Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Provide a short summary of the findings and key conclusions (including methodology and model system(s) where appropriate). Please place your comments about significance in section 2.

In this manuscript, the authors describe their efforts to develop a methodology for determining time-resolved protein-protein interactions using quantitative mass spectrometry. With TRIP (time-resolved interactome profiling), they combine a pulsed bio-orthogonal unnatural amino acid labelling (homopropargylglycine, Hpg), CuAAC conjugation and biotin-streptavidin pulldowns to enrich at different timepoints and time-resolve by combining TMT labelling and LC-MS/MS (Figure 1). This technique is then applied to the maturation of the secreted WT and mutant thyroglobulin (Tg-WT, Tg-C1264R, Tg-A2234D) expressed in HEK293 and rat thyroid cells (FRT) and linked to hyperthyroidism. There, they identify a collection of ER resident proteins involved in protein folding/processing (e.g. chaperones, redox, glycans, hydroxylation) as well as degradation (e.g. autophagy, ERAD/proteasomes) (Fig. 2). Here the authors effectively use pulse-labelled form of TRIPs to highlight the different interactions formed with Tg-WT vs. Tg-mutants during biogenesis and secretion (or retention). The analysis found ~200 new interactions compared to previous studies along with about 40% of those identified previously. Differences in interactions were observed for mutants, which shown extended interaction with chaperones and redox processing pathways. While many interactions appeared as might be expected, the identification of membrane protein processing elements (e.g. EMC, PAT) was puzzling and raised some questions about the specificity within the protocol. Mutants enriched for CANX CALR and UGGT, suggesting prolonged association with glyco-processing factors. Interaction of C1264R with the ER-phagy factors CCPG1 and RTN3 was greater than WT. The authors note that their interaction correlated with that of EMC1 & 4, but it is not clear why that might be.

With interactors in hand, the authors complemented the TRIP protocol with siRNA KD of identified factors, to investigate any changes to secreted vs intracellular Tg upon loss. KD of NAPA (a-SNAP) and LMAN1 increased WT lysate (intracellular) Tg but not mutants. NAPA also reduced Tg-WT secretion. In contrast, KD of NAPA increased A2234D secretion while LEPRE1 increased C1264R (but not A2234D or WT), suggesting mutants have differential processing paths and requirements. KD of VCP increased secretion of both mutants. Some ER-phagy receptors were found among interactors (e.g. RTN3 in Tg-C1264R only) but often their KD had no impact on secretion (CCPG1, SEC62, FAM134B). NAMA observations were recapitulated in thyroid derived cell line (FRT). KD of TEX264 and VCP increased Tg-C1264 secretion while RTN3 KD in FRTs decreased Tg-C1264 secretion. This was in contrast to data from HEK293s for reasons that are not clear. Co-IP with TEX264 enriched for all Tg forms but more so for C1264R and A2234D - motivating the authors to propose selective targeting of Tg to TEX264 and the consideration of ER-phagy as a "major" degradative pathway during Tg processing.

Given the observations with siRNAs to VCP, the authors next use a selection of VCP inhibitors to ask whether secretion can be rescued upon pharmacological impairment of the AAA ATPase. They observed that ML-240, but interestingly not the more conventionally used CB-5083 or NMS-873, increased secretion of Tg-C1264R but not lysate. Inhibitors increased lysate but decreased the secreted fraction for Tg-WT (Fig 7). Finally, the authors used TRIP again in ML-240 treated Tg-C1264R expressing cells to look for changes to interactome with treatment - observed decreases to glycan and chaperone interactions, CANX and UGGT1, decreased interaction with DNAJB11 and C10, like that of WT. There was no apparent change to the UPR, although activation was not directly measured.

Major comments:

• Are the key conclusions convincing?

The TRIP methodology appears to be quite robust and should be a powerful strategy for this field and others going forward. The drawback will be the length of pulse required will limit the number/type of proteins to be monitored to ones with longer t1/2's. There were interesting interactions found with Tg and the mutants linked to hyperthyroidism, but cut and dry differences did not appear as obvious, even though strong "trends" appear to be present. The path from identifying interactors in a time-resolved manner to then following them up with targeted KD does provides some clarity, which is important. - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

The data regarding VCP silencing and pharmacological impairment appear clear but leave some questions outstanding in this reviewer's opinion. The lack of effect with the 2 highly selective inhibitors suggests that the underlying mechanism for switching fate of intracellularly retained Tg-C1264R towards secreted forms is not at all clear. ML-240 is an early derivative of DBeQ and reportedly impairs both ERAD and autophagic pathways, similarly to DBeQ. The differences between the VCP inhibitors' mechanism of action were not discussed, but perhaps should be elaborated upon, particularly in the matter of how ERAD and ER-phagy pathways might be being differentially affected. At the risk of asking for too many additional experiments, this reviewer would just prefer to see this fleshed out in a bit more detail. - Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.

Q1. The degree (if any) of Tg-C1264 aggregation during and/or detergent solubility do not appear to have been considered as a potential source of the increase in released secreted material (Figure 4, 5). Do Tg mutants partition into RIPA-insoluble fractions at all? That is to say.. is the total population of synthesized Tg being considered? A full accounting? Could the authors address this and if biochemical extraction data (via urea or high SDS) is available, include it to answer this concern.

Q2. Along the same lines, what does Tg-WT and mutant expression look like by microscopy? Is Tg-WT uniformly distributed while Tg-mutants appear in puncta... more aggregated - perhaps reflecting the increased engagement of chaperones and redox machinery? Changes in the pattern of Tg-C1264R mutant (e.g. w/ VCP KD or inhibition) would add additional support for the authors interpretation of improved secretion. If this data is at hand, including it might be worth consideration.

Q3. Does the level of Tg mutant expression in the FRT clones impact the profiles obtained by TRIP? (Figure 3). This is a question of gauging the relative saturation of QC machinery and how that might impact profiles from TRIP. Were clones expressing at different levels tested? Perhaps a brief discussion of this.

Q4. For Figure 3, the hour-long labelling period seems a bit long, compared with 3 hr of chase. Perhaps this reviewer missed this but how long does Tg take to mature and/or mutants to misfold and degrade? Is there any possibility to shorten this so that the profiles of labelled Tg could be more synchronized? If not, perhaps this could just be discussed.

Q5. It is curious that only ML-240 and not other well characterized inhibitors of VCP/p97, has an effect, as both are used far more often than ML-240. The authors do not really address this in detail but does it suggest that the ML-240 effect on VCP/p97 could be affecting different pathways, given the nature of this compound. Is this compound acting on Tg-C1264R maturation at the level of translation or post-translationally? If the latter, through what means?

Q6. Continuing from Q5.. At what point and where is VCP/p97 able to affect mutant Tg processing? In line 317, the authors seem to correlate increased VCP association with mutants to their increased secretion. It is not clear how this would result, as engagement with VCP would be in a compartment different to that which supports trafficking and secretion. Could the authors expand on how this might come about. This is also relevant to the ML-240 data in Figure 7. Moreover, VCP is associated with ERAD (as is HerpUD1) rather than ER-phagy and at least in the siRNA raw data, there are also effects from Derlin3 and FAF2 KDs.. both ERAD factors. Some clarity here would be appreciated.

Q7. There does not appear to be a direct demonstration of Tg-C1264R turnover by ER-phagy (via TEX264). Given the inconsistency with it not being detected by TRIP, while another receptor RTN3 was, but has not impact on Tg-C1264R secretion, perhaps including that data would go some way to demonstrating a fate of ER-phagy (at least partly) for this mutant.

Q9. The authors provide data that the UPR was not induced by ML-240 at 3hrs (10µM) (Figure 7, supplemental 1). This is in stark contrast to the results of Chou et al (2013) which the authors reference, reporting that ML-240 induced ATF4 and CHOP by 2 hrs at concentrations lower than used here (albeit a different cell type). While not exclusively UPR, could the authors address the potential activation of the integrated stress response (eIF2a phosphorylation, ATF4 and CHOP) in the FRT cells due to ML-240 treatment? If present, is there some link that could this provide an explanation for increased Tg-C1264R secretion? - Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

Any of the suggested experiments above all use reagents reported in the manuscript and so would presumably incur minimal cost and hopefully time. This reviewer is sympathetic to time and financial constraints and so discussion of the issue could suffice. - Are the data and the methods presented in such a way that they can be reproduced?

Yes. The methodology is explained in detail. - Are the experiments adequately replicated and statistical analysis adequate?

Yes. Relevant information is either in the figure legends or is provided in the source data.

Minor comments:

• Specific experimental issues that are easily addressable.
• Are prior studies referenced appropriately?

The references are generally appropriate, with a few exceptions of more general references used - Are the text and figures clear and accurate?

The text is clearly written, and the figures are clear. - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

A summary figure comparing the changing profiles of WT and C1264R and the factors implicated for them could be helpful.

Perhaps include common nomenclature for proteins as well (e.g. HSP5A - BiP, HSP90B1 - Grp94, etc..)

Line 317 - our is misspelled

Figure 4 - Supplemental Figure 1 - Legend has text referring to panels J and K, but Figure only goes up to F.

Significance

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.
• Place the work in the context of the existing literature (provide references, where appropriate).

Protein-protein interactions are often used to illustrate complexes and functionality, but these provide only snapshots, rather than "movies". There are many datasets out there exploring P-P interactions, but most if not all lack any temporal resolution for the interactions they report. The TRIP method described approaches this from the dynamic perspective - identifying the transient interactions formed by folding nascent chains with proteins that aid in their maturation and trafficking, or degradation. This represents an important technical advance in our ability to dynamically monitor protein interactions. The use of Tg mutants is valuable and perhaps this will lead to new perspectives on how to rescue it or other pathophysiological mutants with loss of function phenotypes.<br /> - State what audience might be interested in and influenced by the reported findings.

This work should appeal to a broad audience within cell biology, particularly as the TRIP technique is attempting to address a fundamental question - what interactions form during the biogenesis/lifetime of a protein. Moreover, the effort to try to understand the different interactions formed with pathologically relevant mutant proteins as a strategy to try to rescue functionality, is a valuable exercise of this approach. - Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

ER quality control

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

In the manuscript 'Time-Resolved Interactome Profiling Deconvolutes Secretory Protein Quality Control Dynamics' Wright et al. developed an approach for time-resolved protein protein interaction mapping relying on pulsed unnatural amino acid incorporation, protein cross linking, sequential affinity purification, and quantitative mass spectrometry named time-resolved interactome profiling (TRIP). The authors applied the TRIP method to compare the interactions of the secreted thyroid prohormone thyroglobulin (Tg) comparing the WT protein to secretion-defective mutations implicated in congenital hypothyroidism. They further employed an RNA interference screening platform (1) to investigate if (1) interactors identified via TRIP are functionally relevant for Tg protein quality control and (2) to identify factors that can rescue mutant Tg secretion. The screen was initially performed in HEK293 cells, but selected hits with a phenotype in HEK cells were then followed up in Fisher rat thyroid cells. Further functional validation was performed by pharmacologic inhibition of VCP, a hit from the RNAi screen with an effect on Tg lysate abundance and Tg secretion. While the authors present a comprehensive study including identification of protein-protein interactions using proteomics followed up by an RNA interference screen for functional validation, major comments need to be addressed for both the proteomics as well as the functional genomics aspects of the study (see comments below).

Major comments:

• The authors describe a new method for quantitative, temporal interaction mapping. The protocol involves two enrichment steps as well as several reactions including cross-linking of the samples as well as functionalization of the unnatural amino acids. Given all these steps, the authors should rigorously characterize the quantitative reproducibility of the experiment when performed in independent biological replicates. This is important because in the final quantitative MS experiment, the authors only use two biological replicates, which is too low especially for such an involved sample preparation procedure, which would expect to have a high variability between replicates. Given the low number of replicates and the unknown reproducibility of the quantification for this protocol, it is questionable at this point how reliable the quantification over the time course is.
• Compared to the previous dataset published last year, the authors discover an overlap in interactors, but also a huge discrepancy, with 96 previously identified interactors not detected in the current study, but 198 additional interactors identified. How do the authors explain the big differences between these datasets?
• For the temporal interaction analysis the authors describe differences in the temporal profiles of selected interactions comparing wt and mutant, however no statistical analysis is performed comparing wt and mutant interaction profiles across the time course. Furthermore the variability between the replicates for the temporal profiles is not shown and some of the temporal profiles appear to be noisy. A more rigorous statistical analysis should be performed including additional biological replicates to evaluate the changes over the time course, especially as the temporal interaction analysis is the novelty of this study.
• To functionally validate interactors derived from the TRIP analysis as well as to identify factors that can rescue mutant Tg secretion the authors developed an RNA interference screen. There are a number of aspects that need to be addressed/clarified for this part of the study.
• While the authors validate the stable cell lines expressing the nanoluciferase tagged Tg and the linearity of luminescence signal in lysate and media carefully, they do not validate their platform in combination with the RNAi knockdown strategy. The authors should select genes as positive controls that are expected to modulate Tg secretion and demonstrate that the knockout of these positive controls indeed results in changes in Tg secretion in their system.
• For the screen the authors select 167 Tg interactors and PN (Proteostasis network) related factors. This statement is very vague and the authors should clarify which genes were knocked down and which criteria were applied to narrow down the list of interactors and to select PN factors. The authors should therefore provide a supplementary table including all genes included in the screen, their source (were this derived from the initial study by Wright et al, from the current study or compiled from prior knowledge about PN), as well as their results from the screen based on luminescence in media and lysate. It is unclear how many of the selected factors are actually coming from the TRIP analysis.
• Only a small number of the 167 selected genes shows an effect on Tg abundance/secretion. How do the authors explain this result? Would we not expect that Tg interactors, especially those from the TRIP method which interact with the newly synthesized are more enriched for functionally relevant genes.
• The authors initially performed the screen in HEK293 cells and as a second step wanted to validate the hits from the HEK cells in more relevant Fisher rat thyroid cells. Indeed they could show that knockdown of NAPA increased WT TG in lysate and decreased WT Tg secretion. Furthermore, they further validated genes to modulate mutant Tg lysate and media abundance. The authors should perform a rescue experiment to demonstrate that the observed phenotype can be reversed through re-introduction of NAPA.
• One hit from this analysis was the ER-phagy receptor TEX264, while TEX264 was not identified in the TRIP data, is selectively increased the C1264R secretion, but not wt and the other Tg mutant. Following Co-IP data however revealed some interaction between the C1264R and to a lesser extent the A2234D mutant. How do the authors explain that TEX264 was missed in the TRIP dataset?

Minor comments:

• The workflow needs to be described clearer. For example, it should be better explained why the authors selected a two stage enrichment strategy, I assume that the first based on the Flag affinity tag is to purify the protein of interest and the second step based on the incorporation and functionalization of the unnatural amino acids to enrich for the newly synthesized fraction at specific time points after protein synthesis? These are critical steps for the method but the rationals are not well explained, neither in the text nor the figures captures all these steps of the method very clearly, which makes it really difficult for the reader to understand the individual steps of the method. Moreover, the structures in Figure 1 workflow are not clearly labeled, so that it is confusing which part represents which protein/molecule.
• Except for the general workflow shown in Figure 1, a more detailed workflow showing the experimental steps, such as the sample fractions with the following steps could be added so that the design of the method is clearer. Also the style of the workflows including Figure 1, Figure 2A, and Figure 3A are different. It would be helpful to make them the same style and make the Figure 2A as a zoom in or more detailed illustration on part of Figure 1.
• A summary of proteomics results of time course labeling after all enrichment steps, including the total number of identified proteins at different conditions and control would be helpful for having an overview impression on the proteomics results
• In Figure 2B, the WB for PDIA4 in the Biotin PD elution is missing. Why was the PDIA4 interaction missing for the time course analysis, but the interaction was captured in the initial test for Wt Tg (Figure 1D). Additionally, in this panel the Rhodamine Probe Gel shows inconsistencies at the time points 1.5 - 3h. Does this mean that the labeling did not work well for these conditions? As we would expect a consistent Rhodamine Probe signal at every time point.
• In Figure 2, why was there no WB results for the A2234D? In Figure 2D and 2E, at which time point are the changes significant compared to WT?
• All figure legends should indicate how many biological replicates were performed for each experiment represented in the figure.
• The heatmaps shown in Figure 3, Figure 3 - Figure Supplement 3, and Figure 7 are in the current form incomprehensible. The heatmaps depict the relative enrichment vs the control sample, which was scaled between 1 and -1. The color coding with 5 different colors from 1 to -1 is very confusing and should be changed to just two colors, one for positive and one for negative relative enrichment. I would also suggest changing the visualization of the heatmap showing the wt and mutants side by side, instead of stacked on top of each other for each individual protein.
• The data analysis method for generating relative enrichment shown in the heatmap is not explained. This should be described in the method section for a better understanding of the data analysis. There are no legends of flowcharts in Figure 2A and Figure 3A and it is difficult to understand which are the key components in the complex and what are the differences among different periods of labeling.
• Why did only one of the VCP inhibitors (ML-240) exhibit a phenotype in Tg abundance and secretion, but not the other VCP inhibitors?

Significance

The authors describe a novel and elegant method to map time resolved protein interactions of newly synthesized proteins, which allows monitoring of proteins regulating protein quality control. Authors describe it as a general method, however, they only demonstrate the applicability to one protein and do not systematically evaluate the quantitative nature of their approach by determining quantitative reproducibility, which would be necessary to be able to claim that this is a method with broad applicability.

Given my expertise in quantitative proteomics, I can mainly comment on the technological aspects of the proteomics part of the manuscript, but do not feel qualified to evaluate the significance of this study in terms of novel biology. Nevertheless, it feels that there is a stronger emphasis on the biology in the current form of the manuscript which will raise interest of scientists with a focus on protein quality control and Tg biology.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

The authors report a mass spectrometry (MS)-based interactomics technique, time-resolved interactome profiling (TRIP), which allows for tracking temporal changes in the interactome of protein of interest. To show that TRIP can successfully deconvolute interactomes over time, they pulsed thyroid cells with homopropargylglycine (Hpg), immunoprecipitated the Hpg incorporated thyroglobulin (Tg) and its interacting proteins at different time points, and subjected the samples to tandem mass tag (TMT)-based quantitative MS analysis. The MS results show that WT and variant Tg proteins indeed associate with different proteostasis network factors in a differential manner over the course of time. In addition, they utilized an siRNA-based luciferase fusion assay to evaluate whether silencing each proteostasis network component changes the levels of Tg in both lysate and media. From the combination of the TRIP and siRNA-based assays, they found many hits, including hits implicated in protein degradation, VCP and TEX264, which they validated with multiple experiments.

I am overall quite positive and think this is an important study. But there are some meaningful points to consider.

Significant comments:

1. Only two replicates of the main data (the TRIP-MS experiments) for this paper is problematic. Especially since the manuscript is supposed to be demonstrating and validating the new technique. Consistent with this concern, the relative enrichment profiles for some of the results were surprising. For instance, interaction with CCDC47 was tapering off but then at 3 h it suddenly reaches the maximum level of engagement. Is this a real finding or the variability in the method? Impossible to tell with two replicates. Presenting heat maps based on biological duplicates is also very problematic. It masks the error, which is large as can be seen in some of the panels showing individual proteins. In my view, triplicates and a clear understanding of the error in the technique should be required.
2. The same concern arises for the high-throughput siRNA screen, which was performed only in duplicate for WT and A2234D.
3. There are issues with some of the immunoprecipitation experiments: In Figure 1C, a negative control for FLAG IP is missing. In Figure 2B, I am curious why the band (Hpg -, chase time 0 h) is so faint for the first WB (IB for FLAG) - is Hpg treatment indeed leading to much more Tg present at 0 h? If so, that is a concern. Also, a negative control must be included (either plain cells or cells expressing fluorescent protein or a different epitope-tagged WT Tg). In this same figure, I am puzzled why the bands for 1.5-3 timepoints in Biotin PD elution, probed for Rhodamine, are very faint especially considering that in Figure 1D, the corresponding bands, which are 4 h after the pulse, look fine. It seems like the IP failed here?

Suggestion to consider:

This manuscript, supported by the title and abstract, mainly focuses on the presentation of the development and application of TRIP, which is highly significant. The story becomes less coherent and harder to follow as significant amounts of text/figures are dedicated to siRNA-based high throughput screening and follow-up. In addition, although the discovery of TEX264 as one of the hits is very interesting and exciting, TEX264 apparently was not a hit in the TRIP experiment and is pretty distracting from the main point of the paper highlighted in the abstract and title, therefore. The siRNA-based assay and follow-up studies could be a separate scientific story of their own. Especially considering my concerns on the number of replicates for both the TRIP and siRNA-based assay, it could be beneficial to actually split the manuscript into two and conduct more replicates of the -omic work, which should corroborate the exciting discoveries the authors have made.

Minor comments:

Throughout the manuscript, the authors have not defined what FT is; presumably it means FLAG tag.

The authors might discuss their rationale for choosing 0-3 hrs for their TRIP studies. That includes any relevant information about the half-life of WT versus variant Tg, whether the Hpg pulse time is short enough to avoid missing key features of the temporal interactome, and discussion of what would happen if the TRIP were performed at prolonged time points (e.g. 6-10 h).

Lines 68-69: the two citations should probably come one sentence earlier (at least Coscia et al 2020 is a structure paper).

Line 91: "(Figure 1A)" should follow the sentence "To develop the time-resolved..." to help readers better understand the system.

Line 101: Fisher should be Fischer

Line 131: Should be 1.5 hrs instead of 2 hrs.

Lines 135-136: I do not agree with the claim that HSPA5 profile looked similar for MS and WB. I do not see a peak for HSPA5 at 2 hrs in Figure 2D.

Line 186: The cited paper Shurtleff et al 2018 is missing in the reference list.

Line 188: I disagree with the authors' claim here because, at least for CCDC47, interactions with C1264R seem to come back at the 3 hr time point.

Line 203: I am not sure if P4HA1 can be included in the examples for showing distinct patterns for mutants compared to the WT according to their data in Figure 3H.

Line 216: The authors should add citations about the functions of STT3A and STT3B proteins.

Lines 248-251, "We found that interactions with these components...": this sentence should refer to Figure 3 - Figure Supplement 3 instead of Figure 3L and S4.

Lines 258-260, "Another striking observation was that the temporal profile of EMC interactions for C1264R correlated with RTN3, PGRMC1, CTSB, and CTSD interactions.": Please provide more evidence to support the potential correlation between different interaction profiles. Or the authors should move this sentence to the discussion section as it sounds speculative. This highlights the issue of only having duplicates, as well.

Line 340: As written, should cite more than one paper

Line 371: Should be Figure 4 - figure supplement 2

Line 1231: "Zhang et al 2018" needs to be removed

Line 1286: FRTR should be FRT

Figure 3E: Color used to highlight the three proteins (CCDC47, EMC1, EMC4) should match the color used in Figure 3 - Figure Supplement 3

Figure 4A: The bottom figure where lysate signal is inversely proportional to time is misleading because the authors are assessing steady-state level of proteins in this assay.

Figure 4 - Figure Supplement 1 caption: in (C), (F) should be (B). (K) should be (G) and I am not sure what the authors mean when they refer to (J) in caption of (G).

Figure 5 caption for (C and D): Need to specify the time that the samples were collected (8 hrs), as it seems different from A and B according to the main text.

Figure 5 - Figure Supplement 1: Data for HERPUD1 and P3H1 should be included.

Figure 5 - Figure Supplement 2B: Please mention in the caption how degradation is defined.

Significance

This manuscript is highly significant because the authors (1) designed and validated a new methodology for time-resolved interactomics study, (2) presented the dynamic changes in Tg interactome for WT and variants, and (3) discovered how proteins implicated in degradation pathways (e.g. VCP, TEX264, RTN3) can change the secretion profile of WT and mutant Tg proteins. With TRIP, the authors demonstrated that they could obtain valuable data that were previously not captured from steady-state interactomics studies (Wright et al. 2021; Figure 3M and Figure 3 - Figure supplement 4D-4I). Furthermore, the authors treated cells with VCP inhibitors and performed both 35S pulse-chase analyses and TRIP. These experiments provide valuable information to the field by (1) presenting a new method to rescue Tg secretion defect, and (2) demonstrating a broader applicability of TRIP. If the major comments above can be addressed I believe this is a tremendous contribution to the field.

Transparent Peer Review

---

Download the complete Review Process [PDF] including:

• reviews
• authors' reply
• editorial decisions

</br>

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

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

This manuscript investigates the dynamics of GC-content patterns in the 5'end of the transcription start sites (TSS) of protein-coding genes (pc-genes). The manuscript introduces a quite careful and comprehensive analysis of GC content in pc-genes in humans and other vertebrates, specially around the TSS. The result of this investigation states that "GC-content surrounding the TSS is largely influenced by patterns of recombination." (from end of Introduction)

My main concern with this manuscript is one of causal reasoning, whether intended or not. I hope the authors can follow my reasoning bellow on how the logic sometimes seems to fail, and that they introduce changes to clarify their suggested mechanisms of action.

The above quoted sentence form the end of the Intro is in conflict with this other sentence that appears at the end of the Abstract "the dynamics of GC-content in mammals are largely shaped by patterns of recombination". The sentence in the Intro seems to indicate that the effect is specific to TSSs, but the one in the abstract seem to indicate the opposite, that is, that the effect is ubiquitous.

We are sorry about the lack of clarity. We have now rewritten the abstract and intro to emphasize that our results are restricted to the 5' end of genes, and that by "patterns of recombination" we mean "historic patterns of recombination".

The observations as stated in the abstract are: "We observe that in primates and rodents, where recombination is directed away from TSSs by PRDM9, GC-content at protein-coding gene TSSs is currently undergoing mutational decay."

If I understand the measurements described in the manuscript correctly, and the arguments around them, you seem to show that the mutational decay of GC-content in humans is independent of location (TSSS or not), as noted here (also from the abstract) "These patterns extend into the open reading frame affecting protein-coding regions, and we show that changes in GC-content due to recombination affect synonymous codon position choices at the start of the open reading frame."

Again, we have rewritten this section to clarify these points.

There is one more result described in the manuscript, that in my mind is very important, but it is not given the relevance that it appears to me that it has. That is presented in Figure S3G. "we concluded that GC-content at the TSS of protein-coding genes is not at equilibrium, but in decay in primates and rodents. This decay rate is similar to the decay seen in intergenic regions that have the same GC-content (Figure S3G)"

Thus, if the decaying effect happens everywhere, how can it be related to "recombination being directed away from TSSs by PRDM9" as it is stated in the abstract and in the model described in Figure 7?

We make the argument that the GC-peak as likely caused by past recombination events. This is based on:

1) The change in GC-content at the TSS in Dogs and Fox, coupled to the fact that they perform recombination at the TSS

2) That the TSS can act as a default recombination site in mice when PRDM9 is knocked out

3) That some forms of PRDM9 allow for recombination at TSS (see Schield et al., 2020, Hoge et al. 2023, and Joseph et al., 2023) and that this is expected to cause an increase in GC-content

We thus speculate that the GC-peak in humans and rodents was caused by past recombination at TSSs that were permitted by ancient variants of PRDM9. We further point out that PRDM9 is undergoing rapid evolution, and some of the past versions of the protein may have had this property.

We have tried to clarify these points in the latest version of the text.

The fact that the decay rate is similar to any other region with similar GC-content should be an indication that the effect is not related to anything having to do with TSS or recombination being directed away from TSSs by PRDM9.

We are sorry about the lack of clarity. TSSs in humans, chimpanzees, mouse and rats are are experiencing GC-decay at the same rate as in non-functional DNA regions with high GC-content. Thus the GC-peak is not being maintained by selection. This is surprising, given the role that GC-content plays in gene expression. This is a critical point, and we added it to the "conclusion" section of the abstract.

I hope these paragraphs show my confusion about the relationship between the results presented which I think are very comprehensive and their interpretation and suggested model for GC-content dynamics around TSSs in human.

On another note, can you provided a bit more background on recombination and its mechanisms?

We have done our best to clarify these issues.

You seem to have confident sets of genes under high/low/med recombination. How are those determined.

We used the recombination rates per gene provided in Pouyet et al 2017 to identify the sets of genes under low/med/high recombination. Those rates were estimated from the HapMap genetic map (Frazer et al., 2007). This is now all specified in the methods section.

You also seem to concentrate the cause of recombination on PRDM9, please explain. Is PRDM9 the unique indicator of recombination?

PRDM9 has been shown to be the primary determinant of where recombination occurs in the genome (Grey et al., 2011, Brick et al., 2012). This is very well established. We now reword some of the introduction to make this clear.

specific comments

---

Figure 1, it is very hard to understand the differences between the three rows. Please explain more clearly in the legend, and add more information to the figure itself.

We altered the axis titles to make this clearer. We also label "Upsream", "Exon 1" and "Part of Intron 1" in Figure 1C, F and I, and in Figure 2C. We now spell this out in the Figure Legend.

Figure 7, express somewhere in the figure that the y axis measures GC content.

We now added "GC Content" to the left of the first "graph" in Figure 7.

Figure seems to introduce a 'causal' model of GC-content dismissing (diminishing?) based on recombination being directed away from TSSs. How about the diminishing of GC-content on any other genomic regions as you have shown in Figure S3G?

Our focus in this model, and manuscript, is on TSSs. I think that to add the dynamics of other GC-rich regions is distracting. We do not know what caused these intergenic genomic regions to be high in GC-content prior to decay. After excluding known recombination sites and TSSs, these regions are very rare in the human genome. They may be ancient recombination sites that are decaying in GC-content. However, unlike TSSs, which have some connection to recombination (i.e. data from PRDM9 knockout mice and dogs and fox), we do not have any direct or indirect evidence that these other sites were used for recombination in the past. Alternatively, there could have been some other pressure on these sites in the past to increase GC-content that we are not aware of.

-- The title is too selective, as to the results, and it has the implication that the decay is exclusive to the surrounding of the TSSs.

Decay of GC-content towards equilibrium is the default state for non-functional DNA. That it is occurring at the TSS is surprising, as it indicates that the GC-peak is not maintained by selection. We now state this in the paper and include this in the "conclusion" portion of the abstract.

Reviewer #1 (Significance (Required)):

The statistical analysis is comprehensive and robust.

We thank the reviewer for this.

Their model interpretation as is describe induces confusion and needs to be clarified.

We are sorry about this. Hopefully our revised text will clear up the confusion.

I am an expert computational biologist, I do not have a deep knowledge of sequence implications of recombination, and it would be good if the manuscript could add some more background on that.

We thank the reviewer for their perspective, and we hope that our text changes better explain to the non-expert why our findings are so surprising. We further clarify how recombination affects DNA sequence by gBGC and some of these changes are detailed in our response to the other reviewers.

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

In this work, the author present various analyses suggesting that GC-content in TSS of coding genes is affected by recombination. The article findings are interesting and novel and are important to our understanding of how various non-adaptive evolutionary forces shape vertebrate genome evolutionary history.

We thank the reviewer for these kind words.

The Methods section includes most needed details (see comments below for missing information), and the scripts and data provided online help in transparency and usability of these analyses.

I have several comments, mostly regarding clarifications in the text and several suggestions:

1. In introduction: CpG islands, have been shown to activate transcription (Fenouil et al., 2012) - what is known about CpG Islands is somewhat inaccurately described. It should be rephrased more accurately, e.g. - CpG Islands found near TSS are associated with robust and high expression level of genes, including genes expressed in many tissues, such as housekeeping genes.

We thank the reviewer for that. We have rewrote this part of the introduction.

1. The following claim (in Introduction), regarding retrogenes and their GC content is not in agreement recent analyses: "Indeed, it has been observed that these genes have elevated GC-content at their 5' ends in comparison to their intron-containing counterparts, suggesting that elevation of GC-content can be driven by positive selection to drive their efficient export (Mordstein et al., 2020). Moreover, retrogenes tend to arise from parental genes that have high GC-content at their 5'ends (Kaessmann et al.,2009)." Recent work showed that retrogenes in mouse and human are significantly depleted of CpG islands in their promoters (PMID: 37055747). This follows the notion that young genes, such as these retrogenes, have simple promoters (PMID: 30395322) with few TF binding sites and without CpGs. The two reported trends should be both mentioned with some suggestions regarding why they seem to be contrasting each other and how they can be reconciled.

We thank the reviewer for this information. The previous report (Mordstein et al., 2020) indicated that the increase in GC-content occurs downstream of the TSS in retrogenes. Since sequences upstream of the TSS are not part of the retro-insertion, it is not surprising that GC-content may differ between the retrogene and the parental gene. That retrogenes have lower numbers of CpGs upstream of the TSS, bolsters the idea that GC-content is not required for transcription and that the GC-peak is not being maintained in most genes by purging selection.

1. In "Thus GC-content is expected, and is indeed observed to be higher near recombination hotspots due to gBGC (REF)." I think you forgot the reference...

We thank the reviewer for catching this.

1. In Results, regarding average GC content (Fig 2X): "Interestingly, this pattern is different in the nonamniotes examined, including anole lizard, coelacanth, shark and lamprey." - in lizard, it seems that the genomic average is lower (and lizards are amniotes)

You are absolutely right. We now fix this.

1. In Discussion, the statement: "This model is supported by findings in a recent preprint, which documents the equilibrium state of GC-content in TSS regions from numerous organisms" seems to contrast with the findings of the mentioned preprint. If "most mammals have a high GC-content equilibrium state" but still have a functional PRDM9, in the lack of evidence for functional differences between ortholog PRDM9 proteins (such as signatures for positive selection or functional assays), the authors' findings regarding the relationship between a lack of PRDM9 in canids and the trends observed in their TSS, are weakened.

We are sorry about the confusion. We were not exactly sure what points were being commented on. 1) whether GC-content is at equilibrium for most mammals or 2) that the equilibrium state is high for most mammals despite containing PRDM9. We rewrote this sentence to clarify both issues (especially given that these concepts may not be clear to non-experts, such as the first reviewer). To answer the first potential concern, the paper in question (Joseph et al., 2023), does not show that GC-content at the TSS in mammals is at equilibrium, rather, it calculates what the equilibrium state is given the nucleotide substitution rates. In most organisms, the TSS is not at equilibrium. To answer both 1 and 2, Joseph et al., show that the equilibrium GC-content at the TSS for canids is much higher than for other mammals. They and others infer that the diversity between other mammals (where the equilibrium state is higher than humans and rodents but lower than canids) has to do with the variation between PRDM9 orthologues, however this has yet to be tested. Although the action of PRDM9 has not been evaluated in most mammals, we do point out that in snakes PRDM9 allows for some recombination at the TSS.

1. In Methods, the ENSEMBL version (in addition of the per-species genome version) should be mentioned.

This has been fixed.

1. In Fig 1, it is worth clarifying in the legend that the differences between the first and second rows of panels is in the length of the plotted region.

We have now indicated this in the figure legend.

Reviewer #2 (Significance (Required)):

The manuscript provides a rigorous analysis of the possible processes that have impacted the TSS GC-content during evolution. It should be of interest to a diverse set of investigators in the genomics community, since it touches on different topics including genome evolution, transcription and gene structures.

Thank you.

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

This study analyzes the distribution of GC-content along genes in humans and vertebrates, and particularly the higher GC-content in the 5'-end than in the 3'-end of genes. The results suggest that this pattern is ancient in vertebrates, currently decaying in mouse and humans, and probably driven by recombination and GC-biased gene conversion. It is proposed that the 5'-3' gradient was generated during evolution when PRDM9 was less active (in which case recombination occurs mostly near transcription start sites), and decays when PRDM9 is very active, as it is currently in humans and mouse. This is a very interesting hypothesis, also corroborated by a recent, similar analysis in mammals (Joseph et al. 2023). These two preprints, which appeared around the same time, are, I think, quite novel and important. The analyses performed here are thorough and convincing. Source code and raw data sets are openly distributed. I only have a couple of minor comments and suggestions, which I hope might help improve the manuscript.

Thank you very much for the kind words.

A1. There has been quite some work on the 5'-3' GC-content gradient in plants (e.g. Clément et al. 2014 GBE, Ressayre et al. 2015 GBE, Brazier & Glemin 2023 biorxiv), which you might like to cite.

Thank you for pointing out these very interesting papers, we have incorporated them into the latest version.

A2. CpG-content and GC-content are related in various ways (e.g. see Galtier & Duret 2000 MBE, Fryxell & Moon 2005 MBE) that you might like to discuss; currently the manuscript discusses the CpG hypermutation rate as a driver of GC-content but the picture might be a bit more complex.

Thank you for this, we have incorporated these citations.

A3. The model introduced by this manuscript (figure 7) is dependent on the evolution of recombination determination in vertebrates and the role of PRDM9. A recent preprint by Raynaud et al (biorxiv) seems relevant to this issue.

Thank you for pointing out this pre-print. We have added a paragraph to the discussion that mentions this work. This also initiated a conversation with the authors, and we include some "personal communications" that illuminate what is going on in teleost fish.

Line-by-line comments

B1. "First, highly spliced mRNAs tend to have high GC-content at their 5' ends despite the fact that it is not required for export and does not affect expression levels (Mordstein et al., 2020)" -> I do not totally understand this sentence, which seems to imply some link between splicing and export/expression, could you please clarify?

We rewrote that sentence to make it clearer.

B2. "mismatches will form in the heteroduplex which are typically corrected in favor of Gs and Cs over As and Ts by about 70%" -> This 70% figure is human-specific, and varies a lot among species; I know in this introduction you're mainly reviewing the human literature but since this part of the text introduces gBGC as a process maybe clarify by adding "in humans" or refrain from giving this figure?

Thank you. This is a good point. We fixed this.

B3. "Thus GC-content is expected, and is indeed observed to be higher near recombination hotspots due to gBGC (REF)." -> reference missing here; actually I'm not sure you will find a good reference for this because PRDM9-dependent hotspots are so short-lived that GC-content would only respond weakly; mayber rather refer to the equilibrium GC-content (and cite, for instance, Pratto et al 2014 Science), or to high-recombining regions instead of hotspots (and you have plenty of papers to cite)?

Thanks for this.

B4. Paragraph starting: "PRDM9 and recombination hotspots also experience accelerated rates of evolution..." -> I would suggest removing the word "also" and moving this paragraph up, just before the sentence I'm commenting above (the one starting "Thus GC-content..."). This will justify my suggestion in comment B3 of mentioning high-recombining regions instead of hotspots, while also avoiding to have the important paragraph on recombination at TSS (the one starting "There are interesting connections...") being sandwiched between two sections on PRDM9.

We did not move this paragraph, although we did adjust the wording slightly.

B5. Paragraph starting "There are interesting connections..." is crucial to your discussion and might be emphasized a bit more in introduction, in my opinion. For instance, what about adding a sentence like "Also not directly relevant to humans, these observations suggest that gBGC might have played a role in shaping the observed 5'-3' GC-content gradient."

We did not alter the structure of this paragraph but we did reword sections of it.

1. "Interestingly, this pattern is different in the non-amniotes examined, including anole lizard, coelacanth, shark and lamprey. These organisms had clear differences in GC-content between their first exon and surrounding sequences (upstream and intronic sequences), which came close to the overall genomic GC-content." -> I'm not sure I got the point the authors are intending to make here. Also please note that lizards are amniotes.

We thank the reviewer for catching this error, we have fixed this.

Reviewer #3 (Significance (Required)):

This is one of two preprints having appeared ~at the same time (the other one being the cited Joseph et al 2023), which I think are quite important and convincing regarding the role of PRDM9-dependent and PRDM9-independent recombination on GC-content evolution in vertebrates. I support publication of this preprint in a molecular evolutionary journal.

We thank the reviewer for their kind assessment!

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

This study analyzes the distribution of GC-content along genes in humans and vertebrates, and particularly the higher GC-content in the 5'-end than in the 3'-end of genes. The results suggest that this pattern is ancient in vertebrates, currently decaying in mouse and humans, and probably driven by recombination and GC-biased gene conversion. It is proposed that the 5'-3' gradient hass generated during evolution when PRDM9 was less active (in which case recombination occurs mostly near transcription start sites), and decays when PRDM9 is very active, as it is currently in humans and mouse. This is a very interesting hypothesis, also corroborated by a recent, similar analysis in mammals (Joseph et al. 2023). These two preprints, which appeared around the same time, are, I think, quite novel and important. The analyses performed here are thorough and convincing. Source code and raw data sets are openly distributed. I only have a couple of minor comments and suggestions, which I hope might help improve the manuscript.

A1. There has been quite some work on the 5'-3' GC-content gradient in plants (e.g. Clément et al. 2014 GBE, Ressayre et al. 2015 GBE, Brazier & Glemin 2023 biorxiv), which you might like to cite.

A2. CpG-content and GC-content are related in various ways (e.g. see Galtier & Duret 2000 MBE, Fryxell & Moon 2005 MBE) that you might like to discuss; currently the manuscript discusses the CpG hypermutation rate as a driver of GC-content but the picture might be a bit more complex.

A3. The model introduced by this manuscript (figure 7) is dependent on the evolution of recombination determination in vertebrates and the role of PRDM9. A recent preprint by Raynaud et al (biorxiv) seems relevant to this issue.

Line-by-line comments

B1. "First, highly spliced mRNAs tend to have high GC-content at their 5' ends despite the fact that it is not required for export and does not affect expression levels (Mordstein et al., 2020)" -> I do not totally understand this sentence, which seems to imply some link between splicing and export/expression, could you please clarify?

B2. "mismatches will form in the heteroduplex which are typically corrected in favor of Gs and Cs over As and Ts by about 70%" -> This 70% figure is human-specific, and varies a lot among species; I know in this introduction you're mainly reviewing the human literature but since since this part of the text introduces gBGC as a process maybe clarify by adding "in humans" or refrain from giving this figure?

B3. "Thus GC-content is expected, and is indeed observed to be higher near recombination hotspots due to gBGC (REF)." -> reference missing here; actually I'm not sure you will find a good reference for this because PRDM9-dependent hotspots are so short-lived that GC-content would only respond weakly; mayber rather refer to the equilibrium GC-content (and cite, for instance, Pratto et al 2014 Science), or to high-recombining regions instead of hotspots (and you have plenty of papers to cite)?

B4. Paragraph starting: "PRDM9 and recombination hotspots also experience accelerated rates of evolution..." -> I would suggest removing the word "also" and moving this paragraph up, just before the sentence I'm commenting above (the one starting "Thus GC-content..."). This will justify my suggestion in comment B3 of mentioning high-recombining regions instead of hotspots, while also avoiding to have the important paragraph on recombination at TSS (the one starting "There are interesting connections...") being sandwiched between two sections on PRDM9.

B5. Paragraph starting "There are interesting connections..." is crucial to your discussion and might be emphasized a bit more in introduction, in my opinion. For instance, what about adding a sentence like "Also not directly relevant to humans, these observations suggest that gBGC might have played a role in shaping the observed 5'-3' GC-content gradient."

1. "Interestingly, this pattern is different in the non-amniotes examined, including anole lizard, coelacanth, shark and lamprey. These organisms had clear differences in GC-content between their first exon and surrounding sequences (upstream and intronic sequences), which came close to the overall genomic GC-content." -> I'm not sure I got the point the authors are intending to make here. Also please note that lizards are amniotes.

Significance

This is one of two preprints having appeared ~at the same time (the other one being the cited Joseph et al 2023), which I think are quite important and convincing regarding the role of PRDM9-dependent and PRDM9-independent recombination on GC-content evolution in vertebrates. I support publication of this preprint in a molecular evolutionary journal.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

In this work, the author present various analyses suggesting that GC-content in TSS of coding genes is affected by recombination. The article findings are interesting and novel and are important to our understanding of how various non-adaptive evolutionary forces shape vertebrate genome evolutionary history.

The Methods section includes most needed details (see comments below for missing information), and the scripts and data provided online help in transparency and usability of these analyses.

I have several comments, mostly regarding clarifications in the text and several suggestions:

1. In introduction: CpG islands, have been shown to activate transcription (Fenouil et al., 2012) - what is known about CpG Islands is somewhat inaccurately described. It should be rephrased more accurately, e.g. - CpG Islands found near TSS are associated with robust and high expression level of genes, including genes expressed in many tissues, such as housekeeping genes.
2. The following claim (in Introduction), regarding retrogenes and their GC content is not in agreement recent analyses: "Indeed, it has been observed that these genes have elevated GC-content at their 5' ends in comparison to their intron-containing counterparts, suggesting that elevation of GC-content can be driven by positive selection to drive their efficient export (Mordstein et al., 2020). Moreover, retrogenes tend to arise from parental genes that have high GC-content at their 5'ends (Kaessmann et al.,2009)." Recent work showed that retrogenes in mouse and human are significantly depleted of CpG islands in their promoters (PMID: 37055747). This follows the notion that young genes, such as these retrogenes, have simple promoters (PMID: 30395322) with few TF binding sites and without CpGs. <br /> The two reported trends should be both mentioned with some suggestions regarding why they seem to be contrasting each other and how they can be reconciled.
3. In "Thus GC-content is expected, and is indeed observed to be higher near recombination hotspots due to gBGC (REF)." I think you forgot the reference...
4. In Results, regarding average GC content (Fig 2X): "Interestingly, this pattern is different in the nonamniotes examined, including anole lizard, coelacanth, shark and lamprey." - in lizard, it seems that the genomic average is lower (and lizards are amniotes)
5. In Discussion, the statement: "This model is supported by findings in a recent preprint, which documents the equilibrium state of GC-content in TSS regions from numerous organisms" seems to contrast with the findings of the mentioned preprint. If "most mammals have a high GC-content equilibrium state" but still have a functional PRDM9, in the lack of evidence for functional differences between ortholog PRDM9 proteins (such as signatures for positive selection or functional assays), the authors' findings regarding the relationship between a lack of PRDM9 in canids and the trends observed in their TSS, are weakened.
6. In Methods, the ENSEMBL version (in addition of the per-species genome version) should be mentioned.
7. In Fig 1, it is worth clarifying in the legend that the differences between the first and second rows of panels is in the length of the plotted region.

Significance

The manuscript provides a rigorous analysis of the possible processes that have impacted the TSS GC-content during evolution. It should be of interest to a diverse set of investigators in the genomics community, since it touches on different topics including genome evolution,transcription and gene structures.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

This manuscript investigates the dynamics of GC-content patterns in the 5'end of the transcription start sites (TSS) of protein-coding genes (pc-genes). The manuscript introduces a quite careful and comprehensive analysis of GC content in pc-genes in humans and other vertebrates, specially around the TSS. The result of this investigation states that "GC-content surrounding the TSS is largely influenced by patterns of recombination." (from end of Introduction)

My main concern with this manuscript is one of causal reasoning, whether intended or not. I hope the authors can follow my reasoning bellow on how the logic sometimes seems to fail, and that they introduce changes to clarify their suggested mechanisms of action.

The above quoted sentence form the end of the Intro is in conflict with this other sentence that appears at the end of the Abstract "the dynamics of GC-content in mammals are largely shaped by patterns of recombination". The sentence in the Intro seems to indicate that the effect is specific to TSSs, but the one in the abstract seem to indicate the opposite, that is, that the effect is ubiquitous.

The observations as stated in the abstract are: "We observe that in primates and rodents, where recombination is directed away from TSSs by PRDM9, GC-content at protein-coding gene TSSs is currently undergoing mutational decay."

If I understand the measurements described in the manuscript correctly, and the arguments around them, you seem to show that the mutational decay of GC-content in humans is independent of location (TSSS or not), as noted here

(also from the abstract) "These patterns extend into the open reading frame affecting protein-coding regions, and we show that changes in GC-content due to recombination affect synonymous codon position choices at the start of the open reading frame."

There is one more result described in the manuscript, that in my mind is very important, but it is not given the relevance that it appears to me that it has. That is presented in Figure S3G. "we concluded that GC-content at the TSS of protein-coding genes is not at equilibrium, but in decay in primates and rodents. This decay rate is similar to the decay seen in intergenic regions that have the same GC-content (Figure S3G)"

Thus, if the decaying effect happens everywhere, how can it be related to "recombination being directed away from TSSs by PRDM9" as it is stated in the abstract and in the model described in Figure 7?

The fact that the decay rate is similar to any other region with similar GC-content should be an indication that the effect is not related to anything having to do with TSS or recombination being directed away from TSSs by PRDM9.

I hope these paragraphs show my confusion about the relationship between the results presented which I think are very comprehensive and their interpretation and suggested model for GC-content dynamics around TSSs in human.

On another note, can you provided a bit more background on recombination and its mechanisms? You seem to have confident sets of genes under high/low/med recombination. How are those determined. You also seem to concentrate the cause of recombination on PRDM9, please explain. Is PRDM9 the unique indicator of recombination?

Specific comments

Figure 1, it is very hard to understand the differences between the three rows. Please explain more clearly in the legend, and add more information to the figure itself.

Figure 7, express somewhere in the figure that the y axis measures GC content. Figure seems to introduce a 'causal' model of GC-content dismissing based on recombination being directed away from TSSs. How about the diminishing of GC-content on any other genomic regions as you have shown in Figure S3G?

The title is too selective, as to the results, and it has the implication that the decay is exclusive to the surrounding of the TSSs.

Significance

The statistical analysis is comprehensive and robust. Their model interpretation as is describe induces confusion and needs to be clarified.

I am an expert computational biologist, I do not have a deep knowledge of sequence implications of recombination, and it would be good if the manuscript could add some more background on that.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

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

In "BDNF signaling requires matrix metalloproteinase-9 during structural synaptic plasticity", Legutko et al. used two-photon microscopy and glutamate uncaging to show that rapid release (seconds) of MMP-9 from dendritic spines following synaptic stimulation as well as MMP-9 dependent activation of TrkB. The authors also show and MMP-dependent increase on dendritic spine volume. These data support the possibility that MMP-9 rapidly activates BDNF to promote the spine maturation required for LTP. All is all the manuscript is well written, and the data is convincing and important.

Answer: We thank the reviewer for that comment.

Questions/Concerns:

• The authors show cell free cleavage of BDNF by recombinant MMP-9. It would be more convincing to show that MMP-9 cleaved BDNF using concentrated supernatants following synaptic stimulation in control versus inhibitor treated slices. Answer: In the present study we focus on a single-spine approach; thus, we did not include general stimulation techniques and biochemical analyses. To our knowledge, there is no method to show BDNF cleavage by MMP-9 directly at a single synapse. We agree with the reviewer that the general stimulation is important; however, at the synapse, there is potentially a whole array of proteases such as plasmin, tissue plasminogen activator (tPA) that might not only create catalytic cascade and proteolytically activate MMP-9 but also directly cleave proBDNF. When stimulating neurons and analysing supernatants, it is therefore impossible to determine if MMP-9 directly digests proBDNF to mBDNF or, alternatively, whether it is just a part of a proteolytic cascade leading to BDNF maturation. Therefore, our result where we use recombinant proteins provide an important piece of evidence that MMP-9 can indeed cleave proBDNF directly. Of note, experiments using brain extracts have been published previously, for example in a paper of Mizoguchi et al., J.Neurosci. (2011); DOI:10.1523/JNEUROSCI.3118-11.2011, where the authors showed increased cleavage of BDNF after pentylenetetrazole kindling and the kindling induced proBDNF cleavage was decreased in MMP-9 KO mice.

• The concentration of the MMP-9/13 inhibitor used was quite high and would also inhibit MMP-1, -3 and -7. This concern is, however, abrogated by the use of the MMP-9 KO. But it might be important to mention that the inhibitor is not MMP-9 specific at higher concentrations. Answer: To comply with this remark, we have stressed the notion in the Discussion of the revised ms.:

"There are over twenty MMPs with overlapping substrate specificity (Fields, 2015; Cieplak & Strongin, 2017) and there are no fully specific, commercially available inhibitors for MMP-9. Since Inhibitor I might affect also other MMPs, to further test the involvement of the protease in sLTP, we have used hippocampal slice cultures prepared from MMP-9 KO mice and their WT littermates (Fig. 1E, 1F)."

• In figure 1C vs E, as well as Fig 3C vs E, it appears that the DMSO to inhibitor (1C and 3C) change is larger than the WT vs MMP-9 KO (1E and 3E). Is this possibly because DMSO has a potentiating effect and/or because the inhibitor is getting other MMPs or the MMP-9 KO has compensatory increases in other MMPs? __Answer: __At the concentrations used in the study (not exceeding 0.08%), we do not consider DMSO having any potentiating effect. As we discuss in the manuscript, the difference between DMSO control and MMP-9 WT is most likely due to differences between genetic lines of the mice. This is also a reason why each set of experiments has its own control. Of note, in the paper preceding this study, Harvard et al., Nature (2016); doi:10.1038/nature19766, spine volume change induced by uncaging, vary between 200 and 300% depending on mice strain used in the experiment.

• The idea that MMP-9 and pro-BDNF are in the same vesicular stores is an interesting and very plausible one. Perhaps the authors could discuss what is known about the types of vesicles thought to harbor these two proteins. Answer: To follow on this remark, we added information about the vesicles containing BDNF and MMP-9 in the Discussion:

"Given that the release kinetics of BDNF and MMP-9 are similar, one could speculate that the effect of MMP-9 inhibition on early TrkB activation can be achieved because both, MMP-9 and BDNF are co-localized and co-released from the same release vesicles. BDNF is widely considered to be stored and released from Large Dense-Core Vesicles (Dieni et al, 2012; Kojima et al, 2020), and MMP-9 release although not studied in neurons but in cell lines, also points to the same type of vesicles (Stephens et al, 2019)."

• It might be useful to add to the discussion pathological conditions such as major depression and post-stroke plasticity in which MMP-9 dependent BDNF activation could be important. Answer: We thank the reviewer for that suggestion. We have added the information about MMP-9 and BDNF link in the brain pathologies in the Discussion:

"Additionally, our data may provide a functional link between the involvement of MMP-9 and BDNF in various brain pathologies, in which such a link has previously been implicated, for example in addiction (Cheng et al, 2019), schizophrenia (Pan et al, 2022; Yamamori et al, 2013), ischemic stroke (Li et al, 2022) or even following cochlear implantation (Matusiak et al, 2023)."

Reviewer #1 (Significance (Required)):

The results are significant to understanding synaptic plasticity in health and disease.

__Answer: __We thank the reviewer for that comment stressing the importance of our study.

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

The study addresses the molecular mechanisms of activity-dependent morphological plasticity of dendritic spines, focusing on the role of MMP-9 and BDNF-TrkB in the signalling and biochemical activities that lead to and maintain spine enlargement ('structural LTP', sLTP) induced experimentally.

It is based on a combination of 2-photon imaging of spine morphology, 2-photon imaging of MMP-9-SEP fluorescence, 2-photon FLIM of a biosensor for TrkB activity and 2-photon glutamate uncaging in organotypic hippocampal brain slices. In addition, it includes an assay of protein digestion based on Western immuno blots.

As results, the study reports that diminishing MMP-9 activity (pharmacologically or genetically) in the slices reduces sLTP, that repetitive glutamate uncaging evokes the release of MMP-9 from the spines that undergo sLTP, and that this effect can be blocked by pharmacological blockade of NMDA or exocytosis, that repetitive glutamate uncaging on a spine increases TrkB activation in the spine, and that this effect is diminished in slices from MMP-9 KO animals or treated by an MMP-9 blocker, and that MMP-9 can cleave proto-BDNF into mature BDNF in a cell-free medium.

The experiments are technically challenging but they are well conceived, designed and executed. The conclusions are well supported by the results, which are clearly discussed in light of the substantial and somewhat contradictory literature.

Reviewer #2 (Significance (Required)):

The study provides a finer view of the dynamic role of MMP-9 in activity-dependent spine plasticity, reinforcing and expanding existing knowledge on this timely topic.

The study is well executed and the conclusions are warranted. The study is an experimental tour de force, even if the biological results and insights are rather incremental and don't force us to revise our main assumptions or expectations.

Answer: We thank the reviewer for that comment and the appreciation of our work.

I only have a few questions and suggestions:

• 2: Do TeTx and AP5 treatments also block spine enlargement? The MMP9-SEP and mCherry signals in the spines are going up, what about their ratio F/R? __Answer: __Yes, we do have results showing that TeTx and AP5 block spine enlargement, however we did not present them in the original manuscript. The AP5 application on spine enlargement was previously demonstrated for example by Tanaka and co-workers (2008); DOI: 10.1126/science.1152864, and the effect of TeTx on LTP and insertion of AMPA receptors has also been demonstrated multiple times for example by Penn et al., Nature (2017); doi:10.1038/nature23658. To comply with the reviewer's request we have included the data in the revised version of the manuscript (Figure 2C).

As far as the F/R ratio is concerned we shall stress that the aim of our experiments was to show the release of MMP-9 into extracellular space upon uncaging. We have initially tried to analyse the ratio of F/R, however the green signal that comes from MMP9-SEP does not accumulate at the spine, apparently being rapidly diffused. Therefore, the overall red signal for mCherry increases much faster (mCherry fills the cytoplasm in the spine) than the MMP9-SEP; therefore, the F/R ratio is decreasing over time. Figure 2G shows that increases in MMP9-SEP fluorescence are only transient (around 0.5 s) after uncaging pulses.

• 3B shows increased TrkB activation after glutamate uncaging, but is it possible to see the spine enlargement in the FRET-FLIM signal/images? Answer: Yes, it is possible to observe spine enlargement during FRET-FLIM experiments by counting photons from the red channel (RFP) as well as from the green one (GFP), however due to technical difficulties spine volume change was measured in separate experiments.

• Fix: mW and Chameleon in the Methods section - corrected

• Consider streamlining the Discussion a bit - we have reviewed the discussion
• Consider adding a schematic to summarise the new and existing findings Answer: We thank the reviewer for the suggestion, we have added a schematic summarising the paper as a separate figure (Fig.4).

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

In this short report, Legutko et al address the role of MMP9 in BDNF signaling in the context of structural long-term potentiation (sLTP). In particular, they assess whether MMP9 is secreted fast enough to mediate the cleavage of proBDNF in mBDNF during sLTP. The study uses 2-photon imaging of hippocampal organotypic slices, glutamate uncaging and FRET-based sensors of TrkB activity. The authors demonstrate that MMP9 is secreted within seconds upon 2-photon glutamate uncaging and that MMP9 secretion precedes spine enlargement. They also show that MMP9 can cleave proBDNF in vitro. However, the role of MMP9 in sLTP and associated TrkB signaling remains speculative at the end of the manuscript.

Major comments

• The title of the first result section "spine head enlargement during structural plasticity depends on MMP9 activity" is an overstatement. The authors provide evidence that MMP inhibition and MMP9 KO decrease spine enlargement during the early phase of sLTP. However, after the first few minutes, spines still display long-term enlargement, and no difference between WT and MMP9 KO mice can be detected. These data suggest that MMP9 is only involved in the initial phase of sLTP, and that other MMPs are involved in sLTP.

__Answer: __We thank the reviewer for that comment. We have change the wording in the revised manuscript to accommodate the suggestion.

• The authors cannot conclude that "spine head enlargement during sLTP depends on MMP9 activity".

__Answer: __We thank the reviewer for that comment. We have changed the title and wording in the revised manuscript to accommodate the suggestion.

• The authors should apply Inhibitor I on MMP9 KO slices to determine if MMPs other than MMP9 are involved in spine enlargement.

__Answer: __We thank the reviewer for the suggestion, and indeed we agree that other MMPs might be involved in spine enlargement induced by glutamate uncaging. Furthermore, applying Inhibitor I will not resolve the question which MMPs or other proteases are involved in the spine enlargement. Applying Inhibitor I on MMP-9 KO slices would only eliminate one of the proteases. To deal with this difficult issue, we have used slices from MMP-9 KO mice and showed the influence of MMP-9 on the transient phase of spine enlargement induced by glutamate uncaging.

• If Inhibitor I still impacts sLTP in MMP9 KO slice, it would greatly benefit this study to determine which MMPs are involved (for example by analyzing the expression patterns of MMPs in their neurons and selectively inactivating those expressed with shRNAs).

Answer: The proposed experiment is an excellent suggestion for a future project however it is not an easy experiment to perform. MMPs expression pattern could be assessed by single cell RNA sequencing to distinguish it from for example astrocytic expression, however it often fails to detect mRNAs which are expressed at low level. For example mRNA coding MMP-9 belongs to this group as its mRNA is kept at very low level, see, e.e.g, Konopacki et al., Neuroscience (2007); https://doi.org/10.1016/j.neuroscience.2007.08.026, Dziembowska et al. J.Neurosci (2012); https://doi.org/10.1523/JNEUROSCI.6028-11.2012. There is also quite low correlation between mRNA levels and protein levels at a global scale, see e.g., Reimegård et al., Comm. Biol. (2021); https://doi.org/10.1038/s42003-021-02142-w, therefore predictive power of mRNA sequencing for the importance of a particular protein might not be sufficiently informative. Moreover, the situation is even more complex in neurons which are strongly compartmentalized, and where local translation plays a significant role. We have previously studied this particular aspect for MMP-9, Dziembowska et al. J.Neurosci. (2012); DOI:10.1523/JNEUROSCI.6028-11.2012..

• The title of the third/last result section "TrkB signaling depends on MMP9 activity" is also an overstatement. In Figure 3, the authors show that the pharmacological inhibition of MMPs slightly inhibits TrkB signaling in the early phase of sLTP, and almost abolishes TrkB signaling in the second phase (> 3 min after uncaging). However, the data suggesting a specific role for MMP9 in TrkB signaling are not convincing (Figure 3E-F). The activation of trkB during sLTP is weak even in WT, the peak of trkB activation upon glutamate uncaging in not disrupted in MMP9 KO mice, and the data are noisy. It is a major concern that the authors cannot convincingly show that TrkB signaling is altered in MMP9-deficient neurons. Answer: To the best of our knowledge, using FRET-FLIM sensors is the best and state-of-the-art method to track biochemical changes (such as receptor activation) in real time using live preparations. The method is very sensitive and published previously by one of the authors of the current study where TrkB sensor is activated in the same magnitude (Harward et al., Nature, 2016; doi: 10.1038/nature19766). Moreover similar magnitude of sensor activation was reported previously in single dendritic spines for other sensors using FLIM-FRET method: Rho GTPases (Hedrick et al., Nature 2016; doi: 10.1038/nature19784), IGF1R (Tu et al., Sci Advanc. 2023; doi: 10.1126/sciadv.adg0666) or CaMKII (Chang et al., Nat. Commun. 2019; https://doi.org/10.1038/s41467-019-10694-z). The noise is to be expected, as we are imaging small compartments in a short time where collecting enough number of photons is challenging. Similarly to previous studies using FRET-FLIM sensors, we bin experimental points to reduce noise for statistical analysis. Notably, the biological effect we observe, namely sensor activation, is well above the experimental noise that in inevitable in this experimental approach. For statistical analyses we have used repeated measures ANOVA, which is very sensitive to noise and signal fluctuation. The differences we measure are statistically significant.

• The authors discuss that the problem might stem from mouse genetic backgrounds. However, if the MMP9 KO mouse model is not appropriate to answer the question, the authors should use another one (i.e. MMP9 knockdown using sh/siRNAs).

Answer: We believe that the effect of MMP-9 KO in this experiment is evident, as supported by Fig. 3 E,F and statistical analysis. Furthermore, the experiment with the inhibitor further supports our reasoning.

• In addition to the graphs, the authors should mention in the text the percentage of inhibition compared to WT). This would make the results easier to read.

Answer: To comply with this request the appropriate information has been added to the revised manuscript.

• The change in TrkB activation following glutamate uncaging is low (max 5-7 % at the peak, compared to 200% for spine volume). This raises the question of the physiological relevance of TrkB activation in this model. The authors should include experiments with a trkB inhibitor to assess whether it prevents sLTP in WT and MMP9 KO mice. They should also discuss other potential targets of MMP9. This would strengthen the rationale of the experiments. Answer: Previously published results using the same TrkB sensor (Harward et al., Nature, 2016; doi: 10.1038/nature19766), show exactly the same change in binding fraction calculated from a change in GFP fluorescence lifetime. These data are also in agreement with well-established standard in the field, see, e.g., Rho GTPases (Hedrick et al., Nature 2016; doi: 10.1038/nature19784), IGF1R (Tu et al., Sci Advanc. 2023; doi: 10.1126/sciadv.adg0666) or CaMKII (Chang et al., Nat. Commun. 2019; https://doi.org/10.1038/s41467-019-10694-z). In response to the comment we have addressed this issue in the Discussion in the revised ms.

Minor comments

• In the introduction, the authors should provide more context. Could the authors develop the "long standing debate on which enzymes process proBDNF to mBDNF"? Answer: We have removed the sentence as we realized it was too confusing and the paper does not compare between different proteases which may process proBDNF to mBDNF.

• In the result section:

• First paragraph, the last sentence should be moved from the end of the paragraph to before "During sLTP induction...".

Answer: Following the reviewer suggestion, we have moved the sentence.

• Several paragraphs in the result section lack a proper conclusion/interpretation, which makes it difficult to read. Examples: after (Fig. 2E), after (Fig. 2F). The authors should explicit what their results mean.

Answer: We have changed the paragraphs and tried to explain the results better.

• Clarify when and for how long the MMP inhibitor was applied. Answer: The inhibitor was applied 30 min. before stimulation. We have added the information in the Methods section.

• In figure 1, The authors observe a specific alteration of the early, transient, sustained increase in spine head volume in MMP9 KO mice. The later phase of sLTP is not impacted, which means that sLTP is induced and maintained in the KO. Could the authors discuss the role/importance of this transient peak in spine head volume? Answer: In response to this comment, we have discussed this issue in the revised ms. as follows:

" The transient spine expansion might be important for the remodeling of the synapse (Lang et al, 2004) and is associated with NMDAR-dependent formation of "memory gel" created by enlargement pool of actin (Honkura et al, 2008; Kasai et al, 2010; Bonilla-Quintana & Rangamani, 2024). It has also been reported that TrkB activity can influence actin dynamics (Woo et al, 2019; Hedrick et al, 2016), in some instances in concert with integrin 1 (Wang et al, 2016), which is also activated by MMP-9 (Wang et al, 2008; Michaluk et al, 2009, 2011) and further supports our observations."

Reviewer #3 (Significance (Required)):

The manuscript aims to bring conceptual advance in our understanding of structural synaptic plasticity by investigating the role and timing of MMP9 secretion in TrkB signaling. Previous work from the Yasuda lab and others have shown that trkB is activated early on by BDNF during sLTP. However, how, when and where BDNF is cleaved from proBDNF in mBDNF is poorly understood. The authors demonstrate that the pharmacological inhibition of metalloproteases attenuates structural long-term plasticity (sLTP) and that MMP9 is secreted early enough to cleave proBDNF. They also show that MMP9 can cleave proBDNF in BDNF in vitro. Whether MMP9 specifically cleaves BDNF during sLTP and whether this cleavage is physiologically relevant for sLTP remain an open question.

This report will be of interest to neurobiologists interested in the molecular mechanisms of synaptic plasticity.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

In this short report, Legutko et al address the role of MMP9 in BDNF signaling in the context of structural long-term potentiation (sLTP). In particular, they assess whether MMP9 is secreted fast enough to mediate the cleavage of proBDNF in mBDNF during sLTP. The study uses 2-photon imaging of hippocampal organotypic slices, glutamate uncaging and FRET-based sensors of TrkB activity. The authors demonstrate that MMP9 is secreted within seconds upon 2-photon glutamate uncaging and that MMP9 secretion precedes spine enlargement. They also show that MMP9 can cleave proBDNF in vitro. However, the role of MMP9 in sLTP and associated TrkB signaling remains speculative at the end of the manuscript.

Major comments

1. The title of the first result section "spine head enlargement during sLTP depends on MMP9 activity" is an overstatement. The authors provide evidence that MMP inhibition and MMP9 KO decrease spine enlargement during the early phase of sLTP. However, after the first few minutes, spines still display long-term enlargement, and no difference between WT and MMP9 KO mice can be detected. These data suggest that MMP9 is only involved in the initial phase of sLTP, and that other MMPs are involved in sLTP.
   • The authors cannot conclude that "spine head enlargement during sLTP depends on MMP9 activity".
   • The authors should apply Inhibitor I on MMP9 KO slices to determine if MMPs other than MMP9 are involved in spine enlargement.
   • If Inhibitor I still impacts sLTP in MMP9 KO slice, it would greatly benefit this study to determine which MMPs are involved (for example by analyzing the expression patterns of MMPs in their neurons and selectively inactivating those expressed with shRNAs).
2. The title of the third/last result section "TrkB signaling depends on MMP9 activity" is also an overstatement. In Figure 3, the authors show that the pharmacological inhibition of MMPs slightly inhibits TrkB signaling in the early phase of sLTP, and almost abolishes TrkB signaling in the second phase (> 3 min after uncaging). However, the data suggesting a specific role for MMP9 in TrkB signaling are not convincing (Figure 3E-F). The activation of trkB during sLTP is weak even in WT, the peak of trkB activation upon glutamate uncaging in not disrupted in MMP9 KO mice, and the data are noisy. It is a major concern that the authors cannot convincingly show that TrkB signaling is altered in MMP9-deficient neurons.
   • The authors discuss that the problem might stem from mouse genetic backgrounds. However, if the MMP9 KO mouse model is not appropriate to answer the question, the authors should use another one (i.e. MMP9 knockdown using sh/siRNAs).
   • In addition to the graphs, the authors should mention in the text the percentage of inhibition compared to WT). This would make the results easier to read.
3. The change in TrkB activation following glutamate uncaging is low (max 5-7 % at the peak, compared to 200% for spine volume). This raises the question of the physiological relevance of TrkB activation in this model. The authors should include experiments with a trkB inhibitor to assess whether it prevents sLTP in WT and MMP9 KO mice. They should also discuss other potential targets of MMP9. This would strengthen the rationale of the experiments.

Minor comments

1. In the introduction, the authors should provide more context. Could the authors develop the "long standing debate on which enzymes process proBDNF to mBDNF"?
2. In the result section:
   • First paragraph, the last sentence should be moved from the end of the paragraph to before "During sLTP induction...".
   • Several paragraphs in the result section lack a proper conclusion/interpretation, which makes it difficult to read. Examples: after (Fig. 2E), after (Fig. 2F). The authors should explicit what their results mean.
3. Clarify when and for how long the MMP inhibitor was applied.
4. In figure 1, The authors observe a specific alteration of the early, transient, sustained increase in spine head volume in MMP9 KO mice. The later phase of sLTP is not impacted, which means that sLTP is induced and maintained in the KO. Could the authors discuss the role/importance of this transient peak in spine head volume?

Significance

The manuscript aims to bring conceptual advance in our understanding of structural synaptic plasticity by investigating the role and timing of MMP9 secretion in TrkB signaling. Previous work from the Yasuda lab and others have shown that trkB is activated early on by BDNF during sLTP. However, how, when and where BDNF is cleaved from proBDNF in mBDNF is poorly understood. The authors demonstrate that the pharmacological inhibition of metalloproteases attenuates structural long-term plasticity (sLTP) and that MMP9 is secreted early enough to cleave proBDNF. They also show that MMP9 can cleave proBDNF in BDNF in vitro. Whether MMP9 specifically cleaves BDNF during sLTP and whether this cleavage is physiologically relevant for sLTP remain an open question.

This report will be of interest to neurobiologists interested in the molecular mechanisms of synaptic plasticity.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

The study addresses the molecular mechanisms of activity-dependent morphological plasticity of dendritic spines, focusing on the role of MMP-9 and BDNF-TrkB in the signalling and biochemical activities that lead to and maintain spine enlargement ('structural LTP', sLTP) induced experimentally.

It is based on a combination of 2-photon imaging of spine morphology, 2-photon imaging of MMP-9-SEP fluorescence, 2-photon FLIM of a biosensor for TrkB activity and 2-photon glutamate uncaging in organotypic hippocampal brain slices. In addition, it includes an assay of protein digestion based on Western immuno blots.

As results, the study reports that diminishing MMP-9 activity (pharmacologically or genetically) in the slices reduces sLTP, that repetitive glutamate uncaging evokes the release of MMP-9 from the spines that undergo sLTP, and that this effect can be blocked by pharmacological blockade of NMDA or exocytosis, that repetitive glutamate uncaging on a spine increases TrkB activation in the spine, and that this effect is diminished in slices from MMP-9 KO animals or treated by an MMP-9 blocker, and that MMP-9 can cleave proto-BDNF into mature BDNF in a cell-free medium.

The experiments are technically challenging but they are well conceived, designed and executed. The conclusions are well supported by the results, which are clearly discussed in light of the substantial and somewhat contradictory literature.

Significance

The study provides a finer view of the dynamic role of MMP-9 in activity-dependent spine plasticity, reinforcing and expanding existing knowledge on this timely topic.

The study is well executed and the conclusions are warranted. The study is an experimental tour de force, even if the biological results and insights are rather incremental and don't force us to revise our main assumptions or expectations.

I only have a few questions and suggestions:

• Fig. 2: Do TeTx and AP5 treatments also block spine enlargement? The MMP9-SEP and mCherry signals in the spines are going up, what about their ratio F/R?
• Fig. 3B shows increased TrkB activation after glutamate uncaging, but is it possible to see the spine enlargement in the FRET-FLIM signal/images?
• Fix: mW and Chameleon in the Methods section
• Consider streamlining the Discussion a bit
• Consider adding a schematic to summarise the new and existing findings

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

In "BDNF signaling requires matrix metalloproteinase-9 during structural synaptic plasticity", Legutko et al. used two-photon microscopy and glutamate uncaging to show that rapid release (seconds) of MMP-9 from dendritic spines following synaptic stimulation as well as MMP-9 dependent activation of TrkB. The authors also show and MMP-dependent increase on dendritic spine volume. These data support the possibility that MMP-9 rapidly activates BDNF to promote the spine maturation required for LTP. All is all the manuscript is well written, and the data is convincing and important.

Questions/Concerns:

1. The authors show cell free cleavage of BDNF by recombinant MMP-9. It would be more convincing to show that MMP-9 cleaved BDNF using concentrated supernatants following synaptic stimulation in control versus inhibitor treated slices.
2. The concentration of the MMP-9/13 inhibitor used was quite high and would also inhibit MMP-1, -3 and -7. This concern is, however, abrogated by the use of the MMP-9 KO. But it might be important to mention that the inhibitor is not MMP-9 specific at higher concentrations.
3. 1. In figure 1C vs E, as well as Fig 3C vs E, it appears that the DMSO to inhibitor (1C and 3C) change is larger than the WT vs MMP-9 KO (1E and 3E). Is this possibly because DMSO has a potentiating effect and/or because the inhibitor is getting other MMPs or the MMP-9 KO has compensatory increases in other MMPs?
4. The idea that MMP-9 and pro-BDNF are in the same vesicular stores is an an interesting and very plausible one. Perhaps the authors could discuss what is known about the types of vesicles thought to harbor these two proteins.
5. It might be useful to add to the discussion pathological conditions such as major depression and post-stroke plasticity in which MMP-9 dependent BDNF activation could be important.

Significance

The results are significant to understanding synaptic plasticity in health and disease.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

Compared to our initial submission to Review Commons, we have addressed all the reviewers' comments. We have extensively re-written the manuscript to make it clearer to a larger audience. In particular, we have transferred Figure EV1 to Figure 1 with more complete panels and included a scheme (Figure EV3) on the steps of D2R internalization which we measure with live cell imaging. We have added a new paragraph to the start of the Discussion to summarize our main conclusions and reordered the discussion on the possible mechanisms of membrane PUFA enrichment on D2R endocytosis. All the changes in the text are in red for easier comparison with the previous version.

As suggested by reviewer 1, we have performed additional experiments to test the specificity of the effects of PUFA treatments on D2R endocytosis, reinforcing the results shown in Figure 4 using feeding assays. We show with live cell TIRF imaging and the ppH assay that TfR-SEP endocytosis is not affected (Figure EV5) and that SEP-β2AR endocytosis and βarr2-mCherry recruitment to the plasma membrane are not affected (Figure EV6).

Reviewer #1

Evidence, reproducibility and clarity

*The manuscript, using different live and fixed cell trafficking assays, demonstrates that incorporation of poly-unsaturated, but not saturated, free fatty acids in the membrane phospholipids reduce agonist induced internalization of the D2 dopamine receptor but not the adrenergic beta2 receptors or the transferrin receptor. Pulsed pH (ppH) live microscopy further demonstrated that the reduced internalization by incorporation of free fatty acid was accompanied by a blunted recruitment of Beta-arrestin for the D2R.

I believe said claims put forward in the manuscript are overall well supported by the data and as such I do not believe that further experiments are necessarily needed to uphold these key claims. Also, the methodology is satisfactorily reported, and statistics are robust, although two-way Anova like used in Fig 1 seems appropriate for Fig 2 and 3*

We thank the reviewer for his/her positive assessment of our work. We have checked the statistical tests used for all our measures. For Figure 2 and 3 (now 3 and 4) we test for only one factor (PUFA treatment or not) so we ran ordinary one-way ANOVA using Graphpad Prism.

That said, I suggest that the fixed cell internalization experiments (Fig 2 and 3), which relate the effect on the D2R to B2AR and transferrin are revised. This is important since this is relevant to judge whether the effect is a general or a selective molecular mechanism since this is the one of the three assay which this comparison relies on. Alternatively, I suggest omitting this data and include the B2AR in the Live DERET assay and both B2AR and TfR in the ppH assay. Specifically, my concerns with the fixed cell internalization are: • The analysis is based on counting the number of endosomes, which is not necessarily equivalent to the number of receptors internalized

The number of puncta, as well as their fluorescence, is reported by the analysis program (written in Matlab2021 and available upon request). We chose to show number of puncta because they reflect more directly the number of labelled endosomes (in Figures 3 and 4). As shown in the figure below, we found slight but significant differences between groups for FLAG-D2R (88.6 % and 87.6 % of average fluorescence in DHA and DPA treated cells compared to control cells), (panel A), and no differences for FLAG-β2AR (panel B). We find a significant decrease in puncta fluorescence for transferrin uptake in cells incubated with DHA (but not DPA) relative to control cells (panel C). However, because we did not detect differences in the number of puncta or in the frequency and amplitude of endocytic vesicle creation events (see below), we still conclude that enrichment with exogenous PUFAs does not affect clathrin mediated endocytosis.

In conclusion, the most robust measure of endocytosis for this assay is the number of detected puncta per cell rather than their fluorescence.

• The analysis relies on fully effective stripping of the surface pool of receptors - i.e clustered surface receptors not stripped by the protocol will be assessed as internalized. It is often very difficult to obtain full efficiency of the Flag-tag stripping and this is somewhat expression dependent. • The protocol for the constitutive and agonist induced internalization is different and yet shown on the same absolute graph. Although I take it the microscope gain setting are unaltered between the constitutive and agonist induced internalization I don't believe the quantification can be directly related. This is confusing at the very least. More critically however, the membrane signal from the non-stripped condition of constitutive internalization will likely fully shield internalized receptors in the Rab4 membrane proximal recycling pathway leading to under-estimation of the in the constitutive endocytosis. I believe this methodological limitation underlies the massive relative difference in the constitutive endocytosis between panel 2A,B and 2C,D. For comparison, by a quantitative dual color FACS endocytosis assay, we have previously demonstrated the ligand endocytosis a ~4 fold increased over constitutive (in concert with Fig 2A,B here) (Schmidt et al 20XX). Importantly, high relative variability by this methodology could well shield an actual effect of incorporation of FFAs on the constitutive endocytosis. We thank the reviewer for pointing this difference in the protocol. As a matter of fact, we have not used acid stripping in all the conditions used for the uptake assays (Figures 3 and 4). We apologize for the confusion and we have clarified this point in the Methods section. In early experiments we compared conditions with or without stripping but we concluded from these experiments that indeed, the stripping was not complete. Moreover, we noticed early on that many cells treated with DHA or DPA did not have any detectable cluster (13 cells out of 58 quantified cells treated with DHA after addition of QPL, 12/56 cells treated with DPA, 0/68 for cells treated with vehicle). Stripping the antibody would have made these cells undetectable, biasing the analysis. Therefore, to make our results more consistent we decided to use non-stripping conditions. To detect endosomes specifically, we used a segmentation tool developed earlier (see Rosendale et al.* 2019). This tool is based on wavelet transforms which recognizes dot-like structures. In addition, we excluded from the cell mask the labelled plasma membrane by a mask erosion.

We agree the design of experiments was not aimed at comparing the effect of PUFA treatment on low levels of constitutive D2R endocytosis. This would require more sensitive assays and be addressed in subsequent studies.

'Optional' Also, it would be informative to see the ppH Beta-arrestin experiments with the B2AR to assess, whether the putative discrepancy between D2R and B2AR is upstream or downstream of the blunted Beta-arrestin recruitment. To the same point, it would be very informative to assess how the incorporation of the free fatty acids affect receptor signalling, which would also help relate the effect of incorporation of the FFA's in the phospholipids to previous experiment using short term incubation with FFA's

We have now performed live imaging experiments in HEK293 cells expressing SEP-β2AR, GRK2 and βarr2-mCherry and stimulated with isoproterenol (Figure EV6). We show that the clustering of SEP-β2AR, of βarr2-mCherry, as well as endocytosis, are not affected by treatments with DHA or DPA. In this study, we focused on the early trafficking steps of D2R internalization. It will be interesting in a future study to address its consequences on G protein dependent and independent signaling. Moreover, and for good measure, we performed experiments to assess TfR-SEP endocytosis with the ppH assay. Again, we found no difference between cells treated or not with PUFAs (Figure EV5)

*References overall seem appropriate although Schmidt et al would be relevant for reference of the constitutive vs agonist induced endocytosis of D2R and B2AR. *

We have now cited Schmidt et al. 2020 doi 10.1111/bcpt.13274 in the discussion with the following sentences: "D2R also shows constitutive endocytosis (Schmidt et al, 2020) which may be modulated by PUFAs although we did not detect any significant difference in our measures (see Figure 3) which were aimed at detecting high levels of internalization induced by agonists. Further work will be required to specifically examine the effect of PUFAs on constitutive GPCR internalization."

Overall, the figures are well composed and convey the messages fairly well. Specific point that would strengthen the rigor include: • Chosing actual representative pictures of the quantitative data in Fig 2 and 3 (e.g. hard to see 25 endocytic events in Fig 2A constitutive endo, EtOH)

We apologize for the confusion. We employ a normalization procedure to account for cell size. In addition, all numbers have been normalized to the condition stimulated with agonist with no PUFA treatment). In fact, we detect in unstimulated cells very few puncta (on average 0.6, range 0-5) compared to 27.3 clusters (range 2-87) in cells stimulated with QPL.

• Showing actual p values for the statistical comparisons* For easier reading, we have kept the stars convention for the figures but added two tables with all statistical tests and the p values for both main figures and EV figures.

Moreover, for ease of reading the figures (without consulting the legend repeatedly) it would be very helpful to headline individual panel with what the experiments assesses. Figure 1a and 1b for example can't be distinguished at all before reading the figure legend. Also, y-axis could be more informative on what I measured rather than just giving the unit.

We have added titles to panels (in particular for Figure 2A,B which correspond to former Figure 1A,B) and we have given new titles to Y axes to make them clearer. We hope that the reading of our figures will now be easier.

Finally, the figure presentation and description of S1 is very hard to follow. I cannot really make out what is assessed in the different panels.

We have changed substantially Figure EV1 (now Figure 1) with new presentation of data: all 4 conditions (control, treated with DHA, DPA or BA) systematically presented in the same graph, and clearer titles for the parameter displayed on the Y axes. We hope that this figure is now easier to follow.

Significance

*The strength of the manuscript is the use and validation of incorporation of FFA's in the plasma membrane, which more closely mimics the physiological situation than brief application of FFAs as often done. Is addition, the blunted recruitment of beta-arrestin as assessed by the ppH protocol is quite intriguing mechanistically. The limitation are the relative narrow focus on the D2 receptor (and not multiple GPCRs) that does not really speak to as or assess the physiological, pathophysiological or therapeutic role of the observations (except from referring the relation between FFAs and disease). Also, despite the putative role of Beta-arrestin recruitment in the process, the actual causation in the process is not clear. This shortcoming is underscored by the putative effect on the constitutive internalization described above.

My specific expertise for assessing the paper is within general trafficking processes (including the trafficking methodology applied), trafficking of GPCRs and function of the dopamine system including the role of D2 receptors.*

• *

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

• *

The only conclusion that I was able to understand from the study was that enrichment of cell membranes with polyunsaturated fatty acids specifically inhibited agonist-induced internalization of D2 receptors. However, I think that the experiments used to conclude that PUFAs do not alter D2R clustering but reduce the recruitment of β-arrestin2 and D2R endocytosis need some clarification (i.e. data depicted in Fig. 2-5). This lack of clarity might be due to the fact I am not familiar enough with the employed technologies or to the unclear writing style of the paper. There was an overuse of acronyms, initialisms and abbreviations, which are difficult to understand for researchers outside of the specific lipid field. I think that the manuscript should be written in a way to be legible also for researchers not working in the immediate filed.

The paper was not written in a manner that a general audience of cell biologists or those interested in GPCR biology could understand and judge. It is indeed interesting that polyunsaturated fatty acids specifically inhibit D2R internalization in HEK293 cells, and it could be significant. But, it is difficult to judge the significance of the observation without more in vivo data.

I would suggest the following. Remove all acronyms and abbreviations. Significantly, expand the Materials and Methods section, either in the manuscript or in the Supplemental section. I suggest clearly explaining each construct used, and the function of each module in the construct, with diagrams. In addition, provide a comprehensive step by step description of each experimental protocol, providing the reader with the rationale for each step in the protocol with explanatory diagrams. The authors should also more clearly explain the rationale and logic that was utilized to make the conclusions that they did from the depicted observations. Only then can a broader audience determine if the authors' conclusions are justified.

We thank the reviewer for his/her comments. Indeed, our main message was that two types of PUFAs (DHA and DPA) specifically alter D2R endocytosis by reducing the recruitment of β-arrestin2 without changing D2R clustering at the plasma membrane. We are sorry that our writing was not clear enough. We also found out that in the last steps of the submission to Review Commons, the first paragraph of the Discussion was inadvertently erased. This made our main conclusions, summarized in this first paragraph, less clear. We have now put back this important paragraph. Moreover, we have extensively rewritten the manuscript thriving to make it as clear as possible to a large audience. We have reduced the use of acronyms to keep only the most used ones [e.g. PUFA (used 99 times), DHA (37 times), GPCR (34 times), D2R (126 times), GRK (17 times)] and made them consistent throughout the manuscript. Following the reviewer's suggestion, we have also added a scheme of the steps following D2R activation by agonist leading to its internalization (Figure EV3).

We understand that the reviewer implies by "in vivo data" results obtained in the brain of animals. As written in the Introduction and in the Discussion, the current work follows up on a recently published manuscripts by a subset of the authors, namely (i) Ducrocq et al. 2020 (doi 10.1016/j.cmet.2020.02.012) in which we show that deficits in motivation in animals deprived in ω3-PUFAs can be restored specifically by conditional expression of a fatty acid desaturase from c. elegans (FAT1) that allows restoring PUFA levels specifically in D2R-expressing striatal projection neurons (which mediate the so-called indirect pathway), and (ii) Jobin et al. 2023 (doi: 10.1038/s41380-022-01928-6) which combines in cellulo (HEK 293 cells) and in vivo data to show that PUFAs affects the ligand binding of the dopamine D2 receptor and its signaling in a lipid context that reflects patient lipid profiles regarding poly-unsaturation levels.

