Lamp1 immunostaining, and that we considered as a negative control. In this non-transfected cell, we detected no PLA signal. We added an asterisk to point the non-transfected cell on Figure 5C. Quantification will also be added in the revised version after we have performed the PLA experiment required by Reviewer 1.

Reviewer #3 (Significance (Required)):

Since spatacsin, AP5Z1 and spastizin are all implicated in hereditary spastic paraplegia, the data are of potential interest not only for basic cell biology, but also to understand the pathogenesis of the disease. In addition, the manuscript proposes a novel model regulating trafficking of dynamic lysosomes.

Reviewer #4 (Evidence, reproducibility and clarity (Required)):

Pierga et al. reveal subtle differences in lysosome morphology, ER-contact, and trafficking in the absence of Spatascin. These data are replicated with a truncated Spatascin, presumably a loss of function. Two-hybrid screening of the deleted sequence from this truncation for interactors and then asked whether these hits could phenocopy the lysosome morphology changes. This led to an assertion for a role for ubiquitination in these effects. Rather than these hits the group then investigates previously known Spatascin interactors and reports similar complex but subtle abnormalities via overexpression or knockdown of these. While data show overlapping phenotypes by modulation Spatascin, AP5z1, and Spastizin, the manuscript is confusing, leaps from experiment to experiment, and does not provide novel rigorous mechanisitic insight. It conflates all the discrete lysosomes aspects into a collective to link them. The title is over-stated and not appropriate for the experiments.

The localization of endogenous Spatascin is lacking - over-expression is prone to artifact and the punctate data on the V5 suggests much more work is needed to understand where in the cell it is. It would seem much more work is needed here.

Authors response : As stated by reviewer 1, there are no good antibody to endogenous spatacsin, and therefore we have to rely on expression of tagged spatacsin to study its localization by immunofluorescence. When performing the images, we avoided the cells with the highest ovexpression of tagged spatacsin. Yet, we agree that this is still overexpression. That’s why we included subcellular fractionation data where we can detect endogenous spatacsin (Figure 1A-1B). These data confirmed that spatacsin is enriched in the ER or in lysosome fraction tightly associated with the ER.

Furthermore, the EM data (1E) would suggest the far majority of lysosomes are in contact with ER - these seems uncharacteristic.

Authors response : The EM data in figure 1E indeed shows that the majority of lysosomes are in contact with the ER, as previously shown by other groups (Friedman et al, 2013, Höglinger et al, 2019).

The phenotypes analyzed are very subtle, and while statistically significant the biological impact is unclear - in many cases individual lysosomes (or lysosome-ER contacts) are considered as an 'n'. While these results are probed across multiple independent experiments the batch effects and how uniform per cell the events are is unclear.

Authors response : We agree with the comments of the reviewer regarding data presentation. ‘n’ represented individual cells, but did not actually take into account the variability across experiments. We have therefore changed the presentation of all graphs of the manuscript using superplots that allow us to show all the points that were analyzed as well as the mean value for each biological replicate, and performed statistical analyses by comparing the biological replicates as proposed in Lord et al, JCB 2020 (10.1083/jcb.202001064).

In fig 2H critical data are missing - the effect of Spatascin KO on the transition between these morphologies should be considered as in G. Otherwise the relevance is unclear.

Authors response : We have added this quantification on Figure 2I. It shows that transition of morphology of lysosomes from round to tubular in Spg11 KO cells is still associated with a change of speed, although the average speed attained is halved compared to conditions where spatacsin is present. This shows that loss of spatacsin does not abolish morphological transition of lysosomes but limit their speed in the tubular shape. We commented on this new data in the text (p.8).

The impact of over-expressing a lysine-null Ub ( Fig 3) is far too crude and non-specific to have meaning here. It is assumed that the only proteins affected are those of interest. This is consistent with much of the paper where "true-true-and unrelated" is more likely than the presumption of causality.

Authors response : It is true that the expression of lysine-null ubiquitin is really crude and may impact many different cellular pathways. Furthermore, the results obtained with the lysine-null ubiquitin do not contribute to the rest of the paper. We therefore removed the original Fig3G, H, I and Fig 4B and updated the text accordingly (p.10).

The blots in Fig4 are a relatively poor quality and not quantified over repetition.

*Authors response :Spatacsin and spastizin are large proteins, and there is not much choice for antibodies able to detect these proteins. Yet we have validated their specificity by western blot using knockout cells (spatacsin) (Supplementary Figure 4 A-B) or siRNA (spastizin) (Supplementary Figure 7B). We agree that our presentation did not indicate that the western blots were repeated several times. We have added quantifications for the western blots present in Figures 4 and 5. We also changed some illustrative western blots to improve quality. *

Controls are missing and Fig5 suffers from a reliance on over-expression - there is a massive over-expression of AP5Z1 which may be affected the stoichiometry of these overall interactions, but with an n=1 its hard to know and its not clear what these data add. Again, while statistically significant (5E and F) due to the nature of data analysis (every lysosome=n of 1) it is not clear how biologically significant UBR4 siRNA or AP5Z1 over-expression is - as the accumulation of AP5Z1 in these two conditions is orders of magnitude apart - again likely unrelated.

Authors response : We added quantification for this western blot (Supplementary Figure 6A).

*As stated above we have changed the representation of the graphs. Each point represents one cell, and we included the mean value for each biological replicate. *

Preventing degradation of AP5Z1 by UBR4 siRNA or overexpression of AP5Z1 do not indeed have the same effect on total AP5Z1 but do have a similar effect on the interaction of spatacsin with its partners evaluated by co-immunoprecipitation, as illustrated by the quantifications that we have added. We clarified this in the text (p.12). As requested by reviewer 3, we will also investigate the effect of AP5Z1 knockout or downregulation on the interaction between spatacsin and spastizin assessed by co-immunoprecipitation. These data will be added in Figure 5 and will strengthen our conclusions.

Fig 6 begins to conflate the fact that different lysosome morphologies appear to have different trafficking properties even in WT cells and that many of these targets affect morphology - therefore to conclude a direct effect on trafficking seems inappropriate.

Authors response : In original Figure 6, we showed that Kif13A-ST and p150CC1 changed the proportion of tubular lysosomes (previous Figure 6 and H), and the data showing that these constructs changed the trafficking of lysosomes were presented in Supplementary Figure 5 B-C. We have now moved the data showing the effect of Kif13A-ST and p150CC1 in the main Figure (Figure 6F and 6I) to facilitate the interpretation of the data. Therefore, expression of Kif13A-ST and p150CC1 do not only affect the morphology of lysosomes, but also impaired their trafficking. We thus do not extrapolate lysosome dynamics from their morphology, we actually quantify lysosome dynamics.

Fig 7 extends this into polar cells (neurons) but still it is not clear whether form (morphology) dictates function (likelihood of trafficking or directionality.

Authors response : We did not only analyzed neurons because they are polarized cells, but because neurons are the main cells affected by neurodegeneration observed in absence of spatacsin (Branchu et al, 2017). We added new data on Figure 7 showing that tubular lysosomes in axons are actually more dynamic than round lysosomes, as observed in fibroblasts. We added these data in Figure 7 and text (p.13).

Investigation of lysosome trafficking in axons also allowed us to investigate the directionality of movement, which is difficult in MEFs. We clarified this point in the text (p.13).

In sum, there is a lot of data that collectively points to a partial localization of Spatascin at Er-lysosome contacts and an influence on morphology and trafficking of lysosomes in the cell, but at the end of the day very new mechanism is brought to light.

Authors response : The mechanisms regulating trafficking of lysosomes are far from being fully resolved. Our manuscript shows that spatacsin contributes to this regulation by modulating the degradation of AP5Z1. This in turn regulate the lysosomal association of AP5Z1 and spastizin that interact with motor proteins to control lysosomal dynamics.

Reviewer #4 (Significance (Required)):

This manuscript is directed to the basic cell biology community - involving ER, lysosome, and microtubule dependent trafficking. There are some new analytical tools employed and many co-factors and binding partners of Spatascin considered but frankly too many to adequately and rigorously control for. Because of this the manuscript is very unfocused, hard to follow and makes too many assumptions about shared dynamics ? necessarily arising from shared morphology - lysosomes are highly dynamic and can be affected by virtually any change in intracellular trafficking or protein/membrane transport. This is not appropriately considered.

Authors response : We have clarified our manuscript to show that dynamics is not necessarily arising from a tubular morphology. It turns out that lysosomes with a tubular morphology indeed are more dynamic that lysosomes with a round morphology. Importantly, in all our experiments dealing with lysosomal dynamics, we have actually included a quantification of lysosome dynamics using time lapse imaging as detailed in methods (p.21).

digital bearer asset means a token (or luggage tag?)

Predatory inclusion is a form of rent-seeking in which one preys on customers using monopoly power to extract excessive value for small add-on services.

So, does this mean that hyperlinks influence the PageRank? If you were to tag a website multiple times, it's PageRank index will significantly increase?

It's from the first project "Fluffy Tag". In this essay I wrote a story about my chilhood and how this memory was recalled. I had a dream to my grandma sewing my worn pillowcase, which reminds me of her throwing away my favorite pillowcase with my special smell on its tag when years ago. But I woke up that morning holding the tag on my comforter and caught a trace of the familiar smell, and I finally found my unique smell back.

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

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Referee #2

Evidence, reproducibility and clarity

In this manuscript by Rodriguez-Real et al, the authors address the contribution of the centrosome to cellular process unrelated to organizing the microtubule cytoskeleton, namely DNA repair. As many proteins contributing to the DNA damage response physically associate with centrosomes, this appears a relevant question that has been neglected so far and led to a number of studies that appeared controversial. To do so, the authors exploit a variety of tissue culture models that are well established in the fields of centrosomes and DNA repair, including U2OS and RPE1 cells, exposed to perturbations promoting DNA damage (such as ionizing radiation or pharmacologic perturbation of DNA stability) in conjunction with siRNA mediated depletion of candidate centrosomal proteins., followed by the visualization of repair events either using fluorescent reporters, or visualizing endogenous repair foci by immunofluorescence. On this basis, the authors propose that a discrete centrosomal sub-structure, namely sub-distal appendages and the CEP170 protein therein concur to promote a particular nuclear DNA repair process, namely homologous recombination.

The manuscript suffers of two main limitation:

1. the authors provide no mechanistic understanding of how CEP170, a protein that resides at centriolar subdistal appendages and shows no nuclear translocation upon DNA damage, concurs to regulate processes in the nucleus. The fact that all reported phenomena appear to be independent of microtubules suggests that neither the LINC complex nor the precise position of the centrosome in the vicinity of nuclear pore complexes contribute to the reported phenomena.
2. some of the experimental perturbations performed in the manuscript might elicit the reported phenotypes due to spurious effects on cellular processes that have not been considered with sufficient caution.

Given that uncovering the mechanism underlying the contribution of CEP170 to homologous recombination might prove very demanding, my comments will focus primarily on the second point.

Major comments:

The centriolar depletion using centrinone is known to impinge on cell proliferation in p53 WT cells. Thus, I am not convinced that the data shown in Figure S1B and S1C will sufficiently document that the observed unbalance between HDR and NHEJ are not simply reflecting a different cell cycling speed/behavior. Moreover, it would be important to address whether centrinone or depletion of CEP170 (an essential gene, according to the authors!) will trigger DNA damage by themselves. In fact, even a small extent of chronic genotoxic stress caused by the perturbations used in the manuscript might explain the reported differential proficiency of HDR.

Minor comments:

It is a pity that CEP170 is not amenable to functional dissection using a complete knockout. The fact that in PMID: 27818179 a complete knockout of CEP128 has been achieved, suggests however that subdistal appendage mediated DNA repair is not the essential process in itself. As the authors employ other cell lines stemming from the same laboratory, they could consider acquiring CEP128 KO to complement their own experiments.

The proposal that CEP170 phosphorylation of by ATM/ATR upon DNA damage might require SDA localization of the protein is plausible, yet not circumstantiated by any experimental evidence. If the authors could monitor the phosphorylation of the endogenous CEP170 protein in WT vs CEP128 KO cells (phosphor-specific antibody, MS-based proteomics or simply "phos-tag" gels), this could provide a first spark towards a mechanistic understanding of the reported phenomenon.

The entire Figure 4 is based on quantifications of clonogenic potential.

1. it would be helpful if the data were accompanied by images displaying representative crystal violet stained dishes.
2. clonogenic potential potential is discussed as a mere readout of cell survival, yet a combination between survival and proliferation concur to the reported differential clonogenic potential

Odf2 contribution to both DAs and SDAs: while Odf2 has been initially proposed to be necessary for the assembly of both types of appendages, its contribution to distal appendages has been disputed by Tanos et al using siRNA (PMID: 23348840), also confirmed by our group using CRISPR (unpublished). Thus, the role of Odf2 in SDA assembly appears more crucial than for DA assembly.

CEP164 contribution to ATM/ATR activation: this has been disputed in this paper by the Morrison lab (PMID: 26966185). Thus, a cautionary note should be mentioned when referring to this concept.

Significance

Taken together, this manuscript addresses the contribution of the centrosome to DNA repair. This is in itself a very interesting topic with the potential to attract the interest of both cell/molecular biologists as well as cancer researchers. The major advance strength is represented by pinpointing a specific centriolar substructure, namely subdistal appendages, in the control of HDR. CEP170 had been previously shown to be target of phosphorylation by ATM/R and the present study highlights that the abovementioned phosphorylation is not a mere passenger event during DNA repair, but that potentially reflects a decisive event informing the repair pathway of choice. However, several experiments have alternative explanations/interpretations and no understanding of the underlying mechanism is provided.

The expertise of this reviewer is the study of cell cycle regulation and on the centrosome structure/function.

Mastodon has RSS feeds available for tags!

I'm enamored of this idea as well and this is a fascinating example.

It seems similar to the related (and also difficult-to-name) concept which I've called combinatorial creativity. One of the earliest versions I've seen is that of Raymond Llullus' work with respect to combinatorial mnemonics described in Frances Yates' The Art of Memory (1966). Farnam Street's post is a good start https://fs.blog/networked-knowledge-and-combinatorial-creativity/, but I've been collecting other examples: https://hypothes.is/users/chrisaldrich?q=tag%3A%22combinatorial+creativity%22 and other names for it over time.

I can't help but wonder what Ericsson's role of deliberate practice would look like with arts as the subject? What motivates long term deliberate practice?

Yates, Frances A. The Art of Memory. 1966. Reprint, Chicago, IL: University of Chicago Press, 2001. https://www.amazon.com/Art-Memory-Frances-Yates/dp/0226950018.

Ericsson, K. Anders, Ralf Th. Krampe, and Clemens Tesch-Romer. The Role of Deliberate Practice in the Acquisition of Expert Performance. Psychological Review, 1993.

add the mailto: tag and add a fullstop

"In case you want a white logo, contact us."(hyperlink contact us)

A protein that is popularly used as a tag for the purification of recombinant proteins. It can be fused to either ends of the desired protein, usually the end that does not affect the function of the target protein.

A recombinant protein is produced by cloning a gene into a system that allows the expression of that gene and the translation of its gene product.

