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

These authors have developed a method to induce MI or MII arrest. While this was previously possible in MI, the advantage of the method presented here is it works for MII, and chemically inducible because it is based on a system that is sensitive to the addition of ABA. Depending on when the ABA is added, they achieve a MI or MII delay. The ABA promotes dimerizing fragments of Mps1 and Spc105 that can't bind their chromosomal sites. The evidence that the MI arrest is weaker than the MII arrest is convincing and consistent with published data and indicating the SAC in MI is less robust than MII or mitosis. The authors use this system to find evidence that the weak MI arrest is associated with PP1 binding to Spc105. This is a nice use of the system.

The remainder of the paper uses the SynSAC system to isolate populations enriched for MI or MII stages and conduct proteomics. This shows a powerful use of the system but more work is needed to validate these results, particularly in normal cells.

Overall the most significant aspect of this paper is the technical achievement, which is validated by the other experiments. They have developed a system and generated some proteomics data that maybe useful to others when analyzing kinetochore composition at each division. Overall, I have only a few minor suggestions.

We appreciate the reviewers’ support of our study.

1) In wild-type - Pds1 levels are high during M1 and A1, but low in MII. Can the authors comment on this? In line 217, what is meant by "slightly attenuated? Can the authors comment on how anaphase occurs in presence of high Pds1? There is even a low but significant level in MII.

The higher levels of Pds1 in meiosis I compared to meiosis II has been observed previously using immunofluorescence and live imaging1–3. Although the reasons are not completely clear, we speculate that there is insufficient time between the two divisions to re-accumulate Pds1 prior to separase re-activation.

We agree “slightly attenuated” was confusing and we have re-worded this sentence to read “Addition ABA at the time of prophase release resulted in Pds1securin stabilisation throughout the time course, consistent with delays in both metaphase I and II”.

We do not believe that either anaphase I or II occur in the presence of high Pds1. Western blotting represents the amount of Pds1 in the population of cells at a given time point. The time between meiosis I and II is very short even when treated with ABA. For example, in Figure 2B, spindle morphology counts show that the anaphase I peak is around 40% at its maxima (105 min) and around 40% of cells are in either metaphase I or metaphase II, and will be Pds1 positive. In contrast, due to the better efficiency of meiosis II, anaphase II hardly occurs at all in these conditions, since anaphase II spindles (and the second nuclear division) are observed at very low frequency (maximum 10%) from 165 minutes onwards. Instead, metaphase II spindles partially or fully breakdown, without undergoing anaphase extension. Taking Pds1 levels from the western blot and the spindle data together leads to the conclusion that at the end of the time-course, these cells are biochemically in metaphase II, but unable to maintain a robust spindle. Spindle collapse is also observed in other situations where meiotic exit fails, and potentially reflects an uncoupling of the cell cycle from the programme governing gamete differentiation3–5. We will explain this point in a revised version while referring to representative images that from evidence for this, as also requested by the reviewer below.

2) The figures with data characterizing the system are mostly graphs showing time course of MI and MII. There is no cytology, which is a little surprising since the stage is determined by spindle morphology. It would help to see sample sizes (ie. In the Figure legends) and also representative images. It would also be nice to see images comparing the same stage in the SynSAC cells versus normal cells. Are there any differences in the morphology of the spindles or chromosomes when in the SynSAC system?

This is an excellent suggestion and will also help clarify the point above. We will provide images of cells at the different stages. For each timepoint, 100 cells were scored. We have already included this information in the figure legends

3) A possible criticism of this system could be that the SAC signal promoting arrest is not coming from the kinetochore. Are there any possible consequences of this? In vertebrate cells, the RZZ complex streams off the kinetochore. Yeast don't have RZZ but this is an example of something that is SAC dependent and happens at the kinetochore. Can the authors discuss possible limitations such as this? Does the inhibition of the APC effect the native kinetochores? This could be good or bad. A bad possibility is that the cell is behaving as if it is in MII, but the kinetochores have made their microtubule attachments and behave as if in anaphase.

In our view, the fact that SynSAC does not come from kinetochores is a major advantage as this allows the study of the kinetochore in an unperturbed state. It is also important to note that the canonical checkpoint components are all still present in the SynSAC strains, and perturbations in kinetochore-microtubule interactions would be expected to mount a kinetochore-driven checkpoint response as normal. Indeed, it would be interesting in future work to understand how disrupting kinetochore-microtubule attachments alters kinetochore composition (presumably checkpoint proteins will be recruited) and phosphorylation but this is beyond the scope of this work. In terms of the state at which we are arresting cells – this is a true metaphase because cohesion has not been lost but kinetochore-microtubule attachments have been established. This is evident from the enrichment of microtubule regulators but not checkpoint proteins in the kinetochore purifications from metaphase I and II. While this state is expected to occur only transiently in yeast, since the establishment of proper kinetochore-microtubule attachments triggers anaphase onset, the ability to capture this properly bioriented state will be extremely informative for future studies. We appreciate the reviewers’ insight in highlighting these interesting discussion points which we will include in a revised version.

Reviewer #1 (Significance (Required)):

These authors have developed a method to induce MI or MII arrest. While this was previously possible in MI, the advantage of the method presented here is it works for MII, and chemically inducible because it is based on a system that is sensitive to the addition of ABA. Depending on when the ABA is added, they achieve a MI or MII delay. The ABA promotes dimerizing fragments of Mps1 and Spc105 that can't bind their chromosomal sites. The evidence that the MI arrest is weaker than the MII arrest is convincing and consistent with published data and indicating the SAC in MI is less robust than MII or mitosis. The authors use this system to find evidence that the weak MI arrest is associated with PP1 binding to Spc105. This is a nice use of the system.

The remainder of the paper uses the SynSAC system to isolate populations enriched for MI or MII stages and conduct proteomics. This shows a powerful use of the system but more work is needed to validate these results, particularly in normal cells.

Overall the most significant aspect of this paper is the technical achievement, which is validated by the other experiments. They have developed a system and generated some proteomics data that maybe useful to others when analyzing kinetochore composition at each division.

We appreciate the reviewer’s enthusiasm for our work.

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

The manuscript submitted by Koch et al. describes a novel approach to collect budding yeast cells in metaphase I or metaphase II by synthetically activating the spinde checkpoint (SAC). The arrest is transient and reversible. This synchronization strategy will be extremely useful for studying meiosis I and meiosis II, and compare the two divisions. The authors characterized this so-named syncSACapproach and could confirm previous observations that the SAC arrest is less efficient in meiosis I than in meiosis II. They found that downregulation of the SAC response through PP1 phosphatase is stronger in meiosis I than in meiosis II. The authors then went on to purify kinetochore-associated proteins from metaphase I and II extracts for proteome and phosphoproteome analysis. Their data will be of significant interest to the cell cycle community (they compared their datasets also to kinetochores purified from cells arrested in prophase I and -with SynSAC in mitosis).

I have only a couple of minor comments:

1) I would add the Suppl Figure 1A to main Figure 1A. What is really exciting here is the arrest in metaphase II, so I don't understand why the authors characterize metaphase I in the main figure, but not metaphase II. But this is only a suggestion.

This is a good suggestion, we will do this in our full revision.

2) Line 197, the authors state: ...SyncSACinduced a more pronounced delay in metaphase II than in metaphase I. However, line 229 and 240 the auhtors talk about a "longer delay in metaphase Thank you for pointing this out, this is indeed a typo and we have corrected it.

3) The authors describe striking differences for both protein abundance and phosphorylation for key kinetochore associated proteins. I found one very interesting protein that seems to be very abundant and phosphorylated in metaphase I but not metaphase II, namely Sgo1. Do the authors think that Sgo1 is not required in metaphase II anymore? (Top hit in suppl Fig 8D).

This is indeed an interesting observation, which we plan to investigate as part of another study in the future. Indeed, data from mouse indicates that shugoshin-dependent cohesin deprotection is already absent in meiosis II in mouse oocytes6, though whether this is also true in yeast is not known. Furthermore, this does not rule out other functions of Sgo1 in meiosis II (for example promoting biorientation). We will include this point in the discussion.

Reviewer #2 (Significance (Required)):

The technique described here will be of great interest to the cell cycle community. Furthermore, the authors provide data sets on purified kinetochores of different meiotic stages and compare them to mitosis. This paper will thus be highly cited, for the technique, and also for the application of the technique.

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

In their manuscript, Koch et al. describe a novel strategy to synchronize cells of the budding yeast Saccharomyces cerevisiae in metaphase I and metaphase II, thereby facilitating comparative analyses between these meiotic stages. This approach, termed SynSAC, adapts a method previously developed in fission yeast and human cells that enables the ectopic induction of a synthetic spindle assembly checkpoint (SAC) arrest by conditionally forcing the heterodimerization of two SAC components upon addition of the plant hormone abscisic acid (ABA). This is a valuable tool, which has the advantage that induces SAC-dependent inhibition of the anaphase promoting complex without perturbing kinetochores. Furthermore, since the same strategy and yeast strain can be also used to induce a metaphase arrest during mitosis, the methodology developed by Koch et al. enables comparative analyses between mitotic and meiotic cell divisions. To validate their strategy, the authors purified kinetochores from meiotic metaphase I and metaphase II, as well as from mitotic metaphase, and compared their protein composition and phosphorylation profiles. The results are presented clearly and in an organized manner.

We are grateful to the reviewer for their support.

Despite the relevance of both the methodology and the comparative analyses, several main issues should be addressed: 1.- In contrast to the strong metaphase arrest induced by ABA addition in mitosis (Supp. Fig. 2), the SynSAC strategy only promotes a delay in metaphase I and metaphase II as cells progress through meiosis. This delay extends the duration of both meiotic stages, but does not markedly increase the percentage of metaphase I or II cells in the population at a given timepoint of the meiotic time course (Fig. 1C). Therefore, although SynSAC broadens the time window for sample collection, it does not substantially improve differential analyses between stages compared with a standard NDT80 prophase block synchronization experiment. Could a higher ABA concentration or repeated hormone addition improve the tightness of the meiotic metaphase arrest?

For many purposes the enrichment and extended time for sample collection is sufficient, as we demonstrate here. However, as pointed out by the reviewer below, the system can be improved by use of the 4A-RASA mutations to provide a stronger arrest (see our response below). We did not experiment with higher ABA concentrations or repeated addition since the very robust arrest achieved with the 4A-RASA mutant deemed this unnecessary.

2.- Unlike the standard SynSAC strategy, introducing mutations that prevent PP1 binding to the SynSAC construct considerably extended the duration of the meiotic metaphase arrests. In particular, mutating PP1 binding sites in both the RVxF (RASA) and the SILK (4A) motifs of the Spc105(1-455)-PYL construct caused a strong metaphase I arrest that persisted until the end of the meiotic time course (Fig. 3A). This stronger and more prolonged 4A-RASA SynSAC arrest would directly address the issue raised above. It is unclear why the authors did not emphasize more this improved system. Indeed, the 4A-RASA SynSAC approach could be presented as the optimal strategy to induce a conditional metaphase arrest in budding yeast meiosis, since it not only adapts but also improves the original methods designed for fission yeast and human cells. Along the same lines, it is surprising that the authors did not exploit the stronger arrest achieved with the 4A-RASA mutant to compare kinetochore composition at meiotic metaphase I and II.

We agree that the 4A-RASA mutant is the best tool to use for the arrest and going forward this will be our approach. We collected the proteomics data and the data on the SynSAC mutant variants concurrently, so we did not know about the improved arrest at the time the proteomics experiment was done. Because very good arrest was already achieved with the unmutated SynSAC construct, we could not justify repeating the proteomics experiment which is a large amount of work using significant resources. However, we will highlight the potential of the 4A-RASA mutant more prominently in our full revision.

3.- The results shown in Supp. Fig. 4C are intriguing and merit further discussion. Mitotic growth in ABA suggest that the RASA mutation silences the SynSAC effect, yet this was not observed for the 4A or the double 4A-RASA mutants. Notably, in contrast to mitosis, the SynSAC 4A-RASA mutation leads to a more pronounced metaphase I meiotic delay (Fig. 3A). It is also noteworthy that the RVAF mutation partially restores mitotic growth in ABA. This observation supports, as previously demonstrated in human cells, that Aurora B-mediated phosphorylation of S77 within the RVSF motif is important to prevent PP1 binding to Spc105 in budding yeast as well.

We agree these are intriguing findings that highlight key differences as to the wiring of the spindle checkpoint in meiosis and mitosis and potential for future studies, however, currently we can only speculate as to the underlying cause. The effect of the RASA mutation in mitosis is unexpected and unexplained. However, the fact that the 4A-RASA mutation causes a stronger delay in meiosis I compared to mitosis can be explained by a greater prominence of PP1 phosphatase in meiosis. Indeed, our data (Figure 4A) show that the PP1 phosphatase Glc7 and its regulatory subunit Fin1 are highly enriched on kinetochores at all meiotic stages compared to mitosis.

We agree that the improved growth of the RVAF mutant is intriguing and points to a role of Aurora B-mediated phosphorylation, though previous work has not supported such a role 7.

We will include a discussion of these important points in a revised version.

4.- To demonstrate the applicability of the SynSAC approach, the authors immunoprecipitated the kinetochore protein Dsn1 from cells arrested at different meiotic or mitotic stages, and compared kinetochore composition using data independent acquisition (DIA) mass spectrometry. Quantification and comparative analyses of total and kinetochore protein levels were conducted in parallel for cells expressing either FLAG-tagged or untagged Dsn1 (Supp. Fig. 7A-B). To better detect potential changes, protein abundances were next scaled to Dsn1 levels in each sample (Supp. Fig. 7C-D). However, it is not clear why the authors did not normalize protein abundance in the immunoprecipitations from tagged samples at each stage to the corresponding untagged control, instead of performing a separate analysis. This would be particularly relevant given the high sensitivity of DIA mass spectrometry, which enabled quantification of thousands of proteins. Furthermore, the authors compared protein abundances in tagged-samples from mitotic metaphase and meiotic prophase, metaphase I and metaphase II (Supp. Fig. 7E-F). If protein amounts in each case were not normalized to the untagged controls, as inferred from the text (lines 333 to 338), the observed differences could simply reflect global changes in protein expression at different stages rather than specific differences in protein association to kinetochores.

While we agree with the reviewer that at first glance, normalising to no tag makes the most sense, in practice there is very low background signal in the no tag sample which means that any random fluctuations have a big impact on the final fold change. This approach therefore introduces artefacts into the data rather than improving normalisation.

To provide reassurance that our kinetochore immunoprecipitations are specific, and that the background (no tag) signal is indeed very low, we will provide a new supplemental figure showing the volcanos comparing kinetochore purifications at each stage with their corresponding no tag control. These volcano plots show very clearly that the major enriched proteins are kinetochore proteins and associated factors, in all cases.

It is also important to note that our experiment looks at relative changes of the same protein over time, which we expect to be relatively small in the whole cell lysate. We previously documented proteins that change in abundance in whole cell lysates throughout meiosis8. In this study, we found that relatively few proteins significantly change in abundance, supporting this view.

Our aim in the current study was to understand how the relative composition of the kinetochore changes and for this, we believe that a direct comparison to Dsn1, a central kinetochore protein which we immunoprecipitated is the most appropriate normalisation.

5.- Despite the large amount of potentially valuable data generated, the manuscript focuses mainly on results that reinforce previously established observations (e.g., premature SAC silencing in meiosis I by PP1, changes in kinetochore composition, etc.). The discussion would benefit from a deeper analysis of novel findings that underscore the broader significance of this study.

We strongly agree with this point and we will re-frame the discussion to focus on the novel findings, as also raised by the other reviewers.

Finally, minor concerns are: 1.- Meiotic progression in SynSAC strains lacking Mad1, Mad2 or Mad3 is severely affected (Fig. 1D and Supp. Fig. 1), making it difficult to assess whether, as the authors state, the metaphase delays depend on the canonical SAC cascade. In addition, as a general note, graphs displaying meiotic time courses could be improved for clarity (e.g., thinner data lines, addition of axis gridlines and external tick marks, etc.).

We will generate the data to include a checkpoint mutant +/- ABA for direct comparison. We will take steps to improve the clarity of presentation of the meiotic timecourse graphs, though our experience is that uncluttered graphs make it easier to compare trends.

2.- Spore viability following SynSAC induction in meiosis was used as an indicator that this experimental approach does not disrupt kinetochore function and chromosome segregation. However, this is an indirect measure. Direct monitoring of genome distribution using GFP-tagged chromosomes would have provided more robust evidence. Notably, the SynSAC mad3Δ mutant shows a slight viability defect, which might reflect chromosome segregation defects that are more pronounced in the absence of a functional SAC.

Spore viability is a much more sensitive way of analysing segregation defects that GFP-labelled chromosomes. This is because GFP labelling allows only a single chromosome to be followed. On the other hand, if any of the 16 chromosomes mis-segregate in a given meiosis this would result in one or more aneuploid spores in the tetrad, which are typically inviable. The fact that spore viability is not significantly different from wild type in this analysis indicates that there are no major chromosome segregation defects in these strains, and we therefore do not plan to do this experiment.

3.- It is surprising that, although SAC activity is proposed to be weaker in metaphase I, the levels of CPC/SAC proteins seem to be higher at this stage of meiosis than in metaphase II or mitotic metaphase (Fig. 4A-B).

We agree, this is surprising and we will point this out in the revised discussion. We speculate that the challenge in biorienting homologs which are held together by chiasmata, rather than back-to-back kinetochores results in a greater requirement for error correction in meiosis I. Interestingly, the data with the RASA mutant also point to increased PP1 activity in meiosis I, and we additionally observed increased levels of PP1 (Glc7 and Fin1) on meiotic kinetochores, consistent with the idea that cycles of error correction and silencing are elevated in meiosis I.

4.- Although a more detailed exploration of kinetochore composition or phosphorylation changes is beyond the scope of the manuscript, some key observations could have been validated experimentally (e.g., enrichment of proteins at kinetochores, phosphorylation events that were identified as specific or enriched at a certain meiotic stage, etc.).

We agree that this is beyond the scope of the current study but will form the start of future projects from our group, and hopefully others.

5.- Several typographical errors should be corrected (e.g., "Knetochores" in Fig. 4 legend, "250uM ABA" in Supp. Fig. 1 legend, etc.)

Thank you for pointing these out, they have been corrected.

Reviewer #3 (Significance (Required)):

Koch et al. describe a novel methodology, SynSAC, to synchronize budding yeast cells in metaphase I or metaphase II during meiosis, as well and in mitotic metaphase, thereby enabling differential analyses among these cell division stages. Their approach builds on prior strategies originally developed in fission yeast and human cells models to induce a synthetic spindle assembly checkpoint (SAC) arrest by conditionally forcing the heterodimerization of two SAC proteins upon addition of abscisic acid (ABA). The results from this manuscript are of special relevance for researchers studying meiosis and using Saccharomyces cerevisiae as a model. Moreover, the differential analysis of the composition and phosphorylation of kinetochores from meiotic metaphase I and metaphase II adds interest for the broader meiosis research community. Finally, regarding my expertise, I am a researcher specialized in the regulation of cell division.

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 their manuscript, Koch et al. describe a novel strategy to synchronize cells of the budding yeast Saccharomyces cerevisiae in metaphase I and metaphase II, thereby facilitating comparative analyses between these meiotic stages. This approach, termed SynSAC, adapts a method previously developed in fission yeast and human cells that enables the ectopic induction of a synthetic spindle assembly checkpoint (SAC) arrest by conditionally forcing the heterodimerization of two SAC components upon addition of the plant hormone abscisic acid (ABA). This is a valuable tool, which has the advantage that induces SAC-dependent inhibition of the anaphase promoting complex without perturbing kinetochores. Furthermore, since the same strategy and yeast strain can be also used to induce a metaphase arrest during mitosis, the methodology developed by Koch et al. enables comparative analyses between mitotic and meiotic cell divisions. To validate their strategy, the authors purified kinetochores from meiotic metaphase I and metaphase II, as well as from mitotic metaphase, and compared their protein composition and phosphorylation profiles. The results are presented clearly and in an organized manner. Despite the relevance of both the methodology and the comparative analyses, several main issues should be addressed:

1.- In contrast to the strong metaphase arrest induced by ABA addition in mitosis (Supp. Fig. 2), the SynSAC strategy only promotes a delay in metaphase I and metaphase II as cells progress through meiosis. This delay extends the duration of both meiotic stages, but does not markedly increase the percentage of metaphase I or II cells in the population at a given timepoint of the meiotic time course (Fig. 1C). Therefore, although SynSAC broadens the time window for sample collection, it does not substantially improve differential analyses between stages compared with a standard NDT80 prophase block synchronization experiment. Could a higher ABA concentration or repeated hormone addition improve the tightness of the meiotic metaphase arrest? 2.- Unlike the standard SynSAC strategy, introducing mutations that prevent PP1 binding to the SynSAC construct considerably extended the duration of the meiotic metaphase arrests. In particular, mutating PP1 binding sites in both the RVxF (RASA) and the SILK (4A) motifs of the Spc105(1-455)-PYL construct caused a strong metaphase I arrest that persisted until the end of the meiotic time course (Fig. 3A). This stronger and more prolonged 4A-RASA SynSAC arrest would directly address the issue raised above. It is unclear why the authors did not emphasize more this improved system. Indeed, the 4A-RASA SynSAC approach could be presented as the optimal strategy to induce a conditional metaphase arrest in budding yeast meiosis, since it not only adapts but also improves the original methods designed for fission yeast and human cells. Along the same lines, it is surprising that the authors did not exploit the stronger arrest achieved with the 4A-RASA mutant to compare kinetochore composition at meiotic metaphase I and II. 3.- The results shown in Supp. Fig. 4C are intriguing and merit further discussion. Mitotic growth in ABA suggest that the RASA mutation silences the SynSAC effect, yet this was not observed for the 4A or the double 4A-RASA mutants. Notably, in contrast to mitosis, the SynSAC 4A-RASA mutation leads to a more pronounced metaphase I meiotic delay (Fig. 3A). It is also noteworthy that the RVAF mutation partially restores mitotic growth in ABA. This observation supports, as previously demonstrated in human cells, that Aurora B-mediated phosphorylation of S77 within the RVSF motif is important to prevent PP1 binding to Spc105 in budding yeast as well. 4.- To demonstrate the applicability of the SynSAC approach, the authors immunoprecipitated the kinetochore protein Dsn1 from cells arrested at different meiotic or mitotic stages, and compared kinetochore composition using data independent acquisition (DIA) mass spectrometry. Quantification and comparative analyses of total and kinetochore protein levels were conducted in parallel for cells expressing either FLAG-tagged or untagged Dsn1 (Supp. Fig. 7A-B). To better detect potential changes, protein abundances were next scaled to Dsn1 levels in each sample (Supp. Fig. 7C-D). However, it is not clear why the authors did not normalize protein abundance in the immunoprecipitations from tagged samples at each stage to the corresponding untagged control, instead of performing a separate analysis. This would be particularly relevant given the high sensitivity of DIA mass spectrometry, which enabled quantification of thousands of proteins. Furthermore, the authors compared protein abundances in tagged-samples from mitotic metaphase and meiotic prophase, metaphase I and metaphase II (Supp. Fig. 7E-F). If protein amounts in each case were not normalized to the untagged controls, as inferred from the text (lines 333 to 338), the observed differences could simply reflect global changes in protein expression at different stages rather than specific differences in protein association to kinetochores. 5.- Despite the large amount of potentially valuable data generated, the manuscript focuses mainly on results that reinforce previously established observations (e.g., premature SAC silencing in meiosis I by PP1, changes in kinetochore composition, etc.). The discussion would benefit from a deeper analysis of novel findings that underscore the broader significance of this study.

Finally, minor concerns are:

1.- Meiotic progression in SynSAC strains lacking Mad1, Mad2 or Mad3 is severely affected (Fig. 1D and Supp. Fig. 1), making it difficult to assess whether, as the authors state, the metaphase delays depend on the canonical SAC cascade. In addition, as a general note, graphs displaying meiotic time courses could be improved for clarity (e.g., thinner data lines, addition of axis gridlines and external tick marks, etc.). 2.- Spore viability following SynSAC induction in meiosis was used as an indicator that this experimental approach does not disrupt kinetochore function and chromosome segregation. However, this is an indirect measure. Direct monitoring of genome distribution using GFP-tagged chromosomes would have provided more robust evidence. Notably, the SynSAC mad3Δ mutant shows a slight viability defect, which might reflect chromosome segregation defects that are more pronounced in the absence of a functional SAC. 3.- It is surprising that, although SAC activity is proposed to be weaker in metaphase I, the levels of CPC/SAC proteins seem to be higher at this stage of meiosis than in metaphase II or mitotic metaphase (Fig. 4A-B). 4.- Although a more detailed exploration of kinetochore composition or phosphorylation changes is beyond the scope of the manuscript, some key observations could have been validated experimentally (e.g., enrichment of proteins at kinetochores, phosphorylation events that were identified as specific or enriched at a certain meiotic stage, etc.). 5.- Several typographical errors should be corrected (e.g., "Knetochores" in Fig. 4 legend, "250uM ABA" in Supp. Fig. 1 legend, etc.)

Significance

Koch et al. describe a novel methodology, SynSAC, to synchronize budding yeast cells in metaphase I or metaphase II during meiosis, as well and in mitotic metaphase, thereby enabling differential analyses among these cell division stages. Their approach builds on prior strategies originally developed in fission yeast and human cells models to induce a synthetic spindle assembly checkpoint (SAC) arrest by conditionally forcing the heterodimerization of two SAC proteins upon addition of abscisic acid (ABA). The results from this manuscript are of special relevance for researchers studying meiosis and using Saccharomyces cerevisiae as a model. Moreover, the differential analysis of the composition and phosphorylation of kinetochores from meiotic metaphase I and metaphase II adds interest for the broader meiosis research community. Finally, regarding my expertise, I am a researcher specialized in the regulation of cell division.

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 manuscript submitted by Koch et al. describes a novel approach to collect budding yeast cells in metaphase I or metaphase II by synthetically activating the spinde checkpoint (SAC). The arrest is transient and reversible. This synchronization strategy will be extremely useful for studying meiosis I and meiosis II, and compare the two divisions. The authors characterized this so-named syncSACapproach and could confirm previous observations that the SAC arrest is less efficient in meiosis I than in meiosis II. They found that downregulation of the SAC response through PP1 phosphatase is stronger in meiosis I than in meiosis II. The authors then went on to purify kinetochore-associated proteins from metaphase I and II extracts for proteome and phosphoproteome analysis. Their data will be of significant interest to the cell cycle community (they compared their datasets also to kinetochores purified from cells arrested in prophase I and -with SynSAC in mitosis).

I have only a couple of minor comments:

1) I would add the Suppl Figure 1A to main Figure 1A. What is really exciting here is the arrest in metaphase II, so I don't understand why the authors characterize metaphase I in the main figure, but not metaphase II. But this is only a suggestion.

2) Line 197, the authors state: ...SyncSACinduced a more pronounced delay in metaphase II than in metaphase I. However, line 229 and 240 the auhtors talk about a "longer delay in metaphase <i compared to metaphase II"... this seems to be a mix-up.

3) The authors describe striking differences for both protein abundance and phosphorylation for key kinetochore associated proteins. I found one very interesting protein that seems to be very abundant and phosphorylated in metaphase I but not metaphase II, namely Sgo1. Do the authors think that Sgo1 is not required in metaphase II anymore? (Top hit in suppl Fig 8D).

Significance

The technique described here will be of great interest to the cell cycle community. Furthermore, the authors provide data sets on purified kinetochores of different meiotic stages and compare them to mitosis. This paper will thus be highly cited, for the technique, and also for the application of the technique.

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

These authors have developed a method to induce MI or MII arrest. While this was previously possible in MI, the advantage of the method presented here is it works for MII, and chemically inducible because it is based on a system that is sensitive to the addition of ABA. Depending on when the ABA is added, they achieve a MI or MII delay. The ABA promotes dimerizing fragments of Mps1 and Spc105 that can't bind their chromosomal sites. The evidence that the MI arrest is weaker than the MII arrest is convincing and consistent with published data and indicating the SAC in MI is less robust than MII or mitosis. The authors use this system to find evidence that the weak MI arrest is associated with PP1 binding to Spc105. This is a nice use of the system.

The remainder of the paper uses the SynSAC system to isolate populations enriched for MI or MII stages and conduct proteomics. This shows a powerful use of the system but more work is needed to validate these results, particularly in normal cells.

Overall the most significant aspect of this paper is the technical achievement, which is validated by the other experiments. They have developed a system and generated some proteomics data that maybe useful to others when analyzing kinetochore composition at each division. Overall, I have only a few minor suggestions.

1) In wild-type - Pds1 levels are high during M1 and A1, but low in MII. Can the authors comment on this? In line 217, what is meant by "slightly attenuated? Can the authors comment on how anaphase occurs in presence of high Pds1? There is even a low but significant level in MII.

2) The figures with data characterizing the system are mostly graphs showing time course of MI and MII. There is no cytology, which is a little surprising since the stage is determined by spindle morphology. It would help to see sample sizes (ie. In the Figure legends) and also representative images. It would also be nice to see images comparing the same stage in the SynSAC cells versus normal cells. Are there any differences in the morphology of the spindles or chromosomes when in the SynSAC system?

3) A possible criticism of this system could be that the SAC signal promoting arrest is not coming from the kinetochore. Are there any possible consequences of this? In vertebrate cells, the RZZ complex streams off the kinetochore. Yeast don't have RZZ but this is an example of something that is SAC dependent and happens at the kinetochore. Can the authors discuss possible limitations such as this? Does the inhibition of the APC effect the native kinetochores? This could be good or bad. A bad possibility is that the cell is behaving as if it is in MII, but the kinetochores have made their microtubule attachments and behave as if in anaphase.

Significance

These authors have developed a method to induce MI or MII arrest. While this was previously possible in MI, the advantage of the method presented here is it works for MII, and chemically inducible because it is based on a system that is sensitive to the addition of ABA. Depending on when the ABA is added, they achieve a MI or MII delay. The ABA promotes dimerizing fragments of Mps1 and Spc105 that can't bind their chromosomal sites. The evidence that the MI arrest is weaker than the MII arrest is convincing and consistent with published data and indicating the SAC in MI is less robust than MII or mitosis. The authors use this system to find evidence that the weak MI arrest is associated with PP1 binding to Spc105. This is a nice use of the system.

The remainder of the paper uses the SynSAC system to isolate populations enriched for MI or MII stages and conduct proteomics. This shows a powerful use of the system but more work is needed to validate these results, particularly in normal cells.

Overall the most significant aspect of this paper is the technical achievement, which is validated by the other experiments. They have developed a system and generated some proteomics data that maybe useful to others when analyzing kinetochore composition at each division.

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Reply to the reviewers

Manuscript number: RC-2025-03160

Corresponding author(s) Padinjat, Raghu

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1. General Statements [optional]

We thank all three reviewers for appreciating the novelty of our analysis of CERT function in a physiological context in vivo. While many studies have been published on the biochemistry and function of CERT in cultured cells, there are limited studies, if any, relating the impact of CRT function at the biochemical level to its function on a physiological process, in our case the electrical response to light.

We also that all reviewers for commenting on the importance of our rescue of dcert mutants with hCERT and the scientific insights raised by this experiment. All reviewers have also noted the importance of strengthening our observation that hCERT, in these cells, is localized at ER-PM MCS rather that the more widely reported localization at the Golgi. We highlight that many excellent studies which have localized CERT at the Golgi are performed in cultured, immortalized, mammalian cells. There are limited studies on the localization of this protein in primary cells, neurons or in polarized cells. With the additional experiments we have proposed in the revision for this aspect of the manuscript, we believe the findings will be of great novelty and widespread interest.

We believe we can address almost all points raised by reviewers thereby strengthening this exciting manuscript.

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.

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

This manuscript dissects the physiological function of ceramide transfer protein (CERT) by studying the phenotype of CERT null Drosophila.

dCERT null animals have a reduced electrical response to light in their photoreceptors, reduced baseline PIP2 accumulation in the cells and delayed re-synthesis of PIP2 and its precursor, PI4P after light stimulation. There are also reduced ER:PM contact sites at the rhabdomere and a corresponding reduction in the localization of PI/PA exchange protein, RDGB at this site. Therefore, the animals seem to have an impaired ability for sustaining phototransduction, which is nonetheless milder than that seen after loss of RDGB, for example. In terms of biochemical function, there is no overall change in ceramides, with some minor increases in specific short chain pools. There is however a large decrease in PE-ceramide species, again selective for a few molecular species. Curiously, decreasing ceramides with a mutant in ceramide synthesis is able to partially rescue both the electrical response and RDGB localization in dCERT flies, implying the increased ceramide species contribute to the phenotype. In addition, a mutation in PE-ceramide synthase largely phenocopies the dCERT null, exhiniting both increases ceramides and decreased PE-ceramide.

In addition, dCERT flies were shown to have reduced localization of some plasma membrane proteins to detergent-resistant membrane fractions, as well as up regulation of the IRE1 and PERK stress-response pathways. Finally, dCERT nulls could be rescued with the human CERT protein, demonstrating conservation of core physiological function between these animals. Surprisingly, CERT is reported to localize to the ER:PM junctions at rhabdomeres, as opposed to the expected ER:Golgi contact sites. Specific areas where the manuscript could be strengthened include:

Figure 2 studies the phototransduction system. Although clear changes in PI4P and PIP2 are seen, it would be interesting to see if changed PA accumulation occur in the dCERT animals, since RDGB localization is disrupted: this is expected to cause PM PA accumulation along with reduced PIP2 synthesis.

It is an important question raised by the reviewer to check PA levels. In the present study we have noticed that localization of RDGB at the base of the rhabdomere in dcert1 is reduced but not completely removed. Consequently, one may consider the situation on dcert1 as a partial loss of function of RDGB and consistent with this, the delay in PI4P and PI(4,5)P2 resynthesis is not as severe as in rdgB9 which is a strong hypomorph (PMID: 26203165).

rdgB9 mutants also show an elevation in PA levels and the reviewer is right that one might expect changes in PA levels too as RDGB is a PI/PA transfer protein. We expect that if measured, there will be a modest elevation in PA levels. However, previous work has shown that elevation of PA levels at the or close to the rhabdomere lead to retinal degeneration Specifically, elevated PA levels by dPLD overexpression disrupts rhabdomere biogenesis and leads to retinal degeneration (PMID: 19349583). Similarly, loss of the lipid transfer protein RDGB leads to photoreceptor degeneration (PMID: 26203165). In this study, we report that retinal degeneration is not a phenotype of dcert1. Thus measurements of PA levels though interesting may not be that informative in the context of the present study. However, if necessary, we can measure PA levels in dcert1.

Lines 228-230 state: "These findings suggest an important contribution for reduced PE - Cer levels in the eye phenotypes of dcert". Does it not also suggest a contribution of the elevated ceramide species, since these are also observed in the CPES animals?

We agree with the reviewer that not only reduced PE-Ceramide but also elevated ceramide levels in GMR>CPESi could contribute to the eye phenotype. This statement will be revised to reflect this conclusion.

Figure 6D is a key finding that human CERT localized to the rhabdomere at ER:PM contact sites, though the reviewer was not convinced by these images. Is the protein truly localized to the contact sites, or simply have a pool of over-expressed protein localized to the surrounding cytoplasm? It also does not rule out localization (and therefore function) at ER:PM contact sites.

Since hCERT completely rescued eye phenotype of dcert1 the localization we observe for hCERT must be at least partly relevant. We will perform additional IHC experiments to

• Co-localize hCERT with an ER-PM MCS marker, e.g RDGB in wild type flies
• Co-localize hCERT with VAP-A that is enriched at the ER-PM MCS. This should help to determine if there are MCS and non-MCS pools of hCERT in these cells. marker, e.g RDGB in wild type flies
• Test if there is a pool of hCERT, in these cells that also localizes (or not) with the Golgi marker Golgin 84. These will be included in the revision to strengthen this important point.

Statistics: There are a large number of t-tests employed that do not correct for multiple comparisons, for example in figures 3B, 3D, 3H, 4C, 6C, S2A, S2B, S3B and S3C.

We will performed multiple comparisons with mentioned data and incorporate in the revised manuscript.

There are two Western blotting sections in the methods.

The first Western blotting methods is for general blots in the paper. The second western blotting section is related to the samples from detergent resistant membrane (DRM) fractions. We will clearly explain this information in the methods section of the manuscript.

Reviewer #1 (Significance (Required)):

Overall, the manuscript is clearly and succinctly written, with the data well presented and mostly convincing. The paper demonstrates clear phenotypes associated with loss of dCERT function, with surprising consequences for the function of a signaling system localized to ER:PM contact sites. To this reviewer, there seem to be three cogent observations of the paper: (i) loss of dCERT leads to accumulation of ceramides and loss of PE-ceramide, which together drive the phenotype. (ii) this ceramide alteration disrupts ER:PM contact sites and thus impairs phototransduction and (iii) rescue by human CERT and its apparent localization to ER:PM contact sites implies a potential novel site of action. Although surprising and novel, the significance of these observations are a little unclear: there is no obvious mechanism by which the elevated ceramide species and decreased PE-ceramide causes the specific failure in phototrasnduction, and the evidence for a novel site of action of CERT at the ER:PM contact sites is not compelling. Therefore, although an interesting and novel set of observations, the manuscript does not reveal a clear mechanistic basis for CERT physiological function.

We thank reviewer for appreciating the quality of our manuscript while also highlighting points through which its impact can be enhanced. To our knowledge this is one of the first studies to tackle the challenging problem of a role for CERT in physiological function. We would like to highlight two points raised:

• We do understand that the localisation of hCERT at ER-PM MCS is unusual compared to the traditional reported localization to ER-Golgi sites. This is important for the overall interpretation of the results in the paper on how dCERT regulates phototransduction. As indicated in response to an earlier comment by the reviewer we will perform additional experiments to strengthen our conclusion of the localization of hCERT.
• With regard to how loss of dCERT affects phototransduction, we feel to likely mechanisms contribute. If the localization of hCERT to ER-PM MCS is verified through additional experiments (see proposal above) then it is important to note that ER-PM MCS in these cells includes the SMC (smooth endoplasmic reticulum) the major site of lipid synthesis. It is possible that loss of dCERT leads to ceramide accumulation in the smooth ER and disruption of ER-PM contacts. That may explain why reducing the levels of ceramide at this site partially rescues the eye phenotype.

The multi-protein INAD-TRP-NORPA complex, central to phototransduction have previously been shown to localise to DRMs in photoreceptors. PE-Ceramides are important contributors to the formation of plasma membrane DRMs and we have presented biochemical evidence that the formation of these DRMs are reduced in the dcert1. This may be a mechanism contributing to reduced phototransduction. This latter mechanism has been proposed as a physiological function of DRMs but we think our data may be the first to show it in a physiological model.

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

Summary Non-vesicular lipid transfer by lipid transfer proteins regulates organelle lipid compositions and functions. CERT transfers ceramide from the ER to Golgi to produce sphingomyelin, although CERT function in animal development and physiology is less clear. Using dcert1 (a protein-null allele), this paper shows a disruption of the sole Drosophila CERT gene causes reduced ERG amplitude in photoreceptors. While the level and localization of phototransduction machinery appears unaffected, the level of PIP2 and the localization of RDGB are perturbed. Collectively, these observations establish a novel link between CERT and phospholipase signaling in phototransduction. To understand the molecular mechanism further, the authors performed lipid chromatography and mass spec to characterize ceramide species in dcert1. This analysis reveals that whereas the total ceramide remains unaffected, most PE-ceramide species are reduced. The authors use lace mutant (serine palmitoyl transferase) and CPES (ceramide phosphoethanolamine synthase) RNAi to distinguish whether it is the accumulation of ceramide in the ER or the reduction of sphingolipid derivates in the Golgi that is the cause for the reduced ERG amplitude. Mutating one copy of lace reduces ceramide level by 50% and partially rescues the ERG defect, suggesting that the accumulation of ceramide in the ER is a cause. CPES RNAi phenocopies the reduced ERG amplitude, suggesting the production of certain sphingolipid is also relevant.

Major comments: 1. By showing the reduced PIP2 level, the decreased SMC sites at the base of rhabdomeres, and the diffused RDGB localization in dcert1, the authors favor the model, in which the disruption of ceramide metabolism affects PIP transport. However, it is unclear if the reduced PIP2 level (i.e., reduced PH-PLCd::GFP staining) is specific to the rhabdomeres. It should be possible to compare PH-PLCd::GFP signals in different plasma membranes between wildtype and dcert1. If PH-PLCd::GFP signal is specifically reduced at the rhabdomeres, this conclusion will be greatly strengthened. In addition, the photoreceptor apical plasma membrane includes rhabdomere and stalk membrane. Is the PH-PLCd::GFP signal at the stalk membrane also affected?

Due to the physical organization of optics in the fly eye, the pseudopupil imaging method used in this study collects the signal for the PIP2 probe (PH-PLCd::GFP) mainly from the apical rhabdomere membrane of photoreceptors in live imaging experimental mode. Therefore, the PIP2 signal from these experiments cannot be used to interpret the level of PIP2 either at the stalk membrane or indeed the basolateral membrane.

The point raised by the reviewer, i.e whether CERT selectively controls PIP2 levels at the rhabdomere membrane or not, is an interesting one. To do this, we will need to fix fly photoreceptors and determine the PH-PLCd::GFP signal using single slice confocal imaging. When combined with a stalk marker such as CRUMBS, it should be possible to address the question of which are the membrane domains at which dCERT controls PIP2 levels. If the sole mechanism of action of dCERT is via disruption of ER-PM MCS then only the apical rhabdomere membrane PIP2 should be affected leaving the stalk membrane and basolateral membrane unaffected.

Thank you very much for raising this specific point.

The analysis of RDGB localization should be done in mosaic dcert1 retinas, which will be more convincing with internal control for each comparison. In addition, the phalloidin staining in Figure 2J shows distinct patterns of adherens junctions, indicating that the wildtype and dcert1 were imaged at different focal planes.

We understand that having mosaics is an alternative an elegant way to perform a a side by side analysis of control and mutant. However this would require significant investment of time and effort, perhaps beyond the scope of this study. If we were to perform a mosaic analysis, this would compromise our ERG analysis since ERG is an extracellular recording We feel that this is beyond the scope of this study and perhaps may not be necessary as such (see below).

In the revision we will present equivalent sections of control and dcert1 taken from the nuclear plane of the photoreceptor. This should resolve the reviewer’s concerns.

The significance of ceramide species levels in dcert1 and GMR>CPESRNAi needs to be explained better. Do certain alterations represent accumulation of ceramides in the ER?

Species level analysis of changes in ceramides reveal that elevations in dcert1 are seen mainly in the short chain ceramides (14 and 16 carbon chains). These most likely represent the short chain ceramides synthesised in the ER and accumulating due to the block in further metabolism to PE-Cer due to depletion in CPES.

Species level analysis of changes in ceramides reveal that in dcert1 there is a ceramide transport related defect leading to elevation, primarily, in the short chain ceramides (14 and 16 carbon chains), and this selective supply defect leads to a reduction in PE-Cer levels, with a maximum change in the ratio of short-chain Cer:PE Cer (Figure 3A-D). Though there is no apparent change in the total ceramide level the species specific elevation in the ceramides disturb the fine -balance between the short-chain ceramides and the long and very-long chain ceramides. As the function of long and very-long chain ceramides are implicated in dendrite development and neuronal morphology (doi: 10.1371/journal.pgen.1011880), therefore this alteration in the fine balance between different ceramide species probably impacts the integrity and fluidity of the membrane environment. On the other hand it leads to a possibility of a defined function of the short-chain ceramides in electrical responses to light signalling in the eye, especially with respect to the PE-ceramides that are reduced by around 50%.

In contrast the GMR>CPESRNAi leads to more of a substrate accumulation showing ceramide increase (14, 16, 18, 20 carbon chains) and decrease in PE-Cer levels (Figure 4D, E). In this case Cer accumulation is due to the block in further metabolism to PE-Cer arising from depletion in CPES.

We will include this in the discussion of a revised version.

The suppression by lace is interpreted as evidence that the reduced ERG amplitude in dcert1 is caused by ceramide accumulation in the ER. This interpretation seems preliminary as lace may interact with dcert genetically by other mechanisms.

The dcert1 mutant exhibits increased levels of short-chain ceramides (Fig 3B), whereas the lace heterozygous mutant (laceK05305/+) displays reduced short-chain ceramide levels (Supp Fig 2B). In the laceK05305/+; dcert1 double mutant, ceramide levels are lower than those observed in the dcert1 mutant alone (Supp Fig 2B), indicating a partial genetic rescue of the elevated ceramide phenotype.

Furthermore, through multiple independent genetic manipulations that modulate ceramide metabolism (alterations of dcert, cpes and lace), we consistently observe that increased ceramide levels correlate with a reduction in ERG amplitude, suggesting that ceramide accumulation negatively impacts photoreceptor function. Taken together, these observations indicate that the reduction in ceramide levels in the laceK05305/+; dcert1 double mutant likely contributes to the suppression of the ERG defect observed in the dcert1 mutant.

The authors show that ERG amplitude is reduced in GMR>CPESRNAi. While this phenocopying is consistent with the reduced ERG amplitude in dcert1 being caused by reduced production of PE-ceramide, GMR>CPESRNAi also shows an increase in total ceramide level. Could this support the hypothesis that reduced ERG amplitude is caused by an accumulation of ceramide elsewhere? In addition, is the ERG amplitude reduction in GMR>CPESRNAi sensitive to lace?

We agree that in addition to reduced PE-Ceramide, the elevated ceramide levels in GMR>CPESi could contribute to the eye phenotype. We will introduce lace heterozygous mutant in the GMR>CPESi background to test the contribution of elevated ceramide levels in the *GMR>CPESi * background and incorporate the data in the revision. Thank you for this suggestion.

Along the same line, while the total ceramide level is significantly reduced in lace heterozygotes, is the PE-ceramide level also reduced? If yes, wouldn't this be contradictory to PE-ceramide production being important for ERG amplitude?

Mass spec measurements show that levels of PE-Cer were not reduced in lacek05305/+ compared to wild type. This data will be included in the revised manuscript. However, the ERG amplitude of these flies and also in those with lace depletion using two independent RNAi lines were not reduced.

What is the explanation and significance for the age-dependent deterioration of ERG amplitude in dcert1? Likewise, the significance of no retinal degeneration is not clearly presented.

There could be multiple reasons for the age dependent deterioration of the ERG amplitude, in the absence of retinal degeneration. Drosophila phototransduction cascade depends heavily on ATP production. The age dependent reduction in ATP synthesis could lead to deterioration in the ERG amplitude. These may include instability of the DRMs due to reduced PE-Cer, lower ATP levels due to mitochondrial dysfunction, an perhaps others. A previous study has shown that ATP production is highly reduced along with oxidative stress and metabolic dysfunction in dcert1 flies aged to 10 days and beyond (PMID: 17592126). The same study has also found no neuronal degeneration in dcert1 that phenocopies absence of photoreceptor degeneration in the present study. We will attempt a few experiments to rule in or rule out the these and revise the discussion accordingly.

The rescue of dcert1 phenotype by the expression of human CERT is a nice result. In addition to demonstrating a functional conservation, it allows a determination of CERT protein localization. However, the quality of images in Figure 6D should be improved. The phalloidin staining was rather poor, and the CNX99A in the lower panel was over-exposed, generating bleed-through signals at the rhabdomeres. In addition, the localization of hCERT should be explored further. For instance, does hCERT colocalize with RDGB? Is the hCERT localization altered in lace or GMR>CPESRNAi background?

As indicated in response to reviewer 1:

We will perform additional IHC experiments to

• Co-localize hCERT with an ER-PM MCS marker, e.g RDGB in wild type flies
• Co-localize hCERT with VAP-A that is enriched at the ER-PM MCS. This should help to determine if there are MCS and non-MCS pools of hCERT in these cells. marker, e.g RDGB in wild type flies
• Test if there is a pool of hCERT, in these cells that also localizes (or not) with the Golgi marker Golgin 84. These will be included in the revision to strengthen this important point.

We will also attempt to perform hCERT localization in lace or GMR>CPESRNAi background

Minor comments: 1. In Line 128, Df(732) should be Df(3L)BSC732.

Changes will be incorporated in the main manuscript.

GMR-SMSrRNAi shows an increase in ERG peak amplitude. Is there an explanation for this?

GMR-SMSrRNAi did show slight increase in ERG peak amplitude but was not statistically significant.

Reviewer #2 (Significance (Required)):

Significance As CERT mutations are implicated in human learning disability, a better understanding of CERT function in neuronal cells is certainly of interest. While the link between ceramide transport and phospholipase signaling is novel and interesting, this paper does not clearly explain the mechanism. In addition, as the ERG were measured long after the retinal cells were deficient in CERT or CPES, it is difficult to assess whether the observed phenotype is a primary defect. Furthermore, the quality of some images needs to be improved. Thus, I feel the manuscript in its current form is too preliminary.

We thank reviewer for highlighting the importance and significance of our work in the light of recent studies of CERT function in ID. As with all genetic studies it is difficult to completely disentangle the role of a gene during development from a role only in the adult. However, we will attempt to perhaps use the GAL80ts system to uncouple these two potential components of CERT function in photoreceptors. The goal will be to determine if CERT has a specific role only in adult photoreceptors or if this is coupled to a developmental role. Since ID is as a neurodevelopmental disorder, a developmental role for CERT would be equally interesting.

As previously indicated images will be improved bearing in mind the reviewer comments.

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

Summary: Lipid transfer proteins (LTPs) shuttle lipids between organelle membranes at membrane contact sites (MCSs). While extensive biochemical and cell culture studies have elucidated many aspects of LTP function, their in vivo physiological roles are only beginning to be understood. In this manuscript, the authors investigate the physiological role of the ceramide transfer protein (CERT) in Drosophila adult photoreceptors-a model previously employed by this group to study LTP function at ER-PM contact sites under physiological conditions. Using a combination of genetic, biochemical, and physiological approaches, they analyze a protein-null mutant of dcert. They show that loss of dcert causes a reduction in electrical response to light with progressive decrease in electroretinogram (ERG) amplitude with age but no retinal degeneration. Lipidomic analysis shows that while the total levels of ceramides are not changed in dcert mutants, they do observe significant change in certain species of ceramides and depletion of downstream metabolite phosphoethanolamine ceramide (PE-Cer). Using fluorescent biosensors, the authors demonstrate reduced PIP2 levels at the plasma membrane, unchanged basal PI4P levels and slower resynthesis kinetics of both lipids following depletion. Electron microscopy and immunolabeling further reveal a reduced density of ER-PM MCSs and mislocalization of the MCS-resident lipid transfer protein RDGB. Genetic interaction studies with lace and RNAi-mediated knockdown of CPES support the conclusion that both ER ceramide accumulation and PM PE-Cer depletion contribute to the observed defects in dcert mutants. In addition, detergent-resistant membrane fractionation indicates altered plasma membrane organization in the absence of dcert. The study also reports upregulation of unfolded protein response transcripts, including IRE1 and PERK, suggesting increased ER stress. Finally, expression of human CERT rescues the reduced electrical response, demonstrating functional conservation across species. Overall the manuscript is well written that builds on established work and experiments are technically rigorous. The results are clearly presented and provide valuable insights into the physiological role of CERT.

Major comments: 1.The reduced ERG amplitude appears to be the central phenotype associated with the loss of dcert, and most of the experiments in this manuscript effectively build a mechanistic framework to explain this observation. However, the experiments addressing detergent-resistant membrane domains (DRMs) and the unfolded protein response (UPR) seem somewhat disconnected from the main focus of the study. The DRM and UPR data feel peripheral and could benefit from few experiments for functional linkage to the ERG defect or should be moved to supplementary.

We agree with the reviewer that further experiments are needed to link the DRM data to the ERG defects. That would need specific biochemical alteration at the PM to modulate PE-Cer species and their effect on scaffolding proteins required for phototransduction (that is beyond the scope of the present study). We will consider moving these to the supplementary section as suggested by the reviewer.

2.The changes in ceramide species and reduction in PE-Cer are key findings of the study. These results should be further validated by performing a genetic rescue using the BAC or hCERT fly line to confirm that the lipidomic changes are specifically due to loss of CERT function.

Thank you for this comment. We will include this in the revised manuscript.

3.Figure 2B-C and 2E-F: Representative images corresponding to the quantified data should be included to illustrate the changes in PIP2 and PI4P reporters. Given that the fluorescence intensity of the PIP2 reporter at the PM is reduced in the dcert mutant relative to control, the authors should also verify that the reporter is expressed at comparable levels across genotypes.

• As mentioned by the reviewer we will include representative images alongside our quantified data both of the basal ones and that of the kinetic study.

• Western blot of reporters (PH-PLCd::GFP and P4M::GFP) across genotypes will be added to the revised manuscript. 4.Figure 2J-K: The partial mislocalization of RDGB represents an important observation that could mechanistically explain the reduced resynthesis of PI4P and PIP2 and consequently, the decreased ERG amplitude in dcert mutants. However, this result requires further validation. First, the authors should confirm whether this mislocalization is specific to RDGB by performing co-staining with another ER-PM MCS marker, such as VAP-A, to assess whether overall MCS organization is disrupted. Second, the quantification of RDGB enrichment at ER-PM MCSs should be refined. From the representative images, RDGB appears redistributed toward the photoreceptor cell body, but the presented quantification does not clearly reflect this shift. The authors should therefore include an analysis comparing RDGB levels in the cell body versus the submicrovillar region across genotypes. This analysis should be repeated for similar experiments across the study. Additionally, the total RDGB protein level should be quantified and reported. Finally, since RDGB mislocalization could directly contribute to the decreased ERG amplitude, it would be valuable to test whether overexpression of RDGB in dcert mutants can rescue the ERG phenotype.

• In our ultrastructural studies (Fig. 2H, 2I and Sup. Fig. 1A, 1B) we did see reduction in PM-SMC MCS that was corroborated with RDGB staining.

• Comparative ratio analysis of RDGB localisation at ER-PM MCS vs cell body will be included in the manuscript for all RDGB staining.
• We have done western analysis for total RDGB protein level in ROR and dcert1. This data will be included in the revised manuscript.
• This is a very interesting suggestion and we will test if RDGB overexpression can rescue ERG phenotype in dcert1.

5.Figure 3F and I-J: Inclusion of appropriate WT and laceK05205/+ controls is necessary to allow proper interpretation of the results. These controls would strengthen the conclusions regarding the functional relationship between dcert and lace.

Changes will be incorporated as per the suggestion.

6.Figure 5C: The representative images shown here appear to contradict the findings described in Figure 2A. In Figure 5C, Rhodopsin 1 levels seem markedly reduced in the dcert mutants, whereas the text states that Rh1 levels are comparable between control and mutant photoreceptors. The authors should replace or reverify the representative images to ensure that they accurately reflect the conclusions presented in the text.

We will reverify the representative images and changes will be accordingly incorporated.

7.Figure 6D: The reported localization of hCERT to ER-PM MCSs is a key and potentially insightful observation, as it suggests the subcellular site of dcert activity in photoreceptors. However, the representative images provided are not sufficiently conclusive to support this claim. The authors should validate hCERT localization by co-staining with established markers like RDGB for ER-PM CNX99A for the ER and a Golgi marker since mammalian CERT is classically localized to ER-Golgi interfaces. Optionally, the authors could also quantify the relative distribution of hCERT among these compartments to provide a clearer assessment of its subcellular localization.

As indicated in response to reviewer 1:

We will perform additional IHC experiments to

• Co-localize hCERT with an ER-PM MCS marker, e.g RDGB in wild type flies
• Co-localize hCERT with VAP-A that is enriched at the ER-PM MCS. This should help to determine if there are MCS and non-MCS pools of hCERT in these cells. marker, e.g RDGB in wild type flies
• Test if there is a pool of hCERT, in these cells that also localizes (or not) with the Golgi marker Golgin 84. These will be included in the revision to strengthen this important point.

Minor comments: 1.In the first paragraph of introduction, authors should consider citing few of the key MCS literature.

Additional literature will be included as per the suggestion.

2.Line 132: data not shown is not acceptable. Authors should consider presenting the findings in the supplemental figure.

Data will be added in supplement as per the suggestion.

3.The authors should include a comprehensive table or Excel sheet summarizing all statistical analyses. This should include the sample size, type of statistical test used and exact p-values. Providing this information will improve the transparency, reproducibility and overall rigor of the study.

We will provide all the statistical analyses in mentioned format as per the suggestion.

4.The materials and methods section can be reorganized to include citation for flystocks which do not have stock number or RRIDs if the stocks were previously described but are not available from public repositories. They should expand on the details of various quantification methods used in the study. Finally including a section of Statistical analyses would further enhance transparency and reproducibility

• Stock details will be added wherever missing as per the suggestion.
• Statistical analyses section will be included in the material and methods. **Referee cross-commenting**

1.I concur with Reviewer 1 regarding the need for more detailed reporting of statistical analyses.

We will perform multiple comparisons with mentioned data and incorporate in the revised manuscript.

2.I also agree with Reviewer 3 that the discussion should be expanded to address the age-dependent deterioration of ERG amplitude observed in the dcert mutants. This progressive decline could provide valuable insight into the long-term requirement of CERT function and signaling capacity at the photoreceptor membrane.

Expanded discussion on the age dependent ERG amplitude decline will be incorporated in the discussion as per the suggestion.

Reviewer #3 (Significance (Required)):

This study explores the physiological function of CERT, a LTP localized at MCSs in Drosophila photoreceptors and uncovers a novel role in regulating plasma membrane PE-Cer levels and GPCR-mediated signaling. These findings significantly advances our understanding of how CERT-mediated lipid transport regulates G-protein coupled phospholipase C signaling in vivo. This work also highlights Drosophila photoreceptors as a powerful system to analyze the physiological significance of lipid-dependent signaling processes. This work will be of interest to researchers in neuronal cell biology, membrane dynamics and lipid signaling community. This review is based on my expertise in neuronal cell biology.

We thank the reviewer for appreciating the significance of our work from a neuroscience perspective.

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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.

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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.

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We can address all reviewer points in the revision. However, we will not be able to perform a mosaic analysis of the impact of dcert1 mutant in the retina. We feel this is beyond the scope of this revision. In our response, we have highlighted how controls included in the revision offset the need for a mosaic analysis at this stage.

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Referee #3

Evidence, reproducibility and clarity

Summary:

Lipid transfer proteins (LTPs) shuttle lipids between organelle membranes at membrane contact sites (MCSs). While extensive biochemical and cell culture studies have elucidated many aspects of LTP function, their in vivo physiological roles are only beginning to be understood. In this manuscript, the authors investigate the physiological role of the ceramide transfer protein (CERT) in Drosophila adult photoreceptors-a model previously employed by this group to study LTP function at ER-PM contact sites under physiological conditions. Using a combination of genetic, biochemical, and physiological approaches, they analyze a protein-null mutant of dcert. They show that loss of dcert causes a reduction in electrical response to light with progressive decrease in electroretinogram (ERG) amplitude with age but no retinal degeneration. Lipidomic analysis shows that while the total levels of ceramides are not changed in dcert mutants, they do observe significant change in certain species of ceramides and depletion of downstream metabolite phosphoethanolamine ceramide (PE-Cer). Using fluorescent biosensors, the authors demonstrate reduced PIP2 levels at the plasma membrane, unchanged basal PI4P levels and slower resynthesis kinetics of both lipids following depletion. Electron microscopy and immunolabeling further reveal a reduced density of ER-PM MCSs and mislocalization of the MCS-resident lipid transfer protein RDGB. Genetic interaction studies with lace and RNAi-mediated knockdown of CPES support the conclusion that both ER ceramide accumulation and PM PE-Cer depletion contribute to the observed defects in dcert mutants. In addition, detergent-resistant membrane fractionation indicates altered plasma membrane organization in the absence of dcert. The study also reports upregulation of unfolded protein response transcripts, including IRE1 and PERK, suggesting increased ER stress. Finally, expression of human CERT rescues the reduced electrical response, demonstrating functional conservation across species.Overall the manuscript is well written that builds on established work and experiments are technically rigorous. The results are clearly presented and provide valuable insights into the physiological role of CERT.

Major comments:

1.The reduced ERG amplitude appears to be the central phenotype associated with the loss of dcert, and most of the experiments in this manuscript effectively build a mechanistic framework to explain this observation. However, the experiments addressing detergent-resistant membrane domains (DRMs) and the unfolded protein response (UPR) seem somewhat disconnected from the main focus of the study. The DRM and UPR data feel peripheral and could benefit from few experiments for functional linkage to the ERG defect or should be moved to supplementary. 2.The changes in ceramide species and reduction in PE-Cer are key findings of the study. These results should be further validated by performing a genetic rescue using the BAC or hCERT fly line to confirm that the lipidomic changes are specifically due to loss of CERT function. 3.Figure 2B-C and 2E-F: Representative images corresponding to the quantified data should be included to illustrate the changes in PIP2 and PI4P reporters. Given that the fluorescence intensity of the PIP2 reporter at the PM is reduced in the dcert mutant relative to control, the authors should also verify that the reporter is expressed at comparable levels across genotypes. 4.Figure 2J-K: The partial mislocalization of RDGB represents an important observation that could mechanistically explain the reduced resynthesis of PI4P and PIP2 and consequently, the decreased ERG amplitude in dcert mutants. However, this result requires further validation. First, the authors should confirm whether this mislocalization is specific to RDGB by performing co-staining with another ER-PM MCS marker, such as VAP-A, to assess whether overall MCS organization is disrupted. Second, the quantification of RDGB enrichment at ER-PM MCSs should be refined. From the representative images, RDGB appears redistributed toward the photoreceptor cell body, but the presented quantification does not clearly reflect this shift. The authors should therefore include an analysis comparing RDGB levels in the cell body versus the submicrovillar region across genotypes. This analysis should be repeated for similar experiments across the study. Additionally, the total RDGB protein level should be quantified and reported. Finally, since RDGB mislocalization could directly contribute to the decreased ERG amplitude, it would be valuable to test whether overexpression of RDGB in dcert mutants can rescue the ERG phenotype. 5.Figure 3F and I-J: Inclusion of appropriate WT and laceK05205/+ controls is necessary to allow proper interpretation of the results. These controls would strengthen the conclusions regarding the functional relationship between dcert and lace. 6.Figure 5C: The representative images shown here appear to contradict the findings described in Figure 2A. In Figure 5C, Rhodopsin 1 levels seem markedly reduced in the dcert mutants, whereas the text states that Rh1 levels are comparable between control and mutant photoreceptors. The authors should replace or reverify the representative images to ensure that they accurately reflect the conclusions presented in the text. 7.Figure 6D: The reported localization of hCERT to ER-PM MCSs is a key and potentially insightful observation, as it suggests the subcellular site of dcert activity in photoreceptors. However, the representative images provided are not sufficiently conclusive to support this claim. The authors should validate hCERT localization by co-staining with established markers like RDGB for ER-PM CNX99A for the ER and a Golgi marker since mammalian CERT is classically localized to ER-Golgi interfaces. Optionally, the authors could also quantify the relative distribution of hCERT among these compartments to provide a clearer assessment of its subcellular localization.

Minor comments:

1.In the first paragraph of introduction, authors should consider citing few of the key MCS literature. 2.Line 132: data not shown is not acceptable. Authors should consider presenting the findings in the supplemental figure. 3.The authors should include a comprehensive table or Excel sheet summarizing all statistical analyses. This should include the sample size, type of statistical test used and exact p-values. Providing this information will improve the transparency, reproducibility and overall rigor of the study. 4.The materials and methods section can be reorganized to include citation for flystocks which do not have stock number or RRIDs if the stocks were previously described but are not available from public repositories. They should expand on the details of various quantification methods used in the study. Finally including a section of Statistical analyses would further enhance transparency and reproducibility

Referee cross-commenting

1.I concur with Reviewer 1 regarding the need for more detailed reporting of statistical analyses. 2.I also agree with Reviewer 3 that the discussion should be expanded to address the age-dependent deterioration of ERG amplitude observed in the dcert mutants. This progressive decline could provide valuable insight into the long-term requirement of CERT function and signaling capacity at the photoreceptor membrane.

Significance

This study explores the physiological function of CERT, a LTP localized at MCSs in Drosophila photoreceptors and uncovers a novel role in regulating plasma membrane PE-Cer levels and GPCR-mediated signaling. These findings significantly advances our understanding of how CERT-mediated lipid transport regulates G-protein coupled phospholipase C signaling in vivo. This work also highlights Drosophila photoreceptors as a powerful system to analyze the physiological significance of lipid-dependent signaling processes. This work will be of interest to researchers in neuronal cell biology, membrane dynamics and lipid signaling community. This review is based on my expertise in neuronal cell biology.

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Referee #2

Evidence, reproducibility and clarity

Summary

Non-vesicular lipid transfer by lipid transfer proteins regulates organelle lipid compositions and functions. CERT transfers ceramide from the ER to Golgi to produce sphingomyelin, although CERT function in animal development and physiology is less clear. Using dcert1 (a protein-null allele), this paper shows a disruption of the sole Drosophila CERT gene causes reduced ERG amplitude in photoreceptors. While the level and localization of phototransduction machinery appears unaffected, the level of PIP2 and the localization of RDGB are perturbed. Collectively, these observations establish a novel link between CERT and phospholipase signaling in phototransduction. To understand the molecular mechanism further, the authors performed lipid chromatography and mass spec to characterize ceramide species in dcert1. This analysis reveals that whereas the total ceramide remains unaffected, most PE-ceramide species are reduced. The authors use lace mutant (serine palmitoyl transferase) and CPES (ceramide phosphoethanolamine synthase) RNAi to distinguish whether it is the accumulation of ceramide in the ER or the reduction of sphingolipid derivates in the Golgi that is the cause for the reduced ERG amplitude. Mutating one copy of lace reduces ceramide level by 50% and partially rescues the ERG defect, suggesting that the accumulation of ceramide in the ER is a cause. CPES RNAi phenocopies the reduced ERG amplitude, suggesting the production of certain sphingolipid is also relevant.

Major comments:

1. By showing the reduced PIP2 level, the decreased SMC sites at the base of rhabdomeres, and the diffused RDGB localization in dcert1, the authors favor the model, in which the disruption of ceramide metabolism affects PIP transport. However, it is unclear if the reduced PIP2 level (i.e., reduced PH-PLC::GFP staining) is specific to the rhabdomeres. It should be possible to compare PH-PLC::GFP signals in different plasma membranes between wildtype and dcert1. If PH-PLC::GFP signal is specifically reduced at the rhabdomeres, this conclusion will be greatly strengthened. In addition, the photoreceptor apical plasma membrane includes rhabdomere and stalk membrane. Is the PH-PLC::GFP signal at the stalk membrane also affected?
2. The analysis of RDGB localization should be done in mosaic dcert1 retinas, which will be more convincing with internal control for each comparison. In addition, the phalloidin staining in Figure 2J shows distinct patterns of adherens junctions, indicating that the wildtype and dcert1 were imaged at different focal planes.
3. The significance of ceramide species levels in dcert1 and GMR>CPESRNAi needs to be explained better. Do certain alterations represent accumulation of ceramides in the ER?
4. The suppression by lace is interpreted as evidence that the reduced ERG amplitude in dcert1 is caused by ceramide accumulation in the ER. This interpretation seems preliminary as lace may interact with dcert genetically by other mechanisms.
5. The authors show that ERG amplitude is reduced in GMR>CPESRNAi. While this phenocopying is consistent with the reduced ERG amplitude in dcert1 being caused by reduced production of PE-ceramide, GMR>CPESRNAi also shows an increase in total ceramide level. Could this support the hypothesis that reduced ERG amplitude is caused by an accumulation of ceramide elsewhere? In addition, is the ERG amplitude reduction in GMR>CPESRNAi sensitive to lace?
6. Along the same line, while the total ceramide level is significantly reduced in lace heterozygotes, is the PE-ceramide level also reduced? If yes, wouldn't this be contradictory to PE-ceramide production being important for ERG amplitude?
7. What is the explanation and significance for the age-dependent deterioration of ERG amplitude in dcert1? Likewise, the significance of no retinal degeneration is not clearly presented.
8. The rescue of dcert1 phenotype by the expression of human CERT is a nice result. In addition to demonstrating a functional conservation, it allows a determination of CERT protein localization. However, the quality of images in Figure 6D should be improved. The phalloidin staining was rather poor, and the CNX99A in the lower panel was over-exposed, generating bleed-through signals at the rhabdomeres. In addition, the localization of hCERT should be explored further. For instance, does hCERT colocalize with RDGB? Is the hCERT localization altered in lace or GMR>CPESRNAi background?

Minor comments:

1. In Line 128, Df(732) should be Df(3L)BSC732.
2. GMR-SMSrRNAi shows an increase in ERG peak amplitude. Is there an explanation for this?

Significance

As CERT mutations are implicated in human learning disability, a better understanding of CERT function in neuronal cells is certainly of interest. While the link between ceramide transport and phospholipase signaling is novel and interesting, this paper does not clearly explain the mechanism. In addition, as the ERG were measured long after the retinal cells were deficient in CERT or CPES, it is difficult to assess whether the observed phenotype is a primary defect. Furthermore, the quality of some images needs to be improved. Thus, I feel the manuscript in its current form is too preliminary.

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Referee #1

Evidence, reproducibility and clarity

This manuscript dissects the physiological function of ceramide transfer protein (CERT) by studying the phenotype of CERT null Drosophila.

dCERT null animals have a reduced electrical response to light in their photoreceptors, reduced baseline PIP2 accumulation in the cells and delayed re-synthesis of PIP2 and its precursor, PI4P after light stimulation. There are also reduced ER:PM contact sites at the rhabdomere and a corresponding reduction in the localization of PI/PA exchange protein, RDGB at this site. Therefore, the animals seem to have an impaired ability for sustaining phototransduction, which is nonetheless milder than that seen after loss of RDGB, for example. In terms of biochemical function, there is no overall change in ceramides, with some minor increases in specific short chain pools. There is however a large decrease in PE-ceramide species, again selective for a few molecular species. Curiously, decreasing ceramides with a mutant in ceramide synthesis is able to partially rescue both the electrical response and RDGB localization in dCERT flies, implying the increased ceramide species contribute to the phenotype. In addition, a mutation in PE-ceramide synthase largely phenocopies the dCERT null, exhiniting both increases ceramides and decreased PE-ceramide.

In addition, dCERT flies were shown to have reduced localization of some plasma membrane proteins to detergent-resistant membrane fractions, as well as up regulation of the IRE1 and PERK stress-response pathways. Finally, dCERT nulls could be rescued with the human CERT protein, demonstrating conservation of core physiological function between these animals. Surprisingly, CERT is reported to localize to the ER:PM junctions at rhabdomeres, as opposed to the expected ER:Golgi contact sites.

Specific areas where the manuscript could be strengthened include:

Figure 2 studies the phototransduction system. Although clear changes in PI4P and PIP2 are seen, it would be interesting to see if changed PA accumulation occur in the dCERT animals, since RDGB localization is disrupted: this is expected to cause PM PA accumulation along with reduced PIP2 synthesis.

Lines 228-230 state: "These findings suggest an important contribution for reduced PE - Cer levels in the eye phenotypes of dcert". Does it not also suggest a contribution of the elevated ceramide species, since these are also observed in the CPES animals?

Figure 6D is a key finding that human CERT localized to the rhabdomere at ER:PM contact sites, though the reviewer was not convinced by these images. Is the protein truly localized to the contact sites, or simply have a pool of over-expressed protein localized to the surrounding cytoplasm? It also does not rule out localization (and therefore function) at ER:PM contact sites.

Statistics: There are a large number of t-tests employed that do not correct for multiple comparisons, for example in figures 3B, 3D, 3H, 4C, 6C, S2A, S2B, S3B and S3C.

There are two Western blotting sections in the methods.

Significance

Overall, the manuscript is clearly and succinctly written, with the data well presented and mostly convincing. The paper demonstrates clear phenotypes associated with loss of dCERT function, with surprising consequences for the function of a signaling system localized to ER:PM contact sites. To this reviewer, there seem to be three cogent observations of the paper: (i) loss of dCERT leads to accumulation of ceramides and loss of PE-ceramide, which together drive the phenotype. (ii) this ceramide alteration disrupts ER:PM contact sites and thus impairs phototransduction and (iii) rescue by human CERT and its apparent localization to ER:PM contact sites implies a potential novel site of action. Although surprising and novel, the significance of these observations are a little unclear: there is no obvious mechanism by which the elevated ceramide species and decreased PE-ceramide causes the specific failure in phototrasnduction, and the evidence for a novel site of action of CERT at the ER:PM contact sites is not compelling. Therefore, although an interesting and novel set of observations, the manuscript does not reveal a clear mechanistic basis for CERT physiological function.

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Reply to the reviewers

Reviewer #1

Evidence, reproducibility and clarity

This paper addresses a very interesting problem of non-centrosomal microtubule organization in developing Drosophila oocytes. Using genetics and imaging experiments, the authors reveal an interplay between the activity of kinesin-1, together with its essential cofactor Ensconsin, and microtubule organization at the cell cortex by the spectraplakin Shot, minus-end binding protein Patronin and Ninein, a protein implicated in microtubule minus end anchoring. The authors demonstrate that the loss of Ensconsin affects the cortical accumulation non-centrosomal microtubule organizing center (ncMTOC) proteins, microtubule length and vesicle motility in the oocyte, and show that this phenotype can be rescued by constitutively active kinesin-1 mutant, but not by Ensconsin mutants deficient in microtubule or kinesin binding. The functional connection between Ensconsin, kinesin-1 and ncMTOCs is further supported by a rescue experiment with Shot overexpression. Genetics and imaging experiments further implicate Ninein in the same pathway. These data are a clear strength of the paper; they represent a very interesting and useful addition to the field.

The weaknesses of the study are two-fold. First, the paper seems to lack a clear molecular model, uniting the observed phenomenology with the molecular functions of the studied proteins. Most importantly, it is not clear how kinesin-based plus-end directed transport contributes to cortical localization of ncMTOCs and regulation of microtubule length.

Second, not all conclusions and interpretations in the paper are supported by the presented data.

We thank the reviewer for recognizing the impact of this work. In response to the insightful suggestions, we performed extensive new experiments that establish a well-supported cellular and molecular model (Figure 7). The discussion has been restructured to directly link each conclusion to its corresponding experimental evidence, significantly strengthening the manuscript.

Below is a list of specific comments, outlining the concerns, in the order of appearance in the paper/figures.

Figure 1. The statement: "Ens loading on MTs in NCs and their subsequent transport by Dynein toward ring canals promotes the spatial enrichment of the Khc activator Ens in the oocyte" is not supported by data. The authors do not demonstrate that Ens is actually transported from the nurse cells to the oocyte while being attached to microtubules. They do show that the intensity of Ensconsin correlates with the intensity of microtubules, that the distribution of Ensconsin depends on its affinity to microtubules and that an Ensconsin pool locally photoactivated in a nurse cell can redistribute to the oocyte (and throughout the nurse cell) by what seems to be diffusion. The provided images suggest that Ensconsin passively diffuses into the oocyte and accumulates there because of higher microtubule density, which depends on dynein. To prove that Ensconsin is indeed transported by dynein in the microtubule-bound form, one would need to measure the residence time of Ensconsin on microtubules and demonstrate that it is longer than the time needed to transport microtubules by dynein into the oocyte; ideally, one would like to see movement of individual microtubules labelled with photoconverted Ensconsin from a nurse cell into the oocyte. Since microtubules are not enriched in the oocyte of the dynein mutant, analysis of Ensconsin intensity in this mutant is not informative and does not reveal the mechanism of Ensconsin accumulation.

As noted by Reviewer 3, the directional movement of microtubules traveling at ~140 nm/s from nurse cells toward the oocyte through Ring Canals was previously reported using a tagged Ens-MT binding domain reporter line by Lu et al. (2022). We have therefore added the citation of this crucial work in the novel version of the manuscript (lane 155-157) and removed the photo-conversion panel.

Critically, however, our study provides mechanistic insight that was missing from this earlier work: this mechanism is also crucial to enrich MAPs in the oocyte. The fact that Dynein mutants fail to enrich Ensconsin is a crucial piece of evidence: it supports a model of Ensconsin-loaded MT transport (Figure 1D-1F).

Figure 2. According to the abstract, this figure shows that Ensconsin is "maintained at the oocyte cortex by Ninein". However, the figure doesn't seem to prove it - it shows that oocyte enrichment of Ensonsin is partially dependent on Ninein, but this applies to the whole cell and not just to the cell cortex. Furthermore, it is not clear whether Ninein mutation affects microtubule density, which in turn would affect Ensconsin enrichment, and therefore, it is not clear whether the effect of Ninein loss on Ensconsin distribution is direct or indirect.

Ninein plays a critical role in Ensconsin enrichment and microtubule organization in the oocyte (new Figure 2, Figure 3, Figure S3). Quantification of total Tubulin signal shows no difference between control and Nin mutant oocytes (new Figure S3 panels A, B). We found decreased Ens enrichment in the oocyte, and Ens localization on MTs and to the cell cortex (Figure 2E, 2F, and Figure S3C and S3D).

Novel quantitative analyses of microtubule orientation at the anterior cortex, where MTs are normally preferentially oriented toward the posterior pole (Parton et al. 2011), demonstrate that Nin mutants exhibit randomized MT orientation compared to wild-type oocytes (new Figure 3C-3E).These findings establish that Ninein (although not essential) favors Ensconsin localization on MTs, Ens enrichment in the oocyte, ncMTOC cortical localization, and more robust MT orientation toward the posterior cortex. It also suggests that Ens levels in the oocyte acts as a rheostat to control Khc activation.

The observation that the aggregates formed by overexpressed Ninein accumulate other proteins, including Ensconsin, supports, though does not prove their interactions. Furthermore, there is absolutely no proof that Ninein aggregates are "ncMTOCs". Unless the authors demonstrate that these aggregates nucleate or anchor microtubules (for example, by detailed imaging of microtubules and EB1 comets), the text and labels in the figure would need to be altered.

We have modified the manuscript, we now refer to an accumulation of these components in large puncta, rather than aggregates, consistent with previous observations (Rosen et al., 2000). We acknowledge in the revised version that these puncta recruit Shot, Patronin and Ens without mentioning direct interaction (lane 218).

Importantly, we conducted a more detailed characterization of these Ninein/Shot/Patronin/Ens-containing puncta in a novel Figure S4. To rigorously assess their nucleation capacity, we analyzed Eb1-GFP-labeled MT comets, a robust readout of MT nucleation (Parton et al., 2011, Nashchekin et al., 2016). While few Eb1-positive comets occasionally emanate from these structures, confirming their identity as putative ncMTOCs, these puncta function as surprisingly weak nucleation centers (new Figure S4 E, Video S1) and, their presence does not alter overall MT architecture (new Figure S4 F). Moreover, these puncta disappear over time, are barely visible at stage 10B, they do not impair oocyte development or fertility (Figure S4 G and Table 1).

Minor comment: Note that a "ratio" (Figure 2C) is just a ratio, and should not be expressed in arbitrary units.

We have amended this point in all the figures.

Figure 3B: immunoprecipitation results cannot be interpreted because the immunoprecipitated proteins (GFP, Ens-GFP, Shot-YFP) are not shown. It is also not clear that this biochemical experiment is useful. If the authors would like to suggest that Ensconsin directly binds to Patronin, the interaction would need to be properly mapped at the protein domain level.

This is a good point: the GFP and Ens-GFP immunoprecipitated proteins are now much clearly identified on the blots and in the figure legend (new Figure 4G). Shot-YFP IP, was used as a positive control but is difficult to be detected by Western blot due to its large size (>106 Da) using conventional acrylamide gels (Nashchekin et al., 2016).

We now explicitly state that immunoprecipitations were performed at 4°C, where microtubules are fully depolymerized, thereby excluding undirect microtubule-mediated interactions. We agree with this reviewer: we cannot formally rule out interactions through bridging by other protein components. This is stated in the revised manuscript (lane 238-239).

One of the major phenotypes observed by the authors in Ens mutant is the loss of long microtubules. The authors make strong conclusions about the independence of this phenotype from the parameters of microtubule plus-end growth, but in fact, the quality of their data does not allow to make such a conclusion, because they only measured the number of EB1 comets and their growth rate but not the catastrophe, rescue or pausing frequency."Note that kinesin-1 has been implicated in promoting microtubule damage and rescue (doi: 10.1016/j.devcel.2021).In the absence of such measurements, one cannot conclude whether short microtubules arise through defects in the minus-end, plus-end or microtubule shaft regulation pathways.

We thank the reviewer for raising this important point. Our data demonstrate that microtubule (MT) nucleation and polymerization rates remain unaffected under Khc RNAi and ens mutant conditions, indicating that MT dynamics alterations must arise through alternative mechanisms.

As the reviewer suggested, recent studies on Kinesin activity and MT network regulation are indeed highly relevant. Two key studies from the Verhey and Aumeier laboratories examined Kinesin-1 gain-of-function conditions and revealed that constitutively active Kinesin-1 induces MT lattice damage (Budaitis et al., 2022). While damaged MTs can undergo self-repair, Aumeier and colleagues demonstrated that GTP-tubulin incorporation generates "rescue shafts" that promote MT rescue events (Andreu-Carbo et al., 2022). Extrapolating from these findings, loss of Kinesin-1 activity could plausibly reduce rescue shaft formation, thereby decreasing MT rescue frequency and stability. Although this hypothesis is challenging to test directly in our system, it provides a mechanistic framework for the observed reduction in MT number and stability.

Additionally, the reviewer highlighted the role of Khc in transporting the dynactin complex, an anti-catastrophe factor, to MT plus ends (Nieuwburg et al., 2017), which could further contribute to MT stabilization. This crucial reference is now incorporated into the revised Discussion.

Importantly, our work also demonstrates the contribution of Ens/Khc to ncMTOC targeting to the cell cortex. Our new quantitative analyses of MT organization (new Figure 5 B) reveal a defective anteroposterior orientation of cortical MTs in mutant conditions, pointing to a critical role for cortical ncMTOCs in organizing the MT network.

Taken together, we propose that the observed MT reduction and disorganization result from multiple interconnected mechanisms: (1) reduced rescue shaft formation affecting MT stability; (2) impaired transport of anti-catastrophe factors to MT plus ends; and (3) loss of cortical ncMTOCs, which are essential for minus-end MT stabilization and network organization. The Discussion has been revised to reflect this integrated model in a dedicated paragraph (“A possible regulation of MT dynamics in the oocyte at both plus end minus MT ends by Ens and Khc” lane 415-432).

It is important to note in that a spectraplakin, like Shot, can potentially affect different pathways, particularly when overexpressed.

We agree that Shot harbors multiple functional domains and acts as a key organizer of both actin and microtubule cytoskeletons. Overexpression of such a cytoskeletal cross-linker could indeed perturb both networks, making interpretation of Ens phenotype rescue challenging due to potential indirect effects.

To address this concern, we selected an appropriate Shot isoform for our rescue experiments that displayed similar localization to “endogenous” Shot-YFP (a genomic construct harboring shot regulatory sequences) and importantly that was not overexpressed.

Elevated expression of the Shot.L(A) isoform (see Western Blot Figure S8 A), considered as the wild-type form with two CH1 and CH2 actin-binding motifs (Lee and Kolodziej, 2002), showed abnormal localization such as strong binding to the microtubules in nurse cells and oocyte confirming the risk of gain-of-function artifacts and inappropriate conclusions (Figure S8 B, arrows).

By contrast, our rescue experiments using the Shot.L(C) isoform (that only harbors the CH2 motif) provide strong evidence against such artifacts for three reasons. First, Shot-L(C) is expressed at slightly lower levels than a Shot-YFP genomic construct (not overexpressed), and at much lower levels than Shot-L(A), despite using the same driver (Figure S8 A). Second, Shot-L(C) localization in the oocyte is similar to that of endogenous Shot-YFP, concentrating at the cell cortex (Figure S8 B, compare lower and top panels). Taken together, these controls rather suggest our rescue with the Shot-L(C) is specific.

Note that this Shot-L(C) isoform is sufficient to complement the absence of the shot gene in other cell contexts (Lee and Kolodziej, 2002).

Unjustified conclusions should be removed: the authors do not provide sufficient data to conclude that "ens and Khc oocytes MT organizational defects are caused by decreased ncMTOC cortical anchoring", because the actual cortical microtubule anchoring was not measured.

This is a valid point. We acknowledge that we did not directly measure microtubule anchoring in this study. In response, we have revised the discussion to more accurately reflect our observations. Throughout the manuscript, we now refer to "cortical microtubule organization" rather than "cortical microtubule anchoring," which better aligns with the data presented.

Minor comment: Microtubule growth velocity must be expressed in units of length per time, to enable evaluating the quality of the data, and not as a normalized value.

This is now amended in the revised version (modified Figure S7).

A significant part of the Discussion is dedicated to the potential role of Ensconsin in cortical microtubule anchoring and potential transport of ncMTOCs by kinesin. It is obviously fine that the authors discuss different theories, but it would be very helpful if the authors would first state what has been directly measured and established by their data, and what are the putative, currently speculative explanations of these data.

We have carefully considered the reviewer's constructive comments and are confident that this revised version fully addresses their concerns.

First, we have substantially strengthened the connection between the Results and Discussion sections, ensuring that our interpretations are more directly anchored in the experimental data. This restructuring significantly improves the overall clarity and logical flow of the manuscript.

Second, we have added a new comprehensive figure presenting a molecular-scale model of Kinesin-1 activation upon release of autoinhibition by Ensconsin (new Figure 7D). Critically, this figure also illustrates our proposed positive feedback loop mechanism: Khc-dependent cytoplasmic advection promotes cortical recruitment of additional ncMTOCs, which generates new cortical microtubules and further accelerates cytoplasmic transport (Figure 7 A-C). This self-amplifying cycle provides a mechanistic framework consistent with emerging evidence that cytoplasmic flows are essential for efficient intracellular transport in both insect and mammalian oocytes.

Minor comment: The writing and particularly the grammar need to be significantly improved throughout, which should be very easy with current language tools. Examples: "ncMTOCs recruitment" should be "ncMTOC recruitment"; "Vesicles speed" should be "Vesicle speed", "Nin oocytes harbored a WT growth,"- unclear what this means, etc. Many paragraphs are very long and difficult to read. Making shorter paragraphs would make the authors' line of thought more accessible to the reader.

We have amended and shortened the manuscript according to this reviewer feed-back. We have specifically built more focused paragraphs to facilitates the reading.

Significance

This paper represents significant advance in understanding non-centrosomal microtubule organization in general and in developing Drosophila oocytes in particular by connecting the microtubule minus-end regulation pathway to the Kinesin-1 and Ensconsin/MAP7-dependent transport. The genetics and imaging data are of good quality, are appropriately presented and quantified. These are clear strengths of the study which will make it interesting to researchers studying the cytoskeleton, microtubule-associated proteins and motors, and fly development.

The weaknesses of this study are due to the lack of clarity of the overall molecular model, which would limit the impact of the study on the field. Some interpretations are not sufficiently supported by data, but this can be solved by more precise and careful writing, without extensive additional experimentation.

We thank the reviewer for raising these important concerns regarding clarity and data interpretation. We have thoroughly revised the manuscript to address these issues on multiple fronts. First, we have substantially rewritten key sections to ensure that our conclusions are clearly articulated and directly supported by the data. Second, we have performed several new experiments that now allow us to propose a robust mechanistic model, presented in new figures. These additions significantly strengthen the manuscript and directly address the reviewer's concerns.

My expertise is cell biology and biochemistry of the microtubule cytoskeleton, including both microtubule-associated proteins and microtubule motors.

Reviewer #2

Evidence, reproducibility and clarity

In this manuscript, Berisha et al. investigate how microtubule (MT) organization is spatially regulated during Drosophila oogenesis. The authors identify a mechanism in which the Kinesin-1 activator Ensconsin/MAP7 is transported by dynein and anchored at the oocyte cortex via Ninein, enabling localized activation of Kinesin-1. Disruption of this pathway impairs ncMTOC recruitment and MT anchoring at the cortex. The authors combine genetic manipulation with high-resolution microscopy and use three key readouts to assess MT organization during mid-to-late oogenesis: cortical MT formation, localization of posterior determinants, and ooplasmic streaming. Notably, Kinesin-1, in concert with its activator Ens/MAP7, contributes to organizing the microtubule network it travels along. Overall, the study presents interesting findings, though we have several concerns we would like the authors to address. Ensconsin enrichment in the oocyte 1. Enrichment in the oocyte • Ensconsin is a MAP that binds MTs. Given that microtubule density in the oocyte significantly exceeds that in the nurse cells, its enrichment may passively reflect this difference. To assess whether the enrichment is specific, could the authors express a non-Drosophila MAP (e.g., mammalian MAP1B) to determine whether it also preferentially localizes to the oocyte?

To address this point, we performed a new series of experiments analyzing the enrichment of other Drosophila and non-Drosophila MAPs, including Jupiter-GFP, Eb1-GFP, and bovine Tau-GFP, all widely used markers of the microtubule cytoskeleton in flies (see new Figure S2). Our results reveal that Jupiter-GFP, Eb1-GFP, and bovine Tau-GFP all exhibit significantly weaker enrichment in the oocyte compared to Ens-GFP. Khc-GFP also shows lower enrichment. These findings indicate that MAP enrichment in the oocyte is MAP-dependent, rather than solely reflecting microtubule density or organization. Of note, we cannot exclude that microtubule post-translational modifications contribute to differential MAP binding between nurse cells and the oocyte, but this remains a question for future investigation.

The ability of ens-wt and ens-LowMT to induce tubulin polymerization according to the light scattering data (Fig. S1J) is minimal and does not reflect dramatic differences in localization. The authors should verify that, in all cases, the polymerization product in their in vitro assays is microtubules rather than other light-scattering aggregates. What is the control in these experiments? If it is just purified tubulin, it should not form polymers at physiological concentrations.

The critical concentration Cr for microtubule self-assembly in classical BRB80 buffer found by us and others is around 20 µM (see Fig. 2c in Weiss et al., 2010). Here, microtubules were assembled at 40 µM tubulin concentration, i.e., largely above the Cr. As stated in the materials and methods section, we systematically induced cooling at 4°C after assembly to assess the presence of aggregates, since those do not fall apart upon cooling. The decrease in optical density upon cooling is a direct control that the initial increase in DO is due to the formation of microtubules. Finally, aggregation and polymerization curves are widely different, the former displaying an exponential shape and the latter a sigmoid assembly phase (see Fig. 3A and 3B in Weiss et al., 2010).

Photoconversion caveatsMAPs are known to dynamically associate and dissociate from microtubules. Therefore, interpretation of the Ens photoconversion data should be made with caution. The expanding red signal from the nurse cells to the oocyte may reflect a any combination of dynein-mediated MT transport and passive diffusion of unbound Ensconsin. Notably, photoconversion of a soluble protein in the nurse cells would also result in a gradual increase in red signal in the oocyte, independent of active transport. We encourage the authors to more thoroughly discuss these caveats. It may also help to present the green and red channels side by side rather than as merged images, to allow readers to assess signal movement and spatial patterns better.

This is a valid point that mirrors the comment of Reviewers 1 and 3. The directional movement of microtubules traveling at ~140 nm/s from nurse cells toward the oocyte via the ring canals was previously reported by Lu et al. (2022) with excellent spatial resolution. Notably, this MT transport was measured using a fusion protein containing the Ens MT-binding domain. We now cite this relevant study in our revised manuscript and have removed this redundant panel in Figure 1.

Reduction of Shot at the anterior cortex• Shot is known to bind strongly to F-actin, and in the Drosophila ovary, its localization typically correlates more closely with F-actin structures than with microtubules, despite being an MT-actin crosslinker. Therefore, the observed reduction of cortical Shot in ens, nin mutants, and Khc-RNAi oocytes is unexpected. It would be important to determine whether cortical F-actin is also disrupted in these conditions, which should be straightforward to assess via phalloidin staining.

As requested by the reviewer, we performed actin staining experiments, which are now presented in a new Figure S5. These data demonstrate that the cortical actin network remains intact in all mutant backgrounds analyzed, ruling out any indirect effect of actin cytoskeleton disruption on the observed phenotypes.

MTs are barely visible in Fig. 3A, which is meant to demonstrate Ens-GFP colocalization with tubulin. Higher-quality images are needed.

The revised version now provides significantly improved images to show the different components examined. Our data show that Ens and Ninein localize at the cell cortex where they co-localize with Shot and Patronin (Figure 2 A-C). In addition, novel images show that Ens extends along microtubules (new Figure 4 A).

MT gradient in stage 9 oocytesIn ens-/-, nin-/-, and Khc-RNAi oocytes, is there any global defect in the stage 9 microtubule gradient? This information would help clarify the extent to which cortical localization defects reflect broader disruptions in microtubule polarity.

We now provide quantitative analysis of microtubule (MT) array organization in novel figures (Figure 3D and Figure 5B). Our data reveal that both Khc RNAi and ens mutant oocytes exhibit severe disruption of MT orientation toward the posterior (new Figure 5B). Importantly, this defect is significantly less pronounced in Nin-/- oocytes, which retain residual ncMTOCs at the cortex (new Figure 3D). This differential phenotype supports our model that cortical ncMTOCs are critical for maintaining proper MT orientation toward the posterior side of the oocyte.

Role of Ninein in cortical anchoringThe requirement for Ninein in cortical anchorage is the least convincing aspect of the manuscript and somewhat disrupts the narrative flow. First, it is unclear whether Ninein exhibits the same oocyte-enriched localization pattern as Ensconsin. Is Ninein detectable in nurse cells? Second, the Ninein antibody signal appears concentrated in a small area of the anterior-lateral oocyte cortex (Fig. 2A), yet Ninein loss leads to reduced Shot signal along a much larger portion of the anterior cortex (Fig. 2F)-a spatial mismatch that weakens the proposed functional relationship. Third, Ninein overexpression results in cortical aggregates that co-localize with Shot, Patronin, and Ensconsin. Are these aggregates functional ncMTOCs? Do microtubules emanate from these foci?

We now provide a more comprehensive analysis of Ninein localization. Similar to Ensconsin (Ens), endogenous Ninein is enriched in the oocyte during the early stages of oocyte development but is also detected in NCs (see modified Figure 2 A and Lasko et al., 2016). Improved imaging of Ninein further shows that the protein partially co-localizes with Ens, and ncMTOCs at the anterior cortex and with Ens-bound MTs (Figure 2B, 2C).

Importantly, loss of Ninein (Nin) only partially reduces the enrichment of Ens in the oocyte (Figure 2E). Both Ens and Kinesin heavy chain (Khc) remain partially functional and continue to target non-centrosomal microtubule-organizing centers (ncMTOCs) to the cortex (Figure 3A). In Nin-/- mutants, a subset of long cortical microtubules (MTs) is present, thereby generating cytoplasmic streaming, although less efficiently than under wild-type (WT) conditions (Figure 3F and 3G). As a non-essential gene, we envisage Ninein as a facilitator of MT organization during oocyte development.

Finally, our new analyses demonstrate that large puncta containing Ninein, Shot, Patronin, and despite their size, appear to be relatively weak nucleation centers (revised Figure S4 E and Video 1). In addition, their presence does not bias overall MT architecture (Figure S4 F) nor impair oocyte development and fertility (Figure S4 G and Table 1).

Inconsistency of Khc^MutEns rescueThe Khc^MutEns variant partially rescues cortical MT formation and restores a slow but measurable cytoplasmic flow yet it fails to rescue Staufen localization (Fig. 5). This raises questions about the consistency and completeness of the rescue. Could the authors clarify this discrepancy or propose a mechanistic rationale?

This is a good point. The cytoplasmic flows (the consequence of cargo transport by Khc on MTs) generated by a constitutively active KhcMutEns in an ens mutant condition, are less efficient than those driven by Khc activated by Ens in a control condition (Figure 6C). The rescued flow is probably not efficient enough to completely rescue the Staufen localization at stage 10.

Additionally, this KhcMutEns variant rescues the viability of embryos from Khc27 mutant germline clones oocytes but not from ens mutants (Table1). One hypothesis is that Ens harbors additional functions beyond Khc activation.

This incomplete rescue of Ens by an active Khc variant could also be the consequence of the “paradox of co-dependence”: Kinesin-1 also transport the antagonizing motor Dynein that promotes cargo transport in opposite directions (Hancock et al., 2016). The phenotype of a gain of function variant is therefore complex to interpret. Consistent with this, both KhcMutEns-GFP and KhcDhinge2 two active Khc only rescues partially centrosome transport in ens mutant Neural Stem Cells (Figure S10).

Minor points: 1. The pUbi-attB-Khc-GFP vector was used to generate the Khc^MutEns transgenic line, presumably under control of the ubiquitous ubi promoter. Could the authors specify which attP landing site was used? Additionally, are the transgenic flies viable and fertile, given that Kinesin-1 is hyperactive in this construct?

All transgenic constructs were integrated at defined genomic landing sites to ensure controlled expression levels. Specifically, both GFP-tagged KhcWT and KhcMutEns were inserted at the VK05 (attP9A) site using PhiC31-mediated integration. Full details of the landing sites are provided in the Materials and Methods section. Both transgenic flies are homozygous lethal and the transgenes are maintained over TM6B balancers.

On page 11 (Discussion, section titled "A dual Ensconsin oocyte enrichment mechanism achieves spatial relief of Khc inhibition"), the statement "many mutations in Kif5A are causal of human diseases" would benefit from a brief clarification. Since not all readers may be familiar with kinesin gene nomenclature, please indicate that KIF5A is one of the three human homologs of Kinesin heavy chain.

We clarified this point in the revised version (lane 465-466).

On page 16 (Materials and Methods, "Immunofluorescence in fly ovaries"), the sentence "Ovaries were mounted on a slide with ProlonGold medium with DAPI (Invitrogen)" should be corrected to "ProLong Gold."

This is corrected.

Significance

This study shows that enrichment of MAP7/ensconsin in the oocyte is the mechanism of kinesin-1 activation there and is important for cytoplasmic streaming and localization non-centrosomal microtubule-organizing centers to the oocyte cortex

We thank the reviewers for the accurate review of our manuscript and their positive feed-back.

Reviewer #3

Evidence, reproducibility and clarity

The manuscript of Berisha et al., investigates the role of Ensconsin (Ens), Kinesin-1 and Ninein in organisation of microtubules (MT) in Drosophila oocyte. At stage 9 oocytes Kinesin-1 transports oskar mRNA, a posterior determinant, along MT that are organised by ncMTOCs. At stage 10b, Kinesin-1 induces cytoplasmic advection to mix the contents of the oocyte. Ensconsin/Map7 is a MT associated protein (MAP) that uses its MT-binding domain (MBD) and kinesin binding domain (KBD) to recruit Kinesin-1 to the microtubules and to stimulate the motility of MT-bound Kinesin-1. Using various new Ens transgenes, the authors demonstrate the requirement of Ens MBD and Ninein in Ens localisation to the oocyte where Ens activates Kinesin-1 using its KBD. The authors also claim that Ens, Kinesin-1 and Ninein are required for the accumulation of ncMTOCs at the oocyte cortex and argue that the detachment of the ncMTOCs from the cortex accounts for the reduced localisation of oskar mRNA at stage 9 and the lack of cytoplasmic streaming at stage 10b. Although the manuscript contains several interesting observations, the authors' conclusions are not sufficiently supported by their data. The structure function analysis of Ensconsin (Ens) is potentially publishable, but the conclusions on ncMTOC anchoring and cytoplasmic streaming not convincing.

We are grateful that the regulation of Khc activity by MAP7 was well received by all reviewers. While our study focuses on Drosophila oogenesis, we believe this mechanism may have broader implications for understanding kinesin regulation across biological systems.

For the novel function of the MAP7/Khc complex in organizing its own microtubule networks through ncMTOC recruitment, we have carefully considered the reviewers' constructive recommendations. We now provide additional experimental evidence supporting a model of flux self-amplification in which ncMTOC recruitment plays a key role. It is well established that cytoplasmic flows are essential for posterior localization of cell fate determinants at stage 10B. Slow flows have also been described at earlier oogenesis stages by the groups of Saxton and St Johnston. Building on these early publications and our new experiments, we propose that these flows are essential to promote a positive feedback loop that reinforces ncMTOC recruitment and MT organization (Figure 7).

1) The main conclusion of the manuscript is that "MT advection failure in Khc and ens in late oogenesis stems from defective cortical ncMTOCs recruitment". This completely overlooks the abundant evidence that Kinesin-1 directly drives cytoplasmic streaming by transporting vesicles and microtubules along microtubules, which then move the cytoplasm by advection (Palacios et al., 2002; Serbus et al, 2005; Lu et al, 2016). Since Kinesin-1 generates the flows, one cannot conclude that the effect of khc and ens mutants on cortical ncMTOC positioning has any direct effect on these flows, which do not occur in these mutants.

We regret the lack of clarity of the first version of the manuscript and some missing references. We propose a model in which the Kinesin-1- dependent slow flows (described by Serbus/Saxton and Palacios/StJohnston) play a central role in amplifying ncMTOC anchoring and cortical MT network formation (see model in the new Figure 7).

2) The authors claim that streaming phenotypes of ens and khs mutants are due to a decrease in microtubule length caused by the defective localisation of ncMTOCs. In addition to the problem raised above, However, I am not convinced that they can make accurate measurements of microtubule length from confocal images like those shown in Figure 4. Firstly, they are measuring the length of bundles of microtubules and cannot resolve individual microtubules. This problem is compounded by the fact that the microtubules do not align into parallel bundles in the mutants. This will make the "microtubules" appear shorter in the mutants. In addition, the alignment of the microtubules in wild-type allows one to choose images in which the microtubule lie in the imaging plane, whereas the more disorganized arrangement of the microtubules in the mutants means that most microtubules will cross the imaging plane, which precludes accurate measurements of their length.

As mentioned by Reviewer 4, we have been transparent with the methodology, and the limitations that were fully described in the material and methods section.

Cortical microtubules in oocytes are highly dynamic and move rapidly, making it technically impossible to capture their entire length using standard Z-stack acquisitions. We therefore adopted a compromise approach: measuring microtubules within a single focal plane positioned just below the oocyte cortex. This strategy is consistent with established methods in the field, such as those used by Parton et al. (2011) to track microtubule plus-end directionality. To avoid overinterpretation, we explicitly refer to these measurements as "minimum detectable MT length," acknowledging that microtubules may extend beyond the focal plane, particularly at stage 10, where long, tortuous bundles frequently exit the plane of focus. These methodological considerations and potential biases are clearly described in the Materials and Methods section and the text now mentions the possible disorganization of the MT network in the mutant conditions (lane 272-273).

In this revised version, we now provide complementary analyses of MT network organization.Beyond length measurements (and the mentioned limitations), we also quantified microtubule network orientation at stage 9, assessing whether cortical microtubules are preferentially oriented toward the posterior axis as observed in controls (revised Figure 3D and Figure 5B). While this analysis is also subject to the same technical limitations, it reveals a clear biological difference: microtubules exhibit posterior-biased orientation in control oocytes similar to a previous study (Parton et al., 2011) but adopt a randomized orientation in Nin-/-, ens, and Khc RNAi-depleted oocytes (revised Figure 3D and Figure 5B).

Taken together, these complementary approaches, despite their technical constraints, provide convergent evidence for the role of the Khc/Ens complex in organizing cortical microtubule networks during oogenesis.