Reviewer #2 (Significance (Required)):

• *

In summary, I will reiterate that the reported experiments need to be much better explained to make the study understandable to a broader audience and for that audience to determine whether the conclusions are justified.

• *

• *

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

• *

Summary:

The authors investigate the role of lipid polyunsaturation in endocytic uptake of the dopamine D2 receptor (D2R). To modulate the degree of unsaturation in live cell plasma membranes, the authors incubate cell lines with pure fatty acid that is metabolized and incorporated into the cellular membranes. To quantify the internalization of D2R in these live cells, the authors utilized quantitative fluorescence assays such as DERET and endosome analysis to determine the degree and rate of D2R internalization in the presence of two model agonists - dopamine and quinpirole. The authors conclude that when the PUFA content of the plasma membrane is increased (i.e., via ω3 or ω6 fatty acids), both the quantity and rate of D2R internalization decrease substantially. The authors confirmed that these phenomena are specific to D2R as caveolar endocytosis and clathrin-mediated endocytosis were unaffected when these same experimental techniques were utilized for β2 adrenergic receptor and transferrin. Additionally, the authors conclude that the clustering ability of D2R is unaffected by lipid unsaturation but that the ability of D2R clusters to interact with β-arrestin2 is inhibited in the presence of excess PUFA. Based on these findings, the authors propose several hypothetical mechanisms for lipid-D2R interactions on the plasma membrane, which will likely be the scope of future work.

Overall, this is a highly thorough and rigorous body of work that convincingly illustrates the connection between PUFA levels and D2R activity. However, I do not agree with the authors' conclusions pertaining to how their results should be interpreted in the context of fatty acid-related disorders. Additionally, this manuscript could benefit from some reorganization which would present the work more clearly. Please see the comments below.

We thank the reviewer for the positive appreciation of our work, qualified as a "thorough and rigorous body of work that convincingly illustrates the connection between PUFA levels and D2R activity". We will address the specific points raised by the reviewer with our answers below.

Comments:

1. • A recurring motivation for this study that is brought up by the authors is that dietary deficiency of ω3 fatty acids is tied to D2R dysfunction. This would indicate that PUFA reduction in the plasma membrane results in D2R dysfunction. However, the experiments emphasized in this manuscript investigate the condition where PUFA content is INCREASED in the plasma membrane and D2R function is compromised. It seems inappropriate for the authors to cite dietary deficiency of ω3 as a motivation when they experimentally test a condition that is tied to ω3 surplus.* Regarding the general comment of the reviewer, we agree that direct conclusion cannot be drawn on the etiology of psychiatric disorders by looking at the effect of membrane fatty acid levels on D2R in HEK 293 cells. Nevertheless, we mention in the Introduction the intriguing occurrence of low PUFA levels in psychiatric disorders as starting point to look at D2R as an important target for psychoactive drugs prescribed for these disorders. In the Discussion, we propose that manipulating fatty acid levels might potentiate the efficacy of D2R ligands used as treatments. We felt raising these aspects was not putting too much emphasis on psychiatric disorders. However, in accordance with the reviewer's comment, we toned down these descriptions in the revised manuscript.

The goal of increasing the levels of fatty acids at the membrane in HEK 293, the most widely used cellular system to study GPCR trafficking, was to try to emulate the levels of lipids in brain cells. Indeed, the levels of PUFAs in our culture conditions are much lower (~8 %, Figure 1B) than in brain extracts (~30 %). Therefore, the "control" condition in HEK 293 cells would correspond to PUFA deficiency while after our enrichment protocol these levels are closer to those found in brain cells. Our results could therefore be interpreted as endocytosis of D2R being augmented under membrane PUFA decrease. Importantly, increased receptor internalization often correlates with decreased signaling. Therefore, membrane PUFA enrichment in our conditions would rather potentiate D2R signaling.

• Following up on the first comment, the authors' results seem to indicate that excess ω3's are detrimental to D2R function. This result would be at odds with the conventional view that ω3's are essential and that excessive ω3 may not be harmful. The authors should rationalize their findings in the context of what is known about excess dietary ω3.*

The Reviewer is right that the conventional view is that excessive ω3 PUFA may not be harmful. However, this rather applies to dietary consumption, which might have limited effect to brain fatty acid contents since their accretion is highly regulated. Moreover, the majority of studies looking at ω3 supplementation have been performed in young adults and the effects on the developing brain - as it might be happening in pathological conditions in which D2R is involved - remain poorly understood. Furthermore, as mentioned above, blunted internalization of D2R under membrane PUFA enrichment is not an indication of "detrimental" to D2R function. Nor do we argue that membrane enrichment corresponds to excess PUFAs.

• I would argue that the control experiments with saturated fatty acids (i.e., Behenic Acid in figure 1), represent a scenario mimicking ω3 deficiency as the enrichment of Behenic Acid causes an overall reduction in PUFAs (Figure EV1C - an increase in SFA must correspond to a decrease in PUFA). These Behenic acid results are the only experiments presented by the authors that mimic a scenario resembling ω3 deficiency and the results show that the D2R internalization is unaffected (Figure 1G-H). Therefore, I would further argue that if anything, the authors results suggest that ω3 deficiency is NOT correlated to D2R internalization. Again, the authors must rationalize these findings in the context of what is known about dietary intake of ω3's.*

The Reviewer must refer to the fact that nutrients rich in SFAs are usually poor in PUFAs and vice-versa. Based on our lipidomic analysis, we now present in Figure 1B the effect of treatments (DHA, DPA, BA) on the levels of PUFAs (Figure 1B) and saturated fatty acids (Figure 1C). In cells treated with behenic acid (BA), PUFA levels are not significantly changed relative to control, untreated cells, while saturated fatty acid levels are increased. BA was used here to determine whether the effects observed with PUFAs was related to the enrichment in unsaturations or due to carbon chain length (C22). It is not the case because BA treatment, unlike DHA or DPA treatment, does not affect D2R endocytosis (Figure 2G,H).

• It's not clear why the authors decided to include an ω6 fatty acid in this study. The authors built up a detailed rationale for investigating ω3's as they are dietarily essential and tied to disease when deficient. To my knowledge, ω6's are considered much less beneficial than ω3's in a dietary sense. The inclusion of an ω6 almost seems coerced as the ω6-related results don't provide any interesting additional insights. It would benefit the manuscript if the authors provided some additional discussion explaining why ω6's are being investigated in addition to ω3's. *

We agree that we could have made the rationale clearer. The goal in comparing ω3-DHA and ω6-DPA was to assess whether the position of the first unsaturation (n-3 vs n-6), with the same carbon chain length (C22) might differentially impact D2R endocytosis.

• In Figure EV1D, the AHA and DPA percentages each increase by ~6%. The corresponding Figure EV1B indicates that the overall PUFA% in the plasma membrane also increases by 6%. This makes sense as the total change in PUFA content is consistent with the amount of AHA or DPA being internalized to cells. However, this consistency was not observed with BA and SFAs. In Figure EV1E, the BA percentage increases only ~1% while the total SFA percentage in Figure EV1C increases by ~6%. How can something undergoing a 1% change (relative to total lipid content) result in a 6% overall change in SFA content?*

The reviewer is correct: the level of SFAs is increased by 5.2% (34.5 % of total FAs in control cells to 39.7 % in BA treated cells), more than the increase in BA alone (1.18% from 0.35 % to 1.53 %). A close look at our lipidomics data showed that many of the 10 saturated fatty acids quantified are enhanced. In particular, the two most abundant ones, palmitic acid (16:0) and stearic acid (18:0) are increased, from 21.37 % to 22.28 % and 8.47 % to 11.17%, respectively. The reasons for these apparent discrepancies may involve lipid metabolic pathways which convert the rare and long BA into more common and shorter SFAs to preserve lipid contents and thus membrane properties.

• In Figure 4, the discussion of kinetics does not make sense. How exactly are kinetics being monitored in this figure? (Recruitment kinetics are discussed in panels D and G)*

We wanted to convey the impression that the time to reach the peak βarr2-mCherry recruitment was shorter in PUFA-treated cells than in control cells. However, after analyzing the kinetics in individual cells, we did not find a statistically significant difference in the time to maximum fluorescence. Therefore, we removed this reference to the kinetics of recruitment.

We now write: " However, treatment with DHA or DPA significantly decreased peak βarr2-mCherry fluorescence (Figure 5F-G).."

• In Figure 5, What is the purpose of panel D? Would it be more helpful to include additional, overlaid "cumulative N" plots for scenarios in which PUFAs were enriched? This would work well in conjunction with panel F.*

The purpose of this panel is to show the kinetics of increase in the frequency of endocytic vesicle formation upon agonist addition, and the decrease in frequency when the agonist is removed. We have now added examples of cells treated with DHA and DPA of similar surface for direct comparison with control (EtOH) cells.

• For the readers who are new to this area or unfamiliar with the assays used, Figure 1 is not intuitive and initially difficult to interpret. It would greatly benefit the flow of the manuscript if Figures EV1A-C and EV2A were included in the main text and "Normalized R" was clearly defined in the main text, prior to discussion of Figure 1.*

We have now transferred Figure EV1 as Figure 1. We have adapted the scheme of the DERET assay and its legend (now in Figure EV1A) to make it clearer. We did not put in Figure 2 because this figure is already very big. We have changed "Normalized R" to "Ratio 620/520) (% max)" to be clearer and more consistent with the scheme.

Reviewer #3 (Significance (Required)):

• *

General assessment: The work, for the most part, is rigorous and scientifically sound. The authors utilize impressive, quantitative assays to expand our understanding of protein-lipid interactions. However, the authors need to improve their discussion of the actual physiological conditions that correspond to their experimental results.

• *

Advance: This work may fill a gap in our understanding of disorders related to the dopamine D2 receptor. However, some of the results may be at odds with what is currently known/understood about dietary ω3 fatty acids.

• *

Audience: This work will be of broad interest to researchers in the biophysics field, with particular emphasis on researchers who study protein and membrane biophysics. This work will also be of interest to researchers who study membrane molecular biology.

• *

Reviewer Expertise: quantitative fluorescence spectroscopy and microscopy; membrane biophysics; protein-lipid interactions

• *

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Summary:

The authors investigate the role of lipid polyunsaturation in endocytic uptake of the dopamine D2 receptor (D2R). To modulate the degree of unsaturation in live cell plasma membranes, the authors incubate cell lines with pure fatty acid that is metabolized and incorporated into the cellular membranes. To quantify the internalization of D2R in these live cells, the authors utilized quantitative fluorescence assays such as DERET and endosome analysis to determine the degree and rate of D2R internalization in the presence of two model agonists - dopamine and quinpirole. The authors conclude that when the PUFA content of the plasma membrane is increased (i.e., via ω3 or ω6 fatty acids), both the quantity and rate of D2R internalization decrease substantially. The authors confirmed that these phenomena are specific to D2R as caveolar endocytosis and clathrin-mediated endocytosis were unaffected when these same experimental techniques were utilized for β2 adrenergic receptor and transferrin. Additionally, the authors conclude that the clustering ability of D2R is unaffected by lipid unsaturation but that the ability of D2R clusters to interact with β-arrestin2 is inhibited in the presence of excess PUFA. Based on these findings, the authors propose several hypothetical mechanisms for lipid-D2R interactions on the plasma membrane, which will likely be the scope of future work.

Overall, this is a highly thorough and rigorous body of work that convincingly illustrates the connection between PUFA levels and D2R activity. However, I do not agree with the authors' conclusions pertaining to how their results should be interpreted in the context of fatty acid-related disorders. Additionally, this manuscript could benefit from some reorganization which would present the work more clearly. Please see the comments below.

Comments:

1. A recurring motivation for this study that is brought up by the authors is that dietary deficiency of ω3 fatty acids is tied to D2R dysfunction. This would indicate that PUFA reduction in the plasma membrane results in D2R dysfunction. However, the experiments emphasized in this manuscript investigate the condition where PUFA content is INCREASED in the plasma membrane and D2R function is compromised. It seems inappropriate for the authors to cite dietary deficiency of ω3 as a motivation when they experimentally test a condition that is tied to ω3 surplus.
2. Following up on the first comment, the authors' results seem to indicate that excess ω3's are detrimental to D2R function. This result would be at odds with the conventional view that ω3's are essential and that excessive ω3 may not be harmful. The authors should rationalize their findings in the context of what is known about excess dietary ω3.
3. I would argue that the control experiments with saturated fatty acids (i.e., Behenic Acid in figure 1), represent a scenario mimicking ω3 deficiency as the enrichment of Behenic Acid causes an overall reduction in PUFAs (Figure EV1C - an increase in SFA must correspond to a decrease in PUFA). These Behenic acid results are the only experiments presented by the authors that mimic a scenario resembling ω3 deficiency and the results show that the D2R internalization is unaffected (Figure 1G-H). Therefore, I would further argue that if anything, the authors results suggest that ω3 deficiency is NOT correlated to D2R internalization. Again, the authors must rationalize these findings in the context of what is known about dietary intake of ω3's.
4. It's not clear why the authors decided to include an ω6 fatty acid in this study. The authors built up a detailed rationale for investigating ω3's as they are dietarily essential and tied to disease when deficient. To my knowledge, ω6's are considered much less beneficial than ω3's in a dietary sense. The inclusion of an ω6 almost seems coerced as the ω6-related results don't provide any interesting additional insights. It would benefit the manuscript if the authors provided some additional discussion explaining why ω6's are being investigated in addition to ω3's.
5. In Figure EV1D, the AHA and DPA percentages each increase by ~6%. The corresponding Figure EV1B indicates that the overall PUFA% in the plasma membrane also increases by 6%. This makes sense as the total change in PUFA content is consistent with the amount of AHA or DPA being internalized to cells. However, this consistency was not observed with BA and SFAs. In Figure EV1E, the BA percentage increases only ~1% while the total SFA percentage in Figure EV1C increases by ~6%. How can something undergoing a 1% change (relative to total lipid content) result in a 6% overall change in SFA content?
6. In Figure 4, the discussion of kinetics does not make sense. How exactly are kinetics being monitored in this figure? (Recruitment kinetics are discussed in panels D and G)
7. In Figure 5, What is the purpose of panel D? Would it be more helpful to include additional, overlaid "cumulative N" plots for scenarios in which PUFAs were enriched? This would work well in conjunction with panel F.
8. For the readers who are new to this area or unfamiliar with the assays used, Figure 1 is not intuitive and initially difficult to interpret. It would greatly benefit the flow of the manuscript if Figures EV1A-C and EV2A were included in the main text and "Normalized R" was clearly defined in the main text, prior to discussion of Figure 1.

Significance

General assessment: The work, for the most part, is rigorous and scientifically sound. The authors utilize impressive, quantitative assays to expand our understanding of protein-lipid interactions. However, the authors need to improve their discussion of the actual physiological conditions that correspond to their experimental results.

Advance: This work may fill a gap in our understanding of disorders related to the dopamine D2 receptor. However, some of the results may be at odds with what is currently known/understood about dietary ω3 fatty acids.

Audience: This work will be of broad interest to researchers in the biophysics field, with particular emphasis on researchers who study protein and membrane biophysics. This work will also be of interest to researchers who study membrane molecular biology.

Reviewer Expertise: quantitative fluorescence spectroscopy and microscopy; membrane biophysics; protein-lipid interactions

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

The only conclusion that I was able to understand from the study was that enrichment of cell membranes with polyunsaturated fatty acids specifically inhibited agonist-induced internalization of D2 receptors. However, I think that the experiments used to conclude that PUFAs do not alter D2R clustering but reduce the recruitment of β-arrestin2 and D2R endocytosis need some clarification (i.e. data depicted in Fig. 2-5). This lack of clarity might be due to the fact I am not familiar enough with the employed technologies or to the unclear writing style of the paper . There was an overuse of acronyms, initialisms and abbreviations, which are difficult to understand for researchers outside of the specific lipid field. I think that the manuscript should be written in a way to be legible also for researchers not working in the immediate filed.

The paper was not written in a manner that a general audience of cell biologists or those interested in GPCR biology could understand and judge. It is indeed interesting that polyunsaturated fatty acids specifically inhibit D2R internalization in HEK293 cells, and it could be significant. But, it is difficult to judge the significance of the observation without more in vivo data.

I would suggest the following. Remove all acronyms and abbreviations. Significantly, expand the Materials and Methods section, either in the manuscript or in the Supplemental section. I suggest clearly explaining each construct used, and the function of each module in the construct, with diagrams. In addition, provide a comprehensive step by step description of each experimental protocol, providing the reader with the rationale for each step in the protocol with explanatory diagrams. The authors should also more clearly explain the rationale and logic that was utilized to make the conclusions that they did from the depicted observations. Only then can a broader audience determine if the authors' conclusions are justified.

Significance

In summary, I will reiterate that the reported experiments need to be much better explained to make the study understandable to a broader audience and for that audience to determine whether the conclusions are justified.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

The manuscript, using different live and fixed cell trafficking assays, demonstrates that incorporation of poly-unsaturated, but not saturated, free fatty acids in the membrane phospholipids reduce agonist induced internalization of the D2 dopamine receptor but not the adrenergic beta2 receptors or the transferrin receptor. Pulsed pH (ppH) live microscopy further demonstrated that the reduced internalization by incorporation of free fatty acid was accompanied by a blunted recruitment of Beta-arrestin for the D2R.

I believe said claims put forward in the manuscript are overall well supported by the data and as such I do not believe that further experiments are necessarily needed to uphold these key claims. Also, the methodology is satisfactorily reported, and statistics are robust, although two-way Anova like used in Fig 1 seems appropriate for Fig 2 and 3

That said, I suggest that the fixed cell internalization experiments (Fig 2 and 3), which relate the effect on the D2R to B2AR and transferrin are revised. This is important since this is relevant to judge whether the effect is a general or a selective molecular mechanism since this is the one of the three assay which this comparison relies on. Alternatively, I suggest omitting this data and include the B2AR in the Live DERET assay and both B2AR and TfR in the ppH assay. Specifically, my concerns with the fixed cell internalization are:

• The analysis is based on counting the number of endosomes, which is not necessarily equivalent to the number of receptors internalized
• The analysis relies on fully effective stripping of the surface pool of receptors - i.e clustered surface receptors not stripped by the protocol will be assessed as internalized. It is often very difficult to obtain full efficiency of the Flag-tag stripping and this is somewhat expression dependent.
• The protocol for the constitutive and agonist induced internalization is different and yet shown on the same absolute graph. Although I take it the microscope gain setting are unaltered between the constitutive and agonist induced internalization I don't believe the quantification can be directly related. This is confusing at the very least. More critically however, the membrane signal from the non-stripped condition of constitutive internalization will likely fully shield internalized receptors in the Rab4 membrane proximal recycling pathway leading to under-estimation of the in the constitutive endocytosis. I believe this methodological limitation underlies the massive relative difference in the constitutive endocytosis between panel 2A,B and 2C,D. For comparison, by a quantitative dual color FACS endocytosis assay, we have previously demonstrated the ligand endocytosis a ~4 fold increased over constitutive (in concert with Fig 2A,B here) (Schmidt et al 20XX). Importantly, high relative variability by this methodology could well shield an actual effect of incorporation of FFAs on the constitutive endocytosis.

'Optional' Also, it would be informative to see the ppH Beta-arrestin experiments with the B2AR to assess, whether the putative discrepancy between D2R and B2AR is upstream or downstream of the blunted Beta-arrestin recruitment. To the same point, it would be very informative to assess how the incorporation of the free fatty acids affect receptor signalling, which would also help relate the effect of incorporation of the FFA's in the phospholipids to previous experiment using short term incubation with FFA's

References overall seem appropriate although Schmidt et al would be relevant for reference of the constitutive vs agonist induced endocytosis of D2R and B2AR. Overall, the figures are well composed and convey the messages fairly well. Specific point that would strengthen the rigor include:

• Chosing actual representative pictures of the qunatiative data in Fig 2 and 3 (e.g. har to see 25 endocytic events in Fig 2A constitutive endo, EtOH)
• Showing actual p values for the statistical comparisions

Moreover, for ease of reading the figures (without consulting the legend repeatedly) it would be very helpful to headline individual panel with what the experiments assesses. Figure 1a and 1b for example can't be distinguished at all before reading the figure legend. Also, y-axis could be more informative on what I measured rather than just giving the unit.

Finally, the figure presentation and description of S1 is very hard to follow. I cannot really make out what is assessed in the different panels.

Significance

The strength of the manuscript is the use and validation of incorporation of FFA's in the plasma membrane, which more closely mimics the physiological situation than brief application of FFAs as often done. Is addition, the blunted recruitment of beta-arrestin as assessed by the ppH protocol is quite intriguing mechanistically. The limitation are the relative narrow focus on the D2 receptor (and not multiple GPCRs) that does not really speak to as or assess the physiological, pathophysiological or therapeutic role of the observations (except from referring the relation between FFAs and disease). Also, despite the putative role of Beta-arrestin recruitment in the process, the actual causation in the process is not clear. This shortcoming is underscored by the putative effect on the constitutive internalization described above.

My specific expertise for assessing the paper is within general trafficking processes (including the trafficking methodology applied), trafficking of GPCRs and function of the dopamine system including the role of D2 receptors.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

Compared to our initial submission to Review Commons, we have addressed all the reviewers' comments. We have extensively re-written the manuscript to make it clearer to a larger audience. In particular, we have transferred Figure EV1 to Figure 1 with more complete panels and included a scheme (Figure EV3) on the steps of D2R internalization which we measure with live cell imaging. We have added a new paragraph to the start of the Discussion to summarize our main conclusions and reordered the discussion on the possible mechanisms of membrane PUFA enrichment on D2R endocytosis. All the changes in the text are in red for easier comparison with the previous version.

As suggested by reviewer 1, we have performed additional experiments to test the specificity of the effects of PUFA treatments on D2R endocytosis, reinforcing the results shown in Figure 4 using feeding assays. We show with live cell TIRF imaging and the ppH assay that TfR-SEP endocytosis is not affected (Figure EV5) and that SEP-β2AR endocytosis and βarr2-mCherry recruitment to the plasma membrane are not affected (Figure EV6).

Reviewer #1

Evidence, reproducibility and clarity

*The manuscript, using different live and fixed cell trafficking assays, demonstrates that incorporation of poly-unsaturated, but not saturated, free fatty acids in the membrane phospholipids reduce agonist induced internalization of the D2 dopamine receptor but not the adrenergic beta2 receptors or the transferrin receptor. Pulsed pH (ppH) live microscopy further demonstrated that the reduced internalization by incorporation of free fatty acid was accompanied by a blunted recruitment of Beta-arrestin for the D2R.

I believe said claims put forward in the manuscript are overall well supported by the data and as such I do not believe that further experiments are necessarily needed to uphold these key claims. Also, the methodology is satisfactorily reported, and statistics are robust, although two-way Anova like used in Fig 1 seems appropriate for Fig 2 and 3*

We thank the reviewer for his/her positive assessment of our work. We have checked the statistical tests used for all our measures. For Figure 2 and 3 (now 3 and 4) we test for only one factor (PUFA treatment or not) so we ran ordinary one-way ANOVA using Graphpad Prism.

That said, I suggest that the fixed cell internalization experiments (Fig 2 and 3), which relate the effect on the D2R to B2AR and transferrin are revised. This is important since this is relevant to judge whether the effect is a general or a selective molecular mechanism since this is the one of the three assay which this comparison relies on. Alternatively, I suggest omitting this data and include the B2AR in the Live DERET assay and both B2AR and TfR in the ppH assay. Specifically, my concerns with the fixed cell internalization are: • The analysis is based on counting the number of endosomes, which is not necessarily equivalent to the number of receptors internalized

The number of puncta, as well as their fluorescence, is reported by the analysis program (written in Matlab2021 and available upon request). We chose to show number of puncta because they reflect more directly the number of labelled endosomes (in Figures 3 and 4). As shown in the figure below, we found slight but significant differences between groups for FLAG-D2R (88.6 % and 87.6 % of average fluorescence in DHA and DPA treated cells compared to control cells), (panel A), and no differences for FLAG-β2AR (panel B). We find a significant decrease in puncta fluorescence for transferrin uptake in cells incubated with DHA (but not DPA) relative to control cells (panel C). However, because we did not detect differences in the number of puncta or in the frequency and amplitude of endocytic vesicle creation events (see below), we still conclude that enrichment with exogenous PUFAs does not affect clathrin mediated endocytosis.

In conclusion, the most robust measure of endocytosis for this assay is the number of detected puncta per cell rather than their fluorescence.

• The analysis relies on fully effective stripping of the surface pool of receptors - i.e clustered surface receptors not stripped by the protocol will be assessed as internalized. It is often very difficult to obtain full efficiency of the Flag-tag stripping and this is somewhat expression dependent. • The protocol for the constitutive and agonist induced internalization is different and yet shown on the same absolute graph. Although I take it the microscope gain setting are unaltered between the constitutive and agonist induced internalization I don't believe the quantification can be directly related. This is confusing at the very least. More critically however, the membrane signal from the non-stripped condition of constitutive internalization will likely fully shield internalized receptors in the Rab4 membrane proximal recycling pathway leading to under-estimation of the in the constitutive endocytosis. I believe this methodological limitation underlies the massive relative difference in the constitutive endocytosis between panel 2A,B and 2C,D. For comparison, by a quantitative dual color FACS endocytosis assay, we have previously demonstrated the ligand endocytosis a ~4 fold increased over constitutive (in concert with Fig 2A,B here) (Schmidt et al 20XX). Importantly, high relative variability by this methodology could well shield an actual effect of incorporation of FFAs on the constitutive endocytosis. We thank the reviewer for pointing this difference in the protocol. As a matter of fact, we have not used acid stripping in all the conditions used for the uptake assays (Figures 3 and 4). We apologize for the confusion and we have clarified this point in the Methods section. In early experiments we compared conditions with or without stripping but we concluded from these experiments that indeed, the stripping was not complete. Moreover, we noticed early on that many cells treated with DHA or DPA did not have any detectable cluster (13 cells out of 58 quantified cells treated with DHA after addition of QPL, 12/56 cells treated with DPA, 0/68 for cells treated with vehicle). Stripping the antibody would have made these cells undetectable, biasing the analysis. Therefore, to make our results more consistent we decided to use non-stripping conditions. To detect endosomes specifically, we used a segmentation tool developed earlier (see Rosendale et al.* 2019). This tool is based on wavelet transforms which recognizes dot-like structures. In addition, we excluded from the cell mask the labelled plasma membrane by a mask erosion.

We agree the design of experiments was not aimed at comparing the effect of PUFA treatment on low levels of constitutive D2R endocytosis. This would require more sensitive assays and be addressed in subsequent studies.

'Optional' Also, it would be informative to see the ppH Beta-arrestin experiments with the B2AR to assess, whether the putative discrepancy between D2R and B2AR is upstream or downstream of the blunted Beta-arrestin recruitment. To the same point, it would be very informative to assess how the incorporation of the free fatty acids affect receptor signalling, which would also help relate the effect of incorporation of the FFA's in the phospholipids to previous experiment using short term incubation with FFA's

We have now performed live imaging experiments in HEK293 cells expressing SEP-β2AR, GRK2 and βarr2-mCherry and stimulated with isoproterenol (Figure EV6). We show that the clustering of SEP-β2AR, of βarr2-mCherry, as well as endocytosis, are not affected by treatments with DHA or DPA. In this study, we focused on the early trafficking steps of D2R internalization. It will be interesting in a future study to address its consequences on G protein dependent and independent signaling. Moreover, and for good measure, we performed experiments to assess TfR-SEP endocytosis with the ppH assay. Again, we found no difference between cells treated or not with PUFAs (Figure EV5)

*References overall seem appropriate although Schmidt et al would be relevant for reference of the constitutive vs agonist induced endocytosis of D2R and B2AR. *

We have now cited Schmidt et al. 2020 doi 10.1111/bcpt.13274 in the discussion with the following sentences: "D2R also shows constitutive endocytosis (Schmidt et al, 2020) which may be modulated by PUFAs although we did not detect any significant difference in our measures (see Figure 3) which were aimed at detecting high levels of internalization induced by agonists. Further work will be required to specifically examine the effect of PUFAs on constitutive GPCR internalization."

Overall, the figures are well composed and convey the messages fairly well. Specific point that would strengthen the rigor include: • Chosing actual representative pictures of the quantitative data in Fig 2 and 3 (e.g. hard to see 25 endocytic events in Fig 2A constitutive endo, EtOH)

We apologize for the confusion. We employ a normalization procedure to account for cell size. In addition, all numbers have been normalized to the condition stimulated with agonist with no PUFA treatment). In fact, we detect in unstimulated cells very few puncta (on average 0.6, range 0-5) compared to 27.3 clusters (range 2-87) in cells stimulated with QPL.

• Showing actual p values for the statistical comparisons* For easier reading, we have kept the stars convention for the figures but added two tables with all statistical tests and the p values for both main figures and EV figures.

Moreover, for ease of reading the figures (without consulting the legend repeatedly) it would be very helpful to headline individual panel with what the experiments assesses. Figure 1a and 1b for example can't be distinguished at all before reading the figure legend. Also, y-axis could be more informative on what I measured rather than just giving the unit.

We have added titles to panels (in particular for Figure 2A,B which correspond to former Figure 1A,B) and we have given new titles to Y axes to make them clearer. We hope that the reading of our figures will now be easier.

Finally, the figure presentation and description of S1 is very hard to follow. I cannot really make out what is assessed in the different panels.

We have changed substantially Figure EV1 (now Figure 1) with new presentation of data: all 4 conditions (control, treated with DHA, DPA or BA) systematically presented in the same graph, and clearer titles for the parameter displayed on the Y axes. We hope that this figure is now easier to follow.

Significance

*The strength of the manuscript is the use and validation of incorporation of FFA's in the plasma membrane, which more closely mimics the physiological situation than brief application of FFAs as often done. Is addition, the blunted recruitment of beta-arrestin as assessed by the ppH protocol is quite intriguing mechanistically. The limitation are the relative narrow focus on the D2 receptor (and not multiple GPCRs) that does not really speak to as or assess the physiological, pathophysiological or therapeutic role of the observations (except from referring the relation between FFAs and disease). Also, despite the putative role of Beta-arrestin recruitment in the process, the actual causation in the process is not clear. This shortcoming is underscored by the putative effect on the constitutive internalization described above.

My specific expertise for assessing the paper is within general trafficking processes (including the trafficking methodology applied), trafficking of GPCRs and function of the dopamine system including the role of D2 receptors.*

• *

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

• *

The only conclusion that I was able to understand from the study was that enrichment of cell membranes with polyunsaturated fatty acids specifically inhibited agonist-induced internalization of D2 receptors. However, I think that the experiments used to conclude that PUFAs do not alter D2R clustering but reduce the recruitment of β-arrestin2 and D2R endocytosis need some clarification (i.e. data depicted in Fig. 2-5). This lack of clarity might be due to the fact I am not familiar enough with the employed technologies or to the unclear writing style of the paper. There was an overuse of acronyms, initialisms and abbreviations, which are difficult to understand for researchers outside of the specific lipid field. I think that the manuscript should be written in a way to be legible also for researchers not working in the immediate filed.

The paper was not written in a manner that a general audience of cell biologists or those interested in GPCR biology could understand and judge. It is indeed interesting that polyunsaturated fatty acids specifically inhibit D2R internalization in HEK293 cells, and it could be significant. But, it is difficult to judge the significance of the observation without more in vivo data.

I would suggest the following. Remove all acronyms and abbreviations. Significantly, expand the Materials and Methods section, either in the manuscript or in the Supplemental section. I suggest clearly explaining each construct used, and the function of each module in the construct, with diagrams. In addition, provide a comprehensive step by step description of each experimental protocol, providing the reader with the rationale for each step in the protocol with explanatory diagrams. The authors should also more clearly explain the rationale and logic that was utilized to make the conclusions that they did from the depicted observations. Only then can a broader audience determine if the authors' conclusions are justified.

We thank the reviewer for his/her comments. Indeed, our main message was that two types of PUFAs (DHA and DPA) specifically alter D2R endocytosis by reducing the recruitment of β-arrestin2 without changing D2R clustering at the plasma membrane. We are sorry that our writing was not clear enough. We also found out that in the last steps of the submission to Review Commons, the first paragraph of the Discussion was inadvertently erased. This made our main conclusions, summarized in this first paragraph, less clear. We have now put back this important paragraph. Moreover, we have extensively rewritten the manuscript thriving to make it as clear as possible to a large audience. We have reduced the use of acronyms to keep only the most used ones [e.g. PUFA (used 99 times), DHA (37 times), GPCR (34 times), D2R (126 times), GRK (17 times)] and made them consistent throughout the manuscript. Following the reviewer's suggestion, we have also added a scheme of the steps following D2R activation by agonist leading to its internalization (Figure EV3).

We understand that the reviewer implies by "in vivo data" results obtained in the brain of animals. As written in the Introduction and in the Discussion, the current work follows up on a recently published manuscripts by a subset of the authors, namely (i) Ducrocq et al. 2020 (doi 10.1016/j.cmet.2020.02.012) in which we show that deficits in motivation in animals deprived in ω3-PUFAs can be restored specifically by conditional expression of a fatty acid desaturase from c. elegans (FAT1) that allows restoring PUFA levels specifically in D2R-expressing striatal projection neurons (which mediate the so-called indirect pathway), and (ii) Jobin et al. 2023 (doi: 10.1038/s41380-022-01928-6) which combines in cellulo (HEK 293 cells) and in vivo data to show that PUFAs affects the ligand binding of the dopamine D2 receptor and its signaling in a lipid context that reflects patient lipid profiles regarding poly-unsaturation levels.

Reviewer #2 (Significance (Required)):

• *

In summary, I will reiterate that the reported experiments need to be much better explained to make the study understandable to a broader audience and for that audience to determine whether the conclusions are justified.

• *

• *

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

• *

Summary:

The authors investigate the role of lipid polyunsaturation in endocytic uptake of the dopamine D2 receptor (D2R). To modulate the degree of unsaturation in live cell plasma membranes, the authors incubate cell lines with pure fatty acid that is metabolized and incorporated into the cellular membranes. To quantify the internalization of D2R in these live cells, the authors utilized quantitative fluorescence assays such as DERET and endosome analysis to determine the degree and rate of D2R internalization in the presence of two model agonists - dopamine and quinpirole. The authors conclude that when the PUFA content of the plasma membrane is increased (i.e., via ω3 or ω6 fatty acids), both the quantity and rate of D2R internalization decrease substantially. The authors confirmed that these phenomena are specific to D2R as caveolar endocytosis and clathrin-mediated endocytosis were unaffected when these same experimental techniques were utilized for β2 adrenergic receptor and transferrin. Additionally, the authors conclude that the clustering ability of D2R is unaffected by lipid unsaturation but that the ability of D2R clusters to interact with β-arrestin2 is inhibited in the presence of excess PUFA. Based on these findings, the authors propose several hypothetical mechanisms for lipid-D2R interactions on the plasma membrane, which will likely be the scope of future work.

Overall, this is a highly thorough and rigorous body of work that convincingly illustrates the connection between PUFA levels and D2R activity. However, I do not agree with the authors' conclusions pertaining to how their results should be interpreted in the context of fatty acid-related disorders. Additionally, this manuscript could benefit from some reorganization which would present the work more clearly. Please see the comments below.

We thank the reviewer for the positive appreciation of our work, qualified as a "thorough and rigorous body of work that convincingly illustrates the connection between PUFA levels and D2R activity". We will address the specific points raised by the reviewer with our answers below.

Comments:

1. • A recurring motivation for this study that is brought up by the authors is that dietary deficiency of ω3 fatty acids is tied to D2R dysfunction. This would indicate that PUFA reduction in the plasma membrane results in D2R dysfunction. However, the experiments emphasized in this manuscript investigate the condition where PUFA content is INCREASED in the plasma membrane and D2R function is compromised. It seems inappropriate for the authors to cite dietary deficiency of ω3 as a motivation when they experimentally test a condition that is tied to ω3 surplus.* Regarding the general comment of the reviewer, we agree that direct conclusion cannot be drawn on the etiology of psychiatric disorders by looking at the effect of membrane fatty acid levels on D2R in HEK 293 cells. Nevertheless, we mention in the Introduction the intriguing occurrence of low PUFA levels in psychiatric disorders as starting point to look at D2R as an important target for psychoactive drugs prescribed for these disorders. In the Discussion, we propose that manipulating fatty acid levels might potentiate the efficacy of D2R ligands used as treatments. We felt raising these aspects was not putting too much emphasis on psychiatric disorders. However, in accordance with the reviewer's comment, we toned down these descriptions in the revised manuscript.

The goal of increasing the levels of fatty acids at the membrane in HEK 293, the most widely used cellular system to study GPCR trafficking, was to try to emulate the levels of lipids in brain cells. Indeed, the levels of PUFAs in our culture conditions are much lower (~8 %, Figure 1B) than in brain extracts (~30 %). Therefore, the "control" condition in HEK 293 cells would correspond to PUFA deficiency while after our enrichment protocol these levels are closer to those found in brain cells. Our results could therefore be interpreted as endocytosis of D2R being augmented under membrane PUFA decrease. Importantly, increased receptor internalization often correlates with decreased signaling. Therefore, membrane PUFA enrichment in our conditions would rather potentiate D2R signaling.

• Following up on the first comment, the authors' results seem to indicate that excess ω3's are detrimental to D2R function. This result would be at odds with the conventional view that ω3's are essential and that excessive ω3 may not be harmful. The authors should rationalize their findings in the context of what is known about excess dietary ω3.*

The Reviewer is right that the conventional view is that excessive ω3 PUFA may not be harmful. However, this rather applies to dietary consumption, which might have limited effect to brain fatty acid contents since their accretion is highly regulated. Moreover, the majority of studies looking at ω3 supplementation have been performed in young adults and the effects on the developing brain - as it might be happening in pathological conditions in which D2R is involved - remain poorly understood. Furthermore, as mentioned above, blunted internalization of D2R under membrane PUFA enrichment is not an indication of "detrimental" to D2R function. Nor do we argue that membrane enrichment corresponds to excess PUFAs.

• I would argue that the control experiments with saturated fatty acids (i.e., Behenic Acid in figure 1), represent a scenario mimicking ω3 deficiency as the enrichment of Behenic Acid causes an overall reduction in PUFAs (Figure EV1C - an increase in SFA must correspond to a decrease in PUFA). These Behenic acid results are the only experiments presented by the authors that mimic a scenario resembling ω3 deficiency and the results show that the D2R internalization is unaffected (Figure 1G-H). Therefore, I would further argue that if anything, the authors results suggest that ω3 deficiency is NOT correlated to D2R internalization. Again, the authors must rationalize these findings in the context of what is known about dietary intake of ω3's.*

The Reviewer must refer to the fact that nutrients rich in SFAs are usually poor in PUFAs and vice-versa. Based on our lipidomic analysis, we now present in Figure 1B the effect of treatments (DHA, DPA, BA) on the levels of PUFAs (Figure 1B) and saturated fatty acids (Figure 1C). In cells treated with behenic acid (BA), PUFA levels are not significantly changed relative to control, untreated cells, while saturated fatty acid levels are increased. BA was used here to determine whether the effects observed with PUFAs was related to the enrichment in unsaturations or due to carbon chain length (C22). It is not the case because BA treatment, unlike DHA or DPA treatment, does not affect D2R endocytosis (Figure 2G,H).

• It's not clear why the authors decided to include an ω6 fatty acid in this study. The authors built up a detailed rationale for investigating ω3's as they are dietarily essential and tied to disease when deficient. To my knowledge, ω6's are considered much less beneficial than ω3's in a dietary sense. The inclusion of an ω6 almost seems coerced as the ω6-related results don't provide any interesting additional insights. It would benefit the manuscript if the authors provided some additional discussion explaining why ω6's are being investigated in addition to ω3's. *

We agree that we could have made the rationale clearer. The goal in comparing ω3-DHA and ω6-DPA was to assess whether the position of the first unsaturation (n-3 vs n-6), with the same carbon chain length (C22) might differentially impact D2R endocytosis.

• In Figure EV1D, the AHA and DPA percentages each increase by ~6%. The corresponding Figure EV1B indicates that the overall PUFA% in the plasma membrane also increases by 6%. This makes sense as the total change in PUFA content is consistent with the amount of AHA or DPA being internalized to cells. However, this consistency was not observed with BA and SFAs. In Figure EV1E, the BA percentage increases only ~1% while the total SFA percentage in Figure EV1C increases by ~6%. How can something undergoing a 1% change (relative to total lipid content) result in a 6% overall change in SFA content?*

The reviewer is correct: the level of SFAs is increased by 5.2% (34.5 % of total FAs in control cells to 39.7 % in BA treated cells), more than the increase in BA alone (1.18% from 0.35 % to 1.53 %). A close look at our lipidomics data showed that many of the 10 saturated fatty acids quantified are enhanced. In particular, the two most abundant ones, palmitic acid (16:0) and stearic acid (18:0) are increased, from 21.37 % to 22.28 % and 8.47 % to 11.17%, respectively. The reasons for these apparent discrepancies may involve lipid metabolic pathways which convert the rare and long BA into more common and shorter SFAs to preserve lipid contents and thus membrane properties.

• In Figure 4, the discussion of kinetics does not make sense. How exactly are kinetics being monitored in this figure? (Recruitment kinetics are discussed in panels D and G)*

We wanted to convey the impression that the time to reach the peak βarr2-mCherry recruitment was shorter in PUFA-treated cells than in control cells. However, after analyzing the kinetics in individual cells, we did not find a statistically significant difference in the time to maximum fluorescence. Therefore, we removed this reference to the kinetics of recruitment.

We now write: " However, treatment with DHA or DPA significantly decreased peak βarr2-mCherry fluorescence (Figure 5F-G).."

• In Figure 5, What is the purpose of panel D? Would it be more helpful to include additional, overlaid "cumulative N" plots for scenarios in which PUFAs were enriched? This would work well in conjunction with panel F.*

The purpose of this panel is to show the kinetics of increase in the frequency of endocytic vesicle formation upon agonist addition, and the decrease in frequency when the agonist is removed. We have now added examples of cells treated with DHA and DPA of similar surface for direct comparison with control (EtOH) cells.

• For the readers who are new to this area or unfamiliar with the assays used, Figure 1 is not intuitive and initially difficult to interpret. It would greatly benefit the flow of the manuscript if Figures EV1A-C and EV2A were included in the main text and "Normalized R" was clearly defined in the main text, prior to discussion of Figure 1.*

We have now transferred Figure EV1 as Figure 1. We have adapted the scheme of the DERET assay and its legend (now in Figure EV1A) to make it clearer. We did not put in Figure 2 because this figure is already very big. We have changed "Normalized R" to "Ratio 620/520) (% max)" to be clearer and more consistent with the scheme.

Reviewer #3 (Significance (Required)):

• *

General assessment: The work, for the most part, is rigorous and scientifically sound. The authors utilize impressive, quantitative assays to expand our understanding of protein-lipid interactions. However, the authors need to improve their discussion of the actual physiological conditions that correspond to their experimental results.

• *

Advance: This work may fill a gap in our understanding of disorders related to the dopamine D2 receptor. However, some of the results may be at odds with what is currently known/understood about dietary ω3 fatty acids.

• *

Audience: This work will be of broad interest to researchers in the biophysics field, with particular emphasis on researchers who study protein and membrane biophysics. This work will also be of interest to researchers who study membrane molecular biology.

• *

Reviewer Expertise: quantitative fluorescence spectroscopy and microscopy; membrane biophysics; protein-lipid interactions

• *

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Summary:

The authors investigate the role of lipid polyunsaturation in endocytic uptake of the dopamine D2 receptor (D2R). To modulate the degree of unsaturation in live cell plasma membranes, the authors incubate cell lines with pure fatty acid that is metabolized and incorporated into the cellular membranes. To quantify the internalization of D2R in these live cells, the authors utilized quantitative fluorescence assays such as DERET and endosome analysis to determine the degree and rate of D2R internalization in the presence of two model agonists - dopamine and quinpirole. The authors conclude that when the PUFA content of the plasma membrane is increased (i.e., via ω3 or ω6 fatty acids), both the quantity and rate of D2R internalization decrease substantially. The authors confirmed that these phenomena are specific to D2R as caveolar endocytosis and clathrin-mediated endocytosis were unaffected when these same experimental techniques were utilized for β2 adrenergic receptor and transferrin. Additionally, the authors conclude that the clustering ability of D2R is unaffected by lipid unsaturation but that the ability of D2R clusters to interact with β-arrestin2 is inhibited in the presence of excess PUFA. Based on these findings, the authors propose several hypothetical mechanisms for lipid-D2R interactions on the plasma membrane, which will likely be the scope of future work.

Overall, this is a highly thorough and rigorous body of work that convincingly illustrates the connection between PUFA levels and D2R activity. However, I do not agree with the authors' conclusions pertaining to how their results should be interpreted in the context of fatty acid-related disorders. Additionally, this manuscript could benefit from some reorganization which would present the work more clearly. Please see the comments below.

Comments:

1. A recurring motivation for this study that is brought up by the authors is that dietary deficiency of ω3 fatty acids is tied to D2R dysfunction. This would indicate that PUFA reduction in the plasma membrane results in D2R dysfunction. However, the experiments emphasized in this manuscript investigate the condition where PUFA content is INCREASED in the plasma membrane and D2R function is compromised. It seems inappropriate for the authors to cite dietary deficiency of ω3 as a motivation when they experimentally test a condition that is tied to ω3 surplus.
2. Following up on the first comment, the authors' results seem to indicate that excess ω3's are detrimental to D2R function. This result would be at odds with the conventional view that ω3's are essential and that excessive ω3 may not be harmful. The authors should rationalize their findings in the context of what is known about excess dietary ω3.
3. I would argue that the control experiments with saturated fatty acids (i.e., Behenic Acid in figure 1), represent a scenario mimicking ω3 deficiency as the enrichment of Behenic Acid causes an overall reduction in PUFAs (Figure EV1C - an increase in SFA must correspond to a decrease in PUFA). These Behenic acid results are the only experiments presented by the authors that mimic a scenario resembling ω3 deficiency and the results show that the D2R internalization is unaffected (Figure 1G-H). Therefore, I would further argue that if anything, the authors results suggest that ω3 deficiency is NOT correlated to D2R internalization. Again, the authors must rationalize these findings in the context of what is known about dietary intake of ω3's.
4. It's not clear why the authors decided to include an ω6 fatty acid in this study. The authors built up a detailed rationale for investigating ω3's as they are dietarily essential and tied to disease when deficient. To my knowledge, ω6's are considered much less beneficial than ω3's in a dietary sense. The inclusion of an ω6 almost seems coerced as the ω6-related results don't provide any interesting additional insights. It would benefit the manuscript if the authors provided some additional discussion explaining why ω6's are being investigated in addition to ω3's.
5. In Figure EV1D, the AHA and DPA percentages each increase by ~6%. The corresponding Figure EV1B indicates that the overall PUFA% in the plasma membrane also increases by 6%. This makes sense as the total change in PUFA content is consistent with the amount of AHA or DPA being internalized to cells. However, this consistency was not observed with BA and SFAs. In Figure EV1E, the BA percentage increases only ~1% while the total SFA percentage in Figure EV1C increases by ~6%. How can something undergoing a 1% change (relative to total lipid content) result in a 6% overall change in SFA content?
6. In Figure 4, the discussion of kinetics does not make sense. How exactly are kinetics being monitored in this figure? (Recruitment kinetics are discussed in panels D and G)
7. In Figure 5, What is the purpose of panel D? Would it be more helpful to include additional, overlaid "cumulative N" plots for scenarios in which PUFAs were enriched? This would work well in conjunction with panel F.
8. For the readers who are new to this area or unfamiliar with the assays used, Figure 1 is not intuitive and initially difficult to interpret. It would greatly benefit the flow of the manuscript if Figures EV1A-C and EV2A were included in the main text and "Normalized R" was clearly defined in the main text, prior to discussion of Figure 1.

Significance

General assessment: The work, for the most part, is rigorous and scientifically sound. The authors utilize impressive, quantitative assays to expand our understanding of protein-lipid interactions. However, the authors need to improve their discussion of the actual physiological conditions that correspond to their experimental results.

Advance: This work may fill a gap in our understanding of disorders related to the dopamine D2 receptor. However, some of the results may be at odds with what is currently known/understood about dietary ω3 fatty acids.

Audience: This work will be of broad interest to researchers in the biophysics field, with particular emphasis on researchers who study protein and membrane biophysics. This work will also be of interest to researchers who study membrane molecular biology.

Reviewer Expertise: quantitative fluorescence spectroscopy and microscopy; membrane biophysics; protein-lipid interactions

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

The only conclusion that I was able to understand from the study was that enrichment of cell membranes with polyunsaturated fatty acids specifically inhibited agonist-induced internalization of D2 receptors. However, I think that the experiments used to conclude that PUFAs do not alter D2R clustering but reduce the recruitment of β-arrestin2 and D2R endocytosis need some clarification (i.e. data depicted in Fig. 2-5). This lack of clarity might be due to the fact I am not familiar enough with the employed technologies or to the unclear writing style of the paper . There was an overuse of acronyms, initialisms and abbreviations, which are difficult to understand for researchers outside of the specific lipid field. I think that the manuscript should be written in a way to be legible also for researchers not working in the immediate filed.

The paper was not written in a manner that a general audience of cell biologists or those interested in GPCR biology could understand and judge. It is indeed interesting that polyunsaturated fatty acids specifically inhibit D2R internalization in HEK293 cells, and it could be significant. But, it is difficult to judge the significance of the observation without more in vivo data.

I would suggest the following. Remove all acronyms and abbreviations. Significantly, expand the Materials and Methods section, either in the manuscript or in the Supplemental section. I suggest clearly explaining each construct used, and the function of each module in the construct, with diagrams. In addition, provide a comprehensive step by step description of each experimental protocol, providing the reader with the rationale for each step in the protocol with explanatory diagrams. The authors should also more clearly explain the rationale and logic that was utilized to make the conclusions that they did from the depicted observations. Only then can a broader audience determine if the authors' conclusions are justified.

Significance

In summary, I will reiterate that the reported experiments need to be much better explained to make the study understandable to a broader audience and for that audience to determine whether the conclusions are justified.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

The manuscript, using different live and fixed cell trafficking assays, demonstrates that incorporation of poly-unsaturated, but not saturated, free fatty acids in the membrane phospholipids reduce agonist induced internalization of the D2 dopamine receptor but not the adrenergic beta2 receptors or the transferrin receptor. Pulsed pH (ppH) live microscopy further demonstrated that the reduced internalization by incorporation of free fatty acid was accompanied by a blunted recruitment of Beta-arrestin for the D2R.

I believe said claims put forward in the manuscript are overall well supported by the data and as such I do not believe that further experiments are necessarily needed to uphold these key claims. Also, the methodology is satisfactorily reported, and statistics are robust, although two-way Anova like used in Fig 1 seems appropriate for Fig 2 and 3

That said, I suggest that the fixed cell internalization experiments (Fig 2 and 3), which relate the effect on the D2R to B2AR and transferrin are revised. This is important since this is relevant to judge whether the effect is a general or a selective molecular mechanism since this is the one of the three assay which this comparison relies on. Alternatively, I suggest omitting this data and include the B2AR in the Live DERET assay and both B2AR and TfR in the ppH assay. Specifically, my concerns with the fixed cell internalization are:

• The analysis is based on counting the number of endosomes, which is not necessarily equivalent to the number of receptors internalized
• The analysis relies on fully effective stripping of the surface pool of receptors - i.e clustered surface receptors not stripped by the protocol will be assessed as internalized. It is often very difficult to obtain full efficiency of the Flag-tag stripping and this is somewhat expression dependent.
• The protocol for the constitutive and agonist induced internalization is different and yet shown on the same absolute graph. Although I take it the microscope gain setting are unaltered between the constitutive and agonist induced internalization I don't believe the quantification can be directly related. This is confusing at the very least. More critically however, the membrane signal from the non-stripped condition of constitutive internalization will likely fully shield internalized receptors in the Rab4 membrane proximal recycling pathway leading to under-estimation of the in the constitutive endocytosis. I believe this methodological limitation underlies the massive relative difference in the constitutive endocytosis between panel 2A,B and 2C,D. For comparison, by a quantitative dual color FACS endocytosis assay, we have previously demonstrated the ligand endocytosis a ~4 fold increased over constitutive (in concert with Fig 2A,B here) (Schmidt et al 20XX). Importantly, high relative variability by this methodology could well shield an actual effect of incorporation of FFAs on the constitutive endocytosis.

'Optional' Also, it would be informative to see the ppH Beta-arrestin experiments with the B2AR to assess, whether the putative discrepancy between D2R and B2AR is upstream or downstream of the blunted Beta-arrestin recruitment. To the same point, it would be very informative to assess how the incorporation of the free fatty acids affect receptor signalling, which would also help relate the effect of incorporation of the FFA's in the phospholipids to previous experiment using short term incubation with FFA's

References overall seem appropriate although Schmidt et al would be relevant for reference of the constitutive vs agonist induced endocytosis of D2R and B2AR. Overall, the figures are well composed and convey the messages fairly well. Specific point that would strengthen the rigor include:

• Chosing actual representative pictures of the qunatiative data in Fig 2 and 3 (e.g. har to see 25 endocytic events in Fig 2A constitutive endo, EtOH)
• Showing actual p values for the statistical comparisions

Moreover, for ease of reading the figures (without consulting the legend repeatedly) it would be very helpful to headline individual panel with what the experiments assesses. Figure 1a and 1b for example can't be distinguished at all before reading the figure legend. Also, y-axis could be more informative on what I measured rather than just giving the unit.

Finally, the figure presentation and description of S1 is very hard to follow. I cannot really make out what is assessed in the different panels.

Significance

The strength of the manuscript is the use and validation of incorporation of FFA's in the plasma membrane, which more closely mimics the physiological situation than brief application of FFAs as often done. Is addition, the blunted recruitment of beta-arrestin as assessed by the ppH protocol is quite intriguing mechanistically. The limitation are the relative narrow focus on the D2 receptor (and not multiple GPCRs) that does not really speak to as or assess the physiological, pathophysiological or therapeutic role of the observations (except from referring the relation between FFAs and disease). Also, despite the putative role of Beta-arrestin recruitment in the process, the actual causation in the process is not clear. This shortcoming is underscored by the putative effect on the constitutive internalization described above.

My specific expertise for assessing the paper is within general trafficking processes (including the trafficking methodology applied), trafficking of GPCRs and function of the dopamine system including the role of D2 receptors.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Summary

In this manuscript, Széliová et al. used a simple self-replicating cell model to study why the ribosome consists of both RNA and protein from an economic point of view. Their base model predicts an RNA-only ribosome, which is not surprising since the smaller RNAP has a higher turnover number compared to the larger ribosome. When rRNA instability is included, the model predicts an "RNA+Protein" ribosome. In particular, the predicted ribosome composition is comparable to the measured ribosome composition when strong cooperative binding of ribosomal proteins to rRNA is considered. The authors conclude that the maximal growth rate is achieved by the real ribosome composition when rRNA instability is taken into account.

Major comments:

1. The authors modeled the rRNA degradation rate as a function of the concentration of fully assembled ribosomes (equation 5). However, only partially assembled ribosomes are susceptible to RNase, and they make up only a small fraction of total ribosomes. The majority of ribosomes are fully assembled. In addition, the turnover number obtained from Fazal et al. (2015) and used here is the degradation rate of double-stranded RNA, not the fully assembled ribosomes, which have a stable tertiary structure. In my opinion, the rRNA degradation rate should be modeled as a function of the concentration of partially assembled ribosomes (i.e., pre-R in Figure 7) rather than the concentration of fully assembled ribosomes.
2. Compared to the work by Kostinski and Reuveni (2020), the authors have made an improvement by avoiding the use of constant ribosome allocation to ribosomal protein (Φ_rP^R) and RNAP (Φ_RNAP^R), allowing these parameters to vary with predicted growth rates (by changing 𝑥_rP). This is indeed important, as bacteria are very likely to adjust these parameters in response to different growth conditions. However, certain other growth rate-dependent parameters are still treated as constants (or treated as nutrient-specific parameters) across predicted growth rates under given conditions. For example, experiments have shown that the fraction of active RNAP (f_RNAP^act) and the ribosome elongation rate (k_R^el) are growth rate-dependent (Bremer and Dennis, 1996). In contrast, when the authors predict the maximum growth rate by changing 𝑥_rP, f_RNAP^act and k_R^el are held constant regardless of the predicted growth rates.
3. If amino acids or nucleotides are provided in the media, the cell does not have to synthesize all of them de novo. However, the model assumes that the cell always synthesizes all amino acids or nucleotides de novo for growth on growth on amino acid-supplemented media or on LB. This problem could in principle be solved by assuming very fast kinetics of the metabolic reactions in these media, but that should be discussed in the manuscript. Furthermore, why does the turnover number for EAA depend on the growth rate while that of ENT is constant?
4. All parameters related to transcription (RNAP) and translation (ribosome) used in this manuscript are adopted from Kostinski and Reuveni (2020), which are slightly modified based on Bremer and Dennis' research (1996, 2008). However, the authors changed some of the original parameters or data points, but did not provide explanations for these changes:

(a) The original data depicted a growth rate-dependent translation elongation rate, but Table 2 presents it as a constant value.

(b) Figure 2b displays five experimental data points, as opposed to the six data points in the original dataset and other figures in this manuscript.

(c) The model does not consider the fraction of RNAP transcribing rRNA (Φ_rRNA^RNAP), except in Appendix Figure 4. In the original data (Bremer and Dennis 1996), the fraction of RNAP transcribing rRNA increases dramatically with growth rate; however, in this study, it remains constant at 1. Furthermore, Φ_rRNA^RNAP was first introduced in line 205 but was not explained until line 337. The value(s) of Φ_rRNA^RNAP for Appendix Figure 4 are also missing from this manuscript. 5. How, exactly, is the unit of flux converted to mmol g-1 h-1? 6. What is the (dry) mass constraint and how is it defined? In the manuscript, both the second equation in line 101 and the bottom row of Table 1 are dry mass constraint(s). Why are they different? Furthermore, why is the right-hand side of the second equation in line 101 a dimensionless 1, and how does the last row of Table 1 result in the unit of growth rate, time^(-1)? 7. The concentrations of all components that serve as "substrates" will be zero when growth rate is maximized, as these molecules do not catalyze any reactions, nor do they influence reaction kinetics in the model. These "0" concentration components are C, AA, NT, rP, and rRNA. Why are these concentrations even included in the model?

Minor comments:

1. Questions regarding Figure 2:

(a) The explanation of Figure 2a is unclear. Intuitively, I assumed that it was a comparison between model predictions and experimental data, with the points representing experimental data and the line representing predictions; and the authors wrote in the figure legend "The points represent maximum growth rates in six experimental conditions". However, the growth rates shown in the figure do not match the original experimental data. Are all the data in the figure predictions?

(b) Figure 2b is difficult to understand. This figure shows the non-optimal solutions of the model. It is unclear how these solutions are achieved and why there are three lines in the figure. 2. Table 1 is also difficult to understand. While the stoichiometric constraints can be easily derived, the capacity constraints and the dry mass constraint cannot be easily derived from related equations from the text.<br /> 3. As the authors ask a question in the title, they should provide an explicit answer in the abstract. 4. The authors should cite a seminal modeling paper, which was the first to examine resource allocation in simplified self-replicating cell systems (Molenaar et al. 2009, Molecular Systems Biology 5:323). 5. The meaning of v is not consistently defined throughout the manuscript. It refers to the fluxes of enzymatic reactions in some instances, but in other contexts, it refers to the fluxes of the entire network of enzymatic reactions and protein synthesis reactions (Figure 1, Equation 1, and Line 386). 6. Line 85, it might be difficult to interpret "RNAP fluxes" as the flux of rRNA synthesis without reading the subsequent text. 7. Typo in line 102-103. "...protein fluxes 𝒘" → "...protein synthesis fluxes 𝒘". 8. Line 104, f_RNAP^act and f_R^act are not explained in the text; and their biological significance cannot be understood from their names in Table 2 ("RNAP activity" and "Ribosome activity"). 9. Notion "**" in Table 2. The coupling between transcription and translation means the coupling of "mRNA" transcription and translation, not rRNA. At least in E. coli, the transcription rate of rRNA is faster than that of mRNA. 10. Is the citation correct in line 136? I didn't find related information in Bremer and Dennis' paper after a quick scan.<br /> 11. Lines 136-138. The statement is not accurate, as the fraction of inactive ribosomes increases with decreasing growth rate in E. coli (Dai et al. 2016, Nat Microbiol 2, 16231). If the studied growth rates are relatively high, it is acceptable to use a constant active ribosome fraction as an approximation, but this approximation should be made explicit. 12. The citation in line 142 is not accurate. It should be (Bremer and Dennis, 1996). 13. Lines 192-193: "six" different growth media, not five. 14. Line 287: The statement "... translation rate does not increase in ribosomes with a higher protein content" could be misinterpreted as discussing translation elongation rate changes with different protein content in ribosomal protein mutant strains in a given species. It should be rephrased to remove ambiguity. 15. Parameters for the three panels in Figure 8 are missing.

Significance

Strengths: Why the ribosome is composed of RNA and protein parts is a fundamental biological question. This manuscript proposes a very interesting hypothesis, arguing that the mixed ribosome composition results from rRNA instability. To test their hypothesis, the authors parameterize a simplified self-replicating cell model with realistic parameters. The model is first developed/parameterized for E. coli, and it could be easily adapted to other organisms with higher ribosomal protein content.

Limitations: The main limitations of this manuscript lie in the development of the model, especially the modeling of rRNA degradation and the use of constant values for growth rate-dependent parameters.

Advances: (1) This manuscript proposes a new hypothesis that rRNA instability is a universal factor that influences the ribosome composition across living organisms. (2) Compared to Kostinski and Reuveni's work, the authors have made certain improvements by including adjustable ribosome allocation to RNA and ribosomal protein when maximizing growth rate, which may lead to more realistic conclusions.

Audience: This work will be of interest to people in the field of theoretical biology, computational biology, and evolution, as well as to researchers studying ribosome structure and function.

Areas of expertise: Microbial systems biology, computational biology, and prokaryotic genomics.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

General Statements

We thank all three reviewers for their time and care in reviewing our manuscript, in particular Reviewer 3 for providing a detailed critique that was very useful for planning revisions. We are grateful that all three reviewers indicate that the new genome resources presented in this work are of high-quality and address an existing knowledge gap. We are also grateful for general assessments that the manuscript is 'well-written', and the analyses 'well performed' and 'thorough'.

We acknowledge Reviewer 3’s legitimate criticism that the assembly and annotation data is not already publicly available and would like to assure the reviewing team that we have been pressing NCBI to progress the submission status since before the preprint was submitted. We regret the delay but hope that we can resolve this issue promptly. Furthermore, as some additional fields in the REAT genome annotation are lost during the NCBI submission process, we will ensure that comprehensive annotation files are also added to Zenodo.

Reviewer 3 also made the general comment that 'the manuscript could greatly benefit from merging the result and discussion sections' and we would naturally be happy to make this adjustment if the journal in question uses that format.

Description of the planned revisions

• We will follow suggestions by Reviewer 3 to improve clarity of two figures:

Figure S9: Please use a more appropriate colour palette. It is difficult to know the copy number based on the colour gradient.

Figure 5: Consider changing panel B for a similar version of Fig S12. I think it gives a cleaner and more general perspective of the presence of starship elements.

• We will address the choice of LOESS versus linear regression for investigating the relationship between candidate secreted effector protein (CSEP) density and transposable element (TE) density, as queried by Reviewer 3:

Lines 140-144: LOESS smoothing functions are based on local regressions and usually find correlations when there are very weak associations. The authors have to justify the use of this model versus a simpler and more straightforward linear regression. My suspicion is that the latter would fail to find an association. Also, there is no significance of Kendall's Tau estimate (p-value).

We agree with the reviewer, that as we did not find an association with the more sensitive LOESS, we expect that linear regression would also not find an association, supporting our current conclusions. We will add this negative result into the text.

• We will check for other features associated with the distribution of CSEPs, as queried by Reviewer 3:

Lines 157-163: Was there any other feature associated with the CSEP enrichment? GC content? Repetitive content? Centromere likely localisation?

• We will integrate TE variation into the PERMANOVA lifestyle testing, as suggested by Reviewer 3:

Line 186: Why not to test the variation content of TEs as a factor for the PERMANOVA?

In reviewing this suggestion, we also spotted an error in our data plotting code, and the PERMANOVA lifestyle result for all genes will be corrected from 17% to 15% in Fig. 4a. Correcting this error does not impact our ultimate results or interpretation.

• To complement the current graphical-based assessment of approximate data normality, we will include additional tests (Shapiro-Wilk for sample sizes

Line 743: Q-Q plots are not a formal statistical test for normality.

• One of the main critiques from Reviewer 3 was that, although we already acknowledged low sample sizes being a limitation of this work, the manuscript could benefit from reframing with greater consideration of this factor. They also highlighted a few specific places in the text that could be rephrased in consideration of this:

Line 267: "Multiple strains" can be misleading about the magnitude.

Lines 305-307: The fact that there is significant copy number variation between the two GtA strains suggests that the variation in the GtA lineage has not been fully captured and that there may be an unsampled substructure. Although the authors acknowledge the need for pangenomic references, they should recognize this limitation in the sample size of their own study, especially when expressing its size as "multiple strains" (line 267).

Lines 314-317: Again, the sample size is still very small and likely not representative. It suggests UNSAMPLED substructure even for the UK populations.

Line 164 (and whole section): I would invite the authors to cautiously revisit the use of the terms "core", "soft core". The sample size is very low, as they themselves acknowledge, and probably not representative of the diversity of Gaeumannomyces.

We intend to edit the text to address this, including removal of both text and figure references to ‘soft-core’ genes, as we agree the term is likely not meaningful in this case, and removing it has no bearing on the results or interpretation.

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

• We have amended the text in a number of places for clarity/fluency as suggested by Reviewer 3:

ii) There need to be an explicit conclusion about the differences between pathogenic Gt and non-pathogenic Gh. Somehow, this is not entirely clear and is probably only a matter of rephrasing.

Please see new lines 477-478: ‘Regarding differences between pathogenic Gt and non-pathogenic Gh, we found that Gh has a larger overall genome size and greater number of genes.’

Lines 309-314: The message seems a bit out of context in the paragraph.

This is valid, these lines have now been removed.

Lines 392-395: The idea that crop pathogenic fungi are under pressure that favours heterothallism does not take into account the multiple cases of successful pathogenic clonal lineages in which sexual reproduction is absent. This paragraph seems very speculative to me. Please rephrase it.

Our intention here was the exact reverse, that crop pathogens are under pressure to favour homothallism (as Reviewer 3 points out, anecdotally this often seems to play out in nature). We have rephrased lines 386-390 to hopefully make our stance more explicit: 'Together, this could suggest a selective pressure towards homothallism for crop fungal pathogens, and a switch from heterothallism in Gh to homothallism in Gt and Ga may, therefore, have been a key innovation underlying lifestyle divergence between non-pathogenic Gh and pathogenic Gt and Ga.'

Lines 463-464: Please refer to the analyses when discussing the genetic divergence.

We have rephrased this sentence to make our intended point clearer, please see new lines 459-461: ‘If we compare Ga and Gt in terms of synteny, genome size and gene content, the magnitude of differences does not appear to be more pronounced than those between GtA and GtB.’

• We have also fixed the following typographic errors highlighted by Reviewer 3:

Line 399: You mean, Fig 4C?

Line 722: You missed "trimAI"

Lines 723-727: Missing citations for "AMAS" and RAxML-NG, "AHDR" and "OrthoFinder"

• We have added genome-wide RIP estimates to Supplementary Table S1 as requested by Reviewer 3:

Lines 416-422: Please provide the data related to the genome-wide estimates of RIP.

• We have added a note clarifying that differences in overall genome size between lineages are not fully explained by differences in gene copy-number (lines 406-408: 'We should note that the total length of HCN genes was not sufficiently large to account for the overall greater genome size of GtB compared to GtA (Supplemental Table S1).') in response to a comment from Reviewer 3:

Line 396: The difference in duplicated genes raises the question of whether there are differences in overall genome size between lineages and, if so, whether they can be explained by the presence of genes.

• We have made an alteration to the author order and added equal second-author contributions.

Description of analyses that authors prefer not to carry out

• In response to our analysis regarding the absence of TE-effector compartmentalisation in this system, Reviewer 1 requested additional analyses:

While TE enrichment is typically associated with accessory compartments, it is not a defining feature. To bolster the authors' claim, it is essential to demonstrate that there is no bias in the ratio of conserved and non-conserved genes across the genomes.

We believe that there are two slightly different compartmentalisation concepts being somewhat conflated here – (1) the idea of compartments where TEs and virulence proteins such as effectors are significantly colocalised in comparison with the rest of the genome, and (2) the idea of compartments containing gene content that is not shared in all strains (i.e. accessory). The two may overlap – as Reviewer 2 states, accessory compartments may also be enriched with TEs – but not necessarily. We specifically address the first concept in our text, and we appreciate Reviewer 3’s response on this subject:

There is a clear answer for the compartmentalisation question. The authors favour the idea of "one-compartment" with compelling analyses.

We believe that the second concept of accessory compartments is shown to be irrelevant in this case from our GENESPACE results (see Fig. 2), which demonstrate that gene content is conserved, broadly syntenic even, across strains, with no clear evidence of accessory compartments or chromosomes regarding gene content. We have already acknowledged that other mechanisms of compartmentalisation beyond TE-effector colocalisation may be at play (as seen from our exploration of effector distributions biased towards telomeres, see section from line 156: ‘Although CSEPs were not broadly colocalised with TEs, we did observe that they appeared to be non-randomly distributed in some pseudochromosomes (Fig. 3a)…’).

• Reviewer 1 questioned the statement that higher level of genome-wide RIP is consistent with lower levels of gene duplication:

L422: Is the highest RIP rate in GtA consistent with its low levels of gene duplication? Does this suggest that duplicated sequences in GtA are no longer recognizable due to RIP mutations? This seems counterintuitive, as RIP is primarily triggered by gene duplication.

Our understanding is that, while RIP can directly mutate coding regions, it predominantly acts on duplicated sequences within repetitive regions such as TEs (https://genomebiology.biomedcentral.com/articles/10.1186/s13059-020-02060-w), which has a knock-on effect of reducing TE-mediated gene duplication. In Neurospora crassa, where RIP was first discovered and thus the model species for much of our understanding of the process, a low number of gene duplicates has been linked to the activity of RIP (https://www.nature.com/articles/nature01554). We therefore believe the current text is reasonable.

• Reviewer 2 stated that experimental validation of gene function is required to make clear links to lifestyle or pathogenicity:

In my eyes, the study has two main limitations. First of all, the research only concerns genomics analyses, and therefore is rather descriptive and observational, and as such does not provide further mechanistic details into the pathogen biology and/or into pathogenesis. This is further enhanced by the lack of clear observations that discriminate particular species/lineages or life styles from others in the study. Some observations are made with respect to variations in candidate secreted effector proteins and biosynthetic gene clusters, but clear links to life style or pathogenicity are missing. To further substantiate such links, lab-based experimental work would be required.

We agree that in an ideal world supportive wet biology gene function experimental evidence would be included. Unfortunately, transformation has not been successfully developed yet in this system (see lines 33-35: ‘There have also been considerable difficulties in producing a reliable transformation system for Gt, preventing gene disruption experiments to elucidate function (Freeman and Ward 2004).’) not for lack of trying – after 18 months of effort using all available transformation techniques and selectable markers neither Gt or Gh was transformable. Undertaking that challenge has proven to be far beyond the scope of this paper, the purpose of which was to generate and analyse high-quality genomic data, a major task in itself. We again appreciate Reviewer 3’s response to this point, agreeing that it is out of scope for this work:

I just want to respectfully disagree with reviewer #2 about the need for more experimental laboratory work, as in my opinion it clearly goes beyond the intention and scope of the submitted work. This could be a limitation that would depend on the chosen journal and its specific format and requirements. Finally, I think it would suffice for the authors to discuss on the lack of in-depth experimental work as part of the limitations of their overall approach.

As per the suggestion by Reviewer 3, we will add text to address the absence of in-depth experimental work within the scope of this study.

• Reviewer 3 suggested we might 'consider including formal population differentiation estimators', however, as they previously highlighted above, our sample sizes are too small to produce reliable population-level statistics.

• Reviewer 3 raised the disparity in the appearance of branches at the root of phylogenetic trees in various figures:

Figure 4a (and Figs S5, S13): The depicted tree has a trichotomy at the basal node. Please correct it so Magnaporthiopsis poae is resolved as an outgroup, as in Fig. S17.

All the trees were rooted with M. poae as the outgroup, and although it may seem counterintuitive, a trifurcation at the root is the correct outcome in the case of rerooting a bifurcating tree, please see this discussion including the developers of both leading phylogeny visualisation tools ggtree and phytools (https://www.biostars.org/p/332030/). Although it is possible to force a bifurcating tree after rooting by positioning the root along an edge, the resulting branch lengths in the tree can be misleading, and so in cases where we wanted to include meaningful branch lengths in the figure (i.e. estimated from DNA substitute rates, in Figures 4a, S5 and S13) we have not circumvented the trifurcation. In Fig S17 meaningful branch lengths have not been included and the tree only represents the topology, resulting in the appearance of bifurcation at the root.

• Reviewer 3 suggested that the discussion on giant Starship TEs resembled more of a review:

Lines 434-451: This section resembles more a review than a discussion of the results of the present work. This also highlights the lack of analysis on the genetic composition and putative function of the identified starship-like elements.

The reviewer has a valid point. However, Starships are a recently discovered and thus underexplored genetic feature that readers from the wider mycology/plant pathology community may not yet be aware of. We believe it is warranted to include some additional exposition to give context for why their discovery here is novel, interesting and unexpected. We are naturally keen to investigate the make-up of the elements we have found in this lineage, however that will require a substantial amount of further work. Analysis of Starships is not trivial, for example the starfish tool is still under development and a limited number of species have been used to train it. How best to compare elements is also an active area of investigation – they are dynamic in their structure and may include genes originating from the host genome or a previous host – and for this reason we believe is out of scope to interrogate alongside the other foundational genomic data presented in this paper.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Summary:

The manuscript "Evolutionary genomics reveals variation in structure and genetic content implicated in virulence and lifestyle in the genus Gaeumannomyces" by Rowena Hill and collaborators is a thorough, well-planned and designed work. They have described 9 almost complete new assemblages, from their most general characteristics to their genetic content and implications. I am very pleased with the quality and completeness of this work and agree that it provides a very useful resource and framework for further research on this important organism.

The three main motivations of the present study were:

1) Are there genomic signatures distinguishing Gt A/B virulence lineages?;

2) How do gene repertoires differ between pathogenic Gt and non-pathogenic Gh? And, iii) Is there evidence of genome compartmentalisation in Gaeumannomyces?

a) The authors themselves recognise the low number of samples in their work (Lines 453-454) and this limitation hampers the establishment of a clear association between lineage-specific virulence and genomic signatures. I would argue that the present work needs to be reframed factoring this main limitation.

b) There need to be an explicit conclusion about the differences between pathogenic Gt and non-pathogenic Gh. Somehow, this is not entirely clear and is probably only a matter of rephrasing.

c) There is a clear answer for the compartmentalisation question. The authors favour the idea of "one-compartment" with compelling analyses.

Major comments:

The authors have not published the genomic data. Therefore, it is impossible to audit the quality of the assemblies and impedes its reproducibility. It is also bad practice by current scientific standards.

I strongly believe that the manuscript could greatly benefit from merging the result and discussion sections. It would be easier for the reader to follow their entire logic. This is of course something optional and contingent on the journal format.

Minor and specific comments:

RESULTS

• Lines 140-144: LOESS smoothing functions are based on local regressions and usually find correlations when there are very weak associations. The authors have to justify the use of this model versus a simpler and more straightforward linear regression. My suspicion is that the latter would fail to find an association. Also, there is no significance of Kendall's Tau estimate (p-value).

• Lines 157-163: Was there any other feature associated with the CSEP enrichment? GC content? Repetitive content? Centromere likely localisation?

• Line 164 (and whole section): I would invite the authors to cautiously revisit the use of the terms "core", "soft core". The sample size is very low, as they themselves acknowledge, and probably not representative of the diversity of Gaeumannomyces.

• Figure 4a (and Figs S5, S13): The depicted tree has a trichotomy at the basal node. Please correct it so Magnaporthiopsis poae is resolved as an outgroup, as in Fig. S17.

• Line 186: Why not to test the variation content of TEs as a factor for the PERMANOVA?

• Figure S9: Please use a more appropriate colour palette. It is difficult to know the copy number based on the colour gradient.

• Figure 5: Consider changing panel B for a similar version of Fig S12. I think it gives a cleaner and more general perspective of the presence of starship elements.

DISCUSSION

• Line 267: "Multiple strains" can be misleading about the magnitude.

• Lines 305-307: The fact that there is significant copy number variation between the two GtA strains suggests that the variation in the GtA lineage has not been fully captured and that there may be an unsampled substructure. Although the authors acknowledge the need for pangenomic references, they should recognize this limitation in the sample size of their own study, especially when expressing its size as "multiple strains" (line 267).

• Lines 309-314: The message seems a bit out of context in the paragraph.

• Lines 314-317: Again, the sample size is still very small and likely not representative. It suggests UNSAMPLED substructure even for the UK populations.

• Lines 392-395: The idea that crop pathogenic fungi are under pressure that favours heterothallism does not take into account the multiple cases of successful pathogenic clonal lineages in which sexual reproduction is absent. This paragraph seems very speculative to me. Please rephrase it.

• Line 396: The difference in duplicated genes raises the question of whether there are differences in overall genome size between lineages and, if so, whether they can be explained by the presence of genes.

• Line 399: You mean, Fig 4C?

• Lines 416-422: Please provide the data related to the genome-wide estimates of RIP.

• Lines 434-451: This section resembles more a review than a discussion of the results of the present work. This also highlights the lack of analysis on the genetic composition and putative function of the identified starship-like elements.

• Lines 463-464: Please refer to the analyses when discussing the genetic divergence. Consider including formal population differentiation estimators.

METHODS

• Line 722: You missed "trimAI"

• Lines 723-727: Missing citations for "AMAS" and RAxML-NG, "AHDR" and "OrthoFinder" Line 743: Q-Q plots are not a formal statistical test for normality.

Referees cross-commenting

I agree with my peer reviewers and appreciate that we have shared common concerns and suggestions. I also agree with their comments.

I just want to respectfully disagree with reviewer #2 about the need for more experimental laboratory work, as in my opinion it clearly goes beyond the intention and scope of the submitted work. This could be a limitation that would depend on the chosen journal and its specific format and requirements. Finally, I think it would suffice for the authors to discuss on the lack of in-depth experimental work as part of the limitations of their overall approach.

Significance

The work presented by Hill and co-workers contributes to the understanding of the genetic basis of host-pathogen interactions and evolutionary dynamics in the important fungus responsible for wheat "take-all-disease", Gaeumannomyces tritici. By providing 9 new near-complete assemblages, this work will provide a valuable resource for research on this agronomically important organism. This work sets the stage for developing a global pangenome of G. tritici that can expand analyses of its population structure and specific genetic elements that are associated with its virulence.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

In this study, the authors present genome assemblies for nine strains of the genus Gaeumannomyces, including 5 strains that belong to two different virulence lineages of the wheat take-all decline pathogen G. tritici, 2 strains of the antagonist G. hyphopodioides and 2 of the oat take-all decline pathogen G. avenae. The authors assess gene catalogs, CAZyme repertoires, effector catalogs, TE abundance, compartmentalisation and the occurrence of Starship giant transposable elements. Overall, there are no striking differences that discriminate the genomes and that can be linked to differential life styles. Weak correlations were found for some of the different lineages, but no functional analyses have been performed to further solidify such differences.

Significance

• Overall, the study fills a knowledge gap, given that no-few high quality genomes for the soil-borne fungi of the Gaeumannomyces genus are available. The genome assemblies are of high quality, and the work that is presented is mainly solid and robust. The analyses are well performed, sound and informative.

• In my eyes, the study has two main limitations. First of all, the research only concerns genomics analyses, and therefore is rather descriptive and observational, and as such does not provide further mechanistic details into the pathogen biology and/or into pathogenesis. This is further enhanced by the lack of clear observations that discriminate particular species/lineages or life styles from others in the study. Some observations are made with respect to variations in candidate secreted effector proteins and biosynthetic gene clusters, but clear links to life style or pathogenicity are missing. To further substantiate such links, lab-based experimental work would be required.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

The manuscript by Hill et al. presents nearly complete genomes of nine Gaeumannomyces strains, including both phytopathogenic and non-pathogenic (symbiotic) fungi. The manuscript is well-written, and the data it presents are of high quality, offering implications for understanding the evolution and diversification of Magnaporthales fungi, which encompass economically important phytopathogenic species such as Gaeumannomyces graminis and Pyricularia oryzae. I believe that the determination of these nearly complete genomes alone justifies publication. However, I have some concerns as described below.

Major concern:

One potential criticism pertains to whether the authors' assertion that Gaeumannomyces taxa have one-compartment genomes is fully supported by the data. The authors demonstrate in this manuscript that transposable elements (TE) and putative effector genes (CSEPs) are not co-localized in the Gaeumannomyces genomes. However, this evidence may not be robust enough to substantiate their claim. The concept of two- or multi-speed genomes suggests that fungal genomes consist of compartments that differ in the rate of evolution but not necessarily in TE content. While TE enrichment is typically associated with accessory compartments, it is not a defining feature. To bolster the authors' claim, it is essential to demonstrate that there is no bias in the ratio of conserved and non-conserved genes across the genomes.

Minor concern:

L422: Is the highest RIP rate in GtA consistent with its low levels of gene duplication? Does this suggest that duplicated sequences in GtA are no longer recognizable due to RIP mutations? This seems counterintuitive, as RIP is primarily triggered by gene duplication.

In my opinion, the analysis of the genomic differences facilitating parasitic and symbiotic lifestyles seems somewhat weak.

Significance

This manuscript offers new genomic insights into economically important phytopathogenic fungal species, and sheds light on the diversification of parasitic and symbiotic fungi during evolution. While the analyses conducted are mostly appropriate and reasonable, they do not yield particularly surprising findings.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

Manuscript number: RC- 2023-02122

Corresponding author(s): Andrew Graham Cox and Juan Manuel González-Rosa

1. General Statements

We thank the reviewers for taking the time to assess our work and for their considered and constructive comments. We are glad that they appreciate the value of the methodology we have developed. In addressing the points raised by the reviewers, we have significantly strengthened the conclusions reached in our study. Below is a point-by-point response (in regular type, blue) to the specific reviewer comments (in italics, black).

1. Point-by-point description of the revisions

Experiment 1: Perform lineage tracing of hepatocytes following cryoinjury.

Reviewer #1 would like us to have a better understanding of the origin of the regenerative hepatocytes following cryoinjury. There are two potential sources of regenerating hepatocytes. In many cases, hepatocytes proliferate giving rise to regenerative hepatocytes. However, during severe injury, the liver can undergo a ductular reaction in which biliary epithelial cells (BECs) can expand and transdifferentiate to give rise to regenerating hepatocytes.

● To address this query we have now used a new transgenic line created in laboratory that can indelibly label hepatocytes for lineage tracing Tg(fabp10a:Tet-ON-Cre). We have crossed this line to floxed reporters (Ubb:Switch) and collect livers at 7 dpci. The healthy parenchyma surrounding the injured area was predominantly labelled in the tracing experiment suggesting that pre-existing hepatocytes are driving the regenerative response.

Experiment 2: Examine BEC and EC proliferation in the ventral and contralateral lobes following cryoinjury.

Reviewers #1 and #2 would like us to better characterise the temporal dynamics of proliferation in BECs and ECs following cryoinjury. Specifically, the reviewers would like to know whether then compensatory hyperplasia in the contralateral lobe also leads to increased BEC and EC proliferation. Moreover, the reviewers would like us to better quantify the extent of EC and BEC proliferation at different stages of regeneration after cryoinjury.

● We have now performed extensive BrdU pulse-chase cryoinjury experiments using Tg(fli1a:nEGFP) zebrafish to visualise ECs. We have also conducted multiplexed immunostaining of the regenerating livers with the BEC marker (Anxa4) in conjunction with immunodetection of proliferation (BrdU and PCNA). These studies outline the kinetics of the regenerative response and provide evidence to support epimorphic regeneration around the site of injury as well as a compensatory hyperplasia on the contralateral lobe.

Experiment 3: Quantification of the temporal dynamics of fibrosis upon cryoinjury.

Reviewer #1 suggested we better characterise the extent of fibrosis in our model.

● We have now performed extensive studies quantifying the extent of collagen deposition at the regenerative margin over the time course (SHAM, 1, 3, 5, and 7 dpci) using immunohistochemical detection.

Experiment 4: Examine the role of Macrophage depletion in liver regeneration.

Reviewer #1 suggested we examine regeneration following cryoinjury in immunodeficient zebrafish in order to understand the role of macrophages in the model.

● To address this question, we have now performed studies involving macrophage depletion, using the well established IP injection of clodronate liposomes. We have now performed cryoinjury comparing untreated and chlodronate-treated Tg(fabp10a:NLSmCherry) or Tg(fabp10a: GreenLantern-H2B) zebrafish and examined the extent of regeneration at 3 and 7 dpci.

Experiment 5: Examine the impact of age and gender on liver regeneration following cryoinjury.

Reviewer #3 wanted to know if the regenerative response to cryoinjury was different depending on age and gender.

● To address this query, we have now performed cryoinjuries on young (4 month) and aged (9 month) males and females in a Tg(fabp10a:NLS-mCherry) or Tg(fabp10a: GreenLantern-H2B) background and examined regeneration at 7 dpci.

Experiment 6: Characterization of the dynamics of Hepatoblasts, Hepatic Stellate Cells, Macrophages and Neutrophils following cryoinjury.

Reviewer #3 suggested that it would be good to have a better cellular characterization of regeneration in the cryoinjury model.

● To address this question, we have now examined distinct cell types over the cryoinjury timecourse including SHAM, 1, 3, 5, and 7 dpci livers to provide a temporal landscape of the cellular response. In addition to BECs and ECs as discussed above, we have also performed immunofluorescence to detect macrophages (mfap4) neutrophils (mpx) during liver regeneration.

Specific Reviewer comments

Reviewer #1

Major points:

Full Revision

1) In this cryoinjury model, the authors found cell proliferation in hepatocytes, BECs, and other cell types near the injury site. The proliferating hepatocytes exclusively provide hepatocytes, and BECs provide BECs, or some transdifferentiation is involved? Like other extreme ablation models, BECs can contribute to some hepatocytes in this model.