BIOmastodonte

Authors' response (28 November 2022)

GENERAL ASSESSMENT

This interesting preprint by Suárez-Delgado et al. explores the mechanism by which activation of the Hv1 voltage-activated proton channel is dependent upon both the voltage and pH difference across the membrane. The authors are the first to incorporate the fluorescent unnatural amino acid, Anap, into the extracellular regions of the S4 helix of human Hv1 to monitor transitions of S4 upon changes in voltage or pH. The authors first checked that Anap is pH insensitive for practical use in Hv1, where changes in local pH are known to occur when the voltage sensor activates and the proton pore opens. Anap was incorporated at positions throughout the S3-S4 linker and the extracellular end of S4 (up to the 202nd residue) of hHv1 and some positions showed clear voltage-dependent changes in fluorescence intensity. The authors also obtained fluorescence spectra at different voltages and observed no spectral shifts, raising the possibility that voltage dependent changes in fluorescence intensity could primarily be due to fluorescence quenching. Upon mutation of F150, the Anap signal at the resting membrane voltage increased, suggesting dequenching upon removal of F150. The authors also discovered that the kinetics of Anap fluorescence upon membrane repolarization have two phases (rapid and slow) under certain pH conditions and that there is a pH-dependent negative shift of the conductance-voltage (G-V) relation compared with the fluorescence-voltage (F-V) relation in some mutants. The biphasic kinetics of the fluorescence decay upon repolarization were explained by modelling a slower transition of return from intermediate resting state to a resting state. The pH-dependent shift of the G-V relation from the F-V relation provides insight into mechanisms of ΔpH-dependent gating of Hv1, a longstanding enigma. Overall, the approaches are rigorous, the figures show important results, and this work paves the way for the use of Anap fluorescence to study Hv1 gating and modulation.

We thank the reviewers for the careful reading and assessment of our manuscript and for the constructive criticism. We have tried to respond to all the essential revisions, both by rewriting sections and performing some experiments or new analysis. Below we respond one by one to all the points raised. Please also note that we have added an author to the manuscript, who has carried out new experiments included in this revised version of the preprint.

RECOMMENDATIONS

Revisions essential for endorsement:

1) In its current form, the narrative of the preprint has two threads. One on the mechanisms of Anap fluorescence changes (mainly quenching) and another on a previously unappreciated transition of the voltage sensor, as revealed by Anap. Our impression is that the preprint suffers somewhat from this split focus, which could be resolved by explaining why Anap was used to explore voltage sensor activation in Hv1 in the introduction. Perhaps the authors could also explain the advantage of smaller sized fluorophores compared to other maleimide-based fluorophores earlier in the introduction, or the utility of being able to insert Anap into transmembrane segments. The authors should more clearly point out how they exploited the advantages of Anap as a tool in this study. It would furthermore be helpful to discuss previous studies using nongenetic tools for VCF and spell out how they have delineated key aspects of Hv1, which would help to emphasize how several positions studied here (for example, 201 and 202) could not be labelled with cysteine-based fluorophores.

We think that this is a very useful suggestion and we have expanded the introduction to more pointedly indicate the contributions of previous voltage-clamp fluorometry experiments in Hv1 channels and to clearly explain why we chose to pursue the use of a genetically-encoded small fluorophore such as Anap.

2) We think the authors should be cautious about understanding the physicochemical nature of Anap using prodan as a model. It would be helpful to discuss the possibility that undetected spectral shifts due to a nonquenching mechanism could be overlooked, even though major signal changes can be explained by fluorescence quenching in their data. Regarding the mechanisms of remaining voltage-dependent fluorescence changes of F150A-A197Anap, it would be helpful for the authors to suggest possible ideas about which residues might account for remaining signals.

The beautiful spectral data for Anap is impressive. However, the physicochemical basis of the fluorescence change of Anap cannot be understood by simple extension of findings for prodan, which shows structural similarity to Anap. Our understanding is that changes in Anap fluorescence can only reveal a change in the structural relationship between Anap and one of its neighbors because the physicochemical basis of Anap fluorescence is complicated. For example, fluorescence could also be affected by the electrostatic environment, stretch of peptide bond, etc. Previous studies, including those of TRP channels, showed that the kind of environmental changes that Anap faces in ion channels do not necessarily induce large spectral shifts, unlike in cell-free spectral analyses using distinct solvents. Further, only minor shifts in spectra occur upon local structural change, as seen in previous work including Xu et al. Nat. Commun. 2020 11:3790. Such minor shifts could be perhaps overlooked even when Anap is incorporated into S4 and exposed to environmental change. Therefore, it is not easy to decode the physicochemical basis of Anap fluorescence changes. F150A-A197Anap has increased fluorescence and no change in spectral pattern, leading the authors to conclude that F150 quenches Anap fluorescence of A197 position. However, a significant amount of fluorescence change still occurs upon changes in membrane potential after F150 is changed to alanine (Figure 4). It is very likely that quenching is not the only mechanism underlying the observed voltage induced change of Anap fluorescence of Hv1. The authors suggest that remaining voltage-dependent fluorescence change of F150A-A197Anap could be due to interaction with other aromatic residues, but this has not been tested.

Thank you for pointing out our oversimplified discussion of the mechanisms of Anap fluorescence changes in Hv1 channels. We have taken into account your comments and present a more nuanced and toned-down discussion of the possible mechanisms at play in our experimental system.

3) The current version of the preprint is missing important control experiments, ideally performed using western blots to measure protein expression or, if that is not possible, proton current and fluorescence measurements, to demonstrate that protein expression or functional channels are not seen for all mutants in the absence of ANAP (but in the presence of the tRNA and Rs construct). A similar control for imaging would be to use ANAP alone without encoding.

We thank the reviewers for this recommendation. We show that the number of cells showing mCherry fluorescence is greatly diminished in the absence of L-Anap, but in the presence of the tRNA and synthetase. As suggested, we have included results of control experiments in which we attempted to record currents from cells expressing the constructs: F150A-A197tag, Q191tag, A197tag and L201tag co-expressed with the tRNA and synthetase-coding plasmid (pANAP) and in the absence of L-Anap. We struggled to find red fluorescing cells and recorded currents from a relatively small number of these cells, most of which was leak current. We now include these data in Figure 1-Supplement 1B. These control experiments show that there is very little leakage of expression of channels that did not incorporate Anap.

4) Aromatics in the S4 segment were ruled out as potential quenchers on the assumption that they would move together with Anap during gating. It should be noted, however, that Hv1 is a dimer and therefore a fluorophore attached to S4 in one subunit could be quenched by S4 aromatics in the neighboring subunit if were close to the dimer interface. In Fujiwara et al. J. Gen. Physiol. 2014 143:377-386, for example, W207 does not appear very far from labeled positions in the adjacent S4. This possibility should be mentioned in the discussion.

We appreciate the reviewers' concern regarding the role of other aromatic residues near Anap incorporation sites, especially the ones close to the subunit interface given that Hv1 is a dimer. We now mention the possibility that other residues could be quenching groups, especially given the fact that some quenching remains in the double mutant F150A-A197Anap (line 272 in results and line 432 in discussion). We have also included a new analysis of the ratio of Anap/mCherry fluorescence (at resting membrane potential) for all insertion sites. This shows a decreased ratio as Anap gets inserted in residues closer to the c-terminus of S4, which is evidence of a quenching group located near the center of the transmembrane domains (Figure 4-Supplement 1).

5) It is not clear whether the Anap spectra purely represent Hv1 incorporated into the plasma membrane or perhaps include signals from the cytoplasm or channels in internal membranes (whether assembled or incompletely assembled). It would be helpful to provide a more complete presentation of the data obtained and to provide more information in the Methods Section. In the Methods section, it is stated "The spectra of both fluorophores (Anap and mCherry) were recorded by measuring line scans of the spectral image of the cell membrane, and the background fluorescence from a region of the image without cells was subtracted". How are signals from cell membranes specified in this method being discriminated from those associated with the cytoplasm and intracellular membranes? If spectral data include signals from free Anap in the cytoplasm or Hv1 in intracellular membranes, spectral shifts upon membrane potential changes will be difficult to detect, even when Anap is incorporated into Hv1 and senses environmental change by voltage-induced conformational change. In Figure 3E, wavelength spectra were shown as standardized signals for different voltages. Amplitude change would be demonstrated (spectrum at different voltages without standardization should be shown).

We appreciate the concern related to the origin of the fluorescence signals and we have improved both the presentation and the associated figures. Since this is also a concern for the experiments that determined the pH-dependence of Anap incorporated at position Q191, we have included a figure supplement 1 to Figure 2 in which we explain how the membrane was visualized. We use mCherry fluoresce as an indication of plasma membrane-associated channels, since its red fluorescence is easier to detect in the membrane than Anap fluorescence (even though cytoplasm dialysis in whole-cell should diminish the amount of free Anap, it is difficult to distinguish Anap fluorescence in the membrane by itself). Once the membrane associated mCherry fluorescence is detected, the measurement of the spectrum from a very small membrane area is insured because the spectrograph slit delimits light collection to a very small vertical area and the horizontal line scan further limits light measurement. These procedures are now made explicit in methods section and supplementary figure mentioned before. Moreover, we explain that they were also followed in experiments where the cell was under voltage-clamp. The spectral data in Figure 3E is now presented without normalization to show the voltage-dependent change in amplitude without changes in peak emission wavelength.

In Figure 4, spectra were compared between A197Anap and F150A-A197Anap, showing increases of fluorescence in F150A-A197Anap. Was this signal measured at resting membrane potential? How does the spectrum change when the membrane potential is changed?

As in the experiments of figure 1E, the spectra were obtained in non-patched cells. Thus, the signal was measured at the HEK cell resting potential (~ -30 mV) and a ΔpH ≈ 0.2. We have now incorporated that information in the methods section and the figure description. On the other hand, we did not perform experiments measuring the double mutant spectra at different voltage steps, so we cannot respond to the second question.

Rationales for the confirmation of signals originating from the cell surface for Hv1 Anap might include the observations that: a) some mutants showed slightly different spectral patterns (in particular, Q191Anap showed a small hump at longer wavelengths, which is proposed to represent FRET between mCherry and Anap) and b) signal intensity was voltage dependent (if signals originate from endomembranes, they should not be voltage dependent). Mentioning these two points earlier in the text might help to alleviate concerns about the location of the protein that contributes to the measured signals.

These are great suggestions and we have incorporated them to the text (lines 156, 190 and 216 Results section), along with a better explanation of procedures followed to measure mostly membrane-associated fluorescence (see new Figure 2-Supplement 1).

6) In Fig 5, the fluorescence kinetics do not really match the current activation kinetics for panels A, B, and C. Is there an explanation for this mismatch? It would be helpful to have the fitted data in the figure. A more thorough comparison of the kinetics of currents and fluorescence would be helpful throughout the study.

We believe that the kinetics of fluorescence and current does not match because the current activation rate is overestimated due to a small amount of proton depletion present in recordings from large currents. This is an unavoidable problem in proton current recordings, even with the high concentration of proton buffer used in our experiments and the long time-intervals between each voltage pulse. For this reason, we did not undertake a systematic exploration of kinetics. Nonetheless, the current and fluorescence rates are very close and have the same voltage dependence, indicating a close correlation between voltage-sensor movement and current activation. We now explain this limitation in the manuscript text (line 223 and 327, results section).

7) Which construct of hHv1 was used to obtain the data in Figure 6? Unless we missed it, this information is not provided in the text or figure legend. Is it for L201Anap? This figure also shows an intriguing finding that the G-V relationship is negatively shifted from the F-V relationship at pHo7-pHi7 but not at pHo5.5-pHi5.5. A shifted G-V relation with the same ΔpH contrasts with what has been reported in other papers. However, the authors did not really discuss this surprising finding in the light of previous references. Could the shift of the G-V relation between two pH conditions with the same ΔpH be due to any position-specific effect of Anap? If Figure 6 represents L201Anap mutant, the presence of Anap at L201 probably makes such shift of G-V curve in Figure 6C? The authors should openly discuss this finding in relation to what has been reported in the literature.

Yes, construct L201Anap was used in Figure 6. This is stated now in the figure legend and in the corresponding main text. We agree that the leftward shift of the GV with respect to the FV in pHi7-pHo7 is an intriguing finding, suggesting that coupling between S4 movement and proton permeation can be regulated by the absolute value of the pH. We discuss this in the results section. The DeCoursey group has shown evidence in W207 mutants of hHv1 that the absolute value of pH can modulate the voltage dependence of the conductance. Although we had mentioned these results, we now mention them more prominently and also discuss the possibility that this might be a unique feature of introducing Anap at L201.

8) The authors suggest that the small hump near 600 nm in Figure 1E represents FRET between Anap and mCherry. It is surprising that FRET can take place across the membrane. Can the authors point to another case of FRET taking place across a cell membrane? One possibility might be that misfolded proteins place mCherry and Anap close to each other. It is also curious that only A191Anap did not show such a FRET-like signal. Also, if there is FRET, why wouldn't this also contribute to the voltage-dependent changes in fluorescence?

We thank the reviewers for bringing up this point. Based on published data, we assumed that mCherry could not be excited by 405 nm radiation, thus our conclusion that the observed emission near 604 nm is FRET between Anap and mCherry. We have now measured the excitation of the Hv1-mCherry construct and observe that the 405 nm laser is capable of exciting mCherry and produced ~2 % emission (as compared to 514 nm excitation), which is almost the same as that observed for the Hv1Anap-mCherry channels. We now conclude that the second hump in the emission spectrum near 600 nm is due to direct excitation of mCherry.

On the other hand, FRET across the membrane has been demonstrated for the membrane-bound hydrophobic anion dipicrylamine and membrane-anchored GFP (Chanda, et al. A hybrid approach to measuring electrical activity in genetically specified neurons. Nature neuroscience, 2005, vol. 8, no 11, p. 1619-1626.) and dipicrylamine and GFP in the c-terminus of CNG channels (Taraska & Zagotta, Structural dynamics in the gating ring of cyclic nucleotide–gated ion channels. Nature structural & molecular biology, 2007, vol. 14, no 9, p. 854). Finally, single-molecule FRET between dyes placed extracellularly and intracellularly in Hv1 channels has been demonstrated (Han et al. eLife 2022;11:e73093. DOI: https:// doi. org/ 10. 7554/ eLife. 73093).

A191Anap shows the hump at ~600 nm, but we think it's less evident because Anap at 191 is less quenched (see Figure 4-Supplement 1 and answer to point 4 above).

9) F150A-A197Anap shows a leftward shift of the F-V relation compared with the G-V relation only when ΔpH=1. Another unusual finding with F150A-A197Anap is the very small shift of the G-V relation between ΔpH=0 and ΔpH=1, when other reports in the literature suggest it should be 40 mV or more. Are these peculiar properties simply due to the absence of Phe at position 150, which might play a critical role in gating as one of the hydrophobic plugs of Hv1? To address this possibility, it would be ideal to compare different ΔpH values with and without F150 when Anap is incorporated at a different position (such as L201Anap). Regardless, it would be helpful to discuss this point.

We now discuss these changes in the discussion (lines 440-446).

10) In Figure 1E, I202Anap exhibits a blue shift in its spectrum suggesting the environment of Anap on I202 is more hydrophobic than the other sites. We presume these spectra were obtained at a negative membrane voltage, but the text or legend should clearly state how these were obtained. The authors should also explain whether the whole cell or edge was imaged. If these are at negative membrane voltages, might the Anap spectrum shift to higher wavelengths (i.e. more hydrophilic) when the membrane is depolarized? Did the authors find any spectral shift for I202Anap when doing a similar test as depicted in Figure 3E?