3) "To investigate whether the presence of these short microtubules in ens and Khc RNAi oocytes is due to defects in microtubule anchoring or is also associated with a decrease in microtubule polymerization at their plus ends, we quantified the velocity and number of EB1comets, which label growing microtubule plus ends (Figure S3)." I do not understand how the anchoring or not of microtubule minus ends to the cortex determines how far their plus ends grow, and these measurements fall short of showing that plus end growth is unaffected. It has already been shown that the Kinesin-1-dependent transport of Dynactin to growing microtubule plus ends increases the length of microtubules in the oocyte because Dynactin acts as an anti-catastrophe factor at the plus ends. Thus, khc mutants should have shorter microtubules independently of any effects on ncMTOC anchoring. The measurements of EB1 comet speed and frequency in FigS2 will not detect this change and are not relevant for their claims about microtubule length. Furthermore, the authors measured EB1 comets at stage 9 (where they did not observe short MT) rather than at stage 10b. The authors' argument would be better supported if they performed the measurements at stage 10b.

We thank the reviewer for raising this important point. The short microtubule (MT) length observed at stage 10B could indeed result from limited plus-end growth. Unfortunately, we were unable to test this hypothesis directly: strong endogenous yolk autofluorescence at this stage prevented reliable detection of Eb1-GFP comets, precluding velocity measurements.

At least during stage 9, our data demonstrate that MT nucleation and polymerization rates are not reduced in both KhcRNAi and ens mutant conditions, indicating that the observed MT alterations must arise through alternative mechanisms.

In the discussion, we propose the following interconnected explanations, supported by recent literature and the reviewers’ suggestions:

1- Reduced MT rescue events. Two seminal studies from the Verhey and Aumeier laboratories have shown that constitutively active Kinesin-1 induces MT lattice damage (Budaitis et al., 2022), which can be repaired through GTP-tubulin incorporation into "rescue shafts" that promote MT rescue (Andreu-Carbo et al., 2022). Extrapolating from these findings, loss of Kinesin-1 activity could plausibly reduce rescue shaft formation, thereby decreasing MT stability. While challenging to test directly in our system, this mechanism provides a plausible framework for the observed phenotype.

2- Impaired transport of stabilizing factors. As that reviewer astutely points out, Khc transports the dynactin complex, an anti-catastrophe factor, to MT plus ends (Nieuwburg et al., 2017). Loss of this transport could further compromise MT plus end stability. We now discuss this important mechanism in the revised manuscript.

3- Loss of cortical ncMTOCs. Critically, our new quantitative analyses (revised Figure 3 and Figure 5) also reveal defective anteroposterior orientation of cortical MTs in mutant conditions. These experiments suggest that Ens/Khc-mediated localization of ncMTOCs to the cortex is essential for proper MT network organization, and possibly minus-end stabilization as suggested in several studies (Feng et al., 2019, Goodwin and Vale, 2011, Nashchekin et al., 2016).

Altogether, we now propose an integrated model in which MT reduction and disorganization may result from multiple complementary mechanisms operating downstream of Kinesin-1/Ensconsin loss. While some aspects remain difficult to test directly in our in vivo system, the convergence of our data with recent mechanistic studies provides an interesting conceptual framework. The Discussion has been revised to reflect this comprehensive view in a dedicated paragraph (“A possible regulation of MT dynamics in the oocyte at both plus end minus MT ends by Ens and Khc” lane 415-432).

4) The Shot overexpression experiments presented in Fig.3 E-F, Fig.4D and TableS1 are very confusing. Originally , the authors used Shot-GFP overexpression at stage 9 to show that there is a decrease of ncMTOCs at the cortex in ens mutants (Fig.3 E-F) and speculated that this caused the defects in MT length and cytoplasmic advection at stage 10B. However the authors later state on page 8 that : "Shot overexpression (Shot OE) was sufficient to rescue the presence of long cortical MTs and ooplasmic advection in most ens oocytes (9/14), resembling the patterns observed in controls (Figures 4B right panel and 4D). Moreover, while ens females were fully sterile, overexpression of Shot was sufficient to restore that loss of fertility (Table S1)". Is this the same UAS Shot-GFP and VP16 Gal4 used in both experiments? If so, this contradictions puts the authors conclusions in question.

This is an important point that requires clarification regarding our experimental design.

The Shot-YFP construct is a genomic insertion on chromosome 3. The ens mutation is also located on chromosome 3 and we were unable to recombine this transgene with the ens mutant for live quantification of cortical Shot. To circumvent this technical limitation, we used a UAS-Shot.L(C)-GFP transgenic construct driven by a maternal driver, expressed in both wild-type (control) and ens mutant oocytes. We validated that the expression level and subcellular localization of UAS-Shot.L(C)-GFP were comparable to those of the genomic Shot-YFP (new Figure S8 A and B).

From these experiments, we drew two key conclusions. First, cortical Shot.L(C)-GFP is less abundant in ens mutant oocytes compared to wild-type (the quantification has been removed from this version). Second, despite this reduced cortical accumulation, Shot.L(C)-GFP expression partially rescues ooplasmic flows and microtubule streaming in stage 10B ens mutant oocytes, and restores fertility to ens mutant females.

5) The authors based they conclusions about the involvement of Ens, Kinesin-1 and Ninein in ncMTOC anchoring on the decrease in cortical fluorescence intensity of Shot-YFP and Patronin-YFP in the corresponding mutant backgrounds. However, there is a large variation in average Shot-YFP intensity between control oocytes in different experiments. In Fig. 2F-G the average level of Shot-YFP in the control sis 130 AU while in Fig.3 G-H it is only 55 AU. This makes me worry about reliability of such measurements and the conclusions drawn from them.

To clarify this point, we have harmonized the method used to quantify the Shot-YFP signals in Figure 4E with the methodology used in Figure 3B, based on the original images. The levels are not strictly identical (Control Figure 2 B: 132.7+/-36.2 versus Control Figure 4 E: 164.0+/- 37.7). These differences are usual when experiments are performed at several-month intervals and by different users.

6) The decrease in the intensity of Shot-YFP and Patronin-YFP cortical fluorescence in ens mutant oocytes could be because of problems with ncMTOC anchoring or with ncMTOCs formation. The authors should find a way to distinguish between these two possibilities. The authors could express Ens-Mut (described in Sung et al 2008), which localises at the oocyte posterior and test whether it recruits Shot/Patronin ncMTOCs to the posterior.

We tried to obtain the fly stocks described in the 2008 paper by contacting former members of Pernille Rørth's laboratory. Unfortunately, we learned that the lab no longer exists and that all reagents, including the requested stocks, were either discarded or lost over time. To our knowledge, these materials are no longer available from any source. We regret that this limitation prevented us from performing the straightforward experiments suggested by the reviewer using these specific tools.

7) According to the Materials and Methods, the Shot-GFP used in Fig.3 E-F and Fig.4 was the BDSC line 29042. This is Shot L(C), a full-length version of Shot missing the CH1 actin-binding domain that is crucial for Shot anchoring to the cortex. If the authors indeed used this version of Shot-GFP, the interpretation of the above experiments is very difficult.

The Shot.L(C) isoform lacks the CH1 domain but retains the CH2 actin-binding motif. Truncated proteins with this domain and fused to GST retains a weak ability to bind actin in vitro. Importantly, the function of this isoform is context-dependent: it cannot rescue shot loss-of-function in neuron morphogenesis but fully restores Shot-dependent tracheal cell remodeling (Lee and Kolodziej, 2002).

In our experiments, when the Shot.L(C) isoform was expressed under the control of a maternal driver, its localization to the oocyte cortex was comparable to that of the genomic Shot-YFP construct (new Figure S8). This demonstrates unambiguously that the CH1 domain is dispensable for Shot cortical localization in oocytes, and that CH2-mediated actin binding is sufficient for this localization. Of note, a recent study showed that actin network are not equivalent highlighting the need for specific Shot isoforms harboring specialized actin-binding domain (Nashchekin et al., 2024).

We note that the expression level of Shot.L(C)-GFP in the oocyte appeared slightly lower than that of Shot-YFP (expressed under endogenous Shot regulatory sequences), as assessed by Western blot (Figure S8 A).

Critically, Shot.L(C)-GFP expression was substantially lower than that of Shot.L(A)-GFP (that harbored both the CH1 and CH2 domain). Shot.L(A)-GFP was overexpressed (Figure 8 A) and ectopically localized on MTs in both nurse cells and the ooplasm (Figure S8 B middle panel and arrow). These observations are in agreement that the Shot.L(C)-GFP rescue experiment was performed at near-physiological expression levels, strengthening the validity of our conclusions.

8) Page 6 "converted in NCs, in a region adjacent to the ring canals, Dendra-Ens-labeled MTs were found in the oocyte compartment indicating they are able to travel from NC toward the oocyte through ring canals". I have difficulty seeing the translocation of MT through the ring canals. Perhaps it would be more obvious with a movie/picture showing only one channel. Considering that f Dendra-Ens appears in the oocyte much faster than MT transport through ring canals (140nm/s, Lu et al 2022), the authors are most probably observing the translocation of free Ens rather than Ens bound to MT. The authors should also mention that Ens movement from the NC to the oocyte has been shown before with Ens MBD in Lu et al 2022 with better resolution.

We fully agree on the caveat mentioned by this reviewer: we may observe the translocation of free Dendra-Ensconsin. The experiment, was removed and replaced by referring to the work of the Gelfand lab. The movement of MTs that travel at ~140 nm/s between nurse cells toward the oocyte through the Ring Canals was reported before by Lu et al. (2022) with a very good resolution. Notably, this directional directed movement of MTs was measured using a fusion protein encompassing Ens MT-binding domain. We decided to remove this inclusive experiment and rather refer to this relevant study.

9) Page 6: The co-localization of Ninein with Ens and Shot at the oocyte cortex (Figure 2A). I have difficulty seeing this co-localisation. Perhaps it would be more obvious in merged images of only two channels and with higher resolution images

10) "a pool of the Ens-GFP co-localized with Ch-Patronin at cortical ncMTOCs at the anterior cortex (Figure 3A)". I also have difficulty seeing this.

We have performed new high-resolution acquisitions that provide clearer and more convincing evidence for the localization cortical distribution of these proteins (revised Figure 2A-2C and Figure 4A). These improved images demonstrate that Ens, Ninein, Shot, and Patronin partially colocalize at cortical ncMTOCs, as initially proposed. Importantly, the new data also reveal a spatial distinction: while Ens localizes along microtubules extending from these cortical sites, Ninein appears confined to small cytoplasmic puncta adjacent but also present on cortical microtubules.

11) "Ninein co-localizes with Ens at the oocyte cortex and partially along cortical microtubules, contributing to the maintenance of high Ens protein levels in the oocyte and its proper cortical targeting". I could not find any data showing the involvement of Ninein in the cortical targeting of Ens.

We found decreased Ens localization to MTs and to the cell cortex region (new Figure S3 A-B).

12) "our MT network analyses reveal the presence of numerous short MTs cytoplasmic clustered in an anterior pattern." "This low cortical recruitment of ncMTOCs is consistent with poor MT anchoring and their cytoplasmic accumulation." I could not find any data showing that short cortical MT observed at stage 10b in ens mutant and Khc RNAi were cytoplasmic and poorly anchored.

The sentence was removed from the revised manuscript.

13) "The egg chamber consists of interconnected cells where Dynein and Khc activities are spatially separated. Dynein facilitates transport from NCs to the oocyte, while Khc mediates both transport and advection within the oocyte." Dynein is involved in various activities in the oocyte. It anchors the oocyte nucleus and transports bcd and grk mRNA to mention a few.

The text was amended to reflect Dynein involvement in transport activities in the oocyte, with the appropriate references (lane 105-107).

14) The cartoons in Fig.2H and 3I exaggerate the effect of Ninein and Ens on cortical ncMTOCs. According to the corresponding graphs, there is a 20 and 50% decrease in each case.

New cartoons (now revised Figure 3E and 4F), are amended to reflect the ncMTOC values but also MT orientation (Figure 3E).

Significance

Given the important concerns raised, the significance of the findings is difficult to assess at this stage.

We sincerely thank the reviewer for their thorough evaluation of our manuscript. We have carefully addressed their concerns through substantial new experiments and analyses. We hope that the revised manuscript, in its current form, now provides the clarifications and additional evidence requested, and that our responses demonstrate the significance of our findings.

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

Summary: This manuscript presents an investigation into the molecular mechanisms governing spatial activation of Kinesin-1 motor protein during Drosophila oogenesis, revealing a regulatory network that controls microtubule organization and cytoplasmic transport. The authors demonstrate that Ensconsin, a MAP7 family protein and Kinesin-1 activator, is spatially enriched in the oocyte through a dual mechanism involving Dynein-mediated transport from nurse cells and cortical maintenance by Ninein. This spatial enrichment of Ens is crucial for locally relieving Kinesin-1 auto-inhibition. The Ens/Khc complex promotes cortical recruitment of non-centrosomal microtubule organizing centers (ncMTOCs), which are essential for anchoring microtubules at the cortex, enabling the formation of long, parallel microtubule streams or "twisters" that drive cytoplasmic advection during late oogenesis. This work establishes a paradigm where motor protein activation is spatially controlled through targeted localization of regulatory cofactors, with the activated motor then participating in building its own transport infrastructure through ncMTOC recruitment and microtubule network organization.

There's a lot to like about this paper! The data are generally lovely and nicely presented. The authors also use a combination of experimental approaches, combining genetics, live and fixed imaging, and protein biochemistry.

We thank the reviewer for this enthusiastic and supportive review, which helped us further strengthen the manuscript.

Concerns: Page 6: "to assay if elevation of Ninein levels was able to mis-regulate Ens localization, we overexpressed a tagged Ninein-RFP protein in the oocyte. At stage 9 the overexpressed Ninein accumulated at the anterior cortex of the oocyte and also generated large cortical aggregates able to recruit high levels of Ens (Figures 2D and 2H)... The examination of Ninein/Ens cortical aggregates obtained after Ninein overexpression showed that these aggregates were also able to recruit high levels of Patronin and Shot (Figures 2E and 2H)." Firstly, I'm not crazy about the use of "overexpressed" here, since there isn't normally any Ninein-RFP in the oocyte. In these experiments it has been therefore expressed, not overexpressed. Secondly, I don't understand what the reader is supposed to make of these data. Expression of a protein carrying a large fluorescent tag leads to large aggregates (they don't look cortical to me) that include multiple proteins - in fact, all the proteins examined. I don't understand this to be evidence of anything in particular, except that Ninein-RFP causes the accumulation of big multi-protein aggregates. While I can understand what the authors were trying to do here, I think that these data are inconclusive and should be de-emphasized.

We have revised the manuscript by replacing overexpressed with expressed (lanes 211 and 212). In addition, we now provide new localization data in both cortical (new Figure S4 A, top) and medial focal planes (new Figure S4 A, bottom), demonstrating that Ninein puncta (the word used in Rosen et al, 2019), rather than aggregates are located cortically. We also show that live IRP-labelled MTs do not colocalize with Ninein-RFP puncta. In light of the new experiments and the comments from the other reviewers, the corresponding text has been revised and de-emphasized accordingly.

Page 7: "Co-immunoprecipitations experiments revealed that Patronin was associated with Shot-YFP, as shown previously (Nashchekin et al., 2016), but also with EnsWT-GFP, indicating that Ens, Shot and Patronin are present in the same complex (Figure 3B)." I do not agree that association between Ens-GFP and Patronin indicates that Ens is in the same complex as Shot and Patronin. It is also very possible that there are two (or more) distinct protein complexes. This conclusion could therefore be softened. Instead of "indicating" I suggest "suggesting the possibility."

We have toned down this conclusion and indicated “suggesting the possibility” (lane 238-239).

Page 7: "During stage 9, the average subcortical MT length, taken at one focal plane in live oocytes (see methods)..." I appreciate that the authors have been careful to describe how they measured MT length, as this is a major point for interpretation. I think the reader would benefit from an explanation of why they decided to measure in only one focal plane and how that decision could impact the results.

We appreciate this helpful suggestion. Cortical microtubules are indeed highly dynamic and extend in multiple directions, including along the Z-axis. Moreover, their diameter is extremely small (approximately 25 nm), making it technically challenging to accurately measure their full length with high resolution using our Zeiss Airyscan confocal microscope (over several, microns): the acquisition of Z-stacks is relatively slow and therefore not well suited to capturing the rapid dynamics of these microtubules. Consequently, our length measurements represent a compromise and most likely underestimate the actual lengths of microtubules growing outside the focal plane. We note that other groups have encountered similar technical limitations (Parton et al., 2011).

Page 7: "... the MTs exhibited an orthogonal orientation relative to the anterior cortex (Figures 4A left panels, 4C and 4E)." This phenotype might not be obvious to readers. Can it be quantified?

We have now analyzed the orientation of microtubules (MTs) along the dorso-ventral axis. Our analysis shows that ens, Khc RNAi oocytes (new Figure 5B), and, to a lesser extent, Nin mutant oocytes (new Figure 3D), display a more random MT orientation compared to wild-type (WT) oocytes. In WT oocytes, MTs are predominantly oriented toward the posterior pole, consistent with previous findings (Parton et al., 2011).

Page 8: "Altogether, the analyses of Ens and Khc defective oocytes suggested that MT organization defects during late oogenesis (stage 10B) were caused by an initial failure of ncMTOCs to reach the cell cortex. Therefore, we hypothesized that overexpression of the ncMTOC component Shot could restore certain aspects of microtubule cortical organization in ens-deficient oocytes. Indeed, Shot overexpression (Shot OE) was sufficient to rescue the presence of long cortical MTs and ooplasmic advection in most ens oocytes (9/14)..." The data are clear, but the explanation is not. Can the authors please explain why adding in more of an ncMTOC component (Shot) rescues a defect of ncMTOC cortical localization?

We propose that cytoplasmic ncMTOCs can bind the cell cortex via the Shot subunit that is so far the only component that harbors actin-binding motifs. Therefore, we propose that elevating cytoplasmic Shot increase the possibility of Shot to encounter the cortex by diffusion when flows are absent. This is now explained lane 282-285.

I'm grateful to the authors for their inclusion of helpful diagrams, as in Figures 1G and 2H. I think the manuscript might benefit from one more of these at the end, illustrating the ultimate model.

We have carefully considered and followed the reviewer’s suggestions. In response, we have included a new figure illustrating our proposed model: the recruitment of ncMTOCs to the cell cortex through low Khc-mediated flows at stage 9 enhances cortical microtubule density, which in turn promotes self-amplifying flows (new Figure 7, panels A to C). Note that this Figure also depicts activation of Khc by loss of auto-inhibition (Figure 7, panel D).

I'm sorry to say that the language could use quite a bit of polishing. There are missing and extraneous commas. There is also regular confusion between the use of plural and singular nouns. Some early instances include:

1. Page 3: thought instead of "thoughted."
2. Page 5: "A previous studies have revealed"
3. Page 5: "A significantly loss"
4. Page 6: "troughs ring canals" should be "through ring canals"
5. Page 7: lives stage 9 oocytes
6. Page 7: As ens and Khc RNAi oocytes exhibits
7. Page 7: we examined in details
8. Page 7: This average MT length was similar in Khc RNAi and ens mutant oocyte..

We apologize for errors. We made the appropriate corrections of the manuscript.

Reviewer #4 (Significance (Required)):

This work makes a nice conceptual advance by showing that motor activation controls its own transport infrastructure, a paradigm that could extend to other systems requiring spatially regulated transport.

We thank the reviewers for their evaluation of the manuscript and helpful comments.

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Referee #4

Evidence, reproducibility and clarity

Summary: This manuscript presents an investigation into the molecular mechanisms governing spatial activation of Kinesin-1 motor protein during Drosophila oogenesis, revealing a regulatory network that controls microtubule organization and cytoplasmic transport. The authors demonstrate that Ensconsin, a MAP7 family protein and Kinesin-1 activator, is spatially enriched in the oocyte through a dual mechanism involving Dynein-mediated transport from nurse cells and cortical maintenance by Ninein. This spatial enrichment of Ens is crucial for locally relieving Kinesin-1 auto-inhibition. The Ens/Khc complex promotes cortical recruitment of non-centrosomal microtubule organizing centers (ncMTOCs), which are essential for anchoring microtubules at the cortex, enabling the formation of long, parallel microtubule streams or "twisters" that drive cytoplasmic advection during late oogenesis. This work establishes a paradigm where motor protein activation is spatially controlled through targeted localization of regulatory cofactors, with the activated motor then participating in building its own transport infrastructure through ncMTOC recruitment and microtubule network organization.

There's a lot to like about this paper! The data are generally lovely and nicely presented. The authors also use a combination of experimental approaches, combining genetics, live and fixed imaging, and protein biochemistry.

Concerns:

Page 6: "to assay if elevation of Ninein levels was able to mis-regulate Ens localization, we overexpressed a tagged Ninein-RFP protein in the oocyte. At stage 9 the overexpressed Ninein accumulated at the anterior cortex of the oocyte and also generated large cortical aggregates able to recruit high levels of Ens (Figures 2D and 2H)... The examination of Ninein/Ens cortical aggregates obtained after Ninein overexpression showed that these aggregates were also able to recruit high levels of Patronin and Shot (Figures 2E and 2H)." Firstly, I'm not crazy about the use of "overexpressed" here, since there isn't normally any Ninein-RFP in the oocyte. In these experiments it has been therefore expressed, not overexpressed. Secondly, I don't understand what the reader is supposed to make of these data. Expression of a protein carrying a large fluorescent tag leads to large aggregates (they don't look cortical to me) that include multiple proteins - in fact, all the proteins examined. I don't understand this to be evidence of anything in particular, except that Ninein-RFP causes the accumulation of big multi-protein aggregates. While I can understand what the authors were trying to do here, I think that these data are inconclusive and should be de-emphasized.

Page 7: "Co-immunoprecipitations experiments revealed that Patronin was associated with Shot-YFP, as shown previously (Nashchekin et al., 2016), but also with EnsWT-GFP, indicating that Ens, Shot and Patronin are present in the same complex (Figure 3B)." I do not agree that association between Ens-GFP and Patronin indicates that Ens is in the same complex as Shot and Patronin. It is also very possible that there are two (or more) distinct protein complexes. This conclusion could therefore be softened. Instead of "indicating" I suggest "suggesting the possibility."

Page 7: "During stage 9, the average subcortical MT length, taken at one focal plane in live oocytes (see methods)..." I appreciate that the authors have been careful to describe how they measured MT length, as this is a major point for interpretation. I think the reader would benefit from an explanation of why they decided to measure in only one focal plane and how that decision could impact the results.

Page 7: "... the MTs exhibited an orthogonal orientation relative to the anterior cortex (Figures 4A left panels, 4C and 4E)." This phenotype might not be obvious to readers. Can it be quantified?

Page 8: "Altogether, the analyses of Ens and Khc defective oocytes suggested that MT organization defects during late oogenesis (stage 10B) were caused by an initial failure of ncMTOCs to reach the cell cortex. Therefore, we hypothesized that overexpression of the ncMTOC component Shot could restore certain aspects of microtubule cortical organization in ens-deficient oocytes. Indeed, Shot overexpression (Shot OE) was sufficient to rescue the presence of long cortical MTs and ooplasmic advection in most ens oocytes (9/14)..." The data are clear, but the explanation is not. Can the authors please explain why adding in more of an ncMTOC component (Shot) rescues a defect of ncMTOC cortical localization?

I'm grateful to the authors for their inclusion of helpful diagrams, as in Figures 1G and 2H. I think the manuscript might benefit from one more of these at the end, illustrating the ultimate model.

I'm sorry to say that the language could use quite a bit of polishing. There are missing and extraneous commas. There is also regular confusion between the use of plural and singular nouns. Some early instances include:

1. Page 3: thought instead of "thoughted."
2. Page 5: "A previous studies have revealed"
3. Page 5: "A significantly loss"
4. Page 6: "troughs ring canals" should be "through ring canals"
5. Page 7: lives stage 9 oocytes
6. Page 7: As ens and Khc RNAi oocytes exhibits
7. Page 7: we examined in details
8. Page 7: This average MT length was similar in Khc RNAi and ens mutant oocyte..

Significance

This work makes a nice conceptual advance by showing that motor activation controls its own transport infrastructure, a paradigm that could extend to other systems requiring spatially regulated transport.

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

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Referee #3

Evidence, reproducibility and clarity

The manuscript of Berisha et al., investigates the role of Esconsin (Ens), Kinesin-1 and Ninein in organisation of microtubules (MT) in Drosophila oocyte. At stage 9 oocytes Kinesin-1 transports oskar mRNA, a posterior determinant, along MT that are organised by ncMTOCs. At stage 10b, Kinesin-1 induces cytoplasmic advection to mix the contents of the oocyte. Ensconsin/Map7 is a MT associated protein (MAP) that uses its MT-binding domain (MBD) and kinesin binding domain (KBD) to recruit Kinesin-1 to the microtubules and to stimulate the motility of MT-bound Kinesin-1. Using various new Ens transgenes, the authors demonstrate the requirement of Ens MBD and Ninein in Ens localisation to the oocyte where Ens activates Kinesin-1 using its KBD. The authors also claim that Ens, Kinesin-1 and Ninein are required for the accumulation of ncMTOCs at the oocyte cortex and argue that the detachment of the ncMTOCs from the cortex accounts for the reduced localisation of oskar mRNA at stage 9 and the lack of cytoplasmic streaming at stage 10b.

Although the manuscript contains several interesting observations, the authors' conclusions are not sufficiently supported by their data. The structure function analysis of Ensconsin (Ens) is potentially publishable, but the conclusions on ncMTOC anchoring and cytoplasmic streaming not convincing

1. The main conclusion of the manuscript is that "MT advection failure in Khc and ens in late oogenesis stems from defective cortical ncMTOCs recruitment". This completely overlooks the abundant evidence that Kinesin-1 directly drives cytoplasmic streaming by transporting vesicles and microtubules along microtubules, which then move the cytoplasm by advection (Palacios et al., 2002; Serbus et al, 2005; Lu et al, 2016). Since Kinesin-1 generates the flows, one cannot conclude that the effect of khc and ens mutants on cortical ncMTOC positioning has any direct effect on these flows, which do not occur in these mutants.
2. The authors claim that streaming phenotypes of ens and khs mutants are due to a decrease in microtubule length caused by the defective localisation of ncMTOCs. In addition to the problem raised above, However, I am not convinced that they can make accurate measurements of microtubule length from confocal images like those shown in Figure 4. Firstly, they are measuring the length of bundles of microtubules and cannot resolve individual microtubules. This problem is compounded by the fact that the microtubules do not align into parallel bundles in the mutants. This will make the "microtubules" appear shorter in the mutants. In addition, the alignment of the microtubules in wild-type allows one to choose images in which the microtubule lie in the imaging plane, whereas the more disorganised arrangement of the microtubules in the mutants means that most microtubules will cross the imaging plane, which precludes accurate measurements of their length.
3. "To investigate whether the presence of these short microtubules in ens and Khc RNAi oocytes is due to defects in microtubule anchoring or is also associated with a decrease in microtubule polymerization at their plus ends, we quantified the velocity and number of EB1comets, which label growing microtubule plus ends (Figure S3)." I do not understand how the anchoring or not of microtubule minus ends to the cortex determines how far their plus ends grow, and these measurements fall short of showing that plus end growth is unaffected. It has already been shown that the Kinesin-1-dependent transport of Dynactin to growing microtubule plus ends increases the length of microtubules in the oocyte because Dynactin acts as an anti-catastrophe factor at the plus ends. Thus, khc mutants should have shorter microtubules independently of any effects on ncMTOC anchoring. The measurements of EB1 comet speed and frequency in FigS2 will not detect this change and are not relevant for their claims about microtubule length. Furthermore, the authors measured EB1 comets at stage 9 (where they did not observe short MT) rather than at stage 10b. The authors' argument would be better supported if they performed the measurements at stage 10b.
4. The Shot overexpression experiments presented in Fig.3 E-F, Fig.4D and TableS1 are very confusing. Originally , the authors used Shot-GFP overexpression at stage 9 to show that there is a decrease of ncMTOCs at the cortex in ens mutants (Fig.3 E-F) and speculated that this caused the defects in MT length and cytoplasmic advection at stage 10B. However the authors later state on page 8 that : "Shot overexpression (Shot OE) was sufficient to rescue the presence of long cortical MTs and ooplasmic advection in most ens oocytes (9/14), resembling the patterns observed in controls (Figures 4B right panel and 4D). Moreover, while ens females were fully sterile, overexpression of Shot was sufficient to restore that loss of fertility (Table S1)". Is this the same UAS Shot-GFP and VP16 Gal4 used in both experiments? If so, this contradictions puts the authors conclusions in question.
5. The authors based they conclusions about the involvement of Ens, Kinesin-1 and Ninein in ncMTOC anchoring on the decrease in cortical fluorescence intensity of Shot-YFP and Patronin-YFP in the corresponding mutant backgrounds. However, there is a large variation in average Shot-YFP intensity between control oocytes in different experiments. In Fig. 2F-G the average level of Shot-YFP in the control sis 130 AU while in Fig.3 G-H it is only 55 AU. This makes me worry about reliability of such measurements and the conclusions drawn from them.
6. The decrease in the intensity of Shot-YFP and Patronin-YFP cortical fluorescence in ens mutant oocytes could be because of problems with ncMTOC anchoring or with ncMTOCsformation. The authors should find a way to distinguish between these two possibilities. The authors could express Ens-Mut (described in Sung et al 2008), which localises at the oocyte posterior and test whether it recruits Shot/Patronin ncMTOCs to the posterior.
7. According to the Materials and Methods, the Shot-GFP used in Fig.3 E-F and Fig.4 was the BDSC line 29042. This is Shot L(C), a full-length version of Shot missing the CH1 actin-binding domain that is crucial for Shot anchoring to the cortex. If the authors indeed used this version of Shot-GFP, the interpretation of the above experiments is very difficult.
8. Page 6 "converted in NCs, in a region adjacent to the ring canals, Dendra-Ens-labeled MTs were found in the oocyte compartment indicating they are able to travel from NC toward the oocyte trough ring canals". I have difficulty seeing the translocation of MT through the ring canals. Perhaps it would be more obvious with a movie/picture showing only one channel. Considering that f Dendra-Ens appears in the oocyte much faster than MT transport through ring canals (140nm/s, Lu et al 2022) , the authors are most probably observing the translocation of free Ens rather than Ens bound to MT. The authors should also mention that Ens movement from the NC to the oocyte has been shown before with Ens MBD in Lu et al 2022 with better resolution.
9. Page 6: The co-localization of Ninein with Ens and Shot at the oocyte cortex (Figure 2A). I have difficulty seeing this co-localisation. Perhaps it would be more obvious in merged images of only two channels and with higher resolution images
10. "a pool of the Ens-GFP co-localized with Ch-Patronin at cortical ncMTOCs at the anterior cortex (Figure 3A)". I also have difficulty seeing this.
11. "Ninein co-localizes with Ens at the oocyte cortex and partially along cortical microtubules, contributing to the maintenance of high Ens protein levels in the oocyte and its proper cortical targeting". I could not find any data showing the involvement of Ninein in the cortical targeting of Ens.
12. "our MT network analyses reveal the presence of numerous short MTs cytoplasmic clustered in an anterior pattern." "This low cortical recruitment of ncMTOCs is consistent with poor MT anchoring and their cytoplasmic accumulation." I could not find any data showing that short cortical MT observed at stage 10b in ens mutant and Khc RNAi were cytoplasmic and poorly anchored.
13. "The egg chamber consists of interconnected cells where Dynein and Khc activities are spatially separated. Dynein facilitates transport from NCs to the oocyte, while Khc mediates both transport and advection within the oocyte." Dynein is involved in various activities in the oocyte. It anchors the oocyte nucleus and transports bcd and grk mRNA to mention a few.
14. The cartoons in Fig.2H and 3I exaggerate the effect of Ninein and Ens on cortical ncMTOCs. According to the corresponding graphs, there is a 20 and 50% decrease in each case.

Significance

Given the important concerns raised, the significance of the findings is difficult to assess at this stage.

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Referee #2

Evidence, reproducibility and clarity

In this manuscript, Berisha et al. investigate how microtubule (MT) organization is spatially regulated during Drosophila oogenesis. The authors identify a mechanism in which the Kinesin-1 activator Ensconsin/MAP7 is transported by dynein and anchored at the oocyte cortex via Ninein, enabling localized activation of Kinesin-1. Disruption of this pathway impairs ncMTOC recruitment and MT anchoring at the cortex. The authors combine genetic manipulation with high-resolution microscopy and use three key readouts to assess MT organization during mid-to-late oogenesis: cortical MT formation, localization of posterior determinants, and ooplasmic streaming. Notably, Kinesin-1, in concert with its activator Ens/MAP7, contributes to organizing the microtubule network it travels along. Overall, the study presents interesting findings, though we have several concerns we would like the authors to address.

Ensconsin enrichment in the oocyte

1. Enrichment in the oocyte
   • Ensconsin is a MAP that binds MTs. Given that microtubule density in the oocyte significantly exceeds that in the nurse cells, its enrichment may passively reflect this difference. To assess whether the enrichment is specific, could the authors express a non-Drosophila MAP (e.g., mammalian MAP1B) to determine whether it also preferentially localizes to the oocyte?
   • The ability of ens-wt and ens-LowMT to induce tubulin polymerization according to the light scattering data (Fig. S1J) is minimal and does not reflect dramatic differences in localization. The authors should verify that, in all cases, the polymerization product in their in vitro assays is microtubules rather than other light-scattering aggregates. What is the control in these experiments? If it is just purified tubulin, it should not form polymers at physiological concentrations.
2. Photoconversion caveats MAPs are known to dynamically associate and dissociate from microtubules. Therefore, interpretation of the Ens photoconversion data should be made with caution. The expanding red signal from the nurse cells to the oocyte may reflect a any combination of dynein-mediated MT transport and passive diffusion of unbound Ensconsin. Notably, photoconversion of a soluble protein in the nurse cells would also result in a gradual increase in red signal in the oocyte, independent of active transport. We encourage the authors to more thoroughly discuss these caveats. It may also help to present the green and red channels side by side rather than as merged images, to allow readers to assess signal movement and spatial patterns better.
3. Reduction of Shot at the anterior cortex
   • Shot is known to bind strongly to F-actin, and in the Drosophila ovary, its localization typically correlates more closely with F-actin structures than with microtubules, despite being an MT-actin crosslinker. Therefore, the observed reduction of cortical Shot in ens, nin mutants, and Khc-RNAi oocytes is unexpected. It would be important to determine whether cortical F-actin is also disrupted in these conditions, which should be straightforward to assess via phalloidin staining.
   • MTs are barely visible in Fig. 3A, which is meant to demonstrate Ens-GFP colocalization with tubulin. Higher-quality images are needed.
4. MT gradient in stage 9 oocytes In ens-/-, nin-/-, and Khc-RNAi oocytes, is there any global defect in the stage 9 microtubule gradient? This information would help clarify the extent to which cortical localization defects reflect broader disruptions in microtubule polarity.
5. Role of Ninein in cortical anchoring The requirement for Ninein in cortical anchorage is the least convincing aspect of the manuscript and somewhat disrupts the narrative flow. First, it is unclear whether Ninein exhibits the same oocyte-enriched localization pattern as Ensconsin. Is Ninein detectable in nurse cells? Second, the Ninein antibody signal appears concentrated in a small area of the anterior-lateral oocyte cortex (Fig. 2A), yet Ninein loss leads to reduced Shot signal along a much larger portion of the anterior cortex (Fig. 2F)-a spatial mismatch that weakens the proposed functional relationship. Third, Ninein overexpression results in cortical aggregates that co-localize with Shot, Patronin, and Ensconsin. Are these aggregates functional ncMTOCs? Do microtubules emanate from these foci?
6. Inconsistency of Khc^MutEns rescue The Khc^MutEns variant partially rescues cortical MT formation and restores a slow but measurable cytoplasmic flow yet it fails to rescue Staufen localization (Fig. 5). This raises questions about the consistency and completeness of the rescue. Could the authors clarify this discrepancy or propose a mechanistic rationale?

Minor points:

1. The pUbi-attB-Khc-GFP vector was used to generate the Khc^MutEns transgenic line, presumably under control of the ubiquitous ubi promoter. Could the authors specify which attP landing site was used? Additionally, are the transgenic flies viable and fertile, given that Kinesin-1 is hyperactive in this construct?
2. On page 11 (Discussion, section titled "A dual Ensconsin oocyte enrichment mechanism achieves spatial relief of Khc inhibition"), the statement "many mutations in Kif5A are causal of human diseases" would benefit from a brief clarification. Since not all readers may be familiar with kinesin gene nomenclature, please indicate that KIF5A is one of the three human homologs of Kinesin heavy chain.
3. On page 16 (Materials and Methods, "Immunofluorescence in fly ovaries"), the sentence "Ovaries were mounted on a slide with ProlonGold medium with DAPI (Invitrogen)" should be corrected to "ProLong Gold."

Significance

This study shows that enrichment of MAP7/ensconsin in the oocyte is the mechanism of kinesin-1 activation there and is important for cytoplasmic streaming and localization non-centrosomal microtubule-organizing centers to the oocyte cortex

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Referee #1

Evidence, reproducibility and clarity

This paper addresses a very interesting problem of non-centrosomal microtubule organization in developing Drosophila oocytes. Using genetics and imaging experiments, the authors reveal an interplay between the activity of kinesin-1, together with its essential cofactor Ensconsin, and microtubule organization at the cell cortex by the spectraplakin Shot, minus-end binding protein Patronin and Ninein, a protein implicated in microtubule minus end anchoring. The authors demonstrate that the loss of Ensconsin affects the cortical accumulation non-centrosomal microtubule organizing center (ncMTOC) proteins, microtubule length and vesicle motility in the oocyte, and show that this phenotype can be rescued by constitutively active kinesin-1 mutant, but not by Ensconsin mutants deficient in microtubule or kinesin binding. The functional connection between Ensconsin, kinesin-1 and ncMTOCs is further supported by a rescue experiment with Shot overexpression. Genetics and imaging experiments further implicate Ninein in the same pathway. These data are a clear strength of the paper; they represent a very interesting and useful addition to the field.

The weaknesses of the study are two-fold. First, the paper seems to lack a clear molecular model, uniting the observed phenomenology with the molecular functions of the studied proteins. Most importantly, it is not clear how kinesin-based plus-end directed transport contributes to cortical localization of ncMTOCs and regulation of microtubule length.

Second, not all conclusions and interpretations in the paper are supported by the presented data. Below is a list of specific comments, outlining the concerns, in the order of appearance in the paper/figures.

1. Figure 1. The statement: "Ens loading on MTs in NCs and their subsequent transport by Dynein toward ring canals promotes the spatial enrichment of the Khc activator Ens in the oocyte" is not supported by data. The authors do not demonstrate that Ens is actually transported from the nurse cells to the oocyte while being attached to microtubules. They do show that the intensity of Ensconsin correlates with the intensity of microtubules, that the distribution of Ensconsin depends on its affinity to microtubules and that an Ensconsin pool locally photoactivated in a nurse cell can redistribute to the oocyte (and throughout the nurse cell) by what seems to be diffusion. The provided images suggest that Ensconsin passively diffuses into the oocyte and accumulates there because of higher microtubule density, which depends on dynein. To prove that Ensconsin is indeed transported by dynein in the microtubule-bound form, one would need to measure the residence time of Ensconsin on microtubules and demonstrate that it is longer than the time needed to transport microtubules by dynein into the oocyte; ideally, one would like to see movement of individual microtubules labelled with photoconverted Ensconsin from a nurse cell into the oocyte. Since microtubules are not enriched in the oocyte of the dynein mutant, analysis of Ensconsin intensity in this mutant is not informative and does not reveal the mechanism of Ensconsin accumulation.
2. Figure 2. According to the abstract, this figure shows that Ensconsin is "maintained at the oocyte cortex by Ninein". However, the figure doesn't seem to prove it - it shows that oocyte enrichment of Ensonsin is partially dependent on Ninein, but this applies to the whole cell and not just to the cell cortex. Furthermore, it is not clear whether Ninein mutation affects microtubule density, which in turn would affect Ensconsin enrichment, and therefore, it is not clear whether the effect of Ninein loss on Ensconsin distribution is direct or indirect. The observation that the aggregates formed by overexpressed Ninein accumulate other proteins, including Ensconsin, supports, though does not prove their interactions. Furthermore, there is absolutely no proof that Ninein aggregates are "ncMTOCs". Unless the authors demonstrate that these aggregates nucleate or anchor microtubules (for example, by detailed imaging of microtubules and EB1 comets), the text and labels in the figure would need to be altered.

Minor comment: Note that a "ratio" (Figure 2C) is just a ratio, and should not be expressed in arbitrary units. 3. Figure 3B: immunoprecipitation results cannot be interpreted because the immunoprecipitated proteins (GFP, Ens-GFP, Shot-YFP) are not shown. It is also not clear that this biochemical experiment is useful. If the authors would like to suggest that Ensconsin directly binds to Patronin, the interaction would need to be properly mapped at the protein domain level. 4. One of the major phenotypes observed by the authors in Ens mutant is the loss of long microtubules. The authors make strong conclusions about the independence of this phenotype from the parameters of microtubule plus-end growth, but in fact, the quality of their data does not allow to make such a conclusion, because they only measured the number of EB1 comets and their growth rate but not the catastrophe, rescue or pausing frequency. Note that kinesin-1 has been implicated in promoting microtubule damage and rescue (doi: 10.1016/j.devcel.2021). In the absence of such measurements, one cannot conclude whether short microtubules arise through defects in the minus-end, plus-end or microtubule shaft regulation pathways. It is important to note in that a spectraplakin, like Shot, can potentially affect different pathways, particularly when overexpressed. Unjustified conclusions should be removed: the authors do not provide sufficient data to conclude that "ens and Khc oocytes MT organizational defects are caused by decreased ncMTOC cortical anchoring", because the actual cortical microtubule anchoring was not measured.

Minor comment: Microtubule growth velocity must be expressed in units of length per time, to enable evaluating the quality of the data, and not as a normalized value. 5. A significant part of the Discussion is dedicated to the potential role of Ensconsin in cortical microtubule anchoring and potential transport of ncMTOCs by kinesin. It is obviously fine that the authors discuss different theories, but it would be very helpful if the authors would first state what has been directly measured and established by their data, and what are the putative, currently speculative explanations of these data.

Minor comment: The writing and particularly the grammar need to be significantly improved throughout, which should be very easy with current language tools. Examples: "ncMTOCs recruitment" should be "ncMTOC recruitment"; "Vesicles speed" should be "Vesicle speed", "Nin oocytes harbored a WT growth,"- unclear what this means, etc. Many paragraphs are very long and difficult to read. Making shorter paragraphs would make the authors' line of thought more accessible to the reader.

Significance

This paper represents significant advance in understanding non-centrosomal microtubule organization in general and in developing Drosophila oocytes in particular by connecting the microtubule minus-end regulation pathway to the Kinesin-1 and Ensconsin/MAP7-dependent transport. The genetics and imaging data are of good quality, are appropriately presented and quantified. These are clear strengths of the study which will make it interesting to researchers studying the cytoskeleton, microtubule-associated proteins and motors, and fly development.

The weaknesses of this study are due to the lack of clarity of the overall molecular model, which would limit the impact of the study on the field. Some interpretations are not sufficiently supported by data, but this can be solved by more precise and careful writing, without extensive additional experimentation.

My expertise is cell biology and biochemistry of the microtubule cytoskeleton, including both microtubule-associated proteins and microtubule motors.

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Reply to the reviewers

Revision Plan

Manuscript number: RC-2025-03208

Corresponding author(s): Jared Nordman

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1. General Statements [optional]

All three reviewers of our manuscript were very positive about our work. The reviewers noted that our work represents a necessary advance that is timely, addresses important issues in the chromatin field, and will of broad interest to this community. Given the nature of our work and the positive reviews, we feel that this manuscript would best be suited for the Journal of Cell Biology.

2. Description of the planned revisions

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

Summary:

The authors investigate the function of the H3 chaperone NASP, which is known to bind directly to H3 and prevent degradation of soluble H3. What is unclear is where NASP functions in the cell (nucleus or cytoplasm), how NASP protects H3 from degradation (direct or indirect), and if NASP affects H3 dynamics (nuclear import or export). They use the powerful model system of Drosophila embryos because the soluble H3 pool is high due to maternal deposition and they make use of photoconvertable Dendra-tagged proteins, since these are maternally deposited and can be used to measure nuclear import/export rates.

Using these systems and tools, they conclude that NASP affects nuclear import, but only indirectly, because embryos from NASP mutant mothers start out with 50% of the maternally deposited H3. Because of the depleted H3 and reduced import rates, NASP deficient embryos also have reduced nucleoplasmic and chromatin-associated H3. Using a new Dendra-tagged NASP allele, the authors show that NASP and H3 have different nuclear import rates, indicating that NASP is not a chaperone that shuttles H3 into the nucleus. They test H3 levels in embryos that have no nuclei and conclude that NASP functions in the cytoplasm, and through protein aggregation assays they conclude that NASP prevents H3 aggregation.

Major comments:

The text was easy to read and logical. The data are well presented, methods are complete, and statistics are robust. The conclusions are largely reasonable. However, I am having trouble connecting the conclusions in text to the data presented in Figure 4.

First, I'm confused why the conclusion from Figure 4A is that NASP functions in the cytoplasm of the egg. Couldn't NASP be required in the ovary (in, say, nurse cell nuclei) to stimulate H3 expression and deposition into the egg? The results in 4A would look the same if the mothers deposit 50% of the normal H3 into the egg. Why is NASP functioning specifically in the cytoplasm when it is also so clearly imported into the nucleus? Maybe NASP functions wherever it is, and by preventing nuclear import, you force it to function in the cytoplasm. I do not have additional suggestions for experiments, but I think the authors need to be very clear about the different interpretations of these data and to discuss WHY they believe their conclusion is strongest.

The concern raised by the reviewer regarding NASP function during oogenesis has been addressed in a previous work published from our lab. Unfortunately, we did not do a good job conveying this work in the original version of this manuscript. We demonstrated that total H3 levels are unaffected when comparing WT and NASP mutant stage 14 egg chambers. This means that the amount of H3 deposited into the eggs does not change in the absence of NASP. To address the reviewer's comment, we will change the text to make the link to our previous work clear.

Second, an alternate conclusion from Figure 4D/E is that mothers are depositing less H3 protein into the egg, but the same total amount is being aggregated. This amount of aggregated protein remains constant in activated eggs, but additional H3 translation leads to more total H3? The authors mention that additional translation can compensate for reduced histone pools (line 416).

Similar to our response above, the total amount of H3 in wild type and NASP mutant stage 14 egg chambers is the same. Therefore, mothers are depositing equal amounts of H3 into the egg. We will make the necessary changes in the text to make this point clear.

As the function of NASP in the cytoplasm (when it clearly imports into the nucleus) and role in H3 aggregation are major conclusions of the work, the authors need to present alternative conclusions in the text or complete additional experiments to support the claims. Again, I do not have additional suggestions for experiments, but I think the authors need to be very clear about the different interpretations of these data and to discuss WHY they believe their conclusion is strongest.

A common issue raised by all three reviewers was to more convincingly demonstrate that assay that we have used to isolate protein aggregates does, in fact, isolate protein aggregates. To verify this, we will be performing the aggregate isolation assay using controls that are known to induce more protein aggregation. We will perform the aggregation assay with egg chambers or extracts that are exposed to heat shock or the aggregation-inducing chemicals Canavanine and Azetidine-2-carboxylic acid. The chemical treatment was a welcome suggestion from reviewer #3. These experiments will significantly strengthen any claims based on the outcome of the aggregation assay.

We will also make changes to the text and include other interpretations of our work as the reviewer has suggested.

Data presentation:

Overall, I suggest moving some of the supplemental figures to the main text, adding representative movie stills to show where the quantitative data originated, and moving the H3.3 data to the supplement. Not because it's not interesting, but because H3.3 and H3.2 are behaving the same.

Where possible, we will make changes to the figure display to improve the logic and flow of the manuscript

Fig 1:

It would strengthen the figure to include representative still images that led to the quantitative data, mostly so readers understand how the data were collected.

We will add representative stills to Figure 1 to help readers understand how the data is collected. We will also a representative H3-Dendra movie similar to the NASP supplemental movie.

The inclusion of a "simulated 50% H3" in panel C is confusing. Why?

We used a 50% reduction in H3 levels because that is reduction in H3 we measure in embryos laid by NASP-mutant mothers in our previous work. A reduction in H3 levels alone would be predicted to change the nuclear import rate of H3. Thus, having a quantitative model of H3 import kinetics was key in our understanding of NASP function in vivo. We will revise the text to make this clear.

I would also consider normalizing the data between A and B (and C and D) by dividing NASP/WT. This could be included in the supplement (OPTIONAL)

We can normalize the values and include the data in a supplemental figure.

Fig S1:

The data simulation S1G should be moved to the main text, since it is the primary reason the authors reject the hypothesis that NASP influences H3 import rates.

This is a good point. We will move S1G into the Figure 1.

Fig 2:

Once again, I think it would help to include a few representative images of the photoconverted Dendra2 in the main text.

We will add representative images of the photoconversion in Figure 2.

I struggled with A/B, I think due to not knowing how the data were normalized. When I realized that the WT and NASP data are not normalized to each other, but that the NASP values are likely starting less than the WT values, it made way more sense. I suggest switching the order of data presentation so that C-F are presented first to establish that there is less chromatin-bound H3 in the first place, and then present A/B to show no change in nuclear export of the H3 that is present, allowing the conclusion of both less soluble AND chromatin-bound H3.

The order of the presentation of the data was to test if NASP was acting as a nuclear receptor. Since Figure 1 compares the nuclear import, we wanted to address the nuclear export and provide a comprehensive analysis of the role of NASP in H3 nuclear dynamics before advancing on to other consequences of NASP depletion. We can add the graphs with the un-normalized values in the Supplemental Figure to show the actual difference in total intensity values.

Fig S2:

If M1-M3 indicate males, why are the ovaries also derived from males? I think this is just confusing labeling.

We will change the labelling.

Supplemental Movie S1:

Beautiful. Would help to add a time stamp (OPTIONAL).

Thank you! We will add the time stamp to the movie

Fig 3:

Panel C is the same as Fig S1A (not Fig 1A, as is said in the legend), though I appreciate the authors pointing it out in the legend. Also see line 276.

We appreciate the reviewer for pointing this out. We will make the change in the text to correct this.

Panel D is a little confusing, because presumably the "% decrease in import rate" cannot be positive (Y axis). This could be displayed as a scatter (not bar) as in Panels B/C (right) where the top of the Y axis is set to 0.

We understand the reviewer's concern that the decrease value cannot be positive. We can adjust the y-axis so that it caps off at 0.

Fig S3:

A: What do the different panels represent? I originally thought developmental time, but now I think just different representative images? Are these age-matched from time at egg lay?

The different panels show representative images. We can clarify that in the figure legend.

C: What does "embryos" mean? Same question for Fig 4A.

In this figure, embryos mean the exact number of embryos used to form the lysate for the western blot. We will clarify this in the figure legend.

Fig 4:

A: What does "embryos" mean? Number of embryos? Age in hours?

In this figure, embryos mean the exact number of embryos used to form the lysate for the western blot. We will clarify this in the figure legend.

C: Not sure the workflow figure panel is necessary, as I can't tell what each step does. This is better explained in methods. However I appreciated the short explanation in the text (lines 314-5).

The workflow panel helps to identify the samples labelled as input and aggregate for the western blot analysis. Since our input in the western blots does not refer to the total protein lysate, we feel it is helpful to point out exactly what stage at the protocol we are utilizing the sample for our analysis.

Minor comments:

The authors should describe the nature of the NASP alleles in the main text and present evidence of robust NASP depletion, potentially both in ovaries and in embryos. The antibody works well for westerns (Fig S2B). This is sort of demonstrated later in Figure 4A, but only in NAAP x twine activated eggs.

We appreciate the reviewer's comments about the NASP mutant allele. In our previous publication, we characterized the NASP mutant fly line and its effect on both stage 14 egg chambers and the embryos. We will emphasize the reference to our previous work in the text.

Lines 163, 251, 339: minor typos

Line 184: It would help to clarify- I'm assuming cytoplasmic concentration (or overall) rather than nuclear concentration. If nuclear, I'd expect the opposite relationship. This occurs again when discussing NASP (line 267). I suspect it's also not absolute concentration, but relative concentration difference between cytoplasm and nucleus. It would help clarify if the authors were more precise.

We appreciate the reviewer's point and will add the clarification in the text.

Line 189: Given that the "established integrative model" helps to reject the hypothesis that NASP is involved in H3 import, I think it's important to describe the model a little more, even though it's previously published.

We will add few sentences giving a brief description of the model to the text.

Line 203: "The measured rate of H3.2 export from the nucleus is negligible" clarify this is in WT situations and not a conclusion from this study.

We will add the clarification of this statement in the text.

Line 211: How can the authors be so sure that the decrease in WT is due to "the loss of non-chromatin bound nucleoplasmic H3.2-Dendra2?"

From the live imaging experiments, the H3.2-Dendra2 intensity in the nucleus reduces dramatically upon nuclear envelope breakdown with the only H3.2-Dendra2 intensity remaining being the chromatin bound H3.2. Excess H3.2 is imported into the nucleus and not all of it is incorporated into the chromatin. This is a unique feature of the embryo system that has been observed previously. We mention that the intensity reduction is due to the loss of non-chromatin bound nucleoplasmic H3.2.

Line 217: In the conclusion, the authors indicate that NASP indirectly affects soluble supply of H3 in the nucleoplasm. I do believe they've shown that the import rate effect is indirect, but I don't know why they conclude that the effect of NASP on the soluble nucleoplasmic H3 supply is indirect. Similarly, the conclusion is indirect on line 239. Yet, the authors have not shown it's not direct, just assumed since NASP results in 50% decrease to deposited maternal histones.

We appreciate the feedback on the conclusions of Figure 2 from the reviewer. Our conclusions are primarily based on the effect of H3 levels in the absence of NASP in the early embryos. To establish direct causal effects, it would be important to recover the phenotypes by complementation experiments and providing molecular interactions to cause the effects. In this study we have not established those specific details to make conclusions of direct effects. We will change the text to make this more clear.

Line 292: What is the nature of the NASP "mutant?" Is it a null? Similarly, what kind of "mutant" is the twine allele? Line 295.

We will include descriptions of the NASP and twine mutants in the text.

Line 316: Why did the authors use stage 14 egg chambers here when they previously used embryos? This becomes more clear later shortly, when the authors examine activated eggs, but it's confusing in text.

The reason to use stage 14 egg chambers was to establish NASP function during oogenesis. We will modify the text to emphasize the reason behind using stage 14 egg chambers.

Lines 343-348: It's unclear if the authors are drawing extended conclusions here or if they are drawing from prior literature (if so, citations would be required). For example, why during oogenesis/embryogenesis are aggregation and degradation developmentally separated?

This conclusion is based primarily based on the findings from this study (Figure 4) and out previous published work. We will modify the text for more clarity.

Lines 386-7: I do not understand why the authors conclude that H3 aggregation and degradation are "developmentally uncoupled" and why, in the absence of NASP, "H3 aggregation precedes degradation."

This is based data in Figure 4 combined with our previous working showing that the total level of H3 in not changed in NASP-mutant stage 14 egg chambers. Aggregates seem to be more persistent in the stage 14 egg chambers (oogenesis) and they get cleared out upon egg activation (entry into embryogenesis). This provides evidence for aggregation occurring prior to degradation and these two events occurring in different developmental stages. We will change the text to make this more clear.

Line 395: Why suddenly propose that NASP also functions in the nucleus to prevent aggregation, when earlier the authors suggest it functions only in the cytoplasm?

We will make the necessary edits to ensure that the results don't suggest a role of NASP exclusive to the cytoplasm. Our findings highlight a cytoplasmic function of NASP, however, we do not want to rule out that this same function couldn't occur in the nucleus.

Lines 409-413: The authors claim that histone deficiency likely does not cause the embryonic arrest seen in embryos from NASP mutant mothers. This is because H3 is reduced by 50% yet some embryos arrest long before they've depleted this supply. However, the authors also showed that H3 import rates are affected in these embryos due to lower H3 concentration. Since the early embryo cycles are so rapid, reduced H3 import rates could lead to early arrest, even though available H3 remains in the cytoplasm.

We thank the reviewer for their suggestion. This conclusion is based on the findings from the previous study from our lab which showed that the majority of the embryos laid by NASP mutant females get arrested in the very early nuclear cycles (Reviewer #1 (Significance (Required)):

The significance of the work is conceptual, as NASP is known to function in H3 availability but the precise mechanism is elusive. This work represents a necessary advance, especially to show that NASP does not affect H3 import rates, nor does it chaperone H3 into the nucleus. However, the authors acknowledge that many questions remain. Foremost, why is NASP imported into the nucleus and what is its role there?

I believe this work will be of interest to those who focus on early animal development, but NASP may also represent a tool, as the authors conclude in their discussion, to reduce histone levels during development and examine nucleosome positioning. This may be of interest to those who work on chromatin accessibility and zygotic genome activation.

I am a genetics expert who works in Drosophila embryogenesis. I do not have the expertise to evaluate the aggregate methods presented in Figure 4.

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

Summary:

This manuscript focuses on the role of the histone chaperone NASP in Drosophila. NASP is a chaperone specific to histone H3 that is conserved in mammals. Many aspects of the molecular mechanisms by which NASP selectively binds histone H3 have been revealed through biochemical studies. However, key aspects of NASP's in vivo roles remain unclear, including where in the cell NASP functions, and how it prevents H3 degradation. Through live imaging in the early Drosophila embryo, which possesses large amounts of soluble H3 protein, Das et al determine that NASP does not control nuclear import or export of H3.2 or H3.3. Instead, they find through differential centrifugation analysis that NASP functions in the cytoplasm to prevent H3 aggregation and hence its subsequent degradation.

Major Comments:

The protein aggregation assays raise several questions. From a technical standpoint, it would be helpful to have a positive control to demonstrate that the assay is effective at detecting protein aggregates. Ie. a genotype that exhibits increased protein aggregation; this could be for a protein besides H3. A common issue raised by all three reviewers was to more convincingly demonstrate that assay that we have used to isolate protein aggregates does, in fact, isolate protein aggregates. To verify this, we will be performing the aggregate isolation assay using controls that are known to induce more protein aggregation. We will perform the aggregation assay with egg chambers or extracts that are exposed to heat shock or the aggregation-inducing chemicals Canavanine and Azetidine-2-carboxylic acid. The chemical treatment was a welcome suggestion from reviewer #3. These experiments will significantly strengthen any claims based on the outcome of the aggregation assay.

If NASP is not required to prevent H3 degradation in egg chambers, then why are H3 levels much lower in NASP input lanes relative to wild-type egg chambers in Fig 4D? We appreciate the reviewer's inputs regarding the reduced H3 levels in the NASP mutant egg chambers. We observe this reduction in H3 levels in the input because of the altered solubility of H3 which leads to the loss of H3 protein at different steps of the aggregate isolation assay. We will add a supplement figure showing H3 levels at different steps of the aggregate isolation assay. We do want to stress, however, that the total levels of H3 in stage 14 egg chambers does not change between WT and the NASP mutant.

A corollary to this is that the increased fraction of H3 in aggregates in NASP mutants seems to be entirely due to the reduction in total H3 levels rather than an increase in aggregated H3. If NASP's role is to prevent aggregation in the cytoplasm, and degradation has not yet begun in egg chambers, then why are aggregated H3 levels not increased in NASP mutants relative to wild-type egg chambers? If the same number of egg chambers were used, shouldn't the total amount of histone be the same in the absence of degradation?

In previously published work, we demonstrated that total H3 levels are unaffected when comparing WT and NASPmutant stage 14 egg chambers. This means that the amount of H3 deposited into the eggs does not change in the absence of NASP. To address the reviewer's comment, we will change the text to make the link to our previous work clear. As stated above, we will add a supplement figure showing H3 levels at different steps of the aggregate isolation assay.

The live imaging studies are well designed, executed, and quantified. They use an established genotype (H3.2-Dendra2) in wild-type and NASP maternal mutants to demonstrate that NASP is not directly involved in nuclear import of H3.2. Decreased import is likely due to reduced H3.2 levels in NASP mutants rather than reduced import rates per se. The same methodology was used to determine that loss of NASP did not affect H3.2 nuclear export. These findings eliminate H3.2 nuclear import/export regulation as possible roles for NASP, which had been previously proposed.

Thank you.

Live imaging also conclusively demonstrates that the levels of H3.2 in the nucleoplasm and in mitotic chromatin are significantly lower in NASP mutants than wild-type nuclei. Despite these lower histone levels, the nuclear cycle duration is only modestly lengthened. The live imagining of NASP-Dendra2 nuclear import conclusively demonstrate that NASP and H3.2 are unlikely to be imported into the nucleus as one complex.

Thank you.

Minor Comments:

Additional details on how the NASP-Dendra2 CRISPR allele was generated should be provided. In addition, additional details on how it was determined that this allele is functional should be provided (e.g. quantitative assays for fertility/embryo viability of NASP-Dendra2 females) We will make these additions to the text.

If statistical tests are used to determine significance, the type of test used should be reported in the figure legends throughout.

We will make the addition of the statistical tests to the figure legends.

The western blot shown in Figure 4A looks more like a 4-fold reduction in H3 levels in NASP mutants relative to wild-type embryos, rather than the quantified 2-fold reduction. Perhaps a more representative blot can be shown.

We have additional blots in the supplemental figure S3C. The quantification was performed after normalization to the total protein levels and we can highlight that in the figure legend.

Reviewer #2 (Significance (Required)):

As a fly chromatin biologist with colleagues that utilize mammalian experimental systems, I feel this manuscript will be of broad interest to the chromatin research community. Packaging of the genome into chromatin affects nearly every DNA-templated process, making the mechanisms by which histone proteins are expressed, chaperoned, and deposited into chromatin of high importance to the field. The study has multiple strengths, including high-quality quantitative imaging, use of a terrific experimental system (storage and deposition of soluble histones in early fly embryos). The study also answers outstanding questions in the field, specifically that NASP does not control nuclear import/export of histone H3. Instead, the authors propose that NASP functions to prevent protein aggregation. If this could be conclusively demonstrated, it would be valuable to the field. However, the protein aggregation studies need improvement. Technical demonstration that their differential centrifugation assay accurately detects aggregated proteins is needed. Further, NASP mutants do not exhibit increased H3 protein aggregation in the data presented. Instead, the increased fraction of aggregated H3 in NASP mutants seems to be due to a reduction in the overall levels of H3 protein, which is contrary to the model presented in this paper.

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

This manuscript by Das et al. entitled "NASP functions in the cytoplasm to prevent histone H3 aggregation during early embryogenesis", explores the role of the histone chaperone NASP in regulating histone H3 dynamics during early Drosophila embryogenesis. Using primarily live imaging approaches, the authors found that NASP is not directly involved in the import or export of H3. Moreover, the authors claimed that NASP prevents H3 aggregation rather than protects against degradation.

Major Comments:

Figure 1A-B: The plotted data appear to have substantial dispersion. Could the authors include individual data points or provide representative images to help the reader assess variability?

We chose to show unnormalized data in Figure 1 so readers could better compare the actual import values of H3 in the presence and absence of NASP. We felt it was a better representation of the true biological difference although raw data is more dispersive. We did also include normalized data in the supplement. Regardless, we will add representative stills to Figure 1 and include a H3-Dendra2 movie in the supplement to show the representative data.

Given that the authors conclude that the reduced nuclear import is due to lowered H3 levels in NASP-deficient embryos, would overexpression of H3 rescue this phenotype? This would directly test whether H3 levels, rather than import machinery per se, drive the effect.

We thank the reviewer for their valuable suggestion. We and others have tried to overexpress histones in the Drosophila early embryo without success. There must be an undefined feedback mechanism preventing histone overexpression in the germline. In fact, a recent paper has been deposited on bioRxiv (https://doi.org/10.1101/2024.12.23.630206) that suggest H4 protein could provide a feedback mechanism to prevent histone overexpression. While we would love to do this experiment, it is not technically feasible at this time.

Figure 2A-B: The authors present the Relative Intensity of H3-Dendra2, but this metric obscures absolute differences between Control and NASP knockout embryos. Please include Total Intensity plots to show the actual reduction in H3 levels.

We will add the total H3-Dendra2 intensity plots to the supplemental figure for the export curves.

Additionally, Western blot analysis of nucleoplasmic H3 from wild-type vs. NASP-deficient embryos would provide essential biochemical confirmation of H3 level reductions.

We will measure nuclear H3 levels by western from 0-2 hr embryos laid by WT and NASP mutant flies.

Figure 4: To support the conclusion that NASP prevents H3 aggregation, I recommend performing aggregation assays by adding compounds that induce unfolding (amino acid analogues that induce unfolding, like canavanine or Azetidine-2-carboxylic acid) or using aggregation-prone H3 mutants.

This is a very helpful suggestion! It is difficult to get chemicals into Drosophila eggs, but we will treat extracts directly with these chemicals. Additionally, we will use heat shocked eggs and extracts as an additional control.

Inclusion of CMA and proteasome inhibition experiments could also clarify whether degradation pathways are secondarily involved or compensatory in the absence of NASP.

The degradation pathway for H3 in the absence of NASP is unknown and a major focus of our future work is to define this pathway. Drosophila does not have a CMA pathway and therefore, we don't know how H3 aggregates are being sensed.

Minor Comments:

(1) The Introduction would benefit from mentioning the two NASP isoforms that exist in mammals (sNASP and tNASP), as this evolutionary context may inform interpretation of the Drosophila results.

We will make the edits in the text to include that Drosophila NASP is the sole homolog of sNASP and that tNASP ortholog is not found in Drosophila.

(2) Could the authors comment on the status of histone H4 in their experimental system? Given the observed cytoplasmic pool of H3, is it likely to exist as a monomer? If this H3 pool is monomeric, does that suggest an early failure in H3-H4 dimerization, and could this contribute to its aggregation propensity?

In our previous work we noted that NASP binds more preferentially to H3 and the levels of H3 we much more reduced upon NASP depletion than H4. We pointed out in this publication that our data was consistent with H3 stores being monomeric in the Drosophila embryo. We don't' have a H4-Dendra2 line to test. In the future, however, this is something we are very keen to look at.

Reviewer #3 (Significance (Required)):

This work addresses a timely and important question in the field of chromatin biology and developmental epigenetics. The focus on histone homeostasis during embryogenesis and the cytoplasmic role of NASP adds a novel perspective. The live imaging experiments are a clear strength, providing valuable spatiotemporal insights. However, I believe that the manuscript would benefit significantly from additional biochemical validation to support and clarify some of the mechanistic claims.

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

• *

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.

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Referee #3

Evidence, reproducibility and clarity

This manuscript by Das et al. entitled "NASP functions in the cytoplasm to prevent histone H3 aggregation during early embryogenesis", explores the role of the histone chaperone NASP in regulating histone H3 dynamics during early Drosophila embryogenesis. Using primarily live imaging approaches, the authors found that NASP is not directly involved in the import or export of H3. Moreover, the authors claimed that NASP prevents H3 aggregation rather than protects against degradation.

Major Comments:

Figure 1A-B: The plotted data appear to have substantial dispersion. Could the authors include individual data points or provide representative images to help the reader assess variability? Given that the authors conclude that the reduced nuclear import is due to lowered H3 levels in NASP-deficient embryos, would overexpression of H3 rescue this phenotype? This would directly test whether H3 levels, rather than import machinery per se, drive the effect.

Figure 2A-B: The authors present the Relative Intensity of H3-Dendra2, but this metric obscures absolute differences between Control and NASP knockout embryos. Please include Total Intensity plots to show the actual reduction in H3 levels. Additionally, Western blot analysis of nucleoplasmic H3 from wild-type vs. NASP-deficient embryos would provide essential biochemical confirmation of H3 level reductions.

Figure 4: To support the conclusion that NASP prevents H3 aggregation, I recommend performing aggregation assays by adding compounds that induce unfolding (amino acid analogues that induce unfolding, like canavanine or Azetidine-2-carboxylic acid) or using aggregation-prone H3 mutants. Inclusion of CMA and proteasome inhibition experiments could also clarify whether degradation pathways are secondarily involved or compensatory in the absence of NASP.

Minor Comments:

(1) The Introduction would benefit from mentioning the two NASP isoforms that exist in mammals (sNASP and tNASP), as this evolutionary context may inform interpretation of the Drosophila results.

(2) Could the authors comment on the status of histone H4 in their experimental system? Given the observed cytoplasmic pool of H3, is it likely to exist as a monomer? If this H3 pool is monomeric, does that suggest an early failure in H3-H4 dimerization, and could this contribute to its aggregation propensity?

Significance

This work addresses a timely and important question in the field of chromatin biology and developmental epigenetics. The focus on histone homeostasis during embryogenesis and the cytoplasmic role of NASP adds a novel perspective. The live imaging experiments are a clear strength, providing valuable spatiotemporal insights. However, I believe that the manuscript would benefit significantly from additional biochemical validation to support and clarify some of the mechanistic claims.

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:

This manuscript focuses on the role of the histone chaperone NASP in Drosophila. NASP is a chaperone specific to histone H3 that is conserved in mammals. Many aspects of the molecular mechanisms by which NASP selectively binds histone H3 have been revealed through biochemical studies. However, key aspects of NASP's in vivo roles remain unclear, including where in the cell NASP functions, and how it prevents H3 degradation. Through live imaging in the early Drosophila embryo, which possesses large amounts of soluble H3 protein, Das et al determine that NASP does not control nuclear import or export of H3.2 or H3.3. Instead, they find through differential centrifugation analysis that NASP functions in the cytoplasm to prevent H3 aggregation and hence its subsequent degradation.

Major Comments:

1. The protein aggregation assays raise several questions.

a. From a technical standpoint, it would be helpful to have a positive control to demonstrate that the assay is effective at detecting protein aggregates. Ie. a genotype that exhibits increased protein aggregation; this could be for a protein besides H3.

b. If NASP is not required to prevent H3 degradation in egg chambers, then why are H3 levels much lower in NASP input lanes relative to wild-type egg chambers in Fig 4D?

c. A corollary to this is that the increased fraction of H3 in aggregates in NASP mutants seems to be entirely due to the reduction in total H3 levels rather than an increase in aggregated H3. If NASP's role is to prevent aggregation in the cytoplasm, and degradation has not yet begun in egg chambers, then why are aggregated H3 levels not increased in NASP mutants relative to wild-type egg chambers? If the same number of egg chambers were used, shouldn't the total amount of histone be the same in the absence of degradation? 2. The live imaging studies are well designed, executed, and quantified. They use an established genotype (H3.2-Dendra2) in wild-type and NASP maternal mutants to demonstrate that NASP is not directly involved in nuclear import of H3.2. Decreased import is likely due to reduced H3.2 levels in NASP mutants rather than reduced import rates per se. The same methodology was used to determine that loss of NASP did not affect H3.2 nuclear export. These findings eliminate H3.2 nuclear import/export regulation as possible roles for NASP, which had been previously proposed. 3. Live imaging also conclusively demonstrates that the levels of H3.2 in the nucleoplasm and in mitotic chromatin are significantly lower in NASP mutants than wild-type nuclei. Despite these lower histone levels, the nuclear cycle duration is only modestly lengthened. 4. The live imagining of NASP-Dendra2 nuclear import conclusively demonstrate that NASP and H3.2 are unlikely to be imported into the nucleus as one complex.

Minor Comments:

1. Additional details on how the NASP-Dendra2 CRISPR allele was generated should be provided. In addition, additional details on how it was determined that this allele is functional should be provided (e.g. quantitative assays for fertility/embryo viability of NASP-Dendra2 females)
2. If statistical tests are used to determine significance, the type of test used should be reported in the figure legends throughout.
3. The western blot shown in Figure 4A looks more like a 4-fold reduction in H3 levels in NASP mutants relative to wild-type embryos, rather than the quantified 2-fold reduction. Perhaps a more representative blot can be shown.

Significance

As a fly chromatin biologist with colleagues that utilize mammalian experimental systems, I feel this manuscript will be of broad interest to the chromatin research community. Packaging of the genome into chromatin affects nearly every DNA-templated process, making the mechanisms by which histone proteins are expressed, chaperoned, and deposited into chromatin of high importance to the field. The study has multiple strengths, including high-quality quantitative imaging, use of a terrific experimental system (storage and deposition of soluble histones in early fly embryos). The study also answers outstanding questions in the field, specifically that NASP does not control nuclear import/export of histone H3. Instead, the authors propose that NASP functions to prevent protein aggregation. If this could be conclusively demonstrated, it would be valuable to the field. However, the protein aggregation studies need improvement. Technical demonstration that their differential centrifugation assay accurately detects aggregated proteins is needed. Further, NASP mutants do not exhibit increased H3 protein aggregation in the data presented. Instead, the increased fraction of aggregated H3 in NASP mutants seems to be due to a reduction in the overall levels of H3 protein, which is contrary to the model presented in this paper.

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

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Referee #1

Evidence, reproducibility and clarity

Summary:

The authors investigate the function of the H3 chaperone NASP, which is known to bind directly to H3 and prevent degradation of soluble H3. What is unclear is where NASP functions in the cell (nucleus or cytoplasm), how NASP protects H3 from degradation (direct or indirect), and if NASP affects H3 dynamics (nuclear import or export). They use the powerful model system of Drosophila embryos because the soluble H3 pool is high due to maternal deposition and they make use of photoconvertable Dendra-tagged proteins, since these are maternally deposited and can be used to measure nuclear import/export rates.

Using these systems and tools, they conclude that NASP affects nuclear import, but only indirectly, because embryos from NASP mutant mothers start out with 50% of the maternally deposited H3. Because of the depleted H3 and reduced import rates, NASP deficient embryos also have reduced nucleoplasmic and chromatin-associated H3. Using a new Dendra-tagged NASP allele, the authors show that NASP and H3 have different nuclear import rates, indicating that NASP is not a chaperone that shuttles H3 into the nucleus. They test H3 levels in embryos that have no nuclei and conclude that NASP functions in the cytoplasm, and through protein aggregation assays they conclude that NASP prevents H3 aggregation.

Major comments:

The text was easy to read and logical. The data are well presented, methods are complete, and statistics are robust. The conclusions are largely reasonable. However, I am having trouble connecting the conclusions in text to the data presented in Figure 4.

First, I'm confused why the conclusion from Figure 4A is that NASP functions in the cytoplasm of the egg. Couldn't NASP be required in the ovary (in, say, nurse cell nuclei) to stimulate H3 expression and deposition into the egg? The results in 4A would look the same if the mothers deposit 50% of the normal H3 into the egg. Why is NASP functioning specifically in the cytoplasm when it is also so clearly imported into the nucleus? Maybe NASP functions wherever it is, and by preventing nuclear import, you force it to function in the cytoplasm. I do not have additional suggestions for experiments, but I think the authors need to be very clear about the different interpretations of these data and to discuss WHY they believe their conclusion is strongest.

Second, an alternate conclusion from Figure 4D/E is that mothers are depositing less H3 protein into the egg, but the same total amount is being aggregated. This amount of aggregated protein remains constant in activated eggs, but additional H3 translation leads to more total H3? The authors mention that additional translation can compensate for reduced histone pools (line 416).

As the function of NASP in the cytoplasm (when it clearly imports into the nucleus) and role in H3 aggregation are major conclusions of the work, the authors need to present alternative conclusions in the text or complete additional experiments to support the claims. Again, I do not have additional suggestions for experiments, but I think the authors need to be very clear about the different interpretations of these data and to discuss WHY they believe their conclusion is strongest.

Data presentation:

Overall, I suggest moving some of the supplemental figures to the main text, adding representative movie stills to show where the quantitative data originated, and moving the H3.3 data to the supplement. Not because it's not interesting, but because H3.3 and H3.2 are behaving the same.

Fig 1:

It would strengthen the figure to include representative still images that led to the quantitative data, mostly so readers understand how the data were collected. The inclusion of a "simulated 50% H3" in panel C is confusing. Why? I would also consider normalizing the data between A and B (and C and D) by dividing NASP/WT. This could be included in the supplement (OPTIONAL)

Fig S1:

The data simulation S1G should be moved to the main text, since it is the primary reason the authors reject the hypothesis that NASP influences H3 import rates.

Fig 2:

Once again, I think it would help to include a few representative images of the photoconverted Dendra2 in the main text. I struggled with A/B, I think due to not knowing how the data were normalized. When I realized that the WT and NASP data are not normalized to each other, but that the NASP values are likely starting less than the WT values, it made way more sense. I suggest switching the order of data presentation so that C-F are presented first to establish that there is less chromatin-bound H3 in the first place, and then present A/B to show no change in nuclear export of the H3 that is present, allowing the conclusion of both less soluble AND chromatin-bound H3.

Fig S2:

If M1-M3 indicate males, why are the ovaries also derived from males? I think this is just confusing labeling. Supplemental Movie S1: Beautiful. Would help to add a time stamp (OPTIONAL).

Fig 3:

Panel C is the same as Fig S1A (not Fig 1A, as is said in the legend), though I appreciate the authors pointing it out in the legend. Also see line 276. Panel D is a little confusing, because presumably the "% decrease in import rate" cannot be positive (Y axis). This could be displayed as a scatter (not bar) as in Panels B/C (right) where the top of the Y axis is set to 0.

Fig S3:

A: What do the different panels represent? I originally thought developmental time, but now I think just different representative images? Are these age-matched from time at egg lay? C: What does "embryos" mean? Same question for Fig 4A. Fig 4: A: What does "embryos" mean? Number of embryos? Age in hours? C: Not sure the workflow figure panel is necessary, as I can't tell what each step does. This is better explained in methods. However I appreciated the short explanation in the text (lines 314-5).

Minor comments:

The authors should describe the nature of the NASP alleles in the main text and present evidence of robust NASP depletion, potentially both in ovaries and in embryos. The antibody works well for westerns (Fig S2B). This is sort of demonstrated later in Figure 4A, but only in NAAP x twine activated eggs.

Lines 163, 251, 339: minor typos Line 184: It would help to clarify- I'm assuming cytoplasmic concentration (or overall) rather than nuclear concentration. If nuclear, I'd expect the opposite relationship. This occurs again when discussing NASP (line 267). I suspect it's also not absolute concentration, but relative concentration difference between cytoplasm and nucleus. It would help clarify if the authors were more precise. Line 189: Given that the "established integrative model" helps to reject the hypothesis that NASP is involved in H3 import, I think it's important to describe the model a little more, even though it's previously published. Line 203: "The measured rate of H3.2 export from the nucleus is negligible" clarify this is in WT situations and not a conclusion from this study. Line 201: How can the authors be so sure that the decrease in WT is due to "the loss of non-chromatin bound nucleoplasmid H3.2-Dendra2?" Line 217: In the conclusion, the authors indicate that NASP indirectly affects soluble supply of H3 in the nucleoplasm. I do believe they've shown that the import rate effect is indirect, but I don't know why they conclude that the effect of NASP on the soluble nucleoplasmic H3 supply is indirect. Similarly, the conclusion is indirect on line 239. Yet, the authors have not shown it's not direct, just assumed since NASP results in 50% decrease to deposited maternal histones. Line 292: What is the nature of the NASP "mutant?" Is it a null? Similarly, what kind of "mutant" is the twine allele? Line 295. Line 316: Why did the authors use stage 14 egg chambers here when they previously used embryos? This becomes more clear later shortly, when the authors examine activated eggs, but it's confusing in text. Lines 343-348: It's unclear if the authors are drawing extended conclusions here or if they are drawing from prior literature (if so, citations would be required). For example, why during oogenesis/embryogenesis are aggregation and degradation developmentally separated? Lines 386-7: I do not understand why the authors conclude that H3 aggregation and degradation are "developmentally uncoupled" and why, in the absence of NASP, "H3 aggregation precedes degradation." Line 395: Why suddenly propose that NASP also functions in the nucleus to prevent aggregation, when earlier the authors suggest it functions only in the cytoplasm? Lines 409-413: The authors claim that histone deficiency likely does not cause the embryonic arrest seen in embryos from NASP mutant mothers. This is because H3 is reduced by 50% yet some embryos arrest long before they've depleted this supply. However, the authors also showed that H3 import rates are affected in these embryos due to lower H3 concentration. Since the early embryo cycles are so rapid, reduced H3 import rates could lead to early arrest, even though available H3 remains in the cytoplasm.

Significance

The significance of the work is conceptual, as NASP is known to function in H3 availability but the precise mechanism is elusive. This work represents a necessary advance, especially to show that NASP does not affect H3 import rates, nor does it chaperone H3 into the nucleus. However, the authors acknowledge that many questions remain. Foremost, why is NASP imported into the nucleus and what is its role there?

I believe this work will be of interest to those who focus on early animal development, but NASP may also represent a tool, as the authors conclude in their discussion, to reduce histone levels during development and examine nucleosome positioning. This may be of interest to those who work on chromatin accessibility and zygotic genome activation.

I am a genetics expert who works in Drosophila embryogenesis. I do not have the expertise to evaluate the aggregate methods presented in Figure 4.

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Reply to the reviewers

Review report for 'Sterols regulate ciliary membrane dynamics and hedgehog signaling in health and disease', Lamazière et al.

Reviewer #1

In this manuscript, Lamazière et al. address an important understudied aspect of primary cilium biology, namely the sterol composition in the ciliary membrane. It is known that sterols especially play an important role in signal transduction between PTCH1 and SMO, two upstream components of the Hedgehog pathway, at the primary cilium. Moreover, several syndromes linked to cholesterol biosynthesis defects present clinical phenotypes indicative of altered Hh signal transduction. To understand the link between ciliary membrane sterol composition and Hh signal transduction in health and disease, the authors developed a method to isolate primary cilia from MDCK cells and coupled this to quantitative metabolomics. The results were validated using biophysical methods and cellular Hh signaling assays. While this is an interesting study, it is not clear from the presented data how general the findings are: can cilia be isolated from different mammalian cell types using this protocol? Is the sterol composition of MDCK cells expected to the be the same in fibroblasts or other cell types? Without this information, it is difficult to judge whether the conclusions reached in fibroblasts are indeed directly related to the sterol composition detected in MDCK cells. Below is a detailed breakdown of suggested textual changes and experimental validations to strengthen the conclusions of the manuscript.

We would like to thank the reviewer for their helpful comments

Major comments:

• It appears that the comparison has been made between ciliary membranes and the rest of the cell's membranes, which includes many other membranes besides the plasma membrane. This significantly weakens the conclusions on the sterol content specific to the cilium, as it may in fact be highly similar to the rest of the plasma membrane. It is for example known that lathosterol is biosynthesized in the ER, and therefore the non-presence in the cilium may reflect a high abundance in the ER but not necessarily in the plasma membrane.

The reviewer is correct that we compared the sterol composition of the primary ciliary membrane to the average of the remaining cellular membranes. We agree that this broader reference fraction contains multiple intracellular membranes, including ER- and Golgi-derived compartments, and therefore does not isolate the plasma membrane specifically. We would like to emphasize that our study did not aim to compare the cilium directly to the plasma membrane, nor did we claim that the comparison was in any way related to the plasma membrane. It is also worth noting that previous studies in other ciliated organisms have reported a higher cholesterol content in cilia compared to the plasma membrane, suggesting that the two membranes may not be compositionally identical despite their continuity. However, we concur that determining the sterol composition of the MDCK plasma membrane would provide valuable context and enable a comparison with the membrane continuous with the ciliary membrane. Hence, we are willing to try isolating plasma membrane in the same cellular contexts.

• While the protocol to isolate primary cilium from MDCK cells is a valuable addition to the methods available, it would be good to at least include a discussion on its general applicability. Have the authors tried to use this protocol on fibroblasts for example?

Thank you for the reviewer's positive comment on the value of the ciliary isolation protocol. Indeed, we have attempted to apply the same approach to other ciliated cell types, namely IMCD3 and MEF cells. In the case of IMCD3 cells, we were able to isolate primary cilia using the same general strategy; however, we are still refining the preparation, as the overall yield is lower than in MDCK cells and the amount of material obtained is currently insufficient for comprehensive biochemical analyses. With MEF (fibroblast) cells, the procedure proved even more challenging, as the yield of isolated cilia was extremely low. This difficulty is likely due to the shorter length of fibroblast cilia and to their positioning beneath the cell body, which probably makes them more resistant to detachment. Overall, these observations suggest that while the protocol can be adapted to other cell types, its efficiency depends on cellular architecture. We have added a discussion of these aspects in the revised manuscript to clarify the method's current scope and limitations (lines 492-502).

• Some of the conclusions in the introduction (lines 75-80) seem to be incorrectly phrased based on the data: in basal conditions, ciliary membranes are already enriched in cholesterol and desmosterol, and the treatment lowers this in all membranes.

We agree, this was modified in the revised manuscript (lines 75-80).

• There seems to be little effect of simvastatin on overall cholesterol levels. Can the authors comment on this result? How would the membrane fluidity be altered when mimicking simvastatin-induced composition? Since the effect on Hh signaling appears to be the biggest (Figure 5B) under simvastatin treatment, it would be interesting to compare this against that found for AY9944 treatment. Also, the authors conclude that the effects of simvastatin treatment on ciliary membrane sterol composition are the mildest, however, one could argue that they are the strongest as there is a complete lack of desmosterol.

We thank the reviewer for these insightful comments. Regarding the modest overall effect of simvastatin on cholesterol levels, we would like to note that MDCK cells are an immortalized epithelial cell line with high metabolic plasticity. Such cancer-like cell types are known to exhibit enhanced de novo lipogenesis, particularly under culture conditions with ample glucose availability. This compensatory lipid biosynthesis can partially counterbalance pharmacological inhibition of the cholesterol biosynthetic pathway. Because simvastatin acts upstream in the pathway (at HMG-CoA reductase), its inhibition primarily reduces early intermediates rather than fully depleting end-product cholesterol, explaining the relatively mild changes observed in total cholesterol content.

Concerning desmosterol, we agree with the reviewer that its complete loss under simvastatin treatment is a striking finding that deserves further discussion. Interestingly, our data show that simvastatin treatment produces the strongest inhibition of pathway activation (as measured by SMO activation), but the weakest effect on signal transduction downstream of constitutively active SMOM2. This dichotomy suggests that the absence of desmosterol may preferentially affect the activation step of Hedgehog signaling at the ciliary membrane, without equally impacting downstream propagation. We have expanded the Result section to highlight this potential role of desmosterol in the activation phase of Hedgehog signaling and to contrast it with the effects observed under AY9944 treatment (lines 463-469).

It is not clear to me why the authors have chosen to use SAG to activate the Hh pathway, as this is a downstream mode of activation and bypasses PTCH1 (and therefore a potentially sterol-mediated interaction between the two proteins). It would be very informative to compare the effect of sterol modulation on the ability of ShhN vs SAG to activate the pathway.

Our study aims to demonstrate that the sterol composition of the ciliary membrane plays an essential role in the proper functioning of the Hedgehog (Hh) signaling pathway, comparable in importance to that of oxysterols and free cholesterol. Because ShhN itself is covalently modified by cholesterol, and Smoothened (SMO) can be directly activated by both oxysterols and cholesterol, we reasoned that using a non-native SMO agonist such as SAG would allow us to specifically assess defects arising from alterations in membrane-bound sterols. In this way, pathway activation by SAG provides a more direct readout of the functional contribution of ciliary membrane sterols to SMO activity, independent of potential confounding effects related to ShhN processing, secretion, or PTCH1-mediated regulation.

• The conclusions about the effect of tamoxifen on SMO trafficking in MEFs should be validated in human patient cells before being able to conclude that there is a potential off-target effect (line 438). Also, if that is the case, the experiment of tamoxifen treatment of EBP KO cells should give an additional effect on SMO trafficking. Also, could the CDPX2 phenotypes in patients be the result of different cell types being affected than the fibroblast used in this study?

We agree that carrying the proposed experiment would be a good way to assess a potential off-target effect. However, such validation is beyond the scope of the present study, as this comment on off-target effect was aimed primarily to propose a mechanistic hypothesis to explain the differences observed in Hedgehog pathway activation between patient-derived fibroblasts and tamoxifen-treated MEFs. We leaned towards this hypothesis because drug treatments are known for their overall variable specificity, but we agree other hypotheses are possible, and among them the difference in cell type, as both are fibroblasts but from different origin. We rephrased this passage in the revised manuscript (lines 447-448 ).

Regarding the reviewer's third point, we fully agree that the CDPX2 phenotype in patients is unlikely to arise solely from fibroblast dysfunction. Nevertheless, fibroblasts are the only patient-derived cells currently available to us, and they provide a useful model for assessing ciliary signaling. It is reasonable to expect that similar defects could occur in other, more physiologically relevant cell types.

• For the experiments with the SMO-M2 mutant, it would be useful to show the extent of pathway activation by the mutant compared to SAG or ShhN treatment of non-transfected cells. Moreover, it will be necessary to exclude any direct effects of the compound treatment on the ability of this mutant to traffic to the primary cilium, which can easily be done using fluorescence microscopy as the mutant is tagged with mCherry.

The SmoM2 mutant is indeed a well-characterized constitutively active form of Smoothened that has been extensively studied by us and others. It is well established that this mutant correctly localizes to the primary cilium and robustly activates the Hedgehog pathway in MEFs (see Eguether et al., Dev. Cell, 2014 or Eguether et al, mol.biol.cell, 2018). In our study, we have already included supporting evidence for pathway activation in Supplementary Figure S1b, showing Gli1 expression levels in untreated MEFs transfected with SmoM2, which illustrates the extent of its activation compared to ligand-induced conditions.

In line with the reviewer's recommendation, we will additionally include microscopy data showing SmoM2 localization in MEFs treated with the different sterol modulators. These data should confirm that the observed effects are not due to altered ciliary trafficking of the mutant protein but instead reflect changes in downstream signaling or membrane composition.

Minor comments:

Line 74: 'in patients', should be rephrased to 'patient-derived cells'

This was modified in the revised manuscript

Figure 2A: What do the '+/-' indicate? They seem to be erroneously placed.

We apologize for the oversight, the figures initially submitted with the manuscript inadvertently included some earlier versions, which explains several of the discrepancies noted by the reviewers. This issue has been corrected in the revised submission, and all figures have now been updated to reflect the finalized data.

Figure 2B: no label present for which bar represents cilia/other membranes

We apologize for the oversight, the figures initially submitted with the manuscript inadvertently included some earlier versions, which explains several of the discrepancies noted by the reviewers. This issue has been corrected in the revised submission, and all figures have now been updated to reflect the finalized data.

Figure 2C: this representation is slightly deceptive, since the difference between cells and cilia for lanosterol is not significantly different as shown in figure 2A.

This representation has been removed in the revised figures.

Figure 3A: it would be useful to also show where 8-DHC is in the biosynthetic pathway.

This has been modified in the revised figures.

Line 373: the title should be rephrased as it infers that DHCR7 was blocked in model membranes, which is not the case.

This has been modified in the revised manuscript.

Lines 377-384: this paragraph seems to be a mix of methods and some explanation, but should be rephrased for clarity.

We believe the technical information within this paragraph are useful for the understanding of the reader. We would rather leave as is unless recommended by other reviewers or editorial staff.

Line 403: 'which could explain the resulting defects in Hedgehog signaling': how and what defects? At this point in the study no defects in Hh signaling have been shown.

This has been modified in the revised manuscript.

Figure 4D: 'd' is missing

We apologize for the oversight, the figures initially submitted with the manuscript inadvertently included some earlier versions, which explains several of the discrepancies noted by the reviewers. This issue has been corrected in the revised submission, and all figures have now been updated to reflect the finalized data.

Line 408: SAG treatment resulted in slightly shorter cilia: this is not the case for just SAG treated cilia, but only for the combination of SAG + AY9944. However, in that condition there appears to be a subpopulation of very short cilia, are those real?

This is correct, this is not the case for untreated cilia, but the short population is real, not only in AY9944 but also in Tamoxifen and Simvastatin. Again, the relevance and significance of minor cilia length change is unclear and we are not trying to draw any other conclusion from this than saying that the ciliary compartment is modified.

Figure 5b: it would be good to add that all conditions contained SAG.

This has been modified in the revised figures.

Figure 5D: Since it is shown in Fig 5C that there are no positive cilia -SAG, there is no point to have empty graphs in Fig 5D on the left side, nor can any statistics be done. Similarly for 5K.

We think this is still worth having in the figure. As the reviewer noted in one of his next comment, there are cases where Smoothened or Patched can be abnormally distributed (see also Eguether et al, mol biol cell, 2018). This shows that we checked all conditions for presence or absence of Smo and that there is no signal to be found. We would rather leave it as is unless asked otherwise by editorial staff.

Figure 5E: it is not clearly indicated what is visualized in the inserts, sometimes it's a box, sometimes a line and they seem randomly integrated into the images.

We apologize for the oversight - the figures initially submitted with the manuscript inadvertently included some earlier versions, which explains several of the discrepancies noted by the reviewers. This issue has been corrected in the revised submission, and all figures have now been updated to reflect the finalized data.

Figure 5H: is this the intensity in just SMO positive cilia? If yes, this should be indicated, and the line at '0' for WT-SAG should be removed. I am also surprised there is then ns found for WT vs SLO, since in WT there are no positive cilia, but in SLO there are a few, so it appears to be more of a black-white situation. Perhaps it would be useful to split the data from different experiments to see if it consistently the case that there is a low percentage of SMO positive cilia in SLO cells.

Yes, as in the rest of figure 5, the fluorescence intensity of Smo is only taken into account in SMO positive cells. This is now indicated in figure legend (lines 890, 898, 903 ). As for Smo positive, this is a good suggestion. We checked and for cilia in non-activated SLO patients, there are 8 positive cilia over a total of 240 counted cilia, mainly from one of the experiments. We could remove the data or leave as is given that the result is not significant.

Fig S1: panels are inverted compared to mentioning in the text.

We apologize for the oversight, the figures initially submitted with the manuscript inadvertently included some earlier versions, which explains several of the discrepancies noted by the reviewers. This issue has been corrected in the revised submission, and all figures have now been updated to reflect the finalized data.

Methods-pharmacological treatments: there appear to be large differences in concentrations chosen to treat MDCK versus MEF cells - can the authors comment on these choices and show that the enzymes are indeed inhibited at the indicated concentrations?

We thank the reviewer for this important comment. The concentrations of the pharmacological treatments were optimized separately for MDCK and MEF cells based on cell-type-specific tolerance. For each compound, we used the highest concentration that produced no detectable cytotoxicity or morphological changes. These conditions ensured that the treatments were effective (as seen by changes in sterol composition in MDCK cilia and Hh pathway phenotypes in treated MEFs) and compatible with cell viability and ciliation. Although we did not directly assay enzymatic inhibition in each case, the selected concentrations are consistent with those previously reported to inhibit the targeted enzymes in similar cellular contexts.

Compound

Typical Concentration Range in Mammalian Cell Culture

Typical Exposure Duration

Example Cell Types

Representative Peer-Reviewed References

AY9944 (DHCR7 inhibitor)

1-10 µM widely used; 1 µM for minimal on-target effects; 2.5-10 µM for robust sterol shifts

24-72 h; some sterol studies up to several days

HEK293, fibroblasts, neuronal cells, macrophages

Kim et al., J Biol Chem, 2001 - used 1 µM in dose-response experiments.; Haas et al., Hum Mol Genet, 2007 - 1 µM in cell-based assays.; Recent macrophage sterol study - 2.5-10 µM to induce 7-DHC accumulation.

Simvastatin (HMG-CoA reductase inhibitor)

0.1-10 µM common; 1-10 µM most widely used for robust pathway inhibition

24-72 h

Diverse mammalian lines, including liver, fibroblasts, epithelial cells

Bytautaite et al., Cells (2020) - discusses common in-vitro ranges (1-10 µM).; Mullen et al., 2011 - used 10 µM simvastatin, noting it is a standard in-vitro concentration.

Tamoxifen (modulator of sterol metabolism)

1-20 µM; 1-5 µM for mild/longer treatments; 10-20 µM in cancer/cilia signaling studies

24-72 h (longer treatments often at 1-5 µM)

MDCK, MEFs, MCF-7, diverse epithelial lines

Schlottmann et al., Cells (2022) - used 5-25 µM in sterol-related cell studies.; MCF-7 literature - 0.1-1 µM for estrogenic signaling, higher (5-10 µM) for metabolic/sterol pathway effects.; Additional cancer cell work indicating similar ranges.

This information has been clarified in the revised Methods section (lines 222-224).

(optional): it would be interesting to include a gamma-tubulin staining on the cilium prep to see if there is indeed a presence of the basal body as suggested by the proteomics data.

Thank you, we will try this.

There are many spelling mistakes and inconsistencies throughout the manuscript and its figures (mix of French and English for example) so careful proofreading would be warranted. Moreover, there are many mentionings of 'Hedgehog defects' or 'Hedgehog-linked', where in fact it is a defect in or link to the Hedgehog pathway, not the protein itself. This should be corrected.

We thank the reviewer for noting these issues. We apologize for the inconsistencies observed in the initial submission, as mentioned previously, some of the figures inadvertently included earlier versions, which may have contributed to the errors identified. All figures have now been carefully revised and updated in the resubmitted manuscript.

Regarding the text, we are surprised to hear about the spelling inconsistencies, as the manuscript was professionally proofread prior to submission (documentation can be provided upon request). Nevertheless, we have conducted an additional round of thorough proofreading to ensure consistency throughout the text and figures.

Finally, we have corrected all instances of "Hedgehog defects" or "Hedgehog-linked" to the more accurate phrasing "Hedgehog pathway defect" or "Hedgehog pathway-linked," as suggested by the reviewer throughout the manuscript.

Reviewer #1 (Significance (Required)):

The study of ciliary membrane composition is highly relevant to understand signal transduction in health and disease. As such, the topic of this manuscript is significant and timely. However, as indicated above, there are limitations to this study, most notably the comparison of ciliary membrane versus all cellular membranes (rather than the plasma membrane), which weakens the conclusions that can be drawn. Moreover, cell-type dependency should be more thoroughly addressed. There certainly is a methodological advance in the form of cilia isolation from MDCK cells, however, it is unclear how broadly applicable this is to other mammalian cell types.

We would like to thank the reviewer for their helpful comments and we appreciate the reviewer's recognition of the relevance and timeliness of studying ciliary membrane composition in the context of signaling regulation. We fully acknowledge that our comparison was made between the primary ciliary membrane and the total cellular membrane fraction, which encompasses multiple intracellular membranes. Our intent, however, was to obtain a global overview of how the ciliary membrane differs from the average membrane environment within the cell, thereby highlighting features that are unique to the cilium as a signaling organelle. This approach provides valuable baseline information that complements, rather than replaces, future targeted comparisons with the plasma membrane. As mentioned in this reply, we aim at carrying out these experiments before publication. Regarding cell-type dependency, we concur that ciliary lipid composition may vary between cell types, reflecting differences in their functional specialization. Our method was intentionally established in MDCK cells, which are epithelial and highly ciliated, to ensure sufficient yield and reproducibility. We have initiated trials with other mammalian cell types, including IMCD3 and MEF cells, and while yields remain limited, preliminary results indicate that the approach is adaptable with further optimization. Thus, our current work establishes a robust and reproducible proof of concept in a mammalian model, providing the first detailed sterol fingerprint of a mammalian primary cilium.

We believe this constitutes a significant methodological and conceptual advance, as it opens the way for systematic exploration of ciliary lipid composition across diverse mammalian systems and pathological contexts.

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

Overview Accumulating evidence suggests that sterols play critical roles in signal transduction within the primary cilium, perhaps most notably in the Hedgehog cascade. However, the precise sterol composition of the primary cilium, and how it may change under distinct biological conditions, remains unknown, in part because of the lack of reproducible, widely accepted procedures to purify primary cilia from mammalian cultured cells. In the present study, the authors have designed a method to isolate the cilium from the MDCK cells efficiently and then utilized this procedure in conjunction with mass spectrometry to systematically analyze the sterol composition of the ciliary membrane, which they then compare to the sterol composition of the cell body. By analyzing this sterol profiling. the authors claim that the cilium has a distinct sterol composition from the cell body, including higher levels of cholesterol and desmosterol but lower levels of 8-DHC and & Lathosterol. This manuscript further demonstrates that alteration of sterol composition within cilia modulates Hedgehog signaling. These results strengthen the link between dysregulated Hedgehog signaling and defects in cholesterol biosynthesis pathways, as observed in SLOS and CDPX2.

While the ability to isolate primary cilia from cultured MDCK cells represents an important technical achievement, the central claim of the manuscript - that cilia have a different sterol composition from the cell body - is not adequately supported by the data, and more rigorous comparisons between the ciliary membrane and key organellar membranes (such as plasma membrane) are required to make this claim. Moreover, although the authors have repeatedly mention that the ciliary sterol composition is "tightly regulated" there is no evidence provided to support such claim. At best, the data suggest that the cilium and cell body may differ in sterol composition (though even that remains uncertain), but no underlying regulatory mechanisms are demonstrated. In addition, much of the 2nd half of the paper represents a rehash of experiments with sterol biosynthesis inhibitors that have already been published in the literature, making the conceptual advance modest at best. Lastly, the link between CDPX2 and defective Hedgehog signaling is tenuous.

We would like to thank the reviewer for their helpful comments

Major comments

Figure 1. C) Although the isolation of cilium from the MDCK cells using dibucaine treatment seems to be very efficient, the quality control of their fractionation procedure to monitor the isolation is limited to a single western blot of the purified cilia vs. cell body samples, with no representative data shown from the sucrose gradient fractionation steps. Given that prior studies (including those from the Marshall lab cited in this manuscript) found that 1) sucrose gradient fractionation was essential to obtain relatively pure ciliary fractions, and 2) the ciliary fractions appear to spread over many sucrose concentrations in those prior studies , the authors should have included the comparison of the fractionation profile from the sucrose gradient while isolating the primary cilium. This additional information would have further clarified and supported the efficiency of their proposed method.

We thank the reviewer for their insightful comments regarding the quality control of our ciliary fractionation. We would like to clarify several important methodological aspects that distinguish our approach from those used in the studies cited (including those from the Marshall lab). In the cited work, the authors used a continuous sucrose gradient ranging from 30 % to 45 %, which allowed visualization of the distribution of ciliary proteins across the gradient. In contrast, we employed a discontinuous sucrose gradient (25 % / 50 %) optimized for higher recovery and reproducibility in our hands. In our preparation, the primary cilia consistently localize at the interface between the 25 % and 50 % layers. We systematically collect five 1 mL fractions from this interface and use fractions 1-3 for downstream analyses, as fractions 4-5 are typically already depleted of ciliary material. This targeted collection ensures good enrichment and low contamination, while avoiding unnecessary dilution of the limited ciliary sample. We also note that the prior studies the reviewer refers to were optimized for proteomic analyses, and therefore used actin as a marker of contamination from the cell body. In our case, the downstream application is lipidomic profiling, for which such protein-based contamination markers are not directly informative, since no reliable lipid marker exists to differentiate between organelle membranes. For this reason, we limited the protein-level validation to a semi-quantitative assessment of ciliary enrichment using ARL13B Western blotting, which robustly reports the presence and enrichment of ciliary membranes. Finally, to complement this targeted validation, we performed proteomic analysis followed by Gene Ontology (GO) Enrichment Analysis using the PANTHER database. This analysis evaluates the overrepresentation of proteins associated with ciliary structures and functions relative to the background frequency in the Canis lupus familiaris proteome. The resulting enrichment profile confirms that the isolated material is highly enriched in ciliary components and somewhat depleted of non-ciliary contaminants, thereby serving as an unbiased and global assessment of sample specificity and purity. We believe that, together, these methodological choices provide a rigorous and quantitative validation of our fractionation efficiency and support the robustness of the cilia isolation protocol used in this study.

1. D) The authors presented proteomic data for the peptides analyzed from the isolated cilia in the form of GO term analysis; however, they did not provide examples of different proteins enriched within their fractionation procedure, aside from Arl13b shown in the blot. Including a summary table with representative proteins identified in the isolated ciliary fraction, along with the relative abundance or percentage distribution of these proteins, would make the data more informative.