We thank the Reviewer #1 for the interesting suggestion. We have addressed this by performing lineage tracing analysis as explained in Experiment 1 (above). For this approach, we have used Tg(fabp10a:Tet-ON-Cre; Ubb:Switch) to indelibly label and trace hepatocytes. These experiments reveal that the new regenerated tissue is derived from pre-existing hepatocytes (see Supplementary Figure 2 Q, R, S, T).

2) In this model, the authors observed the long-range effect of the cryoinjury as they identified increased cell proliferation in the contralateral liver lobes. Is this long-range effect specific to hepatocytes? BECs or endothelial cells also undergo increased cell proliferation in the contralateral lobes?

We thank the Reviewer #1 for this question. We have addressed this query by performing Experiment 2 (above). Briefly, cryoinjuries were performed and markers of proliferating HCs and BECs (PCNA or BrdU stained) were quantified in the ventral and contralateral lobes (see Supplementary Figure 6). The data clearly demonstrates that proliferation is higher at the site of injury, however lower rates of compensatory hyperplasia are still evident on the contralateral lobe. A strong epimorphic hyperplasia and weaker compensatory growth response, has been previously observed in the cardiac cryoinjury model (Pauline Sallin et al. Developmental Biology 2015).

3) This model is a unique liver regeneration model as it induces transient focal fibrosis. Is the fibrosis beneficial for liver regeneration? What happens if you reduce fibrosis pharmacologically? Will it interfere with the rate of regeneration?

We thank the Reviewer #1 for the comments. Although pharmacological interventions of fibrosis are beyond the scope of the current manuscript, we have better quantified the extent of fibrosis in the first week following cryoinjury in Experiment 3 (above; Figure 3I).

4) Do Lcp1+ leucocytes contribute to liver regeneration in this model? In immunodeficiency models such as irf8 mutant, liver regeneration after cryoinjury changed?

We thank the Reviewer #1 for the suggestion of using an immunodeficiency model. We addressed this question by performing Experiment 4 (above). Briefly, we have IP injected clodronate liposomes, which are a well-established method for macrophage depletion, and examined the effect on liver regeneration (Supplementary Figure 5). These extensive experiments showed that macrophage depletion had no significant effect on liver regeneration at 3 and 7 dpci.

5) The CUBIC-clearing procedure is beneficial in the field. The quantitative benefit of the CUBICbased method should be added. Supplement figures 1C and D need scale bars, especially for X Z and Z-Y planes. Can you quantify the Z-plane depth that you can scan with or without CUBIC treatment?

We thank the Reviewer #1 for the input and apologise if we did not present the current data clearly. We have now included the scale bars on the reviewed manuscript in Supplementary Figure 1C, 1D, and 1G. We have quantified the Z-plane depth on our current acquisitions and modified our current panels to make clear the difference in depth (z-stack) that CUBIC-imaging enables during liver acquisitions in Supplementary Figure 1D-I.

6) In the manuscript, the authors measured the injured area after the cryoinjury. But how about the depth of the injury? Does the procedure induce a relatively constant injury depth, or can it not be controlled? The total volume of injured tissue would be more important than the surface injured area.

We thank the Reviewer #1 for the comments. The hepatic cryoinjury approach was developed to injure the liver and avoid deeper tissue lesions to the gastrointestinal tract. Our existing CUBIC data suggests that injury depth remains constant.

Minor points:

7) The sham procedure means exposing the liver by removing the scale and cutting the skin, right? What is the survival rate of the sham procedure? Is the survival rate of sham group significantly lower than cryoinjury-induced group?

The Reviewer #1 is correct about the cryoinjury procedure in SHAM samples. SHAM survival is 95% while the injured animal survival is 92.97% (Figure below; n= 444). This analysis shows no significant difference between the groups (unpaired Student's t-test; p-value: 0.5843)

8) The original RNA-seq data, including FASTQ files, should be deposited to NCBI (Gene Expression Omnibus) or other public databases.

We apologize for not submitting our Bulk RNA-seq data to NCBI GEO during the initial submission. The Bulk RNA-seq data can be found under the accession number GSE245878.

Full Revision

Reviewer #2

Major points:

1) While the authors assayed changes in major cell types during liver regeneration in this model, the selection of varying timepoints for analysis and incomplete quantification for all timepoints precludes detailed comparisons that may lead to mechanistic insights. For example, closure of injury area is assayed at 1,3,7,14 dpci but hepatocyte proliferation is measured at 1,3,5,7, 18, 30 dpi. Fibrosis was only assayed at 5 dpi (assume dpi is the same as dpci). Cholangiocytes and endothelial cells are imaged at 1, 3, 7, 30 dpci but no quantification was provided only a single image. Since most changes are occurring at 1-7 dpci, the authors should at least measure the same timepoints from 1-7 dpci for the different cell types so comparisons can be made and conclusions can be drawn. For example, does hepatocyte proliferation, which seem to peak at 5 dpci, happen before endothelial proliferation, which is measured at 3 and 5 dpci but not measured at 5 dpci?

We thank the Reviewer #2 for the comments regarding temporal dynamics of regeneration. In response we have performed Experiment 2 (above). Briefly, this included examination of BECs and ECs at different time points during regeneration (SHAM, 1, 3, 5, and 7 dpci; Figure 6, Supplementary Figure 6L-P).

2) Fibrosis level seems to be highly variable at 5 dpci, which is the only time point measured. If this level of variability is found across all timepoints then this might not be a good model to study the intersection of fibrosis and regeneration. Since the authors have collected animals at all timepoints, it should be fairly straight forward to carry out collagen staining and quantification across different timepoints without the need of additional fish experiments.

We thank the Reviewer #2 for the comments regarding the fibrotic response. In response we have undertaken Experiment 3 (above). This experiment involves quantifying collagen deposition at the different timepoints (SHAM, 1, 3, 5, and 7 dpci; Figure 3I).

3) The lack of quantification of cholangiocytes and endothelial cells makes it difficult to gauge the reproducibility of this model across different animals and experiments.

We thank the Reviewer #2 for the comments regarding the need to quantify ECs and BECs during regeneration. In response we will undertake Experiment 2 (above). Briefly, this included examination of BECs and ECs at different time points during regeneration (SHAM, 1, 3, and 7 dpci; Figure 6 and Supplementary Figure 7).

4) Transcriptomic data analysis/presentation in Figure 7 can be improved. Cannot read any of the gene labels in Figure 7B. Figure 7H should use at least a few different gene markers from each cell type to approximate cell abundance.

We apologise for the inconvenience and have addressed the issue of legibility. We have increased font size on the volcano plots in Figure 7 and incorporate a new analysis with more markers for each cell type in Figure 7H. In addition, we have included the comparison between Bulk RNA-seq ventral samples and contralateral lobe samples, together with further GOenrichment of the samples in Supplementary Figure 8.

Full Revision

Minor:

5) Is "dpi" the same as "dpci"? Please use the same nomenclature throughout manuscript.

We apologise. Dpi means days post-injury and dpci means days post-cryoinjury. Nomenclature has been corrected in revised version of the manuscript.

6) In the mouse PHx model, hepatocytes reach max proliferation (as measured with Ki67/PCNA staining) at 40-48hrs across different labs and experiments, not at 24rs.

We thank the Reviewer #2, we have changed this reference.

7) Zebrafish references are used when the author is talking about mouse PHx model on page 12.

We thank the Reviewer #2, we have changed this reference 7 and 8 to reference the right papers.

Reviewer #3

Major points:

1) It is not clear whether both male and female fish were used in the analyses and whether there is any gender difference in regeneration responses at cellular and molecular levels. The method mentioned that 4-9 month old fish were used in the study. Was there any difference between young and old fish?

We thank the Reviewer #3 for the comments regarding the need to consider age and gender in regeneration studies. Our experiments have been performed on adult male zebrafish. To examine the impact of age and gender on regeneration we have performed Experiment 5 (above). In brief, we have undertaken cryoinjuries in 4 month or 9 month old females and males in the Tg(fabp10a:NLS-mCherry) or Tg(fabp10a: GreenLantern-H2B) background and examine regeneration at 7 dpci (Supplementary Figure 2 J-N and P. We could not detect a significant difference among any of these comparisons. However, we observed a subtle trend with female adult zebrafish showing smaller insult area compared to adult male zebrafish, both at 3 and 7 dpci (Supplementary Figure 2P).

2) The authors detected increased hepatocyte proliferation following cryoinjury. It will be interesting to investigate if activation of stem cells and transdifferentiation of cholangiocytes also contribute to regeneration in this particular model.

We thank the Reviewer #3 for the comments regarding the need to examine the potential involvement of hepatoblasts and transdifferentiating BECs in regeneration following cryoinjury. We have addressed these aspects with Experiment 6 (above). Briefly, we have performed cryoinjuries in adult zebrafish and utilised Anxa4 staining for detection of BECs at SHAM, 1, 3, 5, and 7 dpci (Figure 6A-F). This analysis showed that the were no detectable signs of transdifferentiation between hepatocytes and cholangiocytes (ie: there were no double positive cells (Anxa+/fabp10a:H2B-GreenLantern+ or fabp10a:H2B-mCherry+). Moreover, we performed lineage tracing experiments and found evidence that pre-existing hepatocytes give rise to the regenerating tissue (Supplementary Figure 2 Q-T). Together, these experiments indicate that hepatocytes are responsible for the regeneration of the liver upon cryoinjury without the necessity of BEC transdifferentiation.

3) It will be important to characterize hepatic stellate cells, macrophages, and neutrophils in this model, given their critical and complex roles in liver regeneration. Transgenic reporter lines marking these cell types are available.

We thank the Reviewer #3 for the comments regarding the need to examine hepatic stellate cells (HSCs), macrophages and neutrophils in regeneration following cryoinjury. We have addressed these aspects with Experiment 6 (above). Briefly, we have studied the temporal dynamics of neutrophils upon cryoinjury by immunofluorescent detection of myeloperoxidase (mpx) (Supplementary Figure 4). We have also explored the role of macrophage depletion in response to cryoinjury by performing clodronate injections. We found no significant changes in liver regeneration following clodronate injections (Supplementary Figure 5). To examine the temporal dynamics of HSCs we attempted to use two approaches, namely imaging transgenic lines labelling HSCs (Tg(BAC-pdgfrb:EGFP) and HCR for HSCs (pdgfrb), but unfortunately we were not able to detect HSCs with these approaches.

4) It is not appropriate to call Fli1a + cells liver sinusoidal cells. As far as I know, there is no specific marker for LSEC in zebrafish. Fli1a transgene labels all vascular cells.

We acknowledge this mistaken nomenclature and have made the necessary amendment to use the term endothelial cells (ECs).

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

In this manuscript, Sande-Melon et al described a new model for studying liver regeneration in zebrafish that is induced by cryoinjury. They showed that this model induced hepatocyte proliferation, transient fibrosis and inflammation, and regeneration of the biliary and vascular network. Compared to the other established models, such as partial hepatectomy, drug-induced liver injury, the cryoinjury model is easy to perform, consistent, and involves shorter recovery time. Overall, it is a useful tool that complements existing liver regeneration models. The tissue clearing methodology is highly effective.

Main critiques:

1. It is not clear whether both male and female fish were used in the analyses and whether there is any gender difference in regeneration responses at cellular and molecular levels. The method mentioned that 4-9 month old fish were used in the study. Was there any difference between young and old fish?
2. The authors detected increased hepatocyte proliferation following cryoinjury. It will be interesting to investigate if activation of stem cells and transdifferentiation of cholangiocytes also contribute to regeneration in this particular model.
3. It will be important to characterize hepatic stellate cells, macrophages, and neutrophils in this model, given their critical and complex roles in liver regeneration. Transgenic reporter lines marking these cells types are available.
4. It is not appropriate to call Fli1a + cells liver sinusoidal cells. As far as I know, there is no specific marker for LSEC in zebrafish. Fli1a transgene labels all vascular cells.

Significance

In this manuscript, Sande-Melon et al described a new model for studying liver regeneration in zebrafish that is induced by cryoinjury. They showed that this model induced hepatocyte proliferation, transient fibrosis and inflammation, and regeneration of the biliary and vascular network. Compared to the other established models, such as partial hepatectomy, drug-induced liver injury, the cryoinjury model is easy to perform, consistent, and involves shorter recovery time. Overall, it is a useful tool that complements existing liver regeneration models. The tissue clearing methodology is highly effective.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

In this manuscript titled "Development of a hepatic cryoinjury model to study liver regeneration" by Sande-Melon et al., the authors developed a novel model to study liver regeneration, namely a cryoinjury model in adult zebrafish. The authors described the methodology in detail and extensively characterized the kinetics of liver regeneration in this model, including hepatocyte necrosis/apoptosis, the proliferation of hepatocytes, cholangiocytes, endothelial cells, and infiltration of leukocytes. Most of the characterization were performed by immunostaining for various cell markers, which the authors corroborated with transcriptomic analysis by bulk RNAseq.

Major comments:

• While the authors assayed changes in major cell types during liver regeneration in this model, the selection of varying timepoints for analysis and incomplete quantification for all timepoints precludes detailed comparisons that may lead to mechanistic insights. For example, closure of injury area is assayed at 1,3,7,14 dpci but hepatocyte proliferation is measured at 1,3,5,7, 18, 30 dpi. Fibrosis was only assayed at 5 dpi (assume dpi is the same as dpci). Cholangiocytes and endothelial cells are imaged at 1, 3, 7, 30 dpci but no quantification was provided only a single image. Since most changes are occurring at 1-7 dpci, the authors should at least measure the same timepoints from 1-7 dpci for the different cell types so comparisons can be made and conclusions can be drawn. For example, does hepatocyte proliferation, which seem to peak at 5 dpci, happen before endothelial proliferation, which is measured at 3 and 5 dpci but not measured at 5 dpci?
• Fibrosis level seems to be highly variable at 5dpci, which is the only time point measured. If this level of variability is found across all timepoints then this might not be a good model to study the intersection of fibrosis and regeneration. Since the authors have collected animals at all timepoints, it should be fairly straight forward to carry out collagen staining and quantification across different timepoints without the need of additional fish experiments.
• The lack of quantification of cholangiocytes and endothelial cells makes it difficult to gauge the reproducibility of this model across different animals and experiments.
• Transcriptomic data analysis/presentation in Figure 7 can be improved. Cannot read any of the gene labels in Figure 7B. Figure 7H should use at least a few different gene markers from each cell type to approximate cell abundance.
• OPTIONAL: Sheets of DAPI staining are observed in Figure 6G'. Is this DNA from necrotic cells? Could they make up a neutrophil extracellular trap (NET)-scaffold like structure that covers/protects the injury site from infection? This is purely speculative but might represent an interesting area of study.
• OPTIONAL: To demonstrate this a useful model that complements existing models of liver regeneration, the authors can try to capitalize on the proposed strength of the model to provide some novel insights into liver regeneration. A notable feature of this model that is missing from the PHx and APAP rodent models is the development of robust fibrosis that rapidly resolves within a short time frame, providing an unique opportunity to investigate the potential crosstalk between fibrosis and regeneration that often co-occur in chronic liver disease patients.

Minor comments:

• Is "dpi" the same as "dpci"? Please use the same nomenclature throughout manuscript
• In the mouse PHx model, hepatocytes reach max proliferation (as measured with Ki67/PCNA staining) at 40-48hrs across different labs and experiments, not at 24rs
• Zebrafish references are used when the author is talking about mouse PHx model on page 12

Significance

Mouse 2/3 partial hepatectomy surgery (PHx) is the most frequently used model to study liver regeneration and much has been learnt from this model. However, mouse PHx involving tying off certain lobes of the liver and the inducing a sterile injury, where hepatocyte proliferation and liver regeneration occurs in the absence of significant inflammation and fibrosis. To understand the full complexity of the liver regeneration response, especially against the backdrop of a necroinflammatory environment that characterize chronic liver disease in patients, alternative models to study liver regeneration have been used such as the rodent APAP model of chemically induced injury. Here, Sande-Melon et al. aims to establish such a liver regeneration model in adult zebrafish that would harness the power of the zebrafish model, such as availability of various transgenic lines that label different cell populations, ease of accessibility to imaging techniques, large N number, and the convenience of working with lower complexity model organisms. While such a zebrafish liver regeneration model will be welcomed by the greater research community interested in studying liver regeneration, this paper in its current forms falls short of demonstrating the robustness and reproducibility of this model that would make it a useful research tool.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Summary:

In this study, the authors presented a novel cryoinjury model of liver damage and regeneration that reflects essential features of liver disease, including local fibrosis. Because of its rapid and consistent method, this model will be helpful and provide opportunities to delve into the molecular basis of liver regeneration. This manuscript also contains a high technique of visualization of the regenerating liver. The manuscript is well-written, and the points are clear. However, this form of manuscript might be overly descriptive, and adding functional, mechanical, or lineage tracing-based fate decision insights would make this manuscript significantly better.

Major points:

1. In this cryoinjury model, the authors found cell proliferation in hepatocytes, BECs, and other cell types near the injury site. The proliferating hepatocytes exclusively provide hepatocytes, and BECs provide BECs, or some transdifferentiation is involved? Like other extreme ablation models, BECs can contribute to some hepatocytes in this model.
2. In this model, the authors observed the long-range effect of the cryoinjury as they identified increased cell proliferation in the contralateral liver lobes. Is this long-range effect specific to hepatocytes? BECs or endothelial cells also undergo increased cell proliferation in the contralateral lobes?
3. This model is a unique liver regeneration model as it induces transient focal fibrosis. Is the fibrosis beneficial for liver regeneration? What happens if you reduce fibrosis pharmacologically? Will it interfere with the rate of regeneration?
4. Do Lcp1+ leucocytes contribute to liver regeneration in this mode? In immunodeficiency models such as irf8 mutant, liver regeneration after cryoinjury changed?
5. The CUBIC-clearing procedure is beneficial in the field. The quantitative benefit of the CUBIC-based method should be added. Supplement figures 1C and D need scale bars, especially for X-Z and Z-Y planes. Can you quantify the Z-plane depth that you can scan with or without CUBIC treatment?
6. In the manuscript, the authors measured the injured area after the cryoinjury. But how about the depth of the injury? Does the procedure induce a relatively constant injury depth, or can it not be controlled? The total volume of injured tissue would be more important than the surface injured area.

Minor points:

1. The sham procedure means exposing the liver by removing the scale and cutting the skin, right? What is the survival rate of the sham procedure? Is the survival rate of sham group significantly lower than cryoinjury-induced group?
2. The original RNA-seq data, including FASTQ files, should be deposited to NCBI (Gene Expression Omnibus) or other public databases.

Significance

The strength of this manuscript is that the authors established the new cryoinjury liver regeneration model. Compared to other models, this model introduced local fibrosis and relatively quick resolution of the fibrosis, which is unique to this model. Fibrosis is like a double-edged sword, as it can be a severe problem, but it may also enhance healing and regeneration. This useful model would advance our understanding of the role of fibrosis in liver regeneration. Also, this manuscript contains important new technologies, such as CUBIC-clearing, and will be helpful for the research field.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

Reply to the Reviewers

We thank the referees for their careful reading of the manuscript and their valuable suggestions for improvements.

General Statements:

Existing SMC-based loop extrusion models successfully predict and characterize mesoscale genome spatial organization in vertebrate organisms, providing a valuable computational tool to the genome organization and chromatin biology fields. However, to date this approach is highly limited in its application beyond vertebrate organisms. This limitation arises because existing models require knowledge of CTCF binding sites, which act as effective boundary elements, blocking loop-extruding SMC complexes and thus defining TAD boundaries. However, CTCF is the predominant boundary element only in vertebrates. On the other hand, vertebrates only contain a small proportion of species in the tree of life, while TADs are nearly universal and SMC complexes are largely conserved. Thus, there is a pressing need for loop extrusion models capable of predicting Hi-C maps in organisms beyond vertebrates.

The conserved-current loop extrusion (CCLE) model, introduced in this manuscript, extends the quantitative application of loop extrusion models in principle to any organism by liberating the model from the lack of knowledge regarding the identities and functions of specific boundary elements. By converting the genomic distribution of loop extruding cohesin into an ensemble of dynamic loop configurations via a physics-based approach, CCLE outputs three-dimensional (3D) chromatin spatial configurations that can be manifested in simulated Hi-C maps. We demonstrate that CCLE-generated maps well describe experimental Hi-C data at the TAD-scale. Importantly, CCLE achieves high accuracy by considering cohesin-dependent loop extrusion alone, consequently both validating the loop extrusion model in general (as opposed to diffusion-capture-like models proposed as alternatives to loop extrusion) and providing evidence that cohesin-dependent loop extrusion plays a dominant role in shaping chromatin organization beyond vertebrates.

The success of CCLE unambiguously demonstrates that knowledge of the cohesin distribution is sufficient to reconstruct TAD-scale 3D chromatin organization. Further, CCLE signifies a shifted paradigm from the concept of localized, well-defined boundary elements, manifested in the existing CTCF-based loop extrusion models, to a concept also encompassing a continuous distribution of position-dependent loop extrusion rates. This new paradigm offers greater flexibility in recapitulating diverse features in Hi-C data than strictly localized loop extrusion barriers.

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

This manuscript presents a mathematical model for loop extrusion called the conserved-current loop extrusion model (CCLE). The model uses cohesin ChIP-Seq data to predict the Hi-C map and shows broad agreement between experimental Hi-C maps and simulated Hi-C maps. They test the model on Hi-C data from interphase fission yeast and meiotic budding yeast. The conclusion drawn by the authors is that peaks of cohesin represent loop boundaries in these situations, which they also propose extends to other organism/situations where Ctcf is absent.

__Response: __

We would like to point out that the referee's interpretation of our results, namely that, "The conclusion drawn by the authors is that peaks of cohesin represent loop boundaries in these situations, ...", is an oversimplification, that we do not subscribe to. The referee's interpretation of our model is correct when there are strong, localized barriers to loop extrusion; however, the CCLE model allows for loop extrusion rates that are position-dependent and take on a range of values. The CCLE model also allows the loop extrusion model to be applied to organisms without known boundary elements. Thus, the strict interpretation of the positions of cohesin peaks to be loop boundaries overlooks a key idea to emerge from the CCLE model.

__ Major comments:__

1. More recent micro-C/Hi-C maps, particularly for budding yeast mitotic cells and meiotic cells show clear puncta, representative of anchored loops, which are not well recapitulated in the simulated data from this study. However, such punta are cohesin-dependent as they disappear in the absence of cohesin and are enhanced in the absence of the cohesin release factor, Wapl. For example - see the two studies below. The model is therefore missing some key elements of the loop organisation. How do the authors explain this discrepency? It would also be very useful to test whether the model can predict the increased strength of loop anchors when Wapl1 is removed and cohesin levels increase.

Costantino L, Hsieh TS, Lamothe R, Darzacq X, Koshland D. Cohesin residency determines chromatin loop patterns. Elife. 2020 Nov 10;9:e59889. doi: 10.7554/eLife.59889. PMID: 33170773; PMCID: PMC7655110. Barton RE, Massari LF, Robertson D, Marston AL. Eco1-dependent cohesin acetylation anchors chromatin loops and cohesion to define functional meiotic chromosome domains. Elife. 2022 Feb 1;11:e74447. doi: 10.7554/eLife.74447. Epub ahead of print. PMID: 35103590; PMCID: PMC8856730.

__Response: __

We are perplexed by this referee comment. While we agree that puncta representing loop anchors are a feature of Hi-C maps, as noted by the referee, we would reinforce that our CCLE simulations of meiotic budding yeast (Figs. 5A and 5B of the original manuscript) demonstrate an overall excellent description of the experimental meiotic budding yeast Hi-C map, including puncta arising from loop anchors. This CCLE model-experiment agreement for meiotic budding yeast is described and discussed in detail in the original manuscript and the revised manuscript (lines 336-401).

To further emphasize and extend this point we now also address the Hi-C of mitotic budding yeast, which was not included the original manuscript. We have now added an entire new section of the revised manuscript entitled "CCLE Describes TADs and Loop Configurations in Mitotic S. cerevisiae" including the new Figure 6, which presents a comparison between a portion of the mitotic budding yeast Hi-C map from Costantino et al. and the corresponding CCLE simulation at 500 bp-resolution. In this case too, the CCLE model well-describes the data, including the puncta, further addressing the referee's concern that the CCLE model is missing some key elements of loop organization.

Concerning the referee's specific comment about the role of Wapl, we note that in order to apply CCLE when Wapl is removed, the corresponding cohesin ChIP-seq in the absence of Wapl should be available. To our knowledge, such data is not currently available and therefore we have not pursued this explicitly. However, we would reinforce that as Wapl is a factor that promotes cohesin unloading, its role is already effectively represented in the optimized value for LEF processivity, which encompasses LEF lifetime. In other words, if Wapl has a substantial effect it will be captured already in this model parameter.

1. Related to the point above, the simulated data has much higher resolution than the experimental data (1kb vs 10kb in the fission yeast dataset). Given that loop size is in the 20-30kb range, a good resolution is important to see the structural features of the chromosomes. Can the model observe these details that are averaged out when the resolution is increased?

__Response: __

We agree with the referee that higher resolution is preferable to low resolution. In practice, however, there is a trade-off between resolution and noise. The first experimental interphase fission yeast Hi-C data of Mizuguchi et al 2014 corresponds to 10 kb resolution. To compare our CCLE simulations to these published experimental data, as described in the original manuscript, we bin our 1-kb-resolution simulations to match the 10 kb experimental measurements. Nevertheless, CCLE can readily predict the interphase fission yeast Hi-C map at higher resolution by reducing the bin size (or, if necessary, reducing the lattice site size of the simulations themselves). In the revised manuscript, we have added comparisons between CCLE's predicted Hi-C maps and newer Micro-C data for S. pombe from Hsieh et al. (Ref. [50]) in the new Supplementary Figures 5-9. We have chosen to present these comparisons at 2 kb resolution, which is the same resolution for our meiotic budding yeast comparisons. Also included in Supplementary Figures 5-9 are comparisons between the original Hi-C maps of Mizuguchi et al. and the newer maps of Hsieh et al., binned to 10 kb resolution. Inspection of these figures shows that CCLE provides a good description of Hsieh et al.'s experimental Hi-C maps and does not reveal any major new features in the interphase fission yeast Hi-C map on the 10-100 kb scale, that were not already apparent from the Hi-C maps of Mizuguchi et al 2014. Thus, the CCLE model performs well across this range of effective resolutions.

3. Transcription, particularly convergent has been proposed to confer boundaries to loop extrusion. Can the authors recapitulate this in their model?

__Response: __

In response to the suggestion of the reviewer we have now calculated the correlation between cohesin ChIP-seq and the locations of convergent gene pairs, which is now presented in Supplementary Figures 17 and 18. Accordingly, in the revised manuscript, we have added the following text to the Discussion (lines 482-498):

"In vertebrates, CTCF defines the locations of most TAD boundaries. It is interesting to ask what might play that role in interphase S. pombe as well as in meiotic and mitotic S. cerevisiae. A number of papers have suggested that convergent gene pairs are correlated with cohesin ChIP-seq in both S. pombe [65, 66] and S. cerevisiae [66-71]. Because CCLE ties TADs to cohesin ChIP-seq, a strong correlation between cohesin ChIP-seq and convergent gene pairs would be an important clue to the mechanism of TAD formation in yeasts. To investigate this correlation, we introduce a convergent-gene variable that has a nonzero value between convergent genes and an integrated weight of unity for each convergent gene pair. Supplementary Figure 17A shows the convergent gene variable, so-defined, alongside the corresponding cohesin ChIP-seq for meiotic and mitotic S. cerevisiae. It is apparent from this figure that a peak in the ChIP-seq data is accompanied by a non-zero value of the convergent-gene variable in about 80% of cases, suggesting that chromatin looping in meiotic and mitotic S. cerevisiae may indeed be tied to convergent genes. Conversely, about 50% of convergent genes match peaks in cohesin ChIP-seq. The cross-correlation between the convergent-gene variable and the ChIP-seq of meiotic and mitotic S. cerevisiae is quantified in Supplementary Figures 17B and C. By contrast, in interphase S. pombe, cross-correlation between convergent genes and cohesin ChIP-seq in each of five considered regions is unobservably small (Supplementary Figure 18A), suggesting that convergent genes per se do not have a role in defining TAD boundaries in interphase S. pombe."

Minor comments:

1. In the discussion, the authors cite the fact that Mis4 binding sites do not give good prediction of the HI-C maps as evidence that Mis4 is not important for loop extrusion. This can only be true if the position of Mis4 measured by ChIP is a true reflection of Mis4 position. However, Mis4 binding to cohesin/chromatin is very dynamic and it is likely that this is too short a time scale to be efficiently cross-linked for ChIP. Conversely, extensive experimental data in vivo and in vitro suggest that stimulation of cohesin's ATPase by Mis4-Ssl3 is important for loop extrusion activity.

__Response: __

We apologize for the confusion on this point. We actually intended to convey that the absence of Mis4-Psc3 correlations in S. pombe suggests, from the point of view of CCLE, that Mis4 is not an integral component of loop-extruding cohesin, during the loop extrusion process itself. We agree completely that Mis4/Ssl3 is surely important for cohesin loading, and (given that cohesin is required for loop extrusion) Mis4/Ssl3 is therefore important for loop extrusion. Evidently, this part of our Discussion was lacking sufficient clarity. In response to both referees' comments, we have re-written the discussion of Mis4 and Pds5 to more carefully explain our reasoning and be more circumspect in our inferences. The re-written discussion is described below in response to Referee #2's comments.

Nevertheless, on the topic of whether Nipbl-cohesin binding is too transient to be detected in ChIP-seq, the FRAP analysis presented by Rhodes et al. eLife 6:e30000 "Scc2/Nipbl hops between chromosomal cohesin rings after loading" indicates that, in HeLa cells, Nipbl has a residence time bound to cohesin of about 50 seconds. As shown in the bottom panel of Supplementary Fig. 7 in the original manuscript (and the bottom panel of Supplementary Fig. 20 in the revised manuscript), there is a significant cross-correlation (~0.2) between the Nipbl ChIP-seq and Smc1 ChIP-seq in humans, indicating that a transient association between Nipbl and cohesin can be (and in fact is) detected by ChIP-seq.

1. *Inclusion of a comparison of this model compared to previous models (for example bottom up models) would be extremely useful. What is the improvement of this model over existing models? *

__Response: __

As stated in the original manuscript, as far as we are aware, "bottom up" models, that quantitatively describe the Hi-C maps of interphase fission yeast or meiotic budding yeast or, indeed, of eukaryotes other than vertebrates, do not exist. Bottom-up models would require knowledge of the relevant boundary elements (e.g. CTCF sites), which, as stated in the submitted manuscript, are generally unknown for fission yeast, budding yeast, and other non-vertebrate eukaryotes. The absence of such models is the reason that CCLE fills an important need. Since bottom-up models for cohesin loop extrusion in yeast do not exist, we cannot compare CCLE to the results of such models.

In the revised manuscript we now explicitly compare the CCLE model to the only bottom-up type of model describing the Hi-C maps of non-vertebrate eukaryotes by Schalbetter et al. Nat. Commun. 10:4795 2019, which we did cite extensively in our original manuscript. Schalbetter et al. use cohesin ChIP-seq peaks to define the positions of loop extrusion barriers in meiotic S. cerevisiae, for which the relevant boundary elements are unknown. In their model, specifically, when a loop-extruding cohesin anchor encounters such a boundary element, it either passes through with a certain probability, as if no boundary element is present, or stops extruding completely until the cohesin unbinds and rebinds.

In the revised manuscript we refer to this model as the "explicit barrier" model and have applied it to interphase S. pombe, using cohesin ChIP-seq peaks to define the positions of loop extrusion barriers. The corresponding simulated Hi-C map is presented in Supplementary Fig. 19 in comparison with the experimental Hi-C. It is evident that the explicit barrier model provides a poorer description of the Hi-C data of interphase S. pombe compared to the CCLE model, as indicated by the MPR and Pearson correlation scores. While the explicit barrier model appears capable of accurately reproducing Hi-C data with punctate patterns, typically accompanied by strong peaks in the corresponding cohesin ChIP-seq, it seems less effective in several conditions including interphase S. pombe, where the Hi-C data lacks punctate patterns and sharp TAD boundaries, and the corresponding cohesin ChIP-seq shows low-contrast peaks. The success of the CCLE model in describing the Hi-C data of both S. pombe and S. cerevisiae, which exhibit very different features, suggests that the current paradigm of localized, well-defined boundary elements may not be the only approach to understanding loop extrusion. By contrast, CCLE allows for a concept of continuous distribution of position-dependent loop extrusion rates, arising from the aggregate effect of multiple interactions between loop extrusion complexes and chromatin. This paradigm offers greater flexibility in recapitulating diverse features in Hi-C data than strictly localized loop extrusion barriers.

We have also added the following paragraph in the Discussion section of the manuscript to elaborate this point (lines 499-521):

"Although 'bottom-up' models which incorporate explicit boundary elements do not exist for non-vertebrate eukaryotes, one may wonder how well such LEF models, if properly modified and applied, would perform in describing Hi-C maps with diverse features. To this end, we examined the performance of the model described in Ref. [49] in describing the Hi-C map of interphase S. cerevisiae. Reference [49] uses cohesin ChIP-seq peaks in meiotic S. cerevisiae to define the positions of loop extrusion barriers which either completely stall an encountering LEF anchor with a certain probability or let it pass. We apply this 'explicit barrier' model to interphase S. pombe, using its cohesin ChIP-seq peaks to define the positions of loop extrusion barriers, and using Ref. [49]'s best-fit value of 0.05 for the pass-through probability. Supplementary Figure 19A presents the corresponding simulated Hi-C map the 0.3-1.3 kb region of Chr 2 of interphase S. pombe in comparison with the corresponding Hi-C data. It is evident that the explicit barrier model provides a poorer description of the Hi-C data of interphase S. pombe compared to the CCLE model, as indicated by the MPR and Pearson correlation scores of 1.6489 and 0.2267, respectively. While the explicit barrier model appears capable of accurately reproducing Hi-C data with punctate patterns, typically accompanied by strong peaks in the corresponding cohesin ChIP-seq, it seems less effective in cases such as in interphase S. pombe, where the Hi-C data lacks punctate patterns and sharp TAD boundaries, and the corresponding cohesin ChIP-seq shows low-contrast peaks. The success of the CCLE model in describing the Hi-C data of both S. pombe and S. cerevisiae, which exhibit very different features, suggests that the current paradigm of localized, well-defined boundary elements may not be the only approach to understanding loop extrusion. By contrast, CCLE allows for a concept of continuous distribution of position-dependent loop extrusion rates, arising from the aggregate effect of multiple interactions between loop extrusion complexes and chromatin. This paradigm offers greater flexibility in recapitulating diverse features in Hi-C data than strictly localized loop extrusion barriers."

Reviewer #1 (Significance (Required)):

This simple model is useful to confirm that cohesin positions dictate the position of loops, which was predicted already and proposed in many studies. However, it should be considered a starting point as it does not faithfully predict all the features of chromatin organisation, particularly at better resolution.

Response:

As described in more detail above, we do not agree with the assertion of the referee that the CCLE model "does not faithfully predict all the features of chromatin organization, particularly at better resolution" and provide additional new data to support the conclusion that the CCLE model provides a much needed approach to model non-vertebrate contact maps and outperforms the single prior attempt to predict budding yeast Hi-C data using information from cohesin ChIP-seq.

*It will mostly be of interest to those in the chromosome organisation field, working in organisms or systems that do not have ctcf. *

__Response: __

We agree that this work will be of special interest to researchers working on chromatin organization of non-vertebrate organisms. We would reinforce that yeast are frequently used models for the study of cohesin, condensin, and chromatin folding more generally. Indeed, in the last two months alone there are two Molecular Cell papers, one Nature Genetics paper, and one Cell Reports paper where loop extrusion in yeast models is directly relevant. We also believe, however, that the model will be of interest for the field in general as it simultaneously encompasses various scenarios that may lead to slowing down or stalling of LEFs.

This reviewer is a cell biologist working in the chromosome organisation field, but does not have modelling experience and therefore does not have the expertise to determine if the modelling part is mathematically sound and has assumed that it is.

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

Summary: Yuan et al. report on their development of an analytical model ("CCLE") for loop extrusion with genomic-position-dependent speed, with the idea of accounting for barriers to loop extrusion. They write down master equations for the probabilities of cohesin occupancy at each genomic site and obtain approximate steady-state solutions. Probabilities are governed by cohesin translocation, loading, and unloading. Using ChIP-seq data as an experimental measurement of these probabilities, they numerically fit the model parameters, among which are extruder density and processivity. Gillespie simulations with these parameters combined with a 3D Gaussian polymer model were integrated to generate simulated Hi-C maps and cohesin ChIP-seq tracks, which show generally good agreement with the experimental data. The authors argue that their modeling provides evidence that loop extrusion is the primary mechanism of chromatin organization on ~10-100 kb scales in S. pombe and S. cerevisiae.

Major comments:

1. I am unconvinced that this analysis specifically is sufficient to demonstrate that extrusion is the primary organizer of chromatin on these scales; moreover, the need to demonstrate this is questionable, as extrusion is widely accepted, even if not universally so. How is the agreement of CCLE with experiments more demonstrative of loop extrusion than previous modeling?

__Response: __

We agree with the referee's statement that "loop extrusion is extrusion is widely accepted, even if not universally so". We disagree with the referee that this state of affairs means that "the need to demonstrate this (i.e. loop extrusion) is questionable". On the contrary, studies that provide further compelling evidence that cohesin-based loop extrusion is the primary organizer of chromatin, such as ours, must surely be welcomed, first, in order to persuade those who remain unconvinced by the loop extrusion mechanism in general, and, secondly, because, until the present work, quantitative models of loop extrusion, capable of reproducing Hi-C maps quantitatively, in yeasts and other non-vertebrate eukaryotes have been lacking, leaving open the question of whether loop extrusion can describe Hi-C maps beyond vertebrates. CCLE has now answered that question in the affirmative. Moreover, the existence of a robust model to predict contact maps in non-vertebrate models, which are extensively used in the pursuit of research questions in chromatin biology, will be broadly enabling to the field.

It is fundamental that if a simple, physically-plausible model/hypothesis is able to describe experimental data quantitatively, it is indeed appropriate to ascribe considerable weight to that model/hypothesis (until additional data become available to refute the model).

How is the agreement of CCLE with experiments more demonstrative of loop extrusion than previous modeling?

Response:

As noted above and in the original manuscript, we are unaware of previous quantitative modeling of cohesin-based loop extrusion and the resultant Hi-C maps in organisms that lack CTCF, namely non-vertebrate eukaryotic models such as fission yeast or budding yeast, as we apply here. As noted in the original manuscript, previous quantitative modeling of Hi-C maps based on cohesin loop extrusion and CTCF boundary elements has been convincing that loop extrusion is indeed relevant in vertebrates, but the restriction to vertebrates excludes most of the tree of life.

Below, the referee cites two examples of loop extrusion outside of vertebrates. The one that is suggested to correspond to yeast cells (Dequeker et al. Nature 606:197 2022) actually corresponds to mouse cells, which are vertebrate cells. The other one models the Hi-C map of the prokaryote, Bacillus subtilis, based on loop extrusion of the bacterial SMC complex thought to most resemble condensin (not cohesin), subject to barriers to loop extrusion that are related to genes or involving prokaryote-specific Par proteins (Brandao et al. PNAS 116:20489 2019). We have referenced this work in the revised manuscript but would reinforce that it lacks utility in predicting the contact maps for non-vertebrate eukaryotes.

Relatedly, similar best fit values for S. pombe and S. cerevisiae might not point to a mechanistic conclusion (same "underlying mechanism" of loop extrusion), but rather to similar properties for loop-extruding cohesins in the two species.

Response:

In the revised manuscript, we have replaced "suggesting that the underlying mechanism that governs loop extrusion by cohesin is identical in both species" with "suggesting loop-extruding cohesins possess similar properties in both species" (lines 367-368).

As an alternative, could a model with variable binding probability given by ChIP-seq and an exponential loop-size distribution work equally well? The stated lack of a dependence on extrusion timescale suggests that a static looping model might succeed. If not, why not?

Response:

A hypothetical mechanism that generates the same instantaneous loop distributions and correlations as loop extrusion would lead to the same Hi-C map as does loop extrusion. This circumstance is not confined to CCLE, but is equally applicable to previous CTCF-based loop extrusion models. It holds because Hi-C and ChIP-seq, and therefore models that seek to describe these measurements, provide a snapshot of the chromatin configuration at one instant of time.

We would reinforce that there is no physical basis for a diffusion capture model with an approximately-exponential loop size distributions. Nevertheless, one can reasonably ask whether a physically-sensible diffusion capture model can simultaneously match cohesin ChIP-seq and Hi-C. Motivated by the referee's comment we have addressed this question and, accordingly, in the revised manuscript, we have added (1) an entire subsection entitled "Diffusion capture does not reproduce experimental interphase S. pombe Hi-C maps" (lines 303-335) and (2) Supplementary Figure 15. As we now demonstrate, the CCLE model vastly outperforms an equilibrium binding model in reproducing the experimental Hi-C maps and measured P(s).

*2. I do not understand how the loop extrusion residence time drops out. As I understand it, Eq 9 converts ChIP-seq to lattice site probability (involving N_{LEF}, which is related to \rho, and \rho_c). Then, Eqs. 3-4 derive site velocities V_n and U_n if we choose rho, L, and \tau, with the latter being the residence time. This parameter is not specified anywhere and is claimed to be unimportant. It may be true that the choice of timescale is arbitrary in this procedure, but can the authors please clarify? *

__Response: __

As noted above, Hi-C and ChIP-seq both capture chromatin configuration at one instant in time. Therefore, such measurements cannot and do not provide any time-scale information, such as the loop extrusion residence time (LEF lifetime) or the mean loop extrusion rate. For this reason, neither our CCLE simulations, nor other researchers' previous simulations of loop extrusion in vertebrates with CTCF boundary elements, provide any time-scale information, because the experiments they seek to describe do not contain time-scale information. The Hi-C map simulations can and do provide information concerning the loop size, which is the product of the loop lifetime and the loop extrusion rate. Lines 304-305 of the revised manuscript include the text: "Because Hi-C and ChIP-seq both characterize chromatin configuration at a single instant of time, and do not provide any direct time-scale information, ..."

In practice, we set the LEF lifetime to be some explicit value with arbitrary time-unit. We have added a sentence in the Methods that reads, "In practice, however, we set the LEF dissociation rate to 5e-4 time-unit-1 (equivalent to a lifetime of 2000 time-units), and the nominal LEF extrusion rate (aka \rho*L/\tau, see Supplementary Methods) can be determined from the given processivity" (lines 599-602), to clarify this point. We have also changed the terminology from "timesteps" to "LEF events" in the manuscript as the latter is more accurate for our purpose.

1. The assumptions in the solution and application of the CCLE model are potentially constraining to a limited number of scenarios. In particular the authors specify that current due to binding/unbinding, A_n - D_n, is small. This assumption could be problematic near loading sites (centromeres, enhancers in higher eukaryotes, etc.) (where current might be dominated by A_n and V_n), unloading sites (D_n and V_{n-1}), or strong boundaries (D_n and V_{n-1}). The latter scenario is particularly concerning because the manuscript seems to be concerned with the presence of unidentified boundaries. This is partially mitigated by the fact that the model seems to work well in the chosen examples, but the authors should discuss the limitations due to their assumptions and/or possible methods to get around these limitations.

4. Related to the above concern, low cohesin occupancy is interpreted as a fast extrusion region and high cohesin occupancy is interpreted as a slow region. But this might not be true near cohesin loading and unloading sites.

__Response: __

Our response to Referee 2's Comments 3. and 4. is that both in the original manuscript and in the revised manuscript we clearly delineate the assumptions underlying CCLE and we carefully assess the extent to which these assumptions are violated (lines 123-126 and 263-279 in the revised manuscript). For example, Supplementary Figure 12 shows that across the S. pombe genome as a whole, violations of the CCLE assumptions are small. Supplementary Figure 13 shows that violations are similarly small for meiotic S. cerevisiae. However, to explicitly address the concern of the referee, we have added the following sentences to the revised manuscript:

Lines 277-279:

"While loop extrusion in interphase S. pombe seems to well satisfy the assumptions underlying CCLE, this may not always be the case in other organisms."

Lines 359-361:

"In addition, the three quantities, given by Eqs. 6, 7, and 8, are distributed around zero with relatively small fluctuations (Supplementary Fig. 13), indicating that CCLE model is self-consistent in this case also."

In the case of mitotic S. cerevisiae, Supplementary Figure 14 shows that these quantities are small for most of genomic locations, except near the cohesin ChIP-seq peaks. We ascribe these greater violations of CCLE's assumptions at the locations of cohesin peaks in part to the low processivity of mitotic cohesin in S. cerevisiae, compared to that of meiotic S. cerevisiae and interphase S. pombe, and in part to the low CCLE loop extrusion rate at the cohesin peaks. We have added a paragraph at the end of the Section "CCLE Describes TADs and Loop Configurations in Mitotic S. cerevisiae" to reflect these observations (lines 447-461).

1. *The mechanistic insight attempted in the discussion, specifically with regard to Mis4/Scc2/NIPBL and Pds5, is problematic. First, it is not clear how the discussion of Nipbl and Pds5 is connected to the CCLE method; the justification is that CCLE shows cohesin distribution is linked to cohesin looping, which is already a questionable statement (point 1) and doesn't really explain how the model offers new insight into existing Nipbl and Pds5 data. *

Furthermore, I believe that the conclusions drawn on this point are flawed, or at least, stated with too much confidence. The authors raise the curious point that Nipbl ChIP-seq does not correlate well with cohesin ChIP-seq, and use this as evidence that Nipbl is not a part of the loop-extruding complex in S. pombe, and it is not essential in humans. Aside from the molecular evidence in human Nipbl/cohesin (acknowledged by authors), there are other reasons to doubt this conclusion. First, depletion of Nipbl (rather than binding partner Mau2 as in ref 55) in mouse cells strongly inhibits TAD formation (Schwarzer et al. Nature 551:51 2017). Second, at least two studies have raised concerns about Nibpl ChIP-seq results: 1) Hu et al. Nucleic Acids Res 43:e132 2015, which shows that uncalibrated ChIP-seq can obscure the signal of protein localization throughout the genome due to the inability to distinguish from background * and 2) Rhodes et al. eLife 6:e30000, which uses FRAP to show that Nipbl binds and unbinds to cohesin rapidly in human cells, which could go undetected in ChIP-seq, especially when uncalibrated. It has not been shown that these dynamics are present in yeast, but there is no reason to rule it out yet.*

Similar types of critiques could be applied to the discussion of Pds5. There is cross-correlation between Psc3 and Pds5 in S. pombe, but the authors are unable to account for whether Pds5 binding is transient and/or necessary to loop extrusion itself or, more importantly, whether Pds5 ChIP is associated with extrusive or cohesive cohesins; cross-correlation peaks at about 0.6, but note that by the authors own estimates, cohesive cohesins are approximately half of all cohesins in S. pombe (Table 3).

*Due to the above issues, I suggest that the authors heavily revise this discussion to better reflect the current experimental understanding and the limited ability to draw such conclusions based on the current CCLE model. *

__Response: __

As stated above, our study demonstrates that the CCLE approach is able to take as input cohesin (Psc3) ChIP-seq data and produce as output simulated Hi-C maps that well reproduce the experimental Hi-C maps of interphase S. pombe and meiotic S. cerevisiae. This result is evident from the multiple Hi-C comparison figures in both the original and the revised manuscripts. In light of this circumstance, the referee's statement that it is "questionable", that CCLE shows that cohesin distribution (as quantified by cohesin ChIP-seq) is linked to cohesin looping (as quantified by Hi-C), is demonstrably incorrect.

However, we did not intend to suggest that Nipbl and Pds5 are not crucial for cohesin loading, as the reviewer states. Rather, our inquiries relate to a more nuanced question of whether these factors only reside at loading sites or, instead, remain as a more long-lived constituent component of the loop extrusion complex. We regret any confusion and have endeavored to clarify this point in the revised manuscript in response to Referee 2's Comment 5. as well as Referee 1's Minor Comment 1. We have now better explained how the CCLE model may offer new insight from existing ChIP-seq data in general and from Mis4/Nipbl and Pds5 ChIP-seq, in particular. Accordingly, we have followed Referee 2's advice to heavily revise the relevant section of the Discussion.

To this end, we have removed the following text from the original manuscript:

"The fact that the cohesin distribution along the chromatin is strongly linked to chromatin looping, as evident by the success of the CCLE model, allows for new insights into in vivo LEF composition and function. For example, recently, two single-molecule studies [37, 38] independently found that Nipbl, which is the mammalian analogue of Mis4, is an obligate component of the loop-extruding human cohesin complex. Ref. [37] also found that cohesin complexes containing Pds5, instead of Nipbl, are unable to extrude loops. On this basis, Ref. [32] proposed that, while Nipbl-containing cohesin is responsible for loop extrusion, Pds5-containing cohesin is responsible for sister chromatid cohesion, neatly separating cohesin's two functions according to composition. However, the success of CCLE in interphase S. pombe, together with the observation that the Mis4 ChIP-seq signal is uncorrelated with the Psc3 ChIP-seq signal (Supplementary Fig. 7) allows us to infer that Mis4 cannot be a component of loop-extruding cohesin in S. pombe. On the other hand, Pds5 is correlated with Psc3 in S. pombe (Supplementary Fig. 7) suggesting that both proteins are involved in loop-extruding cohesin, contradicting a hypothesis that Pds5 is a marker for cohesive cohesin in S. pombe. In contrast to the absence of Mis4-Psc3 correlation in S. pombe, in humans, Nipbl ChIP-seq and Smc1 ChIP-seq are correlated (Supplementary Fig. 7), consistent with Ref. [32]'s hypothesis that Nipbl can be involved in loop-extruding cohesin in humans. However, Ref. [55] showed that human Hi-C contact maps in the absence of Nipbl's binding partner, Mau2 (Ssl3 in S. pombe [56]) show clear TADs, consistent with loop extrusion, albeit with reduced long-range contacts in comparison to wild-type maps, indicating that significant loop extrusion continues in live human cells in the absence of Nipbl-Mau2 complexes. These collected observations suggest the existence of two populations of loop-extruding cohesin complexes in vivo, one that involves Nipbl-Mau2 and one that does not. Both types are present in mammals, but only Mis4-Ssl3-independent loop-extruding cohesin is present in S. pombe."

And we have replaced it by the following text in the revised manuscript (lines 533-568):

"As noted above, the input for our CCLE simulations of chromatin organization in S. pombe, was the ChIP-seq of Psc3, which is a component of the cohesin core complex [75]. Accordingly, Psc3 ChIP-seq represents how the cohesin core complex is distributed along the genome. In S. pombe, the other components of the cohesin core complex are Psm1, Psm3, and Rad21. Because these proteins are components of the cohesin core complex, we expect that the ChIP-seq of any of these proteins would closely match the ChIP-seq of Psc3, and would equally well serve as input for CCLE simulations of S. pombe genome organization. Supplementary Figure 20C confirms significant correlations between Psc3 and Rad21. In light of this observation, we then reason that the CCLE approach offers the opportunity to investigate whether other proteins beyond the cohesin core are constitutive components of the loop extrusion complex during the extrusion process (as opposed to cohesin loading or unloading). To elaborate, if the ChIP-seq of a non-cohesin-core protein is highly correlated with the ChIP-seq of a cohesin core protein, we can infer that the protein in question is associated with the cohesin core and therefore is a likely participant in loop-extruding cohesin, alongside the cohesin core. Conversely, if the ChIP-seq of a putative component of the loop-extruding cohesin complex is uncorrelated with the ChIP-seq of a cohesin core protein, then we can infer that the protein in question is unlikely to be a component of loop-extruding cohesin, or at most is transiently associated with it.

For example, in S. pombe, the ChIP-seq of the cohesin regulatory protein, Pds5 [74], is correlated with the ChIP-seq of Psc3 (Supplementary Fig. 20B) and with that of Rad21 (Supplementary Fig. 20D), suggesting that Pds5 can be involved in loop-extruding cohesin in S. pombe, alongside the cohesin core proteins. Interestingly, this inference concerning fission yeast cohesin subunit, Pds5, stands in contrast to the conclusion from a recent single-molecule study [38] concerning cohesin in vertebrates. Specifically, Reference [38] found that cohesin complexes containing Pds5, instead of Nipbl, are unable to extrude loops.

Additionally, as noted above, in S. pombe the ChIP-seq signal of the cohesin loader, Mis4, is uncorrelated with the Psc3 ChIP-seq signal (Supplementary Fig. 20A), suggesting that Mis4 is, at most, a very transient component of loop-extruding cohesin in S. pombe, consistent with its designation as a "cohesin loader". However, both References [38] and [39] found that Nipbl (counterpart of S. pombe's Mis4) is an obligate component of the loop-extruding human cohesin complex, more than just a mere cohesin loader. Although CCLE has not yet been applied to vertebrates, from a CCLE perspective, the possibility that Nipbl may be required for the loop extrusion process in humans is bolstered by the observation that in humans Nipbl ChIP-seq and Smc1 ChIP-seq show significant correlations (Supplementary Fig. 20G), consistent with Ref. [32]'s hypothesis that Nipbl is involved in loop-extruding cohesin in vertebrates. A recent theoretical model of the molecular mechanism of loop extrusion by cohesin hypothesizes that transient binding by Mis4/Nipbl is essential for permitting directional reversals and therefore for two-sided loop extrusion [41]. Surprisingly, there are significant correlations between Mis4 and Pds5 in S. pombe (Supplementary Fig. 20E), indicating Pds5-Mis4 association, outside of the cohesin core complex."

In response to Referee 2's specific comment that "at least two studies have raised concerns about Nibpl ChIP-seq results", we note (1) that, while Hu et al. Nucleic Acids Res 43:e132 2015 present a general method for calibrating ChIP-seq results, they do not measure Mis4/Nibpl ChIP-seq, nor do they raise any specific concerns about Mis4/Nipbl ChIP-seq, and (2) that (as noted above, in response to Referee 1's comment) while the FRAP analysis presented by Rhodes et al. eLife 6:e30000 indicates that, in HeLa cells, Nipbl has a residence time bound to cohesin of about 50 seconds, nevertheless, as shown in Supplementary Fig. 20G in the revised manuscript, there is a significant cross-correlation between the Nipbl ChIP-seq and Smc1 ChIP-seq in humans, indicating that a transient association between Nipbl and cohesin is detected by ChIP-seq, the referees' concerns notwithstanding.

We thank the referee for pointing out Schwarzer et al. Nature 551:51 2017. However, our interpretation of these data is different than the referee's. As noted in our original manuscript, Nipbl has traditionally been considered to be a cohesin loading factor. If the role of Nipbl was solely to load cohesin, then we would expect that depleting Nipbl would have a major effect on the Hi-C map, because fewer cohesins are loaded onto the chromatin. Figure 2 of Schwarzer et al. Nature 551:51 2017, shows the effect of depleting Nibpl on a vertebrate Hi-C map. Even in this case when Nibpl is absent, this figure (Figure 2 of Schwarzer et al. Nature 551:51 2017) shows that TADs persist, albeit considerably attenuated. According to the authors' own analysis associated with Fig. 2 of their paper, these attenuated TADs correspond to a smaller number of loop-extruding cohesin complexes than in the presence of Nipbl. Since Nipbl is depleted, these loop-extruding cohesins necessarily cannot contain Nipbl. Thus, the data and analysis of Schwarzer et al. Nature 551:51 2017 actually seem consistent with the existence of a population of loop-extruding cohesin complexes that do not contain Nibpl.

Concerning the referee's comment that we cannot be sure whether Pds5 ChIP is associated with extrusive or cohesive cohesin, we note that, as explained in the manuscript, we assume that the cohesive cohesins are uniformly distributed across the genome, and therefore that peaks in the cohesin ChIP-seq are associated with loop-extruding cohesins. The success of CCLE in describing Hi-C maps justifies this assumption a posteriori. Supplementary Figure 20B shows that the ChIP-seq of Pds5 is correlated with the ChIP-seq of Psc3 in S. pombe, that is, that peaks in the ChIP-seq of Psc3, assumed to derive from loop-extruding cohesin, are accompanied by peaks in the ChIP-seq of Pds5. This is the reasoning allowing us to associate Pds5 with loop-extruding cohesin in S. pombe.

1. I suggest that the authors recalculate correlations for Hi-C maps using maps that are rescaled by the P(s) curves. As currently computed, most of the correlation between maps could arise from the characteristic decay of P(s) rather than smaller scale features of the contact maps. This could reduce the surprising observed correlation between distinct genomic regions in pombe (which, problematically, is higher than the observed correlation between simulation and experiment in cervisiae).

Response:

We thank the referee for this advice. Following this advice, throughout the revised manuscript, we have replaced our original calculation of the Pearson correlation coefficient of unscaled Hi-C maps with a calculation of the Pearson correlation coefficient of rescaled Hi-C maps. Since the MPR is formed from ratios of simulated to experimental Hi-C maps, this metric is unchanged by the proposed rescaling.

As explained in the original manuscript, we attribute the lower experiment-simulation correlation in the meiotic budding yeast Hi-C maps to the larger statistical errors of the meiotic budding yeast dataset, which arises because of its higher genomic resolution - all else being equal we can expect 25 times the counts in a 10 kb x10 kb bin as in a 2 kb x 2 kb bin. For the same reason, we expect larger statistical errors in the mitotic budding yeast dataset as well. Lower correlations for noisier data are to be expected in general.

*7. Please explain why the difference between right and left currents at any particular site, (R_n-L_n) / Rn+Ln, should be small. It seems easy to imagine scenarios where this might not be true, such as directional barriers like CTCF or transcribed genes. *

__Response: __

For simplicity, the present version of CCLE sets the site-dependent loop extrusion rates by assuming that the cohesin ChIP-seq signal has equal contributions from left and right anchors. Then, we carry out our simulations which subsequently allow us to examine the simulated left and right currents and their difference at every site. The distributions of normalized left-right difference currents are shown in Supplementary Figures 12B, 13B, and 14D, for interphase S. pombe, meiotic S. cerevisiae, and mitotic S. cerevisiae, respectively. They are all centered at zero with standard deviations of 0.12, 0.16, and 0.33. Thus, it emerges from our simulations that the difference current is indeed generally small.

8. Optional, but I think would greatly improve the manuscript, but can the authors: a) analyze regions of high cohesin occupancy (assumed to be slow extrusion regions) to determine if there's anything special in these regions, such as more transcriptional activity

__Response: __

In response to Referee 1's similar comment, we have calculated the correlation between the locations of convergent genes and cohesin ChIP-seq. Supplementary Figure 18A in the revised manuscript shows that for interphase S. pombe no correlations are evident, whereas for both of meiotic and mitotic S. cerevisiae, there are significant correlations between these two quantities (Supplementary Fig. 17).

*b) apply this methodology to vertebrate cell data *

__Response: __

The application of CCLE to vertebrate data is outside the scope of this paper which, as we have emphasized, has the goal of developing a model that can be robustly applied to non-vertebrate eukaryotic genomes. Nevertheless, CCLE is, in principle, applicable to all organisms in which loop extrusion by SMC complexes is the primary mechanism for chromatin spatial organization.

1. *A Github link is provided but the code is not currently available. *

__Response: __

The code is now available.

Minor Comments:

1. Please state the simulated LEF lifetime, since the statement in the methods that 15000 timesteps are needed for equilibration of the LEF model is otherwise not meaningful. Additionally, please note that backbone length is not necessarily a good measure of steady state, since the backbone can be compacted to its steady-state value while the loop distribution continues to evolve toward its steady state.

__Response: __

The terminology "timesteps" used in the original manuscript in fact should mean "the number of LEF events performed" in the simulation. Therefore, we have changed the terminology from "timesteps" to "LEF events".

The choice of 15000 LEF events is empirically determined to ensure that loop extrusion steady state is achieved, for the range of parameters considered. To address the referee's concern regarding the uncertainty of achieving steady state after 15000 LEF events, we compared two loop size distributions: each distribution encompasses 1000 data points, equally separated in time, one between LEF event 15000 and 35000, and the other between LEF event 80000 and 100000. The two distributions are within-errors identical, suggesting that the loop extrusion steady state is well achieved within 15000 LEF events.

2. How important is the cohesive cohesin parameter in the model, e.g., how good are fits with \rho_c = 0?

__Response: __

As stated in the original manuscript, the errors on \rho_c on the order of 10%-20% (for S. pombe). Thus, fits with \rho_c=0 are significantly poorer than with the best-fit values of \rho_c.

*3. A nice (but non-essential) supplemental visualization might be to show a scatter of sim cohesin occupancy vs. experiment ChIP. *

__Response: __

We have chosen not to do this, because we judge that the manuscript is already long enough. Figures 3A, 5D, and 6C already compare the experimental and simulated ChIP-seq, and these figures already contain more information than the figures proposed by the referee.

1. *A similar calculation of Hi-C contacts based on simulated loop extruder positions using the Gaussian chain model was previously presented in Banigan et al. eLife 9:e53558 2020, which should be cited. *

__Response: __

We thank the referee for pointing out this citation. We have added it to the revised manuscript.

1. It is stated that simulation agreement with experiments for cerevisiae is worse in part due to variability in the experiments, with MPR and Pearson numbers for cerevisiae replicates computed for reference. But these numbers are difficult to interpret without, for example, similar numbers for duplicate pombe experiments. Again, these numbers should be generated using Hi-C maps scaled by P(s), especially in case there are systematic errors in one replicate vs. another.

__Response: __

As noted above, throughout the revised manuscript, we now give the Pearson correlation coefficients of scaled-by-P(s) Hi-C maps.

1. *In the model section, it is stated that LEF binding probabilities are uniformly distributed. Did the authors mean the probability is uniform across the genome or that the probability at each site is a uniformly distributed random number? Please clarify, and if the latter, explain why this unconventional assumption was made. *

__Response: __

It is the former. We have modified the manuscript to clarify that LEFs "initially bind to empty, adjacent chromatin lattice sites with a binding probability, that is uniformly distributed across the genome." (lines 587-588).

*7. Supplement p4 line 86 - what is meant by "processivity of loops extruded by isolated LEFs"? "size of loops extruded by..." or "processivity of isolated LEFs"? *

__Response: __

Here "processivity of isolated LEFs" is defined as the processivity of one LEF without the interference (blocking) from other LEFs. We have changed "processivity of loops extruded by isolated LEFs" to "processivity of isolated LEFs" for clarity.

1. The use of parentheticals in the caption to Table 2 is a little confusing; adding a few extra words would help.

__Response: __

In the revised manuscript, we have added an additional sentence, and have removed the offending parentheses.

1. *Page 12 sentence line 315-318 is difficult to understand. The barrier parameter is apparently something from ref 47 not previously described in the manuscript. *

__Response: __

In the revised manuscript, we have removed mention of the "barrier parameter" from the discussion.

1. *Statement on p14 line 393-4 is false: prior LEF models have not been limited to vertebrates, and the authors have cited some of them here. There are also non-vertebrate examples with extrusion barriers: genes as boundaries to condensin in bacteria (Brandao et al. PNAS 116:20489 2019) and MCM complexes as boundaries to cohesin in yeast (Dequeker et al. Nature 606:197 2022). *

__Response: __

In fact, Dequeker et al. Nature 606:197 2022 concerns the role of MCM complexes in blocking cohesin loop extrusion in mouse zygotes. Mouse is a vertebrate. The sole aspect of this paper, that is associated with yeast, is the observation of cohesin blocking by the yeast MCM bound to the ARS1 replication origin site, which is inserted on a piece of lambda phage DNA. No yeast genome is used in the experiment. Therefore, the referee is mistaken to suggest that this paper models yeast genome organization.

We thank the referee for pointing out Brandao et al. PNAS 116:20489 2019, which includes the development of a tour-de-force model of condensin-based loop extrusion in the prokaryote, Bacillus subtilis, in the presence of gene barriers to loop extrusion. To acknowledge this paper, we have changed the objectionable sentence to now read (lines 571-575):

"... prior LEF models have been overwhelmingly limited to vertebrates, which express CTCF and where CTCF is the principal boundary element. Two exceptions, in which the LEF model was applied to non-vertebrates, are Ref. [49], discussed above, and Ref. [76] (Brandao et al.), which models the Hi-C map of the prokaryote, Bacillus subtilis, on the basis of condensin loop extrusion with gene-dependent barriers."

*Referees cross-commenting *

I agree with the comments of Reviewer 1, which are interesting and important points that should be addressed.

*Reviewer #2 (Significance (Required)):

Analytically approaching extrusion by treating cohesin translocation as a conserved current is an interesting approach to modeling and analysis of extrusion-based chromatin organization. It appears to work well as a descriptive model. But I think there are major questions concerning the mechanistic value of this model, possible applications of the model, the provided interpretations of the model and experiments, and the limitations of the model under the current assumptions. I am unconvinced that this analysis specifically is sufficient to demonstrate that extrusion is the primary organizer of chromatin on these scales; moreover, the need to demonstrate this is questionable, as extrusion is widely accepted, even if not universally so. It is also unclear that the minimal approach of the CCLE necessarily offers an improved physical basis for modeling extrusion, as compared to previous efforts such as ref 47, as claimed by the authors. There are also questions about significance due to possible limitations of the model (detailed above). Applying the CCLE model to identify barriers would be interesting, but is not attempted. Overall, the work presents a reasonable analytical model and numerical method, but until the major comments above are addressed and some reasonable application or mechanistic value or interpretation is presented, the overall significance is somewhat limited.*

__Response: __

We agree with the referee that analytically approaching extrusion by treating cohesin translocation as a conserved current is an interesting approach to modeling and analysis of extrusion-based chromatin organization. We also agree with the referee that it works well as a descriptive model (of Hi-C maps in S. pombe and S. cerevisiae). Obviously, we disagree with the referee's other comments. For us, being able to describe the different-appearing Hi-C maps of interphase S. pombe (Fig. 1 and Supplementary Figures 1-9), meiotic S. cerevisiae (Fig. 5) and mitotic S. cerevisiae (Fig. 6), all with a common model with just a few fitting parameters that differ between these examples, is significant and novel. The reviewer prematurely ignores the fact that there are still debates about whether "diffusion-capture"-like model is the more dominant mechanism that shape chromatin spatial organization at the TAD-scale. Many works have argued that such models could describe TAD-scale chromatin organization, as cited in the revised manuscript (Refs. [11, 14, 15, 17, 20, 22-24, 55]). However, in contrast to the poor description of the Hi-C map using diffusion capture model (as demonstrated in the revised manuscript and Supplementary Fig. 15), the excellent experiment-simulation agreement achieved by CCLE provides compelling evidence that cohesin-based loop extrusion is indeed the primary organizer of TAD-scale chromatin.

Importantly, CCLE provides a theoretical base for how loop extrusion models can be generalized and applied to organisms without known loop extrusion barriers. Our model also highlights that (and provides means to account for) distributed barriers that impede but do not strictly block LEFs could also impact chromatin configurations. This case might be of importance to organisms with CTCF motifs that infrequently coincide with TAD boundaries, for instance, in the case of Drosophila melanogaster. Moreover, CCLE promises theoretical descriptions of the Hi-C maps of other non-vertebrates in the future, extending the quantitative application of the LEF model across the tree of life. This too would be highly significant if successful.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

Summary:

Yuan et al. report on their development of an analytical model ("CCLE") for loop extrusion with genomic-position-dependent speed, with the idea of accounting for barriers to loop extrusion. They write down master equations for the probabilities of cohesin occupancy at each genomic site and obtain approximate steady-state solutions. Probabilities are governed by cohesin translocation, loading, and unloading. Using ChIP-seq data as an experimental measurement of these probabilities, they numerically fit the model parameters, among which are extruder density and processivity. Gillespie simulations with these parameters combined with a 3D Gaussian polymer model were integrated to generate simulated Hi-C maps and cohesin ChIP-seq tracks, which show generally good agreement with the experimental data. The authors argue that their modeling provides evidence that loop extrusion is the primary mechanism of chromatin organization on ~10-100 kb scales in S. pombe and S. cerevisiae.

Major comments:

1. I am unconvinced that this analysis specifically is sufficient to demonstrate that extrusion is the primary organizer of chromatin on these scales; moreover, the need to demonstrate this is questionable, as extrusion is widely accepted, even if not universally so. How is the agreement of CCLE with experiments more demonstrative of loop extrusion than previous modeling? Relatedly, similar best fit values for S. pombe and S. cerevisiae might not point to a mechanistic conclusion (same "underlying mechanism" of loop extrusion), but rather to similar properties for loop-extruding cohesins in the two species. As an alternative, could a model with variable binding probability given by ChIP-seq and an exponential loop-size distribution work equally well? The stated lack of a dependence on extrusion timescale suggests that a static looping model might succeed. If not, why not?
2. I do not understand how the loop extrusion residence time drops out. As I understand it, Eq 9 converts ChIP-seq to lattice site probability (involving N_{LEF}, which is related to \rho, and \rho_c). Then, Eqs. 3-4 derive site velocities V_n and U_n if we choose rho, L, and \tau, with the latter being the residence time. This parameter is not specified anywhere and is claimed to be unimportant. It may be true that the choice of timescale is arbitrary in this procedure, but can the authors please clarify?
3. The assumptions in the solution and application of the CCLE model are potentially constraining to a limited number of scenarios. In particular the authors specify that current due to binding/unbinding, A_n - D_n, is small. This assumption could be problematic near loading sites (centromeres, enhancers in higher eukaryotes, etc.) (where current might be dominated by A_n and V_n), unloading sites (D_n and V_{n-1}), or strong boundaries (D_n and V_{n-1}). The latter scenario is particularly concerning because the manuscript seems to be concerned with the presence of unidentified boundaries. This is partially mitigated by the fact that the model seems to work well in the chosen examples, but the authors should discuss the limitations due to their assumptions and/or possible methods to get around these limitations.
4. Related to the above concern, low cohesin occupancy is interpreted as a fast extrusion region and high cohesin occupancy is interpreted as a slow region. But this might not be true near cohesin loading and unloading sites.
5. The mechanistic insight attempted in the discussion, specifically with regard to Mis4/Scc2/NIPBL and Pds5, is problematic. First, it is not clear how the discussion of Nipbl and Pds5 is connected to the CCLE method; the justification is that CCLE shows cohesin distribution is linked to cohesin looping, which is already a questionable statement (point 1) and doesn't really explain how the model offers new insight into existing Nipbl and Pds5 data.

Furthermore, I believe that the conclusions drawn on this point are flawed, or at least, stated with too much confidence. The authors raise the curious point that Nipbl ChIP-seq does not correlate well with cohesin ChIP-seq, and use this as evidence that Nipbl is not a part of the loop-extruding complex in S. pombe, and it is not essential in humans. Aside from the molecular evidence in human Nipbl/cohesin (acknowledged by authors), there are other reasons to doubt this conclusion. First, depletion of Nipbl (rather than binding partner Mau2 as in ref 55) in mouse cells strongly inhibits TAD formation (Schwarzer et al. Nature 551:51 2017). Second, at least two studies have raised concerns about Nibpl ChIP-seq results: 1) Hu et al. Nucleic Acids Res 43:e132 2015, which shows that uncalibrated ChIP-seq can obscure the signal of protein localization throughout the genome due to the inability to distinguish from background and 2) Rhodes et al. eLife 6:e30000, which uses FRAP to show that Nipbl binds and unbinds to cohesin rapidly in human cells, which could go undetected in ChIP-seq, especially when uncalibrated. It has not been shown that these dynamics are present in yeast, but there is no reason to rule it out yet.

Similar types of critiques could be applied to the discussion of Pds5. There is cross-correlation between Psc3 and Pds5 in S. pombe, but the authors are unable to account for whether Pds5 binding is transient and/or necessary to loop extrusion itself or, more importantly, whether Pds5 ChIP is associated with extrusive or cohesive cohesins; cross-correlation peaks at about 0.6, but note that by the authors own estimates, cohesive cohesins are approximately half of all cohesins in S. pombe (Table 3).

Due to the above issues, I suggest that the authors heavily revise this discussion to better reflect the current experimental understanding and the limited ability to draw such conclusions based on the current CCLE model. 6. I suggest that the authors recalculate correlations for Hi-C maps using maps that are rescaled by the P(s) curves. As currently computed, most of the correlation between maps could arise from the characteristic decay of P(s) rather than smaller scale features of the contact maps. This could reduce the surprising observed correlation between distinct genomic regions in pombe (which, problematically, is higher than the observed correlation between simulation and experiment in cervisiae). 7. Please explain why the difference between right and left currents at any particular site, (R_n-L_n) / Rn+Ln, should be small. It seems easy to imagine scenarios where this might not be true, such as directional barriers like CTCF or transcribed genes. 8. Optional, but I think would greatly improve the manuscript, but can the authors: a) analyze regions of high cohesin occupancy (assumed to be slow extrusion regions) to determine if there's anything special in these regions, such as more transcriptional activity

b) apply this methodology to vertebrate cell data 9. A Github link is provided but the code is not currently available.

Minor Comments:

1. Please state the simulated LEF lifetime, since the statement in the methods that 15000 timesteps are needed for equilibration of the LEF model is otherwise not meaningful. Additionally, please note that backbone length is not necessarily a good measure of steady state, since the backbone can be compacted to its steady-state value while the loop distribution continues to evolve toward its steady state.
2. How important is the cohesive cohesin parameter in the model, e.g., how good are fits with \rho_c = 0?
3. A nice (but non-essential) supplemental visualization might be to show a scatter of sim cohesin occupancy vs. experiment ChIP.
4. A similar calculation of Hi-C contacts based on simulated loop extruder positions using the Gaussian chain model was previously presented in Banigan et al. eLife 9:e53558 2020, which should be cited.
5. It is stated that simulation agreement with experiments for cerevisiae is worse in part due to variability in the experiments, with MPR and Pearson numbers for cerevisiae replicates computed for reference. But these numbers are difficult to interpret without, for example, similar numbers for duplicate pombe experiments. Again, these numbers should be generated using Hi-C maps scaled by P(s), especially in case there are systematic errors in one replicate vs. another.
6. In the model section, it is stated that LEF binding probabilities are uniformly distributed. Did the authors mean the probability is uniform across the genome or that the probability at each site is a uniformly distributed random number? Please clarify, and if the latter, explain why this unconventional assumption was made.
7. Supplement p4 line 86 - what is meant by "processivity of loops extruded by isolated LEFs"? "size of loops extruded by..." or "processivity of isolated LEFs"?
8. The use of parentheticals in the caption to Table 2 is a little confusing; adding a few extra words would help.
9. Page 12 sentence line 315-318 is difficult to understand. The barrier parameter is apparently something from ref 47 not previously described in the manuscript.
10. Statement on p14 line 393-4 is false: prior LEF models have not been limited to vertebrates, and the authors have cited some of them here. There are also non-vertebrate examples with extrusion barriers: genes as boundaries to condensin in bacteria (Brandao et al. PNAS 116:20489 2019) and MCM complexes as boundaries to cohesin in yeast (Dequeker et al. Nature 606:197 2022).

Referees cross-commenting

I agree with the comments of Reviewer 1, which are interesting and important points that should be addressed.

Significance

Analytically approaching extrusion by treating cohesin translocation as a conserved current is an interesting approach to modeling and analysis of extrusion-based chromatin organization. It appears to work well as a descriptive model. But I think there are major questions concerning the mechanistic value of this model, possible applications of the model, the provided interpretations of the model and experiments, and the limitations of the model under the current assumptions. I am unconvinced that this analysis specifically is sufficient to demonstrate that extrusion is the primary organizer of chromatin on these scales; moreover, the need to demonstrate this is questionable, as extrusion is widely accepted, even if not universally so. It is also unclear that the minimal approach of the CCLE necessarily offers an improved physical basis for modeling extrusion, as compared to previous efforts such as ref 47, as claimed by the authors. There are also questions about significance due to possible limitations of the model (detailed above). Applying the CCLE model to identify barriers would be interesting, but is not attempted. Overall, the work presents a reasonable analytical model and numerical method, but until the major comments above are addressed and some reasonable application or mechanistic value or interpretation is presented, the overall significance is somewhat limited.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

This manuscript presents a mathematical model for loop extrusion called the conserved-current loop extrusion model (CCLE). The model uses cohesin ChIP-Seq data to predict the Hi-C map and shows broad agreement between experimental Hi-C maps and simulated Hi-C maps. They test the model on Hi-C data from interphase fission yeast and meiotic budding yeast. The conclusion drawn by the authors is that peaks of cohesin represent loop boundaries in these situations, which they also propose extends to other organism/situations where Ctcf is absent.

Major comments

1. More recent micro-C/Hi-C maps, particularly for budding yeast mitotic cells and meiotic cells show clear puncta, representative of anchored loops, which are not well recapitulated in the simulated data from this study. However, such punta are cohesin-dependent as they disappear in the absence of cohesin and are enhanced in the absence of the cohesin release factor, Wapl. For example - see the two studies below. The model is therefore missing some key elements of the loop organisation. How do the authors explain this discrepency? It would also be very useful to test whether the model can predict the increased strength of loop anchors when Wapl1 is removed and cohesin levels increase.

Costantino L, Hsieh TS, Lamothe R, Darzacq X, Koshland D. Cohesin residency determines chromatin loop patterns. Elife. 2020 Nov 10;9:e59889. doi: 10.7554/eLife.59889. PMID: 33170773; PMCID: PMC7655110. Barton RE, Massari LF, Robertson D, Marston AL. Eco1-dependent cohesin acetylation anchors chromatin loops and cohesion to define functional meiotic chromosome domains. Elife. 2022 Feb 1;11:e74447. doi: 10.7554/eLife.74447. Epub ahead of print. PMID: 35103590; PMCID: PMC8856730. 2. Related to the point above, the simulated data has much higher resolution than the experimental data (1kb vs 10kb in the fission yeast dataset). Given that loop size is in the 20-30kb range, a good resolution is important to see the structural features of the chromosomes. Can the model observe these details that are averaged out when the resolution is increased? 3. Transcription, particularly convergent has been proposed to confer boundaries to loop extrusion. Can the authors recapitulate this in their model?

Minor comments

1. In the discussion, the authors cite the fact that Mis4 binding sites do not give good prediction of the HI-C maps as evidence that Mis4 is not important for loop extrusion. This can only be true if the position of Mis4 measured by ChIP is a true reflection of Mis4 position. However, Mis4 binding to cohesin/chromatin is very dynamic and it is likely that this is too short a time scale to be efficiently cross-linked for ChIP. Conversely, extensive experimental data in vivo and in vitro suggest that stimulation of cohesin's ATPase by Mis4-Ssl3 is important for loop extrusion activity.
2. Inclusion of a comparison of this model compared to previous models (for example bottom up models) would be extremely useful. What is the improvement of this model over existing models?

Significance

This simple model is useful to confirm that cohesin positions dictate the position of loops, which was predicted already and proposed in many studies. However, it should be considered a starting point as it does not faithfully predict all the features of chromatin organisation, particularly at better resolution. It will mostly be of interest to those in the chromosome organisation field, working in organisms or systems that do not have ctcf.

This reviewer is a cell biologist working in the chromosome organisation field, but does not have modelling experience and therefore does not have the expertise to determine if the modelling part is mathematically sound and has assumed that it is.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

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

I have trialled the package on my lab's data and it works as advertised. It was straightforward to use and did not require any special training. I am confident this is a tool that will be approachable even to users with limited computational experience. The use of artificial data to validate the approach - and to provide clear limits on applicability - is particularly helpful.

The main limitation of the tool is that it requires the user to manually select regions. This somewhat limits the generalisability and is also more subjective - users can easily choose "nice" regions that better match with their hypothesis, rather than quantifying the data in an unbiased manner. However, given the inherent challenges in quantifying biological data, such problems are not easily circumventable.

*

* I have some comments to clarify the manuscript:

1. A "straightforward installation" is mentioned. Given this is a Method paper, the means of installation should be clearly laid out.*

__This sentence is now modified. In the revised manuscript we now describe how to install the toolset and we give the link to the toolset website if further information is needed. __On this website, we provide a full video tutorial and a user manual. The user manual is provided as a supplementary material of the manuscript.

* It would be helpful if there was an option to generate an output with the regions analysed (i.e., a JPG image with the data and the drawn line(s) on top). There are two reasons for this: i) A major problem with user-driven quantification is accidental double counting of regions (e.g., a user quantifies a part of an image and then later quantifies the same region). ii) Allows other users to independently verify measurements at a later time.*

We agree that it is helpful to save the analyzed regions. To answer this comment and the other two reviewers' comments pointing at a similar feature, we have now included an automatic saving of the regions of interest. The user will be able to reopen saved regions of interest using a new function we included in the new version of PatternJ.

* 3. Related to the above point, it is highlighted that each time point would need to be analysed separately (line 361-362). It seems like it should be relatively straightforward to allow a function where the analysis line can be mapped onto the next time point. The user could then adjust slightly for changes in position, but still be starting from near the previous timepoint. Given how prevalent timelapse imaging is, this seems like (or something similar) a clear benefit to add to the software.*

We agree that the analysis of time series images can be a useful addition. We have added the analysis of time-lapse series in the new version of PatternJ. The principles behind the analysis of time-lapse series and an example of such analysis are provided in Figure 1 - figure supplement 3 and Figure 5, with accompanying text lines 140-153 and 360-372. The analysis includes a semi-automated selection of regions of interest, which will make the analysis of such sequences more straightforward than having to draw a selection on each image of the series. The user is required to draw at least two regions of interest in two different frames, and the algorithm will automatically generate regions of interest in frames in which selections were not drawn. The algorithm generates the analysis immediately after selections are drawn by the user, which includes the tracking of the reference channel.

* Line 134-135. The level of accuracy of the searching should be clarified here. This is discussed later in the manuscript, but it would be helpful to give readers an idea at this point what level of tolerance the software has to noise and aperiodicity.

*

We agree with the reviewer that a clarification of this part of the algorithm will help the user better understand the manuscript.__ We have modified the sentence to clarify the range of search used and the resulting limits in aperiodicity (now lines 176-181). __Regarding the tolerance to noise, it is difficult to estimate it a priori from the choice made at the algorithm stage, so we prefer to leave it to the validation part of the manuscript. We hope this solution satisfies the reviewer and future users.

*

**Referees cross-commenting**

I think the other reviewer comments are very pertinent. The authors have a fair bit to do, but they are reasonable requests. So, they should be encouraged to do the revisions fully so that the final software tool is as useful as possible.

Reviewer #1 (Significance (Required)):

Developing software tools for quantifying biological data that are approachable for a wide range of users remains a longstanding challenge. This challenge is due to: (1) the inherent problem of variability in biological systems; (2) the complexity of defining clearly quantifiable measurables; and (3) the broad spread of computational skills amongst likely users of such software.

In this work, Blin et al., develop a simple plugin for ImageJ designed to quickly and easily quantify regular repeating units within biological systems - e.g., muscle fibre structure. They clearly and fairly discuss existing tools, with their pros and cons. The motivation for PatternJ is properly justified (which is sadly not always the case with such software tools).

Overall, the paper is well written and accessible. The tool has limitations but it is clearly useful and easy to use. Therefore, this work is publishable with only minor corrections.

*We thank the reviewer for the positive evaluation of PatternJ and for pointing out its accessibility to the users.

*

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

# Summary

The authors present an ImageJ Macro GUI tool set for the quantification of one-dimensional repeated patterns that are commonly occurring in microscopy images of muscles.

# Major comments

In our view the article and also software could be improved in terms of defining the scope of its applicability and user-ship. In many parts the article and software suggest that general biological patterns can be analysed, but then in other parts very specific muscle actin wordings are used. We are pointing this out in the "Minor comments" sections below. We feel that the authors could improve their work by making a clear choice here. One option would be to clearly limit the scope of the tool to the analysis of actin structures in muscles. In this case we would recommend to also rename the tool, e.g. MusclePatternJ. The other option would be to make the tool about the generic analysis of one-dimensional patterns, maybe calling the tool LinePatternJ. In the latter case we would recommend to remove all actin specific wordings from the macro tool set and also the article should be in parts slightly re-written.

*

We agree with the reviewer that our initial manuscript used a mix of general and muscle-oriented vocabulary, which could make the use of PatternJ confusing especially outside of the muscle field. To make PatternJ useful for the largest community, we corrected the manuscript and the PatternJ toolset to provide the general vocabulary needed to make it understandable for every biologist. We modified the manuscript accordingly.

* # Minor/detailed comments

# Software

We recommend considering the following suggestions for improving the software.

## File and folder selection dialogs

In general, clicking on many of the buttons just opens up a file-browser dialog without any further information. For novel users it is not clear what the tool expects one to select here. It would be very good if the software could be rewritten such that there are always clear instructions displayed about which file or folder one should open for the different buttons.*

We experienced with the current version of macOS that the file-browser dialog does not display any message; we suspect this is the issue raised by the reviewer. This is a known issue of Fiji on Mac and all applications on Mac since 2016. We provided guidelines in the user manual and on the tutorial video to correct this issue by changing a parameter in Fiji. Given the issues the reviewer had accessing the material on the PatternJ website, which we apologize for, we understand the issue raised. We added an extra warning on the PatternJ website to point at this problem and its solution. Additionally, we have limited the file-browser dialog appearance to what we thought was strictly necessary. Thus, the user will experience fewer prompts, speeding up the analysis.

*

## Extract button

The tool asks one to specify things like whether selections are drawn "M-line-to-M-line"; for users that are not experts in muscle morphology this is not understandable. It would be great to find more generally applicable formulations. *

We agree that this muscle-oriented vocabulary can make the use of PatternJ confusing. We have now corrected the user interface to provide both general and muscle-specific vocabulary ("center-to-center or edge-to-edge (M-line-to-M-line or Z-disc-to-Z-disc)").*

## Manual selection accuracy

The 1st step of the analysis is always to start from a user hand-drawn profile across intensity patterns in the image. However, this step can cause inaccuracy that varies with the shape and curve of the line profile drawn. If not strictly perpendicular to for example the M line patterns, the distance between intensity peaks will be different. This will be more problematic when dealing with non-straight and parallelly poised features in the image. If the structure is bended with a curve, the line drawn over it also needs to reproduce this curve, to precisely capture the intensity pattern. I found this limits the reproducibility and easy-usability of the software.*

We understand the concern of the reviewer. On curved selections this will be an issue that is difficult to solve, especially on "S" curved or more complex selections. The user will have to be very careful in these situations. On non-curved samples, the issue may be concerning at first sight, but the errors go with the inverse of cosine and are therefore rather low. For example, if the user creates a selection off by 5 degrees, which is visually obvious, lengths will be affected by an increase of only 0.38%. The point raised by the reviewer is important to discuss, and we therefore added a paragraph to comment on the choice of selection (lines 94-98) and a supplementary figure to help make it clear (Figure 1 - figure supplement 1).*

### Reproducibility

Since the line profile drawn on the image is the first step and very essential to the entire process, it should be considered to save together with the analysis result. For example, as ImageJ ROI or ROIset files that can be re-imported, correctly positioned, and visualized in the measured images. This would greatly improve the reproducibility of the proposed workflow. In the manuscript, only the extracted features are being saved (because the save button is also just asking for a folder containing images, so I cannot verify its functionality). *

We agree that this is a very useful and important feature. We have added ROI automatic saving. Additionally, we now provide a simplified import function of all ROIs generated with PatternJ and the automated extraction and analysis of the list of ROIs. This can be done from ROIs generated previously in PatternJ or with ROIs generated from other ImageJ/Fiji algorithms. These new features are described in the manuscript in lines 120-121 and 130-132.