Yes, the spectrum of I202Anap was obtained at the resting potential (~ -30 mV), as were all spectra in Figure 1E. We now indicate this clearly in the methods section and in the figure legend. Fluorescence was measured from the membrane region as indicated by mCherry fluorescence and as illustrated in Figure 2-Supplement 1. We did not explore this mutant further and we cannot answer the question of whether a depolarizing potential might produce a red shift of the spectrum.

11) In Figure 3E, spectra are shown as normalized signals for different voltages, but an amplitude change should also be demonstrated by providing raw spectra at different voltages.

We have changed figure 3E to show non-normalized data that now show the increase in fluorescence intensity and no wavelength shift in the fluorescence spectrum of Anap (see also response to point 5).

12) In Figure 4, spectra are compared between A197Anap and F150A-A197Anap, showing increase of fluorescence in F150A-A197Anap. Were these obtained at a negative membrane voltage? How do these spectra change when membrane potential is changed?

See response to point 4 of "Revisions essential for endorsement" section.

Additional suggestions for the authors to consider:

1) The authors propose that Anap fluorescence tracks an S4 movement involved in the opening of the channel. They also argue that the existence of more than one open state could explain why the increase in florescence upon depolarization lags the proton current in most cases. While they convincingly show that Anap is not pH sensitive per se, when incorporated into the protein, the fluorescence efficiency of the fluorophore could still be affected by protonation of channel residues in the immediate environment when the channel opens, even after S4 has completed its movement. To address this alternative explanation, the authors could use Hv1 mutants with strongly reduced proton conductance. Channels bearing mutations corresponding to N214R or D112N were used successfully to isolate Hv1 gating currents from the much larger proton currents (De La Rosa & Ramsey, Biophys. J. 2018 114:2844-2854; Carmona et al. PNAS 2018 115:9240-9245; Carmona et al. PNAS 2021 118: e2025556118). Perhaps, they could be used with patch clamp fluorometry as well?

This is an interesting suggestion that could be explored in a follow up study.

2) The data showing that Hv1-197Anap is quenched by Phe at position 150 are very nice. Yet, it would be useful to show that the quenching is specific to F150 using a negative control. F149, for instance, is just next to F150 but points in a different direction, so its mutation to alanine should not affect Hv1-197Anap fluorescence.

This is an interesting suggestion, but, as suggested by reviewers, we think there is a possibility that other aromatic residues could contribute to quenching. Given the absence of a reliable structure for Hv1, prediction of the relative positions of any resides is very difficult and thus we did not attempt the suggested experiment.

3) A major finding of this work is the identification of a slow kinetic component that is highly sensitive to ΔpH. Earlier studies found that the ability of Hv1 to sense ΔpH is altered by some channel modifications, e.g., in the loop between TMH2 and TMH3 (Cherny et al. J. Gen. Physiol. 2018 150:851-862). Did the authors check whether any of these modifications alter the transition responsible for the slow kinetic component? For instance, a suppression of the transition resulting from a H168X mutation would help tighten the link to ΔpH sensing.

We did not carry out any of these experiments.

4) We understand that it is difficult to tightly control intracellular and extracellular pH when Hv1 is heterologously expressed in mammalian cells. The G-V relation is not always reliable because accumulation of protons or depletion of protons upon Hv channel activity will alter gating, as the authors have previously published (De La Rosa et al., J. Gen. Physiol. 2016 147:127-136). Could the kinetic analysis of Anap fluorescence be affected by similar alterations to proton concentration in the vicinity of Hv1? It would be helpful for the authors to comment on this specifically.

Thanks for this suggestion. Yes, we think that the kinetics, specially of ionic currents can be affected by even small changes in the pH gradient, for this reason we did not attempt a systematic kinetic analysis. We mention this in the text where we compare the voltage dependence of current and fluorescence activation for construct A197Anap (line 223).

5) Quenching of Anap by Phe could be verified in cell free conditions using a spectrophotometer with different concentrations of Phe, or citing the literature if it has already been reported.

We attempted this experiment but were unsuccessful in observing Anap quenching by phenylalanine at the concentrations of phenylalanine that can be attained in aqueous solution. We suspect that Phe quenching of Anap could happen by electron transfer or ground-state complex formation, in which case near proximity is necessary and higher concentrations of Phe would be required to detect quenching in solution. However, we measured the absorbance of Anap in the absence and presence of phenylalanine (Phe) (and tyrosine (Tyr)) at the concentrations that can be achieved in aqueous solution (8 mM and 1mM, respectively). Absorbance measurements can detect ground-state complex formation even at relatively low concentrations (J.R. Lakowicz, 1999, Principles of Fluorescence Spectroscopy). We observed that the absorbance of Anap is modified by the presence of Tyr or Phe, indicating that these amino acids indeed interact with Anap, possibly through ground-state complex formation. We include this data for the reviewers to inspect.

6) The authors did not cite any example of Anap incorporation into S4 helices, but there are several recent papers where Anap was utilized to probe motion of S4 in other channels. Examples include Dai et al., Nat. Commun. 2021 12:2802 and Mizutani et al. PNAS 2022 119:e2200364119.

Thanks for this observation, we have included these important results in the discussion.

7) In the Anap-free negative control (with only A197TAG plasmid transfection), the mCherry signal seems positive (Supplementary Figure 1, left row, second from the top). Is this due to unexpected skipping of the TAG codon to make mCherry-containing partial polypeptides? It would seem like an explanation is needed.

Thanks for bringing this up. We do not know the exact origin of these leak expression of red fluorescence. We think that, as suggested, there is a possibility that skipping of the Amber codon can lead to a methionine at the end of S4 acting as a second translation initiation site, giving rise to truncated channels that would express mCherry but not currents. This is consistent with the fact that we cannot detect currents in the absence of Anap but we see a small number of red cells.

8) The data of Figure 3E are shown as data with different membrane voltages. But there is no information about membrane voltage for Fig. 1E and Fig. 2A and Fig. 4B. Are these from unpatched cells? Please clarify.

See response to point 4 of "Revisions essential for endorsement" section.

9) G-V relations are shown for F150A-A197Anap, but current traces of F150A-A197Anap are missing.

We have modified the figure to include current and fluorescence traces.

10) On Page 11, Line 303 says "experimental F-V relationship is positively shifted by 10 mV with respect to the G-V curve". But looking at the data Fig5D, the shift at ΔpH=2 seems the opposite. Perhaps "positively" should be "negatively" in this sentence?

Thanks for pointing out this mistake. We have found that this misunderstanding was provoked because of a mistake with the image labeling of F-V and G-V curves for the ΔpH=2 data, we have now corrected the figure. The shift of F-V is indeed positive to G-V as stated before.

(This is a response to peer review conducted by Biophysics Colab on version 1 of this preprint.)

https://brainsteam.co.uk/2022/11/26/one-week-with-hypothesis/

I too read a lot of niche papers and feel the emptiness, but because I'm most often writing for myself anyway, its alright. There are times, however, when I see a growing community of people who've left their associative trails behind before I've found a particular page.

I've used the phrase "digital exhaust" before, but I like the more positive framing of "learning exhaust".

If you've not found it yet, my own experimentations with the platform can largely be found here: https://boffosocko.com/tag/hypothes.is/

She wants to show the world that no matter how your body is, your beauty doesn't depend on it. She created the trend called #realsizebeauty to let people recognize and be confidence to yourself.

The Strep-tag system is a method which allows the purification and detection of proteins by affinity chromatography. The Strep-tag II is a synthetic peptide consisting of eight amino acids (Trp-Ser-His-Pro-Gln-Phe-Glu-Lys). This peptide sequence exhibits intrinsic affinity towards Strep-Tactin, a specifically engineered streptavidin, and can be N- or C- terminally fused to recombinant proteins. By exploiting the highly specific interaction, Strep-tagged proteins can be isolated in one step from crude cell lysates. Because the Strep-tag elutes under gentle, physiological conditions, it is especially suited for generation of functional proteins.

So this blot has affinity for the MBP tag on COP1- it will therefore be attached at all time. The HY5 and HY5 mutants are being washed over this background (each row has 1x HY5 added). The MBP-only column is a negative control to show that the HY5 do not interact with the MBP tag on its own.

same tag used for cop1 and spa1

TAP-SPA1--- is this a control? Paik et al. 2019 paper uses both-- need to check if used for different things? Is this to show that the LUC tag is not having an effect in the complementation mutants? By showing that the phenotype is unaffected by the addition of the TAP-SPA1? BUT shouldn't they have done a LUC-SPA1 only expressing plant (with no spaQ mutant background) as well, to show this? That TAP-SPA1 and LUC-SPA1 produce the same phenotype?

So the Phospho-tagged SDS-PAGE gel will enhance the difference in mobility of phosphorylated---- or not. The lack of band shift is shown between the B and CIP conditions in fig.2c. This is the same result as shown for the HY5-S26A, so the phosphorylation is at this residue by the SPA kinase

See Is Gout Itchy and associated new pages.

---

GoutPal Links Documentation

Notes like this are part of my GoutPal Links service. Which is currently in the pre-launch phase. I will add documentation for this feature as I answer requests from readers. So if you need help using this feature, the best way is to subscribe to my free GoutPal Links Newsletter. Where you can email and message me directly. Or you can use the feedback options near the end of every page.

Joint Public Review:

In this work Malis et al introduce a novel spin-labeling MRI sequence to measure cerebrospinal fluid (CSF) outflow. The glymphatic system is of growing interest in a range of diseases, but few studies have been conducted in humans due to the requirement for and invasiveness of contrast injections. By labeling one hemisphere of the brain the authors attempt to assess outflow through the superior sagittal sinus (SSS), one of the major drainage pathways for CSF, signal changes across time were assessed to extract commonly used metrics. Additionally, correlations with age are explored in their cohort of healthy volunteers. The authors report the movement of labeled CSF from the subarachnoid space to the dura mater, parasagittal dura, and ultimately SSS, evidence of leakage from the subarachnoid space to the SSS, and decreases in CSF outflow metrics with older age.

1. I don't think that the description of Parasagittal dura in figure 1 is correct. There is no anatomical structure at the top of SSS that is known as PSD. The location of the lymphatic structures is also incorrect. Please review "Anatomic details of intradural channels in the parasagittal dura: a possible pathway for flow of cerebrospinal fluid" Neurosurgery 1996 Fox at al. There is usually no obvious tissue between the upper wall of the SSS and the calvarium, which can also be seen in the authors' fig 2A and 2B. All of the tissues located lateral to the SSS are known as PSD. Also, the SSS wall is not as thick as the authors stated and is known as PSD in this region. For this reason, the authors need to revise Fig 1 and it should be changed to PSD in the areas referred to as the SSS wall in the article.

2. The authors described tagged CSF in two pathways: from dura mater to PSD and SAS into the SSS and directly from SAS to SSS. Flow from dura mater to PSD and SAS in the main and supplement cannot be seen. Only a flow from PSD to SSS can be seen. Also, regular dura cannot carry flow-collagen-rich fibrous tissue, except parasagittal dura. There is no flow from dura to the CSF in the figures.

3. The authors have conducted many tests to prevent venous contamination. However, measurements were made based on SSS flow rates in all tests. Small parenchymal venous structures, and small cortical-SAS veins might be tagged due to different flow patterns and T2- Relaxation times.

4. The rate of CSF formation in humans is 0.3 - 0.4 ml min-1. ( Brinker et al 2014. Fluids Barriers CNS). We can assume that the absorption rate is also similar to the CSF formation for the entire system brain and Spine. Therefore, the absorption rate of this very small amount of CSF by SSS is very low in seconds. It is hard to detect by MR and especially CSF flow from the PSD to SSS. The authors concluded that using this technique the rate averaged less than a couple of seconds, rather than on the order of hours or days as previously reported with the use of intrathecal administration of GBCA (Ringstad et al., 2020).

5. Overall, I think that the CSF flow from the PSD to the CNS described by the authors - the CSF flow, might be the venous flow that drains into the SSS slowly, predominantly in the rich venous channels, venous lacunae, and previously described channels in the PSD. Additional explanations are needed.

6. The study is generally well described and to the best of my knowledge an innovative approach. The findings are broadly consistent with what might be expected from the literature and the authors make a good argument in support of their findings. However, the lack of validation is a major limitation of the presented work. In introducing a novel technique a comparison with an existing approach, such as Gd enhanced contrast techniques, or phase contrast would have been expected. Several considerations could have been mentioned/addressed in more detail e.g. what effect labeling efficiency, tortuosity of vessels, lack of gating, the effectiveness of the intensity thresholding to remove the signal from blood, etc may have on the quantification, etc. Without a more thorough validation, it is difficult to evaluate the findings. While scans were conducted on two volunteers to assess reproducibility this is a very small sample and it is notable that scans were conducted consecutively, which might be expected to reduce variance relative to scans further apart e.g. on different dates, scanned by a different operator and no information is provided on how the two scans were positioned (i.e. separately vs copied from the first to the second scan), some metrics showed large percentage differences, which were more pronounced in one subject than the other. Without further data, it is difficult to interpret the reproducibility results. No assessment of the effect of physiological parameters e.g. breathing, cardiac pulsations, or factors affecting glymphatic clearance e.g. amount of sleep the evening before was given.

7. Given these limitations it is hard to adequately assess the likely impact or utility. In recent years several groups have published work e.g. doi.org/10.1038/s41467-020-16002-4 , doi.org/10.1016/j.neuroimage.2021.118755 assessing the blood-CSF barrier. However, previous work has generally focused on larger structures, and by labeling in the oblique-sagittal plane it is unclear how drainage and blood flow rates may affect the presented values here.

8. Some validation data would greatly increase the value of the reported work. I would therefore encourage the authors to consider acquiring some additional datasets to compare measures of CSF draining against another method e.g. 2-D or 4-D phase contrast, or Gd-based contrast-enhanced techniques. Some additional points to consider are noted below.

8. Abstract

CSF outflow may also be imaged with phase contrast MRI (albeit in a limited way).<br /> Demographics would fit better in Results, breakdown could be given for the young and old groups i.e. n, ages, sex.<br /> Conclusion - unless further validation can be provided I think some of the claims should be toned down.

9. Introduction

The authors emphasise the role of Nedergaard, however, there was some relevant earlier work (e.g. Rennels et al, PMID: 2396537).

10. Methods

It would be more conventional to summarise the volunteer characteristics in the Results.<br /> Given the age difference between the two groups, and the fact that for conventional ASL we know of differences in labelling efficiency and the need for a different post-labelling duration in more elderly patients how did the authors account for this?<br /> More broadly what would the effect of differences in labeling efficiency be, given the labeling plane is unlikely to be perpendicular to the draining vessels?<br /> While the authors mention circadian effects there is no mention of controlling for other factors before the scan e.g. caffeine consumption, smoking, etc.<br /> Various mechanisms have been hypothesised to drive glymphatic pulsations. Assessing how physiological signals correlated with the flow may have been a useful proof of concept. Why was it not considered necessary to use a gated acquisition? Did the authors consider the potential impact of respiratory and cardiac pulsations on their measurements?<br /> ROI segmentation - manually selected by two raters, was this done independently and blinded? How were consensus ROIs agreed?<br /> Intensity values outwith MEAN +/- 2 SD were excluded from further analyses. This is justified as removing pulsatile blood. However, was this done independently for tag-on and tag-off? Does this mean slight differences were present in the number of voxels between the two?<br /> The starting points and parameter ranges are given in Eq'n 3, how were the ranges defined? Was there a reason for constraining the fit to positive values only, is there a risk of bias from this?<br /> While the main results appear to have a reasonable sample size n=2 for the reproducibility analysis is very limited. Additional datasets would be useful in properly interpreting the results.