We thank the reviewer for this valuable suggestion. As mentioned in the manuscript, our proteomic dataset includes numerous hallmark components of the cilium, such as 18 IFT proteins, 4 BBS proteins, and several Hedgehog pathway components (including SuFu and Arl13b), as well as axonemal (Tubulin, Kinesin, Dynein) and centrosomal proteins (Centrin, CEPs, γ-Tubulin, and associated factors). This composition demonstrates that the isolated fraction is highly enriched in bona fide ciliary components while retaining a small proportion of basal body proteins, which is expected given their physical continuity. Importantly, our dataset shows a 70% overlap with the ciliary proteome published by Ishikawa et al. and a 41% overlap with the CysCilia consortium's list of potential ciliary proteins, which supports both the specificity and reliability of our isolation procedure. Regarding the suggestion to present relative protein abundances, we would like to clarify that defining "relative to what" is challenging in this context. The stoichiometry of ciliary proteins is largely unknown, and relative abundance normalized to total protein content can be misleading, as ciliary structural and signaling components differ greatly in copy number and membrane association. For this reason, we chose to highlight in the text proteins such as BBS and IFTs, which are known to be of low abundance within the cilium; their detection supports the depth and specificity of our proteomic coverage. In addition, we performed an unbiased Gene Ontology (GO) Enrichment Analysis using the PANTHER database, which provides a systematic and quantitative overview of the biological processes and cellular components overrepresented in our dataset relative to the canine proteome. This analysis with regard to purity wa already discussed in the submitted manuscript discussion. To further address the reviewer's comment, we will include as a supplemental table in the revised manuscript, a summary table listing representative ciliary proteins identified in our fraction, including those overlapping with the CysCilia (Gold ans potential lists), CiliaCarta and Ishikawa/Marshall proteomes. This addition should make the dataset more transparent and informative while preserving scientific rigor.

Figure 2.

The authors represented the comparison of sterol content within the cilia versus whole cell (as cell membranes). Since different organelles have a very diverse degree of cholesterol contents within them, for instance plasma membrane itself is around 50 mol% cholesterol levels while organelles like ER have barely any cholesterol. Thus, comparing these two samples and claiming a 2.5-fold increase in cholesterol levels is misleading. A more appropriate comparison would be between isolated primary cilia and isolated plasma membranes (procedures to isolate plasma membranes have been described previously, e.g., Naito et al., eLife 2019; Das et al, PNAS 2013. The absence of such controls makes it difficult to fully validate the reported magnitude of sterols enrichment in cilia relative to the cell surface.

As already discussed above for reviewer 1, we would like to emphasize that our study did not aim to compare the cilium directly to the plasma membrane, nor did we claim that the comparison was in any way related to the plasma membrane. Our intent, was to obtain a global overview of how the ciliary membrane differs from the average membrane environment within the cell, thereby highlighting features that are unique to the cilium as a signaling organelle. This approach provides valuable baseline information that complements, rather than replaces, future targeted comparisons with the plasma membrane. However, we concur that determining the sterol composition of the MDCK plasma membrane would provide valuable context and enable a comparison with the membrane continuous with the ciliary membrane. Hence, we are willing to try isolating plasma membrane in the same cellular contexts, and we thank the reviewer for the proposed literature.

Also, because dibucaine was used here to isolate MDCK cilia, a control experiment to exclude possible effects of the dibucaine treatment on sterol biosynthesis would be helpful.

Thank you for this comment, we will verify this point by quantifying by GC-MS the sterol content of whole MDCK cells with and without 15 minutes-dibucaine treatments.

Figure 3.

Tamoxifen is a potent drug for nuclear hormone receptor activity and thus can independently influence various cellular processes. As several experiments in the later sections of the manuscript rely on tamoxifen treatment of cells, it is important that the authors include appropriate controls for tamoxifen treatment, to confirm that the observed effects do not stem from effects on nuclear hormone receptor activity. This would ensure that the observed effects can be confidently attributed to the experimental manipulation rather than to the intrinsic effects of tamoxifen.

The reviewer is right, tamoxifen, like many drugs, has pleiotropic effects in different cell processes. Aware of this possible issue, we turned to a genetic model creating a CRISPR-CAS9 mediated knock down of EBP, the enzyme targeted by tamoxifen. We showed in figure 5 that the results between tamoxifen treated cells and CRIPSR EBP cells were in accordance with one another, showing that, for hedgehog signaling, the effect of tamoxifen recapitulates the effect of the enzyme KO.

Figure4. The authors present the results of spectroscopy studies to analyze generalized polarization (GP) of liposomes in vitro , but only processed data are shown, and the raw spectra are not provided. The authors need to present representative spectra to enable the readers to interact the raw data from the experiments.

This has been added to new supplemental figure 1 and corresponding figure legend (lines 898-904)

Figure5. B) The experiment shown Gli1 mRNA levels following treatment with inhibitors of cholesterol biosynthesis, but similar findings have already been reported previously (e.g., Cooper et al, Nature Genetics 2003; Blassberg et al, Hum Mol Genet 2016), and the present results do not provide a significant conceptual advance over those earlier studies.

We thank the reviewer for this comment and for highlighting the importance of earlier studies on Hedgehog (Hh) signaling and cholesterol metabolism. While we fully agree that confirming and extending established findings has intrinsic scientific value, we respectfully disagree with the assertion that our work does not provide conceptual novelty.

The seminal work by Cooper et al. (Nature Genetics, 2003) indeed laid the foundation for linking sterol metabolism to Hedgehog signaling, and we cite it as such. However, that study was conducted in chick embryos, a model that is relatively distant from mammalian systems and human pathophysiology. Moreover, their approach relied heavily on cyclodextrin-mediated cholesterol depletion, which is non-specific and extracts multiple sterols from membranes (discussed in this article lines 512-516). In contrast, our study employs pharmacological inhibitors targeting specific enzymes in the sterol biosynthetic pathway, thereby allowing us to modulate distinct steps and intermediates in a controlled and mechanistically informative manner. We also extend these analyses to patient-derived fibroblasts and CRISPR-engineered cells, providing direct human and genetic validation of the observed effects. Importantly, we complement these cellular studies with biochemical characterization of isolated ciliary membranes from MDCK cells, enabling a direct assessment of how specific sterol alterations affect ciliary composition and Hh pathway function - an angle not addressed in prior work.

Regarding Blassberg et al. (Hum. Mol. Genet., 2016), we agree that part of our findings recapitulates their observations on SMO-related signaling defects, which we view as an important confirmation of reproducibility. However, their study primarily sought to distinguish whether Hh pathway impairment in SLOS results from 7-DHC accumulation or cholesterol depletion, concluding that cholesterol deficiency was the main cause. Our results expand on this by demonstrating that perturbations extend beyond these two sterols, and that additional intermediates in the biosynthetic pathway also impact ciliary membrane composition and signaling competence. Furthermore, our experiments using the constitutively active SmoM2 mutant show that Hh signaling defects are not restricted to SMO activation per se, revealing a broader disruption of the signaling machinery within the cilium.

Finally, neither of the above studies examined CDPX2 patient-derived cells or the consequences of EBP enzyme deficiency on Hh signaling. Our finding that this pathway is altered in this genetic context represents, to our knowledge, a novel link between CDPX2 and Hedgehog pathway dysfunction.

Taken together, our work builds upon and extends previous findings by integrating cell-type-specific, biochemical, and patient-based analyses to provide a more comprehensive and mechanistically detailed view of how sterol composition of the ciliary membrane regulates Hedgehog signaling.

In addition, the authors analyze the effect of these inhibitors on SAG stimulation, but the experiment lacks the control for Gli mRNA levels in the absence of SAG treatment. Without this control, it is impossible to know where the baseline in the experiment is and how large the effects in question really are.

Below, we provide the data expressed using the ΔΔCt method (NT + SAG normalized to NT - SAG), which more clearly illustrates the magnitude of the effect in question. As similar qPCR-based Hedgehog pathway activation assays in MEFs have been published previously (see Eguether et al., Dev. Cell 2014; Eguether et al., Mol. Biol. Cell 2018), our goal here was not to re-establish the assay itself but to highlight the comparative effects across experimental conditions. In addition, one of the datasets was obtained using a new batch of SAG, which exhibited stronger pathway activation across all conditions (visible as higher overall expression levels). To ensure valid statistical comparisons across experiments and to focus on relative rather than absolute activation, we therefore chose to present the data as fold change values, which provides a more robust and statistically consistent measure for cross-condition analysis.

J-K) The data represented in these panels for SAG treatment as fraction of Smo and its fluorescence intensity for the same sample appears to be inconsistent between the two graphs. Under SAG treatment for EBP mutants shows higher Smo fluorescence intensity while Smo positive cilia seems to be less than the wild type control cells. If the number of Smo+ cilia (quantified by eye) differs between conditions, shouldn't the quantification of Smo intensity within cilia show a similar difference?

We thank the reviewer for this careful observation. The apparent discrepancy arises because the two panels quantify different parameters. In panel (j), we counted the percentage of cilia positive for SMO (i.e., cilia in which SMO was detected above background). In contrast, panel (k) reports the fluorescence intensity of SMO, but this measurement was performed only within the SMO-positive cilia identified in panel (j). This distinction has now been explicitly clarified in the figure legend, as also suggested by Reviewer 1.

Taken together, these two analyses indicate that although fewer cilia display detectable SMO accumulation in the EBP mutant cells, the amount of SMO present within those cilia that do recruit it is comparable to wild-type levels (as reflected by the non-significant difference in fluorescence intensity). This interpretation helps explain the partial functional preservation of Hedgehog signaling in this condition and contrasts with cases such as AY9944 treatment, where both the number of SMO-positive cilia and the SMO intensity are reduced.

1. I) The rationale for using SmoM2 in the analysis of cholesterol metabolism-related diseases such as SLOS and CDPX2 is unclear. The SmoM2 variant is primarily associated with cancer rather than cholesterol biosynthesis defects and its relevance either of these disorders is not immediately apparent.

We thank the reviewer for this pertinent observation. We fully agree that SmoM2 was originally identified as an oncogenic mutation and is not directly associated with cholesterol biosynthesis disorders. However, our rationale for using this mutant was mechanistic rather than pathological. SmoM2 is a constitutively active form of SMO that triggers pathway activation independently of upstream components such as PTCH1 or ligand-mediated regulation.

By using SmoM2, we aimed to determine whether the signaling defects observed under conditions that alter sterol metabolism (e.g., treatment with AY9944 or tamoxifen) occur upstream or downstream of SMO activation. The results demonstrate that, even when SMO is constitutively active, the Hedgehog pathway remains impaired under AY9944 treatment-and to a lesser extent with tamoxifen-indicating that these sterol perturbations disrupt the pathway beyond the level of SMO activation itself. In contrast, cells treated with simvastatin maintain normal pathway responsiveness, reinforcing the specificity of this effect.

This experiment is therefore central to our study, as it reveals that sterol imbalance can hinder Hedgehog signaling even in the presence of an active SMO, providing new insight into how membrane composition influences downstream signaling competence.

Minor corrections

1. Line 385 seems to be a bit confusing which mentions cilia were treated with AY9944 - do the authors mean that cells were been treated with the drugs before isolation of cilia, or were the purified cilia actually treated with the drugs?

Thank you, this has been modified in the revised manuscript

The authors should add proper label in Figure 2 panel b for the bars representing the cilia and cell membranes.

We apologize for the oversight, the figures initially submitted with the manuscript inadvertently included some earlier versions, which explains several of the discrepancies noted by the reviewers. This issue has been corrected in the revised submission, and all figures have now been updated to reflect the finalized data.

Panels in Figure S1 should be re-arranged according to the figure legend and figure reference in line 450.

We apologize for the oversight, the figures initially submitted with the manuscript inadvertently included some earlier versions, which explains several of the discrepancies noted by the reviewers. This issue has been corrected in the revised submission, and all figures have now been updated to reflect the finalized data.

Legend for the Figure S1b should be corrected as data sets in graph represents 7 points while technical replicates in legend shows 6 experimental values.

Thank you, this has been modified in the revised manuscript

The labels for drug in Figure 3 and 5 should be corrected from tamoxifene to tamoxifen and simvastatine to simvastatin.

We apologize for the oversight, the figures initially submitted with the manuscript inadvertently included some earlier versions, which explains several of the discrepancies noted by the reviewers. This issue has been corrected in the revised submission, and all figures have now been updated to reflect the finalized data.

Reviewer #2 (Significance (Required)):

In the present study, the authors have designed a method to isolate the cilium from the MDCK cells efficiently and then utilized this procedure in conjunction with mass spectrometry to systematically analyze the sterol composition of the ciliary membrane, which they then compare to the sterol composition of the cell body. By analyzing this sterol profiling. the authors claim that the cilium has a distinct sterol composition from the cell body, including higher levels of cholesterol and desmosterol but lower levels of 8-DHC and & Lathosterol. This manuscript further demonstrates that alteration of sterol composition within cilia modulates Hedgehog signaling. These results strengthen the link between dysregulated Hedgehog signaling and defects in cholesterol biosynthesis pathways, as observed in SLOS and CDPX2.

While the ability to isolate primary cilia from cultured MDCK cells represents an important technical achievement, the central claim of the manuscript - that cilia have a different sterol composition from the cell body - is not adequately supported by the data, and more rigorous comparisons between the ciliary membrane and key organellar membranes (such as plasma membrane) are required to make this claim. Moreover, although the authors have repeatedly mention that the ciliary sterol composition is "tightly regulated" there is no evidence provided to support such claim. At best, the data suggest that the cilium and cell body may differ in sterol composition (though even that remains uncertain), but no underlying regulatory mechanisms are demonstrated. In addition, much of the 2nd half of the paper represents a rehash of experiments with sterol biosynthesis inhibitors that have already been published in the literature, making the conceptual advance modest at best. Lastly, the link between CDPX2 and defective Hedgehog signaling is tenuous.

We thank the reviewer for this detailed summary and for acknowledging the technical advance represented by our method for isolating primary cilia from MDCK cells. However, we respectfully disagree with several aspects of the reviewer's assessment of our work.

As we elaborated in our responses to earlier comments, particularly regarding Figure 5, we disagree with the characterization of part of our study as a "rehash", a somewhat derogatory word, of previously published experiments. Our approach differs from earlier studies by relying on specific pharmacological modulation of defined enzymes in the sterol biosynthesis pathway, rather than using non-specific agents such as cyclodextrins, and by linking these manipulations to direct biochemical measurements of ciliary sterol composition. This strategy allows, for the first time, a targeted and physiologically relevant examination of how specific sterol perturbations affect Hedgehog signaling.

Regarding our statement that ciliary sterol composition is "tightly regulated," we acknowledge that we have not yet explored the underlying molecular mechanisms of this regulation. Nevertheless, the experimental evidence supporting this statement lies in the variation of ciliary sterol composition across multiple treatments that strongly perturb cellular sterols. Despite broad cellular changes, the ciliary sterol profile remains very resilient for some parameters, an observation that, in our view, strongly supports the idea of a selective or regulated process maintaining ciliary sterol identity. This conclusion does not depend on comparison with other membrane compartments.

We also respectfully disagree that the observed differences between cilia and the cell body (which doesn't equal to plasma membrane) are "uncertain." The consistent enrichment in cholesterol and desmosterol, combined with the relative depletion in 8-DHC and lathosterol, were detected across independent replicates using robust lipidomic profiling and are statistically supported. These findings are, to our knowledge, the first quantitative demonstration of a sterol fingerprint specific to a mammalian cilium.

Finally, while we agree that the mechanistic link between CDPX2 and defective Hedgehog signaling warrants further exploration, the data we present, combining pharmacological inhibition (tamoxifen), CRISPR-mediated EBP knockout, and SMOM2 activation assays, all consistently indicate a functional impairment of the Hedgehog pathway under EBP deficiency. This is further reinforced by clinical reports describing Hedgehog-related phenotypes in CDPX2 patients. We therefore believe that our work provides a solid experimental and conceptual basis for connecting EBP dysfunction to Hedgehog signaling defects.

In summary, our study introduces a validated and reproducible method for mammalian cilia isolation, provides the first detailed sterol composition profile of primary cilia, and establishes a functional link between ciliary sterol imbalance and Hedgehog pathway modulation. We believe these findings represent a meaningful conceptual advance and a valuable resource for the field

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

Lamaziere et al. describe an improved protocol for isolating primary cilia from MDCK cells for downstream lipidomics analysis. Using this protocol, they characterize sterol profile of MDCK cilia membrane under standard growth conditions and following pharmacological perturbations that are meant to mimic SLOS and CDPX2 disorders in humans. The authors then assess the impact of the same pharmacological manipulations on Shh pathway activity and validate their findings from these experiments using orthogonal genetic approaches. Major and minor concerns that require attention prior to publication are outlined below.

We would like to thank the reviewer for their comments

Major 1.Since the extent of contamination of the cilia preps with non-cilia membranes is unclear, and variability between replicates is not reported, it makes interpretation of changes in cilia membrane sterol composition in response to pharmacological manipulations somewhat difficult to interpret. Discussing reproducibility of cilia sterol composition between replicates (and including corresponding data) could alleviate these concerns to some extent.

We thank the reviewer for this comment. We would like to clarify that variability between replicates is indeed reported throughout the manuscript. In Figures 2 and 3, all data are presented as mean {plus minus} SEM, as indicated in the figure legends. Specifically, the data in Figure 2 are derived from six independent experiments, reflecting the central dataset used for comparative analyses, while the data in Figure 3 are based on three independent experiments.

We also note that the overall variability between replicates is low, further supporting the reproducibility of our ciliary sterol composition measurements. This consistency across independent biological replicates provides confidence that the differences observed between cilia and the cell body are robust and not due to stochastic contamination or technical variation.

2.An abundant non-ciliary membrane protein (rather than GAPDH) may be a more appropriate loading control in Fig. 1C.

This is a valuable comment and we will find a non-ciliary membrane protein to complement this experiment.

3.Fig. 2b - which bar corresponds to cells and which one to cilia? What do numbers inside bars represent? Please label accordingly.

We apologize for the oversight, the figures initially submitted with the manuscript inadvertently included some earlier versions, which explains several of the discrepancies noted by the reviewers. This issue has been corrected in the revised submission, and all figures have now been updated to reflect the finalized data.

4.Fig. 3b-d, right panels - please define what numbers inside bars represent

Thank you, this was done in the revised manuscript. The numbers are reports of absolute quantification.

5.The font in Figs 2, 3, and 4 is very small and difficult to read. Please make the font and/or panels bigger to improve readability.

We did our best to enlarge font despite space limitations, but we are willing to work with editorial staff to improve readability as suggested.

6.It would help to have a diagram of the key steps in the cholesterol synthesis pathway for reference early in the paper rather than in figure 3.

We thank the reviewer for his comment, but we don't understand why this would be helpful as we only use sterol modulators involving the pathway's enzyme in fig3. We are open to discussion with editorial staff about moving it up to fig2. If they feel this is needed

7.The authors need to discuss why/how global inhibition of enzymes (e.g. via AY9944 treatment) in a cell could cause reduction in cholesterol levels only in the cilium and not in other cell membranes (see also point 1). Yet, tamoxifen treatment lowers cholesterol across the board.

We thank the reviewer for these insightful comments. Regarding the modest overall effect of simvastatin on cholesterol levels, we would like to note that MDCK cells are an immortalized epithelial cell line with high metabolic plasticity. Such cancer-like cell types are known to exhibit enhanced de novo lipogenesis, particularly under culture conditions with ample glucose availability. This compensatory lipid biosynthesis can partially counterbalance pharmacological inhibition of the cholesterol biosynthetic pathway. Because simvastatin acts upstream in the pathway (at HMG-CoA reductase), its inhibition primarily reduces early intermediates rather than fully depleting end-product cholesterol, explaining the relatively mild changes observed in total cholesterol content. . This has been added in a new paragraph in the revised manuscript (lines 371-378).

8.Fig. 5c, g, and j - statistical analyses are missing and need to be added in support of conclusions drawn in the text of the manuscript.

Thank you, this has been done in the revised manuscript

9.The decrease in the fraction of Smo+ cilia observed in EBP KO cells is mild (panel j, no statistics), and there is possibly a clone-specific effect here as well (statistical analysis is needed to determine if EBP139 is indeed different from WT and whether EBP139 and 141 are different from each other). Similarly, Smo fluorescence intensity after SAG treatment (panel k) is the same in WT and EBP KO cells, while there is a marked difference in intraciliary Smo intensity after tamoxifen treatment. The author's conclusion "...we were able to show that results with human cells aligned with our tamoxifen experiments" (line 436) should be modified to more accurately reflect the presented data. Ditto conclusions on lines 440-442, 530-531. In fact, it is the lack of Hh phenotypes in CDPX2 patients that is consistent with the EBP KO data presented in the paper.

We thank the reviewer for this detailed comment. We have now performed the requested statistical analyses and incorporated them into the revised manuscript.

The new analyses confirm that both EBP139 and EBP141 CRISPR KO clones show a statistically significant reduction in the fraction of Smo⁺ cilia compared to WT cells. They also reveal that the two clones differ significantly from each other, consistent with the expected clonal variability inherent to independently derived CRISPR lines.

Despite this variability, several lines of evidence support our conclusion that the EBP KO phenotypes align with the effects observed after tamoxifen treatment:

1- Directionally consistent reduction in Smo⁺ cilia:

Although the magnitude of the decrease differs between clones, both clones display a significant reduction compared to WT, paralleling the reduction observed in tamoxifen-treated cells. This directional consistency is the key point for comparing pharmacological and genetic perturbations.

2-Converging evidence from SmoM2 experiments:

Tamoxifen treatment also reduces pathway output in the context of SmoM2 overexpression. This supports the interpretation that both EBP inhibition (tamoxifen) and EBP loss (CRISPR KO) impair Hedgehog signaling at the level of ciliary function, albeit more mildly than AY9944/SLOS-like perturbations.

3-Interpretation of Smo intensity (panel k):

As clarified in the revised text, the fluorescence intensities in panel K correspond only to cilia that are Smo-positive. The absence of a difference in intensity therefore does not contradict the observed reduction in the number of Smo⁺ cilia. Rather, it explains why the phenotype is milder than that observed for SLOS/AY9944: when Smo is able to enter the cilium, its enrichment level is comparable to WT.

4- Clinical relevance for CDPX2:

While Hedgehog-related phenotypes in CDPX2 patients may be milder or under-reported, several documented features, such as polydactyly (10% of cases), as well as syndactyly and clubfoot, are classically associated with ciliary/Hedgehog signaling defects. This clinical pattern is consistent with the milder yet detectable defects we observe in EBP KO cells.

Minor •Line 310: 'intraflagellar' rather than 'intraciliary' transport particle B is a more conventional term

We agree that intraflagellar is more conventional than intraciliary, but in this case, this is how the GO term is labeled in the database. In our opinion, it should stay as is.

• Fig. 2c - typos in the color key, is grey meant to be "cells" and blue "cilia"? Individual panels are not referenced in the text

This panel has been removed thanks to comment from reviewer 1 and 3 finding it misleading.

• Lines 357-358: "Notably, AY9944 treatment led to a greater reduction in cholesterol content as well as a greater increase in 7-DHC and 8-DHC in cilia than in the other cell membranes" - the authors need to support this statement with appropriate statistical analysis

We respectfully believe there may be a misunderstanding in the reviewer's concern. In all cases, our comparisons are made between treated vs. untreated conditions within each compartment (cell bulk vs. ciliary membrane), and the statistical significance of these differences is already reported as determined by a Mann-Whitney test. In every case, the changes observed are greater in cilia than in the cell body. The statement in the manuscript simply summarizes this quantitative observation. However, if the reviewer feels that an additional statistical test directly comparing the magnitude of the two compartment-specific changes would strengthen the claim, we are willing to include this analysis. Alternatively, if preferred, we can remove the sentence entirely, as the comparison is already clearly visible in Figure 3b.

• Line 473 - unclear what is meant by "olfactory cilia are mainly sensory and not primary". Primary cilia are sensory.

We agree, primary cilia are sensory, but still different from cilia belonging to sensory epithelia like retina photoreceptors or olfactory cilia. Nevertheless, this statement was modified in revised manuscript

• Line 551: 'data not shown'. Please include the data that you would like to discuss or remove discussion of these data from the manuscript.

The data is not shown because there is nothing to show, as we discussed in that sentence, use of cholesterol probe resulted in the disappearance of primary cilia altogether. We are willing to work with editorial staff to find a better way of expressing this idea.

Reviewer #3 (Significance (Required)):

Overall, the manuscript expands our knowledge of cilia membrane composition and reports an interesting link between SLOS and Shh signaling defects, which could at least in part explain SLOS patients' symptoms. The findings reported in the manuscript could be of interest to a broad audience of cell biologists and geneticists.

We would like to thank the reviewer for his recognition of the importance of this work

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Referee #3

Evidence, reproducibility and clarity

Lamaziere et al. describe an improved protocol for isolating primary cilia from MDCK cells for downstream lipidomics analysis. Using this protocol, they characterize sterol profile of MDCK cilia membrane under standard growth conditions and following pharmacological perturbations that are meant to mimic SLOS and CDPX2 disorders in humans. The authors then assess the impact of the same pharmacological manipulations on Shh pathway activity and validate their findings from these experiments using orthogonal genetic approaches. Major and minor concerns that require attention prior to publication are outlined below.

Major

1. Since the extent of contamination of the cilia preps with non-cilia membranes is unclear, and variability between replicates is not reported, it makes interpretation of changes in cilia membrane sterol composition in response to pharmacological manipulations somewhat difficult to interpret. Discussing reproducibility of cilia sterol composition between replicates (and including corresponding data) could alleviate these concerns to some extent.
2. An abundant non-ciliary membrane protein (rather than GAPDH) may be a more appropriate loading control in Fig. 1C.
3. Fig. 2b - which bar corresponds to cells and which one to cilia? What do numbers inside bars represent? Please label accordingly.
4. Fig. 3b-d, right panels - please define what numbers inside bars represent
5. The font in Figs 2, 3, and 4 is very small and difficult to read. Please make the font and/or panels bigger to improve readability.
6. It would help to have a diagram of the key steps in the cholesterol synthesis pathway for reference early in the paper rather than in figure 3.
7. The authors need to discuss why/how global inhibition of enzymes (e.g. via AY9944 treatment) in a cell could cause reduction in cholesterol levels only in the cilium and not in other cell membranes (see also point 1). Yet, tamoxifen treatment lowers cholesterol across the board.
8. Fig. 5c, g, and j - statistical analyses are missing and need to be added in support of conclusions drawn in the text of the manuscript.
9. The decrease in the fraction of Smo+ cilia observed in EBP KO cells is mild (panel j, no statistics), and there is possibly a clone-specific effect here as well (statistical analysis is needed to determine if EBP139 is indeed different from WT and whether EBP139 and 141 are different from each other). Similarly, Smo fluorescence intensity after SAG treatment (panel k) is the same in WT and EBP KO cells, while there is a marked difference in intraciliary Smo intensity after tamoxifen treatment. The author's conclusion "...we were able to show that results with human cells aligned with our tamoxifen experiments" (line 436) should be modified to more accurately reflect the presented data. Ditto conclusions on lines 440-442, 530-531. In fact, it is the lack of Hh phenotypes in CDPX2 patients that is consistent with the EBP KO data presented in the paper.

Minor

• Line 310: 'intraflagellar' rather than 'intraciliary' transport particle B is a more conventional term
• Fig. 2c - typos in the color key, is grey meant to be "cells" and blue "cilia"? Individual panels are not referenced in the text
• Lines 357-358: "Notably, AY9944 treatment led to a greater reduction in cholesterol content as well as a greater increase in 7-DHC and 8-DHC in cilia than in the other cell membranes" - the authors need to support this statement with appropriate statistical analysis
• Line 473 - unclear what is meant by "olfactory cilia are mainly sensory and not primary". Primary cilia are sensory.
• Line 551: 'data not shown'. Please include the data that you would like to discuss or remove discussion of these data from the manuscript.

Significance

Overall, the manuscript expands our knowledge of cilia membrane composition and reports an interesting link between SLOS and Shh signaling defects, which could at least in part explain SLOS patients' symptoms. The findings reported in the manuscript could be of interest to a broad audience of cell biologists and geneticists.

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

Overview

Accumulating evidence suggests that sterols play critical roles in signal transduction within the primary cilium, perhaps most notably in the Hedgehog cascade. However, the precise sterol composition of the primary cilium, and how it may change under distinct biological conditions, remains unknown, in part because of the lack of reproducible, widely accepted procedures to purify primary cilia from mammalian cultured cells. In the present study, the authors have designed a method to isolate the cilium from the MDCK cells efficiently and then utilized this procedure in conjunction with mass spectrometry to systematically analyze the sterol composition of the ciliary membrane, which they then compare to the sterol composition of the cell body. By analyzing this sterol profiling. the authors claim that the cilium has a distinct sterol composition from the cell body, including higher levels of cholesterol and desmosterol but lower levels of 8-DHC and & Lathosterol. This manuscript further demonstrates that alteration of sterol composition within cilia modulates Hedgehog signaling. These results strengthen the link between dysregulated Hedgehog signaling and defects in cholesterol biosynthesis pathways, as observed in SLOS and CDPX2.

While the ability to isolate primary cilia from cultured MDCK cells represents an important technical achievement, the central claim of the manuscript - that cilia have a different sterol composition from the cell body - is not adequately supported by the data, and more rigorous comparisons between the ciliary membrane and key organellar membranes (such as plasma membrane) are required to make this claim. Moreover, although the authors have repeatedly mention that the ciliary sterol composition is "tightly regulated" there is no evidence provided to support such claim. At best, the data suggest that the cilium and cell body may differ in sterol composition (though even that remains uncertain), but no underlying regulatory mechanisms are demonstrated. In addition, much of the 2nd half of the paper represents a rehash of experiments with sterol biosynthesis inhibitors that have already been published in the literature, making the conceptual advance modest at best. Lastly, the link between CDPX2 and defective Hedgehog signaling is tenuous.

Major comments

Figure 1.

C) Although the isolation of cilium from the MDCK cells using dibucaine treatment seems to be very efficient, the quality control of their fractionation procedure to monitor the isolation is limited to a single western blot of the purified cilia vs. cell body samples, with no representative data shown from the sucrose gradient fractionation steps. Given that prior studies (including those from the Marshall lab cited in this manuscript) found that 1) sucrose gradient fractionation was essential to obtain relatively pure ciliary fractions, and 2) the ciliary fractions appear to spread over many sucrose concentrations in those prior studies , the authors should have included the comparison of the fractionation profile from the sucrose gradient while isolating the primary cilium. This additional information would have further clarified and supported the efficiency of their proposed method. D) The authors presented proteomic data for the peptides analyzed from the isolated cilia in the form of GO term analysis; however, they did not provide examples of different proteins enriched within their fractionation procedure, aside from Arl13b shown in the blot. Including a summary table with representative proteins identified in the isolated ciliary fraction, along with the relative abundance or percentage distribution of these proteins, would make the data more informative.

Figure 2.

The authors represented the comparison of sterol content within the cilia versus whole cell (as cell membranes). Since different organelles have a very diverse degree of cholesterol contents within them, for instance plasma membrane itself is around 50 mol% cholesterol levels while organelles like ER have barely any cholesterol. Thus, comparing these two samples and claiming a 2.5-fold increase in cholesterol levels is misleading. A more appropriate comparison would be between isolated primary cilia and isolated plasma membranes (procedures to isolate plasma membranes have been described previously, e.g., Naito et al., eLife 2019; Das et al, PNAS 2013. The absence of such controls makes it difficult to fully validate the reported magnitude of sterols enrichment in cilia relative to the cell surface. Also, because dibucaine was used here to isolate MDCK cilia, a control experiment to exclude possible effects of the dibucaine treatment on sterol biosynthesis would be helpful.

Figure 3.

Tamoxifen is a potent drug for nuclear hormone receptor activity and thus can independently influence various cellular processes. As several experiments in the later sections of the manuscript rely on tamoxifen treatment of cells, it is important that the authors include appropriate controls for tamoxifen treatment, to confirm that the observed effects do not stem from effects on nuclear hormone receptor activity. This would ensure that the observed effects can be confidently attributed to the experimental manipulation rather than to the intrinsic effects of tamoxifen.

Figure4.

The authors present the results of spectroscopy studies to analyze generalized polarization (GP) of liposomes in vitro , but only processed data are shown, and the raw spectra are not provided. The authors need to present representative spectra to enable the readers to interact the raw data from the experiments.

Figure5.

B) The experiment shown Gli1 mRNA levels following treatment with inhibitors of cholesterol biosynthesis, but similar findings have already been reported previously (e.g., Cooper et al, Nature Genetics 2003; Blassberg et al, Hum Mol Genet 2016), and the present results do not provide a significant conceptual advance over those earlier studies. In addition, the authors analyze the effect of these inhibitors on SAG stimulation, but the experiment lacks the control for Gli mRNA levels in the absence of SAG treatment. Without this control, it is impossible to know where the baseline in the experiment is and how large the effects in question really are. J-K) The data represented in these panels for SAG treatment as fraction of Smo and its fluorescence intensity for the same sample appears to be inconsistent between the two graphs. Under SAG treatment for EBP mutants shows higher Smo fluorescence intensity while Smo positive cilia seems to be less than the wild type control cells. If the number of Smo+ cilia (quantified by eye) differs between conditions, shouldn't the quantification of Smo intensity within cilia show a similar difference? I) The rationale for using SmoM2 in the analysis of cholesterol metabolism-related diseases such as SLOS and CDPX2 is unclear. The SmoM2 variant is primarily associated with cancer rather than cholesterol biosynthesis defects and its relevance either of these disorders is not immediately apparent.

Minor corrections

1. Line 385 seems to be a bit confusing which mentions cilia were treated with AY9944 - do the authors mean that cells were been treated with the drugs before isolation of cilia, or were the purified cilia actually treated with the drugs?
2. The authors should add proper label in Figure 2 panel b for the bars representing the cilia and cell membranes.
3. Panels in Figure S1 should be re-arranged according to the figure legend and figure reference in line 450.
4. Legend for the Figure S1b should be corrected as data sets in graph represents 7 points while technical replicates in legend shows 6 experimental values.
5. The labels for drug in Figure 3 and 5 should be corrected from tamoxifene to tamoxifen and simvastatine to simvastatin.

Significance

In the present study, the authors have designed a method to isolate the cilium from the MDCK cells efficiently and then utilized this procedure in conjunction with mass spectrometry to systematically analyze the sterol composition of the ciliary membrane, which they then compare to the sterol composition of the cell body. By analyzing this sterol profiling. the authors claim that the cilium has a distinct sterol composition from the cell body, including higher levels of cholesterol and desmosterol but lower levels of 8-DHC and & Lathosterol. This manuscript further demonstrates that alteration of sterol composition within cilia modulates Hedgehog signaling. These results strengthen the link between dysregulated Hedgehog signaling and defects in cholesterol biosynthesis pathways, as observed in SLOS and CDPX2.

While the ability to isolate primary cilia from cultured MDCK cells represents an important technical achievement, the central claim of the manuscript - that cilia have a different sterol composition from the cell body - is not adequately supported by the data, and more rigorous comparisons between the ciliary membrane and key organellar membranes (such as plasma membrane) are required to make this claim. Moreover, although the authors have repeatedly mention that the ciliary sterol composition is "tightly regulated" there is no evidence provided to support such claim. At best, the data suggest that the cilium and cell body may differ in sterol composition (though even that remains uncertain), but no underlying regulatory mechanisms are demonstrated. In addition, much of the 2nd half of the paper represents a rehash of experiments with sterol biosynthesis inhibitors that have already been published in the literature, making the conceptual advance modest at best. Lastly, the link between CDPX2 and defective Hedgehog signaling is tenuous.

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Referee #1

Evidence, reproducibility and clarity

Review report for 'Sterols regulate ciliary membrane dynamics and hedgehog signaling in health and disease', Lamazière et al.

In this manuscript, Lamazière et al. address an important understudied aspect of primary cilium biology, namely the sterol composition in the ciliary membrane. It is known that sterols especially play an important role in signal transduction between PTCH1 and SMO, two upstream components of the Hedgehog pathway, at the primary cilium. Moreover, several syndromes linked to cholesterol biosynthesis defects present clinical phenotypes indicative of altered Hh signal transduction. To understand the link between ciliary membrane sterol composition and Hh signal transduction in health and disease, the authors developed a method to isolate primary cilia from MDCK cells and coupled this to quantitative metabolomics. The results were validated using biophysical methods and cellular Hh signaling assays. While this is an interesting study, it is not clear from the presented data how general the findings are: can cilia be isolated from different mammalian cell types using this protocol? Is the sterol composition of MDCK cells expected to the be the same in fibroblasts or other cell types? Without this information, it is difficult to judge whether the conclusions reached in fibroblasts are indeed directly related to the sterol composition detected in MDCK cells. Below is a detailed breakdown of suggested textual changes and experimental validations to strengthen the conclusions of the manuscript.

Major comments:

• It appears that the comparison has been made between ciliary membranes and the rest of the cell's membranes, which includes many other membranes besides the plasma membrane. This significantly weakens the conclusions on the sterol content specific to the cilium, as it may in fact be highly similar to the rest of the plasma membrane. It is for example known that lathosterol is biosynthesized in the ER, and therefore the non-presence in the cilium may reflect a high abundance in the ER but not necessarily in the plasma membrane.
• While the protocol to isolate primary cilium from MDCK cells is a valuable addition to the methods available, it would be good to at least include a discussion on its general applicability. Have the authors tried to use this protocol on fibroblasts for example?
• Some of the conclusions in the introduction (lines 75-80) seem to be incorrectly phrased based on the data: in basal conditions, ciliary membranes are already enriched in cholesterol and desmosterol, and the treatment lowers this in all membranes.
• There seems to be little effect of simvastatin on overall cholesterol levels. Can the authors comment on this result? How would the membrane fluidity be altered when mimicking simvastatin-induced composition? Since the effect on Hh signaling appears to be the biggest (Figure 5B) under simvastatin treatment, it would be interesting to compare this against that found for AY9944 treatment. Also, the authors conclude that the effects of simvastatin treatment on ciliary membrane sterol composition are the mildest, however, one could argue that they are the strongest as there is a complete lack of desmosterol.
• It is not clear to me why the authors have chosen to use SAG to activate the Hh pathway, as this is a downstream mode of activation and bypasses PTCH1 (and therefore a potentially sterol-mediated interaction between the two proteins). It would be very informative to compare the effect of sterol modulation on the ability of ShhN vs SAG to activate the pathway.
• The conclusions about the effect of tamoxifen on SMO trafficking in MEFs should be validated in human patient cells before being able to conclude that there is a potential off-target effect (line 438). Also, if that is the case, the experiment of tamoxifen treatment of EBP KO cells should give an additional effect on SMO trafficking. Also, could the CDPX2 phenotypes in patients be the result of different cell types being affected than the fibroblast used in this study?
• For the experiments with the SMO-M2 mutant, it would be useful to show the extent of pathway activation by the mutant compared to SAG or ShhN treatment of non-transfected cells. Moreover, it will be necessary to exclude any direct effects of the compound treatment on the ability of this mutant to traffic to the primary cilium, which can easily be done using fluorescence microscopy as the mutant is tagged with mCherry.

Minor comments:

Line 74: 'in patients', should be rephrased to 'patient-derived cells'

Figure 2A: What do the '+/-' indicate? They seem to be erroneously placed.

Figure 2B: no label present for which bar represents cilia/other membranes

Figure 2C: this representation is slightly deceptive, since the difference between cells and cilia for lanosterol is not significantly different as shown in figure 2A.

Figure 3A: it would be useful to also show where 8-DHC is in the biosynthetic pathway.

Line 373: the title should be rephrased as it infers that DHCR7 was blocked in model membranes, which is not the case.

Lines 377-384: this paragraph seems to be a mix of methods and some explanation, but should be rephrased for clarity.

Line 403: 'which could explain the resulting defects in Hedgehog signaling': how and what defects? At this point in the study no defects in Hh signaling have been shown.

Figure 4D: 'd' is missing

Line 408: SAG treatment resulted in slightly shorter cilia: this is not the case for just SAG treated cilia, but only for the combination of SAG + AY9944. However, in that condition there appears to be a subpopulation of very short cilia, are those real?

Figure 5b: it would be good to add that all conditions contained SAG.

Figure 5D: Since it is shown in Fig 5C that there are no positive cilia -SAG, there is no point to have empty graphs in Fig 5D on the left side, nor can any statistics be done. Similarly for 5K.

Figure 5E: it is not clearly indicated what is visualized in the inserts, sometimes it's a box, sometimes a line and they seem randomly integrated into the images.

Figure 5H: is this the intensity in just SMO positive cilia? If yes, this should be indicated, and the line at '0' for WT-SAG should be removed. I am also surprised there is then ns found for WT vs SLO, since in WT there are no positive cilia, but in SLO there are a few, so it appears to be more of a black-white situation. Perhaps it would be useful to split the data from different experiments to see if it consistently the case that there is a low percentage of SMO positive cilia in SLO cells. Fig S1: panels are inverted compared to mentioning in the text.

Methods-pharmacological treatments: there appear to be large differences in concentrations chosen to treat MDCK versus MEF cells - can the authors comment on these choices and show that the enzymes are indeed inhibited at the indicated concentrations?

(optional): it would be interesting to include a gamma-tubulin staining on the cilium prep to see if there is indeed a presence of the basal body as suggested by the proteomics data.

There are many spelling mistakes and inconsistencies throughout the manuscript and its figures (mix of French and English for example) so careful proofreading would be warranted. Moreover, there are many mentionings of 'Hedgehog defects' or 'Hedgehog-linked', where in fact it is a defect in or link to the Hedgehog pathway, not the protein itself. This should be corrected.

Significance

The study of ciliary membrane composition is highly relevant to understand signal transduction in health and disease. As such, the topic of this manuscript is significant and timely. However, as indicated above, there are limitations to this study, most notably the comparison of ciliary membrane versus all cellular membranes (rather than the plasma membrane), which weakens the conclusions that can be drawn. Moreover, cell-type dependency should be more thoroughly addressed. There certainly is a methodological advance in the form of cilia isolation from MDCK cells, however, it is unclear how broadly applicable this is to other mammalian cell types.

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Reply to the reviewers

The authors do not wish to provide a response at this time.

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Referee #3

Evidence, reproducibility and clarity

This manuscript investigates the role of DOT1L and its H3K79 methyltransferase activity in dendritic cell (DC) differentiation. The authors employ a combination of in vitro FLT3L/SCF bone marrow culture systems, in vivo inducible knockout models, and genome-wide H3K79me2 ChIP-seq and RNA-seq analyses to demonstrate that DOT1L influences the balance between pDC and cDC2 differentiation, while leaving cDC1 development largely unaffected. The study further identifies transcriptional and epigenetic programs associated with these changes, linking DOT1L deficiency to altered antigen presentation pathways and loss of pDC-associated transcription factors. The paper provides valuable insights into DC biology. However, some of the key conclusions rely heavily on in vitro systems and short-term tamoxifen deletion models, which limit the interpretation of the in vivo data. Strengthening or clearly defining these limitations would substantially improve the paper's impact and clarity.

Major Comments

1. To strengthen the paper, the authors could follow one of two alternative strategies:

(1) Validate their in vitro observations through in vivo experiments, or

(2) Focus on deepening and refining their in vitro findings, moving the limited in vivo data to the supplementary material and explicitly acknowledging the limitations of the tamoxifen-inducible system.

Strategy 1 - Strengthen in vivo validation

-   The experiments presented in Figures 3 and 5 could be repeated in a competitive bone marrow chimera setting (e.g. CD45.1/CD45.2 irradiated hosts reconstituted with a 1:1 mix of WT CD45.1⁺ and Dot1l-KO CD45.2⁺ cells).
-   This design would allow dissection of direct (cell-intrinsic) versus indirect effects of DOT1L deficiency and could mitigate confounding effects of incomplete or asynchronous deletion.
-   After reconstitution, mice could be maintained on tamoxifen-supplemented chow for a longer period to ensure efficient recombination and adequate time for observing phenotypic consequences.
-   Flow cytometric analysis of spleen and bone marrow should use more refined panels to explore DC precursor and subset deficiencies. Suggested reference panels: Rodrigues et al., Immunity 2024; Minutti et al., Nat. Immunol. 2024; Zhu et al., Nat. Immunol. 2015.

Strategy 2 - Refine in vitro system and reposition in vivo data - The authors could replicate their differentiation assays under conditions that emulate the chimera approach by co-culturing WT (CD45.1⁺) and Dot1l-KO (CD45.2⁺) bone marrow cells. - This would reveal potential competition or cross-talk between WT and mutant cells and provide clearer mechanistic insight into cell-intrinsic versus extrinsic effects. - The authors should examine how tamoxifen itself affects differentiation and measure the kinetics of deletion and H3K79me loss to better contextualize the dynamic response. - It would also be valuable to assess which cDC2 subtypes (A vs. B) are preferentially affected by Dot1l deficiency, again using more sophisticated flow cytometry panels (see references above). If this in vitro-focused strategy is adopted, the in vivo data could be moved to the supplementary material, with explicit acknowledgment that the inducible deletion model and the gradual nature of H3K79me dilution limit the interpretation of the in vivo findings. 2. In Figures 2 and 3, the efficiency of H3K79me2 depletion following Dot1l excision should be assessed directly. Although DOT1L is the sole H3K79 methyltransferase, the dilution kinetics of H3K79me2 can vary depending on the proliferation rate. Quantifying the H3K79me2 signal in bone marrow-derived cell culture samples would clarify whether the deletion window allowed complete loss of the methylation mark. 3. Several observations are not discussed in sufficient depth: - The finding that Dot1l deletion increases antigen-presentation signatures might reflect stress or activation rather than lineage fate change. - The authors could also acknowledge that DOT1L's effect might be indirect, acting through cytokine feedback loops or altered progenitor proliferation, especially given the co-expression of Kit, Flt3, and Irf8 in early DC progenitors. - Moreover, because H3K79 methylation is primarily associated with transcriptional elongation rather than initiation, the observed transcriptional changes could result from broader alterations in chromatin accessibility or polymerase processivity, rather than direct promoter regulation. Discussing this mechanistic aspect would help clarify whether DOT1L's role in DC differentiation reflects a direct control of lineage-defining gene expression or a secondary consequence of disrupted transcriptional elongation dynamics.

Minor Comments

1. Terminology: The manuscript repeatedly refers to "mature" DCs-please clarify whether this means activated or fully differentiated cells.
2. Ontogeny statements: <br /> The assertion that DCs of lymphoid origin are well established should be softened; the lymphoid contribution to some DC lineages remains under discussion.
3. Transitional DCs (tDCs): <br /> The equivalence between tDCs and pre-cDC2As remains controversial. This should be acknowledged.
4. Cytokine supplementation: <br /> The inclusion of SCF in the FLT3L-based differentiation assays should be justified, it is not a standard procedure.
5. Macrophage contamination: <br /> The presence of C1qa, C1qb, and C1qc transcripts in some datasets suggests possible macrophage contamination. Please discuss how this was controlled for or how it might affect interpretation.

Significance

This study provides important insights into the epigenetic regulation of DC differentiation by DOT1L. The conclusions would be more compelling if supported by in vivo validation or, alternatively, if the limitations of the current in vivo data were transparently acknowledged and the focus shifted toward mechanistic in vitro depth.

With these revisions, the manuscript would represent a valuable contribution to understanding how chromatin modification integrates with transcriptional control in shaping dendritic cell fate.

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Referee #2

Evidence, reproducibility and clarity

Bouma et al. present a comprehensive analysis of DOT1L-mediated histone H3K79 methylation across canonical DC subsets. By mapping the methylation landscape, the authors demonstrate that DOT1L regulates both shared and subset-specific gene programs. They show that in vitro or in vivo deletion of Dot1l, followed by in vitro differentiation, results in reduced myeloid progenitors and pDCs alongside an increase in cDC2s, while cDC1 numbers remain largely unaffected. Functionally, Dot1l-deficient DCs fail to produce IFNα upon stimulation. Transcriptomic profiling reveals enrichment of antigen presentation pathways in Dot1l-KO subsets, with upregulated MHC class II surface expression in pDCs. Mechanistically, pharmacological inhibition of DOT1L links these effects to its methyltransferase activity. Collectively, the data suggest that DOT1L differentially regulates canonical DC subset development and represses antigen presentation pathways.

The manuscript is well-written and technically sound. However, several conclusions would benefit from deeper discussion or additional experimental validation.

Major Comments

1. Interpretation of DC balance changes and cell-cycle effects

The authors propose that DOT1L loss skews DC differentiation toward a pDC-like phenotype. However, DOT1L deletion or inhibition, and the consequent global loss of H3K79 methylation, is well known to downregulate key cell-cycle genes (e.g., Cyclin D1, Cyclin E, CDK4/6, MCM family) while upregulating cell-cycle inhibitors (e.g., Cdkn1a and b). These transcriptional changes are associated with slower proliferation, G1 arrest or delayed S-phase entry, and reduced DNA replication fork progression. Importantly, blocking DNA synthesis (e.g., with aphidicolin or mitomycin C) during early culture inhibits DC emergence, underscoring that proliferation is essential for differentiation. The authors should discuss how their findings align with this established literature. Could the observed DC subset shifts result from impaired cell-cycle progression rather than lineage-specific transcriptional reprogramming? A more detailed consideration of this point is needed. 2. Discrepancy between in vitro and in vivo pDC phenotypes

The in vitro data show a marked reduction in pDCs, yet in vivo pDC numbers appear unchanged. Although the discussion briefly mentions proliferation differences, this discrepancy deserves a clearer explanation or experimental follow-up.

Minor Comments

• Clarify statistical methods, specify biological replicate numbers, and indicate whether corrections for multiple comparisons were applied to transcriptomic analyses.
• The introduction is somewhat lengthy and repetitive; condensing it would improve focus.
• In the discussion sometimes it is not clear the distinction between findings and speculation.
• Ensure consistent gene name formatting throughout (e.g., Dot1l, Dot1L).

Significance

The current manuscript fills a gap in knowledge, and this is its major strength. Other strengths are clarity and technical appropriateness.

The major weakness is that the work is mainly descriptive. Mechanistic insights into DOT1L-dependent transcriptional regulation are still weak. The proposed mechanism -that DOT1L maintains pDC identity through H3K79 methylation at key transcription factors (Tcf4, SpiB, Irf8)- is intriguing but currently lacks functional evidence. The authors should consider validating this model experimentally, by modulating the expression of these genes without affecting DOT1L activity. Also the model suggesting that DOT1L indirectly represses antigen presentation via the Fbxo11-Ciita pathway is interesting but remains speculative. Additional mechanistic data would help support this claim.

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Referee #1

Evidence, reproducibility and clarity

Summary:

In this study, Bouma et al. investigate the epigenetic mechanisms involved in dendritic cell (DC) development, focusing on the role of the lysine methyltransferase DOT1L, which mediates histone H3 lysine 79 (H3K79) methylation. The authors first show that Dot1l is expressed across most DC subsets and their progenitors. Consistently, DOT1L activity was detected in these subsets, as ChIP-seq analysis revealed an enrichment of H3K79 methylation marks around the transcription start sites of numerous genes that regulate DC fate. These marks were associated with active transcription, as confirmed by RNA sequencing. To assess the functional role of Dot1l in DC development, the authors used Rosa26Cre-ERT2 × Dot1l^flox/flox mice. Bone marrow (BM) cells from these mice were treated in vitro with tamoxifen and cultured with FLT3L and SCF to induce DC differentiation. Dot1l deletion impaired the development of plasmacytoid DCs (pDCs) and enhanced the generation of conventional DC2 (cDC2), while leaving cDC1 development unaffected. Similarly, in vivo tamoxifen treatment of Rosa26Cre-ERT2 × Dot1l^flox/flox mice for three days led to a comparable impairment of DC development upon in vitro culture of BM cells. Beyond mature DCs, Dot1l deletion also disrupted the ability of BM cells to generate common myeloid progenitors (CMPs), monocyte-dendritic cell progenitors (MDPs), and common DC progenitors (CDPs). These effects were attributed to the methyltransferase activity of DOT1L, as pharmacological inhibition of DOT1L produced similar outcomes. Interestingly, while in vivo tamoxifen treatment altered the frequencies of progenitor populations (MDP, CDP, CMP) in the BM, it did not significantly change the frequency of pDCs in the BM or spleen. Moreover, an increase in the cDC2 population was observed only in the BM, with no effect detected in the spleen. With these findings the authors claim that epigenetic regulation of gene expression by DOT1L is important for proper dendritic cell development.

Major comments.

While this study demonstrates that DOT1L regulates DC development in vitro, its inducible deletion in vivo using tamoxifen does not appear to significantly affect the overall distribution or function of DCs. Therefore, further investigation is needed to clarify the role of DOT1L in regulating DC fate under physiological conditions. The authors analyzed DC populations at only two time points (3 and 12 days) following tamoxifen-induced Dot1l deletion. As noted in the discussion, these time points are relatively early considering the lifespan of DCs, which often extends beyond this period. It would thus be important to assess the effects of Dot1l deletion over a longer duration (e.g., at least one month) to fully evaluate its impact on DC development. In addition to the BM, an extensive analysis of DCs population should be carried in the spleen as well as lymph nodes. Given the broad activity of the Rosa26-Cre system, prolonged deletion may affect overall mouse health and/or the function of other cell types that contribute to DC development; therefore, using a DC-specific Cre driver (e.g., CD11c-Cre) would provide a more targeted approach. Alternatively, competitive BM chimera experiments could be performed by reconstituting irradiated control mice with a 1:1 mixture of BM cells from Rosa26Cre-ERT2 × Dot1l^flox/flox and Rosa26Cre-ERT2 × Dot1l^wt/flox mice, both pre-treated with tamoxifen in vitro. Such experiments would offer more definitive evidence for the role of DOT1L in DC development in vivo. Aside from this point, the data and methods are clearly presented, and the figures are largely self-explanatory. All experiments were adequately replicated three times. Statistical analyses were primarily performed using t-tests, and ANOVA with multiple comparisons when appropriate. Since these are parametric tests that assume a normal distribution, it would be important to confirm whether the analyzed samples meet this assumption. If not, non-parametric tests should be used instead.

Minor comments.

It would be informative to show how specific Dot1l expression is in DCs and their progenitors compared with other immune lineages (e.g., lymphocytes) and their precursors. The data suggest that DOT1L regulates H3K79 methylation of both shared and subset-specific genes among DC populations. The authors could elaborate on how this regulation achieves cell-type specificity-perhaps through differential Dot1l expression levels across DC subsets.

Interestingly, Dot1l deletion both in vitro and in vivo markedly reduces the frequency of common DC progenitors (CDPs), which give rise to cDC1 and cDC2. The authors should discuss how such a substantial loss of progenitors does not proportionally affect downstream cDC populations. Although in vivo tamoxifen-induced deletion of Dot1l in Rosa26Cre-ERT2 × Dot1l^flox/flox mice does not significantly alter the overall distribution of DC subsets (pDCs and cDCs), it appears to modify their phenotype. It would therefore be valuable to examine how Dot1l loss impacts the functional properties of individual DC subsets. While pDC responsiveness to CpG stimulation seems preserved in the absence of Dot1l, assessing how cDCs respond to TLR3 and TLR4 stimulation and their capacity to activate T cells would provide important additional insights.

Significance

General assessment: Bouma et al. present compelling evidence that DOT1L is an important regulator of DC differentiation in vitro from bone marrow-derived cells. They further demonstrate that DOT1L regulates DC development through its lysine methyltransferase activity, mediating histone H3K79 methylation. While these in vitro findings are robust and well supported, the physiological relevance of DOT1L function in vivo remains less clearly established. Additional experiments would help to strengthen the conclusions regarding its role under physiological conditions.

Advance: While numerous transcription factors have been described as key regulators of DC subset development and fate, the role of epigenetic regulation in this process remains relatively understudied and poorly understood. This study addresses this important gap in the literature and provides novel insights into the role of H3K79 methylation mediated by DOT1L in controlling DC development.

Audience: This paper will be of interest for a specialized audience in the field of the regulation of dendritic cell ontogeny. This work could influence additional research to investigate the epigenitc regulation of DCs development.

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Reply to the reviewers

We would like to thank all the reviewers for their valuable comments and criticisms. We have thoroughly revised the manuscript and the resource to address all the points raised by the reviewers. Below, we provide a point-by-point response for the sake of clarity.

Reviewer #1

__Evidence, reproducibility and clarity __

Summary: This manuscript, "MAVISp: A Modular Structure-Based Framework for Protein Variant Effects," presents a significant new resource for the scientific community, particularly in the interpretation and characterization of genomic variants. The authors have developed a comprehensive and modular computational framework that integrates various structural and biophysical analyses, alongside existing pathogenicity predictors, to provide crucial mechanistic insights into how variants affect protein structure and function. Importantly, MAVISp is open-source and designed to be extensible, facilitating reuse and adaptation by the broader community.

Major comments: - While the manuscript is formally well-structured (with clear Introduction, Results, Conclusions, and Methods sections), I found it challenging to follow in some parts. In particular, the Introduction is relatively short and lacks a deeper discussion of the state-of-the-art in protein variant effect prediction. Several methods are cited but not sufficiently described, as if prior knowledge were assumed. OPTIONAL: Extend the Introduction to better contextualize existing approaches (e.g., AlphaMissense, EVE, ESM-based predictors) and clarify what MAVISp adds compared to each.

We have expanded the introduction on the state-of-the-art of protein variant effects predictors, explaining how MAVISp departs from them.

- The workflow is summarized in Figure 1(b), which is visually informative. However, the narrative description of the pipeline is somewhat fragmented. It would be helpful to describe in more detail the available modules in MAVISp, and which of them are used in the examples provided. Since different use cases highlight different aspects of the pipeline, it would be useful to emphasize what is done step-by-step in each.

We have added a concise, narrative description of the data flow for MAVISp, as well as improved the description of modules in the main text. We will integrate the results section with a more comprehensive description of the available modules, and then clarify in the case studies which modules were applied to achieve specific results.

OPTIONAL: Consider adding a table or a supplementary figure mapping each use case to the corresponding pipeline steps and modules used.

We have added a supplementary table (Table S2) to guide the reader on the modules and workflows applied for each case study

We also added Table S1 to map the toolkit used by MAVISp to collect the data that are imported and aggregated in the webserver for further guidance.

- The text contains numerous acronyms, some of which are not defined upon first use or are only mentioned in passing. This affects readability. OPTIONAL: Define acronyms upon first appearance, and consider moving less critical technical details (e.g., database names or data formats) to the Methods or Supplementary Information. This would greatly enhance readability.

We revised the usage of acronyms following the reviewer’s directions of defying them at first appearance.

• The code and trained models are publicly available, which is excellent. The modular design and use of widely adopted frameworks (PyTorch and PyTorch Geometric) are also strong points. However, the Methods section could benefit from additional detail regarding feature extraction and preprocessing steps, especially the structural features derived from AlphaFold2 models. OPTIONAL: Include a schematic or a table summarizing all feature types, their dimensionality, and how they are computed.

We thank the reviewer for noticing and praising the availability of the tools of MAVISp. Our MAVISp framework utilizes methods and scores that incorporate machine learning features (such as EVE or RaSP), but does not employ machine learning itself. Specifically, we do not use PyTorch and do not utilize features in a machine learning sense. We do extract some information from the AlphaFold2 models that we use (such as the pLDDT score and their secondary structure content, as calculated by DSSP), and those are available in the MAVISp aggregated csv files for each protein entry and detailed in the Documentation section of the MAVISp website.

• The section on transcription factors is relatively underdeveloped compared to other use cases and lacks sufficient depth or demonstration of its practical utility. OPTIONAL: Consider either expanding this section with additional validation or removing/postponing it to a future manuscript, as it currently seems preliminary.

We have removed this section and included a mention in the conclusions as part of the future directions.

Minor comments: - Most relevant recent works are cited, including EVE, ESM-1v, and AlphaFold-based predictors. However, recent methods like AlphaMissense (Cheng et al., 2023) could be discussed more thoroughly in the comparison.

We have revised the introduction to accommodate the proper space for this comparison.

• Figures are generally clear, though some (e.g., performance barplots) are quite dense. Consider enlarging font sizes and annotating key results directly on the plots.

We have revised Figure 2 and presented only one case study to simplify its readability. We have also changed Figure 3, whereas retained the other previous figures since they seemed less problematic.

• Minor typographic errors are present. A careful proofreading is highly recommended. Below are some of the issues I identified: Page 3, line 46: "MAVISp perform" -> "MAVISp performs" Page 3, line 56: "automatically as embedded" -> "automatically embedded" Page 3, line 57: "along with to enhance" -> unclear; please revise Page 4, line 96: "web app interfaces with the database and present" -> "presents" Page 6, line 210: "to investigate wheatear" -> "whether" Page 6, lines 215-216: "We have in queue for processing with MAVISp proteins from datasets relevant to the benchmark of the PTM module." -> unclear sentence; please clarify Page 15, line 446: "Both the approaches" -> "Both approaches" Page 20, line 704: "advantage of multi-core system" -> "multi-core systems"

We have done a proofreading of the entire article, including the points above

Significance

General assessment: the strongest aspects of the study are the modularity, open-source implementation, and the integration of structural information through graph neural networks. MAVISp appears to be one of the few publicly available frameworks that can easily incorporate AlphaFold2-based features in a flexible way, lowering the barrier for developing custom predictors. Its reproducibility and transparency make it a valuable resource. However, while the technical foundation is solid and the effort substantial, the scientific narrative and presentation could be significantly improved. The manuscript is dense and hard to follow in places, with a heavy use of acronyms and insufficient explanation of key design choices. Improving the descriptive clarity, especially in the early sections, would greatly enhance the impact of this work.

Advance

to the best of my knowledge, this is one of the first modular platforms for protein variant effect prediction that integrates structural data from AlphaFold2 with bioinformatic annotations and even clinical data in an extensible fashion. While similar efforts exist (e.g., ESMfold, AlphaMissense), MAVISp distinguishes itself through openness and design for reusability. The novelty is primarily technical and practical rather than conceptual.

Audience

this study will be of strong interest to researchers in computational biology, structural bioinformatics, and genomics, particularly those developing variant effect predictors or analyzing the impact of mutations in clinical or functional genomics contexts. The audience is primarily specialized, but the open-source nature of the tool may diffuse its use among more applied or translational users, including those working in precision medicine or protein engineering.

Reviewer expertise: my expertise is in computational structural biology, molecular modeling, and (rather weak) machine learning applications in bioinformatics. I am familiar with graph-based representations of proteins, AlphaFold2, and variant effects based on Molecular Dynamics simulations. I do not have any direct expertise in clinical variant annotation pipelines.

Reviewer #2

__Evidence, reproducibility and clarity __

Summary: The authors present a pipeline and platform, MAVISp, for aggregating, displaying and analysis of variant effects with a focus on reclassification of variants of uncertain clinical significance and uncovering the molecular mechanisms underlying the mutations.

Major comments: - On testing the platform, I was unable to look-up a specific variant in ADCK1 (rs200211943, R115Q). I found that despite stating that the mapped refseq ID was NP_001136017 in the HGVSp column, it was actually mapped to the canonical UniProt sequence (Q86TW2-1). NP_001136017 actually maps to Q86TW2-3, which is missing residues 74-148 compared to the -1 isoform. The Uniprot canonical sequence has no exact RefSeq mapping, so the HGVSp column is incorrect in this instance. This mapping issue may also affect other proteins and result in incorrect HGVSp identifiers for variants.

We would like to thank the reviewer for pointing out these inconsistencies. We have revised all the entries and corrected them. If needed, the history of the cases that have been corrected can be found in the closed issues of the GitHub repository that we use for communication between biocurators and data managers (https://github.com/ELELAB/mavisp_data_collection). We have also revised the protocol we follow in this regard and the MAVISp toolkit to include better support for isoform matching in our pipelines for future entries, as well as for the revision/monitoring of existing ones, as detailed in the Method Section. In particular, we introduced a tool, uniprot2refseq, which aids the biocurator in identifying the correct match in terms of sequence length and sequence identity between RefSeq and UniProt. More details are included in the Method Section of the paper. The two relevant scripts for this step are available at: https://github.com/ELELAB/mavisp_accessory_tools/

- The paper lacks a section on how to properly interpret the results of the MAVISp platform (the case-studies are helpful, but don't lay down any global rules for interpreting the results). For example: How should a variant with conflicts between the variant impact predictors be interpreted? Are specific indicators considered more 'reliable' than others?

We have added a section in Results to clarify how to interpret results from MAVISp in the most common use cases.

• In the Methods section, GEMME is stated as being rank-normalised with 0.5 as a threshold for damaging variants. On checking the data downloaded from the site, GEMME was not rank-normalised but rather min-max normalised. Furthermore, Supplementary text S4 conflicts with the methods section over how GEMME scores are classified, S4 states that a raw-value threshold of -3 is used.

We thank the reviewer for spotting this inconsistency. This part in the main text was left over from a previous and preliminary version of the pre-print, we have revised the main text. Supplementary Text S4 includes the correct reference for the value in light of the benchmarking therewithin.

• Note. This is a major comment as one of the claims is that the associated web-tool is user-friendly. While functional, the web app is very awkward to use for analysis on any more than a few variants at once. The fixed window size of the protein table necessitates excessive scrolling to reach your protein-of-interest. This will also get worse as more proteins are added. Suggestion: add a search/filter bar. The same applies to the dataset window.

We have changed the structure of the webserver in such a way that now the whole website opens as its own separate window, instead of being confined within the size permitted by the website at DTU. This solves the fixed window size issue. Hopefully, this will improve the user experience.

We have refactored the web app by adding filtering functionality, both for the main protein table (that can now be filtered by UniProt AC, gene name or RefSeq ID) and the mutations table. Doing this required a general overhaul of the table infrastructure (we changed the underlying engine that renders the tables).

• You are unable to copy anything out of the tables.
• Hyperlinks in the tables only seem to work if you open them in a new tab or window.

The table overhauls fixed both of these issues

• All entries in the reference column point to the MAVISp preprint even when data from other sources is displayed (e.g. MAVE studies).

We clarified the meaning of the reference column in the Documentation on the MAVISp website, as we realized it had confused the reviewer. The reference column is meant to cite the papers where the computationally-generated MAVISp data are used, not external sources. Since we also have the experimental data module in the most recent release, we have also refactored the MAVISp website by adding a “Datasets and metadata” page, which details metadata for key modules. These include references to data from external sources that we include in MAVISp on a case-by-case basis (for example the results of a MAVE experiment). Additionally, we have verified that the papers using MAVISp data are updated in https://elelab.gitbook.io/mavisp/overview/publications-that-used-mavisp-data and in the csv file of the interested proteins.

Here below the current references that have been included in terms of publications using MAVISp data:

SMPD1

ASM variants in the spotlight: A structure-based atlas for unraveling pathogenic mechanisms in lysosomal acid sphingomyelinase

Biochim Biophys Acta Mol Basis Dis

38782304

https://doi.org/10.1016/j.bbadis.2024.167260

TRAP1

Point mutations of the mitochondrial chaperone TRAP1 affect its functions and pro-neoplastic activity

Cell Death & Disease

40074754

https://doi.org/10.1038/s41419-025-07467-6

BRCA2

Saturation genome editing-based clinical classification of BRCA2 variants

Nature

39779848

0.1038/s41586-024-08349-1

TP53, GRIN2A, CBFB, CALR, EGFR

TRAP1 S-nitrosylation as a model of population-shift mechanism to study the effects of nitric oxide on redox-sensitive oncoproteins

Cell Death & Disease

37085483

10.1038/s41419-023-05780-6

KIF5A, CFAP410, PILRA, CYP2R1

Computational analysis of five neurodegenerative diseases reveals shared and specific genetic loci

Computational and Structural Biotechnology Journal

38022694

https://doi.org/10.1016/j.csbj.2023.10.031

KRAS

Combining evolution and protein language models for an interpretable cancer driver mutation prediction with D2Deep

Brief Bioinform

39708841

https://doi.org/10.1093/bib/bbae664

OPTN

Decoding phospho-regulation and flanking regions in autophagy-associated short linear motifs

Communications Biology

40835742

10.1038/s42003-025-08399-9

DLG4,GRB2,SMPD1

Deciphering long-range effects of mutations: an integrated approach using elastic network models and protein structure networks

JMB

40738203

doi: 10.1016/j.jmb.2025.169359

Entering multiple mutants in the "mutations to be displayed" window is time-consuming for more than a handful of mutants. Suggestion: Add a box where multiple mutants can be pasted in at once from an external document.

During the table overhaul, we have revised the user interface to add a text box that allows free copy-pasting of mutation lists. While we understand having a single input box would have been ideal, the former selection interface (which is also still available) doesn’t allow copy-paste. This is a known limitation in Streamlit.

Minor comments

• Grammar. I appreciate that this manuscript may have been compiled by a non-native English speaker, but I would be remiss not to point out that there are numerous grammar errors throughout, usually sentence order issues or non-pluralisation. The meaning of the authors is mostly clear, but I recommend very thoroughly proof-reading the final version.

We have done proofreading on the final version of the manuscript

• There are numerous proteins that I know have high-quality MAVE datasets that are absent in the database e.g. BRCA1, HRAS and PPARG.

Yes, we are aware of this. It is far from trivial to properly import the datasets from multiplex assays. They often need to be treated on a case-by-case basis. We are in the process of carefully compiling locally all the MAVE data before releasing it within the public version of the database, so this is why they are missing. We are giving priorities to the ones that can be correlated with our predictions on changes in structural stability and then we will also cover the rest of the datasets handling them in batches. Having said this, we have checked the dataset for BRCA1, HRAS, and PPARG. We have imported the ones for PPARG and BRCA1 from ProtGym, referring to the studies published in 10.1038/ng.3700 and 10.1038/s41586-018-0461-z, respectively. Whereas for HRAS, checking in details both the available data and literature, while we did identify a suitable dataset (10.7554/eLife.27810), we struggled to understand what a sensible cut-off for discriminating between pathogenic and non-pathogenic variants would be, and so ended up not including it in the MAVISp dataset for now. We will contact the authors to clarify which thresholds to apply before importing the data.

• Checking one of the existing MAVE datasets (KRAS), I found that the variants were annotated as damaging, neutral or given a positive score (these appear to stand-in for gain-of-function variants). For better correspondence with the other columns, those with positive scores could be labelled as 'ambiguous' or 'uncertain'.

In the KRAS case study presented in MAVISP, we utilized the protein abundance dataset reported in (http://dx.doi.org/10.1038/s41586-023-06954-0) and made available in the ProteinGym repository (specifically referenced at https://github.com/OATML-Markslab/ProteinGym/blob/main/reference_files/DMS_substitutions.csv#L153). We adopted the precalculated thresholds as provided by the ProteinGym authors. In this regard, we are not really sure the reviewer is referring to this dataset or another one on KRAS.

• Numerous thresholds are defined for stabilizing / destabilizing / neutral variants in both the STABILITY and the LOCAL_INTERACTION modules. How were these thresholds determined? I note that (PMC9795540) uses a ΔΔG threshold of 1/-1 for defining stabilizing and destabilizing variants, which is relatively standard (though they also say that 2-3 would likely be better for pinpointing pathogenic variants).

We improved the description of our classification strategies for both modules in the Documentation page of our website. Also, we explained more clearly the possible sources of ‘uncertain’ annotations for the two modules in both the web app (Documentation page) and main text. Briefly, in the STABILITY module, we consider FoldX and either Rosetta or RaSP to achieve a final classification. We first classify one and the other independently, according to the following strategy:

If DDG ≥ 3, the mutation is Destabilizing If DDG ≤ −3, the mutation is Stabilizing If −2 We then compare the classifications obtained by the two methods: if they agree, then that is the final classification, if they disagree, then the final classification is Uncertain. The thresholds were selected based on a previous study, in which variants with changes in stability below 3 kcal/mol were not featuring a markedly different abundance at cellular level [10.1371/journal.pgen.1006739, 10.7554/eLife.49138]

Regarding the LOCAL_INTERACTION module, it works similarly as for the Stability module, in that Rosetta and FoldX are considered independently, and an implicit classification is performed for each, according to the rules (values in kcal/mol)

If DDG > 1, the mutation is Destabilizing. If DDG Each mutation is therefore classified for both methods. If the methods agree (i.e., if they classify the mutation in the same way), their consensus is the final classification for the mutation; if they do not agree, the final classification will be Uncertain.

If a mutation does not have an associated free energy value, the relative solvent accessible area is used to classify it: if SAS > 20%, the mutation is classified as Uncertain, otherwise it is not classified.

Thresholds here were selected according to best practices followed by the tool authors and more in general in the literature, as the reviewer also noticed.

• "Overall, with the examples in this section, we illustrate different applications of the MAVISp results, spanning from benchmarking purposes, using the experimental data to link predicted functional effects with structural mechanisms or using experimental data to validate the predictions from the MAVISp modules."

The last of these points is not an application of MAVISp, but rather a way in which external data can help validate MAVISp results. Furthermore, none of the examples given demonstrate an application in benchmarking (what is being benchmarked?).

We have revised the statements to avoid this confusion in the reader.

• Transcription factors section. This section describes an intended future expansion to MAVISp, not a current feature, and presents no results. As such, it should be moved to the conclusions/future directions section.

We have removed this section and included a mention in the conclusions as part of the future directions.

• Figures. The dot-plots generated by the web app, and in Figures 4, 5 and 6 have 2 legends. After looking at a few, it is clear that the lower legend refers to the colour of the variant on the X-axis - most likely referencing the ClinVar effect category. This is not, however, made clear either on the figures or in the app.

The reviewer’s interpretation on the second legend is correct - it does refer to the ClinVar classification. Nonetheless, we understand the positioning of the legend makes understanding what the legend refers to not obvious. We also revised the captions of the figures in the main text. On the web app, we have changed the location of the figure legend for the ClinVar effect category and added a label to make it clear what the classification refers to.

• "We identified ten variants reported in ClinVar as VUS (E102K, H86D, T29I, V91I, P2R, L44P, L44F, D56G, R11L, and E25Q, Fig.5a)" E25Q is benign in ClinVar and has had that status since first submitted.

We have corrected this in the text and the statements related to it.

Significance

Platforms that aggregate predictors of variant effect are not a new concept, for example dbNSFP is a database of SNV predictions from variant effect predictors and conservation predictors over the whole human proteome. Predictors such as CADD and PolyPhen-2 will often provide a summary of other predictions (their features) when using their platforms. MAVISp's unique angle on the problem is in the inclusion of diverse predictors from each of its different moules, giving a much wider perspective on variants and potentially allowing the user to identify the mechanistic cause of pathogenicity. The visualisation aspect of the web app is also a useful addition, although the user interface is somewhat awkward. Potentially the most valuable aspect of this study is the associated gitbook resource containing reports from biocurators for proteins that link relevant literature and analyse ClinVar variants. Unfortunately, these are only currently available for a small minority of the total proteins in the database with such reports. For improvement, I think that the paper should focus more on the precise utility of the web app / gitbook reports and how to interpret the results rather than going into detail about the underlying pipeline.

We appreciate the interest in the gitbook resource that we also see as very valuable and one of the strengths of our work. We have now implemented a new strategy based on a Python script introduced in the mavisp toolkit to generate a template Markdown file of the report that can be further customized and imported into GitBook directly (​​https://github.com/ELELAB/mavisp_accessory_tools/). This should allow us to streamline the production of more reports. We are currently assigning proteins in batches for reporting to biocurator through the mavisp_data_collection GitHub to expand their coverage. Also, we revised the text and added a section on the interpretation of results from MAVISp. with a focus on the utility of the web-app and reports.

In terms of audience, the fast look-up and visualisation aspects of the web-platform are likely to be of interest to clinicians in the interpretation of variants of unknown clinical significance. The ability to download the fully processed dataset on a per-protein database would be of more interest to researchers focusing on specific proteins or those taking a broader view over multiple proteins (although a facility to download the whole database would be more useful for this final group).

While our website only displays the dataset per protein, the whole dataset, including all the MAVISp entries, is available at our OSF repository (https://osf.io/ufpzm/), which is cited in the paper and linked on the MAVISp website. We have further modified the MAVISp database to add a link to the repository in the modes page, so that it is more visible.

My expertise. - I am a protein bioinformatician with a background in variant effect prediction and large-scale data analysis.

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

Evidence, reproducibility and clarity:

Summary:

The authors present MAVISp, a tool for viewing protein variants heavily based on protein structure information. The authors have done a very impressive amount of curation on various protein targets, and should be commended for their efforts. The tool includes a diverse array of experimental, clinical, and computational data sources that provides value to potential users interested in a given target.

Major comments:

Unfortunately I was not able to get the website to work correctly. When selecting a protein target in simple mode, I was greeted with a completely blank page in the app window. In ensemble mode, there was no transition away from the list of targets at all. I'm using Firefox 140.0.2 (64-bit) on Ubuntu 22.04. I would like to explore the data myself and provide feedback on the user experience and utility.

We have tried reproducing the issue mentioned by the reviewer, using the exact same Ubuntu and Firefox versions, but unfortunately failed to produce it. The website worked fine for us under such an environment. The issue experienced by the reviewer may have been due to either a temporary issue with the web server or a problem with the specific browser environment they were working in, which we are unable to reproduce. It would be useful to know the date that this happened to verify if it was a downtime on the DTU IT services side that made the webserver inaccessible.

I have some serious concerns about the sustainability of the project and think that additional clarifications in the text could help. Currently is there a way to easily update a dataset to add, remove, or update a component (for example, if a new predictor is published, an error is found in a predictor dataset, or a predictor is updated)? If it requires a new round of manual curation for each protein to do this, I am worried that this will not scale and will leave the project with many out of date entries. The diversity of software tools (e.g., three different pipeline frameworks) also seems quite challenging to maintain.

We appreciate the reviewer’s concerns about long-term sustainability. It is a fair point that we consider within our steering group, who oversee and plans the activities and meet monthly. Adding entries to MAVISp is moving more and more towards automation as we grow. We aim to minimize the manual work where applicable. Still, an expert-based intervention is really needed in some of the steps, and we do not want to renounce it. We intend to keep working on MAVISp to make the process of adding and updating entries as automated as possible, and to streamline the process when manual intervention is necessary. From the point of view of the biocurators, they have three core workflows to use for the default modules, which also automatically cover the source of annotations. We are currently working to streamline the procedures behind LOCAL_INTERACTION, which is the most challenging one. On the data manager and maintainers' side, we have workflows and protocols that help us in terms of automation, quality control, etc, and we keep working to improve them. Among these, we have workflows to use for the old entries updates. As an example, the update of erroneously attributed RefSeq data (pointed out by reviewer 2) took us only one week overall (from assigning revisions and importing to the database) because we have a reduced version of Snakemake for automation that can act on only the affected modules. Also, another point is that we have streamlined the generation of the templates for the gitbook reports (see also answer to reviewer 2).

The update of old entries is planned and made regularly. We also deposit the old datasets on OSF for transparency, in case someone needs to navigate and explore the changes. We have activities planned between May and August every year to update the old entries in relation to changes of protocols in the modules, updates in the core databases that we interact with (COSMIC, Clinvar etc). In case of major changes, the activities for updates continue in the Fall. Other revisions can happen outside these time windows if an entry is needed or a specific research project and needs updates too.

Furthermore, the community of people contributing to MAVISp as biocurators or developers is growing and we have scientists contributing from other groups in relation to their research interest. We envision that for this resource to scale up, our team cannot be the only one producing data and depositing it to the database. To facilitate this we launched a pilot for a training event online (see Event page on the website) and we will repeat it once per year. We also organize regular meetings with all the active curators and developers to plan the activities in a sustainable manner and address the challenges we encounter.

As stated in the manuscript, currently with the team of people involved, automatization and resources that we have gathered around this initiative we can provide updates to the public database every third month and we have been regularly satisfied with them. Additionally, we are capable of processing from 20 to 40 proteins every month depending also on the needs of revision or expansion of analyses on existing proteins. We also depend on these data for our own research projects and we are fully committed to it.

Additionally, we are planning future activities in these directions to improve scale up and sustainability:

• Streamlining manual steps so that they are as convenient as fast as possible for our curators, e.g. by providing custom pages on the MAVISp website
• Streamline and automatize the generation of useful output, for instance the reports, by using a combination of simple automation and large language models
• Implement ways to share our software and scripts with third parties, for instance by providing ready made (or close to) containers or virtual machines
• For a future version 2 if the database grows in a direction that is not compatible with Streamlit, the web data science framework we are currently using, we will rewrite the website using a framework that would allow better flexibility and performance, for instance using Django and a proper database backend. On the same theme, according to the GitHub repository, the program relies on Python 3.9, which reaches end of life in October 2025. It has been tested against Ubuntu 18.04, which left standard support in May 2023. The authors should update the software to more modern versions of Python to promote the long-term health and maintainability of the project.

We thank the reviewer for this comment - we are aware of the upcoming EOL of Python 3.9. We tested MAVISp, both software package and web server, using Python 3.10 (which is the minimum supported version going forward) and Python 3.13 (which is the latest stable release at the time of writing) and updated the instructions in the README file on the MAVISp GitHub repository accordingly.

We plan on keeping track of Python and library versions during our testing and updating them when necessary. In the future, we also plan to deploy Continuous Integration with automated testing for our repository, making this process easier and more standardized.

I appreciate that the authors have made their code and data available. These artifacts should also be versioned and archived in a service like Zenodo, so that researchers who rely on or want to refer to specific versions can do so in their own future publications.

Since 2024, we have been reporting all previous versions of the dataset on OSF, the repository linked to the MAVISp website, at https://osf.io/ufpzm/files/osfstorage (folder: previous_releases). We prefer to keep everything under OSF, as we also use it to deposit, for example, the MD trajectory data.

Additionally, in this GitHub page that we use as a space to interact between biocurators, developers, and data managers within the MAVISp community, we also report all the changes in the NEWS space: https://github.com/ELELAB/mavisp_data_collection

Finally, the individual tools are all available in our GitHub repository, where version control is in place (see Table S1, where we now mapped all the resources used in the framework)

In the introduction of the paper, the authors conflate the clinical challenges of variant classification with evidence generation and it's quite muddled together. They should strongly consider splitting the first paragraph into two paragraphs - one about challenges in variant classification/clinical genetics/precision oncology and another about variant effect prediction and experimental methods. The authors should also note that they are many predictors other than AlphaMissense, and may want to cite the ClinGen recommendations (PMID: 36413997) in the intro instead.

We revised the introduction in light of these suggestions. We have split the paragraph as recommended and added a longer second paragraph about VEPs and using structural data in the context of VEPs. We have also added the citation that the reviewer kindly recommended.

Also in the introduction on lines 21-22 the authors assert that "a mechanistic understanding of variant effects is essential knowledge" for a variety of clinical outcomes. While this is nice, it is clearly not the case as we can classify variants according to the ACMG/AMP guidelines without any notion of specific mechanism (for example, by combining population frequency data, in silico predictor data, and functional assay data). The authors should revise the statement so that it's clear that mechanistic understanding is a worthy aspiration rather than a prerequisite.

We revised the statement in light of this comment from the reviewer

In the structural analysis section (page 5, lines 154-155 and elsewhere), the authors define cutoffs with convenient round numbers. Is there a citation for these values or were these arbitrarily chosen by the authors? I would have liked to see some justification that these assignments are reasonable. Also there seems to be an error in the text where values between -2 and -3 kcal/mol are not assigned to a bin (I assume they should also be uncertain). There are other similar seemingly-arbitrary cutoffs later in the section that should also be explained.

We have revised the text making the two intervals explicit, for better clarity.

On page 9, lines 294-298 the authors talk about using the PTEN data from ProteinGym, rather than the actual cutoffs from the paper. They get to the latter later on, but I'm not sure why this isn't first? The ProteinGym cutoffs are somewhat arbitrarily based on the median rather than expert evaluation of the dataset, and I'm not sure why it's even worth mentioning them when proper classifications are available. Regarding PTEN, it would be quite interesting to see a comparison of the VAMP-seq PTEN data and the Mighell phosphatase assay, which is cited on page 9 line 288 but is not actually a VAMP-seq dataset. I think this section could be interesting but it requires some additional attention.

We have included the data from Mighell’s phosphatase assay as provided by MAVEdb in the MAVISp database, within the experimental_data module for PTEN, and we have revised the case study, including them and explaining better the decision of supporting both the ProteinGym and MAVEdb classification in MAVISp (when available). See revised Figure3, Table 1 and corresponding text.

The authors mention "pathogenicity predictors" and otherwise use pathogenicity incorrectly throughout the manuscript. Pathogenicity is a classification for a variant after it has been curated according to a framework like the ACMG/AMP guidelines (Richards 2015 and amendments). A single tool cannot predict or assign pathogenicity - the AlphaMissense paper was wrong to use this nomenclature and these authors should not compound this mistake. These predictors should be referred to as "variant effect predictors" or similar, and they are able to produce evidence towards pathogenicity or benignity but not make pathogenicity calls themselves. For example, in Figure 4e, the terms "pathogenic" and "benign" should only be used here if these are the classifications the authors have derived from ClinVar or a similar source of clinically classified variants.

The reviewer is correct, we have revised the terminology we used in the manuscript and refers to VEPs (Variant Effect Predictors)

Minor comments:

The target selection table on the website needs some kind of text filtering option. It's very tedious to have to find a protein by scrolling through the table rather than typing in the symbol. This will only get worse as more datasets are added.

We have revised the website, adding a filtering option. In detail, we have refactored the web app by adding filtering functionality, both for the main protein table (that can now be filtered by UniProt AC, gene name, or RefSeq ID) and the mutations table. Doing this required a general overhaul of the table infrastructure (we changed the underlying engine that renders the tables).

The data sources listed on the data usage section of the website are not concordant with what is in the paper. For example, MaveDB is not listed.

We have revised and updated the data sources on the website, adding a metadata section with relevant information, including MaveDB references where applicable.

Figure 2 is somewhat confusing, as it partially interleaves results from two different proteins. This would be nicer as two separate figures, one on each protein, or just of a single protein.

As suggested by the reviewer, we have now revised the figure and corresponding legends and text, focusing only on one of the two proteins.

Figure 3 panel b is distractingly large and I wonder if the authors could do a little bit more with this visualization.

We have revised Figure 3 to solve these issues and integrating new data from the comparison with the phosphatase assay

Capitalization is inconsistent throughout the manuscript. For example, page 9 line 288 refers to VampSEQ instead of VAMP-seq (although this is correct elsewhere). MaveDB is referred to as MAVEdb or MAVEDB in various places. AlphaMissense is referred to as Alphamissense in the Figure 5 legend. The authors should make a careful pass through the manuscript to address this kind of issues.

We have carefully proofread the paper for these inconsistencies

MaveDB has a more recent paper (PMID: 39838450) that should be cited instead of/in addition to Esposito et al.

We have added the reference that the reviewer recommended

On page 11, lines 338-339 the authors mention some interesting proteins including BLC2, which has base editor data available (PMID: 35288574). Are there plans to incorporate this type of functional assay data into MAVISp?

The assay mentioned in the paper refers to an experimental setup designed to investigate mutations that may confer resistance to the drug venetoclax. We started the first steps to implement a MAVISp module aimed at evaluating the impact of mutations on drug binding using alchemical free energy perturbations (ensemble mode) but we are far from having it complete. We expect to import these data when the module will be finalized since they can be used to benchmark it and BCL2 is one of the proteins that we are using to develop and test the new module.

Reviewer #3 (Significance (Required)):

Significance:

General assessment:

This is a nice resource and the authors have clearly put a lot of effort in. They should be celebrated for their achievments in curating the diverse datasets, and the GitBooks are a nice approach. However, I wasn't able to get the website to work and I have raised several issues with the paper itself that I think should be addressed.

Advance:

New ways to explore and integrate complex data like protein structures and variant effects are always interesting and welcome. I appreciate the effort towards manual curation of datasets. This work is very similar in theme to existing tools like Genomics 2 Proteins portal (PMID: 38260256) and ProtVar (PMID: 38769064). Unfortunately as I wasn't able to use the site I can't comment further on MAVISp's position in the landscape.

We have expanded the conclusions section to add a comparison and cite previously published work, and linked to a review we published last year that frames MAVISp in the context of computational frameworks for the prediction of variant effects. In brief, the Genomics 2 Proteins portal (G2P) includes data from several sources, including some overlapping with MAVISp such as Phosphosite or MAVEdb, as well as features calculated on the protein structure. ProtVar also aggregates mutations from different sources and includes both variant effect predictors and predictions of changes in stability upon mutation, as well as predictions of complex structures. These approaches are only partially overlapping with MAVISp. G2P is primarily focused on structural and other annotations of the effect of a mutation; it doesn’t include features about changes of stability, binding, or long-range effects, and doesn’t attempt to classify the impact of a mutation according to its measurements. It also doesn’t include information on protein dynamics. Similarly, ProtVar does include information on binding free energies, long effects, or dynamical information.

Audience:

MAVISp could appeal to a diverse group of researchers who are interested in the biology or biochemistry of proteins that are included, or are interested in protein variants in general either from a computational/machine learning perspective or from a genetics/genomics perspective.

My expertise:

I am an expert in high-throughput functional genomics experiments and am an experienced computational biologist with software engineering experience.

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

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Referee #3

Evidence, reproducibility and clarity

Summary:

The authors present MAVISp, a tool for viewing protein variants heavily based on protein structure information. The authors have done a very impressive amount of curation on various protein targets, and should be commended for their efforts. The tool includes a diverse array of experimental, clinical, and computational data sources that provides value to potential users interested in a given target.

Major comments:

Unfortunately I was not able to get the website to work properly. When selecting a protein target in simple mode, I was greeted with a completely blank page in the app window, and in ensemble mode, there was no transition away from the list of targets at all. I'm using Firefox 140.0.2 (64-bit) on Ubuntu 22.04. I would have liked to be able to explore the data myself and provide feedback on the user experience and utility.

I have some serious concerns about the sustainability of the project and think that additional clarifications in the text could help. Currently is there a way to easily update a dataset to add, remove, or update a component (for example, if a new predictor is published, an error is found in a predictor dataset, or a predictor is updated)? If it requires a new round of manual curation for each protein to do this, I am worried that this will not scale and will leave the project with many out of date entries. The diversity of software tools (e.g., three different pipeline frameworks) also seems quite challenging to maintain.

On the same theme, according to the GitHub repository, the program relies on Python 3.9, which reaches end of life in October 2025. It has been tested against Ubuntu 18.04, which left standard support in May 2023. The authors should update the software to more modern versions of Python to promote the long-term health and maintainability of the project.

I appreciate that the authors have made their code and data available. These artifacts should also be versioned and archived in a service like Zenodo, so that researchers who rely on or want to refer to specific versions can do so in their own future publications.

In the introduction of the paper, the authors conflate the clinical challenges of variant classification with evidence generation and it's quite muddled together. The y should strongly consider splitting the first paragraph into two paragraphs - one about challenges in variant classification/clinical genetics/precision oncology and another about variant effect prediction and experimental methods. The authors should also note that they are many predictors other than AlphaMissense, and may want to cite the ClinGen recommendations (PMID: 36413997) in the intro instead.

Also in the introduction on lines 21-22 the authors assert that "a mechanistic understanding of variant effects is essential knowledge" for a variety of clinical outcomes. While this is nice, it is clearly not the case as we are able to classify variants according to the ACMG/AMP guidelines without any notion of specific mechanism (for example, by combining population frequency data, in silico predictor data, and functional assay data). The authors should revise the statement so that it's clear that mechanistic understanding is a worthy aspiration rather than a prerequisite.

In the structural analysis section (page 5, lines 154-155 and elsewhere), the authors define cutoffs with convenient round numbers. Is there a citation for these values or were these arbitrarily chosen by the authors? I would have liked to see some justification that these assignments are reasonable. Also there seems to be an error in the text where values between -2 and -3 kcal/mol are not assigned to a bin (I assume they should also be uncertain). There are other similar seemingly-arbitrary cutoffs later in the section that should also be explained.

On page 9, lines 294-298 the authors talk about using the PTEN data from ProteinGym, rather than the actual cutoffs from the paper. They get to the latter later on, but I'm not sure why this isn't first? The ProteinGym cutoffs are somewhat arbitrarily based on the median rather than expert evaluation of the dataset and I'm not sure why it's even worth mentioning them when proper classifications are available. Regarding PTEN, it would be quite interesting to see a comparison of the VAMP-seq PTEN data and the Mighell phosphatase assay, which is cited on page 9 line 288 but is not actually a VAMP-seq dataset. I think this section could be interesting but it requires some additional attention.

The authors mention "pathogenicity predictors" and otherwise use pathogenicity incorrectly throughout the manuscript. Pathogenicity is a classification for a variant after it has been curated according to a framework like the ACMG/AMP guidelines (Richards 2015 and amendments). A single tool cannot predict or assign pathogenicity - the AlphaMissense paper was wrong to use this nomenclature and these authors should not compound this mistake. These predictors should be referred to as "variant effect predictors" or similar, and they are able to produce evidence towards pathogenicity or benignity but not make pathogenicity calls themselves. For example, in Figure 4e, the terms "pathogenic" and "benign" should only be used here if these are the classifications the authors have derived from ClinVar or a similar source of clinically classified variants.

Minor comments:

The target selection table on the website needs some kind of text filtering option. It's very tedious to have to find a protein by scrolling through the table rather than typing in the symbol. This will only get worse as more datasets are added.

The data sources listed on the data usage section of the website are not concordant with what is in the paper. For example, MaveDB is not listed.

I found Figure 2 to be a bit confusing in that it partially interleaves results from two different proteins. I think this would be nicer as two separate figures, one on each protein, or just of a single protein.

Figure 3 panel b is distractingly large and I wonder if the authors could do a little bit more with this visualization.

Capitalization is inconsistent throughout the manuscript. For example, page 9 line 288 refers to VampSEQ instead of VAMP-seq (although this is correct elsewhere). MaveDB is referred to as MAVEdb or MAVEDB in various places. AlphaMissense is referred to as Alphamissense in the Figure 5 legend. The authors should make a careful pass through the manuscript to address this kind of issues.

MaveDB has a more recent paper (PMID: 39838450) that should be cited instead of/in addition to Esposito et al.

On page 11, lines 338-339 the authors mention some interesting proteins including BLC2, which has base editor data available (PMID: 35288574). Are there plans to incorporate this type of functional assay data into MAVISp?

Significance

General assessment:

This is a nice resource and the authors have clearly put a lot of effort in. They should be celebrated for their achievments in curating the diverse datasets, and the GitBooks are a nice approach. However, I wasn't able to get the website to work and I have raised several issues with the paper itself that I think should be addressed.

Advance:

New ways to explore and integrate complex data like protein structures and variant effects are always interesting and welcome. I appreciate the effort towards manual curation of datasets. This work is very similar in theme to existing tools like Genomics 2 Proteins portal (PMID: 38260256) and ProtVar (PMID: 38769064). Unfortunately as I wasn't able to use the site I can't comment further on MAVISp's position in the landscape.

Audience:

MAVISp could appeal to a diverse group of researchers who are interested in the biology or biochemistry of proteins that are included, or are interested in protein variants in general either from a computational/machine learning perspective or from a genetics/genomics perspective.

My expertise:

I am an expert in high-throughput functional genomics experiments and am an experienced computational biologist with software engineering experience.

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Referee #2

Evidence, reproducibility and clarity

Summary:

The authors present a pipeline and platform, MAVISp, for aggregating, displaying and analysis of variant effects with a focus on reclassification of variants of uncertain clinical significance and uncovering the molecular mechanisms underlying the mutations.

Major comments:

• On testing the platform, I was unable to look-up a specific variant in ADCK1 (rs200211943, R115Q). I found that despite stating that the mapped refseq ID was NP_001136017 in the HGVSp column, it was actually mapped to the canonical UniProt sequence (Q86TW2-1). NP_001136017 actually maps to Q86TW2-3, which is missing residues 74-148 compared to the -1 isoform. The Uniprot canonical sequence has no exact RefSeq mapping, so the HGVSp column is incorrect in this instance. This mapping issue may also affect other proteins and result in incorrect HGVSp identifiers for variants.
• The paper lacks a section on how to properly interpret the results of the MAVISp platform (the case-studies are useful, but don't lay down any global rules for interpreting the results). For example: How should a variant with conflicts between the variant impact predictors be interpreted? Are certain indicators considered more 'reliable' than others?
• In the Methods section, GEMME is stated as being rank-normalised with 0.5 as a threshold for damaging variants. On checking the data downloaded from the site, GEMME was not rank-normalised but rather min-max normalised. Furthermore, Supplementary text S4 conflicts with the methods section over how GEMME scores are classified, S4 states that a raw-value threshold of -3 is used.
• Note. This is a major comment as one of the claims is that the associated web-tool is user-friendly. While functional, the web app is very awkward to use for analysis on any more than a few variants at once.
  • The fixed window size of the protein table necessitates excessive scrolling to reach your protein-of-interest. This will also get worse as more proteins are added. Suggestion: add a search/filter bar.
  • The same applies to the dataset window.
  • You are unable to copy anything out of the tables.
  • Hyperlinks in the tables only seem to work if you open them in a new tab or window.
  • All entries in the reference column point to the MAVISp preprint even when data from other sources is displayed (e.g. MAVE studies).
  • Entering multiple mutants in the "mutations to be displayed" window is time-consuming for more than a handful of mutants. Suggestion: Add a box where multiple mutants can be pasted in at once from an external document.

Minor comments

• Grammar. I appreciate that this manuscript may have been compiled by a non-native English speaker, but I would be remiss not to point out that there are numerous grammar errors throughout, usually sentence order issues or non-pluralisation. The meaning of the authors is mostly clear, but I recommend very thoroughly proof-reading the final version.
• There are numerous proteins that I know have high-quality MAVE datasets that are absent in the database e.g. BRCA1, HRAS and PPARG.
• Checking one of the existing MAVE datasets (KRAS), I found that the variants were annotated as damaging, neutral or given a positive score (these appear to stand-in for gain-of-function variants). For better correspondence with the other columns, those with positive scores could be labelled as 'ambiguous' or 'uncertain'.
• Numerous thresholds are defined for stabilizing / destabilizing / neutral variants in both the STABILITY and the LOCAL_INTERACTION modules. How were these thresholds determined? I note that (PMC9795540) uses a ΔΔG threshold of 1/-1 for defining stabilizing and destabilizing variants, which is relatively standard (though they also say that 2-3 would likely be better for pinpointing pathogenic variants).
• "Overall, with the examples in this section, we illustrate different applications of the MAVISp results, spanning from benchmarking purposes, using the experimental data to link predicted functional effects with structural mechanisms or using experimental data to validate the predictions from the MAVISp modules."

The last of these points is not an application of MAVISp, but rather a way in which external data can help validate MAVISp results. Furthermore, none of the examples given demonstrate an application in benchmarking (what is being benchmarked?). - Transcription factors section. This section describes an intended future expansion to MAVISp, not a current feature, and presents no results. As such, it should probably be moved to the conclusions/future directions section. - Figures. The dot-plots generated by the web app, and in Figures 4, 5 and 6 have 2 legends. After looking at a few, it is clear that the lower legend refers to the colour of the variant on the X-axis - most likely referencing the ClinVar effect category. This is not, however, made clear either on the figures or in the app. - "We identified ten variants reported in ClinVar as VUS (E102K, H86D, T29I, V91I, P2R, L44P, L44F, D56G, R11L, and E25Q, Fig.5a)"

E25Q is benign in ClinVar and has had that status since first submitted.

Significance

Platforms that aggregate predictors of variant effect are not a new concept, for example dbNSFP is a database of SNV predictions from variant effect predictors and conservation predictors over the whole human proteome. Predictors such as CADD and PolyPhen-2 will often provide a summary of other predictions (their features) when using their platforms. MAVISp's unique angle on the problem is in the inclusion of diverse predictors from each of its different moules, giving a much wider perspective on variants and potentially allowing the user to identify the mechanistic cause of pathogenicity. The visualisation aspect of the web app is also a useful addition, although the user interface is somewhat awkward. Potentially the most valuable aspect of this study is the associated gitbook resource containing reports from biocurators for proteins that link relevant literature and analyse ClinVar variants. Unfortunately, these are only currently available for a small minority of the total proteins in the database with such reports.

For improvement, I think that the paper should focus more on the precise utility of the web app / gitbook reports and how to interpret the results rather than going into detail about the underlying pipeline.

In terms of audience, the fast look-up and visualisation aspects of the web-platform are likely to be of interest to clinicians in the interpretation of variants of unknown clinical significance. The ability to download the fully processed dataset on a per-protein database would be of more interest to researchers focusing on specific proteins or those taking a broader view over multiple proteins (although a facility to download the whole database would be more useful for this final group).

My expertise.

• I am a protein bioinformatician with a background in variant effect prediction and large-scale data analysis.

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Referee #1

Evidence, reproducibility and clarity

Summary: This manuscript, "MAVISp: A Modular Structure-Based Framework for Protein Variant Effects," presents a significant new resource for the scientific community, particularly in the interpretation and characterization of genomic variants. The authors have developed a comprehensive and modular computational framework that integrates various structural and biophysical analyses, alongside existing pathogenicity predictors, to provide crucial mechanistic insights into how variants affect protein structure and function. Importantly, MAVISp is open-source and designed to be extensible, facilitating reuse and adaptation by the broader community.

Major comments:

• While the manuscript is formally well-structured (with clear Introduction, Results, Conclusions, and Methods sections), I found it challenging to follow in some parts. In particular, the Introduction is relatively short and lacks a deeper discussion of the state-of-the-art in protein variant effect prediction. Several methods are cited but not sufficiently described, as if prior knowledge were assumed. OPTIONAL: Extend the Introduction to better contextualize existing approaches (e.g., AlphaMissense, EVE, ESM-based predictors) and clarify what MAVISp adds compared to each.
• The workflow is summarized in Figure 1(b), which is visually informative. However, the narrative description of the pipeline is somewhat fragmented. It would be helpful to describe in more detail the available modules in MAVISp, and which of them are used in the examples provided. Since different use cases highlight different aspects of the pipeline, it would be useful to emphasize what is done step-by-step in each. OPTIONAL: Consider adding a table or a supplementary figure mapping each use case to the corresponding pipeline steps and modules used.
• The text contains numerous acronyms, some of which are not defined upon first use or are only mentioned in passing. This affects readability. OPTIONAL: Define acronyms upon first appearance, and consider moving less critical technical details (e.g., database names or data formats) to the Methods or Supplementary Information. This would greatly enhance readability.
• The code and trained models are publicly available, which is excellent. The modular design and use of widely adopted frameworks (PyTorch and PyTorch Geometric) are also strong points. However, the Methods section could benefit from additional detail regarding feature extraction and preprocessing steps, especially the structural features derived from AlphaFold2 models. OPTIONAL: Include a schematic or a table summarizing all feature types, their dimensionality, and how they are computed.
• The section on transcription factors is relatively underdeveloped compared to other use cases and lacks sufficient depth or demonstration of its practical utility. OPTIONAL: Consider either expanding this section with additional validation or removing/postponing it to a future manuscript, as it currently seems preliminary.

