5,450 Matching Annotations
  1. Mar 2024
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      Referee #3

      Evidence, reproducibility and clarity

      Summary

      In this manuscript the authors have studied a variety of phenotype of two generated viral stocks of SIVmac239/316 molecular cloned virus generated in either CD4 T-cells (T-SIV) and macrophages (M-SIV). These stocks are isogenic apart from the cell type produced in and are identical in Env amino acid sequence. Stocks generated from the different cell-types were found to alter EndoH digestion, mannose profiling, infectivity, Env incorporation and lectin interactions and sensitivity to CBS and monkey sera neutralisation. The claim is that producer cell-type can influence SIV biological properties that associate with viral transmission, dissemination and inhibition.

      Major comments

      1. Line 85 "These substitutions facilitate efficient utilization of CCR5 in the absence or at very low levels of CD4 expression (Puffer et al.2002). This makes the molecular clone studied rather unique and the authors should aim to address this throughout. It does not take away from the results presented but should be addressed.
      2. (Figure 1) State the predicted size differences between T-SIV and M-SIV stocks with EndoH digestion (and similar for all 3 runs?).
      3. Line 95 Data should be shown. This describes infectivity and could incorporated within Figure 3 along with infection of the TZM-bl cells. Infectivity of T-SIV and M-SIV on primary CD4 T-cells and macrophages is of importance. This would only be possible I assume if p27 levels were measured at each time-point collected.
      4. There is a lack of statistical difference in the results shown in Figure 2. I assume this is due to a single measurement, but can comment be made on likelihood of biological significance with such difference between values.
      5. (Figure 3) On TZM-bl cells the T-SIV stock shown 55-fold lower infectivity compared to M-SIV. This is the reverse as to what was found on macaque CD4 T-cells where T-SIV showed a 6.5-fold higher infectivity than M-SIV? Needs addressing. Again, this should be considered in context of the results with CEMx174 R5 cells where infection between the 2 stocks appears to be similar (Figure 6).
      6. (Figure 5) The result may look cleaner if No Lectin value is subtracted from the cell lines carrying the lectin expression?
      7. A much clearer introduction to CBA's would be beneficial.
      8. A concern I have is the presentation of data in Figures 6 and 7, especially given that the cell line used is the TZM-bl cell which has been shown to be 55-fold less infectible with T-SIV. Plotting the results as % infectivity on the same graph could be somewhat misleading. Two graphs one panel for M-SIV and one for T-SIV may be easier to follow. The CEMx174 cell line may have been a better choice as similarity to infection was found? But assume those experiments were not performed?
      9. I do feel the Discussion is extremely long and could be stream-lined to make it clearer and to the point.
      10. Materials and Methods section. Is the first section on Animal studies required. Could this not just be cited if it has been previously published.

      Minor comments

      1. A) needs to be removed from Figure legend 1.
      2. Line 160 I assume this the result from (Fig 3A).
      3. Line 255-257 Difficult sentence to understand.

      Significance

      This is an interesting study and where there is significance for understanding how HIV/SIV viral phenotypes (those associated with transmission and emergence following transmssion) can be influenced by the cell type infected and modifications to glycosylation profiling).

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      Referee #2

      Evidence, reproducibility and clarity

      Assessment for Karsten et al

      In this manuscript, Karsten et al described the biology of simian macrophage derived SIV and simian CD4+ T cells derived SIV have different levels and types of glycosylation in their particles. The authors attributed that these differences in glycosylation are related to SIV function (infection / spread).

      It appears to this assessor that some of the supplementary data can be brought to the front as part of the main figures for presentation.

      CURRENT figures 3, 5, and 7 can be combined into one figure.

      Similarly, CUREENT Figure 4, and 6 can also be grouped.

      Alternatively, incorporating additional approaches in each set of figures to tighten the claims.

      I would support the manuscript for its eventual publication, but I believe several major (but achievable) amendments are needed.

      Major suggestions

      Karsten et al pitched their story as glycosylation of SIV from different primary cells are linked to different functionality in its title and abstract, yet the authors then declared in discussion (line 318) that establishing a direct link between Env glycosylation and viral functions is technically challenging and beyond the scope of the study. This assessor feels that authors need to decide whether current manuscript should be a descriptive study (which is more fitting for a less impactful journal) or a study with further mechanistic insights.

      Table S1 is highly important and should be part of the main figure. Specifically, authors took the opportunity to highlight the differential % of sialic acid terminal glycans in line 133. The charge of the sialic acids would be simple mechanism for these M-SIV particle to attach. Authors should consider some of the described nano-luciferase based viral particle attachment assays used in HIV-glycan biology. Authors should be able to treat SIV (or SIV VLPs) with sialidase to quantify the role of sialic acids on binding.

      As authors carefully pointed out (throughput the manuscript) that the identity (and biology) of the producer cells can have profound impacts on glycosylation events of viral particles that are being produced. This assessor was then interested to understand precisely how their simian PBMCs and monocytes derived macrophages were prepared. Additional details in M&M would be very helpful.

      With the emphasis of cell type and glycosylation relationship, it is puzzling that authors would have chosen to use TZM-bl (artificially engineered cell line) and spinoculation (2hr to push the viruses down to cell surface with 870 x G force) in Figure 3 for comparison of M-SIV and T-SIV infectivity. To this assessor, this assay neglected the biological roles of SIV glycans. In context, 870 x G is ~150x higher than most human can withstand.

      Using a single antibody DA6 (in Figure 4, cited Edinger 2000) for Env incorporation estimation via Western seems to be crude and inadequate, even in the context of isogenic virus clone. As authors pointed out, different levels of glycosylation can affect protein folding, therefore affecting Env incorporation. By the same argument, differentially glycosylated Env protein can also impact on the ability of 'epitopes within Env protein' to be recognised by Ab. Therefore, virion incorporation of Env might not be affected, but just the detectability by a specific Ab. Western evaluation with a panel of anti-Env antibodies will help. Furthermore, quantitative proteomics coupling with glycomics would be highly useful.

      It is understood that T-SIV were pooled from supernatant derived from 9 animals of PBMCs. Levels of p27 production (presumed as particles but including free p27 in reality) from each animal donor should be listed in supplement. Similar types of details should be made available for M-SIV that were derived from 8 animal donors of macrophages. qPCR estimations on the levels of viral particles production in T-SIV and M-SIV from primary cell culture amplifications appear to be already available, such information should be included in supplementary to strengthen the authors' estimated / relationships amongst glycosylation, virion Env incorporation levels, and viral particle productions are carefully controlled.

      Non-glycan biologists generally do not appreciate some of the fine details in glycan biology. The T-SIV and M-SIV system is a great model system to decode some of the functionality of glycan biology. The current team should have (in my opinion) a clear graphic representation on describing what types of different glycans in T-SIV and M-SIV are likely to contribute to the potential differences in biological outcomes. Such incorporation will guide non-glycan biologists to better appreciate the focus and the directions of authors, thereby further improving the citation of this work when it is published after peer reviewed. Importantly, focusing a specific question to be addressed may help to consolidate effort to accelerate publication of this work. A beautiful story line, just need to cross many 't' and dot a few 'i' in my view.

      Most primate centres often incorporate transcriptomic studies in their animal works. It will be helpful for the audience if the authors could provide additional transcriptomic data (with a focus on glycosylation related genes) of simian CD4+ T cells, simian macrophages, SIV infected simian CD4+ T cells, and SIV infected simian macrophages. These data will improve the comprehensiveness of this study (and should not require any major wet-lab studies) and add weight on the arguments of the authors.

      Significance

      General Assessment - The biological significance system these authors possess is highly valuable in virology and will reveal significant insights in the functions of glycans in infectious diseases. Authors are generally (in my opinion) correct with the big picture impacts / contributions of glycan biology. Presented experimentations need to be tighter controlled to avoid over-interpretations. A tighter focus of research question (or claim) will reduce levels of extra work prior to publication.

      Advance - level of advance will be high regarding the role of glycan in biology and infectious diseases. The T-SIV and M-SIV system is a naturally relevant system with many prior works that lay the foundation to understand viral glycan biology.

      Audience - with the right pitch and proper explanations, general audience will be highly interested. At the end of the day, glycan biology is shared amongst all living cells.

      My expertise is in virology, particular in HIV. I also have a strong interest in glycan biology. I described the first glycan-glycan interaction in viral pathogenesis recently, explaining how these glycan-based interaction serves as a molecular Velcro for attachment, likely a shared mechanism in virology and biology in general.

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      Referee #1

      Evidence, reproducibility and clarity

      This is interesting data and will add to the relatively sparse literature in this area, but there are several issues limiting its utility and accessibility, and other data, experiments or explanations are needed to address these issues. The other major issue is that there is no direct experimental evidence showing specifically that the glycosylation being described, particularly the differences in T-SIV vs. M-SIV, as there had been in some of the prior studies. Specifically removing or adding particular glycans, and then showing changed effects on viral entry - particularly in primary cells - would add substantively to the findings and make this a much stronger study. In addition, there are a number of other more specific and/or minor changes that could be made to enhance the value of this manuscript.

      1. As noted above, the differences in glycosylation are difficult to understand without more background and perhaps a figure, but it is also not clear that the changes described between lines 119 and 137 are biologically or statistically meaningful. For example, does it matter that more M-SIV virions have glycans with four antennae than T-SIV? Are there other data that show this or could experiments be done to specifically cleave these glycans at certain points to reduce their complexity and show that the infectivity differences between M-SIV and T-SIV disappear? Further, it is difficult to confirm the statement on lines 124-125 that "profiles of complex-type N-glycans differed between the two viruses (Fig. 2C)", as no statistical tests were done to compare the glycosylation being detailed in the M-SIV and T-SIV. It is more appropriate to make note that there are minor between M-SIV and T-SIV or run specific statistical tests on the data.
      2. On line 161, the authors note that the results showing that "the virus-producing cell has a broader impact on SIV infectivity beyond its influence on Env incorporation." This is certainly one possibility that is suggested by these and prior data, there are also other possibilities. For example, the impact of Env is not linear and perhaps a certain number of Env need to be engaged, creating some kind of threshold effect that means that the virions with fewer Env just have less infectivity. Given that there is significant data that virions are generated in different locations in macrophages and T-cells, this could also be a function of which specific membrane areas in different cell types that Env embeds in, or it could be something else associated with Env that is not cell type specific.
      3. For the studies in Figure 5, looking at the direct vs. indirect infectivity, it is not clear why CEMx174 R5 cells (a T-cell/B-cell hybrid line) were used instead of primary macrophages or T-cells, or macrophage or T-cell lines or a fully agnostic cell type. This would be more convincing tested on primary cells, or at least comparing in a myeloid lineage line as well.
      4. In Figure 6, it is not clear that VSV-G pseudotyped virus is an appropriate control, as it enters via the acidified endosome pathway and not via similar processes as the T- and M-SIV derived virions. While this may show that the glycans can bind to CBA to inhibit entry, it could also mean that the general process of endocytosis is not as susceptible to CBA inhibition and this difference in pathways should be noted as a caveat.
      5. A very large number of cell lines were used, and it is not clear why experiments were done using so many different indicator or target lines, instead of performing most assays in a single line or set of lines so that they are comparable across experiments. Some discussion of the rationale for this would be helpful.

      Minor comments

      1. Inclusion of the p27 data characterizing the amount of virus in M-SIV and T-SIV stocks (line 95) should be shown as at least a supplemental figure or could easily be added to figure 1.
      2. The figures are relatively thin and could be combined with other figures to better connect the experiments. For instance, Figure 1 could serve as panel A for what is currently listed as Figure 2 because it is a preliminary data to the experiments in Figure 2.
      3. The authors should include quantitation of the Western blot data in Figure 1 in an adjoining graph.
      4. The legend states that the results in Figure 7 were obtained from two independent experiments (line 778), each with 3 technical replicates. As this represents only 2 biological replicates, and the experiments were performed in easily accessible cells (TZM-bl), they should be performed 1 - 3 more times to provide a more appropriate and robust data set for statistical analysis.

      Significance

      The manuscript Karsten et. al., 2024, discusses the differences in infectivity resulting from the cellular origin of SIV virions, specifically comparing virus generated in macrophages and T-cells. The primary focus of this comparison is the differences in glycosylation of the Env proteins on the virions with a T-cell origin (T-SIV) and a macrophage origin (M-SIV). These studies are expansions of a small number of prior publications that focus on this area and are cited extensively. The major innovation in this study were that the differences in glycan composition were assessed using xCGE-LIF glycan profiling, which is more detailed than the glycan profiling methods in the prior studies. Then the T-SIV and M-SIV were compared for their susceptibility to distinct carbohydrate binding agents, either ulex europaeus agglutinin (UEA), cyanovirin-N (CV-N), or galanthus nivalis agglutinin (GNA). These agents each bind different glycans, so differences in the capacity of these agents to bind T-SIV vs. M-SIV suggest confirming the presence of different types of glycans. Similar studies with serum from SIV infected macaques, the results suggesting some differences in susceptibility to neutralization in viruses of different cellular origin.

      One primary issue is that many readers will not be familiar with the different types of glycosylation, the differences between subtypes of glycans, different branches, etc ... and what the biological relevance of these differences is to viral infection and/or immune activity. For example, the discussion refers to M5, M6, M8 and M9 on T-SIV vs. M-SIV (lines 234 - 5) but knowledge of these is not universal and there is no background to place these statements in context and understand why this might matter. To address this, additional language is needed, as well as the addition of a figure that helps to visualize the different glycans being discussed. Adding this to the beginning as part of the introduction, or at the end as a summary of the findings in the paper, would increase accessibility for a broader audience.

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      Reply to the reviewers

      We would like to thank both reviewers for their thorough and constructive evaluation and comments on our manuscript. Following their suggestions, we have edited our manuscript to address all criticisms and comments from them. We hope that, with these introduced changes, this manuscript will be suitable for publication in an appropriate journal. Detailed point-to-point responses are shown below.

      __Point-to-point response to reviewers’ critiques: __

      Reviewer 1

      Summary: Stadler and colleagues characterized CFAP410, using molecular structural biology, biophysics, biochemistry, cellular imaging and genetic engineering, to address molecular mechanism of ciliopathies caused by defect of this protein. They crystalized the C-terminal domain of CFAP410 and its homologue, from Trypanosoma, human and Chlamydomonas. All of them take tetrameric complex formation with four bundle helices in the center. Then they mutated highly conserved residues, L219 and L224, which are located at the helix bundle, and characterized its biophysical properties, demonstrating oligomerization defect and, in case of L224 mutation, collapse of secondary structure as well. This was supported by molecular dynamics. Next they examined the effect of these mutation in vivo using Trypanosoma brucei. They visualized the localization of CFAP410 at the postrior cell tip and its transfer to the basal body. By mutation, transfer of CFAP410 is prohibited and cytokinesis defect occurs. The experiments are logically designed and the results are clearly and convincingly stated. Undoubtedly this work deserves publication after minor revision of the manuscript.

      Strength:* This is a compact paper, clearly stating the biological aim and experiments designed for that.

      Limitation: While it is undoubtedly proved that the C-terminal domain of CFAP410 forms tetramer and L219 and L224 are key residues and that mutation of these residues causes severe defect at the localization of CFAP410, it is an overstatement to conclude the tetramer formation is essential for the localization. The authors experiments cannot exclude the possibility of another consequence of mutation (different from origomerization), which is the cause of abnormal localization.

      *

      : Indeed, the reason for the disrupted localization of the disease-causing mutation L224P to the basal body could be caused by mis-folding of TbCFAP410 if that is the only mutation we had tested. However, as shown in our results, the point mutation A267E of TbCFAP410 that breaks the tetramer into two dimers (so as Hs/Cr-CFAP410-A219E) did not change its folding or structural stability. Nevertheless, TbCFAP410-A267E lost its ability to localize to the basal body effectively (Figure 6A). It suggests that even a folded dimer is insufficient to correctly localize to the basal body. Therefore, we can confidently conclude that the fully assembled tetramer of CFAP410 is required for its localization to the basal body.

      * Minor points: p.7: It would be interesting, if the authors, beside MD, attempt to predict conformation of the mutants using Alphafold2. *

      : We tried to predict conformational changes of the point mutations of CFAP410 via AlphaFold2, but did not observe significant changes in the generated models. It was not so surprising to us though, because, as shown previously, although experimentally point mutations induced complete unfolding of some proteins, the AlphaFold2 models of the same point mutants folded similarly to the wild-type crystal structures (Buel & Walters, 2022, Nat. Struct. Mol. Biol. 29:1-2.)