11. Results<br /> While the authors have taken some measures to reduce potential contamination from blood I would be concerned about the risk of surface vessels affecting the signal, and there does not seem to be an evaluation of how effective their measures are.<br /> The labeling pulse is applied in the oblique sagittal orientation, but in tandem with differing rates of blood flow and CSF drainage from the labeling plane does that not risk circulating flow from other slices potentially affecting the values?<br /> Figure 4. The authors focus on the parasagittal dura, but in both the subtraction image and panel C showing different slices at TI=1250 ms some movement appears visible in the opposing hemisphere. Similarly in S2 If the signal does represent CSF movement then this seems counterintuitive and should be explained.<br /> In Figures 4 and 5 the angulation of the TIME-SLIP tag pulse seems quite different. What procedure was used to standardise this, and what effect may this have on the results?

12. Discussion<br /> Phrasing error 'which will be assessed in future studies'.<br /> I would suggest that some of the claims of novelty be moderated e.g. 'may facilitate establishment of normative values for CSF outflow' seems a stretch given multiple pathways exist and this is only considered one.<br /> More consideration should be given to some of the points mentioned in the results. The lack of validation should be properly discussed.

CVC looks like Ceramic with the "era" starting with "emblem"

** not affiliated with QWERTY either. ECMA

Author Response

Reviewer #1 (Public Review):

The authors have generated a set of seven nanobody tools against two of the largest Drosophila proteins, which are related to vertebrate titin and essential for muscle function. The study of such gigantic proteins is a challenge. They show that each of these nanobodies recognizes their epitope with high affinity (as expected from antibodies), fails to generate a signal after immune-fixation of a mutant for the cognate protein, do not cross-react with each other, and generates a signal in the muscle that makes sense with what one would anticipate for fly titin homologs. In addition, they show that these nanobodies have better penetration and labeling efficiency than conventional antibodies in thick tissues after classical paraformaldehyde fixation. Using these nanobodies, they could deduce the organization of the epitopes in different muscle types and propose a model for Sallimus and Projectin arrangement in muscles, including in larvae which are difficult to label with traditional antibodies due to their impermeable chitin skeleton. Finally, they could fuse the gene encoding one of the nanobodies to the open reading frame of NeonGreen and express the corresponding fusion protein in animals to use the probe in FRAP assays.

The work is very well performed and convincing. However, given its significant redundancy in terms of biological conclusions with the companion study "Nanobodies combined with DNAPAINT super-resolution reveal a staggered titin nano-architecture in flight muscles" by the same authors, and other published papers, I recommend the authors further prove the use of their nanobodies in live assays. In particular, the authors should test whether they can use the nanobodies to induce protein degradation either permanently or conditionally.

Thanks for this nice summary of our findings. We have now extended the analysis of the Nanobody-NeonGreen fusion expressing larval muscles and provide first proof of principle analysis of new fly strains that we generated that contain Sls-Nano2 or Sls-Nano42 nanobodies fused to a degradation signal. These induce lethality of the animals suggesting that Sls protein is partially non functional. We verified this by providing quantitative stainings of various Sls epitopes in these muscles suggesting that Sls is not fully degraded but rather partially modified in the Sls-Nano-deGrad expressing muscle fibers. These will be interesting tools to study Sls function during sarcomere homeostasis.

Reviewer #2 (Public Review):

The data presented in this manuscript are sound but rather descriptive. The contribution - as presented - is mostly of a technical nature. The authors correctly state that anti-GFP nanobodies, while used extensively across many model organisms, have limited utility for in vivo applications when the GFP-tagged protein in question displays abnormal behavior or is non-functional. The creation of nanobodies that are uniquely specific for the protein(s) of interest is therefore a significant improvement, especially since the Sallimus and Projectinspecific reagents reported here react with PFA-fixed material. At least one of these nanobodies, when expressed in vivo, decorates the appropriate target. The source of antigens used for the construction of the nanobody library is Drosophila-derived. The extent of homology of Drosophila Sallimus and Projectin with related proteins in other species is not discussed. Whether the nanobodies reported here would be useful in other (closely related?) species, therefore, remains to be established. For those studying muscle biology in Drosophila, the nanobodies described here will be publicly available as cDNAs. Ease of production implies a readily shared and standardized resource for the field.

We thank this reviewer for appreciating that our Sallimus and Projectin nanobodies are useful. We now have extended the collection even further, including anti-Obscurin, αActinin and Zasp52 nanobodies, the latter two will also be useful for researcher studying other tissues, in particular Drosophila epithelial tissues. As always in the Drosophila field, all the here generated fly strains and plasmids will be made easily available to the community by placing them in stock centers or shipping them to the laboratories directly. As indicated, also the plasmids will be deposited at Addgene.

Further characterization of these nanobodies by biochemical methods such as immunoblotting would be challenging, given the size of the target proteins. In view of the technical nature of this manuscript, the authors should perhaps critically discuss the distinction between bulky GFP tags versus the much smaller epitope tags and the nanobodies that recognize them, although this was covered in a recent eLife paper from the Perrimon lab. Insertion of small tags, in conjunction with nanobodies that recognize them, would be less perturbing than the much bulkier GFP tag and lend itself to genome-wide applications. Creating nanobodies uniquely specific for each protein encoded in the Drosophila genome is not realistic, and the targeted approach deployed here is obviously valuable.

We are discussing the drawbacks of solely relying on GFP nanobodies, which requires GFP tagged proteins to be available and being functional. In particular for the sarcomeric proteins this is often not the case. We also cite the Perrimon paper, which was just published as we prepared this manuscript. We would like to point out to this reviewer that even tagging with a small epitope tag is considerable work in Drosophila and that the Perrimon paper, on which this reviewer is an author, does describe only two endogenously tagged genes with a nanotag (histone H2Av and Dilp2) the other genes described were expressed from a UAS source or in cell culture. We show here 22 nanobodies against 11 target epitopes.

Nanobodies recognise typically folded epitopes and are rather unlikely to work in immunoblotting.

The authors apply two different approaches to characterize the newly generated Nanobodies: more or less conventional immunohistochemistry with fluorescently labeled nanobodies, and in vivo expression of nanobodies fused to the fluorescent neongreen protein. The superiority of nanobodies in terms of tissue penetration has been shown by others in a direct comparison of intact fluorescently labeled immunoglobulins versus nanobodies. The authors state that in vivo labeling with nanobody fusions "thus far was done only with nanobodies against GFP, mCherry or short epitope tags." There is no fundamental difference between these recognition events and what the authors report for their Sallimus and Projectin-specific reagents. The section that starts at line 304 is thus a little bit of a 'straw man'. There is no reason to assume that a nanobody that recognizes a muscle protein would behave differently than a nanobody that would recognize that same protein (or another) when epitope- or GFP-tagged. What might be interesting is to examine the behavior of these muscle-specific nanobodies in the course of muscle contraction/relaxation: are there conformational alterations that promote dissociation of bound nanobodies? Do different nanobodies display discrete behavior in this regard? The manuscript is silent on how muscles behave in live L3 larvae. The FRAP experiment seems to suggest that not much is happening, but the text refers to the contraction of larval sarcomeres from 8.5 µM to 4.5 µM. Does the in vivo expressed nanobody remain stably bound during this contraction/relaxation cycle? What about the other nanobodies reported in this manuscript? Since the larval motion was reduced by exposure to diethylether, have the authors considered imaging the contractive cycle in the absence of such exposure?

We appreciate the expert knowledge about nanobodies by this reviewer. However, nanobodies were not extensively applied in Drosophila tissues. Hence, we believe it is important to characterise their penetration in stainings and compare them carefully to antibodies. Such, the Drosophila reader will be aware of their advantages.

We have now also included more data on the larval muscle morphology in the nanobody expressing muscles. Their morphology is normal. As larvae move around extensively all the time, the binding of the nanobodies to the target must be stable, otherwise it would not be bound when we fix them or anesthetize them. However, we have not attempted to image them at high resolution while crawling freely. From quantifying the crawling speed (about 1.5 mm per second, see Figure 9 S1) we hope this reviewer appreciates that high resolution imaging of sarcomeres in freely crawling larvae is highly non trivial.

Given that the nanobodies bind well-folded epitopes with low picomolar dissociations constants, it is hard to imagine that conformational changes of the target would dissociate them. The nanobody would stabilise the recognised conformation by a ΔG of ≈60 KJ/ mole, and we would not expect that the chosen domains undergo major conformational changes.

Reviewer #3 (Public Review):

Loreau et al. have presented a well-written manuscript reporting clever, original work taking advantage of fairly new biotechnology - the generation and use of single chain antibodies called nanobodies. The authors demonstrate the production of multiple nanobodies to two titin homologs in Drosophila and use these nanobodies to localize these proteins in several fly muscle types and discover interesting aspects of the localization and span of these elongated proteins in the muscle sarcomere. They also demonstrate that one of these single chain antibodies can be expressed in muscle fused to a fluorescent protein to image the localization of a segment of one of these giant proteins called Sallimus in muscle in a live fly. Their project is well-justified given the limitations of the usual approaches for localizing and studying the dynamics of proteins in the muscle of model organisms such as the possibility that GFP tagging of a protein will interfere with its localization or function, and poor penetration of large IgG or IgM antibodies into densly packed structures like the sarcomere after fixation as compared to smaller nanbodies.

They achieved their goals consistent with the known/expected properties of nanobodies: (1) They demonstrate that at least one of their nanobodies binds with very high affinity. (2) They bind with high specificity. (3) The nanobodies show much better penetration of fixed stage 17 embryos than do conventional antibodies.

They use their nanobodies mostly generated to the N- and C-terminal ends of Sallimus and Projectin to learn new information about how these elongated proteins span and are oriented in the sarcomere. For example, in examining larval muscles which have long sarcomeres (8.5 microns), using nanobodies to domains located near the N- and C-termini, they show definitively that the predicted 2.1 MDa protein Sallimus spans the entire I-band and extends a bit into the A-band with its N-terminus embedded in the Z-disk and C-terminus in the outer edge of the A-band. Using a similar approach they also show that the 800 kDa Projectin decorates the entire myosin thick filament except for the H-zone and M-line in a polar orientation. Their final experiment is most exciting! They were able to express in fly larval muscles a nanobody directed to near the N-terminus of Sallimus fused to NeonGreen and show that it localizes to Z-disks in living larvae, and by FRAP experiments demonstrate that the binding of this nanobody to Sallimus in vivo is very stable. This opens the door to using a similar approach to study the assembly, dynamics, and even conformational changes of a protein in a complex in a live animal in real time.

We thank this reviewer for appreciating the quality and impact of our approach and the our obtained results.

There are only a few minor weaknesses about their conclusions: (1) They should note that in fact their estimate of the span of Sallimus could be an underestimate since their Nano2 nanobody is directed to Ig13/14 so if all of these 12 Ig domains N-terminal of their epitope were unwound it would add 12 X 30 nm = 360 nm of length, and even if unwound would add about 50 nm of length.

We are discussing the length contribution of the 12 Ig domains now more extensively in the DNA PAINT super-resolution paper, however not in this resource paper as the 50 nm difference was not resolved with the confocal microscopy applied here to the larval muscle sarcomere.

(2) They discuss how Sallimus and Projectin are the two Drosophila homologs of mammalian titin, however, they ignore the fact that there is more similarity between Sallimus and Projectin to muscle proteins in invertebrates. For example, in C. elegans, TTN-1 is the counterpart of Sallimus, and twitchin is the counterpart of Projectin, both in size and domain organization. The authors present definitive data to support Figure 9, their nice model for a fly larval sarcomere but fail to point out that this model likely pertains to C. elegans and other invertebrates. In Forbes et al. (2010) it was shown that TTN-1, which can be detected by western blot as ~2 MDa protein and using two polyclonal antibodies spans the entire Iband and extends into the outer edge of the A-band, very similar to what the authors here have shown, more elegantly for Sallimus. In addition, several studies have shown that twitchin (Projectin) does not extend into the M-line; the M-line is exclusively occupied by UNC-89, the homolog of Obscurin.

We thank this reviewer for pointing out the important C. elegans literature that we have now included in this revised manuscript. We apologise for initially omitting them. They are indeed highly relevant.

Reviewer #4 (Public Review):

Authors report the generation and characterisation of several nanobodies for giant Drosophila sarcomeric proteins, Sallimus and Projectin the functional orthologs of titin. They describe an efficient pipeline that could potentially help in designing and producing nanobodies for other proteins. There are several advantages to using nanobodies in comparison to conventional antibodies and the authors nicely demonstrate that the generated nanobodies allow to precisely map subcellular localisation and even the protein orientation in the case of Projectin. They also show that small nanobody molecules have superior penetration and labelling efficiencies with respect to classical antibodies. Finally, the authors select one of the nanobodies to test whether it will efficiently detect native proteins in living tissue. They confirm that Sls-Nano2NeoGreen binds Sls in vivo in muscles of temporarily immobilized 3rd instar larva allowing to reveal sarcomeric Sls pattern and to demonstrate by FRAP experiments that Sls does not exchange during a short time period.

This work is of significant value to a large audience. It provides a clear and precise pipeline for the generation of efficient nanobodies, which are invaluable tools of modern biology.

We thank this reviewer for expressing strong support for our manuscript and appreciating its value for a large readership.

Reviewer #2 (Public Review):

The data presented in this manuscript are sound but rather descriptive. The contribution - as presented - is mostly of a technical nature. The authors correctly state that anti-GFP nanobodies, while used extensively across many model organisms, have limited utility for in vivo applications when the GFP-tagged protein in question displays abnormal behavior or is non-functional. The creation of nanobodies that are uniquely specific for the protein(s) of interest is therefore a significant improvement, especially since the Sallimus and Projectin-specific reagents reported here react with PFA-fixed material. At least one of these nanobodies, when expressed in vivo, decorates the appropriate target. The source of antigens used for the construction of the nanobody library is Drosophila-derived. The extent of homology of Drosophila Sallimus and Projectin with related proteins in other species is not discussed. Whether the nanobodies reported here would be useful in other (closely related?) species, therefore, remains to be established. For those studying muscle biology in Drosophila, the nanobodies described here will be publicly available as cDNAs. Ease of production implies a readily shared and standardized resource for the field.

Further characterization of these nanobodies by biochemical methods such as immunoblotting would be challenging, given the size of the target proteins. In view of the technical nature of this manuscript, the authors should perhaps critically discuss the distinction between bulky GFP tags versus the much smaller epitope tags and the nanobodies that recognize them, although this was covered in a recent eLife paper from the Perrimon lab. Insertion of small tags, in conjunction with nanobodies that recognize them, would be less perturbing than the much bulkier GFP tag and lend itself to genome-wide applications. Creating nanobodies uniquely specific for each protein encoded in the Drosophila genome is not realistic, and the targeted approach deployed here is obviously valuable.