Minor comments:

• Most relevant recent works are cited, including EVE, ESM-1v, and AlphaFold-based predictors. However, recent methods like AlphaMissense (Cheng et al., 2023) could be discussed more thoroughly in the comparison.
• Figures are generally clear, though some (e.g., performance barplots) are quite dense. Consider enlarging font sizes and annotating key results directly on the plots.
• Minor typographic errors are present. A careful proofreading is highly recommended. Below are some of the issues I identified:

Page 3, line 46: "MAVISp perform" -> "MAVISp performs"

Page 3, line 56: "automatically as embedded" -> "automatically embedded"

Page 3, line 57: "along with to enhance" -> unclear; please revise

Page 4, line 96: "web app interfaces with the database and present" -> "presents"

Page 6, line 210: "to investigate wheatear" -> "whether"

Page 6, lines 215-216: "We have in queue for processing with MAVISp proteins from datasets relevant to the benchmark of the PTM module." -> unclear sentence; please clarify

Page 15, line 446: "Both the approaches" -> "Both approaches"

Page 20, line 704: "advantage of multi-core system" -> "multi-core systems"

Significance

General assessment: the strongest aspects of the study are the modularity, open-source implementation, and the integration of structural information through graph neural networks. MAVISp appears to be one of the few publicly available frameworks that can easily incorporate AlphaFold2-based features in a flexible way, lowering the barrier for developing custom predictors. Its reproducibility and transparency make it a valuable resource. However, while the technical foundation is solid and the effort substantial, the scientific narrative and presentation could be significantly improved. The manuscript is dense and hard to follow in places, with a heavy use of acronyms and insufficient explanation of key design choices. Improving the descriptive clarity, especially in the early sections, would greatly enhance the impact of this work.

Advance: to the best of my knowledge, this is one of the first modular platforms for protein variant effect prediction that integrates structural data from AlphaFold2 with bioinformatic annotations and even clinical data in an extensible fashion. While similar efforts exist (e.g., ESMfold, AlphaMissense), MAVISp distinguishes itself through openness and design for reusability. The novelty is primarily technical and practical rather than conceptual.

Audience: this study will be of strong interest to researchers in computational biology, structural bioinformatics, and genomics, particularly those developing variant effect predictors or analyzing the impact of mutations in clinical or functional genomics contexts. The audience is primarily specialized, but the open-source nature of the tool may diffuse its use among more applied or translational users, including those working in precision medicine or protein engineering.

Reviewer expertise: my expertise is in computational structural biology, molecular modeling, and (rather weak) machine learning applications in bioinformatics. I am familiar with graph-based representations of proteins, AlphaFold2, and variant effects based on Molecular Dynamics simulations. I do not have any direct expertise in clinical variant annotation pipelines.

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I thank the Referees for their...

Referee #1

1. The authors should provide more information when...

Responses + The typical domed appearance of a hydrocephalus-harboring skull is apparent as early as P4, as shown in a new side-by-side comparison of pups at that age (Fig. 1A). + Though this is not stated in the MS 2. Figure 6: Why has only...

Response: We expanded the comparison

Minor comments:

1. The text contains several...

Response: We added...

Referee #2

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Referee #3

Evidence, reproducibility and clarity

Meroni and colleagues present evidence that CIP2A is required to recruit the SMX complex to sites of replication stress in mitotic cells. Whilst the data generated when using U2OS cells seems to support a role for CIP2A in recruiting the SMX complex to sites of replication stress to facilitate MiDAS, as the authors point out, this pathway is not conserved in DLD1 cells. Although the authors suggest that this discrepancy in the data may relate to the fact that U2OS cells are ALT positive and the DLD1 cells are not, there is no experimental evidence to support this hypothesis. It would have been nice if the authors had backed up this hypothesis with data relating to how CIP2A regulates the SMX-MiDAS pathway in other ALT positive and negative cell lines. Taken together, after reading this manuscript, I am left wondering whether CIP2A is really important for SMX-dependent MiDAS or whether it is phenomenon that is found in some commonly used cancer cell lines and not others. Whilst it is important to publish conflicting results as they can explain why some research labs can reproduce published data and others can't, I think this manuscript would benefit from assessment of the role of CIP2A in mediating the recruitment of the SMX complex to carry out MiDAS in a variety of additional cancer cell lines and also non-cancer cell lines, such as RPE1-hTERT cells to obtain some sort of consensus about the importance of CIP2A in dealing with mitotic replication stress.

Comments:

1. Fig.2A-E: Can the authors comment on the difference in number of APH-induced FANCD2, SLX4, Mus81 and XPF foci in mitotic U2OS cells? Given that SLX4 should be recruiting both XPF and Mus81, there is a disparity between the numbers of mitotic foci given that there are approximately 30 FANCD3 foci per mitotic cell following APH treatment. Additionally, why do the XPF foci not increase after APH exposure?
2. Fig.2G: I would say that the 'full rescue' of Mus81 foci in the CIP2A KO cells complemented with WT CIP2A is not hugely convincing since there is only a difference of 1-2 foci between the WT and CIP2A KO cells treated with APH.
3. Fig.3A: I am not really sure how biologically meaningful a difference of 0.03-0.04 EdU foci per chromosome is when comparing BRCA2 KO DLD1 cells treated with control siRNA versus CIP2A siRNA. Would it not have been better to treat the BRCA2 KO DLD1 cells with APH?
4. Fig.3H-I: Given that the reduction in MiDAS in the CIP2A KO cl.7 cell line is likely a clonal artifact not related to the loss of CIP2A, it is unclear how to interpret the data about the EdU foci pattern on chromosomes presented in Fig.3H-I and its relevance to CIP2A. Therefore, I am not sure this data really adds anything to the manuscript.
5. Fig.4H: The difference in Mus81 foci per mitotic cell with/without the expression of B6L is only one focus per mitotic cell. Based on this, it is difficult to make any real conclusions about whether the TOPBP1-CIP2A interaction is really required for the recruitment of Mus81 to sites of mitotic replication stress.

Significance

As mentioned above, it is clear that the role of CIP2A in regulating the mitotic replication stress response by promoting recruitment of the SMX complex to sites of mitotic replication stress to promote MiDAS is complicated and may be specific to some cancer cell lines and not others. Whilst it is not clear what the underlying reason for this is, this manuscript would definitely benefit from additional analysis of this pathway in other cancer and non-cancer cell lines to obtain a consensus about the role of CIP2A.

This manuscript would appeal to fundamental research scientists interested in understanding the mechanisms underlying DNA damage repair, the replication stress response and mitotic regulation.

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Referee #2

Evidence, reproducibility and clarity

Summary:

In the manuscript entitled "CIP2A Mediates the Recruitment of the SLX4-MUS81-XPF Tri-Nuclease Complex in Mitosis and Protects Against Replication Stress" by Meroni et al the authors have characterized localization of the CIP2A-TopBP1 complex as well as some aspects of its function in U2OS and DLD1 cell lines exposed to different types of stress. They find that replication stress due to BRCA2 KO, APH or ATRi results in increased focus formation of the CIP2A-TopBP1 complex in mitotic cells. Moreover, the authors find significant decrease in EdU incorporartion in mitotic cells when disrupting CIP2A in (i) U2OS exposed to ATRi or Aph; (ii) in DLD1 BRCA2 KO; (iii) in one clone of DLD1 with Cip2A KO, and a non significant decrease the other DLD1 with Cip2A KO that they tested. Thus, under most of the tested conditions CIP2A is facilitating MiDAS. However, the authors find that expression of a previously characterised fragment of TopBP1 called B6L, which disrupts CIP2A-TopBP1 interaction, does not inhibit MiDAS in DLD1 cells.

Major comments:

It is convincing but not surprising that CIP2A-TopBP1 form more foci in mitotic cells after replication stress. The authors statement in the abstract: "We demonstrate that in the absence of CIP2A, cells fail to recruit the SLX4-MUS81-XPF (SMX) tri-nuclease complex to sites of under-replicated DNA in mitosis, resulting in a high incidence of lagging chromosomes during anaphase and subsequent micronuclei formation" is not supported by experiments. The authors indeed show that absence of CIP2A leads to lagging chromosomes during anaphase and subsequent micronuclei formation (which has previously been shown) but they have not shown that it is the failure to recruit the SMX complex that results in the phenotypes they mention. The authors should rephrase or remove this claim.

There is a discrepancy between the B6L-mediated disruption of TopBP1-CIP2A interaction having no effect on MiDAS in DLD1 cells (fig. 4F) whereas knockout of CIP2A in DLD1 cells seem to have an effect (fig 3E). The most obvious explanation for this observation is that the B6L peptide does not fully abolish TopBP1-CIP2A interaction and can still allow for some SLX4-MUS81 recruitment that is not visible as foci but still sufficient to induce MiDAS. To understand whether MiDAS in DLD1 expressing B6L is dependent on the fraction of TopBP1 that can still form foci (according to Fig 4D) the authors must co-stain for TopBP1 together with EdU detection to address whether they observe any colocalization of TopBP1 with MiDAS.

Many of the experiments are only performed with two independent replicates. The authors must perform 3 independent replicates. Also, it is not clear how many cells were analysed for each replicate. This should be clearly stated and the mean of each replicate should always be shown. Statistical analyses should be carried out using the means of the replicates. The authors must provide data showing the efficiency of CIP2A knockdown and CIP2A expression in the complementation assay (Fig. 2G)

Minor comments:

The authors should change "U-2 OS" in the figures to "U2OS" for consistency.

In figure 4D - is the increase with APH and S1 significant compared to S1 alone?

Figure 3 B and C. It is worrying that there is a huge difference in the EdU foci/mitotic cell in untreated condition from panel B to pabel C.

Fig 3F - is the increase in EdU incorporation after complementation significant?

For figure 3I representative images should be added

Significance

The data presented in the manuscript is of high quality but unfortunately does not present a big advance compared to current knowledge. Nevertheless, it is useful to have side-by-side comparison of different cell lines and conditions and IF localization studies. Given the therapeutic interest in the CIP2A-TopBP1 pathway it is important to get all the details right and researches with interest in DNA repair during mitosis will have interest in this work.

Moreover, in this manuscript the authors demonstrate that the impact of CIP2A disruption on MiDAS is variable across different cell lines-and even between individual clones. The concept of MiDAS is still clouded by considerable ambiguity, possibly due to earlier studies overstating the consequences of knockdown or knockout. It is therefore great that this manuscript presents clear, unbiased observations, highlighting both inter-cell line differences and the partial nature of the effects. This kind of nuanced reporting is valuable for the field.

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Referee #1

Evidence, reproducibility and clarity

Summary and Significance

This is a timely and exciting study that provides us with some new molecular insights into mitotic DNA repair. It builds on previous studies that identified the CIP2A-TOPBP1 complex as a molecular tether that connects broken DNA ends that get transmitted from interphase into mitosis (PMID: 30898438, 35842428, 35842428). The results are also largely complementary with those of Martin et al. (BioRxiv preprint at https://doi.org/10.1101/2024.11.12.621593) and de Haan et al. (BioRxiv preprint at https://www.biorxiv.org/content/10.1101/2025.04.03.647079v1).

The authors report three main findings, as summarized below.

1) The CIP2A oncoprotein is involved in the cellular response to replication stress in mitosis.

2) CIP2A is required for the recruitment of SLX4, MUS81, and XPF into foci during mitosis. SLX4 is a well-established protein scaffold for multiple DNA repair factors, including three structure-selective endonucleases called SLX1, MUS81-EME1, and XPF-ERCC1 that together, form the SMX tri-nuclease that removes DNA repair intermediates and chromosome entanglements during mitosis. In some cell lines, the SMX complex is required for mitotic DNA synthesis at sites of under-replicated DNA, thus ensuring complete DNA replication prior to cell division.

3) The role(s) of CIP2A in MiDAS are cell line-dependent/context-dependent.

In general, this is a solid body of microscopy-based work that includes appropriate cell models and experimental controls. The manuscript is well-written, and the data is presented coherently. The main findings will have important implications for researchers interested in mitotic DNA damage, genome stability, and cancer biology. After addressing the points below, I believe this manuscript will be suitable for publication.

Major comments

1) Figure 1C: The CIP2A-TOPBP1 PLA experiments are lacking critical controls, namely cells lacking or depleted of CIP2A and TOPBP1. These controls are necessary to provide confidence for the results presented in Figure 1C. If these controls are too expensive or time-demanding for the manuscript, then I recommend removing the PLA data from Figure 1C.

2) In Figure 2, the authors conclude that the loss of SLX4, XPF, and MUS81 foci in CIP2A depleted cells is synonymous with the loss of recruitment to DNA lesions. However, I can think of many other reasons that could explain the loss of foci. For example, do the authors know that the proteins are expressed to similar levels in cells with and without CIP2A (this should be tested by a simple western blot). Along the same vein, a biochemical fractionation and western blot of the soluble vs chromatin-bound fraction would complement and substantiate their microscopy-based assays in Figure 2. If the fractionation is not possible, then the text should be adjusted accordingly.

3) The experimental set-up in Figure 2 probes whether CIP2A mediates the recruitment of SMX subunits - SLX4, XPF, MUS81 - but not the SMX complex per se, which would require the study of SLX4 point mutants that selectively ablate the interactions with XPF or MUS81 (but not CIP2A). As such, I suggest that they rephrase their wording appropriately.

4) Western blots must be provided to substantiate the experiments performed with siRNA (Figure 1G-J, Figure 2A-E and 2H, Figure 3A-D, Figure 5B-D). Similarly, the authors should provide western blots to confirm the BRCA2 and CIP2A statuses in their KO cell lines, as well as the complementation cell lines. In the absence of this information, it is difficult for someone to make an independent and meaningful interpretation of their data.

5) Most of the data presented in this manuscript is derived from n = 2 biological replicates. All of the experiments reported in the study should be repeated for n = 3 biological replicates.

6) Since the authors report the median of their data, they should also report the interquartile range or confidence interval to display the uncertainty.

Minor comments

1) The references can be improved by acknowledging some of the foundational papers on SLX4 and the SMX tri-nuclease.

1.a) Page 3: Neither Minocherhomji et al. 2015 nor Pedersen et al. 2015 were the first to describe SLX4 as a scaffold for structure-selective endonucleases. The founding papers were published in 2009 (Svendsen et al. 2009, Munoz et al. 2009, Fekairi et al. 2009, Andersen et al. 2009) with important mechanistic studies on nuclease activation reported in 2013 (Wyatt et al. 2013, Castor et al. 2013) and 2017 (Wyatt et al. 2017).

1.b) Page 6: The authors should cite Wyatt et al. 2013, alongside Castor et al. 2013 and Garner et al. 2013 since these 3 articles were published at similar times. They may also want to acknowledge previous work from the Hickson and Rosselli labs showing that XPF-ERCC1 and MUS81-EME1 are recruited to fragile sites in mitosis.

2) To improve broad readability, the authors should remove the following abbreviations: Aph and WT.

3) In several figures, the authors show that a given treatment causes a very small change in the number of foci observed per mitotic cell. Although the values may be statistically different, it is important that they discuss the biological significance of these small effects - for example, I am not convinced that a difference of 2-3 foci per cell is sufficient to induce a robust cellular response.

4) The methods could be expanded to ensure reproducibility, particularly with respect to the drug treatments (e.g., timing, washes, etc.).

Significance

This is a timely and exciting study that provides us with some new molecular insights into mitotic DNA repair. It builds on previous studies that identified the CIP2A-TOPBP1 complex as a molecular tether that connects broken DNA ends that get transmitted from interphase into mitosis (PMID: 30898438, 35842428, 35842428). The results are also largely complementary with those of Martin et al. (BioRxiv preprint at https://doi.org/10.1101/2024.11.12.621593) and de Haan et al. (BioRxiv preprint at https://www.biorxiv.org/content/10.1101/2025.04.03.647079v1).

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Reply to the reviewers

We thank the reviewers for their detailed comments, which have already helped us improve our manuscript. The responses below detail changes we have already made as part of the Review Commons revision plan, and further changes we expect to make in a longer revision period.

__Reviewer #1 __

Major points __ It is mentioned throughout the manuscript that 3 plates were evaluated per line. I believe these are independently differentiated plates. This detail is critical concerning rigor and reproducibility. This should be clearly stated in the Methods section and in the first description of the experimental system in the Results section for Figure 1.__

These experimental details have now been clarified. Unless otherwise stated, all findings were confirmed in three independently differentiated plates from the same line or at least one differentiation from each of three lines.

For the patient-specific lines - how many lines were derived per patient?

This has now been clarified in the methods. Microfluidic reprogramming of a small number of amniocytes produces one line per patient representing a pool of clones. Subcloning from individual cells would not be possible within the timeframe of a pregnancy.

Methods: For patient-specific iPSC lines, one independent iPSC line was obtained per patient following microfluidic mmRNA reprogramming.

Was the Vangl2 variant introduced by prime editing? Base editing? The details of the methods are sparse.

We have now expanded these details:

Methods: VANGL2 knock-in lines were generated using CRSIPR-Cas9 homology directed repair editing by Synthego (SO-9291367-1). The guide sequence was AUGAGCGAAGGGUGCGCAAG and the donor sequence was CAATGAGTACTACTATGAGGAGGCTGAGCATGAGCGA AGGGTGTGCAAGAGGAGGGCCAGGTGGGTCCCTGGGGGAGAAGAGGAGAG. Sequence modification was confirmed by Sanger sequencing before delivery of the modified clones, and Sanger sequencing was repeated after expansion of the lines (Supplementary Figure 5) as well as SNP arrays (Illumina iScan, not shown) confirming genomic stability.

Some additional suggestions for improvement. __ The abstract could be more clearly written to effectively convey the study's importance. Here are some suggestions.__

Line 26: Insert "apicobasal" before "elongation" - the way it is written, I initially interpreted it as anterior-posterior elongation.

Line 29: Please specify that the lines refer to 3 different established parent iPSC lines with distinct origins and established using different reprogramming methods, plus 2 control patient-derived lines. - The reproducibility of the cell behaviors is impressive, but this is not captured in the abstract.

Line 32: add that this mutation was introduced by CRISPR-Cas9 base/prime editing.

The last sentence of the abstract states that the study only links apical constriction to human NTDs, but also reveals that neural differentiation and apical-basal elongation were found. __ The introduction could also use some editing. __ Line 71: insert "that pulls actin filaments together" after "power strokes" __ Line 73: "apically localized," do you mean "mediolaterally" or "radially"? __ Line 75: Can you specify that PCP components promote "mediolaterally orientated" apical constriction __ Lines 127: Specify that NE functions include apical basal elongation and neurodifferentiation are disrupted in patient-derived models__

These text changes have all been made.

Reviewer #2:____ __ __Major comments: __ 1. Figure 1. The authors use F-actin to segment cell areas. Perhaps this could be done more accurately with ZO-1, as F-actin cables can cross the surface of a single cell. In any case, the authors need to show a measure of segmentation precision: segmented image vs. raw image plus a nuclear marker (DAPI, H2B-GFP), so we can check that the number of segmented cells matches the number of nuclei.__

We used ZO-1 to quantify apical areas of the VANGL2-konckin lines in Figure 3. Segmentation of neuroepithelial apical areas based on F-actin staining is commonplace in the field (e.g. Fig 9 of Bogart & Brooks 2025 as a recent example), and is generally robust because the cell junctions are much brighter than any apical fibres not associated with the apical cortex. However, we accept that at earlier stages of differentiation there may be more apical fibres when cells are cuboidal. We have therefore repeated our analysis of apical area using ZO-1 staining as suggested, shown in the new Supplementary Figure 1, analysing a more temporally-detailed time course in one iPSC line. This new analysis confirms our finding of lack of apical area change between days 2-4 of differentiation, then progressive reduction of apical area between days 4-8, further validating our system. Including nuclear images is not helpful because of the high nuclear index of pseudostratified epithelia (e.g. see Supplementary Figure 7) which means that nuclei overlap along the apicobasal axis. Individual nuclei cannot be related to their apical surface in projected images.

__2.Lines 156-166. The authors claim that changes in gene expression precede morphological changes. I am not convinced this is supported by their data. Fig. 1g (epithelial thickness) and Fig. 1k (PAX6 expression) seem to have similar dynamics. The authors can perform a cross-correlation between the two plots to see which Δt gives maximum correlation. If Δt __We are happy to do this analysis fully in revision. __Our initial analysis performing cross-correlation between apical area and CDH2 protein in one line shows the highest cross-correlation at Δt = -1, suggesting neuroepithelial CDH2 increases before apical area decreases. In contrast, the same analysis comparing apical area versus PAX6 shows Δt = 0, suggesting concurrence. This analysis will be expanded to include the other markers we quantified and the manuscript text amended accordingly. We are keen to undertake additional experiments to test whether these cells swap their key cadherins - CDH1 and CDH2 - before they begin to undergo morphological changes (see the response to Reviewer 3's minor comment 1 immediately below).

3. Figure 2d. The laser ablation experiment in the presence of ROCK inhibitor is clear, as I can easily see the cell outlines before and after the experiment. In the absence of ROCK inhibitor, the cell edges are blurry, and I am not convinced the outline that the authors drew is really the cell boundary. Perhaps the authors can try to ablate a larger cell patch so that the change in area is more defined.

The outlines on these images are not intended to show cell boundaries, but rather link landmarks visible at both timepoints to calculate cluster (not cell) change in area. This is as previously shown in Galea et al Nat Commun 2021 and Butler et al J Cell Sci 2019. We have now amended the visualisation of retraction in Figure 2 to make representation of differences between conditions more intuitive.

4. Figure 2d. Do the cells become thicker after recoil?

This is unlikely because the ablated surface remains in the focal plane. Unfortunately, we are unable to image perpendicularly to the direction of ablation to test whether their apical surface moves in Z even by a very small amount. This has now been clarified in the results:

Results: The ablated surface remained within the focal plane after ablation, indicating minimal movement along the apical-basal axis.

5. Figure 3. The authors mention their previous study in which they show that Vangl2 is not cell-autonomously required for neural closure. It will be interesting to study whether this also the case in the present human model by using mosaic cultures.

We agree with the reviewer that this is one of the exciting potential future applications of our model, which will first require us to generate stable fluorescently-tagged lines (to identify those cells which lack VANGL2). We will also need to extensively analyze controls to validate that mixing fluo-tagged and untagged lines does not alter the homogeneity of differentiation, or apical constriction, independently of VANGL2 deletion. As such, the reviewer is suggesting an altogether new project which carries considerable risk and will require us to secure dedicated funding to undertake.

6. Lines 403-415. The authors report poor neural induction and neuronal differentiation in GOSB2. As far as I understand, this phenotype does not represent the in vivo situation. Thus, it is not clear to what extent the in vitro 2D model describes the human patient.

The GOSB2 iPSC line we describe does represent the in vivo situation in Med24 knockout mouse embryos, but is clearly less severe because we are still able to detect MED24 protein expressed in this line. We do not have detailed clinical data of the patient from which this line was obtained to determine whether their neurological development is normal. However, it is well established that some individuals who have spina bifida also have abnormalities in supratentorial brain development. It is therefore likely that abnormalities in neuron differentiation/maturation are concomitant with spina bifida. Our findings in the GOSB2 line complement earlier studies which also identified deficiencies in the ability of patient-derived lines to form neurons, but were unable to functionally assess neuroepithelial cell behaviours we studied. This has now been clarified in the discussion:

Discussion: *Neuroepithelial cells of the GOSB2 line described here, which has partial loss of MED24, similarly produces a thinner neuroepithelium with larger apical areas. Although apical areas were not analysed in mouse models of Med24 deletion, these embryos also have shorter and non-pseudostratified neuroepithelium. *

Our GOSB2 line - which retains readily detectable MED24 protein - is clearly less severe than the mouse global knockout, and the clinical features of the patient from which this line was derived are milder than the phenotype of Med24 knockout embryos68. Mouse embryos lacking one of Med24's interaction partners in the mediator complex, Med1, also have thinner neuroepithelium and diminished neuronal differentiation but successfully close their neural tube85.

7.The experimental feat to derive cell lines from amniotic fluid and to perform experiments before birth is, in my view, heroic. However, I do not feel I learned much from the in vitro assays. There are many genetic changes that may cause the in vivo phenotype in the patient. The authors focus on MED24, but there is not enough convincing evidence that this is the key gene. I would like to suggest overexpression of MED24 as a rescue experiment, but I am not sure this is a single-gene phenotype. In addition, the fact that one patient line does not differentiate properly leads me to think that the patient lines do not strengthen the manuscript, and that perhaps additional clean mutations might contribute more.

We thank the reviewer for their praise of our personalised medicine approach and fully agree that neural tube defects are rarely monogenic. The patient lines we studied were not intended to provide mechanistic insight, but rather to demonstrate the future applicability of our approach to patient care. Our vision is that every patient referred for fetal surgery of spina bifida will have amniocytes (collected as part of routine cystocentesis required before surgery) reprogrammed and differentiated into neuroepithelial cells, then neural progenitors, to help stratify their post-natal care. One could also picture these cells becoming an autologous source for future cell-based therapies if they pass our reproducible analysis pipeline as functional quality control. This has now been clarified in the discussion:

Discussion____: The multi-genic nature of neural tube defect susceptibility, compounded by uncontrolled environmental risk factors (including maternal age and parity102), mean that patient-derived iPSC models are unlikely to provide mechanistic insight. They do provide personalised disease models which we anticipate will enable functional validation of genetic diagnoses for patients and their parents' recurrence risk in future pregnancies, and may eventually stratify patients' postnatal care. We also envision this model will enable quality control of patient-derived cells intended for future autologous cell replacement therapies, as is being developed in post-natal spinal cord injury103.

Minor comments: __ 1.Figure 1c. Text is cropped at the edge of the image.__

This image has been corrected.

Reviewer #2 (Significance (Required)): __ ...In addition, the model was unsuccessful in one of the two patient-derived lines, which limits generalizability and weakens claims of patient-specific predictive value.__

We disagree with the reviewer that "the model was unsuccessful in one of the two patient-derived lines". The GOSB1 line demonstrated deficiency of neuron differentiation independently of neuroepithelial biomechanical function, whereas the GOSB2 line showed earlier failure of neuroepithelial function. We also do not, at this stage, make patient-specific predictive claims: this will require longer-term matching of cell model findings with patient phenotypes over the next 5-10 years.

Reviewer #3: Major comments __ 1) One of my few concerns with this work is that the relative constriction of the apical surface with respect to the basal surface is not directly quantified for any of the experiments. This worry is slightly compounded by the 3D reconstructions Figure 1h, and the observation that overall cell volume is reduced and cell height increased simultaneously to area loss. Additionally, the net impact of apical constriction in tissues in vivo is to create local or global curvature change, but all the images in the paper suggest that the differentiated neural tissues are an uncurved monolayer even missing local buckles. I understand that these cells are grown on flat adherent surfaces limiting global curvature change, but is there evidence of localized buckling in the monolayer? While I believe-along with the authors-that their phenotypes are likely failures in apical constriction, I think they should work to strengthen this conclusion. I think the easiest way (and hopefully using data they already have) would be to directly compare apical area to basal area on a cell wise basis for some number of cells. Given the heterogeneity of cells, perhaps 30-50 cells per condition/line/mutant would be good? I am open to other approaches; this just seems like it may not require additional experiments.__

As the reviewer observes, our cultures cannot bend because they are adhered on a rigid surface. The apical and basal lengths of the cultures will therefore necessarily be roughly equal in length. Some inwards bending of the epithelium is expected at the edges of the dish, but these cannot be imaged. The live imaging we show in Figure 2 illustrates that, just as happens in vivo, apical constriction is asynchronous. This means not all cells will have 'bottle' shapes in the same culture. We now illustrate the evolution of these shapes in more detail in Supplementary Figure 1 (shown in point 2.1 above).

Additionally, the reviewer's comment motivated us to investigate local buckles in the apical surface of our cultures when their apical surfaces are dilated by ROCK inhibition. We hypothesised that the very straight apical surface in normal cultures is achieved by a balance of apical cell size and tension with pressure differences at the cell-liquid interface. Consistent with our expectation, the apical surface of ROCK-inhibited cultures becomes wrinkled (new Supplementary Figure 3). The VANGL2-KI lines do not develop this tortuous apical surface (as shown in Figure 3), which is to be expected given their modification is present throughout differentiation unlike the acute dilation caused by ROCK inhibition.

This new data complements our visualisation of apical constriction in live imaging, apical accumulation of phospho-myosin, and quantification of ROCK-dependent apical tension as independent lines of evidence that our cultures undergo apical constriction.

2) Another slight experimental concern I have regards the difference in laser ablation experiments detailed in Figure 3h-i from those of Figure 2d-e. It seems like WT recoil values in 3h-I are more variable and of a lower average than the earlier experiments and given that it appears significance is reached mainly by impact of the lower values, can the authors explain if this variability is expected to be due to heterogeneity in the tissue, i.e. some areas have higher local tension? If so, would that correspond with more local apical constriction?

There is no significant difference in recoil between the control lines in Figures 2 and 3, albeit the data in Figure 3 is more variable (necessitating more replicates: none were excluded). We also showed laser ablation recoil data in Supplementary Figure 10, in which we did identify a graphing error (now corrected, also no significant difference in recoil from the other control groups).

Minor comments __ 1) There seems to be a critical window at day 5 of the differentiation protocol, both in terms of cell morphology and the marker panel presented in Figure 1i. Do the authors have any data spanning the hours from day 5 to 6? If not, I don't think they need to generate any, but do I think this is a very interesting window worthy of further discussion for a couple of reasons. First, several studies of mouse neural tube closure have shown that various aspects of cell remodeling are temporally separable. For example, between Grego-Bessa et al 2016 and Brooks et al 2020 we can infer that apicobasal elongation rapidly increases starting at E8.5, whereas apical surface area reduction and constriction are apparent somewhat earlier at E8.0. I think it would be interesting to see if this separability is conserved in humans. Second, is there a sense of how the temporal correlation between the pluripotent and early neural fate marker data presented here corroborate or contradict the emerging set of temporally resolved RNA seq data sets of mouse development at equivalent early neural stages?__

Cell shape analysis between days 5 and 6 has now been added (see the response to point 2.1 below). As the reviewer predicted, this is a transition point when apical area begins to decrease and apicobasal elongation begins to increase.

We also thank the reviewer for this prompt to more closely compare our data to the previous mouse publications, which we have added to the discussion. The Grego-Bessa 2016 paper appears to show an increase in thickness between E7.75 and E8.5, but these are not statistically compared. Previous studies showed rapid apicobasal elongation during the period of neural fold elevation, when neuroepithelial cells apically constrict. This has now been added to the discussion:

Discussion In mice, neuroepithelial apicobasal thickness is spatially-patterned, with shorter cells at the midline under the influence of SHH signalling14,77,78. Apicobasal thickness of the cranial neural folds increases from ~25 µm at E7.75 to ~50 µm at E8.579: closely paralleling the elongation between days 2 and 8 of differentiation in our protocol. The rate of thickening is non-uniform, with the greatest increase occurring during elevation of the neural folds80, paralleled in our model by the rapid increase in thickness between days 4-6 as apical areas decrease. Elevation requires neuroepithelial apical constriction and these cells' apical area also decreases between E7.75 and E8.5 in mice79, but we and others have recently shown that this reduction is both region and sex-specific14,81. Specifically, apical constriction occurs in the lateral (future dorsal) neuroepithelium: this corresponds with the identity of the cells generated by the dual SMAD inhibition model we use56. More recently, Brooks et al82 showed that the rapid reduction in apical area from E8-E8.5 is associated with cadherin switching from CDH1 (E-cadherin) to CDH2 (N-cadherin). This is also directly paralleled in our human system, which shows low-level co-expression of CDH1 and CDH2 at day 4 of differentiation, immediately before apical area shrinks and apicobasal thickness increases.

Prompted by the in vivo data in Brooks et al (2025)82, we are keen to further explore the timing of CDH1/CDH2 switching versus apical constriction with new experimental data in revisions.

2) Can the authors elaborate a bit more on what is known regarding apicobasal thickening and pseudo-stratification and how their work fits into the current understanding in the discussion? This is a very interesting and less well studied mechanism critical to closure, which their model is well suited to directly address. I am thinking mainly of the Grego-Bessa at al., 2016 work on PTEN, though interestingly the work of Ohmura et al., 2012 on the NUAK kinases also shows reduced tissue thickening (and apical constriction) and I am sure I have missed others. Given that the authors identify MED24 as a likely candidate for the lack of apicobasal thickening in one of their patient derived lines, is there any evidence that it interacts with any of the known players?

We have now added further discussion on the mechanisms by which the neuroepithelium undergoes apicobasal elongation. Nuclear compaction is likely to be necessary to allow pseudostratification and apicobasal elongation. The reviewer's comment has led us to realise that diminished chromatin compaction is a potential outcome of MED24 down-regulation in our GOSB2 patient-derived line. Figure 4D suggests the nuclei of our MED24 deficient patient-derived line are less compacted than control equivalents and we propose to quantify nuclear volume in more detail to explore this possibility.

Additionally, we have already expanded our discussion as suggested by the reviewer:

Discussion: *Mechanistic separability of apical constriction and apicobasal elongation is consistent with biomechanical modelling of Xenopus neural tube closure showing that both are independently required for tissue bending61. Nonetheless, neuroepithelial apical constriction and apicobasal elongation are co-regulated in mouse models: for example, deletion of Nuak1/283, Cfl184, and Pten79 all produce shorter neuroepithelium with larger apical areas. Neuroepithelial cells of the GOSB2 line described here, which has partial loss of MED24, similarly produces a thinner neuroepithelium with larger apical areas. Although apical areas were not analysed in mouse models of Med24 deletion, these embryos also have shorter and non-pseudostratified neuroepithelium. *

Our GOSB2 line - which retains readily detectable MED24 protein - is clearly less severe than the mouse global knockout, and the clinical features of the patient from which this line was derived are milder than the phenotype of Med24 knockout embryos68. Mouse embryos lacking one of Med24's interaction partners in the mediator complex, Med1, also have thinner neuroepithelium and diminished neuronal differentiation but successfully close their neural tube85. As general regulators of polymerase activity, MED proteins have the potential to alter the timing or level of expression of many other genes, including those already known to influence pseudostratification or apicobasal elongation. MED depletion also causes redistribution of cohesion complexes86 which may impact chromatin compaction, reducing nuclear volume during differentiation.

3) Is there any indication that Vangl2 is weakly or locally planar polarized in this system? Figure 2F seems to suggest not, but Supplementary Figure 5 does show at least more supracellular cable like structures that may have some polarity. I ask because polarization seems to be one of the properties that differs along the anteroposterior axis of the neural plate, and I wonder if this offers some insight into the position along the axis that this system most closely models?

VANGL2 does not appear to be planar polarised in this system. This is similar to the mouse spinal neuroepithelium, in which apical VANGL2 is homogenous but F-actin is planar polarised (Galea et al Disease Models and Mechanisms 2018). We do observe local supracellular cable-like enrichments of F-actin in the apical surface of iPSC-derived neuroepithelial cells. _We propose to compare the length of F-actin cables and coherency of their orientation at the start and end of neuroepithelial differentiation, and in wild-type versus VANGL2-mutant epithelia._

4) I think some of the commentary on the strengths and limitations of the model found in the Results section should be collated and moved to the discussion in a single paragraph. For example ' This could also briefly touch on/compare to some of the other models utilizing hiPSCs (These are mentioned briefly in the intro, but this comparison could be elaborated on a bit after seeing all the great data in this work).

These changes have now been made:

__Discussion: __Some of these limitations, potentially including inclusion of environmental risk factors, can be addressed by using alternative iPSC-derived models93,94. For example, if patients have suspected causative mutations in genes specific to the surface (non-neural) ectoderm, such as GRHL2/3, 3D models described by Karzbrun et al49 or Huang et al95 may be informative. Characterisation of surface ectoderm behaviours in those models is currently lacking. These models are particularly useful for high-throughput screens of induced mutations95, but their reproducibility between cell lines, necessary to compare patient samples to non-congenic controls, remains to be validated. Spinal cell identities can be generated in human spinal cord organoids, although these have highly variable morphologies96,97. As such, each iPSC model presents limitations and opportunities, to which this study contributes a reductionist and highly reproducible system in which to quantitatively compare multiple neuroepithelial functions.

5) While the authors are generally good about labeling figures by the day post smad inhibition, in some figures it is not clear either from the images or the legend text. I believe this includes supplemental figures 2,5,6,8, and 10 (apologies if I simply missed it in one or more of them)

These have now been added.

6) The legend for Figure 2 refers to a panel that is not present and the remaining panel descriptions are off by a letter. I'm guessing this is a versioning error as the text itself seems largely correct, but it may be good to check for any other similar errors that snuck in

This has now been corrected.

7) The cell outlines in Figure 3d are a bit hard to see both in print and on the screen, perhaps increase the displayed intensity?

This has now been corrected.

8) The authors show a fascinating piece of data in Supplementary Figure 1, demonstrating that nuclear volume is halved by day 8. Do they have any indication if the DNA content remains constant (e.g., integrated DAPI density)? I suppose it must, and this is a minor point in the grand scheme, but this represents a significant nuclear remodeling and may impact the overall DNA accessibility.

We agree with the reviewer that the reduction in nuclear volume is important data both because it informs understanding of the reduction in total cell volume, and because it suggests active chromatin compaction during differentiation. Unfortunately, the thicker epithelium and superimposition of nuclei in the differentiated condition means the laser light path is substantially different, making direct comparisons of intensity uninterpretable. Additionally, the apical-most nuclei will mostly be in G2/M phase due to interkinetic nuclear migration. As such, the comparison of DAPI integrated density between epithelial morphologies would not be informative.

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Referee #3

Evidence, reproducibility and clarity

This manuscript by Ampartzidis et al., significantly extends the human induced pluripotent stem cell system originally characterized by the same group as a tool for examining cellular remodeling during differentiation stages consistent with those of human neural tube closure (Ampartzidis et al., 2023). Given that there are no direct ways to analyze cellular activity in human neural tube closure in vivo, this model represents an important platform for investigating neural tube defects which are a common and deleterious human developmental disease. Here, the authors carefully test whether this system is robust and reproducible when using hiPSC cells from different donors and pluripotency induction methods and find that despite all these variables the cellular remodeling programs that occur during early neural differentiation are statistically equivalent, suggesting that this system is a useful experimental substrate. Additionally, the carefully selected donor populations suggest these aspects of human neural tube closure are likely to be robust to sexual dimorphism and to reasonable levels of human genetic background variation, though more fully testing that proposition would require significant effort and be beyond the scope of the current work. Subsequent to this careful characterization, the authors next tested whether this system could be used to derive specific insights into cell remodeling during early neural differentiation. First, they used a reverse genetics approach to knock in a human point mutation in the critical regulator of planar cell polarity and apical constriction, Vangl2. Despite being identified in a patient, this R353C variant has not been directly functionally tested in a human system. The authors find that this variant, despite showing normal expression and phospho-regulation, leads to defects consistent with a failure in apical constriction, a key cell behavior required to drive curvature change during cranial closure. Finally, the authors test the utility of their hiPSC platform to understand human patient-specific defects by differentiating cells derived from two clinical spina bifida patients. The authors identify that one of these patients is likely to have a significant defect in fully establishing early proneural identity as well as defects in apicobasal thickening. While early remodeling occurs normally in the other patient, the authors observe significant defects in later neuronal induction and maturation. In addition, using whole exome sequencing the authors identify candidate variant loci that could underly these defects.

Major comments

1) One of my few concerns with this work is that the relative constriction of the apical surface with respect to the basal surface is not directly quantified for any of the experiments. This worry is slightly compounded by the 3D reconstructions Figure 1h, and the observation that overall cell volume is reduced and cell height increased simultaneously to area loss. Additionally, the net impact of apical constriction in tissues in vivo is to create local or global curvature change, but all the images in the paper suggest that the differentiated neural tissues are an uncurved monolayer even missing local buckles. I understand that these cells are grown on flat adherent surfaces limiting global curvature change, but is there evidence of localized buckling in the monolayer? While I believe-along with the authors-that their phenotypes are likely failures in apical constriction, I think they should work to strengthen this conclusion. I think the easiest way (and hopefully using data they already have) would be to directly compare apical area to basal area on a cell wise basis for some number of cells. Given the heterogeneity of cells, perhaps 30-50 cells per condition/line/mutant would be good? I am open to other approaches; this just seems like it may not require additional experiments.

2) Another slight experimental concern I have regards the difference in laser ablation experiments detailed in Figure 3h-i from those of Figure 2d-e. It seems like WT recoil values in 3h-I are more variable and of a lower average than the earlier experiments and given that it appears significance is reached mainly by impact of the lower values, can the authors explain if this variability is expected to be due to heterogeneity in the tissue, i.e. some areas have higher local tension? If so, would that correspond with more local apical constriction?

Minor comments

1) There seems to be a critical window at day 5 of the differentiation protocol, both in terms of cell morphology and the marker panel presented in Figure 1i. Do the authors have any data spanning the hours from day 5 to 6? If not, I don't think they need to generate any, but do I think this is a very interesting window worthy of further discussion for a couple of reasons. First, several studies of mouse neural tube closure have shown that various aspects of cell remodeling are temporally separable. For example, between Grego-Bessa et al 2016 and Brooks et al 2020 we can infer that apicobasal elongation rapidly increases starting at E8.5, whereas apical surface area reduction and constriction are apparent somewhat earlier at E8.0. I think it would be interesting to see if this separability is conserved in humans. Second, is there a sense of how the temporal correlation between the pluripotent and early neural fate marker data presented here corroborate or contradict the emerging set of temporally resolved RNA seq data sets of mouse development at equivalent early neural stages?

2) Can the authors elaborate a bit more on what is known regarding apicobasal thickening and pseudo-stratification and how their work fits into the current understanding in the discussion? This is a very interesting and less well studied mechanism critical to closure, which their model is well suited to directly address. I am thinking mainly of the Grego-Bessa at al., 2016 work on PTEN, though interestingly the work of Ohmura et al., 2012 on the NUAK kinases also shows reduced tissue thickening (and apical constriction) and I am sure I have missed others. Given that the authors identify MED24 as a likely candidate for the lack of apicobasal thickening in one of their patient derived lines, is there any evidence that it interacts with any of the known players?

3) Is there any indication that Vangl2 is weakly or locally planar polarized in this system? Figure 2F seems to suggest not, but Supplementary Figure 5 does show at least more supracellular cable like structures that may have some polarity. I ask because polarization seems to be one of the properties that differs along the anteroposterior axis of the neural plate, and I wonder if this offers some insight into the position along the axis that this system most closely models?

4) I think some of the commentary on the strengths and limitations of the model found in the Results section should be collated and moved to the discussion in a single paragraph. For example ' This could also briefly touch on/compare to some of the other models utilizing hiPSCs (These are mentioned briefly in the intro, but this comparison could be elaborated on a bit after seeing all the great data in this work).

5) While the authors are generally good about labeling figures by the day post smad inhibition, in some figures it is not clear either from the images or the legend text. I believe this includes supplemental figures 2,5,6,8, and 10 (apologies if I simply missed it in one or more of them)

6) The legend for Figure 2 refers to a panel that is not present and the remaining panel descriptions are off by a letter. I'm guessing this is a versioning error as the text itself seems largely correct, but it may be good to check for any other similar errors that snuck in

7) The cell outlines in Figure 3d are a bit hard to see both in print and on the screen, perhaps increase the displayed intensity?

8) The authors show a fascinating piece of data in Supplementary Figure 1, demonstrating that nuclear volume is halved by day 8. Do they have any indication if the DNA content remains constant (e.g., integrated DAPI density)? I suppose it must, and this is a minor point in the grand scheme, but this represents a significant nuclear remodeling and may impact the overall DNA accessibility.

Significance

Overall, I am enthusiastic about this work and believe it represents a significant step forward in the effort to establish precision medicine approaches for diagnoses of the patient-specific causative cellular defects underlying human neural tube closure defects. This work systematizes an important and novel tool to examine the cellular basis of neural tube defects. While other hiPSC models of neural tube closure capture some tissue level dynamics, which this model does not, they require complex microfluidic approaches and have limited accessibility to direct imaging of cell remodeling. Comparatively, the relative simplicity of the reported model and the work demonstrating its tractability as a patient-specific and reverse genetic platform make it unique and attractive. This work will be of interest to a broad cross section of basic scientists interested in the cellular basis of tissue remodeling and/or the early events of nervous system development as well as clinical scientists interested in modeling the consequences of patient specific human genetic deficits identified in neural tube defect pregnancies.

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Referee #2

Evidence, reproducibility and clarity

The authors' work focuses on studying cell morphological changes during differentiation of hPSCs into neural progenitors in a 2D monolayer setting. The authors use genetic mutations in VANGL2 and patient-derived iPSCs to show that (1) human phenotypes can be captured in the 2D differentiation assay, and (2) VANGL2 in humans is required for neural contraction, which is consistent with previous studies in animal models. The results are solid and convincing, the data are quantitative, and the manuscript is well written. The 2D model they present successfully addresses the questions posed in the manuscript. However, the broad impact of the model may be limited, as it does not contain NNE cells and does not exhibit tissue folding or tube closure, as seen in neural tube formation. Patient-derived lines are derived from amniotic fluid cells, and the experiments are performed before birth, which I find to be a remarkable achievement, showing the future of precision medicine.

Major comments:

1.Figure 1. The authors use F-actin to segment cell areas. Perhaps this could be done more accurately with ZO-1, as F-actin cables can cross the surface of a single cell. In any case, the authors need to show a measure of segmentation precision: segmented image vs. raw image plus a nuclear marker (DAPI, H2B-GFP), so we can check that the number of segmented cells matches the number of nuclei. 2.Lines 156-166. The authors claim that changes in gene expression precede morphological changes. I am not convinced this is supported by their data. Fig. 1g (epithelial thickness) and Fig. 1k (PAX6 expression) seem to have similar dynamics. The authors can perform a cross-correlation between the two plots to see which Δt gives maximum correlation. If Δt < 0, then it would suggest that gene expression precedes morphology, as they claim. Fig. 1j shows that NANOG drops before the morphological changes, but loss of NANOG is not specific to neural differentiation and therefore should not be related to the observed morphological changes. 3.Figure 2d. The laser ablation experiment in the presence of ROCK inhibitor is clear, as I can easily see the cell outlines before and after the experiment. In the absence of ROCK inhibitor, the cell edges are blurry, and I am not convinced the outline that the authors drew is really the cell boundary. Perhaps the authors can try to ablate a larger cell patch so that the change in area is more defined. 4.Figure 2d. Do the cells become thicker after recoil? 5.Figure 3. The authors mention their previous study in which they show that Vangl2 is not cell-autonomously required for neural closure. It will be interesting to study whether this also the case in the present human model by using mosaic cultures. 6.Lines 403-415. The authors report poor neural induction and neuronal differentiation in GOSB2. As far as I understand, this phenotype does not represent the in vivo situation. Thus, it is not clear to what extent the in vitro 2D model describes the human patient. 7.The experimental feat to derive cell lines from amniotic fluid and to perform experiments before birth is, in my view, heroic. However, I do not feel I learned much from the in vitro assays. There are many genetic changes that may cause the in vivo phenotype in the patient. The authors focus on MED24, but there is not enough convincing evidence that this is the key gene. I would like to suggest overexpression of MED24 as a rescue experiment, but I am not sure this is a single-gene phenotype. In addition, the fact that one patient line does not differentiate properly leads me to think that the patient lines do not strengthen the manuscript, and that perhaps additional clean mutations might contribute more.

Minor comments:

1.Figure 1c. Text is cropped at the edge of the image.

Significance

This study establishes a quantitative, reproducible 2D human iPSC-to-neural-progenitor platform for analyzing cell-shape dynamics during differentiation. Using VANGL2 mutations and patient-derived iPSCs, the work shows that (1) human phenotypes can be captured in a 2D differentiation assay and (2) VANGL2 is required for neural contraction (apical constriction), consistent with animal studies. The results are solid, the data are quantitative, and the manuscript is well written. Although the planar system lacks non-neural ectoderm and does not exhibit tissue folding or tube closure, it provides a tractable baseline for mechanistic dissection and genotype-phenotype mapping. The derivation of patient lines from amniotic fluid and execution of experiments before birth is a remarkable demonstration that points toward precision-medicine applications, while motivating rescue strategies and additional clean genetic models. However, overall I did not learn anything substantively new from this manuscript; the conclusions largely corroborate prior observations rather than extend them. In addition, the model was unsuccessful in one of the two patient-derived lines, which limits generalizability and weakens claims of patient-specific predictive value.

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Referee #1

Evidence, reproducibility and clarity

In this manuscript, Ampartzidis et al. report the establishment of an iPSC-derived neuroepithelial model to examine how mutations from spina bifida patients disrupt fundamental cellular properties that underlie neural tube closure. The authors utilize an adherent neural induction protocol that relies on dual SMAD inhibition to differentiate three previously established iPSC lines with different origins and reprogramming methods. The analysis is comprehensive and outstanding, demonstrating reproducible differentiation, apical-basal elongation, and apical constriction over an 8-day period among the 3 lines. In inhibitor studies, it is shown that apical constriction is dependent on ROCK and generates tension, which can be measured using an annular laser ablation assay. Since this pathway is dependent on PCP signaling, which is also implicated in neural tube defects, the authors investigated whether VANGL2 is required by generating 2 lines with a pathogenic patient-derived sequence variant. Both lines showed reduced apical constriction and reduced tension in the laser ablation assays. The authors then established lines obtained from amniocentesis, including 2 control and 2 spina bifida patient-derived lines. These remarkably exhibited different defects. One line showed defects in apical-basal elongation, while the other showed defects in neural differentiation. Both lines were sequenced to identify candidate variants in genes implicated in NTDs. While no smoking gun was found in the line that disrupts neural differentiation (as is often the case with NTDs), compound heterozygous MED24 variants were found in the patient whose cells were defective in apical-basal elongation. Since MED24 has been linked to this phenotype, this finding is especially significant.

Some details are missing regarding the method to evaluate the rigor and reproducibility of the study.

Major points

It is mentioned throughout the manuscript that 3 plates were evaluated per line. I believe these are independently differentiated plates. This detail is critical concerning rigor and reproducibility. This should be clearly stated in the Methods section and in the first description of the experimental system in the Results section for Figure 1. For the patient-specific lines - how many lines were derived per patient? Was the Vangl2 variant introduced by prime editing? Base editing? The details of the methods are sparse.<br /> Some additional suggestions for improvement.<br /> The abstract could be more clearly written to effectively convey the study's importance. Here are some suggestions Line 26: Insert "apicobasal" before "elongation" - the way it is written, I initially interpreted it as anterior-posterior elongation. Line 29: Please specify that the lines refer to 3 different established parent iPSC lines with distinct origins and established using different reprogramming methods, plus 2 control patient-derived lines. - The reproducibility of the cell behaviors is impressive, but this is not captured in the abstract. Line 32: add that this mutation was introduced by CRISPR-Cas9 base/prime editing The last sentence of the abstract states that the study only links apical constriction to human NTDs, but also reveals that neural differentiation and apical-basal elongation were found. The introduction could also use some editing. Line 71: insert "that pulls actin filaments together" after "power strokes" Line 73: "apically localized," do you mean "mediolaterally" or "radially"? Line 75: Can you specify that PCP components promote "mediolaterally orientated" apical constriction Lines 127: Specify that NE functions include apical basal elongation and neurodifferentiation are disrupted in patient-derived models

Significance

This paper is significant not only for verifying the cell behaviors necessary for neural tube closure in a human iPSC model, but also for establishing a robust assay for the functional testing of NTD-associated sequence variants. This will not only demonstrate that sequence variants result in loss of function but also determine which cellular behaviors are disrupted.

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Reply to the reviewers

Manuscript number: RC-2025-03220

Corresponding author(s): Ryusuke Niwa, Yuko Shimada-Niwa, and Wei Sun

Dear Editors,

We are pleased to submit our revised manuscript of RC-2025-03220R. The reviewers’ comments from Review Commons are presented in italic.

For submission of our current revised manuscript, we provide two Word files, which are the “clean” and “Track-and-Change” files. Page and line numbers described below correspond to those of the “clean” file. The “Track-and-Change” file might be helpful for Reviewers to find what we have changed for the current revision.

We hope that the revised version is now suitable for the next stage of evaluation.

Sincerely,

Ryusuke Niwa, Yuko Shimada-Niwa, and Wei Sun

1. General Statements [optional]

We sincerely thank the reviewers for their thoughtful feedback on our initial submission. Experiments that we will conduct and the revisions on the manuscript that have already been incorporated are detailed below in the point-by-point response. For this revised submission, two versions of the manuscript are provided: a clean copy and a tracked-changes file. Page and line numbers mentioned below refer to the clean version, while the tracked-changes file is intended to help reviewers easily identify the revisions made.

In preparing the revision plan, we have included additional data, some of which were generated in collaboration with new contributors. Accordingly, we would like to propose adding Yuichi Shichino and Shintaro Iwasaki as co-authors to acknowledge their contributions.

2. Description of the planned revisions__ __

__

- Also, the authors show that two different RNAi lines for NudC give the same defects - it would be good to know if the RNAi lines target the same or different sequences in the NudC transcripts. Alternatively, it would be equally good to show that trans-allelic combinations of NudC mutants have the same defects in the prothoracic glands and the salivary glands as the RNAi. Instead, they examine only overall body size, developmental delays and lethality in the trans-hetero allelic NudC mutants.

Author response:

In response to the second part of the criticism, we will further validate the observed phenotypes by examining tissue and nuclear size, chromosomal structure, and the levels of Fibrillarin and RpS6 proteins in the prothoracic glands and salivary glands of NudC mutants.

__

- It would be quite helpful to characterize the "5 blob" and "shortened polytene chromosome arm" defects shown in Figure 2 and Figure 6. Are these partially polytenized chromosomes or are large sections of the chromosomes missing or just underreplicated? What do the chromosomes look like if you lyse the nuclei, spread the chromosomes and stain with DAPI or Hoechst - this is a pretty standard practice and would reveal much more about the structure of the polytene chromosomes.

Author response:

To address these structural concerns more clearly, we plan to apply established protocols to obtain higher-resolution images and gather more detailed information on chromosome morphology.

__ - Discussion, line 468. I don't think the authors have provided evidence of DNA damage. With the experiments they have shown, the chromosomes look abnormal - not clear what is abnormal.

Author response:

To further confirm DNA damage in NudC knockdown salivary gland cells, we plan to perform a TUNEL assay, which detects DNA fragmentation associated with damage.

We would like to note that, in the current manuscript, we have shown that depletion of NudC, eIF5, RpLP0-like, or Nopp140 increased γH2Av levels, suggesting activation of the DNA damage response (Figures 6B and 6C).

__

*The authors claim that NudC has a dual role as a cell cycle/cytoskeleton regulator and as a ribosome biogenesis factor. However, because NudC knockdown reduces nuclear size and ploidy (Figures 1F and 2H-2I), the authors cannot exclude that decreased rDNA dosage and nucleolar volume contribute to reduced rRNA signals and that the effects seen are due to a NudC involvement in endoreplication, the rRNA reduction being a consequence of lower polyploidy. Different allelic combinations of NudC induce larval growth defects (Figure S5), consistent with a NudC role in endoreplication. To circumvent this, the authors could genetically modulate endocycle progression (e.g., E2F or Fzr overexpression) in the NudC RNAi background to test whether inducing endoreplication rescues rRNA production and nucleolar volume. This would establish causality between the endocycle state and rRNA output and clarify whether NudC's primary role is in RiBi or endocycle control. *

Author response: In response to Reviewer #2’s suggestion, we plan to genetically modify the progression of the endocycle by inducing continuous expression of Cyclin E (CycE), E2F1, and Fzr in NudC RNAi salivary glands to test whether promoting endoreplication can restore rRNA production and nucleolar volume.

In fact, we have attempted to rescue the developmental arrest in animals with NudC-deficient prothoracic glands (PGs) by inducing continuous expression of CycE. Two constructs, UAS-CycE-1 (BDSC#30725) and UAS-CycE-2 (BDSC#30924), were used. UAS-CycE-1 has previously been shown to rescue developmental arrest in PG-specific TOR loss-of-function animals (Ohhara, Kobayashi, and Yamanaka. PLoS Genetics 13 (1): e1006583, 2017). We introduced each construct into NudC knockdown PGs. However, continuous expression of CycE did not restore development (Figure A as shown below), suggesting that NudC functions in the polyploid cells extend beyond endocycle regulation. We do not currently plan to include the PG data shown in Figure A in the revised manuscript. We will evaluate whether it would be meaningful to present PG data alongside salivary gland results once we have obtained and analyzed data from the salivary gland rescue experiment.

__Figure A. _Survival and developmental progression following continuous expression of CycE._ __Control (phtm>dicer2, +), NudC knockdown (phtm>dicer2, NudC RNAi), and NudC RNAi + CycE (phtm>dicer2, NudC RNAi, CycE) flies were analyzed at 10 days after hatching (10 dAH). Dead indicates dead larvae; L3 denotes third-instar larvae. Sample sizes (number of flies) are shown below each bar.

__

*The conclusion that NudC maintains rRNA levels is derived from salivary gland RNAi phenotypes with strong reductions in ITS1/ITS2 and 18S/28S signals (Figure 4B-4K) and reduced 28S by Northern (Figure 4L), plus corroboration in fat body cells (Figure S7). The authors verified knockdown using two independent RNAi lines for growth phenotypes and NudC::GFP reduction (Figure S2) and generated a UAS-FLAG::NudC transgene (Key Resources), but rRNA measurements were reported for only one RNAi line without rescue. Rescue of the rRNA phenotype by transgenic NudC re-expression, or replication of the rRNA decrease with a second, non-overlapping RNAi, would directly attribute the effect to NudC. In the absence of these standard validation controls, an off-target explanation remains plausible. *

Author response:

We plan to analyze rRNA FISH signals in salivary glands and fat bodies using a second, non-overlapping RNAi strain to confirm the reproducibility of the observed effects.

__ - The authors report in Fig. 2 elevated γH2Av in SG cells upon NudC knockdown and interpret this as evidence of chromosome destabilization. They also state that apoptosis is not observed in Fig S10. However, the increase in γH2Av could reflect transient or early apoptotic events or other stress responses triggered by NudC depletion, rather than direct defects in endoreplication or genome stability. I suggest that the authors clarify this important point, for example, by co-expressing apoptotic inhibitors such as P35, or by using the TUNEL assay, which is more sensitive than anti-Caspase3 or Dcp1 antibodies.

Author response:

We plan to perform a TUNEL assay on salivary gland cells to evaluate apoptosis associated with NudC depletion.

__ - Activation of the JNK pathway is often accompanied by apoptosis. It would strengthen the conclusions if the authors included a positive control to confirm that apoptosis is not induced under these experimental conditions, ensuring that the observed effects are specific to autophagy and not confounded by cell death.

Author response:

We will analyze pJNK and autophagy levels in animals expressing a constitutively-active form of hemipterous (hep) (hep[CA] ) under the control of fkh-GAL4 driver as a positive control. hep encodes the Drosophila JNK kinase, and it is well established that forced expression of hep[CA] induces JNK phosphorylation and activation.

__ - In Figure S1, reduction of NudC in the fat body appears to induce a starvation-like phenotype, suggesting a potential impairment of metabolic or nutrient-sensing pathways. It would be important to determine whether modulation of nutrient-responsive signaling could rescue this phenotype. Specifically, have the authors examined whether activation of the TOR or PI3K pathways mitigates the effects of NudC knockdown? Assessing pathway activity (e.g., via phospho-S6K or phospho-Akt levels) or performing genetic rescue experiments with pathway activators could clarify whether the observed phenotypes are mediated through disrupted nutrient signaling rather than a secondary effect of general cellular stress. Such analyses could also provide a mechanistic explanation for the increased autophagy observed in these cells.

Author response:

1. We will analyze phospho-S6K levels in salivary glands and fat bodies by immunostaining.
2. To activate the TOR pathway in NudC RNAi fat bodies, we will overexpress Rheb, an established upstream activator of the TOR pathway in Drosophila, which has been shown to robustly increase TOR signaling and S6K phosphorylation.

   __ - The current images of autophagic vesicles in the SG in Fig. 8B are not clearly visible and quantified. Considering the large size of these polyploid cells, higher-resolution images or alternative imaging approaches should be presented to better visualize and quantify autophagy. This would make the conclusions regarding enhanced autophagy more convincing. In addition, this data could be further strengthened by expanding the analysis of autophagy to other cell types. For example, examining autophagy in fat body cells, where autophagy plays a primary physiological role associated with rRNA accumulation (Fig. S7), rather than a reduction like in SG (Fig. 4), could provide a useful comparison for the function of NudC between polyploid cells.

Author response:

In response to the second part of the reviewer’s comment, we will conduct additional experiments using anti-Atg8a immunostaining and/or LysoTracker staining to analyze autophagy in NudC RNAi fat bodies and prothoracic glands. These experiments will help further characterize the cellular responses associated with NudC depletion.

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

__

-The title is a bit problematic since they haven't shown that NudC doesn't also affect normal mitotic cells - they only look at polyploid cells, but that doesn't mean normal mitotic cells are not also affected.

Author response:

In response to the suggestion from Reviewer #1, we have revised the title from “NudC moonlights in ribosome biogenesis and homeostasis in Drosophila melanogaster polyploid cells” to “NudC moonlights in ribosome biogenesis and homeostasis in polyploid cells of Drosophila melanogaster” to place greater emphasis on “polyploid cells.”

Regarding mitotic cells, we have added new data in the revised manuscript (Figure S7; lines 249–256 and 417–418) demonstrating that NudC regulates apoptosis and stress responses in mitotic imaginal wing disc cells. However, as the main focus of our study remains polyploid cells, we have chosen to retain the emphasis in the title.

__

- Also, the authors show that two different RNAi lines for NudC give the same defects - it would be good to know if the RNAi lines target the same or different sequences in the NudC transcripts. Alternatively, it would be equally good to show that trans-allelic combinations of NudC mutants have the same defects in the prothoracic glands and the salivary glands as the RNAi. Instead, they examine only overall body size, developmental delays and lethality in the trans-hetero allelic NudC mutants.

Author response:

In response to the first half of criticism, the two RNAi lines used for NudC target distinct sequences. We have added the corresponding RNAi target sites to Figure S4A for clarity.

__

- Results: Lines 261 - 266. Seeing electron dense structures in TEMs and seeing increased Me31B staining by confocal imaging in the cytoplasm is insufficient evidence that the electron dense structures are P-bodies. They could be the P-bodies but they could also be aggregated ribosomes; there is insufficient evidence to "confirm" that they are P-bodies - maybe just say "suggests".

Author response:

In response to Reviewer #1’s suggestion, we have revised lines 261–262 to avoid using the word "confirm." The new sentence reads: “Immunostaining with the P-body marker Me31B reveals numerous cytoplasmic P-bodies in NudC-deficient SG cells,” which appears in lines 293–295.

__

- Abstract, lines 28 - 31. I think this gene has been identified before. The authors probably want to say they have discovered a role for this gene in RiBi.

Author response:

We have followed Reviewer #1’s suggestion and revised the sentence in lines 35–37 to: “In this study, we discovered a role for the gene NudC (nuclear distribution C, dynein complex regulator) in RiBi within polyploid cells of Drosophila melanogaster larvae.”

__

- Introduction, line 66. The protein is imported into the nucleus, where it localizes to the nucleolus - technically the protein is not imported into the nucleolus.

Author response:

To correct the misrepresentation in line 66, we have revised the sentence to: “RP mRNAs are synthesized by RNA polymerase II, and exported to the cytoplasm for translation. Then, RPs are imported into the nucleus, where they localize to the nucleolus.” in lines 70–73.

__ - Introduction, line 70. To be comprehensive in the description of ribosome biogenesis, the authors may want to mention that the 40S and 60S subunits are then exported from the nucleus and form the 80S subunit in the cytoplasm during translation.

Author response:

To improve the representation, we have revised the sentences in lines 73 – 78 as follows: “Within the nucleolus, rRNAs and RPs assemble into pre-40S and pre-60S subunits. immature versions of the small (40S) and large (60S) subunits, respectively, that undergo maturation with numerous ribosome biogenesis factors (RBFs) (Greber, 2016). The 40S and 60S subunits are then transported separately to the cytoplasm, where they combine to form functional 80S ribosomes, capable of sustaining protein synthesis (Pelletier et al., 2018).”

__ - Introduction, line 98. May want to cite paper showing that Minute mutations turn out to be mutations in individual ribosomal protein genes.

Author response:

As Reviewer #1 suggested, we have cited two, Marygold et al. (2007) entitled “The ribosomal protein genes and Minute loci of Drosophila melanogaster” and Recasens-Alvarez et al. (2021) entitled “Ribosomopathy-associated mutations cause proteotoxic stress that is alleviated by TOR inhibition” along with He et al. (2015). The inappropriate citation to Brehme (1939) has been removed.

__ - Results, lines 292. Since they didn't knock down NudC in the fat body cells in this experiment, this comment seems irrelevant.

Author response:

We would like to clarify that the phenotype observed with fkh-GAL4-driven NudC RNAi was specific to salivary glands, and no obvious phenotypes were detected in the surrounding fat body cells, which do not express fkh-GAL4. In this context, the adjacent fat body cells serve as an internal control.

In the revised manuscript, the sentence has been rewritten as: “In contrast, the fat body cells surrounding NudC-deficient SGs did not show this reduction (Figure S9),” in lines 323–324.

__ - Figure 6A. Hoechst is misspelled.

__

- Fig. 2 I - Hoeschest should be Hoescht.

Author response:

We have fixed the error.

__ *- Given that prothoracic gland (PG) size influences ecdysone production, the finding that NudC knockdown alters PG cell size, morphology, and cytoskeletal organization raises the possibility that ecdysone synthesis or signaling may also be affected. This, in turn, could explain the delayed maturation phenotype observed in Figure 1. I recommend testing whether ectopic activation of ecdysone signaling, for instance through 20-hydroxyecdysone (20E) supplementation, can rescue the defects in PG size and developmental timing. Such an experiment would strengthen the link between NudC function, PG morphology, and ecdysone-dependent developmental progression. *

Author response:

We have conducted experiments showing that developmental defects in NudC RNAi animals can be partially rescued by administering 20E. Approximately 32% of NudC RNAi larvae fed with 20E completed pupariation. These new data have been added to Figure S1B and are described in the main text (lines 165-168).

Regarding PG size, our experiments show that PG growth remains inhibited following 20E administration (Figure B as shown below). This observation indicates that treatment with exogenous 20E does not restore PG growth in NudC RNAi animals, suggesting that other factors may be required for normal PG development beyond ecdysone supplementation.

Because this analysis is not the main focus of our manuscript, we currently plan not to include these data in the revised manuscript.

Figure B. Prothoracic gland (PG) size ____after 20E administration.

To assess whether 20E supplementation could restore PG size, control (phtm>dicer2, +) and NudC RNAi (phtm>dicer2, NudC RNAi) larvae were transferred at 60 hours after hatching (hAH) to standard medium containing 20E dissolved in 100% ethanol. Control groups were transferred to medium containing the same volume of 100% ethanol at the same time point. PG size was quantified at the wandering stage. Sample sizes (number of glands) are shown below each bar. Bars represent mean ± SD. **p * *

__ - Additionally, qRT-PCR can be performed to assess the expression levels of ecdysone precursors or target genes in whole larvae, serving as a readout of ecdysone activity, including dilp8, which is usually upregulated when ecdysone levels are reduced.

Author response: To investigate ecdysone biosynthesis, Halloween genes including nvd, spok, sro, phm, dib, and sad were measured by conducting qRT-PCR. In NudC RNAi animals, nvd, sro and phm were suppressed at late L3 stage, indicating that NudC in the PG is required for ecdysone biosynthesis. The new data are described in Figure S1A and in the main text (lines 159-164) in the revised manuscript.

__ - The current images of autophagic vesicles in the SG in Fig. 8B are not clearly visible and quantified. Considering the large size of these polyploid cells, higher-resolution images or alternative imaging approaches should be presented to better visualize and quantify autophagy. This would make the conclusions regarding enhanced autophagy more convincing.

Author response:

Regarding the image quality issue, we have provided improved images of anti-Atg8a immunostaining in the salivary gland mosaic clones (Figure 8B) and included additional data from SG-specific knockdown cells (Supplemental Figures S13A-S13F) to provided quantitative results.

__ - Furthermore, including experiments in other cell types, such as imaginal disc cells, where apoptosis is more readily induced, would help determine whether the effects of NudC knockdown are specific to polyploid cells or are more broadly applicable.

Author response: We found that apoptosis was observed in NudC RNAi wing discs. In the revised manuscript, we have included this data in Figure S7 and referenced it in the main text (lines 249–256).

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

__ - Results, lines 285 to 298. In situs with multiple probes that detect all parts of both the pre-rRNA and processed rRNA indicate that all are down in the SG in NudC knockdowns, but that the 18S and 28S rRNAs are down the internal transcribed spacers go up - can the authors explain or hypothesize how this could happen?

Author response:

As Reviewer #1 indicated, we indeed observed that internal transcribed spacer (ITS) levels decrease in NudC knockdown salivary glands, but increase in knockdown fat bodies. Our hypothesis is that, as noted in the Discussion (lines 529–534), ribosome abundance is typically linked to protein synthesis. Salivary gland cells, which are highly active in protein production, may be particularly sensitive to disruptions in ribosome biogenesis. Therefore, NudC may maintain appropriate levels of rRNA with its impact varying according to the specific regulatory mechanisms of each cell type. We do not have a further explanation for this phenomenon, and therefore we have retained the original sentences without adding new ones.

__ - The data presented in Fig 4 show that NudC knockdown reduces pre-rRNA (ITS1/ITS2) and mature 18S/28S rRNAs in a tissue-specific manner. However, it remains unclear whether these reductions have functional consequences for ribosome assembly and translation. I recommend that the authors perform polysome profiling or an equivalent assay to assess the impact of NudC loss on actively translating ribosomes. This approach would provide a quantitative readout of translation efficiency and clarify whether the observed rRNA defects lead to impaired protein synthesis. Additionally, polysome profiling could help explain the tissue-specific differences observed between salivary glands and fat body cells.

Author response:

We performed ribosome fractionation using wild-type salivary glands and repeated the experiment three times with 56–62 gland pairs per sample. As shown in Figure C, the polyribosome peaks (grey lines) are not prominent, indicating that a much larger number of glands would be required for robust polysome profiling. Given that NudC RNAi salivary glands are significantly smaller than wild-type glands, collecting enough tissue for equivalent profiling would be technically difficult. Therefore, we concluded that obtaining sufficient RNAi samples for polysome profiling is extremely challenging, and these data have not been included in the revised manuscript.

On the other hand, we would like to emphasize that we observed a significant reduction in O-propargyl puromycin (OPP) labeling in NudC-deficient salivary gland cells (Figure 3B), which provides strong evidence for reduced translational activity.

__Figure C. Ribosomal fraction profiles of wild-type salivary glands. __Salivary glands from the late L3 larvae were dissected for analysis. Polyribosome peaks are indicated in grey. The number of salivary gland pairs used for each sample is shown above each bar.

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Referee #3

Evidence, reproducibility and clarity

Summary:

NudC (Nuclear Distribution Protein C) is a conserved, dynein-associated protein that plays a critical role in nuclear positioning and neuronal development. It functions as a co-chaperone, stabilizing components of the dynein-motor complex, thereby facilitating proper microtubule-dependent nuclear migration and intracellular transport. In developing neurons, NudC is essential for correct dendritic morphogenesis, ensuring nuclei and dendritic processes attain their proper spatial organization. Loss or knockdown of nudC leads to defects in nuclear localization, aberrant dendritic architecture, and mitotic stress, which can predispose cells to apoptosis. Highlighting NudC as a pivotal regulator of intracellular dynamics, cytoskeletal organization, In this paper, the authors propose a role for the gene in regulating ribosomal biogenesis. However, the interpretation of these results remains somewhat unclear, as the observed effects on ribosome biogenesis could potentially result from nonspecific cellular stress or toxicity caused by gene knockdown in polyploid cells. At this stage, the link between NudC and the regulation of ribosomal biogenesis is not fully convincing. Additional experiments could help clarify whether this relationship is direct or secondary to other cellular effects. I suggest conducting additional experiments to strengthen this hypothesis; for example, by examining whether knocking down NudC would give similar effects as observed for other genes that regulate RiBi in other organs and tissues where ribosomal biogenesis and stress responses have been well-characterized, such as the imaginal discs. Comparing the results across these different tissues would help clarify whether the effects of gene knockdown are specific to polyploid cells or represent a more general cellular response.

Suggested experiments to sustain the paper:

1. Given that prothoracic gland (PG) size influences ecdysone production, the finding that NudC knockdown alters PG cell size, morphology, and cytoskeletal organization raises the possibility that ecdysone synthesis or signaling may also be affected. This, in turn, could explain the delayed maturation phenotype observed in Figure 1. I recommend testing whether ectopic activation of ecdysone signaling, for instance through 20-hydroxyecdysone (20E) supplementation, can rescue the defects in PG size and developmental timing. Such an experiment would strengthen the link between NudC function, PG morphology, and ecdysone-dependent developmental progression.
2. Additionally, qRT-PCR can be performed to assess the expression levels of ecdysone precursors or target genes in whole larvae, serving as a readout of ecdysone activity, including dilp8, which is usually upregulated when ecdysone levels are reduced.
3. The authors report in Fig. 2 elevated γH2Av in SG cells upon NudC knockdown and interpret this as evidence of chromosome destabilization. They also state that apoptosis is not observed in Fig S10. However, the increase in γH2Av could reflect transient or early apoptotic events or other stress responses triggered by NudC depletion, rather than direct defects in endoreplication or genome stability. I suggest that the authors clarify this important point, for example, by co-expressing apoptotic inhibitors such as P35, or by using the TUNEL assay, which is more sensitive than anti-Caspase3 or Dcp1 antibodies.
4. The data presented in Fig 4 show that NudC knockdown reduces pre-rRNA (ITS1/ITS2) and mature 18S/28S rRNAs in a tissue-specific manner. However, it remains unclear whether these reductions have functional consequences for ribosome assembly and translation. I recommend that the authors perform polysome profiling or an equivalent assay to assess the impact of NudC loss on actively translating ribosomes. This approach would provide a quantitative readout of translation efficiency and clarify whether the observed rRNA defects lead to impaired protein synthesis. Additionally, polysome profiling could help explain the tissue-specific differences observed between salivary glands and fat body cells.
5. Activation of the JNK pathway is often accompanied by apoptosis. It would strengthen the conclusions if the authors included a positive control to confirm that apoptosis is not induced under these experimental conditions, ensuring that the observed effects are specific to autophagy and not confounded by cell death.
6. In Figure S1, reduction of NudC in the fat body appears to induce a starvation-like phenotype, suggesting a potential impairment of metabolic or nutrient-sensing pathways. It would be important to determine whether modulation of nutrient-responsive signaling could rescue this phenotype. Specifically, have the authors examined whether activation of the TOR or PI3K pathways mitigates the effects of NudC knockdown? Assessing pathway activity (e.g., via phospho-S6K or phospho-Akt levels) or performing genetic rescue experiments with pathway activators could clarify whether the observed phenotypes are mediated through disrupted nutrient signaling rather than a secondary effect of general cellular stress. Such analyses could also provide a mechanistic explanation for the increased autophagy observed in these cells.
7. The current images of autophagic vesicles in the SG in Fig. 8B are not clearly visible and quantified. Considering the large size of these polyploid cells, higher-resolution images or alternative imaging approaches should be presented to better visualize and quantify autophagy. This would make the conclusions regarding enhanced autophagy more convincing. In addition, this data could be further strengthened by expanding the analysis of autophagy to other cell types. For example, examining autophagy in fat body cells, where autophagy plays a primary physiological role associated with rRNA accumulation (Fig. S7), rather than a reduction like in SG (Fig. 4), could provide a useful comparison for the function of NudC between polyploid cells.
8. Furthermore, including experiments in other cell types, such as imaginal disc cells, where apoptosis is more readily induced, would help determine whether the effects of NudC knockdown are specific to polyploid cells or are more broadly applicable.

Significance

NudC is a conserved dynein-associated protein essential for nuclear positioning, dendritic morphogenesis, and intracellular transport. This study suggests a novel role for NudC in regulating ribosome biogenesis, potentially linking cytoskeletal organization with protein synthesis and cellular homeostasis. Validating this connection across different tissues could reveal whether NudC serves as a general coordinator of intracellular architecture and translational capacity, providing new insights into how cells integrate structural and biosynthetic functions.

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Referee #2

Evidence, reproducibility and clarity

Summary

In this manuscript, Duoduo Shi and colleagues, propose that NudC, previously known for its role in dynein regulation, has a second role as a critical regulator of ribosome biogenesis (RiBi) in Drosophila melanogaster polyploid cells, where its depletion reduces rRNA levels and ribosome abundance, triggering a compensatory homeostatic response that upregulates ribosomal proteins and biogenesis factors, similar to the response observed upon depletion of established ribosome biogenesis factors.

Strengths

The authors propose a novel role for NudC as a regulator of ribosome biogenesis (RiBi) which is dynein-independent and they provide a detailed homeostatic response to RiBi stress.

Weaknesses

NudC downregulation may be affecting the endocycle and an endoreplication defect may drive rRNA reduction.

Major comments

The authors claim that NudC has a dual role as a cell cycle/cytoskeleton regulator and as a ribosome biogenesis factor. However, because NudC knockdown reduces nuclear size and ploidy (Figures 1F and 2H-2I), the authors cannot exclude that decreased rDNA dosage and nucleolar volume contribute to reduced rRNA signals and that the effects seen are due to a NudC involvement in endoreplication, the rRNA reduction being a consequence of lower polyploidy. Different allelic combinations of NudC induce larval growth defects (Figure S5), consistent with a NudC role in endoreplication. To circumvent this, the authors could genetically modulate endocycle progression (e.g., E2F or Fzr overexpression) in the NudC RNAi background to test whether inducing endoreplication rescues rRNA production and nucleolar volume. This would establish causality between the endocycle state and rRNA output and clarify whether NudC's primary role is in RiBi or endocycle control.

The conclusion that NudC maintains rRNA levels is derived from salivary gland RNAi phenotypes with strong reductions in ITS1/ITS2 and 18S/28S signals (Figure 4B-4K) and reduced 28S by Northern (Figure 4L), plus corroboration in fat body cells (Figure S7). The authors verified knockdown using two independent RNAi lines for growth phenotypes and NudC::GFP reduction (Figure S2) and generated a UAS-FLAG::NudC transgene (Key Resources), but rRNA measurements were reported for only one RNAi line without rescue. Rescue of the rRNA phenotype by transgenic NudC re-expression, or replication of the rRNA decrease with a second, non-overlapping RNAi, would directly attribute the effect to NudC. In the absence of these standard validation controls, an off-target explanation remains plausible.

Minor comments

Fig. 2 I - Hoeschest should be Hoescht

Significance

The findings shown in this manuscript introduce a new player in endoreplication/ribosome biogenesis, a protein previously know as a dynein regulator. The strengths of the work lie on its novelty and thorough analysis of the cellular phenotypes induced by NudC depletion. However, its weaknesses are related to some claims not completely backed by the data, with some uncertainties related with a possible function of NudC in endoreplication.

This basic research work will be of interest to a broad cell and developmental biology community as they provide a novel cellular function of a known protein. It is of specific interest to the specialized field of polyploidy and ribosome biogenesis.

Field of expertise:

Drosophila, morphogenesis, tubulogenesis, cytoskeleton, DNA damage and repair.

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Referee #1

Evidence, reproducibility and clarity

Summary: This manuscript describes evidence for a role for the Nuclear distribution C dynein complex regulator (NudC) in ribosome biogenesis (RiBi) independent of its role in microtubule-associated dynein function.

Evidence: NudC was picked up in a screen for genes affecting ecdysteroid biosynthesis, a process that occurs in the prothoracic gland (PG; an endocrine organ). In the absence of ecdysone, larvae fail to pupate. Consistent with this finding, the authors find that prothoracic RNAi knockdown of NudC results in a failure in pupation and a decrease in total PG size. They also show defects in polytene chromosome architecture and a mild decrease in overall DNA content. They then turn to the salivary gland (SG) to further characterize the phenotypes associated with NudC knockdown. First, they show that an endogenously tagged version of NudC is abundant in the cytosol and has very weak nuclear staining in the region of the nucleolus (marked by the very low levels of DAPI staining). Knockdown of NudC using RNAi results in reduced NudC-GFP staining, a reduction in SG size, and a reduction in nuclear size. They also find that the SG polytene chromosomes are abnormal and that the production of a SG glue protein as measured by Sgs3-GFP levels and electron dense secretory granules is significantly reduced with NudC knockdown. Interestingly, they also observe the presence of abundant virus-like particles in the nucleus (these structures are thought to originate from retrotransposons and are an indicator of stress). Consistent with increased cellular stress, the authors show activation of JNK signalling. Ultrastructural analysis reveals an abnormally organized ER with an apparent loss of ER-associated ribosomes. They do see other electron dense structures in the cytosol, which they provide evidence (see below) of being P-bodies (structures associated with mRNA). They show that, consistent with a decrease in ribosomes, protein translation is reduced. This is supported by FISH experiments where they show significant decreases in ribosomal RNA (rRNA) transcript levels and decreased translation. Seeing the significant decreases in rRNA levels prompted them to look at overall changes in gene expression, where they discovered that both ribosomal protein gene expression as well as expression of other genes involved in ribosome biogenesis (RiBi) are upregulated with knockdown of NudC. They confirm the changes in mRNA for two genes by showing that levels of the corresponding proteins are also upregulated based on immunostaining of SG cells in which NudC is knocked down. Linking NudC function to a response to defects in RiBi, they shown that SG knockdown of several ribosomal biogenesis factors (RBFs) have similar chromosome structural defects and result in an increase in expression of ribosomal protein genes and of NudC itself. Finally, they show that knock down of genes encoding proteins linked to NudC function in microtubule dynamics do not have any of the same phenotypes as knockdown of NudC and RBFs. Altogether, their data support a moonlighting function for NudC in ribosome biogenesis. Moreover, defects in RiBi wherein ribosomal RNAs are decreased seem to result in compensatory changes where both RBFs and ribosomal protein genes are upregulated.

Major issues:

The title is a bit problematic since they haven't shown that NudC doesn't also affect normal mitotic cells - they only look at polyploid cells, but that doesn't mean normal mitotic cells are not also affected.

Also, the authors show that two different RNAi lines for NudC give the same defects - it would be good to know if the RNAi lines target the same or different sequences in the NudC transcripts. Alternatively, it would be equally good to show that trans-allelic combinations of NudC mutants have the same defects in the prothoracic glands and the salivary glands as the RNAi. Instead, they examine only overall body size, developmental delays and lethality in the trans-hetero allelic NudC mutants.

Results: Lines 261 - 266. Seeing electron dense structures in TEMs and seeing increased Me31B staining by confocal imaging in the cytoplasm is insufficient evidence that the electron dense structures are P-bodies. They could be the P-bodies but they could also be aggregated ribosomes; there is insufficient evidence to "confirm" that they are P-bodies - maybe just say "suggests".

It would be quite helpful to characterize the "5 blob" and "shortened polytene chromosome arm" defects shown in Figure 2 and Figure 6. Are these partially polytenized chromosomes or are large sections of the chromosomes missing or just underreplicated? What do the chromosomes look like if you lyse the nuclei, spread the chromosomes and stain with DAPI or Hoechst - this is a pretty standard practice and would reveal much more about the structure of the polytene chromosomes.

Minor points:

Abstract, lines 28 - 31. I think this gene has been identified before. The authors probably want to say they have discovered a role for this gene in RiBi.

Introduction, line 66. The protein is imported into the nucleus, where it localizes to the nucleolus - technically the protein is not imported into the nucleolus.

Introduction, line 70. To be comprehensive in the description of ribosome biogenesis, the authors may want to mention that the 40S and 60S subunits are then exported from the nucleus and form the 80S subunit in the cytoplasm during translation.

Introduction, line 98. May want to cite paper showing that Minute mutations turn out to be mutations in individual ribosomal protein genes.

Results, lines 285 to 298. In situs with multiple probes that detect all parts of both the pre-rRNA and processed rRNA indicate that all are down in the SG in NudC knockdowns, but that the 18S and 28S rRNAs are down the internal transcribed spacers go up - can the authors explain or hypothesize how this could happen?

Results, lines 292. Since they didn't knock down NudC in the fat body cells in this experiment, this comment seems irrelevant.

Discussion, line 468. I don't think the authors have provided evidence of DNA damage. With the experiments they have shown, the chromosomes look abnormal - not clear what is abnormal.

Figure 6A. Hoechst is misspelled.

Referee cross-commenting

I think the other reviewers have valid criticisms. I think among the most critical issues to sort out is (1) what is wrong with the chromosomes, (2) are diploid tissues also affected, (3) are the RIBI phenotypes a primary or secondary consequence of nudC loss. I'm not sure how easy it is to do ribosomal profiling on tissues dissected from larvae as the third reviewer is suggesting.

Significance

It is a novel discovery that a protein regulating microtubule dynamics is moonlighting, presumably in the nucleolus, to regulate rRNA synthesis or stabilization. A little information regarding mechanism of action would make this a much more exciting paper - how does it do it? Right now, it is unclear whether rRNA synthesis or maintenance is being regulated and there are no hypotheses regarding how this protein localizes to nucleoli and exactly what it is doing there. Is it regulating all RNA Pol I-dependent transcription? Is it involved in processing or stabilizing rRNAs? The description of the chromosomal defects also fall short of satisfying. As is, this paper probably of most interest to those who study ribosome biogenesis - an important topic, but without more mechanistic insight, not so interesting to a more general audience.

My expertise

I am an experienced Drosophila biologist who is familiar with the system and who fully understands all of the experiments presented in this manuscript and the relevance of the findings.

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Referee #1

Evidence, reproducibility and clarity

Summary: This manuscript describes evidence for a role for the Nuclear distribution C dynein complex regulator (NudC) in ribosome biogenesis (RiBi) independent of its role in microtubule-associated dynein function.

Evidence: NudC was picked up in a screen for genes affecting ecdysteroid biosynthesis, a process that occurs in the prothoracic gland (PG; an endocrine organ). In the absence of ecdysone, larvae fail to pupate. Consistent with this finding, the authors find that prothoracic RNAi knockdown of NudC results in a failure in pupation and a decrease in total PG size. They also show defects in polytene chromosome architecture and a mild decrease in overall DNA content. They then turn to the salivary gland (SG) to further characterize the phenotypes associated with NudC knockdown. First, they show that an endogenously tagged version of NudC is abundant in the cytosol and has very weak nuclear staining in the region of the nucleolus (marked by the very low levels of DAPI staining). Knockdown of NudC using RNAi results in reduced NudC-GFP staining, a reduction in SG size, and a reduction in nuclear size. They also find that the SG polytene chromosomes are abnormal and that the production of a SG glue protein as measured by Sgs3-GFP levels and electron dense secretory granules is significantly reduced with NudC knockdown. Interestingly, they also observe the presence of abundant virus-like particles in the nucleus (these structures are thought to originate from retrotransposons and are an indicator of stress). Consistent with increased cellular stress, the authors show activation of JNK signalling. Ultrastructural analysis reveals an abnormally organized ER with an apparent loss of ER-associated ribosomes. They do see other electron dense structures in the cytosol, which they provide evidence (see below) of being P-bodies (structures associated with mRNA). They show that, consistent with a decrease in ribosomes, protein translation is reduced. This is supported by FISH experiments where they show significant decreases in ribosomal RNA (rRNA) transcript levels and decreased translation. Seeing the significant decreases in rRNA levels prompted them to look at overall changes in gene expression, where they discovered that both ribosomal protein gene expression as well as expression of other genes involved in ribosome biogenesis (RiBi) are upregulated with knockdown of NudC. They confirm the changes in mRNA for two genes by showing that levels of the corresponding proteins are also upregulated based on immunostaining of SG cells in which NudC is knocked down. Linking NudC function to a response to defects in RiBi, they shown that SG knockdown of several ribosomal biogenesis factors (RBFs) have similar chromosome structural defects and result in an increase in expression of ribosomal protein genes and of NudC itself. Finally, they show that knock down of genes encoding proteins linked to NudC function in microtubule dynamics do not have any of the same phenotypes as knockdown of NudC and RBFs. Altogether, their data support a moonlighting function for NudC in ribosome biogenesis. Moreover, defects in RiBi wherein ribosomal RNAs are decreased seem to result in compensatory changes where both RBFs and ribosomal protein genes are upregulated.

Major issues:

The title is a bit problematic since they haven't shown that NudC doesn't also affect normal mitotic cells - they only look at polyploid cells, but that doesn't mean normal mitotic cells are not also affected.

Also, the authors show that two different RNAi lines for NudC give the same defects - it would be good to know if the RNAi lines target the same or different sequences in the NudC transcripts. Alternatively, it would be equally good to show that trans-allelic combinations of NudC mutants have the same defects in the prothoracic glands and the salivary glands as the RNAi. Instead, they examine only overall body size, developmental delays and lethality in the trans-hetero allelic NudC mutants.

Results: Lines 261 - 266. Seeing electron dense structures in TEMs and seeing increased Me31B staining by confocal imaging in the cytoplasm is insufficient evidence that the electron dense structures are P-bodies. They could be the P-bodies but they could also be aggregated ribosomes; there is insufficient evidence to "confirm" that they are P-bodies - maybe just say "suggests".

It would be quite helpful to characterize the "5 blob" and "shortened polytene chromosome arm" defects shown in Figure 2 and Figure 6. Are these partially polytenized chromosomes or are large sections of the chromosomes missing or just underreplicated? What do the chromosomes look like if you lyse the nuclei, spread the chromosomes and stain with DAPI or Hoechst - this is a pretty standard practice and would reveal much more about the structure of the polytene chromosomes.

Minor points:

Abstract, lines 28 - 31. I think this gene has been identified before. The authors probably want to say they have discovered a role for this gene in RiBi.

Introduction, line 66. The protein is imported into the nucleus, where it localizes to the nucleolus - technically the protein is not imported into the nucleolus.

Introduction, line 70. To be comprehensive in the description of ribosome biogenesis, the authors may want to mention that the 40S and 60S subunits are then exported from the nucleus and form the 80S subunit in the cytoplasm during translation.

Introduction, line 98. May want to cite paper showing that Minute mutations turn out to be mutations in individual ribosomal protein genes.

Results, lines 285 to 298. In situs with multiple probes that detect all parts of both the pre-rRNA and processed rRNA indicate that all are down in the SG in NudC knockdowns, but that the 18S and 28S rRNAs are down the internal transcribed spacers go up - can the authors explain or hypothesize how this could happen?

Results, lines 292. Since they didn't knock down NudC in the fat body cells in this experiment, this comment seems irrelevant.

Discussion, line 468. I don't think the authors have provided evidence of DNA damage. With the experiments they have shown, the chromosomes look abnormal - not clear what is abnormal.

Figure 6A. Hoechst is misspelled.

Referee cross-commenting

I think the other reviewers have valid criticisms. I think among the most critical issues to sort out is (1) what is wrong with the chromosomes, (2) are diploid tissues also affected, (3) are the RIBI phenotypes a primary or secondary consequence of nudC loss. I'm not sure how easy it is to do ribosomal profiling on tissues dissected from larvae as the third reviewer is suggesting.

Significance

It is a novel discovery that a protein regulating microtubule dynamics is moonlighting, presumably in the nucleolus, to regulate rRNA synthesis or stabilization. A little information regarding mechanism of action would make this a much more exciting paper - how does it do it? Right now, it is unclear whether rRNA synthesis or maintenance is being regulated and there are no hypotheses regarding how this protein localizes to nucleoli and exactly what it is doing there. Is it regulating all RNA Pol I-dependent transcription? Is it involved in processing or stabilizing rRNAs? The description of the chromosomal defects also fall short of satisfying. As is, this paper probably of most interest to those who study ribosome biogenesis - an important topic, but without more mechanistic insight, not so interesting to a more general audience.

My expertise

I am an experienced Drosophila biologist who is familiar with the system and who fully understands all of the experiments presented in this manuscript and the relevance of the findings.

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Reply to the reviewers

1. General Statements

*We thank the reviewers for their valuable comments. A common suggestion by all reviewers was that the manuscript would benefit from restructuring. Following their recommendation we have restructured this manuscript to improve its readability. *

2. Point-by-point description of the revisions

__Reviewer #1 (Evidence, reproducibility and clarity (Required)): __ The paper from Louka et al. studies the function of Cep104 during the development of Xenopus embryos. They perform overexpression and knock down experiments and address the consequences on neural tube closure, on ciliogenesis, and MT stability and on apical intercalation. There is a lot of data presented on a wide range of topics. While the data on MTs tracks reasonably well with other reports on Cep104, there are some concerns regarding the quality of some of the data and the interpretations based on the experimental results.

Specific Points: It is difficult to assess the effect on apical constriction with the data provided. Please show zoomed in higher mag images. Also this should be coupled with a quantification of cell number and proliferation rates, as it is possible that Cep104 mildly affects proliferation / cell division which could affect cell size. Overall this experiment is not really addressing apical constriction since there is no before and after data. Lots of things could affect apical surface area, most notably proliferation rates which one might predict would be affected by subtle changes to MT dynamics.

__Response: __Following the reviewer's recommendation we now show zoomed in higher magnification images to more clearly demonstrate the larger cell surface area in the morpholino injected neural plate compared to the control non-injected side in the same embryo. We agree with the reviewer that defects in cell proliferation could affect the cell size. If the effect of Cep104 on the cell surface area is caused by defects in cell proliferation, then we would expect this phenotype to persist in other tissues such as the ectoderm. However, we show that this phenotype is specific to the neural plate. On the other hand, if the cell surface area defect is caused by defects in apical constriction, we would expect this phenotype to be stage specific. Following the reviewer's recommendation, we compared the surface area of neuroectoderm cells before and after extensive apical constriction takes. The new data is shown in Figure S2. Our results show no difference in the surface area of neuroectoderm cells in control tracer injected and morpholino injected neuroepithelial cells at stage 13, before extensive apical constriction whereas significant differences are observed in stage 15 embryos during which cells undergo apical constriction. This data strengthens our conclusion that downregulation of Cep104 affects apical constriction.

"This defect was rescued with expression of exogenous human CEP104-GFP mRNA (300pg mRNA) (Figure 1D-E)." This was partially rescued as the control and the rescue are significantly different.

__Response: __We thank the reviewer for this important clarification. We edited the text to more clearly reflect our data.

I am unclear what is being depicted in Figure 1F and G. What is the intense red staining? Is that the blastopore? Which would imply that the stage of analysis is quite different between C and F which is concerning. The same stages should be used.

__Response: __This is an image of the anterior most region of a stage 15 embryo. Occasionally some embryos do display intense phalloidin staining at the neural plate. We replaced the image with a more clear one and moved this data to Figure S2C.

S1A has a boxed region as if there was going to be a zoomed in image, but there is not. It would be nice to see it zoomed in. While the localization is indeed at the base and tips of cilia the base looks too dispersed and big to be the basal body?

__Response: __Following the reviewer's recommendation we now show a zoomed in image of a primary cilium. The boxed area in figure S2A shows the cilium that was used to generate the fluorescence intensity profile plot shown in S2B. The Cep104 signal at the basal body is much stronger compared to the ciliary tip signal. Exposure that allows simultaneous detection of both the base and the tip signal results in overexposure of the signal at the base. This is consistent with observations in primary cilia in cell culture (please refer to Figure 4 in Frikstad et al. 2019 and Figure 3 in Yamazoe et al 2020).

In other systems the depletion of Cep104 decreases primary cilia length. While the authors claim that neural tube cilia are normal there is no quantification to support that and the provided image is hard to assess.

__Response: __Following the reviewer's recommendation we now show quantifications of the length of floor plate cilia (Figure S3C). Floor plate cilia are longer than the cilia found elsewhere in the neural tube. This inherent variability in the length of cilia will likely prevent the detection of small changes in the cilium length elicited by downregulation of Cep104. Therefore, we chose to examine the length of floor plate cilia only, in control and morpholino injected cells. Our results show that downregulation of Cep104 leads to the formation of shorter floor plate cilia which is in agreement with published data in other systems.

While the authors claim broad expression in humans and MO effects in cells without cilia, there is little data supporting the expression of Cep104 in the Xenopus cells being assayed (e.g. goblet cells).

__Response: __We agree with the reviewer that there is little evidence supporting the expression of Cep104 in Xenopus goblet cells. Cep104 is a very low abundance protein and thus very difficult to detect it at endogenous levels For example, Ryniawec et al. (2023) raised an antibody against Drosophila Cep104 that failed to detect the native (endogenous) protein via western blot or immunofluorescence, but successfully recognized the overexpressed (transgenic) Cep104. A proteomic study by Peshkin et al. 2019 showed that Cep104 levels remain relatively constant throughout Xenopus development suggesting that this protein is expressed ubiquitously. This data is shown in Figure 4 where we plot the relative expression levels of Cep104 along with two motile cilia specific genes: hydin and RSPH9.

The data in Figure 2 regarding the explants is difficult to understand and I think missing some key data. The text refers to the level of Gli increasing in the BF injected explants compared to uninjected explants, but the presentation of that is odd as the levels are normalized against uninjected rather than directly compared. And there are no stats for this key experiment. However, I think a bigger concern is the lack of information regarding the presence of cilia. While elongation and Sox2 expression are important they don't address if this tissue is similar to the neural tube in terms of cilia which is key to the interpretations.

__Response: __Following the reviewer's recommendation we changed the presentation of this data. GLI1 levels are now normalized to XBF2 injected explants. The results are the same, Gli1 levels are 25% lower in morphant XBF2 explants (ttest pWe understand the reviewer's concern regarding the presence of cilia in the explants. To our knowledge there are currently no reports on the presence of cilia in the neural ectoderm in Xenopus. We have made several attempts to determine if cilia are present in this tissue during neurulation. However, we have not been able to detect cilia based on immunofluorescence staining for acetylated tubulin and Arl13b in the neural ectoderm. We conclude from this experiment that downregulation of Cep104 negatively affects hedgehog signaling and it remains to be addressed whether this is due to defects in primary cilia.

The localization of Cep104 GFP in the epidermis and the neuroepithelium does not look similar as stated. Ones does not really see the punctate pattern in the neuroectoderm.

Response: We thank the reviewer for pointing this out. To more clearly present this data we now show a plot of the fluorescence profile of Cep104-GFP along cell-cell junctions to demonstrate the punctate localization in the neuroepithelium.

The experiments linking Cep104 to the tips of paused MTs is not particularly convincing. The depolymerization of MTs with nocodazole, will decrease all MTs as well as MT trafficking which could affect Cep104. Comparing this experiment with taxol treatment to stabilize MTs (and decrease dynamics) would be more convincing. Plus the image provided does not support the claim that the leftover EMTB is marked with Cep104.

__Response: __Following the reviewer's recommendation we have examined the effect of taxol on the density of Cep104 apical puncta. We injected embryos with CEP104-GFP and EMTB-scarlet and exposed them to 20 μm taxol and imaged them live at stage 38. Embryos non treated with taxol served as the control. As shown in Figure S4 treatment with taxol led to an increase in the density of Cep104 puncta. This further supports our conclusion that Cep104 localizes to the ends of stable or paused microtubules. We also revised Figure 5 to more clearly show that Cep104 remains associated with the ends of nocodazole resistant EMTB labeled microtubules.

The data in Figure 6 is very difficult to interpret / believe. The quantified effects on MTs are pretty subtle (which is fine...that is why you quantify), but the massive experimental variability questions the meaningfulness of those quantifications. In Fig 6B There are cells with lots of MTs right next to cells with no MTs and both have similar expression levels of Cep104. The staining just doesn't look consistent enough to accurately quantify. Also the effect of Nocodozole on MT stability is quite rapid, on the order of seconds to minutes, it is unclear what ON treatment with nocodazole would even be measuring since in that time there would be lots of secondary effects.

__Response: __We thank the reviewer for this comment. Some cells in the epidermis lack apical microtubules as the reviewer correctly points out. Cells without strong apical microtubule staining are seen in both control and morpholino injected cells. Here we quantified the number of control and morphant cells per embryo that lack apical microtubules (DMSO treated embryos). Our results show that similar numbers of control and morphant cells per embryo appear to lack apical microtubules. We think that the heterogeneity in tubulin signal is not an artifact of immunofluorescence staining since these cells are adjacent to cells with clear tubulin staining. Although the source of this variability is still unknown, the fact that an equal number of control and morphant cells show this phenotype suggests that this is unlikely to be linked to the injections or drug treatment. Those cells were excluded from the quantifications shown in Figures 6C and 6D It is possible that these cells are preparing to enter mitosis.

We think that the reviewer refers to the acute effects of nocodazole seen in cell cultures. However, in Xenopus tadpoles we didn't observe any effect on microtubules after short nocodazole treatment at low temperatures.

The authors propose that overexpressing Cep104 would lead to stabilized MTs which is a reasonable hypothesis, however, they test this in multiciliated cells that already have a ton of acetylated MTs. If their hypothesis is correct it should lead to an increase in acetylated tubulin in non multiciliated cells which don't have much to begin with. This would be a marked improvement as the side projection quantification seems a little suspect as the analysis requires a precises ROI that eliminates the strong cilia acetylation staining. While I believe that could be done, the image provided looks as if it might cut off some of the apical surface which highlights the challenge.

__Response: __Following the reviewer's recommendation, we examined the effect of Cep104 overexpression in non-MCCs on Xenopus epidermis. We show in Figure 7 that overexpression of Cep104 leads to a significant increase in the levels of acetylated tubulin in the cytoplasm of non-MCCs. We also show that overexpression of GFP alone did not have an effect on microtubule acetylation (Figure S5A). We moved the data on the cytoplasmic levels of acetylated microtubules in MCCs to figure S5B. We would like to clarify that the ROI to mark the cell body of MCCs was drawn right below the apical phalloidin signal to ensure that no signal derived from motile cilia will be included in the quantifications. A more detailed explanation of the quantification methods is included in this revised manuscript.

Minor: Overall the color choice of images does not conform to the color blind favorable options that are becoming standard in the field. Also to the extent possible the colors should be consistent (e.g. Fig 4 A Cep104-GFP is green but in B it is red).

__Response: __We thank the reviewer for this comment. We have changed the color choices in the figures to conform to the color blind.

The recent Xenopus Cep104 paper was referenced with two references, and the wording of those two sentences was redundant.

__Response: __We thank the reviewer for this comment. We edited the text accordingly.

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__Reviewer #2 (Evidence, reproducibility and clarity (Required)): __ This study by Louka et al., investigates the function of Cep104, a protein associated with Joubert syndrome, in Xenopus. Several aspects are studied at different scales. Loss of function of this protein suggests a role in neural tube closure, apical constriction, and HH signaling. Moving on in the study, the authors investigate the localization of Cep104 in the primary cilia of the neural tube before focusing on its localization in multiciliated cells. They then look at the consequences of loss of function on motile cilia and conclude that it plays a role in the length of the distal segment. They then show an association of Cep104 with cytoplasmic microtubules in non-multiciliated cells of the Xenopus epidermis. They then analyze the function of Cep104 on these microtubules and show that loss of Cep104 function increases the speed of EB1 comets. They then looked at the impact of loss of function on microtubule stability and finally the impact of gain of function. Finally, they returned to the multiciliated cells and described an intercalation defect that correlated with decreases in acetylated tubulin. I think that certain controls are missing and that the choice of illustrations should be reconsidered (better quality, appropriate zoom). In terms of form, the text is not easy to read and the manuscript would benefit from reformatting to highlight the logical links between the different experiences and avoid a catalog-like effect. I would advise the authors to revise their introduction to make it less disjointed and guide readers toward the questions addressed by the manuscript.

Response: We thank the reviewer for the constructive criticism. We have revised the introduction to make it easier to read.

Below are specific comments and remarks: Figure 1: Why the conclusion is a "delay" in neural tube closure? At what stage is this analyzed? Is there a recovery of NT closure at later stage? A: I would suggest to provide control picture of non-injected and tracer only injected embryos. B: Statistics are missing on the graph D: mention what was injected instead of "+ rescue". Close up picture would allow a better appreciation of the differences in surface area.