      * p.7-8: A cartoon to describe what proteins exist between the posterior tip and the basal body will help readers to understand. Do the authors have any thought how CFAP410 is transported to the basal body? *

      : We thank the reviewer for the suggestion and have revised Figure 7 to illustrate the two distinct localization sites of CFAP410 in T. brucei.

      We do not know the mechanism through which CFAP410 localizes to the posterior cell tip and the basal body. Both structures are microtubule based, with the basal body consisting of a barrel of microtubule triplets and the posterior cell tip is the site at which the ends of the microtubules which form the sub-pellicular array in T. brucei are located. This suggests that CFAP410 could interact with microtubules or microtubule binding proteins in these locations. Additionally, in human cells CFAP410 appears to interact with NEK1 and the equivalent interaction in trypanosomes may be important for CFAP410 localization. We have refined our ideas on this in the Discussion section (p.11): “It was shown previously that the L224P mutant of CFAP410 abolishes its interaction with NEK1 [4]. Given that the mutant L224P disassembles the tetramer of CFAP410-CTD (Figure 3), the tetrameric assembly of CFAP410 seems to play an essential role in its interaction with NEK1. Therefore, the disrupted location of TbCFAP410-L272P to the basal body we observed here could be attributed to its abolished interaction with the trypanosome equivalent of NEK1 as occurs in human cells. However, we cannot exclude another possibility that CFAP410 localizes to the basal body by interacting with an unidentified anchoring target there and NEK1 is subsequently recruited via its binding to CFAP410.

      It is worth mentioning though that the localization of TbCFAP410 to the posterior cell tip has only been reported in T. brucei and no other cellular localization sites have been reported for CFAP410 orthologs in other organisms including human. Moreover, in the genome-wide protein tagging project TrypTag many other proteins were found to localize to both the posterior tip and another site in the cell, including the basal body (Billington et al, 2023, Nat. Microbiol. 8: 533-547). The following paragraph discussing about this has been added to the Discussion section (p. 10): “Notably, recent genome-wide protein localizations revealed that the posterior cell tip in T. brucei has unexpectedly high complexity and contains many proteins that also localize to other organelles _[16]_. The tip may thus serve as a “moonlighting” site for those proteins. However, the extra localization site of CFAP410 at the cell tip has only been reported in T. brucei and no other cellular localization sites have been observed for CFAP410 in any other organisms.”

      * p.10: Can the authors define "NTD linker" precisely (from which to which residues)? *

      : We have defined the sequence range of both the NTD (aa1-160) and NTD-linker (aa1-254) of TbCFAP410 both in the text (p. 9 & p. 10) and legend of Figure 6.

      * p.12: Alphafold-multimer may help to have information, which part of CFAP410 is likely interface to NEK1 and SPATA7. *

      : We attempted to predict how CFAP410 interacts with NEK1 or SPATA7 by Alphafold-multimer. Results of the former prediction, which are consistent with previous studies (Gregorczyk et al, 2023, Life Sci. Alliance), have been added as a new figure (Figure S4). However, no convincing results were obtained for the latter pair.

      * p.16: The paragraph starting with "DSF measurements were ..." is probably not necessary. Figure 4 caption: "HsCFP0-CTD" should be defined precisely. Or is it a typo of HsCFAP410-CTD? *

      : We thank the reviewer for pointing out this mistake. This paragraph has been removed.

      * Figure 5ad, Figure 6: blue is not defined.

      *

      : We have now defined blue in the figure legends for 5A, D and 6A. These cells have been counterstained with the DNA stain Hoechst 33342 to highlight the nucleus and kinetoplast (mitochondrial DNA) and this is the blue element in the images.

      * Advances: This interdisciplenary work nicely characterized CFAP410 at atomic, molecular and cellular levels and acquired insight of its functional mechanism. *

      : We appreciate the reviewer’s constructive comments and positive feedback.

      Reviewer 2

      *In this paper, the authors described 3 crystal structures of the CTD of CFAP410 from 3 different species. They explored the phenotype mutation L224P in humans which causes ciliopathies using in vitro and in vivo analysis. They were able to explain the oligomerization role of the L224P mutations and its importance for correct localization. In addition, using their structure, they also found A219 as an important residue for tetramerization as well. The paper is well-written and easier to read. *

      * __There are some minor concerns: __

      1. Fig. 5C: Why would the line reduce to lower value at 24hr, 48hr for both non-induced and induced one. *

      : During routine culture of T. brucei, we had to split the cells to ensure they do not overgrow and are maintained in log phase growth. The reduction in value at each time point represents the cell splitting event and gives these characteristic “sawtooth” graphs for cell growth. At each time point the cell density is measured and then the cells (both non-induced and induced) are diluted to the same cell density, in this case 2x106 cells/ml, and grown for a further 24 hours before the next measurement.

      *2. The authors wrote "Although we observed only little change in the average distance from the posterior cell tip to kinetoplast in 1K1N cytoskeletons after induction, there was a substantial increase in the range of these measurements, with cytoskeletons observed having a more reduced or increased distance from the kinetoplast to the posterior cell tip (Figure 5F)." *

      *Why not back the wide range with a standard deviation calculation in the figure caption of 5F or display the std dev directly in the figure if it looks good? Also, the author can include legends for color dots in the figure as Replicate 1,2,3 for easy reading/comprehension. *

      : We have included the standard deviations for each of the replicates in 5F in the figure legend. The spread of data is shown in the figure already with the individual points and the overlay of the standard deviation was not clear when we tried it. We have now included a legend for the dots in the figure as suggested.

      *3.The information about the construct of Trypanosoma used for Figure 6 is not described at all. What exactly is the region of the construct of the NTD and NTD-linker? *

      : The following sentence has been added to the legend of Figure 6: “Except for NTD (aa1-168) and NTD-linker (aa1-254), all other constructs are full-length proteins.

      *4. The author wrote "In the mutant A267E, the mNG::CFAP410 signal was exclusively found at the posterior of most cytoskeletons (63.5%), while full-length TbCFAP410-L272P and the two CTD-lacking constructs, NTD and NTD-linker ... This suggests that both the presence of the CTD and the integrity of its oligomerization are essential for the interaction of TbCFAP410 with the basal body and posterior cell tip." *

      *This statement needs to be revised a bit. First, seems like the tetramerization is important for the localization, not dimerization. Second, is there any evidence that full-length TbCFAP410-L272P folds properly? Without the evidence that the NTD and NTD-linker region can fold properly in both full-length TbCFAP410-L272P and CTD truncation, it is not possible to exclude that the N-terminal is essential for the localization as well. *

      : Thanks for the comments. We have managed to express and purify TbCFAP410-NTD, which shows that it folds properly on its own. We further checked whether NTD directly interacts with CTD, but ended up with negative results. The following part has been added to the last paragraph of the Results section to address the reviewer’s question. “We found that TbCFAP410-NTD folded properly on its own when expressed in bacteria, and no direct interaction between NTD and CTD was detected (data now shown). It suggests that the two structural modules of TbCFAP410 that are connected by a long disordered linker are folded independently. Therefore, we conclude that the localization of TbCFAP410 to the basal body and the posterior cell tip requires the CTD and its ability to oligomerize.”

      * Small things: 1. It is worth define 1K1N, 2K1N and 2kK2N stages in the text for reader not in Trypanosoma field.

      *: We have explained the KN nomenclature, and how during the cell cycle the kinetoplast and nucleus are duplicated and segregated in a defined order.

      *2.Fig. 5C: label Non-induced black & induced orange as legends directly in the figure so readers don't have to read the Figure captions.

      *: This has been done as suggested.

      *3. In Methods, there is the part about DSF measurement in the Molecular Dynamic (MD) simulations *

      : This paragraph is unnecessary and has been removed. We thank the reviewer for pointing it out.

      4.* Abbreviation not defined: DSF (in Methods/MD simulations). Also, the molecular dynamics phrase appears well before the abbreviation MD in the Methods section. *

      : As stated above, this paragraph has been removed.

      *

      Reviewer #2 (Significance (Required)):

      Overall I found the methodology and results of the paper solid, and the interpretation and conclusion are sound. *

      *The paper addresses the molecular mechanism of a mutation in CFAP410 resulting in severe spondylometaphyseal dysplasia, axial. *

      * The audience of the paper should be the cilia field but also the paper is also good for other researchers as the paper is easy to read.*

      : We appreciate the reviewer’s constructive feedback and positive evaluation.

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      Referee #2

      Evidence, reproducibility and clarity

      In this paper, the authors described 3 crystal structures of the CTD of CFAP410 from 3 different species. They explored the phenotype mutation L224P in humans which causes ciliopathies using in vitro and in vivo analysis. They were able to explain the oligomerization role of the L224P mutations and its importance for correct localization. In addition, using their structure, they also found A219 as an important residue for tetramerization as well. The paper is well-written and easier to read.

      There are some minor concerns:

      1. Fig. 5C: Why would the line reduce to lower value at 24hr, 48hr for both non-induced and induced one.
      2. The authors wrote "Although we observed only little change in the average distance from the posterior cell tip to kinetoplast in 1K1N cytoskeletons after induction, there was a substantial increase in the range of these measurements, with cytoskeletons observed having a more reduced or increased distance from the kinetoplast to the posterior cell tip (Figure 5F)."

      Why not back the wide range with a standard deviation calculation in the figure caption of 5F or display the std dev directly in the figure if it looks good? Also, the author can include legends for color dots in the figure as Replicate 1,2,3 for easy reading/comprehension. 3. The information about the construct of Trypanosoma used for Figure 6 is not described at all. What exactly is the region of the construct of the NTD and NTD-linker? 4. The author wrote "In the mutant A267E, the mNG::CFAP410 signal was exclusively found at the posterior of most cytoskeletons (63.5%), while full-length TbCFAP410-L272P and the two CTD-lacking constructs, NTD and NTD-linker ... This suggests that both the presence of the CTD and the integrity of its oligomerization are essential for the interaction of TbCFAP410 with the basal body and posterior cell tip."

      This statement needs to be revised a bit. First, seems like the tetramerization is important for the localization, not dimerization. Second, is there any evidence that full-length TbCFAP410-L272P folds properly? Without the evidence that the NTD and NTD-linker region can fold properly in both full-length TbCFAP410-L272P and CTD truncation, it is not possible to exclude that the N-terminal is essential for the localization as well.

      Small things:

      1. It is worth define 1K1N, 2K1N and 2kK2N stages in the text for reader not in Trypanosoma field.
      2. Fig. 5C: label Non-induced black & induced orange as legends directly in the figure so readers don't have to read the Figure captions.
      3. In Methods, there is the part about DSF measurement in the Molecular Dynamic (MD) simulations
      4. Abbreviation not defined: DSF (in Methods/MD simulations). Also, the molecular dynamics phrase appears well before the abbreviation MD in the Methods section.

      Significance

      Overall I found the methodology and results of the paper solid, and the interpretation and conclusion are sound.

      The paper addresses the molecular mechanism of a mutation in CFAP410 resulting in severe spondylometaphyseal dysplasia, axial.

      The audience of the paper should be the cilia field but also the paper is also good for other researchers as the paper is easy to read.

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      Referee #1

      Evidence, reproducibility and clarity

      Summary: Stadler and colleagues characterized CFAP410, using molecular structural biology, biophysics, biochemistry, cellular imaging and genetic engineering, to address molecular mechanism of ciliopathies caused by defect of this protein. They crystalized the C-terminal domain of CFAP410 and its homologue, from Trypanosoma, human and Chlamydomonas. All of them take tetrameric complex formation with four bundle helices in the center. Then they mutated highly conserved residues, L219 and L224, which are located at the helix bundle, and characterized its biophysical properties, demonstrating oligomerization defect and, in case of L224 mutation, collapse of secondary structure as well. This was supported by molecular dynamics. Next they examined the effect of these mutation in vivo using Trypanosoma brucei. They visualized the localization of CFAP410 at the postrior cell tip and its transfer to the basal body. By mutation, transfer of CFAP410 is prohibited and cytokinesis defect occurs.

      The experiments are logically designed and the results are clearly and convincingly stated. Undoubtedly this work deserves publication after minor revision of the manuscript.

      Significance

      strength: This is a compact paper, clearly stating the biological aim and experiments designed for that.

      Limitation: While it is undoubtedly proved that the C-terminal domain of CFAP410 forms tetramer and L219 and L224 are key residues and that mutation of these residues causes severe defect at the localization of CFAP410, it is an overstatement to conclude the tetramer formation is essential for the localization. The authors experiments cannot exclude the possibility of another consequence of mutation (different from origomerization), which is the cause of abnormal localization.

      Minor points:

      p.7: It would be interesting, if the authors, beside MD, attempt to predict conformation of the mutants using Alphafold2.

      p.7-8: A cartoon to describe what proteins exist between the posterior tip and the basal body will help readers to understand. Do the authors have any thought how CFAP410 is transported to the basal body?

      p.10: Can the authors define "NTD linker" precisely (from which to which residues)?

      p.12: Alphafold-multimer may help to have information, which part of CFAP410 is likely interface to NEK1 and SPATA7.

      p.16: The paragraph starting with "DSF measurements were ..." is probably not necessary.

      Figure 4 caption: "HsCFP0-CTD" should be defined precisely. Or is it a typo of HsCFAP410-CTD?

      Figure 5ad, Figure 6: blue is not defined.

      advances: This interdisciplenary work nicely characterized CFAP410 at atomic, molecular and cellular levels and acquired insight of its functional mechanism.

      audience: cilia community

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      Reply to the reviewers

      1. General Statements

      Regarding significance, we would like to highlight that the main finding and breakthrough of our manuscript is the discovery that intronic polyadenylation (IPA) isoforms are a source of microproteins (indeed, IPA was not known to induce sORF-encoded microproteins). We make the proof of principle of this concept (called miP-5’UTR-IPA) and of its functional relevance for one gene (PRKAR1B).

      A second finding of this study is that IPA (including miP-5’UTR-IPA) isoforms are widely upregulated in cell response to cisplatin, and therefore we show the functional relevance of miP-5’UTR-IPA isoforms in this biological context.

      Regarding the generality of the miP-5’UTR-IPA concept, we provide evidence that many genes generate miP-5’UTR-IPA isoforms, by crossing our 3’-seq data with available Ribo-Seq and mass spectrometry datasets, which were generated without cisplatin treatment. Also, the miP-5’UTR-IPA isoforms of PHF20 and PRKAR1B are detected both in the presence and absence of cisplatin. Thus, the novel concept of microprotein-coding IPA isoforms opens wide perspectives, way beyond cisplatin response.

      2. Description of the planned revisions

      REVIEWER #1

      Evidence, reproducibility and clarity

      Microporteins originating from coding and non-coding transcript are increasingly understood to control various cellular processes. In the present study, the authors investigated whether intronic polyadenylation (IPA) contributes to the formation of transcript isoforms encoding microproteins. Using genotoxic stress by cisplatin as a model in cell cultures, the authors detect abundant IPA. IPA in a subset of such transcripts leads to short 5'UTR transcript isoforms that are poorly associated with heavy polysomes and encode microproteins. For PRKAR1B, they demonstrate the expression of a corresponding microprotein and a function in modulating the cisplatin response. Based on depletion experiments of FANCD2 and STX1, the authors propose that impaired transcription processivity after cisplatin is one mechanism leading to IPA and microprotein production.

      While this is an interesting manuscript, I felt the support for the claimed generalization falls a bit short.

      Our response: The generality of the miP-5’UTR-IPA concept is supported by the large-scale analysis that we presented (Fig. 6): indeed, by crossing our 3’-seq data with Ribo-Seq and MS data (both of which originate from multiple cell types and tissues), we identified 156 genes with cisplatin-regulated miP-5’UTR-IPA isoforms. To strengthen this part and highlight the generality of the miP-5’UTR-IPA concept, we will provide the cell type/ tissue distribution of our set of 156 miP-5’UTR-IPA isoforms, by exploiting available 3’-seq datasets from various cells/tissues. (Please also see major point 1 below.)