*

## ? button

It would be great if that button would open up some usage instructions.

*

We agree with the reviewer that the "?" button can be used in a better way. We have replaced this button with a Help menu, including a simple tutorial showing a series of images detailing the steps to follow by the user, a link to the user website, and a link to our video tutorial.

* ## Easy improvement of workflow

I would suggest a reasonable expansion of the current workflow, by fitting and displaying 2D lines to the band or line structure in the image, that form the "patterns" the author aims to address. Thus, it extracts geometry models from the image, and the inter-line distance, and even the curve formed by these sets of lines can be further analyzed and studied. These fitted 2D lines can be also well integrated into ImageJ as Line ROI, and thus be saved, imported back, and checked or being further modified. I think this can largely increase the usefulness and reproducibility of the software.

*

We hope that we understood this comment correctly. We had sent a clarification request to the editor, but unfortunately did not receive an answer within the requested 4 weeks of this revision. We understood the following: instead of using our 1D approach, in which we extract positions from a profile, the reviewer suggests extracting the positions of features not as a single point, but as a series of coordinates defining its shape. If this is the case, this is a major modification of the tool that is beyond the scope of PatternJ. We believe that keeping our tool simple, makes it robust. This is the major strength of PatternJ. Local fitting will not use line average for instance, which would make the tool less reliable.

* # Manuscript

We recommend considering the following suggestions for improving the manuscript. Abstract: The abstract suggests that general patterns can be quantified, however the actual tool quantifies specific subtypes of one-dimensional patterns. We recommend adapting the abstract accordingly.

*

We modified the abstract to make this point clearer.

* Line 58: Gray-level co-occurrence matrix (GLCM) based feature extraction and analysis approach is not mentioned nor compared. At least there's a relatively recent study on Sarcomeres structure based on GLCM feature extraction: https://github.com/steinjm/SotaTool with publication: *https://doi.org/10.1002/cpz1.462

• *

We thank the reviewer for making us aware of this publication. We cite it now and have added it to our comparison of available approaches.

* Line 75: "...these simple geometrical features will address most quantitative needs..." We feel that this may be an overstatement, e.g. we can imagine that there should be many relevant two-dimensional patterns in biology?!*

We have modified this sentence to avoid potential confusion (lines 76-77).

• *

• Line 83: "After a straightforward installation by the user, ...". We think it would be convenient to add the installation steps at this place into the manuscript. *

__This sentence is now modified. We now mention how to install the toolset and we provide the link to the toolset website, if further information is needed (lines 86-88). __On the website, we provide a full video tutorial and a user manual.

* Line 87: "Multicolor images will give a graph with one profile per color." The 'Multicolor images' here should be more precisely stated as "multi-channel" images. Multi-color images could be confused with RGB images which will be treated as 8-bit gray value (type conversion first) images by profile plot in ImageJ. *

We agree with the reviewer that this could create some confusion. We modified "multicolor" to "multi-channel".

* Line 92: "...such as individual bands, blocks, or sarcomeric actin...". While bands and blocks are generic pattern terms, the biological term "sarcomeric actin" does not seem to fit in this list. Could a more generic wording be found, such as "block with spike"? *

We agree with the reviewer that "sarcomeric actin" alone will not be clear to all readers. We modified the text to "block with a central band, as often observed in the muscle field for sarcomeric actin" (lines 103-104). The toolset was modified accordingly.

* Line 95: "the algorithm defines one pattern by having the features of highest intensity in its centre". Could this be rephrased? We did not understand what that exactly means.*

We agree with the reviewer that this was not clear. We rewrote this paragraph (lines 101-114) and provided a supplementary figure to illustrate these definitions (Figure 1 - figure supplement 2).

* Line 124 - 147: This part the only description of the algorithm behind the feature extraction and analysis, but not clearly stated. Many details are missing or assumed known by the reader. For example, how it achieved sub-pixel resolution results is not clear. One can only assume that by fitting Gaussian to the band, the center position (peak) thus can be calculated from continuous curves other than pixels. *

Note that the two sentences introducing this description are "Automated feature extraction is the core of the tool. The algorithm takes multiple steps to achieve this (Fig. S2):". We were hoping this statement was clear, but the reviewer may refer to something else. We agree that the description of some of the details of the steps was too quick. We have now expanded the description where needed.

* Line 407: We think the availability of both the tool and the code could be improved. For Fiji tools it is common practice to create an Update Site and to make the code available on GitHub. In addition, downloading the example file (https://drive.google.com/file/d/1eMazyQJlisWPwmozvyb8VPVbfAgaH7Hz/view?usp=drive_link) required a Google login and access request, which is not very convenient; in fact, we asked for access but it was denied. It would be important for the download to be easier, e.g. from GitHub or Zenodo.

*

We are sorry for issues encountered when downloading the tool and additional material. We thank the reviewer for pointing out these issues that limited the accessibility of our tool. We simplified the downloading procedure on the website, which does not go through the google drive interface nor requires a google account. Additionally, for the coder community the code, user manual and examples are now available from GitHub at github.com/PierreMangeol/PatternJ, and are provided as supplementary material with the manuscript. To our knowledge, update sites work for plugins but not for macro toolsets. Having experience sharing our codes with non-specialists, a classical website with a tutorial video is more accessible than more coder-oriented websites, which deter many users.

* Reviewer #2 (Significance (Required)):

The strength of this study is that a tool for the analysis of one-dimensional repeated patterns occurring in muscle fibres is made available in the accessible open-source platform ImageJ/Fiji. In the introduction to the article the authors provide an extensive review of comparable existing tools. Their new tool fills a gap in terms of providing an easy-to-use software for users without computational skills that enables the analysis of muscle sarcomere patterns. We feel that if the below mentioned limitations could be addressed the tool could indeed be valuable to life scientists interested in muscle patterning without computational skills.

In our view there are a few limitations, including the accessibility of example data and tutorials at sites.google.com/view/patternj, which we had trouble to access. In addition, we think that the workflow in Fiji, which currently requires pressing several buttons in the correct order, could be further simplified and streamlined by adopting some "wizard" approach, where the user is guided through the steps.

*As answered above, the links on the PatternJ website are now corrected. Regarding the workflow, we now provide a Help menu with:

1. __a basic set of instructions to use the tool, __
2. a direct link to the tutorial video in the PatternJ toolset
3. a direct link to the website on which both the tutorial video and a detailed user manual can be found. We hope this addresses the issues raised by this reviewer.

*Another limitation is the reproducibility of the analysis; here we recommend enabling IJ Macro recording as well as saving of the drawn line ROIs. For more detailed suggestions for improvements please see the above sections of our review. *

We agree that saving ROIs is very useful. It is now implemented in PatternJ.

We are not sure what this reviewer means by "enabling IJ Macro recording". The ImageJ Macro Recorder is indeed very useful, but to our knowledge, it is limited to built-in functions. Our code is open and we hope this will be sufficient for advanced users to modify the code and make it fit their needs.*

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

Summary In this manuscript, the authors present a new toolset for the analysis of repetitive patterns in biological images named PatternJ. One of the main advantages of this new tool over existing ones is that it is simple to install and run and does not require any coding skills whatsoever, since it runs on the ImageJ GUI. Another advantage is that it does not only provide the mean length of the pattern unit but also the subpixel localization of each unit and the distributions of lengths and that it does not require GPU processing to run, unlike other existing tools. The major disadvantage of the PatternJ is that it requires heavy, although very simple, user input in both the selection of the region to be analyzed and in the analysis steps. Another limitation is that, at least in its current version, PatternJ is not suitable for time-lapse imaging. The authors clearly explain the algorithm used by the tool to find the localization of pattern features and they thoroughly test the limits of their tool in conditions of varying SNR, periodicity and band intensity. Finally, they also show the performance of PatternJ across several biological models such as different kinds of muscle cells, neurons and fish embryonic somites, as well as different imaging modalities such as brightfield, fluorescence confocal microscopy, STORM and even electron microscopy.

This manuscript is clearly written, and both the section and the figures are well organized and tell a cohesive story. By testing PatternJ, I can attest to its ease of installation and use. Overall, I consider that PatternJ is a useful tool for the analysis of patterned microscopy images and this article is fit for publication. However, i do have some minor suggestions and questions that I would like the authors to address, as I consider they could improve this manuscript and the tool:

*We are grateful to this reviewer for this very positive assessment of PatternJ and of our manuscript.

* Minor Suggestions: In the methodology section is missing a more detailed description about how the metric plotted was obtained: as normalized intensity or precision in pixels. *

We agree with the reviewer that a more detailed description of the metric plotted was missing. We added this information in the method part and added information in the Figure captions where more details could help to clarify the value displayed.

* The validation is based mostly on the SNR and patterns. They should include a dataset of real data to validate the algorithm in three of the standard patterns tested. *

We validated our tool using computer-generated images, in which we know with certainty the localization of patterns. This allowed us to automatically analyze 30 000 images, and with varying settings, we sometimes analyzed 10 times the same image, leading to about 150 000 selections analyzed. From these analyses, we can provide with confidence an unbiased assessment of the tool precision and the tool capacity to extract patterns. We already provided examples of various biological data images in Figures 4-6, showing all possible features that can be extracted with PatternJ. In these examples, we can claim by eye that PatternJ extracts patterns efficiently, but we cannot know how precise these extractions are because of the nature of biological data: "real" positions of features are unknown in biological data. Such validation will be limited to assessing whether a pattern was found or not, which we believe we already provided with the examples in Figures 4-6.

* The video tutorial available in the PatternJ website is very useful, maybe it would be worth it to include it as supplemental material for this manuscript, if the journal allows it. *

As the video tutorial may have been missed by other reviewers, we agree it is important to make it more prominent to users. We have now added a Help menu in the toolset that opens the tutorial video. Having the video as supplementary material could indeed be a useful addition if the size of the video is compatible with the journal limits.

* An example image is provided to test the macro. However, it would be useful to provide further example images for each of the three possible standard patterns suggested: Block, actin sarcomere or individual band.*

We agree this can help users. We now provide another multi-channel example image on the PatternJ website including blocks and a pattern made of a linear intensity gradient that can be extracted with our simpler "single pattern" algorithm, which were missing in the first example. Additionally, we provide an example to be used with our new time-lapse analysis.

* Access to both the manual and the sample images in the PatternJ website should be made publicly available. Right now they both sit in a private Drive account. *

As mentioned above, we apologize for access issues that occurred during the review process. These files can now be downloaded directly on the website without any sort of authentication. Additionally, these files are now also available on GitHub.

* Some common errors are not properly handled by the macro and could be confusing for the user: When there is no selection and one tries to run a Check or Extraction: "Selection required in line 307 (called from line 14). profile=getProfile( ;". A simple "a line selection is required" message would be useful there. When "band" or "block" is selected for a channel in the "Set parameters" window, yet a 0 value is entered into the corresponding "Number of bands or blocks" section, one gets this error when trying to Extract: "Empty array in line 842 (called from line 113). if ( ( subloc . length == 1 ) & ( subloc [ 0 == 0) ) {". This error is not too rare, since the "Number of bands or blocks" section is populated with a 0 after choosing "sarcomeric actin" (after accepting the settings) and stays that way when one changes back to "blocks" or "bands".*

We thank the reviewer for pointing out these bugs. These bugs are now corrected in the revised version.

* The fact that every time one clicks on the most used buttons, the getDirectory window appears is not only quite annoying but also, ultimately a waste of time. Isn't it possible to choose the directory in which to store the files only once, from the "Set parameters" window?*

We have now found a solution to avoid this step. The user is only prompted to provide the image folder when pressing the "Set parameter" button. We kept the prompt for directory only when the user selects the time-lapse analysis or the analysis of multiple ROIs. The main reason is that it is very easy for the analysis to end up in the wrong folder otherwise.

* The authors state that the outputs of the workflow are "user friendly text files". However, some of them lack descriptive headers (like the localisations and profiles) or even file names (like colors.txt). If there is something lacking in the manuscript, it is a brief description of all the output files generated during the workflow.*

PatternJ generates multiple files, several of which are internal to the toolset. They are needed to keep track of which analyses were done, and which colors were used in the images, amongst others. From the user part, only the files obtained after the analysis All_localizations.channel_X.txt and sarcomere_lengths.txt are useful. To improve the user experience, we now moved all internal files to a folder named "internal", which we think will clarify which outputs are useful for further analysis, and which ones are not. We thank the reviewer for raising this point and we now mention it in our Tutorial.

I don't really see the point in saving the localizations from the "Extraction" step, they are even named "temp".

We thank the reviewer for this comment, this was indeed not necessary. We modified PatternJ to delete these files after they are used.

* In the same line, I DO see the point of saving the profiles and localizations from the "Extract & Save" step, but I think they should be deleted during the "Analysis" step, since all their information is then grouped in a single file, with descriptive headers. This deleting could be optional and set in the "Set parameters" window.*

We understand the point raised by the reviewer. However, the analysis depends on the reference channel picked, which is asked for when starting an analysis, and can be augmented with additional selections. If a user chooses to modify the reference channel or to add a new profile to the analysis, deleting all these files would mean that the user will have to start over again, which we believe will create frustration. An optional deletion at the analysis step is simple to implement, but it could create problems for users who do not understand what it means practically.

* Moreover, I think it would be useful to also save the linear roi used for the "Extract & Save" step, and eventually combine them during the "Analysis step" into a single roi set file so that future re-analysis could be made on the same regions. This could be an optional feature set from the "Set parameters" window. *

We agree with the reviewer that saving ROIs is very useful. ROIs are now saved into a single file each time the user extracts and saves positions from a selection. Additionally, the user can re-use previous ROIs and analyze an image or image series in a single step.

* In the "PatternJ workflow" section of the manuscript, the authors state that after the "Extract & Save" step "(...) steps 1, 2, 4, and 5 can be repeated on other selections (...)". However, technically, only steps 1 and 5 are really necessary (alternatively 1, 4 and 5 if the user is unsure of the quality of the patterning). If a user follows this to the letter, I think it can lead to wasted time.

*

We agree with the reviewer and have corrected the manuscript accordingly (line 119-120).

• *

*I believe that the "Version Information" button, although important, has potential to be more useful if used as a "Help" button for the toolset. There could be links to useful sources like the manuscript or the PatternJ website but also some tips like "whenever possible, use a higher linewidth for your line selection" *

We agree with the reviewer as pointed out in our previous answers to the other reviewers. This button is now replaced by a Help menu, including a simple tutorial in a series of images detailing the steps to follow, a link to the user website, and a link to our video tutorial.

* It would be interesting to mention to what extent does the orientation of the line selection in relation to the patterned structure (i.e. perfectly parallel vs more diagonal) affect pattern length variability?*

As answered to reviewer 1, we understand this concern, which needs to be clarified for readers. The issue may be concerning at first sight, but the errors grow only with the inverse of cosine and are therefore rather low. For example, if the user creates a selection off by 3 degrees, which is visually obvious, lengths will be affected by an increase of only 0.14%. The point raised by the reviewer is important to discuss, and we therefore have added a comment on the choice of selection (lines 94-98) as well as a supplementary figure (Figure 1 - figure supplement 1).

* When "the algorithm uses the peak of highest intensity as a starting point and then searches for peak intensity values one spatial period away on each side of this starting point" (line 133-135), does that search have a range? If so, what is the range? *

We agree that this information is useful to share with the reader. The range is one pattern size. We have modified the sentence to clarify the range of search used and the resulting limits in aperiodicity (now lines 176-181).

* Line 144 states that the parameters of the fit are saved and given to the user, yet I could not find such information in the outputs. *

The parameters of the fits are saved for blocks. We have now clarified this point by modifying the manuscript (lines 186-198) and modifying Figure 1 - figure supplement 5. We realized we made an error in the description of how edges of "block with middle band" are extracted. This is now corrected.

* In line 286, authors finish by saying "More complex patterns from electron microscopy images may also be used with PatternJ.". Since this statement is not backed by evidence in the manuscript, I suggest deleting it (or at the very least, providing some examples of what more complex patterns the authors refer to). *

This sentence is now deleted.

* In the TEM image of the fly wing muscle in fig. 4 there is a subtle but clearly visible white stripe pattern in the original image. Since that pattern consists of 'dips', rather than 'peaks' in the profile of the inverted image, they do not get analyzed. I think it is worth mentioning that if the image of interest contains both "bright" and "dark" patterns, then the analysis should be performed in both the original and the inverted images because the nature of the algorithm does not allow it to detect "dark" patterns. *

We agree with the reviewer's comment. We now mention this point in lines 337-339.

* In line 283, the authors mention using background correction. They should explicit what method of background correction they used. If they used ImageJ's "subtract background' tool, then specify the radius.*

We now describe this step in the method section.

*

Reviewer #3 (Significance (Required)):

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field. Being a software paper, the advance proposed by the authors is technical in nature. The novelty and significance of this tool is that it offers quick and simple pattern analysis at the single unit level to a broad audience, since it runs on the ImageJ GUI and does not require any programming knowledge. Moreover, all the modules and steps are well described in the paper, which allows easy going through the analysis.
• Place the work in the context of the existing literature (provide references, where appropriate). The authors themselves provide a good and thorough comparison of their tool with other existing ones, both in terms of ease of use and on the type of information extracted by each method. While PatternJ is not necessarily superior in all aspects, it succeeds at providing precise single pattern unit measurements in a user-friendly manner.
• State what audience might be interested in and influenced by the reported findings. Most researchers working with microscopy images of muscle cells or fibers or any other patterned sample and interested in analyzing changes in that pattern in response to perturbations, time, development, etc. could use this tool to obtain useful, and otherwise laborious, information. *

We thank the reviewer for these enthusiastic comments about how straightforward for biologists it is to use PatternJ and its broad applicability in the bio community.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Summary

In this manuscript, the authors present a new toolset for the analysis of repetitive patterns in biological images named PatternJ. One of the main advantages of this new tool over existing ones is that it is simple to install and run and does not require any coding skills whatsoever, since it runs on the ImageJ GUI. Another advantage is that it does not only provide the mean length of the pattern unit but also the subpixel localization of each unit and the distributions of lengths and that it does not require GPU processing to run, unlike other existing tools. The major disadvantage of the PatternJ is that it requires heavy, although very simple, user input in both the selection of the region to be analyzed and in the analysis steps. Another limitation is that, at least in its current version, PatternJ is not suitable for time-lapse imaging.

The authors clearly explain the algorithm used by the tool to find the localization of pattern features and they thoroughly test the limits of their tool in conditions of varying SNR, periodicity and band intensity. Finally, they also show the performance of PatternJ across several biological models such as different kinds of muscle cells, neurons and fish embryonic somites, as well as different imaging modalities such as brightfield, fluorescence confocal microscopy, STORM and even electron microscopy.

This manuscript is clearly written, and both the section and the figures are well organized and tell a cohesive story. By testing PatternJ, I can attest to its ease of installation and use. Overall, I consider that PatternJ is a useful tool for the analysis of patterned microscopy images and this article is fit for publication. However, i do have some minor suggestions and questions that I would like the authors to address, as I consider they could improve this manuscript and the tool:

Minor Suggestions:

In the methodology section is missing a more detailed description about how the metric plotted was obtained: as normalized intensity or precision in pixels. The validation is based mostly on the SNR and patterns. They should include a dataset of real data to validate the algorithm in three of the standard patterns tested. The video tutorial available in the PatternJ website is very useful, maybe it would be worth it to include it as supplemental material for this manuscript, if the journal allows it. An example image is provided to test the macro. However, it would be useful to provide further example images for each of the three possible standard patterns suggested: Block, actin sarcomere or individual band. Access to both the manual and the sample images in the PatternJ website should be made publicly available. Right now they both sit in a private Drive account. Some common errors are not properly handled by the macro and could be confusing for the user: When there is no selection and one tries to run a Check or Extraction: "Selection required in line 307 (called from line 14). profile=getProfile( <)>;". A simple "a line selection is required" message would be useful there. When "band" or "block" is selected for a channel in the "Set parameters" window, yet a 0 value is entered into the corresponding "Number of bands or blocks" section, one gets this error when trying to Extract: "Empty array in line 842 (called from line 113). if ( ( subloc . length == 1 ) & ( subloc [ 0 <]> == 0) ) {". This error is not too rare, since the "Number of bands or blocks" section is populated with a 0 after choosing "sarcomeric actin" (after accepting the settings) and stays that way when one changes back to "blocks" or "bands".<br /> The fact that every time one clicks on the most used buttons, the getDirectory window appears is not only quite annoying but also, ultimately a waste of time. Isn't it possible to choose the directory in which to store the files only once, from the "Set parameters" window? The authors state that the outputs of the workflow are "user friendly text files". However, some of them lack descriptive headers (like the localisations and profiles) or even file names (like colors.txt). If there is something lacking in the manuscript, it is a brief description of all the output files generated during the workflow. I don't really see the point in saving the localizations from the "Extraction" step, they are even named "temp". In the same line, I DO see the point of saving the profiles and localizations from the "Extract & Save" step, but I think they should be deleted during the "Analysis" step, since all their information is then grouped in a single file, with descriptive headers. This deleting could be optional and set in the "Set parameters" window. Moreover, I think it would be useful to also save the linear roi used for the "Extract & Save" step, and eventually combine them during the "Analysis step" into a single roi set file so that future re-analysis could be made on the same regions. This could be an optional feature set from the "Set parameters" window. In the "PatternJ workflow" section of the manuscript, the authors state that after the "Extract & Save" step "(...) steps 1, 2, 4, and 5 can be repeated on other selections (...)". However, technically, only steps 1 and 5 are really necessary (alternatively 1, 4 and 5 if the user is unsure of the quality of the patterning). If a user follows this to the letter, I think it can lead to wasted time. I believe that the "Version Information" button, although important, has potential to be more useful if used as a "Help" button for the toolset. There could be links to useful sources like the manuscript or the PatternJ website but also some tips like "whenever possible, use a higher linewidth for your line selection" It would be interesting to mention to what extent does the orientation of the line selection in relation to the patterned structure (i.e. perfectly parallel vs more diagonal) affect pattern length variability? When "the algorithm uses the peak of highest intensity as a starting point and then searches for peak intensity values one spatial period away on each side of this starting point" (line 133-135), does that search have a range? If so, what is the range? Line 144 states that the parameters of the fit are saved and given to the user, yet I could not find such information in the outputs. In line 286, authors finish by saying "More complex patterns from electron microscopy images may also be used with PatternJ.". Since this statement is not backed by evidence in the manuscript, I suggest deleting it (or at the very least, providing some examples of what more complex patterns the authors refer to). In the TEM image of the fly wing muscle in fig. 4 there is a subtle but clearly visible white stripe pattern in the original image. Since that pattern consists of 'dips', rather than 'peaks' in the profile of the inverted image, they do not get analyzed. I think it is worth mentioning that if the image of interest contains both "bright" and "dark" patterns, then the analysis should be performed in both the original and the inverted images because the nature of the algorithm does not allow it to detect "dark" patterns. In line 283, the authors mention using background correction. They should explicit what method of background correction they used. If they used ImageJ's "subtract background' tool, then specify the radius.

Significance

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field. Being a software paper, the advance proposed by the authors is technical in nature. The novelty and significance of this tool is that it offers quick and simple pattern analysis at the single unit level to a broad audience, since it runs on the ImageJ GUI and does not require any programming knowledge. Moreover, all the modules and steps are well described in the paper, which allows easy going through the analysis.
• Place the work in the context of the existing literature (provide references, where appropriate). The authors themselves provide a good and thorough comparison of their tool with other existing ones, both in terms of ease of use and on the type of information extracted by each method. While PatternJ is not necessarily superior in all aspects, it succeeds at providing precise single pattern unit measurements in a user-friendly manner.
• State what audience might be interested in and influenced by the reported findings. Most researchers working with microscopy images of muscle cells or fibers or any other patterned sample and interested in analyzing changes in that pattern in response to perturbations, time, development, etc. could use this tool to obtain useful, and otherwise laborious, information.
• Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. I am a biologist with extensive experience in confocal microscopy and image analysis using classical machine vision tools, particularly using ImageJ and CellProfiler.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

Summary

The authors present an ImageJ Macro GUI tool set for the quantification of one-dimensional repeated patterns that are commonly occurring in microscopy images of muscles.

Major comments

In our view the article and also software could be improved in terms of defining the scope of its applicability and user-ship. In many parts the article and software suggest that general biological patterns can be analysed, but then in other parts very specific muscle actin wordings are used. We are pointing this out in the "Minor comments" sections below. We feel that the authors could improve their work by making a clear choice here. One option would be to clearly limit the scope of the tool to the analysis of actin structures in muscles. In this case we would recommend to also rename the tool, e.g. MusclePatternJ. The other option would be to make the tool about the generic analysis of one-dimensional patterns, maybe calling the tool LinePatternJ. In the latter case we would recommend to remove all actin specific wordings from the macro tool set and also the article should be in parts slightly re-written.

Minor/detailed comments

Software

We recommend considering the following suggestions for improving the software.

File and folder selection dialogs

In general, clicking on many of the buttons just opens up a file-browser dialog without any further information. For novel users it is not clear what the tool expects one to select here. It would be very good if the software could be rewritten such that there are always clear instructions displayed about which file or folder one should open for the different buttons.

Extract button

The tool asks one to specify things like whether selections are drawn "M-line-to-M-line"; for users that are not experts in muscle morphology this is not understandable. It would be great to find more generally applicable formulations.

Manual selection accuracy

The 1st step of the analysis is always to start from a user hand-drawn profile across intensity patterns in the image. However, this step can cause inaccuracy that varies with the shape and curve of the line profile drawn. If not strictly perpendicular to for example the M line patterns, the distance between intensity peaks will be different. This will be more problematic when dealing with non-straight and parallelly poised features in the image. If the structure is bended with a curve, the line drawn over it also needs to reproduce this curve, to precisely capture the intensity pattern. I found this limits the reproducibility and easy-usability of the software.

Reproducibility

Since the line profile drawn on the image is the first step and very essential to the entire process, it should be considered to save together with the analysis result. For example, as ImageJ ROI or ROIset files that can be re-imported, correctly positioned, and visualized in the measured images. This would greatly improve the reproducibility of the proposed workflow. In the manuscript, only the extracted features are being saved (because the save button is also just asking for a folder containing images, so I cannot verify its functionality).

? button

It would be great if that button would open up some usage instructions.

Easy improvement of workflow

I would suggest a reasonable expansion of the current workflow, by fitting and displaying 2D lines to the band or line structure in the image, that form the "patterns" the author aims to address. Thus, it extracts geometry models from the image, and the inter-line distance, and even the curve formed by these sets of lines can be further analyzed and studied. These fitted 2D lines can be also well integrated into ImageJ as Line ROI, and thus be saved, imported back, and checked or being further modified. I think this can largely increase the usefulness and reproducibility of the software.

Manuscript

We recommend considering the following suggestions for improving the manuscript. Abstract: The abstract suggests that general patterns can be quantified, however the actual tool quantifies specific subtypes of one-dimensional patterns. We recommend adapting the abstract accordingly.

Line 58: Gray-level co-occurrence matrix (GLCM) based feature extraction and analysis approach is not mentioned nor compared. At least there's a relatively recent study on Sarcomeres structure based on GLCM feature extraction: https://github.com/steinjm/SotaTool with publication: https://doi.org/10.1002/cpz1.462

Line 75: "...these simple geometrical features will address most quantitative needs..." We feel that this may be an overstatement, e.g. we can imagine that there should be many relevant two-dimensional patterns in biology?!

Line 83: "After a straightforward installation by the user, ...". We think it would be convenient to add the installation steps at this place into the manuscript.

Line 87: "Multicolor images will give a graph with one profile per color." The 'Multicolor images' here should be more precisely stated as "multi-channel" images. Multi-color images could be confused with RGB images which will be treated as 8-bit gray value (type conversion first) images by profile plot in ImageJ.

Line 92: "...such as individual bands, blocks, or sarcomeric actin...". While bands and blocks are generic pattern terms, the biological term "sarcomeric actin" does not seem to fit in this list. Could a more generic wording be found, such as "block with spike"?

Line 95: "the algorithm defines one pattern by having the features of highest intensity in its centre". Could this be rephrased? We did not understand what that exactly means.

Line 124 - 147: This part the only description of the algorithm behind the feature extraction and analysis, but not clearly stated. Many details are missing or assumed known by the reader. For example, how it achieved sub-pixel resolution results is not clear. One can only assume that by fitting Gaussian to the band, the center position (peak) thus can be calculated from continuous curves other than pixels.

Line 407: We think the availability of both the tool and the code could be improved. For Fiji tools it is common practice to create an Update Site and to make the code available on GitHub. In addition, downloading the example file (https://drive.google.com/file/d/1eMazyQJlisWPwmozvyb8VPVbfAgaH7Hz/view?usp=drive_link) required a Google login and access request, which is not very convenient; in fact, we asked for access but it was denied. It would be important for the download to be easier, e.g. from GitHub or Zenodo.

Significance

The strength of this study is that a tool for the analysis of one-dimensional repeated patterns occurring in muscle fibres is made available in the accessible open-source platform ImageJ/Fiji. In the introduction to the article the authors provide an extensive review of comparable existing tools. Their new tool fills a gap in terms of providing an easy-to-use software for users without computational skills that enables the analysis of muscle sarcomere patterns. We feel that if the below mentioned limitations could be addressed the tool could indeed be valuable to life scientists interested in muscle patterning without computational skills.

In our view there are a few limitations, including the accessibility of example data and tutorials at sites.google.com/view/patternj, which we had trouble to access. In addition, we think that the workflow in Fiji, which currently requires pressing several buttons in the correct order, could be further simplified and streamlined by adopting some "wizard" approach, where the user is guided through the steps. Another limitation is the reproducibility of the analysis; here we recommend enabling IJ Macro recording as well as saving of the drawn line ROIs. For more detailed suggestions for improvements please see the above sections of our review.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

I have trialled the package on my lab's data and it works as advertised. It was straightforward to use and did not require any special training. I am confident this is a tool that will be approachable even to users with limited computational experience. The use of artificial data to validate the approach - and to provide clear limits on applicability - is particularly helpful.

The main limitation of the tool is that it requires the user to manually select regions. This somewhat limits the generalisability and is also more subjective - users can easily choose "nice" regions that better match with their hypothesis, rather than quantifying the data in an unbiased manner. However, given the inherent challenges in quantifying biological data, such problems are not easily circumventable.

I have some comments to clarify the manuscript:

1. A "straightforward installation" is mentioned. Given this is a Method paper, the means of installation should be clearly laid out.
2. It would be helpful if there was an option to generate an output with the regions analysed (i.e., a JPG image with the data and the drawn line(s) on top). There are two reasons for this: i) A major problem with user-driven quantification is accidental double counting of regions (e.g., a user quantifies a part of an image and then later quantifies the same region). ii) Allows other users to independently verify measurements at a later time.
3. Related to the above point, it is highlighted that each time point would need to be analysed separately (line 361-362). It seems like it should be relatively straightforward to allow a function where the analysis line can be mapped onto the next time point. The user could then adjust slightly for changes in position, but still be starting from near the previous timepoint. Given how prevalent timelapse imaging is, this seems like (or something similar) a clear benefit to add to the software.
4. Line 134-135. The level of accuracy of the searching should be clarified here. This is discussed later in the manuscript, but it would be helpful to give readers an idea at this point what level of tolerance the software has to noise and aperiodicity.

Referees cross-commenting

I think the other reviewer comments are very pertinent. The authors have a fair bit to do, but they are reasonable requests. So, they should be encouraged to do the revisions fully so that the final software tool is as useful as possible.

Significance

Developing software tools for quantifying biological data that are approachable for a wide range of users remains a longstanding challenge. This challenge is due to: (1) the inherent problem of variability in biological systems; (2) the complexity of defining clearly quantifiable measurables; and (3) the broad spread of computational skills amongst likely users of such software.

In this work, Blin et al., develop a simple plugin for ImageJ designed to quickly and easily quantify regular repeating units within biological systems - e.g., muscle fibre structure. They clearly and fairly discuss existing tools, with their pros and cons. The motivation for PatternJ is properly justified (which is sadly not always the case with such software tools).

Overall, the paper is well written and accessible. The tool has limitations but it is clearly useful and easy to use. Therefore, this work is publishable with only minor corrections.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

Response to Reviewer 1

---

__Glycosaminoglycan (GAG)-binding proteins regulating essential processes such as cell growth and migration are essential for cell homeostasis. It is reported that the GAG has the ability to bind to Herpin sulfate. As both GAGs and the LPS lipid A disaccharide core of gram-negative bacteria contain negatively charged disaccharide units, the researchers proposed that heparin-binding peptides might have cryptic antimicrobial peptide motifs. To prove the hypothesis, they have synthesized five candidates [HBP1-5], which showed a binding affinity towards heparin and LPS binding. By using various methods, they showed that these molecules have antimicrobial activity. The key finding in this study is the finding of the CPC domain, where C is a cationic amino acid and P is a polar amino acid. __

Major comments

1. __ Even though the Authors propose here that CPC' clip motif is needed for antimicrobial activity. However, various studies have demonstrated that the mere presence of cationic amino or hydrophobic amino acids does not give the activity, the location of these amino acids at the strategic position is critically needed. The major issue in this work, the authors have not presented, whether there was a single CPC motif or multiple in the 5 peptides they have synthesized. Further, they need to demonstrate how are the charged and hydrophobic amino acids distributed in the peptides. these things will clearly explain the difference in the activity as well spectrum of the peptides. The authors should make an extra figure or add information highlighting this unique characteristic for better understanding to the reader.__

We thank the reviewer for his/her comments and suggestions. We concur that the distribution of amino acids is crucial for the antimicrobial activity of the peptides and their ability to bind heparin. We also agree with the suggestion of illustrating the location of the CPC' motifs of HBPs in the context of the parental proteins and have accordingly done so in the new Supplementary Figure 1. In all cases, only one CPC' motif was identified in the antimicrobial region, as highlighted in the figure, and the inter-residue distances measured are consistent with the CPC' motif definition. Thus, we demonstrate that a CPC' motif exists in all five HBPs, which explains how they recognize and bind heparin.

To illustrate the distribution of charged and hydrophobic amino acids in HBPs, we have also prepared new Supplementary Figure 2, displaying electrostatic potentials in the predicted HBP structures, and showing how the distribution of charged residues creates hydrophobic and cationic patches on the surface of the peptides. Our analysis reveals cationic patches to be surrounded by hydrophobic residues, which may explain the ability of the peptides to disrupt membranes and exert antimicrobial activity.

__ It is strange to observe that there are quite a number of reports showing that the peptides derived from the Herprin binding proteins have antimicrobial activity, but no one has reported their efficacy in the in vivo mouse model. if possible, the authors could add their observations if in vivo studies were done. or as a future line of study.__

We thank the reviewer for his/her comment on the observation of antimicrobial activity in peptides derived from heparin-binding proteins. Indeed, a few such studies have appeared in the literature, some with moderate success [1]. It is possible that a lack of understanding on how to identify heparin-binding regions in proteins and AMPs underlies their relative paucity. In this context, we believe our results will spur further efforts, specifically by providing a rationale on how to identify CPC' motifs hence heparin-binding regions in protein sequences.

Regarding the suggestion of assessing the in vivo efficacy of HBPs, we would agree that it would be helpful for better understanding their potential therapeutic applications. However, we feel that such experiments are beyond the scope of our manuscript, which offers ample, compelling in vitro and in silico evidence of how heparin-binding proteins can be a source of AMPs. We have done this by showing that CPC' motifs embedded in such proteins can be unveiled, accurately defined in structural terms, and experimentally shown to possess antimicrobial activity. Furthermore, we have shown that heparin binding correlates with LPS binding, allowing us to propose a mechanistic explanation for how heparin binding can be related to antimicrobial activity.

Translating these results to animal models is possibly premature at this stage as, from a classical medicinal chemistry perspective, it would require previous structural elaboration in terms of, e.g., optimized serum half-life or serum protein binding, both of which can modulate activity in in vivo studies regardless of heparin affinity or bactericidal activity per se. Ongoing work in our laboratories is focused in these directions and will be reported in due time.

*Referees cross-commenting**

Minor comments

1. __ The presence of Cryptic antimicrobial domain in various heparin-binding proteins like laminin isoforms, von Willebrand factor, vitronectin, protein C inhibitor, matrix glycoproteins thrombospondin, proline arginine-rich end leucine-rich repeat protein and fibronectin, have been reported previous. It is not clear why the authors did not refer to that work. The authors should refer to the works. (same as reviewer 3)__

We were aware of other prior studies on heparin-binding proteins and did indeed cite some of them, though not exhaustively for conciseness' sake. However, as encouraged by reviewers 1 and 3 we have cited the following studies:

Malmström E, Mörgelin M, Malmsten M, Johansson L, Norrby-Teglund A, Shannon O, Schmidtchen A, Meijers JC, Herwald H. Protein C inhibitor--a novel antimicrobial agent. PLoS Pathog. 2009 Dec;5(12):e1000698. doi: 10.1371/journal.ppat.1000698. Epub 2009 Dec 18. PMID: 20019810; PMCID: PMC2788422.

Ishihara, J., Ishihara, A., Fukunaga, K. et al. Laminin heparin-binding peptides bind to several growth factors and enhance diabetic wound healing. Nat Commun 9, 2163 (2018). https://doi.org/10.1038/s41467-018-04525-w

Chillakuri Chandramouli R, Jones Céline and Mardon Helen J(2010), Heparin binding domain in vitronectin is required for oligomerization and thus enhances integrin mediated cell adhesion and spreading, FEBS Letters, 584, doi: 10.1016/j.febslet.2010.06.023

Papareddy P, Kasetty G, Kalle M, Bhongir RK, Mörgelin M, Schmidtchen A, Malmsten M. NLF20: an antimicrobial peptide with therapeutic potential against invasive Pseudomonas aeruginosa infection. J Antimicrob Chemother. 2016 Jan;71(1):170-80. doi: 10.1093/jac/dkv322. Epub 2015 Oct 26. PMID: 26503666.

All the earlier studies related to the antimicrobial activity of the peptides derived from the Heparin-binding protein reported a consensus Cardin and Weintraub motifs i.e, XBBBXXBX or XBBXBX, where X represents hydrophobic or uncharged amino acids, and B represents basic amino acids. However, in this work, the researchers report about the presence of the new CPC motif. So, this is unique and a novelty in the study.

We thank the reviewers for these observations. Indeed, our quest to unveil CPC' motifs in antimicrobial regions of heparin-binding proteins is the key point of our investigation, and what distinguishes it from previous studies on consensus motifs such as XBBBXXBX or XBBXBX. We believe our definition of CPC' motifs in simple, structure-based, and experimentally verifiable terms is not only a significant departure but also a step forward from earlier views, highlighting the importance of a structural perspective in defining heparin-binding regions. In point of fact, we show that our peptides, even without consensus Cardin-Weintraub motifs, bind heparin with high affinity. The presence of the CPC' motif is crucial for such binding, as well as for LPS binding, and the new experiments performed at editor/reviewer's request, where the CPC motif in HBP5 is abolished, with predictable impact, fully support our view, see new section "Insights into the CPC' motif of HBP-5 and its implication on the antibacterial mechanism" and new Table 3 in the revised manuscript.

__ Even though the researchers report on the role of the CPC motif in the antimicrobial activity and binding to the heprin, the authors did not show any data or draw the conclusions related to the CPC domain when it comes to differences in the activity. this is the weakness of the manuscript. (same as reviewer 2)__

We welcome the reviewer's observation. To address it, we made and tested three HBP-5 mutants aimed at showing how alterations in the CPC' motif might influence interaction with heparin and LPS, as well as antimicrobial properties. The first two mutants involved replacing positively charged R10 and R14 residues with glutamine, similar in size and polarity but uncharged. As shown in the new section "Insights into the CPC' motif of HBP-5 and its implication on the antibacterial mechanism" and on the new Table 3 of the revised manuscript, the changes reduced heparin binding, i.e., shorter retention times on affinity chromatography, as well as LPS binding, i.e., a decrease in EC50 in the cadaverine assay (Table 3). The modifications had a lesser impact on antimicrobial activity, most likely due to the low resolution of MIC assays.

In a further step to assess the effect of the CPC' motif on antimicrobial activity, we deleted it in full by replacing residues H9, R10 and R14 of HBP-5 by alanine. As expected, this DCPC' peptide showed a sharp reduction in both heparin and LPS binding (Table 3) and, most importantly, a significant and asymmetric change in antimicrobial activity, with substantial impact on Gram-negatives yet practically no effect on Gram-positives, suggesting that LPS plays a key role in this selective response. Altogether, these observations align with our hypothesis that heparin-binding proteins might exploit their intrinsic affinity for heparin as an opportunity to developing antimicrobial properties by leveraging structural similarities between glycosaminoglycans and LPS.

__ It is strange to observe that there are quite a number of reports showing that the peptides derived from the Herprin (sic) binding proteins have antimicrobial activity, but no one has reported their efficacy in the in vivo mouse model. if possible, the authors could add their observations if in vivo studies were done. or as a future line of study. (Same as reviewer 2)__

We would kindly direct attention to #2 in the response to reviewer 1 above.

__ There are more than 20 different AMP databases or prediction software. however, not all of them are 100 % current, their success rate varies from 30-50% only. It needs to be investigated if adding this search in the hit peptides might increase the success rate of the extra in silico-based AMPs prediction software.__

If we understand the question correctly, the reviewer wonders whether including a CPC' motif predictor would increase the accuracy of AMP search algorithms. In our view, this strategy has two main limitations to be considered: (i) locating a CPC' motif in a peptide sequence typically requires a known 3D structure. Unfortunately, this is not always the case, and for proteins lacking reliable 3D data it can be a challenging and resource-intensive process; (ii) while CPC' motifs may predispose proteins to evolve antimicrobial properties, it is unclear if this is a required feature for all AMPs. Imposing the presence of a CPC' motif may not be applicable to all AMPs, although it might help identifying peptides with specific activity against gram-negative strains.

In summary, while the query of including a CPC' motif search tool in AMP predictors is intriguing and worthy of exploration for its potential bearing on antimicrobial research, it is technically complicated and beyond the scope of our manuscript.

__Reviewer #1 (Significance (Required)): __

__All the earlier studies related to the antimicrobial activity of the peptides derived from the Heparin-binding protein reported a consensus Cardin and Weintraub motifs i.e, XBBBXXBX or XBBXBX, where X represents hydrophobic or uncharged amino acids, and B represents basic amino acids. However, in this work, the researchers report about the presence of the new CPC motif. So this is unique and a novelty in the study. __

Even though the researchers report on the role of the CPC motif in the antimicrobial activity and binding to the heparin, the authors did not show any data or draw conclusions related to the CPC domain when it comes to differences in the activity. This is the weakness of the manuscript.

We would direct reviewer's attention to #1 in the Referee's cross-commenting section above.

---

Response to Reviewer 2

---

This is a very nice paper by the Andreu and Torrent groups that report the antimicrobial and heparin-binding of several encrypted peptides. Overall, this study presents an intriguing exploration into the potential dual functionality of glycosaminoglycan (GAG)-binding proteins, specifically heparin-binding proteins (HBPs), in recognizing lipopolysaccharide (LPS) and exhibiting antimicrobial properties. The findings, particularly the identification and characterization of novel encrypted peptides, such as HBP-5, are promising and contribute to our understanding of the intricate interplay between GAG-binding proteins and immunity. The data provided and methodology are thorough and well described. In sum, this is a very nice work. Please see below my minor comments.

---

Minor comments:

1. __ Fig. 1 legend does not show antimicrobial activity. Please remove from the figure legend title.__

As pointed out by the reviewer, the legend was incorrect and has been corrected accordingly and now reads "Figure 1. Structural and bioinformatics analysis of HBPs".

__ Discussion section: the authors should expand this section a bit to discuss recent work in the encrypted/cryptic peptide area. There are some recent relevant papers published in the past 3 years that should be discussed.__

We agree with the reviewer's suggestion to expand the discussion section to address recent work in the field of encrypted/cryptic peptides. We have carefully reviewed the recent literature and added several references in this topic:

Torres MDT, Melo MCR, Flowers L, Crescenzi O, Notomista E, de la Fuente-Nunez C. Mining for encrypted peptide antibiotics in the human proteome. Nat Biomed Eng. 2022 Jan;6(1):67-75. doi: 10.1038/s41551-021-00801-1. Epub 2021 Nov 4. Erratum in: Nat Biomed Eng. 2022 Dec;6(12):1451. PMID: 34737399.

• *

Santos MFDS, Freitas CS, Verissimo da Costa GC, Pereira PR, Paschoalin VMF. Identification of Antibacterial Peptide Candidates Encrypted in Stress-Related and Metabolic Saccharomyces cerevisiae Proteins. Pharmaceuticals (Basel). 2022 Jan 28;15(2):163. doi: 10.3390/ph15020163. PMID: 35215278; PMCID: PMC8877035.

• *

Boaro A, Ageitos L, Torres MT, Blasco EB, Oztekin S, de la Fuente-Nunez C. Structure-function-guided design of synthetic peptides with anti-infective activity derived from wasp venom. Cell Rep Phys Sci. 2023 Jul 19;4(7):101459. doi: 10.1016/j.xcrp.2023.101459. PMID: 38239869; PMCID: PMC10795512.

__ References provided are a bit outdated and do not accurately reflect the latest in the field (see comment above).__

We thank the reviewer for this comment. Older references were updated as suggested.

__ Gram should be capitalized throughout the text.__

Gram has been capitalized as suggested by the reviewer.

__ Can the authors comment on the potential translatability of HBP-5? Please also comment on the potential advantages of having peptides that 1) bind to heparin; and 2) kill bacteria.__

We appreciate the reviewer's interest in the potential of HBP-5. Indeed, we believe it has promise for clinical applications due to its unique attributes, but further studies, including in vivo experiments and pharmacokinetic assessments, are needed to fully evaluate its potential. The advantages of peptides that bind to heparin and kill bacteria include targeted delivery or localization of therapeutic agents, enhanced efficacy, and minimized off-target effects. HBP-5's ability to perturb outer membrane LPS, a crucial aspect of its antibacterial activity, makes it a promising approach to combat Gram-negative bacterial infections, which are often challenging to treat. By disrupting the outer membrane integrity, HBP-5 may also enhance the susceptibility of Gram-negative bacteria to other antimicrobial agents or host immune responses, underscoring its translational potential for treating bacterial infections.

__ More details on the computational tools and methods used to mine the peptides are needed.__

We have updated the Methods section to provide more details on the computational tools used for defining AMPs. Briefly, from the library of heparin-binding proteins obtained from previous studies [2] and AMP scanning for all these proteins was performed using the AMPA tool. The predicted antibacterial segments were located in the 3D structure of their respective proteins. Then, the CPC' motifs were searched in each segment following the criteria previously reported in [3, 4]. The motif involves two cationic residues (Arg or Lys) and a polar residue (preferentially Asn, Gln, Thr, Tyr or Ser), with fairly conserved distances between the carbons and the side chain center of gravity, defining a clip-like structure where heparin would be lodged. This structural motif is highly conserved and can be found in many proteins with reported heparin binding capacity. Finally, for all these regions, docking with a heparin disaccharide was performed using AutoDock Vina to evaluate the potential binding energy.

---

---

Response to Reviewer 3

---

__Summary: This manuscript has identified and investigated antimicrobial peptides from GAG binding proteins. Authors hypothesized that due to physiochemical similarity between GAG and LPS, fragments of GAG binding proteins might exert antimicrobial activity particularly against G- bacteria. Authors have identified few such AMPs that demonstrate LPS binding and displayed antibacterial activity. They have also solved NMR structure of the potent peptide and mode of action. __

Major comments: AMPs are promising molecules that can serve as lead for the development of therapeutics against MDR bacteria. In particular, currently therapeutic options to treat MDR Gram negative pathogens are limited. The current study is interesting and provides new non-toxic AMPs. Conclusions drawn from the works are largely valid. However, authors should address following comments:

1. __ The design and characterization of the peptide YI12WF is not described. Previous studies had shown design of β-boomerang peptides (Bhattacharjya and coworkers) that target LPS.__

---

We thank the reviewer for this comment. YI12WF (YVLWKRKRFIFI-amide) has been previously reported [4, 5] and shown to bind LPS with high affinity. YI12WF also contains a CPC' motif that, if deleted, reduces heparin binding [4]. References have been added in the text.

__ Mutations or substitution of the key residues peptide 5 might improve the novelty of the work.__

We thank the reviewer for this comment and agree that targeted substitutions in HBP-5 might shed light on the importance of the CPC' motif. As this point was also raised by reviewer 1, we would direct the reviewer's attention to #2 in the *Referees cross-commenting** section above.

__ How these peptides disrupt LPS permeability is not investigated. As LPS is the major target.__

We thank the reviewer for this suggestion and have accordingly evaluated the outer membrane (OM) permeability of the peptides by the 1-N-phenyl-naphthylamine (NPN) assay, a widely used method to assess OM integrity in Gram-negative bacteria. NPN is typically unable to cross the intact outer membrane; however, when the membrane is damaged or disrupted, it can penetrate and interact with lipids and proteins inside the cell, leading to an increase in fluorescence which is directly correlated with the degree of OM permeability and serves as an indicator of membrane damage.

Our results, illustrated in the new Figure 2D, show that all peptides are able to disrupt the OM of Gram-negative bacteria comparably to the LL-37 positive control, except for HBP2. Notably, HBP-5 exhibits the highest activity against OM, consistent with findings elsewhere in the manuscript and altogether confirming the ability of HBPs to bind to and disrupt the LPS structure.

__ Are the D-enantiomers of the peptides active against bacteria?__

We tested the antibacterial activity of the D-enantiomer of HBP5 (dHBP-and 5) and found it to be even higher than that of all-L HBP-5 against both Gram-negative and -positive bacteria, probably due to increased proteolytic stability as found in many AMP studies [6, 7]. As for LPS and heparin affinity, L- and D-HBP-5 behaved similarly (Table R1). As expected, the CD signatures of L- and D-HBP-5 were mirror images (Figure R1). These results suggest that the conformation of the CPC' motif is preserved in dHBP5, in tune with all previous results.

Antibacterial Activity

ID

E. Coli

P. Aeruginosa

A. Baumannii

S. Aureus

E. Faecium

L. monocytognes

HPB-5

0.4

0.8

0.2

6.3

25

1.6

dHBP-5

0.1

0.2

0.2

1.6

0.4

0.2

---

---

Binding Affinity

---

LPS (EC50, µM)

Heparin (% Elution buffer)

HPB-5

0.9 {plus minus} 0.7

98.0

dHBP-5

1.1 {plus minus} 0.8

97.2

Table R1. Antimicrobial activity of HBP-5 and dHBP-5

---

---

---

---

---

---

---

---

Figure R1. CD spectra of HBP-5 (red line) and dHBP-5 (green line) in LPS (left panel) and heparin (right panel).

---

__ 3D structure of peptide 5 is solved in DPC micelle which is a mimic for eukaryotic cells. Authors should attempt to determine structure in LPS as shown in several recent studies with potent AMPs thanatin, MSI etc.__

We appreciate the suggestion and have indeed attempted to obtain NMR spectra of HBP-5 in LPS micelles. However, we've been hindered by peptide precipitation and, despite considerable efforts, have not been able to obtain satisfactory results thus far. In contrast, we have succeeded in obtaining CD spectra of HBP5 in LPS micelles, showing an a-helix conformation similar to the one in SDS micelles, hence suggesting similar conformation in both environments.

Minor comments: There are examples of AMPs derived from human proteins. Authors should highlight such works.

Other studies have been cited according to the reviewers' comments:

Malmström E, Mörgelin M, Malmsten M, Johansson L, Norrby-Teglund A, Shannon O, Schmidtchen A, Meijers JC, Herwald H. Protein C inhibitor--a novel antimicrobial agent. PLoS Pathog. 2009 Dec;5(12):e1000698. doi: 10.1371/journal.ppat.1000698. Epub 2009 Dec 18. PMID: 20019810; PMCID: PMC2788422.

Ishihara, J., Ishihara, A., Fukunaga, K. et al. Laminin heparin-binding peptides bind to several growth factors and enhance diabetic wound healing. Nat Commun 9, 2163 (2018). https://doi.org/10.1038/s41467-018-04525-w

Chillakuri Chandramouli R, Jones Céline and Mardon Helen J(2010), Heparin binding domain in vitronectin is required for oligomerization and thus enhances integrin mediated cell adhesion and spreading, FEBS Letters, 584, doi: 10.1016/j.febslet.2010.06.023

Papareddy P, Kasetty G, Kalle M, Bhongir RK, Mörgelin M, Schmidtchen A, Malmsten M. NLF20: an antimicrobial peptide with therapeutic potential against invasive Pseudomonas aeruginosa infection. J Antimicrob Chemother. 2016 Jan;71(1):170-80. doi: 10.1093/jac/dkv322. Epub 2015 Oct 26. PMID: 26503666.

---

---

References

1. Papareddy, P., et al., An antimicrobial helix A-derived peptide of heparin cofactor II blocks endotoxin responses in vivo. Biochimica et Biophysica Acta (BBA) - Biomembranes, 2014. 1838(5): p. 1225-1234.
2. Ori, A., M.C. Wilkinson, and D.G. Fernig, A systems biology approach for the investigation of the heparin/heparan sulfate interactome. J Biol Chem, 2011. 286(22): p. 19892-904.
3. Torrent, M., et al., The "CPC Clip Motif": A Conserved Structural Signature for Heparin-Binding Proteins.PLOS ONE, 2012. 7(8): p. e42692.
4. Pulido, D., et al., Structural similarities in the CPC clip motif explain peptide-binding promiscuity between glycosaminoglycans and lipopolysaccharides. J R Soc Interface, 2017. 14(136).
5. Bhunia, A., et al., Designed beta-boomerang antiendotoxic and antimicrobial peptides: structures and activities in lipopolysaccharide. J Biol Chem, 2009. 284(33): p. 21991-22004.
6. Varponi, I., et al., Fighting Pseudomonas aeruginosa Infections: Antibacterial and Antibiofilm Activity of D-Q53 CecB, a Synthetic Analog of a Silkworm Natural Cecropin B Variant. Int J Mol Sci, 2023. 24(15).
7. Chen, Y., et al., Comparison of Biophysical and Biologic Properties of α-Helical Enantiomeric Antimicrobial Peptides. Chemical Biology & Drug Design, 2006. 67(2): p. 162-173.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Summary: This manuscript has identified and investigated antimicrobial peptides from GAG binding proteins. Authors hypothesized that due to physiochemical similarity between GAG and LPS, fragments of GAG binding proteins might exert antimicrobial activity particularly against G- bacteria. Authors have identified few such AMPs that demonstrate LPS binding and displayed antibacterial activity. They have also solved NMR structure of the potent peptide and mode of action.

Major comments: AMPs are promising molecules that can serve as lead for the development of therapeutics against MDR bacteria. In particular, currently therapeutic options to treat MDR Gram negative pathogens are limited. The current study is interesting and provides new non-toxic AMPs. Conclusions drawn from the works are largely valid. However, authors should address following comments

1. The design and characterization of the peptide YI12WF is not described. Previous studies had shown design of b-boomerang peptides (Bhattacharjya and coworkers) that target LPS.
2. Mutations or substitution of the key residues peptide 5 might improve the novelty of the work.
3. How these peptides disrupt LPS permeability is not investigated. As LPS is the major target.
4. Are the D-enantiomers of the peptides active against bacteria?
5. 3-D structure of peptide 5 is solved in DPC micelle which is a mimic for eukaryotic cells. Authors should attempt to determine structure in LPS as shown in several recent studies with potent AMPs thanatin, MSI etc,

Minor comments: There are examples of AMPs derived from human proteins. Authors should highlight such works.

Significance

The work described in the manuscript is novel and hold promises to develop antimicrobials in future.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

This is a very nice paper by the Andreu and Torrent groups that report the antimicrobial and heparin-binding of several encrypted peptides. Overall, this study presents an intriguing exploration into the potential dual functionality of glycosaminoglycan (GAG)-binding proteins, specifically heparin-binding proteins (HBPs), in recognizing lipopolysaccharide (LPS) and exhibiting antimicrobial properties. The findings, particularly the identification and characterization of novel encrypted peptides, such as HBP-5, are promising and contribute to our understanding of the intricate interplay between GAG-binding proteins and immunity. The data provided and methodology are thorough and well described. In sum, this is a very nice work. Please see below my minor comments.

Minor comments:

• Fig. 1 legend does not show antimicrobial activity. Please remove from the figure legend title.
• Discussion section: the authors should expand this section a bit to discuss recent work in the encrypted/cryptic peptide area. There are some recent relevant papers published in the past 3 years that should be discussed.
• References provided are a bit outdated and do not accurately reflect the latest in the field (see comment above).
• Gram should be capitalized throughout the text.
• Can the authors comment on the potential translatability of HBP-5? Please also comment on the potential advantages of having peptides that 1) bind to heparin; and 2) kill bacteria.
• More details on the computational tools and methods used to mine the peptides are needed.

Significance

The data provided and methodology are thorough and well described. In sum, this is a very nice work.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Glycosaminoglycan (GAG)-binding proteins regulating essential processes such as cell growth and migration are essential for cell homeostasis. It is reported that the GAG has the ability to bind to Herpin sulfate. As both GAGs and the LPS lipid A disaccharide core of gram-negative bacteria contain negatively charged disaccharide units, the researchers proposed that heparin-binding peptides might have cryptic antimicrobial peptide motifs. To prove the hypothesis, they have synthesized five candidates [HBP1-5], which showed a binding affinity towards heparin and LPS binding. By using various methods, they showed that these molecules have antimicrobial activity. The key finding in this study is the finding of the CPC domain, where C is a cationic amino acid and P is a polar amino acid.

Major comments

1. Even though the Authors propose here that CPC' clip motif is needed for antimicrobial activity. However, various studies have demonstrated that the mere presence of cationic amino or hydrophobic amino acids does not give the activity, the location of these amino acids at the strategic position is critically needed. The major issue in this work, the authors have not presented, whether there was a single CPC motif or multiple in the 5 peptides they have synthesised. Further, they need to demonstrate how are the charged and hydrophobic amino acids distributed in the peptides. these things will clearly explain the difference in the activity as well spectrum of the peptides. The authors should make an extra figure or add information highlighting this unique characteristic for better understanding to the reader.
2. It is strange to observe that there are quite a number of reports showing that the peptides derived from the Herprin binding proteins have antimicrobial activity, but no one has reported their efficacy in the in vivo mouse model. if possible, the authors could add their observations if in vivo studies were done. or as a future line of study.

Minor comments

1. The presence of Cryptic antimicrobial domain in various heparin-binding proteins like laminin isoforms, von Willebrand factor, vitronectin, pro-tein C inhibitor, matrix glycoproteins thrombospondin, proline arginine-rich end leucine-rich repeat protein and fibronectin, have been reported previous. It is not clear why the authors did not refer to that work. the authors should refer to the works.

Referees cross-commenting

Minor comments

1. The presence of Cryptic antimicrobial domain in various heparin-binding proteins like laminin isoforms, von Willebrand factor, vitronectin, pro-tein C inhibitor, matrix glycoproteins thrombospondin, proline arginine-rich end leucine-rich repeat protein and fibronectin, have been reported previous. It is not clear why the authors did not refer to that work. the authors should refer to the works. (same as reviewer 3)

All the earlier studies related to the antimicrobial activity of the peptides derived from the Heparin-binding protein reported a consensus Cardin and Weintraub motifs i.e, XBBBXXBX or XBBXBX, where X represents hydrophobic or uncharged amino acids, and B represents basic amino acids. However, in this work, the researchers report about the presence of the new CPC motif. So this is unique and a novelty in the study.

Even though the researchers report on the role of the CPC motif in the antimicrobial activity and binding to the heprin, the authors did not show any data or draw the conclusions related to the CPC domain when it comes to differences in the activity. this is the weakness of the manuscript. (same as reviwer 2) 2. It is strange to observe that there are quite a number of reports showing that the peptides derived from the Herprin binding proteins have antimicrobial activity, but no one has reported their efficacy in the in vivo mouse model. if possible, the authors could add their observations if in vivo studies were done. or as a future line of study.(Same as reviewer 2)

Significance

All the earlier studies related to the antimicrobial activity of the peptides derived from the Heparin-binding protein reported a consensus Cardin and Weintraub motifs i.e, XBBBXXBX or XBBXBX, where X represents hydrophobic or uncharged amino acids, and B represents basic amino acids. However, in this work, the researchers report about the presence of the new CPC motif. So this is unique and a novelty in the study.

Even though the researchers report on the role of the CPC motif in the antimicrobial activity and binding to the heprin, the authors did not show any data or draw the conclusions related to the CPC domain when it comes to differences in the activity. this is the weakness of the manuscript.

There are more than 20 different AMP databases or prediction software. however, not all of them are 100 % current, their success rate varies from 30-50% only. It needs to be investigated if adding this search in the hit peptides might increase the success rate of the extra in silico-based AMPs prediction software

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

Description of the planned revisions

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

• Again, in Figure 5, were FoxP3/CD4+ cells enumerated? Author Response: Fig 5 showed that the inflammatory score, and activation of CD4 and CD8 cells, were lower in the intestine of DSS-treated mice transplanted with Jag1Ndr/Ndr lymphocytes than in those transplanted with Jag1+/+ lymphocytes. However, in Figure 5 we had not quantified the number of FoxP3/CD4+ cells (Tregs). We agree that it would be interesting to know whether the dampened intestinal inflammation (in response to a classical inflammatory disease model (DSS-treatment)) is also mediated by excess Tregs. We will therefore now quantify Foxp3+ cells on the intestinal sections of experimental animals used for acquisition of data in Fig 5.

• *

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

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

Reviewer 1 comment: This is an interesting study that examines defects in the Jag1ndr/ndr mouse model of Alagille syndrome. The novel aspects of this manuscript are the comparisons, at many levels, between the mouse model and ALG patient samples, including an examination of immune profiles. The conclusions that the Jag1ndr/ndr mouse model is an accurate representation of the human ALG syndrome appear valid. However the reported differences in immune profiles, particularly in the Jag1ndr/ndr mouse model are difficult to understand. The data presented indicate a reduction in CD4+ cells in the Jag1ndr/ndr mouse at day P3 in both liver and spleen. Additionally, the authors report differences between the the Jag1ndr/ndr mouse and controls at day P30 in the relative percentages of DN, DP and SP CD4 and CD8 cells in the thymus. When examining the peripheral lymphoid system, CD4+ numbers are the same in both the Jag1ndr/ndr animals and controls however CD8+ numbers are reduced and FoxP3/CD4+ cells are increased in both the spleen and the thymus. FoxP3/CD4+ T cells are usually assumed to be regulatory T cells that dampen the inflammatory responses of T cells. Therefore, the increase in this population in an animal model of what is assumed to be an inflammatory disease is confusing and confounding. The authors do not present a clear analysis of how they feel an increase of Tregs would lead to this disease. One possibility is that this population is not functioning as conventional Tregs and rather are promoting inflammation but this conclusion would require a functional analysis of this population of cells, at the very least in an in vitro analysis of T cell suppression. From an immunologist's point of view, their data are antithetical to what one would expect to find in an inflammatory disease. Perhaps this reviewer is missing an important point but if I am missing it, then other who read this manusgcript also may be confused.

Author Response: *We thank the reviewer for carefully assessing our work, and for noting which aspects of the immune analyses should be more thoroughly explained. We apologize for any confusion, which a clearer introduction will help to avoid. *

*Alagille syndrome is not thought of as an inflammatory disorder, it is a congenital disorder affecting bile duct development (Kohut et al 2021, Semin Liver Dis). During normal bile duct development, JAG1+ portal fibroblasts signal to NOTCH2+ hepatoblasts to instruct bile duct development. In the context of low JAG1 signaling, hepatoblasts either fail to adopt a cholangiocyte fate, or fail to undergo bile duct morphogenesis, resulting in bile duct paucity and cholestasis. This cholestasis should activate inflammatory processes leading to fibrosis, which is the subject of this study. *

• *

We agree with the reviewer that Tregs would be expected to suppress inflammation, and our data are consistent with Treg suppression of inflammation. We show, for the first time, that Tregs are enriched in Jag1Ndr/Ndr mice (Fig 4) and present evidence that they suppress inflammation (Fig 5) and fibrosis (Fig 6), which could explain the atypical fibrosis seen in patients with ALGS.

• *

*To clarify that ALGS is a genetic liver disease affecting bile duct formation, we: *

1. Modified and extended the following text in the Introduction (Page 2, lines 14-17): “ALGS is mainly caused by mutations in the Notch ligand JAGGED1 (JAG1, 94%) (Mašek & Andersson, 2017; Oda et al, 1997), affecting bile duct development and morphogenesis, resulting in bile duct paucity and cholestasis. Immune dysregulation has also been described (Tilib Shamoun et al, 2015), but how this might interact with liver disease in ALGS to affect fibrosis is not known.”
2. *Introduce the disease, the animal model, and the scientific question in a schematic in new Fig 1A. *
3. * Reviewer 1 comment: Minor points that should be addressed include: • The source cells used in the transfer experiments reported in Figure 5 is unclear. Are they using total spleen cells with T, B and myeloid cells or are they using purified T cells. And if it is the latter, have they assessed the ratio of CD4+ versus FoxP3/CD4+ cells in the transferred cells?

Author Response: *Total spleen cells including all lymphocytes were transplanted, as described in Materials and Methods. The constituent T-cell populations are characterized and shown in Fig 4F. To clarify this, we: *

1. *added the text “Adoptive transfer of lymphocytes” to the schematic in Fig 5A, FigS5A, and Fig 6A, and *
2. modified the opening paragraph related to results presented in Fig.5 and FigS5 in the following way (page 8, line 209): “To investigate Jag1Ndr/Ndr T cell function, we performed adoptive transfer of the splenic lymphocytes into Rag1-/- mice, which lack mature B- and T cell populations, but provide a host environment with normal Jag1 (Mombaerts et al, 1992).”
3. *

*To acknowledge that B-cells and innate lymphoid cells might contribute to the observed results, we include a following sentence in the Discussion: *

(page 12, lines 369-371) “Finally, our experimental setup does not exclude an additional contribution of other lymphocytes (B-cells or innate lymphoid cells) to the BDL-induced fibrosis, and selective testing of the individual subpopulations would be an intriguing follow up to this study.”

Reviewer 1 comment: In the DSS experiments in Figure 5, there does not appear to be a no DSS control. What does the architecture look like without DSS?

Author Response: The intestinal architecture and phenotype of mice transplanted with Jag1+/+ or Jag1Ndr/Ndr lymphocytes, not treated with DSS, are presented in Supplementary Figure 5. In the absence of DSS, Jag1+/+- or Jag1Ndr/Ndr -transplanted mice exhibit no overt differences in survival or weight gain/loss. The intestinal inflammatory score was not different in the two conditions and was *2.29 +/-0.44 and 2.03 +/-0.92 for Jag1+/+- or Jag1Ndr/Ndr -transplanted mice, respectively. *

To compare the results with and without DSS, we added the following text to the results section, when describing the DSS results (Page 9, lines 223-226):

“As expected, histological scoring of intestinal and colonic inflammation revealed elevated inflammation in Jag1+/+→Rag1-/- mice treated with DSS (Fig. 5C,D) compared to Jag1+/+→Rag1-/- mice not treated with DSS (Fig. S5). However, there was significantly less inflammation in Jag1Ndr/Ndr→Rag1-/- mice than in Jag1+/+→Rag1-/- mice (Fig. 5C,D)."

Reviewer 1 comment: The authors noted that splenomegaly was observed in the Jag1ndr/ndr mouse model. Again this is antithetical to what one would expect when one sees an increase in FoxP3/CD4+ T regs.

Author Response: *We thank the reviewer for pointing at a possible discrepancy, related to Fig1 in which we report the presence of splenomegaly. Although there can be multiple causes of splenomegaly, it is one of the hallmarks of portal hypertension (as also corroborated by Reviewer 2), tightly connected with liver fibrosis, present in patients with ALGS and we report it as such in the manuscript. To clarify this, we added the following text sections: *

1. Results (page 2, lines 37,38) “Liver fibrosis compresses blood vessels and reduces their blood flow, leading to portal hypertension, a serious consequence of liver disease which can manifest as splenomegaly.”
2. Discussion (page 13, line 394-401): “Splenomegaly has been described as a consequence of portal hypertension in ALGS (Kamath et al, 2020), but could also be attributed to immune-related pathology. Jag1Ndr/Ndr mice exhibit splenomegaly as early as P10, and is exacerbated at P30 ( 1E,F). Patients with other liver diseases display portal hypertension and cirrhosis, with both splenomegaly and hypersplenism associated with a high CD4+/CD8+ ratio, but a low Treg+/CD4+ ratio (Nomura et al, 2014). However, Jag1Ndr/Ndr mice present with splenomegaly but not hypersplenism. An overactive spleen (hypersplenism) would remove red blood cells which are instead enriched in Jag1Ndr/Ndr mice, and Tregs were enriched in Jag1Ndr/Ndr mice, not depleted as seen in cirrhosis/hypersplenism. These data are thus consistent with portal hypertension-induced splenomegaly rather than hypersplenism.*” *

Reviewer #1 (Significance (Required)):

Reviewer 1 comment: The strengths of this paper are the careful comparisons between the mouse model and the human ALG syndrome. These comparisons are valuable and worth publication.

Author Response: We thank the reviewer for these comments.

Reviewer 1 comment: Weaknesses are stated above. Needs a clearer explanation for their immune analysis.

Author Response: *We thank the reviewers for highlighting points requiring clarification and hope the proposed text changes and additional data presented in response to the comments of all three reviewers lead to a significant clarification of the immunological aspect of our study. *

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

Reviewer 2 comment:

Summary: Masek and colleagues use multi-pronged studies on the Jag1[Ndr/Ndr] mouse model of Alagille syndrome (ALGS) combined with transcriptomic analysis on livers from patients with ALGS to elucidate the potential mechanisms regulating liver fibrosis in this disease. The authors first show that Jag1[Ndr/Ndr] animals develop pericellular and perisinusoidal fibrosis and exhibit evidence for portal hypertension, similar to patients with ALGS. Single-cell RNA-sequencing indicated more hepatoblasts and less hepatocytes, relatively speaking, in Jag1[Ndr/Ndr] P3 livers, which suggested hampering of hepatoblast differentiation to hepatocytes. Deconvolution of previously generated bulk RNA-seq data from Jag1[Ndr/Ndr] P10 livers and GESA on RNAseq data from livers of these mice and patients with ALGS confirmed the P3 scRNA-seq observations and indicated mild pro-inflammatory activation of immature hepatocytes in ALGS livers. GESA also suggested an inability of Jag1[Ndr/Ndr] livers to attract T cells upon cholestatic injury. Indeed, 25-color flow cytometry on liver and spleen from mutant and control mice indicated a defect in T cell response to cholestasis in this model. The authors then examined the effects of the Ndr mutation on T-cell development and function. They found that the Ndr/Ndr thymi were significantly smaller than control thymi. Moreover, Ndr/Ndr thymi showed an increase in CD4+ T-cells and Tregs at the expense of double-positive T-cells. The authors then performed lymphocyte transplantation studies and concluded that Ndr/Ndr T-cells fail to mount an adequate response to inflammation in a DSS model of ulcerative colitis. The authors tested the contribution of Ndr/Ndr immune cells to liver fibrosis in a model of experimentally induced cholestasis (bile duct ligation; BDL). Ndr/Ndr T-cells did not show any defects in migrating into the liver upon BDL. However, the periportal fibrosis observed in BDL model was reduced in animals receiving Ndr/Ndr immune cells compared to those receiving Jag1+/+ immune cells. This was accompanied by significantly less aSMA staining in these livers. Finally, reanalysis of bulk RNAseq data from liver samples from ALGS and other liver diseases suggested that the presence of FOXP3+ T-reg cells in the liver is associated with higher liver fibrosis in non-ALGS liver diseases but lower liver fibrosis in ALGS livers. The authors have used an impressive combination of single-cell RNA-sequencing, reanalysis of previous bulk RNA-sequencing data from their group and others, 25-color FACS analysis, and adoptive immune transfer experiments in this manuscript, and systematically provide quantification and statistical analysis for their data. Overall, this is an interesting and important study. Prior studies are referenced appropriately. The text and figures are clear and accurate. I don't think any additional experiments are essential. However, the issues listed under Major comments should be discussed and clarified in the manuscript, especially the first item.

Author Response: *We sincerely thank the reviewer for the comprehensive and insightful assessment of our manuscript. We are particularly gratified to note your acknowledgment of the thoroughness of our experimental approach and the clarity of our presentation. We are pleased that no further experiments would be required, and will address the points raised under Major comments which enhance our study's quality and accessibility. *

Reviewer 2 comment:

Major comments:

• Only a small fraction of the cells in scRNA-seq experiments have been assigned to hepatocytes/hepatoblast clusters, with the majority of these cells allocated to Hepato-Ery cluster. This suggests that many hepatocytes and potentially hepatoblasts have been lost during sample preparation. The authors should discuss this issue and its potential implications on the interpretation of the cell ratios and gene expression conclusions of scRNA-seq data. Author Response: We agree with the reviewer regarding this aspect of our study. We mentioned this limitation in the supplementary methods section: ”Liver parenchymal cells constituted ~6.5% of cells at E16.5, and ~7.5% of cells at P3 and included mesenchymal cells, endothelial cells, hepatoblasts and hepatocytes (Fig. S1D), this parenchymal proportion is lower than in vivo, but consistent with ex vivo liver digest (Guilliams et al, 2022).” We recognize it may be too inaccessible there, and we thus added the following text to the Discussion section of the manuscript: (Pages 11-12, lines 330-337) “A limitation of this study is the underrepresentation of the hepatoblast/cyte parenchymal cells in the scRNA-seq dataset (Fig. 2A-D), which constituted ~6.5% of analyzed cells at E16.5, and ~7.5% of cells at P3 (Fig. S1D). This parenchymal proportion is lower than in vivo, but is consistent with scRNA seq datasets obtained with ex vivo liver digest (Guilliams et al, 2022). One risk is that cell stress as a result of dissociation could result in further loss of injured Jag1Ndr/Ndr hepatocytes, impacting the interpretation of cell type abundance. Nuclear scRNAseq can overcome cell type-dependent dissociation sensitivity bias (Guilliams et al, 2022), and could provide further insights into Jag1Ndr/Ndr livers at the single cell level. Nonetheless, both bulk RNA seq deconvolution and histological analyses confirmed that patients and Jag1Ndr/Ndr mice exhibit hepatoblast enrichment and less differentiated hepatocytes.”

Reviewer 2 comment: The Jag1[Ndr/Ndr] strain is an excellent model for various aspects of ALGS phenotypes. However, when it comes to linking the effects of this mutation to the function of a specific cell type, it is worth considering that Jag1[Ndr/Ndr] might not recapitulate the effects of loss of one copy of JAG1 observed in most patients with ALGS. This is especially important given the sensitivity of various cellular and organ-level processes to the degree of Notch pathway activation. In the context of the present manuscript, it is possible that what the authors have observed in Jag1[Ndr/Ndr] lymphocytes does not mirror how a JAG1-heterozygous human lymphocyte behaves. This is not a major concern, but it is worth considering.

Author Response: We agree and thus added the following discussion paragraph (page 11, lines 315-321) “In patients with ALGS, who have a single mutation in either JAG1 or NOTCH2, the remnant healthy allele(s) could be expected to mediate signaling. However, some JAG1 mutations exhibit dominant negative effects (Ponio et al, 2007; Xiao et al, 2013; Guan et al, 2023), which could entail further repression of JAG1/NOTCH2 signaling. In this context, it is important to note that the Jag1Ndr/Ndr mice are homozygous for the missense mutation, but retain some JAG1 activity, and it is not clear to which degree this mimics JAG1 heterozygosity in humans. It would be of interest to test whether Jag1 potency affects hepatoblast differentiation or injury-induced reversion of hepatocytes in patients as a function of their genotype.”

Reviewer 2 comment: •The basis for the opposite type of correlation between COL1A1 expression and POXP3 level in ALGS versus non-ALGS liver disease is not clear.

Author Response: We thank the reviewer for pointing out the unclear interpretation of the patient data. In patients with ALGS, the extent of fibrosis is likely to be highly multifactorial, involving (as we show) hepatocyte immaturity, dampened inflammation, and immune system dysregulation (possibly involving more than T-cells). Since human patients ARE so heterogeneous, teasing apart the relative contribution of each is currently outside the scope of our study, but will be an important area of future research. Nonetheless we thought it was important and interesting to show these patterns in supplementary Fig 6, now extended with further data, and analyses, and described in the following manner:

• *

Results section: (page 10, lines 267-275) “Liver damage in non-ALGS liver disease (using liver injury marker LGALS3BP) (Yang et al, 2021), was positively correlated with recruitment of lymphocytes (including CD8A+,and FOXP3+ populations of T cells), as well as the extent of fibrosis (COL1A1 abundance) (Fig. S6G). However, in ALGS, the extent of liver damage, lymphocyte recruitment and fibrosis were unlinked (Fig. S6G). These data are in line with the observation that liver stiffness (a proxy for fibrosis) in ALGS is independent of biomarkers of liver disease (Leung et al, 2023). While Treg infiltration in ALGS was independent of liver damage, it exhibited a tendency towards a negative correlation with fibrosis (Fig. S6G), corroborating that elevated levels of Tregs may limit fibrosis in ALGS. Altogether, these data suggest that the liver and lymphocytes may be differentially affected in different patients with ALGS, a disorder that is well known for its heterogenous presentation.”

Minor comments:

• Page 2, last paragraph of Introduction, Page 12 last sentence, and Supplementary Methods: Please use "adoptive immune transfer" instead of "adaptive immune transfer". • Pages 3 and 4: Reference is made to Figures 3E-O, which appears to be Figure 2E-O. • Figure 3 legend: "Analysis in (E) is one-way ANOVA with Dunnett's multiple comparison test". Panel E compares two means, so ANOVA is not the appropriate statistical analysis for these data. Is this sentence related to panel D? • Page 9: Please correct misspelling: "response to intestinal insult (Fig. 5). W therefore". • The Science Translation Medicine references lack page number. Author Response: *We thank the reviewer deeply for taking the time to meticulously note and convey these errors, helping us to correct these. The suggested corrections have been implemented. Science Transl Med is an online journal and does not have page numbers – we have added an issue number to facilitate retrieval of these references. *

• *

Additionally, we noticed that the image of a consecutive liver section with CYP1A2 staining from Jag1Ndr/Ndr liver in Fig 2 L was accidentally flipped along the horizontal axis, which we have now corrected. We also changed the scRNAseq cell cluster naming from Hepatoblasts/cytes, Hepato_Ery, and Kupffer cells, Kuffer cells_Ery to Hepatoblasts/cytes I, and II, and Kupffer cells I and II, respectively, to match the Neutrophil progenitors I and II naming convention. Names were subsequently also changed in Fig S1 and methods.

**Referees cross-commenting**

To my knowledge, ALGS is not considered to be an inflammatory disorder. Furthermore, the splenomagaly observed in the mouse model could be due to portal hypertension rather than a primary immune disturbance. Having said that, I agree with the other reviewers that the manuscript will benefit from further discussion and clarification on the immune-related observations.

Author Response: We thank Reviewer 2 for indicating to Reviewer 1 that ALGS is not considered an inflammatory disorder, which we agree with. It was not our intention to convey this idea. To avoid confusion, we now:

1. *Added a schematic in Fig 1A. *
2. Modified and extended the following text in the Introduction: (Page 2, lines 14-17): “ALGS is mainly caused by mutations in the Notch ligand JAGGED1 (JAG1, 94%) (Mašek & Andersson, 2017; Oda et al, 1997), affecting bile duct development and morphogenesis, resulting in bile duct paucity and cholestasis. Immune dysregulation has also been described (Tilib Shamoun et al, 2015), but how this might interact with liver disease in ALGS to affect fibrosis is not known.” *Furthermore, we have addressed or will address all comments from reviewer 1 to clarify the immune-related observations. *

Reviewer #2 (Significance (Required)):

Despite severe cholestasis, ALGS patients do not show as much fibrosis as other cholestatic diseases, including biliary atresia (BA). A previous study had suggested that this phenomenon could be due to the difference in the nature of reactive hepatobiliary cells in ALGS compared to BA (Fabris et al, 2007). Moreover, a number of studies have suggested a role for Notch pathway activation in several cell types in the liver in the development of liver fibrosis (for example, Sawitza et al, Hepatology, 2009; Chen et al, Plos One, 2012; Duan et al, Hepatology, 2018; Yu et al, Science Translational Medicine, 2021). However, although a role for Notch signaling in T-cells is well established, it was not known whether impaired T-cell development/function contributes to reduced fibrosis in ALGS liver disease. Accordingly, the current manuscript provides novel insight into the mechanism of fibrosis in this disease. Moreover, the observation that Jag1-mutant T-cells do not confer as much protection as control T-cells to immunodeficient mice subjected to DSS-induced ulcerative colitis provides strong evidence for impaired T-cell immunity in this ALGS model and might help explain other aspects of ALGS phenotypes.

The manuscript will be of interest to broad audience (Notch signaling, cholestatic liver disease, mechanisms of liver fibrosis, T-cell development).

I have expertise in Notch signaling and in using animal models of human developmental disorders.

__Author Response: __We thank the reviewer for the balanced assessment of our manuscript in light of the current knowledge, and for highlighting its importance in the context of not only Notch and ALGS, but also other cholestatic and fibrotic liver diseases.

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

The article entitled "Jag1 Insufficiency Disrupts Neonatal T Cell Differentiation and Impairs Hepatocyte Maturation, Leading to Altered Liver Fibrosis" by Mašek et al described the role of Notch ligand JAGGED1 (JAG1) in the T-cell differentiation contributing to liver fibrosis and immune system development in ALGS. This article is well written and has important preliminary findings that could establish Jag1 and its downstream signaling pathways as potential therapeutic targets to attenuate liver fibrosis.

Author Response: We thank the reviewer for recognizing our work and pointing out the therapeutical implications of our findings.

Reviewer 3 comment 1: Minor comments: In page 4, they mentioned that "the hepatoblast marker alpha fetoprotein (AFP) was 3.1-fold enriched (Fig. 3J,K), while the mature hepatocyte marker CYP1A2 protein was 1.7-fold less expressed (Fig. 3L-M)", the figure numbers should be changed to 2J, K, L-M etc.

Author Response:* We thank the reviewer for identifying these errors. The suggested corrections have been implemented. *

Reviewer 3 comment 2: In liver fibrosis the Th17 cells play crucial roles. Please show the level of IL17A mRNA level in the liver in the Jag1Ndr/Ndr mice compared to the Jag1+/+ mice.

Author Response: We thank the reviewer for the insightful comments. We indeed investigated the Th17 vs Treg immune response, however we detect neither Th17-expressed Il17, Il17a, Il17f, nor Il21 and Il22 mRNA in the bulk RNA data, suggesting their expression is either masked or they are not present in significant numbers within the liver tissue at P10, preventing us from drawing any conclusions about this cell population.

Reviewer ____3 comment 3: Also, please show the expression level of pro-inflammatory molecules, for example, TNFα, IL1β, MCP1 etc and the level of MMPs (especially MMP2, MMP8, MMP9) in the livers of the mice models used.

Author Response: *The expression of Il10, Il1b, Mcp1(Ccl2), was presented in the manuscript Fig. 2O, and we attach in the response to reviewers *

*a full list together with the expression levels of Mmp2/8/9, Tnfa, Ifng, Il17 receptor family and Tgfb1-3. Out of these, Mmp8 (0.9 Log2fold change = 1.9-fold), Ccl2 (2.2 Log2fold change = 4.7-fold), and Tl17rb (1.1 Log2fold change = 2.1-fold) were significantly upregulated, but do not indicate any specific leukocyte population’s response. This is in line with data in Fig S2E, demonstrating a dominance of myeloid over adaptive immune response in the GSEA of the immune KEGGs. *

*Since lymphocytes are underrepresented in the bulk transcriptomics, and individual genes might report activity of many different cell types, we chose to focus on the list of genes shown to be markers of activated hepatocytes, to avoid over interpretation of the RNA sequencing data. Instead, the immune analyses were based on flow cytometry data, which we expect should accurately report cell type abundance across organ systems. *

Reviewer 3 comment____ 4. Authors have shown significant alterations in the Treg population in their Jag1Ndr/Ndr mice of ALGS. Please also show the expression of IL10 and TGFβ in the liver and whether they are correlated with the level of Treg populations.

Author response:* IL10 and Tgfb mRNA levels in liver are shown in the heatmap in the response to reviewers, and were not significantly different between genotypes at P10. They were also not correlated with Foxp3 levels, as shown in the correlation matrices below (Pearson’s R values in top row, significance values in bottom row). *

Reviewer 3 comment 5. It would be interesting to know whether the IFNγ mRNA expression in the livers were altered in the Jag1Ndr/Ndr mice with altered populations of CD8 T cells.

Author Response: There was no significant difference in IFNγ mRNA expression levels between Jag1+/+ and Jag1Ndr/Ndr *livers at P10 (please see the heatmap in response to comment no.3, above). *

Reviewer #3 (Significance (Required)): Strength: This article is well written and has important preliminary findings that could establish Jag1 and its downstream signaling pathways as potential therapeutic targets to attenuate liver fibrosis.

Author Response: Thank you for these comments and pointing out the wider implications of our findings.

---

Reviewer 3____ Limitations: This study lacked the detailed molecular pathways which could explain how the Jag1 altered the T-cell recruitment, development and hepatocyte maturation in the development of liver fibrosis in the ALGS model.

Author Response: We agree that this study does not focus on molecular pathways. The intention of this study was to identify which cell populations contribute to atypical neonatal fibrosis in ALGS. Because we expected this process to be multifactorial, Jag1Ndr/Ndr mice, carrying a systemic mutation, present both advantages (Jag1 abrogation in all cells --> ALGS-like organ interactions) and limitations (inability to identify contributions of individual cell types). However, by identifying maturing hepatocytes and Tregs as dysregulated, and demonstrating that Jag1Ndr/Ndr lymphocytes behave abnormally and suppress inflammation and fibrosis in Rag1-/- mice (with normal Jag1 expression), we establish a biological framework that can now be further investigated with conditional genetic tools and in vitro systems, to elucidate specific molecular pathways, that were beyond the scope of the current study.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

The article entitled "Jag1 Insufficiency Disrupts Neonatal T Cell Differentiation and Impairs Hepatocyte Maturation, Leading to Altered Liver Fibrosis" by Mašek et al described the role of Notch ligand JAGGED1 (JAG1) in the T-cell differentiation contributing to liver fibrosis and immune system development in ALGS. This article is well written and has important preliminary findings that could establish Jag1 and its downstream signaling pathways as potential therapeutic targets to attenuate liver fibrosis.