Response: We thank the reviewer for this comment. The image shown in Figure 1A is from late neurula embryos, stage 18. We conclude that it is a delay in neural tube closure because the neural tube does close and the embryos develop to tailbud stages. To demonstrate the delay in neural tube closure we now include a time lapse sequence of a neurula stage embryo injected with the morpholino unilaterally which shows that the morpholino injected side moves towards the midline slower compared to the control uninjected side (movie 1). We also included a representative image of the dorsal side of a tailbud embryo injected unilaterally with the CEP104 morpholino to show that the neural tube has closed and the embryos develop to tailbud stages (figure S1D).

Following the reviewer's recommendation, we also show images of embryos injected unilaterally with the tracer alone (Figure S2), we included the statistical analysis for graph 1D, revised image 1D to show that the embryo is injected with the morpholino and CEP104-GFP and provide close ups to allow for better appreciation of the differences in surface area.

Figure S1: To illustrate the claim that cilia are not affected, it would be good to show injection of tracer alone and compare to tracer + morpholino. Also, to provide a measure of the cilia size.

__Response: __Following the reviewer's recommendation we quantified the length of floor plate cilia in the neural tube of control and morpholino injected embryos. As explained in our response to a comment by reviewer 1, the floor plate cilia are longer than the cilia found elsewhere in the neural tube. This inherent variability in the length of cilia will likely prevent the detection of small changes in the cilium length elicited by downregulation of Cep104. Therefore, we chose to examine the length of floor plate cilia only in control and morpholino injected cells. Our results show that downregulation of Cep104 leads to the formation of shorter floor plate cilia which is in agreement with published data in other systems (Figure S3C).

Figure 2: Please provide pictures to illustrate graph D.

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__Response: __The graph in Figure 2D shows RT-qPCR results for CEP104 in BF2 and BF2 and morpholino injected explants as compared to non-injected explants. We do not have a working antibody that would allow us to show the downregulation at the protein level.

Figure 5: "Interestingly, most of the nocodazole-resistant stable microtubules were positive for Cep104 (Figure 5C, arrows). " The variation in density of Cep104-GFP signal is not visible on the pictures provided in C. I would suggest to show higher magnifications. Also, in the DMSO treated picture the Cep104GFP signal looks really different when compared to Cep104-GFP signal shown in B. Arrows should be reported on all channels. However, it not clear what we should see with this arrows. 5C: it seems that in nocodazole treated condition the Cep104-GFP is at the cilia base in MCCs which is different from the DMSO control condition. The basal body signal was not seen in the figure 3A which analyze the localization of Cep104-GFP in MCCs. Why not comment on this? Is it a phenotype on MCCs ?

Response: __Following the reviewer's recommendation, we now show higher magnifications of the images shown in Figure 5C. We removed the arrows as most reviewers found them confusing. To demonstrate the presence of Cep104 at the ends of nocodazole resistant EMTB labeled microtubules we show zoomed images and a representative fluorescence intensity profile plot. __Figure 5B shows an image of a non-MCC whereas Figure 5C shows a larger area on the tadpole epidermis which includes both MCCs and non-MCCs. We thank the reviewer for pointing out that the localization of Cep104 in 5C looks different from 3A. We do not think this is a phenotype on MCCs. In Figure 3A we imaged only the tips of cilia which is why it looks different from 5C in which we imaged the apical surface of the cells as well. We disagree with the reviewer regarding the comment '5C: it seems that in nocodazole treated condition the Cep104-GFP is at the cilia base in MCCs which is different from the DMSO control condition'. The basal body localization of Cep104 is shown in the DMSO image as well. We hope that it will be clear in this revised figure.

Figure 6: Intriguingly, morphant non-MCCs have significantly more mean β-tubulin signal compared to control non-MCCs in embryos treated with DMSO (Figure 6C). impossible to appreciate on the figures. Please specify on the figure what is considered as a morphant non-MCC versus a control non-MCC. The membrane-cherry positive cells (supposedly morphant? it has to be clarified show very heterogenous tubulin expression) If the point here is to show that microtubules are more sensitive to nocodazole in morphant cells as compared to control. I would suggest to show all conditions on a same graph. At least annotate more the graph for a self-explanatory figure (DMSO , Nocodazole).

__Response: __We agree with the reviewer that it impossible to appreciate the difference in β-tubulin signal between control and morphant non-MCCs. Based on the quantifications of mean β-tubulin fluorescence intensity there is 5% difference in the fluorescence intensity between the two groups. Statistical analysis using t-test shows that although very small, this difference is statistically significant which is why we mention it in the manuscript. We have removed this statement and data from the revised manuscript because this is a very subtle phenotype, and it is beyond the scope of this experiment.

Following the reviewer's recommendation, we clarify that mem-cherry positive cells contain the morpholino and mem-cherry negative cells are the control cells. We marked with a white asterisk the morphant non-MCCs. To address the heterogenous tubulin levels we provide quantifications which show that a similar number of control and morphant cells appear to lack microtubules. We think that the heterogeneity in tubulin signal is not an artifact of immunofluorescence staining since these cells are adjacent to cells with clear tubulin staining. Although the source of this variability is still unknown, the fact that an equal number of control and morphant cells show this phenotype suggests that this is unlikely to be linked to the injections or drug treatment. Those cells were excluded from the quantifications shown in figure 6. It is possible that these cells are preparing to enter mitosis. The reviewer is correct; the point of this experiment is to examine the effect of Cep104 downregulation on the sensitivity of microtubules to nocodazole. To more clearly present the results of this experiment we normalize the β-tubulin fluorescence Intensity in morphant cells to the one in control cells in the same embryo and we compare the normalized intensity in DMSO and nocodazole treated embryos.

Figure 7: Statistics are missing on Graph B

__ ____Response: __Following the reviewer's recommendation, we added the statistics on the graph.

Comment on the text: "Cep104 signal shows the characteristic two dot pattern in motile cilia (Figure 3A) that was also observed in a recent study using Xenopus Cep10465 and in the cilia of Tetrahymena50. This is in agreement with a recent study showing the characteristic two dot pattern for Xenopus Cep104 as well66 " ref 65 and 66b are the same (Hong et al., preprint)

__ ____Response: __We thank the reviewer for pointing this out. We edited the text to avoid repetition and corrected the references.

"This data suggests that downregulation of CEP104 affects the stability of cytoplasmic microtubules." I would suggest a more precise conclusion by stating how is it affected? More stable? Less stable? Important for the follow-up demonstration.

__ _Response: _We edited the text according to the reviewer's recommendation to precisely conclude that downregulation of Cep104 makes cytoplasmic microtubules less stable. __

Movies: Please annotate properly movie 2 and 3 so the reader can know what he/she is looking.

---

__Response: __Following the reviewer's comment, we revised the movie annotations to help the reader know what they are looking.

---

__Reviewer #3 (Evidence, reproducibility and clarity (Required)): __ The manuscript entitled "Ciliary and non-ciliary functions of Cep104 in Xenopus" by Louka et al. investigate roles for the centriole and cilia tip protein Cep104 in Xenopus embryos. The authors show that depletion of Cep104 prevents neural tube closure due to inefficient apical constriction of neural cells and defective hedgehog signaling. Cep104 depletion also resulted in structural and functional ciliary defects in multi-ciliated cells. Surprisingly, the authors discover a role for Cep104 in stabilizing cytoplasmic microtubules in non-ciliated and multi-ciliated cells. Reduced microtubule stability in Cep104-depleted cells correlated with reduced apical intercalation of multi-ciliated cells in the epidermis.

Overall, I find this manuscript difficult to understand because the experiments lack description of the findings within a normal developmental context and the findings are not developed into a cohesive narrative. I do find the study to be potentially impactful as the authors characterize Cep104 in a novel system (previous peer-reviewed studies have investigated Cep104 in human cell lines, Drosophila, zebrafish, Tetrahymena, and Chlamydomonas) with disease-relevant biology (neural development); however, mechanistic links are not properly explored. Over the course of their investigation, the authors made the novel finding that Cep104 controls the dynamics of cytoplasmic microtubules. However, this is not directly tested and potential pleiotropic effects of the developmental defects caused by Cep104 depletion confound the results.

Response: We thank the reviewer for their comments. We tried to address this by restructuring the manuscript to describe the results in more detail within a normal developmental context.

Major Critiques: The developmental context of experiments is not made clear. The authors use different tissues at varying developmental stages to perform experiments. However, these findings are not explored in depth and, therefore, the manuscript does not advance our understanding of Cep104's role in any of the processes explored.

__ ____Response:__ We thank the reviewer for their comment. We took advantage of different tissues during Xenopus development to understand the cellular and molecular function of this protein in vivo. In this manuscript we show that Cep104 is involved in neural tube closure likely through its effect on apical constriction. Our data show that Cep104 is important for the stability of cytoplasmic microtubules and this is further demonstrated through its role in apical intercalation of multiciliated cells, a process known to depend on stable microtubules. Although our data do not advance our understanding on developmental processes such as apical constriction and MCC apical intercalation, they do improve our understanding of how Cep104 impacts cytoplasmic microtubules which has not been addressed in vivo yet.

While the potential role of Cep104 in cytoplasmic microtubule regulation is intriguing, the experiments in the manuscript do not directly test this function. Because Cep104 depletion appears to have a profound developmental effect, it is difficult to interpret changes to EB1 velocity as directly attributed to Cep104 function. Additionally, the only evidence for Cep104 localization occurs in cells overexpressing human Cep104. The authors must directly visualize endogenous Cep104 to conclude microtubule or membrane localization, which they can also use to demonstrate Cep104 depletion in the morpholino experiments. Additionally, the assertion that Cep104 is binding plus-ends of cytoplasmic microtubules is not experimentally supported.

__ ____Response: __Unfortunately, we cannot directly visualize endogenous Cep104 because there is no commercially available antibody that works in Xenopus. Cep104 is a very low abundance protein, and this is highlighted in the study by John M.Ryniawec et al. 2023, where they generated an antibody against the drosophila Cep104 which detected the GFP-tagged DmCep104 but failed to detect the endogenous protein. Given that the ciliary and basal body signal of Cep104 represents the cumulative signal from nine microtubules, one can appreciate the difficulty of observing the Cep104 signal in individual microtubules. None of the commercially available Cep104 antibodies that we have tested worked against the Xenopus protein in immunofluorescence or western blot experiments. We agree with the reviewer that we do not experimentally test the binding of Cep104 to the microtubule plus-end. This has been demonstrated by others. In Jiang et al. 2012 it was showed that GFP-Cep104 co-immunoprecipitates with GST-EB1 but not with GST-EB1 that lacks the tail which contains the SxIP binging motif. In Yamazoe et al. 2020 study it was shown that exogenous Cep104 co-immunoprecipitates with exogenous EB1 and Cep104 with mutated SxIP motif (SKNN) fails to co-immunoprecipitate with EB1. This shows that Cep104 interacts with EB1 through its SxIP motif. In addition, overexpression of Cep104 recruits Cep97 to microtubule tips suggesting that it acts as a +TIP protein. A recent study by Saunders et al. 2025 showed that in in vitro microtubule reconstitution assays, Cep104 could not autonomously bind the microtubule plus-end at low concentrations but in the presence of EB3 it could bind the microtubule plus-end and block microtubule polymerization at the same low concentration. This shows that Cep104 interacts with EB3, localizes to the microtubule plus-end and affects its dynamics in vitro. We added this information in the manuscript to more clearly show that the interaction of Cep104 and EB proteins is well documented. We anticipate that this interaction will hold true in all cell types where the two proteins are co-expressed.

Additional Critiques: Figure S1. I only see the emergence of a shorter product after Cep104 depletion. Should PCR using Exon5-7 still work in successful knockdown? If not, then it is unclear what was quantified to determine Cep104 depletion as morpholino bands appear no different than control.

__ ____Response: __We thank the reviewer for this comment. PCR using exon5-7 will not work when splice blocking by the morpholino takes place. This is a knockdown approach and the efficiency of the morpholino is about 90%. Upon completion of the RT-qPCR cycle the samples were analyzed by gel electrophoresis to demonstrate that 1) alternative splicing took place (see two products with exon 3-7 primers) and 2) the presence of a single product for all primer sets used.

Figure 1A. Is this an example of an open or closed NTC? Show data used to determine the statement "no difference during convergent extension".

__ ____Response: __This is an example of an embryo that was unilatterally injected with the morpholino. The left side is the control non-injected side and the right side is the morpholino injected. We added this information on the figure to make it more self-explanatory. In Figure 2 the elongation of the BF2 injected explants is due to convergent extension. The statement "no difference during convergent extension" was removed from the revised manuscript.

Figure S2C. What does "Does not effect formation of cilia" mean? Does Cep104 depletion does not effect number, length, etc? Show quantitation used to determine this?

__ ____Response:__ Following the reviewer's recommendation, we quantified the length of floor plate cilia in control and morpholino injected embryos. As mentioned in our response to reviewer 1 and 2, floor plate cilia are longer than the cilia found elsewhere in the neural tube. This inherent variability in the length of cilia will likely prevent the detection of small changes in the cilium length elicited by downregulation of Cep104. Therefore, we chose to examine the length of floor plate cilia only, in control and morpholino injected cells. Our results show that downregulation of Cep104 leads to the formation of shorter floor plate cilia which is in agreement with published data in other systems.

Figure 5B. Along with strong Cep104 localization to membranes, there also appears to be strong EMTB localization. Is this also present in beta-tubulin immunostaining? Are these localizing to a cortical population of microtubules or to the membrane?

__ ____Response: __We thank the reviewer for their comment. The Cep104 puncta at the cell periphery, are reduced/lost upon nocodazole treatment thus we conclude that Cep104 localizes to microtubules and not the cell membrane (Figure 5C, zoomed images). Of course, we cannot exclude the possibility that microtubules are required to target CEP104 to the plasma membrane. We edited the text to clearly state this conclusion.

Figure 6C and 6D. These two panels have the same labels. The authors should denote that 6D is in nocodazole-treated explants.

__ ____Response:__ We thank the reviewer for this comment. We edited this figure to more clearly present the results of this experiment: We normalized the β -tubulin levels in morphant cells to that of control cells in the same embryo (mosaic morphant embryos were used in this experiment). The graph shows the mean normalized β -tubulin levels per embryo treated with DMSO or nocodazole.

Figure 7. What are Cep104 levels at stage 18-19?

__ ____Response: __Following the reviewer's comment we now show the Cep104 protein expression levels during Xenopus development as reported on Xenbase (Figure 4). Cep104 is expressed at low levels from gastrulation to tailbud stages (Figure 4D).

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Referee #3

Evidence, reproducibility and clarity

The manuscript entitled "Ciliary and non-ciliary functions of Cep104 in Xenopus" by Louka et al. investigate roles for the centriole and cilia tip protein Cep104 in Xenopus embryos. The authors show that depletion of Cep104 prevents neural tube closure due to inefficient apical constriction of neural cells and defective hedgehog signaling. Cep104 depletion also resulted in structural and functional ciliary defects in multi-ciliated cells. Surprisingly, the authors discover a role for Cep104 in stabilizing cytoplasmic microtubules in non-ciliated and multi-ciliated cells. Reduced microtubule stability in Cep104-depleted cells correlated with reduced apical intercalation of multi-ciliated cells in the epidermis.

Overall, I find this manuscript difficult to understand because the experiments lack description of the findings within a normal developmental context and the findings are not developed into a cohesive narrative. I do find the study to be potentially impactful as the authors characterize Cep104 in a novel system (previous peer-reviewed studies have investigated Cep104 in human cell lines, Drosophila, zebrafish, Tetrahymena, and Chlamydomonas) with disease-relevant biology (neural development); however, mechanistic links are not properly explored. Over the course of their investigation, the authors made the novel finding that Cep104 controls the dynamics of cytoplasmic microtubules. However, this is not directly tested and potential pleiotropic effects of the developmental defects caused by Cep104 depletion confound the results.

Major Critiques:

The developmental context of experiments is not made clear. The authors use different tissues at varying developmental stages to perform experiments. However, these findings are not explored in depth and, therefore, the manuscript does not advance our understanding of Cep104's role in any of the processes explored.

While the potential role of Cep104 in cytoplasmic microtubule regulation is intriguing, the experiments in the manuscript do not directly test this function. Because Cep104 depletion appears to have a profound developmental effect, it is difficult to interpret changes to EB1 velocity as directly attributed to Cep104 function. Additionally, the only evidence for Cep104 localization occurs in cells overexpressing human Cep104. The authors must directly visualize endogenous Cep104 to conclude microtubule or membrane localization, which they can also use to demonstrate Cep104 depletion in the morpholino experiments. Additionally, the assertion that Cep104 is binding plus-ends of cytoplasmic microtubules is not experimentally supported.

Additional Critiques:

Figure S1. I only see the emergence of a shorter product after Cep104 depletion. Should PCR using Exon5-7 still work in successful knockdown? If not, then it is unclear what was quantified to determine Cep104 depletion as morpholino bands appear no different than control.

Figure 1A. Is this an example of an open or closed NTC? Show data used to determine the statement "no difference during convergent extension".

Figure S2C. What does "Does not effect formation of cilia" mean? Does Cep104 depletion does not effect number, length, etc? Show quantitation used to determine this?

Figure 5B. Along with strong Cep104 localization to membranes, there also appears to be strong EMTB localization. Is this also present in beta-tubulin immunostaining? Are these localizing to a cortical population of microtubules or to the membrane?

Figure 6C and 6D. These two panels have the same labels. The authors should denote that 6D is in nocodazole-treated explants.

Figure 7. What are Cep104 levels at stage 18-19?

Significance

Overall, I find this manuscript difficult to understand because the experiments lack description of the findings within a normal developmental context and the findings are not developed into a cohesive narrative. I do find the study to be potentially impactful as the authors characterize Cep104 in a novel system (previous peer-reviewed studies have investigated Cep104 in human cell lines, Drosophila, zebrafish, Tetrahymena, and Chlamydomonas) with disease-relevant biology (neural development); however, mechanistic links are not properly explored. Over the course of their investigation, the authors made the novel finding that Cep104 controls the dynamics of cytoplasmic microtubules. However, this is not directly tested and potential pleiotropic effects of the developmental defects caused by Cep104 depletion confound the results.

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Referee #2

Evidence, reproducibility and clarity

This study by Louka et al., investigates the function of Cep104, a protein associated with Joubert syndrome, in Xenopus. Several aspects are studied at different scales. Loss of function of this protein suggests a role in neural tube closure, apical constriction, and HH signaling. Moving on in the study, the authors investigate the localization of Cep104 in the primary cilia of the neural tube before focusing on its localization in multiciliated cells. They then look at the consequences of loss of function on motile cilia and conclude that it plays a role in the length of the distal segment. They then show an association of Cep104 with cytoplasmic microtubules in non-multiciliated cells of the Xenopus epidermis. They then analyze the function of Cep104 on these microtubules and show that loss of Cep104 function increases the speed of EB1 comets. They then looked at the impact of loss of function on microtubule stability and finally the impact of gain of function. Finally, they returned to the multiciliated cells and described an intercalation defect that correlated with decreases in acetylated tubulin. I think that certain controls are missing and that the choice of illustrations should be reconsidered (better quality, appropriate zoom). In terms of form, the text is not easy to read and the manuscript would benefit from reformatting to highlight the logical links between the different experiences and avoid a catalog-like effect. I would advise the authors to revise their introduction to make it less disjointed and guide readers toward the questions addressed by the manuscript.

Below are specific comments and remarks:

Figure 1:

Why the conclusion is a "delay" in neural tube closure? At what stage is this analyzed? Is there a recovery of NT closure at later stage? A: I would suggest to provide control picture of non-injected and tracer only injected embryos. B: Statistics are missing on the graph D: mention what was injected instead of "+ rescue". Close up picture would allow a better appreciation of the differences in surface area.

Figure S1:

To illustrate the claim that cilia are not affected, it would be good to show injection of tracer alone and compare to tracer + morpholino. Also, to provide a measure of the cilia size.

Figure 2:

Please provide pictures to illustrate graph D.

Figure 5:

"Interestingly, most of the nocodazole-resistant stable microtubules were positive for Cep104 (Figure 5C, arrows). " - The variation in density of Cep104-GFP signal is not visible on the pictures provided in C. I would suggest to show higher magnifications. Also, in the DMSO treated picture the Cep104GFP signal looks really different when compared to Cep104-GFP signal shown in B. Arrows should be reported on all channels. However, it not clear what we should see with this arrows. 5C: it seems that in nocodazole treated condition the Cep104-GFP is at the cilia base in MCCs which is different from the DMSO control condition. The basal body signal was not seen in the figure 3A which analyze the localization of Cep104-GFP in MCCs. Why not comment on this? Is it a phenotype on MCCs ? Figure 6: Intriguingly, morphant non-MCCs have significantly more mean β-tubulin signal compared to control non-MCCs in embryos treated with DMSO (Figure 6C). - impossible to appreciate on the figures. Please specify on the figure what is considered as a morphant non-MCC versus a control non-MCC. The membrane-cherry positive cells (supposedly morphant? it has to be clarified show very heterogenous tubulin expression)

If the point here is to show that microtubules are more sensitive to nocodazole in morphant cells as compared to control. I would suggest to show all conditions on a same graph. At least annotate more the grap for a self-explanatory figure (DMSO , Nocodazole). Figure 7: Statistics are missing on Graph B Comment on the text: "Cep104 signal shows the characteristic two dot pattern in motile cilia (Figure 3A) that was also observed in a recent study using Xenopus Cep10465 and in the cilia of Tetrahymena50. This is in agreement with a recent study showing the characteristic two dot pattern for Xenopus Cep104 as well66 " - ref 65 and 66b are the same (Hong et al., preprint)

"This data suggests that downregulation of CEP104 affects the stability of cytoplasmic microtubules." - I would suggest a more precise conclusion by stating how is it affected? More stable? Less stable? Important for the follow-up demonstration.

Movies:

Please annotate properly movie 2 and 3 so the reader can know what he/she is looking.

Referees cross-commenting

Similar feeling that reviews are consistent

Significance

This study investigates the role of the proprotein Cep104 in Xenopus. Cep104 is a protein associated with Joubert syndrome, whose role in primary cilia has been extensively documented. While its localization at the tip of motile cilia has also been reported, this study provides functional evidence for the role of Cep104 in motile cilia. In addition, the study looks at the role of Cep104 on non-cilial microtubules, which is the original aspect of the paper and may ultimately lead to a better understanding of Joubert syndrome. However, I believe that the evidence provided (controls, illustrations) needs to be improved. This paper will be of interest to a specialized audience with an interest in proteins associated with cilia and microtubules.

I am a cell biologist specialized in the study of multiciliated cells using advanced imaging methods and Xenopus and mice as models. I believe my expertise was a perfect match for this manuscript.

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Referee #1

Evidence, reproducibility and clarity

The paper from Louka et al. studies the function of Cep104 during the development of Xenopus embryos. They perform overexpression and knock down experiments and address the consequences on neural tube closure, on ciliogenesis, and MT stability and on apical intercalation. There is a lot of data presented on a wide range of topics. While the data on MTs tracks reasonably well with other reports on Cep104, there are some concerns regarding the quality of some of the data and the interpretations based on the experimental results.

Specific Points:

It is difficult to assess the effect on apical constriction with the data provided. Please show zoomed in higher mag images. Also this should be coupled with a quantification of cell number and proliferation rates, as it is possible that Cep104 mildly affects proliferation / cell division which could affect cell size. Overall this experiment is not really addressing apical constriction since there is no before and after data. Lots of things could affect apical surface area, most notably proliferation rates which one might predict would be affected by subtle changes to MT dynamics.

"This defect was rescued with expression of exogenous human CEP104-GFP mRNA (300pg mRNA) (Figure 1D-E)." This was partially rescued as the control and the rescue are significantly different.

I am unclear what is being depicted in Figure 1F and G. What is the intense red staining? Is that the blastopore? Which would imply that the stage of analysis is quite different between C and F which is concerning. The same stages should be used.

S1A has a boxed region as if there was going to be a zoomed in image, but there is not. It would be nice to see it zoomed in. While the localization is indeed at the base and tips of cilia the base looks too dispersed and big to be the basal body?

In other systems the depletion of Cep104 decreases primary cilia length. While the authors claim that neural tube cilia are normal there is no quantification to support that and the provided image is hard to assess.

While the authors claim broad expression in humans and MO effects in cells without cilia, there is little data supporting the expression of Cep104 in the Xenopus cells being assayed (e.g. goblet cells).

The data in Figure 2 regarding the explants is difficult to understand and I think missing some key data. The text refers to the level of Gli increasing in the BF injected explants compared to uninjected explants, but the presentation of that is odd as the levels are normalized against uninjected rather than directly compared. And there are no stats for this key experiment. However, I think a bigger concern is the lack of information regarding the presence of cilia. While elongation and Sox2 expression are important they don't address if this tissue is similar to the neural tube in terms of cilia which is key to the interpretations.

The localization of Cep104 GFP in the epidermis and the neuroepithelium does not look similar as stated. Ones does not really see the punctate pattern in the neuroectoderm.

The experiments linking Cep104 to the tips of paused MTs is not particularly convincing. The depolymerization of MTs with nocodazole, will decrease all MTs as well as MT trafficking which could affect Cep104. Comparing this experiment with taxol treatment to stabilize MTs (and decrease dynamics) would be more convincing. Plus the image provided does not support the claim that the leftover EMTB is marked with Cep104.

The data in Figure 6 is very difficult to interpret / believe. The quantified effects on MTs are pretty subtle (which is fine...that is why you quantify), but the massive experimental variability questions the meaningfulness of those quantifications. In Fig 6B There are cells with lots of MTs right next to cells with no MTs and both have similar expression levels of Cep104. The staining just doesn't look consistent enough to accurately quantify. Also the effect of Nocodozole on MT stability is quite rapid, on the order of seconds to minutes, it is unclear what ON treatment with nocodazole would even be measuring since in that time there would be lots of secondary effects.

The authors propose that overexpressing Cep104 would lead to stabilized MTs which is a reasonable hypothesis, however, they test this in multiciliated cells that already have a ton of acetylated MTs. If their hypothesis is correct it should lead to an increase in acetylated tubulin in non multiciliated cells which don't have much to begin with. This would be a marked improvement as the side projection quantification seems a little suspect as the analysis requires a precises ROI that eliminates the strong cilia acetylation staining. While I believe that could be done, the image provided looks as if it might cut off some of the apical surface which highlights the challenge.

Minor:

Overall the color choice of images does not conform to the color blind favorable options that are becoming standard in the field. Also to the extent possible the colors should be consistent (e.g. Fig 4 A Cep104-GFP is green but in B it is red).

The recent Xenopus Cep104 paper was referenced with two references, and the wording of those two sentences was redundant.

Referees cross-commenting

I feel that all three reviews are pretty consistent and I do not have any issues with the other reviews.

Significance

Strengths. Cep104 appears to be a hot topic right now as there are several papers in bioRXiv. I suspect that this led to a bit of a rushed submission. The other papers focus mostly on understanding the mechanisms of the ciliary roles of Cep104 which is well established. In other systems the broad phenotypes associated with Cep104 depletion are assumed to be through loss of cilia mediated HH signaling. This paper proposes a number of non ciliary roles for Cep104 which given its broad distribution could be relevant. If true these findings would add considerably to the field. Given that MTs do lots of things other than make cilia it would not be too surprising for Cep104 to have MT specific phenotypes as proposed here.

Weaknesses. The quality of much of the data makes it difficult to assess the claims of broad importance. Key experiments critical to the interpretation of the data are lacking.

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Reply to the reviewers

Authors’ reply (____Ono et al)

Review Commons Refereed Preprint #RC-2025-03137

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

Ono et al addressed how condensin II and cohesin work to define chromosome territories (CT) in human cells. They used FISH to assess the status of CT. They found that condensin II depletion leads to lengthwise elongation of G1 chromosomes, while double depletion of condensin II and cohesin leads to CT overlap and morphological defects. Although the requirement of condensin II in shortening G1 chromosomes was already shown by Hoencamp et al 2021, the cooperation between condensin II and cohesin in CT regulation is a new finding. They also demonstrated that cohesin and condensin II are involved in G2 chromosome regulation on a smaller and larger scale, respectively. Though such roles in cohesin might be predictable from its roles in organizing TADs, it is a new finding that the two work on a different scale on G2 chromosomes. Overall, this is technically solid work, which reports new findings about how condensin II and cohesin cooperate in organizing G1 and G2 chromosomes.

We greatly appreciate the reviewer’s supportive comments. The reviewer has accurately recognized our new findings concerning the collaborative roles of condensin II and cohesin in establishing and maintaining interphase chromosome territories.

Major point:

They propose a functional 'handover' from condensin II to cohesin, for the organization of CTs at the M-to-G1 transition. However, the 'handover', i.e. difference in timing of executing their functions, was not experimentally substantiated. Ideally, they can deplete condensin II and cohesin at different times to prove the 'handover'. However, this would require the use of two different degron tags and go beyond the revision of this manuscript. At least, based on the literature, the authors should discuss why they think condensin II and cohesin should work at different timings in the CT organization.

We take this comment seriously, especially because Reviewer #2 also expressed the same concern.　

First of all, we must admit that the basic information underlying the “handover” idea was insufficiently explained in the original manuscript. Let us make it clear below:

• Condensin II bound to chromosomes and is enriched along their axes from anaphase through telophase (Ono et al., 2004; Hirota et al., 2004; Walther et al., 2018).
• In early G1, condensin II is diffusely distributed within the nucleus and does not bind tightly to chromatin, as shown by detergent extraction experiments (Ono et al., 2013).
• Cohesin starts binding to chromatin when the cell nucleus reassembles (i.e., during the cytokinesis stage shown in Fig. 1B), apparently replacing condensins I and II (Brunner et al., 2025).
• Condensin II progressively rebinds to chromatin from S through G2 phase (Ono et al., 2013). The cell cycle-dependent changes in chromosome-bound condensin II and cohesin summarized above are illustrated in Fig. 1A. We now realize that Fig. 1B in the original manuscript was inconsistent with Fig. 1A, creating unnecessary confusion, and we sincerely apologize for this. The fluorescence images shown in the original Fig. 1B were captured without detergent extraction prior to fixation, giving the misleading impression that condensin II remained bound to chromatin from cytokinesis through early G1. This was not our intention. To clarify this, we have repeated the experiment in the presence of detergent extraction and replaced the original Fig. 1B with a revised panel. Figs. 1A and 1B are now more consistent with each other. Accordingly, we have modified the correspsonding sentences as follows:

Although condensin II remains nuclear throughout interphase, its chromatin binding is weak in G1 and becomes robust from S phase through G2 (Ono et al., 2013). Cohesin, in contrast, replaces condensin II in early G1 (Fig. 1 B)(Abramo et al., 2019; Brunner et al., 2025), and establishes topologically associating domains (TADs) in the G1 nucleus (Schwarzer et al., 2017; Wutz et al., 2017)*. *

While there is a loose consensus in the field that condensin II is replaced by cohesin during the M-to-G1 transition, it remains controversial whether there is a short window during which neither condensin II nor cohesin binds to chromatin (Abramo et al., 2019), or whether there is a stage in which the two SMC protein complexes “co-occupy” chromatin (Brunner et al., 2025). Our images shown in the revised Fig. 1B cannot clearly distinguish between these two possibilities.

From a functional point of view, the results of our depletion experiments are more readily explained by the latter possibility. If this is the case, the “interplay” or “cooperation” rather than the “handover” may be a more appropriate term to describe the functional collaboration between condensin II and cohesin during the M-to-G1 transition. For this reason, we have avoided the use of the word “handover” in the revised manuscript. It should be emphasized, however, that given their distinct chromosome-binding kinetics, the cooperation of the two SMC complexes during the M-to-G1 transition is qualitatively different from that observed in G2. Therefore, the central conclusion of the present study remains unchanged.

For example, a sentence in Abstract has been changed as follows:

a functional interplay between condensin II and cohesin during the mitosis-to-G1 transition is critical for establishing chromosome territories (CTs) in the newly assembling nucleus.

While the reviewer suggested one experiment, it is clearly beyond the scope of the current study. It should also be noted that even if such a cell line were available, the proposed application of sequential depletion to cells progressing from mitosis to G1 phase would be technically challenging and unlikely to produce results that could be interpreted with confidence.

Other points:

Figure 2E: It seems that the chromosome length without IAA is shorter in Rad21-aid cells than H2-aid cells or H2-aid Rad21-aid cells. How can this be interpreted? This comment is well taken. A related comment was made by Reviewer #3 (Major comment #2). Given the substantial genetic manipulations applied to establish multiple cell lines used in the present study, it is, strictly speaking, not straightforward to compare the -IAA controls between different cell lines. Such variations are most prominently observed in Fig. 2E, although they can also be observed to lesser extent in other experiments (e.g., Fig. 3E). This issue is inherently associated with all studies using genetically manipulated cell lines and therefore cannot be completely avoided. For this reason, we focus on the differences between -IAA and +IAA within each cell line, rather than comparing the -IAA conditions across different cell lines. In this sense, a sentence in the original manuscript (lines 178-180) was misleading. In the revised manuscript, we have modified the corresponding and subsequent sentence as follows:

Although cohesin depletion had a marginal effect on the distance between the two site-specific probes (Fig.2, C and E), double depletion did not result in a significant change (Fig.2, D and E), consistent with the partial restoration of centromere dispersion (Fig. 1G).

• *

In addition, we have added a section entitled “Limitations of the study” at the end of the Discussion to address technical issues that are inevitably associated with the current approach.

Figure 3: Regarding the CT morphology, could they explain further the difference between 'elongated' and 'cloud-like (expanded)'? Is it possible to quantify the frequency of these morphologies? In the original manuscript, we provided data that quantitatively distinguished between the “elongated” and “cloud-like” phenotypes. Specifically, Fig. 2E shows that the distance between two specific loci (Cen 12 and 12q15) is increased in the elongated phenotype but not in the cloud-like phenotype. In addition, the cloud-like morphology was clearly deviated from circularity, as indicated by the circularity index (Fig. 3F). However, because circularity can also decrease in rod-shaped chromosomes, these datasets alone may not be sufficiently convincing, as the reviewer pointed out. We have now included an additional parameter, the aspect ratio, defined as the ratio of an object’s major axis to its minor axis (new Fig. 3F). While this intuitive parameter was altered upon condensin II depletion and double depletion, again, we acknowledge that it is not sufficient to convincingly distinguish between the elongated and cloud-like phenotypes proposed in the original manuscript. For these reasons, in the revised manuscript, we have toned down our statements regarding the differences in CT morphology between the two conditions. Nonetheless, together with the data from Figs. 1 and 2, it is that the Rabl configuration observed upon condensin II depletion is further exacerbated in the absence of cohesin. Accordingly, we have modified the main text and the cartoon (Fig 3H) to more accurately depict the observations summarized above.

Figure 5: How did they assign C, P and D3 for two chromosomes? The assignment seems obvious in some cases, but not in other cases (e.g. in the image of H2-AID#2 +IAA, two D3s can be connected to two Ps in the other way). They may have avoided line crossing between two C-P-D3 assignments, but can this be justified when the CT might be disorganized e.g. by condensin II depletion? This comment is well taken. As the reviewer suspected, we avoided line crossing between two sets of assignments. Whenever there was ambiguity, such images were excluded from the analysis. Because most chromosome territories derived from two homologous chromosomes are well separated even under the depleted conditions as shown in Fig. 6C, we did not encounter major difficulties in making assignments based on the criteria described above. We therefore remain confident that our conclusion is valid.

That said, we acknowledge that our assignments of the FISH images may not be entirely objective. We have added this point to the “Limitations of the study” section at the end of the Discussion.

Figure 6F: The mean is not indicated on the right-hand side graph, in contrast to other similar graphs. Is this an error? We apologize for having caused this confusion. First, we would like to clarify that the right panel of Fig. 6F should be interpreted together with the left panel, unlike the seemingly similar plots shown in Figs. 6G and 6H. In the left panel of Fig. 6F, the percentages of CTs that contact the nucleolus are shown in grey, whereas those that do not are shown in white. All CTs classified in the “non-contact” population (white) have a value of zero in the right panel, represented by the bars at 0 (i.e., each bar corresponds to a collection of dots having a zero value). In contrast, each CT in the “contact” population (grey) has a unique contact ratio value in the right panel. Because the right panel consists of two distinct groups, we reasoned that placing mean or median bars would not be appropriate. This was why no mean or median bars were shown in in the tight panel (The same is true for Fig. S5 A and B).

That said, for the reviewer’s reference, we have placed median bars in the right panel (see below). In the six cases of H2#2 (-/+IAA), Rad21#2 (-/+IAA), Double#2 (-IAA), and Double#3 (-IAA), the median bars are located at zero (note that in these cases the mean bars [black] completely overlap with the “bars” derived from the data points [blue and magenta]). In the two cases of Double#2 (+IAA) and Double#3 (+IAA), they are placed at values of ~0.15. Statistically significant differences between -IAA and +IAA are observed only in Double#2 and Double#3, as indicated by the P-value shown on the top of the panel. Thus, we are confident in our conclusion that CTs undergo severe deformation in the absence of both condensin II and cohesin.

Figure S1A: The two FACS profiles for Double-AID #3 Release-2 may be mixed up between -IAA and +IAA. The review is right. This inadvertent error has been corrected.

The method section explains that 'circularity' shows 'how closely the shape of an object approximates a perfect circle (with a value of 1 indicating a perfect circle), calculated from the segmented regions'. It would be helpful to provide further methodological details about it. We have added further explanations regarding the circularity in Materials and Methods together with a citation (two added sentences are underlined below):

To analyze the morphology of nuclei, CTs, and nucleoli, we measured “circularity,” a morphological index that quantifies how closely the shape of an object approximates a perfect circle (value =1). Circularity was defined as 4π x Area/Perimeter2, where both the area and perimeter of each segmented object were obtained using ImageJ. This index ranges from 0 to 1, with values closer to 1 representing more circular objects and lower values correspond to elongated or irregular shapes (Chen et al, 2017).

Chen, B., Y. Wang, S. Berretta and O. Ghita. 2017. Poly Aryl Ether Ketones (PAEKs) and carbon-reinforced PAEK powders for laser sintering. J Mater Sci 52:6004-6019.

Reviewer #1 (Significance (Required)):

Ono et al addressed how condensin II and cohesin work to define chromosome territories (CT) in human cells. They used FISH to assess the status of CT. They found that condensin II depletion leads to lengthwise elongation of G1 chromosomes, while double depletion of condensin II and cohesin leads to CT overlap and morphological defects. Although the requirement of condensin II in shortening G1 chromosomes was already shown by Hoencamp et al 2021, the cooperation between condensin II and cohesin in CT regulation is a new finding. They also demonstrated that cohesin and condensin II are involved in G2 chromosome regulation on a smaller and larger scale, respectively. Though such roles in cohesin might be predictable from its roles in organizing TADs, it is a new finding that the two work on a different scale on G2 chromosomes. Overall, this is technically solid work, which reports new findings about how condensin II and cohesin cooperate in organizing G1 and G2 chromosomes.

See our reply above.

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

Summary:

Ono et al use a variety of imaging and genetic (AID) depletion approaches to examine the roles of condensin II and cohesin in the reformation of interphase genome architecture in human HCT16 cells. Consistent with previous literature, they find that condensin II is required for CENP-A dispersion in late mitosis/early G1. Using in situ FISH at the centromere/q arm of chromosome 12 they then establish that condensin II removal causes lengthwise elongation of chromosomes that, interestingly, can be suppressed by cohesin removal. To better understand changes in whole-chromosome morphology, they then use whole chromosome painting to examine chromosomes 18 and 19. In the absence of condensin II, cells effectively fail to reorganise their chromosomes from rod-like structures into spherical chromosome territories (which may explain why CENP-A dispersion is suppressed). Cohesin is not required for spherical CT formation, suggesting condensin II is the major initial driver of interphase genome structure. Double depletion results in complete disorganisation of chromatin, leading the authors to conclude that a typical cell cycle requires orderly 'handover' from the mitotic to interphase genome organising machinery. The authors then move on to G2 phase, where they use a variety of different FISH probes to assess alterations in chromosome structure at different scales. They thereby establish that perturbation of cohesin or condensin II influences local and longer range chromosome structure, respectively. The effects of condensin II depletion become apparent at a genomic distance of 20 Mb, but are negligible either below or above. The authors repeat the G1 depletion experiment in G2 and now find that condensin II and cohesin are individually dispensable for CT organisation, but that dual depletion causes CT collapse. This rather implies that there is cooperation rather than handover per se. Overall this study is a broadly informative multiscale investigation of the roles of SMC complexes in organising the genome of postmitotic cells, and solidifies a potential relationship between condensin II and cohesin in coordinating interphase genome structure. The deeper investigation of the roles of condensin II in establishing chromosome territories and intermediate range chromosome structure in particular is a valuable and important contribution, especially given our incomplete understanding of what functions this complex performs during interphase.

We sincerely appreciate the reviewer’s supportive comments. The reviewer has correctly acknowledged both the current gaps in our understanding of the role of condensin II in interphase chromosome organization and our new findings on the collaborative roles of condensin II and cohesin in establishing and maintaining interphase chromosome territories.

Major comments:

In general the claims and conclusions of the manuscript are well supported by multiscale FISH labelling. An important absent control is western blotting to confirm protein depletion levels. Currently only fluorescence is used as a readout for the efficiency of the AID depletion, and we know from prior literature that even small residual quantities of SMC complexes are quite effective in organising chromatin. I would consider a western blot a fairly straightforward and important technical control.

Let me explain why we used immunofluorescence measurements to evaluate the efficiency of depletion. In our current protocol for synchronizing at the M-to-G1 transition, ~60% of control and H2-depleted cells, and ~30% of Rad21-depleted and co-depleted cells, are successfully synchronized in G1 phase. The apparently lower synchronization efficiency in the latter two groups is attributable to the well-documented mitotic delay caused by cohesin depletion. From these synchronized populations, early G1 cells were selected based on their characteristic morphologies (see the legend of Fig. 1C). In this way, we analyzed an early G1 cell population that had completed mitosis without chromosome segregation defects. We acknowledge that this represents a technically challenging aspect of M-to-G1 synchronization in HCT116 cells, whose synchronization efficiency is limited compared with that of HeLa cells. Nevertheless, this approach constitutes the most practical strategy currently available. Hence, immunofluorescence provides the only feasible means to evaluate depletion efficiency under these conditions.

Although immunoblotting can, in principle, be applied to G2-arrested cell populations, we do not believe that information obtained from such experiments would affect the main conclusions of the current study. Please note that we carefully designed and performed all experiments with appropriate controls: H2 depletion, RAD21 depletion, and double depletion, with outcomes confirmed using independent cell lines (Double-AID#2 and Double-AID#3) whenever deemed necessary.

We fully acknowledge the technical limitations associated with the AID-mediated depletion techniques, which are now described in the section entitled “Limitations of the study” at the end of the Discussion. Nevertheless, we emphasize that these limitations do not compromise the validity of our findings.

I find the point on handover as a mechanism for maintaining CT architecture somewhat ambiguous, because the authors find that the dependence simply switches from condensin II to both condensin II and cohesin, between G1 and G2. To me this implies augmented cooperation rather than handover. I have two further suggestions, both of which I would strongly recommend but would consider desirable but 'optional' according to review commons guidelines.

First of all, we would like to clarify a possible misunderstanding regarding the phrase “handover as a mechanism for maintaining CT architecture somewhat ambiguous”. In the original manuscript, we proposed handover as a mechanism for establishing G1 chromosome territories, not for maintaining CTs.

That said, we take this comment very seriously, especially because Reviewer #1 also expressed the same concern. Please see our reply to Reviewer #1 (Major point).

In brief, we agree with the reviewer that the word “handover” may not be appropriate to describe the functional relationship between condensin II and cohesin during the M-to-G1 transition. In the revised manuscript, we have avoided the use of the word “handover”, replacing it with “interplay”. It should be emphasized, however, that given their distinct chromosome-binding kinetics, the cooperation of the two SMC complexes during the M-to-G1 transition is qualitatively different from that observed in G2. Therefore, the central conclusion of the present study remains unchanged.

For example, a sentence in Abstract has been changed as follows:

a functional interplay between condensin II and cohesin during the mitosis-to-G1 transition is critical for establishing chromosome territories (CTs) in the newly assembling nucleus.

Firstly, the depletions are performed at different stages of the cell cycle but have different outcomes. The authors suggest this is because handover is already complete, but an alternative possibility is that the phenotype is masked by other changes in chromosome structure (e.g. duplication/catenation). I would be very curious to see, for example, how the outcome of this experiment would change if the authors were to repeat the depletions in the presence of a topoisomerase II inhibitor.

The reviewer’s suggestion here is somewhat vague, and it is unclear to us what rationale underlies the proposed experiment or what meaningful outcomes could be anticipated. Does the reviewer suggest that we perform topo II inhibitor experiments both during the M-to-G1 transition and in G2 phase, and then compare the outcomes between the two conditions?

For the M-to-G1 transition, Hildebrand et at (2024) have already reported such experiments. They used a topo II inhibitor to provided evidence that mitotic chromatids are self-entangled and that the removal of these mitotic entanglements is required to establish a normal interphase nucleus. Our own preliminary experiments (not presented in the current manuscript) showed that ICRF treatment of cells undergoing the M-to-G1 transition did not affect post-mitotic centromere dispersion. The same treatment also had little effect on the suppression of centromere dispersion observed in condensin II-depleted cells.

Under G2-arrested condition, because chromosome territories are largely individualized, we would expect topo II inhibition to affect only the extent of sister catenation, which is not the focus of our current study. We anticipate that inhibiting topo II in G2 would have only a marginal, if any, effect on the maintenance of chromosome territories detectable by our current FISH approaches.

In any case, we consider the suggested experiment to be beyond the scope of the present manuscript, which focuses on the collaborative roles of condensin II and cohesin as revealed by multi-scale FISH analyses.

Secondly, if the author's claim of handover is correct then one (not exclusive) possibility is that there is a relationship between condensin II and cohesin loading onto chromatin. There does seem to be a modest co-dependence (e.g. fig S4 and S7), could the authors comment on this?

First of all, we wish to point out the reviewer’s confusion between the G2 experiments and the M-to-G1 experiments. Figs. S4 and S7 concern experiments using G2-arrested cells, not M-to-G1 cells in which a possible handover mechanism is discussed. Based on Fig. 1, in which the extent of depletion in M-to-G1 cells was tested, no evidence of “co-dependence” between H2 depletion and RAD21 depletion was observed.

That said, as the reviewer correctly points out, we acknowledge the presence of marginal yet statistically significant reductions in the RAD21 signal upon H2 depletion (and vice versa) in G2-arrested cells (Figs. S4 and S7).

Another control experiment here would be to treat fully WT cells with IAA and test whether non-AID labelled H2 or RAD21 dip in intensity. If they do not, then perhaps there's a causal relationship between condensin II and cohesin levels?

According to the reviewer’s suggestion, we tested whether IAA treatment causes an unintentional decreases in the H2 or RAD21 signals in G2-arrested cells, and found that it is not the case (see the attached figure below).

Thus, these data indicate that there is a modest functional interdependence between condensin II and cohesin in G2-arrested cells. For instance, condensin II depletion may modestly destabilize chromatin-bound cohesin (and vice versa). However, we note that these effects are minor and do not affect the overall conclusions of the study. In the revised manuscript, we have described these potentially interesting observations briefly as a note in the corresponding figure legends (Fig. S4).

I recognise this is something considered in Brunner et al 2025 (JCB), but in their case they depleted SMC4 (so all condensins are lost or at least dismantled). Might bear further investigation.

Methods:

Data and methods are described in reasonable detail, and a decent number of replicates/statistical analyses have been. Documentation of the cell lines used could be improved. The actual cell line is not mentioned once in the manuscript. Although it is referenced, I'd recommend including the identity of the cell line (HCT116) in the main text when the cells are introduced and also in the relevant supplementary tables. Will make it easier for readers to contextualise the findings.

We apologize for the omission of important information regarding the parental cell line used in the current study. The information has been added to Materials and Methods as well as the resource table.

Minor comments:

Overall the manuscript is well-written and well presented. In the introduction it is suggested that no experiment has established a causal relationship between human condensin II and chromosome territories, but this is not correct, Hoencamp et al 2021 (cell) observed loss of CTs after condensin II depletion. Although that manuscript did not investigate it in as much detail as the present study, the fundamental relationship was previously established, so I would encourage the authors to revise this statement.

We are somewhat puzzled by this comment. In the original manuscript, we explicitly cited Hoencamp et al (2021) in support of the following sentences:

• *

(Lines 78-83 in the original manuscript)

*Moreover, high-throughput chromosome conformation capture (Hi-C) analysis revealed that, under such conditions, chromosomes retain a parallel arrangement of their arms, reminiscent of the so-called Rabl configuration (Hoencamp et al., 2021). These findings indicate that the loss or impairment of condensin II during mitosis results in defects in post-mitotic chromosome organization. *

• *

That said, to make the sentences even more precise, we have made the following revision in the manuscript.

• *

(Lines 78- 82 in the revised manuscript)

*Moreover, high-throughput chromosome conformation capture (Hi-C) analysis revealed that, under such conditions, chromosomes retain a parallel arrangement of their arms, reminiscent of the so-called Rabl configuration (Hoencamp et al., 2021). These findings,together with cytological analyses of centromere distributions, indicate that the loss or impairment of condensin II during mitosis results in defects in post-mitotic chromosome organization. *

• *

The following statement was intended to explain our current understanding of the maintenance of chromosome territories. Because Hoencamp et al (2021) did not address the maintenance of CTs, we have kept this sentence unchanged.

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(Lines 100-102 in the original manuscript)

Despite these findings, there is currently no evidence that either condensin II, cohesin, or their combined action contributes to the maintenance of CT morphology in mammalian interphase cells (Cremer et al., 2020).

• *

• *

Reviewer #2 (Significance (Required)):

General assessment:

Strengths: the multiscale investigation of genome architecture at different stages of interphase allow the authors to present convincing and well-analysed data that provide meaningful insight into local and global chromosome organisation across different scales.

Limitations:

As suggested in major comments.

Advance:

Although the role of condensin II in generating chromosome territories, and the roles of cohesin in interphase genome architecture are established, the interplay of the complexes and the stage specific roles of condensin II have not been investigated in human cells to the level presented here. This study provides meaningful new insight in particular into the role of condensin II in global genome organisation during interphase, which is much less well understood compared to its participation in mitosis.

Audience:

Will contribute meaningfully and be of interest to the general community of researchers investigating genome organisation and function at all stages of the cell cycle. Primary audience will be cell biologists, geneticists and structural biochemists. Importance of genome organisation in cell/organismal biology is such that within this grouping it will probably be of general interest.

My expertise is in genome organization by SMCs and chromosome segregation.

We appreciate the reviewer’s supportive comments. As the reviewer fully acknowledges, this study is the first systematic survey of the collaborative role of condensin II and cohesin in establishing and maintaining interphase chromosome territories. In particular, multi-scale FISH analyses have enabled us to clarify how the two SMC protein complexes contribute to the maintenance of G2 chromosome territories through their actions at different genomic scales. As the reviewer notes, we believe that the current study will appeal to a broad readership in cell and chromosome biology. The limitations of the current study mentioned by the reviewer are addressed in our reply above.

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

Summary:

The manuscript “Condensin II collaborates with cohesin to establish and maintain interphase chromosome territories" investigates how condensin II and cohesin contribute to chromosome organization during the M-to-G1 transition and in G2 phase using published auxin-inducible degron (AID) cell lines which render the respective protein complexes nonfunctional after auxin addition. In this study, a novel degron cell line was established that enables the simultaneous depletion of both protein complexes, thereby facilitating the investigation of synergistic effects between the two SMC proteins. The chromosome architecture is studied using fluorescence in situ hybridization (FISH) and light microscopy. The authors reproduce a number of already published data and also show that double depletion causes during the M-to-G1 transition defects on chromosome territories, producing expanded, irregular shapes that obscure condensin II-specific phenotypes. Findings in G2 cells point to a new role of condensin II for chromosome conformation at a scale of ~20Mb. Although individual depletion has minimal effects on large-scale CT morphology in G2, combined loss of both complexes produces marked structural abnormalities, including irregular crescent-shaped CTs displaced toward the nucleolus and increased nucleolus-CT contact. The authors propose that condensin II and cohesin act sequentially and complementarily to ensure proper post-mitotic CT formation and maintain chromosome architecture across genomic scales.

We greatly appreciate the reviewer’s supportive comments. The reviewer has accurately recognized our new findings concerning the collaborative roles of condensin II and cohesin in the establishment and maintenance of interphase chromosome territories.

Concenrs about statistics:

• The authors provide the information on how many cells are analyzed but not the number of independent experiments. My concern is that there might variations in synchronization of the cell population and in the subsequent preparation (FISH) affecting the final result. We appreciate the reviewer’s important comment regarding the biological reproducibility of our experiments. As the reviewer correctly points out, variations in cell-cycle synchronization and FISH sample preparation can occur across experiments. To address this concern, we repeated the key experiments supporting our main conclusions (Figs. 3 and 6) two additional times, resulting in three independent biological replicas in total. All replicate experiments reproduced the major observations from the original analyses. These results further substantiated our original conclusion, despite the inevitable variability arising from cell synchronization or sample preparation in this type of experiments. In the revised manuscript, we have now explicitly indicated the number of biological replicates in the corresponding figures.

The analyses of chromosome-arm conformation shown in Fig. 5 were already performed in three independent rounds of experiments, as noted in the original submission. In addition, similar results were already obtained in other analyses reported in the manuscript. For example, centromere dispersion was quantified using an alternative centromere detection method (related to Fig. 1), and distances between specific chromosomal sites were measured using different locus-specific probes (related to Figs. 2 and 4). In both cases, the results were consistent with those presented in the manuscript.

• Statistically the authors analyze the effect of cells with induced degron vs. vehicle control (non-induced). However, the biologically relevant question is whether the data differ between cell lines when the degron system is induced. This is not tested here (cf. major concern 2 and 3). See our reply to major concerns 2 and 3.

• Some Journal ask for blinded analysis of the data which might make sense here as manual steps are involved in the data analysis (e.g. line 626 / 627the convex hull of the signals was manually delineated, line 635 / 636 Chromosome segmentation in FISH images was performed using individual thresholding). However personally I have no doubts on the correctness of the work. We thank the reviewer for pointing out that some steps in our data analysis were performed manually, such as delineating the convex hull of signals and segmenting chromosomes in FISH and IF images using individual thresholds. These manual steps were necessary because signal intensities vary among cells and chromosomes, making fully automated segmentation unreliable. To ensure objectivity, we confirmed that the results were consistent across two independently established double-depletion cell lines, which produced essentially identical findings. In addition, we repeated the key experiments underpinning our main conclusions (Figs. 3 and 6) two additional times, and the results were fully consistent with the original analyses. Therefore, we are confident that our current data analysis approach does not compromise the validity of our conclusions. Finally, we appreciate the reviewer’s kind remark that there is no doubt regarding the correctness of our work.

Major concerns:

• Degron induction appears to delay in Rad21-AID#1 and Double-AID#1 cells the transition from M to G1, as shown in Fig. S1. After auxin treatment, more cells exhibit a G2 phenotype than in an untreated population. What are the implications of this for the interpretation of the experiments? In our protocol shown in Fig. 1C, cells were released into mitosis after G2 arrest, and IAA was added 30 min after release. It is well established that cohesin depletion causes a prometaphase delay due to spindle checkpoint activation (e.g., Vass et al, 2003, Curr Biol; Toyoda and Yanagida, 2006, MBoC; Peters et al, 2008, Genes Dev), which explains why cells with 4C DNA content accumulated, as judged by FACS (Fig. S1). The same was true for doubly depleted cells. However, a fraction of cells that escaped this delay progressed through mitosis and enter the G1 phase of the next cell cycle. We selected these early G1 cells and used them for down-stream analyses. This experimental procedure was explicitly described in the legends of Fig. 1C and Fig. S1A as follows:

(Lines 934-937; Legend of Fig. 1C)

From the synchronized populations, early G1cells were selected based on their characteristic morphologies (i.e., pairs of small post-mitotic cells) and subjected to downstream analyses. Based on the measured nuclear sizes (Fig. S2 G), we confirmed that early G1 cells were appropriately selected.

(Lines 1114-1119; Legend of Fig. S1A)

In this protocol, ~60% of control and H2-depleted cells, and ~30% of Rad21-depleted and co-depleted cells, were successfully synchronized in G1 phase. The apparently lower synchronization efficiency in the latter two groups is attributable to the well documented mitotic delay caused by cohesin depletion (Hauf et al., 2005; Haarhuis et al., 2013; Perea-Resa et al., 2020). From these synchronized populations, early G1 cells were selected based on their characteristic morphologies (see the legend of Fig. 1 C).

• *

Thus, using this protocol, we analyzed an early G1 cell population that had completed mitosis without chromosome segregation defects. We acknowledge that this represents a technically challenging aspect of synchronizing cell-cycle progression from M to G1 in HCT116 cells, whose synchronization efficiency is limited compared with that of HeLa cells. Nevertheless, this approach constitutes the most practical strategy currently available.

• Line 178 "In contrast, cohesin depletion had a smaller effect on the distance between the two site-specific probes compared to condensin II depletion (Fig. 2, C and E)." The data in Fig. 2 E show both a significant effect of H2 and a significant effect of RAD21 depletion. Whether the absolute difference in effect size between the two conditions is truly relevant is difficult to determine, as the distribution of the respective control groups also appears to be different. This comment is well taken. Reviewer #1 has made a comment on the same issue. See our reply to Reviewer #1 (Other points, Figure 2E).

In brief, in the current study, we should focus on the differences between -IAA and +IAA within each cell line, rather than comparing the -IAA conditions across different cell lines. In this sense, a sentence in the original manuscript (lines 178-180) was misleading. In the revised manuscript, we have modified the corresponding and subsequent sentence as follows:

Although cohesin depletion had a marginal effect on the distance between the two site-specific probes (Fig.2, C and E), double depletion did not result in a significant change (Fig.2, D and E), consistent with the partial restoration of centromere dispersion (Fig. 1G).

• In Figures 3, S3 and related text in the manuscript I cannot follow the authors' argumentation, as H2 depletion alone leads to a significant increase in the CT area (Chr. 18, Chr. 19, Chr. 15). Similar to Fig. 2, the authors argue about the different magnitude of the effect (H2 depletion vs double depletion). Here, too, appropriate statistical tests or more suitable parameters describing the effect should be used. I also cannot fully follow the argumentation regarding chromosome elongation, as double depletion in Chr. 18 and Chr. 19 also leads to a significantly reduced circularity. Therefore, the schematic drawing Fig. 3 H (double depletion) seems very suggestive to me. This comment is related to the comment above (Major comment #2). See our reply to Reviewer #1 (Other points, Figure 2E).

It should be noted that, in Figure 3 (unlike in Figure 2), we did not compare the different magnitudes of the effect observed between H2 depletion and double depletion. Thus, the reviewer’s comment that “Similar to Fig. 2, the authors argue about the different magnitude of the effect (H2 depletion vs double depletion) ” does not accurately reflected our description.

Moreover, while the distance between two specific loci (Fig. 2E) and CT circularity (Fig. 3G) are intuitively related, they represent distinct parameters. Thus, it is not unexpected that double depletion resulted in apparently different outcomes for the two measurements. Thus, the reviewer’s counter-argument is not strictly applicable here.

That said, we agree with the reviewer that our descriptions here need to be clarified.

The differences between H2 depletion and double depletion are two-fold: (1) centromere dispersion is suppressed upon H2 depletion, but not upon double depletion (Fig 1G); (2) the distance between Cen 12 and 12q15 increased upon H2 depletion, but not upon double depletion (Fig 2E).

We have decided to remove the “homologous pair overlap” panel (formerly Fig. 3E) from the revised manuscript. Accordingly, the corresponding sentence has been deleted from the main text. Instead, we have added a new panel of “aspect ratio”, defined as the ratio of the major to the minor axis (new Fig. 3F). While this intuitive parameter was altered upon condensin II depletion and double depletion, again, we acknowledge that it is not sufficient to convincingly distinguish between the elongated and cloud-like phenotypes proposed in the original manuscript. For these reasons, in the revised manuscript, we have toned down our statements regarding the differences in CT morphology between the two conditions. Nonetheless, together with the data from Figs. 1 and 2, it is clear that the Rabl configuration observed upon condensin II depletion is further exacerbated in the absence of cohesin. Accordingly, we have modified the main text and the cartoon (Fig 3H) to more accurately depict the observations summarized above.

• 5 and accompanying text. I agree with the authors that this is a significant and very interesting effect. However, I believe the sharp bends is in most cases an artifact caused by the maximum intensity projection. I tried to illustrate this effect in two photographs: Reviewer Fig. 1, side view, and Reviewer Fig. 2, same situation top view (https://cloud.bio.lmu.de/index.php/s/77npeEK84towzJZ). As I said, in my opinion, there is a significant and important effect; the authors should simply adjust the description. This comment is well taken. We appreciate the reviewer’s effort to help clarify our original observations. We have therefore added a new section entitled “Limitations of the study” to explicitly describe the constrains of our current approach. That said, as the reviewer also acknowledges, our observations remain valid because all experiments were performed with appropriate controls.

Minor concerns:

• I would like to suggest proactively discussing possible artifacts that may arise from the harsh conditions during FISH sample preparation. We fully agree with the reviewer’s concerns. For FISH sample preparation, we used relatively harsh conditions, including (1) fixation under a hypotonic condition (0.3x PBS), (2) HCl treatment, and (3) a denaturation step. We recognize that these procedures inevitably affect the preservation of the original structure; however, they are unavoidable in the standard FISH protocol. We also acknowledge that our analyses were limited to 2D structures based on projected images, rather than full 3D reconstructions. These technical limitations are now explicitly described in a new section entitled “Limitations of the study”, and the technical details are provided in Materials and Methods.

• It would be helpful if the authors could provide the original data (microscopic image stacks) for download. We thank the reviewer for this suggestion and understand that providing the original image stacks could be of interest to readers. We agree that if the nuclei were perfectly spherical, as is the case for example in lymphocytes, 3D image stacks would contain much more information than 2D projections. However, as is typical for adherent cultured cells, including the HCT116-derived cells used in this study, the nuclei are flattened due to cell adhesion to the culture dish, with a thickness of only about one-tenth of the nuclear diameter (10–20 μm). Considering also the inevitable loss of structural preservation during FISH sample preparation, we were concerned that presenting 3D images might confuse rather than clarify. We therefore believe that representing the data as 2D projections, while explicitly acknowledging the technical limitations, provides the clearest and most interpretable presentation of our results. These limitations are now described in a new section of the manuscript.

• The authors use a blind deconvolution algorithm to improve image quality. It might be helpful to test other methods for this purpose (optional). We thank the reviewer for this valuable suggestion and fully agree that it is a valid point. We recognize that alternative image enhancement methods can offer advantages, particularly for smaller structures or when multiple probes are analyzed simultaneously. In our study, however, the focus was on detecting whole chromosome territories (CTs) and specific chromosomal loci, which can be visualized clearly with our current FISH protocol combined with blind deconvolution. We therefore believe that the image quality we obtained is sufficient to support the conclusions of this manuscript.

Reviewer #3 (Significance (Required)):

Advance:

Ono et al. addresses the important question on how the complex pattern of chromatin is reestablished after mitosis and maintained during interphase. In addition to affinity interactions (1,2), it is known that cohesin plays an important role in the formation and maintenance of chromosome organization interphase (3). However, current knowledge does not explain all known phenomena. Even with complete loss of cohesin, TAD-like structures can be recognized at the single-cell level (4), and higher structures such as chromosome territories are also retained (5). The function of condensin II during mitosis is another important factor that affects chromosome architecture in the following G1 phase (6). Although condensin II is present in the cell nucleus throughout interphase, very little is known about the role of this protein in this phase of the cell cycle. This is where the present publication comes in, with a new double degron cell line in which essential subunits of cohesin AND condensin can be degraded in a targeted manner. I find the data from the experiments in the G2 phase most interesting, as they suggest a previously unknown involvement of condensin II in the maintenance of larger chromatin structures such as chromosome territories.

The experiments regarding the M-G1 transition are less interesting to me, as it is known that condensin II deficiency in mitosis leads to elongated chromosomes (Rabl configuration)(6), and therefore the double degradation of condensin II and cohesin describes the effects of cohesin on an artificially disturbed chromosome structure.

For further clarification, we provide below a table summarizing previous studies relevant to the present work. We wish to emphasize three novel aspects of the present study. First, newly established cell lines designed for double depletion enabled us to address questions that had remained inaccessible in earlier studies. Second, to our knowledge, no study has previously reported condensin II depletion, cohesin depletion and double depletion in G2-arrested cells. Third, the present study represents the first systematic comparison of two different stages of the cell cycle using multiscale FISH under distinct depletion conditions. Although the M-to-G1 part of the present study partially overlaps with previous work, it serves as an important prelude to the subsequent investigations. We are confident that the reviewer will also acknowledge this point.

cell cycle

cond II depletion

cohesin depletion

double depletion

M-to-G1

Hoencamp et al (2021); Abramo et al (2019); Brunner et al (2025);

this study

Schwarzer et al (2017);

Wutz et al (2017);

this study

this study

G2

this study

this study

this study

Hoencamp et al (2021): Hi-C and imaging (CENP-A distribution)

Abramo et al (2019): Hi-C and imaging

Brunner et al (2025): mostly imaging (chromatin tracing)

Schwarzer et al (2017); Wutz et al (2017): Hi-C

this study: imaging (multi-scale FISH)

General limitations:

(1) Single cell imaging of chromatin structure typically shows only minor effects which are often obscured by the high (biological) variability. This holds also true for the current manuscript (cf. major concern 2 and 3).

See our reply above.

(2) A common concern are artefacts introduced by the harsh conditions of conventional FISH protocols (7). The authors use a method in which the cells are completely dehydrated, which probably leads to shrinking artifacts. However, differences between samples stained using the same FISH protocol are most likely due to experimental variation and not an artefact (cf. minor concern 1).

See our reply above.

• The anisotropic optical resolution (x-, y- vs. z-) of widefield microscopy (and most other light microscopic techniques) might lead to misinterpretation of the imaged 3D structures. This seems to be the cases in the current study (cf. major concern 4). See our reply above.

• In the present study, the cell cycle was synchronized. This requires the use of inhibitors such as the CDK1 inhibitor RO-3306. However, CDK1 has many very different functions (8), so unexpected effects on the experiments cannot be ruled out. The current approaches involving FISH inevitably require cell cycle synchronization. We believe that the use of the CDK1 inhibitor RO-3306 to arrest the cell cycle at G2 is a reasonable choice, although we cannot rule out unexpected effects arising from the use of the drug. This issue has now been addressed in the new section entitled “Limitations of the study”.

Audience:

The spatial arrangement of genomic elements in the nucleus and their (temporal) dynamics are of high general relevance, as they are important for answering fundamental questions, for example, in epigenetics or tumor biology (9,10). The manuscript from Ono et al. addresses specific questions, so its intended readership is more likely to be specialists in the field.

We are confident that, given the increasing interest in the 3D genome and its role in regulating diverse biological functions, the current manuscript will attract the broad readership of leading journals in cell biology.

About the reviewer:

By training I'm a biologist with strong background in fluorescence microscopy and fluorescence in situ hybridization. In recent years, I have been involved in research on the 3D organization of the cell nucleus, chromatin organization, and promoter-enhancer interactions.

We greatly appreciate the reviewer’s constructive comments on both the technical strengths and limitations of our fluorescence imaging approaches, which have been very helpful in revising the manuscript. As mentioned above, we have decided to add a special paragraph entitled “Limitations of the study” at the end of the Discussion section to discuss these issues.

All questions regarding the statistics of angularly distributed data are beyond my expertise. The authors do not correct their statistical analyses for "multiple testing". Whether this is necessary, I cannot judge.

We thank the reviewer for raising this important point. In our study, the primary comparisons were made between -IAA and +IAA conditions within the same cell line. Accordingly, the figures report P-values for these pairwise comparisons.

For the distance measurements, statistical evaluations were performed in PRISM using ANOVA (Kruskal–Wallis test), and the P-values shown in the figures are based on these analyses (Fig. 1, G and H; Fig. 2 E; Fig. 3 F and G; Fig. 4 F; Fig. 6 F [right]–H; Fig. S2 B and G; Fig. S3 D and H; Fig. S5 A [right] and B [right]; Fig. S8 B). While the manuscript focuses on pairwise comparisons between -IAA and +IAA conditions within the same cell line, we also considered potential differences across cell lines as part of the same ANOVA framework, thereby ensuring that multiple testing was properly addressed. Because cell line differences are not the focus of the present study, the corresponding results are not shown.

For the angular distribution analyses, we compared -IAA and +IAA conditions within the same cell line using the Mardia–Watson–Wheeler test; these analyses do not involve multiple testing (circular scatter plots; Fig. 5 C–E and Fig. S6 B, C, and E–H). In addition, to determine whether angular distributions exhibited directional bias under each condition, we applied the Rayleigh test to each dataset individually (Fig. 5 F and Fig. S6 I). As these tests were performed on a single condition, they are also not subject to the problem of multiple testing. Collectively, we consider that the statistical analyses presented in our manuscript appropriately account for potential multiple testing issues, and we remain confident in the robustness of the results.

Literature

Falk, M., Feodorova, Y., Naumova, N., Imakaev, M., Lajoie, B.R., Leonhardt, H., Joffe, B., Dekker, J., Fudenberg, G., Solovei, I. et al. (2019) Heterochromatin drives compartmentalization of inverted and conventional nuclei. Nature, 570, 395-399. Mirny, L.A., Imakaev, M. and Abdennur, N. (2019) Two major mechanisms of chromosome organization. Curr Opin Cell Biol, 58, 142-152. Rao, S.S.P., Huang, S.C., Glenn St Hilaire, B., Engreitz, J.M., Perez, E.M., Kieffer-Kwon, K.R., Sanborn, A.L., Johnstone, S.E., Bascom, G.D., Bochkov, I.D. et al. (2017) Cohesin Loss Eliminates All Loop Domains. Cell, 171, 305-320 e324. Bintu, B., Mateo, L.J., Su, J.H., Sinnott-Armstrong, N.A., Parker, M., Kinrot, S., Yamaya, K., Boettiger, A.N. and Zhuang, X. (2018) Super-resolution chromatin tracing reveals domains and cooperative interactions in single cells. Science, 362. Cremer, M., Brandstetter, K., Maiser, A., Rao, S.S.P., Schmid, V.J., Guirao-Ortiz, M., Mitra, N., Mamberti, S., Klein, K.N., Gilbert, D.M. et al. (2020) Cohesin depleted cells rebuild functional nuclear compartments after endomitosis. Nat Commun, 11, 6146. Hoencamp, C., Dudchenko, O., Elbatsh, A.M.O., Brahmachari, S., Raaijmakers, J.A., van Schaik, T., Sedeno Cacciatore, A., Contessoto, V.G., van Heesbeen, R., van den Broek, B. et al. (2021) 3D genomics across the tree of life reveals condensin II as a determinant of architecture type. Science, 372, 984-989. Beckwith, K.S., Ødegård-Fougner, Ø., Morero, N.R., Barton, C., Schueder, F., Tang, W., Alexander, S., Peters, J.-M., Jungmann, R., Birney, E. et al. (2023) Nanoscale 3D DNA tracing in single human cells visualizes loop extrusion directly in situ. BioRxiv 8 of 9https://doi.org/10.1101/2021.04.12.439407. Massacci, G., Perfetto, L. and Sacco, F. (2023) The Cyclin-dependent kinase 1: more than a cell cycle regulator. Br J Cancer, 129, 1707-1716. Bonev, B. and Cavalli, G. (2016) Organization and function of the 3D genome. Nat Rev Genet, 17, 661-678. Dekker, J., Belmont, A.S., Guttman, M., Leshyk, V.O., Lis, J.T., Lomvardas, S., Mirny, L.A., O'Shea, C.C., Park, P.J., Ren, B. et al. (2017) The 4D nucleome project. Nature, 549, 219-226.

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Referee #3

Evidence, reproducibility and clarity

Summary:

The manuscript „Condensin II collaborates with cohesin to establish and maintain interphase chromosome territories" investigates how condensin II and cohesin contribute to chromosome organization during the M-to-G1 transition and in G2 phase using published auxin-inducible degron (AID) cell lines which render the respective protein complexes nonfunctional after auxin addition. In this study, a novel degron cell line was established that enables the simultaneous depletion of both protein complexes, thereby facilitating the investigation of synergistic effects between the two SMC proteins. The chromosome architecture is studied using fluorescence in situ hybridization (FISH) and light microscopy. The authors reproduce a number of already published data and also show that double depletion causes during the M-to-G1 transition defects on chromosome territories, producing expanded, irregular shapes that obscure condensin II-specific phenotypes. Findings in G2 cells point to a new role of condensin II for chromosome conformation at a scale of ~20Mb. Although individual depletion has minimal effects on large-scale CT morphology in G2, combined loss of both complexes produces marked structural abnormalities, including irregular crescent-shaped CTs displaced toward the nucleolus and increased nucleolus-CT contact. The authors propose that condensin II and cohesin act sequentially and complementarily to ensure proper post-mitotic CT formation and maintain chromosome architecture across genomic scales.

Concerns about statistics:

(1) The authors provide the information on how many cells are analyzed but not the number of independent experiments. My concern is that there might variations in synchronization of the cell population and in the subsequent preparation (FISH) affecting the final result.

(2) Statistically the authors analyze the effect of cells with induced degron vs. vehicle control (non-induced). However, the biologically relevant question is whether the data differ between cell lines when the degron system is induced. This is not tested here (cf. major concern 2 and 3).

(3) Some Journal ask for blinded analysis of the data which might make sense here as manual steps are involved in the data analysis (e.g. line 626 / 627the convex hull of the signals was manually delineated, line 635 / 636 Chromosome segmentation in FISH images was performed using individual thresholding). However personally I have no doubts on the correctness of the work.

Major concerns:

(1) Degron induction appears to delay in Rad21-AID#1 an Double-AID#1 cells the transition from M to G1, as shown in Fig. S1. After auxin treatment, more cells exhibit a G2 phenotype than in an untreated population. What are the implications of this for the interpretation of the experiments?

(2) Line 178 "In contrast, cohesin depletion had a smaller effect on the distance between the two site-specific probes compared to condensin II depletion (Fig. 2, C and E)." The data in Fig. 2 E show both a significant effect of H2 and a significant effect of RAD21 depletion. Whether the absolute difference in effect size between the two conditions is truly relevant is difficult to determine, as the distribution of the respective control groups also appears to be different.

(3) In Figures 3, S3 and related text in the manuscript I cannot follow the authors' argumentation, as H2 depletion alone leads to a significant increase in the CT area (Chr. 18, Chr. 19, Chr. 15). Similar to Fig. 2, the authors argue about the different magnitude of the effect (H2 depletion vs double depletion). Here, too, appropriate statistical tests or more suitable parameters describing the effect should be used. I also cannot fully follow the argumentation regarding chromosome elongation, as double depletion in Chr. 18 and Chr. 19 also leads to a significantly reduced circularity. Therefore, the schematic drawing Fig. 3 H (double depletion) seems very suggestive to me.

(4) Fig. 5 and accompanying text. I agree with the authors that this is a significant and very interesting effect. However, I believe the sharp bends is in most cases an artifact caused by the maximum intensity projection. I tried to illustrate this effect in two photographs: Reviewer Fig. 1, side view, and Reviewer Fig. 2, same situation top view (https://cloud.bio.lmu.de/index.php/s/77npeEK84towzJZ). As I said, in my opinion, there is a significant and important effect; the authors should simply adjust the description.

Minor concerns:

(1) I would like to suggest proactively discussing possible artifacts that may arise from the harsh conditions during FISH sample preparation..

(2) It would be helpful if the authors could provide the original data (microscopic image stacks) for download

(3) The authors use a blind deconvolution algorithm to improve image quality. It might be helpful to test other methods for this purpose (optional).

Significance

Advance:

Ono et al. addresses the important question on how the complex pattern of chromatin is reestablished after mitosis and maintained during interphase. In addition to affinity interactions (1,2), it is known that cohesin plays an important role in the formation and maintenance of chromosome organization interphase (3). However, current knowledge does not explain all known phenomena. Even with complete loss of cohesin, TAD-like structures can be recognized at the single-cell level (4), and higher structures such as chromosome territories are also retained (5). The function of condensin II during mitosis is another important factor that affects chromosome architecture in the following G1 phase (6). Although condensin II is present in the cell nucleus throughout interphase, very little is known about the role of this protein in this phase of the cell cycle. This is where the present publication comes in, with a new double degron cell line in which essential subunits of cohesin AND condensin can be degraded in a targeted manner. I find the data from the experiments in the G2 phase most interesting, as they suggest a previously unknown involvement of condensin II in the maintenance of larger chromatin structures such as chromosome territories. The experiments regarding the M-G1 transition are less interesting to me, as it is known that condensin II deficiency in mitosis leads to elongated chromosomes (Rabl configuration)(6), and therefore the double degradation of condensin II and cohesin describes the effects of cohesin on an artificially disturbed chromosome structure.

General limitations:

(1) Single cell imaging of chromatin structure typically shows only minor effects which are often obscured by the high (biological) variability. This holds also true for the current manuscript (cf. major concern 2 and 3).

(2) A common concern are artefacts introduced by the harsh conditions of conventional FISH protocols (7). The authors use a method in which the cells are completely dehydrated, which probably leads to shrinking artifacts. However, differences between samples stained using the same FISH protocol are most likely due to experimental variation and not an artefact (cf. minor concern 1).

(3) The anisotropic optical resolution (x-, y- vs. z-) of widefield microscopy (and most other light microscopic techniques) might lead to misinterpretation of the imaged 3D structures. This seems to be the cases in the current study (cf. major concern 4).

(4) In the present study, the cell cycle was synchronized. This requires the use of inhibitors such as the CDK1 inhibitor RO-3306. However, CDK1 has many very different functions (8), so unexpected effects on the experiments cannot be ruled out.

Audience:

The spatial arrangement of genomic elements in the nucleus and their (temporal) dynamics are of high general relevance, as they are important for answering fundamental questions, for example, in epigenetics or tumor biology (9,10). The manuscript from Ono et al. addresses specific questions, so its intended readership is more likely to be specialists in the field.

About the reviewer: By training I'm a biologist with strong background in fluorescence microscopy and fluorescence in situ hybridization. In recent years, I have been involved in research on the 3D organization of the cell nucleus, chromatin organization, and promoter-enhancer interactions.

All questions regarding the statistics of angularly distributed data are beyond my expertise. The authors do not correct their statistical analyses for "multiple testing". Whether this is necessary, I cannot judge.

Literature

1. Falk, M., Feodorova, Y., Naumova, N., Imakaev, M., Lajoie, B.R., Leonhardt, H., Joffe, B., Dekker, J., Fudenberg, G., Solovei, I. et al. (2019) Heterochromatin drives compartmentalization of inverted and conventional nuclei. Nature, 570, 395-399.
2. Mirny, L.A., Imakaev, M. and Abdennur, N. (2019) Two major mechanisms of chromosome organization. Curr Opin Cell Biol, 58, 142-152.
3. Rao, S.S.P., Huang, S.C., Glenn St Hilaire, B., Engreitz, J.M., Perez, E.M., Kieffer-Kwon, K.R., Sanborn, A.L., Johnstone, S.E., Bascom, G.D., Bochkov, I.D. et al. (2017) Cohesin Loss Eliminates All Loop Domains. Cell, 171, 305-320 e324.
4. Bintu, B., Mateo, L.J., Su, J.H., Sinnott-Armstrong, N.A., Parker, M., Kinrot, S., Yamaya, K., Boettiger, A.N. and Zhuang, X. (2018) Super-resolution chromatin tracing reveals domains and cooperative interactions in single cells. Science, 362.
5. Cremer, M., Brandstetter, K., Maiser, A., Rao, S.S.P., Schmid, V.J., Guirao-Ortiz, M., Mitra, N., Mamberti, S., Klein, K.N., Gilbert, D.M. et al. (2020) Cohesin depleted cells rebuild functional nuclear compartments after endomitosis. Nat Commun, 11, 6146.
6. Hoencamp, C., Dudchenko, O., Elbatsh, A.M.O., Brahmachari, S., Raaijmakers, J.A., van Schaik, T., Sedeno Cacciatore, A., Contessoto, V.G., van Heesbeen, R., van den Broek, B. et al. (2021) 3D genomics across the tree of life reveals condensin II as a determinant of architecture type. Science, 372, 984-989.
7. Beckwith, K.S., Ødegård-Fougner, Ø., Morero, N.R., Barton, C., Schueder, F., Tang, W., Alexander, S., Peters, J.-M., Jungmann, R., Birney, E. et al. (2023) Nanoscale 3D DNA tracing in single human cells visualizes loop extrusion directly in situ. BioRxiv https://doi.org/10.1101/2021.04.12.439407.
8. Massacci, G., Perfetto, L. and Sacco, F. (2023) The Cyclin-dependent kinase 1: more than a cell cycle regulator. Br J Cancer, 129, 1707-1716.
9. Bonev, B. and Cavalli, G. (2016) Organization and function of the 3D genome. Nat Rev Genet, 17, 661-678.
10. Dekker, J., Belmont, A.S., Guttman, M., Leshyk, V.O., Lis, J.T., Lomvardas, S., Mirny, L.A., O'Shea, C.C., Park, P.J., Ren, B. et al. (2017) The 4D nucleome project. Nature, 549, 219-226.

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Referee #2

Evidence, reproducibility and clarity

Summary:

• Ono et al use a variety of imaging and genetic (AID) depletion approaches to examine the roles of condensin II and cohesin in the reformation of interphase genome architecture in human HCT16 cells. Consistent with previous literature, they find that condensin II is required for CENP-A dispersion in late mitosis/early G1. Using in situ FISH at the centromere/q arm of chromosome 12 they then establish that condensin II removal causes lengthwise elongation of chromosomes that, interestingly, can be suppressed by cohesin removal. To better understand changes in whole-chromosome morphology, they then use whole chromosome painting to examine chromosomes 18 and 19. In the absence of condensin II, cells effectively fail to reorganise their chromosomes from rod-like structures into spherical chromosome territories (which may explain why CENP-A dispersion is suppressed). Cohesin is not required for spherical CT formation, suggesting condensin II is the major initial driver of interphase genome structure. Double depletion results in complete disorganisation of chromatin, leading the authors to conclude that a typical cell cycle requires orderly 'handover' from the mitotic to interphase genome organising machinery.

• The authors then move on to G2 phase, where they use a variety of different FISH probes to assess alterations in chromosome structure at different scales. They thereby establish that perturbation of cohesin or condensin II influences local and longer range chromosome structure, respectively. The effects of condensin II depletion become apparent at a genomic distance of 20 Mb, but are negligible either below or above. The authors repeat the G1 depletion experiment in G2 and now find that condensin II and cohesin are individually dispensable for CT organisation, but that dual depletion causes CT collapse. This rather implies that there is cooperation rather than handover per se.

• Overall this study is a broadly informative multiscale investigation of the roles of SMC complexes in organising the genome of postmitotic cells, and solidifies a potential relationship between condensin II and cohesin in coordinating interphase genome structure. The deeper investigation of the roles of condensin II in establishing chromosome territories and intermediate range chromosome structure in particular is a valuable and important contribution, especially given our incomplete understanding of what functions this complex performs during interphase.

Major comments:

• In general the claims and conclusions of the manuscript are well supported by multiscale FISH labelling. An important absent control is western blotting to confirm protein depletion levels. Currently only fluorescence is used as a readout for the efficiency of the AID depletion, and we know from prior literature that even small residual quantities of SMC complexes are quite effective in organising chromatin. I would consider a western blot a fairly straightforward and important technical control.

• I find the point on handover as a mechanism for maintaining CT architecture somewhat ambiguous, because the authors find that the dependence simply switches from condensin II to both condensin II and cohesin, between G1 and G2. To me this implies augmented cooperation rather than handover.

• I have two further suggestions, both of which I would strongly recommend but would consider desirable but 'optional' according to review commons guidelines.

Firstly, the depletions are performed at different stages of the cell cycle but have different outcomes. The authors suggest this is because handover is already complete, but an alternative possibility is that the phenotype is masked by other changes in chromosome structure (e.g. duplication/catenation). I would be very curious to see, for example, how the outcome of this experiment would change if the authors were to repeat the depletions in the presence of a topoisomerase II inhibitor.

Secondly, if the author's claim of handover is correct then one (not exclusive) possibility is that there is a relationship between condensin II and cohesin loading onto chromatin. There does seem to be a modest co-dependence (e.g. fig S4 and S7), could the authors comment on this? Another control experiment here would be to treat fully WT cells with IAA and test whether non-AID labelled H2 or RAD21 dip in intensity. If they do not, then perhaps there's a causal relationship between condensin II and cohesin levels?

• I recognise this is something considered in Brunner et al 2025 (JCB), but in their case they depleted SMC4 (so all condensins are lost or at least dismantled). Might bear further investigation.

Methods:

Data and methods are described in reasonable detail, and a decent number of replicates/statistical analyses have been. Documentation of the cell lines used could be improved. The actual cell line is not mentioned once in the manuscript. Although it is referenced, I'd recommend including the identity of the cell line (HCT116) in the main text when the cells are introduced and also in the relevant supplementary tables. Will make it easier for readers to contextualise the findings.

Minor comments:

Overall the manuscript is well-written and well presented. In the introduction it is suggested that no experiment has established a causal relationship between human condensin II and chromosome territories, but this is not correct, Hoencamp et al 2021 (cell) observed loss of CTs after condensin II depletion. Although that manuscript did not investigate it in as much detail as the present study, the fundamental relationship was previously established, so I would encourage the authors to revise this statement.

Significance

General assessment: Strengths: the multiscale investigation of genome architecture at different stages of interphase allow the authors to present convincing and well-analysed data that provide meaningful insight into local and global chromosome organisation across different scales. Limitations: As suggested in major comments.

Advance: Although the role of condensin II in generating chromosome territories, and the roles of cohesin in interphase genome architecture are established, the interplay of the complexes and the stage specific roles of condensin II have not been investigated in human cells to the level presented here. This study provides meaningful new insight in particular into the role of condensin II in global genome organisation during interphase, which is much less well understood compared to its participation in mitosis.

Audience: Will contribute meaningfully and be of interest to the general community of researchers investigating genome organisation and function at all stages of the cell cycle. Primary audience will be cell biologists, geneticists and structural biochemists. Importance of genome organisation in cell/organismal biology is such that within this grouping it will probably be of general interest.

My expertise is in genome organization by SMCs and chromosome segregation.

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Referee #1

Evidence, reproducibility and clarity

Ono et al addressed how condensin II and cohesin work to define chromosome territories (CT) in human cells. They used FISH to assess the status of CT. They found that condensin II depletion leads to lengthwise elongation of G1 chromosomes, while double depletion of condensin II and cohesin leads to CT overlap and morphological defects. Although the requirement of condensin II in shortening G1 chromosomes was already shown by Hoencamp et al 2021, the cooperation between condensin II and cohesin in CT regulation is a new finding. They also demonstrated that cohesin and condensin II are involved in G2 chromosome regulation on a smaller and larger scale, respectively. Though such roles in cohesin might be predictable from its roles in organizing TADs, it is a new finding that the two work on a different scale on G2 chromosomes. Overall, this is technically solid work, which reports new findings about how condensin II and cohesin cooperate in organizing G1 and G2 chromosomes.

Major point:

They propose a functional 'handover' from condensin II to cohesin, for the organization of CTs at the M-to-G1 transition. However, the 'handover', i.e. difference in timing of executing their functions, was not experimentally substantiated. Ideally, they can deplete condensin II and cohesin at different times to prove the 'handover'. However, this would require the use of two different degron tags and go beyond the revision of this manuscript. At least, based on the literature, the authors should discuss why they think condensin II and cohesin should work at different timings in the CT organization.

Other points:

• Figure 2E: It seems that the chromosome length without IAA is shorter in Rad21-aid cells than H2-aid cells or H2-aid Rad21-aid cells. How can this be interpreted?

• Figure 3: Regarding the CT morphology, could they explain further the difference between 'elongated' and 'cloud-like (expanded)'? Is it possible to quantify the frequency of these morphologies?

• Figure 5: How did they assign C, P and D3 for two chromosomes? The assignment seems obvious in some cases, but not in other cases (e.g. in the image of H2-AID#2 +IAA, two D3s can be connected to two Ps in the other way). They may have avoided line crossing between two C-P-D3 assignments, but can this be justified when the CT might be disorganized e.g. by condensin II depletion?

• Figure 6F: The mean is not indicated on the right-hand side graph, in contrast to other similar graphs. Is this an error?

• Figure S1A: The two FACS profiles for Double-AID #3 Release-2 may be mixed up between -IAA and +IAA.

• The method section explains that 'circularity' shows 'how closely the shape of an object approximates a perfect circle (with a value of 1 indicating a perfect circle), calculated from the segmented regions'. It would be helpful to provide further methodological details about it.

Significance

Ono et al addressed how condensin II and cohesin work to define chromosome territories (CT) in human cells. They used FISH to assess the status of CT. They found that condensin II depletion leads to lengthwise elongation of G1 chromosomes, while double depletion of condensin II and cohesin leads to CT overlap and morphological defects. Although the requirement of condensin II in shortening G1 chromosomes was already shown by Hoencamp et al 2021, the cooperation between condensin II and cohesin in CT regulation is a new finding. They also demonstrated that cohesin and condensin II are involved in G2 chromosome regulation on a smaller and larger scale, respectively. Though such roles in cohesin might be predictable from its roles in organizing TADs, it is a new finding that the two work on a different scale on G2 chromosomes. Overall, this is technically solid work, which reports new findings about how condensin II and cohesin cooperate in organizing G1 and G2 chromosomes.

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity (Required)): * Summary: * In this manuscript, Turner AH. et al. demonstrated the viral replication in cells depleting Rab11B small GTPase, which is a paralogue of Rab11A. It has been reported that Rab11A is responsible for the intracellular transport of viral RNP via recycling endosomes. The authors showed that Rab11B knockdown reduced the viral protein expression and viral titer. This may be caused by reduced attachment of viral particles on Rab11B knockdown cells.

• Major comments:*
• Comment 1 Fig 2-4: The authors should provide Western blot results with equal amount of loading control (GAPDH). The bands shown in these figures lack quantifiability and are not reliable as data.*

We have rerun these western blots with more equal loading, and included a second loading control (beta-actin) in addition to the GAPDH. These blots can be seen in new Figures 2 and 3, and the quantification against both GAPDH (Figure 2/3) as well as actin (Fig S2) is now included. We have also included additional biological replicates for Fig 2 B-D. These additional experiments have strengthened our conclusion that Rab11B is required for efficient protein production in cells infected with recent H3N2, but not H1N1, isolates.

Comment 2 Fig 2-4: Why are the results different between Rab11B knockdown alone and Rab11A/B double knockdown? If the authors claims are correct, the results of Rab11B knockdown should be reproducible in Rab11A/B double knockdown cells.

Prior literature indicates that the Rab11A and Rab11B isoforms can play opposing roles in the trafficking of some cargos (ie, with one isoform transporting a molecule to the cell surface, while the other isoform takes it off again). In this scenario, it is possible that removing both 'halves' of the trafficking loop can ablate a phenotype. However, since our double knockdown used half the amount of siRNA for each isoform (for the same total amount), it is also possible this observation is simply the result of less efficient knockdown. In order to distinguish between these possibilities we depleted Rab11A or Rab11B individually, with this same 'half dose' of siRNA (see new Figure S3). We observed that Rab11B was still robustly required for H3N2 viral protein production. These results suggest that Rab11A and Rab11B could be playing mutually opposing roles in this case, which is consistent with prior Rab11 literature.

Comment 3 Fig 6: For better understanding, please provide a schematic illustration of experimental setting.

We have added a new graphical overview to this figure (see new Figure 6A).

Comment 4: It is necessary to test other siRNA sequences or perform a rescue experiment by expressing an siRNA-resistant clone in the knockdown cells. There seems to be an activation of host defense system, such as IFN pathways.

In order to rule out the possibility of off-target effects we created a novel cell line that inducibly expresses a Rab11B shRNA sequence (see new Fig 4). This knockdown strategy used a completely different method (shRNA delivered by lentiviral vector vs transient transfection of siRNA), in a different cellular background (H441 "club like" cells vs A549 lung adenocarcinoma). This new depletion strategy showed that the Rab11B dependent H3N2 protein production phenotype is seen across multiple knockdown strategies and cellular backgrounds.

**Referees cross-commenting**

I agree with other reviewers' comments in part.

Reviewer #1 (Significance (Required)):

The authors propose a novel role for Rab11B in modulating attachment pathway of H3N2 influenza A virus by unknown mechanism. Although previous studies focus on the function of Rab11A on endocytic transport, the function and specificity of Rab11B has remained less clear. The findings may be of interest to a broad audience, including researchers in cell biology, immunology, and host-pathogen interactions. However, the study remains at a superficial level of analysis and does not lead to a deeper understanding of the underlying mechanisms.

We agree with the reviewer that a strength of this manuscript is its multi-disciplinary nature, particularly with regard to advances in our understanding of Rab11B function. We have added a significant number of experiments and new figures to bolster the rigor and reproducibility of our findings. We have also added a new figure (Fig 7) that uses reverse genetics to map the Rab11B phenotype to the HA gene of the H3N2 isolate under study. By creating '7+1' reassortant viruses with the H3 HA or the N2 NA on a PR8 (H1N1) background (see Fig 7E-H) we were able to demonstrate that Rab11B is acting specifically on one of the HA-mediated entry steps. This provides additional mechanistic insight, by mapping the Rab11B-phenotype to a step at or prior to fusion. Fundamentally, we believe the novelty and rigor of our observation that recent H3N2 viruses enter through a different route than H1N1 isolates is worthy of observation in this updated form, so that the field can begin follow up studies.

Reviewer #2 (Evidence, reproducibility and clarity (Required)): Summary: The authors compare the effect of RAB11A and RAB11B knockdown on replication of contemporary H1N1 and H3N2 influenza A virus strains in A549 cells (human lung epithelials cells). They find a reduction in viral protein expression for tested H3N2 but not for H1N1 isolates. Mechanistically they suggest that RAB11A affects virion attachment to the cell surface.

Major comments: The provided data do not conclusively support the suggested mechanism of action and essential controls are missing to substantiate the authors claims: • Knockdown efficacy has to be confirmed on protein level, showing reduced levels of RAB11A and B by Western blot. This is a standard in the field. Off target effects cannot be avoided by RNAi approaches and are usually ruled out by using multiple siRNAs or by complementing the targeted protein in trans.

We have verified knockdown efficacy at the protein level in new Fig 1A/B. However, due to the high degree of protein level conservation between Rab11A and Rab11B it is very difficult to develop isoform specific antibodies, and we were unable to obtain a Rab11B-specific antibody that can detect endogenous protein (despite testing 6 commercially available antibodies for specificity). Using an antibody that detects both 11A and 11B (Fig1A) we were able to observe very slight changes in the molecular weight of the Rab11 band(s) detected upon knockdown of 11A vs 11B (suggestive of the two isoforms running as a dimer, with Rab11A the lower band and Rab11B the upper band). Cells depleted of both isoforms simultaneously showed a near complete loss of signal. Using a Rab11A antibody (that we confirmed as specific) we were able to observe loss of the Rab11A signal in both the 11A and 11A+B knockdowns (Fig 1B).

• Viral titers should be presented as absolute titers not as % (here the labelling is actually misleading in all graphs indicating pfu/ml)

This data is now shown in new Figure S1, where it is clear that the trends remain consistent across biological replicates. The axis labels of Fig 1D/E and Fig 3A have been corrected as requested to make clear we are normalizing to account for experiment-to-experiment variation in peak titer.

• Reduction of viral protein expression goes hand in hand with a reduction in GAPDH. While this is accounted for in the quantification a general block of protein expression cannot be ruled out since the stability of house keeper proteins and viral proteins might be different. Testing multiple house keeping proteins could overcome this issue.

We have included a second loading control (beta-actin) in addition to the GAPDH for new Figure 2 and 3. The quantification of viral protein production compared to beta actin is now included in new Fig S2. We have also included additional biological replicates for Fig 2 B-D. These additional experiments have strengthened our conclusion that Rab11B is required for efficient protein production in cells infected with recent H3N2, but not H1N1, isolates.

• The FACS data in Fig 5 are not convincing. The previous figures showed modest reduction in viral protein expression and the fluorescence is indicated here on a logarithmic scale. Quantification and indication of mean fluorescence intensity from the same data would be a better readout to convincingly show that less cells are infected.

We have reanalyzed the existing data to quantify the geometric mean of viral protein expression in the infected cell populations (new Figure 5D, E). This analysis shows no significant difference in geometric mean of HA (Fig 5D) or M2 (Fig 5E) expression between cells treated with NT, 11A or 11B siRNA. This additional analysis strengthens our original conclusion that when Rab11B is knocked down, fewer cells get infected, but those that do produce the same level of viral proteins.

• During the time of addition experiment in Fig 6, the authors are testing for HA/M2 positive cells after 16h of infection. This is a multicycle scnario so in a second round they would measure the effect of knockdown in absence of amonium chloride. Shorter infections up to 8h with higher MOI would overcome this problem.

By maintaining cells in ammonium chloride throughout the infection we are preventing endosomal acidification at any point in the infection period, so this experiment should be measuring solely the effect of one round of infection. The 16 hr timepoint was chosen to allow for optimized staining and analysis of samples by flow cytometry, within the available hours of the flow cytometry facility.

• Standard error of mean is not an appropriate way of representing experimental error for the provided results and should be replaced by SD. Correct labeling of axis with units is required.

We have updated the axes throughout the manuscript as requested. We have obtained additional statistical expertise (reflected in the updated author list) regarding the issue of SD vs SEM. Standard deviation (SD) would show a measure of the spread of the data, however the full distribution can be clearly seen as we plotted every individual data point. Standard error of the mean (SEM) is a measure of confidence for the mean of the population which takes into account SD and also sample size. SEM is not obvious to estimate by eye in the same way as SD, and we feel is more helpful to the reader to understand how likely the two population means differ from each other on a given graph.

Minor comments: • The authors show a rescue of viral replication upon double knockdown of RAB11A and B. Maybe this is just a consequence of inefficient knockdown since only half of the siRNAs were used?

In order to determine if this was the case we depleted Rab11A or Rab11B individually, with this same 'half dose' of siRNA (see new Figure S3). We observed that Rab11B was still robustly required for H3N2 viral protein production. These results suggest that Rab11A and Rab11B could be playing mutually opposing roles in this case (ie, Rab11B transporting a molecule to the surface, while Rab11A recycles it off), which is consistent with prior Rab11 literature.

• Specific experimental issues that are easily addressable. • Are prior studies referenced appropriately? • Are the text and figures clear and accurate? • Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

• Reviewer #2 (Significance (Required)): Significance The authors claim an H3N2 specific dependency on RAB11B for early steps of infection. While this is per se interesting the provided data do not fully support the claims and lack a mechanistic explanation. What is the difference between H1 and H3 strains (virion shape, HA load per virion, attachment force of H1 vs H3). The readouts used are not close enough to the events with regards to timing and could be supported by established entry assays in the field.

We have provided additional discussion of the differences between H1s and H3s, including sialic acid binding preferences and changes in the HA-sialic acid avidity (lines 76-84). Notably, we have included a new assay (new Fig 7) that provides additional mechanistic insight into the observation that recent H3N2 but not H1N1 isolates depend on Rab11B early in infection. Using reverse genetics we were able to map the Rab11B phenotype to the HA gene of the H3N2 isolate under study. By creating '7+1' reassortant viruses with either the H3 HA or the N2 NA on a PR8 (H1N1) background (see Fig 7E) we are able to demonstrate that Rab11B is acting specifically at one of the HA-mediated entry steps. This excludes several non-HA dependent steps early in the life cycle (uncoating, RNP transport to the nucleus, nuclear import), thus providing additional confirmation that Rab11B acts at one of the earliest steps in the viral life cycle (and by definition, at or prior to fusion). Fundamentally, we believe the novelty and rigor of our observation that recent H3N2 viruses enter through a different route than H1N1 isolates is worthy of observation in this updated form, so that the field can begin follow up studies.

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

Manuscript Reference: RC-2025-03007 TITLE: Rab11B is required for binding and entry of recent H3N2, but not H1N1, influenza A isolates Allyson Turner, Sara Jaffrani, Hannah Kubinski, Deborah Ajayi, Matthew Owens, Madeline McTigue, Conor Fanuele, Cailey Appenzeller, Hannah Despres, Madaline Schmidt, Jessica Crothers, and Emily Bruce

Summary Here, Turner et al. build upon existing knowledge of Influenza A virus (IAV) dependence on the Rab11 family of proteins and provide insights into the specific role of Rab11B isoform in H3N2 virus binding and entry. The introduction is clearly written and provides sufficient background on prior research involving Rab11. It effectively identifies the current gap in knowledge and justifies the investigation of more clinically relevant, circulating strains of IAV. The methods section provides sufficient detail to ensure reproducibility. Similarly, the discussion is well structured, aligns with the introduction, and thoughtfully outlines relevant follow-up experiments. The authors present data from a series of experiments which suggest that the reduced H3N2 infection and viral protein production in Rab11B-depleted cells is due to impaired virus binding. While the evidence supports a Rab11B-specific phenotype in the context of H3N2 infection, we recommend additional experiments (outlined below), to further validate and strengthen these findings. These would help solidify the mechanistic link between Rab11B depletion and the observed phenotype for H3N2 strains of IAV.

Major comments Figure 1. (B) & (C) The authors normalise viral titers to the non-targeting control (NTC) siRNA set at 100. While this approach allows for relative comparisons, we recommend including the corresponding raw PFU/ml values, at least in the supplementary materials. This will better illustrate the biological significance of gene depletion and variability of the results.

We have included the raw PFU/mL values in new Figure S1, while peak viral production varied by biological replicate (pasted below, with each biological replicate having a differently shaped data point). While the depletion-induced trends are clearly visible across biological replicates, normalization to average titer in the NT condition for each replicate allows for cleaner visualization.

In addition, the current protocol uses a high MOI (1), and a relatively short infection period (16 hours) to capture single-cycle replication. However, to better assess the impact of gene knockdown on virus production and spread, we suggest performing a multicycle replication assay using a lower MOI (e.g, 0.01-0.001) over an extended time period, such as 48 hours before titration, provided that cell viability under these conditions is acceptable.

We appreciate this suggestion and repeatedly attempted to carry out a multicycle growth curve to obtain this data. Unfortunately, out of four independent biological replicates we attempted, we were only able to maintain cell viability and adherence in one biological replicate (shown below). We have not included this data in the revised manuscript due to the limited replicates we were able to obtain, though we can add it in a further revision if the reviewer feels it is warranted.

Figure 7. (B) & (C) The authors present interesting data showing that siRNA-mediated depletion of Rab11B reduces virion binding of a recently circulating strain of H3N2, but not H1N1, suggesting a subtype-specific role. However, we strongly recommend complementing this assay with a single-cell resolution approach such as immunofluorescence detection of surface-bound viruses through HA staining and image quantification. This would allow the authors to directly assess virion binding per cell and visualise the phenotype, strengthening the mechanistic insight on H3N2 binding in Rab11B-depleted cells. Furthermore, the data, particularly for H1N1 (Figure 7.C), shows substantial variance, which suggests a suboptimal assay sensitivity and limits the strength of the conclusion that the knockdown does not affect H1N1 binding, this limitation may be overcome by implementing the above experimental suggestion.