      Major:

        • If I see it correctly, the authors mainly refer to existing riboSeq data and evidence from mass spectrometry/proteomics to infer the generality of the mechanism (beyond PRKAR1B). It is important to back this up with further experiments and validate this for the set-up used in this manuscript. This concerns the existence of the microproteins but also the downstream functional impact. Our response: In our study, we make the proof of principle of miP-5’UTR-IPA (that is, a microprotein-encoding IPA isoform) for the PRKAR1B gene and its sORF#2 (microprotein detection by WB and IF, functional evidence by siRNA and CRISPR of IPA site and sORF initiation codon). If I understand well (also based on minor point 3 below), this reviewer is requesting further evidence of microprotein existence (in addition to Ribo-Seq and mass spectrometry [MS] data) and function, for a second IPA-derived sORF that we study in this manuscript (either PHF20 sORF or PRKAR1B sORF#1). To the best of our knowledge, a proof of principle for a new concept is usually done on a single gene. Nevertheless, for the miP-5’UTR-IPA isoform of PHF20*, we already provided evidence for its function by using siRNAs (Fig. 3A-C) and for its translation by polysome profiling (Fig. 4C) in addition to Ribo-Seq and MS evidence (Fig. 4A). The fact that for PHF20 we did not detect the transfected Flag-tagged microprotein in HEK cells could be due to several reasons (as discussed on page 16); __we will __try this approach again with different biological conditions (cell lines, stress) or construct designs (as the sORF context may be important).
      1. Also, I wonder is this limited to cisplatin-induced genotoxic stress and the specific cell line used or is this a more global mechanism?*

      Our response: We provided evidence of IPA isoform regulation by cisplatin in two lung cancer cell lines (A549 and H358; Fig. 1A-B) but we agree that our analyses of miP-5’UTR-IPA were mainly done in A549 cells. We will: (i) clarify that we detected the miP-5’UTR-IPA isoforms of PRKAR1B and PHF20 in A549 cells (total cytosol and light polysomes) both in the presence and absence of cisplatin (Fig. 2D, 3A and S3D); (ii) add RT-qPCR validation of their cisplatin regulation in H358 cells; (iii) try to detect the PRKAR1B-encoded microprotein in a second cell line (Fig. 4); (iv) test the impact of PRKAR1B and PHF20 miP-5’UTR-IPA isoforms on cell survival in a second cell line and with a second genotoxic agent; (v) clarify in Fig. 6 that miP-5’UTR-IPA isoforms are regulated by cisplatin in both A549 and H358 cells (our 3’-seq data) and that the Ribo-Seq and MS datasets supporting their translation originate from multiple cell types and tissues without cisplatin treatment; and (vi) provide the cell type/ tissue distribution of our set of 156 miP-5’UTR-IPA isoforms (by exploiting available 3’-seq datasets from various cells/tissues).

      Minor:

        • While the rest of the paper reads well, the abstract could be improved/simplified to increase accessibility* Our response: We will improve the abstract.

      Page 11: Pertaining to Figure 3 and the functional impact: The authors analyze the IPA effect by probing cell viability and cell survival. It would be important to define the effects in further detail, as the mere regulation of cell cycle and/or apoptosis could also result in such outcome (which is then not necessarily a direct cisplatin response). Does this also impact the response to other genotoxic stress (also pertains to the effects studied and shown in Fig. 5)?

      Our response: Because cisplatin effects on cell growth are usually mediated by effects on cell cycle and cell death, we will determine which aspect is impacted by PRKAR1B and PHF20 miP-5’UTR-IPA isoforms, by carrying out FACS analysis of PI/BrdU and Annexin V (both in the presence and absence of cisplatin). As mentioned in major point 2, we will also test the impact of these isoforms on cell survival to a second genotoxic agent.

      Page 12 concerning the microprotein expression: the authors refer to data from other resources to claim that the microproteins are expressed, however they fail to demonstrate this for their setup (at least for 2 out of three they study here). I think this is a weak point as it does not directly support the general claim.

      Our response: Please see major point 1 above.

      Also, I did not understand what the authors intended to demonstrate with the immunoflourescence (Fig. 4E). What should a defined nuclear expression imply versus the diffuse staining throughout after cisplatin? How does this relate to the functional effects?

      Our response: We included in Fig. 4E the observation that the subcellular localization of the PRKAR1B-encoded micropotein is altered in response to cisplatin, because this supports the notion that this micropotein plays a role in cell response to cisplatin. We can remove this data if requested.

      Page 13/Fig. 5E: the different clones of the mATG show very high variability. To my understanding it is difficult to draw a clear conclusion from this heterogeneity.

      Our response: The statistical analysis shows a significant difference between the mATG and Control groups (p Page 15 on the mechanism: SETX has been demonstrated to control poly(A) site choice (PMID: 21700224, 32976578). However the quantitative role of SETX in poly(A) site choice regulation (compared to other regulators) seems to be rather marginal and not strictly unidirectional, i.e after SETX depletion also longer transcript isoforms can be detected (PMID: 32976578). How does this relate to the proposed mechanism of SETX-dependent processivity? Interestingly, from PMID: 32976578 it also appears that PRKAR1A has a 5'UTR poly(A) site that is regulated in a SETX-dependent manner.

      Our response: We will add in the discussion statements that (i) the role of SETX in cisplatin regulation of IPA:LE isoform ratio and processivity might be different from its role in APA regulation in the absence of genotoxic treatment (citing PMID 32976578; keeping in mind that we did not compare them side by side on a genome-wide scale) and (ii) PRKAR1A seems to have a 5'UTR poly(A) site regulated by SETX in TREND-DB (PMID 32976578).

      • Page 16, discussion first paragraph. While refs 1-4 are nice reviews that could be quoted here a study that appeared later represents the most comprehensive analysis to date covering the different facets from transcription to RNA processing and the resulting impact on poly(A) site choice (PMID: 30552333).*

      Our response: We will cite PMID 30552333 and 32976578 as resources of APA regulation by various regulators of gene expression (keeping in mind, however, that for most factors these studies do not exclude indirect effects).

      Significance

      This could be a very significant report, provided the generality of the claims and mechanistic insigths are further strengthend.

      Overall it targets a rather specialized readership. This could be improved by simplifing the abstract, additional experimental evidence for the generality of the proposed mechanism, and a stringent rewording of the main text drawing a clear line, omitting unnecessary details and focussing on the novel findings.

      Our response: Please see our responses above. In addition, we will reword the main text where necessary.

      REVIEWER #2

      Evidence, reproducibility and clarity

      Summary:

      *In this manuscript, Devaux et al. report that the anti-cancer drug cisplatin upregulates intronic polyadenylation (IPA) isoforms in non-small cell lung cancer cell lines. Their finding was based on 3' end sequencing and long-read sequencing. Through polysome profiling they confirmed that many of the IPA isoforms are translated, despite being inefficient in most cases. *

      Our response: There is some misunderstanding here. We will clarify in the text that inefficient association with heavy polysomes is observed for a minority (not the majority) of IPA isoforms. For this, in Fig. 2B and S2A, we will add the information that for the majority of IPA sites, the IPA:LE ratio is not significantly different (neither up or down) between total cytosol and heavy polysomes.

      They validated functions of IPA isoforms from two genes, PHF20 and PRKAR1B, in cell survival upon cisplatin treatment, based on an array of methods, including siRNA knockdown, CRISPR knockout of IPA polyA site, and CRISPR mutation of the start codon. They further found that FANCD2 and Senataxin can regulate cisplatin-mediated IPA activation. The authors advocate a new paradigm of expression of IPA-encoding microproteins in cisplatin-treated cells.

      Our response: We would like to point out that our data indicate that cisplatin upregulation of the IPA:LE isoform ratio is mediated at least in part by an inhibition of transcription processivity (explaining the decrease of LE isoforms), and that we do not claim an ‘IPA activation’ (that is, enhanced used of IPA sites) by cisplatin. This remark is also related to major point 1 below.

      Major comments:

        • While the phenomenon of IPA isoform upregulation by Cisplatin is quite convincing, the underlying mechanism is largely elusive. The authors indicated processivity as a potential mechanism and the effects of FACD2 and Senataxin appear in line with this hypothesis. However, they cannot rule out other possibilities based on the data presented in the manuscript. For example, it is not clear if the elongation rate of Pol II (distinct from its processivity) or nuclear RNA degradation is affected by cisplatin, which could also lead to increased expression of IPA isoforms. In addition, enhanced 3' end processing activity has been previously shown to activate IPA sites. Therefore, the underlying mechanism is mostly speculative. Our response: As explained on page 14, the reason why we focused on transcription processivity is that the cisplatin-induced upregulation of the IPA:LE isoform ratio was enriched in long genes and was accompanied by a decrease of LE isoform levels. Importantly, our data (e.g., for the PHF20 and PRKAR1B genes) indicate that the cisplatin-induced decrease of processivity explains –at least in part– the selective decrease of the LE but not IPA isoform levels and therefore the increase of the IPA:LE isoform ratio; we will clarify this in the manuscript (on pages 14 and 15). Our data also show that cisplatin effects on both processivity and IPA:LE isoform ratio are dependent on FANCD2 and SETX. We agree with the reviewer that we cannot exclude that IPA:LE isoform ratio upregulation by cisplatin might also be mediated in part by additional mechanisms (e.g.*, ‘factors involved in cleavage/ polyadenylation, splicing, transcription elongation and termination, and epigenetic marks’, as mentioned in the discussion on page 16) and we will add nuclear RNA degradation to the list of potential factors. However, we want to emphasize that the role of processivity is not speculative.

      The authors used the polysome:cytosolic ratio to indicate translational efficiency. However, because the CDS size affects the number of ribosomes per mRNA, the translational efficiency should be based on polysome:cytosolic ratio normalized to CDS size. Ideally, the authors should calculate number of ribosome per transcript based on monosome, light polysome and heavy polysome.

      Our response: We cannot normalize ribosome number by CDS size because (i) heavy polysomes are not a precise number of ribosomes and (ii) sORFs are not annotated as CDS.

      The functions of PHF20 and PRKAR1B IPA isoforms are based on knockdown or knockout mutations. Because of its gain-of-function property, overexpression of the isoforms in cisplatin-treated cells would be necessary to definitively confirm their funcitons.

      Our response: For PRKAR1B sORF#2, we ____will carry out overexpression of the sORF microprotein in A549 cells and CRISPR clones and analyze its effects on cell growth and cisplatin survival. We have appropriate constructs for this.

      Minor:

        • Fig. 1H, the numbers of IPA and LE transcripts should be provided. The statistical significance for the difference should also be included.* Our response: The numbers of IPA and LE transcripts were provided in Fig. S1I and we will provide the statistical significance (which is good), as requested.

      Fig. 1I, the image should be accompanied with fold difference as indicated in the text. Some statistics for difference between vehicle only and CisPt only is necessary.

      Our response: We will indicate the fold differences and provide the statistical significance, as requested.

      • Fig. 6, the authors did data mining of ribo-seq data and mass-spec data and identified 156 genes whose IPA isoforms have potentials of protein expression. The enriched GO terms for the 156 IPA genes are different than the overall IPA isoforms shown in Fig. 1C. Does this mean some genes, like those in DNA damage stimulus, produce IPA isoforms with different consequences, such as to inhibit their expression? *

      Our response: We think it is difficult to compare the enriched GO terms between overall IPA and miP-5’UTR-IPA. Indeed, differences could be due in part to trivial reasons (e.g., different number of genes in the lists). As suggested by this reviewer, it could be that for some gene sets enriched in particular functions, IPA may serve to downregulate the expression level of the full-length (canonical) mRNA. We discuss that this may be the case for the PRIM2 gene involved in DNA replication (page 17), but expanding on this would be speculative. Likewise, IPA isoforms encoding carboxy-terminal isoforms of canonical proteins, or IPA isoforms with a noncoding function (like ASCC3 or SPUD), might be enriched in particular gene functions, but again this idea is speculative and it goes beyond the scope of our manuscript.

      In addition, the authors need to use ribo-seq and mass spec data as a validation tool for their polysome profiling data to indicate the reliability of using polysome data to call protein expression.

      Our response: This comment seems to concern those IPA isoforms that are abundant in heavy polysomes. We do not wish to validate protein production from such isoforms, because they are not the focus of our study.

      Significance

      The significance of this work is its novelty in reporting IPA isoform activation by cisplatin. More importantly, some IPA isoform give rise to microproteins that have functional roles in cell survival upon cisplatin treatment.

      Our response: We would like to highlight that the main finding of our manuscript is the discovery that IPA isoforms are a source of microproteins. Cisplatin response is the biological context in which we did the study, and therefore our functional and mechanistic analyses.

      REVIEWER #3

      Evidence, reproducibility and clarity

      Devaux et al. report how cisplatin treatment changes the abundance of mRNA isoforms, favoring the expression of short transcripts originating from intronic polyadenylation (IPA) events relative to the expression of the corresponding mRNA isoform that includes the last annotated exon (LE). To detect IPA events the authors performed 3' end sequencing of polyadenylated mRNAs, long-read sequencing and conventional total RNA sequencing experiments in control and cisplatin treated cells. Analysis of the 3' end sequencing data revealed numerous genes showing an increase in the IPA:LE ratio upon cisplatin treatment, whereas few events with a decreased IPA:LE ratio were detected. Many of the identified events could be corroborated by the long-read sequencing data, sequencing of total RNA, and an existing polyA database. Furthermore, the authors validate IPA:LE ratios for a few selected genes using quantitative PCR. Subsequently, the authors continue to analyze if IPA isoforms are translated with a specific focus on IPA isoforms that do not contain any parts of the LE isoform coding sequence but terminated transcription in what is annotated as 5' untranslated region (UTR). These experiments show that IPA isoforms (including 5' UTR-IPAs) are translated but frequently associated with fewer ribosomes than the corresponding LE isoform. For two selected 5' UTR-IPA isoforms the authors identified potential small open reading frames (sORFs) that could give rise to microproteins with a potential function during cisplatin treatment. siRNA experiments targeting either the 5' UTR-IPA or the LE mRNA isoform of selected genes identified a small but significant differential effect on cell viability upon cisplatin treatment. Similar results were obtained when the endogenous IPA locus was deleted or the start codon of the potential sORF was mutated. Finally, the authors shed some light onto the molecular mechanisms of how cisplatin affects the IPA:LE ratio by decreasing transcription processivity.

      *This is an interesting manuscript suggesting a link between IPA, sORFs and cancer treatment. The manuscript offers valuable datasets as a resource for the research community. While the authors generally present a well-analyzed and validated dataset supporting their claims, some aspects require further evidence or clearer presentation for robustness and reader comprehension. In addition, the manuscript would benefit from improving data visualization and we have several suggestions (see below) on how to make the representation of the data in the figures more appealing to the reader. We encourage the authors to reconsider several of their bar plots and instead plot their data on a continuous axis, e.g. using a scatter plot (fold change versus FDR) instead of a bar chart that can only represent up/down total numbers. *

      Our response: Please see our responses below.

      Main points:

        • We disagree with one of the data interpretations concerning the high polysome (HP) versus total cytosolic polysomes (cytosol) localized IPA and LE mRNA isoforms in the paragraph "A subset of IPA isoforms are depleted in heavy polysomes and terminate in the annotated 5'UTR part of genes". Preferential IPA isoform localization to cytosol versus HP in comparison to the LE isoform does not mean that the IPA isoform translation efficiency is lower than that of the LE isoform. It just reflects the fact that IPA isoform coding sequence is considerably shorter than the coding sequence of the LE isoform (and thus can accommodate fewer ribosomes!). The authors mention that point later in the text but it should already be made clear at this point in the manuscript. They should make sure not to confuse translation efficiency (ribosome density across an open reading frame) and open reading frame length. * Our response: We will modify the text of this section (pages 10-11). We will __state that ‘the HP:cytosol ratio is usually considered as a proxy for translation efficiency’ and __we will only make conclusions in terms of ‘HP:cytosol ratio’ or ‘HP recruitment efficiency’, instead of ‘translation efficiency’ (we had used this term in a few sentences for the sake of simplicity). Please note that these changes will not alter the main conclusion of this part, because both the title (‘a subset of IPA isoforms are depleted in heavy polysomes and terminate in the annotated 5'UTR part of genes’) and the end of this section (page 11), as well as the legend of Fig. 2, were already written in such terms. Thus, in this section, we do not need to discuss ORF length (and we cannot, because sORFs are not annotated as CDS and we introduce sORFs only two sections later [Fig. 4]).
      1. In Figure 5, the authors claim that the "cisplatin survival phenotype of the PRKAR1B 5'UTR-IPA isoform is attributable to its small ORF#2". This is an interesting phenotype but the authors only present a WST1 assay to support these claims. Given that it is an important Figure in their manuscript and links the observations made earlier to cisplatin-induced survival, it would be critical to bolster these claims with additional data, e.g. AnnexinV/PI staining and flow cytometry to distinguish changes in cisplatin-induced apoptosis from proliferation.*

      Our response: We will make the requested experiments with FACS analysis of Annexin V and PI/BrdU to distinguish changes in cisplatin-induced apoptosis from proliferation (cell cycle).