1. Minor comments: In page 4, they mentioned that "the hepatoblast marker alpha fetoprotein (AFP) was 3.1-fold enriched (Fig. 3J,K), while the mature hepatocyte marker CYP1A2 protein was 1.7-fold less expressed (Fig. 3L-M)", the figure numbers should be changed to 2J, K, L-M etc.
2. In liver fibrosis the Th17 cells play crucial roles. Please show the level of IL17A mRNA level in the liver in the Jag1Ndr/Ndr mice compared to the Jag1+/+ mice.
3. Also, please show the expression level of pro-inflammatory molecules, for example, TNFα, IL1β, MCP1 etc and the level of MMPs (especially MMP2, MMP8, MMP9) in the livers of the mice models used.
4. Authors have shown significant alterations in the Treg population in their Jag1Ndr/Ndr mice of ALGS. Please also show the expression of IL10 and TGFβ in the liver and whether they are correlated with the level of Treg populations.
5. It would be interesting to know whether the IFNγ mRNA expression in the livers were altered in the Jag1Ndr/Ndr mice with altered populations of CD8 T cells.

Significance

Strength: This article is well written and has important preliminary findings that could establish Jag1 and its downstream signaling pathways as potential therapeutic targets to attenuate liver fibrosis.

Limitations: This study lacked the detailed molecular pathways which could explain how the Jag1 altered the T-cell recruitment, development and hepatocyte maturation in the development of liver fibrosis in the ALGS model.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

Summary:

Masek and colleagues use multi-pronged studies on the Jag1[Ndr/Ndr] mouse model of Alagille syndrome (ALGS) combined with transcriptomic analysis on livers from patients with ALGS to elucidate the potential mechanisms regulating liver fibrosis in this disease. The authors first show that Jag1[Ndr/Ndr] animals develop pericellular and perisinusoidal fibrosis and exhibit evidence for portal hypertension, similar to patients with ALGS. Single-cell RNA-sequencing indicated more hepatoblasts and less hepatocytes, relatively speaking, in Jag1[Ndr/Ndr] P3 livers, which suggested hampering of hepatoblast differentiation to hepatocytes. Deconvolution of previously generated bulk RNA-seq data from Jag1[Ndr/Ndr] P10 livers and GESA on RNAseq data from livers of these mice and patients with ALGS confirmed the P3 scRNA-seq observations and indicated mild pro-inflammatory activation of immature hepatocytes in ALGS livers. GESA also suggested an inability of Jag1[Ndr/Ndr] livers to attract T cells upon cholestatic injury. Indeed, 25-color flow cytometry on liver and spleen from mutant and control mice indicated a defect in T cell response to cholestasis in this model. The authors then examined the effects of the Ndr mutation on T-cell development and function. They found that the Ndr/Ndr thymi were significantly smaller than control thymi. Moreover, Ndr/Ndr thymi showed an increase in CD4+ T-cells and Tregs at the expense of double-positive T-cells. The authors then performed lymphocyte transplantation studies and concluded that Ndr/Ndr T-cells fail to mount an adequate response to inflammation in a DSS model of ulcerative colitis. The authors tested the contribution of Ndr/Ndr immune cells to liver fibrosis in a model of experimentally induced cholestasis (bile duct ligation; BDL). Ndr/Ndr T-cells did not show any defects in migrating into the liver upon BDL. However, the periportal fibrosis observed in BDL model was reduced in animals receiving Ndr/Ndr immune cells compared to those receiving Jag1+/+ immune cells. This was accompanied by significantly less aSMA staining in these livers. Finally, reanalysis of bulk RNAseq data from liver samples from ALGS and other liver diseases suggested that the presence of FOXP3+ T-reg cells in the liver is associated with higher liver fibrosis in non-ALGS liver diseases but lower liver fibrosis in ALGS livers. The authors have used an impressive combination of single-cell RNA-sequencing, reanalysis of previous bulk RNA-sequencing data from their group and others, 25-color FACS analysis, and adoptive immune transfer experiments in this manuscript, and systematically provide quantification and statistical analysis for their data. Overall, this is an interesting and important study. Prior studies are referenced appropriately. The text and figures are clear and accurate. I don't think any additional experiments are essential. However, the issues listed under Major comments should be discussed and clarified in the manuscript, especially the first item.

Major comments:

• Only a small fraction of the cells in scRNA-seq experiments have been assigned to hepatocytes/hepatoblast clusters, with the majority of these cells allocated to Hepato-Ery cluster. This suggests that many hepatocytes and potentially hepatoblasts have been lost during sample preparation. The authors should discuss this issue and its potential implications on the interpretation of the cell ratios and gene expression conclusions of scRNA-seq data.
• The Jag1[Ndr/Ndr] strain is an excellent model for various aspects of ALGS phenotypes. However, when it comes to linking the effects of this mutation to the function of a specific cell type, it is worth considering that Jag1[Ndr/Ndr] might not recapitulate the effects of loss of one copy of JAG1 observed in most patients with ALGS. This is especially important given the sensitivity of various cellular and organ-level processes to the degree of Notch pathway activation. In the context of the present manuscript, it is possible that what the authors have observed in Jag1[Ndr/Ndr] lymphocytes does not mirror how a JAG1-heterozygous human lymphocyte behaves. This is not a major concern, but it is worth considering.
• The basis for the opposite type of correlation between COL1A1 expression and POXP3 level in ALGS versus non-ALGS liver disease is not clear.

Minor comments:

• Page 2, last paragraph of Introduction, Page 12 last sentence, and Supplementary Methods: Please use "adoptive immune transfer" instead of "adaptive immune transfer".
• Pages 3 and 4: Reference is made to Figures 3E-O, which appears to be Figure 2E-O.
• Figure 3 legend: "Analysis in (E) is one-way ANOVA with Dunnett's multiple comparison test". Panel E compares two means, so ANOVA is not the appropriate statistical analysis for these data. Is this sentence related to panel D?
• Page 9: Please correct misspelling: "response to intestinal insult (Fig. 5). W therefore".
• The Science Translation Medicine references lack page number.

Referees cross-commenting

To my knowledge, ALGS is not considered to be an inflammatory disorder. Furthermore, the splenomagaly observed in the mouse model could be due to portal hypertension rather than a primary immune disturbance. Having said that, I agree with the other reviewers that the manuscript will benefit from further discussion and clarification on the immune-related observations.

Significance

Despite severe cholestasis, ALGS patients do not show as much fibrosis as other cholestatic diseases, including biliary atresia (BA). A previous study had suggested that this phenomenon could be due to the difference in the nature of reactive hepatobiliary cells in ALGS compared to BA (Fabris et al, 2007). Moreover, a number of studies have suggested a role for Notch pathway activation in several cell types in the liver in the development of liver fibrosis (for example, Sawitza et al, Hepatology, 2009; Chen et al, Plos One, 2012; Duan et al, Hepatology, 2018; Yu et al, Science Translational Medicine, 2021). However, although a role for Notch signaling in T-cells is well established, it was not known whether impaired T-cell development/function contributes to reduced fibrosis in ALGS liver disease. Accordingly, the current manuscript provides novel insight into the mechanism of fibrosis in this disease. Moreover, the observation that Jag1-mutant T-cells do not confer as much protection as control T-cells to immunodeficient mice subjected to DSS-induced ulcerative colitis provides strong evidence for impaired T-cell immunity in this ALGS model and might help explain other aspects of ALGS phenotypes.

The manuscript will be of interest to broad audience (Notch signaling, cholestatic liver disease, mechanisms of liver fibrosis, T-cell development).

I have expertise in Notch signaling and in using animal models of human developmental disorders.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

This is an interesting study that examines defects in the Jag1ndr/ndr mouse model of Alagille syndrome. The novel aspects of this manuscript are the comparisons, at many levels, between the mouse model and ALG patient samples, including an examination of immune profiles. The conclusions that the Jag1ndr/ndr mouse model is an accurate representation of the human ALG syndrome appear valid. However the reported differences in immune profiles, particularly in the Jag1ndr/ndr mouse model are difficult to understand. The data presented indicate a reduction in CD4+ cells in the Jag1ndr/ndr mouse at day P3 in both liver and spleen. Additionally, the authors report differences between the the Jag1ndr/ndr mouse and controls at day P30 in the relative percentages of DN, DP and SP CD4 and CD8 cells in the thymus. When examining the peripheral lymphoid system, CD4+ numbers are the same in both the Jag1ndr/ndr animals and controls however CD8+ numbers are reduced and FoxP3/CD4+ cells are increased in both the spleen and the thymus. FoxP3/CD4+ T cells are usually assumed to be regulatory T cells that dampen the inflammatory responses of T cells. Therefore, the increase in this population in an animal model of what is assumed to be an inflammatory disease is confusing and confounding. The authors do not present a clear analysis of how they feel an increase of Tregs would lead to this disease. One possibility is that this population is not functioning as conventional Tregs and rather are promoting inflammation but this conclusion would require a functional analysis of this population of cells, at the very least in an in vitro analysis of T cell suppression. From an immunologist's point of view, their data are antithetical to what one would expect to find in an inflammatory disease. Perhaps this reviewer is missing an important point but if I am missing it, then other who read this manuscript also may be confused.

Minor points that should be addressed include:

• The source cells used in the transfer experiments reported in Figure 5 is unclear. Are they using total spleen cells with T, B and myeloid cells or are they using purified T cells. And if it is the latter, have they assessed the ratio of CD4+ versus FoxP3/CD4+ cells in the transferred cells?
• In the DSS experiments in Figure 5, there does not appear to be a no DSS control. What does the architecture look like without DSS?
• Again, in Figure 5, were FoxP3/CD4+ cells enumerated?
• The authors noted that splenomegaly was observed in the Jag1ndr/ndr mouse model. Again this is antithetical to what one would expect when one sees an increase in FoxP3/CD4+ T regs.

Significance

The strengths of this paper are the careful comparisons between the mouse model and the human ALG syndrome. These comparisons are valuable and worth publication.

Weaknesses are stated above. Needs a clearer explanation for their immune analysis.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

Reviewer #1

Evidence, reproducibility and clarity (Required):

Au et al. used two fly models to study how mitochondrial defects are implicated in C9ALS, the most common familial ALS type. They found that in these flies, mitochondrial, but not cytosolic, ROS is upregulated, accompanied by locomotion defects agreeing with previous publications. Consistent with these data, sod2, but not sod1, rescues the behavioral defects in these flies. Also, manipulating mitochondrial dynamics or mitophagy does not rescue these defects. Furthermore, the authors showed that the Nrf2 activity is upregulated, likely due to oxidative stress, and genetically or pharmacologically suppressing the Keap1 function, which activates Nrf2 and thereby its downstream antioxidative genes, suppresses behavior defects in these flies. This part is generally solid and convincing, with minor issues that need some revision. Finally, the authors showed that mitochondrial ROS and nuclear Nrf2 are both upregulated in C9 iPS neurons, both of which are suppressed by the Keap1 inhibitor DMF, or a known antioxidant. For this part, the data are convincing but insufficient to support a good translation of their fly data.

__Major concerns: __

1a. The authors really need a phenotypic readout for their iPS experiments, either cell death or some sort of toxicity, to support the translatability of their fly data.

• We agree and appreciate the value of having such as phenotypic readout for the iPSC experiments but, unfortunately, within the context of the current work we did not obvious any clear phenotype of toxicity or diminished viability under basal, unchallenged conditions. To support this, we have added our analysis of cell viability at the time of imaging, shown in new Supplementary Figure 3C and mentioned in the text (line 620-621).

1b. The authors also need to test the toxicity of DMF in iPS neurons.

• As above, we found that treatment with DMF conferred no overt toxicity within the time-course of our experiments. These data are shown in new Supplementary Figure 3D and mentioned in the text (line 626-628).

The authors should use genetic ways, e.g., knocking down Keap1, to activate Nrf2 and test whether this suppresses ROS and neurodegeneration phenotype in iPS neurons, as they did in flies.

They need to better characterize the Nrf2 activity in iPS neurons (see Minor Concern #1).

• Regarding these two points, we agree that it would be interesting to further investigate the Keap1/Nrf2 pathway in these cells, but time, personnel and resource constraints preclude additional investigations on this occasion. It is important to note that the cell models were used specifically to validate that elevated mitochondrial oxidative stress and increased nuclear Nrf2 localisation also occurred in patient-derived neurons, and whether DMF treatment could reverse the oxidative stress. This was the extent to which the cell models were used in this instance and the current data are sufficient to support the conclusions made based on this. We regret that it was not possible to delve deeper into this at the current time but will be possible in future work.

---

__Minor concerns: __

1a. Fig 4A and B are hard to comprehend. Can the authors show images with more obvious differences?

• We have now revised these figure panels replacing with alternative images. We hope that the new images show more appreciable differences. We understand that the differences can sometimes be subtle which is why we rely on the quantification for unbiased interpretation.

1b. Also, Gst-D1 is the only Nrf2 downstream gene tested. Can the authors use RT-PCR to test multiple genes? These will strengthen the point that Nrf2 is activated. Similar things should be done in iPS neurons.

• Thanks for this suggestion. To complement the immunoblots of the genomic GstD1-GFP reporter, we have now performed qRT-PCR on flies treated with or without DMF for additional Keap1/Nrf2 pathway targets, including GstD1, Gclc, GstD2 and Cyp6a2. These data show that the degree of transcriptional activation was variable between different targets, but DMF treatment caused a general upregulation of CncC targets in G4C2x36 flies (new Fig. 6A).

What about cytosolic ROS in C9 iPS neurons? Is it similar to the fly models?

• We agree that this would be interesting to analyse. Unfortunately, given time and resource constraints we did not have the capacity to also explore this out of curiosity. Again, the specific focus for the iPSC neuron work was to validate the mitochondrial ROS aspect and action of DMF.

Unless the authors confirm that mitochondrial dynamics or mitophagy are not contributing to neurodegeneration in iPS neurons, I wouldn't emphasize their related negative data in flies. Overall, the authors need to tone down their arguments if the findings are not verified in iPS or other mammalian models.

• On reflection, we agree that the iNeuron data was given an overly prominent status within the study and we have adjusted the text accordingly throughout, including removing a specific mention of this in the title. That said, we still consider that the negative results regarding the lack of rescue of organism-scale phenotypes (e.g., locomotion) by manipulating mitochondrial dynamics or mitophagy to be important indicators of the relative mechanistic contribution of these processes to the organism-scale pathology (most closely reflecting the clinical condition). As discussed above (major point 1a), within the context of the current work we did not obvious any clear phenotype of toxicity or diminished viability in the patient iNeurons. Therefore, it is not readily possible to test the relative contribution of mitochondrial dynamics vs mitophagy vs ROS to the survival of these cells, so we have based our interpretations of this on the in vivomodels. In summary, we have toned down our statements relating to and stemming from data arising from the iNeuron work but our interpretation of the negative results in flies remains the same.

Can the authors measure the activities of OXPHOS complexes and ATP synthase/complex V?

• The intention of this study was to explore mechanisms that could alleviate pathological phenotypes in vivo. We have characterised a wide-range of cellular defects relating to mitochondrial dysfunction including overall OXPHOS function by OCR. Analysing individual OXPHOS complexes from animal tissue is not a trivial undertaking and, other than providing a little more granularity to the nature of the respiratory defect, we considered that this would be a distraction from the main focus of the study.

5a. Edavarone is one of the only two effective drugs for general ALS, and it's believed to work as an antioxidant. The authors should discuss it along with relating their findings to therapeutic development.

• A statement on Edaravone being an FDA-approved treatment for ALS and an antioxidant (ROS scavenger) were included in the text (lines 628-629). We have added further comment on this in the Discussion (lines 686-690). Since edaravone was used as a comparator in this study, and to maintain the focus on DMF, we prefer to not elaborate on this further in the discussion.

5b. Also, the discussion on SOD1 aggregation sounds somewhat farfetched. Plus, it's not directly related to the central message of this paper. I would remove it.

• Fair enough. We have removed these statements from the text.

__Significance (Required): __

C9orf72-mediated ALS is the most common familial ALS type and also accounts for a fraction of sporadic ALS cases. Its pathomechanism is incompletely understood. Previous studies have linked mitochondrial defects and ROS to pathogenesis in fly, iPS, mouse, etc. models, and antioxidants can suppress some neurodegenerative features in these models. Consistent with these findings, one of the only two effective drugs for general ALS, edaravone, is believed to mitigate oxidative stress in motor neurons. Hence, oxidative stress is a critical pathogenic contributor that holds great potential as a therapeutic target. However, our understanding of its cause and consequence in ALS is limited. This paper includes at least two novel points: 1) identifying mitochondrial, but not cytosolic, ROS is upregulated and contributes to neurodegeneration in C9ALS models; 2) discovering that the Keap1/Nrf2 is altered and activating Nrf2 suppresses neurodegeneration. The first point presents an incremental advance in the field, but the second one is potentially critical, especially from a translational aspect. That being said, the novelty of the second point is somewhat dampened by a recently published paper (Jiménez-Villegas, et al. 2022), which showed that Nrf2/Keap1 is altered in C9 patient leukocytes and NSC cells overexpressing or treated with C9-DPRs. However, these cells/models are remotely related to the disease. The current manuscript still provided evidence in an in vivo neuronal model for the first time. If the authors could make their iPS part comprehensive, this could still be a major advance towards translation.

This paper could be interesting to a broad audience beyond the ALS field.

Another strength of this paper is that the fly analyses are comprehensive, the data are convincing, and the conclusions are solid. However, the major weakness is that the iPSN part is incomplete to support the translatability of their findings in flies. Current data only suggest that DMF and EDV are functional in iPSNs.

Reviewer #2

__Evidence, reproducibility and clarity (Required): __

the study of ALS uses almost exclusively drosophila larvae and adults and has a few expts with iNeurons (human) at the end. THe results are interesting and relevant to human disease and do suggest potential ways to treat disease. Not all the effect sizes are large, but nonetheless this is publishable material. More expts would of course strengthen their case. None of what I suggest is essential, but this depends in part on where they eventually want to publish their work.

__Some comments below: __

All are overexpression models with strong phenotypes. This has to be mentioned.

• The nature of the genetic models is clearly delineated in the manuscript. To highlight this further in the text, we have added comments at the start of the Results section stating that Drosophila do not have an orthologue of C9orf72, so we use previously established transgenic models (lines 372-376). In fact, it is incorrect to call these 'overexpression' models because there isn't a C9orf72 orthologue to be overexpressed. Formally, they are ectopic expression models.

Furthermore, in any ageing model every aspect of cell biology is affected.

• Agreed.

In fig 1E to the non-expert it is hard to work out what is a mitochondrion. Some higher res imaging might help.

• It is indeed difficult to discern individual mitochondria with this particular approach. We have a lot of experience in this kind of analysis and higher resolution imaging does not resolve the problem. The challenges with imaging mitochondria in such tiny cell bodies is the reason that we have adopted a categorical scoring system.

Line 390 comments on morphology but fig s1b-c is survival. Do they have morphology data? If not then they should rephrase the text

• This is a misunderstanding. The brief mention of mitochondrial morphology at the start of the paragraph ("Mitochondrial morphology is known to respond to changes in reactive oxygen species (ROS) levels as well as other physiological stimuli." - lines 414-415) is to provide as a segue from the preceding section describing the morphology defects to the following sections that investigate the possible mechanisms affecting this.

Line 441. Can they provide reference for 1000 being physiologically relevant? 36 is certainly pathological in humans. In my opinion the only genuinely physiologicall relevant model is a genetically faithful knockin without codon alteration.

• We have rephrased this to be 'more physiologically relevant repeat length' and provided a reference.

Line 482 - they say mitophagy is downstream, but isn't that obvious in a C9 transgenic model?

• We appreciate that this statement was confusing. We are referring to 'upstream' or 'downstream' in the cascade of events that ensuing from expression of DPRs, not upstream or downstream with respect to C9 mutations themselves, so we have rephrased this as "not a primary contributor to C9orf72 pathology" (lines 502-503).

7a. Line 502 - they indicate 'exploring the basis', but I am a little unclear what they are saying. What is the reason for the reduced SOD1 in x36 v x3 flies? Are they simply killing cells that have the most SOD1 and therefore their qPCRs/blots only represent those cells with less SOD1? There is still SOD1 being expressed there of course.

• Thanks for allowing us to clarify this point. We have not been able to clarify the mechanism for why Sod1 appears to be downregulated upon G4C2x36 expression, which we acknowledge is a limitation. So, we have decided to adjust the language from 'exploring the basis', to now simply report this as an associated observation (line 527).

7b. In the text it would help if they clarified if the genes overexpressed are human or fly. If human, it might be worth overexpressing mutant ALS SOD1 if they are able.

• In general, when reporting on experiments with a model organism such as Drosophila, we work on the assumption that genetic manipulations will typically be that of the host species, i.e., transgenic expression with be of Drosophila genes, unless specifically stated otherwise. In any case, all the necessary details of all genetic strains used in this study are laid out in Methods.

Line 521 - this para should perhaps be in intro section, not results.

• Agreed. We have now edited the start of this section (lines 543-546).

In Fig5, do they have CnnC IHC to back up their conclusion that keap1 mutation is affecting this process?

• Thank you for this suggestion. We have now analysed CncC localisation in C9 models {plus minus} Keap1 mutation. As before, we saw that G4C2x36 caused an increase in CncC nuclear localisation, although there was a trend towards an increase with Keap1 heterozygosity this was not consistent enough to be significant. These data are presented in new Fig. 5D, E and discussed in the text (lines 579-581). Although these results do not show an additional increase of nuclear CncC by this treatment of DMF, we also performed qRT-PCR analysis of CncC target genes GstD1, GstD2, Gclc and Cyp6a2,from flies treated with or without DMF. These data show that the degree of transcriptional activation was variable between different targets, but DMF treatment caused a general upregulation of CncC targets in G4C2x36 flies (new Fig. 6A).

The Induced neuron results are interesting. What kind of neurons are they? Have they been confirmed to be so with ICC? The figures in 6 are poor. They should make the point that correction of the mutation to ensure isogenicity would be an additional confirmatory measure. Isogenic lines are available from JAX and the UK MND Institute.

• Agreed. We now provide further characterisation of the iNeurons that was done at the time of the original experiments but not presented. These analyses include immunostaining with neuronal marker antibodies against β-III Tubulin, MAP2 and NeuN. These data are shown in new Supplementary Figure 3A, B. We also report the relative viability of these neurons at the point of analysis (new Supplementary Figure 3C, D). We have added mention of this in the text (lines 620-621 and 627-628). Of note, these patient cell lines have been used and reported before (Reference 53) which we cite on line 618. We also acknowledge the limitations of using these lines, and that future work would be better done with isogenic controls (lines 690-692) as the reviewer indicates.

Suppl fig 3 - interesting observation with edaravone, but do they have any survival/motility data in neurons/flies? Also, would be good to compare with another drug that works on a different mechamism E.g. riluzole.

• Since edaravone is a known therapeutic for ALS and was used as a comparator, rather than being the primary focus, we do not have additional data on edaravone.

Overall, the conclude they have done a comprehensive analysis of mito function, but I would argue that while a good analysis there are plenty of other studies they could have done e.g. assess mitochondrial respiratory chain.

• We agree that additional studies can always be envisaged.

13a. I also think the imaging of mitochondria could be better, and much work needs to be done on the iNeurons to characterise them.

• As mentioned above, we have provided additional characterisation of the iNeurons in this revision.

13b. Sentence line 674 - needs rephrasing.

• Thanks for prompting this. We have now rewritten these sentences (now lines 700-701).

In their final paragraph what do you they mean by oxidative stress being upstream? I would argue it is downstream of the C9 expansion, right?

• We apologise that this was confusingly written. As per the comment above (response to point 6), we were referring to events 'upstream' or 'downstream' in the cascade of events that ensuing from expression of DPRs. We have now rephrased this to be a "proximal" pathogenic mechanism (lines 708-710). We hope that our intended meaning is now clearer in the text.

__Significance (Required): __

A good study, modest degree of advancement in the field.

Reviewer #3

__Evidence, reproducibility and clarity (Required): __

In the present paper the authors focused on the hyper-production of ROS in a C9orf72 fly model. they the sought to rescue the observed fly phenotype by manipulating mitochondria dysfunctions or pathways downstream these dysfunctions.

__Majors: __

Given the wide varieties of statistical tests used a rationale should be given to why a certain test (one way anova) was used in one experiment (WB, qPCR) and another for another (Chi square) experiment (mitochondria morphology)

• In all cases, the choice of statistical test is dictated by the nature of the data being analysed - a principal that should be well-understood by all experienced researchers - and so may vary between experiments but will be consistent between different data sets of the same type of experiment. For instance, for those data sets consisting of two groups, an unpaired t-test would be appropriate. Most other experiments consist of three or more experimental groups and so will need an appropriate test with additional post-hoc test to correct for multiple comparisons, such as one-way ANOVA with Bonferroni's post-hoc correction. Where data sets are not normally distributed, such as generated by our climbing assay, a non-parametric analysis is required, such as the Kruskal-Wallis test. Here we also use a Dunn's post-hoc correction for multiple comparisons. In some assays of multiple groups, there are also multiple variables, such as the different drug concentrations tested on control and C9 iNeurons, a two-way ANOVA with an appropriate post-hoc correction test is used. Finally, some assays employ a categorical scored system, such as the mitochondrial morphology analysis, which will require a different type of statistical analysis such as Chi squared test.

      These types of analysis are in no way unusual or 'cherry-picked' to give the most desirable outcomes but are selected simply based on the type of the data to be analysed following standard rules of statistical analysis. For this reason, we do not feel that any more elaborate explanation is necessary in the manuscript text itself, but we hope that the explanation given here will satisfy the reviewer of the rationale for employing different statistical tests for different data sets.
  

The entire second part of the paper, and most important one to the authors (given the tile), rely mostly on a supposed loss in protection against antioxidant. I feel the experiment in support of this hypothesis are not strong. It is true that there is an overproduction of ROS (as evaluated in the first figures) but the loss in protection stated based on Fig 4H does not hold much. I think more experiment are needed to support this hypothesis.

• This is a fair comment and on reflection we also agree that our claim that the response to oxidative stress is blunted in the C9 models is based almost exclusively on the data from (old) Fig. 4H, and so is not strong. On reflection, prompted by the reviewer's comment, we have removed this interpretation from the manuscript and revised our comments accordingly. Consequently, we have also removed Fig. 4H.

Moreover, I counter intuitive that to rescue a phenotype the authors over expressed that is already high in C9orf72 flies (nrf). I would suggest to match this results with downregulation of nrf, to effectively proof that nrf decrease is detrimental to counteract ROS species in C9orf72 flies (further reducing protection against ROS). I believe this experiment is quite critical for the entire manuscript.

• We appreciate the thinking behind this suggestion, but this experiment can't be performed because loss of CncC function is lethal, as expected from a master regulator of a major cell-protection mechanism.

Also to me there is a little bit of disconnection between the first three figures and the last three. The authors also find a reuse effect over expressing SOD2 etc as shown in figure 3 where they actually show rescue in mitochondrial dysfunction (morphology etc). The only piece of data that shows rescue in mitochondrial dysfunction upon nrf over expression is figure 5H. More extensive characterization of mitochondrial dysfunction recur should be performed if the title want to kept focused on keep/nrf mechanism. Otherwise a broader title like "modulation of the mitochondria damage rescue C9orf72 phenotype." could help the reader understanding the overarching message of the paper

• We do not see a disconnect between the first part of the paper and the second. To be clear, the first part was documenting mitochondria-related defects (morphology, ROS, mitophagy) and determining their causative hierarchy and mechanistic impact on organismal phenotypes (we found only certain antioxidants rescued locomotor deficits and could reverse mitochondrial morphology and mitophagy defects). As stated, these results strongly implicated oxidative stress as a major driver in organismal pathology. The second part of the study was characterising whether a major antioxidant defence pathway (Keap1/Nrf2) could be manipulated to provide phenotypic rescue on the organismal scale (i.e., locomotor behaviours). On reflection of the original title, we agree that this was too focussed on the mitochondrial dysfunction angle (and also gave too much prominence to the iNeuron part of the study). Therefore, we have now modified the title to reflect a greater focus on oxidative stress and locomotor behaviours across the study. We hope this the reviewer feels that this better represents the study but will be happy to consider suggested alternatives.

__Minors: __

Figure 1n does each for represent a cell? or is an average of more cells and each dot represent an animal? I could not find this information anywhere, but if each dots is a single cells, I would recommend scaling up to at least 10 cells. Same concern for Figure 3F

We agree that this point needs clarification. Each dot represents data for one animal. The quantification per animal is based on at least 10 cells from one image. This has been added to the Methods section for clarification (lines 220-221).

Line 550-1-2 I do not agree with the statement. I do not think that the data shown that the protection against ross is less efficient. The only difference is the starting point. But the final point is the same so why should protection against ROS be less efficient in G4C2x36 drosophilas?

- This comment relates to point 2 above. As stated there, we agree that the data are not compelling enough to make this interpretation, so we have revised our comments accordingly.

There are some concerns about the neurons in figure 3: they do not appear to have axons and dendrites. I'd suggest containing with neuronal marker.

- The reviewer may be unfamiliar with the specific tissue in question; the larval ventral ganglion. As a complex, mature tissue there are multiple cell types (e.g., neurons and glia) very closely packed. Neuronal processes are very thin in this tissue, and they are squeezed between neighbouring cells. Thus, microscopy of neuronal cell biology within such a complex tissue does not look like in vitro cultured neurons. In the specific context of Figure 3, we are looking at markers for mitochondria or mitophagy. The reviewer may also be aware that mitochondria and mitolysosomes are most abundant in the cell bodies and have very limited abundance in neuronal processes. Thus, we do not generally try to observe these organelles in processes because there would be very little to see. We know that the signal is within neurons because the markers are transgenically expressed exclusively by a neuronal driver system i.e. nSyb-GAL4. In summary, there is no problem with how these cells or how they look. This is quite normal.

iNeurons were only used to confirm the second part of the paper. Would be interesting to also confirm some of the results in the first part, like SOD2 over expression etc etc.

• We appreciate this suggestion, which is similar to a comment from Reviewer 1, but, as replied above, time, personnel and resource constraints preclude additional investigations on this occasion. Just to reiterate, it is worth noting that the cell models were used specifically to validate that elevated mitochondrial oxidative stress and increased nuclear Nrf2 localisation also occurred in patient-derived neurons, and whether DMF treatment could reverse the oxidative stress. This was the extent to which the cell models were used in this instance and the current data are sufficient to support the conclusions made based on this. We regret that it was not possible to delve deeper into this at the current time but would be the focus of future work.

__Significance (Required): __

The present work while not extremely novel in the hypothesis, it is well performed with state-of-the-art techniques, some of them also very novel to the field. The concept of oxidative stress as an important in ALS pathogenesis is not new in the field, but the identification of Nrf as an important players might pave the way for more human related studies and possibly to therapeutic interventions.

I think the work is technically sounded and well performed; certain evidence are solidly demonstrated with multiple different techniques. other evidences instead need a little more work to prove their solidity to widen the audience which will appreciate the content of this paper.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

In the present paper the authors focused on the hyper-production of ROS in a C9orf72 fly model. they the sought to rescue the observed fly phenotype by manipulating mitochondria dysfunctions or pathways downstream these dysfunctions.

Majors:

• Given the wide varieties of statistical tests used a rationale should be given to why a certain test (one way anova) was used in one experiment (WB, qPCR) and another for another (Chi square) experiment (mitochondria morphology)
• The entire second part of the paper, and most important one to the authors (given the tile), rely mostly on a supposed loss in protection against antioxidant. I feel the experiment in support of this hypothesis are not strong. It is true that there is an overproduction of ROS (as evaluated in the first figures) but the loss in protection stated based on Fig 4H does not hold much. I think more experiment are needed to support this hypothesis.
• Moreover, I counter intuitive that to rescue a phenotype the authors over expressed that is already high in C9orf72 flies (nrf). I would suggest to match this results with downregulation of nrf, to effectively proof that nrf decrease is detrimental to counteract ROS species in C9orf72 flies (further reducing protection against ROS). I believe this experiment is quite critical for the entire manuscript.
• Also to me there is a little bit of disconnection between the first three figures and the last three. The authors also find a reuse effect over expressing SOD2 etc as shown in figure 3 where they actually show rescue in mitochondrial dysfunction (morphology etc). The only piece of data that shows rescue in mitochondrial dysfunction upon nrf over expression is figure 5H. More extensive characterization of mitochondrial dysfunction recur should be performed if the title want to kept focused on keep/nrf mechanism. Otherwise a broader title like "modulation of the mitochondria damage rescue C9orf72 phenotype." could help the reader understanding the overarching message of the paper

Minors:

• Figure 1n does each for represent a cell? or is an average of more cells and each dot represent an animal? I could not find this information anywhere, but if each dots is a single cells, I would recommend scaling up to at least 10 cells. Same concern for Figure 3F
• Line 550-1-2 I do not agree with the statement. I do not think that the data shown that the protection against ross is less efficient. The only difference is the starting point. But the final point is the same so why should protection against ROS be less efficient in G4C2x36 drosophilas?
• There are some concerns about the neurons in figure 3: they do not appear to have axons and dendrites. I'd suggest containing with neuronal marker.
• iNeurons were only used to confirm the second part of the paper. Would be interesting to also confirm some of the results in the first part, like SOD2 over expression etc etc.

Referees cross-commenting

I want to reinforce the comments of both my colleagues about the IPS model. I do not have further comments on their reviews.

Significance

The present work while not extremely novel in the hypothesis, it is well performed with state-of-the-art techniques, some of them also very novel to the field. The concept of oxidative stress as an important in ALS pathogenesis is not new in the field, but the identification of Nrf as an important players might pave the way for more human related studies and possibly to therapeutic interventions.

I think the work is technically sounded and well performed; certain evidence are solidly demonstrated with multiple different techniques. other evidences instead need a little more work to prove their solidity to widen the audience which will appreciate the content of this paper.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

the study of ALS uses almost exclusively drosophila larvae and adults and has a few expts with iNeurons (human) at the end. THe results are interesting and relevant to human disease and do suggest potential ways to treat disease. Not all the effect sizes are large, but nonetheless this is publishable material. More expts would of course strengthen their case. None of what I suggest is essential, but this depends in part on where they eventually want to publish their work

Some comments below:

All are overexpression models with strong phenotypes. This has to be mentioned. Furthermore, in any ageing model every aspect of cell biology is affected.

In fig 1E to the non-expert it is hard to work out what is a mitochondrion. Some higher res imaging might help.

Line 390 comments on morphology but fig s1b-c is survival. Do they have morphology data? If not then they should rephrase the text

Line 441. Can they provide reference for 1000 being physiologically relevant? 36 is certainly pathological in humans.In my opinion the only genuinely physiologicall relevant model is a genetically faithful knockin without codon alteration.

Line 482 - they say mitophagy is downstream, but isn't that obvious in a C9 transgenic model?

Lone 502 - they indicate 'exploring the basis', but I am a little unclear what they are saying. What is the reason for the reduced SOD1 in x36 v x3 flies? Are they simply killing cells that have the most SOD1 and therefore their qPCRs/blots only represent those cells with less SOD1? There is still SOD1 being expressed there of course. In the text it would help if they clarified if the genes overexpressed are human or fly. If human, it might be worth overexpressing mutant ALS SOD1 if they are able.

Line 521 - this para should perhaps be in intro section, not results.

In Fig5, do they have CnnC IHC to back up their conclusion that keap1 mutation is affecting this process?

The Induced neuron results are interesting. What kind of neurons are they? Have they been confirmed to be so with ICC? The figures in 6 are poor. They should make the point that correction of the mutation to ensure isogenicity would be an additional confirmatory measure. Isogenic lines are available from JAX and the UK MND Institute.

Suppl fig 3 - interesting observation with edaravone, but do they have any survival/motility data in neurons/flies? Also, would be good to compare with another drug that works on a different mech.... E.g. riluzole.

Overall, the conclude they have done a comprehensive analysis of mito function, but I would argue that while a good analysis there are plenty of other studies they could have done e.g. assess mitochondrial respiratory chain.

I also think the imaging of mitochondria could be better, and much work needs to be done on the iNeurons to characterise them. Sentence line 674 - needs rephrasing.

In their final paragraph what do you they mean by oxidative stress being upstream? I would argue it is downstream of the C9 expansion, right?

Significance

A good study, modest degree of advancement in the field.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Au et al. used two fly models to study how mitochondrial defects are implicated in C9ALS, the most common familial ALS type. They found that in these flies, mitochondrial, but not cytosolic, ROS is upregulated, accompanied by locomotion defects agreeing with previous publications. Consistent with these data, sod2, but not sod1, rescues the behavioral defects in these flies. Also, manipulating mitochondrial dynamics or mitophagy does not rescue these defects. Furthermore, the authors showed that the Nrf2 activity is upregulated, likely due to oxidative stress, and genetically or pharmacologically suppressing the Keap1 function, which activates Nrf2 and thereby its downstream antioxidative genes, suppresses behavior defects in these flies. This part is generally solid and convincing, with minor issues that need some revision. Finally, the authors showed that mitochondrial ROS and nuclear Nrf2 are both upregulated in C9 iPS neurons, both of which are suppressed by the Keap1 inhibitor DMF, or a known antioxidant. For this part, the data are convincing but insufficient to support a good translation of their fly data.

Major concerns:

1. The authors really need a phenotypic readout for their iPS experiments, either cell death or some sort of toxicity, to support the translatability of their fly data. The authors also need to test the toxicity of DMF in iPS neurons.
2. The authors should use genetic ways, e.g., knocking down Keap1, to activate Nrf2 and test whether this suppresses ROS and neurodegeneration phenotype in iPS neurons, as they did in flies.
3. They need to better characterize the Nrf2 activity in iPS neurons (see Minor Concern #1).

Minor concerns:

1. Fig 4A and B are hard to comprehend. Can the authors show images with more obvious differences? Also, Gst-D1 is the only Nrf2 downstream gene tested. Can the authors use RT-PCR to test multiple genes? These will strengthen the point that Nrf2 is activated. Similar things should be done in iPS neurons.
2. What about cytosolic ROS in C9 iPS neurons? Is it similar to the fly models?
3. Unless the authors confirm that mitochondrial dynamics or mitophagy are not contributing to neurodegeneration in iPS neurons, I wouldn't emphasize their related negative data in flies. Overall, the authors need to tone down their arguments if the findings are not verified in iPS or other mammalian models.
4. Can the authors measure the activities of OXPHOS complexes and ATP synthase/complex V?
5. Edavarone is one of the only two effective drugs for general ALS, and it's believed to work as an antioxidant. The authors should discuss it along with relating their findings to therapeutic development. Also, the discussion on SOD1 aggregation sounds somewhat farfetched. Plus, it's not directly related to the central message of this paper. I would remove it.

Significance

C9orf72-mediated ALS is the most common familial ALS type and also accounts for a fraction of sporadic ALS cases. Its pathomechanism is incompletely understood. Previous studies have linked mitochondrial defects and ROS to pathogenesis in fly, iPS, mouse, etc. models, and antioxidants can suppress some neurodegenerative features in these models. Consistent with these findings, one of the only two effective drugs for general ALS, edaravone, is believed to mitigate oxidative stress in motor neurons. Hence, oxidative stress is a critical pathogenic contributor that holds great potential as a therapeutic target. However, our understanding of its cause and consequence in ALS is limited. This paper includes at least two novel points: 1) identifying mitochondrial, but not cytosolic, ROS is upregulated and contributes to neurodegeneration in C9ALS models; 2) discovering that the Keap1/Nrf2 is altered and activating Nrf2 suppresses neurodegeneration. The first point presents an incremental advance in the field, but the second one is potentially critical, especially from a translational aspect. That being said, the novelty of the second point is somewhat dampened by a recently published paper (Jiménez-Villegas, et al. 2022), which showed that Nrf2/Keap1 is altered in C9 patient leukocytes and NSC cells overexpressing or treated with C9-DPRs. However, these cells/models are remotely related to the disease. The current manuscript still provided evidence in an in vivo neuronal model for the first time. If the authors could make their iPS part comprehensive, this could still be a major advance towards translation.

This paper could be interesting to a broad audience beyond the ALS field.

Another strength of this paper is that the fly analyses are comprehensive, the data are convincing, and the conclusions are solid. However, the major weakness is that the iPSN part is incomplete to support the translatability of their findings in flies. Current data only suggest that DMF and EDV are functional in iPSNs.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

1. Description of the planned revisions

Insert here a point-by-point reply that explains what revisions, additional experimentations and analyses are planned to address the points raised by the referees.

---

Reviewer 1:

Major comments (numbers correspond to the numbering made by the reviewer):

It is unclear what the TEM in Fig8 is trying to clarify. Since SMCs and elastic fibers are supposed to be bound, it would be better to show the binding site. In addition, the p-MLC in Fig8D-F is a qualitative evaluation, so the difference is not clear, and it is necessary to verify whether there is a difference in Myh11CreERT2;Loxfl/fl mice between aneurysmal (pathogenic) and non-aneurysmal lesions. Overall, this is an associated study that this only speculation since the causal relationship between aneurysm development and Lox functions, which authors found is unclear.

A: While no one has thus far carried out an in vivo deletion of LOX specifically in the smooth muscle cells to demonstrate that in a like manner to the BAPN treatment following its deletion aneurysms occur, the focus of this manuscript is to highlight the as yet undescribed intracellular cytoskeletal phenotypes in the LOX mutant smooth muscle cells and not the related ECM abnormalities. The TEM images in Figure 8 aim to show with high resolution the abnormal cytoskeleton and mitochondria in mice with a specific deletion of Lox in their SMC. Notably, these mice were not induced with AngII and therefore have not developed hypertension. Accordingly, they do not have any aneurysms yet they do display disrupted cytoskeleton and mitochondria within their aortic smooth muscle cells. As suggested by the reviewer, we will monitor SMC interaction with the elastic fibers using TEM. These findings will be presented.

With respect to phosphorylated Myosin Light Chain (p-MLC) - the analysis was carried out on 4 mice, and 6 sections from each mouse from non-aneurysmal regions. In this analysis we plotted the distribution of p-MLC expression which was calculated by quantifying 'intensity x area'. Statistical analysis of the distribution of the histograms (Kolmogorov Smirnov test) depicting p-MLC expression demonstrates they are significantly different (p=6.6E-16). In the mutant aortas, distribution is more dispersed and less organized. We have now elaborated on these findings within the text.

• *

In the discussion (lines 332-334), the Authors described that "Since TGFb signaling is implicated in aneurysm formation..." but the effect of TGFb signal in these Lox-deficient mice has not been examined at all. The effects of pSmad2/3 staining, Western, etc on TGFb activation should be examined and discussed.

A: We agree with the reviewer that we have not monitored TGFβ signaling throughout this manuscript however we and others have previously demonstrated that tight interactions take place between LOX and this signal transduction pathway in multiple processes, in health and disease including within the vasculature (e.g., Taylor MA et al., 2011 Lysyl oxidase contributes to mechanotransduction-mediated regulation of transforming growth factor-beta signaling in breast cancer cells. PMID: 21532881; Atsawasuwan P et al., 2008. Lysyl oxidase binds transforming growth factor-beta and regulates its signaling via amine oxidase activity. PMID: 18835815; Kutchuk L et al., 2015. Muscle composition is regulated by a lox-TGFβ feedback loop. PMID: 25715398; Xu XH et al., 2019. Downregulation of lysyl oxidase and lysyl oxidase-like protein 2 suppressed the migration and invasion of trophoblasts by activating the TGF-β/collagen pathway in preeclampsia. PMID: 30804321; Grunwald H et al., 2021. Lysyl oxidase interactions with transforming growth factor-β during angiogenesis are mediated by endothelin 1. PMID: 34370353). Notably, the effects of LOX on TGFβ signaling has not been the focus of this research and therefore we relate to it only in the Discussion, however as requested by the reviewer, we are now gearing up towards testing activation of the pathway is affected in the LOX mutant SMCs. Should we be unsuccessful we will tone down this statement.

• *

• *

Minor comments (numbers correspond to the numbering made by the reviewer):

---

1. What is the baseline group in Fig1A? and should be required a minimum 3 of animals in each group. A: The baseline for measuring blood pressure was Tamoxifen-treated Loxfl/fl. This was mentioned in the legend but not in the figure. We apologize for this. However since we only had 2 mice of this genotype, we *have replaced them with Myh11CreERT2; Loxfl/fl and have set additional mice that will be added that are Loxfl/fl. Essentially, all 'baseline' mice will have received tamoxifen yet have not been induced with AngII. A minimum of 4 animals per group will be in this figure. *

Reviewer 2:

Major comments (numbers correspond to the order written by the reviewer):

1. All three key conclusions are supported by data throughout the manuscript. However, the evidence is often based on data originating from western-blotting or immunofluorescent experiments and lack depth and rigidity. For example, figure 4 shows a change of cytoskeletal organization upon LOX KO in HAOSMCs but the authors lack to quantify or further analyse these exact differences in actin/tubulin organization. A: We thank the reviewer for stating that our conclusions are supported by data throughout the manuscript. As requested, we will analyze the organization of the cytoskeleton using image analyses software that enable dissecting linearity, number, length and angle of the cytoskeletal elements. We have already acquired the images and these analyses will be added to the manuscript upon their completion.

2. *

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

Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. If no revisions have been carried out yet, please leave this section empty.

• *

__Reviewer 1: __

Major comments (numbers correspond to the numbering by the reviewer):

1. The number of mice used and a number of experiments ("n" number) are not described in each figure or its legends in an overall experiment. Also, there is no information on the statistical analysis, which makes it impossible to judge the validity of the results. A: The minimal number of mice used per analysis in each experiment was 4 apart from the blood pressure measurements for which we have now increased the number (see reply to Minor comment 1 by this Reviewer). These numbers have either been added to the legends or throughout the text. We further added the numbers of cells quantified in the different experiments as well as the p value stemming from the statistical assays (T, Kolmogorov-Smirnov or ANOVA where appropriate).

The Phenotype of Lox-deficient mice is unclear; the picture in Fig1C is not clear and a high-magnified view should be provided. Also, which part (aortic arch or abdominal aorta?) is histologically analyzed? It should be described. In addition to the morphological analysis, it cannot be called "aneurysm" unless the internal diameter is enlarged more than 1.5 times compared to the control aorta. The histological images seem to show only dissection, which is unclear since statistical analysis is not feasible with only 2-3 animals.

A: The images shown in Figure 1C are now larger and of a better resolution so that the various deformities could be easily observed. With respect to the histological analyses - they were carried out on both the thoracic and abdominal aortic sections as reflected by the quantifications in Figure 1E-H. Specifically, the representative histological stainings shown in Figure 1D are of the abdominal regions and this is now mentioned in both the legend and figure. We thank the reviewer for correcting the mistake in our annotation and we have now replaced the images adding higher magnification of aneurysmal and non-pathological regions to demonstrate the relative normal ECM (elastic fibers and collagen) in the non-pathological regions of mutant aortas even though they were derived from hypertensive mice.

• *

Immunostaining in Figs. 4-6 should add nuclei (DAPI) to all experiments. It is unclear how many cells are being looked at. For example, in the staining of Fig4A, the stained nuclei are slightly visible in the shLox group, but not at all in the control above. Phenotypes should be compared under the same conditions. A: *All phenotypes were analyzed under the same conditions and were taken with DAPI. We have added DAPI to all images. As mentioned in comment #1, we have now added to the legends the number of cells analyzed in each experiment. *

• *

For ROCK and RhoA analysis (in Fig4-6), immunostaining and Western alone are not convincing and not sufficient evidence for activation. Other factors, such as methods to measure activation and focal adhesion molecules should be considered.

A: The analyses of ROCK and RhoA are shown in Figure 6. As suggested, we have quantified focal adhesion numbers and size by monitoring vinculin. Our findings demonstrate there are more focal adhesions that form in control cells than in the LOX-devoid ones and that in the latter, those that do form are significantly smaller. These results suggest that the adhesions that form in the mutant cells are weaker and less mature. We have added this data and it will now be presented as Supp. Figure 5. Therefore the previous Supp. Figures 5 and 6 will be shifted accordingly. We have related to these findings in the text.

*As mentioned above, we will use image analysis to quantify the alterations in the cytoskeletal elements such as those shown in Figure 4.

*

---

It is unclear what the TEM in Fig8 is trying to clarify. Since SMCs and elastic fibers are supposed to be bound, it would be better to show the binding site. In addition, the p-MLC in Fig8D-F is a qualitative evaluation, so the difference is not clear, and it is necessary to verify whether there is a difference in Myh11CreERT2;Loxfl/fl mice between aneurysmal (pathogenic) and non-aneurysmal lesions. Overall, this is an associated study that this only speculation since the causal relationship between aneurysm development and Lox functions, which authors found is unclear.

A: The first part of the comment refers to the TEM images. These have been addressed in the previous section (planned revision) and as mentioned, we will monitor the SMC binding sites to the elastic fibers. The comment raised by the reviewer on p-MLC was not clear to us. As mentioned, we primarily focused on the non-aneurysmal regions whether in AngII-induced hypertensive mice or in non-hypertensive mice as our results suggest that even in the lack of hypertension where no aneurysms develop, cytoskeletal organization is lost following the reduction of Lox activity. In the images shown in Figure 8 (and the associated quantifications) we focused on such regions from mice that were not treated with AngII. We find that even in what appears as a "healthy" region, disrupted p-MLC is observed. Notably, this disruption is not that the cells do not respond, but rather that the coordinated response is lost in the mutant mice. This lack of coordination is shown in the quantification where the two histograms depicting p-MLC expression have distinct distributions (Kolmogorov-Smirnov test p value=0). We have rephrased the relevant text in the manuscript.

Minor comments (numbers correspond to the numbering by the reviewer):

Please indicate scale bar in Fig1D, Fig2D, Fig3A-B, D-F, Fig4A-C, Fig5A-E, Fig8D-E.

A: We apologize for omitting the scale bars. They have now been added to all figures.

What the bars in the Fig2A-B graphs indicate? Information on the number of experiments and statistical analysis should be included in Figure or its legend.

A: *The bars in Figure 2A are qRT-PCR results of 3 independent biological samples showing expression of LOX family members in the HAOSMC. In Figure 2B, we set to monitor whether the expression of other member of the LOX family is modified in the shLOX cells. The graph shown the relative genes' expression in relation to shCtrl cells. The error bars in both Fig. 2A and B relate to the results of the 3 independent repeats the experiments were performed. As seen in Fig. 2A, the predominant member of the LOX family expressed in SMC is LOX. Further, the expression of other members of the family is not significantly changed in its loss (Fig. 2B). *

Similarly, Fig3C should include information on the number of analyzed cells and statics in the figure legend.

A: The data has been added.

5. What is the reason for separating Fig4F-G? It is not clear how many times the experiment was conducted. Fig1C, Fig6A-B, F-G should also describe the number of experiments and statistical analysis.

A: We have added all repeat numbers and statistical analysis to the legends. We are not clear as to the separation of Fig. 4F-G as there is no such figure. If the reviewer refers to Fig. 5 F-G, then we simply aimed to show that although the immunostaining results demonstrate that the two proteins are mislocalized, their levels are not affected in the LOX mutant cells.

Please describe the administration of treatment and concentration of drugs such as Calyculin A, in figure legend.

A: Drug concentrations have now been added to the figure legend. A more detailed description is available in the Methods section.

• *

Reviewer 2:

Major comments (numbers correspond to the order written by the reviewer):

• *

The authors state in the introduction "Our results therefore highlight a missing link between the three distinct gene groups associated with aneurysms, thus serving as a molecular paradigm for the development of phenotypes that culminate in aneurysm.", referring to the groups of genes in ECM structural proteins, members of the TGFb signaling pathway and genes involved in VSMC contractile apparatus. However, they do not provide data on the complex interplay between all of these groups and LOX. Therefore, the authors should add more nuance to this statement or change it altogether.

A: We agree with the reviewer that we have not shown any link between TGFβ signaling and LOX, even though these interactions have been previously demonstrated by us and others (see reply to Reviewer 1 comment #6). We are gearing up towards testing the TGFβ pathway also in the LOX devoid SMCs. Should we be unsuccessful, we will tone down this statement.

The authors have provided data on the phenotypic modulation with regards to expression of LOX and the contractile apparatus of VSMCs. However, to support the claim mentioned in the previous point, the authors should add experiments that show the relationship between LOX expression and specific genes involved in ECM structure and/or members of the TGFb family.

A: In a recent manuscript (Melamed et al., Cell Reports, 2023; PMID 37148241) we specifically focused on LOX and Fibronectin and we demonstrated that the LOX-devoid HAOSMC build an abnormal Fibronectin matrix which serves as a scaffold for ECM buildup. Along these lines, Supp. Figure 3A shows LC-MS/MS data of changes in ECM structural proteins' presence in the matrix of cells following LOX knockdown in cultured HAOSMC. As requested in the above comment, we are gearing up towards assessing TGFb signaling in the mutant cells.

In general, the authors provide a detailed description of the experimental setup in the methods section of the manuscript. However, the authors fail to provide methodology on some of their experiments. Per example, in text-line 152 the authors describe removing the cells from the ECM whilst leaving the ECM behind, but do not provide information on how this was done.

A: We thank the reviewer for the comment. We have added the details of the experiment.

The authors partially fail to provide n# for experiments throughout the manuscript and which statistical test was used for the comparisons in the figure.

A: We have now added to the figure legends all the n# and statistical tests that were used.

Minor comments (numbers correspond to the order written by the reviewer):

1. The authors make limited use of referring to appropriate literature. A: We have added additional relevant references.

2. *

The figures including images often lack scalebars. Moreover, the figure description is often incomplete. A: We thank the reviewer for the comment. As mentioned in the replies to Reviewer 1, we will add all the data and bars to the relevant figures.

Use Graphad Prism (or another well designed software) for figure illustration. A: *Graphs and histograms were generated using Matlab, excel and R and the figures were put together using Adobe Illustrator, all of which are designed for such illustrations. *

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

The paper of Rohtem Aviram and colleagues describes the "Coordination between cytoskeletal organization, cell contraction and extracellular development, which is depended on LOX for aneurysm prevention."

The manuscript examines the role of LOX, a collagen/elastin crosslinker, in its mechanism underlying aortic aneurysm, by using an myh11-positive cell inducible KO mouse model or in vitro VSMC culture. The authors confirmed a link between LOX activity and ECM remodeling in the aorta of hypertensive mice and reported a ECM-independent role of LOX in regulating VSMC cytoskeletal organization.

• Are the key conclusions convincing? The key conclusions of this manuscript are:
  • LOX plays a crucial role in regulating VSMCs cytoskeleton, affecting their contractile machinery and viability, independent of its ECM-modifying functions.
  • The study highlights an additional intracellular role for LOX in VSMCs, shedding light on its importance in maintaining aortic tissue integrity and preventing aneurysm formation.
  • LOX is implicated in various processes related to aneurysms, serving as a key player in the vasculature and its inhibition leading to ECM defects that promote thoracic aortic disease.

All three key conclusions are supported by data throughout the manuscript. However, the evidence is often based on data originating from western-blotting or immunofluorescent experiments and lack depth and rigidity. For example, figure 4 shows a change of cytoskeletal organization upon LOX KO in HAOSMCs but the authors lack to quantify or further analyse these exact differences in actin/tubulin organization. - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

The authors state in the introduction "Our results therefore highlight a missing link between the three distinct gene groups associated with aneurysms, thus serving as a molecular paradigm for the development of phenotypes that culminate in aneurysm.", referring to the groups of genes in ECM structural proteins, members of the TGFb signaling pathway and genes involved in VSMC contractile apparatus. However, they do not provide data on the complex interplay between all of these groups and LOX. Therefore, the authors should add more nuance to this statement or change it altogether. - Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.

The authors have provided data on the phenotypic modulation with regards to expression of LOX and the contractile apparatus of VSMCs. However, to support the claim mentioned in the previous point, the authors should add experiments that show the relationship between LOX expression and specific genes involved in ECM structure and/or members of the TGFb family. - Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

Yes, the experiments can be formed using the same VSMCs already used in the manuscript and protein- and/or gene expression can be determined by the same methods already used throughout the manuscript. - Are the data and the methods presented in such a way that they can be reproduced?

In general, the authors provide a detailed description of the experimental setup in the methods section of the manuscript. However, the authors fail to provide methodology on some of their experiments. Per example, in text-line 152 the authors describe removing the cells from the ECM whilst leaving the ECM behind, but do not provide information on how this was done. - Are the experiments adequately replicated and statistical analysis adequate?

The authors partially fail to provide n# for experiments throughout the manuscript and which statistical test was used for the comparisons in the figure.

Minor comments:

• Specific experimental issues that are easily addressable.

See major comments - Are prior studies referenced appropriately?

The authors make limited use of referring to appropriate literature. - Are the text and figures clear and accurate?

The figures including images often lack scalebars. Moreover, the figure description is often incomplete. - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

Use Graphad Prism (or another well designed software) for figure illustration.

Significance

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.

This manuscript brings forward a basic conceptual advantage with regards to the relationship between LOX expression in VSCMs and aortic aneurysm formation. - Place the work in the context of the existing literature (provide references, where appropriate).

Current literature mainly focusses on the role of LOX in ECM-oriented remodeling, this manuscript shows that LOX also plays a role in VSMC phenotypic alterations regardless of its ECM-altering role. - State what audience might be interested in and influenced by the reported findings.

Basic scientist with an interest in aneurysm or VSMC remodeling. - Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Summary:

Dr. Aviram et al investigate the deletion of Lysyl oxidase (LOX) in vascular smooth muscle cells SMCs) leading to aortic aneurysm development. The authors performed in vito assay using primary SMCs and found that cytoskeletal organization and extracellular matrix (ECM) assembly are lost in Lox-deleted SMCs independent of Lox activity manner. The authors concluded that the novel intracellular function of Lox contributes to aortic aneurysm formation. The strength of this study is that it attempts to explain the underlying principle of aortic aneurysm development due to Lox deficiency using a cultured cell-based system, however, it lacks reliability of data due to insufficient technical problems in several experiments. In particular, the causal relationship between the discovered Lox function and the development of aortic aneurysms is unclear and remains a matter of conjecture. My comments are following.

Major comments:

1. The number of mice used and a number of experiments ("n" number) are not described in each figure or its legends in an overall experiment. Also, there is no information on the statistical analysis, which makes it impossible to judge the validity of the results.
2. The Phenotype of Lox-deficient mice is unclear; the picture in Fig1C is not clear and a high-magnified view should be provided. Also, which part (aortic arch or abdominal aorta?) is histologically analyzed? It should be described. In addition to the morphological analysis, it cannot be called "aneurysm" unless the internal diameter is enlarged more than 1.5 times compared to the control aorta. The histological images seem to show only dissection, which is unclear since statistical analysis is not feasible with only 2-3 animals.
3. Immunostaining in Figs. 4-6 should add nuclei (DAPI) to all experiments. It is unclear how many cells are being looked at. For example, in the staining of Fig4A, the stained nuclei are slightly visible in the shLox group, but not at all in the control above. Phenotypes should be compared under the same conditions.
4. For ROCK and RhoA analysis (in Fig4-6), immunostaining and Western alone are not convincing and not sufficient evidence for activation. Other factors, such as methods to measure activation and focal adhesion molecules should be considered.
5. It is unclear what the TEM in Fig8 is trying to clarify. Since SMCs and elastic fibers are supposed to be bound, it would be better to show the binding site. In addition, the p-MLC in Fig8D-F is a qualitative evaluation, so the difference is not clear, and it is necessary to verify whether there is a difference in Myh11CreERT2;Loxfl/fl mice between aneurysmal (pathogenic) and non-aneurysmal lesions. Overall, this is an associated study that this only speculation since the causal relationship between aneurysm development and Lox functions, which authors found is unclear.
6. In the discussion (lines 332-334), the Authors described that "Since TGFb signaling is implicated in aneurysm formation..." but the effect of TGFb signal in these Lox-deficient mice has not been examined at all. The effects of pSmad2/3 staining, Western, etc on TGFb activation should be examined and discussed.

Minor comments:

1. What is the baseline group in Fig1A? and should be required a minimum 3 of animals in each group.
2. Please indicate scale bar in Fig1D, Fig2D, Fig3A-B, D-F, Fig4A-C, Fig5A-E, Fig8D-E.
3. What the bars in the Fig2A-B graphs indicate? Information on the number of experiments and statistical analysis should be included in Figure or its legend.
4. Similarly, Fig3C should include information on the number of analyzed cells and statics in the figure legend.
5. What is the reason for separating Fig4F-G? It is not clear how many times the experiment was conducted. Fig1C, Fig6A-B, F-G should also describe the number of experiments and statistical analysis.
6. Please describe the administration of treatment and concentration of drugs such as Calyculin A, in figure legend.
7. Please show the data "shLox cell death (not shown)" in text, line 248.

Significance

While many studies have shown that the enzymatic activity of Lox is important for aneurysm formation, the focus on intracellular functions such as cytoskeleton remodeling, other than enzymatic activity is a novel point. However, the study is limited to speculation due to insufficient phenotypic analysis of aneurysms and the number of animals, as well as the inability to clearly prove a causal relationship. Revisions are needed to add significant additional data and to conduct more accurate analyses.

Transparent Peer Review

---

Download the complete Review Process [PDF] including:

• reviews
• authors' reply
• editorial decisions

</br>

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

Dear editor and reviewers,

we thank you very much for your constructive comments, criticisms and suggestions for improvement of our manuscript. We have addressed all points raised by you and have added our point-by-point response to your comments below.

With best regards on behalf of all authors,

Andreas Wodarz

1. Point-by-point description of the revisions

Reviewer #1

Evidence, reproducibility and clarity

Baz/Par3 is an important conserved protein acting as a master regulator of cell polarity in a wide range of cell types. This study focuses on re-assessing the subcellular localisation of Baz/Par3 in a range of Drosophila tissues. This is an important study with respect to our understanding of Baz/Par3, as there have been conflicting reports on the localisation of Par complex members - while the majority show localisation to cell cortex and intercellular junctions, several reports have claimed that Par complex members localise at additional subcellular sites including the nucleus, nuclear envelope and neuromuscular junction. In this study the authors re-assess this issue for Baz/Par3 in a comprehensive and thorough manner.

We thank the reviewer for this overall positive assessment of our work.

*1. They used a variety of antibodies raised in different host animals against different epitopes of Baz 2. They tested the specificity of these antisera using mosaic analysis with null mutant baz alleles and tissue-specific RNAi against baz 3. They used a GFP-tagged Baz under control of its endogenous promoter in a baz null mutant background to compare with the subcellular localisation of the respective GFP-Baz fusion proteins to the staining results with anti-Baz antisera

The data from each of these experiments are very clear and convincing. Comprehensive methods are included which means that each of the experiments with specific anti-sera/RNAi lines/GFP-tagged conditions could be reproduced. There are a couple of experiments which were performed in support of the conclusions (extra RNAi lines and stronger expression of Gal4) listed as (data not shown). I would strongly suggest including these data as extra supplemental figures. Together, their results clearly show that Baz/Par3 localises to the cortex and intercellular junctions, but that anti-sera staining at the NMJs and nuclear envelope appear to be a staining artifact, likely due to staining with an unidentified epitope.

Minor comments 1. Many of the figures have overlays of red and green which will be indistinguishable from each other to colour-blind readers. Please alter to make colour-blind friendly (eg magenta-green)*

We have changed all figures in the following way: All single channel images have been converted to inverted grayscale to improve the visibility of weak fluorescence signals. In all multicolor overlay images, red has been omitted and instead green, magenta, blue and grayscale have been used to improve the visibility for color-blind readers.

2. In Fig 2D please indicate where the epidermis and neuroblasts are

We assume that the reviewer refers to Fig. S2D. In the revised version of the manuscript, this figure is now Fig. S2A. We have marked epidermal cells and neuroblasts by different symbols.

*3. In the following two places there are experiments describe where the data is listed as not shown. Please show the data as additional supplemental data. They are P8 - This result was confirmed using the CY2::Gal4 driver line expressed in the follicular epithelium and with three different RNAi lines against baz (data not shown). *

We have deleted this sentence because expression of CY2::Gal4 in our hands was weaker and thus the RNAi effects less reproducible than with tj::Gal4.

P11 - We also did not see any downregulation of Baz or a-spectrin upon baz-RNAi in M12 at 29°C, when the UAS-Gal4 system is maximally active (data not shown).

We now show these results in the new Fig. S8.

4. Figure 3 - this would be easier to interpret with a few arrows/arrowheads indicating the NMJs

We have added arrows pointing to NMJs and arrowheads pointing to nuclei.

---

Significance

It will be important to publish these results as it means that findings for a function of Baz/Par3 at the NJM and the nuclear envelope should be regarded with caution, and it may save researchers chasing for functions for Baz/Par3 in places where they are simply not expressed. As much of our fundamental understanding of how Par3 works in vertebrates has its roots in studies in Drosophila, this is likely to be of wide relevance.

---

Reviewer #2

Evidence, reproducibility and clarity

*Evidence, reproducibility and clarity

1.1 Summary

This reviewer acknowledges the expertise and contributions of Prof. Wodarz and his research group in the field of development, cell polarity regulation and Drosophila genetics.

---

Manuscript summary:

Kim S. et al. explored the localisation of Bazooka, the Drosophila homolog of the polarity protein Par-3, at two non-canonical positions for a cell polarity factor: the nuclear envelope in epithelial tissues and the postsynaptic membrane of the neuromuscular junction (NMJ). Previous work has shown the detection of Par-3/Baz at the nuclear envelope and the NMJ using antibodies against Par-3/Baz. Here, the authors used a combination of genetic perturbations (baz RNAi and generation of genetic mosaics for baz) and GFP-labelled Bazooka lines to test if the antibody-mediated detection of Baz at the nuclear envelope and NMJ is artifactual. The data provided by the authors strongly suggest both the nuclear envelope and NMJ detection of Baz using antibodies is non-specific.

1.2 Major comments

The manuscript is written in a clear manner, easy to be followed by readers. However, there are some important experimental details that should be provided as the authors advance over previous work regarding Baz localization (points 1.2.1 and 1.2.2). Furthermore, if possible, this reviewer considers that performing the experiment in 1.2.3 would strengthen the authors main message of their manuscript.

1.2.1 Methodology information is missing, and would be necessary to be included for: image acquisition (Objectives, Airyscan mode), image processing (projections, details on linear -e.g. brightness, contrast- or non-linear adjustments of signal -e.g. gamma-). For image processing information, please include it within each figure legend. *

We have added the information regarding objectives and imaging modes to the Materials and Methods section. There it now reads: "Tissues were imaged on a Zeiss LSM880 Airyscan confocal microscope using 25x LCI Plan Neofluar NA 0.8 and 63x Plan Apochromat NA 1.4 oil immersion objectives. If not stated otherwise in the figure legend, all confocal images are single optical sections taken at a pinhole setting of 1 Airy unit. Images were processed with Zen black software (Zeiss) without contrast enhancement. Figures were assembled with Inkscape 1.2 (Inkscape.org) and Powerpoint (Microsoft)."

RNAi experiments lines, temperature for each target and tissue (a table would be helpful) and number of heat shocks performed for FRT/FLP clones.

We have added a table in the Supplementary information giving the precise genotypes for each figure. We have furthermore added the following sentences to the Materials and Methods section: "Crossings for RNAi experiments were set up at 25°C if not indicated otherwise. For generating follicle cell clones in ovaries by Flipase-mediated mitotic recombination of the FRT sites flies were heat shocked for 1h at 37°C 5-7 days prior to preparation of the ovaries. For generation of germ line clones by Flipase-mediated mitotic recombination of the FRT sites flies were heat shocked twice for 2 h at 37°C on two consecutive days in late 2nd, early 3rd instar larval stages."

1.2.2 For each experiment it is unclear the number of specimens (experimental units) and independent experiments that were analysed. It is unclear if the Baz localisation phenotypes are fully penetrant or not as judged by the data provided.

We have added the following section to the Materials and Methods: "Images were analyzed for the presence or absence of a fluorescence signal at the nuclear envelope or the NMJ compared to negative or positive controls, either in the same tissue (mutant clones in the follicular epithelium, RNAi in a specific body wall muscle, junctional versus nuclear signal, anti-Baz staining versus Baz-GFP signal) or in samples processed in parallel (ovaries with follicle cell and germ line clones). Fluorescence intensities were not quantified because the results were obvious and fully penetrant. Therefore, no statistical analysis of the results was required."

1.2.3 This reviewer agrees the data provided strongly suggests the detection of Baz along the nuclear envelope and NMJ is artifactual in the Drosophila tissues that have been studied. However, the nature of the bazEH747 mutant allele is not a deletion of the Baz gene, but instead a nonsense mutation, which, as the authors describe, could potentially generate a small product of 51 aminoacids, corresponding to the N-terminal part of Baz, which is also the target of Baz rabbit antibody ('rb Baz 1-297'). Thus: • Would it be possible to complement the FRT/FLP analyses in the FE using a deficiency that uncovers the baz locus? A persistent detection of Baz signal at the nuclear compartment after complete removal of baz gene products would be an ideal experiment, if feasible.

We agree with the reviewer that the use of a clean deletion allele of the whole baz locus would be the ideal tool for the clonal analysis. However, such an allele does not exist according to our knowledge.

• • Would the authors comment on the possibility the rb Baz antibody 1-297 detect a 51 aminoacids peptide? We consider this possibility very unlikely for two reasons: 1) RNAi affects the baz mRNA and thus should knock down all epitopes to the same degree. However, we see a complete loss of junctional Baz signal but no reduction of the signal at the nuclear envelope or the NMJ upon RNAi targeting baz. 2) The GFP-Baz fusion proteins do not show any signal at the NMJ or the nuclear envelope upon imaging of the native GFP fluorescence or upon antibody staining with an anti GFP antibody, although both the Baz-GFP BAC line and the GFP-Baz protein trap line express full-length Baz including the N-terminal epitope that is potentially still expressed in the bazEH747* allele. We have added a passage summarizing these considerations to the Discussion section.

*1.3 Minor comments

This manuscript is largely based on imaging data. Therefore, it would be beneficial for the ease of comprehension of figure panels:

1.3.1 More general use of insets to show with larger magnification and clarity the data indicated with arrows and arrowheads.*

We have added arrowheads, arrows and additional symbols to point to features of interest in all figure panels where this is helpful.

1.3.2 Using negative grayscale either for insets or single channel data.

We have changed all single channel image panels to negative (inverted) grayscale.

1.3.3 For coloured-overlays please bear in mind using colors that would be suitable for colour-blinded readers.

In all multicolor overlay images, red has been omitted and instead green, magenta, blue and grayscale have been used to improve the visibility for color-blind readers.

1.3.4 Figures showcasing the clonal analyses (both MARCM and FRT/FLP): might be worth indicating the boundaries of clones in single channel data with a dotted line.

We have marked the clone boundaries of the MARCM clones by dashed lines in Fig. 2D, E and have added a high magnification inset to show the clone boundaries (Fig. 2D', E').

Significance

*2 Significance

The findings provided by this manuscript will be of importance for researchers in the field of cell polarity, conducting research on Bazooka/Par-3 and associated proteins, both within the Drosophila field and other model organisms. The present study presents an advance towards a specific and most likely artifactual observation of Par-3/Bazooka. It will help to re-think the tools used for detecting Par-3/Bazooka in different animal models, and in this regard, will be helpful for the community.*

We thank the reviewer for appreciating the importance of this work.

*This work does not focus on Par-3/Bazooka biology, nor provides new insights into Par-3/Bazooka function, however, it is clear for this reviewer the later is not the aim of this manuscript.

Reviewer expertise:

• Drosophila genetics
• Developmental cell biology and morphogenesis
• Cytoskeleton, cell cell adhesion and cell polarity*

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

__Kim et al. address a common but frequently neglected problem in molecular and cellular biology: sophisticated tests for the specificity of antibodies. The protein Bazooka (Baz) is a member of the Par complex that usually resides in apicocortical regions of epithelial cells. Several publications, however, report expression in other subcellular compartments or cell types, such as the nuclear lamina or neuromuscular junction (NMJ). The authors have used a panel of polyclonal antibodies, genetic constructs and mutant alleles to show that staining of Baz in the nuclear envelope or NMJ is likely unspecific due to an unknown cross-reactivity. Specifically, four antisera, raised against different GST-Baz fusion proteins in different species, recognized Baz at cortical membranes, around nuclei and at NMJs. Nuclear and NMJ staining, however, persisted in baz-RNAi experiments or baz mutant clones. If the endogenous locus is tagged with GFP, Baz-GFP localized to cortical membranes in imaginal disc epithelial cells but was but not detectable in nuclear envelopes or NMJs in muscles. The authors conclude that they could not find evidence for either nuclear or NMJ localization of Baz and any results derived from these antibodies should be regarded with caution.

The manuscript reports a careful and thorough evaluation of anti-Baz antibodies used in the scientific community. Since it might impact previous findings, any remaining uncertainties should be clarified before publication. I have therefore a number of suggestions to improve the manuscript.

Major comments:

1) Any truncation or addition of amino acids might affect the subcellular localization of proteins. Important molecular information on the baz alleles and GFP-fusion proteins are therefore missing in the manuscript. Specifically, what is the underlying molecular nature of the baz alleles used in the study, e.g. bazEH747 (nonsense? position?)? At which amino acid position and in which protein domain is GFP fused to Baz in Baz-GFP (Bac) and Baz-GFP (Trap)? Would these fusions affect subcellular localization and/or functionality? While the authors positively tested Baz-GFP (Bac) in a baz mutant background, this cannot easily be done for Baz-GFP (Trap). The authors should therefore clarify, e.g. by RT-PCR, which of the four Baz isoforms are fused to GFP in Baz-GFP (Trap) and if this might affect functionality and/or location? This information should be depicted or listed together with the epitopes of the antibodies in a figure or table, respectively, in the main manuscript for better orientation of the reader. *

bazEH747 is a strong loss-of-function allele with a point mutation changing the codon for Q51 to Stop in all four isoforms (numbering is according to isoform A) (Krahn et al., 2010; Shahab et al., 2015). In the Results section, we have changed the wording as follows to make this clear: "For clonal analysis the strong loss-of-function allele bazEH747 was used, where a point mutation in exon 4 results in a premature stop close to the N-terminus of all four isoforms (the codon for amino acid residue Q51 is mutated to a stop in isoform A) (Krahn et al., 2010)."

We have added two additional supplemental figures to precisely show the insertion site of GFP in the GFP-Baz trap line (Fig. S5) and the Baz-GFP BAC line (Fig. S6). We have changed the Results section to precisely explain the nature of the two Baz-GFP lines as follows: "While strong nuclear envelope immunostaining was observed using several independently raised anti Baz antibodies (Fig. 1; Fig. S1), no nuclear envelope localization was detected in follicular epithelial cells and in larval body wall muscles using a Baz-GFP BAC line (Besson et al., 2015) (Fig. S3C-D', S4A, A') nor in a GFP-Baz protein-trap line (Buszczak et al., 2007)(Fig. S3E-F', S4C, C'). In the GFP-Baz protein-trap line an engineered exon encoding for GFP is inserted into the second untranslated exon (Fig. S5). This exon encoding for GFP is predicted to be spliced in frame into the mRNAs RA and RC encoding for isoforms PA and PC whose translation starts in exon 1 (Fig. S5), resulting in insertion of GFP between amino acid residues K40 and P41 of isoforms PA and PC. The transcripts RB and RD encoding Baz isoforms PB and PD have their translation start within exon 3 and thus cannot form fusion proteins with GFP inserted in exon 2 (Fig. S5). However, GFP-Baz protein trap flies are homozygous viable and are phenotypically indistinguishable from wild type flies, indicating that the corresponding GFP fusion protein is fully functional and faithfully reflects the expression pattern and subcellular localization of Baz isoforms PA and PC. The BAC line integrates the GFP within exon 10 between amino acid residues L1424 and Q1425 of isoform PA, giving rise to GFP fusion proteins for all four isoforms (Fig. S6) (Besson et al., 2015). Like the protein-trap GFP-Baz fusion protein, the Baz-GFP fusion protein in the BAC line is fully functional as it completely rescued lethality and fertility of the bazEH747 allele (Fig. S7D-D') and the baz815-8 allele (Besson et al., 2015)."

*2) Figure 3D-G: The images for Baz-GFP nicely show that GFP is expressed in imaginal discs but not at NMJs. However, when brightness of Fig. 3D' and 3F' is increased nuclear envelopes, tracheal branches and some synaptic boutons are clearly visible in the Baz-GFP channels. These are likely background signals due to the staining procedure, but to avoid any confusion, images showing unstained (native) GFP fluorescence should be included to proof that there are no residual signals. GFP fluorescence survives formaldehyde fixation and many GFP exon traps are clearly visible even in the absence of immunofluorescent stainings. Furthermore, Fig. 3G appears vastly different compared to Fig. 3E and Baz localization at cell-cell junctions cannot be recognized by people unfamiliar with imaginal discs. The images in Fig. 3G are therefore not suitable and should be replaced. *

We have added the new Fig. S4 showing the GFP signal without antibody staining of somatic body wall muscles and wing imaginal discs of larvae expressing the Baz-GFP BAC and GFP-Baz trap transgenes. We have also replaced Fig. 3G with images that can easily be compared with the images in Fig. 3E. The following paragraph was added to the Results section: "These findings were confirmed by analysis of fixed larval tissues that were imaged for GFP fluorescence without anti GFP antibody staining (Fig. S4). Neither in the Baz-GFP BAC line (Fig. S4A, A'), nor in the GFP-Baz trap line (Fig. S4C, C') any nuclear envelope or NMJ signal was detectable in somatic muscles, whereas junctional signal in wing imaginal discs was readily detectable in both lines (Fig. S4B, D)."

*3) The argument that baz4 and baz815-8 carry second site mutations is not fully convincing (page 10, 13). Why should two independent baz alleles carry an additional hit that affect Spectrin levels? Other explanations might be possible. While downregulation of Baz in muscles by RNAi is a good approach to tackle the question of Spectrin localization and expression levels, RNAi itself has its own uncertainties. Why not showing the effect on Spectrin levels or the lack of Baz at the NMJ (or the nuclear envelopes) in "clean" baz null embryos or larvae (e.g. bazEH747/Df)? NMJs can be stained in late stage embryos or compound heterozygous null mutants quite frequently survive until larval stages. *

We do not have a good explanation for the published reduction of Baz and a-Spectrin signal at the NMJ in larvae heterozygous for the baz alleles baz4 and baz815-8 (Ruiz-Canada et al., 2004; Ramachandran et al., 2009), as our analysis shows that Baz is not expressed there, rendering the reported phenotypes very difficult to explain. It is beyond the scope of our paper to proof that the data published by Ruiz-Canada et al. (2004) and Ramachandran et al. (2009) are indeed reproducible. Our speculation that second site hits on these two mutant chromosomes may have caused the published effects is just based on our own published observation that commonly used chromosomes with these two mutant baz alleles have stronger phenotypes than a clean baz loss-of-function allele (Shahab et al., 2015). We have changed the wording of the corresponding paragraph as follows: "It has been published that heterozygous baz4 mutant larvae show a significant decrease in immunofluorescence signal of Baz and also of Spectrin at the NMJ (Ruiz-Canada et al., 2004). Another publication showed a significant decrease in Baz and Spectrin immunostaining at the NMJ of larvae heterozygous for the baz815-8 allele (Ramachandran et al., 2009). We did not attempt to reproduce these findings. However, in our hands mitotic clones generated with FRT chromosomes carrying these latter two baz alleles showed polarity phenotypes in the follicular epithelium, whereas clones of the clean bazEH747 null allele did not show any polarity defect (Shahab et al., 2015), raising the possibility that the NMJ phenotypes observed by Ruiz-Canada et al. (2004) and Ramachandran et al. (2009) were caused by second site mutations on these chromosomes rather than by reduced Baz activity.

bazEH747 hemizygous mutant embryos are so abnormal and malformed at late embryonic stages that we did not attempt to stain these for Baz immunoreactivity at NMJs.

4) It is not really made clear in the manuscript, why the additional reactivity of the anti-Baz antibodies has not been noticed earlier. The paper should therefore include a summarizing paragraph that describes how the specificities of the antibodies have been tested in the past in the laboratories that used them. Have they never been tested in null mutant animals? In null mutants it should be obvious to determine, if some staining patterns do not disappear.

The vast majority of publications on Baz including those from our own laboratory focused on the functions of Baz at junctions and in the control of cell polarity. For these functions the cortical localization of Baz is relevant, which has been shown to be specific in many independent studies using null alleles and RNAi. Only few publications, in particular those from the laboratory of Vivian Budnik, have focused on potential functions of Baz at the NMJ and the nuclear envelope. Why in these studies no convincing proof of the specificity of the signal at those "unconventional" locations has been provided is beyond our knowledge.

5) Figure 4 is very difficult to comprehend and should be better labeled (e.g. anterior-posterior, dorsal-ventral, muscle fibers, unspecific signals). It is standard in the field to show ventral muscles 12, 13 or 6, 7 in the center of the image and in a similar orientation (anterior left, dorsal up). Better images should be shown.

We understand that for researchers interested in the function of specific muscles it is important to adhere to conventions regarding the orientation of muscles in figures. However, in our case it is just relevant whether a muscle expresses RNAi against a gene of interest (GFP+) or not (GFP-) in order to compare the signal intensity for Baz and Spectrin in these two situations. Thus, although we appreciate the validity of this comment, we decided to leave the original images unchanged. However, to help the reader in identifying relevant structures more easily, we have added color-coded arrows and arrowheads to mark NMJs and nuclear envelopes in GFP+ and GFP- muscles.

*Reviewer #3 (Significance (Required)):

The authors provide a critical assessment on the specificity of antibodies and highlight the necessity to carefully test antibodies and the conclusions drawn from the resulting stainings, especially when antibodies are bought from companies or have previously been published as specific. This is extremely important for the interpretation of experiments in all fields of molecular and cellular biology. *

We thank the reviewer for appreciating the importance of this work.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Kim et al. address a common but frequently neglected problem in molecular and cellular biology: sophisticated tests for the specificity of antibodies. The protein Bazooka (Baz) is a member of the Par complex that usually resides in apicocortical regions of epithelial cells. Several publications, however, report expression in other subcellular compartments or cell types, such as the nuclear lamina or neuromuscular junction (NMJ). The authors have used a panel of polyclonal antibodies, genetic constructs and mutant alleles to show that staining of Baz in the nuclear envelope or NMJ is likely unspecific due to an unknown cross-reactivity. Specifically, four antisera, raised against different GST-Baz fusion proteins in different species, recognized Baz at cortical membranes, around nuclei and at NMJs. Nuclear and NMJ staining, however, persisted in baz-RNAi experiments or baz mutant clones. If the endogenous locus is tagged with GFP, Baz-GFP localized to cortical membranes in imaginal disc epithelial cells but was but not detectable in nuclear envelopes or NMJs in muscles. The authors conclude that they could not find evidence for either nuclear or NMJ localization of Baz and any results derived from these antibodies should be regarded with caution.

The manuscript reports a careful and thorough evaluation of anti-Baz antibodies used in the scientific community. Since it might impact previous findings, any remaining uncertainties should be clarified before publication. I have therefore a number of suggestions to improve the manuscript.

Major comments:

1. Any truncation or addition of amino acids might affect the subcellular localization of proteins. Important molecular information on the baz alleles and GFP-fusion proteins are therefore missing in the manuscript. Specifically, what is the underlying molecular nature of the baz alleles used in the study, e.g. bazEH747 (nonsense? position?)? At which amino acid position and in which protein domain is GFP fused to Baz in Baz-GFP (Bac) and Baz-GFP (Trap)? Would these fusions affect subcellular localization and/or functionality? While the authors positively tested Baz-GFP (Bac) in a baz mutant background, this cannot easily be done for Baz-GFP (Trap). The authors should therefore clarify, e.g. by RT-PCR, which of the four Baz isoforms are fused to GFP in Baz-GFP (Trap) and if this might affect functionality and/or location? This information should be depicted or listed together with the epitopes of the antibodies in a figure or table, respectively, in the main manuscript for better orientation of the reader.
2. Figure 3D-G: The images for Baz-GFP nicely show that GFP is expressed in imaginal discs but not at NMJs. However, when brightness of Fig. 3D' and 3F' is increased nuclear envelopes, tracheal branches and some synaptic boutons are clearly visible in the Baz-GFP channels. These are likely background signals due to the staining procedure, but to avoid any confusion, images showing unstained (native) GFP fluorescence should be included to proof that there are no residual signals. GFP fluorescence survives formaldehyde fixation and many GFP exon traps are clearly visible even in the absence of immunofluorescent stainings. Furthermore, Fig. 3G appears vastly different compared to Fig. 3E and Baz localization at cell-cell junctions cannot be recognized by people unfamiliar with imaginal discs. The images in Fig. 3G are therefore not suitable and should be replaced.
3. The argument that baz4 and baz815-8 carry second site mutations is not fully convincing (page 10, 13). Why should two independent baz alleles carry an additional hit that affect Spectrin levels? Other explanations might be possible. While downregulation of Baz in muscles by RNAi is a good approach to tackle the question of Spectrin localization and expression levels, RNAi itself has its own uncertainties. Why not showing the effect on Spectrin levels or the lack of Baz at the NMJ (or the nuclear envelopes) in "clean" baz null embryos or larvae (e.g. bazEH747/Df)? NMJs can be stained in late stage embryos or compound heterozygous null mutants quite frequently survive until larval stages.
4. It is not really made clear in the manuscript, why the additional reactivity of the anti-Baz antibodies has not been noticed earlier. The paper should therefore include a summarizing paragraph that describes how the specificities of the antibodies have been tested in the past in the laboratories that used them. Have they never been tested in null mutant animals? In null mutants it should be obvious to determine, if some staining patterns do not disappear.
5. Figure 4 is very difficult to comprehend and should be better labeled (e.g. anterior-posterior, dorsal-ventral, muscle fibers, unspecific signals). It is standard in the field to show ventral muscles 12, 13 or 6, 7 in the center of the image and in a similar orientation (anterior left, dorsal up). Better images should be shown.

Significance

The authors provide a critical assessment on the specificity of antibodies and highlight the necessity to carefully test antibodies and the conclusions drawn from the resulting stainings, especially when antibodies are bought from companies or have previously been published as specific. This is extremely important for the interpretation of experiments in all fields of molecular and cellular biology.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

1. Evidence, reproducibility and clarity

1.1 Summary

This reviewer acknowledges the expertise and contributions of Prof. Wodarz and his research group in the field of development, cell polarity regulation and Drosophila genetics.