The authors apply two different approaches to characterize the newly generated Nanobodies: more or less conventional immunohistochemistry with fluorescently labeled nanobodies, and in vivo expression of nanobodies fused to the fluorescent neongreen protein. The superiority of nanobodies in terms of tissue penetration has been shown by others in a direct comparison of intact fluorescently labeled immunoglobulins versus nanobodies. The authors state that in vivo labeling with nanobody fusions "thus far was done only with nanobodies against GFP, mCherry or short epitope tags." There is no fundamental difference between these recognition events and what the authors report for their Sallimus and Projectin-specific reagents. The section that starts at line 304 is thus a little bit of a 'straw man'. There is no reason to assume that a nanobody that recognizes a muscle protein would behave differently than a nanobody that would recognize that same protein (or another) when epitope- or GFP-tagged. What might be interesting is to examine the behavior of these muscle-specific nanobodies in the course of muscle contraction/relaxation: are there conformational alterations that promote dissociation of bound nanobodies? Do different nanobodies display discrete behavior in this regard? The manuscript is silent on how muscles behave in live L3 larvae. The FRAP experiment seems to suggest that not much is happening, but the text refers to the contraction of larval sarcomeres from 8.5 µM to 4.5 µM. Does the in vivo expressed nanobody remain stably bound during this contraction/relaxation cycle? What about the other nanobodies reported in this manuscript? Since the larval motion was reduced by exposure to diethylether, have the authors considered imaging the contractive cycle in the absence of such exposure?

Author Response

Reviewer #1 (Public Review):

In a very interesting and technically advanced study, the authors measured the force production of curved protofilaments at depolymerizing mammalian microtubule ends using an optical trap assay that they developed previously for yeast microtubules. They found that the magnesium concentration affects this force production, which they argue based on a theoretical model is due to affecting the length of the protofilament curls, as observed previously by electron microscopy. Comparing with their previous force measurements, they conclude that mammalian microtubules produce smaller force pulses than yeast microtubules due to shorter protofilament curls. This work provides new mechanistic insight into how shrinking microtubules exert forces on cargoes such as for example kinetochores during cell division. The experiments are sophisticated and appear to be of high quality, conclusions are well supported by the data, and language is appropriate when conclusions are drawn from more indirect evidence. Given that the experimental setup differs from the previous optical trap assay (antibody plus tubulin attached to bead versus only antibody attached to bead), a control experiment could be useful with yeast microtubules using the same protocol used in the new variant of the assay, or at least a discussion regarding this issue. One open question may be whether the authors can be sure that measured forces are only due to single depolymerizing protofilaments instead of two or more protofilaments staying laterally attached for a while. How would this affect the interpretation of the data?

This work will be of interest to cell biologists and biophysicists interested in spindle mechanics or generally in filament mechanics.

Thank you for your careful reading of our manuscript, your kind remarks, and your favorable review.

Reviewers #1 and #2 both mentioned a concern about potential differences between our previous setup with yeast microtubules, versus our new setup with predominantly bovine microtubules, and whether such differences might underlie the different pulse amplitudes we measured. We think this concern comes mainly from a misunderstanding of how the beads in both setups were tethered to the sides of the microtubules, and we apologize for not making this aspect clearer in our original submission.

It is true that our new setup requires one additional step, pre-decoration of the anti-His beads with His6-tagged yeast tubulin. However, in both cases, the anti-His antibodies were kept very sparse on the beads to ensure that most beads, if they became tethered to a microtubule, were attached by a single antibody. (~30 pM beads were mixed with 30 pM of anti-His antibody, for a molar ratio of 1:1.) And even though the anti-His beads in our previous work did not undergo a separate incubation step for pre-decoration with tubulin, they undoubtedly were decorated immediately after being mixed into the microtubule growth mix, which in that case included ~1 µM of unpolymerized His6-tagged yeast tubulin dimers. Thus, the arrangement with beads tethered laterally to the sides of microtubules via single antibodies was created in both cases by essentially the same three-step process: First, beads decorated very sparsely with anti-His antibodies were bound to unpolymerized His6-tagged yeast tubulin. Second, a bead-tethered His6-tagged yeast tubulin was incorporated into the growing tip of a microtubule (which could be assembling from either yeast or bovine tubulin, depending on the experiment). Third, the tip grew past the bead to create a large extension. Because the beads in both scenarios were tethered by a single antibody to the same C-terminal tail of yeast β-tubulin, the differences in pulse amplitude cannot be explained by differences in the tethering. In our revised manuscript, we now mention explicitly in Results that the beads were tethered by single antibodies (lines 95 to 100). In Methods we significantly expanded the section about preparation of beads and how they became tethered (lines 365 to 393). [We refer here, and below, to line numbers when the document is viewed with “All Markup” shown.]

You also raise an interesting, open question: Do protofilaments curl outward entirely independently of their lateral neighbors? Or under some conditions might they tend to stay laterally associated during the curling process, perhaps curling outward in pairs rather than as individual protofilaments? We cannot formally rule out the possibility that such lateral associations sometimes persist during protofilament curling. However, changes in lateral association seem unlikely to explain the magnesium- and species-dependent differences we measured in pulse amplitude, for several reasons: First, there is good evidence for lengthening of protofilament curls at disassembling tips (e.g., Mandelkow 1991, Tran & Salmon 1997), but we are not aware of convincing evidence for magnesium or species-dependent increases in the propensity of curling protofilaments to remain laterally associated. Second, an increase in lateral association should increase the effective flexural rigidity of the curls, but under all the conditions we examined, pulse enlargement was associated with a steepening of the amplitude-vs-force relation – i.e., with softening, not stiffening. Our model indicates that this softening can be fully explained by an increase in protofilament contour length, without any change in the intrinsic flexural rigidity of the protofilament curls.

Reviewer #2 (Public Review):

Microtubules are regarded as dynamic tracks for kinesin and dynein motors that generate force for moving cargoes through cells, but microtubules also act as motors themselves by generating force from outward splaying protofilaments at depolymerizing ends. Force from depolymerization has been demonstrated in vitro and is thought to contribute to chromosome movement and other contexts in cells. Although this model has been in the field for many years, key questions have remained unanswered, including the mechanism of force generation, how force generated might be regulated in cells, and how this system might be tuned across cellular contexts or organisms. The barrier is that we lack an understanding of experimental conditions that can be used to control protofilament shape and energetics. This study by Murray and colleagues makes an important advance towards overcoming that barrier.

This study builds on previous work from the authors where they developed a system to directly measure forces generated by outward curling protofilaments at depolymerizing microtubule ends. That study showed for the first time that protofilaments act like elastic springs and related the generated force to the estimated energy contained in the microtubule lattice. Furthermore, they showed that slowing polymerization rate did not diminish force generation. That study used recombinant yeast tubulin, including a 6x histidine tag on beta tubulin that created attachment points for the bead on the microtubule lattice. The current study extends that system to show that work output is related to the length of protofilament curls.

We are grateful for your very thoughtful and thorough review, which has helped us improve our manuscript.

Murray and colleagues show this by manipulating curls in two ways - using bovine brain tubulin instead of yeast tubulin and altering magnesium concentration. Previous EM studies indicated that protofilaments on depolymerizing bovine microtubules have similar curvature but are shorter. The authors here use a blend of bovine brain tubulin and bead-linked recombinant yeast tubulin with the 6x histidine tag in their in vitro system and find smaller deflections of the laser-trapped bead than previously observed with pure yeast tubulin. A concern with comparing this heterogeneous bovine/yeast system to the previous work with homogeneous yeast tubulin is that density of 6x histidine-tagged tubulin subunits is likely to be different between the two systems. Also, the rate of incorporation of 6x histidine yeast tubulin into bovine microtubules in the current study may be different from the rate of incorporation into yeast microtubules in the previous study. These differences could lead to changes in the strength of bead attachment to the microtubule lattice and alter the compliance of the bead to deflection by curling protofilaments. These possibilities and lattice attachment strength are not explored in this study, raising concerns about comparing the two systems.

Reviewers #1 and #2 both mentioned a concern about potential differences between our previous setup with yeast microtubules, versus our new setup with predominantly bovine microtubules, and whether such differences might underlie the different pulse amplitudes we measured. As detailed in our response to Reviewer #1 above, we think this concern comes mainly from a misunderstanding of how the beads in both setups were tethered to the sides of the microtubules, and we apologize for not making this aspect clearer in our original submission. For both our yeast and bovine microtubule experiments, the anti-His antibodies were kept very sparse on the beads to ensure that most beads, if they became tethered to a microtubule, were attached by a single antibody. Because the beads in both scenarios were tethered by a single antibody to the same C-terminal tail of yeast β-tubulin, the differences in pulse amplitude cannot be explained by differences in the tethering. In our revised manuscript, we now mention explicitly in Results that the beads were tethered by single antibodies (lines 95 to 100). In Methods we significantly expanded the section about preparation of beads and how they became tethered (lines 365 to 393).

The authors go on to show that magnesium increases bead deflection and work output from the system. The use of magnesium was motivated by earlier studies which showed that increasing magnesium speeds up depolymerization and increases the lengths of protofilament curls. The use of magnesium here provides the first evidence that work output can be tuned biochemically. This is an important finding. The authors then go on to show that the effect of magnesium on bead deflection can be separated from its effect on depolymerization speed. They do this by proteolytically removing the beta tubulin tail domain, which previous studies had shown to be necessary to mediate the magnesium effect on depolymerization rate. The authors arrive at a conclusion that magnesium must promote protofilament work output by increasing their lengths. How magnesium might do this remains unanswered. The mechanistic insight from the magnesium experiments ends there, but the authors discuss possible roles for magnesium in strengthening longitudinal interactions within protofilaments or perhaps complexing with the GDP nucleotide at the exchangeable site, although that seems less likely at the concentrations in these experiments.

The major conclusion of the study is the finding that work output from curling protofilaments is a tunable system. The examples here demonstrate tuning by tubulin composition and by divalent cations. Whether these examples relate to tuning in biological systems will be an important next question and could expand our appreciation for the versatility of depolymerizing microtubules as a motor.

We fully agree that two very important next questions are whether work output from curling protofilaments is truly harnessed in vivo, and whether protofilament properties in vivo might be actively regulated for this purpose. Based on your recommendations, and as detailed below (under Major point 2), we have expanded our discussion of these possibilities in our revised manuscript.

Reviewer #3 (Public Review):

The authors used a previously established optical tweezers-based assay to measure the regulation of the working stroke of curled protofilaments of bovine microtubules by magnesium. To do so, the authors improved the assay by attaching bovine microtubules to trapping beads through an incorporated tagged yeast tubulin.

The assay is state-of-the-art and provides a direct measurement of the stroke size of protofilaments and its dependence on magnesium.

The authors have achieved all their goals and the manuscript is well written.

The reported findings will be of high interest for the cell biology community.

Thank you for reading and evaluating our manuscript. We are grateful for your positive comments.

Reviewer #2 (Public Review):

Microtubules are regarded as dynamic tracks for kinesin and dynein motors that generate force for moving cargoes through cells, but microtubules also act as motors themselves by generating force from outward splaying protofilaments at depolymerizing ends. Force from depolymerization has been demonstrated in vitro and is thought to contribute to chromosome movement and other contexts in cells. Although this model has been in the field for many years, key questions have remained unanswered, including the mechanism of force generation, how force generated might be regulated in cells, and how this system might be tuned across cellular contexts or organisms. The barrier is that we lack an understanding of experimental conditions that can be used to control protofilament shape and energetics. This study by Murray and colleagues makes an important advance towards overcoming that barrier.

This study builds on previous work from the authors where they developed a system to directly measure forces generated by outward curling protofilaments at depolymerizing microtubule ends. That study showed for the first time that protofilaments act like elastic springs and related the generated force to the estimated energy contained in the microtubule lattice. Furthermore, they showed that slowing polymerization rate did not diminish force generation. That study used recombinant yeast tubulin, including a 6x histidine tag on beta tubulin that created attachment points for the bead on the microtubule lattice. The current study extends that system to show that work output is related to the length of protofilament curls.

Murray and colleagues show this by manipulating curls in two ways - using bovine brain tubulin instead of yeast tubulin and altering magnesium concentration. Previous EM studies indicated that protofilaments on depolymerizing bovine microtubules have similar curvature but are shorter. The authors here use a blend of bovine brain tubulin and bead-linked recombinant yeast tubulin with the 6x histidine tag in their in vitro system and find smaller deflections of the laser-trapped bead than previously observed with pure yeast tubulin. A concern with comparing this heterogeneous bovine/yeast system to the previous work with homogeneous yeast tubulin is that density of 6x histidine-tagged tubulin subunits is likely to be different between the two systems. Also, the rate of incorporation of 6x histidine yeast tubulin into bovine microtubules in the current study may be different from the rate of incorporation into yeast microtubules in the previous study. These differences could lead to changes in the strength of bead attachment to the microtubule lattice and alter the compliance of the bead to deflection by curling protofilaments. These possibilities and lattice attachment strength are not explored in this study, raising concerns about comparing the two systems.

The authors go on to show that magnesium increases bead deflection and work output from the system. The use of magnesium was motivated by earlier studies which showed that increasing magnesium speeds up depolymerization and increases the lengths of protofilament curls. The use of magnesium here provides the first evidence that work output can be tuned biochemically. This is an important finding. The authors then go on to show that the effect of magnesium on bead deflection can be separated from its effect on depolymerization speed. They do this by proteolytically removing the beta tubulin tail domain, which previous studies had shown to be necessary to mediate the magnesium effect on depolymerization rate. The authors arrive at a conclusion that magnesium must promote protofilament work output by increasing their lengths. How magnesium might do this remains unanswered. The mechanistic insight from the magnesium experiments ends there, but the authors discuss possible roles for magnesium in strengthening longitudinal interactions within protofilaments or perhaps complexing with the GDP nucleotide at the exchangeable site, although that seems less likely at the concentrations in these experiments.

The major conclusion of the study is the finding that work output from curling protofilaments is a tunable system. The examples here demonstrate tuning by tubulin composition and by divalent cations. Whether these examples relate to tuning in biological systems will be an important next question and could expand our appreciation for the versatility of depolymerizing microtubules as a motor.

As I wrote in my feedback on the M4 Discussion in IOCD, "I agree that this prompt has a 'low floor' and 'high ceiling.' The prompt emphasizes observation, creative thinking, and multiple perspectives. You even state, 'There are no wrong answers.' I like how you require students to explain their reasoning when they answer the ... question about which tag doesn't belong."

BLAST matches the GFPmut3 sequence in rGFP and fGFP to this - so the Voigt lab authors cloned this with the partial degron tag without the LAA amino acids for this paper :

Yang, Lei, et al. "Permanent genetic memory with> 1-byte capacity." Nature methods 11.12 (2014): 1261-1266.

Author Response

Reviewer #2 (Public Review):

“To describe LLPS or to distinguish between polymer-polymer phase separation and LLPS, recent studies have used single particle tracking, a technique allowing to follow the dynamics of individual proteins in living cells (https://doi.org/10.7554/eLife.60577; https://doi.org/10.7554/eLife.69181; https://doi.org/10.7554/eLife.47098). The authors should mention that such an approach can be a good alternative to avoid the artefact of fixation. Using techniques such as single particle tracking or FCS, it is possible to estimate the effective diffusion coefficient of protein-living cells. When a liquid phase separation is formed, it is also possible to estimate the diffusion coefficient of the protein of interest (POI) inside versus outside of the LLPS.”