      • Along the same line, it would be important to test the overexpression of the sORF microprotein upon cisplatin treatment. Changes in the mRNA sequence (such as the AUG mutation) could potentially also alter the mRNA structure. It would therefore be critical to show that the sORF microprotein is indeed responsible for the changes in cisplatin-induced viability (for instance by expression of a sORF::P2A::GFP construct). *

      Our response: As requested, we will test whether overexpression of the sORF microprotein can rescue the cisplatin survival phenotype of our PRKAR1B IPA and ATG mutants. We have appropriate constructs for this.

      • Figure 5C: Please show the Western blot of PRKAR1B and GAPDH and not just the quantification. There is plenty of space in Figure 5. *

      Our response: We will show the Western blots for PRKAR1B and GAPDH.

      • In the following, we list suggestions to improve different figures where the data could be more adequately presented:*

      - Figure 1A and B: We suggest representing the data in a scatter plot log fold change on the x-axis and FDR on the y-axis. The authors decided for an FDR cutoff of 10%. This is quite high. Why did the authors decide for this cutoff? How many genes would be identified with a more stringent cutoff (1% for example)? Please list the corresponding FDR values in TableS4.

      Our response: We have never seen in the literature 3’-seq (or related) data of IPA:LE ratio regulation plotted as a scatter plot with log fold change on the x-axis and FDR on the y-axis. Instead, we propose to provide scatter plots with IPA fold change on the x-axis and LE fold change on the y-axis, as in many previous studies. We were not very stringent on the FDR or adjusted p values, in order to reduce the rate of false negatives, because we then cross our lists of regulated IPAs in different compartments (e.g., cytosol and heavy polysomes; Fig. 2C). We provided adjusted p values in Table S4; with an adjusted p value of 1%, we observe 1986 upregulated IPA sites and 33 downregulated ones.

      *-Figure 1C: There are many ways to visualize fold change, p value and number of genes of a GO term analysis. The authors could choose one of the common ways to represent such data instead of just showing raw numbers in a table. *

      Our response: We like showing GO terms as tables, but we can provide a figure if necessary.

      -Figure 1E-G: Add to the figure that PRIM2 was assayed. It is only written in the figure legend.

      Our response: We will write ‘PRIM2’ in the figure.

      *-Figure 2A and B: Same suggestion as for Figure 1A and B, a scatter plot log fold change on the x-axis and FDR on the y-axis would visualize the data much better. *

      Our response: Same response as for Fig 1A-B above.

      -Figure S1B: Where does the number of 2118 cisplatin regulated genes come from? It was not described anywhere else. Should it not be 1987 regulated genes?

      Our response: We will clarify that 2118 is the union of genes with cisplatin upregulated IPA:LE ratio in H358 and/or A549 cells.

      -Figure S1H: Typo in the y-axis.

      Our response: This typo will be corrected, thanks.

      -Figure S2A: Same suggestion as for Figure 1A and B, a scatter plot log fold change on the x-axis and FDR on the y-axis.

      Our response: Same response as for Fig 1A-B above.

      -Figure S3C: If possible, show the plotted digital data of the polysome curves.

      Our response: We do not have digital data for the polysome curves, just the printed graph shown at the bottom of the figure.

      • Data availability: The provided UCSC genome browser link unfortunately does not load the data bam files. Please fix.*

      Our response: We will fix this upon submission to journal.

      Minor points:

      • Please check the text for typos, e.g. page 8: artefacts instead of artifacts. *

      Our response: We will check for typos.

      Significance

      The manuscript describes an interesting link between intronic polyadenylation, sORFs and cancer treatment and will be of interest to the gene expression regulation and RNA communities. As a relatively unknown mechanism to induce sORF-encoded microproteins, the study could lead to follow-up studies tackling intronic polyadenylation and their role in sORF expression.

      Our response: We would like to highlight that IPA was not previously known to induce sORF-encoded microproteins.

      While the authors generally present a well-analyzed and validated dataset, the link between sORF function and cisplatin response will require additional experiments to strengthen the sORF's impact for cellular survival.

      Our response: Please see our responses to main points 2 and 3 above.

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

      None.

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

      REVIEWER #2

      Major point #2: The authors used the polysome:cytosolic ratio to indicate translational efficiency. However, because the CDS size affects the number of ribosomes per mRNA, the translational efficiency should be based on polysome:cytosolic ratio normalized to CDS size. Ideally, the authors should calculate number of ribosome per transcript based on monosome, light polysome and heavy polysome.

      Our response: We cannot normalize ribosome number by CDS size because (i) heavy polysomes are not a precise number of ribosomes and (ii) sORFs are not annotated as CDS.

      *Minor point #3: Fig. 6, the authors did data mining of ribo-seq data and mass-spec data and identified 156 genes whose IPA isoforms have potentials of protein expression. The enriched GO terms for the 156 IPA genes are different than the overall IPA isoforms shown in Fig. 1C. Does this mean some genes, like those in DNA damage stimulus, produce IPA isoforms with different consequences, such as to inhibit their expression? *

      Our response: We think it is difficult to compare the enriched GO terms between overall IPA and miP-5’UTR-IPA. Indeed, differences could be due in part to trivial reasons (e.g., different number of genes in the lists). As suggested by this reviewer, it could be that for some gene sets enriched in particular functions, IPA may serve to downregulate the expression level of the full-length (canonical) mRNA. We discuss that this may be the case for the PRIM2 gene involved in DNA replication (page 17), but expanding on this would be speculative. Likewise, IPA isoforms encoding carboxy-terminal isoforms of canonical proteins, or IPA isoforms with a noncoding function (like ASCC3 or SPUD), might be enriched in particular gene functions, but again this idea is speculative and it goes beyond the scope of our manuscript.

      In addition, the authors need to use ribo-seq and mass spec data as a validation tool for their polysome profiling data to indicate the reliability of using polysome data to call protein expression.

      Our response: This comment seems to concern those IPA isoforms that are abundant in heavy polysomes. We do not wish to validate protein production from such isoforms, because they are not the focus of our study.

      REVIEWER #3

      -Figure S3C: If possible, show the plotted digital data of the polysome curves.

      Our response: We do not have digital data for the polysome curves, just the printed graph shown at the bottom of the figure.

    2. 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

      Devaux et al. report how cisplatin treatment changes the abundance of mRNA isoforms, favoring the expression of short transcripts originating from intronic polyadenylation (IPA) events relative to the expression of the corresponding mRNA isoform that includes the last annotated exon (LE). To detect IPA events the authors performed 3' end sequencing of polyadenylated mRNAs, long-read sequencing and conventional total RNA sequencing experiments in control and cisplatin treated cells. Analysis of the 3' end sequencing data revealed numerous genes showing an increase in the IPA:LE ratio upon cisplatin treatment, whereas few events with a decreased IPA:LE ratio were detected. Many of the identified events could be corroborated by the long-read sequencing data, sequencing of total RNA, and an existing polyA database. Furthermore, the authors validate IPA:LE ratios for a few selected genes using quantitative PCR. Subsequently, the authors continue to analyze if IPA isoforms are translated with a specific focus on IPA isoforms that do not contain any parts of the LE isoform coding sequence but terminated transcription in what is annotated as 5' untranslated region (UTR). These experiments show that IPA isoforms (including 5' UTR-IPAs) are translated but frequently associated with fewer ribosomes than the corresponding LE isoform. For two selected 5' UTR-IPA isoforms the authors identified potential small open reading frames (sORFs) that could give rise to microproteins with a potential function during cisplatin treatment. siRNA experiments targeting either the 5' UTR-IPA or the LE mRNA isoform of selected genes identified a small but significant differential effect on cell viability upon cisplatin treatment. Similar results were obtained when the endogenous IPA locus was deleted or the start codon of the potential sORF was mutated. Finally, the authors shed some light onto the molecular mechanisms of how cisplatin affects the IPA:LE ratio by decreasing transcription processivity.

      This is an interesting manuscript suggesting a link between IPA, sORFs and cancer treatment. The manuscript offers valuable datasets as a resource for the research community. While the authors generally present a well-analyzed and validated dataset supporting their claims, some aspects require further evidence or clearer presentation for robustness and reader comprehension. In addition, the manuscript would benefit from improving data visualization and we have several suggestions (see below) on how to make the representation of the data in the figures more appealing to the reader. We encourage the authors to reconsider several of their bar plots and instead plot their data on a continuous axis, e.g. using a scatter plot (fold change versus FDR) instead of a bar chart that can only represent up/down total numbers.

      Main points:

      1. We disagree with one of the data interpretations concerning the high polysome (HP) versus total cytosolic polysomes (cytosol) localized IPA and LE mRNA isoforms in the paragraph "A subset of IPA isoforms are depleted in heavy polysomes and terminate in the annotated 5'UTR part of genes". Preferential IPA isoform localization to cytosol versus HP in comparison to the LE isoform does not mean that the IPA isoform translation efficiency is lower than that of the LE isoform. It just reflects the fact that IPA isoform coding sequence is considerably shorter than the coding sequence of the LE isoform (and thus can accommodate fewer ribosomes!). The authors mention that point later in the text but it should already be made clear at this point in the manuscript. They should make sure not to confuse translation efficiency (ribosome density across an open reading frame) and open reading frame length.
      2. In Figure 5, the authors claim that the "cisplatin survival phenotype of the PRKAR1B 5'UTR-IPA isoform is attributable to its small ORF#2". This is an interesting phenotype but the authors only present a WST1 assay to support these claims. Given that it is an important Figure in their manuscript and links the observations made earlier to cisplatin-induced survival, it would be critical to bolster these claims with additional data, e.g. AnnexinV/PI staining and flow cytometry to distinguish changes in cisplatin-induced apoptosis from proliferation.
      3. Along the same line, it would be important to test the overexpression of the sORF microprotein upon cisplatin treatment. Changes in the mRNA sequence (such as the AUG mutation) could potentially also alter the mRNA structure. It would therefore be critical to show that the sORF microprotein is indeed responsible for the changes in cisplatin-induced viability (for instance by expression of a sORF::P2A::GFP construct).
      4. Figure 5C: Please show the Western blot of PRKAR1B and GAPDH and not just the quantification. There is plenty of space in Figure 5.
      5. In the following, we list suggestions to improve different figures where the data could be more adequately presented:

        • Figure 1A and B: We suggest representing the data in a scatter plot log fold change on the x-axis and FDR on the y-axis. The authors decided for an FDR cutoff of 10%. This is quite high. Why did the authors decide for this cutoff? How many genes would be identified with a more stringent cutoff (1% for example)? Please list the corresponding FDR values in TableS4.
        • Figure 1C: There are many ways to visualize fold change, p value and number of genes of a GO term analysis. The authors could choose one of the common ways to represent such data instead of just showing raw numbers in a table.
        • Figure 1E-G: Add to the figure that PRIM2 was assayed. It is only written in the figure legend.
        • Figure 2A and B: Same suggestion as for Figure 1A and B, a scatter plot log fold change on the x-axis and FDR on the y-axis would visualize the data much better.
        • Figure S1B: Where does the number of 2118 cisplatin regulated genes come from? It was not described anywhere else. Should it not be 1987 regulated genes?
        • Figure S1H: Typo in the y-axis.
        • Figure S2A: Same suggestion as for Figure 1A and B, a scatter plot log fold change on the x-axis and FDR on the y-axis.
        • Figure S3C: If possible, show the plotted digital data of the polysome curves.
        • Data availability: The provided UCSC genome browser link unfortunately does not load the data bam files. Please fix.

      Minor points:

      1. Please check the text for typos, e.g. page 8: artefacts instead of artifacts.

      Significance

      The manuscript describes an interesting link between intronic polyadenylation, sORFs and cancer treatment and will be of interest to the gene expression regulation and RNA communities. As a relatively unknown mechanism to induce sORF-encoded microproteins, the study could lead to follow-up studies tackling intronic polyadenylation and their role in sORF expression.

      While the authors generally present a well-analyzed and validated dataset, the link between sORF function and cisplatin response will require additional experiments to strengthen the sORF's impact for cellular survival.

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      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      In this manuscript, Devaux et al. report that the anti-cancer drug cisplatin upregulates intronic polyadenylation (IPA) isoforms in non-small cell lung cancer cell lines. Their finding was based on 3' end sequencing and long-read sequencing. Through polysome profiling they confirmed that many of the IPA isoforms are translated, despite being inefficient in most cases. They validated functions of IPA isoforms from two genes, PHF20 and PRKAR1B, in cell survival upon cisplatin treatment, based on an array of methods, including siRNA knockdown, CRISPR knockout of IPA polyA site, and CRISPR mutation of the start codon. They further found that FANCD2 and Senataxin can regulate cisplatin-mediated IPA activation. The authors advocate a new paradigm of expression of IPA-encoding microproteins in cisplatin-treated cells.

      Major comments:

      • While the phenomenon of IPA isoform upregulation by Cisplatin is quite convincing, the underlying mechanism is largely elusive. The authors indicated processivity as a potential mechanism and the effects of FACD2 and Senataxin appear in line with this hypothesis. However, they cannot rule out other possibilities based on the data presented in the manuscript. For example, it is not clear if the elongation rate of Pol II (distinct from its processivity) or nuclear RNA degradation is affected by cisplatin, which could also lead to increased expression of IPA isoforms. In addition, enhanced 3' end processing activity has been previously shown to activate IPA sites. Therefore, the underlying mechanism is mostly speculative.
      • The authors used the polysome:cytosolic ratio to indicate translational efficiency. However, because the CDS size affects the number of ribosomes per mRNA, the translational efficiency should be based on polysome:cytosolic ratio normalized to CDS size. Ideally, the authors should calculate number of ribosome per transcript based on monosome, light polysome and heavy polysome.
      • The functions of PHF20 and PRKAR1B IPA isoforms are based on knockdown or knockout mutations. Because of its gain-of-function property, overexpression of the isoforms in cisplatin-treated cells would be necessary to definitively confirm their funcitons.

      Minor:

      Fig. 1H, the numbers of IPA and LE transcripts should be provided. The statistical significance for the difference should also be included.

      Fig. 1I, the image should be accompanied with fold difference as indicated in the text. Some statistics for difference between vehicle only and CisPt only is necessary.

      Fig. 6, the authors did data mining of ribo-seq data and mass-spec data and identified 156 genes whose IPA isoforms have potentials of protein expression. The enriched GO terms for the 156 IPA genes are different than the overall IPA isoforms shown in Fig. 1C. Does this mean some genes, like those in DNA damage stimulus, produce IPA isoforms with different consequences, such as to inhibit their expression? In addition, the authors need to use ribo-seq and mass spec data as a validation tool for their polysome profiling data to indicate the reliability of using polysome data to call protein expression.

      Significance

      The significance of this work is its novelty in reporting IPA isoform activation by cisplatin. More importantly, some IPA isoform give rise to microproteins that have functional roles in cell survival upon cisplatin treatment.

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      Referee #1

      Evidence, reproducibility and clarity

      Microporteins originating from coding and non-coding transcript are increasingly understood to control various cellular processes. In the present study, the authors investigated whether intronic polyadenylation (IPA) contributes to the formation of transcript isoforms encoding microproteins. Using genotoxic stress by cisplatin as a model in cell cultures, the authors detect abundant IPA. IPA in a subset of such transcripts leads to short 5'UTR transcript isoforms that are poorly associated with heavy polysomes and encode microproteins. For PRKAR1B, they demonstrate the expression of a corresponding microprotein and a function in modulating the cisplatin response. Based on depletion experiments of FANCD2 and STX1, the authors propose that impaired transcription processivity after cisplatin is one mechanism leading to IPA and microprotein production.

      While this is an interesting manuscript, I felt the support for the claimed generalization falls a bit short.

      Major:

      If I see it correctly, the authors mainly refer to existing riboSeq data and evidence from mass spectrometry/proteomics to infer the generality of the mechanism (beyond PRKAR1B). It is important to back this up with further experiments and validate this for the set-up used in this manuscript. This concerns the existence of the microproteins but also the downstream functional impact.