---

Manuscript summary:

Kim S. et al. explored the localisation of Bazooka, the Drosophila homolog of the polarity protein Par-3, at two non-canonical positions for a cell polarity factor: the nuclear envelope in epithelial tissues and the postsynaptic membrane of the neuromuscular junction (NMJ). Previous work has shown the detection of Par-3/Baz at the nuclear envelope and the NMJ using antibodies against Par-3/Baz. Here, the authors used a combination of genetic perturbations (baz RNAi and generation of genetic mosaics for baz) and GFP-labelled Bazooka lines to test if the antibody-mediated detection of Baz at the nuclear envelope and NMJ is artifactual. The data provided by the authors strongly suggest both the nuclear envelope and NMJ detection of Baz using antibodies is non-specific.

1.2 Major comments

The manuscript is written in a clear manner, easy to be followed by readers. However, there are some important experimental details that should be provided as the authors advance over previous work regarding Baz localization (points 1.2.1 and 1.2.2). Furthermore, if possible, this reviewer considers that performing the experiment in 1.2.3 would strengthen the authors main message of their manuscript.

1.2.1 Methodology information is missing, and would be necessary to be included for: image acquisition (Objectives, Airyscan mode), image processing (projections, details on linear -e.g. brightness, contrast- or non-linear adjustments of signal -e.g. gamma-). For image processing information, please include it within each figure legend. RNAi experiments lines, temperature for each target and tissue (a table would be helpful) and number of heat shocks performed for FRT/FLP clones.

1.2.2 For each experiment it is unclear the number of specimens (experimental units) and independent experiments that were analysed. It is unclear if the Baz localisation phenotypes are fully penetrant or not as judged by the data provided.

1.2.3 This reviewer agrees the data provided strongly suggests the detection of Baz along the nuclear envelope and NMJ is artifactual in the Drosophila tissues that have been studied. However, the nature of the bazEH747 mutant allele is not a deletion of the Baz gene, but instead a nonsense mutation, which, as the authors describe, could potentially generate a small product of 51 aminoacids, corresponding to the N-terminal part of Baz, which is also the target of Baz rabbit antibody ('rb Baz 1-297').

Thus: - Would it be possible to complement the FRT/FLP analyses in the FE using a deficiency that uncovers the baz locus? A persistent detection of Baz signal at the nuclear compartment after complete removal of baz gene products would be an ideal experiment, if feasible. - Would the authors comment on the possibility the rb Baz antibody 1-297 detect a 51 aminoacids peptide?

1.3 Minor comments

This manuscript is largely based on imaging data. Therefore, it would be beneficial for the ease of comprehension of figure panels:

1.3.1 More general use of insets to show with larger magnification and clarity the data indicated with arrows and arrowheads.

1.3.2 Using negative grayscale either for insets or single channel data.

1.3.3 For coloured-overlays please bear in mind using colors that would be suitable for colour-blinded readers.

1.3.4 Figures showcasing the clonal analyses (both MARCM and FRT/FLP): might be worth indicating the boundaries of clones in single channel data with a dotted line.

Referees cross-commenting

I consider that all points/questions raised by other reviewers are fair, in some cases complement this reviewer's points, and in some others coincide. I recommend that all points raised by reviewers #1 and #3 are fully addressed by the authors.

Significance

The findings provided by this manuscript will be of importance for researchers in the field of cell polarity, conducting research on Bazooka/Par-3 and associated proteins, both within the Drosophila field and other model organisms.

The present study presents an advance towards a specific and most likely artifactual observation of Par-3/Bazooka. It will help to re-think the tools used for detecting Par-3/Bazooka in different animal models, and in this regard, will be helpful for the community.

This work does not focus on Par-3/Bazooka biology, nor provides new insights into Par-3/Bazooka function, however, it is clear for this reviewer the later is not the aim of this manuscript.

Reviewer expertise:

• Drosophila genetics
• Developmental cell biology and morphogenesis
• Cytoskeleton, cell cell adhesion and cell polarity

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Baz/Par3 is an important conserved protein acting as a master regulator of cell polarity in a wide range of cell types. This study focuses on re-assessing the subcellular localisation of Baz/Par3 in a range of Drosophila tissues. This is an important study with respect to our understanding of Baz/Par3, as there have been conflicting reports on the localisation of Par complex members - while the majority show localisation to cell cortex and intercellular junctions, several reports have claimed that Par complex members localise at additional subcellular sites including the nucleus, nuclear envelope and neuromuscular junction. In this study the authors re-assess this issue for Baz/Par3 in a comprehensive and thorough manner.

1. They used a variety of antibodies raised in different host animals against different epitopes of Baz
2. They tested the specificity of these antisera using mosaic analysis with null mutant baz alleles and tissue-specific RNAi against baz
3. They used a GFP-tagged Baz under control of its endogenous promoter in a baz null mutant background to compare with the subcellular localisation of the respective GFP-Baz fusion proteins to the staining results with anti-Baz antisera

The data from each of these experiments are very clear and convincing. Comprehensive methods are included which means that each of the experiments with specific anti-sera/RNAi lines/GFP-tagged conditions could be reproduced. There are a couple of experiments which were performed in support of the conclusions (extra RNAi lines and stronger expression of Gal4) listed as (data not shown). I would strongly suggest including these data as extra supplemental figures. Together, their results clearly show that Baz/Par3 localises to the cortex and intercellular junctions, but that anti-sera staining at the NMJs and nuclear envelope appear to be a staining artifact, likely due to staining with an unidentified epitope.

Minor comments

1. Many of the figures have overlays of red and green which will be indistinguishable from each other to colour-blind readers. Please alter to make colour-blind friendly (eg magenta-green)
2. In Fig 2D please indicate where the epidermis and neuroblasts are
3. In the following two places there are experiments describe where the data is listed as not shown. Please show the data as additional supplemental data. They are P8 - This result was confirmed using the CY2::Gal4 driver line expressed in the follicular epithelium and with three different RNAi lines against baz (data not shown). P11 - We also did not see any downregulation of Baz or aspectrin upon baz-RNAi in M12 at 29{degree sign}C, when the UAS-Gal4 system is maximally active (data not shown).
4. Figure 3 - this would be easier to interpret with a few arrows/arrowheads indicating the NMJs

Significance

It will be important to publish these results as it means that findings for a function of Baz/Par3 at the NJM and the nuclear envelope should be regarded with caution, and it may save researchers chasing for functions for Baz/Par3 in places where they are simply not expressed. As much of our fundamental understanding of how Par3 works in vertebrates has its roots in studies in Drosophila, this is likely to be of wide relevance.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

We would like to thank the reviewers for their insightful comments and suggestions, which helped us to streamline and improve our manuscript. Below you can find a detailed response to each of their raised points. In short, we redid most of our experiments to get cleaner data, added some additional experiments (based on suggestions of the reviewers) to strengthen our conclusions, and removed the fly-related data to make the manuscript more straightforward. Moreover, we have combined our Results and Discussion section to adhere to the formatting of EMBO Reports.

Reviewer #1

Major comments

1. The mESC data on the various mutations would be more convincing if derived from two lines, respectively, as in the case of Phe1112Leu NF1 mutation.

We agree with the reviewer that it would have been more convincing if we would have a second mESC line harbouring the Asp633Tyr variant in RAF1. However, we were not successful in creating such an additional line. Moreover, it would not be feasible, both financially and time-wise, to redo all our experiments with this additional line. However, we have unpublished data that shows that the transgenic mESC line harbouring the Asp633Tyr variant in RAF1 shows clustering with and similar effects as several transgenic mESC lines harbouring other genetic variants in different genes from a connected pathway (which we plan to publish in another manuscript), making us less concerned that the observed effects are caused by random off-target effects.

The results concerning ERK1/2 phosphorylation in mESC are actually reflecting the basal MAPK/ERK activity of cells maintained in normal growth medium. It would be important to check the MAPK/ERK activation by specific stimuli like EGF upon starvation in the mESC lines harboring the rare variants.

We thank the reviewer for this suggestion. Based on this comment, we performed additional experiments in which we stimulated our transgenic mESC lines with both EGF and insulin. These experiments showed similar results as the ones we performed in normal growth medium (see updated Figure EV3), strengthening our conclusions that our variants indeed alter MAPK/ERK signalling pathway activity. Moreover, we could additionally show that they also down-regulate phosphorylation of p70 S6K (see updated Figure 2C), indicating reduced mTORC1 activity, which has previously been associated with increased lifespan in different model organisms.

According to the KEGG pathway analysis in Fig 4D PI3K-Akt signaling is activated in both NF1 and RAF1 variants. Because of the well-known cross-talk of PI3K/Akt with MAPK/ERK signaling it would strengthen the paper if PI3K-Akt signaling is analyzed, for example by determining the phosphorylation of Akt.

Based on comment 10 of reviewer 2, we re-analysed the proteomics data and treated each of the genetic variants separately. Although the PI3K-AKT signalling pathway does not show a significant enrichment in the separate groups, we did measure the phosphorylation of AKT and p70 S6K (see reply to comment 2) to probe the effects of the variants on insulin/IGF-1 signalling. We indeed found that both variants up-regulate phosphorylation of AKT at S473 in normal growth medium (although the effect of the NF1 variant is clearly stronger) and down-regulate phosphorylation of AKT at S308 after insulin stimulation, while we observed a RAF1-specific down-regulation of phosphorylation of AKT at S473 after insulin stimulation (see updated Figure 2B and 2D).

Some players in the MAPK/ERK signaling pathway are upregulated, some are down-regulated in mutant NF1 or mutant RAF1 cells, but it is not clear what the net effect of all these changes is on MAPK/ERK signaling. However, what ultimately matters are changes in down-stream gene expression. To really determine the effect of the mutations on MAPK/ERK signaling it would be necessary to perform more detailed transcriptome analysis and especially check the expression of longevity-controlling transcription factors, such as SKN-1, ETS and FOXO.

We thank the reviewer for this very helpful suggestion. We performed an additional experiment in which we looked at the effect of our variants on the transcription of mammalian orthologs of the lifespan-associated transcription factors that belong to the SKN-1, ETS and FOXO family. We specifically focussed on the subset of ETS transcription factors that have been linked with lifespan regulation in fruit flies, given the known relation with MAPK/ERK signalling. In line with our findings from the proteomics, we indeed found consistent (i.e. Nfe2l2, Foxo3, Etv1, and Etv6) as well as opposing effects (i.e. for Ets1, Ets2, and Etv4) on the expression levels of these transcription factors between our cell lines (see new Figure 4). Based on this we concluded that both cell lines show reduced MAPK/ERK signalling activity.

The authors are discussing a gain of function effect of the variants on the activity of RAF1 and of NF1, based on the ERK1/2 phosphorylation data from mESC. Since the variants are residing in protein domains important for the respective protein function (Tubulin-binding domain of NF1 and C-terminus of RAF1, important for its interaction with 14-3-3 proteins, respectively), the authors could speculate on how the mutations might affect the respective protein activity. Furthermore, the data could be strengthened by directly testing the activity of RAF1 or Ras.

We have now added some text in which we speculate on the potential effects of our genetic variants (i.e. gain- or loss-of-function). Since we were mostly interested in the (shared) downstream effects of the variants, we decided to focus on this instead of the activity of Raf1 (for which good assays are also lacking).

Since there is no consistent effect of the investigated mutations and their effects on MAPK/ERK signaling in mESC and no consistent effect on life-span in flies, wouldn´t one have to conclude that the pipeline for functional characterization is actually not working? Along that line, if introducing putative human life-extending mutations in RAF and NF1 in flies leads to lethality in one case and a shortened life-span in the other, doesn´t that proof the model is not suitable to draw conclusions about human mutations in flies?

We have decided to remove the fly data from our manuscript to make the message more straightforward. We also realised that the lifespan-associated effects of the protein in flies had been contributed by its role in the adenylate cyclase-cAMP-protein kinase A pathway and not MAPK/ERK signalling (PMID: 17369827). Hence, we were not sure if the reduced lifespan effects we observed could be attributed to the role of Nf1 on MAPK/ERK signalling, especially since we did not observe any effects on phosphorylation of ERK1/2 in the flies.

Minor issues

1. Introduction, last paragraph.

The sentence "Notably.... is very long and could be changed to two sentences.

We have adapted this.

Results, paragraph "Generation of mESCs..."

It only becomes clear in the discussion that the AN3-12 cells get diploid after a while and that the human donors were heterozygous. This should be mentioned already here.

We have adapted this.

Results, paragraph "Generation and characterization of transgenic flies.."

What is the wDah background?

As mentioned above, we have removed all the fly data from our manuscript.

The dimer consisting of RTK and a GPCR in the simplified illustration of the MAPK/ERK signaling pathway in Fig.1(B) is misleading, it is probably supposes to be a RTK?

We have adapted this.

Reviewer #2

Major comments

1. The NF1 variant and RAF1 variant have different outcomes regarding ERK phosphorylation. Then, how can long-lived family members share these variants?

This is indeed a good point. However, now that we redid most of our experiments, we are able to show that most of the effects of the variants are consistent, especially when looking at the main effects on MAPK/ERK signalling. However, the proteomics and transcriptomic analyses still show some opposing and diverging effects. Hence, we speculate that this likely indicates that there are multiple ways in which genetic variants could influence cellular processes/phenotypes associated with healthy ageing and there is not a single molecular mechanism explaining it all.

The two variants in mESCs showed contradictory results on MAPK/ERK pathway. In addition, fruit fly didn't recapitulate the results of mESC experiments. How can the authors conclude these variants are causally linked to longevity?

See our reply to comment 1 and to major comment 6 of reviewer 1.

Figure 2C, The authors should correct the statistical test (they used a T-test for 4 sample data set).

We have adapted this.

Figure 2C, Is NF1 and MEK1/2 expression altered? What about pMEK1/2 expression? The mechanistic link between NF1 mutations and ERK phosphorylation is speculative.

We thank the reviewer for this suggestion. We have now also added data on the phosphorylation of MEK1/2, which showed consistent results with that of ERK1/2.

Figure 2C, The loading looks very variable. The authors should use fluorescently labelled antibodies for multiplexing. This way, the phospho signal and total protein can be quantified on a single blot.

We have redone all our western blots and now normalised to calnexin, since we realised that vinculin was relatively unstable and therefore not the best reference protein to use. All data looks consistent now.

Figure 2D, Loading control, Vinculin, is variable. Based on vinculin expression, total ERK expression was increased in RAF1 Asp633Tyr variant. It could affect the amount of pERK. The authors should show whether the authors loaded the equal amount of proteins using stain-free as in Fig. 5D.

See reply to comment 5.

Figure 2D, What about total RAF1, MEK1/2 expression and pMEK1/2? I was wondering whether phosphorylation of ERK is increased via RAF1-MEK pathway. The link between RAF1 mutation and ERK phosphorylation is mechanistically speculative.

See reply to comment 4. The expression of Raf1 itself is provided in Figure 3A (i.e. the proteomic dataset) and is differentially influenced by both variants.

Figure 3C and D, It doesn't look like dramatic improvement, especially since the curves run in parallel. The authors should corroborate the findings using an assay that is independent on the cellular metabolism, e.g. cell survival or proliferation using Incucyte

We redid our experiments using the Incucyte® Live-Cell Analysis System and focussed on a stressor (i.e. hydroxyurea) that showed consistent effects across experiments (see updated Figure 5B). The stressors we used previously did not work so well in this system. We also measured proliferation in normal growth medium (see updated Figure 5A). These results indicate that the proliferation of the NF1Phe1112Leu variant mESC lines was increased, while that of the RAF1Asp633Tyr variant mESC line was decreased under normal growth conditions. Moreover, the RAF1Asp633Tyr variant showed improved resistance to replication stress, while this was not the case for the NF1Phe1112Leu variant.

Figure 4, To figure out global phosphorylation changes induced by the variants, I suggest the authors perform phospho-proteomics

We agree with the reviewer that it would be very nice to perform phospho-proteomics. However, this is still relatively expensive and our proteomics facility mentioned that such measurements are likely not yet robust and sensitive enough to get reliable estimates of specific phosphorylation sites.

Figure 4C and D, NF1 variants and RAF1 variants have an opposite effect on phosphorylation of ERK. Why did the authors investigate the shared upregulated or downregulated proteins between two variants? How can they share TFs with the MAPK/ERK signaling pathway?

See our reply to comment 1 and to major comment 4 of reviewer 1.

Figure 4, The conclusion of this figure 4 is not clear to me.

We have now updated the text in the Results and Discussion section to make this clearer.

Minor comments

1. The ultimate goal of aging research will be healthy aging. In LLS, were all long-lived individuals healthy? Do the authors have additional clinical parameters?

There is only limited clinical data available for the long-lived individuals from the Leiden Longevity Study (PMID: 27374409), so we were not able to thoroughly asses this (also because there is no appropriate control group to compare them to). For the sequencing, we focussed on the individuals that had the longest survival within their families, but we cannot rule out that some of them were relatively unhealthy.

Overall, most western blot figures do not look like being representative of the quantification results. The authors need better representative western blot figures

We have repeated all our western blot experiments and updated our figures to show the most representative images.

Figure 3, is there a difference in cell proliferation ability/viability between WT and the NF1/RAF1 variants?

See reply to major comment 8.

Figure 4A, How many replicates were used here?

We used 4 technical replicates per cell line. We have now added this information to the Figure legend and the text in the Methods section.

Figure 4A, The authors should provide the rationale for the cutoff they used: fold change and p-value/FDR?

We have now added this information to the Figure legend and the text in the Results and Discussion section.

Figure 5C and D, Did mutant flies die due to aging or due to any disease?

As mentioned before, we have removed all the fly data from our manuscript.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

Summary

As part of a meta-study using the whole genome sequencing data from Leiden Longevity Study (LLS), the author identified uncommon genetic variants in MAPK/ERK signaling pathway which are potentially associated with human longevity. To characterize these gene variants, the authors employed CRISPR/Cas9 genome-edited mouse embryonic stem cells (mESCs) and fruit flies. Paradoxically, the variants in NF1 and RAF1 (both associated with increased longevity) have functionally opposite effect on activity of MAPK/ERK pathway in vitro. Nf1 variant in flies has no effect on MAPK/ERK pathway, however, it leads to deleterious consequences such as shorter lifespan, delayed developmental time, and decreased locomotor activity. Due to the contradictory results of the in vitro experiments and the in vivo fly model, it is difficult to conclude that the rare genetic variants the identified, are linked to longevity.

Major comments

1. The NF1 variant and RAF1 variant have different outcomes regarding ERK phosphorylation. Then, how can long-lived family members share these variants?
2. The two variants in mESCs showed contradictory results on MAPK/ERK pathway. In addition, fruit fly didn't recapitulate the results of mESC experiments. How can the authors conclude these variants are causally linked to longevity?
3. Figure 2C, The authors should correct the statistical test (they used a T-test for 4 sample data set).
4. Figure 2C, Is NF1 and MEK1/2 expression altered? What about pMEK1/2 expression? The mechanistic link between NF1 mutations and ERK phosphorylation is speculative.
5. Figure 2C, The loading looks very variable. The authors should use fluorescently labelled antibodies for multiplexing. This way, the phospho signal and total protein can be quantified on a single blot.
6. Figure 2D, Loading control, Vinculin, is variable. Based on vinculin expression, total ERK expression was increased in RAF1 Asp633Tyr variant. It could affect the amount of pERK. The authors should show whether the authors loaded the equal amount of proteins using stain-free as in Fig. 5D.
7. Figure 2D, What about total RAF1, MEK1/2 expression and pMEK1/2? I was wondering whether phosphorylation of ERK is increased via RAF1-MEK pathway. The link between RAF1 mutation and ERK phosphorylation is mechanistically speculative.
8. Figure 3C and D, It doesn't look like dramatic improvement, especially since the curves run in parallel. The authors should corroborate the findings using an assay that is independent on the cellular metabolism, e.g. cell survival or proliferation using Incucyte
9. Figure 4, To figure out global phosphorylation changes induced by the variants, I suggest the authors perform phospho-proteomics
10. Figure 4C and D, NF1 variants and RAF1 variants have an opposite effect on phosphorylation of ERK. Why did the authors investigate the shared upregulated or downregulated proteins between two variants? How can they share TFs with the MAPK/ERK signaling pathway?
11. Figure 4, The conclusion of this figure 4 is not clear to me.

Minor comments

1. The ultimate goal of aging research will be healthy aging. In LLS, were all long-lived individuals healthy? Do the authors have additional clinical parameters?
2. Overall, most western blot figures do not look like being representative of the quantification results. The authors need better representative western blot figures
3. Figure 3, is there a difference in cell proliferation ability/viability between WT and the NF1/RAF1 variants?
4. Figure 4A, How many replicates were used here?
5. Figure 4A, The authors should provide the rationale for the cutoff they used: fold change and p-value/FDR?
6. Figure 5C and D, Did mutant flies die due to aging or due to any disease?

Significance

Filtering out meaningful rare variants in MAPK/ERK pathway from long-lived individuals is an interesting and promising approach. However, the link between the NF1/RAF1 variants and longevity is still unclear. The authors were not able to explain the contradictory results from the NF1 and RAF1 mutant mESCs. In addition, the fly model did not support the in vitro mESC results. The authors need to provide more mechanistic insight into the impact of the variants on MAPK signaling. This part of the study is very superficial. Overall, the story seems a bit premature.

Advance: The authors identify rare mutations affecting the ERK pathway in long-lived family members.

Audience: Basic researchers who are interested in signaling and aging.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Hinterding et al. present a manuscript where they characterize rare variants in genes found in long-lived families. The authors concentrated on the MAPK/ERK signaling pathway, because they argued that this pathway has an established role in life-span determination. The rare variants were introduced in mouse embryonic stem cells and in fruit flies and their effects on the MAPK/ERK pathway and on life-span was studied. The authors conclude they established a pipeline for the functional characterization and potential validation of rare genetic variants.

The topic is very interesting and the approach is original and novel. However, the results are in part preliminary and contradictory and the conclusions are overstated. Before publication, we suggest to address a number of issues.

1. The mESC data on the various mutations would be more convincing if derived from two lines, respectively, as in the case of Phe1112Leu NF1 mutation.
2. The results concerning ERK1/2 phosphorylation in mESC are actually reflecting the basal MAPK/ERK activity of cells maintained in normal growth medium. It would be important to check the MAPK/ERK activation by specific stimuli like EGF upon starvation in the mESC lines harboring the rare variants.
3. According to the KEGG pathway analysis in Fig 4D PI3K-Akt signaling is activated in both NF1 and RAF1 variants. Because of the well-known cross-talk of PI3K/Akt with MAPK/ERK signaling it would strengthen the paper if PI3K-Akt signaling is analyzed, for example by determining the phosphorylation of Akt.
4. Some players in the MAPK/ERK signaling pathway are upregulated, some are down-regulated in mutant NF1 or mutant RAF1 cells, but it is not clear what the net effect of all these changes is on MAPK/ERK signaling. However, what ultimately matters are changes in down-stream gene expression. To really determine the effect of the mutations on MAPK/ERK signaling it would be necessary to perform more detailed transcriptome analysis and especially check the expression of longevity-controlling transcription factors, such as SKN-1, ETS and FOXO.
5. The authors are discussing a gain of function effect of the variants on the activity of RAF1 and of NF1, based on the ERK1/2 phosphorylation data from mESC. Since the variants are residing in protein domains important for the respective protein function (Tubulin-binding domain of NF1 and C-terminus of RAF1, important for its interaction with 14-3-3 proteins, respectively), the authors could speculate on how the mutations might affect the respective protein activity. Furthermore, the data could be strengthened by directly testing the activity of RAF1 or Ras.
6. Since there is no consistent effect of the investigated mutations and their effects on MAPK/ERK signaling in mESC and no consistent effect on life-span in flies, wouldn´t one have to conclude that the pipeline for functional characterization is actually not working? Along that line, if introducing putative human life-extending mutations in RAF and NF1 in flies leads to lethality in one case and a shortened life-span in the other, doesn´t that proof the model is not suitable to draw conclusions about human mutations in flies?

Minor issues

1. Introduction, last paragraph. The sentence "Notably.... is very long and could be changed to two sentences.
2. Results, paragraph "Generation of mESCs..." It only becomes clear in the discussion that the AN3-12 cells get diploid after a while and that the human donors were heterozygous. This should be mentioned already here.
3. Results, paragraph "Generation and characterization of transgenic flies.." What is the wDah background?
4. The dimer consisting of RTK and a GPCR in the simplified illustration of the MAPK/ERK signaling pathway in Fig.1(B) is misleading, it is probably supposes to be a RTK?

Referees cross-commenting

Reviewer #2 provides a fair and balanced review and seems to have pretty much the same concerns as I do, namely that there are too many inconsistencies in the experiments to conclude that the identified candidate genes are longevity genes.

Significance

The concept of the study, to look for gene variants in long-lived families, is novel and highly interesting. It should be relevant for a broad audience interested in aging, longevity and the underlying mechanisms.

Strengths:

• identification of potentially long-life associated gene variants in humans

Limitations:

• final outcome on MAPK/ERK signaling not analyzed (downstream genes)
• investigated gene variants don´t show consistent pattern
• use of flies as model for the analysis of human longevity gene variants not convincing since one mutation is lethal, the other life shortening

My expertise is cell biology, aging, senescence. I co-reviewed the paper with my postdoc who worked on MAPK/ERK signaling for many years.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

We would like to thank the three reviewers for their time and effort, the constructive criticism, and suggestions to improve the quality of the manuscript. Below, we address the points raised by providing further clarifications or revising the manuscript as indicated.

__Reviewer #1 (Evidence, reproducibility and clarity (Required)): __

This study investigates mitochondrial and apicoplast division and distribution during the life cycle of Plasmodium falciparum. Utilizing the MitoRed reporter line for fluorescent mitochondrial marking and employing high-resolution 3D imaging techniques, including FIB-SEM, the research unveils the dynamics of these essential organelles across various stages of the parasite's development. The authors' work marks a significant step forward in understanding the cellular biology of Plasmodium falciparum, offering novel insights into the dynamics of mitochondrial and apicoplast division. By addressing the additional comments and incorporating recent findings and clarifications, the research not only underscores the complexity of these processes but also situates the study within the continuum of apicomplexan parasite research.

Major comments: • Suitability of Reporter Line for Oocyst Development: The conclusion regarding the limitations of the MitoRed line for oocyst development stages prompts a discussion on alternative approaches, such as mito trackers, to validate observations in these stages. In the current state, it is difficult to conclude whether the data presented are only true for this specific transgenic line.

We agree with the reviewer that the lack of MitoRed salivary gland sporozoites indeed hints to a developmental issue and therefore interpretation of mitochondrial morphology in oocyst stages should be done carefully. Although we would like to verify these observations with a wild-type line, there are several complications with using a MitoTracker staining. Firstly, a general staining procedure will also highlight the much larger and more abundant host mitochondria thus complicating both the actual imaging and interpretation of the data. Secondly, our own data presented in this manuscript demonstrated that MitoTracker stainings of blood-stage parasites should be considered with great care and it remains to be tested whether mosquito-stage parasite viability and mitochondrial morphology remain unaffected. Thirdly, mosquito experiments are time intensive and costly and we lack the time and funding to expand on this part of the work. We therefore decided to move the oocyst data to the supplement and added additional qualifiers for interpretation to the text.

Line 578: “Although these mitochondrial observations should be interpreted with care since oocysts did not form salivary gland populating sporozoites and might therefore not be representing healthy oocysts, in P. berghei liver-stage schizonts, a very similar mitochondrial organization was observed in sub-compartments created by large membrane invaginations.”

To conclude, we think it is important to be open about the limitations of the MitoRed line and discuss this in the paper to provide a balanced view for others that might want to use this line in the future. At the same time, we think that the observation of the mitochondrial organization centers and the great similarity with mitochondrial organization in liver- and blood-stage schizonts offers tentative support for a biologically relevant phenotype and gives new insights that we would like to share in this manuscript, provided that they are interpreted with care.

• Analysis of Mitochondrion and Apicoplast Association with CPs: Could the author elaborate on how their statistical power and image data support assertions of random association between organelles and CPs (line 438-439) and the dynamic nature of Mito-CP interactions (line 504)? In addition, could the authors comment/discuss their findings regarding the distance between Mito-Api compared to the one reported in Figure S2 of Sun et al. preprint: bioRxiv 2022.09.14.508031; doi: https://doi.org/10.1101/2022.09.14.508031

We would like to clarify the point that the reviewer raises. Although we indeed observed that the distances between the CP-mito are significantly smaller compared to CP-apicoplast in schizont 1 in Figure 7, we do not think that there is interaction between the mitochondrion and CPs. In schizont 3-6, the apicoplast shows close apposition with CPs over the complete length of the apicoplast/with all apicoplast fragments and the distances between CPs and apicoplast range from 0-150 nm, therefore we think there is CP-apicoplast interaction. The distance between CPs and mitochondrion is much larger in all schizonts with an average of 500-600 nm, except for schizont 6 where the CP-mito distances become smaller due to the alignment of the mitochondrion with the apicoplast. Still the CP-mito distance is significantly bigger in schizont 6 compared to CP-apicoplast. Therefore, we do not think there are mito-CP interactions in any of the schizont stages. To clarify this in the text, we added the following sentences:

Line 483: “Although the distances between the mitochondrion and CPs (average 616 nm, SD 235 nm) in this early schizont are significantly smaller than the apicoplast-CPs distances (average 1350 nm, SD 260 nm), there is no direct interaction between the mitochondrion and CPs since the smallest CP-mitochondrion distance measured is 332 nm. The significant difference can be explained by the fact that the apicoplast is located in the center of the parasite, while the mitochondrion is larger and stretched throughout the whole cell leading to coincidental closer proximity to the peripheral CPs.”

We have also added extra comparisons of CP-apicoplast and CP-mitochondrion distances to the text to support this (Line 483-503).

We thank the reviewer for their suggestion of comparison with the data from Sun et al. The EM tomography data in that paper are indeed of much higher resolution and hint at physical interaction between the membranes of the mitochondrion and apicoplast. We have added the following sentences to the discussion:

Line 612: “EM tomography data from Sun et al. show there are hints of connecting structures between the mitochondrion and apicoplast in areas where the distance between the organelles is very small and similar to the distance between the inner and outer membranes of the organelles themselves in merozoites, suggesting physical link between the organelles.”

• Incorporation of Recent Findings into Schematic Models: I recommend the authors modify their current model in Figure 8 to reflect on recent findings on CP outer domain contact with the parasite plasma membrane (PPM) post-mitosis as demonstrated by Liffner et al. PMID: 38108809.

We agree with the reviewer that the data from Liffner et al. suggest contact of the outer CP with the PPM, however, we think ExM data should be interpreted with some care. Contact sites are strictly defined as an area where membranes of two organelles are in close proximity to each other, while there is no membrane fusion, there are tethering forces (protein-lipid or protein-protein interaction), and fulfill a specific function (PMID:30894536). The ExM data do not have the resolution to define the CP-PPM appositions as contact sites. Although we indeed see closeness of the CPs and the PPM in our FIB-SEM data, we do not see evidence of a physical contact between the two. Therefore, for this proposed model, we would keep the focus on the division and segregation of the two endosymbiotic organelles.

Minor comments: • Reference to WHO Report: The manuscript cites malaria incidence and mortality data from an older WHO report. Given the availability of the 2022 WHO reports, authors should update the text and citation (line 36).

Changed accordingly.

• Clarification of Host: The term "its mitochondrion" (line 42) should be specified as "human mitochondrion" to clearly distinguish between the two different hosts.

We changed “The malaria parasite harbors a unique mitochondrion that differs greatly from its host mitochondrion” to “The malaria parasite harbors a unique mitochondrion that differs greatly from the human mitochondrion”.

• Terminology of Parasite Development Stages: The usage of "schizogony" to describe division processes in liver and mosquito stages could be misleading due to the distinct process of endopolygeny nuclear-like division observed during sporogony (line 56; PMID: 31805442). I would recommend the authors use a more general language, such as cell division.

Changed accordingly.

• Prior Research on CP and Apicoplast Association: The observation of centriolar plaques (CPs) associating with the apicoplast (line 91) has precedents in the study of other apicomplexan parasites, such as Sarcosystis (PMID: 16079283). Acknowledging and discussing these findings would contextualize the current study within the broader range of the most commonly studied apicomplexan parasites.

We thank the reviewer for this suggestion and added the following sentence and citation to the discussion:

Line 646: ”In other apicomplexan parasites, such as Toxoplasma gondii and Sarcocystis neurona, centrosomes have also been indicated to be involved in apicoplast organization and distribution during cell division.”

• Depth of Imaging Data: Could the authors indicate the width of their z-stack, for instance, in Figure 1? I would also suggest the authors use hours of post-infection (h.p.i) for clarity (lines 234-254) to aid comprehension by a broader audience as they do later in the manuscript.

As suggested we added the depth and interval ranges of the Z-stacks are added to the legends of Figures 1, 2, 3, and 5.

It is common practice to describe the oocyst stages by days instead of hours post infection (of the mosquito; also referred to as days after feeding) as the development takes ~2 weeks. Later in the manuscript, we refer to the development of asexual blood stages, a ~48h cycle, which is commonly referred to by hours post invasion (of the red blood cell). Sticking to common practices in the field, we have decided leave the time indications used unaltered.

• Visualization of Mitochondrial Structures: Suggestions to include or reference images of bulbous mitochondrial structures (line 445) directly in the main text or within key figures (e.g., Figure 6) would help the reader understand what and where are these bulbous structures.

Arrows are added to Figure 6 to indicate bulins.

• Organelle Communication and Division Mechanisms: The discussion of bulbous invagination structures (buildings) (line 469) and their role in organelle division is interesting; could it be also for organelle communication or storage? Can the authors expand the discussion about it?

We have indeed wondered and discussed possible functions of these bulins extensively. While roles in organelle communication or storage are other interesting theories that also crossed our minds, the timing of appearance, the precise location of the bulins at the entrance of developing merozoites at the stage where bulins are most abundant, and their morphological features together to us strongly suggest a link to (mitochondrial) fission, via membrane remodeling and/or the distribution of certain components, such as mitochondrial DNA, proteins, or protein complexes. We would like to keep the focus of the paper at mitochondrial and apicoplast fission and as such we discuss various observations within this context. Discussing all our observations within the wider context of Plasmodium biology would be lead to overly long and unfocused paper and hence we would like to leave these discussions for other manuscripts with a different focus.

Reviewer #1 (Significance (Required)):

The study is a significant contribution to the field of parasitology, particularly in understanding the cellular biology of Plasmodium falciparum. The development of the MitoRed reporter line is a notable advancement, allowing for the real-time visualization of mitochondrial dynamics. This tool could be invaluable for future studies exploring parasite biology's intricacies and identifying new antimalarial drug targets. Furthermore, while the study provides detailed insights into the division and distribution of mitochondria and apicoplasts, the molecular mechanisms underlying these processes remain to be fully elucidated. Specifically, the role of specific proteins in mediating these divisions and the potential interplay between mitochondrial and apicoplast dynamics during parasite development warrant further investigation.

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

During its development and growth, the human malaria parasite P. falciparum needs to guarantee that cellular organelles, including the mitochondrion and the apicoplast, will be divided and segregated correctly into the daughter parasites. However, the details and mechanisms of these processes are not clear. Here, authors provide a description of mitochondrial replication and segregation in P. falciparum schizonts, gametocytes and oocysts. They generated a reporter cell line by attaching mScarlet red fluorescent protein to the mitochondrial heat shock protein 70-3 and used high-resolution 3D-imaging and focused ion beam scanning electron microscopy to study mitochondrion dynamics in the asexual, gametocytes and mosquito stages. The authors found that in schizonts, the mitochondrion forms a cartwheel structure at the end of early segmentation stage with full division occurring only at a late stage of schizogony. Apicoplast division happens after nuclear division but is complete before nuclear division is completed. Authors also found apicoplast but not mitochondrion is associated with centriolar plaque (analogue of centrosome in P. falciparum) during the schizogony. At the end, authors proposed their model of nuclei, mitochondrial and apicoplast division in the asexual stage schizogony. This well-written manuscript provides insights on mitochondrion and apicoplast fission in P. falciparum blood stage schizogony and mitochondrion dynamic in the blood, gametocytes and mosquito stages. Questions and suggestions are below:

Major comments The marker line forms mature oocysts but does not produce salivary gland sporozoites. This phenotype needs to be explained more clearly. Are sporozoites produced in the midgut, are they released into the hemocoel?

For clarity, we have expanded our explanation of this phenotype and indicated the limitations of the tool in lines 250-259:

“While several free sporozoites were observed in dissected midguts and salivary glands on day 16 (data not shown), we never observed an oocyst containing fully mature sporozoites with a divided mitochondrion or an infected salivary gland on day 16 and 21 after infection. This indicates that sporozoites are produced and released into the hemocoel, however, they have a health defect that prevents them from infecting the salivary glands. Possibly the mitochondrial marker or the integration in the SIL7 locus causes issues for sporozoite development. We conclude that the MitoRed line is a great tool for mitochondrial visualization in asexual blood stages, gametocytes stages, and mosquito stages up until late oocysts (Supplemental Information S1) but that for studies later in the life cycle other tools need to be developed and tested.”

Does introduction of an exogenous copy of HSP70 influence total HSP70 expression in the parasite, and can this cause the observed defect in sporozoite production? Did authors try to tag the endogenous HSP70 to see if it's a suitable reporter?

For clarity, as we describe in the paper (e.g. lines 113-117) we did not express an additional copy of HSP70-3 but merely fused its promoter region and mitochondrial targeting sequence without any further functional domains to mScarlet. This is a strategy that has been employed with great success to study mitochondrial biology in all life-cycle stages of P. berghei (PMID:29669282). While we cannot formally exclude that the use of a second copy of the HSP70-3 promoter could somehow influence the expression of the endogenous copy, it seems rather unlikely. A plethora of promoters of a wide variety of genes have been used for transgenic expression of e.g. drug cassettes and other fluorescent markers in a multitude of studies and to the best of our knowledge there are no reports of this ever interfering with endogenous expression levels. Although we think it would be interesting to know what exactly causes the defective sporozoite production, this information will not add to our understanding of mitochondrial dynamics in mosquito stages and hence beyond the scope of this study (see also our responses to the previous comment and the first comment of reviewer 1).

Did authors compare the growth of the reporter parasite line to wild-type in gametocytes and oocysts?

Typically, conversion rates of gametocyte inductions are highly variable even within the same experiment. MitoRed gametocytes have been induced in at least five independent experiments. Although we have not performed a direct quantification of gametocyte conversion or growth rates between MitoRed and NF54 WT parasites, stage V male and female MitoRed gametocytes developed normally demonstrating no morphological aberrations in each of these experiments within the expected 12-day time frame, similarly as WT parasites, assessed by light microscopy. As we found no indications for a developmental phenotype deviating from what is commonly observed for wild-type parasites as is shown in supplemental figure S3. We have added comparison of exflagellation events in MitoRed vs WT parasites to figure S4, showing no significant difference and indicating formation of healthy male gametes. Normal healthy of MitoRed gametocytes is further supported by the fact that these parasites infect mosquitos.

A direct comparison of the growth of MitoRed with WT in oocyst stages is challenging, since infections can show high variance. In addition, these experiments are very costly and time intensive. As we focused our work on blood-stage development and because there are limitations in the use of MitoRed when studying subsequent mosquito- and liver-stage development as discussed above and in the manuscript, we decided not to invest our limited resources for a direct comparison with WT, reserving such a comparison for future transgenic lines that present no obvious developmental defects.

In figure 1A and Methods, are all MitoTracker stains incubated at 100 nM for 30 minutes? Did authors try to optimize the conditions to improve quality Mitotracker staining can be improved?

Indeed, all MitoTracker stains were performed at 100 nM, except for the Rhodamin123 used for life imaging. In the past, we have performed several pilot experiments to optimize staining conditions of which 100nM for 30 min most consistently resulted in sufficiently bright yet specific signals. Notably, this is the MitoTracker concentration that is described most frequently in other papers. The use of a lower concentration might indeed improve the mitochondrial morphology in MitoTracker stained parasites, however, for the scope of this paper we wanted to compare our new mitochondrial marker with the most commonly used MitoTracker staining conditions. Combined with the fact that MitoTrackers are toxic at low concentrations, we preferred to step away from MitoTracker when looking at mitochondrial division, to ensure we are looking at biologically relevant mitochondria.

In figure 1B, can authors replace the figures for the first ring? The parasite does not seem healthy and the scale bar is shorter than the others. Can authors define DIC in the legend?

Change accordingly.

In figure 8, it looks like some apicoplasts are not associated with the CP, contrary to what is stated in the text, for eg the one at the 7 o'clock position in stage 3.

It is indeed difficult to find an angle of visualization that shows clearly that all CPs associate with the apicoplast, a common challenge when trying to visualize 3D data in a 2D space. However, in the 3D animated movies that are provided with the manuscript, the reader can observe this association more clearly, as the organelles rotate slowly so that all angles can be observed. We therefore think that these movies are indispensable to demonstrate and clarify things that are difficult to extract from still, non-rotating image.

The Discussion should mention the failure in generating sporozoites from this reporter line Can authors discuss the SIL7 locus as the site of integration, in the context of potential effect of its disruption on sporozoite production.

In the discussion, we briefly mention the limitation of the use of MitoRed. We have now also added a reference to the more extensive discussion of this phenotype in the supplemental information and included an additional sentence in the results section to indicate the limitations. As indicated in response to previous comments, we think it is important to discuss these limitations as well as present the observations we made during oocyst development but to compartmentalize these to an extended, supplementary section. This allows us to keep the focus on fission during blood-stage schizogony and not make the discussion overly lengthy.

Authors should explain criteria for identifying organelles in FIB-SEM images eg mitochondria, apicoplast etc.

We added to following sentence to clarify how we identified the mitochondrion and apicoplast in the FIB-SEM images (lines 387-389):

"The mitochondrion and apicoplast can be recognized by their tubular shape in addition to the double membrane of the mitochondrion and the thicker appearance of the four membranes of the apicoplast.”

FIB-SEM images show other prominent organelles in these images (dense granules? hemozoin crystals?). It would be helpful for reader orientation and greater appreciation of the work if these organelles were marked as well.

We agree with the reviewer it would be an interesting addition to visualize other organelles, such as e.g. dense granules, rhoptries, and IMC, to learn more about general organellar biology of the parasite. However, segmentation of these organelles requires the training of a new deep learning model and/or the manual segmentation of +400 image slices per parasite. This is unfortunately not feasible for us. However, the dataset is going to be available online and we encourage researchers to revisit and reuse the dataset for their own research questions.

Minor comments The format of blood, mosquito and liver stage is not consistent. Eg. in line 17, 22, 56 and 65. Some has a dash line while some doesn't.

We use hyphens (dashes are longer and used between clauses/sentences) as appropriate. That is, when we use “blood-stage” as a compound adjective as in “the blood-stage parasites are” but not when using “stages” as the noun as “the blood stages are”. We have double-checked the entire manuscript once more to ensure correct hyphenation throughout.

In line 36, numbers of cases and death by malaria are by estimation.

Changed accordingly

Can authors define Plasmodium falciparum as P. falciparum in line 37?

It is common practice to write the full name of a species at first mention in the main body of a manuscript (not including the abstract).

The sentence in line 57-59 is confusing. At the end of schizogony, the daughter merozoite/sporozoite has one mitochondrion but it's multiple in the parasite.

We adapted the sentence so it will be clearer to the reader that the parasite has a single mitochondrion that divides into multiple fragments during cell division:

“During P. falciparum cell division, the single parasite mitochondrion needs to be properly divided and distributed among the daughter cells.”

Can authors specify which mitochondrial dyes are toxic in line 76?

We have included the following sentence to clarify:

“However, eight of these dyes were tested in a drug screen all showing IC50 values below 1mM with three, Mito Red, DiOC6, and Rhodamine B being highly active against P. falciparum with IC50 values below 30 nM14,15.”

In line 115, can authors indicate the Gene ID for PfNF54? Can authors define the reported parasite line as MitoRed here instead of line 125?

Although we indeed used NF54 as the parental strain for the MitoRed line, we think the 3D7 gene ID is more useful in this context. The 3D7 genome is used as the reference genome by the entire field and it is much better annotated than the NF54 genome. Furthermore, the genomes are not all too different to start with, as 3D7 is a subclone of the NF54 line.

In line 134 and 540, use punctate instead of 'punctuated'?

Changed accordingly.

In line 161 to 163, can authors also cite ref 19?

Reference 19 (now 20) is cited in line 163 precluding the need for an additional citation in the next sentence.

In line 174, pH change can also trigger gametocytes activation.

Changed accordingly.

In Figure S4, please indicate the percentage of parasites having close apposition of mitochondrion to axonemes.

When we revisited our images to check what percentage of parasites have close appositions of the mitochondrion and the axonemes, we found that in all exflagellating parasites that were analyzed there is close apposition or overlap between the mitochondrial and the tubulin signal. We changed the text to reflect this:

Line 189: “We found close apposition of the dispersed mitochondria to the axonemal tubulin in all 19 exflagellating males that were analyzed (Figure S4B, S4C).”

Line 237 to 239, please clarify why authors think there is one fragment in mitochondrial.

We have added the following sentence to clarify:

Line 239: “Segmentation of the fluorescent signal based on manual thresholding indicated that the mitochondrion consisted of one continuous structure.”

In line 259, the ookinete stage is II to IV.

Stage indications have been corrected.

In line 281, please define RBC.

Changed accordingly.

In figure 5A, please provide a scale bar for the original and reconstructed image. Should the unit of fragment volume be um3 but not um?

We have added scale bars to the original fluorescent images and the unit has been changed to mm3. Unfortunately, it is not really appropriate to provide a 2D scale bar with a 3D image, since this will not take the depth of your image into account, unless an orthographic projection is used. Objects that are more to the front are visualized slightly bigger than things in the back and therefore a scale bar would not help for interpreting the size of the depicted objects.

Can author do a statistical analysis in Fig 5B and 5C to show the stage at which the majority of nuclei and mitochondria divide?

Changed accordingly.

In figure 5D, the labels on Y axis are not the same size.

The two different sizes were used intentionally to show clearly it is a logarithmic instead of a linear scale.

In figure 6, what's the green black color organelle in the first column (like the organelle showing up as 4 in the first one, at 1/2/6/8 o'clock)? Can authors provide annotations of organelles using arrows at least in the supplementary?

We have added annotations of the RBC, food vacuole, rhoptries, parasite membrane and parasitophorous vacuole membrane to the micrograph images in Figure 6 and the Table S3.

In line 717, the font of ul is not consistent with others like line 691.

Changed accordingly

In line 731, 37 {degree sign}C.

Changed accordingly

Reviewer #2 (Significance (Required)):

The mitochondria of human malaria parasite Plasmodium falciparum differs from the host's and is an intriguing drug target. During the asexual blood stage replication, parasite mitochondrial elongates to form a branched network and undergoes rapid fissions to be distributed properly imto daughter merozoites. However, the details of these processes are unknown. In this study, authors use confocal microscopy and FIB-SEM to describe the dynamics of mitochondrial division in the asexual schizont stage, gametocytes and oocysts.

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

Summary The authors developed a new reporter parasite line that can facilitates the study of mitochondria cell biology in sexual and asexual stages of Plasmodium falciparum. This strategy gets around the need for antibodies or MitoTracker, that could be toxic in some parasite stages. The authors further provided new insights into how mitochondria divide and interacts with both apicoplast and centriolar plaques (CPs) using informative and cutting-edge imaging. The study showed that mitochondria get segregated during cellular division in a cartwheel model and aligns with the apicoplast. Finally, they highlight a potential unique association between CPs and apicoplast in the later stages of schizogony that might contributes to apicoplast segregation.

Major comments: 1. The authors should provide a positive control in the form of another mitochondrial marker to validate that the signal provided by the fluorescent parasite is specific to mitochondria. They could try to tag a well-known mitochondria protein in the reported cell line and compare the signal using antibody stain.

Although we agree with the reviewer that a co-localization of the mitochondrial marker with a tagged mitochondrial protein would verify the mitochondrial localization of the marker, we do think that the co-localization with MitoTracker (Figure 1 and Figure S2) is a good validation method. MitoTracker is a widely used and accepted mitochondrial dye to stain mitochondria in Plasmodium species and other eukaryotes. We believe that the co-localization of our mitochondrial marker with several MitoTracker dyes is enough to prove mitochondrial localization.

There should be more rigour in the observations: the authors should provide quantification of how many parasites/fields were analysed and the percentage of observations described in Figure 2. Was this data consistent in different parasites/experiments? How many times were the experiment repeated?

To provide more rigor we have included a more detailed description of the number of experiments, the number of parasites imaged, and the percentage of parasites with the described observation:

Line 159: “For each stage, between 11-19 parasites were imaged over two independent experiments and described observations were consistent over all analyzed parasites.”

Line 181: “While this particular activation experiment was performed on a gametocyte culture that did not exflagellate for unclear reasons, it was repeated twice, and very similar results were found in exflagellating males (n=19) (Figure 2C).”

Line 189: “We found close apposition of the dispersed mitochondria to the axonemal tubulin in all 19 exflagellating males that were analyzed (Figure S4).”

More rigour is required also in the analysis of oocyst: what was the criteria to define 'large oocysts' (lines 241-242)? How many oocysts were analysed?

We have added estimated diameters of the oocyst to provide more defined criteria:

Line 238: “At day 7, small oocysts (~10 mm diameter) were observed with a branched mitochondrial network stretched out throughout the cell (Figure 3C).”

Line 241: “Day 10 oocysts were much larger (~35 mm diameter) and the mitochondrial mesh-like network appeared more organized, also localizing to areas directly below the oocyst wall (Figure 3D).”

Line 243: “Some large oocysts (~70 mm diameter) showed a highly organized mitochondrial network, where mitochondrial branches were organized in a radial fashion around a central organizational point (Figure 3E, S5A).”

Line 247: “Some smaller oocysts (~35 mm diameter) at day 13 showed structures that looked like beginning MOCs (Figure S5B).”

Finally figure 5 also lacks rigour: How were the fragments quantified? How many times were the experiment repeated? Is there any statistical difference in different parasite stages? To clarify how mitochondrial fragments were quantified, we added the following sentences to the materials and methods section:

Line 765: “3D visualization and quantifications were done in Arivis 4D Vision software. For mitochondrial measurements, threshold-based segmentation was used. For nuclei, blob-finder function was used for segmentation. Number of segmented objects and volume of objects was determined by Arivis software.”

The experiment was repeated twice, and the second independent experiment, which shows the same mitochondrial division stages, is added to the supplement (Figure S7). We added the following sentence to the text for clarification (Line 310):

“These mitochondrial division stages were confirmed in a second, independent 3D imaging experiment (Figure S7).”

Statistical analysis between different parasite stages was performed and added to Figure 5.

Minor comments: 1. Error bars in Fig S1. should be in a different colour from the line graph (eg. black or white).

Changing the color of the error bars made the figure less clear to interpret, due to their small size. We therefore decided to leave the image unaltered.

Scale bar in Fig 2D is missing.

As indicated in response to reviewer 2, unfortunately, it is not really appropriate to provide a 2D scale bar with a 3D image, since this will not take the depth of your image into account. That is, things that are more to the front are visualized slightly bigger than things in the back and therefore a scale bar would not help for interpreting the size of the depicted objects.

In Fig 4. a square dotted line should be placed to represent the GAP45 crop area.

Changed accordingly.

In Table S3 the authors should provide a colour legend and highlight mitochondria in the micrographs.

Color legend and annotations of RBC, food vacuole, rhoptries, parasite membrane and parasitophorous vacuole membrane have been added to the table.

Lines 282-286. The authors should try to hypothesize why MitoRed does not work for live imaging during schizogony

Despite several attempts to improve imaging conditions to prevent this, including, reduced laser power, increase time interval, better temperature control, and gassing of the imaging chamber with low oxygen mixed gas, parasites remained unhealthy. In the discussion, we hypothesize that the mitochondrial marker might cause parasites to be unhealthy due to phototoxicity.

In Fig. 6B parasite is misspelled

Changed accordingly.

Reviewer #3 (Significance (Required)):

Significance

The current paper provides a significant advance in the study of mitochondria cell biology in P. falciparum. The authors used a new strategy for mitochondria visualization that works well in most of parasite stages, enabling them to described in detail mitochondria and apicoplast division that can be used as guideline for future work. The limitation of this study, is a lack of mechanisms that might explain the reported observations, which leaves the discussion somewhat speculative.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Summary

The authors developed a new reporter parasite line that can facilitates the study of mitochondria cell biology in sexual and asexual stages of Plasmodium falciparum. This strategy gets around the need for antibodies or MitoTracker, that could be toxic in some parasite stages. The authors further provided new insights into how mitochondria divide and interacts with both apicoplast and centriolar plaques (CPs) using informative and cutting-edge imaging. The study showed that mitochondria get segregated during cellular division in a cartwheel model and aligns with the apicoplast. Finally, they highlight a potential unique association between CPs and apicoplast in the later stages of schizogony that might contributes to apicoplast segregation.

Major comments:

1. The authors should provide a positive control in the form of another mitochondrial marker to validate that the signal provided by the fluorescent parasite is specific to mitochondria. They could try to tag a well-known mitochondria protein in the reported cell line and compare the signal using antibody stain.
2. There should be more rigour in the observations: the authors should provide quantification of how many parasites/fields were analysed and the percentage of observations described in Figure 2. Was this data consistent in different parasites/experiments? How many times were the experiment repeated?
3. More rigour is required also in the analysis of oocyst: what was the criteria to define 'large oocysts' (lines 241-242)? How many oocysts were analysed?
4. Finally figure 5 also lacks rigour: How were the fragments quantified? How many times were the experiment repeated? Is there any statistical difference in different parasite stages?

Minor comments:

1. Error bars in Fig S1. should be in a different colour from the line graph (eg. black or white).
2. Scale bar in Fig 2D is missing.
3. In Fig 4. a square dotted line should be placed to represent the GAP45 crop area.
4. In Table S3 the authors should provide a colour legend and highlight mitochondria in the micrographs.
5. Lines 282-286. The authors should try to hypothesize why MitoRed does not work for live imaging during schizogony
6. In Fig. 6B parasite is misspelled

Significance

The current paper provides a significant advance in the study of mitochondria cell biology in P. falciparum. The authors used a new strategy for mitochondria visualization that works well in most of parasite stages, enabling them to described in detail mitochondria and apicoplast division that can be used as guideline for future work.

The limitation of this study, is a lack of mechanisms that might explain the reported observations, which leaves the discussion somewhat speculative.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

During its development and growth, the human malaria parasite P. falciparum needs to guarantee that cellular organelles, including the mitochondrion and the apicoplast, will be divided and segregated correctly into the daughter parasites. However, the details and mechanisms of these processes are not clear. Here, authors provide a description of mitochondrial replication and segregation in P. falciparum schizonts, gametocytes and oocysts. They generated a reporter cell line by attaching mScarlet red fluorescent protein to the mitochondrial heat shock protein 70-3 and used high-resolution 3D-imaging and focused ion beam scanning electron microscopy to study mitochondrion dynamics in the asexual, gametocytes and mosquito stages. The authors found that in schizonts, the mitochondrion forms a cartwheel structure at the end of early segmentation stage with full division occurring only at a late stage of schizogony. Apicoplast division happens after nuclear division but is complete before nuclear division is completed. Authors also found apicoplast but not mitochondrion is associated with centriolar plaque (analogue of centrosome in P. falciparum) during the schizogony. At the end, authors proposed their model of nuclei, mitochondrial and apicoplast division in the asexual stage schizogony. This well-written manuscript provides insights on mitochondrion and apicoplast fission in P. falciparum blood stage schizogony and mitochondrion dynamic in the blood, gametocytes and mosquito stages. Questions and suggestions are below:

Major comments

The marker line forms mature oocysts but does not produce salivary gland sporozoites. This phenotype needs to be explained more clearly. Are sporozoites produced in the midgut, are they released into the hemocoel?

Does introduction of an exogenous copy of HSP70 influence total HSP70 expression in the parasite, and can this cause the observed defect in sporozoite production? Did authors try to tag the endogenous HSP70 to see if it's a suitable reporter?

Did authors compare the growth of the reporter parasite line to wild-type in gametocytes and oocysts? In figure 1A and Methods, are all MitoTracker stains incubated at 100 nM for 30 minutes? Did authors try to optimize the conditions to improve quality Mitotracker staining can be improved? In figure 1B, can authors replace the figures for the first ring? The parasite does not seem healthy and the scale bar is shorter than the others. Can authors define DIC in the legend? In figure 8, it looks like some apicoplasts are not associated with the CP, contrary to what is stated in the text, for eg the one at the 7 o'clock position in stage 3. The Discussion should mention the failure in generating sporozoites from this reporter line Can authors discuss the SIL7 locus as the site of integration, in the context of potential effect of its disruption on sporozoite production. Authors should explain criteria for identifying organelles in FIB-SEM images eg mitochondria, apicoplast etc. FIB-SEM images show other prominent organelles in these images (dense granules? hemozoin crystals?). It would be helpful for reader orientation and greater appreciation of the work if these organelles were marked as well.

Minor comments

The format of blood, mosquito and liver stage is not consistent. Eg. in line 17, 22, 56 and 65. Some has a dash line while some doesn't. In line 36, numbers of cases and death by malaria are by estimation. Can authors define Plasmodium falciparum as P. falciparum in line 37? The sentence in line 57-59 is confusing. At the end of schizogony, the daughter merozoite/sporozoite has one mitochondrion but it's multiple in the parasite. Can authors specify which mitochondrial dyes are toxic in line 76? In line 115, can authors indicate the Gene ID for PfNF54? Can authors define the reported parasite line as MitoRed here instead of line 125? In line 134 and 540, use punctate instead of 'punctuated'? In line 161 to 163, can authors also cite ref 19? In line 174, pH change can also trigger gametocytes activation. In Figure S4, please indicate the percentage of parasites having close apposition of mitochondrion to axonemes. Line 237 to 239, please clarify why authors think there is one fragment in mitochondrial. In line 259, the ookinete stage is II to IV. In line 281, please define RBC. In figure 5A, please provide a scale bar for the original and reconstructed image. Should the unit of fragment volume be um3 but not um? Can author do a statistical analysis in Fig 5B and 5C to show the stage at which the majority of nuclei and mitochondria divide? In figure 5D, the labels on Y axis are not the same size. In figure 6, what's the green black color organelle in the first column (like the organelle showing up as 4 in the first one, at 1/2/6/8 o'clock)? Can authors provide annotations of organelles using arrows at least in the supplementary? In line 717, the font of ul is not consistent with others like line 691. In line 731, 37 {degree sign}C.

Significance

The mitochondria of human malaria parasite Plasmodium falciparum differs from the host's and is an intriguing drug target. During the asexual blood stage replication, parasite mitochondrial elongates to form a branched network and undergoes rapid fissions to be distributed properly imto daughter merozoites. However, the details of these processes are unknown. In this study, authors use confocal microscopy and FIB-SEM to describe the dynamics of mitochondrial division in the asexual schizont stage, gametocytes and oocysts.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

This study investigates mitochondrial and apicoplast division and distribution during the life cycle of Plasmodium falciparum. Utilizing the MitoRed reporter line for fluorescent mitochondrial marking and employing high-resolution 3D imaging techniques, including FIB-SEM, the research unveils the dynamics of these essential organelles across various stages of the parasite's development. The authors' work marks a significant step forward in understanding the cellular biology of Plasmodium falciparum, offering novel insights into the dynamics of mitochondrial and apicoplast division. By addressing the additional comments and incorporating recent findings and clarifications, the research not only underscores the complexity of these processes but also situates the study within the continuum of apicomplexan parasite research.

Major comments:

• Suitability of Reporter Line for Oocyst Development: The conclusion regarding the limitations of the MitoRed line for oocyst development stages prompts a discussion on alternative approaches, such as mito trackers, to validate observations in these stages. In the current state, it is difficult to conclude whether the data presented are only true for this specific transgenic line.
• Analysis of Mitochondrion and Apicoplast Association with CPs: Could the author elaborate on how their statistical power and image data support assertions of random association between organelles and CPs (line 438-439) and the dynamic nature of Mito-CP interactions (line 504)? In addition, could the authors comment/discuss their findings regarding the distance between Mito-Api compared to the one reported in Figure S2 of Sun et al. preprint: bioRxiv 2022.09.14.508031; doi: https://doi.org/10.1101/2022.09.14.508031
• Incorporation of Recent Findings into Schematic Models: I recommend the authors modify their current model in Figure 8 to reflect on recent findings on CP outer domain contact with the parasite plasma membrane (PPM) post-mitosis as demonstrated by Liffner et al. PMID: 38108809.

Minor comments:

• Reference to WHO Report: The manuscript cites malaria incidence and mortality data from an older WHO report. Given the availability of the 2022 WHO reports, authors should update the text and citation (line 36).
• Clarification of Host: The term "its mitochondrion" (line 42) should be specified as "human mitochondrion" to clearly distinguish between the two different hosts.
• Terminology of Parasite Development Stages: The usage of "schizogony" to describe division processes in liver and mosquito stages could be misleading due to the distinct process of endopolygeny nuclear-like division observed during sporogony (line 56; PMID: 31805442). I would recommend the authors use a more general language, such as cell division.
• Prior Research on CP and Apicoplast Association: The observation of centriolar plaques (CPs) associating with the apicoplast (line 91) has precedents in the study of other apicomplexan parasites, such as Sarcosystis (PMID: 16079283). Acknowledging and discussing these findings would contextualize the current study within the broader range of the most commonly studied apicomplexan parasites.
• Depth of Imaging Data: Could the authors indicate the width of their z-stack, for instance, in Figure 1? I would also suggest the authors use hours of post-infection (h.p.i) for clarity (lines 234-254) to aid comprehension by a broader audience as they do later in the manuscript.
• Visualization of Mitochondrial Structures: Suggestions to include or reference images of bulbous mitochondrial structures (line 445) directly in the main text or within key figures (e.g., Figure 6) would help the reader understand what and where are these bulbous structures.
• Organelle Communication and Division Mechanisms: The discussion of bulbous invagination structures (buildings) (line 469) and their role in organelle division is interesting; could it be also for organelle communication or storage? Can the authors expand the discussion about it?

Significance

The study is a significant contribution to the field of parasitology, particularly in understanding the cellular biology of Plasmodium falciparum. The development of the MitoRed reporter line is a notable advancement, allowing for the real-time visualization of mitochondrial dynamics. This tool could be invaluable for future studies exploring parasite biology's intricacies and identifying new antimalarial drug targets. Furthermore, while the study provides detailed insights into the division and distribution of mitochondria and apicoplasts, the molecular mechanisms underlying these processes remain to be fully elucidated. Specifically, the role of specific proteins in mediating these divisions and the potential interplay between mitochondrial and apicoplast dynamics during parasite development warrant further investigation.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

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

*The study examined the mechanisms behind the nuclear transport of capsid proteins of various flaviviruses. The study used mass spectrometry to identify the interaction partners of JEV capsid protein and found Importin 7 as the top hit. After validating this interaction with IP-western blotting, using IPO7 knock-out cells they showed that the nuclear accumulation of capsid is dependent on IPO7. Moreover, they also observed nearly 10-folds reduction in titre of virus produced from knock out cells without reduction in virus replication or particle assembly.

The study needs improvements to bring it to publication standards. Some overaarching problems include, all capsid localization studies being done with GFP-tagged capsid, and not wild type capsid produced during authentic infection, lack of quantitation of most of the localization data and not showing capsid localization from infection experiments in knock out cells, and no in-depth analysis of the potential mechanisms behind the observed reduction in titre in knock out cells etc.

Thank you for your constructive comments. We have sincerely answered all of them, as shown below. We hope you are satisfied with our additional data and the revised manuscript.

The major comments are

Fig 1B: Please add quantitation and statistical analyses of the ratio of nuclear and cytoplasmic capsid protein of all different capsids used. Also include western blot to prove that there is no cleavage between Capsid and GFP and the green signal indeed comes from the fusion protein. Ideally you should use capsid alone instead of a fusion protein for at least selected few constructs to prove that the Capsid-GFP behaves identical to Capsid alone.

Following the reviewer’s comments, we have added quantification and statistical data in Figure 1D. We have added CBB data and western blot data in Figures 1B and S1. Because recombinant proteins of low molecular weights were artificially translocated into the nucleus through diffusion, less than 20 kDa proteins are typically used as GFP or GST fusion proteins for the IJ and PM experiments. Instead of IJ and PM experiments, we have added data on the translocation of the non-tagged core using IFA and its statistical data in Figure 1A. Although in vitro data on the translocation of capsid protein differ somewhat from IFA data, the data on nuclear translocation of core proteins are consistent across different experiments.

Fig 1C: It is unclear from the figure legends the WT JEV capsid means GFP-Capsid or Capsid alone. You should clearly state the GFP part if the construct includes GFP. Quantitation and statistics are missing and the information on how many independent experiments were performed is also not included in the figure legend.

Following the reviewer’s suggestion, we have described that the JEV proteins fused GFP as follows: “AcGFP-JEVCoreWT or AcGFP-JEVCoreGP/AA” (Line. 771). We added quantification and statistical analysis as shown in Figure 1E. IJ and PM experiments were performed three times independently and described in the legend of Figure 1 in the revised manuscript (Lines 773–774).

Fig 2B: Quantitation and statistics are missing. Ideally, the data need to be reproduced with Capsid alone instead of Capsid-GFP. A positive control is needed for the activity of Bimax to prove that the drug was working in the assay.

We have added quantitative and statistical data in the revised Figure 2B. As mentioned above, capsid alone is potentially translocated into the nucleus artificially using the IJ and PM assay. Bimax binds to importin alpha but not importin beta, specifically inhibiting the importin alpha/beta pathway. The RanGTP mutant binds to the importin beta family, including importin beta 1, and widely inhibits importin beta-dependent nuclear import. These inhibitors are well-characterized and recognized in the field. We cited the following reference: Tsujii et al., JBC, 2015.

Fig 2C: How do you reconcile the IP mass spectrometry data that Importin b1 is the second strongest hit with the lack of IP interaction you observed in fig 2C?

As shown in Figure 2C, importin b1 does not interact with the JEV core. Importin b1 is the most abundant member of the importin beta family. Thus, it might be a non-specific interaction between importin b1 and the JEV core. Therefore, we excluded importin b1 from further analyses. We added a sentence to explain why importin b1 was excluded on Line 145.

Fig 3C: How many independent confirmations of this experiment was performed?

All IJ and PM experiments were performed thrice independently. We described this in the legend of Figure 3 in the revised manuscript (Line; 794).

Fig 4A and B: Add quantitation for the western blot. 4A-D Include data on the number of biological repetitions. 4C-D: Add quantitation and statistical analyses of the ratio of nuclear and cytoplasmic capsid protein.

We have added quantification data, as shown in Figures 4A and 4B. All experimental results shown in Figures 4A, 4B, 4C, and 4D were performed thrice independently, as described in the legend of Figure 4 of the revised manuscript (Lines; 810-812).

Fig 5B. This data should be shown in the context of infection with untagged Capsid at least for 1-2 viruses. This is a serious drawback of the present study as there is no clear evidence presented that the native capsid protein in an infection context depend on importin 7 for nuclear accumulation and behave similar to the GFP-Capsid constructs being used.

Following the reviewer’s concerns, we used an un-tagged JEV and DENV core to examine core translocation in WT or IPO7KO Huh7 cells. As shown in Figures 5C and 5D and their quantitative data, nuclear translocation of JEV and DENV core protein was inhibited in IPO7KO Huh7 cells. We tested the translocation of core protein upon infection with DENV as shown in Figure 5F. Although we could not examine ZIKV infection because we could not find appropriate antibodies against the ZIKV core, these data are consistent in that nuclear translocation of flavivirus core protein largely depends on IPO7.

Fig 5 A-D: Two repetitions are insufficient; a minimum of three biological repeats and statistical analysis need to be included. 5E-F: You cannot do statistics on two repeats, need minimum of three repeats to perform statistical analysis. 5G-H: I presume three repetitions based on the data points shown, this should be clearly stated in the figure legend.

We repeated three independent experiments, shown in Figures 5A and 5C-5F, and indicated them on Lines 823. We have added statistical data in Figures 5B-5F. We have corrected the statement of biological repeats in Figures 6A and 6B (Lines; 843-844).

Fig 5E-G: Taking the data of 5E and 5G together it seems Importin 7 functions as the level of particle release and not particle assembly or maturation. Have you checked for the specific infectivity of the particles released from knock out cells to determine the reason behind the reduction in virus titre? You could look at the prM maturation by furin cleavage to check it this is altered in the IPO7 knock out cells.

We determined the ratio of infectious titer per 103 copies of viral RNA in Figure 6F. The proportion of infectious viruses targeting extracellular JEV RNA was decreased in IPO7KO cells. Simultaneously, no difference was observed in the proportion of infectious viruses targeting intracellular JEV RNA between WT and IPO7KO cells. Although we could not find appropriate antibodies against the JEV core, we checked prM expression using the DENV virus. The expression of prM was slightly increased in JEV-infected IPO7-KO Huh7 cells (Figure S3D). This result suggests that the efficiency of prM cleavage by furin was partially involved in the impairment of infectious virus release in IPO7KO Huh7 cells.

Fig 5H: Have you checked if the observation regarding intracellular RNA levels in 5F is applicable to these viruses as well.

We checked the intracellular RNA levels of DENV and ZIKV-infected cells. In contrast to JEV, intracellular ZIKV or DENV RNA showed no difference in IPO7-KO Huh7 cells (Figure 6H). We discuss it in Discussion section (Lines; 269-271)

Fig 6: The figure legend "Data are representative of two (A, B) independent experiments and are presented as the mean {plus minus} SD of three independent experiments (C)" is confusing. The sentence should be reworded to state the repetitions separately for independent experiments. Fig 6C should show original titres and not percentages.

We have corrected Figure legends according to the reviewer’s comments. We have showed the original titers in Figures 6C and 6E.

Fig 7B: This experiment should be performed in IPO7 knock out cells to confirm that the observed reduction of core mutant is mainly contributed from its lack of interaction with IPO7 and not from any other confounding factors.

Following the reviewer’s suggestion, we performed SRIP experiments for GP/AA mutation using IPO7KO Huh7 cells. As shown in Figure 7C, the SRIPs harboring WT core were impaired in IPO7KO Huh7 cells; no difference was observed in the SRIPs harboring GP/AA mutations in WT and IPO7KO cells. These results suggest that IPO7-dependent nuclear translocation of core protein is important for the viral release.

Reviewer #1 (Significance (Required)): While the authors could convincingly demonstrate the interaction between capsid and IPO7, how that interaction results in the observed reduction in viral titre is largely unexplored. As all the localization data used a GFP-tagged capsid outside an infection context, this reviewer is not confident that all the reported observations will hold in an infection setting. This need to be urgently addressed to rise the confidence about the observation. The current data is insufficient to confidently attribute the change in titre to the interaction between capsid and IPO7 and the capsid localization to the nucleus. Knocking out IPO7 could have pleotropic effects independent of capsid nuclear accumulation that could lead to the observed titre reduction. This need to be addressed further before linking both these phenotypes. Certain key experiments needed to address these questions are currently missing. While the interaction of Capsid with IPO7 is certainly intriguing, the implications of this interaction on virus biology needed further investigation before clear conclusions can be drawn regarding this observation.

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

Summary: In this study Itoh and colleagues investigate the mechanism, role and impact of the nuclear localization of the flavivirus core protein. The import of the core protein has long been observed and investigated and herein the authors use some novel approaches to identify potential cellular binding partners that facilitate nuclear import. Via proteomics and biochemical approaches they determine that importin-7 plays a crucial role in the import of the core protein that appears to be conserved across Flavivirus members. In general the findings and conclusions are sound but there are some significant omissions and caveats that warrant further investigation.

Major comments: - one of the major caveats of the study is that the flavivirus NS5 protein also translocates to the nucleus in an Importin-alpha/beta dependent manner. Therefore how can the authors discount any impact of preventing NS5 import, in addition to core, on virus and SRIP replication and production. Some discussion, if not additional experiments are required here ie. NS5 localization in the KO cells during virus infection

We examined the localization of NS5 using IPO7KO Huh7 cells. As shown in Figure S2D and S2E, we confirmed that IPO7 was not involved in the nuclear localization of NS5.

• the localization is predominantly nucleolus rather that nucleoplasm when compared to the SV40 NLS. What are the sequence differences between the flavivirus proteins that potentially could account for this? A protein known to localize solely to the cytoplasm should also be used eg. NS1 or NS3.

The JEV core does not contain a consensus nucleolar localization signal. Nuclear localization of NS5 depended on importin-α similar to the SV40 NLS, while flavivirus core proteins were independent of importin-α. Gly42 and Pro43 are critical amino acids for the nuclear localization of the core protein, as shown in Figures 1C and 1D. The Gly42 to Pro43 of core proteins were well-conserved in the core proteins of the Flaviviridae family.

• controls for Figure 2? Ie. a protein known to be inhibited by Bimax but not the RanGTP mutant and vice versa.

Bimax binds to importin alpha but not importin beta and specifically inhibits the importin alpha/beta pathway. The RanGTP mutant binds to the importin beta family, including importin beta 1, and widely inhibits importin beta-dependent nuclear import. These inhibitors are well-characterized and recognized in the field. Therefore, we have cited the following references: Tsujii et al., JBC, 2015.

• Fig 5. Difference with WNV and DENV in nucleoplasm localization but also WNV still appeared to have Core in the nucleus in the KO cells

We agree with the reviewer’s comment about differences in nuclear localization among the viruses using the IJ assay. We have added new data to examine the localization of the DENV core after DENV infection. Nucleolar localization of the DENV core following DENV infection was observed, as shown in Figure 5F. Therefore, differences in nucleoplasm or nucleolar localization among different viruses shown in Figure 1C and Figure 5B might be artifacts of recombinant proteins. One possibility is that the localization of core proteins using IJ assay was detected by anti-GFP antibodies. Although purified GFP-core proteins, as shown in Figure 1B and S1, were observed as a single band of fusion proteins, core proteins of WNV and DENV might be cleaved during IJ experiments, and GFP alone might be detected at nucleoplasm, as shown in Figure 5B. Because our study focused on the nuclear translocation of flavivirus core proteins, the detailed localization of each core protein in the nucleus will be studied in the future.

• Fig 5C still has substantial JEV and DENV core but not WNV and ZIKV. Why is the DENV and WNV localization pattern different to Fig 5B?

We appreciate the reviewer’s suggestion; we re-checked all our data presented in Figure 5B and other data shown in Figure 5B. We quantified the ratio of nuclear localization as shown in the right of Figure 5B. Our quantification data showed that the nuclear transport of all core proteins used in this study was dependent on IPO7. In contrast, Figure 5A shows that nuclear translocation of WNV core protein is partially dependent on IPO7. This discrepancy might be explained that nuclear translocation of WNV core protein might be regulated by several nuclear carriers. We described this in discussion section (Line; 250-254).

• Fig 5F, does the KO also restrict NS5 from entering the nucleus and could this then results in increase polymerase activity confined to the cytoplasm resulting in more viral RNA?

Following the reviewer’s suggestion, we examined NS5 localization during viral infection and plasmid transfection, as shown in Figure S2D and S2E. Previous data regarding the nuclear localization of NS5 depended on importin-α. Our data are consistent with previous reports that IPO7 was not involved in the nuclear localization of NS5. In contract to JEV, we also confirm that intracellular ZIKV or DENV RNA showed no difference in WT and IPO7-KO Huh7 cells (Figure 6H). As described in the discussion, other factors, such as antiviral factors, might be involved in IPO7-mediated nuclear transports in JEV infected cells (Line; 269-271).

• Why was WNV infection not performed in Fig 5H? What where the viral tires compared to for the relative % values?

Because our institution does not have a BSL3 facility, we could not use WNV. Following the reviewer’s comment, we showed viral titers in Figure 6G.

• Fig 6B, still a significant amount of core present in the nucleolus. Also WT cells have (almost?) no cytoplasmic staining for core where this could be clearly observed in the WT cells in Fig 5D. Why the difference?

Plasmid transfection of AcGFP-Core WT showed that almost all core proteins were located in the nucleus. We assumed that AcGFP might influence nuclear exports of core proteins or the efficiency of nuclear transports as shown in other data of in vitro experiments. However, our finding that IPO7 was involved in the nuclear transport of core proteins is consistent.

• In Fig 7B, D and E, when were the SRIPs collected and what was the time period after subsequent infection?

Following the reviewer’s comments, we have added more details on SRIP experiments in Materials & Methods (Line; 521-523).

• In Fig 7C was the luciferase measured from the initial transfection and how did it correlate with RNA production? A 15-fold increase in replicon RNA actually seems quite low over a 48h period

Because large amounts of in vitro-transcribed replicon RNA were injected into cells in this experiment, we observed that significant amounts of luciferase values were detected after 4 h. However, the 15-fold enhancement in luciferase value was consistent with previous reports (PMID: 30413742, PMID: 17024179). We have added references in the revised manuscript.

• quantitation is required throughout all of the experimental IFA data provided

Following reviewer comments, we have quantified all IFA data and showed their results.

Reviewer #2 (Significance (Required)):

The nuclear translocation of flavivirus protein has long been studied and it has been observed that the core, NS5 (RNA polymerase) and potentially the NS3 (helicase/protease) proteins all translocate the nucleus. Importin alpha and beta have been shown to facilitate this process. The authors aim to extend this to identify importin-7 as a major cellular factor enabling nuclear translocation. Overall the experiments have been performed well but there is a lack of quantitation for many of the results an suitable controls are required.

I am a researcher in the field of flavivirus replication

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

In the presented study the authors identified and mechanistically investigated how Flaviviruses including Japanese encephalitis virus (JEV), Dengue virus (DENV), and Zika virus (ZIKV) commonly use importin-7 (IPO7), an importin-β family protein, as a cellular carrier protein to facilitate nuclear core protein translocation. The authors evaluated how the production of infectious viruses is regulated by IPO7 using cellular infection models including IPO7-deficient knockout cells. In the submitted manuscript, the authors provide evidence that IPO7 facilitates viral core protein import into the nucleus of infected cells, which is essential for effective Flavivirus replication. Taken together, the study is interesting to a broader readership with interest in molecular virology, and its findings are informative for potential future targeting of IPO7 to affect flavivirus replication using small molecule drugs. The manuscript is well-written and easy to follow, the methods are appropriate, the structure is logical, and statistical analysis is adequate.

Major comments:

• It is unclear why the authors specifically used Ala substitution at Gly42 anb Pro43 to obtain the abolishment of nuclear core protein localization. It would be helpful to put this into more context and explain the approach.

Mutations of Gly42 and Pro43 to Ala were previously reported and characterized by the same research group (PMID: 15731239). Following the reviewer’s comment, we have added more details of GP mutations in the text (Lines 66–70).

• In Figure 4, the authors claim that the binding between IPO7 and RPS7 is disrupted upon the addition of RanGTPQ69L. This is not clearly evident from the pulldown experiment and should be proven experimentally with additional experiments (e.g. by using an imaging approach) to underline the statement that the binding mode of IPO7 to the JEV core protein is similar to that of RPS7. Loading controls for pulldown blots should be added.

As described in response to the comment by reviewer#2 regarding Figure 2, the RanGTPQ69L mutant inhibits the interaction between the importin beta family, including IPO7 and its substrates, by directly binding to importin beta proteins. For the benefit of readers without knowledge of the typical Ran-dependent nuclear transport mechanism, we have described its effects with several cited references (Dickmanns et al., 1996; Tachibana et al., 2000). We referred to a study that showed that IPO7 transports RPL proteins, including RPS7 (Jäkel and Görlich, 1998). The data in Figures 4A and 4B demonstrate that adding RanGTPQ69L remarkably reduces the binding of IPO7 to the Core proteins and that the effect is more robust than that for RPS7. We believe that these results are experimentally valid, indicating that nuclear transport of Core proteins by IPO7 is achieved through a typical Ran-dependent pathway.

• Most methods used are presented logically but require some more details so that they can be reproduced. In particular, the difference between Figure 4 E and 4H is confusing. What is the difference? Is 4E showing intracellular viral titers and 4H infectious viral titers in the supernatant of cells? Clarification needed. Put relevance of these experiments in context of the hypothesis.

We apologize for the confusion regarding the data in Figures 5E and 5H (we assume). These data were derived from the same experiments, except for the time-course data presented in Figure 5E. We have removed Figure 5E to simplify our results.

• Identical phenotypes induced by IPO7 knockout in a number of HuH7 clones are shown in Figures 6A to 6C. This data does not add to the overall understanding and should be moved to supplementary figures. Why are 293T cells used in experiments shown in Figure 6D and 6E? What is the relevance of kidney cells to Flavirius infections?

Following the reviewer’s comments, we have moved Figure 6 to supplementary figures. We used 293T cells because of efficient JEV propagation and gene-deficient efficiency. We wanted to demonstrate that our data are not Huh7-dependent through experiments in 293T cells.

• Prior studies are referenced appropriately, however, in a recent study it was demonstrated that IPO7 is stabilized upon Epstein-Barr Virus infection and that IPO7 presence is required for the survival of host cells (Yang YC, Front Microbiol. 2021 Feb 16;12:643327. doi: 10.3389/fmicb.2021.643327).

We deeply appreciate the publications in these fields. Following the reviewer’s comment, we have cited these references.

This important study about the physiological relevance of IPO7 during viral infections has not been cited by Itoh and colleagues in the presented study. However, the results of the uncited study are very relevant to the provided manuscript, since Itoh and colleagues are using IPO7 knockout cells to investigate its function in Flavivirus core protein nuclear import. Hence, the authors should perform cell survival and cellular fitness experiments to demonstrate that observed phenomena of reduced viral replication and virus export in IPO7 knockout cells are independent of compromised cellular fitness due to IPO7 deficiency.

We evaluated cellular fitness between WT and IPO7KO Huh7 cells using PI (Propidium Iodide) staining through flow cytometry. As shown in Figure S2F, no differences were observed in cell viability between WT and IPO7KO Huh7 cells. It suggests that viral titers reduced in IPO7KO Huh7 cells are not involved in cellular fitness.

Minor comments:

• Describing Figure 3B, the authors state that they focused on IPO7 among the core binding proteins belonging to the importin-b family, because IPO7 "was identified the most peptides" in the mass spectrometry approach. This requires a more detailed explanation. Also, an explanation of why HEK293T cells were used for this approach and not HuH7 cells, as used predominately in most parts of the study, would provide more clarity to the reader.

We focused on IPO7 because it had the highest number of detected peptides, and we found that the second most detected peptide, IPOB1, did not bind to JEV core proteins as shown in Figure 2C. Therefore, we included the lack of interaction between IPO7 and IPOB1 as part of the rationale.

• In Figures 4E and 4F, colour coding is missing.

We have indicated color coding in this data. Thank you for your comments.

Reviewer #3 (Significance (Required)):

The provided manuscript 'Importin-7-dependent nuclear localization of the Flavivirus core protein is required for infectious virus production' by Itoh and colleagues investigates a topic with important scientific relevance. The presented study builds on previous findings by the authors where they have demonstrated that Flavivirus core protein nuclear localization is actually conserved among Flaviviridae and represents a potential target for broad-range antiviral small molecule drugs (Tokunaga et al., Virology, 2020 Feb;541:41-51). However, our understanding of Flavivirus core protein nuclear localization during viral replication and how the processes could potentially be targeted using novel therapeutic drugs remains elusive. Here, the provided manuscript addresses a mechanistic investigation of how the Flavivirus core protein is actually translocated from the cytoplasm to the nucleus of infected cells. The study is informative particularly for virologists with expertise in Flavivirus replication.

However, from my point of view as a virologist investigating host-pathogen interactions with a strong interest in clinical translational, the manuscript requires a more careful evaluation and interpretation of some results of key experiments. In addition, some of the results need to be more precisely described for clearer understanding by a broader readership.

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

Summary: In the manuscript entitled "Importin-7-dependent nuclear localization of the Flavivirus core protein is required for infectious virus production", by combining proteomics, CRISPR/Cas9 gene KO, CLSM and standard virology techniques, Yumi Itoh report novel data concerning the involvement of IPO7 in the nuclear and nucleolar localization of Flaviviridae core nuclear and nucleolar localization and viral particle release. Surprisingly, IMPa/b1 inhibition via Bimax2 does not affect core nuclear transport, whereas both RanQ69L and WGA did so. The authors try to identify the cellular transporters involved in core nuclear import, and to this end performed a MS spec analysis of JEV core interactors, which yielded IPO7 as the most likely candidate. After confirming the result by Co-IP, the authors go on showing most core proteins require IPO7 for nuclear delivery using Huh7 and HEK7 IPO7-KO cells, with the exception of WNV core which was able to partially enter the nucleus. In such cells, upon infection, extracellular (but not intracellular) viral titers were strongly reduced, a phenotype which was observed with a JEV core mutant bearing the Gly42 and Pro43 to Ala substitutions in a previous study.

Major comments: - The major conclusions of the study are:

1.IPO7 is the main driver of core nuclear transport 2.Core nuclear localization is somehow important for viral particle release Both conclusions are well-supported by experimental evidence.

Methods are clear and precise, the study appears to have been produced with high quality standards, and so is the presentation of the results. A few controls however should be added to increase the reliability of the results presented here (see below)

Since the authors attempt to link the phenotype observed on virus release upon IPO7 KO to defects on core nuclear import by making a parallelism with core GP/AA mutant, it would be important to know the behavior of such virus in Huh7 wt and Huh IPO7 KO cells. In other words, is GP/AA JEV released efficiently in Huh7 IPO7 KO cells?

We have added new data examining the propagation of the GP/AA JEV mutant in IPO7KO Huh7 cells (Figure 6F). Our new data showed that there were no differences in the propagation of the GP/AA mutant in WT and IPO7-KO Huh7 cells.

A similar approach can be applied to data shown in Figure 7 (effect on release on a capsid nuclear deficient mutant). This would help understand if IPO7 KO, viral release defects and core nuclear import are somehow linked.

We produced SRIPs harboring GP/AA core using WT and IPO7KO Huh7 cells and demonstrated that the number of infectious viruses produced by WT and IPO7KO Huh7 cells was the same (Figure 7C).

Minor comments:

INTRODUCTION • “Flaviviruses...are mosquito-borne human pathogens" What about tick borne encephalitis virus?

We have corrected it (Line; 43-44).

• " replication.... occur in the endoplasmic reticulum (ER)" This sentence is a bit inaccurate. Flaviviridae RNA replication occurs in so-called viral replication factories, double membrane vesicles which are partly derived from the ER. see "PMID: 26958917".

We have corrected this sentence according to the reviewer’s comment (Line; 60-62).