We thank the reviewer for their insight and fully agree that live-cell techniques like SPT and FCS are valuable for investigating LLPS while avoiding fixation artifacts. We have added discussion emphasizing this fact and incorporated the citations recommended by the reviewer in Paragraph 1 on Page 15: “Live imaging techniques that allow estimation of protein diffusion coefficients within specific cellular compartments, e.g., SPT (Hansen et al., 2018 and Heckert et al., 2022) and fluorescence correlation spectroscopy (Lanzanò et al., 2017), can be useful alternative approaches for diagnosing LLPS in vivo without the potential artifact of fixation, as diffusion dynamics are recently shown to be affected by LLPS (Heltberg et al., 2021; McSwiggen et al., 2019a; Miné-Hattab et al., 2021; Chong et al., 2022; and Ladouceur et al., 2020).”

“The authors say that less dynamic interactions are better captured by PFA fixation. In the simulation part, would it be possible to predict from the diffusion coefficients of the POI inside a condensate the effect of the PFA fixation? […] In the simulation part, they could try to incorporate the diffusion coefficient of the protein of interest and see if it is possible to predict the effect of fixation as a function of the diffusion coefficient.”

We thank the reviewer for pointing out the absence of this critical piece that connects our experimental observations to our kinetic model. Our model considers association/dissociation rates rather than diffusion coefficients to describe interaction dynamics, but the reviewers’ point is still very insightful and important. As described in Response 2, we compared two proteins: Halo-TAF15(IDR), which is poorly preserved by fixation, and TAF15(IDR)-Halo-FTH1, which is well preserved by fixation. We used SPT to measure the dissociation rates of Halo-TAF15(IDR) and TAF15(IDR)-Halo-FTH1 and showed that the dissociation rate of Halo-TAF15(IDR) from its puncta is much faster than that of TAF15(IDR)-Halo-FTH1, demonstrating more stable homotypic interactions of the latter than the former. The observation that TAF15(IDR)-Halo-FTH1 has less dynamic interactions and is better preserved by fixation compared to Halo-TAF15(IDR) agrees with our model’s prediction that less dynamic interactions are better captured by fixation. Please see Response 2 for more details. Our new data and discussion have been added to the revised manuscript in Paragraph 3 on Page 13 and in Figure 3B, Figure 3E, Figure 6, and Video 2.

“Finally, the authors propose that in the future, it will be important to design novel fixatives with significantly faster cross-linking rates than biomolecular interactions to eliminate fixation artifacts in the cell. It would be even more interesting if the authors could propose some ideas of potential novel fixatives. Did they test several concentrations of PFA, for example? Did they test different times of PFA incubation? Did they test cryofixation and do they know what would be their effect on LLPS? Do they have novel fixatives in mind? […] To strengthen the manuscript, the authors should try more protocols of fixation.”

We thank the reviewer for these good questions. As described in Response 1, we have done additional quantification of the change of LLPS appearance in cells upon treatment of 0% PFA (only PBS buffer), 1% PFA, 2% PFA, and 8% PFA as well as 4% PFA supplemented by 0.2% GA. We saw statistically significant changes in the LLPS-describing parameters upon all the PFA and PFA/GA treatments except the 0% PFA control. To examine how fixation artifacts depend on the time of PFA incubation, we acquired a time-lapse movie of a cell overexpressing EGFP-FUS(IDR) immediately after 4% PFA treatment and quantified the number of puncta over time (Video 1). We showed that fixation is complete (the number of puncta becomes constant) by roughly 100 seconds (Figure 1 – figure supplement 2). Our new data also justified our choice of a 10-minute PFA incubation time for analyzing fixation-induced change of LLPS appearance in the rest of the paper. Please see Response 1 for more details. Our new data and discussion have been added to the revised manuscript in Paragraph 3 on Page 3 and in Figure 1 - figure supplement 2 (time dependence of fixation artifacts), Figure 1 - figure supplement 3 (fixation artifact at various PFA concentrations), and Figure 1 - figure supplement 4 (fixation artifact upon treatment of 4% PFA supplemented with 0.2% GA).

We agree that testing more cell fixation protocols such as cryofixation on LLPS appearance would be interesting. However, given the complexity of novel fixation protocols like cryofixation and highly specialized equipment and reagents they require, testing widely how different fixation methods might change LLPS appearance would be a tremendous amount of work that is enough to fill a separate paper. These experiments would be much more appropriate for a separate study in the future.

Reviewer #3 (Public Review):

“Understanding whether/how fixation methods affect the detection of biomolecular condensates is of broad interest given the importance of LLPS in regulating different aspects of cell biology. However, in this manuscript, the authors use only paraformaldehyde as a fixation method and study only fluorescently-labelled IDR proteins. The work would benefit from a comparison between living cells and cells fixed with other fixation methods.”

We appreciate the reviewer for this suggestion and agree that more fixation protocols should be investigated. As described in Response 1 and Response 18, besides examining PFA fixation, we have quantified how fixation using 4% PFA supplemented by 0.2% GA changes LLPS appearance in cells. We saw statistically significant changes in all the LLPS-describing parameters upon PFA/GA treatments. Please see Response 1 and Response 18 for details. Our new data and discussion have been added to the revised manuscript in Paragraph 3 on Page 3 and in Figure 1 - figure supplement 4.

“In addition, it would be useful to test the impact of these fixation methods on the detection of endogenous proteins or IDR proteins without fluorescent tag.”

We appreciate the reviewer for this suggestion and have now investigated an endogenous IDR-containing protein in the revised manuscript. Specifically, we quantified the effect of 4% PFA fixation on endogenously expressed EWS::FLI1 in an Ewing sarcoma cell line A673, which is an oncogenic fusion transcription factor that causes Ewing sarcoma (Grünewald et al., 2018) and known to form local, high-concentration hubs at target genes associated with GGAA microsatellites (Chong et al., 2018). We previously Halo-tagged endogenous EWS::FLI1 in A673 cells using CRISPR/Cas9-mediated genome editing (Chong et al., 2018). Here, we quantified the effect of PFA fixation on endogenous EWS::FLI1 puncta in this knock-in cell line and found no significant difference in the distribution of EWS::FLI1 upon fixation. This result suggests that PFA fixation does not change the intracellular distribution of all proteins. Our new data and discussion have been added to the revised manuscript in Paragraph 1 on Page 8 and in Figure 3C.

Unfortunately, testing fixation artifacts of IDR-containing proteins without a fluorescent tag has been infeasible as we rely on fluorescence from a tag on the protein of interest to quantitatively compare LLPS appearance in live and fixed cells. Although we have considered using non-fluorescent methods, e.g., phase contrast microscopy, to visualize putative LLPS in cells, its lack of specificity in imaging proteins or cellular structures makes the type of quantification we do for fixation artifact characterization inaccessible.

Reviewer #3 (Public Review):

The authors compare the detection of biomolecular condensates in living cells overexpressing fluorescently tagged IDR proteins and upon fixation with paraformaldehyde (PFA). Given that they observe differences in the number and size of the condensates in the fixed versus living cells the authors conclude that the fixation method can introduce an artifact in the visualization of these condensates. Next, through kinetic modeling simulations, the authors propose a model in which the extent of the artifact introduced by PFA fixation correlates with the strength of the protein-protein interaction: artifacts are lower when the protein‐protein interactions are stable and less dynamic compared with the overall fixation rate. Based on their comparative analysis of PFA fixation and the kinetic modeling the authors strongly recommend caution in the interpretation of data obtained in PFA-fixed cells and suggest that parallel studies with living cells should be performed.

Understanding whether/how fixation methods affect the detection of biomolecular condensates is of broad interest given the importance of LLPS in regulating different aspects of cell biology. However, in this manuscript, the authors use only paraformaldehyde as a fixation method and study only fluorescently-labelled IDR proteins. The work would benefit from a comparison between living cells and cells fixed with other fixation methods; in addition, it would be useful to test the impact of these fixation methods on the detection of endogenous proteins or IDR proteins without fluorescent tag.

Are the additional bands from the cleaved GFP tag? Again, a WB against HY5, SPA, and GFP may elucidate these bands.

Author Response

Reviewer #3 (Public Review):

The authors use two-photon imaging to visualize various axonal organelle populations that they have virally labeled with fluorescent proteins, including DCVs and late endosomes/ lysosomes. The latter topic is a bit contentious, as the authors use two labels that tag potentially overlapping and not highly specific markers so that the nature of the tagged organelle populations remains unclear. Notably, the authors also have previously published a detailed account of how DCVs traffic in vivo, so the novelty is mostly in comparing the behavior of different organelles and the potential influence of activity.

Overall, the reported results mostly corroborate the expectations from previous in vitro and in vivo work on these organelles and other cargoes, performed by the authors and their collaborators, as well as in many other laboratories:

(i) Different organelles have different transport behaviors regarding speed, the ratio of anterograde to retrograde moving organelles, etc.

(ii) Organelles move in different ways when they pass specific anatomical landmarks in the axons, such as presynaptic terminals.

(iii) Activity of a neuron (here measured by calcium imaging) can impact the measured transport parameters, albeit in a subtle and mechanistically not well-defined manner. The chosen experimental design precludes a more detailed analysis, for example of the precise movement behavior (such as defining the exact pausing/movement behavior of organelles, which would require higher imaging speeds) or of a correlation of different organellar behavior at synaptic sites or during activity (which would require three-channel simultaneous imaging of two organelle classes plus a synaptic or activity marker).

In summary, this publication uses sophisticated in vivo labeling and imaging methods to corroborate and complement previous observations on how different axonal organelles move, and what influences their trafficking.

We thank the reviewer for the time dedicated to our manuscript. We are thankful for the critical and specific comments, which allowed us to further improve our manuscript. We agree that it would have been beneficial to have higher frame rates and there instead of two imaging channels. However, this would have further added technical complexity to an already complex experimental setup resolving fluorescent puncta with sizes below the resolution limit. And we are convinced that all our main conclusions are justified based on the imaging settings in the current data sets.

Reviewer #3 (Public Review):

The authors use two-photon imaging to visualize various axonal organelle populations that they have virally labeled with fluorescent proteins, including DCVs and late endosomes/ lysosomes. The latter topic is a bit contentious, as the authors use two labels that tag potentially overlapping and not highly specific markers so that the nature of the tagged organelle populations remains unclear. Notably, the authors also have previously published a detailed account of how DCVs traffic in vivo, so the novelty is mostly in comparing the behavior of different organelles and the potential influence of activity.

Overall, the reported results mostly corroborate the expectations from previous in vitro and in vivo work on these organelles and other cargoes, performed by the authors and their collaborators, as well as in many other laboratories:<br /> (i) Different organelles have different transport behaviors regarding speed, the ratio of anterograde to retrograde moving organelles, etc.<br /> (ii) Organelles move in different ways when they pass specific anatomical landmarks in the axons, such as presynaptic terminals.<br /> (iii) Activity of a neuron (here measured by calcium imaging) can impact the measured transport parameters, albeit in a subtle and mechanistically not well-defined manner. The chosen experimental design precludes a more detailed analysis, for example of the precise movement behavior (such as defining the exact pausing/movement behavior of organelles, which would require higher imaging speeds) or of a correlation of different organellar behavior at synaptic sites or during activity (which would require three-channel simultaneous imaging of two organelle classes plus a synaptic or activity marker).

In summary, this publication uses sophisticated in vivo labeling and imaging methods to corroborate and complement previous observations on how different axonal organelles move, and what influences their trafficking.

unnecessary use of br tag (breaks)

i believe there should be more space between the heading tag and the content use after it. and the text size need to bigger for the content like month names, as i see in reference image.

its not look same as image reference its better if you use heading tag to make month name as heading.

Alternate thesis for why countries and cities vie to host money-losing events like the World Cup and the Olympics: grift.

With the necessary need for building infrastructure, there's easy and ample opportunity for cooking the books and pushing cash flow into the pockets of contractors and political figures as well as into the pockets of the governing bodies and their officials.

Cross reference FIFA bribery

Some of the money may go into the local economy and workers which is good, but who's really benefitting here? Where is the money going? Who is footing the loss? It can't all be written off to goodwill.

looks and nice and you have mentioned nicely

most of the time I use the "Div" tag instead of "article". I feel it gets easy to work with "Divs". "article " is not the issue still

You can use small tag to make this sentence smaller.

You can use h3 tag instead of strong tag.

You can use h3 tag instead of strong tag.

You can use h3 tag instead of strong tag.

You can use h3 tag instead of strong tag.

You can use h3 tag instead of strong tag.

You can use h3 tag instead of strong tag.

You can use h3 tag instead of strong tag.

You can use h3 tag instead of strong tag.

You can use h3 tag instead of strong tag.

you can use the "main" tag here for the web content. It'll be good to have both header and footer too.

You can use this h1 tag in header section.

ArtículoHDBIOcolores

Zotero

Hello

Author Response

Reviewer #2 (Public Review):

Grasses develop morphologically unique stomata for efficient gas exchange. A key feature of stomata is the subsidiary cell (SC), which laterally flanks the guard cell (GC). Although it has been shown that the lateral SC contributes to rapid stomatal opening and closing, little is known about how the SC is generated from the subsidiary mother cell (SMC) and how the SMC acquires its intracellular polarity. The authors identified BdPOLAR as a polarity factor that forms a polarity domain in the SMC in a BdPAN1-dependent manner. They concluded that BdPAN1 and BdPOLAR exhibit mutually exclusive localization patterns within SMCs and that formative SC division requires both. Further mutant analysis showed that BdPAN1 and BdPOLAR act in SMC nuclear migration and the proper placement of the cortical division site marker BdTANGLED1, respectively. This study reveals a unique developmental process of grass stomata, where two opposing polarity factors form domains in the SMC and ensure asymmetric cell division and SC generation.

The findings of this study, if further validated, are novel and interesting. However, I feel that the data presented in the current manuscript do not fully support some crucial conclusions. The lack of dual-color images is the weakest point of this study. If it is technically impossible to add them, alternative analyses are needed to validate the main conclusions.

1) Is BdPOLAR-mVenus functional? Although the authors interpret that weak BdPOLAR-mVenus expression partially rescued the bdpolar mutant phenotype in Fig. S4D, the localization pattern visualized by BdPOLAR-mVenus may not be completely reliable with this partial rescue activity.

This is indeed a valid point. The partial complementation of weakly expressing translational reporters (Figure 3–figure supplement 1D) and the weak effect of BdPOLAR-mVenus overexpression lines (Figure 3–figure supplement 1J) at least suggest partial functionality which is strongly dependent on dosage. Yet the localization pattern and the temporal dynamics might indeed not fully reflect the spatiotemporal dynamics of the endogenous BdPOLAR. This criticism is, however, true for any transgenic reporter line–even when fully complementing–as the requirement for dosage, stability, and turnover likely varies strongly between different protein classes and functions.

Nonetheless, we have added a sentence on p. 7, which mentions this potential caveat.

2) Regardless of the functionality of the tagged protein, the authors need to provide more information on their localization. For example, is there a difference in polarity pattern depending on expression level? Does overexpressed BdPOLAR-mVenus invade the BdPAN1 zone? In such cases, might the loss of BdPOLAR polarity in the bdpan1 mutant be a side effect of overexpression, not PAN1 exclusion? Does BdPOLAR expression (no tag) show a dose-dependent effect, similar to the mVenus-tagged protein?