      Also, I wonder is this limited to cisplatin-induced genotoxic stress and the specific cell line used or is this a more global mechanism?

      Minor:

      • While the rest of the paper reads well, the abstract could be improved/simplified to increase accessibility
      • Page 11: Pertaining to Figure 3 and the functional impact: The authors analyze the IPA effect by probing cell viability and cell survival. It would be important to define the effects in further detail, as the mere regulation of cell cycle and/or apoptosis could also result in such outcome (which is then not necessarily a direct cisplatin response). Does this also impact the response to other genotoxic stress (also pertains to the effects studied and shown in Fig. 5)?
      • Page 11: Pertaining to Figure 3 and the functional impact: The authors analyze the IPA effect by probing cell viability and cell survival. It would be important to define the effects in further detail, as the mere regulation of cell cycle and/or apoptosis could also result in such outcome (which is then not necessarily a direct cisplatin response). Does this also impact the response to other genotoxic stress (also pertains to the effects studied and shown in Fig. 5)?
      • Page 12 concerning the microprotein expression: the authors refer to data from other resources to claim that the microproteins are expressed, however they fail to demonstrate this for their setup (at least for 2 out of three they study here). I think this is a weak point as it does not directly support the general claim.
      • Also, I did not understand what the authors intended to demonstrate with the immunoflourescence (Fig. 4E). What should a defined nuclear expression imply versus the diffuse staining throughout after cisplatin? How does this relate to the functional effects?
      • Page 13/Fig. 5E: the different clones of the mATG show very high variability. To my understanding it is difficult to draw a clear conclusion from this heterogeneity.
      • Page 15 on the mechanism: SETX has been demonstrated to control poly(A) site choice (PMID: 21700224, 32976578). However the quantitative role of SETX in poly(A) site choice regulation (compared to other regulators) seems to be rather marginal and not strictly unidirectional, i.e after SETX depletion also longer transcript isoforms can be detected (PMID: 32976578). How does this relate to the proposed mechanism of SETX-dependent processivity? Interestingly, from PMID: 32976578 it also appears that PRKAR1A has a 5'UTR poly(A) site that is regulated in a SETX-dependent manner.
      • Page 16, discussion first paragraph. While refs 1-4 are nice reviews that could be quoted here a study that appeared later represents the most comprehensive analysis to date covering the different facets from transcription to RNA processing and the resulting impact on poly(A) site choice (PMID: 30552333).

      Significance

      This could be a very significant report, provided the generality of the claims and mechanistic insigths are further strengthend.

      Overall it targets a rather specialized readership. This could be improved by simplifing the abstract, additional experimental evidence for the generality of the proposed mechanism, and a stringent rewording of the main text drawing a clear line, omitting unnecessary details and focussing on the novel findings.

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      Reply to the reviewers

      Manuscript number: RC-2023-02232

      Corresponding author(s): Shinji, Saiki and Nobutaka, Hattori

      1. General Statements [optional]

      Thank you for the review of our paper entitled “Identification of novel autophagy inducers by accelerating lysosomal clustering against Parkinson's disease” (RC-2023-02232). We have carefully read the critiques and planed experiments. Below we include point-by-point responses to the questions raised by the reviewers. We have also carried out some experiments and highlighted the revised sentences in the transferred manuscript in red. The numbers of pages and lines are indicated based on the MS Word transferred manuscript. We believe this revision plans appropriately addresses the issues raised by Reviewers. Finally, all the authors would like to thank again the Editor and Reviewers for improving our manuscript by providing their invaluable comments and suggestions.

      Point-by-point description of the revisions

      • *

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

      The manuscript by Date et al employed a cell model by stably expressing LGP120-mCherry and GFP-gamma-tubulin to carry out high-content screening in search of chemical compounds that enhance lysosomal clustering and autophagy. They found 6 clinically approved drugs categorized as topoisomerase II inhibitors and the benzimidazole class. They further validated these compounds by a set of well-designed experiments including autophagy flux assays and mTOR dependence. In the mechanistic study, they demonstrated the compounds induce lysosomal clustering in a JIP4-TRPML1-dependent manner. In a PD cell model, one of the compounds albendazole exhibited the effect on boosting the degradation of insoluble alpha-synuclein. The study is of interest, and the cell model and the approach generated by the authors would be transferable for future studies of other high-content imaging screening. Most of the data is clear and convincing.

      Major comment

      1) In addition to its role in facilitating a-syn turnover by autophagy, Is the chemical protective against a-syn toxicity?

      RESPONSE:

      As suggested by the Reviewer, we examined the cytotoxicity of aSyn aggregates in SH-SY5Y cells overexpressing aSyn-GFP by LDH assay. As shown in the revised version of Fig. 1, aSyn aggregates induced by introducing aSyn fibrils into SH-SY5Y cells overexpressing aSyn-GFP did not exhibit any cytotoxicity. In addition, we observed no significant change in cell death after 8 hours of treatment with albendazole compared with DMSO.

      Previous studies have reported that induced pluripotent stem cells (iPSCs) derived from patients with PD with a triplication of the human SNCA genomic locus exhibited reduced capacity for differentiation into dopaminergic or GABAergic neurons, decreased neurite outgrowth, and lower neuronal activity compared with control cultures, albeit without showing cytotoxicity (Cell Death and Disease 6: e1994, Oliveira et al., 2015). Given this context, we were thus unable to conduct the suggested assessment due to technical limitations. Therefore, we consider the evaluation of the recovery of aSyn toxicity by drug treatment challenging in this cellular model using fibril aSyn.

      __Revised Fig 1. __

      SH-SY5Y cells overexpressing aSyn-GFP were transfected with aSyn fibril for 48 h and treated with the indicated albendazole concentrations for 8 h. The cytotoxicity was measured by using Cytotoxicity LDH Assay Kit-WST kit.

      2) Please elaborate why albendazole does not change the levels of soluble a-syn, but those of insoluble, as shown Fig 8D.

      RESPONSE:

      The unchanged aSyn-GFP levels in the soluble fraction (Fig. 8D) are likely due to the abundance of soluble aSyn-GFP. To evaluate the autophagic degradation of aSyn monomers, we used SH-SY5Y cells stably expressing aSyn-Halo and measured aSyn degradation by quantifying cleaved Halo. As shown in the revised version of Fig. 2, albendazole treatment induced a higher cleavage rate of Halo than DMSO treatment for 8 h, suggesting that albendazole degrades both aSyn monomers and aSyn aggregates. We have added the data in Fig. S7A, and the description of these experiments in the Results section (page 10, lines 359 to 364).


      __Revised Fig. 2. __

      SH-SY5Y cells expressing aSyn-Halo were labeled for 20 min with 100 nM of tetramethylrhodamine-conjugated ligand in a nutrient-rich medium. After washing with phosphate-buffered saline and incubating in normal medium for 30 min, the cells were treated with 10 µM albendazole for 8 h. The experiments were performed in triplicate. Cell lysates were separated by electrophoresis and analyzed by in-gel fluorescence detection (left). The HaloTMR band intensity was normalized by the sum of the band intensities of HaloTMR-aSyn and HaloTMR. The vertical axis of the graph represents the intensity multiplied by 100. Mean values of data from five or three experiments are shown. The graph data are expressed as mean ± standard deviation. ****P 

      3) Fig 6A shows that some of the compounds (Teniposide, Amsacrine) affect the levels of JIP4. Can albendazole also reduce JIP4 levels. It might be interesting to test this, as JIP4 is important for lysosomal clustering.

      RESPONSE:

      As the Reviewer pointed out, JIP4 is essential for lysosome accumulation. However, our data showed decreased JIP4 levels with the addition of lysosomal-clustering compounds. We hypothesized that this response was caused by the autophagy-induced degradation of JIP4. The decrease in JIP4 levels was detected by western blot after 4 h of treatment with 10 μM of teniposide. Moreover, the decrease in JIP4 levels induced by teniposide was suppressed by co-treatment with bafilomycin A1, indicating that JIP4 was degraded by teniposide-induced autophagy, as shown in the revised version of Fig. 3. We have added the data in Fig. S6 and the related description of these experiments in the Results section (page 8, lines 289 to 293).

      __Revised Fig 3. __

      SH-SY5Y cells were treated with 10 µM teniposide and with or without 30 nM bafilomycin A1 for 4 h. Cell lysates were immunoblotted with anti-JIP4 and actin antibodies.

      Minor comments: The writing is good generally. Please tide up the text in a few occasions to make the expressions more formal.

      RESPONSE: We have revised our manuscript to adopt a more formal tone.

      Reviewer #1 (Significance (Required)):

      Significance: The study generated a new approach for high-throughput screening of compounds to enhance lysosomal clustering. Audience: Basic and clinical research Expertise: Programmed cell death, neurodegenerative diseases

      • *

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

      In this study, the authors focused on lysosome positioning and autophagy activity to search for novel agents effective against Parkinson's disease. As a result, several compounds were successively identified, including Topoisomerase inhibitors and Benzimidazole. Authors showed that these agents regulate lysosomal positioning through different pathways but commonly require JIP4 to regulate lysosomal positioning and subsequent autophagy. They also showed that albendazole treatment promoted the degradation of insoluble ubiquitinated proteins and αSyn in cultured cells.

      Major Comments.

      1) Two compounds, for instance teniposide and albendazole both requires JIP4 and/or TRPML1 to regulate lysosomal positioning and autophagy but their action seems different. What is the actual mechanism by which these compounds require JIP4/TRPML1. How inhibition of Topoisomerase leads to increase of JIP4 phosphorylation? Do teniposide and albendazole both affect calcium release from TRPML1?

      RESPONSE:

      We previously reported that acrolein/H2O2 accelerates lysosomal retrograde trafficking by TRPML1 and phosphorylated JIP4. Mechanistically, JIP4 was phosphorylated by CaMK2G activated by Ca2+ released from TRPML1 (EMBO J 41: e111476, Sasazawa et al., 2022). TRPML1 acts as a reactive oxygen species (ROS) sensor in lysosomes (Nat Commun 7: 12109, Zhang et al., 2016). We concluded that acrolein induces ROS production, which then activates TRPML1. (EMBO J 41: e111476, Sasazawa et al., 2022). Therefore, topoisomerase inhibitors (topo-i) may induce ROS and stimulate TRPML1. We examined intracellular ROS levels in response to topo-i. As shown in revised Fig. 4A, the topo-i teniposide, etoposide, and amsacrine significantly increased ROS levels. Moreover, N-acetyl-L-cysteine, an ROS scavenger, partially attenuated lysosomal clustering induced by topo-i (revised Fig. 4B). In addition, Ca2+ imaging showed that teniposide, but not albendazole, upregulates Ca2+ flux (revised Fig. 4C). Based on the activity of CaMK2G siRNA as shown in Fig. 5D, 5E, and S5, topo-i may activate TRPML1 in a ROS-dependent manner and increase PI(3,5)P2 binding with TRPML1 (Nat Commun 1, 38, Dong et al., 2010). Consecutive Ca2+ release via TRPML1 activated CaMK2G and is followed by enhanced lysosomal transport toward the MTOC via JIP4 phosphorylation.

      We have added the revised Fig.4A and 4B data in Fig. S8A and S8B, and the related description of these experiments in the Discussion section (page 11, lines 401 to 409). We have also added the data in revised Fig. 4C to Fig. S6 and the related description of these experiments in the Results section (page 7, lines 266 to 267).

      Conversely, we showed that benzimidazoles, including albendazole, induce lysosomal clustering mediated by JIP4, TRPML1, ALG2, and Rab7. Moreover, benzimidazoles showed lysosomal clustering activity within a narrow concentration range, as shown in Fig. S7D. Benzimidazoles inhibit tubulin polymerization (Int J Paras 18:885–936. Lacey et al., 1988). We hypothesized that the effect of tubulin polymerization induced by benzimidazole plays a key role in the induction of lysosomal clustering as described in the Discussion section. To clarify this, we observed the behavior of tubulin filaments in response to various albendazole concentrations under confocal microscopy. As shown in revised Fig. 4D, conditions where albendazole was administered to induce lysosomal clustering, tubulin filaments were observed only near the MTOC, and the filaments in the cell periphery were disassembled. In contrast, when exposed to higher albendazole concentrations, tubulin filaments throughout the cell were disassembled, resulting in the inhibition of lysosomal clustering This would explain why benzimidazole exerts lysosomal clustering activity within a narrow concentration range. Under JIP4, TRPML1, ALG2 and Rab7 silencing, lysosomes may fail to interact with microtubules, resulting in the inhibition of lysosomal clustering. We postulated that albendazole-induced lysosomal clustering is not mediated by factors activated by specific stimuli in lysosomal transport but, rather, is induced by spatially constraining conventional lysosomal transport mediated by various adaptors (i.e., JIP4, TRPML1, ALG2, and Rab7) through tubulin disassembly. We have added the data in Fig. S9C and the related description of these experiments in the Discussion section (page 12, lines 428 to 436).

      A B

      C

      D

      __Revised Fig. 4. __

      1. SH-SY5Y cells were treated with the indicated compounds (10 µM) for 4 h. The amount of intracellular reactive oxygen species (ROS) is examined by ROS Assay Kit -Highly Sensitive DCFH-DA (Dojindo) and the normalized pixels above threshold as measured using an INCellAnalyzer 2200 and ImageJ.
      2. SH-SY5Y cell lines were pretreated with 0.1 mM N-acetyl-L-cysteine (NAC) for 24 h and then treated with the indicated compound (10 µM) for an additional 4 Cells were fixed and stained with anti-g-tubulin (green) and anti-LAMP2 (red) antibodies. Lysosomal distribution was examined using an INCellAnalyzer 2200 and quantified using ImageJ software.
      3. SH-SY5Y cells were treated with teniposide, amsacrine, etoposide, albendazole (1, 5, 10 µM), oxibendazole (0.1, 0.5, and 1 µM), or and mebendazole (0.5,1, and 5 µM) for 4 h, and stained with Fluo4-AM for 30 min. The fluorescence intensity was measured using a plate reader.
      4. SH-SY5Y cells were treated with albendazole (10 and 100 µM) or nocodazole (0.5 and 10 µM) for 4 h. Cells were fixed and stained with LAMP1 (red) and a-tubulin (green) antibodies.

        2) The authors should clarify the functional advantage of these drugs identified in this study as drugs for Parkinson's disease by comparing with known autophagy inducers such as Torin1 or rapamycin. 

      RESPONSE:

      To evaluate the functional advantage of lysosome-clustering compounds over Torin1, we evaluated the degradation activity of insoluble aSyn induced by the addition of aSyn fibrils to aSyn-GFP cells. Torin1 induced the degradation of insoluble aSyn by autophagy, as shown in revised Fig. 5A. However, the degradation activity of albendazole was more vigorous, as shown in revised Fig. 5B. In contrast, we observed that Torin1 exhibited more autophagic induction activity than albendazole, as assessed using Halo-LC3. Similar results were obtained with teniposide (revised Fig. 5C). These results suggest that albendazole, with its ability to concentrate lysosomes around the degradation substrate, facilitates more effective degradation of insoluble aSyn than Torin1. This presents a significant advantage in the development of therapeutics for Parkinson's Disease. Moreover, Torin1 acts on the upstream signals of autophagy by inhibiting mTORC1, potentially impacting diverse cellular responses. Conversely, compounds that induce lysosomal clustering target the final step of autophagic degradation, which may have fewer side effects. We have added the description of these experiments in the Results section (page 10, lines 366 to 380) and the Discussion section (page 11 lines 410 to 412) and presented the data in Fig. S7B–S7E and Fig. 6D.