• "it is known that some flavivirus core proteins are translocated from the cytoplasm into the nucleus" o I think the first evidence of core in the nucleus dates back to 1989, and here it might be appropriate to cite the original reference: "PMID: 2471810". o It might be worth mentioning that NS5 has also been reported in the nucleus (See "PMID: 28106839")

We have corrected the sentence according to the reviewer’s comment (Line; 63-65).

• "In the cytoplasm, NLS-containing proteins are recognized by importin-α " o This is true only for classical NLSs, not every NLS binds IMPa, as the authors confirm in this study! Indeed, we have also PY-NLS, IPO7 specific NLSs, IPOb1 NLSs, etc. I therefore suggest rephrasing.

Thank you for pointing out the exact description of NLS. We agree with the reviewer’s comment that “NLS” includes all types of signal sequences, such as PY-NLS. To clearly distinguish between the CLASSICAL nuclear transport pathway by importin α/β1 and the various nuclear transport pathways by the importin β family, such as transportin, we refer to NLS as classical NLS (cNLS) in the document. We have modified the following sentence by adding “such as transportin” and “without importin-α.”

RESULTS

• Fig. 1. o it is not clear what is new here, with respect to what has been already published. The authors should clearly differentiate novel findings from confirmatory results

Thank you for your suggestion. We would like to introduce our new assay using recombinant virus core proteins, as shown in Figures 1C and 1D. The data shown in Figure 1 are crucial for understanding our data in Figure 2, and we believe this figure is required for broad-ranging readers.

Fig. 2 and 4 o Proteins whose nuclear transport is dependent on IMPa/IMPb1 (such as SV40 NLS) are lacking here

Bimax binds to importin alpha but not to importin beta and specifically inhibits the importin alpha/beta pathway. The RanGTP mutant binds to the importin beta family, including importin beta 1, and widely inhibits importin beta-dependent nuclear import. These inhibitors are well-characterized and recognized in the field. Therefore, we have cited the following references: Tsujii et al., JBC, 2015.

• Fig.5 o It would be important to know the effect on total virus infectivity (intracellular + extracellular) and total viral RNA. It would also be important the effect on RNA replication by using a subgenomic viral replicon (with deletion of the env gene for example). The question here is if IPO7 depletion affects to any extent viral genome replication, and this is impossible to assess in a fully assembling system. We determined the ratio of infectious titer per 103 copies of viral RNA in Figure 5D. The proportion of infectious viruses targeting extracellular JEV RNA was decreased in IPO7KO cells, and there was no difference in the proportion of infectious viruses targeting intracellular JEV RNA between WT and IPO7KO cells. We examined the effects of IPO7 on viral RNA replication of subgenomic replicon. We showed that the deficiency of IPO7 enhanced viral RNA replication as shown in Figure 7E. As described in the Discussion section, IPO7 may transport other factors possessing antiviral activity against flaviviruses. These data will be investigated in the future.

o Panels A-F legend is missing, consider adding it?

We have added more details to Figure 5A-5F following the reviewer’s suggestion.

• Fig.7 o I did not completely understand how NLuc is the readout here To quantify RNA replication, we quantified Nluc values using a plate reader. We have added more details on the reporter assay in Materials and Methods (Line; 521-523).

o Also, I do not understand if the effect of GP/AA substitution of panel B has already been reported or if it is a novel finding

Previous reports regarding the effect of GP/AA substitution of JEV showed the impairment of infectious virus release. However, the SRIP assay was performed to examine the viral release step. Our detailed data showed that the lack of IPO7-mediated nuclear transport of core proteins impaired infectious viral release, and our new results using SRIPs harboring GP/AA core showed that the lack of nuclear transport of core proteins also impaired the release of infectious viruses. Our data strongly suggest that the lack of nuclear transport of core proteins influences the viral release.

• All CLSM figures lack quantification (Fn/c; Fno/n)

We have added quantitative data for IFA experiments in our revised manuscript.

DISCUSSION

• "The nuclear entry of viral genomic DNA has been demonstrated to involve IPO7" o It would be nice to know which viruses the authors are freeing to here

We have added the virus name and corresponding references.

• "While RNA viruses, including flaviviruses, are considered to replicate in the cytoplasm of mammalian cells, increasing evidence suggests nucleolar localization of the viruses " o I suspect Rawlinson did not propose the viruses localize to the nucleolus, as this sentence seems to imply. Rather, a trafficking of viral proteins to nucleoli, to manipulate cell function, is more realistic. I suggest considering rephrasing. We have corrected this sentence.

Reviewer #4 (Significance (Required)):

SECTION B - Significance ========================

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field. As alluded to above, this work presents several advances of current knowledge in the field of viral proteins nuclear trafficking, and in Flavivirus biology. The finding of most core proteins depending on IPO-7 is novel and intriguing, and opens the question of what makes WNV core special. Indeed, this protein nuclear targeting is only partially inhibited in IPO7 deficient cells. The fact that the authors extend their findings to several Flaviviruses adds significance. The role of nuclear core for virus release is also intriguing, but appears poorly characterized. In this respect a mechanistic explanation of the phenomenon would be highly desirable to increase the significance of the work presented here.

In this context I would have a few suggestions:

A) The authors performed MS spec on JEV core, this most likely resulted in a long list of "hits". However, they only report IMPb superfamily members. This is perfectly fine, since they focus at identifying partners responsible for nuclear import. However, it might be helpful for understanding the role of nuclear core. By comparing MS of wt core and GP/AA core, and or wt core in wt and IPO7KO cells, authors could identify core biding partners in the nucleus (in the nucleolus?) which are important for virus release. This could be subsequently addressed by knocking down these factors and study the effect on virus life cycle.

We appreciate the reviewer’s valuable comments. We did not perform MS analysis on GP/AA core protein and core protein using WT or IPO7KO Hun7 cells. To report IPO7-mediated core translocation simply, we would like to cite our manuscript focusing on IPO7. To clarify the importance of nuclear transport of core protein on the viral life cycle, we will perform wide-ranging proteomics.

1. B) Further, the authors should try to address the role of core in the nucleus (and nucleolus). Does it interact with cellular/nucleolar proteins? Does it deliver viral RNA to sites of assembly? Does it interfere with rRNA synthesis? All these findings would be easily obtainable using the GP/AA virus and/or Huh7 KO cells, and tremendously increase the impact of the study, which at the moment is limited at points 1 and 2 in the first section of the current report.

Thank you for your valuable comments. We agree that we should clarify the roles of the nucleus or nucleolar localization of the core protein. We tested the effects of rRNA synthesis on JEV core expression. Our data showed that core protein expression slightly impaired the maturation of rRNA synthesis, as shown here. However, the core expression did not influence protein translation. We focused on the phase separation capacity of core protein localized in the nucleolar or nucleus. From our accumulating data, we hypothesized that the acquisition of phase separation capacity of core protein might be involved in an efficient virus release step. We hope that these data will be reported in the near future.

Overall, this work should be interesting for both cell biologists interested in trafficking of viral proteins, and virologists interested in virus-host interactions. The antiviral approach at the moment is a bit less convincing, but the manuscript might be interesting for scientists trying to develop new antiviral strategies. (In this context it might be worth reading and possible discussing the very recent paper from the Bartenschlager group "PMID: 37702492." Also, I think that it would be worth discussing the recent discovery that a closely related virus belonging to the Hepacivirus genus within the Flaviviridae family, mediated re-localization of Nups to viral replication factories, where they are believed to control access to DMVs interior, thereby regulating virus replication and assembly. Could the core IPO7-interaction have any role in core delivery to DMVs? See "PMID: 26150811".

Thank you for your valuable comments. We have added several sentences in the Discussion section (Line; 297-305). We will investigate the role of nuclear transports in viral life cycles in the future.

Since I am a molecular virologist studying viral nucleocytoplasmic trafficking, virus-host interactions, and antiviral drug-discovery I think I have sufficient expertise for an informative and helpful revision of this work.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #4

Evidence, reproducibility and clarity

Summary:

In the manuscript entitled "Importin-7-dependent nuclear localization of the Flavivirus core protein is required for infectious virus production", by combining proteomics, CRISPR/Cas9 gene KO, CLSM and standard virology techniques, Yumi Itoh report novel data concerning the involvement of IPO7 in the nuclear and nucleolar localization of Flaviviridae core nuclear and nucleolar localization and viral particle release. Surprisingly, IMPa/b1 inhibition via Bimax2 does not affect core nuclear transport, whereas both RanQ69L and WGA did so. The authors try to identify the cellular transporters involved in core nuclear import, and to this end performed a MS spec analysis of JEV core interactors, which yielded IPO7 as the most likely candidate. After confirming the result by Co-IP, the authors go on showing most core proteins require IPO7 for nuclear delivery using Huh7 and HEK7 IPO7-KO cells, with the exception of WNV core which was able to partially enter the nucleus. In such cells, upon infection, extracellular (but not intracellular) viral titers were strongly reduced, a phenotype which was observed with a JEV core mutant bearing the Gly42 and Pro43 to Ala substitutions in a previous study.

Major comments:

• The major conclusions of the study are:

1.IPO7 is the main driver of core nuclear transport 2.Core nuclear localization is somehow important for viral particle release Both conclusions are well-supported by experimental evidence.

Methods are clear and precise, the study appears to have been produced with high quality standards, and so is the presentation of the results.

A few controls however should be added to increase the reliability of the results presented here (see below)

Since the authors attempt to link the phenotype observed on virus release upon IPO7 KO to defects on core nuclear import by making a parallelism with core GP/AA mutant, it would be important to know the behavior of such virus in Huh7 wt and Huh IPO7 KO cells. In other words, is GP/AA JEV released efficiently in Huh7 IPO7 KO cells?

A similar approach can be applied to data shown in Figure 7 (effect on release on a capsid nuclear deficient mutant). This would help understand if IPO7 KO, viral release defects and core nuclear import are somehow linked.

Minor comments:

INTRODUCTION

• "Flaviviruses......are mosquito-borne human pathogens" What about tick borne encephalitis virus?
• " replication.... occur in the endoplasmic reticulum (ER)" This sentence is a bit inaccurate. Flaviviridae RNA replication occurs in so-called viral replication factories, double membrane vesicles which are partly derived from the ER. see "PMID: 26958917".
• "it is known that some flavivirus core proteins are translocated from the cytoplasm into the nucleus"
  • I think the first evidence of core in the nucleus dates back to 1989, and here it might be appropriate to cite the original reference: "PMID: 2471810".
  • It might be worth mentioning that NS5 has also been reported in the nucleus (See "PMID: 28106839")
• "In the cytoplasm, NLS-containing proteins are recognized by importin-α "
  • This is true only for classical NLSs, not every NLS binds IMP, as the authors confirm in this study! Indeed, we have also PY-NLS, IPO7 specific NLSs, IPOb1 NLSs, etc. I therefore suggest rephrasing.

RESULTS

• Fig. 1.
  • it is not clear what is new here, with respect to what has been already published. The authors should clearly differentiate novel findings from confirmatory results
• Fig. 2 and 4
  • Proteins whose nuclear transport is dependent on IMPa/IMPb1 (such as SV40 NLS) are lacking here
• Fig.5
  • It would be important to know the effect on total virus infectivity (intracellular + extracellular) and total viral RNA. It would also be important the effect on RNA replication by using a subgenomic viral replicon (with deletion of the env gene for example). The question here is if IPO7 depletion affects to any extent viral genome replication, and this is impossible to assess in a fully assembling system.
  • Panels A-F legend is missing, consider adding it?
• Fig.7
  • I did not completely understand how NLuc is the readout here
  • Also, I do not understand if the effect of GP/AA substitution of panel B has already been reported or if it is a novel finding
• All CLSM figures lack quantification (Fn/c; Fno/n)

DISCUSSION

• "The nuclear entry of viral genomic DNA has been demonstrated to involve IPO7"
  • It would be nice to know which viruses the authors are freeing to here
• "While RNA viruses, including flaviviruses, are considered to replicate in the cytoplasm of mammalian cells, increasing evidence suggests nucleolar localization of the viruses "
  • I suspect Rawlinson did not propose the viruses localize to the nucleolus, as this sentence seems to imply. Rather, a trafficking of viral proteins to nucleoli, to manipulate cell function, is more realistic. I suggest considering rephrasing.

Significance

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field. As alluded to above, this work presents several advances of current knowledge in the field of viral proteins nuclear trafficking, and in Flavivirus biology. The finding of most core proteins depending on IPO-7 is novel and intriguing, and opens the question of what makes WNV core special. Indeed, this protein nuclear targeting is only partially inhibited in IPO7 deficient cells. The fact that the authors extend their findings to several Flaviviruses adds significance. The role of nuclear core for virus release is also intriguing, but appears poorly characterized. In this respect a mechanistic explanation of the phenomenon would be highly desirable to increase the significance of the work presented here.

In this context I would have a few suggestions:

A) The authors performed MS spec on JEV core, this most likely resulted in a long list of "hits". However, they only report IMP superfamily members. This is perfectly fine, since they focus at identifying partners responsible for nuclear import. However, it might be helpful for understanding the role of nuclear core. By comparing MS of wt core and GP/AA core, and or wt core in wt and IPO7KO cells, authors could identify core biding partners in the nucleus (in the nucleolus?) which are important for virus release. This could be subsequently addressed by knocking down these factors and study the effect on virus life cycle.

B) Further, the authors should try to address the role of core in the nucleus (and nucleolus). Does it interact with cellular/nucleolar proteins? Does it deliver viral RNA to sites of assembly? Does it interfere with rRNA synthesis? All these findings would be easily obtainable using the GP/AA virus and/or Huh7 KO cells, and tremendously increase the impact of the study, which at the moment is limited at points 1 and 2 in the first section of the current report.

Overall, this work should be interesting for both cell biologists interested in trafficking of viral proteins, and virologists interested in virus-host interactions. The antiviral approach at the moment is a bit less convincing, but the manuscript might be interesting for scientists trying to develop new antiviral strategies. (In this context it might be worth reading and possible discussing the very recent paper from the Bartenschlager group "PMID: 37702492."

Also, I think that it would be worth discussing the recent discovery that a closely related virus belonging to the Hepacivirus genus within the Flaviviridae family, mediated re-localization of Nups to viral replication factories, where they are believed to control access to DMVs interior, thereby regulating virus replication and assembly. Could the core IPO7-interaction have any role in core delivery to DMVs? See "PMID: 26150811".

Since I am a molecular virologist studying viral nucleocytoplasmic trafficking, virus-host interactions, and antiviral drug-discovery I think I have sufficient expertise for an informative and helpful revision of this work.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

In the presented study the authors identified and mechanistically investigated how Flaviviruses including Japanese encephalitis virus (JEV), Dengue virus (DENV), and Zika virus (ZIKV) commonly use importin-7 (IPO7), an importin-β family protein, as a cellular carrier protein to facilitate nuclear core protein translocation. The authors evaluated how the production of infectious viruses is regulated by IPO7 using cellular infection models including IPO7-deficient knockout cells. In the submitted manuscript, the authors provide evidence that IPO7 facilitates viral core protein import into the nucleus of infected cells, which is essential for effective Flavivirus replication. Taken together, the study is interesting to a broader readership with interest in molecular virology, and its findings are informative for potential future targeting of IPO7 to affect flavivirus replication using small molecule drugs. The manuscript is well-written and easy to follow, the methods are appropriate, the structure is logical, and statistical analysis is adequate.

Major comments:

• It is unclear why the authors specifically used Ala substitution at Gly42 anb Pro43 to obtain the abolishment of nuclear core protein localization. It would be helpful to put this into more context and explain the approach.
• In Figure 4, the authors claim that the binding between IPO7 and RPS7 is disrupted upon the addition of RanGTPQ69L. This is not clearly evident from the pulldown experiment and should be proven experimentally with additional experiments (e.g. by using an imaging approach) to underline the statement that the binding mode of IPO7 to the JEV core protein is similar to that of RPS7. Loading controls for pulldown blots should be added.
• Most methods used are presented logically but require some more details so that they can be reproduced. In particular, the difference between Figure 4 E and 4H is confusing. What is the difference? Is 4E showing intracellular viral titers and 4H infectious viral titers in the supernatant of cells? Clarification needed. Put relevance of these experiments in context of the hypothsis.
• Identical phenotypes induced by IPO7 knockout in a number of HuH7 clones are shown in Figures 6A to 6C. This data does not add to the overall understanding and should be moved to supplementary figures. Why are 293T cells used in experiments shown in Figure 6D and 6E? What is the relevance of kidney cells to Flavirius infections?
• Prior studies are referenced appropriately, however, in a recent study it was demonstrated that IPO7 is stabilized upon Epstein-Barr Virus infection and that IPO7 presence is required for the survival of host cells (Yang YC, Front Microbiol. 2021 Feb 16;12:643327. doi: 10.3389/fmicb.2021.643327). This important study about the physiological relevance of IPO7 during viral infections has not been cited by Itoh and colleagues in the presented study. However, the results of the uncited study are very relevant to the provided manuscript, since Itoh and colleagues are using IPO7 knockout cells to investigate its function in Flavivirus core protein nuclear import. Hence, the authors should perform cell survival and cellular fitness experiments to demonstrate that observed phenomena of reduced viral replication and virus export in IPO7 knockout cells are independent of compromised cellular fitness due to IPO7 deficiency.

Minor comments:

• Describing Figure 3B, the authors state that they focused on IPO7 among the core binding proteins belonging to the importin-b family, because IPO7 "was identified the most peptides" in the mass spectrometry approach. This requires a more detailed explanation. Also, an explanation of why HEK293T cells were used for this approach and not HuH7 cells, as used predominately in most parts of the study, would provide more clarity to the reader.
• In Figures 4E and 4F, colour coding is missing.

Significance

The provided manuscript 'Importin-7-dependent nuclear localization of the Flavivirus core protein is required for infectious virus production' by Itoh and colleagues investigates a topic with important scientific relevance. The presented study builds on previous findings by the authors where they have demonstrated that Flavivirus core protein nuclear localization is actually conserved among Flaviviridae and represents a potential target for broad-range antiviral small molecule drugs (Tokunaga et al., Virology, 2020 Feb;541:41-51). However, our understanding of Flavivirus core protein nuclear localization during viral replication and how the processes could potentially be targeted using novel therapeutic drugs remains elusive. Here, the provided manuscript addresses a mechanistic investigation of how the Flavivirus core protein is actually translocated from the cytoplasm to the nucleus of infected cells. The study is informative particularly for virologists with expertise in Flavivirus replication.

However, from my point of view as a virologist investigating host-pathogen interactions with a strong interest in clinical translational, the manuscript requires a more careful evaluation and interpretation of some results of key experiments. In addition, some of the results need to be more precisely described for clearer understanding by a broader readership.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

Summary: In this study Itoh and colleagues investigate the mechanism, role and impact of the nuclear localization of the flavivirus core protein. The import of the core protein has long been observed and investigated and herein the authors use some novel approaches to identify potential cellular binding partners that facilitate nuclear import. Via proteomics and biochemical approaches they determine that importin-7 plays a crucial role in the import of the core protein that appears to be conserved across Flavivirus members. In general the findings and conclusions are sound but there are some significant omissions and caveats that warrant further investigation.

Major comments:

• one of the major caveats of the study is that the flavivirus NS5 protein also translocates to the nucleus in an Importin-alpha/beta dependent manner. Therefore how can the authors discount any impact of preventing NS5 import, in addition to core, on virus and SRIP replication and production. Some discussion, if not additional experiments are required here ie. NS5 localization in the KO cells during virus infection
• the localization is predominantly nucleolus rather that nucleoplasm when compared to the SV40 NLS. What are the sequence differences between the flavivirus proteins that potentially could account for this? A protein known to localize solely to the cytoplasm should also be used eg. NS1 or NS3.
• controls for Figure 2? Ie. a protein known to be inhibited by Bimax but not the RanGTP mutant and vice versa.
• Fig 5. Difference with WNV and DENV in nucleoplasm localization but also WNV still appeared to have Core in the nucleus in the KO cells
• Fig 5C still has substantial JEV and DENV core but not WNV and ZIKV. Why is the DENV and WNV localization pattern different to Fig 5B?
• Fig 5F, does the KO also restrict NS5 from entering the nucleus and could this then results in increase polymerase activity confined to the cytoplasm resulting in more viral RNA?
• Why was WNV infection not performed in Fig 5H? What where the viral tires compared to for the relative % values?
• Fig 6B, still a significant amount of core present in the nucleolus. Also WT cells have (almost?) no cytoplasmic staining for core where this could be clearly observed in the WT cells in Fig 5D. Why the difference?
• In Fig 7B, D and E, when were the SRIPs collected and what was the time period after subsequent infection?
• In Fig 7C was the luciferase measured from the initial transfection and how did it correlate with RNA production? A 15-fold increase in replicon RNA actually seems quite low over a 48h period
• quantitation is required throughout all of the experimental IFA data provided

Significance

The nuclear translocation of flavivirus protein has long been studied and it has been observed that the core, NS5 (RNA polymerase) and potentially the NS3 (helicase/protease) proteins all translocate the nucleus. Importin alpha and beta have been shown to facilitate this process. The authors aim to extend this to identify importin-7 as a major cellular factor enabling nuclear translocation. Overall the experiments have been performed well but there is a lack of quantitation for many of the results an suitable controls are required.

I am a researcher in the field of flavivirus replication

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

The study examined the mechanisms behind the nuclear transport of capsid proteins of various flaviviruses. The study used mass spectrometry to identify the interaction partners of JEV capsid protein and found Importin 7 as the top hit. After validating this interaction with IP-western blotting, using IPO7 knock-out cells they showed that the nuclear accumulation of capsid is dependent on IPO7. Moreover, they also observed nearly 10-folds reduction in titre of virus produced from knock out cells without reduction in virus replication or particle assembly.

The study needs improvements to bring it to publication standards. Some overaarching problems include, all capsid localization studies being done with GFP-tagged capsid, and not wild type capsid produced during authentic infection, lack of quantitation of most of the localization data and not showing capsid localization from infection experiments in knock out cells, and no in-depth analysis of the potential mechanisms behind the observed reduction in titre in knock out cells etc.

The major comments are

Fig 1B: Please add quantitation and statistical analyses of the ratio of nuclear and cytoplasmic capsid protein of all different capsids used. Also include western blot to prove that there is no cleavage between Capsid and GFP and the green signal indeed comes from the fusion protein. Ideally you should use capsid alone instead of a fusion protein for at least selected few constructs to prove that the Capsid-GFP behaves identical to Capsid alone.

Fig 1C: It is unclear from the figure legends the WT JEV capsid means GFP-Capsid or Capsid alone. You should clearly state the GFP part if the construct includes GFP. Quantitation and statistics are missing and the information on how many independent experiments were performed is also not included in the figure legend.

Fig 2B: Quantitation and statistics are missing. Ideally, the data need to be reproduced with Capsid alone instead of Capsid-GFP. A positive control is needed for the activity of Bimax to prove that the drug was working in the assay.

Fig 2C: How do you reconcile the IP mass spectrometry data that Importin b1 is the second strongest hit with the lack of IP interaction you observed in fig 2C?

Fig 3C: How many independent confirmations of this experiment was performed?

Fig 4A and B: Add quantitation for the western blot. 4A-D Include data on the number of biological repetitions. 4C-D: Add quantitation and statistical analyses of the ratio of nuclear and cytoplasmic capsid protein.

Fig 5B. This data should be shown in the context of infection with untagged Capsid at least for 1-2 viruses. This is a serious drawback of the present study as there is no clear evidence presented that the native capsid protein in an infection context depend on importin 7 for nuclear accumulation and behave similar to the GFP-Capsid constructs being used.

Fig 5 A-D: Two repetitions are insufficient; a minimum of three biological repeats and statistical analysis need to be included. 5E-F: You cannot do statistics on two repeats, need minimum of three repeats to perform statistical analysis. 5G-H: I presume three repetitions based on the data points shown, this should be clearly stated in the figure legend.

Fig 5E-G: Taking the data of 5E and 5G together it seems Importin 7 functions as the level of particle release and not particle assembly or maturation. Have you checked for the specific infectivity of the particles released from knock out cells to determine the reason behind the reduction in virus titre? You could look at the prM maturation by furin cleavage to check it this is altered in the IPO7 knock out cells.

Fig 5H: Have you checked if the observation regarding intracellular RNA levels in 5F is applicable to these viruses as well.

Fig 6: The figure legend "Data are representative of two (A, B) independent experiments and are presented as the mean {plus minus} SD of three independent experiments (C)" is confusing. The sentence should be reworded to state the repetitions separately for independent experiments. Fig 6C should show original titres and not percentages.

Fig 7B: This experiment should be performed in IPO7 knock out cells to confirm that the observed reduction of core mutant is mainly contributed from its lack of interaction with IPO7 and not from any other confounding factors.

Significance

While the authors could convincingly demonstrate the interaction between capsid and IPO7, how that interaction results in the observed reduction in viral titre is largely unexplored. As all the localization data used a GFP-tagged capsid outside an infection context, this reviewer is not confident that all the reported observations will hold in an infection setting. This need to be urgently addressed to rise the confidence about the observation. The current data is insufficient to confidently attribute the change in titre to the interaction between capsid and IPO7 and the capsid localization to the nucleus. Knocking out IPO7 could have pleotropic effects independent of capsid nuclear accumulation that could lead to the observed titre reduction. This need to be addressed further before linking both these phenotypes. Certain key experiments needed to address these questions are currently missing. While the interaction of Capsid with IPO7 is certainly intriguing, the implications of this interaction on virus biology needed further investigation before clear conclusions can be drawn regarding this observation.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

Manuscript number: RC-2024-02438

Corresponding author(s): Ryusuke, Niwa

1. General Statements [optional]

This section is optional. Insert here any general statements you wish to make about the goal of the study or about the reviews.

Below are quotes from the Reviewers' overall evaluations:

As might be expected based on the authors' skills and expertise, the study is well executed, nicely documented with perfect microscopy images, and well presented. It has been easy to follow. However, suitability for publication depends on where the authors aim to place their paper. Although I like the paper very much, it might seem incomplete for high-end journals.

This is a very nice paper and solid piece of work.

Its major strength is the focus on poorly studied the male reproductive organ and identification of Ldh as a novel target of JH activity in the seminal vesicles.

While the developmental roles of insect Juvenile Hormone (JH) are very well studied, its adult functions are largely unknown. Target genes of JH signaling are poorly described. This study adds significant insight into both of these aspects. The study underscores the usefulness of the JHRE-GFP reporter that identifies JH function, and not just JH presence since the reporter is only expressed after JH binding to Met and Gce, a prerequisite for JHRE reporter activation.

The authors have identified the epithelial cells of the ____Drosophila____ seminal vesicle as a JH target tissue. The authors nicely extended this finding by mining already existing expression data to identify a specific JH induced gene in these cells.

This small study reports new but limited results (one tissue of one stage, one hormone) that could be useful for specialists. The work is solid and includes controls and interpretable data.

2. Description of the planned revisions

Insert here a point-by-point reply that explains what revisions, additional experimentations and analyses are planned to address the points raised by the referees.

1) The study suggests an important role for JH signaling in the SV, likely affecting reproductive capacity of males. The authors depleted the JH receptors through RNAi, achieving a loss in the expression of the WT JHRE-GFP reporter as well as of the authentic target Ldh. Surprisingly, no phenotypic consequences of the double KD of Met and gce are presented. Does that mean that there were none? The authors only discuss a potential impact of Ldh loss for metabolism. Unless I am missing something, the study reports molecular phenotypes that clearly document JH signaling in the SV but no physiological impact of loss of this JH signaling, suggesting that there may be no obvious biological role for JH in this context. I think this is unlikely. Have the authors check fertility of the males, sperm viability and quality, mating competitiveness of the RNAi males? Loss of JH epoxidation (only methyl farnesoate present) made mosquito males less fit and less reproductively competitive relative to epox+ controls (Nouzova et al., 2021, PNAS) -- btw, I think the authors should discuss this paper.

Our response: We will conduct the following experiments to answer these criticisms.

1) We will examine the male fertility by counting the number of offspring from wild-type mothers crossed with males of the seminal vesicle-specific ____Met _& _gce____ double RNAi and with males of control RNAi.

2) We will also examine the mating competitiveness of the RNAi males. In more detail, we will cross ____w1118_ (white eye) wild-type background females with (i) a mixed population of males of _w1118_ wild-type background males and_ w+_ (red eye) control RNAi males, and (ii) a mixed population of males of _w1118_ wild-type background males and_ w+ Met _& _gce____ double RNAi males. We can distinguish between the progenies from RNAi males and those from wild-type males by eye colors.

By conducting plans 1) and 2), we will also indirectly evaluate sperm viability and quality.

In addition, we will also discuss the paper of Nouzova et al. PNAS 2021 in the Discussion section.

2) The authors seem to have made no effort to distinguish between Met and Gce functions. It is always the results from the double knockdown of both paralogs that are presented. Does this mean that single-KD had no effect, thereby indicating entirely redundant functions of both proteins in the studied context? Even if so, it would be of interest to document this redundancy by showing the single-gene KD data. However, I would be surprised if both proteins were equally important in the SV. The authors checked mRNA/protein expression levels. Was any of the two paralogs prevalent in the SV?

Our response: To address this criticism, we will conduct a single transgenic RNAi experiment to knock down either Met or gce separately and assess JHRE-GFP signals in the seminal vesicles.

__ Regarding the expression of Met and gce in the seminal vesicles, a previous study (Baumann et al. Scientific Reports 7: 2132, DOI:10.1038/s41598-017-02264-41) has already reported that GFP signals are observed in the seminal vesicles of _Met-T2A-GAL4>UAS_-GFP and gce-T2A-GAL4>UAS-GFP animals. These results strongly indicate that both Met and gce are expressed in the seminal vesicles. We will describe and discuss this point in our revised manuscript. In addition, we plan to check and analyze gene expression of Met, gce, and Ldh in the seminal vesicles using a publicly-available single-cell RNA-seq database, such as _DRscDB (https://www.flyrnai.org/tools/singlecell/web/).

3) The authors argue for direct regulation of Ldh by Met/Gce (again by which one?). Oddly, the statement in the Results (l.187-188; "suggests ... direct target") is stronger than in the Discussion (l.214, "leaving open the possibility"). The putative JHREs upstream and within the Ldh gene are identified but not tested in a functional study. At least a simple luciferase reporter assay and mutagenesis of the JHREs should be attempted.

Our response: To address this criticism, we plan to conduct a luciferase-based promoter/enhancer analysis in Drosophila S2 cultured cells. A similar system was used for a JH-responsiveness of the JHRE promoter in a previous study (Jindra et al. PLoS Genetics 11: e1005394, DOI: __10.1371/journal.pgen.1005394). We will generate plasmid constructs carrying the luciferase coding regions. In these plasmids, the luciferase coding regions will be fused with the upstream region and the first intron region of Ldh possessing the intact E-boxes or the mutated E-boxes. Then, we will determine whether the luciferase activity is enhanced by the presence of a JH analog (methoprene) when E-boxes are intact. __

__ For this revision, a new collaborator, Ryosuke Hayashi (a graduate student in the Niwa lab), will participate in this analysis. Thus, he becomes a co-author in the revised manuscript.__

l.232-233. It is not surprising that the JHRR-lacZ reporter shows a different expression pattern relative to JHRE-GFP, as these are really different constructs. The problem is that JH-dependent activation of the JHRR-lacZ transgene has not been tested as thoroughly as that of JHRE-GFP. Is it inducible by added JH or methoprene?

Have the authors examined whether JHRE-lacZ expression increases with Methoprene?

Our response: We have yet to do this analysis. To address this important point from Reviewers #1 and #2, we will examine whether JHRR-lacZ expression is upregulated in the seminal vesicles of virgin males fed methoprene-supplemented food. The lacZ signals will be visualized by immunostaining with an anti-LacZ antibody.

Document testis staining of JHRE-GFP. I think the authors missed a chance by not providing a clear/nice picture of the testis staining. Stainings of testes squashed on a slide is easy and would nicely document in which cells the reporter is activated. Similarly, extracting sperm from the seminal vesicle and examining whether the sperm express JHRE-GFP would be informative.

Our response: As the reviewer suggested, we will assess JHRE-GFP signal in sperm in squashed testis samples.

Did the authors try to analyze the 66 genes identified in seminal vesicle whether they had JHRE elements? This could yield additional significant information about other JH responsive genes in the seminal vesicle.

Our response: We have yet to do this analysis. We will follow the reviewer's suggestion and examine whether the 66 genes identified in the seminal vesicle have JHRE elements.

3a. Doublestaining would further confirm that pd8-Gal4 (crossed to UAS-dsRed) and JHRE-GFP overlap.

3b. Similarly, Doublestaining would further confirm that pd8-Gal4 (crossed to UAS-dsREd) and JHRE-GFP overlap.

Our response: To address this question, we will generate males of Pde8-GAL4; UAS-red fluorescent protein (RedStinger, RFP, or DsRed); JHRE-GFP and observe the overlap between the red fluorescent signals and green fluorescent (JHRE-GFP) signals in the seminal vesicle epithelial cells.

Minor comments:

Fig.1a could be in a supplement.

__Our response: At this point, we are unsure whether to follow this reviewer's suggestion. This is because there are no supplemental figures in the current manuscript, so we hesitate to create a supplemental figure just for this one figure. On the other hand, three reviewers now ask us to perform various additional experiments, thus some of the new data may be shown as supplemental figures. In this case, Fig. 1a can be moved to a supplemental figure, but we would like to wait on this decision. __

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

Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. If no revisions have been carried out yet, please leave this section empty.

l.25,91,117, and throughout, "JH analog" or "JHA". The authors only use methoprene, so it would be better to specifically talk about methoprene, which is a proven agonist ligand of the JHR proteins (reference 10 and/or Jindra and Bittova, 2020 [Arch Insect Biochem Physiol] for a review). This would land more credibility to using methoprene than just referring to a "JHA".

Our response: According to the reviewer's suggestion, we have replaced "JHA" with "methoprene" as many as possible. In Figures, we used "MTP" instead of "methoprene" due to space limitations.

l.42,44, "paralogs". I believe in this case the authors refer to orthologs of Met in other species. Paralogs result from gene duplications within species, such as Met and gce in cyclorrhaphous flies or Met 1 and 2 in the Lepidoptera. I recommend a recent review on all bHLH-PAS proteins featuring reconstruction of the phylogenetic position of Met/Gce (Tumova et al., 2024 in J Mol Biol).

Our response: As suggested, we have replaced "paralogs" and "paralogous" with "orthologs" and "orthologous," respectively on P3. We have also cited Tumova et al. J. Mol. Biol. 2023 as a new Ref 12.

l.54, "Met and Gce act redundantly to regulate JH-responsive gene expression". Ref 10 should be cited here as it provides functional cell-based and genetic rescue evidence for each paralog.

Our response: We have cited Ref 10 as suggested.

l.66, It would be better to start "In this study" or "Here" to distinguish from the last cited paper.

Our response:____ We created a new paragraph with the sentence "In this study..." at the beginning. We hope we understand the reviewer's suggestion correctly.

l.175, levels were

Our response: We have fixed this error in the transferred manuscript.

l.209, might be evolutionarily among.... conserved ??

Our response: We have fixed this error in the transferred manuscript.

l.226, study has

Our response: We have fixed this error in the transferred manuscript.

l.227-229. The authors are missing a paper by Shin et al., 2012 (PNAS) that shows physical interaction of Met with Cycle and their regulation of circadian gene activity and another paper by Bajgar et al., 2013 (PNAS) which describes photoperid-dependent seasonal regulation of circadian genes by Met, Clk and Cyc.

On the other hand, the cited reference [51] does NOT demonstrate Met:Clk heterodimer since coIP is by no means adequate to address complex stoichiometry. In fact, it is suspicious that Met would heterodimerize and either Cyc or Clk, as they present class II and class I bHLH-PAS proteins.

Our response: In response to both comments from Reviewer #1, ____we have cited these references and rewritten the discussion on P10-11 as below: "An interesting previous study has reported that the seminal vesicle expresses multiple clock genes such as period, Clock (Clk), and timeless, all of which are necessary for generating proper circadian rhythm [52]. In the case of the mosquito Aedes aegypti female, it is reported that JH controls gene expression via a heterodimer of Met and circadian rhythm factor Cycle (CYC) [53]. It was also suggested that Met binds directly to CLK in D. melanogaster [54]. In addition, in the linden bug, Pyrrhocoris apterus, JH alters gene expression via Met, CLK, and CYC in the gut [55]. Considering these previous reports and our results, circadian rhythm factors and JH may cooperate to regulate gene expression in the seminal vesicles."

l.245. It is not "whether", but for sure the existing reporters only reflect limited JHR activity, being based on Kr-h1 JHREs. These reporters likely uncover only a small subset of JH activity in vivo.

Our response: We have rewritten the sentence as follows: "..., more comprehensive JH reporter strains will be needed in D. melanogaster as well as other insects in future studies."

reference 10/11 is duplicated.

Our response: We have fixed this error in the transferred manuscript.

Have the authors done a careful comparison of JHRE-GFP expression and the Met/gce reporter expression described by Baumann et al (Scientific Reports | 7: 2132 | DOI:10.1038/s41598-017-02264-4)? Would be nice to add a few more sentences in the discussion.

Our response: As suggested, we have added some sentences to explain this point on Page 11 as below: "P____revious studies reported that ____Met-T2A-GAL4_ and _gce-T2A-GAL4_ labeled male accessory glands, ejaculatory duct, and testes as well as seminal vesicles. On the other hand, in our results, JHRE-GFP only labels cells in seminal vesicles and testes [21]. Considering that Met and Gce are expressed in almost all cell types of male reproductive tracts [21], more comprehensive JH reporter strains will be needed in _D. melanogaster____ as well as other insects in future studies."

• In the discussion:*

6.1 Would have liked to see a more in depth discussion of the role of the seminal vesicle. How could that be supported by JH / metabolic processes? Does it have secretory functions that might be induced by JH? Important functions relative to sperm storage? How could that relate to the finding that JH response is enhanced by mating?

Our response: Unfortunately, the function of the seminal vesicles is largely unknown. However, ____in response to the reviewer's suggestion, we have added some sentences to discuss this point and cited some references describing the seminal vesicles in insects other than the fruit fly, as follows on P9-10: "Furthermore, in some insects other than D. melanogaster, morphological and ultrastructural studies revealed that secretory vesicles were observed in the epithelial cells of the seminal vesicles [37,38,40,44]. JH is known to stimulate secretory activity in the male accessory glands of many insects [45]. Based on the JH response in the seminal vesicles, it is possible that JH signaling affects the secretory activity of the seminal vesicles in D. melanogaster."

The arrow in figure is not defined

Our response: We believe that the reviewer pointed out the arrow in Figure 1e. We have added a sentence to define the arrow in the Figure legend as "The arrow indicates the cell with a GFP signal."

Figure 2b graph labels are flipped

Our response: We have fixed the error.

Line 624: Change "Allow heads" to "Arrowheads"

Our response: We have fixed this error in the transferred manuscript.

Major Comments:

The work uses standard methods and strains. Although the specific findings are new and believable, the authors interpret them beyond what is appropriate. For example, based on increased amounts of a single RNA, they propose that JH regulates metabolism in seminal vesicles and because circadian rhythm genes were known to be expressed in this tissue they propose that JH and circadian systems work together there.

Our response: In response to the reviewer's criticisms, we have discussed our arguments more appropriately in the Discussion. For example, we have mentioned circadian rhythm more carefully on Pages 10-11 as follows: "An interesting previous study has reported that the seminal vesicle expresses multiple clock genes such as period, Clock (Clk), and timeless, all of which are necessary for generating proper circadian rhythm [52]. In case of mosquito Aedes aegypti female, it is reported that JH controls gene expression via a heterodimer of Met and circadian rhythm factor Cycle (CYC) [53]. It was also suggested that Met binds directly to CLK in D. melanogaster [54]. In addition, in the linden bug, Pyrrhocoris apterus, JH alter gene expression via Met, CLK and CYC in the gut [55]. Considering these previous reports and our results, it is possible that circadian rhythm factors and JH cooperatively regulate gene expression in the seminal vesicles."

__ Regarding Ldh, we have added a sentence on Page 10 as "Also, the biological significance of the induction of Ldh expression by JH signaling is not clear."__

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

Please include a point-by-point response explaining why some of the requested data or additional analyses might not be necessary or cannot be provided within the scope of a revision. This can be due to time or resource limitations or in case of disagreement about the necessity of such additional data given the scope of the study. Please leave empty if not applicable.

l.244, tract

Our response: We have carefully checked out the usage of "tract" and "tracts" not only on Page 11 but also throughout the manuscript. We have decided to use "tracts," but not "tract," throughout the manuscript.

6.2 What do epithelial cells of spermatheca do?

Our response: We agree with the reviewer that this is a very interesting question. However, please note that this paper focuses on males, and females are beyond our current scope. We plan to examine JHRE-GFP signals in the spermatheca in a different project. We do appreciate the reviewer's kind understanding.

6.3 How do the authors envision that JH enters the epithelial cells?

__Our response:____ We don't have any hypotheses on this point. Transporters may exist to achieve intracellular permeability of JH, but we do not think this point has been discussed in current insect physiology. Furthermore, since this issue is related to all JH-responsive cells, not just seminal vesicle epithelial cells, we do not feel the need to discuss it in this paper. __

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Summary:

Using two existing reporters, the authors showed that cells in Drosophila seminal vesicles are responsive to JH. They believe, but do not show, that these are epithelial cells. JH response of those cell is shown to depend on the known JH receptors and to increase after mating, when JH titers are known to rise. RT-qPCRs show that Ldh expression increases in response to JH.

Major Comments:

The work uses standard methods and strains. Although the specific findings are new and believable, the authors interpret them beyond what is appropriate. For example, based on increased amounts of a single RNA, they propose that JH regulates metabolism in seminal vesicles and because circadian rhythm genes were known to be expressed in this tissue they propose that JH and circadian systems work together there.

Minor comments:

Fig.1a could be in a supplement.

Significance

General Assessment, advance, and audience:

This small study reports new but limited results (one tissue of one stage, one hormone) that could be useful for specialists. The work is solid and includes controls and interpretable data.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

Summary:

The authors identify the epithelial layer of the Drosophila seminal vesicle as a target of Juvenile Hormone (JH) signaling as evidenced by the transcription of two different reporters that are induced by the JH receptors Met and gce via previously identified JH response elements (JHRE). In agreement with this model, the JHRE-GFP reporter is not activated in Met/gce double RNAi knockdowns. Likewise, knockdown of JHAMT, a JH biosynthetic enzyme, reduces reporter expression. That this response is mediated by Juvenile Hormone (JH) is further supported by the finding that application of Methoprene, a JH analogue, through feeding of intact animals or by adding to cultured seminal vesicles, increases reporter expression. Mating, which has previously shown to increase JH levels, similarly increases reporter expression. By mining available RNA and protein data the authors identify Lactate dehydrogenase as a gene that is specifically expressed in the seminal vehicle under JH control. These findings suggest that metabolic processes in the seminal vesicle are regulated by JH and may be important for the function of this organ.

Major comments:

• The claims and the conclusions are supported by the data

• The data and the methods presented in such a way that they can be reproduced

• The experiments adequately replicated and statistical analysis adequate

Optional suggestions for experiments that would enhance the current set of data and are not very time-intensive:

1. Document testis staining of JHRE-GFP. I think the authors missed a chance by not providing a clear/nice picture of the testis staining. Stainings of testes squashed on a slide is easy and would nicely document in which cells the reporter is activated. Similarly, extracting sperm from the seminal vesicle and examining whether the sperm express JHRE-GFP would be informative.

2. Did the authors try to analyze the 66 genes identified in seminal vesicle whether they had JHRE elements? This could yield additional significant information about other JH responsive genes in the seminal vesicle.

3. a) Doublestaining would further confirm that pd8-Gal4 (crossed to UAS-dsRed) and JHRE-GFP overlap.

b) Similarly, Doublestaining would further confirm that pd8-Gal4 (crossed to UAS-dsREd) and JHRE-GFP overlap.

1. Have the authors examined whether JHRE-lacZ expression increases with Methoprene?

2. Have the authors done a careful comparison of JHRE-GFP expression and the Met/gce reporter expression described by Baumann et al (Scientific Reports | 7: 2132 | DOI:10.1038/s41598-017-02264-4)? Would be nice to add a few more sentences in the discussion.

3. In the discussion:

a) Would have liked to see a more in depth discussion of the role of the seminal vesicle. How could that be supported by JH / metabolic processes? Does it have secretory functions that might be induced by JH? Important functions relative to sperm storage? How could that relate to the finding that JH response is enhanced by mating?

b) What do epithelial cells of spermatheca do?

c) How do the authors envision that JH enters the epithelial cells?

Minor comments:

• Prior studies are referenced appropriately

• The text and figures clear and accurate

• Suggestions that would help the authors improve the presentation of their data and conclusions:

• The arrow in figure is not defined

• Figure 2b graph labels are flipped

• Line 624: Change "Allow heads" to "Arrow heads"

Significance

General assessment / Advance:

While the developmental roles of insect Juvenile Hormone (JH) are very well studied, its adult functions are largely unknown. Target genes of JH signaling are poorly described. This study adds significant insight into both of these aspects. The study underscores the usefulness of the JHRE-GFP reporter that identifies JH function, and not just JH presence since the reporter is only expressed after JH binding to Met and gce, a prerequisite for JHRE reporter activation. The authors have identified the epithelial cells of the Drosophila seminal vesicle as a JH target tissue. The authors nicely extended this finding by mining already existing expression data to identify a specific JH induced gene in these cells.

• Audience: Audience interested in the role of insect hormones in general or putative reproductive function (basic research and applied (insect control) will be interested in the finding and the approaches taken by the author.

• Reviewer field of expertise: Drosophila sex-specific gene expression and function, molecular genetic approaches

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

This is an interesting and straightforward study that utilizes a recently developed in vivo sensor of juvenile hormone (JH) signaling in Drosophila. The authors focus on one understudied aspect of insect reproduction, the adult male seminal vesicle (SV), as a target of JH action. Using simple genetics and gaining from previous RNA-seq and proteomics data, the authors identify lactate dehydrogenase (Ldh) as a prime candidate gene positively regulated by JH in the SV. This regulation is potentially important for the SV physiology (metabolism?) and male reproduction, although this has not been addressed (see below).

As might be expected based on the authors' skills and expertise, the study is well executed, nicely documented with perfect microscopy images, and well presented. It has been easy to follow. However, suitability for publication depends on where the authors aim to place their paper. Although I like the paper very much, it might seem incomplete for high-end journals.

Major comments:

1) The study suggests an important role for JH signaling in the SV, likely affecting reproductive capacity of males. The authors depleted the JH receptors through RNAi, achieving a loss in the expression of the WT JHRE-GFP reporter as well as of the authentic target Ldh. Surprisingly, no phenotypic consequences of the double KD of Met and gce are presented. Does that mean that there were none? The authors only discus a potential impact of Ldh loss for metabolism.

Unless I am missing something, the study reports molecular phenotypes that clearly document JH signaling in the SV but no physiological impact of loss of this JH signaling, suggesting that there may be no obvious biological role for JH in this context. I think this is unlikely. Have the authors check fertility of the males, sperm viability and quality, mating competitiveness of the RNAi males? Loss of JH epoxidation (only methyl farnesoate present) made mosquito males less fit and less reproductively competitive relative to epox+ controls (Nouzova et al., 2021, PNAS) -- btw, I think the authors should discuss this paper.

2) The authors seem to have made no effort to distinguish between Met and Gce functions. It is always the results from the double knockdown of both paralogs that are presented. Does this mean that single-KD had no effect, thereby indicating entirely redundant functions of both proteins in the studied context? Even if so, it would be of interest to document this redundancy by showing the single-gene KD data. However, I would be surprised if both proteins were equally important in the SV. The authors checked mRNA/protein expression levels. Was any of the two paralogs prevalent in the SV?

3) The authors argue for direct regulation of Ldh by Met/Gce (again by which one?). Oddly, the statement in the Results (l.187-188; "suggests ... direct target") is stronger than in the Discussion (l.214, "leaving open the possibility"). The putative JHREs upstream and within the Ldh gene are identified but not tested in a functional study. At least a simple luciferase reporter assay and mutagenesis of the JHREs should be attempted.

Minor comments and suggestions (in the order of appearance):

• l.25,91,117, and throughout, "JH analog" or "JHA". The authors only use methoprene, so it would be better to specifically talk about methoprene, which is a proven agonist ligand of the JHR proteins (reference 10 and/or Jindra and Bittova, 2020 [Arch Insect Biochem Physiol] for a review). This would land more credibility to using methoprene than just referring to a "JHA".

• l.42,44, "paralogs". I believe in this case the authors refer to orthologs of Met in other species. Paralogs result from gene duplications within species, such as Met and gce in cyclorrhaphous flies or Met 1 and 2 in the Lepidoptera. I recommend a recent review on all bHLH-PAS proteins featuring reconstruction of the phylogenetic position of Met/Gce (Tumova et al., 2024 in J Mol Biol).

• l.54, "Met and Gce act redundantly to regulate JH-responsive gene expression". Ref 10 should be cited here as it provides functional cell-based and genetic rescue evidence for each paralog.

• l.66, It would be better to start "In this study" or "Here" to distinguish from the last cited paper.

• l.175, levels were

• l.209, might be evolutionarily among.... conserved ??

• l.226, study has

• l.227-229. The authors are missing a paper by Shin et al., 2012 (PNAS) that shows physical interaction of Met with Cycle and their regulation of circadian gene activity and another paper by Bajgar et al., 2013 (PNAS) which describes photoperid-dependent seasonal regulation of circadian genes by Met, Clk and Cyc.

On the other hand, the cited reference [51] does NOT demonstrate Met:Clk heterodimer since coIP is by no means adequate to address complex stoichiometry. In fact, it is suspicious that Met would heterodimerize and either Cyc or Clk, as they present class II and class I bHLH-PAS proteins.

• l.232-233. It is not surprising that the JHRR-lacZ reporter shows a different expression pattern relative to JHRE-GFP, as these are really different constructs. The problem is that JH-dependent activation of the JHRR-lacZ transgene has not been tested as thoroughly as that of JHRE-GFP. Is it inducible by added JH or methoprene?

• l.244, tract

• l.245. It is not "whether", but for sure the existing reporters only reflect limited JHR activity, being based on Kr-h1 JHREs. These reporters likely uncover only a small subset of JH activity in vivo.

reference 10/11 is duplicated.

Significance

This is a very nice paper and solid piece of work.

Its major strength is the focus on poorly studied the male reproductive organ and identification of Ldh as a novel target of JH activity in the seminal vesicles.

The weakness is the limitation to molecular phenotypes without showing physiological relevance of JHR signaling in the seminal vesicles for male reproductive fitness. Evidence for the Ldh gene being directly regulated by the JHR is indirect.

These limitations will likely reduce the impact of this work although otherwise it would be of great interest to the larger community of developmental biologists and insect endocrinologists.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

We thank the reviewers for their time and effort to improve and clarify our manuscript. We now have addressed the reviewers’ suggestions in full on a point-by-point basis. Revisions in the manuscript file are highlighted in yellow.

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

Supernumerary centrosomes are observed in the majority of human tumors. In cells they induce abnormal mitosis leading to chromosome missegregation and aneuploidy. In animal models it is demonstrated that extra centrosomes are sufficient to drive tumor formation. Previous work studying the impact of centrosome amplification on tumor formation in vivo used Plk4 overexpression to drive the formation of supernumerary centrosomes. In this manuscript Moussa and co-workers from the Krämer group developed a mouse model in which centrosome amplification is triggered by the overexpression of the structural centrosomal protein STIL rather than the kinase Plk4 in order to a) assess the potential for centrosome amplification induced by STIL overexpression to drive tumor formation and b) to rule out any potential non-centrosomal related effects of the kinase Plk4 on tumor formation.* The authors show that STIL ovexrexpression in cells (MEFs) drives centrosome amplification and aberrant mitosis (Fig. 1), leading to chromosome missegregation and aneuploidy (Fig. 2). They also show that STIL overexpression is linked to reduced cellular proliferation and apoptosis (Fig 3). The authors then present in vivo experiments performed in mice. They observed that STIL expression causes embryonic lethality, microcephaly and a reduced lifespan (Fig 4). Despite increased STIL mRNA levels they do not detect elevated STIL protein levels in adult tissues except for the spleen. They do not detect significant increase of centrosome amplification or aneuploidy in animal tissues (Fig 4) and they conclude of a STIL translational shut down in most adult tissues. The authors then assess the impact of STIL overexpression on tumor formation. They observed a reduced spontaneous tumor formation despite elevated STIL mRNA levels in both healthy and tumor (lymphomas) tissues of mice overexpressing STIL. They don't detect increased centrosome amplification and aneuploidy in lymphomas from STIL overexpressing mice compared to lymphomas naturally occurring in control animals (Fig 5). Finally, they found that STIL overexpression suppresses chemical skin carcinogenesis using a combination of tamoxifen induction of STIL in the skin with DMBA/TPA carcinogenic treatment (Fig 7). They link this effect to an increased number of centriole and a reduction in cycling cells number in the skin of STIL overexpressing mice (Fig 6).

The manuscript is written in a clear manner. The experimental approaches are properly designed and the experimental methods are described in sufficient details. Most of the experimental data present a good number of replicates. The figures are generally well assembled despite some errors in a few panels/legends (see major and minor points). Most of the conclusions are supported by the experimental data. However, a few specific points or interpretations are not convincingly supported by the experimental data (see major points) and will need to be revised and/or reformulated.

Major points:

1. Figures 1D and F show that MEFs hemizygous (CMV-STIL+/-) and homozygous (CMV-STIL+/+) for STIL present similar level of centrosome amplification and aberrant mitosis. Although, despite these similarities the homozygous MEFs display about two time more micronuclei and chromosomes aberrations (Fig. 2). The authors explain this discrepancy by the fact that MEFs homozygous for STIL have reduced proliferation and an increased propension to stay in interphase compared to hemizygous MEFs (Fig. 3). I don't understand why an interphase arrest would lead to a higher chromosomal instability resulting in higher micronuclei formation and abnormal karyotypes since those phenotypes are the consequences of abnormal mitosis occurring in cycling cells. I would rather argue that Homozygous MEFs are more prone to cell cycle arrest because of mitotic errors, but those mitotic errors cannot be explained by the centrosome status or the mitotic figures quantified in homozygous MEFs. Therefore, the authors explanation written as: "Graded inhibition of proliferation and accumulation of cells in interphase explains why CMV-STIL+/- and CMV-STIL+/+ MEFs contain increasing frequencies of micronuclei and aberrant karyotypes (Fig. 2) despite similar levels of supernumerary centrosomes" is not right for me. The authors should reformulate this section of the manuscript so their conclusion fit their data. The differences between hemi and homozygotes MEFs regarding chromosome stability could come from mitotic errors they did not spot using fixed immunofluorescence images of mitotic MEFs. Thus, as an optional additional experiment, analyzing live mitosis of MEFs could potentially help reconciliate results from mitotic figures and from karyotypes.*

We basically agree with the reviewer and have therefore reanalyzed our data on centriole numbers in a time-dependent manner. As already shown in Figure 3L of the initial manuscript version, the number of both CMV-STIL+/- and CMV-STIL+/+ MEFs with supernumerary centrioles increases with passaging from passage 3 (p3) to p6. Also, in this experiment amplified centrioles were more frequent in CMV-STIL+/+ compared to CMV-STIL+/- MEFs in both passages (p3 and p6) analyzed. We have therefore now pooled the data and substituted the former Figure panel 1D by these combined results. As the results of Figure 1F and especially those for the CMV-STIL+/+ MEFs had to rely on very low mitotic figure counts, because these cells only very rarely divide (as shown in Figure 3A; mitosis frequency of CMV-STIL+/+ MEFs 0.12%), we have now deleted Figure panel 1F from the manuscript. For the same reason - an extremely low proliferation and division rate of especially CMV-STIL+/+ MEFs - live cell imaging to detect different types of mitotic errors, is unfortunately not feasible.

Figure 5 panel F does not support the claim of the main text and does not match the legend of the figure: In the text the authors wrote: "Ki67 immunostaining revealed that, ..., proliferation rates were elevated independent from lymphoma genotypes". If the authors claim and increased cell proliferation in lymphoma compared to lymph nodes, which is expected, they should show the data for the lymph node in the graph. In addition, in the legend the authors mentioned a "Percentage of Ki67-positive cells in healthy spleens and lymphomas from mice with the indicated genotypes." Since there are three genotypes and two tissue types but the figure presents a graph with only three bars did the Spleen and lymphoma data were combined? Or did some data were not inserted in the graph? Thus, since the data does not support the claim for an increased cell proliferation in lymphoma, the authors explanation for the increased protein level observed in these lymphomas (Fig. 5 panel E) is not supported. Therefore, the authors need to present the correct data in the figure or to change their conclusion. They will also need to correct the figure legend and to add a panel with images illustrating the Ki67 labelling in the different tissues in the figure.

We apologize for this mistake and have corrected the legend to Figure panel 5F, which now reads: “Percentage of Ki67-positive cells in two B6-STIL, two CMV-STIL+/- and one CMV-STIL+/+ lymphoma. For comparison, frequencies of Ki67-positive cells in healthy lymph nodes from B6-STIL mice are displayed. Data are means ± SEM from at least two independent immunostainings per lymphoma or healthy lymph node. P-values were calculated using the one-way ANOVA with post-hoc Tukey test for multiple comparison. For space reasons, only statistically significant differences are displayed”.

   We agree with the reviewer that for comparison Ki67 immunostainings of healthy lymph node tissue was missing in the graph and have therefore added this information to the figure panel, which shows increased proliferation of lymphoma compared to normal lymph node cells. Also, a panel with images illustrating Ki67 labelling in healthy lymph node and lymphomas from different genotypes has been added to the figure (panel 5G).

• *

__Minor points:____* * __1. In the introduction, page 4 paragraph 3, the authors wrote: "To assess the impact of centrosome amplification on CIN, senescence, lifespan and tumor formation in vivo without interfering with extracentrosomal traits,..." they need to clarify what they meant by extracentrosomal traits.

As requested by the reviewer we have modified the respective sentence, which now reads: “To assess the impact of centrosome amplification on CIN, senescence, lifespan and tumor formation in vivo with an orthologous approach without interfering with PLK4, we generated transgenic mouse models overexpressing the structural centrosome protein STIL, …”.

• *

In the 1st paragraph of the results, page 4, the authors wrote: "leads to ubiquitous transgene expression at levels similar to the CAG promoter used in most..." but there is no link to a figure presenting the mRNA levels in those mice (potentially Fig. 4F and Fig. S6). Also, in the references cited for comparison, to my knowledge, there was no measurement of Plk4 mRNA levels in tissues in the work from Marthiens and colleagues, in this work the authors assess the expression of the Plk4 transgene by investigating the presence of the protein.

To show STIL transgene expression levels in our system, we have now linked Figure panels 1A (STIL mRNA expression in MEFs), 1B (STIL protein expression in MEFs) and Supplemental Fig. S2 (Supplemental Fig. S6 of the previous manuscript version showing STIL mRNA levels in healthy mouse tissues) to this statement as suggested. In the references now cited for comparison (Kulukian et al. 2015; Vitre et al. 2015; Sercin et al. 2016) PLK4 transgene mRNA (Kulukian et al. 2015; Sercin et al. 2016) and protein levels (Vitre et al. 2015) are shown.

• *

Page 5 second line the authors wrote: "Despite the graded increase in Plk4 expression, CMV-STIL+/- and, CMV-STIL+/+ MEFs exhibited a similar increase in supernumerary centrioles". The authors must meant increase in STIL expression or do they have data not shown about an increase of Plk4 expression? Then they explain this absence of difference in supernumerary centriole by the ability of "excess Plk4" to access the centrosome, again they probably meant STIL. Regarding this point and related to Major Point 1 it might be worth for the authors to quantify actual extra centrosomes in mitosis rather than cells with more than 4 centrioles in interphase (as in Fig. 1C, D). They might find differences in the number of centrosomes in hemizygous versus homozygous MEFs.

We indeed meant STIL instead of PLK4 and have corrected the mistake. As described in our response to the reviewer’s major point 1 we have now reanalyzed our data on centriole numbers in a time-dependent manner. As already shown in Figure 3L of the initial manuscript version, the frequency of both CMV-STIL+/- and CMV-STIL+/+ MEFs with supernumerary centrioles increases with passaging from passage 3 (p3) to p6. Also, in this experiment amplified centrioles were more frequent in CMV-STIL+/+ compared to CMV-STIL+/- MEFs in both passages (p3 and p6) analyzed. We have therefore now pooled and substituted the former Figure panel 1D by these combined results.

Page 5, in the first paragraph the authors mention "the rate of respective mitotic aberrations..." without defining the mitotic aberrations. For instance, in panel 1E a metaphase with 4 centrosomes is shown for CMV-STIL+/- while an anaphase with an unknown number of clustered centrosomes is presented for CMV-STIL+/+. Classifying the different types of aberrant mitotic figures (i.e: multipolar anaphases versus bipolar with clustered centrosomes) might help the authors identify differences between hemi and homozygous MEFS that may explain the differences in the proportions of chromosomes aberrations they present in Fig. 2.

As described in our response to the reviewer’s major point 1 the number of mitotic figures that could be analyzed was extremely low, especially for CMV-STIL+/+ MEFs, which do only rarely divide (mitosis frequency of CMV-STIL+/+ MEFs 0.12%). Therefore, although certainly of value, classification of different types of mitotic aberrations is unfortunately not feasible.

• *

In Fig 4A the number of mice analyzed should be mentioned.

After mating of B6-STIL transgenic animals with CMV-CRE mice and further breeding of successive generations, we obtained a total of 198 pups over four generations, 162 of which were born alive: 116 B6-STIL wildtype animals, 27 CMV-STIL+/- and 19 CMV-STIL-/- mice. We have now added these numbers to the figure legend.

• *

In Fig. 5E, the band corresponding to STIL protein is difficult to visualize in the B6-STIL control, it is therefore difficult to compare its level to the level of STIL protein in the CMV-STIL hemizygotes and homozygotes. If possible, it would improve the manuscript to present a blot with clearer results.

We have tried to improve the quality by repeating the Western blot. Due to the small size of healthy mouse lymph nodes, resulting in low protein yields, only lysates from lymphomas were left, and these were of poor quality with a high lipid content. We therefore tried to delipidate the lymphoma lysates and hope that the result of the new blot is now somewhat clearer. Due to the low lymphoma frequency in CMV-STIL hemizygotes and homozygotes (only 2 in each case) we were unfortunately not able to prepare fresh lysates.

Related to Figure 6B the authors wrote a "5 to 10 fold-increased expression..." in the text while panel 6B show a maximum of 8 fold increase.

The respective statement has been rephrased according to the reviewer´s suggestion.

__Reviewer #1 (Significance (Required)): ______ *Centrosome amplification is a demonstrated cause of genomic instability and tumor development as shown in multiple previous work performed in mice. In this work, Moussa and co-workers developed a mouse model that does not depends on Plk4 to trigger centrosome amplification but which depends on the overexpression of the centrosome structural protein STIL. This effort is welcome as previous works could not formally rule out potential role of Plk4, not related to its centrosome duplication function, on tumor formation. The authors show that their system is functional in MEFs where STIL overexpression drives centrosome amplification and aneuploidy. Unfortunately, in vivo, despite elevated level of STIL mRNA they do not detect centrosome amplification in tissues and consequently, they do not observe an increase rate of aneuploidy and tumor formation. This result is not surprising as previous studies using strong promoters (comparable to the one used to drive STIL expression in this study) to induce Plk4 overexpression led to similar results, i.e. an absence of centrosome amplification in adult tissues and no effects on tumor formation. Therefore, the results and the concepts proposed in this work are not novel but they reinforce previous studies showing the deleterious effect of high level of centrosome amplification on cells. This work also confirms that strong mechanisms, here the authors propose a translational shut-down, are preventing the apparition or the persistence of high level of centrosome amplification in animal tissues. By complementing existing results with the use of an alternate experimental approach this study will be of interest for the scientific community working on the basic biological mechanisms driving aneuploidy and tumor development.*

__Reviewer #2 (Evidence, reproducibility and clarity (Required)):______ *In this manuscript, Moussa et al. describe the effects of over-expressing the centriole duplication factor STIL in whole mice and with expression restricted to the skin. They find that over expression of STIL, similar to that of PLK4, induces centriole overduplication, abnormal mitoses, and genetic instability leading to cell arrest. Additionally, over-expressing STIL results in microcephaly, perinatal lethality and a shortened lifespan. In addition, they do not find that expression of the p53 R127H mutant alleviates the cell growth defect. Moreover, overexpression of STIL does not lead to increased general tumour formation and suppresses tumour formation in an induced skin tumour model.

Although this is an interesting manuscript, the authors need address a number of issues before this manuscript can be recommend the manuscript for publication. Importantly, the manuscript lacks statistical analyses to support some of their conclusions, some figures should be quantified, and controls are missing in some cases. *

__Major Issues____* * __1. Many of the figure panels lack appropriate statistical analyses to support the conclusions (see details below). This needs to be rectified.

In view of the limited number of mice (due to an increased frequency of pups that died around birth) and the resulting impossibility of performing several (>3) independent experiments in many cases, we have decided to limit the statistics in the main text to a descriptive analysis without mentioning inferences (p-values). Nevertheless, we have now included the missing statistical analyses in the figure panels and/or legends. However, the reported p-values (*p≤0.05, **p≤0.01, ***p≤0.001; ns, not significant) should be interpreted as descriptive rather than confirmatory values.

• *

The authors suggest that the interpretation of PLK4 over-expression studies are hampered by the possibility of centriole/centrosome independent PLK4 roles and that STIL overexpression circumvents some of these issues. Although orthologous approaches to problems are always desired, STIL itself has also been implicated in other cellular processes, such as the Sonic hedgehog pathway (Carr AL, 2014) and in cell motility (Liu Y, 2020). In addition, the data presented in the manuscript are suggestive of a STIL function in the mouse that is independent of centriole number. The authors demonstrate that the amount of centriole over-duplication in MEFs containing a single copy of the STIL over-expression locus is equivalent to that of MEFs carrying two copies. However, in most other assays, the homozygous lines display more severe phenotypes, suggesting that STIL might have a function outside centriole duplication. The authors need to discuss this further in a revised manuscript.

As described in our response to major point 1 and minor point 3 of reviewer 1 we have now reanalyzed our data on centriole numbers in a time-dependent manner. As already shown in Figure 3L of the initial manuscript version, the number of both CMV-STIL+/- and CMV-STIL+/+ MEFs with supernumerary centrioles increases with passaging from passage 3 (p3) to p6. Also, in this experiment amplified centrioles were more frequent in CMV-STIL+/+ compared to CMV-STIL+/- MEFs in both passages (p3 and p6) analyzed. We have therefore now pooled the data and substituted the former Figure panel 1D by these combined results, which show that, similar to other models, also regarding STIL overexpression the homozygous line displays a more severe phenotype, which does therefore per se not argue for a STIL function outside the centrosome. However, as a few recent studies indeed suggest additional roles of STIL, we have amended the respective passages in the revised version of the manuscript accordingly.

• *

Why did the authors use the p53 R127H mutant instead of a p53 knockout or null allele system? The R127H mutant has a gain-of-function phenotype and cells expressing this mutant display different phenotypes than a p53 null. The primary conclusion in one of the references cited by the authors (Caulin C, 2007) is that p53R127H is a gain-of-function mutant and behaves distinct from loss-of-function p53 mutations, such as deletions using floxed alleles. Throughout the manuscript, the authors use terms that suggest the R127H allele is equivalent to a loss of function mutant. Given that supernumerary centriole growth arrest is universally suppressed by inactivation of p53 it is somewhat surprising that this pathway is not active in response to STIL over-expression. The authors should confirm this key conclusion by depleting p53 in MEFs using RNAi, or by using mice where complete inactivation of p53 can be achieved.

We agree with the reviewer that the p53-R172H mutant version of p53 is not equivalent to a p53 knockout. We have therefore and as suggested by reviewer 3 as well (see also our response to point 3 of reviewer 3) corrected the wording and have substituted “absence of p53” by “interference with p53 function” where appropriate. In addition, we now have added data to the manuscript, which show that neither p53 expression nor p53-S18 phosphorylation becomes induced during prolonged cultivation and passaging of CMV-STIL transgenic MEFs (see Figure 3B of the revised manuscript). Importantly, this finding is in line with a recent report showing that PLK4-induced extra centrosomes may not rely on p53 for tumor suppression and cell death induction (Braun et al.: Extra centrosomes delay DNA damage-driven tumorigenesis. Sci. Adv. 10: eadk0564, 2024). Similarly, it has been recently shown that centrosome amplification increases apoptosis independently of p53 in PLK4-overexpressing cells treated with DNA-damaging agents (Edwards et al.: Centrosome amplification primes for apoptosis and favors the response to chemotherapy in ovarian cancer beyond multipolar divisions. bioRxiv 2023.07.28.550973, 2023). Therefore, these findings and references have now been added to results and discussion sections of the revised manuscript.

   A plethora of p53-related findings in mouse models, including the majority of results on PLK4-induced tumor formation in mice, is based on p53 knockouts, a situation that is only rarely found in human cancers. In contrast, the p53-R172H missense mutation in mice corresponds to the p53-R175H mutation in human tumors, which has the highest occurrence in diverse human cancer types among all p53 hotspot mutations, and results in a transcriptionally inactive protein that accumulates in cells, similar to the majority of naturally occurring versions of mutant p53 (Yao et al.: Protein-level mutant p53 reporters identify druggable rare precancerous clones in noncancerous tissues. Nat Cancer 4: 1176-1192, 2023; Chiang et al.: The function of mutant p53-R175H in cancer. Cancers 13: 4088, 2021). We therefore believe that it more faithfully recapitulates the situation in p53-mutant tumors than a p53 knockout.

   Although basically an important and valid experiment, depleting p53 in STIL-transgenic MEFs using RNAi is not easily done as (i) transfection of MEFs per se is difficult and (ii) STIL-overexpressing MEFs do only slowly proliferate and are prone to senescence and apoptosis (see Figure 3), all phenotypes which are even further exacerbated after transfection. Generation of STIL-transgenic mice with complete inactivation of p53 on the other hand is an extremely time-consuming endeavor that would lead to a significant delay of publication of our results. Given that currently similar data are published by other groups (Braun et al.: Extra centrosomes delay DNA damage-driven tumorigenesis. Sci. Adv. 10: eadk0564, 2024; Edwards et al.: Centrosome amplification primes for apoptosis and favors the response to chemotherapy in ovarian cancer beyond multipolar divisions. *bioRxiv* 2023.07.28.550973, 2023), we do not think that this would be appropriate.

__Minor Issues and details____* * __Figure 1 1. Panel E. It is unclear what the authors are calling an 'aberrant mitosis'. Typically an aberrant mitosis refers to chromosomal abnormalities such as multipolar spindles, anaphase bridges or micronuclei (which they quantify in Figure 2). The aberrant mitotic figures presented in Figure 1E show a clustered metaphase with 4 centrosomes (2 per pole; 2 centrioles per centrosome) for CMV-STIL+/- MEFs and a clustered telophase with 2 centrosomes (1 per pole; 5 centrioles per centrosome) for CMV-STIL+/+ MEFs. This is now specified in detail in the legend to Figure 1E.

• *

Panel E. Please include images representing a normal mitosis from control cells derived from B6-STIL mice.

As suggested, we have now included a representative image of a normal mitosis from B6-STIL control mice.

Figure 2____ 1. Panels B, E and F. Statistical significance is not indicated between B6-STIL and CMV-STIL+/- or CMV-STIL+/- and CMV-STIL+/+. The authors indicated a 'graded' phenotype which is qualitatively apparent, but should be backed by statistical analysis.

We have now included a statistical analysis. However, and as already described in our answer to major issue 1 of this reviewer, the reported p-values should be interpreted as descriptive rather than confirmatory values due to the limited number of independent experiments.

• *

Can the authors indicate how they scored a tetraploid cell? Some of the cells are 100% tetraploid while others contain other aberrations.

According to the International System for Human Cytogenomic Nomenclature (ISCN) version from 2020, polyploidy is defined by the modal numbers of chromosomes in the karyotype. A number of 81-103 chromosomes is called near-tetraploid, at which a hypotetraploidy (81-91 chromosomes) is distinguished from a hypertetraploidy (93-103 chromosomes) (An International System for Human Cytogenomic Nomenclature, Karger (2020), Eds.: McGowan-Jordan, Hastings, Moore). For mouse karyotypes respective numbers were recalculated on the basis of a diploid chromosome content of 40 instead of 46 chromosomes. To be strictly in accordance with this nomenclature, we have exchanged the term "tetraploid" by "near-tetraploid".

__ Is the height of the rows in Panel D significant? What are the solid black rows?______ We thank the reviewer for this comment/observation. We have now increased the resolution of this part of the figure. Unfortunately, the resolution had deteriorated so much when the pdf file was created that individual lines were no longer recognizable. The height of the lines should be identical, as single lines correspond to the karyotypes of each metaphase cell analyzed, while chromosomes are plotted as columns. The solid black lines separate independently established MEF lines with the indicated STIL genotypes from each other. At least 20 metaphase cells per MEF line were analyzed. We have now explained these points in the figure legend.

Figure 3____ 1. Panels C, F, G, and K require statistical analyses.

We have now included the appropriate statistical analyses in the figure panels and/or legends. However, the reported p-values should be interpreted as descriptive rather than confirmatory values due to the limited number of independent experiments.

• *

Panel D should be quantified.

We have now included a quantification of the protein bands in panels B, E (former panel D), and K of the revised manuscript and explained the quantification procedure in detail in the methods section.

Panel E. mRNA expression is quantified in RPKM here, while GeTMM is used in Figures 3I and Supplementary Figures S2 and S6. Is there a reason this panel uses a different method? RPKM can be used for intra-sample comparisons, but is not ideal for comparison among different samples.

We now uniformly quantify mRNA expression in GeTMM in all figures of the revised manuscript version as requested.

• *

Panel G. Can the authors show the original FACS profiles in Supplementary material?

As requested, we have now included representative examples of original FACS profiles from the cell cycle analyses into Supplemental Figure S5.

• *

Panel H. Requires molecular weight markers

Molecular weight markers for the DNA ladder (L) with the corresponding bp size have now been included into the Figure panel (formerly 3H, 3I in the revised version of the manuscript).

• *

__ Panel J. Missing B6-STIL control. Quantify Western blots.______ We have now included an immunoblot showing STIL protein expression levels in passage p1-p5 of B6-STIL control MEFs as well as a quantification of the protein bands into the Figure panel (formerly 3J, 3K in the revised version of the manuscript). The quantification procedure has been explained in detail in the methods section of the revised manuscript version.

Figure 4____ 1. The authors mention 'Simultaneously, we found an increased frequency of pups that died around birth.' Can the data for this be included?

After mating B6-STIL transgenic animals with CMV-CRE mice and further breeding of successive generations, we obtained a total of 198 pups over four generations, of which 162 were born alive: 116 B6-STIL wildtype animals, 27 CMV-STIL+/- and 19 CMV-STIL+/+ mice. We have now added these numbers to the figure legend. Stillbirths increased over the generations: while in the first generation after mating B6-STIL animals with CMV-CRE mice all pups (B6-STIL wildtype animals and STIL heterozygotes) were born alive, in the fourth generation (from mating CMV-STIL transgenic mice with each other) 54% of the pups were stillborn. We have now included this observation into the main text to further emphasize the impact of STIL overexpression on perinatal lethality.

Panels B and D. Please include the data for CMV-STIL+/-.

We now have included a representative H&E-stained histological section of a CMV-STIL+/- mouse brain into Figure panel 4D as suggested by the reviewer. For space reasons we have not added an extra image of a CMV-STIL+/- total brain into Figure panel 4B, as this does not add novel information.

Panels C, F and K require statistics.

As requested, we have now included the appropriate statistical analysis in the figure panels and/or legends. However, the reported p-values should be interpreted as descriptive rather than confirmatory values due to the limited number of independent experiments.

• *

Panel F. Include statistical analysis.

We have now included the appropriate statistical analysis in the figure panels and/or legends. However, the reported p-values should be interpreted as descriptive rather than confirmatory values due to the limited number of independent experiments.

• *

Panel G/H. The levels of STIL in the CMV-STIL+/+ spleen are higher than the other samples, yet there is no concomitant increase in centriole overduplication. Can the authors comment on this?

Interestingly, we indeed found a higher STIL protein expression level in spleen tissue from CMV-STIL+/+ as compared to B6-STIL control and CMV-STIL+/- mice. Nevertheless, the amount of splenocytes with supernumerary centrioles was only marginally increased in these animals. A similar finding has recently been described for B lymphocytes with upregulated PLK4 expression after PLK4 transgene induction by exposure to doxycycline in vivo (Braun et al.: Extra centrosomes delay DNA damage-driven tumorigenesis. Sci. Adv. 10: eadk0564, 2024). Here, the lack of B cells with supernumerary centrioles despite increased PLK4 levels was explained by increased apoptosis and thereby selection against and rapid loss of PLK4-overexpressing cells. In line, we show that CMV-STIL+/+ MEFs have increased rates of senescence and apoptosis (Fig. 4).

• *

__ Panel J. The font within the plots is difficult to read. ______ We thank the reviewer for this comment/observation. We have now increased the resolution of this figure panel, and the font is now outside of the plots.

Figure 5____** s should be interpreted as descriptive rather than confirmatory values due to the limited number of independent experiments. No further statistical analysis can be done for panel D as in some cases (lymph node from B6-STIL mouse, lymphoma from CMV-STIL+/+ mouse) only one measurement exists.

Panel F. The legend indicates that these data are from spleens and lymphomas. Is this correct? Would the results from non-lymphoma cells in the spleen mask the results from lymphoma cells?

We apologize for this mistake and have corrected the legend to Figure panel 5F, which now reads: “Percentage of Ki67-positive cells in two B6-STIL, two CMV-STIL+/- and one CMV-STIL+/+ lymphoma. For comparison, frequencies of Ki67-positive cells in healthy lymph nodes from B6-STIL mice are displayed. Data are means ± SEM from at least two independent immunostainings per lymphoma or healthy lymph node. P-values were calculated using the one-way ANOVA with post-hoc Tukey test for multiple comparison. For space reasons, only statistically significant differences are displayed”.

• *

Panel F. The authors indicate that 'In line, assessment of lymphomas from B6-STIL control, CMV-STIL+/- and CMV-STIL+/+ mice by Ki67 immunostaining revealed that, corresponding to STIL protein levels, proliferation rates were elevated independent from lymphoma genotypes'. However, Ki67 levels, the marker for proliferation actually decreased in these samples indicating less proliferative cells. This needs to be clarified since the data shown appears to show the opposite of what is stated in the mansucript....

As noticed by the reviewer further below, differences in the percentages of Ki67-positive, proliferating cells between lymphomas from B6-STIL, CMV-STIL+/- and CMV-STIL+/+ mice were statistically not significant. However, we have now for comparison added the results of Ki67 immunostaining of healthy lymph node tissue to Figure panel 5F, which show increased proliferation of lymphoma compared to normal lymph node cells. Also, a panel with images illustrating Ki67 labelling in healthy lymph node and lymphomas from different genotypes has been added to the figure (panel 5G). These data reveal that, independent from the genotype, proliferation rates of lymphoma cells are increased as compared to healthy lymph nodes, thereby further corroborating our assumption that STIL protein levels in lymphomas are increased as a consequence of their increased proliferation and independent from STIL transgene expression.

• *

Corresponding to point 3 above, the authors suggest that 'STIL protein expression is a consequence of increased lymphoma cell proliferation.' This hypothesis cannot explain STIL protein levels if proliferation has actually decreased.

Please see our response to point 3 above.

• *

Corresponding to point 3 and 4 above, the actual data is marked as non-significant indicating there is actually no proliferative difference among the samples.

This is correct. See also our comments to point 3 and 4 above.

__ Panel 5I. The authors state that 'On the other hand, overall levels of chromosomal copy number aberrations were higher in lymphomas (mean gains + losses: 225.2 Å} 173.7 Mb) as compared to healthy tissues (mean gains + losses: 87.3 Å} 127.5 Mb; p=0.06), irrespective of their STIL transgene status (Fig. 4J; Fig. 5I), although the difference did not quite reach statistical significance.' The authors need to soften this statement since statistically, the samples are not different. For example, 'On the other hand, overall levels of chromosomal copy number aberrations appeared to trend higher in lymphomas as compared to healthy tissues irrespective of their STIL transgene status, although the difference did not quite reach statistical significance.'______ The statement was rephrased according to the reviewer´s suggestion.

Figure 6____ 1. Panels A, B, and C require statistical analysis.

We have now included the appropriate statistical analyses into panels A, B, and C in the figure panels and/or legends. However, the reported p-values should be interpreted as descriptive rather than confirmatory values due to the limited number of independent experiments.

• *

The figure legend references to panels C and D appear to be swapped.

We thank the reviewer for this comment/observation. We have corrected this mistake.

Panel F. Indicate that the samples are not significantly different.

We have now included the appropriate statistical analysis including the indication that the samples are not statistically significantly different.

• *

__ Corresponding to point 3, the authors indicate that 'the proportion of Ki67-positive cycling cells was lower in tamoxifen-treated... ... although the difference did not quite reach statistical significance.' The authors need to soften this statement to reflect that the samples are not statistically different (i.e. 'appeared lower' or similar).______ The statement was rephrased according to the reviewer´s suggestion.

__Figure 6 and 7 _ Do you have data for B6-STIL animals treated with and without tamoxifen? The experiments as shown demonstrate the differences between control and tamoxifen-treated animals of the same genotype, but it is unclear if any of these effects are due to the underlying genotypes or from tamoxifen itself. ___ The experiments presented in Figures 6 and 7 have not been performed in B6-STIL control mice with and without tamoxifen treatment.

Supplemental Figure 1____ 1. Please include molecular weight marker for this and all panels showing PCR products.

Molecular weight markers for the DNA ladder (L) with the corresponding bp size have now been included into all Figure panels showing PCR products as requested.

The B6-STIL and CMV-STIL+/- lines should contain a larger MW band corresponding to the STIL-F and STIL-R PCR product. Please show if possible.

We thank the reviewer for the important remark. We agree that there should be a large PCR product band at around 3000 bp containing the bacterial neomycin phosphotransferase gene (TK-neo-pA) and the STOP cassette in the B6-STIL control mice/MEFs, and two PCR product bands (large: 3000 bp, small: 410 bp) in the heterozygous CMV-STIL+/-mice/MEFs. When we began with genotyping, we did indeed observe both bands depending on the STIL background (see figure below). However, the band intensity of the larger PCR product was relatively weak (arrowheads) compared to the smaller PCR product, and its visibility was dependent on genomic DNA input and PCR efficiency. During the PCR optimization process, the PCR conditions were changed in such a way that the yield of the small band were increased despite small input amounts of genomic DNA, but at the expense of the large PCR product band (arrows). At the end of the optimization process the larger PCR product had almost disappeared, making the discrimination between heterozygous CMV-STIL+/- and homozygous CMV-STIL-/- DNA difficult. Therefore, we decided to additionally check for STOP cassette excision in a second PCR approach in parallel. In the genotyping results shown in Supplemental Figure S1B, which have been produced after PCR optimization, no larger STIL PCR product band was visible anymore.

__Supplemental Figure 6 _ 1. The 'Spleen' sample is missing the B6-STIL control data. 'Liver' is missing CMV-STIL+/+. Please include or indicate why they are missing. The plot order of the samples differs for 'Liver' (red, black) compared to the others (black, red, blue). Indicate statistical significances. ___ We apologize for this mistake, have corrected the Figure (formerly Supplemental Figure S6, S2 in the revised version of the manuscript), and have included the missing spleen and liver samples.

• *

General issues ____ 1. The materials and methods indicate that HPRT and PIPB were used as reference genes, but only HPRT is referred to in the qPCR figure legend.

We thank the reviewer for this comment/observation. As generally recommended (Vandesomele et al., Genome Biol 3(7): research0034.1-research0034.11, 2002; Kozer and Rapacz, J Appl Genet 54(4): 391-406, 2013) we used both reference genes for accurate normalization of qPCR in all experiments. We have now corrected this mistake in the figure legend.

• *

Figure panels 1F and 3C display 95% confidence intervals while others use SEM. Is there a reason for this?

In the two referenced figures (former Figure 1F has been deleted from the manuscript, see also our comment to point 1 of reviewer #1 for reasons; Figure 3C of the former manuscript is now Figure 3D in the revised manuscript version) the endpoint variable was defined by whether individual cells in a single experiment showed a certain property or not (binary variables). By definition, these kinds of variables show a nonsymmetric error structure, which cannot be expressed properly by a single value such as the standard error (SEM), but can be covered correctly by a confidence interval. For the same reason, Fisher’s exact tests were employed to obtain p-values in these situations. In the other figures, the relevant endpoint variables were roughly normally distributed, either directly, or due to them being an average of many values. In this case, a symmetric SEM was thus considered sufficient, and t-tests were used for p-values. To make this clear in the figures, we used different display options to distinguish between error bars showing SEM or 95% CI.

__Reviewer #2 (Significance (Required)): ______ *In this manuscript, Moussa et al. describe the effects of over-expressing the centriole duplication factor STIL in whole mice and with expression restricted to the skin. They find that over expression of STIL, similar to that of PLK4, induces centriole overduplication, abnormal mitoses, and genetic instability leading to cell arrest. Additionally, over-expressing STIL results in microcephaly, perinatal lethality and a shortened lifespan. In addition, they do not find that expression of the p53 R127H mutant alleviates the cell growth defect. Moreover, overexpression of STIL does not lead to increased general tumour formation and suppresses tumour formation in an induced skin tumour model. Although this is an interesting manuscript, the authors need address a number of issues before this manuscript can be recommend the manuscript for publication. Importantly, the manuscript lacks statistical analyses to support some of their conclusions, some figures should be quantified, and controls are missing in some cases. *

__Reviewer #3 (Evidence, reproducibility and clarity (Required)): ______ Previously it has been proposed that supernumerary centrioles play important deleterious effects in vivo including increased tumorigenesis. However, the work was inconclusive because the way of inducing centriole amplification via the PLK4 kinase could have induced other effects besides supernumerary centrioles. To resolve this question, the authors generated a mouse model of centrosome amplification, in which the structural centriole protein STIL is overexpressed. Using this mouse model in vivo along with mutant mouse embryonic feeder (MEF) lines in vivo, the authors test out the role of centrosome amplification in vivo in animal development, lifespan, and tumorigenesis. They report both embryonic lethality, defects in brain development, and shortened life span in these mice. They also find that skin tumorigenesis is reduced in the mutant mice, and demonstrates that the STIL overexpression effects are not perturbed in a dominant negative p53 model. The authors demonstrate that STIL overexpression causes centrosome amplification accompanied by aneuploidy, which however is highly deleterious for cell fitness even in the absence of p53. Clearly, tissue corrective mechanisms lead to the elimination of cells with extra centrosomes and/or aneuploidy by impaired proliferation, senescence, and apoptosis. This finding is interesting and significant and seems worthy of dissemination to the broader readership.