We have made substantial efforts to include this data, but were ultimately unable to include this assay due to technical difficulties in implementation (NA stripping caused cells to lift off coverslips, difficulties in antibody sensitivity and specificity, among other issues). We also piloted single cell-based flow cytometry assays to attempt to measure signal from bound virions, but were unable to achieve sufficient differentiation between mock and bound samples with the antibodies we could obtain. However, we have included a new experimental approach that is able to genetically map the 11B-dependent phenotype to the HA gene, thus providing additional mechanistic insight and confirming that Rab11B acts on one of the earliest steps in the viral life cycle (prior to or at fusion).

Minor comments General The authors should state which statistical test was used for each dataset in the respective figure legends.

This information is now included in each figure legend.

Figure 1. Suggest changing Y axis title to PFU/ml [relative to NTC]

We have changed the axis titles of normalized data to "PFU as % of NT" throughout.

The co-depletion of Rab11A and Rab11B appears to be less efficient than individual knockdowns, based on RT- qPCR data (Figure 1.A). It is possible that the partial 'rescue' phenotype observed in Figures 2-4 is due to incomplete knockdown, rather than a true biological interaction. This possibility should be acknowledged.

In order to distinguish between a partial 'rescue' and inefficient knockdown, we depleted Rab11A or Rab11B individually, with the same 'half dose' of siRNA used in the double knockdown (see new Figure S3). We observed that Rab11B was still robustly required for H3N2 viral protein production. These results suggest that Rab11A and Rab11B could be playing mutually opposing roles in this case, which is consistent with prior Rab11 literature, rather than simply inefficient knockdown.

Furthermore, knockdown efficiency is assessed only at the mRNA level. To strengthen the conclusions, the authors are encouraged to provide western blot data confirming protein-level depletion of Rab11A and Rab11B, particularly in the double knockdown condition. This would help clarify whether co-transfection of siRNAs affect the efficiency of each individual knockdown at the protein level.

We have verified knockdown efficacy at the protein level in new Fig 1A/B. However, due to the high degree of protein level conservation between Rab11A and Rab11B it is very difficult to develop isoform specific antibodies, and we were unable to obtain a Rab11B-specific antibody that can detect endogenous protein (despite testing 6 commercially available antibodies for specificity). Using an antibody that detects both 11A and 11B (Fig1A) we were able to observe very slight changes in the molecular weight of the Rab11 band(s) detected upon knockdown of 11A vs 11B (suggestive of the two isoforms running as a dimer, with Rab11A the lower band and Rab11B the upper band). Cells depleted of both isoforms simultaneously showed a near complete loss of signal. Using a Rab11A antibody (that we confirmed as specific) we were able to observe loss of the Rab11A signal in both the 11A and 11A+B knockdowns (Fig 1B).

Figure 6. (A) & (B) are missing error bars, particularly the Rab11B knockdown data points.

Error bars are plotted in each graph, but due to very limited experimental variation these error bars are too small to appear on the graph (11B points in Fig 6B, D).

Figure 7. If including any repeats in the binding assay, authors are encouraged to use appropriate controls in each experiment such as exogenous neuraminidase treatment or sialidase treatment.

When attempting to establish a microscopy based binding assay we included exogenous neuraminidase in each experiment. Unfortunately, the combination of glass coverslips and treatment with exogenous neuraminidase at incubation times sufficient to strip virus also removed cells from the coverslips.

Reviewer #3 (Significance (Required)):

General assessment: Provides a conceptual advancement of subtype specific receptor preferences.

Advance: The study raises interesting observations regarding influenza virus subtype differences in cell surface receptor binding, in a Rab11B-dependent manner.

Audience: Influenza virologists, respiratory virologists

Expertise: Virus entry, Virus cell biology

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

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Referee #3

Evidence, reproducibility and clarity

Title: Rab11B is required for binding and entry of recent H3N2, but not H1N1, influenza A isolates

Allyson Turner, Sara Jaffrani, Hannah Kubinski, Deborah Ajayi, Matthew Owens, Madeline McTigue, Conor Fanuele, Cailey Appenzeller, Hannah Despres, Madaline Schmidt, Jessica Crothers, and Emily Bruce

Summary

Here, Turner et al. build upon existing knowledge of Influenza A virus (IAV) dependence on the Rab11 family of proteins and provide insights into the specific role of Rab11B isoform in H3N2 virus binding and entry. The introduction is clearly written and provides sufficient background on prior research involving Rab11. It effectively identifies the current gap in knowledge and justifies the investigation of more clinically relevant, circulating strains of IAV. The methods section provides sufficient detail to ensure reproducibility. Similarly, the discussion is well structured, aligns with the introduction, and thoughtfully outlines relevant follow-up experiments. The authors present data from a series of experiments which suggest that the reduced H3N2 infection and viral protein production in Rab11B-depleted cells is due to impaired virus binding. While the evidence supports a Rab11B-specific phenotype in the context of H3N2 infection, we recommend additional experiments (outlined below), to further validate and strengthen these findings. These would help solidify the mechanistic link between Rab11B depletion and the observed phenotype for H3N2 strains of IAV.

Major comments

Figure 1. (B) & (C)

The authors normalise viral titers to the non-targeting control (NTC) siRNA set at 100. While this approach allows for relative comparisons, we recommend including the corresponding raw PFU/ml values, at least in the supplementary materials. This will better illustrate the biological significance of gene depletion and variability of the results. In addition, the current protocol uses a high MOI (1), and a relatively short infection period (16 hours) to capture single-cycle replication. However, to better assess the impact of gene knockdown on virus production and spread, we suggest performing a multicycle replication assay using a lower MOI (e.g, 0.01-0.001) over an extended time period, such as 48 hours before titration, provided that cell viability under these conditions is acceptable.

Figure 7. (B) & (C)

The authors present interesting data showing that siRNA-mediated depletion of Rab11B reduces virion binding of a recently circulating strain of H3N2, but not H1N1, suggesting a subtype-specific role. However, we strongly recommend complementing this assay with a single-cell resolution approach such as immunofluorescence detection of surface-bound viruses through HA staining and image quantification. This would allow the authors to directly assess virion binding per cell and visualise the phenotype, strengthening the mechanistic insight on H3N2 binding in Rab11B-depleted cells. Furthermore, the data, particularly for H1N1 (Figure 7.C), shows substantial variance, which suggests a suboptimal assay sensitivity and limits the strength of the conclusion that the knockdown does not affect H1N1 binding, this limitation may be overcome by implementing the above experimental suggestion.

Minor comments

General

The authors should state which statistical test was used for each dataset in the respective figure legends.

Figure 1.

Suggest changing Y axis title to PFU/ml [relative to NTC] The co-depletion of Rab11A and Rab11B appears to be less efficient than individual knockdowns, based on RT- qPCR data (Figure 1.A). It is possible that the partial 'rescue' phenotype observed in Figures 2-4 is due to incomplete knockdown, rather than a true biological interaction. This possibility should be acknowledged. Furthermore, knockdown efficiency is assessed only at the mRNA level. To strengthen the conclusions, the authors are encouraged to provide western blot data confirming protein-level depletion of Rab11A and Rab11B, particularly in the double knockdown condition. This would help clarify whether co-transfection of siRNAs affect the efficiency of each individual knockdown at the protein level.

Figure 6.

(A) & (B) are missing error bars, particularly the Rab11B knockdown data points.

Figure 7.

If including any repeats in the binding assay, authors are encouraged to use appropriate controls in each experiment such as exogenous neuraminidase treatment or sialidase treatment.

Significance

General assessment: Provides a conceptual advancement of subtype specific receptor preferences.

Advance: The study raises interesting observations regarding influenza virus subtype differences in cell surface receptor binding, in a Rab11B-dependent manner.

Audience: Influenza virologists, respiratory virologists

Expertise: Virus entry, Virus cell 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

Summary:

The authors compare the effect of RAB11A and RAB11B knockdown on replication of contemporary H1N1 and H3N2 influenza A virus strains in A549 cells (human lung epithelials cells). They find a reduction in viral protein expression for tested H3N2 but not for H1N1 isolates. Mechanistically they suggest that RAB11A affects virion attachment to the cell surface.

Major comments:

The provided data do not conclusively support the suggested mechanism of action and essential controls are missing to substantiate the authors claims:

• Knockdown efficacy has to be confirmed on protein level, showing reduced levels of RAB11A and B by Western blot. This is a standard in the field. Off target effects cannot be avoided by RNAi approaches and are usually ruled out by using multiple siRNAs or by complementing the targeted protein in trans.
• Viral titers should be presented as absolute titers not as % (here the labelling is actually misleading in all graphs indicating pfu/ml)
• Reduction of viral protein expression goes hand in hand with a reduction in GAPDH. While this is accounted for in the quantification a general block of protein expression cannot be ruled out since the stability of house keeper proteins and viral proteins might be different. Testing multiple house keeping proteins could overcome this issue.
• The FACS data in Fig 5 are not convincing. The previous figures showed modest reduction in viral protein expression and the fluorescence is indicated here on a logarithmic scale. Quantification and indication of mean fluorescence intensity from the same data would be a better readout to convincingly show that less cells are infected.
• During the time of addition experiment in Fig 6, the authors are testing for HA/M2 positive cells after 16h of infection. This is a multicycle scnario so in a second round they would measure the effect of knockdown in absence of amonium chloride. Shorter infections up to 8h with higher MOI would overcome this problem.
• Standard error of mean is not an appropriate way of representing experimental error for the provided results and should be replaced by SD. Correct labeling of axis with units is required.

Minor comments:

• The authors show a rescue of viral replication upon double knockdown of RAB11A and B. Maybe this is just a consequence of inefficient knockdown since only half of the siRNAs were used?
• Specific experimental issues that are easily addressable.
• Are prior studies referenced appropriately?
• Are the text and figures clear and accurate?
• Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

Significance

The authors claim an H3N2 specific dependency on RAB11B for early steps of infection. While this is per se interesting the provided data do not fully support the claims and lack a mechanistic explanation. What is the difference between H1 and H3 strains (virion shape, HA load per virion, attachment force of H1 vs H3). The readouts used are not close enough to the events with regards to timing and could be supported by established entry assays 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

Summary:

In this manuscript, Turner AH. et al. demonstrated the viral replication in cells depleting Rab11B small GTPase, which is a paralogue of Rab11A. It has been reported that Rab11A is responsible for the intracellular transport of viral RNP via recycling endosomes. The authors showed that Rab11B knockdown reduced the viral protein expression and viral titer. This may be caused by reduced attachment of viral particles on Rab11B knockdown cells.

Major comments:

Comment 1 Fig 2-4: The authors should provide Western blot results with equal amount of loading control (GAPDH). The bands shown in these figures lack quantifiability and are not reliable as data.

Comment 2 Fig 2-4: Why are the results different between Rab11B knockdown alone and Rab11A/B double knockdown? If the authors claims are correct, the results of Rab11B knockdown should be reproducible in Rab11A/B double knockdown cells.

Comment 3 Fig 6: For better understanding, please provide a schematic illustration of experimental setting.

Comment 4: It is necessary to test other siRNA sequences or perform a rescue experiment by expressing an siRNA-resistant clone in the knockdown cells. There seems to be an activation of host defense system, such as IFN pathways.

Referees cross-commenting

I agree with other reviewers' comments in part.

Significance

The authors propose a novel role for Rab11B in modulating attachment pathway of H3N2 influenza A virus by unknown mechanism. Although previous studies focus on the function of Rab11A on endocytic transport, the function and specificity of Rab11B has remained less clear. The findings may be of interest to a broad audience, including researchers in cell biology, immunology, and host-pathogen interactions. However, the study remains at a superficial level of analysis and does not lead to a deeper understanding of the underlying mechanisms.

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

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Reply to the reviewers

We will provide the revised manuscript as a PDF with highlighted changes, the Word file with tracked changes linked to reviewer comments, and all updated figures.

To address the reviewers' suggestions, we have conducted additional experiments that are now incorporated into new figures, or we have added new images to several existing figures where appropriate.

Please note that all figures have been renumbered to improve clarity and facilitate cross-referencing throughout the text. As recommended by Referee #3, all figure legends have been thoroughly revised to reflect these updates and are now labeled following the standard A-Z panel format, enhancing readability and ensuring easier identification. In addition, all figure legends now include the sample size for each statistical analysis.

For clarity and ease of reference, we provide below a comprehensive list of all figures included in the revised version. Figures that have undergone modifications are underlined.

Figure 1____. The first spermatogenesis wave in prepuberal mice.

This figure now includes amplified images of representative spermatocytes and a summary schematic illustrating the timeline of spermatogenesis. In addition, it now presents the statistical analysis of spermatocyte quantification to support the visual data.

__Figure 2.____ Cilia emerge across all stages of prophase I in spermatocytes during the first spermatogenesis wave. __

The images of this figure remain unchanged from the original submission, but all the graphs present now the statistical analysis of spermatocyte quantification.

Figure 3. Ultrastructure and markers of prepuberal meiotic cilia.

This figure remains unchanged from the original submission; however, we have replaced the ARL3-labelled spermatocyte image (A) with one displaying a clearer and more representative signal.

__Figure 4. Testicular tissue presents spermatocyte cysts in prepuberal mice and adult humans. __

This figure remains unchanged from the original submission.

__Figure 5. Cilia and flagella dynamics are correlated during prepuberal meiosis. __

This figure remains unchanged from the original submission.

__Figure 6. Comparative proteomics identifies potential regulators of ciliogenesis and flagellogenesis. __

This figure remains unchanged from the original submission.

Figure 7.____ Deciliation induces persistence of DNA damage in meiosis.

This figure has been substantially revised and now includes additional experiments analyzing chloral hydrate treatment, aimed at more accurately assessing DNA damage under both control and treated conditions. Images F-I and graph J are new.

Figure 8____. Aurora kinase A is a regulator of cilia disassembly in meiosis.

This figure is remodelled as the original version contained a mistake in previous panel II, for this, graph in new Fig.8 I has been corrected. In addition, it now contains additional data of αTubulin staining in arrested ciliated metaphases I after AURKA inhibition (new panel L1´).

__Figure 9. Schematic representation of the prepuberal versus adult seminiferous epithelium. __

This figure remains unchanged from the original submission.

__Supplementary Figure 1. Meiotic stages during the first meiotic wave. __

This figure remains unchanged from the original submission.

__Supplementary Figure 2 (new)____. __

This is a new figure that includes additional data requested by the reviewers. It includes additional markers of cilia in spermatocytes (glutamylated Tubulin/GT335), and the control data of cilia markers in non-ciliated spermatocytes. It also includes now the separated quantification of ciliated spermatocytes for each stage, as requested by reviewers, complementing graphs included in Figure 2.

Please note that with the inclusion of this new Supplementary Figure 2, the numbering of subsequent supplementary figures has been updated accordingly.

Supplementary Figure 3 (previously Suppl. Fig. 2)__. Ultrastructure of prophase I spermatocytes. __

This figure is equal in content to the original submission, but some annotations have been included.

Supplementary Figure 4 (previously Suppl. Fig. 3).__ Meiotic centrosome under the electron microscope. __

This figure remains unchanged from the original submission, but additional annotations have been included.

Supplementary Figure 5 (previously Suppl. Fig. 4)__. Human testis contains ciliated spermatocytes. __

This figure has been revised and now includes additional H2AX staining to better determine the stage of ciliated spermatocytes and improve their identification.

Supplementary Figure 6 (previously Suppl. Fig. 5). GLI1 and GLI3 readouts of Hedgehog signalling are not visibly affected in prepuberal mouse testes.

This figure has been remodeled and now includes the quantification of GLI1 and GLI3 and its corresponding statistical analysis. It also includes the control data for Tubulin, instead of GADPH.

Supplementary Figure 7 (previously Suppl. Fig. 6)__. CH and MLN8237 optimization protocol. __

This figure has been remodeled to incorporate control experiments using 1-hour organotypic culture treatment.

Supplementary Figure 8 (previously Suppl. Fig. 7)__. Tracking first meiosis wave with EdU pulse injection during prepubertal meiosis. __This figure remains unchanged from the original submission.

Supplementary Figure 9 (previously Suppl. Fig. 8)__. PLK1 and AURKA inhibition in cultured spermatocytes. __

This figure has been remodeled and now includes additional data on spindle detection in control and AURKA-inhibited spermatocytes (both ciliated and non ciliated).

__Response to the reviewers __

We will submit both the PDF version of the revised manuscript and the Word file with tracked changes relative to the original submission. Each modification made in response to reviewers' suggestions is annotated in the Word document within the corresponding section of the text.

A detailed, point-by-point response to each reviewer's comments is provided in the following section.

Response to the Referee #1

In this manuscript by Perez-Moreno et al., titled "The dynamics of ciliogenesis in prepubertal mouse meiosis reveal new clues about testicular maturation during puberty", the authors characterize the development of primary cilia during meiosis in juvenile male mice. The authors catalog a variety of testicular changes that occur as juvenile mice age, such as changes in testis weight and germ cell-type composition. They next show that meiotic prophase cells initially lack cilia, and ciliated meiotic prophase cells are detected after 20 days postpartum, coinciding with the time when post-meiotic spermatids within the developing testes acquire flagella. They describe that germ cells in juvenile mice harbor cilia at all substages of meiotic prophase, in contrast to adults where only zygotene stage meiotic cells harbor cilia. The authors also document that cilia in juvenile mice are longer than those in adults. They characterize cilia composition and structure by immunofluorescence and EM, highlighting that cilia polymerization may initially begin inside the cell, followed by extension beyond the cell membrane. Additionally, they demonstrate ciliated cells can be detected in adult human testes. The authors next perform proteomic analyses of whole testes from juvenile mice at multiple ages, which may not provide direct information about the extremely small numbers of ciliated meiotic cells in the testis, and is lacking follow up experiments, but does serve as a valuable resource for the community. Finally, the authors use a seminiferous tubule culturing system to show that chemical inhibition of Aurora kinase A likely inhibits cilia depolymerization upon meiotic prophase I exit and leads to an accumulation of metaphase-like cells harboring cilia. They also assess meiotic recombination progression using their culturing system, but this is less convincing.

Author response: We sincerely thank Ref #1 for the thorough and thoughtful evaluation of our manuscript. We are particularly grateful for the reviewer's careful reading and constructive feedback, which have helped us refine several sections of the text and strengthen our discussion. All comments and suggestions have been carefully considered and addressed, as detailed below.

__Major comments: __

1. There are a few issues with the experimental set up for assessing the effects of cilia depolymerization on DNA repair (Figure 7-II). First, how were mid pachytene cells identified and differentiated from early pachytene cells (which would have higher levels of gH2AX) in this experiment? I suggest either using H1t staining (to differentiate early/mid vs late pachytene) or the extent of sex chromosome synapsis. This would ensure that the authors are comparing similarly staged cells in control and treated samples. Second, what were the gH2AX levels at the starting point of this experiment? A more convincing set up would be if the authors measure gH2AX immediately after culturing in early and late cells (early would have higher gH2AX, late would have lower gH2AX), and then again after 24hrs in late cells (upon repair disruption the sampled late cells would have high gH2AX). This would allow them to compare the decline in gH2AX (i.e., repair progression) in control vs treated samples. Also, it would be informative to know the starting gH2AX levels in ciliated vs non-ciliated cells as they may vary.

Response:

We thank Ref #1 for this valuable comment, which significantly contributed to improving both the design and interpretation of the cilia depolymerization assay.

Following this suggestion, we repeated the experiment including 1-hour (immediately after culturing), and 24-hour cultures for both control and chloral hydrate (CH)-treated samples (n = 3 biological replicates). To ensure accurate staging, we now employ triple immunolabelling for γH2AX, SYCP3, and H1T, allowing clear distinction of zygotene (H1T−), early pachytene (H1T−), and late pachytene (H1T+) cells. The revised data (Figure 7) now provide a more complete and statistically robust analysis of DNA damage dynamics. These results confirm that CH-induced deciliation leads to persistence of the γH2AX signal at 24 hours, indicating impaired DNA repair progression in pachytene spermatocytes. The new images and graphs are included in the revised Figure 7.

Regarding the reviewer's final point about the comparison of γH2AX levels between ciliated and non-ciliated cells, we regret that direct comparison of γH2AX levels between ciliated and non-ciliated cells is not technically feasible. To preserve cilia integrity, all cilia-related imaging is performed using the squash technique, which maintains the three-dimensional structure of the cilia but does not allow reliable quantification of DNA damage markers due to nuclear distortion. Conversely, the nuclear spreading technique, used for DNA damage assessment, provides optimal visualization of repair foci but results in the loss of cilia due to cytoplasmic disruption during the hypotonic step. Given that spermatocytes in juvenile testes form developmentally synchronized cytoplasmic cysts, we consider that analyzing a statistically representative number of spermatocytes offers a valid and biologically meaningful measure of tissue-level effects.

In conclusion, we believe that the additional experiments and clarifications included in revised Figure 7 strengthen our conclusion that cilia depolymerization compromises DNA repair during meiosis. Further functional confirmation will be pursued in future works, since we are currently generating a conditional genetic model for a ciliopathy in our laboratory.

The authors analyze meiotic progression in cells cultured with/without AURKA inhibition in Figure 8-III and conclude that the distribution of prophase I cells does not change upon treatment. Is Figure 8-III A and B the same data? The legend text is incorrect, so it's hard to follow. Figure 8-III A shows a depletion of EdU-labelled pachytene cells upon treatment. Moreover, the conclusion that a higher proportion of ciliated zygotene cells upon treatment (Figure 8-II C) suggests that AURKA inhibition delays cilia depolymerization (page 13 line 444) does not make sense to me.

Response:

We thank Ref#1 for identifying this issue and for the careful examination of Figure 8. We discovered that the submitted version of Figure 8 contained a mismatch between the figure legend and the figure panels. The legend text was correct; however, the figure inadvertently included a non-corresponding graph (previously panel II-A), which actually belonged to Supplementary Figure 7 in the original submission. We apologize for this mistake.

This error has been corrected in the revised version. The updated Figure 8 now accurately presents the distribution of EdU-labelled spermatocytes across prophase I substages in control and AURKA-inhibited cultures (previously Figure 8-II B, now Figure 8-A). The corrected data show no significant differences in the proportions of EdU-labelled spermatocytes among prophase I substages after 24 hours of AURKA inhibition, confirming that meiotic progression is not delayed and that no accumulation of zygotene cells occurs under this treatment. Therefore, the observed increase in ciliated zygotene spermatocytes upon AURKA inhibition (new Figure 8 H-I) is best explained by a delay in cilia disassembly, rather than by an arrest or slowdown in meiotic progression. The figure legend and main text have been revised accordingly.

How do the authors know that there is a monopolar spindle in Figure 8-IV treated samples? Perhaps the authors can use a different Tubulin antibody (that does not detect only acetylated Tubulin) to show that there is a monopolar spindle.

Response:

We appreciate Ref#1 for this excellent suggestion. In the original submission (lines 446-447), we described that ciliated metaphase I spermatocytes in AURKA-inhibited samples exhibited monopolar spindle phenotypes. This description was based on previous reports showing that AURKA or PLK1 inhibition produces metaphases with monopolar spindles characterized by aberrant yet characteristic SYCP3 patterns, abnormal chromatin compaction, and circular bivalent alignment around non-migrated centrosomes (1). In our study, we observed SYCP3 staining consistent with these characteristic features of monopolar metaphases I.

However, we agree with Ref #1 that this could be better sustained with data. Following the reviewer's suggestion, we performed additional immunostaining using α-Tubulin, which labels total microtubules rather than only the acetylated fraction. For clarity purposes, the revised Figure 8 now includes α-Tubulin staining in the same ciliated metaphase I cells shown in the original submission, confirming the presence of defective microtubule polymerization and defective spindle organization. For clarity, we now refer to these ciliated metaphases I as "arrested MI". This new data further support our conclusion that AURKA inhibition disrupts spindle bipolarization and prevents cilia depolymerization, indicating that cilia maintenance and bipolar spindle organization are mechanistically incompatible events during male meiosis. The abstract, results, and discussion section has been expanded accordingly, emphasizing that the persistence of cilia may interfere with microtubule polymerization and centrosome separation under AURKA inhibition. The Discussion has been expanded to emphasize that persistence of cilia may interfere with centrosome separation and microtubule polymerization, contrasting with invertebrate systems -e.g. Drosophila (2) and P. brassicae (3)- in which meiotic cilia persist through metaphase I without impairing bipolar spindle assembly.

1. Alfaro, et al. EMBO Rep 22, (2021). DOI: 15252/embr.202051030 (PMID: 33615693)
2. Riparbelli et al . Dev Cell (2012) DOI: 1016/j.devcel.2012.05.024 (PMID: 22898783)
3. Gottardo et al, Cytoskeleton (Hoboken) (2023) DOI: 1002/cm.21755 (PMID: 37036073)

The authors state in the abstract that they provide evidence suggesting that centrosome migration and cilia depolymerization are mutually exclusive events during meiosis. This is not convincing with the data present in the current manuscript. I suggest amending this statement in the abstract.

Response:

We thank Ref#1 for this valuable observation, with which we fully agree. To avoid overstatement, the original statement has been removed from the Abstract, Results, and Discussion, and replaced with a more accurate formulation indicating that cilia maintenance and bipolar spindle formation are mutually exclusive events during mouse meiosis.

This revised statement is now directly supported by the new data presented in Figure 8, which demonstrate that AURKA inhibition prevents both spindle bipolarization and cilia depolymerization. We are grateful to the reviewer for highlighting this important clarification.

Minor comments:

The presence of cilia in all stages of meiotic prophase I in juvenile mice is intriguing. Why is the cellular distribution and length of cilia different in prepubertal mice compared to adults (where shorter cilia are present only in zygotene cells)? What is the relevance of these developmental differences? Do cilia serve prophase I functions in juvenile mice (in leptotene, pachytene etc.) that are perhaps absent in adults?

Related to the above point, what is the relevance of the absence of cilia during the first meiotic wave? If cilia serve a critical function during prophase I (for instance, facilitating DSB repair), does the lack of cilia during the first wave imply differing cilia (and repair) requirements during the first vs latter spermatogenesis waves?

In my opinion, these would be interesting points to discuss in the discussion section.

Response:

We thank the reviewer for these thoughtful observations, which we agree are indeed intriguing.

We believe that our findings likely reflect a developmental role for primary cilia during testicular maturation. We hypothesize that primary cilia at this stage might act as signaling organelles, receiving cues from Sertoli cells or neighboring spermatocytes and transmitting them through the cytoplasmic cysts shared by spermatocytes. Such intercellular communication could be essential for coordinating tissue maturation and meiotic entry during puberty. Although speculative, this hypothesis aligns with the established role of primary cilia as sensory and signaling hubs for GPCR and RTK pathways regulating cell differentiation and developmental patterning in multiple tissues (e.g., 1, 2). The Discussion section has been expanded to include these considerations.

1. Goetz et al, Nat Rev Genet (2010)- DOI: 1038/nrg2774 (PMID: 20395968)
2. Naturky et al , Cell (2019) DOI: 1038/s41580-019-0116-4 (PMID: 30948801) Our study focuses on the first spermatogenic wave, which represents the transition from the juvenile to the reproductive phase. It is therefore plausible that the transient presence of longer cilia during this period reflects a developmental requirement for external signaling that becomes dispensable in the mature testis. Given that this is only the second study to date examining mammalian meiotic cilia, there remains a vast area of research to explore. We plan to address potential signaling cascades involved in these processes in future studies.

On the other hand, while we cannot confirm that the cilia observed in zygotene spermatocytes persist until pachytene within the same cell, it is reasonable to speculate that they do, serving as longer-lasting signaling structures that facilitate testicular development during the critical pubertal window. In addition, the observation of ciliated spermatocytes at all prophase I substages at 20 dpp, together with our proteomic data, supports the idea that the emergence of meiotic cilia exerts a significant developmental impact on testicular maturation.

In summary, although we cannot yet define specific prophase I functions for meiotic cilia in juvenile spermatocytes, our data demonstrate that the first meiotic wave differs from later waves in cilia dynamics, suggesting distinct regulatory requirements between puberty and adulthood. These findings underscore the importance of considering developmental context when using the first meiotic wave as a model for studying spermatogenesis.

The authors state on page 9 lines 286-288 that the presence of cytoplasmic continuity via intercellular bridges (between developmentally synchronous spermatocytes) hints towards a mechanism that links cilia and flagella formation. Please clarify this statement. While the correlation between the timing of appearance of cilia and flagella in cells that are located within the same segment of the seminiferous tubule may be hinting towards some shared regulation, how would cytoplasmic continuity participate in this regulation? Especially since the cytoplasmic continuity is not between the developmentally distinct cells acquiring the cilia and flagella?

Response:

We thank Ref#1 for this excellent question and for the opportunity to clarify our statement.

The presence of intercellular bridges between spermatocytes is well known and has long been proposed to support germ cell communication and synchronization (1,2) as well as sharing mRNA (3) and organelles (4). A classic example is the Akap gene, located on the X chromosome and essential for the formation of the sperm fibrous sheath; cytoplasmic continuity through intercellular bridges allows Akap-derived products to be shared between X- and Y-bearing spermatids, thereby maintaining phenotypic balance despite transcriptional asymmetry (5). In addition, more recent work has further demonstrated that these bridges are critical for synchronizing meiotic progression and for processes such as synapsis, double-strand break repair, and transposon repression (6).

In this context, and considering our proteomic data (Figure 6), our statement did not intend to imply direct cytoplasmic exchange between ciliated and flagellated cells. Although our current methods do not allow comprehensive tracing of cytoplasmic continuity from the basal to the luminal compartment of the seminiferous epithelium, we plan to address this limitation using high-resolution 3D and ultrastructural imaging approaches in future studies.

Based on our current data, we propose that cytoplasmic continuity within developmentally synchronized spermatocyte cysts could facilitate the coordinated regulation of ciliogenesis, and similarly enable the sharing of regulatory factors controlling flagellogenesis within spermatid cysts. This coordination may occur through the diffusion of centrosomal or ciliary proteins, mRNAs, or signaling intermediates involved in the regulation of microtubule dynamics. However, we cannot exclude the possibility that such cytoplasmic continuity extends across all spermatocytes derived from the same spermatogonial clone, potentially providing a larger regulatory network.]] This mechanism could help explain the temporal correlation we observe between the appearance of meiotic cilia and the onset of flagella formation in adjacent spermatids within the same seminiferous segment.

We have revised the Discussion to explicitly clarify this interpretation and to note that, although hypothetical, it is consistent with established literature on cytoplasmic continuity and germ cell coordination.

1. Dym, et al. * Reprod.*(1971) DOI: 10.1093/biolreprod/4.2.195 (PMID: 4107186)
2. Braun et al. Nature. (1989) DOI: 1038/337373a0 (PMID: 2911388)
3. Greenbaum et al. * Natl. Acad. Sci. USA*(2006). DOI: 10.1073/pnas.0505123103 (PMID: 16549803)
4. Ventelä et al. Mol Biol Cell. (2003) DOI: 1091/mbc.e02-10-0647 (PMID: 12857863)
5. Turner et al. Journal of Biological Chemistry (1998). DOI: 1074/jbc.273.48.32135 (PMID: 9822690)
6. Sorkin, et al. Nat Commun (2025). DOI: 1038/s41467-025-56742-9 (PMID: 39929837)
7. *note: due to manuscript-length limitations, not all cited references can be included in the text; they are listed here to substantiate our response.*

Individual germ cells in H&E-stained testis sections in Figure 1-II are difficult to see. I suggest adding zoomed-in images where spermatocytes/round spermatids/elongated spermatids are clearly distinguishable.

Response:

Ref#1 is very right in this suggestion. We have revised Figure 1 to improve the quality of the H&E-stained testis sections and have added zoomed-in panels where spermatocytes, round spermatids, and elongated spermatids are clearly distinguishable. These additions significantly enhance the clarity and interpretability of the figure.

In Figure 2-II B, the authors document that most ciliated spermatocytes in juvenile mice are pachytene. Is this because most meiotic cells are pachytene? Please clarify. If the data are available (perhaps could be adapted from Figure 1-III), it would be informative to see a graph representing what proportions of each meiotic prophase substages have cilia.

Response:

We thank the reviewer for this valuable observation. Indeed, the predominance of ciliated pachytene spermatocytes reflects the fact that most meiotic cells in juvenile testes are at the pachytene stage (Figure 1). We have clarified this point in the text and have added a new supplementary figure (Supplementary Figure 2, new figure) presenting a graph showing the proportion of spermatocytes at each prophase I substage that possess primary cilia. This visualization provides a clearer quantitative overview of ciliation dynamics across meiotic substages.

I suggest annotating the EM images in Sup Figure 2 and 3 to make it easier to interpret.

Response:

We thank the reviewer for this helpful suggestion. We have now added annotations to the EM images in Supplementary Figures 3 and 4 to facilitate their interpretation. These visual guides help readers more easily identify the relevant ultrastructural features described in the text.

The authors claim that the ratio between GLI3-FL and GLI3-R is stable across their analyzed developmental window in whole testis immunoblots shown in Sup Figure 5. Quantifying the bands and normalizing to the loading control would help strengthen this claim as it hard to interpret the immunoblot in its current form.

Response:

We thank the reviewer for this valuable suggestion. Following this recommendation, Supplementary Figure 5 has been revised to include quantification of GLI1 and GLI3 protein levels, normalized to the loading control.

After quantification, we observed statistically significant differences across developmental stages. Specifically, GLI1 expression is slightly higher at 21 dpp compared to 8 dpp. For GLI3, we performed two complementary analyses:

• Total GLI3 protein (sum of full-length and repressor forms normalized to loading control) shows a progressive decrease during development, with the lowest levels at 60 dpp (Supplementary Figure 5D).
• GLI3 activation status, assessed as the GLI3-FL/GLI3-R ratio, is highest during the 19-21 dpp window, compared to 8 dpp and 60 dpp. Although these results suggest a possible transient activation of GLI3 during testicular maturation, we caution that this cannot automatically be attributed to increased Hedgehog signaling, as GLI3 processing can also be affected by other processes, such as changes in ciliogenesis. Furthermore, because the analysis was performed on whole-testis protein extracts, these changes cannot be specifically assigned to ciliated spermatocytes.

We have expanded the Discussion to address these findings and to highlight the potential involvement of the Desert Hedgehog (DHH) pathway, which plays key roles in testicular development, Sertoli-germ cell communication, and spermatogenesis (1, 2, 3). We plan to investigate these pathways further in future studies.

1. Bitgood et al. Curr Biol. (1996). DOI: 1016/s0960-9822(02)00480-3 (PMID: 8805249)
2. Clark et al. Biol Reprod. (2000) DOI: 1095/biolreprod63.6.1825 (PMID: 11090455)
3. O'Hara et al. BMC Dev Biol. (2011) DOI: 1186/1471-213X-11-72 (PMID: 22132805) *note: due to manuscript-length limitations, not all cited references can be included in the text; they are listed here to substantiate our response.

There are a few typos throughout the manuscript. Some examples: page 5 line 172, Figure 3-I legend text, Sup Figure 5-II callouts, Figure 8-III legend, page 15 line 508, page 17 line 580, page 18 line 611.

Response:

We thank the reviewer for detecting this. All typographical errors have been corrected, and figure callouts have been reviewed for consistency.

__ ____Response to the Referee #2__

__ __This study focuses on the dynamic changes of ciliogenesis during meiosis in prepubertal mice. It was found that primary cilia are not an intrinsic feature of the first wave of meiosis (initiating at 8 dpp); instead, they begin to polymerize at 20 dpp (after the completion of the first wave of meiosis) and are present in all stages of prophase I. Moreover, prepubertal cilia (with an average length of 21.96 μm) are significantly longer than adult cilia (10 μm). The emergence of cilia coincides temporally with flagellogenesis, suggesting a regulatory association in the formation of axonemes between the two. Functional experiments showed that disruption of cilia by chloral hydrate (CH) delays DNA repair, while the AURKA inhibitor (MLN8237) delays cilia disassembly, and centrosome migration and cilia depolymerization are mutually exclusive events. These findings represent the first detailed description of the spatiotemporal regulation and potential roles of cilia during early testicular maturation in mice. The discovery of this phenomenon is interesting; however, there are certain limitations in functional research.

We thank Ref#2 for taking the time to evaluate our manuscript and for summarizing its main findings. We regret that the reviewer did not find the study sufficiently compelling, but we respectfully clarify that the strength of our work lies precisely in addressing a largely unexplored aspect of mammalian meiosis for which virtually no prior data exist. Given the extremely limited number of studies addressing cilia in mammalian meiosis (only five to date, including our own previous publication on adult mouse spermatogenesis) (1-5), we consider that the present work provides the first robust and integrative evidence on the emergence, morphology, and potential roles of primary cilia during prepubertal testicular development. The study combines histology, high-resolution microscopy, proteomics, and pharmacological perturbations, supported by quantitative analyses, thereby establishing a solid and much-needed reference framework for future functional studies.

We emphasize that this manuscript constitutes the first comprehensive characterization of ciliogenesis during prepubertal mouse meiosis, complemented by functional in vitro assays that begin to address potential roles of these cilia. For this reason, we want to underscore the importance of this study in providing a solid framework that will support and guide future research

Major points:

1. The prepubertal cilia in spermatocytes discovered by the authors lack specific genetic ablation to block their formation, making it impossible to evaluate whether such cilia truly have functions. Because neither in the first wave of spermatogenesis nor in adult spermatogenesis does this type of cilium seem to be essential. In addition, the authors also imply that the formation of such cilia appears to be synchronized with the formation of sperm flagella. This suggests that the production of such cilia may merely be transient protein expression noise rather than a functionally meaningful cellular structure.

Response:

We agree that a genetic ablation model would represent the ideal approach to directly test cilia function in spermatogenesis. However, given the complete absence of prior data describing the dynamics of ciliogenesis during testis development, our priority in this study was to establish a rigorous structural and temporal characterization of this process in the main mammalian model organism, the mouse. This systematic and rigorous phenotypic characterization is a necessary first step before any functional genetics could be meaningfully interpreted.

To our knowledge, this study represents the first comprehensive analysis of ciliogenesis during prepubertal mouse meiosis, extending our previous work on adult spermatogenesis (1). Beyond these two contributions, only four additional studies have addressed meiotic cilia-two in zebrafish (2, 3), with Mytlys et al. also providing preliminary observations relevant to prepubertal male meiosis that we discuss in the present work, one in Drosophila (4) and a recent one in butterfly (5). No additional information exists for mammalian gametogenesis to date.

1. López-Jiménez et al. Cells (2022) DOI: 10.3390/cells12010142 (PMID: 36611937)
2. Mytlis et al. Science (2022) DOI: 10.1126/science.abh3104 (PMID: 35549308)
3. Xie et al. J Mol Cell Biol (2022) DOI: 10.1093/jmcb/mjac049 (PMID: 35981808)
4. Riparbelli et al . Dev Cell (2012) DOI: 10.1016/j.devcel.2012.05.024 (PMID: 22898783)
5. Gottardo et al, Cytoskeleton (Hoboken) (2023) DOI: 10.1002/cm.21755 (PMID: 37036073) We therefore consider this descriptive and analytical foundation to be essential before the development of functional genetic models. Indeed, we are currently generating a conditional genetic model for a ciliopathy in our laboratory. These studies are ongoing and will directly address the type of mechanistic questions raised here, but they extend well beyond the scope and feasible timeframe of the present manuscript.

We thus maintain that the present work constitutes a necessary and timely contribution, providing a robust reference dataset that will facilitate and guide future functional studies in the field of cilia and meiosis.

Taking this into account, we would be very pleased to address any additional, concrete suggestions from Ref#2 that could further strengthen the current version of the manuscript

The high expression of axoneme assembly regulators such as TRiC complex and IFT proteins identified by proteomic analysis is not particularly significant. This time point is precisely the critical period for spermatids to assemble flagella, and TRiC, as a newly discovered component of flagellar axonemes, is reasonably highly expressed at this time. No intrinsic connection with the argument of this paper is observed. In fact, this testicular proteomics has little significance.

Response:

We appreciate this comment but respectfully disagree with the reviewer's interpretation of our proteomic data. To our knowledge, this is the first proteomic study explicitly focused on identifying ciliary regulators during testicular development at the precise window (19-21 dpp) when both meiotic cilia and spermatid flagella first emerge.

While Piprek et al (1) analyzed the expression of primary cilia in developing gonads, proteomic data specifically covering the developmental transition at 19-21 dpp were not previously available. Furthermore, a recent cell-sorting study (2), detected expression of cilia proteins in pachytene spermatocytes compared to round spermatids, but did not explore their functional relevance or integrate these data with developmental timing or histological context.

In contrast, our dataset integrates histological staging, high-resolution microscopy, and quantitative proteomics, revealing a set of candidate regulators (including DCAF7, DYRK1A, TUBB3, TUBB4B, and TRiC) potentially involved in cilia-flagella coordination. We view this as a hypothesis-generating resource that outlines specific proteins and pathways for future mechanistic studies on both ciliogenesis and flagellogenesis in the testis.

Although we fully agree that proteomics alone cannot establish causal function, we believe that dismissing these data as having little significance overlooks their value as the first molecular map of the testis at the developmental window when axonemal structures arise. Our dataset provides, for the first time, an integrated view of proteins associated with ciliary and flagellar structures at the developmental stage when both axonemal organelles first appear. We thus believe that our proteomic dataset represents an important and novel contribution to the understanding of testicular development and ciliary biology.

Considering this, we would again welcome any specific suggestions from Ref#2 on additional analyses or clarifications that could make the relevance of this dataset even clearer to readers.

1. Piprek et al. Int J Dev Biol. (2019) doi: 10.1387/ijdb.190049rp (PMID: 32149371).
2. Fang et al. Chromosoma. (1981) doi: 10.1007/BF00285768 (PMID: 7227045).

Response to the Referee #3

In "The dynamics of ciliogenesis in prepubertal mouse meiosis reveals new clues about testicular development" Pérez-Moreno, et al. explore primary cilia in prepubertal mouse spermatocytes. Using a combination of microscopy, proteomics, and pharmacological perturbations, the authors carefully characterize prepubertal spermatocyte cilia, providing foundational work regarding meiotic cilia in the developing mammalian testis.

Response: We sincerely thank Ref#3 for their positive assessment of our work and for the thoughtful suggestions that have helped us strengthen the manuscript. We are pleased that the reviewer recognizes both the novelty and the relevance of our study in providing foundational insights into meiotic ciliogenesis during prepubertal testicular development. All specific comments have been carefully considered and addressed as detailed below.

Major concerns:

1. The authors provide evidence consistent with cilia not being present in a larger percentage of spermatocytes or in other cells in the testis. The combination of electron microscopy and acetylated tubulin antibody staining establishes the presence of cilia; however, proving a negative is challenging. While acetylated tubulin is certainly a common marker of cilia, it is not in some cilia such as those in neurons. The authors should use at least one additional cilia marker to better support their claim of cilia being absent.

Response:

We thank the reviewer for this helpful suggestion. In the revised version, we have strengthened the evidence for cilia identification by including an additional ciliary marker, glutamylated tubulin (GT335), in combination with acetylated tubulin and ARL13B (which were included in the original submission). These data are now presented in the new Supplementary Figure 2, which also includes an example of a non-ciliated spermatocyte showing absence of both ARL13B and AcTub signals.

Taken together, these markers provide a more comprehensive validation of cilia detection and confirm the absence of ciliary labelling in non-ciliated spermatocytes.

The conclusion that IFT88 localizes to centrosomes is premature as key controls for the IFT88 antibody staining are lacking. Centrosomes are notoriously "sticky", often sowing non-specific antibody staining. The authors must include controls to demonstrate the specificity of the staining they observe such as staining in a genetic mutant or an antigen competition assay.

Response:

We appreciate the reviewer's concern and fully agree that antibody specificity is critical when interpreting centrosomal localization. The IFT88 antibody used in our study is commercially available and has been extensively validated in the literature as both a cilia marker (1, 2), and a centrosome marker in somatic cells (3). Labelling of IFT88 in centrosomes has also been previously described using other antibodies (4, 5). In our material, the IFT88 signal consistently appears at one of the duplicated centrosomes and at both spindle poles-patterns identical to those reported in somatic cells. We therefore consider the reported meiotic IFT88 staining as specific and biologically reliable.

That said, we agree that genetic validation would provide the most definitive confirmation. We would like to inform that we are currently since we are currently generating a conditional genetic model for a ciliopathy in our laboratory that will directly assess both antibody specificity and functional consequences of cilia loss during meiosis. These experiments are in progress and will be reported in a follow-up study.

1. Wong et al. Science (2015). DOI: 1126/science.aaa5111 (PMID: 25931445)
2. Ocbina et al. Nat Genet (2011). DOI: 1038/ng.832 (PMID: 21552265)
3. Vitre et al. EMBO Rep (2020). DOI: 15252/embr.201949234 (PMID: 32270908)
4. Robert A. et al. J Cell Sci (2007). DOI: 1242/jcs.03366 (PMID: 17264151)
5. Singla et al, Developmental Cell (2010). DOI: 10.1016/j.devcel.2009.12.022 (PMID: 20230748) *note: due to manuscript-length limitations, not all cited references can be included in the text; they are listed here to substantiate our response.

There are many inconsistent statements throughout the paper regarding the timing of the first wave of spermatogenesis. For example, the authors state that round spermatids can be detected at 21dpp on line 161, but on line 180, say round spermatids can be detected a 19dpp. Not only does this lead to confusion, but such discrepancies undermine the validity of the rest of the paper. A summary graphic displaying key events and their timing in the first wave of spermatogenesis would be instrumental for reader comprehension and could be used by the authors to ensure consistent claims throughout the paper.

Response:

We thank the reviewer for identifying this inconsistency and apologize for the confusion. We confirm that early round spermatids first appear at 19 dpp, as shown in the quantitative data (Figure 1J). This can be detected in squashed spermatocyte preparations, where individual spermatocytes and spermatids can be accurately quantified. The original text contained an imprecise reference to the histological image of 21 dpp (previous line 161), since certain H&E sections did not clearly show all cell types simultaneously. However, we have now revised Figure 1, improving the image quality and adding a zoomed-in panel highlighting early round spermatids. Image for 19 dpp mice in Fig 1D shows early, yet still aflagellated spermatids. The first ciliated spermatocytes and the earliest flagellated spermatids are observed at 20 dpp. This has been clarified in the text.

In addition, we also thank the reviewer for the suggestion of adding a summary graphic, which we agree greatly facilitates reader comprehension. We have added a new schematic summary (Figure 1K) illustrating the key stages and timing of the first spermatogenic wave.

In the proteomics experiments, it is unclear why the authors assume that changes in protein expression are predominantly due to changes within the germ cells in the developing testis. The analysis is on whole testes including both the somatic and germ cells, which makes it possible that protein expression changes in somatic cells drive the results. The authors need to justify why and how the conclusions drawn from this analysis warrant such an assumption.

Response:

We agree with the reviewer that our proteomic analysis was performed on whole testis samples, which contain both germ and somatic cells. Although isolation of pure spermatocyte populations by FACS would provide higher resolution, obtaining sufficient prepubertal material for such analysis would require an extremely large number of animals. To remain compliant with the 3Rs principle for animal experimentation, we therefore used whole-testis samples from three biological replicates per age.

We acknowledge that our assumption-that the main differences arise from germ cells-is a simplification. However, germ cells constitute the vast majority of testicular cells during this developmental window and are the population undergoing major compositional changes between 15 dpp and adulthood. It is therefore reasonable to expect that a substantial fraction of the observed proteomic changes reflects alterations in germ cells. We have clarified this point in the revised text and have added a statement noting that changes in somatic cells could also contribute to the proteomic profiles.

The authors should provide details on how proteins were categorized as being involved in ciliogenesis or flagellogenesis, specifically in the distinction criteria. It is not clear how the categorizations were determined or whether they are valid. Thus, no one can repeat this analysis or perform this analysis on other datasets they might want to compare.

Response:

We thank the reviewer for this opportunity to clarify our approach. The categorization of protein as being involved in ciliogenesis or flagellogenesis was based on their Gene Ontology (GO) cellular component annotations obtained from the PANTHER database (Version 19.0), using the gene IDs of the Differentially Expressed Proteins (DEPs). Specifically, we used the GO terms cilium (GO:0005929) and motile cilium (GO:0031514). Since motile cilium is a subcategory of cilium, proteins annotated only with the general cilium term, but not included under motile cilium, were considered to be associated with primary cilia or with shared structural components common to different types of cilia. These GO terms are represented in the bottom panel of the Figure 6.

This information has been added to the Methods section and referenced in the Results for transparency and reproducibility.

In the pharmacological studies, the authors conclude that the phenotypes they observe (DNA damage and reduced pachytene spermatocytes) are due to loss of or persistence of cilia. This overinterprets the experiment. Chloral hydrate and MLN8237 certainly impact ciliation as claimed, but have additional cellular effects. Thus, it is possible that the observed phenotypes were not a direct result of cilia manipulation. Either additional controls must address this or the conclusions need to be more specific and toned down.

Response:

We thank the reviewer for this fair observation and have taken steps to strengthen and refine our interpretation. In the revised version, we now include data from 1-hour and 24-hour cultures for both control and chloral hydrate (CH)-treated samples (n = 3 biological replicates). The triple immunolabelling with γH2AX, SYCP3, and H1T allows accurate staging of zygotene (H1T⁻), early pachytene (H1T⁻), and late pachytene (H1T⁺) spermatocytes.

The revised Figure 7 now provides a more complete and statistically supported analysis of DNA damage dynamics, confirming that CH-induced deciliation leads to persistent γH2AX signal at 24 hours, indicative of delayed or defective DNA repair progression. We have also toned down our interpretation in the Discussion, acknowledging that CH could affect other cellular pathways.

As mentioned before, the conditional genetic model that we are currently generating will allow us to evaluate the role of cilia in meiotic DNA repair in a more direct and specific way.

Assuming the conclusions of the pharmacological studies hold true with the proper controls, the authors still conflate their findings with meiotic defects. Meiosis is not directly assayed, which makes this conclusion an overstatement of the data. The conclusions need to be rephrased to accurately reflect the data.

Response:

We agree that this aspect required clarification. As noted above, we have refined both the Results and Discussion sections to make clear that our assays specifically targeted meiotic spermatocytes.

We now present data for meiotic stages at zygotene, early pachytene and late pachytene. This is demonstrated with the labelling for SYCP3 and H1T, both specific marker for meiosis that are not detectable in non meiotic cells. We believe that this is indeed a way to assay the meiotic cells, however, we have specified now in the text that we are analysing potential defects in meiosis progression. We are sorry if this was not properly explained in the original manuscript: it is now rephrased in the new version both in the results and discussion section.

It is not clear why the authors chose not to use widely accepted assays of Hedgehog signaling. Traditionally, pathway activation is measured by transcriptional output, not GLI protein expression because transcription factor expression does not necessarily reflect transcription levels of target genes.

Response:

We agree with the reviewer that measuring mRNA levels of Hedgehog pathway target genes, typically GLI1 and PTCH1, is the most common method for measuring pathway activation, and is widely accepted by researchers in the field. However, the methods we use in this manuscript (GLI1 and GLI3 immunoblots) are also quite common and widely accepted:

Regarding GLI1 immunoblot, many articles have used this method to monitor Hedgehog signaling, since GLI1 protein levels have repeatedly been shown to also go up upon pathway activation, and down upon pathway inhibition, mirroring the behavior of GLI1 mRNA. Here are a few publications that exemplify this point:

• Banday et al. 2025 Nat Commun. DOI: 10.1038/s41467-025-56632-0 (PMID: 39894896)
• Shi et al 2022 JCI Insight DOI: 10.1172/jci.insight.149626 (PMID: 35041619)
• Deng et al. 2019 eLife, DOI: 10.7554/eLife.50208 (PMID: 31482846)
• Zhu et al. 2019 Nat Commun, DOI: 10.1038/s41467-019-10739-3 (PMID: 31253779)
• Caparros-Martin et al 2013 Hum Mol Genet, DOI: 10.1093/hmg/dds409 (PMID: 23026747) *note: due to manuscript-length limitations, not all cited references can be included in the text; they are listed here to substantiate our response.

As for GLI3 immunoblot, Hedgehog pathway activation is well known to inhibit GLI3 proteolytic processing from its full length form (GLI3-FL) to its transcriptional repressor (GLI3-R), and such processing is also commonly used to monitor Hedgehog signal transduction, of which the following are but a few examples:

• Pedraza et al 2025 eLife, DOI: 10.7554/eLife.100328 (PMID: 40956303)
• Somatilaka et al 2020 Dev Cell, DOI: 10.1016/j.devcel.2020.06.034 (PMID: 32702291)
• Infante et al 2018, Nat Commun, DOI: 10.1038/s41467-018-03339-0 (PMID: 29515120)
• Wang et al 2017 Dev Biol DOI: 10.1016/j.ydbio.2017.08.003 (PMID: 28800946)
• Singh et al 2015 J Biol Chem DOI: 10.1074/jbc.M115.665810 (PMID: 26451044)
• *note: due to manuscript-length limitations, not all cited references can be included in the text; they are listed here to substantiate our response.*

In summary, we think that we have used two well established markers to look at Hedgehog signaling (three, if we include the immunofluorescence analysis of SMO, which we could not detect in meiotic cilia).

These Hh pathway analyses did not provide any convincing evidence that the prepubertal cilia we describe here are actively involved in this pathway, even though Hh signaling is cilia-dependent and is known to be active in the male germline (Sahin et al 2014 Andrology PMID: 24574096; Mäkelä et al 2011 Reproduction PMID: 21893610; Bitgood et al 1996 Curr Biol. PMID: 8805249).

That said, we fully agree that our current analyses do not allow us to draw definitive conclusions regarding Hedgehog pathway activity in meiotic cilia, and we now state this explicitly in the revised Discussion.

Also in the Hedgehog pathway experiment, it is confusing that the authors report no detection of SMO yet detect little to no expression of GLIR in their western blot. Undetectable SMO indicates Hedgehog signaling is inactive, which results in high levels of GLIR. The impact of this is that it is not clear what is going on with Hh signaling in this system.

Response:

It is true that, when Hh signaling is inactive (and hence SMO not ciliary), the GLI3FL/GLI3R ratio tends to be low.

Although our data in prepuberal mouse testes show a strong reduction in total GLI3 protein levels (GLI3FL+GLI3R) as these mice grow older, this downregulation of total GLI3 occurs without any major changes in the GLI3FL/GLI3R ratio, which is only modestly affected (suppl. Figure 6).

Hence, since it is the ratio that correlates with Hh signaling rather than total levels, we do not think that the GLI3R reduction we see is incompatible with our non-detection of SMO in cilia: it seems more likely that overall GLI3 expression is being downregulated in developing testes via a Hh-independent mechanism.

Also potentially relevant here is the fact that some cell types depend more on GLI2 than on GLI3 for Hh signaling. For instance, in mouse embryos, Hh-mediated neural tube patterning relies more heavily on GLI2 processing into a transcriptional activator than on the inhibition of GLI3 processing into a repressor. In contrast, the opposite is true during Hh-mediated limb bud patterning (Nieuwenhuis and Hui 2005 Clin Genet. PMID: 15691355). We have not looked at GLI2, but it is conceivable that it could play a bigger role than GLI3 in our model.

Moreover, several forms of GLI-independent non-canonical Hh signaling have been described, and they could potentially play a role in our model, too (Robbins et al 2012 Sci Signal. PMID: 23074268).

We have revised the discussion to clarify some of these points.

All in all, we agree that our findings regarding Hh signaling are not conclusive, but we still think they add important pieces to the puzzle that will help guide future studies.

There are multiple instances where it is not clear whether the authors performed statistical analysis on their data, specifically when comparing the percent composition of a population. The authors need to include appropriate statistical tests to make claims regarding this data. While the authors state some impressive sample sizes, once evaluated in individual categories (eg specific cell type and age) the sample sizes of evaluated cilia are as low as 15, which is likely underpowered. The authors need to state the n for each analysis in the figures or legends.

We thank the reviewer for highlighting this important issue. We have now included the sample size (n) for every analysis directly in the figure legends. Although this adds length, it improves transparency and reproducibility.

Regarding the doubts of Ref#3 about the different sample sizes, the number of spermatocytes quantified in each stage is in agreement with their distribution in meiosis (example, pachytene lasts for 10 days this stage is widely represented in the preparations, while its is much difficult to quantify metaphases I that are less present because the stage itself lasts for less than 24hours). Taking this into account, we ensured that all analyses remain statistically valid and representative, applying the appropriate statistical tests for each dataset. These details are now clearly indicated in the revised figures and legends.

Minor concerns:

1. The phrase "lactating male" is used throughout the paper and is not correct. We assume this term to mean male pups that have yet to be weaned from their lactating mother, but "lactating male" suggests a rare disorder requiring medical intervention. Perhaps "pre-weaning males" is what the authors meant.

Response:

We thank the reviewer for noticing this terminology error. The expression has been corrected to "pre-weaning males" throughout the manuscript.

The convention used to label the figures in this paper is confusing and difficult to read as there are multiple panels with the same letter in the same figure (albeit distinct sections). Labeling panels in the standard A-Z format is preferred. "Panel Z" is easier to identify than "panel III-E".

Response:

We thank the reviewer for this suggestion. All figures have been relabelled using the standard A-Z panel format, ensuring consistency and easier readability across the manuscript.

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Referee #3

Evidence, reproducibility and clarity

Summary:

In "The dynamics of ciliogenesis in prepubertal mouse meiosis reveals new clues about testicular development" Pérez-Moreno, et al. explore primary cilia in prepubertal mouse spermatocytes. Using a combination of microscopy, proteomics, and pharmacological perturbations, the authors carefully characterize prepubertal spermatocyte cilia, providing foundational work regarding meiotic cilia in the developing mammalian testis.

Major concerns:

1. The authors provide evidence consistent with cilia not being present in a larger percentage of spermatocytes or in other cells in the testis. The combination of electron microscopy and acetylated tubulin antibody staining establishes the presence of cilia; however, proving a negative is challenging. While acetylated tubulin is certainly a common marker of cilia, it is not in some cilia such as those in neurons. The authors should use at least one additional cilia marker to better support their claim of cilia being absent.

2. The conclusion that IFT88 localizes to centrosomes is premature as key controls for the IFT88 antibody staining are lacking. Centrosomes are notoriously "sticky", often sowing non-specific antibody staining. The authors must include controls to demonstrate the specificity of the staining they observe such as staining in a genetic mutant or an antigen competition assay.

3. There are many inconsistent statements throughout the paper regarding the timing of the first wave of spermatogenesis. For example, the authors state that round spermatids can be detected at 21dpp on line 161, but on line 180, say round spermatids can be detected a 19dpp. Not only does this lead to confusion, but such discrepancies undermine the validity of the rest of the paper. A summary graphic displaying key events and their timing in the first wave of spermatogenesis would be instrumental for reader comprehension and could be used by the authors to ensure consistent claims throughout the paper.

4. In the proteomics experiments, it is unclear why the authors assume that changes in protein expression are predominantly due to changes within the germ cells in the developing testis. The analysis is on whole testes including both the somatic and germ cells, which makes it possible that protein expression changes in somatic cells drive the results. The authors need to justify why and how the conclusions drawn from this analysis warrant such an assumption.

5. The authors should provide details on how proteins were categorized as being involved in ciliogenesis or flagellogenesis, specifically in the distinction criteria. It is not clear how the categorizations were determined or whether they are valid. Thus, no one can repeat this analysis or perform this analysis on other datasets they might want to compare.

6. In the pharmacological studies, the authors conclude that the phenotypes they observe (DNA damage and reduced pachytene spermatocytes) are due to loss of or persistence of cilia. This overinterprets the experiment. Chloral hydrate and MLN8237 certainly impact ciliation as claimed, but have additional cellular effects. Thus, it is possible that the observed phenotypes were not a direct result of cilia manipulation. Either additional controls must address this or the conclusions need to be more specific and toned down.

7. Assuming the conclusions of the pharmacological studies hold true with the proper controls, the authors still conflate their findings with meiotic defects. Meiosis is not directly assayed, which makes this conclusion an overstatement of the data. The conclusions need to be rephrased to accurately reflect the data.

8. It is not clear why the authors chose not to use widely accepted assays of Hedgehog signaling. Traditionally, pathway activation is measured by transcriptional output, not GLI protein expression because transcription factor expression does not necessarily reflect transcription levels of target genes.

9. Also in the Hedgehog pathway experiment, it is confusing that the authors report no detection of SMO yet detect little to no expression of GLIR in their western blot. Undetectable SMO indicates Hedgehog signaling is inactive, which results in high levels of GLIR. The impact of this is that it is not clear what is going on with Hh signaling in this system.

10. There are multiple instances where it is not clear whether the authors performed statistical analysis on their data, specifically when comparing the percent composition of a population. The authors need to include appropriate statistical tests to make claims regarding this data. While the authors state some impressive sample sizes, once evaluated in individual categories (eg specific cell type and age) the sample sizes of evaluated cilia are as low as 15, which is likely underpowered. The authors need to state the n for each analysis in the figures or legends.

Minor concerns:

1. The phrase "lactating male" is used throughout the paper and is not correct. We assume this term to mean male pups that have yet to be weaned from their lactating mother, but "lactating male" suggests a rare disorder requiring medical intervention. Perhaps "pre-weaning males" is what the authors meant.

2. The convention used to label the figures in this paper is confusing and difficult to read as there are multiple panels with the same letter in the same figure (albeit distinct sections). Labeling panels in the standard A-Z format is preferred. "Panel Z" is easier to identify than "panel III-E".

Significance

Overall, this is a well-done body of work that deserves recognition for the novel and implicative discoveries it presents. Assuming the conclusions hold true following appropriate statistical analysis and rephrasing, this paper would report the first documented evidence of meiotic cilia in the developing mammalian testis with sufficient rigor to become the foundational work on this topic.

This paper will be of interest to communities focused on germ cell development, cilia, and Hedgehog signaling. It may prompt a new perspective on Desert Hedgehog signaling as it pertains to spermatogenesis. Further, this work will be of interest to those studying male fertility, as it highlights the potential role of cilia in spermatogenesis.

Further, the proteomic analysis presented has the potential to invoke hypotheses and experimentation investigating the role of several proteins with previously uncharacterized roles in ciliogenesis, flagellogenesis, and/or spermatogenesis. The finding that the onset of ciliogenesis and flagellogenesis appear to be temporally linked has the potential to prompt research regarding shared molecular mechanisms dictating axonemal formation. We believe this paper has the potential to have an impact in its respective field, underscored by the exquisite microscopy and detailed characterization of meiotic cilia.

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Referee #2

Evidence, reproducibility and clarity

This study focuses on the dynamic changes of ciliogenesis during meiosis in prepubertal mice. It was found that primary cilia are not an intrinsic feature of the first wave of meiosis (initiating at 8 dpp); instead, they begin to polymerize at 20 dpp (after the completion of the first wave of meiosis) and are present in all stages of prophase I. Moreover, prepubertal cilia (with an average length of 21.96 μm) are significantly longer than adult cilia (10 μm). The emergence of cilia coincides temporally with flagellogenesis, suggesting a regulatory association in the formation of axonemes between the two. Functional experiments showed that disruption of cilia by chloral hydrate (CH) delays DNA repair, while the AURKA inhibitor (MLN8237) delays cilia disassembly, and centrosome migration and cilia depolymerization are mutually exclusive events. These findings represent the first detailed description of the spatiotemporal regulation and potential roles of cilia during early testicular maturation in mice. The discovery of this phenomenon is interesting; however, there are certain limitations in functional research.

Major points:

1. The prepubertal cilia in spermatocytes discovered by the authors lack specific genetic ablation to block their formation, making it impossible to evaluate whether such cilia truly have functions. Because neither in the first wave of spermatogenesis nor in adult spermatogenesis does this type of cilium seem to be essential. In addition, the authors also imply that the formation of such cilia appears to be synchronized with the formation of sperm flagella. This suggests that the production of such cilia may merely be transient protein expression noise rather than a functionally meaningful cellular structure.

2. The high expression of axoneme assembly regulators such as TRiC complex and IFT proteins identified by proteomic analysis is not particularly significant. This time point is precisely the critical period for spermatids to assemble flagella, and TRiC, as a newly discovered component of flagellar axonemes, is reasonably highly expressed at this time. No intrinsic connection with the argument of this paper is observed. In fact, this testicular proteomics has little significance.

Significance

Strengths: The discovery of a very interesting time window for ciliary growth in spermatocytes.

Weaknesses: Insufficient analysis of the function of such cilia.

Readers: Developmental biologists, reproductive biologists

My expertise: Spermatogenesis, genetics

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Referee #1

Evidence, reproducibility and clarity

In this manuscript by Perez-Moreno et al., titled "The dynamics of ciliogenesis in prepubertal mouse meiosis reveal new clues about testicular maturation during puberty", the authors characterize the development of primary cilia during meiosis in juvenile male mice. The authors catalog a variety of testicular changes that occur as juvenile mice age, such as changes in testis weight and germ cell-type composition. They next show that meiotic prophase cells initially lack cilia, and ciliated meiotic prophase cells are detected after 20 days postpartum, coinciding with the time when post-meiotic spermatids within the developing testes acquire flagella. They describe that germ cells in juvenile mice harbor cilia at all substages of meiotic prophase, in contrast to adults where only zygotene stage meiotic cells harbor cilia. The authors also document that cilia in juvenile mice are longer than those in adults. They characterize cilia composition and structure by immunofluorescence and EM, highlighting that cilia polymerization may initially begin inside the cell, followed by extension beyond the cell membrane. Additionally, they demonstrate ciliated cells can be detected in adult human testes. The authors next perform proteomic analyses of whole testes from juvenile mice at multiple ages, which may not provide direct information about the extremely small numbers of ciliated meiotic cells in the testis, and is lacking follow up experiments, but does serve as a valuable resource for the community. Finally, the authors use a seminiferous tubule culturing system to show that chemical inhibition of Aurora kinase A likely inhibits cilia depolymerization upon meiotic prophase I exit and leads to an accumulation of metaphase-like cells harboring cilia. They also assess meiotic recombination progression using their culturing system, but this is less convincing.

Few suggestions/comments are listed below:

Major comments

1. There are a few issues with the experimental set up for assessing the effects of cilia depolymerization on DNA repair (Figure 7-II). First, how were mid pachytene cells identified and differentiated from early pachytene cells (which would have higher levels of gH2AX) in this experiment? I suggest either using H1t staining (to differentiate early/mid vs late pachytene) or the extent of sex chromosome synapsis. This would ensure that the authors are comparing similarly staged cells in control and treated samples. Second, what were the gH2AX levels at the starting point of this experiment? A more convincing set up would be if the authors measure gH2AX immediately after culturing in early and late cells (early would have higher gH2AX, late would have lower gH2AX), and then again after 24hrs in late cells (upon repair disruption the sampled late cells would have high gH2AX). This would allow them to compare the decline in gH2AX (i.e., repair progression) in control vs treated samples. Also, it would be informative to know the starting gH2AX levels in ciliated vs non-ciliated cells as they may vary.

2. The authors analyze meiotic progression in cells cultured with/without AURKA inhibition in Figure 8-III and conclude that the distribution of prophase I cells does not change upon treatment. Is Figure 8-III A and B the same data? The legend text is incorrect, so it's hard to follow. Figure 8-III A shows a depletion of EdU-labelled pachytene cells upon treatment. Moreover, the conclusion that a higher proportion of ciliated zygotene cells upon treatment (Figure 8-II C) suggests that AURKA inhibition delays cilia depolymerization (page 13 line 444) does not make sense to me.

3. How do the authors know that there is a monopolar spindle in Figure 8-IV treated samples? Perhaps the authors can use a different Tubulin antibody (that does not detect only acetylated Tubulin) to show that there is a monopolar spindle.

4. The authors state in the abstract that they provide evidence suggesting that centrosome migration and cilia depolymerization are mutually exclusive events during meiosis. This is not convincing with the data present in the current manuscript. I suggest amending this statement in the abstract.

Minor comments

1. The presence of cilia in all stages of meiotic prophase I in juvenile mice is intriguing. Why is the cellular distribution and length of cilia different in prepubertal mice compared to adults (where shorter cilia are present only in zygotene cells)? What is the relevance of these developmental differences? Do cilia serve prophase I functions in juvenile mice (in leptotene, pachytene etc.) that are perhaps absent in adults?

Related to the above point, what is the relevance of the absence of cilia during the first meiotic wave? If cilia serve a critical function during prophase I (for instance, facilitating DSB repair), does the lack of cilia during the first wave imply differing cilia (and repair) requirements during the first vs latter spermatogenesis waves?

In my opinion, these would be interesting points to discuss in the discussion section.

1. The authors state on page 9 lines 286-288 that the presence of cytoplasmic continuity via intercellular bridges (between developmentally synchronous spermatocytes) hints towards a mechanism that links cilia and flagella formation. Please clarify this statement. While the correlation between the timing of appearance of cilia and flagella in cells that are located within the same segment of the seminiferous tubule may be hinting towards some shared regulation, how would cytoplasmic continuity participate in this regulation? Especially since the cytoplasmic continuity is not between the developmentally distinct cells acquiring the cilia and flagella?

2. Individual germ cells in H&E-stained testis sections in Figure 1-II are difficult to see. I suggest adding zoomed-in images where spermatocytes/round spermatids/elongated spermatids are clearly distinguishable.

3. In Figure 2-II B, the authors document that most ciliated spermatocytes in juvenile mice are pachytene. Is this because most meiotic cells are pachytene? Please clarify. If the data are available (perhaps could be adapted from Figure 1-III), it would be informative to see a graph representing what proportions of each meiotic prophase substages have cilia.

4. I suggest annotating the EM images in Sup Figure 2 and 3 to make it easier to interpret.

5. The authors claim that the ratio between GLI3-FL and GLI3-R is stable across their analyzed developmental window in whole testis immunoblots shown in Sup Figure 5. Quantifying the bands and normalizing to the loading control would help strengthen this claim as it hard to interpret the immunoblot in its current form.

6. There are a few typos throughout the manuscript. Some examples: page 5 line 172, Figure 3-I legend text, Sup Figure 5-II callouts, Figure 8-III legend, page 15 line 508, page 17 line 580, page 18 line 611.

Significance

This work provides new information about an important but poorly understood cellular structure present in meiotic cells, the primary cilium. More generally, this work expands on our understanding of testis development in juvenile mice. The microscopy images presented here are beautiful. The work is mostly descriptive but lays the groundwork for future investigations. I believe that this study would of interest to the germ cell, meiosis, and spermatogenesis communities, and with a few modifications, is suitable for publication.

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Reply to the reviewers

We would like to thank the three reviewers for their careful reading of our manuscript and suggested modifications. We have incorporated their suggestions as described below; these changes have significantly improved the structure and focus of the manuscript.

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

The possibility of observing 3D cellular organisation in tissues at nanometre resolution is a hope for many cell biologists. Here, the authors have combined two volume electron microscopy approaches with scanning electron microscopy: Focused Ion Beam (FIB-SEM) and Array Tomography (AT-SEM) to study the evolution of the shape and organisation of cytoplasmic bridges, the 'ring canals' (RCs) in the Drosophila ovarian follicle that connect nurse cells and oocyte. This type of cytoplasmic link, found in insects and humans, is essential for oocyte development.

RCs have mainly been studied using light microscopy with various markers that constitute them, but this approach does not fully capture an overall view of their organization. Due to their three-dimensional arrangement within the ovarian follicle, characterizing their organization using transmission electron microscopy (TEM) has been very limited until now. This v-EM study allows the authors to document the evolution of RC size and thickness during the development of germline cysts, from the germarium to stage 4, and potentially beyond. This study confirmed previous findings, namely that RC size correlates with lineage: the largest RC is formed after the first division, while the smallest is formed during the last division.

Furthermore, this work allowed a better characterisation of the membrane interdigitation surrounding the RCs. In addition, the authors highlight the important potential of v-EM for further structural analysis of the fusome, migrating border cells and the stem cell niche.

Majors comment

The output of this work can be divided into two parts. First, this work presents a technical challenge, involving image acquisition by volume electron microscopy and manual 3D reconstruction of the contours of the membranes, nuclei, RCs, and fusome in different cysts at different stages.

Secondly, this work is based on a structural study of the RCs and their associated membranes. This work is descriptive but important, although the results largely confirm previous findings, both for the structure of the RCs and their relationship to the division sequence of the cyst cells, and for the organisation of the membranes around the RCs.

Very interestingly, the authors report the spatial characterisation of membrane structures associated with and close to CRs that have already been identified (Loyer et al.). However, their characterisation is somewhat incomplete, as it lacks quantified data - how many CRs were analysed? and, above all, the characteristics of these membranes, their length and orientation according to their position and their connection in the lineage - these data could be obtained from the VEM data already collected and would be an important addition to the RC structural analysis in this work.

*Following the suggestions of this reviewer, we have reduced the emphasis on the technical approach to better highlight the ring canal data. We have summarized the ring canal measurements in graphs presented in Fig. 4B, C and included the sample sizes for these measurements in the figure legend. *

• To gain further insight into the membrane interdigitations, we have developed a detailed model of the oocyte and four ring canals that connect to the posterior nurse cells of the stage 4 egg chamber (Fig. 5). From this model, we see that the interdigitations are longer and more abundant that in the germarium (Fig. S5), but not as extensive as in the stage 8 egg chamber (Fig. 6). The interdigitations were not all oriented in the same direction, and we did not observe an obvious correlation between interdigitation number, orientation, and lineage. We plan to continue to explore these structures in future studies. *

In line with this, the authors importantly report the presence of an ER-like membrane structure lining the RCs. First, it would be nice to have statistics to support the observation of how many RCs..? Secondly, does this ER membrane structure vary according to the position of the RC in the cyst, are they related to the RC lineage?

*We appreciate the reviewer's interest in this novel ER-like structure lining the ring canals. We have generated a detailed model of these structures within the stage 4 egg chamber (Fig. 5D,E). However, because we do not have data from a large number of egg chambers, we believe that performing statistics would not be appropriate. *

The addition of graphs showing the quantitative data with statistics in the figures would improve understanding of the results. This is particularly the case for the characterisation of RCs according to the stage of cyst development, as shown in Figure 3. This also applies to the characterisation of RCs within a cyst and the relationship between RC size and lineage, as shown in Figure 4, and to the characterisation (thickness) of the inner part of the RC.

*We have included graphs of ring canal diameter based on stage (Fig. 4B) or lineage (Fig. 4C); however, because we only have data from a few germline cysts, we have not performed any statistical analysis. *

The part on the structural analysis of the fusome is interesting but still secondary to the characterisation of the RCs. This part should be moved to the results and figures after the various parts concerning the RCs.

        *We have deemphasized the fusome structural analysis in the results section; however, we chose to leave these images in the figures, since there could be a connection between the novel ER-like structures and the fusome.  *

Minor comments The distribution of the fusome in Figure 2 is difficult to see with Hts labelling and does not really correspond to the schematic, especially in regions 2a and 2B.

*We have modified the images and the schematic. *

In panel C of Figure 2, it is a little disturbing that the legend is directly on the image of RC. It hides some information about the images and could be placed at the bottom of the panel. This also the case for the panel G.

We understand the possible confusion and have changed the layout in the figure.

With figure 3B, it would be good to highlight the position of cyst.

We have pseudocolored the portion that corresponds to the relevant cyst in the same color used for the reconstruction (which is now Fig. 3A).

Reviewer #1 (Significance (Required)): As mentioned above, this work can be divided into two parts. The part corresponding to the acquisition of images by volume electron microscopy and manual 3D reconstruction is new and a great source of valuable information. The part related to the spatial characterisation of the RC is important, but corresponds more to an extension and reinforcement of previously available information than to the contribution of significant new insights. I think it will be of great interest to an audience interested in Drosophila oogenesis.

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

This study presents a high-resolution volumetric analysis of germline ring canals (RCs) during Drosophila oogenesis. By combining two complementary electron microscopy techniques-Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) and Array Tomography Scanning Electron Microscopy (AT-SEM)-the authors compare RC structural features at different developmental stages, ranging from the relatively small germarium to the significantly larger, later-stage egg chambers.

At early stages of oogenesis, FIB-SEM analysis confirms that the average RC size increases progressively with cyst development, in agreement with previous studies. The authors further show that lineage reliably predicts RC size (an observation previously reported, but here identified at an earlier stage in region 2a) and, importantly, that the thickness of the actin rim can also be predicted by lineage (reported here for the first time, at stage 1). FIB-SEM analysis also enables a clear delineation of the fusome, allowing for detailed characterization of its assembly and disassembly. Notably, the authors report, for the first time, structural evidence of ER-like membranes capping the inner rim of actin RCs.

At later developmental stages, AT-SEM analysis reveals that the microvilli observed by FIB-SEM evolve into extensive interdigitations extending beyond the outer rim in mid-stage egg chambers, a structural feature detected earlier than previously reported. Moreover, by analyzing a sample in which tissue organization was disrupted during preparation, the authors demonstrate that these interdigitations preferentially occur in proximity to the RC. In addition to RC analysis at later stages, the authors use AT-SEM to readily identify small cell populations, such as the germline stem cell niche and border cells, and provide high-resolution volumetric EM data for these structures.

MAJOR COMMENT My main comment is that we don't learn much new about the biology of these ring canals. The results primarily confirm findings from previous studies using conventional electron microscopy.

Although TEM data has been used to perform foundational studies in the field, there are limitations to this approach. Due to the size of the ring canals, it is challenging to locate them within the large volume of the egg chamber (especially at later stages). Even if ring canals can be located, they are typically not oriented the same way, so a single section is not sufficient. *Although some of the results shown by our complementary vEM approaches do confirm results that have been previously reported by TEM or fluorescence microscopy, our approach provides important additional insight into structures that have been studied for many decades that would not be possible using other approaches. Further, this approach has identified a novel membrane structure lining the ring canals, and it has provided structural details of the membrane interdigitations that would not be possible with conventional electron microscopy. Further, this complementary set of vEM approaches would be applicable to the study of many other structures within other tissue types. *

• *

One particularly interesting biological question, which is briefly mentioned in the text, is whether the oocyte is the cell that inherits the majority of the fusome. Since the authors are able to reconstruct the fusome using their data, they could measure the fusome volume in each cell (especially in the two pro-oocytes) and investigate whether the cell with the larger fusome ultimately becomes the oocyte. This question has been discussed for some time, and recent studies have proposed opposing models based on fusome volume to explain how the oocyte is selected among the 16 sister cells (Nashchekin et al., Science, 2021; Barr et al., Genetics, 2024).

        *We appreciate the reviewer's interest in the fusome, and we agree that our approach has provided significant insight into its three dimensional structure. The rendering of the fusome was performed using a large number of small isosurface volumes, and it is therefore difficult to accurately determine the fusome volume, since additional (non-fusome) material could be included in the model. Further, the fusomes that were rendered were within the germline clusters from region 2b, where the fusome has already started to break down, so these would not provide an accurate quantification of the full fusome volume. Because the focus of the manuscript is on the germline ring canals and associated structures such as the interdigitations (which we have tried to further streamline in this revised version), we believe that additional analysis of the fusome is outside of the scope of this work. *

MINOR COMMENT • The fluorescent markers used in the fly stocks are neither described in the Materials and Methods section nor depicted in the figures.

*We apologize if this was not clear in the original manuscript. Based on the comment from Reviewer #3 (see below), we have repeated the Hts staining using flies that do not have CheerioYFP in the background. We have also clarified the materials and methods section to indicate the panels that correspond with each strain used. *

• The authors should quote (Nashchekin et al., Science, 2021) when mentioning unequal partionning of the fusome (p4) and oocyte determination (p12). *We have added the reference to these parts of the manuscript. *

• P11-12, when mentioning electron dense regions reflecting strong cell-cell adhesion, the authors could refer to (Fichelson et al. Development, 2010), where AJ have been described around ring canals. *We have added the reference to this part of the manuscript. *

• Figure 2A: The schematic diagram (4th line) is not explained in the figure legend. *We have updated the figure legend to describe this schematic. *

• Figure 2D: Please clarify whether the RC stage shown corresponds to stage 1 or stage 10, as indicated in panel 2E. Alternatively, are these examples representing the minimum and maximum RC sizes observed across the entire dataset?. *These were not meant to be examples of the minimum and maximum ring canal sizes observed across the dataset. Instead, they were used to demonstrate the significant expansion that occurs during oogenesis. In the updated version of this figure, this panel has been removed. *

• Figure 5D: Please specify which panel in 5B this corresponds to. • Figure 5E: Please specify which panels in 5B this corresponds to. The two green boxes are not defined. Why is there a grey background under the ovariole assembly? • Figures 5G, 5H: Does panel 5G correspond to the left green box in 5E, and 5H to the right green box in 5E? Please clarify. *We have modified Figure 5 and merged it with the figure 6. In this updated format, panels 5B and 5E have been removed. *

• Figure 6: The figure title is not on the same page as the figure itself.

• We have made this change. *

• Figure 6A: The black box marking the germarium is not defined. *In this revised version, we have modified Fig. 6, and this panel has been removed. *

• Figure 6B-E: The arrows point to long interdigitations. However, arrowheads (which are not mentioned in the legend) appear to indicate the RC outer rim. Please specify this clearly in the figure legend. In the updated version of Fig. 6, these arrowheads have been removed.

Reviewer #2 (Significance (Required)):

I am not an expert in electron microscopy, so I cannot comment in detail on these techniques, but they appear to bridge the gap between conventional EM and optical microscopy in terms of resolution, user-friendliness, and other aspects. This is technically interesting, although these EM approaches have been previously described and applied. The images and movies are beautiful and clearly presented. My main comment is that we don't learn much new about the biology of these ring canals. The results primarily confirm findings from previous studies using conventional electron microscopy.

One particularly interesting biological question, which is briefly mentioned in the text, is whether the oocyte is the cell that inherits the majority of the fusome. Since the authors are able to reconstruct the fusome using their data, they could measure the fusome volume in each cell (especially in the two pro-oocytes) and investigate whether the cell with the larger fusome ultimately becomes the oocyte. This question has been discussed for some time, and recent studies have proposed opposing models based on fusome volume to explain how the oocyte is selected among the 16 sister cells (Nashchekin et al., Science, 2021; Barr et al., Genetics, 2024).

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

Kolotuev et al. used two volume-based electron microscopy based approaches to identify, segment, and document the changes in intercellular bridges, or ring canals, in early egg chambers of the fruit fly, Drosophila melanogaster. Using array tomography and focused ion beam scanning electron microscopy, Kolotuev et al., provide a high resolution and content rich lineage analysis of ring canal size, shape and orientation among early and late egg chambers. Their analysis included parameters such as the presence and shape of the fusome, the recruitment of actin to the inner ring, and development of membrane fingers that presumably spatially stabilize such structures. Last, Kolotuev and co-authors highlight additional aspects of their dataset including a reconstruction of the border cell cluster in stage 9 egg chambers. The data presented are a treasure trove of the ultrastructural features of the developing dipteran germline and subsequent ovarian follicle development. The data presented represent the highest resolution 3D dataset available and thus are a valuable worthwhile contribution to the field. My overall impression is that this paper sits intellectually between a valuable method and a loose experimental manuscript. This critique is not requesting additional experimental evidence because the data are unique and are the foundation for a new experimental paradigm. But there is not sufficient detail presented to be a full method, nor any hypothesis testing to be considered experimental. I suggest the authors consider amplifying their methods in detail and then note that using these methods provide a foundation for additional future investigations (as mentioned in the discussion). Problems with data interpretation and presentation should be addressed before publication. Below are the major and minor concerns that I believe need to be considered.

Major comments: In general images in figures are thought provoking, however changes to figure layout and design should be considered to better highlight the results. For instance, I don't know how to follow figure 1a. The arrow leads from a whole ovary to an ovulated egg with an ovariole strand connecting the two. What is the purpose of the arrow? Is it to represent time? And why is the mature egg in the figure when no data regarding this stage is presented. The authors should consider removing the mature egg and helping the reader understand that the ovariole is a subset of the whole ovary. They might do this by putting a box around a single ovarile in the whole ovary to indicate their ovariole illustration. Several other figures have similar problems. Throughout the authors used black and white arrows on black and white EM data and these arrows were lost. Color should be considered to effectively point out what they want the reader to see.

We have modified the layout of Fig. 1 and added additional explanation to the introduction and figure legend to guide readers through the introduction to the system. We have also added color to some of the arrows throughout the manuscript.

Can the authors provide additional information for the genotypes used? For instance the Cherrio-YFP (which might affect actin). When what this used and can the authors provide information on how this affected the data between when it was used and when it was not used. Additionally, why was analysis done in transgenic flies over fully wild-type?

*We have repeated the Hts staining in Fig. 2A in flies that do not express Cheerio-YFP and have made the appropriate changes to the methods section. For the AT-SEM experiment, we chose to use this genetic background since it would align with that of the negative controls that we often use in RNAi or over-expression experiments. FIB-SEM datasets were collected while imaging other tissues of the fly, so the choice of that genotype was not intentional. However, these datasets provided us with the opportunity to do this proof-of-concept work without such a large financial investment in the acquisition of new image stacks. In the future, we hope to expand this work to generate additional datasets from flies of different genotypes. *

Figure 1 seeks to lay out the ovary system and narrow the reader into the stages that will be analyzed in subsequent figures. Figure 1B is meant to show the types and kinds of electron microscopy, however lacks a full detailed description and legend for each of the colored arrows. And to that fact, so does figure S1. The authors need to provide additional information so the reader can glean what the authors point they are trying to convey. In addition, the authors might add pros and cons to each. I know this was attempted in S1, but did not fully come across.

We appreciate this feedback, and we have modified the layout of Figure 1 and updated Figures S1 to better highlight the technical challenge of EM in general and benefits of vEM in particular.

Figure 1 and 2 seek to set up both the biological and technical system to be understood. The authors might consider combining the two figures and eliminate elements that don't represent a result of any kind (Figure 1B, 2B, 3D and 3F). Or more fully explain the result and point they are trying to make with these illustrations. I fully understand and appreciate what they are trying to get across, but it does not come across clearly. For example, I don't know how figure 2B effectively gets across the point that rotation of the image has an effect on how it is sliced and segmented in EM data. Not sure it is necessary. Furthermore, what is the bottom panel with a green ring canal supposed to allow us to interpret or conclude? The same for 3D and F. The result in 3E is far more interesting and should be two panels that emphasize the growth characteristics between young and old rings or those of M1 and M4.

        *We greatly appreciate these suggestions, and we have modified and reorganized several figures to make the flow of scientific ideas easier to follow.* *We have moved panel 1B to the supplementary figure and gave additional indications in the text as to the differences between the EM methods. We have moved panel 2B to the supplementary material. We have moved Fig. 3D to Fig. S5A,B. Fig. 5 now provides more extensive rendering of membrane interdigitations from the stage 4 egg chamber. We have chosen to leave Fig. 3F to allow readers to compare the novel ER-like structures within the ring canals to the fusome that is present within younger germline clusters. *

The HTS and actin stain in figure 2A overlap significantly and obscure the fusome staining. Can the authors confirm that there is no bleed through in their staining and imaging procedure?

*We have repeated this staining and can confirm that there was no bleed through between the two channels. *

The data in Figure 2C are critical to showing the z-resolution enhancement of sectioned EM. However, the use of green psuedocolor only in one panel is confusing. Can the authors duplicate the whole panel and provide one without and one with psuedocolor? This would be ideal for fully orienting the reader to the sectioning and setting them up to understand the rest of the figures.

*In the revised version of Figure 2, we have split the sections into two rows of panels; we have added the pseudocolor to every other section (in the bottom row of panels). *

• *

The results section for figure 2 does outline the results presented. For example, the germarium contains syncytia of differing stages and ring canals with intervening fusomes... It does more to talk about the pros and cons of different technical aspects and their difficulty This should be saved for the rationale or the discussion. Rather the section should outline the results presented.

*We have modified the layout of figure 2 in order to describe the system in a more straightforward manner with a smoother transition from Figure 1 while further explaining technical points. *

I appreciate the color coding of the differentially segment cysts in Figure 3. The color coding helped orient me to which cysts were being evaluated. However I found the lack of detail bothersome. For instance, which ring canals are in the two panels of D? Are they M1 or M4?

*With the additional analysis of the interdigitations in the stage 4 cluster, we have moved panel D to Fig. S5. We did not have enough coverage of the region 2a cluster (red) to determine lineage, but we have added a statement to the legend to indicate that the ring canal shown in Fig. S5B is an M1 ring canal. *

Also, the presentation of ring canal size and distribution should be presented in a graph. Statistics are not necessary, but a dot-plot would go a long way to presenting the result. Two plots can add value, one in which the ring canals for each phase is shown, and the other is the distribution of sizes for each cyst.

*We have added these graphs in Fig. 4B, C. *

Lastly, the results section for figure 3 interprets the membrane bound vesicles in the ring canal as "ER-like". This should be removed since they neither look ER-like to me, nor have been shown to be ER in the data.

*We appreciate this suggestion, and although we cannot be absolutely certain of the identity of these structures without further study, with our additional analysis of the stage 4 egg chamber, we are further convinced of the similar appearance of these novel structures and the ER in other regions of the nurse cell (Fig. 5). We have clarified this point in the text. *

Figure 4A is not called out specifically in the results and thus should be interpreted or removed from the figure.

In this revised version, we have removed panel 4A.

Figure 5 was confusing. I understand the authors wanted to show the wafer and the ribbons, however, this is not a result and does not offer any interpretation of a result and is thus confusing on why it is in the figure. If this were a method paper, I would understand its presence.

*We have removed this panel from the figure. *

Can the authors comment on the shape of the nuclei in older egg chambers? They are not round at all. I am interested in whether this is a fixation artifact or the real ultrastructure of the nuclei. Of the border cell nuclei for instance. If it is an artifact, this should be added to the discussion.

*Some of the nuclei appear to have a peculiar shape in the cross-section. We cannot entirely exclude the role of the fixation in the shape irregularities. However, since not all the nuclei are subject to this phenomenon, we are inclined to attribute it to the intrinsic qualities of the late-stage nuclei. In numerous cases, different tissue and cell stages determine the shape of the nucleus, which frequently deviates from a spherical shape. *

Although data from "imperfect" samples is interesting, consider relegating Figure 6 to the supplement section, as it takes away from the pre-existing narrative flow established in the paper.

• In this draft, we have combined parts of figures 5 and 6, and much of the data from the imperfect sample has been removed. *

Interpretation of the data throughout the results should be left to the discussion section. For instance, interpretation of Figure 4 results on page 14 beginning with "these data demonstrate the importance...". The importance is not related to the result, but rather discussion of past and future studies.

We have removed this sentence from the results.

In another example, Figure 5I is introduced and discussed in the results section on page 15, second whole paragraph with an overall introduction/discussion on junctions, which convolutes the actual result. Discussion of future studies or how structures like the novel membrane fingers should be viewed in a larger biological context, should not be in the results.

We have made this change.

Minor comments: Remove words such as "pseudo-timelapse", they invoke precision on a point that is imprecise.

*This has been removed. *

Re-consider the acronyms for ring canal and egg chamber.

*We have removed these acronyms. *

Consider finding another way to call out each supplemental movie other than with another acronym.

*We have added small icons to indicate that a supplemental movie is associated with a given figure or panel. *

Reviewer #3 (Significance (Required)): The present manuscript is a technical advance in the field. The use of serial EM imaging with two separate modalities, on what is considered to be a challenging problem in the field, represents a useful technical advance. Light microscopy has thus far limited the resolution to which we can understand the spatial organization and the cellular features there in that regulate germline development. This manuscript brings to bear two serial EM methods to begin approaching this problem. The audience for this work are those working at the forefront of understanding germline architecture and development. I make these statements as an expert in live and super resolution of fruit fly egg chamber development, in addition to having performed 3D SEM in past works.

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

Kolotuev et al. used two volume-based electron microscopy based approaches to identify, segment, and document the changes in intercellular bridges, or ring canals, in early egg chambers of the fruit fly, Drosophila melanogaster. Using array tomography and focused ion beam scanning electron microscopy, Kolotuev et al., provide a high resolution and content rich lineage analysis of ring canal size, shape and orientation among early and late egg chambers. Their analysis included parameters such as the presence and shape of the fusome, the recruitment of actin to the inner ring, and development of membrane fingers that presumably spatially stabilize such structures. Last, Kolotuev and co-authors highlight additional aspects of their dataset including a reconstruction of the border cell cluster in stage 9 egg chambers. The data presented are a treasure trove of the ultrastructural features of the developing dipteran germline and subsequent ovarian follicle development. The data presented represent the highest resolution 3D dataset available and thus are a valuable worthwhile contribution to the field. My overall impression is that this paper sits intellectually between a valuable method and a loose experimental manuscript. This critique is not requesting additional experimental evidence because the data are unique and are the foundation for a new experimental paradigm. But there is not sufficient detail presented to be a full method, nor any hypothesis testing to be considered experimental. I suggest the authors consider amplifying their methods in detail and then note that using these methods provide a foundation for additional future investigations (as mentioned in the discussion). Problems with data interpretation and presentation should be addressed before publication. Below are the major and minor concerns that I believe need to be considered.

Major comments:

• In general images in figures are thought provoking, however changes to figure layout and design should be considered to better highlight the results. For instance, I don't know how to follow figure 1a. The arrow leads from a whole ovary to an ovulated egg with an ovariole strand connecting the two. What is the purpose of the arrow? Is it to represent time? And why is the mature egg in the figure when no data regarding this stage is presented. The authors should consider removing the mature egg and helping the reader understand that the ovariole is a subset of the whole ovary. They might do this by putting a box around a single ovarile in the whole ovary to indicate their ovariole illustration. Several other figures have similar problems. Throughout the authors used black and white arrows on black and white EM data and these arrows were lost. Color should be considered to effectively point out what they want the reader to see.

• Can the authors provide additional information for the genotypes used? For instance the Cherrio-YFP (which might affect actin). When what this used and can the authors provide information on how this affected the data between when it was used and when it was not used. Additionally, why was analysis done in transgenic flies over fully wild-type? Figure 1 seeks to lay out the ovary system and narrow the reader into the stages that will be analyzed in subsequent figures. Figure 1B is meant to show the types and kinds of electron microscopy, however lacks a full detailed description and legend for each of the colored arrows. And to that fact, so does figure S1. The authors need to provide additional information so the reader can glean what the authors point they are trying to convey. In addition, the authors might add pros and cons to each. I know this was attempted in S1, but did not fully come across. Figure 1 and 2 seek to set up both the biological and technical system to be understood. The authors might consider combining the two figures and eliminate elements that don't represent a result of any kind (Figure 1B, 2B, 3D and 3F). Or more fully explain the result and point they are trying to make with these illustrations. I fully understand and appreciate what they are trying to get across, but it does not come across clearly. For example, I don't know how figure 2B effectively gets across the point that rotation of the image has an effect on how it is sliced and segmented in EM data. Not sure it is necessary. Furthermore, what is the bottom panel with a green ring canal supposed to allow us to interpret or conclude? The same for 3D and F. The result in 3E is far more interesting and should be two panels that emphasize the growth characteristics between young and old rings or those of M1 and M4.

• The HTS and actin stain in figure 2A overlap significantly and obscure the fusome staining. Can the authors confirm that there is no bleed through in their staining and imaging procedure?

• The data in Figure 2C are critical to showing the z-resolution enhancement of sectioned EM. However, the use of green psuedocolor only in one panel is confusing. Can the authors duplicate the whole panel and provide one without and one with psuedocolor? This would be ideal for fully orienting the reader to the sectioning and setting them up to understand the rest of the figures.

• The results section for figure 2 does outline the results presented. For example, the germarium contains syncytia of differing stages and ring canals with intervening fusomes... It does more to talk about the pros and cons of different technical aspects and their difficulty This should be saved for the rationale or the discussion. Rather the section should outline the results presented.

• I appreciate the color coding of the differentially segment cysts in Figure 3. The color coding helped orient me to which cysts were being evaluated. However I found the lack of detail bothersome. For instance, which ring canals are in the two panels of D? Are they M1 or M4? Also, the presentation of ring canal size and distribution should be presented in a graph. Statistics are not necessary, but a dot-plot would go a long way to presenting the result. Two plots can add value, one in which the ring canals for each phase is shown, and the other is the distribution of sizes for each cyst. Lastly, the results section for figure 3 interprets the membrane bound vesicles in the ring canal as "ER-like". This should be removed since they neither look ER-like to me, nor have been shown to be ER in the data.

• Figure 4A is not called out specifically in the results and thus should be interpreted or removed from the figure.

• Figure 5 was confusing. I understand the authors wanted to show the wafer and the ribbons, however, this is not a result and does not offer any interpretation of a result and is thus confusing on why it is in the figure. If this were a method paper, I would understand its presence.

• Can the authors comment on the shape of the nuclei in older egg chambers? They are not round at all. I am interested in whether this is a fixation artifact or the real ultrastructure of the nuclei. Of the border cell nuclei for instance. If it is an artifact, this should be added to the discussion.

• Although data from "imperfect" samples is interesting, consider relegating Figure 6 to the supplement section, as it takes away from the pre-existing narrative flow established in the paper. Interpretation of the data throughout the results should be left to the discussion section. For instance, interpretation of Figure 4 results on page 14 beginning with "these data demonstrate the importance...". The importance is not related to the result, but rather discussion of past and future studies. In another example, Figure 5I is introduced and discussed in the results section on page 15, second whole paragraph with an overall introduction/discussion on junctions, which convolutes the actual result. Discussion of future studies or how structures like the novel membrane fingers should be viewed in a larger biological context, should not be in the results.

Minor comments:

• Remove words such as "pseudo-timelapse", they invoke precision on a point that is imprecise.

• Re-consider the acronyms for ring canal and egg chamber.

• Consider finding another way to call out each supplemental movie other than with another acronym.

Significance

The present manuscript is a technical advance in the field. The use of serial EM imaging with two separate modalities, on what is considered to be a challenging problem in the field, represents a useful technical advance. Light microscopy has thus far limited the resolution to which we can understand the spatial organization and the cellular features there in that regulate germline development. This manuscript brings to bear two serial EM methods to begin approaching this problem. The audience for this work are those working at the forefront of understanding germline architecture and development. I make these statements as an expert in live and super resolution of fruit fly egg chamber development, in addition to having performed 3D SEM in past works.

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 presents a high-resolution volumetric analysis of germline ring canals (RCs) during Drosophila oogenesis. By combining two complementary electron microscopy techniques-Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) and Array Tomography Scanning Electron Microscopy (AT-SEM)-the authors compare RC structural features at different developmental stages, ranging from the relatively small germarium to the significantly larger, later-stage egg chambers. At early stages of oogenesis, FIB-SEM analysis confirms that the average RC size increases progressively with cyst development, in agreement with previous studies. The authors further show that lineage reliably predicts RC size (an observation previously reported, but here identified at an earlier stage in region 2a) and, importantly, that the thickness of the actin rim can also be predicted by lineage (reported here for the first time, at stage 1). FIB-SEM analysis also enables a clear delineation of the fusome, allowing for detailed characterization of its assembly and disassembly. Notably, the authors report, for the first time, structural evidence of ER-like membranes capping the inner rim of actin RCs. At later developmental stages, AT-SEM analysis reveals that the microvilli observed by FIB-SEM evolve into extensive interdigitations extending beyond the outer rim in mid-stage egg chambers, a structural feature detected earlier than previously reported. Moreover, by analyzing a sample in which tissue organization was disrupted during preparation, the authors demonstrate that these interdigitations preferentially occur in proximity to the RC. In addition to RC analysis at later stages, the authors use AT-SEM to readily identify small cell populations, such as the germline stem cell niche and border cells, and provide high-resolution volumetric EM data for these structures.

MAJOR COMMENT

My main comment is that we don't learn much new about the biology of these ring canals. The results primarily confirm findings from previous studies using conventional electron microscopy. One particularly interesting biological question, which is briefly mentioned in the text, is whether the oocyte is the cell that inherits the majority of the fusome. Since the authors are able to reconstruct the fusome using their data, they could measure the fusome volume in each cell (especially in the two pro-oocytes) and investigate whether the cell with the larger fusome ultimately becomes the oocyte. This question has been discussed for some time, and recent studies have proposed opposing models based on fusome volume to explain how the oocyte is selected among the 16 sister cells (Nashchekin et al., Science, 2021; Barr et al., Genetics, 2024).

MINOR COMMENTS

• The fluorescent markers used in the fly stocks are neither described in the Materials and Methods section nor depicted in the figures.

• The authors should quote (Nashchekin et al., Science, 2021) when mentioning unequal partionning of the fusome (p4) and oocyte determination (p12).

• P11-12, when mentioning electron dense regions reflecting strong cell-cell adhesion, the authors could refer to (Fichelson et al. Development, 2010), where AJ have been described around ring canals.

• Figure 2A: The schematic diagram (4th line) is not explained in the figure legend.

• Figure 2D: Please clarify whether the RC stage shown corresponds to stage 1 or stage 10, as indicated in panel 2E. Alternatively, are these examples representing the minimum and maximum RC sizes observed across the entire dataset?.

• Figure 5D: Please specify which panel in 5B this corresponds to.

• Figure 5E: Please specify which panels in 5B this corresponds to. The two green boxes are not defined. Why is there a grey background under the ovariole assembly?

• Figures 5G, 5H: Does panel 5G correspond to the left green box in 5E, and 5H to the right green box in 5E? Please clarify.

• Figure 6: The figure title is not on the same page as the figure itself.

• Figure 6A: The black box marking the germarium is not defined.

• Figure 6B-E: The arrows point to long interdigitations. However, arrowheads (which are not mentioned in the legend) appear to indicate the RC outer rim. Please specify this clearly in the figure legend.

Significance

I am not an expert in electron microscopy, so I cannot comment in detail on these techniques, but they appear to bridge the gap between conventional EM and optical microscopy in terms of resolution, user-friendliness, and other aspects. This is technically interesting, although these EM approaches have been previously described and applied. The images and movies are beautiful and clearly presented.

My main comment is that we don't learn much new about the biology of these ring canals. The results primarily confirm findings from previous studies using conventional electron microscopy. One particularly interesting biological question, which is briefly mentioned in the text, is whether the oocyte is the cell that inherits the majority of the fusome. Since the authors are able to reconstruct the fusome using their data, they could measure the fusome volume in each cell (especially in the two pro-oocytes) and investigate whether the cell with the larger fusome ultimately becomes the oocyte. This question has been discussed for some time, and recent studies have proposed opposing models based on fusome volume to explain how the oocyte is selected among the 16 sister cells (Nashchekin et al., Science, 2021; Barr et al., Genetics, 2024).

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

The possibility of observing 3D cellular organisation in tissues at nanometre resolution is a hope for many cell biologists. Here, the authors have combined two volume electron microscopy approaches with scanning electron microscopy: Focused Ion Beam (FIB-SEM) and Array Tomography (AT-SEM) to study the evolution of the shape and organisation of cytoplasmic bridges, the 'ring canals' (RCs) in the Drosophila ovarian follicle that connect nurse cells and oocyte. This type of cytoplasmic link, found in insects and humans, is essential for oocyte development. RCs have mainly been studied using light microscopy with various markers that constitute them, but this approach does not fully capture an overall view of their organization. Due to their three-dimensional arrangement within the ovarian follicle, characterizing their organization using transmission electron microscopy (TEM) has been very limited until now. This v-EM study allows the authors to document the evolution of RC size and thickness during the development of germline cysts, from the germarium to stage 4, and potentially beyond. This study confirmed previous findings, namely that RC size correlates with lineage: the largest RC is formed after the first division, while the smallest is formed during the last division. Furthermore, this work allowed a better characterisation of the membrane interdigitation surrounding the RCs. In addition, the authors highlight the important potential of v-EM for further structural analysis of the fusome, migrating border cells and the stem cell niche.

Major comments

• The output of this work can be divided into two parts. First, this work presents a technical challenge, involving image acquisition by volume electron microscopy and manual 3D reconstruction of the contours of the membranes, nuclei, RCs, and fusome in different cysts at different stages. Secondly, this work is based on a structural study of the RCs and their associated membranes. This work is descriptive but important, although the results largely confirm previous findings, both for the structure of the RCs and their relationship to the division sequence of the cyst cells, and for the organisation of the membranes around the RCs.