The difference in polarity patterns in bdpan1 mutants and wild-type does not depend on expression level. BdPOLAR-mVenus was crossed into bdpan1 and mutant and wild-type siblings in the F2 generation were analyzed. This means that the data presented in Fig. 3E and F show exactly the same transgene insertion line in wt and bdpan1 and were imaged with the same setting for comparability. Therefore, the difference in localization is not due to different expression levels but indeed reflects a PAN1-dependent effect.

To address if BdPOLAR without a tag is also sensitive to dosage, we have generated an untagged complementation line that includes the untagged, genomic locus of BdPOLAR including promoter (-3.1kb) and terminator (+1.1kb). Yet, even though this construct is much better at rescuing the mutant, we still see remaining defects in T0 lines (Figure 3–figure supplement 1K) suggesting that even without a tag we cannot fully recapitulate wild-type functionality. Yet, to actually measure protein levels of untagged BdPOLAR, we would need to raise an antibody against BdPOLAR, which we think is clearly out of the scope of this study.

3) A major conclusion of this study was that the polarity domains of BdPOLAR and BdPAN1 are mutually exclusive. However, not all the cells in the figures were consistent with this statement. For example, the BdPOLAR signals at the GMC/SMC interphase appear to match BdPAN1 localization (compare 0:03 s in Video 1 and 0:20 s in Video 2 [top cell]). The 3D rendered image in Fig. 2F shows that BdPOLAR is excluded near the GMC on the front side of the SMC, where BdPAN1 is not localized. Some cells did not exhibit polarization (Fig. 3A, bottom left; Fig. 3E, bottom left). The most convincing data are the dual-color images of these two proteins. Otherwise, a sophisticated image analysis is required to support this conclusion.

We agree that dual-color image analysis would have provided the most convincing data. As mentioned in our answers to the reviewing editor and reviewer 1, we have generated a dual marker line (BdPAN1p:BdPAN1-CFP; BdPOLARp:BdPOLAR-mCitrine), yet the BdPAN1-CFP signal (compared to mCitrine signal) was too weak to visualize the proximal BdPAN1 domain.

This issue was also raised by reviewer 1 and deemed an essential revision. To determine how BdPOLAR and BdPAN1 relate spatially to each other, we have added data in Figure 2E where we manually traced mature SMC outlines to determine BdPOLAR-mVenus and BdPAN1-mCitrine occupancy along the SMC’s circumference. This confirmed that the polarization is indeed opposite yet not perfectly reciprocal (see details above, Essential Revisions #1).

Finally, we realized that the 3D image renderings were more confusing than helpful and we removed them from the revised version.

4) Another central conclusion was that BdPOLAR was excluded at the future SC division site, marked with BdTANGLED1. However, these data are also not very convincing, as such specific exclusion cannot be seen in some figure panels (e.g., Fig. 3A, bottom left; Fig. 3E, all three cells on the left). If dual-color imaging is not feasible, a quantitative image analysis is needed to support this conclusion.

As for point 3, this was also criticized by reviewer 1 and deemed an essential revision by the reviewing editor.

To determine whether the absence of BdPOLAR signal and the presence of BdTAN1 signal colocalize, we again manually traced mature SMC outlines to determine BdPOLAR-mVenus and BdTAN1-mCitrine occupancy along the SMC’s circumference. We plotted the relative average fluorescence intensity in Figure 4G-I nicely showing that BdTAN1 indeed resides in the BdPOLAR gaps above and below the GMC (again, details above, Essential Revisions #2).

5) I could not find detailed imaging conditions and data processing methods. Are Figs. 2B and 2E max-projection or single-plane images? If they are single-plane images, which planes of the SMC are observed? In addition, how were Figs. 2C and 2F rendered? (e.g., number of images, distance intervals, processing procedures). This information is important for data interpretations.

We agree that we might not have provided sufficient imaging condition details and have added more details regarding image acquisition in the method part (p. 20). We always use a consistent depth and show the midplane of SMCs. As mentioned above, we removed Figs. 2C and 2F and the supplemental movies as these data did not seem to be helpful.

6) [Minor point] The authors should clearly describe where BdPAN1 is expressed and localized. Is it expressed in the GMC and localized at the GMC/SMC interface? Alternatively, is it expressed and localized in the SMC?

BdPAN1 is expressed throughout the epidermis but starts to strongly accumulate at the GMC/SMC interface. According to the literature (Cartwright et al 2009 with immunostainings against ZmPAN1 and Sutimantanapi et al. 2014 with PAN1 and PAN2 reporter) and our own observations (Fig. S3), this accumulation occurs in the SMC rather than in the GMC. In Fig. S3A, third panel, second GMC from the top, for example, one can see that the early PAN1 polarity domain expands beyond the GMC/SMC interface suggesting that it is indeed forming in SMCs rather than in GMCs. We have specified this in the text more clearly now (p. 5).

Reviewer #2 (Public Review):

Grasses develop morphologically unique stomata for efficient gas exchange. A key feature of stomata is the subsidiary cell (SC), which laterally flanks the guard cell (GC). Although it has been shown that the lateral SC contributes to rapid stomatal opening and closing, little is known about how the SC is generated from the subsidiary mother cell (SMC) and how the SMC acquires its intracellular polarity. The authors identified BdPOLAR as a polarity factor that forms a polarity domain in the SMC in a BdPAN1-dependent manner. They concluded that BdPAN1 and BdPOLAR exhibit mutually exclusive localization patterns within SMCs and that formative SC division requires both. Further mutant analysis showed that BdPAN1 and BdPOLAR act in SMC nuclear migration and the proper placement of the cortical division site marker BdTANGLED1, respectively. This study reveals a unique developmental process of grass stomata, where two opposing polarity factors form domains in the SMC and ensure asymmetric cell division and SC generation.

The findings of this study, if further validated, are novel and interesting. However, I feel that the data presented in the current manuscript do not fully support some crucial conclusions. The lack of dual-color images is the weakest point of this study. If it is technically impossible to add them, alternative analyses are needed to validate the main conclusions.

1. Is BdPOLAR-mVenus functional? Although the authors interpret that weak BdPOLAR-mVenus expression partially rescued the bdpolar mutant phenotype in Fig. S4D, the localization pattern visualized by BdPOLAR-mVenus may not be completely reliable with this partial rescue activity.<br /> 2. Regardless of the functionality of the tagged protein, the authors need to provide more information on their localization. For example, is there a difference in polarity pattern depending on expression level? Does overexpressed BdPOLAR-mVenus invade the BdPAN1 zone? In such cases, might the loss of BdPOLAR polarity in the bdpan1 mutant be a side effect of overexpression, not PAN1 exclusion? Does BdPOLAR expression (no tag) show a dose-dependent effect, similar to the mVenus-tagged protein?<br /> 3. A major conclusion of this study was that the polarity domains of BdPOLAR and BdPAN1 are mutually exclusive. However, not all the cells in the figures were consistent with this statement. For example, the BdPOLAR signals at the GMC/SMC interphase appear to match BdPAN1 localization (compare 0:03 s in Video 1 and 0:20 s in Video 2 [top cell]). The 3D rendered image in Fig. 2F shows that BdPOLAR is excluded near the GMC on the front side of the SMC, where BdPAN1 is not localized. Some cells did not exhibit polarization (Fig. 3A, bottom left; Fig. 3E, bottom left). The most convincing data are the dual-color images of these two proteins. Otherwise, a sophisticated image analysis is required to support this conclusion.<br /> 4. Another central conclusion was that BdPOLAR was excluded at the future SC division site, marked with BdTANGLED1. However, these data are also not very convincing, as such specific exclusion cannot be seen in some figure panels (e.g., Fig. 3A, bottom left; Fig. 3E, all three cells on the left). If dual-color imaging is not feasible, a quantitative image analysis is needed to support this conclusion.<br /> 5. I could not find detailed imaging conditions and data processing methods. Are Figs. 2B and 2E max-projection or single-plane images? If they are single-plane images, which planes of the SMC are observed? In addition, how were Figs. 2C and 2F rendered? (e.g., number of images, distance intervals, processing procedures). This information is important for data interpretations.<br /> 6. [Minor point] The authors should clearly describe where BdPAN1 is expressed and localized. Is it expressed in the GMC and localized at the GMC/SMC interface? Alternatively, is it expressed and localized in the SMC?

Reviewer #2 (Public Review):

The study aims to characterize the role of lncRNA H19 in senescence and proposes a mechanism involving CTCF and the activation of p53. The authors suggest that H19 loss induces let7b-mediated repression of EZH2, which is a critical component in the regulation of senescence-associated genes. Additionally, the authors state that H19 is required for inhibition of senescence by the mTOR inhibitor rapamycin.

The experiments appear to be performed to a high standard, and the individual observations, and conclusions about the importance of the individual players in senescence appear solid. For example, the authors convincingly show that H19 decreases in expression in aged cells/tissues and that its knockdown leads to entry into senescence. These results are consistent with recent studies in other systems (e.g., ref 38). Also, the knockdown of CTCF convincingly leads to senescence. However, these observations are largely not very surprising/novel. The premise of the manuscript is a connection between these components into a particular "axis" that regulates entry into senescence. This connection between the different regulators studied (H19, CTCF, EZH2, p53), and in particular, their specificity, which is key to the proposed "axis" remains insufficiently supported, and many of the results, unfortunately, appear to be over-interpreted.

Major comments

1. In Figure 1, the authors claim that H19 levels are reduced during aging in vitro and in vivo and that H19 levels are maintained by rapamycin treatment. To state the connection between H19 and rapamycin and its relation to aging, there is a need to show what happens in "young" cells treated with rapamycin.

Furthermore, the authors state that H19 "is essential for the inhibitory effect of rapamycin on cellular senescence". There doesn't appear to be sufficient evidence to support such a claim; additional data emphasizing the direct connection between H19 and rapamycin is needed - e.g., show that in H19-null cells rapamycin does not affect senescence.

2. CTCF is a general regulator involved in various cellular processes and supporting progression through the cell cycle; therefore, its perturbation can lead to global effects on cell health that are not necessarily related to H19. The data shown in figure 2 is insufficient to indicate a direct correlation between CTCF and H19. This will require showing that mutating specifically the CTCF binding sites near H19 affects senescence.

The same applies to the connection between H19 and let-7b shown in Figure 5. It is not very surprising that let-7b, a general antagonist of proliferation, positively regulates senescence. Here as well, the direct connection to H19 is weak. Can the authors rescue the cells that enter senescence following H19 depletion by H19 expression? If so - is this rescue capacity lost when let-7 sites are mutated? Is it possible to rescue by expressing an artificial let-7 sponge instead of H19? Otherwise, let-7b could very well be another factor related to senescence and/or regulated, but not the main mediator of the effects of H19, or part of an axis that includes H19, as proposed in the manuscript.

3. In figures 2d,3f,5i/j the authors present only representative tracks and regions from CUT&Tag-experiments, and its not clear to what extent these changes are significant when considering genome-wide data, replicates etc., and so these data are uninterpretable. This is important, as these panels are used as evidence for specific connections between members of the axis. The authors should provide a statistical test for all the regions in the genome, based on replicates, and show that these changes are significant to use these data to support their model. Otherwise, the specific connection between CTCF and H19 remains weak, and the specific change in p53 regulation of CTCF in the context of senescence is not convincing. In any case, the number of replicates and the QC of the data should be presented, and the data should be made available to the reviewers.

4. The authors state in the Discussion that the mechanism that lead to decreased H19 expression as part of the senescence program consists of two phases: an acute response driven by p53 activation and a prolonged response dictated by the loss of CTCF. There doesn't appear to be enough evidence to support this claim, as the individual experiments don't measure any such bi-phasic phenomena.

please update the sample code. I have fixed it and am sending on slack

good call using the

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tag to break up the content a bit.

This closing tag is unnecessary you can remove it.

missing head and closing head before the body tag

https://hypothes.is/search?q=tag%3A%27etc556+etcnau%27

Randomly ran across a great tag full of education resources...

Seems to be related to this class:<br /> ETC 556 - Contexts And Methods Of Technology In Adult Education

Description: This course is designed for adult educators in the various contexts, including: higher education, military, non-profit, health and business settings. Through research, readings and collaborative activities, students will gain an understanding of various adult learning methods that include, but are not limited to, training, professional development, performance improvement, online and mobile learning. Letter grade only.

https://catalog.nau.edu/Courses/course?courseId=011553&catalogYear=2223

comment tag again could be used to differentiate which closing div relates to which div class

Without using the <br> tag you can achive the new line by adjusting the width of the block.

It's better to have some space between each tag in order to understand the code easy(i.e., visibility must be good).

You may want to add small tag to this sentence.

take off the padding on the li and give it to the a tag so you can hover less over the word to select the link, makes it better for accessibility.

Reviewer #3 (Public Review):

This manuscript will be of interest primarily to researchers in the field of NADPH oxidases (NOXs) but also to those interested in the wider ferric reductase superfamily, also comprising members of the six-transmembrane epithelial antigen of the prostate enzymes (STEAPs). More limited interest may be expressed by investigators of ferredoxin - NADP reductases, resembling the dehydrogenase region (DH) of NOXs, expressing lesser "visibility" in the structure described in the paper. Considering the fact that NOXs are essentially electron transport machines from NADPH to dioxygen, along a multi-step redox cascade, those interested in hydride and electron transfer, at a more conceptual level, might also want to have a look at the paper. Elucidating structures of NOXs are still rare achievements, with only four published papers, so far (one coming from the group of the present main author) and, thus, any new publication profits from the aura of novelty.

Introduction<br /> This manuscript offers a detailed and in depth description of the structure of the catalytic core of the human phagocyte NADPH oxidase, NOX2, in heterodimeric association with the protein p22phox. The phagocyte NADPH oxidase is responsible for the production of reactive oxygen species (ROS), the primary molecule of which is the superoxide radical (O2.-), derived by the one-electron reduction of molecular oxygen by NADPH. NOX2 belongs to the NOX family, consisting of 7 members (NOX 1-5, and DUOX1 and DUOX2), sharing common structural characteristics but expressing a wide variety of functions. The principal but not the only function of NOX2 is as a source of ROS for the killing of pathogenic microorganisms (bacteria, fungi, protozoa) engulfed by phagocytes in the course of innate and acquired immunity.

The structures of C. stagnale NOX5, and that of murine and human DUOX1 were determined by X-ray crystallography (NOX5) and cryo-EM (DUOX1). As sources of potentially dangerous auto-toxic ROS, NOXs are subject to strict functional regulation. Whereas Nox5 and the DUOXs are regulated by Ca2+, NOXs 1, 2, and 3 are regulated by several cytosolic proteins, that associate with the Nox2-p22phox dimer forming the active O2.-generating complex. The paramount model of cytosolic regulation is Nox2 and the "dream" of structure investigators is to elucidate the structure of NOX2 in both resting and activated states.

Achievements<br /> Note: When this paper was received for review, this reviewer was not aware of any publication dealing with the structure of human Nox2. However, on October 14, 2022 a paper was published on line, dealing with the structure of Nox2 (S. Noreng et al., Structure of the core human NADPH oxidase Nox2, Nature Communications (2022)13:6079). This review will not discuss the present manuscript in relation to the paper by S. Noreng et al.