      A____ ____B








      C











      __Revised Fig. 5. __

      1. SH-SY5Y cells overexpressing aSyn-GFP were transfected with aSyn fibril (0.2 µg/mL) using Lipofectamine 3000. After 48 h, the transfection reagent was washed out, and the SH-SY5Y cells were treated with 100 nM Torin1 with or without 100 nM bafilomycin A1 for 8 h (B). Cell lysates were separated into Triton X-100–soluble (soluble) and pellet fractions (insoluble), then subjected to sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and immunoblotting with the indicated antibody(left). The amount of insoluble aSyn was quantified using Image J software (C).
      2. SH-SY5Y cells overexpressing aSyn-GFP were transfected with aSyn fibril (0.2 µg/mL) using Lipofectamine 3000. After 48 h, and washing out the transfection reagent, SH-SY5Y cells were treated with albendazole (10μM) with or without 100 nM Torin1 for 8 h. Cell lysates were separated into Triton X-100–soluble (soluble) and pellet fractions (insoluble), then subjected to SDS-PAGE and immunoblotting with the indicated antibody (left). The amount of insoluble aSyn was quantified using Image J software.
      3. SH-SY5Y cells stably expressing Halo-LC3 were labeled for 20 min with 100 nM TMR-conjugated ligand in a nutrient-rich medium. After washing with PBS and incubating the cells in normal medium for 30 min, cells were treated with DMSO, teniposide (10 μM), albendazole (10 µM), and/or Torin1 (100 nM) for 8 h. Cell lysates were immunoblotted with the indicated antibody and analyzed by in-gel fluorescence detection (left). The HaloTMR band intensity was normalized by the sum of the band intensities of HaloTMR-LC3B and HaloTMR (right).

        3) Related to the previous question, in Fig.6A and B additional data comparing novel compounds with established autophagy inducers, such as torin1 and rapamycin, should be included and discussed.

      RESPONSE:

      As indicated in a previous response, we evaluated the autophagic induction activity of Torin1, and the results have been added to Fig. 6D. In addition, co-treatment with Torin1 and teniposide or albendazole induced autophagy more effectively than Torin1 treatment alone, without affecting mTOR inhibition activity (revised Fig. 4C). These findings indicate that the induction of autophagy by lysosomal clustering compounds is not caused by autophagosome formation but by the formation of autolysosomes. We have added a description of these experiments in the Results section (page 9, lines 316 to 322) and have added the data in Fig. 6D.

      4) The authors should examined whether increased degradation of insoluble proteins and αSyn are dependent on JIP4.  

      RESPONSE:

      As the Reviewer suggested, we have examined whether lysosomal accumulation through the JIP4-TRPML1 pathway is crucial for the degradation of aSyn aggregates. We evaluated the degradation activity of insoluble aSyn induced by the addition of aSyn fibrils to aSyn-GFP cells when JIP4, TMEM55B, or TRPML1 were knocked down. Interestingly, the insoluble fraction assay showed that JIP4 and TRPML1 knockdown regulated the decrease of aSyn-GFP and p-aSyn levels in the insoluble fraction for both DMSO and albendazole treatments. The results were particularly more pronounced with TRPML1 knockdown. However, the knockdown of TMEM55B did not produce such findings (revised Fig. 6). These data suggest that lysosomal clustering via the JIP4–TRPML1 pathway plays a significant role in aSyn degradation. We have added a relevant description in the Results section (page 10, lines 373 to 380) and have added the data in Fig. S7F and S7G.


      __Revised Fig. 6. __

      SH-SY5Y cells over-expressing aSyn-GFP were transfected with the indicated siRNAs for 24 h and then transfected with aSyn fibril (0.2 µg/mL) using Lipofectamine 3000 for 48 h. After washing out the transfection reagent, the SH-SY5Y cells were treated with dimethyl sulfoxide or albendazole (10 μM) for 8 h. Cell lysates were separated into Triton X-100–soluble (soluble) and pellet fractions (insoluble) and subjected to SDS-PAGE and immunoblotting with the indicated antibody. The bar graph presents the ratio of the insoluble aSyn-GFP to the soluble GAPDH or insoluble p-aSyn to the soluble GAPDH of the intensity of the data in panel F. Data are expressed as mean ± standard deviation.

      5) Authors only utilized. SH-SY5Y cells in this study. It is important to examine whether these compounds also regulate lysosomal positioning and autophagy in other cell lines.

      RESPONSE:

      As per the Reviewer’s suggestion, we evaluated the lysosomal-clustering activity induced by topo-i and benzimidazole in human adenocarcinoma HeLa cells. As shown in revised Fig. 7A and 7B compounds do not induce lysosomal clustering or autophagy in HeLa cells. Furthermore, in the case of benzimidazole, they transport lysosomes to the cell periphery. Previously, we found that oxidative stress accumulates lysosomes in a neuroblastoma-specific manner through the TRPML1–phosphoJIP4-dependent mechanism (EMBO J 41: e111476, Sasazawa et al., 2022). Since we have demonstrated that topo-i-mediated lysosomal trafficking is dependent on the TRPML1–phosphorylated JIP4 complex, we hypothesized that several molecules involved in lysosomal trafficking are absent in HeLa cells.

      In contrast, we showed that albendazole-induced lysosomal clustering is due to tubulin depolymerization. Therefore, we examined the relationships between tubulin depolymerization and lysosomal clustering induced by albendazole in HeLa cells and found that albendazole did not induce lysosomal clustering but rather inhibited it at higher concentrations (revised Fig. 7B). Interestingly, similar to SH-SY5Y cells, a low albendazole concentration (10 μM) induced tubulin depolymerization only at the cell periphery, whereas a high concentration (100 μM) depolymerized the entire cell (revised Fig. 7C). However, unlike SH-SY5Y cells, no characteristic accumulation of tubulin filaments was observed near the MTOC under low albendazole concentration (10 µM); instead, they were arranged around the nucleus. Concurrently, lysosomes were around these dispersed tubulin filaments. Therefore, the differences in the effects of benzimidazole in HeLa and SH-SY5Y cells lies in the dose-dependent effects on the state of tubulin filaments. We have added a relevant description in the Discussions section (page 12, lines 419 to 422, and 437 to 453).

      __ A__

      __ B__

      C D

      __Revised Fig. 7. __

      HeLa cells were treated with teniposide (10 μM), amsacrine (10 μM), etoposide (10 μM), albendazole (10 μM), oxibendazole (1 μM), or mebendazole (5 μM). Images were captured using an INCellAnalyzer2200. INCellAnalyzer2200 images were analyzed using ImageJ for lysosomal clustering. The graph presents the lysosomal clustering values (n > 30). Data are expressed as mean ± standard deviation (SD). ****P HeLa cells were treated with teniposide (10 μM), amsacrine (10 μM), etoposide (10 μM), albendazole (10 μM), oxibendazole (1 μM), or mebendazole (5 μM) for 4 h. Cell lysates were immunoblotted with the indicated antibodies. The amount of LC3II was estimated using Image J software (bottom panel). HeLa cells were treated with albendazole at specified concentrations (in µM). After treatment, cells were fixed and stained with anti-g-tubulin (green) and anti-LAMP2 (red) antibodies, followed by imaging with an INCellAnalyzer2200. INCellAnalyzer2200 images were processed and analyzed using ImageJ for lysosomal clustering. The graph presents the lysosomal clustering values (n > 30). Data are expressed as mean ± SD. *P  HeLa cells were treated with albendazole (10 and 25 µM) for 4 h. Cells were fixed and stained with LAMP1 (red) and a-tubulin (green) antibodies.

      6) The authors conclude that the six compounds do not mediate mTOR signaling in Fig. 3, but should more carefully describe in the manuscript why they performed this experiment and what the results mean for.

      RESPONSE: 

      As per the Reviewer’s advice, we have changed the description in the manuscript as follows:

      Previous studies have shown that lysosomal retrograde transport regulates autophagic flux by facilitating autophagosome formation by suppressing mTORC1 and expediting fusion between autophagosomes and lysosomes (Kimura et al, 2008; Korolchuk et al, 2011). Conversely, we recent found that acrolein/H2O2 induces lysosomal clustering in an mTOR-independent manner (Sasazawa et al., 2022). In this study, we aimed to identify pharmacologic agents that act downstream rather than upstream in the autophagy pathway, with the goal of minimizing side effects. Therefore, we evaluated the effects of the compounds on the mTOR pathway. As shown in Fig. 3, these compounds induced lysosomal clustering without affecting mTOR activity, indicating their potential as promising candidates for PD therapy. We have added the description of these experiments in the Results section (page 6, lines 202 to 208 and line 217).

      Minor comments. 1) The name of the compound should be written in the red point of Fig.2A.

      RESPONSE:

      We have included the names of the six compounds identified and are listed in Fig. 2A.

      2) Regarding images of Fig.2B, the magnified images and quantitative data should be added.

      RESPONSE:

      We have included magnified images, as well as the quantitative results of lysosome clustering analysis using INCellAnalyzer2200 in Fig. 2B.

      3) The results of Fig.2C need to be explained more carefully. A quantitative data is missing.

      RESPONSE:

      We have included the quantitative results of western blot in Fig. 2B.

      4) Fig.S2, which compares autophagy activity with conventional agents, should be quantified and added to the Fig.3.

      RESPONSE:

      We have presented the results of RFP/GFP quantification performed by FACS analysis using SH-SY5Y cells stably expressing RFP-GFP-LC3 in Fig. S2, which is equivalent to the quantification of the data in the Fig. S2 image. These data are now presented as Fig. S2B. Since Fig. 3 focuses on mTOR signaling, we preferred to retain the figure number.

      5) In the statistical analysis of Fig.4B, the clustering value was increased by siRILP, which should be briefly described in the manuscript.

      RESPONSE:

      On the contrary, the enhancement of lysosomal retrograde transport in RILP knockdown cells in Fig. 4B suggests the potential involvement of RILP in anterograde transport. However, to the best of our knowledge, no reports have investigated this matter. We presume that negative feedback mechanisms may be present. We have added this description to the Results section (page 7 lines 238 to 241).

      6) In Fig.4A and B, it is possible that the knockdown efficiency of siRILP and siTMEM55B was not sufficient to observe the effect on lysosomes, and this concern should be described in the manuscript.

      RESPONSE:

      We established starvation conditions, which induce TMEM55B-dependent lysosomal retrograde transport, as a positive control and evaluated the lysosomal induction activity of compounds when TMEM55B was knocked down. As shown below, lysosome accumulation was suppressed only when subjected to starvation treatment, indicating sufficient knockdown efficiency of TMEM55B. These compounds induced lysosomal clustering independently of TMEM55B, unlike under starvation conditions. We have added a description of these experiments in the Results section and presented the data in Fig. S4A (page 7, lines 232 to 237).

      On the other hand, we were unable to establish a positive control for RILP knockdown experiments because conditions that regulate RILP-dependent lysosomal distribution dependent are not understood. While we cannot completely rule out the possibility of insufficient knockdown efficiency, considering that RILP knockdown appears to paradoxically enhance lysosomal induction, as mentioned above, it is reasonable to assume that the knockdown effect has occurred.

      __Revised Fig. 8. __

      SH-SY5Y cells were transfected with TMEM55B siRNA for 48 h and then treated with teniposide (10 μM), albendazole (10 μM), or starvation medium for 4 h. Cells were fixed and stained with anti-g-tubulin (green) and anti-LAMP2 (red) antibodies. Images were captured using an INCellAnalyzer2200. INCellAnalyzer2200 images were analyzed using ImageJ for lysosomal clustering. The graph presents the lysosomal clustering values (n > 30). Data are expressed as mean ± standard deviation (SD). ****P

      7) The authors should add the results of the WB experiment showing the amount of JIP4 protein in Fig.5G. 

      RESPONSE:

      We have added western blot data that introduce flag-JIP4 into JIP4KO SH-SY5Y cells, which are presented in Fig. 5G.

      8) In Fig.5F, images of JIP4KO cells that do not express FLAG-JIP4 should be added as controls, and further quantification should be done on cells in all three conditions.

      RESPONSE:

      We have added immunofluorescence data that do not express flag-JIP4 in Fig. 5F, which had been obtained simultaneously during the acquisition of other images. Furthermore, we quantified lysosomal distribution, which is shown in Fig. 5E. Using ImageJ, we automatically delineated approximately 70% of the cell area toward the cell center and designated the region excluded from this area as the cellular peripheral region (revised Fig. 9A). Subsequently, we quantified the proportion of lysosomes contained within that region in cells expressing flag-JIP4 (revised Fig. 9B). We have added this experimental data in Fig. 5E.

      A B

      __Revised Fig. 9. __

      1. Approximately 70% of the cell area toward the cell center was automatically delineated using ImageJ, with the region excluded from this defined as the cellular peripheral region.
      2. JIP4 KO cells were transfected with flag-tagged JIP4 (wild-type and T217A) for 24 h and treated with teniposide (10 μM) for 4 h. Cell lysates underwent SDS-PAGE and were immunoblotted with anti-JIP4 and anti-actin The graph displays the percentage of cells with peripheral lysosomes. Data are expressed as mean ± standard deviation. *P 20).

        9) In Fig.6A, the total amount of JIP4 seems to change in some agent treatments, which needs to be explained.

      RESPONSE:

      As per our response to Reviewer 1, we evaluated the decrease in JIP4 expression by WB after 4 h of treatment with 10 μM teniposide. The teniposide-induced decrease of JIP4 was suppressed by bafilomycinA1 co-treatment, indicating that JIP4 was degraded by teniposide-induced autophagy (revised Fig. 3). We have added the data in Fig. S6, and the related description of these experiments have been added to the Results section (page 8, lines 289 to 293).

      10) In Fig.7C and D, the effect of drug treatment on the amount of ubiquitinated proteins should also be checked.

      RESPONSE:

      We have included ubiquitin protein blots in Fig. 7C and 7D.

      11) In Fig.8B, it is described that lysosomes are more localized in αSyn by drug treatment, but more convincing images and quantitative data are needed.

      RESPONSE:

      . The colocalization of LAMP2 and aSyn-GFP aggregates was assessed by measuring the fluorescence values of lysosomes in contact within the aSyn-GFP aggregation area using ImageJ. We have added this quantified data in Fig. 8D.

      Reviewer #2 (Significance (Required)): Although the reviewer appreciates the discovery of novel drugs to induce autophagy through regulating lysosomal positioning, the detailed action of these compounds and their superiority in the field are not clear.

      __Reviewer #3 (Evidence, reproducibility and clarity (Required)):____ __ In this manuscript, Date et al. sought to identify compounds that promote protein aggregates clearance - in particular those formed by mutant alpha synuclein. Briefly the authors screened a library of clinically approved compounds for inducers of lysosomal clustering followed by a secondary screen for autophagy inducers. By this two-step procedure, the authors identified three topoisomerase inhibitors and three anthelmintics as hits. Next, the authors unveiled that lysosomal clustering induced by these compounds is independent of mTORC1 but requires TRPML1 and JIP4. Moreover, the topoisomerase inhibitors hits involved phosphorylation of JIP4 while the anthelmintics additionally required Rab7 and ALG2. Intriguingly, the authors found that lysosomal clustering was prerequisite to autophagy induction. Focusing on the class of anthelmintics (i.e. albendazole) the authors showed that these induce autophagy to degrade aggregates formed upon proteasome inhibition. Lastly, the authors demonstrated that albendazole also led to increased degradation of αSyn aggregates through autophagy induction.

      Major points 1) Most importantly, the authors need to tone down the significance of their findings throughout the manuscript. For examples, they should restrain from using "nullified" when it is really reduced only by 10-25 %.

      RESPONSE: 

      We have changed the description in the manuscript according to the Reviewer’s suggestion.

      2) The authors claim that the topoisomerase inhibitors led to JIP4 phosphorylation while Figure 5C actually shows the opposite (partially reduced phosphorylation compared to DMSO treatment) and the Jak3 inhibitor has no obvious effect. The authors should quantify the phostag results.

      RESPONSE:

      We agree with the Reviewer that the Phos-tag PAGE results of JIP4 in Fig. 5C is complicated, and the bands were not clear. We have replaced these with more robust data (Fig. 5C).

      3) Figure 6A/B: Why do all compounds except Mebendazole affect the abundance of JIP4?

      RESPONSE:

      As per our response to Reviewer 1, we evaluated the decrease in JIP4 expression by WB after 4 h of treatment with 10 μM teniposide. The teniposide-induced decrease of JIP4 was suppressed by bafilomycinA1 co-treatment, indicating that JIP4 was degraded by teniposide-induced autophagy (revised Fig. 3). We have added the data in Fig. S6, and the related description of these experiments have been added to the Results section (page 8, lines 289 to 293).

      4) Figure 7C: The blot is not convincing. The authors should quantify this effect.

      RESPONSE:

      We evaluated and confirmed the degradation of p62 by albendazole, as shown in Fig. 7C.

      Reviewer #3 (Significance (Required)):

      Overall, the work of Date and colleague highlights the role of lysosomal clustering in clearing protein aggregates. Importantly, the identified classes of compounds might open new avenues for rationalizing treatment strategies for neurodegenerative diseases. However, several critical points remain.