• Very interestingly, the authors report the spatial characterisation of membrane structures associated with and close to CRs that have already been identified (Loyer et al.). However, their characterisation is somewhat incomplete, as it lacks quantified data - how many CRs were analysed? and, above all, the characteristics of these membranes, their length and orientation according to their position and their connection in the lineage - these data could be obtained from the VEM data already collected and would be an important addition to the RC structural analysis in this work. In line with this, the authors importantly report the presence of an ER-like membrane structure lining the RCs. First, it would be nice to have statistics to support the observation of how many RCs..? Secondly, does this ER membrane structure vary according to the position of the RC in the cyst, are they related to the RC lineage? The addition of graphs showing the quantitative data with statistics in the figures would improve understanding of the results. This is particularly the case for the characterisation of RCs according to the stage of cyst development, as shown in Figure 3. This also applies to the characterisation of RCs within a cyst and the relationship between RC size and lineage, as shown in Figure 4, and to the characterisation (thickness) of the inner part of the RC.

• The part on the structural analysis of the fusome is interesting but still secondary to the characterisation of the RCs. This part should be moved to the results and figures after the various parts concerning the RCs.

Minor comments

• The distribution of the fusome in Figure 2 is difficult to see with Hts labelling and does not really correspond to the schematic, especially in regions 2a and 2B.

• In panel C of Figure 2, it is a little disturbing that the legend is directly on the image of RC. It hides some information about the images and could be placed at the bottom of the panel. This also the case for the panel G.

• With figure 3B, it would be good to highlight the position of cyst.

Significance

As mentioned above, this work can be divided into two parts.

The part corresponding to the acquisition of images by volume electron microscopy and manual 3D reconstruction is new and a great source of valuable information. The part related to the spatial characterisation of the RC is important, but corresponds more to an extension and reinforcement of previously available information than to the contribution of significant new insights.

I think it will be of great interest to an audience interested in Drosophila oogenesis.

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Reply to the reviewers

The authors do not wish to provide a response at this time.

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Referee #3

Evidence, reproducibility and clarity

Summary:

The manuscript by Dufour et al. is a follow-up on the groups' previous publication that introduced the photo-inducible Cre recombinase, LiCre. In the present work, the authors further characterize the properties and kinetics of their optogenetic switch. Initially, the authors show that light affects only LiCre-mediated recombination itself and not DNA binding. Following these observations, they measure and mathematically model LiCre kinetics demonstrating high efficiency in vivo and a surprising temperature sensitivity. Finally, Dufour et al. evaluate several mutations that affect the LOV photo-cycle and provide recommendation for LiCre applications. The study thoroughly investigates various aspects of the function of LiCre, confirming some previously known characteristics (i.e. temperature-dependence of Cre activity and functionality of LOV-based optogenetic tools in yeast without co-factor supplementation), while providing new LiCre-specific insights (kinetics, light-independent DNA binding). Please note that the reviewer is no expert in mathematical modeling and cannot fully judge the methodological details of the models. While I have some concerns as listed below, I believe study should be well-suited for publication after a revision.

Major comments:

1. After completing the initial experiment, the authors discovered that their plasmids carry different numbers of V5 epitopes. I am wondering whether this was due to a recombination event happening during the experiment or whether the constructs were not sequence verified prior to use? In any case, an additional ChIP experiment using Cre and LiCre constructs with the identical number of tag-repeats will be necessary. The result, i.e. the strong reduction of DNA-binding of LiCre (which is close to the negative control), is quite remarkable given that LiCre is still considerably active and high DNA affinities were observed in SPR experiments. In light of these counterindications, identical experiment conditions for test and reference group become even more important.
2. The conclusion that DNA-binding of LiCre is completely light-independent is not entirely convincing to me. The differences between the light and dark conditions in Fig. 2d are indeed small, but the values for LiCre are almost on par with the vector control and therefore hard to interpret. Based on this experiment alone, one could even be inclined to argue that LiCre does not bind DNA at all (which is of course falsified by the later experiments), showing that the resolution of the corresponding dataset is too low to draw final conclusions. Light-independent DNA binding should either be confirmed by a more sensitive method or the conclusion statements on this matter should be revised accordingly.
3. If I understand the explanations correctly, replicates and plotted data points refer to multiple samples (different colonies), that were handled in a single experiment, i.e. by one researcher at the same time/same day. As already mentioned by the authors in the main text, this workflow explains the considerable differences between some of the results in the present manuscript and an identical experiment in a previous publication by the same authors. Providing truly independent experiments (performed on different days) that are therefore independent towards variables such as the fluctuation in incubation temperature (which was the issue in the described experiments) will be crucial, at least for the key datasets.

Minor comments:

1. At the end of the Introduction, the authors mention that the interaction of the Cre heptamers was weakened via point mutations in LiCre. A short sentence about the engineering rationale behind this weakened interaction would help readers, who are not familiar with the author's prior work.
2. Fig. 2a-b depicts images relating to the purification procedure. These could be moved to the supplements as they don't provide any insight apart from the fact that the proteins were successfully purified.
3. The kinetic characterization was only performed for LiCre. Especially for scientists, who have worked with wildtype Cre before, a side-by-side comparison with wt Cre would be valuable to judge the loss in reaction speed that has to be expected when switching from Cre to LiCre.
4. The difference between the ChIP results and the SPR results is striking but not mentioned in the discussion section. Also, the statement: "Finally, our results have practical implications on experimental protocols employing LiCre. First, given its high affinity for loxP (Fig. 5b), over-expressing LiCre at high levels will probably not increase its efficiency." (line 502) refers only to the affinity but seems to ignore the low DNA-occupancy of LiCre observed in Fig. 2d. Adapting the discussion section accordingly would improve the manuscript.

Significance

General assessment and advance:

The present study provides a large set of experiments and analyses characterizing the optogenetic LiCre recombinase. In general, the study is well conceived and executed. Although some of my concerns listed above affect key aspects of the study, they should be straightforward to address. The manuscript is a follow-up study providing a more detailed characterization of an optogenetic tool previously developed by the same authors. Its novelty is therefore somewhat limited. While the study provides a rich body of additional data, many of the findings merely confirmed aspects that were to be expected based on the two proteins LiCre is built of (temperature-dependent activity of Cre, optogenetics in yeast w/o the need of co-factor supplementation, weaker DNA-affinity of the Cre fusion protein as compared to wildtype Cre). New insights are provided by the facts that (i) light only controls recombination but not DNA binding and (ii) light activation of only some protomers within the LiCre heptamer is likely to be sufficient to activate recombination. The former aspect is, however, not entirely evident from the results as described above.

Audience:

The study will be of interest for researchers focusing on inducible DNA recombination and especially relevant to those who plan to work with LiCre and can now rely on a more detailed and extended characterization compared to the original LiCre publication.

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Referee #2

Evidence, reproducibility and clarity

Summary: This manuscript presents a detailed kinetic and mechanistic characterization of the optogenetic recombinase LiCre, which enables site-specific DNA recombination upon blue-light stimulation. The authors combine in vitro surface plasmon resonance assays, yeast-based recombination assays, and mathematical modeling to dissect the DNA-binding properties, activation dynamics, and recombination efficiency of LiCre. They demonstrate that LiCre binds DNA even in the absence of light, albeit with reduced cooperativity compared to Cre recombinase. Through kinetic modeling, they propose that activation of only two LiCre units may suffice for recombination. The study also evaluates the impact of point mutations in the LOV domain on LiCre's photocycle. The experimental methods are described in detail. Statistical analyses are appropriate and clearly reported.

Major Comments:

1. In Figure 1, control experiments with no loxP sequences (i.e. original strain) should be performed to demonstrate specific binding of Cre/LiCre to loxP sequence.
2. In Figure 2, the SPR experiments are robust and informative. However, the lack of measurement of DNA binding of light-activated LiCre is a notable gap, which will help understand whether the cooperativity of LiCre can be modulated by light. If it is difficult due to experimental conditions, there is lit-mimetic mutant of LOV2 (https://www.nature.com/articles/nmeth.3926).

Significance

General Assessment: This is a rigorous study that combines experimental and computational approaches to advance our understanding of LiCre-based optogenetic genome engineering. The strongest aspects are the integration of SPR data with kinetic modeling and the practical insights into LiCre's performance under various conditions. However, the other limitation is the lack of direct validation of some model predictions.

Advance: To the best of my knowledge, this is the first study to quantitatively model the activation dynamics of LiCre. The work extends previous findings on LiCre and provides new mechanistic and practical insights.

Audience: This study will be of interest to specialized audiences, particularly those developing or applying the LiCre system.

Reviewers' Field of Expertise: Protein engineering, Genome editing, Optogenetics, Cell Biology.

Limitations of Expertise: I do not have deep expertise in mathematical modeling.

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Referee #1

Evidence, reproducibility and clarity

Dufour et al describe characterization of the light-activated recombinase LiCre. This work combines the yeast reporter assay, surface plasmon resonance (SPR) and kinetic modeling to provide a comprehensive study of how LiCre functions both in vivo in yeast and in vitro. The authors show that LiCre binds to loxP sites in the dark with high affinity, but reduced cooperativity compared to wild-type Cre, and that recombination efficiency is affected by temperature and illumination regime. Importantly, the authors establish a kinetic model that not only explains these observations but also predicts the altered behavior of a mutant (T418S), which was experimentally validated. It would be valuable to highlight what other predictions the model could make, even if for future work. Overall, this work combines quantitative experiments and modeling to provide new insights into the biochemical and kinetic properties of LiCre.

Specific comments:

Line 110-115: Although described in the Methods section, a brief statement of dark and light treatment conditions would help readers better follow the experiments. Likewise, listing the three unrelated positions would improve the clarity.

Line 185: Is there a typo?

Line 216: Have the authors considered performing surface plasmon resonance (SPR) to confirm the binding affinity of LiCre-V5 DNA?

Line 233-234: To determine whether the observed difference in recombination efficiency is due to the genomic context of the reporter loci or due to the measurement accuracy of GFP and RFP signals, have the authors considered swapping the positions of GFP and RFP?

Line 236: The sentence "Importantly, we never observed recombination in the entire cell population" is ambiguous. I believe it means recombination was never observed in 100% of the cells. Please rephrase it.

Line 245-249: The hypothesis of plasmid loss based on plating samples on selective and non-selective media without illumination assumes that loss of growth on selective media is only due to plasmid loss, without considering other factors like burden or toxicity. Moreover, the broad range of 10-30% makes it difficult to justify that the ~15% recombination-negative fraction falls within expected variation. The conclusion that LiCre-mediated recombination efficiency is close to 100% after prolonged photoactivation (Line 249, 301-303) is not fully convincing unless more evidence is provided.

Line 275-276: The authors suspect that the decrease in recombination efficiency at very high light intensity is possibly attributed to phototoxicity. Could photobleaching also contribute to this effect? A viability assay would help to validate the phototoxicity explanation.

Line 345-346: While the model with x=2 provides a slightly better fit comparing to the others, the possibility of x=4 cannot be excluded. The inference that "photo-activation of at least two LiCre protomers enables recombination" is not sufficiently proven.

Figure 1e: Please clarify whether the Western blots shown represent biological replicates.

Figure 4: Please include the error bars. Panel a - The authors integrated GFP and mCherry reporters at two different loci to avoid positional bias. Why then is only mCherry used as the ON readout in most experiments, rather than analyzing both reporters in parallel? Please clarify. For panel 4h and line 272, the statement that maximal activation was reached at 12 mW/cm² should be rephrased more cautiously, as no intermediate intensities between 12 and 35.6 mW/cm² were tested.

Significance

This study provides a quantitative experimental and predictive analysis of the light-activated recombinase LiCre, offering new insights into its binding, activation and recombination properties. The predictive validation of the mutant is a strength of this work. While the modeling part is an innovative aspect, more clarification is needed, especially regarding the conclusion that photo-activation of at least two LiCre protomers enables recombination. More mechanistic investigations are needed to support the conclusions. The work will be of interest to researchers in optogenetics, genome engineering, and DNA-protein interactions. My expertise is in yeast genome engineering and applications of Cre-mediated recombination system. Modeling is outside my primary area of expertise.

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Reply to the reviewers

1. General Statements

Thank you for providing an assessment of our manuscript. We suggest here a revision plan to address the points raised by the reviewers regarding code documentation, benchmarking, and biological applications.

As part of the revisions implemented we have:

Clarified the management of dependencies of our package Fixed the data download run times of test data Clarified the parameters of the normalization and optimization functions We plan to:

Extend our manuscript to include a section on cross-condition analysis that builds on our tutorials, where we will illustrate how ParTIpy can quantify shifts in the distribution of fibroblasts across the functional space defined by archetypal analysis between healthy and failing hearts. Extend our benchmarks of scalability of coresets, by reporting wall-clock time and peak memory usage across distinct data sizes. Extend our benchmarks of stability of coresets, by reporting the similarity of the estimated archetypes based on the original versus the sampled data. Include the original enrichment analysis of ParTI to provide users with distinct options to work with the archetypes, and provide a larger discussion on the distinct strategies. We believe these revisions will strengthen our__ software manuscript__ and will help us to provide a robust and practical tool to analyze functional trade-offs from biological data.

2. Description of the planned revisions

Reviewer #1

Summary

The paper "ParTIpy: A Scalable Framework for Archetypal Analysis and Pareto Task Inference" presents ParTIpy, an open-source Python package that modernizes and scales the Pareto Task Inference (ParTI) framework for analyzing biological trade-offs and functional specialization. Unlike the earlier MATLAB implementation, which required a commercial license and was limited in scalability, ParTIpy leverages Python's open ecosystem and integration with tools such as scverse to make archetypal analysis more accessible, flexible, and compatible with modern biological data workflows. Through advanced optimization and coreset algorithms, it efficiently handles large scale single cell and spatial transcriptomics datasets. ParTIpy identifies "archetypes", or optimal phenotypic extremes, to reveal how cells balance competing functional programs. The paper demonstrates its application in modeling hepatocyte specialization across the liver lobule, highlighting spatial patterns of metabolic division of labor.

Overall, ParTIpy represents a modern, accessible, and scalable Python-based solution for exploring biological trade-offs and resource allocation in high-dimensional data. The paper is clearly written and addresses an important methodological gap. However, the enrichment analysis differs from the original ParTI framework and should be discussed more explicitly, and the documentation and tutorials, while helpful, could be refined to improve usability and reproducibility.

Major Comments

1. The archetype enrichment analysis used in this paper differs from the original enrichment analysis implemented in ParTI. This is acceptable, but: a) The authors should explicitly state and discuss the differences between the two approaches. b) The enrichment analysis should be made more systematic. For each tested feature (e.g. gene or pathway), the analysis should report a p-value for the hypothesis that the feature is enriched near an archetype - that is, its expression (or value) is high close to the archetype and decreases with distance. Appropriate multiple-hypothesis correction should also be applied.

We thank the reviewer for this valuable comment and agree that the differences between our enrichment analysis and the original ParTI implementation should be stated more explicitly. We will incorporate the original enrichment algorithm into ParTIpy, enabling users to select their preferred method. In the revised manuscript, we will note that two enrichment algorithms are available and describe both in greater detail in the supplementary methods section. We also note that the current enrichment analysis already reports p-values adjusted for multiple hypothesis testing.

Reviewer #2

Summary

This paper introduces the software ParTIpy, a scalable Python implementation of Pareto Task Inference (ParTI), designed to infer functional trade-offs in biological systems through archetypal analysis. The framework modernizes the previous toolbox with efficient optimization, memory-saving coreset construction, and integration with the scverse ecosystem for single-cell transcriptomic data.

Using hepatocytes scRNA-seq data as a test case, the authors identify archetypes corresponding to distinct gene expression patterns. These archetypes align with known liver domains in spatial transcriptomics data, validating both the method's interpretability and its biological relevance.

Major comments

(1) Conclusions

The core computational and biological claims are well supported. ParTIpy clearly scales better than earlier implementations and reproduces known biological structure. However, claims about "scalability to large datasets" should be further qualified (see below).

We will implement further performance benchmarks as discussed below.

(2) Claims

Archetypal analysis based on current matrix computation formulation is non-parametric, and new data require recomputation of archetypes. Therefore, the method cannot generalize to unseen data in the way deep learning approaches, which could be further acknowledged and clarified.

We thank the reviewer for this insightful comment. We agree that deep learning frameworks are typically amortized, allowing them to generalize to unseen data without retraining, and we will clarify this distinction in the discussion of the revised manuscript. However, we note that mapping new cells into an existing archetypal space is computationally inexpensive, as it only requires solving a single convex optimization problem.

(3) Additional suggested analyses or experiments

1） Absolute performance benchmarks : it's suggested to report wall-clock time and memory for a few dataset sizes (10k, 100k, 1M cells).

We thank the reviewer for this helpful suggestion. We will extend the coreset benchmark to quantify how coreset size affects both archetype positions and biological interpretation. Specifically, we will match archetypes across coreset sizes by solving the linear sum assignment problem, as we currently do when comparing bootstrap samples. We will then compare the distances between archetypes inferred from the full dataset and those obtained from different coreset sizes. In addition to measuring displacement, we will assess biological stability by comparing the gene expression vectors of corresponding archetypes as well as their enriched pathways (using metrics such as cosine similarity and Jaccard index).

**Referee cross-commenting**

I agree with the other reviewer's suggestion to check consistency and reproducibility with previous implementation, and enhance the tutorial of the software for users from a biological background. Combined with my comments to further improve the biological application showcase, the revised manuscript could be an impactful contribution to the field, if these comments could be properly addressed.

(1) Advance

This paper is primarily a technical contribution. It modernizes the Pareto Task Inference framework into a scalable and user-friendly Python implementation, which is valuable. However, to further improve its significance especially for the broader biological audience, more detailed analysis could be performed (see below)

(2) Biological scope and applications [optional]

The current biological validation in hepatocyte is technically fine but limited in breadth and impact. It demonstrates that ParTIpy works but falls in short of showing what new insights it can reveal. Several promising applications could be further explored:

1) Cross-condition comparisons: could ParTIpy quantify how the Pareto front shifts between conditions (e.g., normal vs. tumor, treated vs. control)?

We thank the reviewer for this valuable suggestion. We have shown ParTIpy's applicability to cross-condition settings in our online tutorials (https://partipy.readthedocs.io/en/latest/notebooks/cross_condition_lupus.html). However, we agree that a more explicit mention in the manuscript is needed. Thus, we will include a cross-condition analysis as a second application in the revised manuscript, focusing on fibroblasts from heart failure patients from Amrute, et. al. (2023) 1. This will illustrate how ParTIpy can quantify shifts in the distribution of cells across the functional space defined by archetypal analysis.

Because the manuscript does not explore these scenarios, the biological impact remains narrow, and the framework's broader interpretive power is somehow underrepresented.

We hope that the additional application included in the revised manuscript helps better illustrate the framework's strength. We would also like to note that the online tutorials provide a comprehensive overview of ParTIpy's functionality, as we expect these will serve as a primary entry point for many researchers interested in archetypal analysis and Pareto Task Inference.

(3) Audience and impact

The paper will interest computational biologists, systems biologists, and bioinformaticians focused on single-cell analysis, and its impact will grow substantially if the authors demonstrate more biological applications.

(4) Reviewer expertise

Computational biology, single-cell transcriptomics, machine learning, computational math

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

Reviewer #1

2. The package documentation on GitHub and ReadTheDocs is a major strength, but the tutorials can be improved for clarity and accessibility:

We thank the reviewer for this positive feedback. Indeed, providing comprehensive documentation to facilitate ease of adoption was a major motivation behind this project. In response to the reviewer's suggestions, we have revised the tutorials to further improve their clarity, structure, and accessibility, as detailed below.

a) The documentation should list external dependencies that need to be installed seperately, e.g. pybiomart.

We thank the reviewer for pointing this out. We had added all dependencies under the optional-dependencies.extra header, which allows users to run pip install partipy[extra] to be able to run all tutorial notebooks. However, we forgot to explain that in the tutorial or Readme page, which we corrected now. The Readme now reads:

Install the latest stable full release from PyPI with the extra dependencies (e.g., pybiomart, squidpy, liana) that are required to run every tutorial:

``` pip install partipy[extra]

```

Additionally we include clarifications in every tutorial notebook that uses additional dependencies: "To run this notebook, install ParTIpy with the tutorial extras: pip install partipy[extra]".

b) The dataset used in the Quickstart demo appears to be inaccessible or extremely slow to download (the function load_hepatocyte_data_2() did not complete even after 30 minutes, at least in my experience). The authors should verify data availability on Zenodo and consider providing a smaller or cached version to make the demo more reliable and reproducible.

We thank the reviewer for this helpful comment. We agree that the previous implementation of load_hepatocyte_data_2() was not reliable due to slow download speeds from Zenodo. To address this, we now host the required AnnData object on figshare (https://figshare.com/articles/dataset/scRNA-seq_hepatocyte_data_from_Ben-Moshe_et_al_2022_/30588713?file=59459459), ensuring faster and more stable access for the Quickstart tutorial via scanpy.read:

```

adata = sc.read("data/hepatocyte_processed.h5ad", backup_url="https://figshare.com/ndownloader/files/59459459")

adata

```

c) The tutorial order could be more intuitive - for instance, "archetype crosstalk network" appears before "archetypal analysis". Consider starting with the simulated dataset and presenting the full pipeline before moving to more complex real-world examples.

We thank the reviewer for this helpful suggestion and agree that the previous ordering was not intuitive. We have reordered the tutorials such that the notebook introducing archetypal analysis now appears first, followed by the Quickstart tutorial and the subsequent applied examples.

Minor comments

1. In the Python function, the parameter "optim" could use more descriptive option names - for example, renaming "projected_gradients" to "PCHA" would make it clearer and more consistent with terminology used in the paper.

We thank the reviewer for this helpful suggestion. We agree that the previous naming could be misleading. While PCHA does not precisely describe the underlying algorithm, it is the term most users are familiar with from the literature. We have therefore updated the function to accept both "PCHA" and "projected_gradients", which now map to the same underlying optimization routine.

In the Quickstart preprocessing, the authors use the following code:

sc.pp.normalize_total(adata)

sc.pp.log1p(adata)

However, they do not specify the target sum in the normalize_total function. The authors should ensure that the data values before the logarithmic transformation span several orders of magnitude (e.g., 0-10,000); if normalization is performed to a sum of 1, the log transformation becomes ineffective.

We thank the reviewer for this helpful comment. By default, sc.pp.normalize_total scales the counts in each cell to the median total counts across all cells, which preserves the typical range of expression values prior to logarithmic transformation. We therefore consider this default behavior appropriate for the Quickstart example. Nonetheless, we will clarify this explicitly in the tutorial to avoid confusion.

**Referee cross-commenting**

I agree with Reviewer #2 observation that the paper's contribution is primarily technical; however, I consider this technical advance to be an important and timely one that will enable many biologists to apply archetypal analysis more effectively in their own work.

We thank the reviewer for this positive and encouraging assessment.

Reviewer #1 (Significance (Required)):

This study presents ParTIpy, a Python-based implementation of Pareto Task Inference (ParTI) that makes archetypal analysis more accessible, scalable, and compatible with modern single-cell and spatial transcriptomics workflows. Its main strength lies in translating a conceptually powerful but technically limited MATLAB framework into an open-source, efficient Python package, enabling wider use in computational biology. The package is well-documented, which further enhances its accessibility and adoption potential, though documentation could be improved to enhance reproducibility and ease of use. It will be of interest to computational systems biologists, particularly those working with omics data, and those interested in studying functional trade-offs and resource allocation.

We appreciate the reviewer's positive evaluation and are encouraged by their recognition of ParTIpy's relevance and potential impact in computational biology.

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

Reviewer #2

The current biological validation in hepatocyte is technically fine but limited in breadth and impact. It demonstrates that ParTIpy works but falls in short of showing what new insights it can reveal. Several promising applications could be further explored:

2) Transient or plastic states: Cells with mixed archetype weights or high mixture entropy can be interpreted as transient, functionally flexible states. ParTIpy can quantify such transience geometrically, even in static data, which providing a competitive counterpart to models like CellRank or CellSimplex (https://doi.org/10.1093/bioinformatics/btaf119).

We thank the reviewer for this interesting suggestion. While we agree that quantifying transient or plastic states based on archetype mixtures is an intriguing idea, validating whether cells with mixed archetype weights ("generalists") truly represent transient states would require additional data modalities such as temporal or lineage-tracing measurements. Although we find this direction highly interesting, given that the manuscript is intended as a software paper, we prefer to focus on more directly supported applications of cross-condition data, where labeled data is available.

However, we will expand our discussion to relate ParTIpy with CellSimplex since we believe this is an interesting angle that future users could explore.

5. References

1. Amrute, J. M. et al. Defining cardiac functional recovery in end-stage heart failure at single-cell resolution. Nat. Cardiovasc. Res. 2, 399-416 (2023).

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Referee #2

Evidence, reproducibility and clarity

Summary

This paper introduces the software ParTIpy, a scalable Python implementation of Pareto Task Inference (ParTI), designed to infer functional trade-offs in biological systems through archetypal analysis. The framework modernizes the previous toolbox with efficient optimization, memory-saving coreset construction, and integration with the scverse ecosystem for single-cell transcriptomic data.

Using hepatocytes scRNA-seq data as a test case, the authors identify archetypes corresponding to distinct gene expression patterns. These archetypes align with known liver domains in spatial transcriptomics data, validating both the method's interpretability and its biological relevance.

Major comments

(1) Conclusions

The core computational and biological claims are well supported. ParTIpy clearly scales better than earlier implementations and reproduces known biological structure. However, claims about "scalability to large datasets" should be further qualified (see below).

(2) Claims

Archetypal analysis based on current matrix computation formulation is non-parametric, and new data require recomputation of archetypes. Therefore, the method cannot generalize to unseen data in the way deep learning approaches, which could be further acknowledged and clarified.

(3) Additional suggested analyses or experiments

1. Absolute performance benchmarks : it's suggested to report wall-clock time and memory for a few dataset sizes (10k, 100k, 1M cells).
2. Coreset sensitivity analysis: Could authors show how coreset size affects archetype positions and biological interpretation?

Referee cross-commenting

I agree with the other reviewer's suggestion to check consistency and reproducibility with previous implementation, and enhance the tutorial of the software for users from a biological background. Combined with my comments to further improve the biological application showcase, the revised manuscript could be an impactful contribution to the field, if these comments could be properly addressed.

Significance

(1) Advance

This paper is primarily a technical contribution. It modernizes the Pareto Task Inference framework into a scalable and user-friendly Python implementation, which is valuable. However, to further improve its significance especially for the broader biological audience, more detailed analysis could be performed (see below)

(2) Biological scope and applications [optional]

The current biological validation in hepatocyte is technically fine but limited in breadth and impact. It demonstrates that ParTIpy works but falls in short of showing what new insights it can reveal. Several promising applications could be further explored:

1) Cross-condition comparisons: could ParTIpy quantify how the Pareto front shifts between conditions (e.g., normal vs. tumor, treated vs. control)?

2) Transient or plastic states: Cells with mixed archetype weights or high mixture entropy can be interpreted as transient, functionally flexible states. ParTIpy can quantify such transience geometrically, even in static data, which providing a competitive counterpart to models like CellRank or CellSimplex (https://doi.org/10.1093/bioinformatics/btaf119).

Because the manuscript does not explore these scenarios, the biological impact remains narrow, and the framework's broader interpretive power is somehow underrepresented.

(3) Audience and impact

The paper will interest computational biologists, systems biologists, and bioinformaticians focused on single-cell analysis, and its impact will grow substantially if the authors demonstrate more biological applications.

(4) Reviewer expertise Computational biology, single-cell transcriptomics, machine learning, computational math

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Referee #1

Evidence, reproducibility and clarity

Summary

The paper "ParTIpy: A Scalable Framework for Archetypal Analysis and Pareto Task Inference" presents ParTIpy, an open-source Python package that modernizes and scales the Pareto Task Inference (ParTI) framework for analyzing biological trade-offs and functional specialization. Unlike the earlier MATLAB implementation, which required a commercial license and was limited in scalability, ParTIpy leverages Python's open ecosystem and integration with tools such as scverse to make archetypal analysis more accessible, flexible, and compatible with modern biological data workflows. Through advanced optimization and coreset algorithms, it efficiently handles large scale single cell and spatial transcriptomics datasets. ParTIpy identifies "archetypes", or optimal phenotypic extremes, to reveal how cells balance competing functional programs. The paper demonstrates its application in modeling hepatocyte specialization across the liver lobule, highlighting spatial patterns of metabolic division of labor. Overall, ParTIpy represents a modern, accessible, and scalable Python-based solution for exploring biological trade-offs and resource allocation in high-dimensional data. The paper is clearly written and addresses an important methodological gap. However, the enrichment analysis differs from the original ParTI framework and should be discussed more explicitly, and the documentation and tutorials, while helpful, could be refined to improve usability and reproducibility.

Major Comments

1. The archetype enrichment analysis used in this paper differs from the original enrichment analysis implemented in ParTI. This is acceptable, but:

a. The authors should explicitly state and discuss the differences between the two approaches.

b. The enrichment analysis should be made more systematic. For each tested feature (e.g. gene or pathway), the analysis should report a p-value for the hypothesis that the feature is enriched near an archetype - that is, its expression (or value) is high close to the archetype and decreases with distance. Appropriate multiple-hypothesis correction should also be applied. 2. The package documentation on GitHub and ReadTheDocs is a major strength, but the tutorials can be improved for clarity and accessibility:

a. The documentation should list external dependencies that need to be installed seperately, e.g. pybiomart.

b. The dataset used in the Quickstart demo appears to be inaccessible or extremely slow to download (the function load_hepatocyte_data_2() did not complete even after 30 minutes, at least in my experience). The authors should verify data availability on Zenodo and consider providing a smaller or cached version to make the demo more reliable and reproducible.

c. The tutorial order could be more intuitive - for instance, "archetype crosstalk network" appears before "archetypal analysis". Consider starting with the simulated dataset and presenting the full pipeline before moving to more complex real-world examples.

Minor comments

1. In the Python function, the parameter "optim" could use more descriptive option names - for example, renaming "projected_gradients" to "PCHA" would make it clearer and more consistent with terminology used in the paper.
2. In the Quickstart preprocessing, the authors use the following code: sc.pp.normalize_total(adata) sc.pp.log1p(adata) However, they do not specify the target sum in the normalize_total function. The authors should ensure that the data values before the logarithmic transformation span several orders of magnitude (e.g., 0-10,000); if normalization is performed to a sum of 1, the log transformation becomes ineffective.

Referee cross-commenting

I agree with Reviewer #2 observation that the paper's contribution is primarily technical; however, I consider this technical advance to be an important and timely one that will enable many biologists to apply archetypal analysis more effectively in their own work.

Significance

This study presents ParTIpy, a Python-based implementation of Pareto Task Inference (ParTI) that makes archetypal analysis more accessible, scalable, and compatible with modern single-cell and spatial transcriptomics workflows. Its main strength lies in translating a conceptually powerful but technically limited MATLAB framework into an open-source, efficient Python package, enabling wider use in computational biology. The package is well-documented, which further enhances its accessibility and adoption potential, though documentation could be improved to enhance reproducibility and ease of use. It will be of interest to computational systems biologists, particularly those working with omics data, and those interested in studying functional trade-offs and resource allocation.

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

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Reply to the reviewers

Response to referee comments: ____RC-2025-03008

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

Summary In this article, the authors used the synthetic TALE DNA binding proteins, tagged with YFP, which were designed to target five specific repeat elements in Trypanosoma brucei genome, including centromere and telomeres-associated repeats and those of a transposon element. This is in order to detect and identified, using YFP-pulldown, specific proteins that bind to these repetitive sequences in T. brucei chromatin. Validation of the approach was done using a TALE protein designed to target the telomere repeat (TelR-TALE) that detected many of the proteins that were previously implicated with telomeric functions. A TALE protein designed to target the 70 bp repeats that reside adjacent to the VSG genes (70R-TALE) detected proteins that function in DNA repair and the protein designed to target the 177 bp repeat arrays (177R-TALE) identified kinetochore proteins associated T. brucei mega base chromosomes, as well as in intermediate and mini-chromosomes, which imply that kinetochore assembly and segregation mechanisms are similar in all T. brucei chromosome.

Major comments: Are the key conclusions convincing? The authors reported that they have successfully used TALE-based affinity selection of protein-associated with repetitive sequences in the T. brucei genome. They claimed that this study has provided new information regarding the relevance of the repetitive region in the genome to chromosome integrity, telomere biology, chromosomal segregation and immune evasion strategies. These conclusions are based on high-quality research, and it is, basically, merits publication, provided that some major concerns, raised below, will be addressed before acceptance for publication. 1. The authors used TALE-YFP approach to examine the proteome associated with five different repetitive regions of the T. brucei genome and confirmed the binding of TALE-YFP with Chip-seq analyses. Ultimately, they got the list of proteins that bound to synthetic proteins, by affinity purification and LS-MS analysis and concluded that these proteins bind to different repetitive regions of the genome. There are two control proteins, one is TRF-YFP and the other KKT2-YFP, used to confirm the interactions. However, there are no experiment that confirms that the analysis gives some insight into the role of any putative or new protein in telomere biology, VSG gene regulation or chromosomal segregation. The proteins, which have already been reported by other studies, are mentioned. Although the author discovered many proteins in these repetitive regions, their role is yet unknown. It is recommended to take one or more of the new putative proteins from the repetitive elements and show whether or not they (1) bind directly to the specific repetitive sequence (e.g., by EMSA); (2) it is recommended that the authors will knockdown of one or a small sample of the new discovered proteins, which may shed light on their function at the repetitive region, as a proof of concept.

Response

The main request from Referee 1 is for individual evaluation of protein-DNA interaction for a few candidates identified in our TALE-YFP affinity purifications, particularly using EMSA to identify binding to the DNA repeats used for the TALE selection. In our opinion, such an approach would not actually provide the validation anticipated by the reviewer. The power of TALE-YFP affinity selection is that it enriches for protein complexes that associate with the chromatin that coats the target DNA repetitive elements rather than only identifying individual proteins or components of a complex that directly bind to DNA assembled in chromatin.

The referee suggests we express recombinant proteins and perform EMSA for selected candidates, but many of the identified proteins are unlikely to directly bind to DNA - they are more likely to associate with a combination of features present in DNA and/or chromatin (e.g. specific histone variants or histone post-translational modifications). Of course, a positive result would provide some validation but only IF the tested protein can bind DNA in isolation - thus, a negative result would be uninformative.

In fact, our finding that KKT proteins are enriched using the 177R-TALE (minichromosome repeat sequence) identifies components of the trypanosome kinetochore known (KKT2) or predicted (KKT3) to directly bind DNA (Marciano et al., 2021; PMID: 34081090), and likewise the TelR-TALE identifies the TRF component that is known to directly associate with telomeric (TTAGGG)n repeats (Reis et al 2018; PMID: 29385523). This provides reassurance on the specificity of the selection, as does the lack of cross selectivity between different TALEs used (see later point 3 below). The enrichment of the respective DNA repeats quantitated in Figure 2B (originally Figure S1) also provides strong evidence for TALE selectivity.

It is very likely that most of the components enriched on the repetitive elements targeted by our TALE-YFP proteins do not bind repetitive DNA directly. The TRF telomere binding protein is an exception - but it is the only obvious DNA binding protein amongst the many proteins identified as being enriched in our TelR-TALE-YFP and TRF-YFP affinity selections.

The referee also suggests that follow up experiments using knockdown of the identified proteins found to be enriched on repetitive DNA elements would be informative. In our opinion, this manuscript presents the development of a new methodology previously not applied to trypanosomes, and referee 2 highlights the value of this methodological development which will be relevant for a large community of kinetoplastid researchers. In-depth follow-up analyses would be beyond the scope of this current study but of course will be pursued in future. To be meaningful such knockdown analyses would need to be comprehensive in terms of their phenotypic characterisation (e.g. quantitative effects on chromosome biology and cell cycle progression, rates and mechanism of recombination underlying antigenic variation, etc) - simple RNAi knockdowns would provide information on fitness but little more. This information is already publicly available from genome-wide RNAi screens (www.tritrypDB.org), with further information on protein location available from the genome-wide protein localisation resource (Tryptag.org). Hence basic information is available on all targets selected by the TALEs after RNAi knock down but in-depth follow-up functional analysis of several proteins would require specific targeted assays beyond the scope of this study.

NonR-TALE-YFP does not have a binding site in the genome, but YFP protein should still be expressed by T. brucei clones with NLS. The authors have to explain why there is no signal detected in the nucleus, while a prominent signal was detected near kDNA (see Fig.2). Why is the expression of YFP in NonR-TALE almost not shown compared to other TALE clones?

Response

The NonR-TALE-YFP immunolocalisation signal indeed is apparently located close to the kDNA and away from the nucleus. We are not sure why this is so, but the construct is sequence validated and correct. However, we note that artefactual localisation of proteins fused to a globular eGFP tag, compared to a short linear epitope V5 tag, near to the kinetoplast has been previously reported (Pyrih et al, 2023; PMID: 37669165),

The expression of NonR-TALE-YFP is shown in Supplementary Fig. S2 in comparison to other TALE proteins. Although it is evident that NonR-TALE-YFP is expressed at lower levels than other TALEs (the different TALEs have different expression levels), it is likely that in each case the TALE proteins would be in relative excess.

It is possible that the absence of a target sequence for the NonR-TALE-YFP in the nucleus affects its stability and cellular location. Understanding these differences is tangential to the aim of this study.

However, importantly, NonR-TALE-YFP is not the only control for used for specificity in our affinity purifications. Instead, the lack of cross-selection of the same proteins by different TALEs (e.g. TelR-TALE-YFP, 177R-TALE-YFP) and the lack of enrichment of any proteins of interest by the well expressed ingiR-TALE-YFP or 147R-TALE-YFP proteins each provide strong evidence for the specificity of the selection using TALEs, as does the enrichment of similar protein sets following affinity purification of the TelR-TALE-YFP and TRF-YFP proteins which both bind telomeric (TTAGGG)n repeats. Moreover, control affinity purifications to assess background were performed using cells that completely lack an expressed YFP protein which further support specificity (Figure 6).

We have added text to highlight these important points in the revised manuscript:

Page 8:

"However, the expression level of NonR-TALE-YFP was lower than other TALE-YFP proteins; this may relate to the lack of DNA binding sites for NonR-TALE-YFP in the nucleus."

Page 8:

"NonR-TALE-YFP displayed a diffuse nuclear and cytoplasmic signal; unexpectedly the cytoplasmic signal appeared to be in the vicinity the kDNA of the kinetoplast (mitochrondria). We note that artefactual localisation of some proteins fused to an eGFP tag has previously been observed in T. brucei (Pyrih et al, 2023)."

Page 10:

Moreover, a similar set of enriched proteins was identified in TelR-TALE-YFP affinity purifications whether compared with cells expressing no YFP fusion protein (No-YFP), the NonR-TALE-YFP or the ingiR-TALE-YFP as controls (Fig. S7B, S8A; Tables S3, S4). Thus, the most enriched proteins are specific to TelR-TALE-YFP-associated chromatin rather than to the TALE-YFP synthetic protein module or other chromatin.

As a proof of concept, the author showed that the TALE method determined the same interacting partners enrichment in TelR-TALE as compared to TRF-YFP. And they show the same interacting partners for other TALE proteins, whether compared with WT cells or with the NonR-TALE parasites. It may be because NonR-TALE parasites have almost no (or very little) YFP expression (see Fig. S3) as compared to other TALE clones and the TRF-YFP clone. To address this concern, there should be a control included, with proper YFP expression.

Response

See response to point 2, but we reiterate that the ingi-TALE -YFP and 147R-TALE-YFP proteins are well expressed (western original Fig. S3 now Fig. S2) but few proteins are detected as being enriched or correspond to those enriched in TelR-TALE-YFP or TRF-YFP affinity purifications (see Fig. S9). Therefore, the ingi-TALE -YFP and 147R-TALE-YFP proteins provide good additional negative controls for specificity as requested. To further reassure the referee we have also included additional volcano plots which compare TelR-TALE-YFP, 70R-TALE-YFP or 177R-TALE-YFP to the ingiR-TALE-YFP affinity selection (new Figure S8). As with No-YFP or NonR-TALE-YFP controls, the use of ingiR-TALE-YFP as a negative control demonstrates that known telomere associated proteins are enriched in TelR-TALE-YFP affinity purification, RPA subunits enriched with 70R-TALE-YFP and Kinetochore KKT poroteins enriched with 177R-TALE-YFP. These analyses demonstrate specificity in the proteins enriched following affinity purification of our different TALE-YFPs and provide support to strengthen our original findings.

We now refer to use of No-YFP, NonR-TALE-YFP, and ingiR-TALE -YFP as controls for comparison to TelR-TALE-YFP, 70R-TALE-YFP or 177R-TALE-YFP in several places:

Page10:

"Moreover, a similar set of enriched proteins was identified in TelR-TALE-YFP affinity purifications whether compared with cells expressing no YFP fusion protein (No-YFP), the NonR-TALE-YFP or the ingiR-TALE-YFP as controls (Fig. S7B, S8A; Tables S3, S4)."

Page 11:

"Thus, the nuclear ingiR-TALE-YFP provides an additional chromatin-associated negative control for affinity purifications with the TelR-TALE-YFP, 70R-TALE-YFP and 177R-TALE-YFP proteins (Fig. S8)."

"Proteins identified as being enriched with 70R-TALE-YFP (Figure 6D) were similar in comparisons with either the No-YFP, NonR-TALE-YFP or ingiR-TALE-YFP as negative controls."

Top Page 12:

"The same kinetochore proteins were enriched regardless of whether the 177R-TALE proteomics data was compared with No-YFP, NonR-TALE or ingiR-TALE-YFP controls."

Discussion Page 13:

"Regardless, the 147R-TALE and ingiR-TALE proteins were well expressed in T. brucei cells, but their affinity selection did not significantly enrich for any relevant proteins. Thus, 147R-TALE and ingiR-TALE provide reassurance for the overall specificity for proteins enriched TelR-TALE, 70R-TALE and 177R-TALE affinity purifications."

After the artificial expression of repetitive sequence binding five-TALE proteins, the question is if there is any competition for the TALE proteins with the corresponding endogenous proteins? Is there any effect on parasite survival or health, compared to the control after the expression of these five TALEs YFP protein? It is recommended to add parasite growth curves, for all the TALE-proteins expressing cultures.

Response

Growth curves for cells expressing TelR-TALE-YFP, 177R-TALE-YFP and ingiR-TALE-YFP are now included (New Fig S3A). No deficit in growth was evident while passaging 70R-TALE-YFP, 147R-TALE-YFP, NonR-TALE-YFP cell lines (indeed they grew slightly better than controls).

The following text has been added page 8:

"Cell lines expressing representative TALE-YFP proteins displayed no fitness deficit (Fig. S3A)."

Since the experiments were performed using whole-cell extracts without prior nuclear fractionation, the authors should consider the possibility that some identified proteins may have originated from compartments other than the nucleus. Specifically, the detection of certain binding proteins might reflect sequence homology (or partial homology) between mitochondrial DNA (maxicircles and minicircles) and repetitive regions in the nuclear genome. Additionally, the lack of subcellular separation raises the concern that cytoplasmic proteins could have been co-purified due to whole cell lysis, making it challenging to discern whether the observed proteome truly represents the nuclear interactome.

Response

In our experimental design, we confirmed bioinformatically that the repeat sequences targeted were not represented elsewhere in the nuclear or mitochondrial genome (kDNA). The absence of subcellular fractionation could result in some cytoplasmic protein selection, but this is unlikely since each TALE targets a specific DNA sequence but is otherwise identical such that cross-selection of the same contaminating protein set would be anticipated if there was significant non-specific binding. We have previously successfully affinity selected 15 chromatin modifiers and identified associated proteins without major issues concerning cytoplasmic protein contamination (Staneva et al 2021 and 2022; PMID: 34407985 and 36169304). Of course, the possibility that some proteins are contaminants will need to be borne in mind in any future follow-up analysis of proteins of interest that we identified as being enriched on specific types of repetitive element in T. brucei. Proteins that are also detected in negative control, or negative affinity selections such as No-YFP, NoR-YFP, IngiR-TALE or 147R-TALE must be disregarded.

'6'. Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether? As mentioned earlier, the author claimed that this study has provided new information concerning telomere biology, chromosomal segregation mechanisms, and immune evasion strategies. But there are no experiments that provides a role for any unknown or known protein in these processes. Thus, it is suggested to select one or two proteins of choice from the list and validate their direct binding to repetitive region(s), and their role in that region of interaction.

Response

As highlighted in response to point 1 the suggested validation and follow up experiments may well not be informative and are beyond the scope of the methodological development presented in this manuscript. Referee 2 describes the study in its current form as "a significant conceptual and technical advancement" and "This approach enhances our understanding of chromatin organization in these regions and provides a foundation for investigating the functional roles of associated proteins in parasite biology."

The Referee's phrase 'validate their direct binding to repetitive region(s)' here may also mean to test if any of the additional proteins that we identified as being enriched with a specific TALE protein actually display enrichment over the repeat regions when examined by an orthogonal method. A key unexpected finding was that kinetochore proteins including KKT2 are enriched in our affinity purifications of the 177R-TALE-YFP that targets 177bp repeats (Figure 6F). By conducting ChIP-seq for the kinetochore specific protein KKT2 using YFP-KKT2 we confirmed that KKT2 is indeed enriched on 177bp repeat DNA but not flanking DNA (Figure 7). Moreover, several known telomere-associated proteins are detected in our affinity selections of TelR-TALE-YFP (Figure 6B, FigS6; see also Reis et al, 2018 Nuc. Acids Res. PMID: 29385523; Weisert et al, 2024 Sci. Reports PMID: 39681615).

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 answer for this question depends on what the authors want to present as the achievements of the present study. If the achievement of the paper was is the creation of a new tool for discovering new proteins, associated with the repeat regions, I recommend that they add a proof for direct interactions between a sample the newly discovered proteins and the relevant repeats, as a proof of concept discussed above, However, if the authors like to claim that the study achieved new functional insights for these interactions they will have to expand the study, as mentioned above, to support the proof of concept.

Response

See our response to point 1 and the point we labelled '6' above.

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. I think that they are realistic. If the authors decided to check the capacity of a small sample of proteins (which was unknown before as a repetitive region binding proteins) to interacts directly with the repeated sequence, it will substantially add of the study (e.g., by EMSA; estimated time: 1 months). If the authors will decide to check the also the function of one of at least one such a newly detected proteins (e.g., by KD), I estimate the will take 3-6 months.

Response

As highlighted previously the proposed EMSA experiment may well be uninformative for protein complex components identified in our study or for isolated proteins that directly bind DNA in the context of a complex and chromatin. RNAi knockdown data and cell location data (as well as developmental expression and orthology data) is already available through tritrypDB.org and trtyptag.org

Are the data and the methods presented in such a way that they can be reproduced? Yes

Are the experiments adequately replicated, and statistical analysis adequate? The authors did not mention replicates. There is no statistical analysis mentioned.

Response

The figure legends indicate that all volcano plots of TALE affinity selections were derived from three biological replicates. Cutoffs used for significance: PFor ChiP-seq two biological replicates were analysed for each cell line expressing the specific YFP tagged protein of interest (TALE or KKT2). This is now stated in the relevant figure legends - apologies for this oversight. The resulting data are available for scrutiny at GEO: GSE295698.

Minor comments: -Specific experimental issues that are easily addressable. The following suggestions can be incorporated: 1. Page 18, in the material method section author mentioned four drugs: Blasticidine, Phleomycin and G418, and hygromycin. It is recommended to mention the purpose of using these selective drugs for the parasite. If clonal selection has been done, then it should also be mentioned.

Response

We erroneously added information on several drugs used for selection in our labaoratory. In fact all TALE-YFP construct carry the Bleomycin resistance genes which we select for using Phleomycin. Also, clones were derived by limiting dilution immediately after transfection.

We have amended the text accordingly:

Page 17/18:

"Cell cultures were maintained below 3 x 106 cells/ml. Pleomycin 2.5 mg/ml was used to select transformants containing the TALE construct BleoR gene."

"Electroporated bloodstream cells were added to 30 ml HMI-9 medium and two 10-fold serial dilutions were performed in order to isolate clonal Pleomycin resistant populations from the transfection. 1 ml of transfected cells were plated per well on 24-well plates (1 plate per serial dilution) and incubated at 37{degree sign}C and 5% CO2 for a minimum of 6 h before adding 1 ml media containing 2X concentration Pleomycin (5 mg/ml) per well."

In the method section the authors mentioned that there is only one site for binding of NonR-TALE in the parasite genome. But in Fig. 1C, the authors showed zero binding site. So, there is one binding site for NonR-TALE-YFP in the genome or zero?

Response

We thank the reviewer for pointing out this discrepancy. We have checked the latest Tb427v12 genome assembly for predicted NonR-TALE binding sites and there are no exact matches. We have corrected the text accordingly.

Page 7:

"A control NonR-TALE protein was also designed which was predicted to have no target sequence in the T. bruceigenome."

Page 17:

"A control NonR-TALE predicted to have no recognised target in the T. brucei geneome was designed as follows: BLAST searches were used to identify exact matches in the TREU927 reference genome. Candidate sequences with one or more match were discarded."

The authors used two different anti-GFP antibodies, one from Roche and the other from Thermo Fisher. Why were two different antibodies used for the same protein?

Response

We have found that only some anti-GFP antibodies are effective for affinity selection of associated proteins, whereas others are better suited for immunolocalisation. The respective suppliers' antibodies were optimised for each application.

Page 6: in the introduction, the authors give the number of total VSG genes as 2,634. Is it known how many of them are pseudogenes?

Response

This value corresponds to the number reported by Consentino et al. 2021 (PMID: 34541528) for subtelomeric VSGs, which is similar to the value reported by Muller et al 2018 (PMID: 30333624) (2486), both in the same strain of trypanosomes as used by us. Based on the earlier analysis by Cross et al (PMID: 24992042), 80% of the identified VSGs in their study (2584) are pseudogenes. This approximates to the estimation by Consentino of 346/2634 (13%) being fully functional VSG genes at subtelomeres, or 17% when considering VSGs at all genomic locations (433/2872).

I found several typos throughout the manuscript.

Response

Thank you for raising this, we have read through the manuscipt several times and hopefully corrected all outstanding typos.

Fig. 1C: Table: below TOTAL 2nd line: the number should be 1838 (rather than 1828)

Corrected- thank you.

• Are prior studies referenced appropriately? Yes

• Are the text and figures clear and accurate? Yes

• Do you have suggestions that would help the authors improve the presentation of their data and conclusions? Suggested above

Reviewer #1 (Significance (Required)):

Describe the nature and significance of the advance (e.g., conceptual, technical, clinical) for the field: This study represents a significant conceptual and technical advancement by employing a synthetic TALE DNA-binding protein tagged with YFP to selectively identify proteins associated with five distinct repetitive regions of T. brucei chromatin. To the best of my knowledge, it is the first report to utilize TALE-YFP for affinity-based isolation of protein complexes bound to repetitive genomic sequences in T. brucei. This approach enhances our understanding of chromatin organization in these regions and provides a foundation for investigating the functional roles of associated proteins in parasite biology. Importantly, any essential or unique interacting partners identified could serve as potential targets for therapeutic intervention.

• Place the work in the context of the existing literature (provide references, where appropriate). I agree with the information that has already described in the submitted manuscript, regarding its potential addition of the data resulted and the technology established to the study of VSGs expression, kinetochore mechanism and telomere biology.

• State what audience might be interested in and influenced by the reported findings. These findings will be of particular interest to researchers studying the molecular biology of kinetoplastid parasites and other unicellular organisms, as well as scientists investigating chromatin structure and the functional roles of repetitive genomic elements in higher eukaryotes.

• 1Define your field of expertise with a few keywords to help the authors contextualize your point of view. 2Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. (1) Protein-DNA interactions/ chromatin/ DNA replication/ Trypanosomes (2) None

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

Summary

Carloni et al. comprehensively analyze which proteins bind repetitive genomic elements in Trypanosoma brucei. For this, they perform mass spectrometry on custom-designed, tagged programmable DNA-binding proteins. After extensively verifying their programmable DNA-binding proteins (using bioinformatic analysis to infer target sites, microscopy to measure localization, ChIP-seq to identify binding sites), they present, among others, two major findings: 1) 14 of the 25 known T. brucei kinetochore proteins are enriched at 177bp repeats. As T. brucei's 177bp repeat-containing intermediate-sized and mini-chromosomes lack centromere repeats but are stable over mitosis, Carloni et al. use their data to hypothesize that a 'rudimentary' kinetochore assembles at the 177bp repeats of these chromosomes to segregate them. 2) 70bp repeats are enriched with the Replication Protein A complex, which, notably, is required for homologous recombination. Homologous recombination is the pathway used for recombination-based antigenic variation of the 70bp-repeat-adjacent variant surface glycoproteins.

Major Comments

None. The experiments are well-controlled, claims well-supported, and methods clearly described. Conclusions are convincing.

Response Thank you for these positive comments.

Minor Comments

1) Fig. 2 - I couldn't find an uncropped version showing multiple cells. If it exists, it should be linked in the legend or main text; Otherwise, this should be added to the supplement.

Response

The images presented represent reproducible analyses, and independently verified by two of the authors. Although wider field of view images do not provide the resolution to be informative on cell location, as requested we have provided uncropped images in new Fig. S4 for all the cell lines shown in Figure 2A.

In addition, we have included as supplementary images (Fig. S3B) additional images of TelR-TALE-YFP, 177R-TALE-YFP and ingiR-TALE YFP localisation to provide additional support their observed locations presented in Figure 1. The set of cells and images presented in Figure 2A and in Fig S3B were prepared and obtained by a different authors, independently and reproducibly validating the location of the tagged protein.

2) I think Suppl. Fig. 1 is very valuable, as it is a quantification and summary of the ChIP-seq data. I think the authors could consider making this a panel of a main figure. For the main figure, I think the plot could be trimmed down to only show the background and the relevant repeat for each TALE protein, leaving out the non-target repeats. (This relates to minor comment 6.) Also, I believe, it was not explained how background enrichment was calculated.

Response

We are grateful for the reviewer's positive view of original Fig. S1 and appreciate the suggestion. We have now moved these analysis to part B of main Figure 2 in the revised manuscript - now Figure 2B. We have also provided additional details in the Methods section on the approaches used to assess background enrichment.

Page 19:

Background enrichment calculation

The genome was divided into 50 bp sliding windows, and each window was annotated based on overlapping genomic features, including CIR147, 177 bp repeats, 70 bp repeats, and telomeric (TTAGGG)n repeats. Windows that did not overlap with any of these annotated repeat elements were defined as "background" regions and used to establish the baseline ChIP-seq signal. Enrichment for each window was calculated using bamCompare, as log₂(IP/Input). To adjust for background signal amongst all samples, enrichment values for each sample were further normalized against the corresponding No-YFP ChIP-seq dataset.

Note: While revising the manuscript we also noticed that the script had a nomalization error. We have therefore included a corrected version of these analyses as Figure 2B (old Fig. S1)

3) Generally, I would plot enrichment on a log2 axis. This concerns several figures with ChIP-seq data.

Response

Our ChIP-seq enrichment is calculated by bamCompare. The resulting enrichment values are indeed log2 (IP/Input). We have made this clear in the updated figures/legends.

4) Fig. 4C - The violin plots are very hard to interpret, as the plots are very narrow compared to the line thickness, making it hard to judge the actual volume. For example, in Centromere 5, YFP-KKT2 is less enriched than 147R-TALE over most of the centromere with some peaks of much higher enrichment (as visible in panel B), however, in panel C, it is very hard to see this same information. I'm sure there is some way to present this better, either using a different type of plot or by improving the spacing of the existing plot.

Response

We thank the reviewer for this suggestion; we have elected to provide a Split-Violin plot instead. This improves the presentation of the data for each centromere. The original violin plot in Figure 4C has been replaced with this Split-Violin plot (still Figure 4C).

5) Fig. 6 - The panels are missing an x-axis label (although it is obvious from the plot what is displayed). Maybe the "WT NO-YFP vs" part that is repeated in all the plot titles could be removed from the title and only be part of the x-axis label?

Response

In fact, to save space the X axis was labelled inside each volcano plot but we neglected to indicate that values are a log2 scale indicating enrichment. This has been rectified - see Figure 6, and Fig. S7, S8 and S9.

6) Fig. 7 - I would like to have a quantification for the examples shown here. In fact, such a quantification already exists in Suppl. Figure 1. I think the relevant plots of that quantification (YFP-KKT2 over 177bp-repeats and centromere-repeats) with some control could be included in Fig. 7 as panel C. This opportunity could be used to show enrichment separated out for intermediate-sized, mini-, and megabase-chromosomes. (relates to minor comment 2 & 8)

Response

The CIR147 sequence is found exclusively on megabase-sized chromosomes, while the 177 bp repeats are located on intermediate- and mini-sized chromosomes. Due to limitations in the current genome assembly, it is not possible to reliably classify all chromosomes into intermediate- or mini- sized categories based on their length. Therefore, original Supplementary Fig. S1 presented the YFP-KKT2 enrichment over CIR147 and 177 bp repeats as a representative comparison between megabase chromosomes and the remaining chromosomes (corrected version now presented as main Figure 2B). Additionally, to allow direct comparison of YFP-KKT2 enrichment on CIR147 and 177 bp repeats we have included a new plot in Figure 7C which shows the relative enrichment of YFP-KKT2 on these two repeat types.

We have added the following text , page 12:

"Taking into account the relative to the number of CIR147 and 177 bp repeats in the current T.brucei genome (Cosentino et al., 2021; Rabuffo et al., 2024), comparative analyses demonstrated that YFP-KKT2 is enriched on both CIR147 and 177 bp repeats (Figure 7C)."

7) Suppl. Fig. 8 A - I believe there is a mistake here: KKT5 occurs twice in the plot, the one in the overlap region should be KKT1-4 instead, correct?

Response

Thanks for spotting this. It has been corrected

8) The way that the authors mapped ChIP-seq data is potentially problematic when analyzing the same repeat type in different regions of the genome. The authors assigned reads that had multiple equally good mapping positions to one of these mapping positions, randomly. This is perfectly fine when analysing repeats by their type, independent of their position on the genome, which is what the authors did for the main conclusions of the work. However, several figures show the same type of repeat at different positions in the genome. Here, the authors risk that enrichment in one region of the genome 'spills' over to all other regions with the same sequence. Particularly, where they show YFP-KKT2 enrichment over intermediate- and mini-chromosomes (Fig. 7) due to the spillover, one cannot be sure to have found KKT2 in both regions. Instead, the authors could analyze only uniquely mapping reads / read-pairs where at least one mate is uniquely mapping. I realize that with this strict filtering, data will be much more sparse. Hence, I would suggest keeping the original plots and adding one more quantification where the enrichment over the whole region (e.g., all 177bp repeats on intermediate-/mini-chromosomes) is plotted using the unique reads (this could even be supplementary). This also applies to Fig. 4 B & C.

Response

We thank the reviewer for their thoughtful comments. Repetitive sequences are indeed challenging to analyze accurately, particularly in the context of short read ChIP-seq data. In our study, we aimed to address YFP-KKT2 enrichment not only over CIR147 repeats but also on 177 bp repeats, using both ChIP-seq and proteomics using synthetic TALE proteins targeted to the different repeat types. We appreciate the referees suggestion to consider uniquely mapped reads, however, in the updated genome assembly, the 177 bp repeats are frequently immediately followed by long stretches of 70 bp repeats which can span several kilobases. The size and repetitive nature of these regions exceeds the resolution limits of ChIP-seq. It is therefore difficult to precisely quantify enrichment across all chromosomes.

Additionally, the repeat sequences are highly similar, and relying solely on uniquely mapped reads would result in the exclusion of most reads originating from these regions, significantly underestimating the relative signals. To address this, we used Bowtie2 with settings that allow multi-mapping, assigning reads randomly among equivalent mapping positions, but ensuring each read is counted only once. This approach is designed to evenly distribute signal across all repetitive regions and preserve a meaningful average.

Single molecule methods such as DiMeLo (Altemose et al. 2022; PMID: 35396487) will need to be developed for T. brucei to allow more accurate and chromosome specific mapping of kinetochore or telomere protein occupancy at repeat-unique sequence boundaries on individual chromosomes.

Reviewer #2 (Significance (Required)):

This work is of high significance for chromosome/centromere biology, parasitology, and the study of antigenic variation. For chromosome/centromere biology, the conceptual advancement of different types of kinetochores for different chromosomes is a novelty, as far as I know. It would certainly be interesting to apply this study as a technical blueprint for other organisms with mini-chromosomes or chromosomes without known centromeric repeats. I can imagine a broad range of labs studying other organisms with comparable chromosomes to take note of and build on this study. For parasitology and the study of antigenic variation, it is crucial to know how intermediate- and mini-chromosomes are stable through cell division, as these chromosomes harbor a large portion of the antigenic repertoire. Moreover, this study also found a novel link between the homologous repair pathway and variant surface glycoproteins, via the 70bp repeats. How and at which stages during the process, 70bp repeats are involved in antigenic variation is an unresolved, and very actively studied, question in the field. Of course, apart from the basic biological research audience, insights into antigenic variation always have the potential for clinical implications, as T. brucei causes sleeping sickness in humans and nagana in cattle. Due to antigenic variation, T. brucei infections can be chronic.

Response

Thank you for supporting the novelty and broad interest of our manuscript

My field of expertise / Point of view:

I'm a computer scientist by training and am now a postdoctoral bioinformatician in a molecular parasitology laboratory. The laboratory is working on antigenic variation in T. brucei. The focus of my work is on analyzing sequencing data (such as ChIP-seq data) and algorithmically improving bioinformatic tools.

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Referee #2

Evidence, reproducibility and clarity

Summary

Carloni et al. comprehensively analyze which proteins bind repetitive genomic elements in Trypanosoma brucei. For this, they perform mass spectrometry on custom-designed, tagged programmable DNA-binding proteins. After extensively verifying their programmable DNA-binding proteins (using bioinformatic analysis to infer target sites, microscopy to measure localization, ChIP-seq to identify binding sites), they present, among others, two major findings: 1) 14 of the 25 known T. brucei kinetochore proteins are enriched at 177bp repeats. As T. brucei's 177bp repeat-containing intermediate-sized and mini-chromosomes lack centromere repeats but are stable over mitosis, Carloni et al. use their data to hypothesize that a 'rudimentary' kinetochore assembles at the 177bp repeats of these chromosomes to segregate them. 2) 70bp repeats are enriched with the Replication Protein A complex, which, notably, is required for homologous recombination. Homologous recombination is the pathway used for recombination-based antigenic variation of the 70bp-repeat-adjacent variant surface glycoproteins.

Major Comments

None. The experiments are well-controlled, claims well-supported, and methods clearly described. Conclusions are convincing.

Minor Comments

1. Fig. 2 - I couldn't find an uncropped version showing multiple cells. If it exists, it should be linked in the legend or main text; Otherwise, this should be added to the supplement.
2. I think Suppl. Fig. 1 is very valuable, as it is a quantification and summary of the ChIP-seq data. I think the authors could consider making this a panel of a main figure. For the main figure, I think the plot could be trimmed down to only show the background and the relevant repeat for each TALE protein, leaving out the non-target repeats. (This relates to minor comment 6.) Also, I believe, it was not explained how background enrichment was calculated.
3. Generally, I would plot enrichment on a log2 axis. This concerns several figures with ChIP-seq data.
4. Fig. 4C - The violin plots are very hard to interpret, as the plots are very narrow compared to the line thickness, making it hard to judge the actual volume. For example, in Centromere 5, YFP-KKT2 is less enriched than 147R-TALE over most of the centromere with some peaks of much higher enrichment (as visible in panel B), however, in panel C, it is very hard to see this same information. I'm sure there is some way to present this better, either using a different type of plot or by improving the spacing of the existing plot.
5. Fig. 6 - The panels are missing an x-axis label (although it is obvious from the plot what is displayed). Maybe the "WT NO-YFP vs" part that is repeated in all the plot titles could be removed from the title and only be part of the x-axis label?
6. Fig. 7 - I would like to have a quantification for the examples shown here. In fact, such a quantification already exists in Suppl. Figure 1. I think the relevant plots of that quantification (YFP-KKT2 over 177bp-repeats and centromere-repeats) with some control could be included in Fig. 7 as panel C. This opportunity could be used to show enrichment separated out for intermediate-sized, mini-, and megabase-chromosomes. (relates to minor comment 2 & 8)
7. Suppl. Fig. 8 A - I believe there is a mistake here: KKT5 occurs twice in the plot, the one in the overlap region should be KKT1-4 instead, correct?
8. The way that the authors mapped ChIP-seq data is potentially problematic when analyzing the same repeat type in different regions of the genome. The authors assigned reads that had multiple equally good mapping positions to one of these mapping positions, randomly. This is perfectly fine when analyzing repeats by their type, independent of their position on the genome, which is what the authors did for the main conclusions of the work. However, several figures show the same type of repeat at different positions in the genome. Here, the authors risk that enrichment in one region of the genome 'spills' over to all other regions with the same sequence. Particularly, where they show YFP-KKT2 enrichment over intermediate- and mini-chromosomes (Fig. 7) due to the spillover, one cannot be sure to have found KKT2 in both regions. Instead, the authors could analyze only uniquely mapping reads / read-pairs where at least one mate is uniquely mapping. I realize that with this strict filtering, data will be much more sparse. Hence, I would suggest keeping the original plots and adding one more quantification where the enrichment over the whole region (e.g., all 177bp repeats on intermediate-/mini-chromosomes) is plotted using the unique reads (this could even be supplementary). This also applies to Fig. 4 B & C.

Significance

This work is of high significance for chromosome/centromere biology, parasitology, and the study of antigenic variation. For chromosome/centromere biology, the conceptual advancement of different types of kinetochores for different chromosomes is a novelty, as far as I know. It would certainly be interesting to apply this study as a technical blueprint for other organisms with mini-chromosomes or chromosomes without known centromeric repeats. I can imagine a broad range of labs studying other organisms with comparable chromosomes to take note of and build on this study. For parasitology and the study of antigenic variation, it is crucial to know how intermediate- and mini-chromosomes are stable through cell division, as these chromosomes harbor a large portion of the antigenic repertoire. Moreover, this study also found a novel link between the homologous repair pathway and variant surface glycoproteins, via the 70bp repeats. How and at which stages during the process, 70bp repeats are involved in antigenic variation is an unresolved, and very actively studied, question in the field. Of course, apart from the basic biological research audience, insights into antigenic variation always have the potential for clinical implications, as T. brucei causes sleeping sickness in humans and nagana in cattle. Due to antigenic variation, T. brucei infections can be chronic.

My field of expertise / Point of view:

I'm a computer scientist by training and am now a postdoctoral bioinformatician in a molecular parasitology laboratory. The laboratory is working on antigenic variation in T. brucei. The focus of my work is on analyzing sequencing data (such as ChIP-seq data) and algorithmically improving bioinformatic tools.

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Referee #1

Evidence, reproducibility and clarity

Summary

In this article, the authors used the synthetic TALE DNA binding proteins, tagged with YFP, which were designed to target five specific repeat elements in Trypanosoma brucei genome, including centromere and telomeres-associated repeats and those of a transposon element. This is in order to detect and identified, using YFP-pulldown, specific proteins that bind to these repetitive sequences in T. brucei chromatin. Validation of the approach was done using a TALE protein designed to target the telomere repeat (TelR-TALE) that detected many of the proteins that were previously implicated with telomeric functions. A TALE protein designed to target the 70 bp repeats that reside adjacent to the VSG genes (70R-TALE) detected proteins that function in DNA repair and the protein designed to target the 177 bp repeat arrays (177R-TALE) identified kinetochore proteins associated T. brucei mega base chromosomes, as well as in intermediate and mini-chromosomes, which imply that kinetochore assembly and segregation mechanisms are similar in all T. brucei chromosome.

Major comments:

Are the key conclusions convincing?

The authors reported that they have successfully used TALE-based affinity selection of protein-associated with repetitive sequences in the T. brucei genome. They claimed that this study has provided new information regarding the relevance of the repetitive region in the genome to chromosome integrity, telomere biology, chromosomal segregation and immune evasion strategies. These conclusions are based on high-quality research and it is, basically, merits publication, provided that some major concerns, raised below, will be addressed before acceptance for publication. 1. The authors used TALE-YFP approach to examine the proteome associated with five different repetitive regions of the T. brucei genome and confirmed the binding of TALE-YFP with Chip-seq analyses. Ultimately, they got the list of proteins that bound to synthetic proteins, by affinity purification and LS-MS analysis and concluded that these proteins bind to different repetitive regions of the genome. There are two control proteins, one is TRF-YFP and the other KKT2-YFP, used to confirm the interactions. However, there are no experiment that confirms that the analysis gives some insight into the role of any putative or new protein in telomere biology, VSG gene regulation or chromosomal segregation. The proteins, which have already been reported by other studies, are mentioned. Although the author discovered many proteins in these repetitive regions, their role is yet unknown. It is recommended to take one or more of the new putative proteins from the repetitive elements and show whether or not they (1) bind directly to the specific repetitive sequence (e.g., by EMSA); (2) it is recommended that the authors will knockdown of one or a small sample of the new discovered proteins, which may shed light on their function at the repetitive region, as a proof of concept. 2. NonR-TALE-YFP does not have a binding site in the genome, but YFP protein should still be expressed by T. brucei clones with NLS. The authors have to explain why there is no signal detected in the nucleus, while a prominent signal was detected near kDNA (see Fig.2). Why is the expression of YFP in NonR-TALE almost not shown compared to other TALE clones? 3. As a proof of concept, the author showed that the TALE method determined the same interacting partners enrichment in TelR-TALE as compared to TRF-YFP. And they show the same interacting partners for other TALE proteins, whether compared with WT cells or with the NonR-TALE parasites. It may be because NonR-TALE parasites have almost no (or very little) YFP expression (see Fig. S3) as compared to other TALE clones and the TRF-YFP clone. To address this concern, there should be a control included, with proper YFP expression. 4. After the artificial expression of repetitive sequence binding five-TALE proteins, the question is if there is any competition for the TALE proteins with the corresponding endogenous proteins? Is there any effect on parasite survival or health, compared to the control after the expression of these five TALEs YFP protein? It is recommended to add parasite growth curves, for all the TALE-proteins expressing cultures. 5. Since the experiments were performed using whole-cell extracts without prior nuclear fractionation, the authors should consider the possibility that some identified proteins may have originated from compartments other than the nucleus. Specifically, the detection of certain binding proteins might reflect sequence homology (or partial homology) between mitochondrial DNA (maxicircles and minicircles) and repetitive regions in the nuclear genome. Additionally, the lack of subcellular separation raises the concern that cytoplasmic proteins could have been co-purified due to whole cell lysis, making it challenging to discern whether the observed proteome truly represents the nuclear interactome.

Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

As mentioned earlier, the author claimed that this study has provided new information concerning telomere biology, chromosomal segregation mechanisms, and immune evasion strategies. But there are no experiments that provides a role for any unknown or known protein in these processes. Thus, it is suggested to select one or two proteins of choice from the list and validate their direct binding to repetitive region(s), and their role in that region of interaction. <br /> 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 answer for this question depends on what the authors want to present as the achievements of the present study. If the achievement of the paper was is the creation of a new tool for discovering new proteins, associated with the repeat regions, I recommend that they add a proof for direct interactions between a sample the newly discovered proteins and the relevant repeats, as a proof of concept discussed above, However, if the authors like to claim that the study achieved new functional insights for these interactions they will have to expand the study, as mentioned above, to support the proof of concept.

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.

I think that they are realistic. If the authors decided to check the capacity of a small sample of proteins (which was unknown before as a repetitive region binding proteins) to interacts directly with the repeated sequence, it will substantially add of the study (e.g., by EMSA; estimated time: 1 months). If the authors will decide to check the also the function of one of at least one such a newly detected proteins (e.g., by KD), I estimate the will take 3-6 months.

Are the data and the methods presented in such a way that they can be reproduced?

Yes

Are the experiments adequately replicated, and statistical analysis adequate?

The authors did not mention replicates. There is no statistical analysis mentioned.

Minor comments:

Specific experimental issues that are easily addressable.

The following suggestions can be incorporated:

1. Page 18, in the material method section author mentioned four drugs: Blasticidine, Phleomycin and G418, and hygromycin. It is recommended to mention the purpose of using these selective drugs for the parasite. If clonal selection has been done, then it should also be mentioned.
2. In the method section the authors mentioned that there is only one site for binding of NonR-TALE in the parasite genome. But in Fig. 1C, the authors showed zero binding site. So, there is one binding site for NonR-TALE-YFP in the genome or zero?
3. The authors used two different anti-GFP antibodies, one from Roche and the other from Thermo Fisher. Why were two different antibodies used for the same protein?
4. Page 6: in the introduction, the authors give the number of total VSG genes as 2,634. Is it known how many of them are pseudogenes?
5. I found several typos throughout the manuscript.
6. Fig. 1C: Table: below TOTAL 2nd line: the number should be 1838 (rather than 1828)

Are prior studies referenced appropriately?

Yes

Are the text and figures clear and accurate?

Yes

Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

Suggested above

Significance

Describe the nature and significance of the advance (e.g., conceptual, technical, clinical) for the field:

This study represents a significant conceptual and technical advancement by employing a synthetic TALE DNA-binding protein tagged with YFP to selectively identify proteins associated with five distinct repetitive regions of T. brucei chromatin. To the best of my knowledge, it is the first report to utilize TALE-YFP for affinity-based isolation of protein complexes bound to repetitive genomic sequences in T. brucei. This approach enhances our understanding of chromatin organization in these regions and provides a foundation for investigating the functional roles of associated proteins in parasite biology. Importantly, any essential or unique interacting partners identified could serve as potential targets for therapeutic intervention.

Place the work in the context of the existing literature (provide references, where appropriate).

I agree with the information that has already described in the submitted manuscript, regarding its potential addition of the data resulted and the technology established to the study of VSGs expression, kinetochore mechanism and telomere biology.

State what audience might be interested in and influenced by the reported findings.

These findings will be of particular interest to researchers studying the molecular biology of kinetoplastid parasites and other unicellular organisms, as well as scientists investigating chromatin structure and the functional roles of repetitive genomic elements in higher eukaryotes.

1Define your field of expertise with a few keywords to help the authors contextualize your point of view. 2Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

1. Protein-DNA interactions/ chromatin/ DNA replication/ Trypanosomes
2. None

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Reply to the reviewers

This is a reply/revision plan, not definitive. Planned and already implemented revisions are underlined.

First of all, we wish to express our gratitude to the reviewers: they helped to improve the paper.

Reviewer #1:* **

Reviewer #1 wrote: Major Comments: 1.Differential gene/pathway analysis across epithelial clusters: What are the differential genes or pathways among the epithelial clusters? Without CCA/Harmony integration, do the tumor subgroups show distinct differences? In addition, I suggest applying NMF or hdWGCNA to identify shared modules and test whether ATC and PTC harbor overlapping regulatory modules.

*

Reply plan: Both reviewers suggested some regulatory network analysis. We proposed to run SCENIC+ (Nature Methods, 2023, https://doi.org/10.1038/s41592-023-01938-4) on our data__.__

* Reviewer #1 wrote: 2.Validation of TSHR/TPO-based subgrouping: While the TSHR/TPO grouping appears appropriate for stratification at the single-cell level, it is necessary to exclude sequencing depth as a confounding factor. Should validate the existence of these subpopulations using mIHC/IF on corresponding samples. *

__Reply plan: __We made claims about RNA expression, not protein expression. Thus, validation should be at the RNA level:

• We already replicated part of our analysis on the dataset published by Lu et al. (JCI 2023, https://doi.org/10.1172/JCI169653), see Figs. 3 and 4. This effort will be extended to all single cell analysis results from our study in the revised paper.
• We will also present plots demonstrating that the sequencing depth is similar in the different cancer cell subgroups-further excluding it as a confounding factor. Reviewer #1 wrote: *3.Impact of mutational differences on conclusions: According to Supplementary Table 1, almost all PTC cases carried BRAF mutations, whereas four ATC patients harbored no BRAF mutation. Could this difference influence the conclusions of the study? Although the authors briefly mention this in the Discussion, a more thorough clarification is warranted. *

Reply plan: The dataset of Lu et al. includes BRAF-mutated ATCs along with BRAF-mutated PTCs. Therefore, the replication mentioned earlier will also address those concerns. In fact, Fig. 4E-I already confirm in Lu et al. data the ordered loss of markers. Replication will be extended to other results of the study and be more emphasized in the paper.

* Reviewer #1 wrote: 4. The statement "Myeloid and T cells also grouped in specific clusters" seems descriptive. Is this clustering biologically meaningful? Please elaborate.

*

__Reply plan: __This is an important point, and accordingly, a cell mixing experiment was specifically designed to sort apart technical effects from biological effects. We therefore know with certainty that the myeloid and T cell patients-specific clusters are the result of biological variation (Fig. 1). We further demonstrate that part of this variation is associated with hypoxia (Supp. Fig 4). So yes, the clustering is biologically meaningful.

* Reviewer #1 wrote: Minor Comments: In Figure 2C, the "Epith TSHR-" population resembles myeloid cells. Could the authors clarify why this is the case? For the correlation analysis in Figure 2C, were highly variable genes or all genes used?

*

Reply plan: There is a simple explanation: The Epith TSHR- population the reviewer is referring to are cells from anaplastic thyroid cancers (ATC), which are tumors notoriously infiltrated by macrophages (Supp. Fig. 4). A high correlation of Epith TSHR- and macrophages proportion across our panel of ATC and papillary cancer (PTC) is therefore expected. Among other things, Fig. 2C shows that high correlation, but it is not meant to and does not show that Epith TSHR- and macrophages "resemble" one another. It shows that their proportions are highly positively correlated. This correlation analysis does not rely on gene expression but on cell type proportions. It measures co-occurrence rather than resemblance. The text has been clarified in order to prevent any confusion.

• *

* __Reviewer #2: __

Reviewer #2 wrote: 1. This study largely confirms established facts that 1) PTC due to BRAF driver mutation is a heterogeneous tumour entity and 2) ATC is the most dedifferentiated of all thyroid cancers. Although interesting, observations of a highly variable tissue cell composition including immune cells and the gradual loss of thyroid differentiation markers, in part linked to tumor subclone development featured by altered chromosomal copy numbers, are thus not surprising.

*

__Reply plan: __We wish to respectfully express our take on this perception of the work:

• There is a difference between conjecturing a high heterogeneity in the cell composition of thyroid cancers and establishing it with the level of accuracy and quantitative rigor our analysis provides. The extreme amplitude of that variation was surprising to us: the size of the microenvironment makes from 8.4 to 80% of the cells in PTCs driven by the same BRAF mutation.
• We don't simply show that a subclone characterized by a large number of copy number events is less differentiated. We go all the way proving that those copy number alterations are associated with specific cell states that produce specific histology (Fig. 5). It required a combination of single cell transcriptomics, spatial transcriptomics and sophisticated computational analysis to establish that connection between genomic changes and histology. The fragmentation of epithelial sheets uncovered from CNV analysis had escaped the attention of pathologist colleagues and ours at first, this is not a parameter typically assessed in diagnostic, to our knowledge.
• We don't simply show that there is a gradual loss of differentiation markers: this loss is ordered in a very specific way that mirrors the gain of markers during thyroid organoid differentiation. * Reviewer #2 wrote: 2. Considering tumor progression, comparison of PTC and ATC should preferably include specimens with the same driver mutation (BRAF or RAS), which is not the case here. This notion should be more clearly explained to readers. An optional improvement would be to conduct similar analyses on an ATC specimen that contains more differentiated PTC tumor portions arguably suggesting that PTC progresses to ATC (by mechanisms that are still largely unexplored).

*

__Reply plan: __This is clearly a limitation of our study. As already proposed in our reply to reviewer number one, we will extend to all our single cell results the replication of our analysis in the dataset of Lu e al., which includes ATCs and PTCs harboring the BRAF-mutation.

* Reviewer #2 wrote: 3. Comments on findings of lymphocytic infiltration need to be balanced. Although autoimmune thyroid disease in infered a risk factor of developing malignancy it is unlikely that the majority of TCGA samples of PTC is associated with thyroiditis as indicated in Fig. 3 and Suppl Fig. 3. Immune cell abundance may rather reflect the tumor immune microenvironment (TIME).

*

__Reply plan: __The figure the reviewer is referring to demonstrates that PTC occurring in a background of thyroiditis also has a higher proportion of B cells. We did not claim, and the figure did not show, that "the majority of TCGA samples of PTC is associated with thyroiditis", because they don't. This point has been clarified.

* Reviewer #2 wrote: 4. Some tissue sections seem of quite poor quality either shape-wise of containing rifts e.g. PTC7 in Fig. 3 and PTC2 in Fig. 5. The authors should explain whether and how this might influence analysis.

*

__Reply plan: __Spatial transcriptomics is typically performed on frozen sections. Frozen sections, which are obviously of lower visual quality than slice from FFPE preserved samples. Since no computational analyses were performed on the image, this lower quality has no impact on our results. Regarding RNA quality, the RINs were >7 for all tumors. RINs are now presented in Supp table S1.

Reviewer #2 wrote: The experiment on mouse ESC/organoids (Fig. 6H-J) does not show much of an expected enhanced thyroid progenitor cell proliferation after induction of the mutant Braf allele by tamoxifen, which raises doupt whether the subsequent promoted growth by fibronectin at all is oncogene-related. This differs from the impact of BrafCA activation along with mouse thyroid development in vivo (Schoultz et al iScience 2023 PMID: 37534159). In the same experimental setup, it appears that mutant Braf prevents follicle formation (Fig. 6I). A control experiment investigating the influence of fibronectin in the absence of oncogene activation should be conclusive. The effect of Braf and fibronectin on thyroid organoid structure and function should be better explained, if necessary based on complementary experiments, and discussed in relation to the claimed association of fibronectin expression to "...low amounts of thyroid differentiation markers...) and "...loss of epithelial structure (PTC7, Figure 6E)." in the previous section of Results.

__Reply plan: __The induction of the mutant Braf allele for 7 days increases the percentage of BrdU+ cells by 1.43 fold (p-value for Wilcoxon test = 0.035). The effects observed by Schoultz et al. are certainly more dramatic, but they result from an oncogenic activity spanning 1 to 6 months (4 to 26 times longer) in an in vivo model. Most importantly, oncogenic activity is initiated in Nkx2.1+ cells and not Tg+ cells, thus much earlier during development. These two models are thus not comparable. As for the effects of fibronectin on thyroid structure, we do not claim that our organoid model recapitulates the complex interactions between cancer cells and their microenvironment that shapes tissue morphology in vivo. This is now clarified in the text.

We presented controls with no oncogene expression and no Fn1, controls with oncogene induction and no FN1 and organoids with oncogene induction and Fn1 treatment. This alone establishes the effect of Fn1 on induced organoids, which was our goal. We regard it as a novel and interesting but non-essential development in our paper.

As the reviewer points out, while our results show an increased proliferation in Braf-mutated organoids treated with Fn1, they do not allow us to conclude on any potential interaction between Fn1 and the oncogenic process. The suggested experiment with Fn1 in absence of oncogene activation would add information, but we cannot follow up for practical lab management reasons detailed in Section 4 below.

* Reviewer #2 wrote: 6. Concerning EMT profiling (Supplementary Fig. 7B) , there is a great similarity of ATC tumor cells and fibroblasts, and as stated in the text the malignant status of the former is indicated by chromosomal aberrations (refering to Suppl fig. 6). However, looking at Suppl. Fig. 7B it is evident that fractions of cells identified as fibroblasts express TG and TSHR suggesting mismatch. How was this comparison done in order to exclude mismatch? Is there no other profiled markers that distinguish cancer cells from stromal cells that can support conclusions?*

Reply plan: TG-a thyrocyte marker-seems expressed by fibroblasts in Supplementary Figure 7B. The reviewer suggests this could be caused by an incomplete distinction between bona fide fibroblasts and thyrocytes in advanced EMT state. We argue that

• Ambient TG RNA leaking out of thyrocytes nuclei contaminates the transcriptomes of all cell types. It is a well-known technical problem, with dedicated software packages to mitigate it. We preprocessed our data with one of them, SoupX, which corrected for most, but not all, ambient RNA contamination.
• The plot below shows that there is nothing special about fibroblasts in that respect. For example, B and T cells are contaminated by TG at levels comparable to fibroblasts, endothelial cells and pericyte to higher levels.
• In addition, the UMAP of Fig. 2A shows that EMT cells and fibroblast form very distinct clusters. Furthermore, the fibroblast cluster but not the two EMT clusters contain cells from PTC, and the PTC cluster do not contain cells with DNA copy number aberration. Thus, although both EMT cells and fibroblasts express the typical mesenchymal marker of Supplementary Fig. 7B, they are easy to distinguish on the basis of their overall transcriptomes.
• The panel below has been added to the Supplementary Figure 7B. [Panel cannot be displayed here]

Reviewer #2 wrote: *In the same figure, it appears there are no clear differences in EMT marker expression among PTC samples regardless of differentiation state, suggesting that the gradual loss of thyroid differentiation in PTC tumor cells and EMT are not parallel and potentially linked phenomena? Please clarify this dissociation of results. Is possible that refocusing on other EMT markers than the top 10, of which almost all concerns various collagen genes, might better reveal partial EMT in PTCs?

*

__Reply plan: __The technical basis of this comment is related to the previous point. Our perception is that the mesenchymal markers in Supplementary Fig. 7B show a binary effect, i.e. strong expression in ATC and no expression in PTC (beyond ambient RNA noise)-not a gradual effect. Thus, there is no correlation of COL1A1 and other mesenchymal markers with dedifferentiation in PTC as these markers are not expressed beyond the noise level of the experiments. A lot has been written about EMT in PTC, but one of the findings of our study is that while ATC undergo full EMT, EMT in PTC is very limited. PTC express FN1 but no other major mesenchymal markers such as collagens I and III, for example.

• *

Reviewer #2 wrote: *7. According to Suppl. Table 1, the ATC2 tumor does not harbor any mutations. What about chromosomal aberrations, was that included in analysis? Considering previous consistent reports of a high mutation burden in ATC, if not supported by other data (clinical, pathological) the diagnosis might be questioned for this particular case included in multiple analyses of the present study.

*

Reply: There is little doubt about the diagnostic of ATC2 by our pathologist collaborators

• The histology of this tumor is strikingly anaplastic, i.e. without structure, as shown in the image below.
• This tumor has a high level of macrophages infiltration typical of ATCs (Supplementary Fig. 4).
• Reviewer #2 wrote: Minor comments: -The logical order of presentation of Results might benefit from first presenting specific PTC data following by ATC dito. I´m thinking of swapping the section of EMT in ATC to end of Results.*

*Reply plan: We miss why the reviewer thinks that way. We believe that discussing the microenvironment, then tumor cells bring conciseness and clarity about how we propose to stratify the latter. By contrast, the suggested tumor type-centered structure entails going back and forth between the microenvironment and tumor cells, diluting the messages about both.

* Reviewer #2 wrote: -Methods paragraph "Mouse ESC-derived thyroid organoids experiments" (starting with "ccc") seems to be missing some essential information.

*Reply plan: A sentence was missing, indeed, and has been re-introduced in the manuscript. We thank the reviewer for catching that error.

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Referee #2

Evidence, reproducibility and clarity

Summary:

Expression pattern profiling of human thyroid cancer tissues by combining single cell/nuclei RNAseq analysis, spatial transcriptomics and immunofluorescence on corresponding tumor histologic sections. Papillary and anaplastic thyroid carcinomas (PTC n=10 and ATC n=4) were compared; some data were extracted from TCGA. The results indicate that ATCs consists of completely dedifferentiated tumor cells whereas PTCs show variable levels of dedifferentiation, which in a sense mimics the the reverse process of thyroid differentiation as observed in stem cell-based organoids. Moreover, PTC and ATC tumors show different levels of epithelial-mesenchymal transition. Fibronectin is inferred a role in promoting tumor growth, supported by functional studies on organoids. Authors suggest that global profiling of differentiation state is a promising technique to stratifiy tumor heterogeneity, with potentially might be useful distinguishing thyroid malignancies suitable or not to adjuvant treatment e.g. with radioiodine (RAI) therapy.

Major comments:

1. This study largely confirms established facts that 1) PTC due to BRAF driver mutation is a heterogeneous tumour entity and 2) ATC is the most dedifferentiated of all thyroid cancers. Although interesting, observations of a highly variable tissue cell composition including immune cells and the gradual loss of thyroid differentiation markers, in part linked to tumor subclone development featured by altered chromosomal copy numbers, are thus not surprising.
2. Considering tumor progression, comparison of PTC and ATC should preferably include specimens with the same driver mutation (BRAF or RAS), which is not the case here. This notion should be more clearly explained to readers. An optional improvement would be to conduct similar analyses on an ATC specimen that contains more differentiated PTC tumor portions arguably suggesting that PTC progresses to ATC (by mechanisms that are still largely unexplored).
3. Comments on findings of lymphocytic infiltration need to be balanced. Although autoimmune thyroid disease in infered a risk factor of developing malignancy it is unlikely that the majority of TCGA samples of PTC is associated with thyroiditis as indicated in Fig. 3 and Suppl Fig. 3. Immune cell abundance may rather reflect the tumor immune microenvironment (TIME).
4. Some tissue sections seem of quite poor quality either shape-wise of containing rifts e.g. PTC7 in Fig. 3 and PTC2 in Fig. 5. The authors should explain whether and how this might influence analysis.
5. The experiment on mouse ESC/organoids (Fig. 6H-J) does not show much of an expected enhanced thyroid progenitor cell proliferation after induction of the mutant Braf allele by tamoxifen, which raises doupt whether the subsequent promoted growth by fibronectin at all is oncogene-related. This differs from the impact of BrafCA activation along with mouse thyroid development in vivo (Schoultz et al iScience 2023 PMID: 37534159). In the same experimental setup, it appears that mutant Braf prevents follicle formation (Fig. 6I). A control experiment investigating the influence of fibronectin in the absence of oncogene activation should be conclusive. The effect of Braf and fibronectin on thyroid organoid structure and function should be better explained, if necessary based on complementary experiments, and discussed in relation to the claimed association of fibronectin expression to "...low amounts of thyroid differentiation markers...) and "...loss of epithelial structure (PTC7, Figure 6E)." in the previous section of Results.
6. Concerning EMT profiling (Supplementary Fig. 7B) , there is a great similarity of ATC tumor cells and fibroblasts, and as stated in the text the malignant status of the former is indicated by chromosomal aberrations (refering to Suppl fig. 6). However, looking at Suppl. Fig. 7B it is evident that fractions of cells identified as fibroblasts express TG and TSHR suggesting mismatch. How was this comparison done in order to exclude mismatch? Is there no other profiled markers that distinguish cancer cells from stromal cells that can support conclusions? In the same figure, it appears there are no clear differences in EMT marker expression among PTC samples regardless of differentiation state, suggesting that the gradual loss of thyroid differentiation in PTC tumor cells and EMT are not parallel and potentially linked phenomena? Please clarify this dissociation of results. Is is possible that refocusing on other EMT markers than the top 10, of which almost all concerns various collagen genes, might better reveal partial EMT in PTCs?
7. According to Suppl. Table 1, the ATC2 tumor does not harbor any mutations. What about chromosomal aberrations, was that included in analysis? Considering previous consistent reports of a high mutation burden in ATC, if not supported by other data (clinical, pathological) the diagnosis might be questioned for this particular case included in multiple analyses of the present study.

Minor comments:

• The logical order of presentation of Results might benefit from first presenting specific PTC data following by ATC dito. I´m thinking of swapping the section of EMT in ATC to end of Results.
• Methods paragraph "Mouse ESC-derived thyroid organoids experiments" (starting with "ccc") seems to be missing some essential information.

Significance

The study confirms at single cell level the fundamental difference of PTC and ATC that is evident clinically and biologically, but does not address the intriguing issue how ATC may progress from PTC.

Tumor heterogeneity of BRAFV600E-driven PTC in terms of dedifferentiation of functional parameters, which are of potential clinical relevance, is well documented.

Reviewer expertise: thyroid development, thyroid cell and tumor biology, superficial knowledge in scRNAseq analysis

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Referee #1

Evidence, reproducibility and clarity

This study is well designed with a rational sample collection strategy. The authors collected PTC and ATC tissue samples for snRNA and spRNA sequencing, clearly characterizing tumor heterogeneity. Using representative thyroid differentiation markers (TSHR, TPO, TG, NIS), they distinguished different differentiation states of PTC and ATC and further validated the role of FN1 in organoid models. However, the manuscript is largely descriptive in nature, and several key issues remain to be addressed.

Major Comments:

1.Differential gene/pathway analysis across epithelial clusters: What are the differential genes or pathways among the epithelial clusters? Without CCA/Harmony integration, do the tumor subgroups show distinct differences? In addition, I suggest applying NMF or hdWGCNA to identify shared modules and test whether ATC and PTC harbor overlapping regulatory modules. 2.Validation of TSHR/TPO-based subgrouping: While the TSHR/TPO grouping appears appropriate for stratification at the single-cell level, it is necessary to exclude sequencing depth as a confounding factor. Should validate the existence of these subpopulations using mIHC/IF on corresponding samples. 3.Impact of mutational differences on conclusions: According to Supplementary Table 1, almost all PTC cases carried BRAF mutations, whereas four ATC patients harbored no BRAF mutation. Could this difference influence the conclusions of the study? Although the authors briefly mention this in the Discussion, a more thorough clarification is warranted. 4.The statement "Myeloid and T cells also grouped in specific clusters" seems descriptive. Is this clustering biologically meaningful? Please elaborate.

Minor Comments:

In Figure 2C, the "Epith TSHR-" population resembles myeloid cells. Could the authors clarify why this is the case? For the correlation analysis in Figure 2C, were highly variable genes or all genes used?

Significance

This study provides a comprehensive single-nucleus and spatial transcriptomic atlas of papillary and anaplastic thyroid carcinomas. Its strengths include well-designed sample collection, high-resolution profiling of tumor heterogeneity, and validation of FN1 function. By stratifying malignant cells with thyroid differentiation markers (TSHR, TPO, TG, NIS), the authors delineate differentiation states and highlight mechanisms of progression from PTC to ATC. However, the study remains mainly descriptive, and additional analyses of gene modules, pathway regulation would increase its conceptual depth. The findings will interest researchers in thyroid cancer, tumor heterogeneity, and the single-cell/spatial genomics field, with potential relevance for translational oncology.

Field of expertise: thyroid cancer biology, single-cell and spatial transcriptomics.

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Reply to the reviewers

Detailed point-by-point response

__ __The Reviewers provided suggestions to improve the manuscript, most notably by adding experiments to (1) further support the role of Stim and Orai in epidermal heat-off responses and (2) further characterize the thermosensory responses of epidermal cells. We additionally propose to include a new set of calcium imaging experiments to visualize nociceptor sensitization by epidermal cells.

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

Summary: Drosophila larvae are known to respond to noxious stimuli by rolling. The authors propose that this response arises not only by sensory response of nociceptive neurons but also by direct response of larval epidermal cells. They go onto test this idea by independently manipulating epidermal cells and nociceptive sensory neurons using GAL4 lines, GCAMPs and RNAis. The behavioural data are convincing and presented clearly with good statistical analysis. However the involvement of epidermal cells in evoking the behaviour as well as STIM/Orai mediated Ca2+ entry requires further experiments. Use of another independent GAL4 strain for epidermal cells, alternate RNAi lines for STIM and Orai, mutants for STIM and Orai and overexpression constructs for STIM and Orai would significantly enhance the data. Thus, as of now the key results require more convincing. The following additional experiments would be required to support their claims:

1) Either use a second epidermal GAL4 strain to show key results OR provide images of the epidermal GAL4 expression double-labelled with a ppk driver using a different fluorescent protein to establish NO overlap of the epidermal GAL4 with neurons. These strains should be available free in Bloomington.

We agree that the specificity of the GAL4 driver is an important point. In a recent publication (Yoshino et al, eLife, 2025) we provide the most comprehensive analysis of larval epidermal GAL4 drivers published to date. Included in this study is expression analysis of R38F11-GAL4 demonstrating that it is indeed specifically expressed in the epidermis. Based on the detailed expression analysis and functional analysis provided in that paper, R38F11-GAL4 was chosen for these studies as it is both highly specific for epidermal cells and provides uniform expression across the body wall.

In our revised manuscript, we will more clearly detail how the driver was chosen for this study and provide a citation to the prior work to accompany our description of R38F11-GAL4 as an epidermis-specific driver line.

2) Authors need to provide better data for the involvement of STIM and Orai in the Calcium responses observed. A single RNAi for each gene with marginal change in response is insufficient. The authors also do not state if the RNAis used are validated by them or anyone else. Minimally they should repeat their experiments with at least one other validated RNAi and rescue these with overexpression constructs of STIM and Orai (available in Bloomington). It is well established in literature that overexpression of STIM/Orai can rescue SOCE in Drosophila. Ideally, to be fully convincing they should test a Drosophila knockout for STIM (available in Bloomington). Heterozygotes of this are viable and should be tested. Additionally a UAS Orai dominant negative (OraiDN) strain is available in Bloomington and can be tested.

We appreciate the Reviewer’s perspective on the importance of characterizing the efficacy of the reagents we used in this study. However, we disagree with the characterization of the change in response as “marginal”. Our results demonstrate that epidermal knockdown of Stim or Orai causes a significant reduction in the heat-off response of epidermal cells and heat-induced nociceptive sensitization.

In a prior published study (Yoshino et al, eLife, 2025) we validated for their efficacy of these RNAi lines in combination with the same GAL4 driver at the same developmental stage. Specifically, we demonstrated that R38F11GAL4-mediated expression of UAS-Stim RNAi or UAS-Orai RNAi significantly attenuated store operated calcium entry following story depletion by thapsigargin. In the revised manuscript, we will add a statement referring to this prior validation along with a citation. In light of this prior characterization, we disagree that additional RNAi lines are required to corroborate the results.

The most salient point of the Reviewer’s comment is that additional evidence should be provided to demonstrate more convincingly the requirement of Stim/Orai in epidermal heat-off responses. We detail our plans to address this point below, but first address the specific experimental suggestions the Reviewer provides.

First, the Reviewer suggests the use of a dominant-negative version of Orai, and we agree that this could prove complimentary to our RNAi experiments.

The Reviewer suggests two additional genetic approaches which are well-reasoned but problematic. First, they suggest rescuing the RNAi knockdowns with overexpression approaches. In addition to requiring the generation of new, RNAi-refractory transgenes, this approach is confounded by the effects of overexpressing CRAC channel components. Orai channels exhibit highly cooperative activation by Stim, and we previously showed that epidermal Stim overexpression drove mechanical nociceptive sensitization. Although this dosage effect confounds the rescue assays, we will examine whether epidermal Stim overexpression similarly sensitizes larvae to noxious thermal inputs as we would predict from our model.

The final experiment the Reviewer suggests – phenotypic analysis of Stim knockouts – is not possible due to the lethal phase of the mutants. Furthermore, it is not possible using traditional mosaic analysis to generate mutant epidermal clones that span the entire epidermis. Such an approach might be possible with a newly engineered FLP-out Stim allele, but generating that reagent is beyond the scope of this work. The Reviewer suggests characterization of Stim heterozygotes, but Drosophila genes rarely show strong dosage effects as heterozygotes (though we acknowledge that dosage effects can be amplified in the cases of genetic interactions), hence a negative result (no effect on heat-off responses) would not be meaningful. In principle we could test whether Stim hetorozygosity enhances effects of epidermal Stim RNAi. Although a negative result will not be telling, the experiment is straightforward, and an enhancement of the effect of Stim RNA would support the model that RNAi provides an incomplete functional knockdown of Stim. We will therefore perform this experiment and incorporate the results into the revised manuscript, pending a postitive outcome.

To better define the contributions of Stim and Orai to heat-off responses of epidermal cells, we will incorporate results from the following new experiments into our revised manuscript:

• We will monitor effects of epidermis-specific expression of a dominant negative form of Orai on epidermal heat-off responses (calcium imaging) and heat-induced nociceptive sensitization (behavioral assays).
• We will monitor effects of epidermis-specific co-expression of Stim+Orai RNAi on epidermal heat-off responses (calcium imaging) and heat-induced nociceptive sensitization (behavioral assays)
• Orai channels exhibit highly cooperative activation by Stim, therefore we will examine whether epidermal Stim overexpression increases the amplitude of heat-off responses (calcium imaging) and sensitizes larvae to noxious thermal inputs (behavioral assays) as we would predict from our model.

  Minor comments that can be addressed:

1) Figure 1: Further details required on how the rolling response is measured. Figure is uninformative. A video would be really helpful.

We appreciate the suggestion. We will add a more detailed explanation of how the behaviors were scored along with an annotated video.

2) I could not find Figure 1I described in the text. This section should be explained properly.

Figure 1I is described in the figure legend and we will add an in-text citation.

3) Figure 3: There appears to a small response at 32oC - why is this ignored in the text? It would be useful to have S3 in the main figure.

The small response at 32C is not ignored, though that individual response is better understood in the context of all responses plotted in Figure 3D. We will reword the phrase “At temperature maxima below 35°C epidermal cells rarely exhibited heat-off responses” to reflect the small response that is observed at lower temperatures. We will also replace the trace in the figure – the original submission contained the one outlier sample that exhibited robust responses at 32 C.

We appreciate the suggestion to include Fig S3 in the main text – we initially included it, but moved it to the supplement for space considerations. We will include it as a main figure in our revised submission.

4) Fig 4: The DF/F traces for the two RNAis should be included in this figure.

We appreciate the suggestion; we will add these traces to our revised submission.

5) Extent of knockdown in the epidermis by each RNAi should be shown by RTPCRs.

We note that efficacy of the knockdowns has been validated by us in acutely dissociated epidermal cells. RTPCR validation as described would require FACS-sorting of acutely dissociated, GFP-labeled epidermal cells from each specimen, an extremely time- and resource intensive experiment that provides limited information. The more relevant information is the physiological readout of Stim/Orai functional knockout using these reagents which we previously conducted. As described above, we will add a description of these experiments and the relevant citation.

6) The authors need to explain why only a small change in the Ca2+ response is seen with either RNAi. Are there other Ca2+ channels involved? Ideally they could test mutants/RNAi for the TRP channel family. Loss of SOCE in Drosophila neurons changes the expression of other membrane channels - is this possible here? Minimally, this possibility needs to be discussed.

We agree with the Reviewer that this topic warrants further discussion. Pending the results of our planned experiments (Orai dominan negative, Stim+Orai RNAi), we will incorporate a discussion of other channels that may contribute to the heat-off response. We appreciate the Reviewers point that loss of SOCE in Drosophila neurons can change the expression of membrane channels – that is an intriguing possibility that might explain the modest effects of Stim or Orai knockdown. We have not investigated effects of epidermal Stim/Orai knockdown on expression of other channels, but will incorporate this possibility into our discussion.

7) In the methods section please explain how the % DF/F calculations are done and how are they normalised to the ionomycin response.

We will incorporate these additional details in the methods section.

8) Authors need to look at previous work on STIM and Orai in Drosophila and reference appropriately.

We appreciate the suggestion and will incorporate additional discussion of relevant Drosophila work on STIM and Orai.

**Referees cross-commenting**

Reviewers 2 and 3 have raised some additional queries to what I had mentioned in my review. I agree with their comments. The authors should attempt to address all comments by all three reviewers.

We address their comments below.