This manuscript is successful in describing the structure of the NOX2-p22phox heterodimer using cryo-EM methodology. In order to compensate for the small size of the complex, use was made of the Fab of a monoclonal anti-Nox2 antibody binding an anti-light chain tagged nanobody. In order to mimic as much as possible the milieu of NOX2-p22phox in the phagocyte membrane bilayer, the authors reconstitute the quaternary complex in a nanodisc, using soybean phosphatidylcholine (PC) and a membrane scaffold protein (MSP). To the best of my knowledge, this is the first report of studying a NOX in a nanodisc, for both function and structure. Peptidiscs were used in determining the structure of human DUOX1 by a group led by the main author of this paper, but nanodiscs offer the advantage of adding a phospholipid chosen by the investigator. The purified nanodiscs incorporating the quaternary complex led to successful structure determination of the transmembrane domain (TMD), extracellular and intracellular loops, inner and outer hemes, distances between hemes and FAD to inner heme, and a hydrophilic tunnel connecting the exterior of the cell to the oxygen-reducing center of NOX2. The structure of the dehydrogenase region (DH) was less well defined; the FAD-binding domain (FBD) was more visible than the NADPH-binding domain (NBD). The structure of p22phox and the interface between Nox2 and p22phox are well described.

The mutations in NOX2 and p22phox causative of the deficient bactericidal function in Chronic Granulomatous Disease are related in detail to the location and role of the mutated residues as revealed by the solved structure.<br /> The authors make it clear that the structure, as presented, is in the resting state. The distances between hemes are suitable for electron transfer but the distance between FAD, in the FBD, and the inner heme is too large for transfer. The poor quality of the obtained structure of the DH (especially, the NBD), even after local refinement focusing, suggests its flexibility (mobility?) relative to the TMD and that, in NOX2, the DH is "displaced" relative to the TMD, when compared to the situation in the activated (by Ca2+) DUOX1. The mobility of NBD in NOX2 also results in weak interaction with FBD, making hydride transfer from NADPH to FAD inefficient

A major achievement of the work described in this manuscript is what I believe to be the first description of the activation of recombinant NOX2-p22phox in a nanodisc, to generate O2.-, when activated by a trimeric fusion protein (trimera), consisting of the functionally important parts of the three cytosolic components, p47phox, p67phox, and Rac (see Y. Berdichevsky et al., J. Biol. Chem. 282, 22122-22139, 2007). This proves that the resting state structure of NOX2-p22phox has all that is needed to be converted to the activated state. The fact that the nature of the phospholipid in the nanodisc can be varied and that this is known to have a major effect on the affinity of the trimera for NOX2-p22phox, offers additional advantages.

Weaknesses<br /> A weakness of this, otherwise impressive work, is the difficulty for readers who are not sufficiently "structure educated" to fully understand the "displacement" of the DH of NOX2, shown in the NOX2/DUOX1 overlay (Figure 5). The meaning of "centers of mass" of FBD and FAD, in Figures 5C and 5D, respectively, is not properly explained.

Yet another weakness is the much too vague wording of the change in NOX2 conformation from the resting to the activated state by cytosolic factors as "the cytosolic factors might likely stabilize the DH of NOX2 in the "docked" conformation which is similar to that observed in the activated DUOX1 in the high-calcium state". First, the evidence from biochemical studies of NOX2 activation indicates clearly distinct targets of individual cytosolic components and not a "block" action. There is also support for the conformational change being the result of the action of a single cytosolic component (p67phox), with the other cytosolic components acting as carriers or activators of one cytosolic component by another, such as Rac-GTP acting as a carrier and inducer of a conformational change in p67phox (see J. El-Benna and P.M-C. Dang, J. Leukoc. Biol. 110, 213-215, 2021, and E. Bechor et al., J. Leukoc. Biol. 110, 219-237, 2021). Also, the concept of "docking of the DH to the TMD" seems like an oversimplification of the many locations and partners of such "docking" and ignores the possible multiple consequence of such docking. Even before the appearance of structural studies of NOXs, revealing precise distances between redox stations (NADPH-FAD; FAD-inner heme; inner heme - outer heme), as first reported for C. stagnale Nox5, by F. Magnani et al., Proc. Natl. Acad. Sci. U.S.A. 114, 6764-6769, 2017, a shortening of the distance between an electron donor and acceptor at specific locations in the redox cascade was proposed. The most popular was the NADPH - FAD hydride transfer, based on structural work by P.A. Karplus on Ferredoxin - NADP reductases, the accepted model for the DH of NOXs.

An unfair request for an unachieved task<br /> Of course, the dream of those hoping for a structure-based response to solving the molecular mechanism of NOX activation is to see the structure of the activated NOX2 in complex with three cytosolic components. The compelling finding in the present manuscript that a nanodisc-embedded recombinant NOX2-p22phox can be activated to ROS production by the use of a [p47phox-p67phox-Rac] trimera (replacing three cytosolic components) will provoke in all the readers the wish to see the structure of such a complex. The size of the trimera with a GFP tag (108 kDa) might make the use of the anti-Nox2 Fab and anti-light chain nanobody, unnecessary. Prenylation of the trimera at the Rac moiety is bound to markedly enhance its affinity for the phospholipids in the nanodisc and is likely to generate a more stable complex, most suitable for cryo-EM (see A. Mizrahi et al., J. Biol. Chem. 285, 25485-25499, 2010).

Is there a way to search for your replies to someone's public annotations?

Currently, they don't show up when I search my user name and the tag I used in the reply. Is there an elegant way to search for these annotations and my reply to them?

I agree with Sahil. I think creating a link to the homepage by placing the img inside an anchor tag would be ideal .

This probably could have been an h2 tag, there will be alot of contrast between Assignment E and your name with it being a paragraph.

you don't actually need the div class= "image" also I think it's missing a closing tag.

Not totally sure why you have an open and closed paragraph tag.

You can use h tag instead of p.

You can change this to h2 tag.

You may want to change this content to article and add h2 tag, so user can understand what the content describes.

comments for tag: undefined vs. null: Technically this is undefined (unset, !diff) vs. true (diff), but it's similar enough that don't need a separate tag just for that.

annotation meta: may need new tag: undefined/unset vs. null/set

MiguelAngelLópezRodríguez

FernandoMoctezumaSoto

you can use list tag instead of using too more br tag

This tag is used very often.

nav tag is good for list instead of p tag

A small tag would give more context to the function of the element

Both Jonathan and Mina keep their journals in shorthand, and yet what we read here is in complete sentences. And Dr. Seward's Diary is spoken into a phonograph. We are experiencing this text very differently from how it is created. We combined with the several posts that contain correspondence that was never opened by or delivered to the intended experience (see Unopened or Undelivered tag), there is much of this story that we experience differently from the characters within it.

This comment is a good idea. Just looks like a slight typo in the closing tag.

might wrap this in a header tag to indicate its your title section

missing its closing tag

I would pay attention to the semantic coding of this section. I'm not sure if a single image would make sense as an article, especially since article typically requires a heading. I would personally just tag it as a figure (that way you can also attach a caption in case it doesn't load) and if you're worried about styling apply a div.

Reviewer #2 (Public Review):

The goal of this study was to understand the molecular mechanism of how transcription factor DUX4, which has a role in cancer, inhibits the induction of genes stimulated by interferon-gamma. The authors achieved this goal, and their results mostly support their conclusions. They found that DUX4, in their experimental model, interacts with STAT1, thereby decreasing STAT1 and Pol-II recruitment to sites of gene transcription.

The present study has many strengths: The topic is of broad interest, the findings are novel and intriguing, the experiments are well-designed and controlled, the data, with one exception, is carefully interpreted, and the manuscript is very well-written.

Two major weaknesses were identified. One is that all experiments, except Figure 6, rely on one experimental setup, which is a human skeletal muscle cell line with an integrated doxycycline-inducible transgene. The concern is that both the treatment of cells with the drug doxycycline and the fact that signaling pathways could be disrupted in this (immortalized?) cell line could lead to artifacts that skew results. Indeed, results in Figure 4C indicate that total STAT1 is completely localized in the nucleus even prior to interferon stimulation when it should be in the cytoplasm. The other weakness is the use of the DUX4-C-terminal-domain (DUX4-CTD) mutant for the majority of the mechanistic experiments. The concern here is that although the phenotype of ISG repression is observed in this truncated mutant, important regulatory domains could be missing that modulate the interaction with STAT1 or other proteins. Is the NLS added after the flag tag identical to the endogenous NLS? Related, I disagree with the interpretation of Figure 4C that "this interaction happens within the nuclei of DUX4-CTC expressing cells". The interaction could happen prior to STAT1 shuttling to the nucleus.

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

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Referee #1

Evidence, reproducibility and clarity

This manuscript reports motility characteristics and load-bearing properties of three human kinesin-6 family proteins that function during late telophase/cytokinesis of mitosis. The authors report single molecule and multiple motor motility assays, and vesicle dispersion assays for the three motors. Because the kinesin motors are important for normal division, their motility characteristics are of interest to workers in the mitosis field. However, data presentation in this manuscript could be greatly improved, along with interpretations of functional differences based on kinesin-6 motility properties.

Major points are the following:

1. Quantitation and presentation of the data throughout the manuscript should be improved.

The criteria used for identifying fluorescent spots as single motors are not given. This is typically based on photobleaching experiments and fluorescence intensity measurements - the authors should show these data to validate that the motility reported is due to single motors.

A table should be included that shows the single molecule motility parameters that were analyzed and compared for the three motors, rather than just the dwell times for the assays shown in Fig. 1. Other motility characteristics should include run lengths, binding rates, detachment rates, and velocity. The percentage of time that the single motors move directionally, diffuse, or remain stationary should also be given.<br /> The authors refer to imaging rates (1 frame/50ms, p. 5), but do not state the total time of the assays, making the statements uninterpretable, as it is not clear what would be expected without knowledge of the total assay time. The authors also state that a slower imaging rate (1 frame/2 sec) was used to detect slow processive motility, but the logic underlying this statement is not clear, as a longer assay time should reveal the slow processive movement irrespective of the imaging rate. These statements should be clarified.<br /> The authors give the data for the dwell times in single motor assays and velocities in multiple motor assays as the mean + SEM, but the SD rather than SEM should be reported for these assays, given that the data are for individual single motors or individual gliding microtubules. The authors state the number of replicate experiments for the assays, but they should also state the number of data points that were obtained for each replicate. Further, they should evaluate the significance of differences in their data by giving P values obtained using appropriate statistical tests and indicate whether the differences among the motors are significant.<br /> The percentages of processive events (p. 5) are most likely dependent on the amount of inactive or denatured protein in a given preparation, rather than a motility property of the motor protein - this could be determined by analysis of whether the percentages differ from preparation to preparation of each motor and whether the mean+SD of the preparations of a given motor differs from the other motors. The statements by the authors on p. 8 that "the majority of proteins do not undergo unidirectional processive motility as single molecules but rather diffuse along the surface of the microtubule for several seconds" and "It is presently unclear why only a subset of kinesin-6 molecules are capable of directional motility (Figure 1 ..." are not meaningful, as they do not take into account the percentages of the kinesin-6 proteins that are inactivated or denatured during protein preparation.<br /> Again, given that inactive motors are produced during preparation of the proteins, it is not clear what the frequency of processive motility events means. If the authors think that the frequency of processive motility events is informative and a characteristic of each motor, they should present controls showing frequencies of processive motility events for specific well characterized motors. For example, does a control of kinesin-1 show 100% or only 95% processive motility events?<br /> For the multiple motor gliding assays, velocities are shown in Fig. 2 without controls demonstrating the dependence of the velocities on motor concentration in the assays - the gliding assays require dilution experiments to show that the velocities are within the linear range of motor concentration and do not fall within the range of higher concentrations in which motor gliding velocity is inhibited or lower motor concentrations in which the density of motors on the surface is too low to support processive movement. These control experiments of motor concentration vs velocity for the gliding assays should be shown for each of the three motors that was assayed. The authors should state whether the gliding velocities that were determined correspond to the Vmax for each of the motors that was assayed.

Again, the velocities given on p. 6 should include the SD and evaluation of the significance of the differences among the motors by obtaining P values.

Proteins for motility assays: Western blots of the purified proteins should be shown as a supplemental figure.

How are the motility characteristics of the three motors related to their spindle functions? This is the central point of the manuscript but is not clearly stated.

1. Functional assays should be relevant to motor function.

Given that the kinesin-6 motors under study are mitotic spindle motors that do not normally transport vesicles, it is not clear why the authors chose to show load dependence using peroxisome and Golgi dispersion assays, rather than assays of spindle function. The authors interpret peroxisomes and Golgi to differ in dispersion load, but this appears to be based on interpretations from assays of highly processive motors, kinesin-1 and myosin V, that function in vesicle trafficking, rather than quantitative data from appropriate controls showing that peroxisomes and Golgi can be dispersed by spindle motors that bear different loads. The problems inherent in the use of these assays for spindle motors are evidenced by the authors' observations on p. 6 that MKLP1- mNG-FRB and KIF20-mNG-FRB in midbodies could not be localized to peroxisomes by rapamycin. There are no data presented showing the dependence of dispersion on protein expression/presence in the cytoplasm, making the dispersion assays difficult to interpret.

The kinesin-6 motor functional tests would be more relevant if they involved mitotic spindle assays, rather than peroxisome or Golgi dispersion assays. It is not clear how the loads involved in peroxisome or Golgi dispersion are related to kinesin motor function in the spindle. What are the implications of low- vs high-load motors in the spindle? How do the authors envision that motor loads in spindles relate to loads borne by vesicle transport motors?

Minor points needed for clarity and reproducibility of the data:

Methods

Plasmids<br /> "MKLP1(1-711) lacks the insert present in KIF23 isoform 1" - the insert present in KIF23 isoform 1 but missing in MKLP1 (1-711) should be depicted/pointed out in Fig. S1 and information provided as to its predicted or actual structure.

"KIF20B contained the protein sequence conflict E713K and natural variations N716I and H749L "- the sites of these changes should be indicated in Fig. S1 and information provided as to their effects on predicted or actual structure.<br /> Protein purification: "MKLP1(1-711)-3xFLAG-Avi was cloned by stitching four oligonucleotide primer sequences together into a digested MKLP1(1-711)-Avitag plasmid" - please explain what this means: what do the four oligonucleotide primer sequences correspond to? if they are the 3xFLAG-Avi tags, why were four sequences stitched together instead of three?<br /> The figures showing the kymographs should include labeled X and Y axes, rather than scale bars.

The significance of the statement that "All motors displayed similar behaviors when tagged with Halo and Flag tags" is not clear, as the Halo and Flag tags were also C-terminal tags, like the 3xmCit tag.

The figures (Fig. 3-5) that contain grey-scale cell depictions would be more readily interpretable by others if they were labeled with the authors' classification of the dispersion phenotype.

Significance

This manuscript reports motility characteristics and load-bearing properties of three human kinesin-6 family proteins that function during late telophase/cytokinesis of mitosis. The authors report single molecule and multiple motor motility assays, and vesicle dispersion assays for the three motors. Because the kinesin motors are important for normal division, their motility characteristics are of interest to workers in the mitosis field. However, data presentation in this manuscript could be greatly improved, along with interpretations of functional differences based on kinesin-6 motility properties.

My expertise: motors, motor function in division, motility assays, microtubules

Because there is no maximum width specified, paragraph elements that are very long like this one show up as very long on the user's browser. This is not very readable.

When you use <span> tags here as an example, they do not render on the user's browser. Character entities must be used if you want to display reserved characters like < and >. See this for more information.

When you talk about how they use the align attribute wrong, they can't see the code you're talking about.

probably keeps the tag together.

annotation meta: may need new tag: no exact translation in other language