This study is thorough and well executed and there is a significant body of work that leads to solid conclusions. The data is convincing, and the figure are well presented. It was refreshing to read this paper, as it was not so cluttered with data that the message gets murky, yet the data was clearly very substantial. The text is clear and easy to follow.

---

There really are only minor aspects of this paper that need correction, in my opinion. The text should be thoroughly checked for typos, few extra redundant words here and there, and a couple of confusing sentences.______ As suggested by the reviewer we have rechecked the manuscript for typos, redundancies, and confusing sentences and corrected where necessary and appropriate. __* *

For example, the last sentence in abstract is confusing 'These results suggest that supernumerary centrosomes... [result in]... tumor formation' because it should read 'reduced tumor formation' or 'impairs tumorigenesis' or otherwise be written more clearly because it seems to convey the opposite message the way it is right now. ______ We thank the reviewer for this comment and have corrected the sentence, which now reads: “These results suggest that supernumerary centrosomes impair proliferation in vitro as well as in vivo, resulting in reduced lifespan and delayed spontaneous as well as carcinogen-induced tumor formation”. The p53 dominant negative mutant is not exactly a KO so it is not fair to say "in the absence of p53"; the verbiage should be corrected and checked throughout the paper - perhaps 'interfering with p53 normal function' is more appropriate.__ As suggested by the reviewer we have corrected the wording and have substituted “absence of p53” by “interference with p53 function” where appropriate. The sentence "Senescence- and apoptosis-driven depletion of the stem cell pool may explain reduced life span and tumor formation in STIL transgenic mice." from discussion is highly speculative and should be edited to clearly convey its speculative nature or removed entirely. ______ We agree with the reviewer and have deleted the sentence from the discussion section of the manuscript.

__Reviewer #3 (Significance (Required)): ______ Clearly, tissue corrective mechanisms lead to the elimination of cells with extra centrosomes and/or aneuploidy by impaired proliferation, senescence, and apoptosis. This finding is interesting and significant and seems worthy of dissemination to the scientific community. It adds to previous work on another centriole related protein PLK4 kinase that led to very different conclusions.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Previously it has been proposed that supernumerary centrioles play important deleterious effects in vivo including increased tumorigenesis. However, the work was inconclusive because the way of inducing centriole amplification via the PLK4 kinase could have induced other effects besides supernumerary centrioles. To resolve this question, the authors generated a mouse model of centrosome amplification, in which the structural centriole protein STIL is overexpressed. Using this mouse model in vivo along with mutant mouse embryonic feeder (MEF) lines in vivo, the authors test out the role of centrosome amplification in vivo in animal development, lifespan, and tumorigenesis. They report both embryonic lethality, defects in brain development, and shortened life span in these mice. They also find that skin tumorigenesis is reduced in the mutant mice, and demonstrates that the STIL overexpression effects are not perturbed in a dominant negative p53 model. The authors demonstrate that STIL overexpression causes centrosome amplification accompanied by aneuploidy, which however is highly deleterious for cell fitness even in the absence of p53. Clearly, tissue corrective mechanisms lead to the elimination of cells with extra centrosomes and/or aneuploidy by impaired proliferation, senescence, and apoptosis. This finding is interesting and significant and seems worthy of dissemination to the broader readership. This study is thorough and well executed and there is a significant body of work that leads to solid conclusions. The data is convincing, and the figure are well presented. It was refreshing to read this paper, as it was not so cluttered with data that the message gets murky, yet the data was clearly very substantial. The text is clear and easy to follow.

• There really are only minor aspects of this paper that need correction, in my opinion. The text should be thoroughly checked for typos, few extra redundant words here and there, and a couple of confusing sentences.
• For example, the last sentence in abstract is confusing 'These results suggest that supernumerary centrosomes... [result in]... tumor formation' because it should read 'reduced tumor formation' or 'impairs tumorigenesis' or otherwise be written more clearly because it seems to convey the opposite message the way it is right now.
• The p53 dominant negative mutant is not exactly a KO so it is not fair to say "in the absence of p53"; the verbiage should be corrected and checked throughout the paper - perhaps 'interfering with p53 normal function' is more appropriate.
• The sentence "Senescence- and apoptosis-driven depletion of the stem cell pool may explain reduced life span and tumor formation in STIL transgenic mice." from discussion is highly speculative and should be edited to clearly convey its speculative nature or removed entirely.

Significance

Clearly, tissue corrective mechanisms lead to the elimination of cells with extra centrosomes and/or aneuploidy by impaired proliferation, senescence, and apoptosis. This finding is interesting and significant and seems worthy of dissemination to the scientific community. It adds to previous work on another centriole related protein PLK4 kinase that led to very different conclusions.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

In this manuscript, Moussa et al. describe the effects of over-expressing the centriole duplication factor STIL in whole mice and with expression restricted to the skin. They find that over expression of STIL, similar to that of PLK4, induces centriole overduplication, abnormal mitoses, and genetic instability leading to cell arrest. Additionally, over-expressing STIL results in microcephaly, perinatal lethality and a shortened lifespan. In addition, they do not find that expression of the p53 R127H mutant alleviates the cell growth defect. Moreover, overexpression of STIL does not lead to increased general tumour formation and suppresses tumour formation in an induced skin tumour model.

Although this is an interesting manuscript, the authors need address a number of issues before this manuscript can be recommend the manuscript for publication. Importantly, the manuscript lacks statistical analyses to support some of their conclusions, some figures should be quantified, and controls are missing in some cases.

Major Issues

1. Many of the figure panels lack appropriate statistical analyses to support the conclusions (see details below). This needs to be rectified.
2. The authors suggest that the interpretation of PLK4 over-expression studies are hampered by the possibility of centriole/centrosome independent PLK4 roles and that STIL overexpression circumvents some of these issues. Although orthologous approaches to problems are always desired, STIL itself has also been implicated in other cellular processes, such as the Sonic hedgehog pathway (Carr AL, 2014) and in cell motility (Liu Y, 2020). In addition, the data presented in the manuscript are suggestive of a STIL function in the mouse that is independent of centriole number. The authors demonstrate that the amount of centriole over-duplication in MEFs containing a single copy of the STIL over-expression locus is equivalent to that of MEFs carrying two copies. However, in most other assays, the homozygous lines display more severe phenotypes, suggesting that STIL might have a function outside centriole duplication. he authros need to discuss this further in a revised manuscript.
3. Why did the authors use the p53 R127H mutant instead of a p53 knockout or null allele system? The R127H mutant has a gain-of-function phenotype and cells expressing this mutant display different phenotypes than a p53 null. The primary conclusion in one of the references cited by the authors (Caulin C, 2007) is that p53R127H is a gain-of-function mutant and behaves distinct from loss-of-function p53 mutations, such as deletions using floxed alleles. Throughout the manuscript, the authors use terms that suggest the R127H allele is equivalent to a loss of function mutant. Given that supernumerary centriole growth arrest is universally suppressed by inactivation of p53 it is somewhat surprising that this pathway is not active in response to STIL over-expression. The authors should confirm this key conclusion by depleting p53 in MEFs using RNAi, or by using mice where complete inactivation of p53 can be achieved.

Minor Issues and details

Figure 1

1. Panel E. It is unclear what the authors are calling an 'aberrant mitosis'. Typically an aberrant mitosis refers to chromosomal abnormalities such as multipolar spindles, anaphase bridges or micronuclei (which they quantify in Figure 2).
2. Panel E. Please include images representing a normal mitosis from control cells derived from B6-STIL mice.

Figure 2

1. Panels B, E and F. Statistical significance is not indicated between B6-STIL and CMV-STIL+/- or CMV-STIL+/- and CMV-STIL+/+. The authors indicated a 'graded' phenotype which is qualitatively apparent, but should be backed by statistical analysis.
2. Can the authors indicate how they scored a tetraploid cell? Some of the cells are 100% tetraploid while others contain other aberrations.
3. Is the height of the rows in Panel D significant? What are the solid black rows?

Figure 3

1. Panels C, F, G, and K require statistical analyses.
2. Panel D should be quantified.
3. Panel E. mRNA expression is quantified in RPKM here, while GeTMM is used in Figures 3I and Supplementary Figures S2 and S6. Is there a reason this panel uses a different method? RPKM can be used for intra-sample comparisons, but is not ideal for comparison among different samples.
4. Panel G. Can the authors show the original FACS profiles in Supplementary material?
5. Panel H. Requires molecular weight markers
6. Panel J. Missing B6-STIL control. Quantify Western blots.

Figure 4

1. The authors mention 'Simultaneously, we found an increased frequency of pups that died around birth.' Can the data for this be included?
2. Panels B and D. Please include the data for CMV-STIL+/-.
3. Panels C, F and K require statistics.
4. Panel F. Include statistical analysis.
5. Panel G/H. The levels of STIL in the CMV-STIL+/+ spleen are higher than the other samples, yet there is no concomitant increase in centriole overduplication. Can the authors comment on this?
6. Panel J. The font within the plots is difficult to read.

Figure 5

1. Panels B, D and G require statistics.
2. Panel F. The legend indicates that these data are from spleens and lymphomas. Is this correct? Would the results from non-lymphoma cells in the spleen mask the results from lymphoma cells?
3. Panel F. The authors indicate that 'In line, assessment of lymphomas from B6-STIL control, CMV-STIL+/- and CMV-STIL+/+ mice by Ki67 immunostaining revealed that, corresponding to STIL protein levels, proliferation rates were elevated independent from lymphoma genotypes'. However, Ki67 levels, the marker for proliferation actually decreased in these samples indicating less proliferative cells. This needs to be clarified since the data shown appears to show the opposite of what is stated in the mansucript....
4. Corresponding to point 3 above, the authors suggest that 'STIL protein expression is a consequence of increased lymphoma cell proliferation.' This hypothesis cannot explain STIL protein levels if proliferation has actually decreased.
5. Corresponding to point 3 and 4 above, the actual data is marked as non-significant indicating there is actually no proliferative difference among the samples.
6. Panel 5I. The authors state that 'On the other hand, overall levels of chromosomal copy number aberrations were higher in lymphomas (mean gains + losses: 225.2 Å} 173.7 Mb) as compared to healthy tissues (mean gains + losses: 87.3 Å} 127.5 Mb; p=0.06), irrespective of their STIL transgene status (Fig. 4J; Fig. 5I), although the difference did not quite reach statistical significance.' The authors need to soften this statement since statistically, the samples are not different. For example, 'On the other hand, overall levels of chromosomal copy number aberrations appeared to trend higher in lymphomas as compared to healthy tissues irrespective of their STIL transgene status, although the difference did not quite reach statistical significance.'

Figure 6

1. Panels A, B, and C require statistical analysis.
2. The figure legend references to panels C and D appear to be swapped.
3. Panel F. Indicate that the samples are not significantly different.
4. Corresponding to point 3, the authors indicate that 'the proportion of Ki67-positive cycling cells was lower in tamoxifen-treated... ... although the difference did not quite reach statistical significance.' The authors need to soften this statement to reflect that the samples are not statistically different (i.e. 'appeared lower' or similar).

Figure 6 and 7

Do you have data for B6-STIL animals treated with and without tamoxifen? The experiments as shown demonstrate the differences between control and tamoxifen-treated animals of the same genotype, but it is unclear if any of these effects are due to the underlying genotypes or from tamoxifen itself.

Supplemental Figure 1

1. Please include molecular weight marker for this and all panels showing PCR products.
2. The B6-STIL and CMV-STIL+/- lines should contain a larger MW band corresponding to the STIL-F and STIL-R PCR product. Please show if possible.

Supplemental Figure 6

1. The 'Spleen' sample is missing the B6-STIL control data. 'Liver' is missing CMV-STIL+/+. Please include or indicate why they are missing. The plot order of the samples differs for 'Liver' (red, black) compared to the others (black, red, blue). Indicate statistical significances.

General issues

1. The materials and methods indicate that HPRT and PIPB were used as reference genes, but only HPRT is referred to in the qPCR figure legend.
2. Figure panels 1F and 3C display 95% confidence intervals while others use SEM. Is there a reason for this?

Significance

In this manuscript, Moussa et al. describe the effects of over-expressing the centriole duplication factor STIL in whole mice and with expression restricted to the skin. They find that over expression of STIL, similar to that of PLK4, induces centriole overduplication, abnormal mitoses, and genetic instability leading to cell arrest. Additionally, over-expressing STIL results in microcephaly, perinatal lethality and a shortened lifespan. In addition, they do not find that expression of the p53 R127H mutant alleviates the cell growth defect. Moreover, overexpression of STIL does not lead to increased general tumour formation and suppresses tumour formation in an induced skin tumour model.

Although this is an interesting manuscript, the authors need address a number of issues before this manuscript can be recommend the manuscript for publication. Importantly, the manuscript lacks statistical analyses to support some of their conclusions, some figures should be quantified, and controls are missing in some cases.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Supernumerary centrosomes are observed in the majority of human tumors. In cells they induce abnormal mitosis leading to chromosome missegregation and aneuploidy. In animal models it is demonstrated that extra centrosomes are sufficient to drive tumor formation. Previous work studying the impact of centrosome amplification on tumor formation in vivo used Plk4 overexpression to drive the formation of supernumerary centrosomes. In this manuscript Moussa and co-workers from the Krämer group developed a mouse model in which centrosome amplification is triggered by the overexpression of the structural centrosomal protein STIL rather than the kinase Plk4 in order to a) assess the potential for centrosome amplification induced by STIL overexpression to drive tumor formation and b) to rule out any potential non-centrosomal related effects of the kinase Plk4 on tumor formation. The authors show that STIL ovexrexpression in cells (MEFs) drives centrosome amplification and aberrant mitosis (Fig. 1), leading to chromosome missegregation and aneuploidy (Fig. 2). They also show that STIL overexpression is linked to reduced cellular proliferation and apoptosis (Fig 3). The authors then present in vivo experiments performed in mice. They observed that STIL expression causes embryonic lethality, microcephaly and a reduced lifespan (Fig 4). Despite increased STIL mRNA levels they do not detect elevated STIL protein levels in adult tissues except for the spleen. They do not detect significant increase of centrosome amplification or aneuploidy in animal tissues (Fig 4) and they conclude of a STIL translational shut down in most adult tissues. The authors then assess the impact of STIL overexpression on tumor formation. They observed a reduced spontaneous tumor formation despite elevated STIL mRNA levels in both healthy and tumor (lymphomas) tissues of mice overexpressing STIL. They don't detect increased centrosome amplification and aneuploidy in lymphomas from STIL overexpressing mice compared to lymphomas naturally occurring in control animals (Fig 5). Finally, they found that STIL overexpression suppresses chemical skin carcinogenesis using a combination of tamoxifen induction of STIL in the skin with DMBA/TPA carcinogenic treatment (Fig 7). They link this effect to an increased number of centriole and a reduction in cycling cells number in the skin of STIL overexpressing mice (Fig 6).

The manuscript is written in a clear manner. The experimental approaches are properly designed and the experimental methods are described in sufficient details. Most of the experimental data present a good number of replicates. The figures are generally well assembled despite some errors in a few panels/legends (see major and minor points). Most of the conclusions are supported by the experimental data. However, a few specific points or interpretations are not convincingly supported by the experimental data (see major points) and will need to be revised and/or reformulated.

Major points:

1. Figures 1D and F show that MEFs hemizygous (CMV-STIL+/-) and homozygous (CMV-STIL+/+) for STIL present similar level of centrosome amplification and aberrant mitosis. Although, despite these similarities the homozygous MEFs display about two time more micronuclei and chromosomes aberrations (Fig. 2). The authors explain this discrepancy by the fact that MEFs homozygous for STIL have reduced proliferation and an increased propension to stay in interphase compared to hemizygous MEFs (Fig. 3). I don't understand why an interphase arrest would lead to a higher chromosomal instability resulting in higher micronuclei formation and abnormal karyotypes since those phenotypes are the consequences of abnormal mitosis occurring in cycling cells. I would rather argue that Homozygous MEFs are more prone to cell cycle arrest because of mitotic errors, but those mitotic errors cannot be explained by the centrosome status or the mitotic figures quantified in homozygous MEFs. Therefore, the authors explanation written as: "Graded inhibition of proliferation and accumulation of cells in interphase explains why CMV-STIL+/- and CMV-STIL+/+ MEFs contain increasing frequencies of micronuclei and aberrant karyotypes (Fig. 2) despite similar levels of supernumerary centrosomes" is not right for me. The authors should reformulate this section of the manuscript so their conclusion fit their data. The differences between hemi and homozygotes MEFs regarding chromosome stability could come from mitotic errors they did not spot using fixed immunofluorescence images of mitotic MEFs. Thus, as an optional additional experiment, analyzing live mitosis of MEFs could potentially help reconciliate results from mitotic figures and from karyotypes.
2. Figure 5 panel F does not support the claim of the main text and does not match the legend of the figure: In the text the authors wrote: "Ki67 immunostaining revealed that, ..., proliferation rates were elevated independent from lymphoma genotypes". If the authors claim and increased cell proliferation in lymphoma compared to lymph nodes, which is expected, they should show the data for the lymph node in the graph. In addition, in the legend the authors mentioned a "Percentage of Ki67-positive cells in healthy spleens and lymphomas from mice with the indicated genotypes." Since there are three genotypes and two tissue types but the figure presents a graph with only three bars did the Spleen and lymphoma data were combined? Or did some data were not inserted in the graph? Thus, since the data does not support the claim for an increased cell proliferation in lymphoma, the authors explanation for the increased protein level observed in these lymphomas (Fig. 5 panel E) is not supported. Therefore, the authors need to present the correct data in the figure or to change their conclusion. They will also need to correct the figure legend and to add a panel with images illustrating the Ki67 labelling in the different tissues in the figure.

Minor points:

1. In the introduction, page 4 paragraph 3, the authors wrote: "To assess the impact of centrosome amplification on CIN, senescence, lifespan and tumor formation in vivo without interfering with extracentrosomal traits,..." they need to clarify what they meant by extracentrosomal traits.
2. In the 1st paragraph of the results, page 4, the authors wrote: "leads to ubiquitous transgene expression at levels similar to the CAG promoter used in most..." but there is no link to a figure presenting the mRNA levels in those mice (potentially Fig. 4F and Fig. S6). Also, in the references cited for comparison, to my knowledge, there was no measurement of Plk4 mRNA levels in tissues in the work from Marthiens and colleagues, in this work the authors assess the expression of the Plk4 transgene by investigating the presence of the protein.
3. Page 5 second line the authors wrote: "Despite the graded increase in Plk4 expression, CMV-STIL+/- and, CMV-STIL+/+ MEFs exhibited a similar increase in supernumerary centrioles". The authors must meant increase in STIL expression or do they have data not shown about an increase of Plk4 expression? Then they explain this absence of difference in supernumerary centriole by the ability of "excess Plk4" to access the centrosome, again they probably meant STIL. Regarding this point and related to Major Point 1 it might be worth for the authors to quantify actual extra centrosomes in mitosis rather than cells with more than 4 centrioles in interphase (as in Fig. 1C, D). They might find differences in the number of centrosomes in hemizygous versus homozygous MEFs.
4. Page 5, in the first paragraph the authors mention "the rate of respective mitotic aberrations..." without defining the mitotic aberrations. For instance, in panel 1E a metaphase with 4 centrosomes is shown for CMV-STIL+/- while an anaphase with an unknown number of clustered centrosomes is presented for CMV-STIL+/+. Classifying the different types of aberrant mitotic figures (i.e: multipolar anaphases versus bipolar with clustered centrosomes) might help the authors identify differences between hemi and homozygous MEFS that may explain the differences in the proportions of chromosomes aberrations they present in Fig. 2.
5. In Fig 4A the number of mice analyzed should be mentioned.
6. In Fig. 5E, the band corresponding to STIL protein is difficult to visualize in the B6-STIL control, it is therefore difficult to compare its level to the level of STIL protein in the CMV-STIL hemizygotes and homozygotes. If possible, it would improve the manuscript to present a blot with clearer results.
7. Related to Figure 6B the authors wrote a "5 to 10 fold-increased expression..." in the text while panel 6 B show a maximum of 8 fold increase.

Significance

Centrosome amplification is a demonstrated cause of genomic instability and tumor development as shown in multiple previous work performed in mice. In this work, Moussa and co-workers developed a mouse model that does not depends on Plk4 to trigger centrosome amplification but which depends on the overexpression of the centrosome structural protein STIL. This effort is welcome as previous works could not formally rule out potential role of Plk4, not related to its centrosome duplication function, on tumor formation.

The authors show that their system is functional in MEFs where STIL overexpression drives centrosome amplification and aneuploidy. Unfortunately, in vivo, despite elevated level of STIL mRNA they do not detect centrosome amplification in tissues and consequently, they do not observe an increase rate of aneuploidy and tumor formation. This result is not surprising as previous studies using strong promoters (comparable to the one used to drive STIL expression in this study) to induce Plk4 overexpression led to similar results, i.e. an absence of centrosome amplification in adult tissues and no effects on tumor formation.

Therefore, the results and the concepts proposed in this work are not novel but they reinforce previous studies showing the deleterious effect of high level of centrosome amplification on cells. This work also confirms that strong mechanisms, here the authors propose a translational shut-down, are preventing the apparition or the persistence of high level of centrosome amplification in animal tissues.

By complementing existing results with the use of an alternate experimental approach this study will be of interest for the scientific community working on the basic biological mechanisms driving aneuploidy and tumor development.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

Reply to the Reviewers

We sincerely thank the Referees for providing important and constructive comments. We have addressed their concerns point-by-point as described below.

Associated to Reviewer#1's comments

*- Diploid embryos are used as controls. Gynogenetic diploids seem to be better controls to ensure that the observed phenotypes are not related to loss of heterozygosity. To limit the amount of work, the use of gynogenetic diploids could be restricted to spindle polarity and centrosome number experiments. *

Response 1-1

__[Experimental plan] __Following the reviewer's suggestion, we will conduct immunostaining of a-tubulin and centrin (for visualizing the spindles and centrioles, respectively) in gynogenetic diploids that will be generated by applying heat shock to gynogenetic haploid embryos during the 1st - 2nd cleavage stage. We will observe the head area of gynogenetic diploid larvae at 3-dpf when the haploid counterparts suffer particularly drastic centrosome loss and spindle monopolarization.

• *

• *

*- As the authors discuss, it would be necessary to rescue centrosome loss to establish a causal relationship between centrosome loss and haploid viability. I certainly acknowledge that this is difficult (if not impossible), but it currently limits the significance of the results. *

Response 1-2

We agree that rescuing centrosome loss would provide an important advancement in understanding the cause of haploid syndrome in the context of our study. However, as the reviewer also pointed out in the above comment, this poses a significant technical challenge. As described in Discussion in the original manuscript, we have attempted to restore normal centrosome number through cell cycle modulations. However, we have not found a condition that rescues centrosome loss without damaging larval viability. As an alternative approach, we have also tried to induce centriole amplification by injecting mRNA encoding plk4, an essential centriole duplication inducer. However, this caused earlier embryonic death, precluding us from observing its effects on larval morphology after 1 dpf. The main challenge is that any treatment to increase centrosome number can cause centrosome overduplication, which is as deleterious to development as centrosome loss. Efforts to identify a key factor enabling the rescue of centrosome loss in haploid larvae are underway in our laboratory, which requires new explorations over several years and is beyond the scope of the present study. Reflecting on the reviewer's comment, we added a new sentence explaining the situation on this issue (line 395, page 19). To further discuss possible contributions of centrosome loss and mitotic defects to haploidy-linked embryonic defects, we also added a citation of a previous study reporting that depletion of centrosomal proteins caused mitotic defects leading to embryonic defects similar to those observed in haploid embryos in zebrafish (Novorol et al., 2013 Open Biology; line 380, page 19).

__[Experimental plan] __Meanwhile, as a new trial to induce centriole amplification in a scalable and temporally controllable manner, we plan the following experiment, which can be conducted within the time range of the revision schedule: We will investigate the effects of low dose treatment of a plk4 inhibitor centrinone B on tissue growth and viability of haploid larvae. A recent study reported that centrinone B had complicated effects on the centriole duplication process, which is highly dose-sensitive (Tkach et al., 2022 Elife, PMID: 35758262). While it blocks centriole duplication at sufficiently high concentrations for blocking plk4 activities, it paradoxically causes centriole amplification at suboptimal conditions, presumably though over-stabilizing plk4 by blocking its autophosphorylation-dependent degradation (while its centriole duplicating function remains active). Since a previous study showed that centrinone B is also effective in zebrafish embryos (Rathbun et al., 2020 Current Biology, PMID: 32916112), we try to find optimal centrinone B treatment condition that potentially restores tissue growth or viability of haploid embryos. If we find such a rescuing condition, we will address the principle of the rescuing effects by investigating the possession of centrioles in mitotic cells in these haploid larvae.

*- Some experiments are not, or arguably, quantified/statistically analyzed. *

o Figure 2, Active caspase level. Larvae are sorted into three categories, and no statistical test is performed on the obtained contingency table. A Fisher'*s exact test here, or much better, the active caspase-3 levels should be quantified, instead of sorting larvae into categories. *

Response 1-3

We apologize that we showed only "zoomed-out" images of the immunostained embryos in the original figures (Fig. 2A), which precluded a clear presentation of the haploidy-associated aggravation of apoptosis and mitotic arrest. We could clearly distinguish cleaved caspase-3- and pH3-positive cells from non-specific background staining with an enlarged view of the same immunostaining data. Therefore, to quantitatively evaluate the extent of the haploidy-linked apoptosis and mitotic arrest, we compared the density of these cells within the right midbrain. This new quantification demonstrated a statistically significant increase in cleaved caspase-3- or pH3-positive cells in haploids compared to diploids.

In the revised manuscript, we added the enlarged views of cleaved-caspase and pH3 immunostaining (Fig. 2B) and new quantifications with statistical analyses (Fig. 2C). Accompanying these revisions, we omitted the categorization of the severeness of the apoptosis, which was pointed out to be subjective in the reviewer#2's comment (see Response 2-3). We rewrote the corresponding section of the manuscript to explain the new quantitative analyses (line 143, page 7).

o Same comment for 3E-F. Larvae are scored as Scarce, Mild or Severe. Looking at Fig S3A, I see one mild p53MO embryo, but the two others are not that different from 'severe' cases, which would completely change the contingency table. Again, a proper quantification would be better.

Response 1-4

We also quantified the frequency of cleaved caspase-3-positive cells in control and p53MO larvae (original Fig. 3E and F) as described in Response 1-3. While conducting the cell counting with enlarged images, we realized that staining quality within the inner larval layers of morphants was relatively poor in these experiments. This problem precluded us from counting cleaved caspase-3-positive cells within the inner larval layers. Therefore, we tentatively quantified only the surface larval layers of these morphants and found that cleaved caspase-3-positive cells were significantly reduced in haploids upon depletion of p53. We currently show this quantification in Fig. 3G of the revised manuscript. While this quantification confirmed the trend of p53MO-dependent decrease in apoptosis, we think it more appropriate to newly conduct the same experiment with better quality of the staining to apply the same standard of quantification for Fig. 3 as Fig. 2.

---

__[Experimental plan] __For the reason described above, we propose to re-conduct immunostaining of cleaved caspase-3 in control and p53MO-injected haploid larvae to improve the visibility of the inner layer of the larvae for better quality of the quantitation.

Meanwhile, we revised Fig. 3 by adding an enlarged view of immunostaining in Fig. 3F and omitting the subjective categorization shown in the original Fig. 3F and S3A. We plan to replace these data with new images and quantification to be obtained during the next revision. We also rewrote the main text to update these changes (line 166, page 8).

*o Figure 4D-E, no stats. *

Response 1-5

We conducted the ANOVA followed by the post-hoc Tukey test for new Fig. 4D and the Fisher exact test with Benjamini-Hochberg multiple testing correction for new Fig. 4E. Please note that statistical analyses were conducted after adding the data from original Fig. 6B-C following the reviewer's suggestion (see also Response 1-6).

*o Figure 6, Reversine treated haploid should be compared to haploid embryos (on the graphs and statistically). If no specific controls have been quantified for this experiment, data could be reused from previous figures, provided this is stated. *

Response 1-6

The live imaging data shown in original Fig. 4C-E and Fig. 6A-C were obtained within the same experimental series conducted in parallel at the same period under the same experimental condition. In the original manuscript, we separated them into two different figures according to the logical flow. However, following the reviewers' comments (see also Response 2-1), we realized it more appropriate to show them as a single figure panel as in the original experimental design. Therefore, we moved the reversine-treated haploid data from the original Fig. 6A-C to Fig. 4C-E to facilitate direct comparison among conditions with statistical analyses (see also Response 1-5).

*o Rescue by p53MO and Reversine, it would be nice to also include diploid measurements on the graphs, so that the reader can appreciate the extent of the rescue. *

Response 1-7

Following the reviewer's comment, we added control MO-injected or DMSO-treated diploid larval data in the corresponding graphs in Fig. 3I and 6G, respectively. Please refer to Response 2-6 for further discussion on the extent of the rescue.

Minor comments:

*- Lines 221-223, authors claim that centriole loss and spindle monopolarization commence earlier in the eyes and brain than in skin. I am note sure I see this in Fig. S5. It could as well be that the defect is less pronounced in skin. *

Response 1-8

We rewrote the manuscript to include the possible interpretation suggested by the reviewer on the result (line 225, page 11).

• *

- Lines 227-229, authors claim that 'The developmental stage when haploid larvae suffered the gradual aggravation of centrosome loss corresponded to the stage when larval cell size gradually decreased through successive cell divisions'. I did not get that. Doesn'*t cell size decrease since the first division? Fig 5D shows that cell size decreases all along development. *

Response 1-9

We agree that the original sentence implies, against our intention, that cell size does not decrease before the developmental stage mentioned here. To correct this problem, we rewrote the corresponding part of Discussion as below (line 230, page 11):

"Since the first division, embryonic cell size continuously reduces through successive cell divisions during early development (Menon et al., 2020). Cell size reduction continued at the developmental stage when we observed the gradual aggravation of the centrosome loss in haploid larvae."

*- Some correlations are used to draw conclusions: *

o Line 301-303. "The correlation between centrosome loss and spindle monopolarization indicates that haploid larval cells fail to form bipolar spindle because of the haploidy-linked centrosome loss."*. As stated by the authors, this is a correlation only. I agree it points in this direction. *

Response 1-10

We added a note to the corresponding sentence to draw readers' attention to the discussion on the limitation of the study with respect to the lack of centrosome rescue experiment (line 332, page 16).

O Line 305-308. "*Interestingly, centrosome loss occurred almost exclusively in haploid cells whose size became smaller than a certain border (Fig. 5), indicating that cell size is a key determinant of centrosome number homeostasis in the haploid state." This one is more problematic. There is no causal link established between cell size and centrosome number homeostasis. It could very well be that some unidentified problem induces both a reduction in cell size and the loss of centrioles. *

Response 1-11

To avoid an over-speculative description, we deleted the subsentence "indicating that cell size is a key determinant of centrosome number homeostasis in the haploid state." (line 336, page 17). We also added a new sentence, "Alternatively, it is also possible that other primary causes, such as the lack of second active allele producing sufficient protein pools induced cell size reduction and centrosome loss in parallel without causality between them." to discuss the possibility raised by the reviewer (line 348, page 17), in association with another comment from the reviewer #3 (see also Response 3-3).

• *

*I have concerns regarding the significance of the reported findings. Haploid zebrafish embryos show numerous developmental defects (some as early as gastrulation, as previously shown by the authors, Menon 2020), and they die by 4 dpf. That they experience massive apoptosis at day 3 does not seem very surprising, and that inhibiting p53 transiently improves the phenotype is not a big surprise. *

Response 1-12

Many reports have revealed tissue-level developmental abnormalities in haploid embryos since the discovery of haploid lethality in vertebrates more than 100 years ago. This has stimulated speculation of underlying causes of haploid intolerance for decades. However, there have been surprisingly few descriptions of cellular abnormalities underlying these tissue defects, precluding an evidence-based understanding of the principle that limits developmental ability in haploid embryos. Our findings of the haploidy-linked p53 upregulation and mitotic defects illustrate what happens in the dying haploid embryos at a cellular level. These findings would provide an evidence-based frame of reference for understanding why vertebrates cannot develop in the haploid state and also provide clues to controlling haploidy-linked embryonic defects in future studies. We added a new section in Discussion to discuss the importance of addressing the haploidy-linked defects at a cellular level (line 276, page 14).

*This reminds me of the non-specific effects of morpholino injection, which can be partially rescued by knocking down p53. *

Response 1-13

We believe the reviewer refers to the previous findings that different morpholinos generally have off-target effects activating p53-mediated apoptosis (e.g., Robu et al., 2007 PLoS Genet, PMID:17530925). However, p53 upregulation and apoptosis aggravation were also observed in uninjected haploid embryos free from morpholinos' artificial effects (Fig. 2, Fig. 3A, and B). To further address this issue, we plan to compare the frequency of cleavage caspase-3-positive cells between uninjected and control MO-injected haploids after revising the immunostaining of morphants in the original Fig. 3E-F (see Response 1-4 for details).

*The observation of mitotic arrest and mitotic defects and the observation that haploid cells often lack a centrosome is interesting. However, I felt that the manuscript suggested that these observations were novel and could explain the haploid syndrome specifically in non-mammalian embryos, when the authors reported the same observations in human haploid cells as well as in mouse haploid embryos (Yaguchi 2018). To me, this manuscript mainly confirms that their previous observation is not mammalian specific, but at least conserved in vertebrates. *

Response 1-14

As we originally wrote (line 341, page 17 in the original manuscript), we think these haploidy-linked cellular defects are conserved among mammalian and non-mammalian vertebrates. To improve the clarity of our interpretation, we rewrote a corresponding part of the manuscript (line 50, page 2).

*While I am no expert at centrosome duplication, I find the observation that haploidy leads to centrosome loss very intriguing, but have the impression that this manuscript falls short of improving our understanding of this phenomenon. *

Response 1-15

We express our gratitude to the reviewer for being interested in our findings. We hope the revisions made in the manuscript and the new results provided by the planned experiments will strengthen the contribution of this study to our understanding of haploidy-linked cellular defects.

• *

• *

Associated to Reviewer#2's comments

- Lack of proper controls in many experiments. For example, in the experiments where the authors treated haploids with reversine to suppress the SAC, there was no no-treatment control (Fig. 6A-C).

Response 2-1

We addressed the same point in__ Response 1-6__. In the original manuscript, we separately presented control and experimental conditions in the same experiment series in Fig. 4 and Fig. 6. We rejoined them in Fig. 4 as in the original experimental design. Please refer to __Response 1-6 __for further details.

• In Fig. 6D, when a DMSO control was included, the control fish were from 3 dpf while the reversine-treated fish were from 0.5-3 dpf. This is a big flaw in experimental design, especially considering the authors were looking at mitotic index, which is hugely impacted by developmental time. *

Response 2-2

In this experiment, we treated haploid larvae with either DMSO or reversine from 0.5 to 3 dpf, isolated cells from the larvae at 3 dpf, and subjected them to flow cytometry. Both DMSO- and reversine-treated larval cells were from 3-dpf larvae. Therefore, this experiment does not have the problem noted by the reviewer. To improve the clarity of the description of the experimental design, we rewrote the corresponding part of the figure legend (line 646, page 34).

- Subjective and inadequate data quantification. In the immunostaining experiments to detect caspase-3 and pH3, the authors either did not quantify at all and only showed single micrographs that might or might not be representative (for pH3), or only did very subjective and unconvincing quantification (for caspase-3). Objective measurements of fluorescence intensity could have been done, but the authors instead chose to categorize the staining into arbitrary categories with unclear standards. In example images they showed in the supplementary data, it is not obvious at all why some of the samples were classified as "mild" and others as "*severe" when their staining did not appear to be very different. *

Response 2-3

We apologize that we showed only "zoomed-out" images of the immunostained embryos in the original figures (Fig. 2A, 3E, and 6F), in which the distribution of individual cleaved caspase-3- or pH3-positive cells could not be clearly recognized. We added the enlarged view of identical immunostaining where these cells were clearly visualized in a countable manner (Fig. 2B, 3F, and 6D). Following the reviewer's suggestion, we newly conducted quantification by comparing the density of these cells within the right midbrain in haploids and diploids.

This new quantification demonstrated the haploidy-linked increase in cleaved caspase-3- or pH3-positive cells and a reversine-dependent decrease in pH3-positive cells. We added these new quantifications with statistical analyses to the revised manuscript (Fig. 2C and 6E). Accompanying these revisions, we omitted the categorization of the severeness of apoptosis, which was pointed out to be subjective. We rewrote the corresponding section of the manuscript to explain the new quantitative analyses (line 143, page 7; line 260, page 12).

While we also quantified cleaved caspase-3-positive cells in control and p53MO larvae in the original Fig. 3E, we realized that the staining quality of the inner larval layers of these morphants was relatively poor and could not apply the same standard of quantification as Fig. 2. Though we confirmed a statistically significant reduction in cleaved caspase-3-positive cells upon p53 depletion by quantified limited number of confocal sections (shown in Fig. 3G, please see also Response 1-4 for details), we decided to re-conduct this experiment for improving the staining quality to apply the same criteria of quantification for Fig 3 as Fig. 2 (Experimental plan is provided in Response 1-4).

Please note that we also tried to evaluate the extent of apoptosis and mitotic arrest based on the fluorescence intensity of organ areas. However, background staining outside the dead cell area precluded the precise quantification.

Additionally, the authors claimed that "*clusters of apoptotic cells" were only present in haploids but not diploids or p53 MO haploids, but they did not show any quantification. From the few example images (Fig.S3A), apoptotic clusters can be seen in p53 MO treated fish. Also, in some cases, the clusters were visible only because those fish were mounted in an incorrect orientation. For example, in Fig. S3A, control #2, that fish was visualized from its side, thus exposing areas around its eye that contained such clusters. These areas are not visible in other images where the fish were visualized from the top. *

__Response 2-4 __

We agree that the definition of "apoptotic clusters" was ambiguous in the original manuscript. We also agree that the visuals of the clusters could be affected by sample conditions, making them less reliable criteria for judging the severity of apoptotic upregulation in larvae. Following the reviewer's suggestion, we newly conducted apoptotic cell counting (Response 2-3), which recapitulated more reliably ploidy- or condition-dependent changes in the extent of apoptosis. Therefore, we decided to omit the description of the clusters in the new version of the manuscript.

*- Subpar data quality. Aside from issues with qualification, the IF data was not convincing as staining appeared to be inconsistent and uneven, with potential artefacts. *

Response 2-5

We apologize that the zoomed-out images in the original figures did not appropriately demonstrate the specific visualization of individual apoptotic or mitotic cells. As described in Response 2-3, we added enlarged views of the immunostaining to the revised manuscript, in which these individual cells are clearly distinguished from non-specific background staining (Fig. 2B, 3F, and 6D). Because of the poorer staining of inner layers of control and p53 morphants, we plan to re-conduct immunostaining for Fig. 3 and Fig. S3 (please refer to Response 1-4 for further detail). The current version of immunostaining and quantification in these figures will be replaced in the next revision.

- Unsupported and overstated claims. There were many overstatements. For one, in line 268, the authors claimed that "*the haploidy-linked mitotic stress with SAC activation is a primary constraint for organ growth in haploid larvae", while what they were actually showed was that reversine treatment, which suppresses the SAC, was partially rescued 2 out of the 3 growth defects they assessed, to such a small extent that the difference between haploid and haploid rescue was only Response 2-6

Following the reviewer's comment, we added control MO-injected or DMSO-treated diploid larval data in the corresponding graphs in Fig. 3I and 6G, respectively. We newly estimated the relative extent of the recovery in Results (line 174, page 8; line 268, page 13).

Reflecting the estimation, we rewrote the manuscript to discuss that haploidy-linked cell death or mitotic defects are a partial cause of organ growth retardation but that there could be other unaddressed cellular defects that also contribute to the growth retardation (line 305, page 15). We also discussed the possibility that incomplete resolution of cell death by p53MO or mitotic defects by reversine treatment may have limited their rescue effects on organ growth retardation (line 303, page 15). We also toned down several descriptions in our manuscript (lines 48 and 50, page 2; line 111, page 5; line 271, page 13; line 298, page 15; line 403, page 20) to achieve a more balanced interpretation on the potential contributions of cell death and mitotic defects to the formation of haploid syndrome.

In association with this issue, we also discussed the difficulty of assuming a priori "fully-rescued" haploid larval size in this context. This is because even normally developing haploid larvae in haplodiplontic species tend to be much smaller than their diploid counterparts. We newly cited a few cases of haplodiplontic species where haploids are smaller than or the same in size as diploids (line 307, page 15).

*With so many fundamental flaws, the data seem unreliable and the paper does not meet publishable standards. *

Response 2-7

We express our gratitude to the reviewer for providing important suggestions to improve the quality of analyses, data presentations, and interpretations in this study. We sincerely hope that one-by-one verifications of the points raised by the reviewer have improved the credibility of the paper and made it suitable for publication.

*The low quality of the analysis makes the significance low. *

*Reviewers have expertise in vertebrate embryogenesis and ploidy manipulation. *

Response 2-8

We hope that by addressing and solving the concerns pointed out by the reviewer, we could have clarified the significance of the study.

Associated to Reviewer#3's comments

*There seem to be a discrepancy between the microscopic images from Figure 2A and the quantification of pH3 positive cells using flow cytometry in Figure 4. According to the flow cytometric results the proportion of pH3 positive cells is about 3 times higher in haploid larvae compared to the control. The increase in mitotic cells in the imaging results however seems much more drastic. It would be helpful if the authors explain here. *

Response 3-1

Following comments provided by other reviewers (see also Response 1-2, 1-4, and__ 2-3__), we newly compared the frequency of pH3 positive cells between the immunostained haploid and diploid larvae. In this new analysis, pH3-positive cells were 6.4 times more frequent in haploids than in diploids, which is a more substantial difference than the one estimated based on the flow cytometric analysis.

The apparent discrepancy between the immunostaining and flow cytometric quantification would arise because pH3-positive mitotic cells tended to be more localized on the surface than in the inner region of larvae. This inevitably results in higher pH3-positive cell density in immunostaining, in which only larval surface is analyzed. To discuss this point, we newly conducted pH3 immunostaining in haploid larvae made transparent using RapiClear reagent and showed a vertical section of 3-d reconstituted larval image of pH3 immunostaining in Fig. S4E. We rewrote the manuscript to add our interpretation of this issue (line 652, page 34).

*Mitotic slippage that the authors observe to be increased in the haploid larvae to up to 5% of cells should result in an increase in the number of aneuploid cells. I am wondering why this is not recapitulated in the analyses of the DNA content in Figure S1. *

Response 3-2

A possible interpretation would be that the limited viability of newly formed aneuploid progenies precluded the detection of these populations in flow cytometric analyses. We discussed the possible generation of aneuploid progenies with our interpretation of their absence in the flow cytometric analyses in Discussion (line 293, page 14).

*Discussion: *

*I find the explanation of centrosomal loss due to depletion of centrosomal protein pools in the cytoplasm during drastic cell reduction interesting. I wonder if the reduction in size is not necessarily caused by the reduction in cells, but rather the result of the absence of a second active allele that produces centrosomal proteins? *

Response 3-3

We added the possible interpretation provided by the reviewer to the corresponding part of Discussion, in association with another comment from reviewer #1 (line 348, page 17; see also Response 1-11).

Reviewer #3 (Significance (Required)):

• *

*Overall, I find the study interesting even to a broader audience since diploid development is a fundamental feature of most animals. The authors also manage to discuss their findings on the consequences of haploidy in this bigger context of the restricted diploid development in animals. The study is very well-written even to non-experts. *

Response 3-4

We express our gratitude to the reviewer for providing positive comments on the significance of our findings. We sincerely hope that one-by-one verifications of the points raised by the reviewer further improve the quality of the paper.

I am not an expert of the literature describing previous characterizations of the consequences associated with haploid cell development in animals, which is why I cannot comment on the novelty of their study. Based on my expertise on centromeres and genome organisation I can however assess the results regarding the mitotic defects observed in haploid larvae (see comments).

Response 3-5

We sincerely thank the reviewer for providing constructive suggestions and critiques based on the expertise.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

In this study the authors aim to shed light onto the molecular reasons why most animals are restricted to diploid cell generations. In mammals, haploid intolerance has been previously attributed to defects linked to genomic imprinting, but the molecular defects associated with haploidy in non-mammalian species are unknown. To fill these gaps, the authors in this study investigate defects associated with haploidy in zebrafish larvae. They found that haploid larvae show elevated numbers of apoptotic cells that could be partially rescued by inhibition of p53. The also detected many cells with prolonged mitosis reflected by an increase of cells positive for the mitotic histone modification phospho- histone H3 (pH3) as well as cell division defects specific to the haploid larvae. These defects are likely caused by the loss of centrosomes in haploid larval cells resulting in an increase of monopolar spindle formation. Loss of centrosomes was particularly pronounced in smaller cells and occurred concomitant with a reduction in cell size through continous cell divisions. The authors could rescue the increase of cells with prolonged mitosis by inhibiting the SAC. Both restoration of mitotic length and decreased apoptosis (by p53 inhibition) also improved some organ growth defects observed in haploid larvae.

I only have some minor comments particularly regarding the mitotic defects.

There seem to be a discrepancy between the microscopic images from Figure 2A and the quantification of pH3 positive cells using flow cytometry in Figure 4. According to the flow cytometric results the proportion of pH3 positive cells is about 3 times higher in haploid larvae compared to the control. The increase in mitotic cells in the imaging results however seems much more drastic. It would be helpful if the authors explain here. Mitotic slippage that the authors observe to be increased in the haploid larvae to up to 5% of cells should result in an increase in the number of aneuploid cells. I am wondering why this is not recapitulated in the analyses of the DNA content in Figure S1.

Discussion:

I find the explanation of centrosomal loss due to depletion of centrosomal protein pools in the cytoplasm during drastic cell reduction interesting. I wonder if the reduction in size is not necessarily caused by the reduction in cells, but rather the result of the absence of a second active allele that produces centrosomal proteins?

Significance

Overall, I find the study interesting even to a broader audience since diploid development is a fundamental feature of most animals. The authors also manage to discuss their findings on the consequences of haploidy in this bigger context of the restricted diploid development in animals. The study is very well-written even to non-experts.

I am not an expert of the literature describing previous characterizations of the consequences associated with haploid cell development in animals, which is why I cannot comment on the novelty of their study. Based on my expertise on centromeres and genome organisation I can however assess the results regarding the mitotic defects observed in haploid larvae (see comments).

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

This study examined cell proliferation and death in haploid and diploid zebrafish and attempted to provide insights into cellular mechanisms underlying haploidy-linked defects in non-mammalian vertebrates. While some of the ideas were potentially interesting, the experiments were not rigorous and inadequate data analyses were performed. Major issues include: - Lack of proper controls in many experiments. For example, in the experiments where the authors treated haploids with reversine to suppress the SAC, there was no no-treatment control (Fig. 6A-C). In Fig. 6D, when a DMSO control was included, the control fish were from 3 dpf while the reversine-treated fish were from 0.5-3 dpf. This is a big flaw in experimental design, especially considering the authors were looking at mitotic index, which is hugely impacted by developmental time. - Subjective and inadequate data quantification. In the immunostaining experiments to detect caspase-3 and pH3, the authors either did not quantify at all and only showed single micrographs that might or might not be representative (for pH3), or only did very subjective and unconvincing quantification (for caspase-3). Objective measurements of fluorescence intensity could have been done, but the authors instead chose to categorize the staining into arbitrary categories with unclear standards. In example images they showed in the supplementary data, it is not obvious at all why some of the samples were classified as "mild" and others as "severe" when their staining did not appear to be very different. Additionally, the authors claimed that "clusters of apoptotic cells" were only present in haploids but not diploids or p53 MO haploids, but they did not show any quantification. From the few example images (Fig.S3A), apoptotic clusters can be seen in p53 MO treated fish. Also, in some cases, the clusters were visible only because those fish were mounted in an incorrect orientation. For example, in Fig. S3A, control #2, that fish was visualized from its side, thus exposing areas around its eye that contained such clusters. These areas are not visible in other images where the fish were visualized from the top. - Subpar data quality. Aside from issues with qualification, the IF data was not convincing as staining appeared to be inconsistent and uneven, with potential artefacts. - Unsupported and overstated claims. There were many overstatements. For one, in line 268, the authors claimed that "the haploidy-linked mitotic stress with SAC activation is a primary constraint for organ growth in haploid larvae", while what they were actually showed was that reversine treatment, which suppresses the SAC, was partially rescued 2 out of the 3 growth defects they assessed, to such a small extent that the difference between haploid and haploid rescue was only <20% of that between haploid and diploid. Again, they did not include proper controls so haploid, haploid rescue, and diploid were never in one experiment together - they were in different figures, plotted in drastically different scales - and 20% is only an estimate. With so many fundamental flaws, the data seem unreliable and the paper does not meet publishable standards.

Significance

The low quality of the analysis makes the significance low.

Reviewers have expertise in vertebrate embryogenesis and ploidy manipulation.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Summary:

Yaguchi et al. investigate the causes of the "haploid syndrome" in the zebrafish embryo, the old observation that haploid embryos suffer from severe developmental defects and growth retardation of organs such as the brain and eyes (these defects are not simply a consequence of loss of heterozygosity, as they are rescued by forced diploidization of haploid larvae). Looking at apoptosis and proliferation, the authors show an increase in the number of apoptotic and mitotic cells in haploid larvae. Regarding apoptosis, they show an increase in p53 levels and demonstrate that knockdown of p53 limits apoptosis and leads to some phenotypic improvement. Regarding mitosis, they show an increase in mitotic delays and failures in haploid larvae. Inhibition of the spindle assembly checkpoint can reduce these defects and leads to some improvement in body axis length and eye size. Looking at the cause of the mitotic defects, the authors show that haploid cells often have monopolar spindles and loss of one centrosome, defects that appear to correlate with cell size.

Major comments:

While some experiments could be better quantified and/or statistically analyzed (see below), overall the results are convincing and clearly presented.

• Diploid embryos are used as controls. Gynogenetic diploids seem to be better controls to ensure that the observed phenotypes are not related to loss of heterozygosity. To limit the amount of work, the use of gynogenetic diploids could be restricted to spindle polarity and centrosome number experiments.
• As the authors discuss, it would be necessary to rescue centrosome loss to establish a causal relationship between centrosome loss and haploid viability. I certainly acknowledge that this is difficult (if not impossible), but it currently limits the significance of the results.
• Some experiments are not, or arguably, quantified/statistically analyzed.
  • Figure 2, Active caspase level. Larvae are sorted into three categories, and no statistical test is performed on the obtained contingency table. A Fisher's exact test here, or much better, the active caspase-3 levels should be quantified, instead of sorting larvae into categories.
  • Same comment for 3E-F. Larvae are scored as Scarce, Mild or Severe. Looking at Fig S3A, I see one mild p53MO embryo, but the two others are not that different from 'severe' cases, which would completely change the contingency table. Again, a proper quantification would be better.
  • Figure 4D-E, no stats.
  • Figure 6, Reversine treated haploid should be compared to haploid embryos (on the graphs and statistically). If no specific controls have been quantified for this experiment, data could be reused from previous figures, provided this is stated.
  • Rescue by p53MO and Reversine, it would be nice to also include diploid measurements on the graphs, so that the reader can appreciate the extent of the rescue.

Minor comments:

• Lines 221-223, authors claim that centriole loss and spindle monopolarization commence earlier in the eyes and brain than in skin. I am note sure I see this in Fig. S5. It could as well be that the defect is less pronounced in skin.
• Lines 227-229, authors claim that 'The developmental stage when haploid larvae suffered the gradual aggravation of centrosome loss corresponded to the stage when larval cell size gradually decreased through successive cell divisions'. I did not get that. Doesn't cell size decrease since the first division? Fig 5D shows that cell size decreases all along development.

• Some correlations are used to draw conclusions:

• Line 301-303. "The correlation between centrosome loss and spindle monopolarization indicates that haploid larval cells fail to form bipolar spindle because of the haploidy-linked centrosome loss.". As stated by the authors, this is a correlation only. I agree it points in this direction.

• Line 305-308. "Interestingly, centrosome loss occurred almost exclusively in haploid cells whose size became smaller than a certain border (Fig. 5), indicating that cell size is a key determinant of centrosome number homeostasis in the haploid state." This one is more problematic. There is no causal link established between cell size and centrosome number homeostasis. It could very well be that some unidentified problem induces both a reduction in cell size and the loss of centrioles.

Significance

I have concerns regarding the significance of the reported findings. Haploid zebrafish embryos show numerous developmental defects (some as early as gastrulation, as previously shown by the authors, Menon 2020), and they die by 4 dpf. That they experience massive apoptosis at day 3 does not seem very surprising, and that inhibiting p53 transiently improves the phenotype is not a big surprise. This reminds me of the non-specific effects of morpholino injection, which can be partially rescued by knocking down p53. The observation of mitotic arrest and mitotic defects and the observation that haploid cells often lack a centrosome is interesting. However, I felt that the manuscript suggested that these observations were novel and could explain the haploid syndrome specifically in non-mammalian embryos, when the authors reported the same observations in human haploid cells as well as in mouse haploid embryos (Yaguchi 2018). To me, this manuscript mainly confirms that their previous observation is not mammalian specific, but at least conserved in vertebrates.

While I am no expert at centrosome duplication, I find the observation that haploidy leads to centrosome loss very intriguing, but have the impression that this manuscript falls short of improving our understanding of this phenomenon.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

---

Reply to the reviewers

RESPONSE TO REVIEWS_RC-2024-02383

We thank all the reviewers for their comments and suggestions. Our point-by-point response is shown below, in bold.

—----------------------------------------------------------------------------------------------------------------------------

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

Summary: the work presented by the authors detail how pharmacological inhibition of the rate limiting one carbon metabolic enzyme DHFR by the drug methotrexate increases the lifespan of yeast and worms. Furthermore, placing aged mice on dietary folate and choline restriction potentially enhanced metabolic plasticity but did not significantly increase lifespan with sex specific differences observed.

The findings in this manuscript are very interesting and important to our understanding of the conserved mechanisms that regulate longevity through one carbon metabolism. This is especially significant in light of the current folate intake and supplementation in the adult human population. The manuscript, however, requires major revisions. Please see comments below for details.

Major comments:

1. The overall tone in this manuscript is colloquial and conversational in nature. A third person academic style and tone, while avoiding the use of subjective descriptive terms would improve the quality of this text. Using terms such as "appeared less diverse", "results are remarkable ...strikingly more pronounced", "possibly positive outcomes" , "appear younger...for unknown reasons", "little Uracil", "tended to be higher", "roughly proportional", "slightly higher", "as a rough readout", and many other examples from the text should not be used in a scientific manuscript. The language should be academic, scientific, precise, and non-ambiguous. A thorough revision of the manuscript with substantial changes to the language and tone is necessary prior to publication. RESPONSE: Thank you for your feedback on the manuscript's tone. We revised most of the expressions mentioned by the reviewer. We note, however, that these phrases were used along with numbers and statistics. Hence, there was no lack of specifics, and readers could quickly evaluate the conclusions. We strive for a balance between scientific rigor and readability to maintain accessibility for a diverse audience.

In the results section, we find multiple instances where the results are interpreted and extensively discussed. This should be reserved for the discussion section. The results section should be used to simply report the findings in a detailed manner.

RESPONSE: We appreciate the suggestion on the integration of interpretation within the Results section. Upon review, we have clarified the presentation of our findings, ensuring a more distinct separation from interpretive commentary. Brief explanations remain to aid the reader's comprehension in light of the complex data, aiming to keep the flow and coherence of the manuscript and prevent overextension of the Discussion section (already ~1,300 words long). We welcome specific suggestions for further refinement.

The materials and methods section is severely lacking in details in some areas. For example, no details were provided regarding how the worm lifespans were conducted and previous work of collaborators were referenced instead. Important details such as worm numbers, biological and technical replicates, solid agar vs liquid culture, temperature, use of FUdR, antibiotics, transfer frequency, methods of scoring, etc... are lacking. Other details such as the preparation of the plates (Was MTX incorporated into the agar, seeded with the bacterial lawn, or liquid culture was used), storage conditions, age of the plates when lifespan started, how was the UV killing of the lawn verified etc...

many other methods subsections lack crucial details. Please carefully review the methodology and include sufficient pertinent details.

RESPONSE: The number of worms assayed in each case were shown in each figure, as described in the legend. We now also added all the information requested by the reviewer in the methods section. The text now reads:

“Briefly, the assays were done on solid agar nematode growth media (NGM) plates prepared fresh before each experiment. The bacterial lawn was exposed twice to a UV dose of 120mJ/cm2 using a UVC-515 Ultraviolet Multilinker (Ultra-Lum, Inc.). Streaking these UV-exposed bacteria to fresh LB agar plates (1% w/v tryptone, 0.5% w/v yeast extract, 1% w/v sodium chloride) produced no visible colonies. Methotrexate, or the ATIC inhibitor, was first dissolved in dimethyl sulfoxide (DMSO) and then added to the media used to prepare the plates after autoclaving (the media were kept in a 50°C water bath until the plates were poured). Mock-treated control plates contained only DMSO. At the start of each experiment, a sufficient number of eggs were collected from plates without any drugs and then placed on plates containing the indicated doses of each compound tested. After hatching and progression to the adult stage, animals were transferred to new plates (marked as the start of the lifespan assay) containing the drug tested and fluorodeoxyuridine (FUDR; dissolved in water), added at 50μM to block hatching of new animals. The plates were scored at least every other day until all the worms died. If an animal responded to gentle touch, it was scored as alive, otherwise a death was recorded, and the animal was removed from the plate. Worms were transferred to fresh plates as needed (e.g., if there was evidence of microbial contamination, dryness/cracks on the agar surface, consumption of the bacterial lawn, or hatching of new animals that escaped the FUDR block). The reported lifespans were compiled from several independent experiments done over several months (9-10 months for the methotrexate experiments and 4-5 months for the ATIC inhibitor), each scored by multiple individuals (4-5 persons per experiment). No experiments were excluded from the analysis.”

In the worms, interventions that impact germline proliferation can extend lifespan. Methotrexate is known to impact germline proliferation and can lead to toxic developmental effects and germline arrest. Was fecundity impacted by methotrexate using the dosages found to extend lifespan?

RESPONSE: We did not score fecundity in our experiments.

The authors stated that UV killed bacteria was used in the worm experiments but did not provide the reasoning for it. Virk had concluded that reduced bacterial pathogenicity is responsible for the lifespan extension and not the worm's OCM. How does your work agree with or refute these previous findings?

RESPONSE: The dose of methotrexate used by Virk et al was very high, so it is difficult to directly compare it to our experiment. Nonetheless, we do not think there is any contradiction. We added the following in the text to clarify this point:

“At higher doses (10-100μΜ), methotrexate did not extend lifespan (not shown), in agreement with (Virk et al., 2016), who treated adult animals with a very high dose of methotrexate (220μM). We also note that the bacteria used to feed the worms in our experiments were killed by ultraviolet radiation to exclude any impacts from bacterial folate metabolism, which is known to affect worm lifespan (Virk et al., 2016, 2012).”

The authors state that AICAR (100 uM administration to the worms (no experimental details were given) increases their lifespan and concluded that this is proof that manipulation of 1C metabolism promotes longevity. There are 2 concerns here; first, AMPK activation leads to inhibition of TOR and that has been shown to promote longevity in multiple models. While we agree that a significant crosstalk between TOR and OCM exists, this experiment does not necessarily contribute to the argument that the authors are making. Second, it has been established by multiple groups that inhibition (RNAi and pharmacological) of DHFR1, TYMS1, SAMS1 and possibly other OCM enzymes leads to lifespan extension in worms. These findings provide stronger evidence that OCM regulates organismal longevity.

RESPONSE: We acknowledged prior research on lifespan extension and do not claim our use of the ATIC inhibitor as the first evidence of 1C metabolism's impact on longevity. Rather, our findings complement existing studies from us and several other groups (including the examples mentioned by the reviewer, which we had cited) by introducing novel evidence of lifespan increase through this specific inhibitor in C. elegans. Please also note that we added a detailed description of the experiment in the Methods, as suggested in a previous comment.

In the mouse study, the authors do not provide a rationale on why a folate and choline deficient diet was adopted as opposed to only a folate deficient diet. Additionally, we assume that the diets did not contain antibiotics (succinyl sulfathiazole) to reduce microbiome folate production since it was not mentioned. Were wire bottom cages used to eliminate coprophagy? Were there any significant differences between male and female serum folate levels that could have contributed to the endpoints. Was only a subset of samples assayed for total folate? (fig 2b shows a possible n of 6 per group?). If no antibiotics and no wire bottom cages were used, mice can maintain adequate folate levels from coprophagy without developing signs of anemia. Please discuss these details as it helps clarify the conditions used.

RESPONSE: Excellent points, and we have now added this information (see Material and Methods):

“We note that when designing experiments to assess the consequences of folate limitation, it is common to control both folate and choline intake to ensure that the observed effects are due to the restriction of folate (Beaudin et al., 2011) because the presence of choline can mask the effects of folate deficiency. Choline can be oxidized to betaine, which provides methyl groups for converting homocysteine to methionine, independent of the folate cycle. Choline can also be incorporated into phosphatidylcholine, a major methyl ‘sink’ in the cell, through the Kennedy pathway. Lastly, we did not use any antibiotics to interfere with the microbiome nor wire bottom cages to eliminate coprophagy. Wire bottom cages were used only in the metabolic chamber experiments.”

Were there any significant differences between male and female serum folate levels that could have contributed to the endpoints. Was only a subset of samples assayed for total folate? (fig 2b shows a possible n of 6 per group?).

RESPONSE: ____Regarding folate levels, no significant sex differences were observed. We assayed all the animals we had at 120 weeks of age, the euthanasia endpoint, as shown in Figure 2B. There were fewer females than males in both diets.

There are instances in the results section where statements were made implying that there are differences observed "slightly higher", "negative association" when it is not statistically significant. There can be either statistically significant differences/correlation or not. please be precise in your wording.

RESPONSE: We have revised the Results section to ensure that qualitative descriptions such as "slightly higher" are only used when supported by appropriate statistical evidence. We have listed____ all the relevant numbers in each case after performing thorough and robust statistical analyses. We note, however, that mentioning qualitative descriptors is not always unwarranted, as long as they are factual.

Graying was observed less significantly in the F/C- group according to the authors. However, no quantitative assessment was made, and it is merely observational.

RESPONSE: It is not clear how to quantify graying non-invasively. Hence, we simply took photographs.

Inference to inhibition of mTOR was made, but mTOR protein and phosphorylation levels were not performed. The authors did perform western blotting on ribosomal S6 protein, however no assessment of the downstream mTOR targets P70S6k1 and 4EBP are shown.

RESPONSE: This is a good suggestion.____ We added a new experiment, looking at 4EBP1 phosphorylation (see new Figure S2). The results mirror those looking at S6 phosphorylation.

Can the change in RER in F/C- mice compared to controls be explained by the increased adiposity in these animals?

RESPONSE: We do not know. The relationship between adiposity and respiratory exchange rate can be quite complex. The increased adiposity of male mice limited for folate may lead to higher RER, reflecting perhaps a greater reliance on carbohydrate metabolism. But this is very speculative, especially since these mice are not obese. It is unclear how the improved metabolic plasticity could be associated with adiposity for the females.

How was the microbiome normalized between groups prior to the beginning of the experiment? (fecal slurry gavage, bedding exchange, cohabitation, none of the above?). There is no mention of this crucial step in the materials and methods section. Furthermore, additional details regarding the microbiome analysis are required (analysis pipeline, read depth, denoising, software, data processing, PCA analysis, etc...). it is not sufficient to state that Zymo performed the analysis.

RESPONSE: We now revised the text and added a detailed description of the methods, as follows:

“There was no microbiome normalization between groups prior to the beginning of the experiment. Mouse fecal pellets were gathered by positioning the mice on a paper towel beneath an overturned glass beaker. A minimum of three fecal pellets from each animal were transferred into cryovials using sterile forceps. The samples were preserved at -80°C and shipped to Zymo Research, where they were processed and analyzed with the ZymoBIOMICS® Shotgun Metagenomic Sequencing Service (Zymo Research, Irvine, CA).For DNA extraction, the ZymoBIOMICS®-96 MagBead DNA Kit (Zymo Research, Irvine, CA) was used according to the manufacturer’s instructions. Genomic DNA samples were profiled with shotgun metagenomic sequencing. Sequencing libraries were prepared with Illumina® DNA Library Prep Kit (Illumina, San Diego, CA) with up to 500 ng DNA input following the manufacturer’s protocol using unique dual-index 10 bp barcodes with Nextera® adapters (Illumina, San Diego, CA). All libraries were pooled in equal abundance. The final pool was quantified using qPCR and TapeStation® (Agilent Technologies, Santa Clara, CA). The final library was sequenced on the NovaSeq® (Illumina, San Diego, CA) platform. The ZymoBIOMICS® Microbial Community DNA Standard (Zymo Research, Irvine, CA) was used as a positive control for each library preparation. Negative controls (i.e. blank extraction control, blank library preparation control) were included to assess the level of bioburden carried by the wet-lab process.

Raw sequence reads were trimmed to remove low quality fractions and adapters with Trimmomatic-0.33 (Bolger et al., 2014): quality trimming by sliding window with 6 bp window size and a quality cutoff of 20, and reads with size lower than 70 bp were removed. Antimicrobial resistance and virulence factor gene identification was performed with the DIAMOND sequence aligner (Buchfink et al., 2015). Microbial composition was profiled with Centrifuge (Kim et al., 2016) using bacterial, viral, fungal, mouse, and human genome datasets. Strain-level abundance information was extracted from the Centrifuge outputs and further analyzed to perform alpha- and beta-diversity analyses and biomarker discovery with LEfSe (Segata et al., 2011) with default settings (p > 0.05 and LDA effect size > 2).”

What is an "easily distinguishable gut microbiome" and "appeared less diverse"?

RESPONSE: To clarify these points, __w__e now edited as follows:

“The different sex and diet groups had an easily distinguishable gut microbiome, occupying different areas of principal component analysis graphs (Figure 5A), based on Bray-Curtis β-diversity dissimilarity indices (Knight et al., 2018). The intestinal microbiome of male mice on the F/C- diet was not statistically less diverse (p=0.222, based on the Wilcoxon rank sum test; Figure 5 - Supplement 1).”

---

a two-dimensional plot using two principal components would be more suitable for image 5A and allow for better visualization of the clustering of the groups.

RESPONSE: We tried displaying the data on a multipanel (3 panels per group, 12 total) two-dimensional figure, but the result is more confusing. Since the sample number is small (n=6 animals per group), the 3D graphs are visually adequate and more pleasing. They are also the standard way of representing this kind of data.

Since the authors suggest that the microbiome could be a source of 1C metabolites (including natural folate), it is important to clarify if coprophagy is involved.

RESPONSE: We agree and have added the information as requested.

How are inflammatory cytokines and marker levels linked to reduced anabolism and immune function in non-challenged animals?

RESPONSE: ____We do not make any claims for such links if that is what the reviewer implied. If the intent was more towards speculation, we suspect one could imagine various situations. For instance, nutrients may be more heavily used during inflammation to support immune cell responses instead of central anabolic processes in other tissues, limiting the building blocks available for tissue growth and repair. Since we do not see major changes in inflammatory cytokines, we prefer not to speculate about possible links.

When discussing the epigenetic analysis, the authors state "no changes in the DNA methylation from liver samples.." and "groups appear younger than expected". Please clarify these statements. Additional details are needed regarding the analysis performed and the choice of methylated loci and methods. Please reference the epigenetic clock or model that was used and if was developed for the same strain and sub-strain of mice. Is it using a modified "Hovarth" mouse DNA age epigenetic clock? If so, provide the necessary details and a possible explanation for the discrepancy other than "unknown reasons"

__RESPONSE: ____The assay is based on the "Hovarth" mouse DNA age epigenetic clock, for the strain we used (C57BL/6). We have now added a detailed description, which we received from the company, as follows (see Materials and Methods): __

"Liver samples (~15mg) collected at euthanasia were placed in 0.75mL of 1X DNA/RNA Shield™ solution (Zymo Research, Irvine, CA), shipped to Zymo Research, and processed with DNAge® Service according to their established protocols. Briefly, after DNA extraction, the EZ DNA Methylation-Lightning Kit (Zymo Research, Irvine, CA) following the standard protocol was used for bisulfite conversion. Samples were enriched specifically for the sequencing of >1000 age-associated gene loci using Simplified Whole-panel Amplification Reaction Method (SWARM®), where specific CpGs are sequenced at minimum 1000X coverage. Sequencing was run on an Illumina NovaSeq instrument. Sequences were identified by Illumina base calling software then aligned to the reference genome using Bismark. Methylation levels for each cytosine were calculated by dividing the number of reads reporting a "c" by the number of reads reporting a "C" or "T". The percentage of methylation for these specific sequences were used to assess DNA age according to Zymo Research's proprietary DNAge® predictor which had been established using elastic net regression to determine the DNAge®."

As for a possible explanation for the discrepancy, since all our "groups appear younger than expected," unfortunately, other than "unknown reasons," we have none to offer. Nonetheless, the critical point for this study is that we saw no diet effects, regardless of where the company's assay draws the baseline.

Regarding Uracil misincorporation, the liver contains significant stores of folate as it is the main hub for several critical OCM reactions (Phospholipid methylation is a major one). Earlier studies used antibiotics with or without coprophagy prevention measures to induce a state of folate depletion to induce uracil incorporation in various tissues of rodent models. There is some controversy whether dietary folic acid restriction/methyl donor restriction alone will lead to uracil misincorporation when there is no apparent depletion or anemia. Please discuss your specific experimental procedures and how it agrees or disagrees with the published literature.

__RESPONSE: We have now added the experimental details, as suggested in a previous comment. Since we do not see uracil misincorporation, we prefer not to comment on the published literature for possible links between misincorporation and anemia. __

The section discussing RPS6 needs to be rewritten and it is difficult to understand.

RESPONSE: We revised the text, which now reads:

“____Immunoblot analysis of liver tissue samples gathered at the time of euthanasia revealed variability in the detected values across individual mice. When examining the male mice, we observed that, on average, those fed the F/C- diet had approximately half the amount of phosphorylated RPS6 (P-RPS6) compared to those on the F/C+ diet. However, due to high variability in the measured values, the overall differences in P-RPS6 levels between the two dietary groups did not reach statistical significance (Figure 7 - Supplement 1; p>0.05, based on the Wilcoxon rank sum test).”

Furthermore, as stated previously, considering phosphorylation of mTOR and its downstream targets 4EBP and S6K1 will give a clear indication of proliferative signaling.

RESPONSE:____ As we mentioned above, we have now added the suggested 4EBP experiment (see new Figure S2).

Additionally, these pathways are impacted by feeding status, diurnal cycles, and sex. Were these factors controlled prior to sacrifice? Were the animals sacrificed at the same time? In a fed or unfed state?

RESPONSE: The animals were sacrificed at the same time, with no feeding limitations.

The western blots provided in supplementary files show uneven protein loading across lanes (ponceau stain). No loading control is shown such as B-actin. A separate blot is used for total and phosphorylated proteins as opposed to gently stripping the membrane of the phosphorylated bolt and re-incubating with the antibody for total. While normalizing phosphorylated to total protein levels will eliminate some of the variability in the author's method. The uneven loading may introduce errors in the calculated ratios.

RESPONSE: The uneven loading across mouse samples is inconsequential. We report the ratio of phospho-RPS6 to the total amount of RPS6 ____within____ each mouse sample. These ratios were then compared among the different animals and diet groups. We also note that stripping could introduce other artifacts if it is not uniform across all the blot areas.

While the authors referenced older studies utilizing low dose methotrexate on rodents and provided a composite lifespan based on these findings, why was dietary folate and choline restriction used instead of a low dose methotrexate in mice in the current study? Please provide a rationale for this approach.

__RESPONSE: First, in the context of current folate fortification policies, we reasoned that testing dietary folate limitation late in life would be more informative. Second, three of us (M.P., B.K.K., and M.K.) proposed to the Interventions Testing Program at the National Institutes of Health to test whether low-dose methotrexate extends lifespan in mice. The proposal was accepted, and the study is ongoing (the ITP decided to test methotrexate at 0.2ppm, starting at 14 months of age; _https://www.nia.nih.gov/research/dab/interventions-testing-program-itp/supported-interventions_). __

Minor comments:

1. While the authors make compelling arguments that lower folate intake later in life may promote healthy aging, an important consideration in the human population that a considerable percentage of older individuals may be consuming an excessive amount of folate due the combination of fortification and voluntary supplementation. An alternate hypothesis that could apply to humans and lab models is that the existing levels of exposure to folate/folic acid may be accelerating the aging process and promoting disease in later life. __RESPONSE: Perhaps, but as we describe in the text (2nd paragraph in the introduction): __

“...analyses ‘did not identify specific risks from existing mandatory folic acid fortification’ in the general population (Field and Stover, 2018). This conclusion neither refutes nor contradicts the idea that a moderate decrease in folic acid intake among older adults may improve healthspan. Merely because high folic acid intake does not harm the health of older adults does not negate the possibility that a lower folic acid intake might enhance health.”

The common C57BL/6j is being referred to as the "long lived strain". Is this relative to mice in wild conditions? There are many transgenic C57bl/6 strains that live considerably longer. Please clarify if this is meant to describe the aged mice used in the experimental process.

RESPONSE: ____This was from a comprehensive comparison of many different inbred strains. We apologize for omitting the citation, which we have now added____ (Yuan et al, 2009).

While the authors state early in the manuscript that longevity was not a measured outcome in the mouse study, the manuscript contains statements discussing animal survival in the results and survival curves (figure 2). This gives the impression that the study was planned as a survival analysis initially and since no difference was observed between the experimental groups during the earlier stages, the secondary endpoints of health span analysis were adopted. Either approach does not detract from the significance of the study's findings. Further clarity on the approach would be beneficial to the readers.

RESPONSE: The study was designed, and the Animal Use Protocol was institutionally approved for healthspan, not lifespan. The number of animals we used did not have sufficient power to detect lifespan differences. Note that, at least for males, very few animals had died by 120 weeks, our approved euthanasia endpoint. However, it was important to report that folate limitation did not adversely affect overall survival during the analysis time frame.

For yeast culture conditions, what are the folate sources and content? Is there added folic acid similar to cell culture conditions where supraphysiological concentrations are used in standard mediums (RPMI and DMEM).

RESPONSE: The yeast media we used ____were undefined (YPD, see Materials and Methods). The source of folate in this media is “yeast extract,” which is generally considered to contain very high amounts of folate (it was used decades ago to treat anemia and folate deficiency in pregnant women). Note also that, unlike animals, yeast can synthesize folate.

In the metabolism section, the authors make statements such as "the differences were minimal" , "probably were due..", "minimal effects", "apparent increase", "tended to be", "little uracil" etc.. please refrain from using subjective language and use precise scientific terms.

RESPONSE: Please see our earlier response to this comment.

Figure 2-c, there is a typo, Weeks not months

RESPONSE: Corrected. Thank you!

** Referees cross-commenting**

while we generally agree with the other reviewer's concerns, we find that reviewer 3 rejection of the authors conclusion without considering the evidence presented in the context of what is currently known in the field potentially limiting. Multiple groups have shown that manipulation of OCM enzymes (DHFR, TYMS, SAMS) can extend lifespan in worms. the recent report Antebi's group (Annibal et al. Nature Com, 2021) provides strong evidence that OCM is central to longevity regulation in worms and mice and that folate intake can interact with and modulate organismal longevity. while this manuscript findings are not conclusive, I think it is premature to dismiss it completely. perhaps the alternative is to discuss the limitations of this approach and interpret the results (or the lack of significant differences) in order to help guide future research into this important subject. generalizing rodent results to human is always going to be a limiting factor in this type of work. Mice have significantly higher circulating folate. additionally, DHFR activity (the rate limiting enzyme in folate OCM) in rodents can be up to 100 times higher than its human equivalent. another consideration is that mice, similar to other rodents, engage in coprophagy, thereby recycling and supplementing bacterially produced folate in the absence of antibiotics in the diet. Therefore, mice placed of dietary folate restriction in the absence of antibiotics do not develop signs of anemia or deficiency. Therefore, it could be argued that there is no loss of nutrients in mice in this scenario and that supplementation at the arbitrarily recommended level of synthetic folic acid (2mg/kg day) or higher could impact health and aging. Similarly , in humans excess folate intake has been controversially associated with a number of deleterious health effects. It is important not to dismiss these reports and encourage further research into this subject that impacts a significant percentage of the human population due to the widespread use of supplements.

RESPONSE: We thank the reviewers for their evaluation of the work we presented. We have also added the following in the discussion, expanding the limitations of the study:

“Since mice engage in coprophagy, microbiome contributions to folate metabolism are bound to be substantial in this species. There are also significant differences in folate status between mice and people. For example, people have lower levels (~10-15 ng/mL) of serum folate than mice (Bailey et al., 2015), and the activity of DHFR, an enzyme essential for maintaining tetrahydrofolate pools -the folate form used in 1C reactions, maybe only 2% of that in rodents (Bailey and Ayling, 2009). Hence, mice are likely more refractory to a low folate dietary intake.”

Reviewer #1 (Significance (Required)):

Significance:

A major strength of this study is that the authors show that manipulation of OCM either through pharmacological inhibition or dietary restriction can impact organismal longevity in a conserved manner across species from yeast to worms and mammals. These findings provide compelling evidence that folate intake and metabolism in humans should be rigorously researched as potential regulator of aging. These findings complement and agree with a recent report by Antebi's group (Annibal et al. Nature Com, 2021) highlighting that long-lived worm and mice strains exhibit similar metabolic regulation of one carbon metabolism. In the same report low levels of folate supplementation partially or completely abrogated the lifespan extension in some models. This study provides additional evidence that restricting OCM through drugs or dietary restriction can significantly impact healthspan and lifespan. Additionally, it raises the question whether excessive folate intake in aged adults may have potentially deleterious effects on health and longevity. The limitations of this study can be seen in the overall lack of significant impact of the dietary intervention on the health metrics that were measured in mice. The study does not provide strong evidence that restricting folate and choline intake will produce favorable effects on health. Similarly, no significant impact on mice lifespan was observed based on the partial lifespan analysis. Further clarity is needed regarding the experimental procedures and methods used. The study, nonetheless, is an important step towards investigating the role of folate and OCM in regulating mammalian healthspan and lifespan. Future studies can expand on these findings and investigate whether OCM interventions that are started in early life can produce significant and measurable effects on longevity and health in mammals. The findings here provide a conceptual and incremental advance in our understanding of these complex interactions.

These findings are important to the research communities especially in the areas of longevity, metabolism, and nutrition.

RESPONSE: We appreciate the recognition of our work's significance in furthering understanding of longevity, metabolism, and nutrition. We would also like to stress that this study is not an incremental advance. We believe our study's focus on dietary folate limitation ____in aged mice____ represents a novel and more radical contribution, considering the lack of prior research in this specific context, underscoring the distinctiveness and importance of our findings.

—---------------------------------------------------------------------------------------------------------------

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

Summary: In this manuscript they investigate whether disruption of the folate cycle can slow ageing/improve health in yeast, worms and mice. There are a few experiments in yeast and C. elegans but the rest is a meta analysis of some old data on folate-deprived mice and their own study of mice on a diet with and without folic acid and choline. The find that various interventions of the folate cycle extend lifespan in yeast and worms, that the old study suggest mice live longer without folic acid supplementation and that there is no change to healthspan with mice without folic acid and choline in the diet late in life and that these mice show some positive benefits. Analysis of the microbiome and the transcriptomics suggest small changes to the microbiota and changes in gene expression. Overall the authors conclude that biosynthetic processes have been inhibited without negative effects on healthspan.

Major comments

1. The two worm lifespan experiments in Fig 1 show very different controls despite the methods stating that the conditions were the same. Controls can vary from one experiment to another but the difference is striking. It would be good to have supplementary data about the number of repeats and other data about these experiments. RESPONSE: We also noted the difference. However, we believe our conclusions are valid and robust because we used only experiment-matched controls for each comparison. We now describe in detail how the experiments were done (see revised Materials and Methods). Lastly, the two compounds were tested years apart from different individuals, and the different lifespans of the controls could arise from differences in the media batches, temperature control, etc.

The diet lack folic acid and choline yet the conclusions are only about folate. The choline aspect of the diet needs to be acknowledged as a potential factor.

RESPONSE: As we mentioned above, we have now added this information (see Material and Methods):

“We note that when designing experiments to assess the consequences of folate limitation, it is common to control both folate and choline intake to ensure that the observed effects are due to the restriction of folate (Beaudin et al., 2011) because the presence of choline can mask the effects of folate deficiency. Choline can be oxidized to betaine, which provides methyl groups for converting homocysteine to methionine, independent of the folate cycle. Choline can also be incorporated into phosphatidylcholine, a major methyl ‘sink’ in the cell, through the Kennedy pathway. Lastly, we did not use any antibiotics to interfere with the microbiome nor wire bottom cages to eliminate coprophagy. Wire bottom cages were used only in the metabolic chamber experiments.”

The authors argue that the effects on the mice are not mediated effects on the diet by the microbiome because there is not a statistical effect on diversity. However they do show a clear difference at the metagenomic level that fits with a metabolic difference. It also ignores work in C. elegans showing that inhibition of bacterial folate synthesis increases lifespan, not by decreasing folate supply but because lowered bacterial folate prevents an age-accelerating activity in the bacteria (Virk et al 2016). It has also been shown that a breakdown product of folic acid can be taken up by bacteria and influence ageing (Maynard et al 2018). I do not think the evidence is strong enough to discounted that the changes seen in the mice are not mediated by microbes.

RESPONSE: We do not state that “changes seen in the mice are not mediated by microbes”. On the contrary, we agree with the reviewer that the microbiome likely contributes significantly, and we hope this is conveyed in the text. We also agree with the references the reviewer pointed out, which we cite (see also our response to point#5 of reviewer 1).

Minor comments

1. It had been shown a long time ago that sams-1 mutants in C. elegans extend lifespan. MTX is likely to influence SAMS levels. This point needs to mentioned. RESPONSE: Thank you. We added the reference.

Page - 6 "folate accelerates worm aging". This statement is not correct and is not what Virk et al 2016 suggests.

RESPONSE: We revised it to the following: “____It has been reported that treating worms with high levels of methotrexate (220μΜ) at the adult stage did not extend their lifespan ____(Virk et al., 2016)____”.

Page 7. "at 100μM, a dose similar to the one used in mice with metabolic syndrome (Asby et al., 2015)." It's not valid to compare the concentration of a drug in the media in a C. elegans experiment to a dose given to mice.

RESPONSE: We appreciate the reviewer's point on comparing drug dosages across species. The intention was to provide a reference point for the concentration used rather than suggesting a direct equivalence with outcomes. We recognize the complexities of cross-species dosage comparisons and have amended the text to clarify that the mention of dosage is for contextual purposes only.

** Referees cross-commenting**

I would like to add that it is important to consider whether there are in fact negative effects of folic acid given in later life and this is one of the only studies that addresses this question in a mammalian model, and thus needs to be reported, once the issues raised have been addressed.

__RESPONSE: As we mentioned in a comment from reviewer 1 and describe in the text (2nd paragraph in the introduction): __

“...analyses ‘did not identify specific risks from existing mandatory folic acid fortification’ in the general population (Field and Stover, 2018). This conclusion neither refutes nor contradicts the idea that a moderate decrease in folic acid intake among older adults may improve healthspan. Merely because high folic acid intake does not harm the health of older adults does not negate the possibility that a lower folic acid intake might enhance health.”

Reviewer #2 (Significance (Required)):

The main strength of this manuscript is that it examines the effect of mice given a folate and choline deficient diet late in life and finds mostly positive effects. This finding challenges the dogma that folate

—--------------------------------------------------------------------------------------------------

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

Blank/Polymenis and colleagues explore how reduced folate metabolism impacts aging. While folate supplementation is known to benefit the development and health of young people, little is known about the impact of this substrate at advanced ages. The paper consists of two parts: 1) blocking folate metabolism in yeast and C. elegans while measuring lifespan (reproductive or age of death); 2) measuring a vast array of traits in mice where folate (and choline) is removed from the diet starting at age 1 year. The second approach is most central to the paper's theme, and the authors conclude their 'data raise the exciting possibility that ... reduced folate intake later in life might be beneficial." However, I do accept this conclusion. Instead, the overwhelming fact is that there were no changes in any phenotype due to the absence of F/C in the older animals. Loss of this nutrient is neutral, although perhaps bad for the kidney. In my view, the authors misinterpret their very basic results: loss of dietary folate has no impact on aged mice (one strain, at that). And there is no way to generalize this simple conclusion to humans.

RESPONSE: ____We respectfully disagree with the reviewer's assessment of our study's conclusions and its significance. With the primary focus on evaluating the effects of reduced folate intake in aged mice, we explored a comprehensive range of healthspan markers and molecular analyses. Contrary to the reviewer's assertion, our data demonstrate significant outcomes such as altered body weight and metabolic parameters in mice subjected to folate restriction, along with insights into molecular changes indicative of lower anabolism.

The reviewer's interpretation that folate limitation has no observable impact on aged mice overlooks the nuanced findings presented in our study. While acknowledging the neutral effects observed in some phenotypes, we contend that our results collectively contribute to a deeper understanding of the implications of late-life folate restriction. It is unwarranted to dismiss these findings.

Generalizing findings from model systems to humans is indeed complex, as noted by the reviewer. However, our study, alongside existing literature, provides valuable insights that warrant consideration and further exploration. We stand by the rigor of our methodology, the diversity of data presented, and the significance of our results in enhancing knowledge on the impact of folate metabolism in aging models.

There are other issues throughout the work that need to be addressed but given weakness on its key argument, I will not elaborate these points.

__RESPONSE: Since the reviewer offered no specifics on “other issues,” we cannot respond. We hope, however, that we have addressed them in our response to the other reviewers’ comments. __

Reviewer #3 (Significance (Required)):

Blank/Polymenis and colleagues explore how reduced folate metabolism impacts aging. While folate supplementation is known to benefit the development and health of young people, little is known about the impact of this substrate at advanced ages.

RESPONSE: ____We concur with the reviewer's observation regarding the knowledge gap surrounding the impact of reduced folate metabolism on aging, particularly in advanced stages of life, which ____is why our study significantly contributes to the field. As we mentioned above, not only do we report that some healthspan metrics were improved in folate-limited animals (e.g., body weight, improved metabolic plasticity), but our study also offers for the first time a comprehensive biomarker analysis of folate limitation late in life (e.g., metabolite and mRNAs changes associated with lower anabolism, lower IGF1 levels in females). ____This original contribution enhances our understanding of the complex interplay between folate metabolism and aging.