Reviewer #1 (Significance (Required)):

This is an interesting study that identifies epidermal cells in Drosophila with the ability to sense a drop in temperature after receiving noxious heat stimuli and invoke appropriate behaviour. Behaviour experiments are well conducted and convincing. So far only nociceptive neurons were thought to control such behavioural responses so the work is significant and important for the field. The mechanism identified needs further convincing and I have suggested experiments that would be of help. With the additional experiments suggested the work will be of interest to neuroethologists, Drosophila neuroscientists and scientists in the field of Ca signaling.

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

Summary:

Noxious heat can have a strong adverse effect on animals, resulting in sensitization when noxious thermal stimuli are applied repeatedly. Noxious heat induces a characteristic rolling behavior in Drosophila melanogaster larvae. This study investigates sensitization, whereby a second heat stimulus evokes this behavior with significantly shorter latency (e.g., 3.4 seconds) than the initial exposure (e.g., 8.79 seconds). While prior research has implicated central and peripheral neurons in this process, recent findings in mammalian systems suggest a role for keratinocytes.

In this manuscript, Yoshino et al. report that epidermal cells are necessary and sufficient to mediate heat sensitization in D. melanogaster larvae. Using an ex vivo epidermal imaging system, the authors demonstrate that calcium influx in epidermal cells is crucial for sensitization. Importantly, this calcium influx was observed only when the temperature was lowered from a dangerously high to a safe temperature. The calcium channel system Orai and Stim facilitates this influx.

Major comments:

(1) The authors clearly demonstrate the heat-off reaction using calcium influx imaging. However, all of the imaging shows the response to the first stimulation. Since the study focuses on sensitization, which shows a quicker response to the second heat stimulus, it would be helpful if the authors showed calcium influx when the second stimulus was applied. It would also be interesting to see how many times the epidermal cells can react to heat stimulation.

We appreciate the suggestion from the Reviewer but note that the calcium influx we show occurs in epidermal cells, which signal to neurons to potentiate future responses in our model. We have emphasized this point in our revised manuscript.

The relevant response to visualize the sensitization is the heat-evoked calcium response in nociceptors, not epidermal cells. We have verified that C4da neurons exhibit calcium responses to the warming stimulus we use in our heat-off paradigm and our preliminary studies suggest that the heat-off stimulus potentiates future responses to noxious heat in nociceptors. We will therefore examine (1) whether epidermal stimulation triggers a sensitization of nociceptors to thermal stimuli by monitoring heat-induced calcium responses using GCaMP, and (2) whether epidermal Stim and Orai are required for this sensitization.

The second comment addresses the response of epidermal cells to repeated rounds of stimuli. We agree that this is an interesting point. We have verified that epidermal cells indeed respond to multiple rounds of heat-off stimuli. We will incorporate results from a paradigm in which epidermal cells are presented with two successive heat-off stimuli, spaced by 5 minutes to allow epidermal cytosolic calcium to return to baseline. We will incorporate new analysis examining the relative magnitude of epidermal cells to the first and second stimulus.

(2) Figure 5 only shows one condition: a 30-second interval between the first and second heat application. While the rolling latency of the Luciferase RNAi control ranges from 4 to 12 seconds (with a median of 5 seconds), Fig. 1E shows a latency ranging from 6 to 12 seconds (with a median of 10 seconds) under the same 30-second interval conditions. This difference makes interpreting the effect of Stim and Orai confusing. The authors need to clarify whether the knockdowns accelerate the first response or delay the second response.

The Reviewer notes that we assayed effects of Stim/Orai RNAi on heat-induced nociceptive sensitization in only one paradigm. Given the kinetics of cytosolic calcium increases following Stim or Orai RNAi in epidermal cells (Fig. 4F), we agree that an additional set of behavior experiments investing sensitization following a 60 sec recovery is warranted. For our revision we will conduct a time-course to assay requirements of epidermal Stim and Orai (using epidermal expression of Stim/Orai RNAi and Orai dominant negative transgenes) on heat-induced nociceptive sensitization. Our preliminary studies indicate that Stim and Orai RNAi significantly reduce heat-induced sensitization following 60 s of recovery (we present results from 30 s of recovery in the original submission).

The Reviewer raises some questions about differences in behavioral latencies in Figure 1E and Figure 5B. We intentionally avoid such comparisons both because the genetic backgrounds are different and the experiments were conducted at very different times (more than 1 year apart). In both experiments the salient feature that we discuss is the presence or absence of sensitization, not the mean latency. We note that we do compare mean latency values in Figure 1B, but that was a distinct experimental paradigm (global heat of variable temperatures followed by focal noxious heat) designed specifically to define heat stimuli that generate the maximum level of sensitization. In that case, the genotype was fixed and all assays were conducted concurrently.

Minor comments:

(i) In Fig. 2C´´, the authors observed clear calcium influx in epidermal cells by combining the GCaMP genetic tool with an ex vivo thermal perfusion system. Although this system applies heat uniformly across the epidermal tissue, calcium influx is spatially restricted, appearing primarily in the head and tail regions of the epidermis. These results suggest that the heat-responsive epidermal cells are localized to these regions or that there are regional differences in sensitivity. The authors should explain the spatial relationship between the heat-applied epidermal cells and the occurrence of calcium influx.

The Reviewer notes that intensity of the epidermal GCaMP signal is particularly intense in the anterior and posterior portions of the fillet preparation (Fig. 1B-1C), and we agree that it would be useful to include an explanation of this result, which is an artifact of the sample preparation.

The specimens we use for calcium preparation are “butterfly” preparations – the body wall is filleted along the long axis with the exception of regions at the head and tail that are pinned down on sylgard plates. Hence, the regions in the head and tail contain intact tissue (including a double layer of skin when we image in widefield), not a single layer of skin (the rest of the prep). More significantly, the head and tail regions are pinned down, creating a wound that triggers lasting local calcium transients (note signal in the absence of temperature stimulus, Figure 1B’ and 1B”, 1C’). We therefore exclude this region from our analysis. We note that our behavior studies relied on stimuli presented to the abdominal segments we sample in the semi-intact calcium imaging. Similarly, we dissociated epidermal cells exclusively from these segments for imaging of acutely isolated epidermal cells.

We do note that there is a periodicity to the signal – within each segment there are local maxima and minima of signal, and we agree with the Reviewer that this spatial segregation is an interesting point for discussion. We will add 1-2 sentences to our discussion of the result to acknowledge this point.

(ii) Related to comment (i) above, if heat stimuli are applied topically using a heat probe under the ex vivo imaging system, how large an area reacts to the stimuli?

The Reviewer raises an interesting question about the local response to heat stimuli. In our dissociated cell experiments we found that the overwhelming majority of isolated epidermal cells exhibit heat-off responses, and we likewise find that the majority of cells in our semi-intact preparation respond to heat-off stimuli. However, our current probe for delivering local heat stimuli is not compatible with our imaging system. We are working to incorporate an IR laser to focally deliver heat stimulus to explore whether epidermal cells signal to neighbors following stimulation, but such studies are beyond the scope of the current work.

(iii) Providing supplementary movie(s) of the calcium live imaging would enhance the reader's understanding.

We agree with the Reviewer that this would be a useful supplement. We will add representative movies as experimental supplements in our revised manuscript.

(iv) The time point of the image in Fig. 2C´ ("before heat") is not the most informative for demonstrating a "heat-off" response. The authors should replace it with an image taken during the heat application to provide a more direct comparison with the post-stimulus influx shown in Fig. 2C´´.

We appreciate the Reviewer’s suggestion and agree this would be a better choice to visually represent the change in fluorescence induced by the heat-off response. We will make this change in our revised manuscript.

(v) The authors state that sensitization occurs "primarily in the 30-45 ºC range." However, the rolling probability and latency developed oppositely at 45 ºC stimulation than at 40 ºC. It would be doubtful that 45 ºC may be approaching a noxious or damaging threshold that engages a different phenomenon. The authors should reconsider including 45 ºC within the optimal sensitization range or provide a justification.

We agree with the Reviewer that a more detailed discussion of the effects of temperature at the end of the range (45 C) is warranted. Exposure to a 45 C global heat stimulus triggered temporary paralysis in some larvae, and we suspect that this accounts for the apparent reduction in roll probability following the second stimulus. We can add a plot depicting the proportion of larvae that exhibited paralysis during 45 C global heat and determine whether these heat-paralyzed larvae exhibited distinct responses from larvae that were not paralyzed and provide a more detailed account of the optimal sensitization range.

Treatment with 45 C stimuli still triggered a significant reduction in roll latency (sensitization), but we did not examine whether the latency was significantly different from what was observed at 40 C. We can add that analysis in the revision.

(vi) In the sentence "To this end, we developed a perfusion system, that would deliver thermal ramps from ~20-45ºC ...," the tilde ~ should be replaced with "approximately".

Noted. We will make the change.

(vii) Throughout the manuscript, please clarify in the figure legends whether the sample size (n) refers to the number of individual animals or the number of cells.

Noted. We will add the relevant details to our sample sizes notations.

(viii) The Key Resources Table does not specify the wild-type (WT) strain used for the control experiments (e.g., in Fig. 1). Please provide the full genotype of the control strain used.

We included the experimental genotypes in each figure legend, which we find more useful than the key resource table, which contains a list of all reagents used in the study (Drosophila alleles included).

Reviewer #2 (Significance (Required)):

General Assessment

This study addresses a fundamental question in sensory biology: whether epidermal cells, long regarded as passive participants in somatosensation, actively contribute to noxious heat detection and avoidance behavior. While previous work has defined the neuronal circuits and TRP channel mechanisms underlying thermal nociception in Drosophila larvae, the potential sensory role of skin cells has remained largely unexplored. The authors integrate behavioral analysis with in vitro and ex vivo calcium imaging to provide a rigorous, multi-level investigation of epidermal thermosensitivity.

Advancement

The work advances the field by revealing that Drosophila epidermal cells are intrinsically thermosensitive and can acutely sensitize larval nociceptive responses to noxious heat through heat-off signaling. This discovery shifts the current paradigm of thermal nociception from a neuron-centric model to one that incorporates epidermal contributions, highlighting a conserved and previously underappreciated role of skin cells in active environmental sensing.

The reviewer's expertise: Molecular genetics, developmental biology, insect physiology and endocrinology.

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

This manuscript describes the temperature responses of Drosophila larval epidermal cells. These cells are activated by cooling and also exhibit strong heat-off responses. Orai and Stim are required in epidermal cells for these heat-off responses. The heat-off responses sensitize the epidermal cells, leading to a greater proportion of animals displaying rolling behaviors and a reduced latency to initiate rolling following noxious heating treatment. The following comments are intended to help improve the manuscript.

Major:

1. In Figure 3A, the conclusion will be strengthened by testing heat-off responses from 10 {degree sign}C to 40 {degree sign}C.

The Reviewer makes an important point. In our original experiment, the lack of response in the 10C – 30C experiment could be due to some cold-induced suppression of the off response. We have found that this is not the case – we have found that off responses following a 10C-40C ramp are indistinguishable from responses to a 20C-40C ramp. In our revised manuscript we will incorporate new results showing epidermal heat off responses to a 10C-40C ramp as well as normalization to 20C-40C responses performed in parallel.

Figure 4C shows that 2-APB suppresses the heat-off response. Since 2-APB blocks both Orai and TRP channels, it is unclear why the authors focused exclusively on the Orai pathway without testing TRP channels.

We found that epidermal cells exhibited minimal responses to warming stimuli, as would be expected for the epidermally expressed TRP channel TRPA1. In addition, the heat-off response we identified was remarkably similar to characteristic heat-off responses of mammalian CRAC channels. Hence, we focused our attention on the Orai pathway. While we agree that contributions of TRP channels could be of interest, especially if our additional analyses (double RNAi and Orai Dominant Negative) support the model that additional channels likely contribute to the heat-off response, the characteristic temperature responses of CRAC channels made them the most plausible candidate.

In parallel to the experiments to further characterize Stim/Orai contributions to the heat-off response, we will assay requirements of TRPA1 to heat-induced nociceptor sensitization.

While 2-APB completely abolishes the heat-off response, Orai and Stim RNAi only slightly (although significantly) reduce calcium responses. The knockdown efficiency of the RNAi constructs should be validated. Furthermore, testing whether combining Orai RNAi and Stim RNAi produces a stronger reduction in calcium responses would be informative.

We addressed the question of knockdown efficiency above, and agree that testing the effects of Orai RNAi and Stim RNAi in combination is worthwhile. We detailed our plans for these experiments above.

The study uses third-instar larvae. Please specify whether early, mid, or late third instar were used.

In our original submission we stated “Third-instar larvae (96-120 AEL) larvae were used in all experiments” We provide additional details on the staging of larvae for all experiments in the methods section of our revised submission. To synchronize cultures, embryos were collected from experimental crosses for 24 h, aged for 96 h, and foraging mid-third instar larvae (96-120 h old) were used for all experiments.

Please provide more details about the thin layer of water used. Specifically, indicate the size of the Peltier plate and the volume of water applied.

We provide additional details on the application of global heat stimulus in the methods section of our revised manuscript. “For assays testing effects of varying the temperature of prior thermal stimuli on thermal nociception, larvae were individually transferred to a pre-warmed Peltier plate (11 x 7 cm; Torrey Pines Scientific). Peltier plates were warmed to the indicated temperatures, a thin layer of water was applied to the surface using a paint brush, and the temperature was verified using an infrared thermometer. Larvae were transferred individually to the Peltier plate, incubated for the indicated time, and recovered to 2% Agar Pads using a paint brush. Following 10 s of recovery, larvae were stimulated with a 41.5°C thermal probe, as above, and latency to the first complete roll was recorded.”

Minor:

1. There is an inconsistency between the text and the figure regarding the sample number in Figure 1D.

We thank the reviewer for identifying the discrepancy. This inconsistency has been corrected in the revised submission.

Please provide the raw representative data for the time course of heat-off calcium responses in Figure 1E.

We will incorporate representative traces for the heat-off responses plotted in Figure 1E.

A period is missing at the end of the sentence: "For curve fitting, sample-averaged fluorescence traces were fitted with a single exponential decay function using R to extract a representative time constant (τ) and assess response kinetics."

We thank the reviewer for identifying the omission. The period has been added.

In the sentence "Behavior Responses were analyzed post-hoc blind to genotype and were plotted according to roll probability and roll latency," the word Responses should begin with a lowercase r.

This has been corrected in the revised submission.

Reviewer #3 (Significance (Required)):

This manuscript describes the heat-off responses of larval epidermal cells and investigates their underlying molecular mechanisms as well as associated behavioral consequences.

The calcium responses and behavioral assays are clearly presented. However, the contribution of Stim and Orai to this process is not convincing.

The study may be of interest to researchers working on Drosophila and temperature sensation, as well as to those studying Orai and Stim function.

I am a researcher specializing in Drosophila thermosensation.

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Referee #3

Evidence, reproducibility and clarity

This manuscript describes the temperature responses of Drosophila larval epidermal cells. These cells are activated by cooling and also exhibit strong heat-off responses. Orai and Stim are required in epidermal cells for these heat-off responses. The heat-off responses sensitize the epidermal cells, leading to a greater proportion of animals displaying rolling behaviors and a reduced latency to initiate rolling following noxious heating treatment. The following comments are intended to help improve the manuscript.

Major:

1. In Figure 3A, the conclusion will be strengthened by testing heat-off responses from 10 {degree sign}C to 40 {degree sign}C.
2. Figure 4C shows that 2-APB suppresses the heat-off response. Since 2-APB blocks both Orai and TRP channels, it is unclear why the authors focused exclusively on the Orai pathway without testing TRP channels.
3. While 2-APB completely abolishes the heat-off response, Orai and Stim RNAi only slightly (although significantly) reduce calcium responses. The knockdown efficiency of the RNAi constructs should be validated. Furthermore, testing whether combining Orai RNAi and Stim RNAi produces a stronger reduction in calcium responses would be informative.
4. The study uses third-instar larvae. Please specify whether early, mid, or late third instar were used.
5. Please provide more details about the thin layer of water used. Specifically, indicate the size of the Peltier plate and the volume of water applied.

Minor:

1. There is an inconsistency between the text and the figure regarding the sample number in Figure 1D.
2. Please provide the raw representative data for the time course of heat-off calcium responses in Figure 1E.
3. A period is missing at the end of the sentence: "For curve fitting, sample-averaged fluorescence traces were fitted with a single exponential decay function using R to extract a representative time constant (τ) and assess response kinetics."
4. In the sentence "Behavior Responses were analyzed post-hoc blind to genotype and were plotted according to roll probability and roll latency," the word Responses should begin with a lowercase r.

Significance

This manuscript describes the heat-off responses of larval epidermal cells and investigates their underlying molecular mechanisms as well as associated behavioral consequences.

The calcium responses and behavioral assays are clearly presented. However, the contribution of Stim and Orai to this process is not convincing.

The study may be of interest to researchers working on Drosophila and temperature sensation, as well as to those studying Orai and Stim function.

I am a researcher specializing in Drosophila thermosensation.

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Referee #2

Evidence, reproducibility and clarity

Summary:

Noxious heat can have a strong adverse effect on animals, resulting in sensitization when noxious thermal stimuli are applied repeatedly. Noxious heat induces a characteristic rolling behavior in Drosophila melanogaster larvae. This study investigates sensitization, whereby a second heat stimulus evokes this behavior with significantly shorter latency (e.g., 3.4 seconds) than the initial exposure (e.g., 8.79 seconds). While prior research has implicated central and peripheral neurons in this process, recent findings in mammalian systems suggest a role for keratinocytes. In this manuscript, Yoshino et al. report that epidermal cells are necessary and sufficient to mediate heat sensitization in D. melanogaster larvae. Using an ex vivo epidermal imaging system, the authors demonstrate that calcium influx in epidermal cells is crucial for sensitization. Importantly, this calcium influx was observed only when the temperature was lowered from a dangerously high to a safe temperature. The calcium channel system Orai and Stim facilitates this influx.

Major comments:

(1) The authors clearly demonstrate the heat-off reaction using calcium influx imaging. However, all of the imaging shows the response to the first stimulation. Since the study focuses on sensitization, which shows a quicker response to the second heat stimulus, it would be helpful if the authors showed calcium influx when the second stimulus was applied. It would also be interesting to see how many times the epidermal cells can react to heat stimulation.

(2) Figure 5 only shows one condition: a 30-second interval between the first and second heat application. While the rolling latency of the Luciferase RNAi control ranges from 4 to 12 seconds (with a median of 5 seconds), Fig. 1E shows a latency ranging from 6 to 12 seconds (with a median of 10 seconds) under the same 30-second interval conditions. This difference makes interpreting the effect of Stim and Orai confusing. The authors need to clarify whether the knockdowns accelerate the first response or delay the second response.

Minor comments:

(i) In Fig. 2C´´, the authors observed clear calcium influx in epidermal cells by combining the GCaMP genetic tool with an ex vivo thermal perfusion system. Although this system applies heat uniformly across the epidermal tissue, calcium influx is spatially restricted, appearing primarily in the head and tail regions of the epidermis. These results suggest that the heat-responsive epidermal cells are localized to these regions or that there are regional differences in sensitivity. The authors should explain the spatial relationship between the heat-applied epidermal cells and the occurrence of calcium influx.

(ii) Related to comment (i) above, if heat stimuli are applied topically using a heat probe under the ex vivo imaging system, how large an area reacts to the stimuli?

(iii) Providing supplementary movie(s) of the calcium live imaging would enhance the reader's understanding.

(iv) The time point of the image in Fig. 2C´ ("before heat") is not the most informative for demonstrating a "heat-off" response. The authors should replace it with an image taken during the heat application to provide a more direct comparison with the post-stimulus influx shown in Fig. 2C´´.

(v) The authors state that sensitization occurs "primarily in the 30-45 ºC range." However, the rolling probability and latency developed oppositely at 45 ºC stimulation than at 40 ºC. It would be doubtful that 45 ºC may be approaching a noxious or damaging threshold that engages a different phenomenon. The authors should reconsider including 45 ºC within the optimal sensitization range or provide a justification.

(vi) In the sentence "To this end, we developed a perfusion system, that would deliver thermal ramps from ~20-45ºC ...," the tilde ~ should be replaced with "approximately".

(vii) Throughout the manuscript, please clarify in the figure legends whether the sample size (n) refers to the number of individual animals or the number of cells.

(viii) The Key Resources Table does not specify the wild-type (WT) strain used for the control experiments (e.g., in Fig. 1). Please provide the full genotype of the control strain used.

Significance

General Assessment

This study addresses a fundamental question in sensory biology: whether epidermal cells, long regarded as passive participants in somatosensation, actively contribute to noxious heat detection and avoidance behavior. While previous work has defined the neuronal circuits and TRP channel mechanisms underlying thermal nociception in Drosophila larvae, the potential sensory role of skin cells has remained largely unexplored. The authors integrate behavioral analysis with in vitro and ex vivo calcium imaging to provide a rigorous, multi-level investigation of epidermal thermosensitivity.

Advancement

The work advances the field by revealing that Drosophila epidermal cells are intrinsically thermosensitive and can acutely sensitize larval nociceptive responses to noxious heat through heat-off signaling. This discovery shifts the current paradigm of thermal nociception from a neuron-centric model to one that incorporates epidermal contributions, highlighting a conserved and previously underappreciated role of skin cells in active environmental sensing.

The reviewer's expertise: Molecular genetics, developmental biology, insect physiology and endocrinology.

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Referee #1

Evidence, reproducibility and clarity

Summary: Drosophila larvae are known to respond to noxious stimuli by rolling. The authors propose that this response arises not only by sensory response of nociceptive neurons but also by direct response of larval epidermal cells. They go onto test this idea by independently manipulating epidermal cells and nociceptive sensory neurons using GAL4 lines, GCAMPs and RNAis. The behavioural data are convincing and presented clearly with good statistical analysis. However the involvement of epidermal cells in evoking the behaviour as well as STIM/Orai mediated Ca2+ entry requires further experiments. Use of another independent GAL4 strain for epidermal cells, alternate RNAi lines for STIM and Orai, mutants for STIM and Orai and overexpression constructs for STIM and Orai would significantly enhance the data. Thus, as of now the key results require more convincing. The following additional experiments would be required to support their claims:

1) Either use a second epidermal GAL4 strain to show key results OR provide images of the epidermal GAL4 expression double-labelled with a ppk driver using a different fluorescent protein to establish NO overlap of the epidermal GAL4 with neurons. These strains should be available free in Bloomington.

2) Authors need to provide better data for the involvement of STIM and Orai in the Calcium responses observed. A single RNAi for each gene with marginal change in response is insufficient. The authors also do not state if the RNAis used are validated by them or anyone else. Minimally they should repeat their experiments with at least one other validated RNAi and rescue these with overexpression constructs of STIM and Orai (available in Bloomington). It is well established in literature that overexpression of STIM/Orai can rescue SOCE in Drosophila. Ideally, to be fully convincing they should test a Drosophila knockout for STIM (available in Bloomington). Heterozygotes of this are viable and should be tested. Additionally a UAS Orai dominant negative (OraiDN) strain is available in Bloomington and can be tested.

Minor comments that can be addressed:

1) Figure 1: Further details required on how the rolling response is measured. Figure is uninformative. A video would be really helpful.

2) I could not find Figure 1I described in the text. This section should be explained properly.

3) Figure 3: There appears to a small response at 32oC - why is this ignored in the text? It would be useful to have S3 in the main figure.

4) Fig 4: The DF/F traces for the two RNAis should be included in this figure.

5) Extent of knockdown in the epidermis by each RNAi should be shown by RTPCRs.

6) The authors need to explain why only a small change in the Ca2+ response is seen with either RNAi. Are there other Ca2+ channels involved? Ideally they could test mutants/RNAi for the TRP channel family. Loss of SOCE in Drosophila neurons changes the expression of other membrane channels - is this possible here? Minimally, this possibility needs to be discussed.

7) In the methods section please explain how the % DF/F calculations are done and how are they normalised to the ionomycin response.

8) Authors need to look at previous work on STIM and Orai in Drosophila and reference appropriately.

Referees cross-commenting

Reviewers 2 and 3 have raised some additional queries to what I had mentioned in my review. I agree with their comments. The authors should attempt to address all comments by all three reviewers.

Significance

This is an interesting study that identifies epidermal cells in Drosophila with the ability to sense a drop in temperature after receiving noxious heat stimuli and invoke appropriate behaviour. Behaviour experiments are well conducted and convincing. So far only nociceptive neurons were thought to control such behavioural responses so the work is significant and important for the field. The mechanism identified needs further convincing and I have suggested experiments that would be of help. With the additional experiments suggested the work will be of interest to neuroethologists, Drosophila neuroscientists and scientists in the field of Ca signaling.

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Reply to the reviewers

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__Reviewer #1 __

Major comments

1. The manuscript posits that the loss of function of MASh components (Ogc1 and Aralar) decreases adrenergic-stimulated lipolysis by altering the cytosolic NAD⁺/NADH ratio, with AMPK/ACC mentioned as possible mediators. However, this remains speculative. Please provide mechanistic data directly linking MASh-dependent NAD⁺/NADH changes to the regulation of lipolysis in brown adipocytes during adrenergic stimulation. Answer 1) The reviewer raises an important point regarding the direct assessment of cytosolic NAD⁺/NADH redox changes as a mechanistic link for altered lipolysis in brown adipocytes lacking MASh components. To address this point, we added new data to the revised manuscript showing lactate/pyruvate ratio as measured by metabolomics. This is a well-established surrogate marker to monitor changes in redox balance. Notably, under basal (non-stimulated) conditions, the lactate/pyruvate ratio did not display any significant differences between Aralar 1 KD and control cells, suggesting preservation of cytosolic NAD⁺/NADH levels in the absence of functional MASh under these conditions. This finding is consistent with reports showing the robustness of NAD⁺ regeneration via multiple shuttles and the possibility of metabolic compensation when one shuttle is compromised (PMID: 40540398; PMID: 37647199).

The results have been added as new supplementary Figure 1 as following:

Our new metabolomics data also revealed substantial reductions in the aspartate/glutamate ratio in Aralar 1 knockdown cells, serving as a metabolomic signature of impaired MASh function and reduced exchange of these amino acids between the cytosol and mitochondria. Given that the MASh is a major mechanism for exporting cytosolic reducing equivalents into the mitochondria under high metabolic demand, its loss would be expected to impact redox homeostasis, particularly under adrenergic stimulation when glycolytic flux and lipolytic activity are elevated (PMID: 40540398).

Importantly, although our redox surrogate marker did not detect alterations, this may be explained by activation of compensatory pathways, most notably the glycerol phosphate shuttle (GPSh), which is highly expressed and active in brown adipocytes. Indirect support for this compensation comes from data shown in figure 4I showing reduced glycerol release in Aralar 1 KD cells upon norepinephrine stimulation and blocked lipolysis. This suggests a redirection of glycolytically derived G3P away from release and toward enhanced cycling within the GPSh, supporting cytosolic NAD⁺ regeneration via mitochondrial FAD-dependent G3PDH and cytosolic NAD⁺-dependent G3PDH activity. This is consistent with studies documenting that the combined action of MASh and GPSh maintains NAD redox homeostasis in brown adipocytes especially during non-thermogenic conditions (PMID: 168075; PMID: 40540398; PMID: 37647199). We have included a discussion about this possibility at page 9, third paragraph as follows:

*“Previous studies have shown that BAT exhibits high activity of mitochondrial FAD-dependent glycerol-3-phosphate dehydrogenase (mG3PDH), which functions as an electron sink to sustain low cytosolic NADH levels essential for continuous glycolytic flux [11]. Accordingly, suppression of the MASh, either genetically or pharmacologically, is likely to induce a compensatory upregulation of the GPSh. This adaptation would enhance G3P turnover, contributing to the maintenance of cytosolic NAD redox balance. Moreover, the increased flux through the GPSh could favor fatty acid esterification and triglyceride synthesis or re-esterification, consistent with our findings in Ogc and/or Aralar 1 KD cells, where (i) triglyceride content rises (Fig. 3), (ii) overall respiratory rates remain largely unaltered (Figs. 2D–G), and (iii) glycerol release declines significantly (Fig. 4I). Notably, the decrease in glycerol release persists even when lipolysis is blocked by ATGlistatin, suggesting that the available G3P pool is rerouted from dephosphorylation and extracellular release toward oxidation to DHAP by mG3PDH to regenerate cytosolic NAD+ under MASh-deficient conditions. We propose that interference with the MASh does not directly impact lipolysis but instead alters the cellular balance between DHAP and G3P owing to enhanced activity of the GPSh. This metabolic shift would favor the esterification of G3P with free fatty acids, thereby promoting triglyceride synthesis. These results support the notion that, even during adrenergic stimulation—when long-chain unsaturated fatty acids and their CoA esters strongly inhibit mG3PDH activity [11]—the residual flux through the glycerophosphate shuttle remains critical for sustaining cytosolic NAD redox equilibrium [11,19,32].” *

• *

At the mechanistic level, adrenergic stimulation in brown adipocytes activates robust lipolysis and thermogenic gene programs, generating high NADH that must be efficiently reoxidized to sustain flux through glycolysis and lipolysis-linked pathways. Our findings are consistent with a model in which the loss of MASh does not prevent cytosolic NAD⁺ regeneration or lipolytic flux during acute adrenergic stimulation, due to compensatory upregulation of the GPSh, as suggested by the glycerol release changes. Thus, while MASh normally acts as a conduit for NADH export and aspartate/glutamate exchange, in its absence, the GPSh maintains cytosolic redox balance, thereby sustaining glycolytic and lipolytic capacity.

We agree that future studies should employ direct measurements of cytosolic NAD⁺/NADH ratios (e.g., genetically-encoded redox sensors) during adrenergic stimulation and specific pharmacological inhibition of both shuttles to dissect these relationships in greater detail. We sincerely appreciate the reviewer's input, which has prompted us to clarify the indirect but robust evidence supporting a role for compensatory redox shuttle activity in preserving brown adipocyte lipolysis in the setting of MASh impairment.

We have further added a new paragraph in the discussion section (page 10)::

*“Mechanistically, the connection between the MASh and lipolysis appears to involve regulation of the cytosolic NAD⁺/NADH redox balance. MASh activity facilitates the regeneration of NAD⁺ from NADH in the cytosol, primarily through the reduction of oxaloacetate to malate by cytosolic malate dehydrogenase (Fig. 1G-H). Despite the theoretical expectation that reductions in MASh activity would disturb redox homeostasis, our metabolomic data show that the lactate/pyruvate ratio remains unchanged under conditions of MASh impairment, indicating that the overall cytosolic NAD⁺/NADH ratio is maintained (Figure S1A-C). While direct measurements of cytosolic NAD⁺/NADH were not performed, the preserved lactate/pyruvate ratio in Aralar 1 KD cells under basal conditions strongly suggests redox stability, likely due to compensatory activity by alternative mitochondrial shuttles or metabolic adaptations that maintain NAD redox homeostasis despite MASh impairment [18,33]. *

Previous evidence indicates that BAT exhibits high activity of mitochondrial FAD-dependent glycerol-3-phosphate dehydrogenase (G3PDH), which acts as an electron sink to sustain low cytosolic NADH levels critical for glycolysis [34]. In this sense, it is conceivable that genetic or pharmacological suppression of MASh triggers compensatory enhancement of the G3P shuttle, increasing G3P availability and facilitating the maintenance of cytosolic NAD redox balance. This adaptation could also promote fatty acid esterification and triglyceride synthesis or re-esterification, aligning with our observations that in Ogc and/or Aralar 1 KD cells: (i) triglyceride levels increase (Fig. 3); (ii) overall respiratory rates are preserved (Figs. 2D–G); and (iii) glycerol release is significantly reduced (Fig 4I).”

• *

__ The absence of in vivo analysis of lipid-droplet size in MASh loss-of-function models is a major concern. In vitro results could be confounded by differences in differentiation stage between groups. Please document equivalent adipogenesis across groups (e.g., Pparg/Cebpa/Plin1/Fabp4 expression).__

Answer 2) We thank the reviewer for the thoughtful and constructive comment regarding potential confounding by differences in differentiation stage, and for highlighting the importance of documenting equivalence between experimental groups. We appreciate the opportunity to clarify and provide additional assurance on this point.

As detailed in our manuscript, we have performed qPCR analysis of multiple well-established markers of brown adipocyte differentiation, including Ucp1, Elovl3, Prdm16, Pparg, Cebpa, Plin1, and Fabp4, in both scramble, aralar1 KD, and Ogc KD cells (see Fig. S1A and accompanying text). Our results show no apparent effect of these genetic interventions on overall differentiation, as the expression levels of these key markers were consistently unaltered across groups. Furthermore, adenoviral-mediated knockdown of Ogc achieved an approximate 80% reduction in Ogc mRNA (see Fig. S1B), yet most differentiation markers remained unaffected. We did observe significant increases in Atgl, Pgc1α, and Tfam mRNA levels, which may indicate a degree of pathway reprogramming without affecting the general differentiation profile. We propose that interference with the MASh does not directly impact lipolysis but instead alters the cellular balance between DHAP and G3P owing to enhanced activity of the GPSh. This metabolic shift would favor the esterification of G3P with free fatty acids, thereby promoting triglyceride synthesis.

Additional experimental support for equivalent differentiation can be drawn from our respirometry data presented in Figures 2E and 2G. These figures demonstrate that respiratory rates upon norepinephrine stimulation, which is a sensitive indicator of brown adipocyte thermogenic capacity, were essentially identical in scramble, aralar1 KD, and Ogc KD cells. Since norepinephrine-stimulated respiration requires both functional mitochondria and the full differentiation of brown adipocytes, these results strongly support the conclusion that silencing either MASh component does not impair the fundamental ability of cells to undergo brown adipocyte differentiation or achieve functional thermogenic competence.

This is consistent with published findings showing that norepinephrine triggers robust respiration and thermogenic activation only in fully differentiated and functional brown adipocytes, making such measurements a widely accepted proxy for differentiation status and mitochondrial integrity. Thus, the equivalent respiratory responses observed in all groups further validate that differentiation was not compromised by the genetic interventions.

We hope this clarifies that equivalent adipogenesis was carefully documented and that any observed phenotypes are unlikely to be attributable to differences in differentiation stages. Thank you again for your rigorous assessment and for helping to ensure the robustness of our study.

__ Please include rescue experiments (add-back OGC1 and Aralar) to rule out siRNA/shRNA off-target effects and verify that the phenotype stems from MASh loss of function.__

Answer 3) We thank the reviewer for this important suggestion regarding the inclusion of rescue experiments with add-back of Ogc and Aralar to definitively exclude off-target effects of the siRNA/shRNA-mediated knockdowns.

We would like to kindly point out that although we did not perform add-back rescue experiments directly, the consistency of phenotypes observed across two independent genetic interventions—aralar 1 KD and Ogc KD—strongly argues against off-target effects being responsible for the observed metabolic and functional alterations. Specifically, both knockdowns yielded remarkably similar phenotypes in multiple assays, including respirometry analyses, mitochondrial morphology, lipid droplet homeostasis, and lipid metabolism, supporting the conclusion that these effects stem from MASh loss of function rather than nonspecific silencing.

Furthermore, our new supplementary data (new Supplementary Figure 1A-F) reveals a significant reduction in the aspartate/glutamate ratio in Aralar 1 KD cells, a compelling functional readout for MASh impairment. This molecular evidence corroborates that our genetic interventions effectively disrupted MASh activity as intended.

We sincerely appreciate the reviewer’s thorough evaluation and understand the importance of rescue experiments. While recognizing their value, we believe the convergent genetic, metabolic, and functional evidence presented across two different MASh components provides strong and consistent support that the phenotypes observed are due to specific loss of MASh function.

__ Please expand on physiological significance: What is the importance of MASh regulation of BAT lipolysis in long-term adaptive thermogenesis?__

Answer 4) This is a very interesting aspect, and we have included a new paragraph in the discussion section (page 14) to address it as follows:

“Our results, supported by recent literature, strongly indicate that the malate–aspartate shuttle (MASh) plays a key role in facilitating fatty acid–dependent thermogenesis in brown adipocytes. Specifically, BAT-targeted overexpression of GOT1 has been shown to enhance β-oxidation and support acute cold-induced thermogenesis (PMID: 40540398). Interestingly, genetic ablation of GOT1—and thus MASh inhibition—preserves cold-induced thermogenesis by promoting a metabolic shift from fatty acid to glucose oxidation. Our findings corroborate and extend these observations by demonstrating that MASh impairment sustains overall respiratory activity in norepinephrine-stimulated brown adipocytes (Figures 2D–2G), while concurrently impairing lipolysis and resulting in an accumulation of small lipid droplets (Figures 3 and 4). Collectively, these data suggest that MASh not only modulates substrate preference towards fatty acid oxidation but also facilitates lipolysis, an essential upstream step that enables lipid oxidation and supports thermogenic heat production.”

Minor comments

1. __ Fig. 4 legend/title contains a typo ("lypolysis" → lipolysis).__ Answer 1) Corrected

__ In Fig. 2 legend line: "Adevirus-mediated" → Adenovirus-mediated; "OCAR" → OCR.__

Answer 2) Corrected

__ For lipolysis imaging, you already show Forskolin/Atglistatin/Etomoxir controls; add a vehicle-only time course overlay in the main figure (currently in text/legend) to aid visual comparison.__

Answer 3) We thank the reviewer for pointing this out. To improve clarity, we have updated the labeling in Figures 3 and 4: “basal” now clearly refers to the unstimulated/untreated condition, and the previously labeled “UT” condition has been clarified as “untransduced.” These changes make the figure legends and data presentation more consistent and easier to interpret.

__ Ensure consistent gene symbols (Atgl/Pnpla2), and protein capitalization.__

Answer 4) Corrected.

__Reviewer #2 __

Major points:

1. __ In the current manuscript, mitochondrial morphology (area, aspect ratio, and roundness) was analyzed in OGC1 KD cells using TMRE, whereas MitoTracker Deep Red (MTDR) was used in Aralar1 KD cells. Notably, TMRE is a ΔΨm-dependent probe. The signal intensity can change, or the distribution may reflect alterations in membrane potential rather than true morphological changes. Therefore, the observed differences in OGC1 KD cells based on TMRE staining may be confounded by the dye's functional dependence, potentially biasing the conclusions. It is recommended to evaluate mitochondrial morphology with consistent trackers across conditions. In addition, in the subsequent OCR analysis, mitochondrial area was used for normalization. Please clarify which staining method was employed, and provide justification for its suitability.__ Answer 1) We thank the reviewer for this insightful comment. Indeed, TMRE is a membrane potential-sensitive dye and could therefore potentially affect measurements of mitochondria.

We would like to point out that mitochondrial morphology was quantified based on mitochondrial area rather than fluorescence intensity. To create an accurate binary map of mitochondria, we used a low threshold, which allowed us to include even weakly stained mitochondria and thereby detect them independently of their membrane potential. In all imaged cells, TMRE signal was sufficient to reliably identify mitochondrial pixels. Moreover, these images were acquired using a confocal microscope, where the risk of pixel expansion due to higher fluorescence intensity is minimized. Lastly, given that overall mitochondrial oxygen consumption in these cells remains largely intact, we do not expect a substantial loss of membrane potential, although minor effects cannot be entirely excluded.

We opted to use TMRE for imaging Ogc KD cells because the scramble control for these shRNA viruses carries an mKate fluorescent tag, which overlaps with the MTDR signal. Since accurate assessment of transduction efficiency relied on detecting mKate, MTDR could not be used in these experiments. Importantly, we only compare mitochondrial morphology within the same staining condition and do not draw conclusions across cells stained with different dyes.

To ensure transparency, we have added a new section at the discussion (page 17, 2nd paragraph) highlighting the potential influence of ΔΨm-dependent dyes on morphological measurements as follows:

“It is also important to note that mitochondrial morphology was quantified using MTDR in Aralar 1 KD cells and TMRE in Ogc KD cells due to experimental constraints (see Methods). TMRE is a membrane potential–dependent dye, which could potentially influence morphology measurements. To minimize this risk, we used confocal microscopy, which reduces the likelihood of pixel expansion due to higher fluorescence intensity, and set thresholds to detect even weakly stained mitochondria. Nonetheless, we cannot fully exclude the possibility that the differences in morphology observed between Aralar 1 and Ogc KD are influenced by the use of different dyes; however, statistical comparisons were never performed across samples stained with different dyes.”

Also, we have expanded the Methods section (page 22, 2nd paragraph) to include a rationale for using these dyes and describe the analysis protocol as following:

“TMRE was used for Ogc KD cells because the scramble control for the shRNA viruses carries an mKate fluorescent tag, which overlaps with MTDR fluorescence, preventing its use. MTDR was used for Aralar KD cells. Image Analysis was performed in FIJI (ImageJ, NIH). For the quantification of mitochondrial morphology and area, images stained with TMRE or MTDR were analyzed. Thresholds were adjusted to ensure that even weakly stained mitochondria were detected and included in the analysis. Only the mitochondrial area was evaluated, independent of fluorescence intensity.”

Minor points:

1. __ In the introduction, the authors state that "LDH activity increases in the context of BAT activation". This point is important for the logic of the manuscript, reference [10] cited here is not sufficient to support this claim. It is recommended to provide appropriate references to support this statement.__ Answer 1) We have substantially changed this paragraph in the revised manuscript to better explain why LDH would not act as a major player in contributing to NAD redox balance in the context of BAT thermogenesis, as follows:

“In mammalian cells, cytosolic NAD⁺ is regenerated through lactate dehydrogenase (LDH), the glycerol-3-phosphate shuttle (GPSh), or the malate-aspartate shuttle (MASh). In BAT, however, lactate production rises only slightly with adrenergic activation and most lactate is oxidized via the TCA cycle, suggesting that LDH primarily consumes NAD⁺ rather than regenerating it [PMID: 30456392; PMID: 37337122; PMID: 30456392; PMID: 37802078; PMID: 40982723]. Consequently, mitochondrial redox shuttles become critical for sustaining cytosolic NAD⁺ supply”.

We have also provided additional references to support this new section at the introduction.

__ In Fig. 1A and B-D, there are inconsistencies and duplications in the abbreviation labels. Please check and revise accordingly. __

Answer 2) We thank the reviewer for this comment. We would like to clarify that Figure 1A is a schematic overview of the system, while Figures 1B–D show protein expression in specific contexts: whole BAT (B), whole liver (C), and BAT mitochondria (D). In Figures 1B and 1C, all components are shown because both cytosolic (MDH1 and GOT1) and mitochondrial proteins (MDH2, GOT2, Aralar 1 and 2 and OGC) are present. In contrast, Figure 1D shows only mitochondrial components (OGC, Aralar1, MDH2, and GOT2). Although Aralar2 is a mitochondrial protein, it was not detected in this study (Forner et al., 2009). Similarly, cytosolic components such as MDH1 and GOT1 are not shown in Figure 1D because they are absent in the mitochondrial fraction. We have revised the figure legend to make these distinctions clearer.

__ In Fig. S1, the number of n indicated does not match the number of data points shown. Please clarify whether these represent technical replicates or biological replicates, and provide a detailed description of the statistical methods used throughout the manuscript.__

Answer 3) We thank the reviewer for catching this and allowing us to correct our mistakes. In the revised version, we have corrected the figure legend of Supplementary Figure 1 so that the number of n matches the data points shown.

__ Please provide details on the normalization strategy used in the BODIPY-C12/BODIPY-493 staining analysis, such as whether fluorescence intensity was quantified as mean or integrated values, and whether the analysis was normalized to lipid droplet area, cell number, or baseline. Since lipolytic stimulation can reduce droplet size and increase droplet number, these factors may bias the results. __

Answer 4) We thank the reviewer for this important comment and apologize for the lack of detail regarding this analysis. The analysis of BODIPY-C12 and BODIPY-493 was performed by quantifying the mean fluorescence intensity of BODIPY-C12 detected within a mask generated from the BODIPY-493 signal. This approach allowed us to define all lipid droplets and measure the release of previously esterified C12. To account for variability across samples, the data were normalized to each sample’s individual baseline at time point 0 and expressed as fold change relative to this baseline. In the revised manuscript we have included this description in the Methods section (page 18, last paragraph) for clarity and reproducibility, as following:

“Lipid Droplet area was defined based on Bodipy 493/503 signal, which was used to generate a mask identifying all lipid droplets. Within this mask, the mean fluorescence intensity of BODIPY C12 was quantified over time to monitor the release of previously esterified C12. To account for variability between samples, data were normalized to each sample’s individual baseline at time point 0 and expressed as fold change relative to this baseline.”

__ The manuscript notes that the unexpected result in Fig. 3K-M in parallel with increased Atgl mRNA expression might be because it does not reflect protein levels or enzymatic activity. To strengthen this point, it is recommended to include data on ATGL and phosphorylation ATGL. __

Answer 5) We thank the reviewer for this constructive comment. We have clarified these aspects in the revised Results and Discussion sections to reflect this interpretation more accurately as follows:

“Notably, Atgl mRNA measurement in our study was primarily used as a marker of brown adipocyte differentiation, rather than as a direct indicator of ATGL protein abundance or enzymatic activity. We detected increased Atgl expression only in Ogc KD cells (Fig. S1H), but not in Aralar 1 KD cells (Fig. S1G). This likely does not reflect a major difference in differentiation status, as other brown adipocyte markers and norepinephrine-stimulated respiration were comparable between scramble and knockdown cells (Fig. 2D-G and 2N-O and S1G-H). Although lipolysis was not evaluated in Ogc KD cells, in Aralar 1 KD cells basal lipolysis remained unchanged (Fig. 4D-E and 4G-I), whereas norepinephrine-stimulated lipolysis was delayed or partially inhibited. Notably, the enhanced fatty acid esterification observed in Ogc KD cells despite elevated Atgl expression is not contradictory, since in brown adipocytes lipolysis and re-esterification occur concurrently to sustain high lipid turnover [34].

__ Red-on-black is not a great color code for IMFs, how about black-and-white? __

Answer 6) We have changed color text for white on figures 2H and K as suggested.

__Reviewer #3 __

Major points;

1. __ Although in the manuscript Veliova and coworkers demonstrated that MAS is functional in brown adipocytes showing kinetic parameters equivalent to that previously described in other tissues, surprisingly, when its components are downregulated, no effect, or very little, on mitochondrial respiration is found (figure 2). This is an intriguing result since MAS disruption has been widely reported to impair respiration in different cell types and tissues. However, since no direct evidence of MAS dysfunction is provided, it is possible that MAS may still remain partially or fully functional under the conditions used by the authors, and therefore this point needs to be clarified to validate these results.__ Answer 1) We thank the reviewer for the insightful comment and the opportunity to clarify these important points regarding MASh dysfunction validation in our study. We acknowledge the reviewer’s observation that mitochondrial respiration was largely unaffected by MASh component knockdown, which is indeed intriguing. Importantly, as already indicated in our responses to Reviewer 1, we have provided new data showing direct molecular evidence of MASh impairment through substantial reductions in the aspartate/glutamate ratio in Aralar 1 KD cells (new Supplementary Figure S1F). This ratio is a well-established functional readout reflecting MASh activity and amino acid exchange between cytosol and mitochondria, as demonstrated in original experimental studies of MASh function in multiple tissues including brown adipocytes (PMID: 4436323). The reduction in the aspartate/glutamate ratio directly confirms loss of MASh functionality even though respiratory rates remained unchanged, likely due to metabolic compensation by robust glycerol phosphate shuttle (GPSh) activity, as further supported by our data showing reduced glycerol release upon norepinephrine stimulation in Aralar 1 KD cells cells (Figure 4I). This metabolic rerouting maintains cytosolic NAD⁺ regeneration and partially preserves respiration and energy metabolism under these experimental conditions (PMID: 168075; PMID: 40540398; PMID: 37647199). Thus, the combination of metabolomic, respirometry, and functional lipid data strongly indicates that MASh activity was disrupted specifically and effectively by our genetic interventions. This molecular evidence was already signposted in our original manuscript and responses, underscoring that MASh loss of function—and not residual or compensatory MASh activity—is responsible for the phenotypes reported. We greatly appreciate the reviewer’s insightful attention to this critical mechanistic issue and hope this provides clear reassurance that MASh impairment was indeed achieved and functionally validated within our study framework.

Furthermore, strategies used to downregulate MAS components produce only a partial reduction in mRNA levels, about 70 %, but its outcome on protein levels has not been determined. and the remaining protein level could be sufficient to maintain shuttle activity. Therefore, the effect of silencing at protein level should be analyzed, because as authors also point out on page 16; "mRNA levels may not reflect actual protein levels or activity".

Answer 2) We thank the reviewer for this important point. Our knockdowns resulted in ~70–80% reduction in mRNA levels. While not complete, this represents a substantial decrease and is sufficient to produce strong functional effects. At the time the experiments were performed, we did not have access to suitable antibodies, and the available antibodies did not provide reliable signals in our samples, which is why we used qPCR to estimate knockdown efficiency. Importantly, we observed clear phenotypic changes in both knockdowns (Aralar and OGC), and both showed very similar phenotypes. This suggests that the level of knockdown was sufficient to significantly impair MAS activity. In the revised version we added new data which further validated the functional impact of Aralar KD (given that this protein has an alternative isoform, as pointed out by the reviewer). We performed metabolomics experiments measuring aspartate and glutamate levels. Our new data shows that the aspartate-to-glutamate ratio is significantly reduced in Aralar KD cells. This ratio serves as a proxy for glutamate catabolism, and the observed decrease suggests reduced glutamate catabolism, likely due to impaired MAS activity. Therefore, the reduced whole-cell aspartate/glutamate ratio serves as a metabolic signature of MAS impairment, consistent with Aralar KD. These data indicate that Aralar is sufficiently downregulated to produce a functional effect, supporting our conclusion that MAS activity is impaired. The results have been added as new supplementary Figure 1 as follows:

__ In the case of aspartate/glutamate carriers (AGCs) the role of citrin/slc25a13, the second AGC paralog, should also be analyzed. This AGC isoform is discarded based on proteomic data from brown adipose tissue, but, as it is shown in figure 1B, its levels are similar those of Aralar/slc25a12, the only AGC silenced. Besides, primary brown adipocytes differentiated for 7 days are used here, and it is possible that factors such as culture conditions or differentiation itself could alter AGC levels. Therefore, it is necessary to determine the protein levels of citrin/AGC2, and, if necessary, downregulate it together with the Aralar/AGC1 isoform. citrin/AGC2 activity may be responsible for the observed difference between the OGC and Aralar/AGC1 KD adipocytes.__

Answer 3) We thank the reviewer for this important point. We chose Aralar1 because it is the isoform predominantly expressed in brown adipose tissue (PMID: 23436904). We acknowledge, however, that compensatory increases in Citrin/AGC2 upon Aralar1 knockdown are possible. To address this, we have included new metabolomics data in the revised manuscript (added as Supplementary Figure 1), which provides additional support that downregulation of Aralar1, even if not complete, is sufficient to cause a metabolic change reflected by a reduced aspartate/glutamate ratio in these cells. This functional change supports that the knockdown of Aralar1 alone is sufficient to study its role in brown adipocytes, although minor compensation by Citrin/AGC2 cannot be entirely excluded.

To address this explicitly, we have added a paragraph to the discussion (page 13, 2nd paragraph) highlighting the potential for partial compensation by Citrin/AGC2 and explaining why the observed metabolic effects are still attributable to Aralar 1 knockdown, as follows:

“Phenotypes observed in Aralar 1 KD cells closely resemble those in Ogc KD cells, particularly in terms of lipid metabolism alterations and energy expenditure. The main difference lies in mitochondrial morphology, which is altered in Ogc KD cells but remains unchanged in Aralar 1-silenced cells (Fig. 2J,M). Unlike Ogc, which lacks an alternative isoform, Aralar 1 has a paralog Aralar 2 (Citrin, or SLC25A13) that may partially compensate for its loss. This potential compensation might explain the preservation of mitochondrial morphology in Aralar 1 KD cells. Nonetheless, our metabolomics data demonstrate that downregulation of Aralar 1 alone significantly reduces the aspartate/glutamate ratio (Fig. S1D-F). Since this ratio reflects glutamate catabolism, its decrease indicates impaired malate-aspartate shuttle activity and reduced glutamate catabolism. Therefore, although compensation by Aralar 2 cannot be entirely excluded, Aralar 1 KD alone suffices to cause substantial impairment of malate-aspartate shuttle function”.

• *

__ OGC and Aralar/AGC1 silencing is associated with the accumulation of smaller lipid droplets and impaired norepinephrine-induced lipolysis, but no mechanistical evidence is provided. The authors discuss a role for AMPK signaling associated with the redox unbalance generated by MAS disfunction but neither of them is proven.__

Answer 4) We thank the reviewer for this insightful question, which was also raised by Reviewer 1 (see Reviewer 1, Question 1 above). Here, we aim to clarify the mechanistic basis by which MASh may regulate lipolysis in BAT in a complementary and refined manner.

Our new data directly addresses this issue by examining cytosolic redox status through the lactate/pyruvate ratio, a well-established indicator of NAD⁺/NADH balance. Under basal conditions, Aralar 1 KD cells showed no change in this ratio compared to controls, indicating preserved cytosolic NAD⁺ regeneration despite reduced MASh activity. This observation is consistent with previous studies demonstrating the resilience of cellular redox homeostasis through overlapping NAD⁺-regenerating systems (PMID: 40540398; PMID: 37647199). The new results are shown in Supplementary Figure 1.

At the same time, we detected a marked decrease in the aspartate/glutamate ratio in Aralar 1 KD cells, confirming impaired MASh function and reduced amino acid exchange between cytosol and mitochondria. The lack of redox imbalance likely reflects compensatory mechanisms, most notably the GPSh, which is highly active in brown adipocytes. Supporting this view, Aralar 1 KD cells displayed significantly reduced glycerol release upon norepinephrine stimulation (Fig. 4I), suggesting enhanced metabolic cycling of G3P through mitochondrial and cytosolic G3PDH, thereby sustaining NAD⁺ regeneration and redox equilibrium.

We therefore propose that, although MASh normally facilitates NADH export and aspartate/glutamate exchange, its loss activates GPSh-mediated compensation that preserves cytosolic NAD⁺/NADH balance and maintains lipolytic flux during adrenergic stimulation. These findings refine our mechanistic understanding of how redox shuttle interplay supports glycolytic and lipolytic processes in BAT. Future studies employing NAD⁺/NADH sensors and simultaneous blockade of both shuttles will be essential to dissect these compensatory mechanisms in greater detail.

Minor points;

1. __ Is pyruvate present in respiration medium? If so, no effect on respiration is expected as pyruvate reverses the respiratory defects caused by MAS inactivation. __ Answer 1) Thanks for this important insight. In fact, as indicated in the methods section (page 17, last paragraph) all respirometry experiments were carried out in the absence of pyruvate in the media. Therefore, preserved overall respiratory rates in Aralar 1 and Ogc KD cannot be explained by compensatory pyruvate oxidation present in the media.

__ In figure 4, only data from Aralar KD cells in relation to norepinephrine-stimulated lipolysis are shown. What happens when OGC is silenced? __

Answer 2) This is a very interesting and relevant question. We did not perform the norepinephrine-stimulated lipolysis experiments in Ogc-silenced cells, since in most of the other experiments presented in the manuscript Ogc and Aralar 1 silencing converged to very similar, if not identical, phenotypes. Based on these consistent overlaps, we anticipate that Ogc KD would likely lead to comparable effects on lipolysis as observed in Aralar 1 KD cells. Nonetheless, we fully agree that direct assessment of lipolysis upon Ogc KD would strengthen this conclusion, and we consider this an important aspect for future studies.

__ Nomenclature used for mitochondrial carriers is confusing. Please do not use OGC1 as there is only one isoform. Furthermore, different names for OGC are used in the manuscript; oxoglutarate carrier, malate-ketoglutarate carrier or OGC1/SLC25A11. In the case of citrin/AGC2, Aralar2 is used and is a uncommon designation.__

Answer 3) We corrected all OGC naming in the revised manuscript. We also changed “aralar 2” for “citrin” since this was more commonly used in the literature.

__ Some panels of figures 3 and 4 should be improved. Panels 3J, 3L and 4G are difficult to see. In panel 3J please clarify UT line from untreated/NE, are they not transduced? No equivalents conditions are assayed in Aralar KD and OGC KO cells.__

Answer 4) We thank the reviewer for giving us the opportunity to improve this figure and apologize for the confusing labeling. In the revised version, we have clarified the labels in panels 3J, 3L, and 4G to improve visibility, and we have added descriptions of all abbreviations to the figure legends, accordingly.

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Referee #3

Evidence, reproducibility and clarity

In this manuscript, Veliova and coworkers explore the contribution of the malate-aspartate NADH shuttle (MAS) to energy metabolism in brown adipose tissue. This work done by a group expert in mitochondrial metabolism, continues an interesting previous one (Veliova, 2020) where it was shown that the inhibition of the mitochondrial pyruvate carrier caused an increase in energy expenditure mediated by the activation of MAS in BAT. Here, the authors have explored the consequences of the lack of MAS activity on BAT metabolism by the silencing of the metabolite transporters that are part of MAS in cultured primary brown adipocytes. Using this loss-of-function approach, the role for MAS in the regulation of lipid homeostasis in BAT is analyzed. The results could be interesting, but in my opinion, they are not sufficiently proven. Much more evidence should be provided to confirm MAS deficiency and the mechanisms involved in the alteration of lipid homeostasis.

Major points

1. Although in the manuscript Veliova and coworkers demonstrated that MAS is functional in brown adipocytes showing kinetic parameters equivalent to that previously described in other tissues, surprisingly, when its components are downregulated, no effect, or very little, on mitochondrial respiration is found (figure 2). This is an intriguing result since MAS disruption has been widely reported to impair respiration in different cell types and tissues. However, since no direct evidence of MAS dysfunction is provided, it is possible that MAS may still remain partially or fully functional under the conditions used by the authors, and therefore this point needs to be clarified to validate these results. Furthermore, strategies used to downregulate MAS components produce only a partial reduction in mRNA levels, about 70 %, but its outcome on protein levels has not been determined. and the remaining protein level could be sufficient to maintain shuttle activity. Therefore, the effect of silencing at protein level should be analyzed, because as authors also point out on page 16; "mRNA levels may not reflect actual protein levels or activity".
2. In the case of aspartate/glutamate carriers (AGCs) the role of citrin/slc25a13, the second AGC paralog, should also be analyzed. This AGC isoform is discarded based on proteomic data from brown adipose tissue, but, as it is shown in figure 1B, its levels are similar those of Aralar/slc25a12, the only AGC silenced. Besides, primary brown adipocytes differentiated for 7 days are used here, and it is possible that factors such as culture conditions or differentiation itself could alter AGC levels. Therefore, it is necessary to determine the protein levels of citrin/AGC2, and, if necessary, downregulate it together with the Aralar/AGC1 isoform. citrin/AGC2 activity may be responsible for the observed difference between the OGC and Aralar/AGC1 KD adipocytes.
3. OGC and Aralar/AGC1 silencing is associated with the accumulation of smaller lipid droplets and impaired norepinephrine-induced lipolysis, but no mechanistical evidence is provided. The authors discuss a role for AMPK signaling associated with the redox unbalance generated by MAS disfunction but neither of them is proven.

Minor points

1. Is pyruvate present in respiration medium? If so, no effect on respiration is expected as pyruvate reverses the respiratory defects caused by MAS inactivation.
2. In figure 4, only data from Aralar KD cells in relation to norepinephrine-stimulated lipolysis are shown. What happens when OGC is silenced?
3. Nomenclature used for mitochondrial carriers is confusing. Please do not use OGC1 as there is only one isoform. Furthermore, different names for OGC are used in the manuscript; oxoglutarate carrier, malate-ketoglutarate carrier or OGC1/SLC25A11. In the case of citrin/AGC2, Aralar2 is used and is a uncommon designation.
4. Some panels of figures 3 and 4 should be improved. Panels 3J, 3L and 4G are difficult to see. In panel 3J please clarify UT line from untreated/NE, are they not transduced? No equivalents conditions are assayed in Aralar KD and OGC KO cells.

Significance

General assessment: The robust part of this study is its analysis of some aspects related to lipid metabolism in cultured primary cells derived from brown adipose tissue. The participating teams are well-versed in this topic and the approaches used are correct. However, no data in animal models supporting these results are provided and this fact rests interest.

Advance: This manuscript is the "logical" continuation of a previous study, Veliova et al., (2020) EMBO Rep, more relevant in my opinion. Also, recently, it has been also proposed using animal models, either by overexpression or using deficient mice for GOT1 a cytosolic protein component of MAS, a role for MAS in BAT thermogenesis (Park et al., Cell Rep. 2025). The novelty in this manuscript is the analysis of deficient cells in the metabolite transporter that regulate the direction of NADH shuttling. However, since no evidence is provided its effect on NAD+/NADH ratio, the conclusions related to the role of MAS, or the mitochondrial carriers silenced, in the regulation of lipolysis in BAT and its involvement in thermogenesis are not convinced.

Audience: These results could be of interest to the audience interested in basic research, but could also be useful in the translational/clinical area because they address metabolic aspects in adipose tissue.

My expertise is focus on mitochondrial metabolism, specifically in the function of a subtype of mitochondrial carriers regulated by cytosolic calcium and how they participate in the control of different mitochondrial functions, such as respiration, calcium buffering, cell proliferation. Some of these transporters are components of MAS such as Aralar/AGC1 or citrin/AGC2.

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Referee #2

Evidence, reproducibility and clarity

This manuscript presents novel findings on the role of the malate-aspartate shuttle (MASh) in brown adipose tissue (BAT). Building on the recent advances in elucidating the contribution of MASh to BAT metabolism, the present study provides new evidence by offering direct biochemical validation using a reconstituted BAT mitochondrial system and by introducing genetic data on the mitochondrial carriers OGC1 and Aralar1, thereby adding significant new insight. However, the following points require further clarification.

Major points:

1. In the current manuscript, mitochondrial morphology (area, aspect ratio, and roundness) was analyzed in OGC1 KD cells using TMRE, whereas MitoTracker Deep Red (MTDR) was used in Aralar1 KD cells. Notably, TMRE is a ΔΨm-dependent probe. The signal intensity can change, or the distribution may reflect alterations in membrane potential rather than true morphological changes. Therefore, the observed differences in OGC1 KD cells based on TMRE staining may be confounded by the dye's functional dependence, potentially biasing the conclusions. It is recommended to evaluate mitochondrial morphology with consistent trackers across conditions. In addition, in the subsequent OCR analysis, mitochondrial area was used for normalization. Please clarify which staining method was employed, and provide justification for its suitability.

Minor points:

1. In the introduction, the authors state that "LDH activity increases in the context of BAT activation". This point is important for the logic of the manuscript, reference [10] cited here is not sufficient to support this claim. It is recommended to provide appropriate references to support this statement.
2. In Fig. 1A and B-D, there are inconsistencies and duplications in the abbreviation labels. Please check and revise accordingly.
3. In Fig. S1, the number of n indicated does not match the number of data points shown. Please clarify whether these represent technical replicates or biological replicates, and provide a detailed description of the statistical methods used throughout the manuscript.
4. Please provide details on the normalization strategy used in the BODIPY-C12/BODIPY-493 staining analysis, such as whether fluorescence intensity was quantified as mean or integrated values, and whether the analysis was normalized to lipid droplet area, cell number, or baseline. Since lipolytic stimulation can reduce droplet size and increase droplet number, these factors may bias the results.
5. The manuscript notes that the unexpected result in Fig. 3K-M in parallel with increased Atgl mRNA expression might be because it does not reflect protein levels or enzymatic activity. To strengthen this point, it is recommended to include data on ATGL and phosphorylation ATGL.
6. Red-on-black is not a great color code for IMFs, how about black-and-white?

Referees cross-commenting

To my opinion, all three reviewers have provided constructive criticism of the work.

Significance

The work dives deeper into mitochondrial function and metabolism of brown adipocytes and, thus, advances our understanding of thermogenesis in an incremental fashion. The work will be relevant to brown adipose tissue researchers and mitochondrial biologist.

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Referee #1

Evidence, reproducibility and clarity

The paper makes a clear, well-supported case that the malate-aspartate shuttle (MAS) is active in brown adipocytes and supports adrenergically stimulated lipolysis. The combination of a functional MAS assay, targeted carrier knockdowns, and multi-modal lipolysis measurements is a strong package. The reconstituted mitochondrial assay paired with live-cell lipolysis imaging is technically elegant and broadly reusable. The main gap is the limited in-vitro scope relative to in-vivo cold adaptation.

Major comments

1. The manuscript posits that the loss of function of MASh components (Ogc1 and Aralar) decreases adrenergic-stimulated lipolysis by altering the cytosolic NAD⁺/NADH ratio, with AMPK/ACC mentioned as possible mediators. However, this remains speculative. Please provide mechanistic data directly linking MASh-dependent NAD⁺/NADH changes to the regulation of lipolysis in brown adipocytes during adrenergic stimulation.
2. The absence of in vivo analysis of lipid-droplet size in MASh loss-of-function models is a major concern. In vitro results could be confounded by differences in differentiation stage between groups. Please document equivalent adipogenesis across groups (e.g., Pparg/Cebpa/Plin1/Fabp4 expression)
3. Please include rescue experiments (add-back OGC1 and Aralar) to rule out siRNA/shRNA off-target effects and verify that the phenotype stems from MASh loss of function.
4. Please expand on physiological significance: What is the importance of MASh regulation of BAT lipolysis in long-term adaptive thermogenesis?

Minor comments

1. Fig. 4 legend/title contains a typo ("lypolysis" → lipolysis).
2. In Fig. 2 legend line: "Adevirus-mediated" → Adenovirus-mediated; "OCAR" → OCR.
3. For lipolysis imaging, you already show Forskolin/Atglistatin/Etomoxir controls; add a vehicle-only time course overlay in the main figure (currently in text/legend) to aid visual comparison.
4. Ensure consistent gene symbols (Atgl/Pnpla2), and protein capitalization.

Referees cross-commenting

In my view, the feedback offered by all three reviewers has been highly constructive, as each of them has contributed thoughtful and meaningful criticism that can help improve the quality, clarity, and overall impact of the work.

Significance

Advance - how it fits the literature and what kind of advance.

Relative to prior work linking MASh (often via GOT1) to fuel preference and redox during thermogenesis, this study fills a mechanistic gap by showing that carrier-level MASh disruption (Aralar1/OGC1) specifically impairs adrenergic lipid mobilization upstream of β-oxidation, while respiration per cell can be buffered by compensatory mitochondrial biogenesis (lower OCR per mitochondrion). Conceptual/fundamental advance: it sharpens the redox - lipolysis axis in BAT and clarifies why changes in fuel availability (lipolysis) may limit thermogenesis even when bulk OCR looks preserved.

Audience - who will be interested/influenced.

Specialized but cross-cutting: adipose biology & thermogenesis, mitochondrial/redox metabolism, lipid-droplet and lipolysis communities, and metabolic-disease researchers exploring strategies to modulate BAT fuel handling.

Reviewer expertise

Adipose tissue and systemic energy metabolism; mitochondrial bioenergetics; thermogenic mechanisms in BAT/beige fat; transcriptional and metabolic control of lipid mobilization. Not a specialist in membrane-carrier biophysics.

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Reply to the reviewers

Response to Reviewer’s Comments

We thank all three reviewers for their thoughtful and detailed comments, which will help us to improve the quality and clarity of our manuscript.

__Reviewer #1 (Evidence, reproducibility and clarity (Required)): __ Summary: In this work, Tripathi et al address the open question of how the Fat/Ds pathway affects organ shape, using the Drosophila wing as a model. The Fat/Ds pathway is a conserved but complex pathway, interacting with Hippo signalling to affect growth and providing planar cell polarity that can influence cellular dynamics during morphogenesis. Here, authors use genetic perturbations combined with quantification of larval, pupal, and adult wing shape and laser ablation to conclude that the Ft/Ds pathway affects wing shape only during larval stages in a way that is at least partially independent of its interaction with Hippo and rather due to an effect on tissue tension and myosin II distribution. Overall the work is clearly written and well presented. I only have a couple major comments on the limitations of the work.

Major comments: 1. Authors conclude from data in Figures 1 and 2 that the Fat/Ds pathway only affects wing shape during larval stages. When looking at the pupal wing shape analysis in Figure 2L, however, it looks there is a difference in wt over time (6h-18h, consistent with literature), but that difference in time goes away in RNAi-ds, indicating that actually there is a role for Ds in changing shape during pupal stages, although the phenotype is clearly less dramatic than that of larval stages. No statistical test was done over time (within the genotype), however, so it's hard to say. I recommend the authors test over time - whether 6h and 18h are different in wild type and in ds mutant. I think this is especially important because there is proximal overgrowth in the Fat/Ds mutants, much of which is contained in the folds during larval stages. That first fold, however, becomes the proximal part of the pupal wing after eversion and contracts during pupal stages to elongate the blade (Aiguoy 2010, Etournay 2015). Also, according to Trinidad Curr Biol 2025, there is a role for Fat/Ds pathway in pupal stages. All of that to say that it seems likely that there would be a phenotype in pupal stages. It's true it doesn't show up in the adult wing in the experiments in Fig 1, but looking at the pupal wing itself is more direct - perhaps the very proximal effect is less prominent later, as there is potential for further development after 18hr before adulthood and the most proximal parts are likely anyway excluded in the analysis.

Response: Our main purpose in examining pupal wing shape was to emphasize that wings lacking ds are visibly abnormal even at early pupal stages. The reviewer makes the point that the change in shape from 6h to 18h APF is greater in control wings than in RNAi-ds wings. We have added quantitation of this to the revised manuscript as suggested. This difference could be interpreted as indicating that Ds-Fat signaling actively contributes to wing shape during pupal morphogenesis. However, given the genetic evidence that Ds-Fat signaling influences wing shape only during larval growth, we favor the interpretation that it reflects consequences of Ds-Fat action during larval stages – eg, overgrowth of the wing, particularly the proximal wing and hinge as occurs in ds and fat mutants, could result in relatively less elongation during the pupal hinge contraction phase. This wouldn’t change our key conclusions, but it is something that we discuss in a revised manuscript.

I think there needs to be a mention and some discussion of the fact that the wing is not really flat. While it starts out very flat at 72h, by 96h and beyond, there is considerable curvature in the pouch that may affect measurements of different axis and cell shape. It is not actually specified in the methods, so I assume the measurements were taken using a 2D projection. Not clear whether the curvature of the pouch was taken into account, either for cell shape measurements presented in Fig 4 or for the wing pouch dimensional analysis shown in Fig 3, 6, and supplements. Do perturbations in Ft/Ds affect this curvature? Are they more or less curved in one or both axes? Such a change could affect the results and conclusions. The extent to which the fat/ds mutants fold properly is another important consideration that is not mentioned. For example, maybe the folds are deeper and contain more material in the ds/fat mutants, and that's why the pouch is a different shape? At the very least, this point about the 3D nature of the wing disc must be raised in discussion of the limitations of the study. For the cell shape analysis, you can do a correction based on the local curvature (calculated from the height map from the projection). For the measurement of A/P, D/V axes of the wing pouch, best would be to measure the geodesic distance in 3D, but this is not reasonable to suggest at this point. One can still try to estimate the pouch height/curvature, however, both in wild type and in fat/ds mutants.

Response: The wing pouch measurements were done on 2D projections of wing discs that were already slightly flattened by coverslips, so there is not much curvature outside of the folds. We will revise the methods to make sure this is clear. While we recognize that the absolute values measured can be affected by this, our conclusions are based on the qualitative differences in proportions between genotypes and time points, and we wouldn’t expect these to differ significantly even if 3D distances were measured. Obtaining accurate 3D measures is technically more challenging - it requires having spacers matching the thickness of the wing disc, which varies at different time points and genotypes, and then measuring distances across curved surfaces. What we propose to address this is to do a limited set of 3D measures on wild-type and dsmutant wing discs at early and late stages and which we expect will confirm our expectation that the conclusions of our analysis are unaffected, while at the same time providing an indication of how much curvature affects the values obtained. We will also make sure the issue of wing disc curvature and folds is discussed in the text.

Minor comments: 1. The analysis of the laser ablation is not really standard - usually one looks at recoil velocity or a more complicated analysis of the equilibrium shape using a model (e.g Shivakumar and Lenne 2016, Piscitello-Gomez 2023, Dye et al 2021). One may be able to extract more information from these experiments - nevertheless, I doubt the conclusions would change, given that that there seems to be a pretty clear difference between wt and ds (OPTIONAL).

Response: We will add measurements of recoil velocities to complement our current analysis of circular cuts.

Figure 7G: I think you also need a statistical test between RNAi-ds and UAS-rokCA+RNAi-ds.

Response: We include this statistical test in the revised manuscript (it shows that they are significantly different).

In the discussion, there is a statement: "However, as mutation or knock down of core PCP components, including pk or sple, does not affect wing shape... 59." Reference 59 is quite old and as far as I can tell shows neither images nor quantifications of the wing shape phenotype (not sure it uses "knockdown" either - unless you mean hypomorph?). A more recent publication Piscitello-Gomez et al Elife 2023 shows a very subtle but significant wing shape phenotype in core PCP mutants. It doesn't change your logic, but I would change the statement to be more accurate by saying "mutation of core PCP components has only subtle changes in adult wing shape"

Response: Thank-you for pointing this out, we have revised the manuscript accordingly.

**Referee cross-commenting**

Reviewer2: Reviewer 2 makes the statement: "The distance along the AP boundary from the pouch border to DV midline is topologically comparable to the PD length of the adult wing. The distance along the DV boundary from A border to P border is topologically comparable to the AP length of the adult wing."

I disagree - the DV boundary wraps around the entire margin of the adult wing (as correctly drawn with the pink line in Fig 2A). It is not the same as the wide axis of the adult wing (perpendicular to the AP boundary). It is not trivial to map the proximal-distal axis of the larval wing to the proximal-distal axis of the adult, due to the changes in shape that occur during eversion. Thus, I find it much easier to look at the exact measurement that the authors make, and it is much more standard in the field, rather than what the reviewer suggests. Alternatively, one could I guess measure in the adult the ratio of the DV margin length (almost the circumference of the blade?) to the AP boundary length. That may be a more direct comparison. Actually the authors leave out the term "boundary" - what they call AP is actually the AP boundary, not the AP axis, and likewise for the DV - what they measure is DV boundary, but I only noticed that in the second read-through now. Just another note, these measurements of the pouch really only correspond to the very distal part of the wing blade, as so much of the proximal blade comes from the folds in the wing disc. Therefore, a measurement of only distal wing shape would be more comparable.

Response: We thank Reviewer 1 for their comments here. In terms of the region measured, we measure to the inner Wg ring in the disc, the location of this ring in the adult is actually more proximal than described above (eg see Fig 1B of Liu, X., Grammont, M. & Irvine, K. D. Roles for scalloped and vestigial in regulating cell affinity and interactions between the wing blade and the wing hinge. Developmental Biology 228, 287–303 (2000)), and this defines roughly the region we have measured in adult wings (with the caveat noted above that the measurements in the disc can be affected by curvature and the hinge/pouch fold, which we will address).

Reviewer 2 states that authors cannot definitively conclude anything about mechanical tension from their reported cutting data because the authors have not looked at initial recoil velocity. I strongly disagree. __The wing disc tissue is elastic on much longer timescales than what's considered after laser ablation (even hours), and the shape of the tissue after it equilibrates from a circular cut (1-2min) can indeed be used to infer tissue stresses (see Dye et al Elife 2021, Piscitello-Gomez et al eLife 2023, Tahaei et al arXiv 2024).__ In the wing disc, the direction of stresses inferred from initial recoil velocity are correlated with the direction of stresses inferred from analysing the equilibrium shape after a circular cut. Rearrangements, a primary mechanism of fluidization in epithelia, does not occur within 1'. Analysing the equilibrium shape after circular ablation may be more accurate for assessing tissue stresses than initial recoil velocity - in Piscitello-Gomez et al 2023, the authors found that a prickle mutation (PCP pathway) affected initial recoil velocity but not tissue stresses in the pupal wing. Such equilibrium circular cuts have also been used to analyze stresses in the avian embryo, where it correlates with directions of stress gathered from force inference methods (Kong et al Scientific Reports 2019). The Tribolium example noted by the reviewer is on the timescale of tens to hundreds of minutes - much longer than the timescale of laser ablation retraction. It is true the analysis of the ablation presented in this paper is not at the same level as those other cited papers and could be improved. But I don't think the analysis would be improved by additional experiments doing timelapse of initial retraction velocity.

Response: Thank-you, we agree with Reviewer 1 here.

Reviewer 2 states "If cell anistropy is caused by polarized myosin activity, that activity is typically polarized along the short edges not long edges" Not true in this case. Myosin II accumulates along long boundaries (Legoff and Lecuit 2013). "Therefore, interpreting what causes the cell anistropy and how DS regulates it is difficult," Agreed - but this is well beyond the scope of this manuscript. The authors clearly show that there is a change of cell shape, at least in these two regions. Better would be to quantify it throughout the pouch and across multiple discs. Similar point for myosin quantifications - yes, polarity would be interesting and possible to look at in these data, and it would be better to do so on multiple discs, but the lack of overall myosin on the junctions shown here is not nothing. Interpreting what Ft/Ds does to influence tension and myosin and eventually tissue shape is a big question that's not answered here. I think the authors do not claim to fully understand this though, and maybe further toning down the language of the conclusions could help.

Response: We agree with Reviewer 1 here and will also add quantitation of myosin across multiple discs and will include higher magnification myosin images and polarity tests.

Reviewer 3: I agree with many of the points raised by Reviewer 3, in particular that relevant for Fig 1. The additional experiments looking at myosin II localization and laser ablation in the other perturbations (Hippo and Rok mutants/RNAi) would certainly strengthen the conclusions.

Response: Reviewer 3 comment on Fig 1 requests Ab stains to assess recovery of expression after downshift, which we will do.

We will add examination of myosin localization in hpo RNAi wing discs, and in the ds/rok combinations. We note that the effects of Rok manipulations on myosin and on recoil velocity have been described previously (eg Rauskolb et al 2014).

Reviewer #1 (Significance (Required)): I think the work provides a clear conceptual advance, arguing that the Ft/Ds pathway can influence mechanical stress independently of its interaction with Hippo and growth. Such a finding, if conserved, could be quite important for those studying morphogenesis and Fat function in this and other organisms. For this point, the genetic approach is a clear strength. Previous work in the Drosophila wing has already shown an adult wing phenotype for Ft/Ds mutations that was attributed to its role in the larval growth phase, as marked clones show aberrant growth in mutants. The novelty of this work is the dissection of the temporal progression of this phenotype and how it relates to Hippo and myosin II activation. It remains unclear exactly how Ft/Ds may affect tissue tension, except that it involves a downregulation of myosin II - the mechanism of that is not addressed here and would involve considerable more work. I think the temporal analysis of the wing pouch shape was quite revealing, providing novel information about how the phenotype evolves in time, in particular that there is already a phenotype quite early in development. As mentioned above, however, the lack of consideration of the wing disc as a 3D object is a potential limitation. While the audience is likely mostly developmental biologists working in basic research, it may also interest those studying the pathway in other contexts, including in vertebrates given its conservation and role in other processes.

__Reviewer #2 (Evidence, reproducibility and clarity (Required)): __ The manuscript begins with very nice data from a ts sensitive period experiment. Instead of a ts mutation, the authors induced RNAi in a temperature dependent manner. The results are striking and strong. Knockdown of FT or DS during larval stages to late L3 changed shape while knockdown of FT or DS during later pupal stages did not. This indicates they are required during larval, not pupal stages of wing development for this shape effect. They did shift-up or shift-down at "early pupa stage" but precisely what stage that means was not described anywhere in the manuscript. White prepupal? Time? Likewise a shift-down was done at "late L3" but that meaning is also vague. Moreover, I was surprised to see they did not do a shift-up at the late L3 stage, to give completeness to the experiment. Why?

Response: We have added more precise descriptions of the timing, and we will also add the requested late L3 shift-up experiment.

Looking at the "shape" of the larval wing pouch they see a difference in the mutants. The pouch can be approximated as an ellipse, but with differing topology to the adult wing. Here, they muddled the analysis. The adult wing surface is analogous to one hemisphere of the larval wing pouch, ie., either dorsal or ventral compartment. The distance along the AP boundary from the pouch border to DV midline is topologically comparable to the PD length of the adult wing. The distance along the DV boundary from A border to P border is topologically comparable to the AP length of the adult wing. They confusingly call this latter metric the "DV length" and the former metric the "AP length" , and in fact they do not measure the PD length but PD+DP length. Confusing. Please change to make this consistent with earlier analysis of the adult and invert the reported ratio and divide by two.

Then you would find the larval PD/AP ratio is smaller in the FT and DS mutants than wildtype, which resembles the smaller PD/AP ratio seen in the mutant adult wings. Totally consistent and also provides further evidence with the ts experiments that FT and DS exert shape effects in the larval phase of life.

Response: As noted by Reviewer 1 in cross-referencing, some of the statements made by Reviewer 2 here are incorrect, eg “The distance along the DV boundary from A border to P border is topologically comparable to the AP length of the adult wing.” They are correct where they note that the A-P length we measure in the discs is actually equivalent to 2x the adult wing length, since we are measuring along both the dorsal and ventral wing, but this makes no difference to the analysis as the point is to compare shape between time points and genotypes, not to make inferences based on the absolute numbers obtained. The numerical manipulations suggested are entirely feasible but we think they are unnecessary.

The remainder of the manuscript has experimental results that are more problematic, and really the authors do not figure out how the shape effect in larval stages is altered. I outline below the main problems.

1. They compare the FT DS shape phenotypes to those of mutants or knockdowns in Hippo pathway genes (Hippo is known to be downstream of FT and DS). They find these Hippo perturbations do have shape effects trending in same direction as FT and DS effects. Knockdown reduces the PD/AP ratio while overexpressing WARTS increases the PD/AP ratio. The effect magnitudes are not as strong, but then again, they are using hypomorphic alleles and RNAi, which often induces partial or hypomorphic phenotypes. The effect strength is comparable when wing pouches are young but then dissipates over time, while FT and DS effects do not dissipate over time. The complexity of the data do not negate the idea that Hippo signaling is also playing some role and could be downstream of FT and DS in all of this. But the authors really downplay the data to the point of stating "These results imply that Ds-Fat influences wing pouch shape during wing disc growth separately from its effects on Hippo signaling." I think a more expansive perspective is needed given the caveats of the experiments.

Response: Our results emphasize that the effects of Ds-Fat on wing shape cannot be explained solely by effects on Hippo signaling, eg as we stated on page 7 “These observations suggest that Hippo signaling contributes to, but does not fully explain, the influence of ds or fat on adult wing shape.” We also note that impairment of Hippo signaling has similar effects in younger discs, but very different effects in older discs, which clearly indicates that they are having very different effects during disc growth; we will revise the text to make sure our conclusions are clear.

              The reviewer wonders whether some of the differences could be due to the nature of the alleles or gene knockdown. First, the *ex*, *ds*, and *fat* alleles that we use are null alleles (eg see FlyBase), so it is not correct to say that we use only hypomorphic alleles and RNAi. We do use a hypomorphic allele for wts, and RNAi for hpo, for the simple reason that null alleles in these genes are lethal, so adult wings could not be examined. A further issue that is not commented on by the reviewer, but is more relevant here, is that there are multiple inputs into Hippo signaling, so of course even a null allele for ex, ds or fat is not a complete shutdown of Hippo signaling. Nonetheless, one can estimate the relative impairment of Hippo signaling by measuring the increased size of the wings, and from this perspective the knockdown conditions that we use are associated with roughly comparable levels of Hippo pathway impairment, so we stand by our results. We do however, recognize that these issues could be discussed more clearly in the text, and will do so in a revised manuscript.

Puzzlingly, this lack of taking seriously a set of complex results does not transfer to another set of experiments in which they inhibit or activate ROK, the rho kinase. When ROK is perturbed, they also see weak effects on shape when compared to FT or DS perturbation. This weakness is seen in adults, larvae, clones and in epistasis experiments. The epistasis experiment in particular convincingly shows that constitutuve ROK activation is not epistatic to loss of DS; in fact if anything the DS phenotype suppresses the ROK phenotype. These results also show that one cannot simply explain what FT and DS are doing with some single pathway or effector molecule like ROK. It is more complex than that.

What I really think was needed were experiments combining FT and DS knockdown with other mutants or knockdowns in the Hippo and Rho pathways, and even combining Hippo and Rho pathway mutants with FT or DS intact, to see if there are genetic interactions (additive, synergistic, epistatic) that could untangle the phenotypic complexity.

Response: We’re puzzled by these comments. First, we never claimed that what Fat or Ds do could be explained simply by manipulation of Rok (eg, see Discussion). Moreover, examination of wings and wing discs where ds is combined with Rho manipulations is in Fig 7, and Hippo and Rho pathway manipulation combinations are in Fig S5. We don’t think that combining ds or fat mutations with other Hippo pathway mutations would be informative, as it is well established that Ds-Fat are upstream regulators of Hippo signaling.

Laser cutting experiments were done to see if there is anisotropy in tissue tension within the wing pouch. This was to test a favored idea that FT and DS activity generates anisotropy in tissue tension, thereby controlling overall anisotropic shape of the pouch. However there is a fundamental flaw to their laser cutting analysis. Laser cutting is a technique used to measure mechanical tension, with initial recoil velocity directly proportional to the tissue's tension. By cutting a small line and observing how quickly the edges of the cut snap apart, people can quantify the initial recoil velocity and infer the stored mechanical stress in the tissue at the time of ablation. Live imaging with high-speed microscopy is required to capture the immediate response of the tissue to the cut since initial recoil velocity occurs in the first few seconds. A kymograph is created by plotting the movement of the tissue edges over this time scale, perpendicular to the cut. The initial recoil velocity is the slope of the kymograph at time zero, representing how fast the severed edges move apart. A higher recoil velocity indicates higher mechanical tension in the tissue. However, the authors did not measure this initial recoil velocity but instead measured the distance between the severed edges at one time point: 60 seconds after cutting. This is much later than the time point at which the recoil usually begins to dissipate or decay. This decay phase typically lasts a minute or two, during which time the edges continue to separate but at a progressively slower rate. This time-dependent decay of the recoil reveals whether the tissue behaves more like a viscous fluid or an elastic solid. Therefore, the distance metric at 60 seconds is a measurement of both tension and the material properties of the cells. One cannot know then whether a difference in the distance is due to a difference in tension or fluidity of the cells. If the authors made measurements of edge separation at several time points in the first 10 seconds after ablation, they can deconvolute the two. Otherwise their analysis is inconclusive. Anisotropy in recoil could be caused by greater tissue fluidity along one axis. Observing a gradient of cell fluidity in a tissue along one axis of a tissue has been observed in the amnioserosa of Tribolium for example. (Related and important point - was the anisotropy of recoil oriented along the PD or AP axis or not oriented to either axis, this key point was never stated)..

The authors cannot definitiviely conclude anything about mechanical tension from their reported cutting data.

Response: As noted by Reviewer 1 in cross-commenting, there is no fluidity on a time scale of 1 minute in the wing disc, and circular ablations are an established methods to investigate tissue stress. We choose the circular ablation method in part because it interrogates stress over a larger area, whereas cutting individual junctions is subject to more variability, particularly as the orientation of the junction (eg radial vs tangential) impacts the tension detected in the wing disc. Nonetheless, we will add recoil measurements to the revised manuscript to complement our circular ablations, which we expect will provide independent confirmation of our results and address the Reviewer’s concern here.

They measured the eccentricity of wing pouch cells near the pouch border, and found they were highly anisotropic compared to DS mutant cells at comparable locations. Cells were elongated but again what if either axis (PD or AP) they were elongated along was never stated. If cell anistropy is caused by polarized myosin activity, that activity is typically polarized along the short edges not long edges. Thus, recoil velocity after laaser cutting would be stonger along the axis aligned with short cell edges. It looks like the cutting anisotropy they see is greater along the axis aligned with long cell edges. Of course, if the cell anisotropy is caused by a pulling force exerted by the pouch boundary, then it would stretch the cells. This would in fact fit their cutting data. But then again, the observed cell anisotropy could also be caused by variation in the fluid-solid properties of the wing cells as discussed earlier. Compression of the cells then would deform them anisotropically and produce the anisotropic shapes that were observed, Therefore, interpreting what causes the cell anistropy and how DS regulates it is difficult,

Response: As noted by Reviewer 1 in cross-commenting, it is well established that tension and myosin are higher along long edges in the proximal wing. However, we acknowledge that we could do a better job of making the location and orientation of the regions shown in these experiments clear and, we will address this in a revised manuscript.

The imaging and analysis of the myosin RLC by GFP tagging is also flawed. SQH-GFP is a tried and true proxy for myosin activity in Drosophila. Although the authors image the wing pouch of wildtype and DS mutants. they did so under low magnification to image the entire pouch. This gives a "low-res" perspective of overall myosin but what they needed to do was image at high magnification in that proximal region of the pouch and see if Sqh-GFP is polarized in wildtype cells along certain cell edges aligned with an axis. And if such a polarity is observed, is it present or absent in the DS mutant. From the data shown in Figure 5, I cannot see any significant difference between wildtype and knocked down samples at this low resolution. Any difference, if there is any, is not really interpretable.

Response: We agree that examination of myosin localization at high resolution to see if it is polarized is a worthwhile experiment. We did in fact do this, and myosin (Sqh:GFP) appeared unpolarized in ds mutants. However, the levels of myosin were so low that we didn’t feel confident in our assessment, so we didn’t include it. We now recognize that this was a mistake, and we will include high resolution myosin images and assessments of (lack of) polarity in a revised manuscript to address this comment.

In conclusion, the manuscript has multiple problems that make it imposiible for the authors to make the claims they make in the current manuscript. And even if they calibrated their interpretations to fit the data, there is not much of a simple clear picture as to how FT and DS regulate pouch eccentricity in the larval wing.

Response: We think that the legitimate issues raised are addressable, as described above, while some of the criticisms are incorrect (as noted by Reviewer 1).

Reviewer #2 (Significance (Required)): This manuscript describes experiments studying the role that the protocadherins FAT and DACHSOUS play in determining the two dimensional "shape" of the fruit fly wing. By "shape", the manuscript really means how much the wing's outline, when approximated as an ellipse, deviates from a circle. The elliptical approximations of FT and DS mutant wings more closely resemble a circle compared to the more eccentric wildtype wings. This suggests the molecules contribute to anisotropic growth in some way. A great deal of attention has been paid on how FT and DS regulate overall organ growth and planar cell polarity, and the Irvine lab has made extensive contributions to these questions over the years. Somewhat understudied is how FT and DS regulate wing shape, and this manuscript focuses on that. It follows up on an interesting result that the Irvine lab published in 2019, in which mud mutants randomized spindle pole orientation in wing cells but did not change the eccentricity of wings, ruling out biased cell division orientation as a mechanism for the anisotropic growth.

__Reviewer #3 (Evidence, reproducibility and clarity (Required)): __ Summary The authors investigate the mechanisms underlying epithelial morphogenesis using the Drosophila wing as a model system. Specifically, they analyze the contribution of the conserved Fat/Ds pathway to wing shape regulation. The main claim of the manuscript is that Ds/Fat controls wing shape by regulating tissue mechanical stress through MyoII levels, independently of Hippo signaling and tissue growth.

Major Comments To support their main conclusions, the authors should address the following major points and consider additional experiments where indicated. Most of the suggested experiments are feasible within a reasonable timeframe, while a few are more technically demanding but would substantially strengthen the manuscript's central claims.

Figure 1: The authors use temperature-sensitive inactivation of Fat or Ds to determine the developmental window during which these proteins regulate wing shape. To support this claim, it is essential to demonstrate that upon downshift during early pupal stages, Ds or Fat protein levels are restored to normal. For consistency, please include statistical analyses in Figure 1P and ensure that all y-axis values in shape quantifications start at 1.

Response: We will do the requested antibody stains for Fat (Ds antibody is unfortunately no longer available, but the point made by the reviewer can be addressed by Fat as the approach and results are the same for both genes). We have also added the requested statistical analysis to Fig 1P, and adjusted the scales as requested.

Figure 2: The authors propose that wing shape is regulated by Fat/Ds during larval development. However, Figure 2L suggests that wing elongation occurs in control conditions between 6 and 12 h APF, while this elongation is not observed upon Ds RNAi. The authors should therefore perform downshift experiments while monitoring wing shape during the pupal stage to substantiate their main claim. In addition, equivalent data for Fat loss of function should be included to support the assertion that Fat and Ds act similarly.

Response: As noted in our response to point 1 of Reviewer 1, we agree that there does seem to be relatively more elongation in control wings than in ds RNAi wings, but we think this likely reflects effects of ds on growth during larval stages, and we will revise the manuscript to comment on this.

We will also add the suggested examination of fat RNAi pupal wings.

The suggested examination of pupal wing shape in downshift experiments is unfortunately not feasible. Our temperature shift experiments expressing ds or fat RNAi are done using the UAS-Gal4-Gal80tssystem. We also use the UAS-Gal4 system to mark the pupal wing. If we do a downshift experiment, then expression of the fluorescent marker will be shut down in parallel with the shut down of ds or fat RNAi, so the pupal wings would no longer be visible.

Figure 3: The authors state that "These observations indicate that Ds-Fat signaling influences wing shape during the initial formation of the wing pouch, in addition to its effects during wing growth." This conclusion is not fully supported, as the authors only examine wing shape at 72 h AEL. At this stage, fat or ds mutant wings already display altered morphology. The authors could only make this claim if earlier time points were fully analyzed. In fact, the current data rather suggest that Ds function is required before 72 h AEL, as a rescue of wing shape is observed between 72 and 120 h AEL.

Response: First, I think we are largely in agreement with the Reviewer, as the basis for our saying that DS-Fat are likely required during initial formation of the wing pouch is that our data show they must be required before 72 h AEL. Second, 72 h is the earliest that we can look using Wg expression as a marker, as at earlier stages it is in a ventral wedge rather than a ring around the future wing pouch + DV line (eg see Fig 8 of Tripathi, B. K. & Irvine, K. D. The wing imaginal disc. Genetics (2022) doi:10.1093/genetics/iyac020.). We can revise the text to make sure this is clear.

Figure 4: The authors state that "The influence of Ds-Fat on wing shape is not explained by Hippo signaling." However, this conclusion is not supported by their data, which show that partial loss of ex or hippo causes clear defects in wing shape. In addition, the initial wing shape is affected in wts and ex mutants, and hypomorphic alleles were used for these experiments. Therefore, the main conclusion requires revision. It would be useful to include a complete dataset for hippo RNAi, ex, and wts conditions in Figure S1. The purpose and interpretation of the InR^CA experiments are also unclear. While InR^CA expression can increase tissue growth, Hippo signaling has functions beyond growth control. Whether Hippo regulates tissue shape through InR^CA-dependent mechanisms remains to be clarified.

Response: As noted in our response to point 1 of Reviewer 2 - our results emphasize that the effects of Ds-Fat on wing shape cannot be explained solely by effects on Hippo signaling, eg as we stated on page 7 “These observations suggest that Hippo signaling contributes to, but does not fully explain, the influence of ds or fat on adult wing shape.” We also note that impairment of Hippo signaling has similar effects in younger discs, but very different effects in older discs, which clearly indicates that they are having very different effects during disc growth. We will make some revisions to the text to make sure that our conclusions are clear throughout.

While we used a hypomorphic allele for wts, because null alleles are lethal, the ex allele that we used is described in Flybase as an amorph, not a hypomorph, and as noted in our response to Reviewer 2, we will add some discussion about relative strength of effects on Hippo signaling.

In Fig S1, we currently show adult wings for ex[e1] and RNAi-Hpo, and wing discs for wts[P2]/wts[x1], and for ex[e1]. The wts combination does not survive to adult so we can’t include this. We will however, add hpo RNAi wing discs as requested.

              The purpose of including InR^CA experiments is to try to separate effects of Hippo signaling from effects of growth, because InR signaling manipulation provides a distinct mechanism for increasing growth. We will revise the text to try to make sure this is clearer.

Figure 5: This figure presents images of MyoII distribution, but no quantification across multiple samples is provided. Moreover, the relationship between changes in tissue stress and MyoII levels remains unclear. Performing laser ablation and MyoII quantification on the same samples would provide stronger support for the proposed conclusions.

Response: We will revise the quantitation so that it presents analysis of averages across multiple discs, rather than representative examples of single discs.

Both the myosin imaging, and the laser ablation were done on the same genotypes (wildtype and ds) at the same ages (108 h AEL) so we think it is valid to directly compare them. Moreover, the imaging conditions for laser ablation and myo quantification are different, so it’s not feasible to do them at the same time (For ablations we do a single Z plane and a single channel (has to include Ecad, or an equivalent junctional marker) on live discs, so that fast imaging can be done. For Myo imaging we do multiple Z stacks and multiple channels (eg Ecad and Myo), which is not compatible with the fast imaging needed for analysis of laser ablations).

Figure 6: It is unclear when Rok RNAi and Rok^CA misexpression were induced. To substantiate their claims, the authors should measure both MyoII levels and mechanical tension under the different experimental conditions in which wing shape was modified through Rok modulation (i.e. the condition shown in Fig. 7G). For comparison, fat and ds data should be added to Fig 6H. Overall, the effects of Rok modulation appear milder than those of Fat manipulation. Given that Dachs has been shown to regulate tension downstream of Fat/Ds, it would be informative to determine whether tissue tension is altered in dachs mutant wings and to assess the relative contribution of Dachs- versus MyoII-mediated tension to wing shape control. It would also be interesting to test whether Rok activation can rescue dachs loss-of-function phenotypes.

Response: In these Rok experiments there was no separate temporal control of Rok RNAi or Rok^CA expression, they were expressed under nub-Gal4 control throughout development.

We will add examination of myosin in combinations of ds RNAi and rok manipulation as in Fig 7G to a revised manuscript.

Data for fat and ds comparable to that shown in Fig 6H is already presented in Fig 3D, and we don’t think its necessary to reproduce this again in Fig 6H.

We agree that the effects of Rok manipulations are milder than those of Fat manipulations; as we try to discuss, this could be because the pattern or polarity of myosin is also important, not just the absolute level, and we will add assessment of myosin polarity.

The suggestion to also look at dachs mutants is reasonable, and we will add this. In addition, we plan to add an "activated" Dachs (a Zyxin-Dachs fusion protein previously described in Pan et al 2013) that we anticipate will provide further evidence that the effects of Ds-Fat are mediated through Dachs. We will also add the suggested experiment combining Rok activation with dachs loss-of-function.

Figure 7: The authors use genetic interactions to support their claim that Fat controls wing shape independently of Hippo signaling. However, these interactions do not formally exclude a role for Hippo. Moreover, previous work has shown that tissue tension regulates Hippo pathway activity, implying that any manipulation of tension could indirectly affect Hippo and growth. To provide more direct evidence, the authors should further analyze MyoII localization and tissue tension under the various experimental conditions tested (as also suggested above).

Response: As discussed above, our data clearly show that Fat has effects independently of Hippo signaling that are crucial for its effects on wing shape, but we did not mean to imply that the regulation of Hippo signaling by Fat makes no contribution to wing shape control, and we will revise the text to make this clearer. We will also add additional analysis of Myosin localization , as described above.

Reviewer #3 (Significance (Required)): How organ growth and shape are controlled remains a fundamental question in developmental biology, with major implications for our understanding of disease mechanisms. The Drosophila wing has long served as a powerful and informative model to study tissue growth and morphogenesis. Work in this system has been instrumental in delineating the conserved molecular and mechanical processes that coordinate epithelial dynamics during development. The molecular regulators investigated by the authors are highly conserved, suggesting that the findings reported here are likely to be of broad biological relevance.

Previous studies have proposed that anisotropic tissue growth regulates wing shape during larval development and that such anisotropy induces mechanical responses that promote MyoII localization (Legoff et al., 2013, PMID: 24046320; Mao et al., 2013, PMID: 24022370). The Ds/Fat system has also been shown to regulate tissue tension through the Dachs myosin, a known modulator of the Hippo/YAP signaling pathway. As correctly emphasized by the authors, the respective contributions of anisotropic growth and mechanical tension to wing shape control remain only partially understood. The current study aims to clarify this issue by analyzing the role of Fat/Ds in controlling MyoII localization and, consequently, wing shape. This represents a potentially valuable contribution. However, the proposed mechanistic link between Fat/Ds and MyoII localization remains insufficiently explored. Moreover, the role of MyoII is not fully discussed in the broader context of Dachs function and its known interactions with MyoII (Mao et al., 2011, PMID: 21245166; Bosveld et al., 2012, PMID: 22499807; Trinidad et al., 2024, PMID: 39708794). Most importantly, the experimental evidence supporting the authors' conclusions would benefit from further strengthening. It should also be noted that disentangling the relative contributions of anisotropic growth and MyoII polarization to tissue shape and size remains challenging, as MyoII levels are known to increase in response to anisotropic growth (Legoff et al., 2013; Mao et al., 2013), and mechanical tension itself can modulate Hippo/YAP signaling (Rauskolb et al., 2014, PMID: 24995985).

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Referee #3

Evidence, reproducibility and clarity

Summary

The authors investigate the mechanisms underlying epithelial morphogenesis using the Drosophila wing as a model system. Specifically, they analyze the contribution of the conserved Fat/Ds pathway to wing shape regulation. The main claim of the manuscript is that Ds/Fat controls wing shape by regulating tissue mechanical stress through MyoII levels, independently of Hippo signaling and tissue growth.

Major Comments

To support their main conclusions, the authors should address the following major points and consider additional experiments where indicated. Most of the suggested experiments are feasible within a reasonable timeframe, while a few are more technically demanding but would substantially strengthen the manuscript's central claims.

Figure 1:

The authors use temperature-sensitive inactivation of Fat or Ds to determine the developmental window during which these proteins regulate wing shape. To support this claim, it is essential to demonstrate that upon downshift during early pupal stages, Ds or Fat protein levels are restored to normal. For consistency, please include statistical analyses in Figure 1P and ensure that all y-axis values in shape quantifications start at 1.

Figure 2:

The authors propose that wing shape is regulated by Fat/Ds during larval development. However, Figure 2L suggests that wing elongation occurs in control conditions between 6 and 12 h APF, while this elongation is not observed upon Ds RNAi. The authors should therefore perform downshift experiments while monitoring wing shape during the pupal stage to substantiate their main claim. In addition, equivalent data for Fat loss of function should be included to support the assertion that Fat and Ds act similarly.

Figure 3:

The authors state that "These observations indicate that Ds-Fat signaling influences wing shape during the initial formation of the wing pouch, in addition to its effects during wing growth." This conclusion is not fully supported, as the authors only examine wing shape at 72 h AEL. At this stage, fat or ds mutant wings already display altered morphology. The authors could only make this claim if earlier time points were fully analyzed. In fact, the current data rather suggest that Ds function is required before 72 h AEL, as a rescue of wing shape is observed between 72 and 120 h AEL.

Figure 4:

The authors state that "The influence of Ds-Fat on wing shape is not explained by Hippo signaling." However, this conclusion is not supported by their data, which show that partial loss of ex or hippo causes clear defects in wing shape. In addition, the initial wing shape is affected in wts and ex mutants, and hypomorphic alleles were used for these experiments. Therefore, the main conclusion requires revision. It would be useful to include a complete dataset for hippo RNAi, ex, and wts conditions in Figure S1. The purpose and interpretation of the InR^CA experiments are also unclear. While InR^CA expression can increase tissue growth, Hippo signaling has functions beyond growth control. Whether Hippo regulates tissue shape through InR^CA-dependent mechanisms remains to be clarified.

Figure 5:

This figure presents images of MyoII distribution, but no quantification across multiple samples is provided. Moreover, the relationship between changes in tissue stress and MyoII levels remains unclear. Performing laser ablation and MyoII quantification on the same samples would provide stronger support for the proposed conclusions.