      • *
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      Referee #3

      Evidence, reproducibility and clarity

      In this manuscript, Date et al. sought to identify compounds that promote protein aggregates clearance - in particular those formed by mutant alpha synuclein. Briefly the authors screened a library of clinically approved compounds for inducers of lysosomal clustering followed by a secondary screen for autophagy inducers. By this two-step procedure, the authors identified three topoisomerase inhibitors and three anthelmintics as hits. Next, the authors unveiled that lysosomal clustering induced by these compounds is independent of mTORC1 but requires TRPML1 and JIP4. Moreover, the topoisomerase inhibitors hits involved phosphorylation of JIP4 while the anthelmintics additionally required Rab7 and ALG2. Intriguingly, the authors found that lysosomal clustering was prerequisite to autophagy induction. Focusing on the class of anthelmintics (i.e. albendazole) the authors showed that these induce autophagy to degrade aggregates formed upon proteasome inhibition. Lastly, the authors demonstrated that albendazole also led to increased degradation of αSyn aggregates through autophagy induction.

      Major points

      1. Most importantly, the authors need to tone down the significance of their findings throughout the manuscript. For examples, they should restrain from using "nullified" when it is really reduced only by 10-25 %.
      2. The authors claim that the topoisomerase inhibitors led to JIP4 phosphorylation while Figure 5C actually shows the opposite (partially reduced phosphorylation compared to DMSO treatment) and the Jak3 inhibitor has no obvious effect. The authors should quantify the phostag results.
      3. Figure 6A/B: Why do all compounds except Mebendazole affect the abundance of JIP4?
      4. Figure 7C: The blot is not convincing. The authors should quantify this effect.

      Significance

      Overall, the work of Date and colleague highlights the role of lysosomal clustering in clearing protein aggregates. Importantly, the identified classes of compounds might open new avenues for rationalizing treatment strategies for neurodegenerative diseases. However, several critical points remain.

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

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      Referee #2

      Evidence, reproducibility and clarity

      In this study, the authors focused on lysosome positioning and autophagy activity to search for novel agents effective against Parkinson's disease. As a result, several compounds were successively identified, including Topoisomerase inhibitors and Benzimidazole. Authors showed that these agents regulate lysosomal positioning through different pathways but commonly require JIP4 to regulate lysosomal positioning and subsequent autophagy. They also showed that albendazole treatment promoted the degradation of insoluble ubiquitinated proteins and αSyn in cultured cells.

      Major Comments.

      • Two compounds, for instance teniposide and albendazole both requires JIP4 and/or TRPML1 to regulate lysosomal positioning and autophagy but their action seems different. What is the actual mechanism by which these compounds require JIP4/TRPML1. How inhibition of Topoisomerase leads to increase of JIP4 phosphorylation? Do teniposide and albendazole both affect calcium release from TRPML1?
      • The authors should clarify the functional advantage of these drugs identified in this study as drugs for Parkinson's disease by comparing with known autophagy inducers such as Torin1 or rapamycin.
      • Related to the previous question, in Fig.6A and B additional data comparing novel compounds with established autophagy inducers, such as torin1 and rapamycin, should be included and discussed.
      • The authors should examined whether increased degradation of insoluble proteins and αSyn are dependent on JIP4.
      • Authors only utilized. SH-SY5Y cells in this study. It is important to examine whether these compounds also regulate lysosomal positioning and autophagy in other cell lines.
      • The authors conclude that the six compounds do not mediate mTOR signaling in Fig. 3, but should more carefully describe in the manuscript why they performed this experiment and what the results mean for.

      Minor comments.

      • The name of the compound should be written in the red point of Fig.2A.
      • Regarding images of Fig.2B, the magnified images and quantitative data should be added.
      • The results of Fig.2C need to be explained more carefully. A quantitative data is missing.
      • Fig.S2, which compares autophagy activity with conventional agents, should be quantified and added to the Fig.3.
      • In the statistical analysis of Fig.4B, the clustering value was increased by siRILP, which should be briefly described in the manuscript.
      • In Fig.4A and B, it is possible that the knockdown efficiency of siRILP and siTMEM55B was not sufficient to observe the effect on lysosomes, and this concern should be described in the manuscript.
      • The authors should add the results of the WB experiment showing the amount of JIP4 protein in Fig.5G.
      • In Fig.5F, images of JIP4KO cells that do not express FLAG-JIP4 should be added as controls, and further quantification should be done on cells in all three conditions.
      • In Fig.6A, the total amount of JIP4 seems to change in some agent treatments, which needs to be explained.
      • In Fig.7C and D, the effect of drug treatment on the amount of ubiquitinated proteins should also be checked.
      • In Fig.8B, it is described that lysosomes are more localized in αSyn by drug treatment, but more convincing images and quantitative data are needed.

      Significance

      Although the reviewer appreciates the discovery of novel drugs to induce autophagy through regulating lysosomal positioning, the detailed action of these compounds and their superiority in the field are not clear.

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      Referee #1

      Evidence, reproducibility and clarity

      The manuscript by Date et al employed a cell model by stably expressing LGP120-mCherry and GFP-gamma-tubulin to carry out high-content screening in search of chemical compounds that enhance lysosomal clustering and autophagy. They found 6 clinically approved drugs categorized as topoisomerase II inhibitors and the benzimidazole class. They further validated these compounds by a set of well-designed experiments including autophagy flux assays and mTOR dependence. In the mechanistic study, they demonstrated the compounds induce lysosomal clustering in a JIP4-TRPML1-dependent manner. In a PD cell model, one of the compounds albendazole exhibited the effect on boosting the degradation of insoluble alpha-synuclein. The study is of interest, and the cell model and the approach generated by the authors would be transferable for future studies of other high-content imaging screening. Most of the data is clear and convincing.

      Major comments:

      1. In addition to its role in facilitating a-syn turnover by autophagy, Is the chemical protective against a-syn toxicity?
      2. Please elaborate why albendazole does not change the levels of soluble a-syn, but those of insoluble, as shown Fig 8D.
      3. Fig 6A shows that some of the compounds (Teniposide, Amsacrine) affect the levels of JIP4. Can albendazole also reduce JIP4 levels. It might be interesting to test this, as JIP4 is important for lysosomal clustering.

      Minor comments:

      The writing is good generally. Please tide up the text in a few occasions to make the expressions more formal.

      Significance

      Significance: The study generated a new approach for high-throughput screening of compounds to enhance lysosomal clustering.

      Audience: Basic and clinical research

      Expertise: Programmed cell death, neurodegenerative diseases

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      Reply to the reviewers

      #Reviewer 1 (Evidence, reproducibility and clarity):

      This manuscript by Deshmukh et al is aimed at generating chimeric antigens that can be useful for making next generation vaccines that block blood stage infection by malaria parasite. Given that there is no blood stage vaccine against malaria and available liver stage vaccine shows only limited efficacy that too only in Africa, there is dire need for having novel approaches to generate successful vaccines. In the past attempts have been made to make multivalent vaccines but have not been successful. Nevertheless, it is still a good option as single target blood-stage vaccines have failed. Authors propose to target cytoadhesion and host erythrocyte invasion. For this purpose, they have selected epitopes from PfEMP1/VarB family members, which poses a major challenge as at least 60 genes encode them and they exhibit variations which facilitate the escape from the immune system. The other two chimeras target invasion related proteins like MSPs and adhesins shed by micronemes and rhoptries, which are critical for invasion. The reported work is interesting and provides a useful approach towards developing vaccines against blood stage infection.

      We appreciate the time and effort given by our reviewer in thoroughly reading the manuscript. We are thankful for all the comments and suggestions for better shaping the article.

      Comments:

      1. __ The peptides used in InvB chimera did not show good reactivity especially when compared to VarB or MSP peptides. Please discuss the possible reasons.__

      Response: Thank you for pointing out the difference in the explanation. With chimeric InvP, we see a strong response against a few peptides of SERA-5 and RH-5, while other peptides, in comparison, have lesser antibody responses. We have now included the following statement detailing this difference with possible explanations in the revised manuscript (Page 8, Line 25 to 30).

      The IgG responses to chimeric InvP were slightly different from those to chimeric varB and MSP. The intensity of IgG to peptides of SERA-5 and RH-5 was very high in comparison to the rest of the peptides used in the construct, whereas in chimeric varB and MSP, the IgG titers were comparable between the peptides. This could be a result of antigen exposure in the cohort of 19 patient samples that we used, and may change when a larger sample size is considered.

      __ It will be interesting to determine if blocking a specific VarB/PfEMP1 alters expression of other members. Based on the data provided in Fig. 4E, can a chimera be designed which only includes PfEMP1 that are represented well in HBEC-5i population?__

      Response: We agree that observing the altered expression of PfEMP1 would be an interesting phenomenon to study. The blocking of PfEMP1 using anti-chimeric varB antibodies is a transient process in our assays (just enough to quantify the cytoadhesion). It may take multiple cycles with negative selection pressure on parasites for the switching to take place. Also, it will be interesting to design chimeras based on the HBEC-5i binding PfEMP1. We can certainly plan these as prospective future experiments.

      __ Some of the invasion related proteins like RH5 and EBA175 are not present at parasite surface, instead, secreted from rhoptries and micronemes. It will be nice to perform Western blots on condition medium and see if InvP (or even MSP and VarB) antibodies recognizes the secreted version of these proteins.__

      Response: We thank the reviewer for this valuable comment and the suggestive experiment. We will perform a western blot on spent media and probe using anti-chimeric MSP and InvP antibodies to detect the proteins selected in chimeric MSP and InvP antigens.

      __ Fig. 6E- Statistics need to be provided for inhibition at 12.3 and 25ug.__

      Response: We apologize for the missed statistics. It is now included in the figure panel.

      __ Plasmodium uses multiple ligand-receptor interaction, which could depend (e.g. EBA-glycohophorins) or operate independent (e.g. RH5-basigin) of sialic acid. While there is representation from candidates from both of these families, most studies especially growth rate assays (Fig. 6E) have been carried using 3D7 strain, which does not require sialic acid. It is possible that if similar experiments were performed using sialic acid-sensitive strains, InvP and MSP antibodies may cause greater inhibition of parasite growth, which may be worth testing.__

      Response: We are grateful for the suggestion of using a sialic acid-dependent strain. Indeed, the pathway of reinvasion chosen by the parasite may determine the growth inhibition assay (GIA) outcome. We will perform the GIA assay on the Dd2 strain and 3D7 with neuraminidase treatment (Sialic acid-dependent invasion). We will also note the difference in growth inhibition potential of chimeric antibodies in sialic-acid dependent and independent pathways.

      __ The direct effect of InvP and MSP Abs should be tested directly on host erythrocyte invasion.__

      Response: We thank the reviewer for this comment. We certainly can determine the inhibitory potential of anti-chimeric MSP and InvP antibodies through invasion assays. We will include the invasion inhibition potential of these antibodies in 3D7, Dd2, with neuraminidase treatment along with GIA data.

      Reviewer #1 Significance:

      Present study proposes novel strategies for the development of anti-malarial vaccine.

      #Reviewer 2 (Evidence, reproducibility and clarity):

      The manuscript describes the vaccine potential of unstructured P. falciparum merozoite protein fragments 25 amino acid long belonging to 3 different protein families. The work is well performed, easily reproducible and clearly described.

      We appreciate the time and effort given by our reviewer in thoroughly reading the manuscript. We are thankful for all the comments and suggestions for better shaping the article.

      Reviewer #2 (Significance):

      1. The use of protein fragments whose structure can be predicted by their sequence has been exploited in many studies for the development of vaccines or other biologicals. In this studies the authors selected 3 different families belonging to the red blood stage of the parasite. The table showing the sequences selected is not readable and should be clearly provided in the supplementary section.

      Response: We apologize for the readability of the sequences. The supplementary Table 1 has the proteins selected, the sequences taken, and the precise order for the stitching.

      In addition, polymorphic residues should be highlighted.

      Response: We thank the reviewer for pointing this out. We will analyze and compile the protein sequences in 3D conformation, highlighting polymorphic residues and the peptides selected in our study.

      In addition, it is not to mention why the authors used immune rabbit sera obtained by injection of the 3 poly-epitopes instead of obtaining by affinity chromatography antigen specific human antibodies from sera of individuals living in endemic regions which could provide a direct and clear answer whether a protective vaccine could be obtained.

      Response: We agree that the clear answer to the protective function of antibodies could have been answered using human antibodies. However, we did not have a sufficient volume of patient sera to perform affinity enrichment. The use of rabbits here was to ensure the generation of antigen-specific antibody responses in ample amounts. The patient sera in quantities available were used in ELISA, epitope mapping, and IP, followed by mass-spectrometry. The IP-MS clearly shows the presence of antibodies against the proteins taken in the generation of chimeric antigens (Supplementary Figure 1 D).

      #Reviewer 3 (Evidence, reproducibility and clarity):

      Multi-protein chimeric antigens... by: Deshmukh et al

      This article addresses an extremely important objective, the development of an effective prophylactic vaccine for Malaria. The disease continues to be widespread claiming the lives of hundreds of thousands of people annually, many of them children. Despite efforts towards producing Malaria vaccines, none thus far have been sufficiently protective or long term. As the authors point out vaccines can target the parasite per se, and possibly more attractive would be to focus on parasite derived antigens expressed on the surface of infected erythrocytes, hence targeting the Blood stage of the infection, which is most directly associated with Malaria pathogenesis. The authors propose a somewhat novel approach in which they have selected an array of short (25 amino acids) segments of Plasmodium derived proteins stitched together to produce 3 chimeric recombinant proteins as potential immunogens. Although a considerable amount of work is described, the results are not compelling in proving the efficacy or advantage of using chimeric antigens as worthy vaccine candidates for Malaria.

      Unfortunately, the rationale behind the experiments are not clearly defined which is a matter of concern. In addition, details of the work done and the technical aspects needs to better explained to fully understand how and why the target segments were selected and the chimeras produced. This review focuses first on scientific issues and then format and editing, both aspects demonstrate that the manuscript in its present form requires major changes for it to be of relevance to the field. This review focuses first on issues of substance and then format and editing, both aspects disqualify the publication of the manuscript in its present form.

      We appreciate the time and effort given by our reviewer in thoroughly reading the manuscript. We are thankful for all the comments and suggestions for better shaping the article.

      Experiments and Results:

      1. The underlying proposal claims that chimeric antigens might be advantageous in eliciting protective antibodies. The authors produced three chimeras: var, MSP and InvP. __The var chimera contains 29 segments of PfEMP1 derived from 8 alleles. The hypothesis is that by expressing 29 different segments one will produce antibodies that can better cope with the antigenic diversity of this target. Indeed, serial monoallelic expression of anyone of the 60 PfEMP1 variants of a given P. falciparum strain has been thought to mediate immune evasion. The parasite is presumed to be able to escape immune defenses, by switching and serially expressing PfEMP1 alleles. Hence, one might assume that by introducing different segments, derived from different alleles, one will gain better protection. The authors have not really tested this idea. They have produced a single chimera and tested it without controlled comparison of performance to any single segment, or for that matter compared to alternative structural domain(s) of PfEMP. This brings me to the question of how the segments were selected and why. The authors implement IEDB-AR to identify presumably preferred B-cell epitopes. The methodology relies on a number of computational methods that predict the propensity of linear segments of proteins to have, for example, secondary structures, or be surface accessible, or relatively hydrophilic or flexible, etc. IEDB-AR is a tool to assist the identification of segments (5-25 amino acids in length), that might be associated with B-cell epitopes, or at least segments comprising linear aspects of B-cell epitopes. The input is a linear sequence of an antigen, proposing linear aspects of what could be associated with B-cell epitopes. B-cell epitopes, however, are typically conformational and discontinuous. They certainly can and do contain linear segments, but even these may require 3D conformations dictated by spatial constraints imposed by the native surrounding aspects of the natural antigen. It is hard to assume that by simply stitching 29 segments, one after the other, one can provide them with the native environment for them to assume a somewhat physiologically relevant conformation. Unfortunately, the authors have not addressed the unique characteristics of the antigen they have selected. PfEMP1, for example, is a family of antigens with discrete sub-domain structures and features (DBL and CIDR for example). It would be relevant and useful to relate the segments that they chose to the natural unique domains of the antigen and how they might best present common vs variant aspects of the antigen. There are at least 30 crystal atomic structures for PfEMP1 in complex with various physiologically relevant proteins (eg ICAM etc). The authors might have considered the 3D structure of PfEMP in their analyses and at least indicated on an atomic structure where the 29 segments lie. __

      More concerning is the fact that the expression of the chimera does not produce a crisp single protein, but rather a complex of products as illustrated in the Supplement Figure 1 B. The authors simply claim that they produce the antigen for immunization of rabbits (or one rabbit?) and they collect gel-derived band(s) of what MW?? Assuming that a 25aa segment should be about 2500-2800 daltons and so 29 such segments strung together should be about 80kDa. The gel shows bands at 124kDa, and a slew of bands shorter than 71kDa. There is no mention what the expected MW should be and there is no explanation why the protein pattern contains so many bands of different sizes and what exact bands were taken for the immunogen or why.

      Response: We thank the reviewer for this comment, as it tells us the reader’s perspective on how the chimeric construct part is underexplained. We have now expanded the section on chimeric construct design, the sequences used, the functional domains they belong to in the PfEMP1 protein (Supplementary Tables 1 and 2), and the expected sizes of the proteins created. As for the B-cell epitope prediction, we have used the linear epitope prediction tool. However, we will include a 3D conformational study highlighting the placement of peptides that we have used to generate chimeric antigens.

      The sequences for chimeric constructs were synthesized commercially and confirmed using Sanger sequencing. The antigens run higher than their expected molecular weights, and we have confirmed them through western blot and mass spectrometry (Supplementary Figure 1 B and C). The chimeric varB antigen specifically shows a cleaving pattern, hence the multiple bands in western blotting (we have considered the top-most band with the highest anti-his intensity). After these confirmations, the antigens were independently injected in rabbits to generate antibodies.

      Similar considerations can be made regarding the selection of the segments for the two other chimeras, although they seem to produce a single polypeptide.

      Response: The antigens were confirmed using Sanger sequencing, expression using anti-his western blot, and proteins were confirmed using mass spectrometry for all three chimeric constructs (Supplementary Figure 1 B and C).

      If the point was to test a "chimera" modality as an improved vaccine, it would have been more useful to focus on one chimera and carefully characterize it and compare it to its components used separately.

      Response: The idea of chimera arises from the fact that individual proteins/components are insufficient to generate optimal responses. The proteins considered in our study have already been validated in the field (as separate components) and show that the efficacy observed was sub-optimal. Since our rationale is to include multiple proteins to tackle the redundancy and parasite virulence, we have focused on generating three chimeric constructs covering the entire blood stage of Plasmodium falciparum. Our objective is to demonstrate that a multi-protein, multi-factorial vaccine, as a proof of concept, works better in tackling malaria. We believe that in proving so, a comparison of chimera with their individual components is an unnecessary and economically unviable.

      The authors devote much effort to the fluidics system and their assay. This might warrant a paper dedicated to the methodology they have developed.

      Response: The Plasmodium virulence genes are extensively studied for their interactions with human endothelial receptors. Unfortunately, these studies fail to take human physiological conditions into account. We wanted to test our anti-chimeric varB antibodies in the best mimicking environment possible. Hence, the efforts were devoted to developing, standardizing, and quantifying the fluidic cytoadherence system. We thank the reviewer for their kind words of encouragement on our methodology.

      Format and Editing:

      1. The manuscript is very poorly written with multiple errors throughout. The authors use abbreviations that are not defined, eg iRBC (pg 5 line 22) or sometimes incorrectly defined, eg MSP ("merozoite-specific proteins - pg 6 line 18).

      Response: We apologize for the abbreviation error. The abbreviation for iRBC is defined in the introduction section (page no 4, Line 15); hence, it is not redefined on page 5, line 22. We have corrected merozoite-specific proteins on page 6, line 18.

      The Figures are of low resolution to the extent that they can not be read (for example Figure 3 pg 34). Figure 1 is somewhat useless and misleading. In Fig1 C - the diagram illustrates 5 hypothetical chimeras where in fact only three were produced. There really is no detail or explanation as to how the chimeras were produced.

      Response: We apologize for the low resolution of the images. We have now improved the image quality. Figure 1C represents the idea of designing the construct, not the number of chimeras we generated. We apologize for this confusion and have explicitly mentioned this in the figure panel for Figure 1C. As for the design and generation of chimeric antigens, we understand that the materials and methods section is underexplained, and we have now expanded on it with all details included.

      In the construction of the chimeras there is no mention as to whether short linkers were introduced between the segments or not. What was the expected weight of the chimera? Was the order of segments random or precise and consistent? Were the constructs sequence validated in addition to the MassSpec?

      Response: We understand that the section on the chimeric construct is underexplained for the readers, and we thank the reviewer for pointing it out. We have now expanded the section on chimeric antigen design and included the details. Chimera was tested with GSGSGS linkers and without linkers for expression. The final antigen injected in rabbits was serially attached peptides without linkers. The segments stitched were in precise order, as mentioned in Supplementary Sheet 1. The construct was commercially synthesized and sequence validated along with the anti-his western blot and mass spectrometry analysis.

      The figures of the Supplement are not numbered.

      Response: We thank the reviewer for pointing this out. The figures are now numbered.

      Note that the headings in Supplement Figure 1 B and C have overlapping text.

      Response: Thank you for pointing this out. We have now rearranged the supplementary figures 1B, and 1C.

      Most disturbing is that multiple references that are incomplete. For example: in References 15, 16, 25, 26, 27 there is no indication of the Journal.

      Response: We apologize for the mistakes in referencing. These references did not have full citations in Endnote. We have now manually checked all the references and corrected the incomplete formats of the references.

      The authors mention reference 13 [2006] in claiming that the antibodies can be protective, and then support this by referring to refs 14, 15 and 16 published in 1961, 1963 and 1962 respectively. Although, old articles can be useful, but the authors should attempt to provide current proof of such basic claims.

      Response: We thank the reviewer for pointing this out. We have now separated these two statements and not mentioned the latter as a support to the former. As for references 14, 15, and 16, these were the early studies in the field that show the protective nature of antibodies through the passive immunization process and are foundations for the idea of blood stage vaccination. Current proofs of antibodies against blood-stage antigens are included for blood-stage vaccine candidates.

      Reviewer #3 (Significance):

      The goal of the study is very important.

      The hypothesis that a chimeric presentation of select peptides could be advantageous was not rigorously tested nor well controlled in a meaningful evaluation and thus no conclusion can be made. There are no comparative analyses to test their hypothesis.

      The method for selection of epitope segments is not well justified. There is little attempt to provide rationale or description of the segments chosen and how they fit within the antigens, thus justifying segments over multiple antigens.

      The grammatical errors, lack of clarity accompanied by little attention to style and readability render the manuscript quite illegible.

      There is no excuse for so many errors in the references.

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      Referee #3

      Evidence, reproducibility and clarity

      Multi-protein chimeric antigens... by: Deshmukh et al

      This article addresses an extremely important objective, the development of an effective prophylactic vaccine for Malaria. The disease continues to be widespread claiming the lives of hundreds of thousands of people annually, many of them children. Despite efforts towards producing Malaria vaccines, none thus far have been sufficiently protective or long term. As the authors point out vaccines can target the parasite per se, and possibly more attractive would be to focus on parasite derived antigens expressed on the surface of infected erythrocytes, hence targeting the Blood stage of the infection, which is most directly associated with Malaria pathogenesis. The authors propose a somewhat novel approach in which they have selected an array of short (25 amino acids) segments of Plasmodium derived proteins stitched together to produce 3 chimeric recombinant proteins as potential immunogens. Although a considerable amount of work is described, the results are not compelling in proving the efficacy or advantage of using chimeric antigens as worthy vaccine candidates for Malaria.

      Unfortunately, the rationale behind the experiments are not clearly defined which is a matter of concern. In addition, details of the work done and the technical aspects needs to better explained to fully understand how and why the target segments were selected and the chimeras produced. This review focuses first on scientific issues and then format and editing, both aspects demonstrate that the manuscript in its present form requires major changes for it to be of relevance to the field. This review focuses first on issues of substance and then format and editing, both aspects disqualify the publication of the manuscript in its present form.

      Experiments and Results:

      The underlying proposal claims that chimeric antigens might be advantageous in eliciting protective antibodies. The authors produced three chimeras: var, MSP and InvP.

      The var chimera contains 29 segments of PfEMP1 derived from 8 alleles. The hypothesis is that by expressing 29 different segments one will produce antibodies that can better cope with the antigenic diversity of this target. Indeed, serial monoallelic expression of anyone of the 60 PfEMP1 variants of a given P. falciparum strain has been thought to mediate immune evasion. The parasite is presumed to be able to escape immune defenses, by switching and serially expressing PfEMP1 alleles. Hence, one might assume that by introducing different segments, derived from different alleles, one will gain better protection. The authors have not really tested this idea. They have produced a single chimera and tested it without controlled comparison of performance to any single segment, or for that matter compared to alternative structural domain(s) of PfEMP. This brings me to the question of how the segments were selected and why. The authors implement IEDB-AR to identify presumably preferred B-cell epitopes. The methodology relies on a number of computational methods that predict the propensity of linear segments of proteins to have, for example, secondary structures, or be surface accessible, or relatively hydrophilic or flexible, etc. IEDB-AR is a tool to assist the identification of segments (5-25 amino acids in length), that might be associated with B-cell epitopes, or at least segments comprising linear aspects of B-cell epitopes. The input is a linear sequence of an antigen, proposing linear aspects of what could be associated with B-cell epitopes. B-cell epitopes, however, are typically conformational and discontinuous. They certainly can and do contain linear segments, but even these may require 3D conformations dictated by spatial constraints imposed by the native surrounding aspects of the natural antigen. It is hard to assume that by simply stitching 29 segments, one after the other, one can provide them with the native environment for them to assume a somewhat physiologically relevant conformation. Unfortunately, the authors have not addressed the unique characteristics of the antigen they have selected. PfEMP1, for example, is a family of antigens with discrete sub-domain structures and features (DBL and CIDR for example). It would be relevant and useful to relate the segments that they chose to the natural unique domains of the antigen and how they might best present common vs variant aspects of the antigen. There are at least 30 crystal atomic structures for PfEMP1 in complex with various physiologically relevant proteins (eg ICAM etc). The authors might have considered the 3D structure of PfEMP in their analyses and at least indicated on an atomic structure where the 29 segments lie. More concerning is the fact that the expression of the chimera does not produce a crisp single protein, but rather a complex of products as illustrated in the Supplement Figure 1 B. The authors simply claim that they produce the antigen for immunization of rabbits (or one rabbit?) and they collect gel-derived band(s) of what MW?? Assuming that a 25aa segment should be about 2500-2800 daltons and so 29 such segments strung together should be about 80kDa. The gel shows bands at 124kDa, and a slew of bands shorter than 71kDa. There is no mention what the expected MW should be and there is no explanation why the protein pattern contains so many bands of different sizes and what exact bands were taken for the immunogen or why.

      Similar considerations can be made regarding the selection of the segments for the two other chimeras, although they seem to produce a single polypeptide.

      If the point was to test a "chimera" modality as an improved vaccine, it would have been more useful to focus on one chimera and carefully characterize it and compare it to its components used separately. The authors devote much effort to the fluidics system and their assay. This might warrant a paper dedicated to the methodology they have developed.

      Format and Editing:

      The manuscript is very poorly written with multiple errors throughout. The authors use abbreviations that are not defined, eg iRBC (pg 5 line 22) or sometimes incorrectly defined, eg MSP ("merozoite-specific proteins - pg 6 line 18).

      The Figures are of low resolution to the extent that they can not be read (for example Figure 3 pg 34). Figure 1 is somewhat useless and misleading. In Fig1 C - the diagram illustrates 5 hypothetical chimeras where in fact only three were produced. There really is no detail or explanation as to how the chimeras were produced.

      In the construction of the chimeras there is no mention as to whether short linkers were introduced between the segments or not. What was the expected weight of the chimera? Was the order of segments random or precise and consistent? Were the constructs sequence validated in addition to the MassSpec?

      The figures of the Supplement are not numbered.

      Note that the headings in Supplement Figure 1 B and C have overlapping text.

      Most disturbing is that multiple references that are incomplete. For example: in References 15, 16, 25, 26, 27 there is no indication of the Journal.

      The authors mention reference 13 [2006] in claiming that the antibodies can be protective, and then support this by referring to refs 14, 15 and 16 published in 1961, 1963 and 1962 respectively. Although, old articles can be useful, but the authors should attempt to provide current proof of such basic claims.

      Significance

      The goal of the study is very important.

      The hypothesis that a chimeric presentation of select peptides could be advantageous was not rigorously tested nor well controlled in a meaningful evaluation and thus no conclusion can be made. There are no comparative analyses to test their hypothesis.

      The method for selection of epitope segments is not well justified. There is little attempt to provide rationale or description of the segments chosen and how they fit within the antigens, thus justifying segments over multiple antigens.

      The grammatical errors, lack of clarity accompanied by little attention to style and readability render the manuscript quite illegible.

      There is no excuse for so many errors in the references.

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      Referee #2

      Evidence, reproducibility and clarity

      The manuscript describes the vaccine potential of unstructured P. falciparum merozoite protein fragments 25 amino acid long belonging to 3 different protein families. The work is well performed, easily reproducible and clearly described.

      Referees cross-commenting

      The polymorphic residues should be highlighted in the supplementary figure.

      Significance

      The use of protein fragments whose structure can be predicted by their sequence has been exploited in many studies for the development of vaccines or other biologicals. In this studies the authors selected 3 different families belonging to the red blood stage of the parasite. The table showing the sequences selected is not readable and should be clearly provided in the supplementary section. In addition, polymorphic residues should be highlighted. In addition, it is not to mention why the authors used immune rabbit sera obtained by injection of the 3 poly-epitopes instead of obtaining by affinity chromatography antigen specific human antibodies from sera of individuals living in endemic regions which could provide a direct and clear answer whether a protective vaccine could be obtained.

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      Referee #1

      Evidence, reproducibility and clarity

      This manuscript by Deshmukh et al is aimed at generating chimeric antigens that can be useful for making next generation vaccines that block blood stage infection by malaria parasite. Given that there is no blood stage vaccine against malaria and available liver stage vaccine shows only limited efficacy that too only in Africa, there is dire need for having novel approaches to generate successful vaccines. In the past attempts have been made to make multivalent vaccines but have not been successful. Nevertheless, it is still a good option as single target blood-stage vaccines have failed. Authors propose to target cytoadhesion and host erythrocyte invasion. For this purpose, they have selected epitopes from PfEMP1/VarB family members, which poses a major challenge as at least 60 genes encode them and they exhibit variations which facilitate the escape from the immune system. The other two chimeras target invasion related proteins like MSPs and adhesins shed by micronemes and rhoptries, which are critical for invasion. The reported work is interesting and provides a useful approach towards developing vaccines against blood stage infection.

      Comments:

      1. The peptides used in InvB chimera did not show good reactivity especially when compared to VarB or MSP peptides. Please discuss the possible reasons.
      2. It will be interesting to determine if blocking a specific VarB/PfEMP1 alters expression of other members. Based on the data provided in Fig. 4E, can a chimera be designed which only includes PfEMP1 that are represented well in HBEC-5i population?
      3. Some of the invasion related proteins like RH5 and EBA175 are not present at parasite surface, instead, secreted from rhoptries and micronemes. It will be nice to perform Western blots on condition medium and see if InvP (or even MSP and VarB) antibodies recognizes the secreted version of these proteins.
      4. Fig. 6E- Statistics need to be provided for inhibition at 12.3 and 25ug.
      5. Plasmodium uses multiple ligand-receptor interaction, which could depend (e.g. EBA-glycohophorins) or operate independent (e.g. RH5-basigin) of sialic acid. While there is representation from candidates from both of these families, most studies especially growth rate assays (Fig. 6E) have been carried using 3D7 strain, which does not require sialic acid. It is possible that if similar experiments were performed using sialic acid-sensitive strains, InvP and MSP antibodies may cause greater inhibition of parasite growth, which may be worth testing.
      6. The direct effect of InvP and MSP Abs should be tested directly on host erythrocyte invasion.

      Significance

      Present study proposes novel strategies for the development of anti-malarial vaccine.

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      Reply to the reviewers

      We thank the reviewers for their kind works and helpful insights and suggestions. Below, we have pasted the reviews (in italics), with our responses:


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

      The study provides insights into how polyploidization via endomitosis may arise in human hepatocytes by studying fetal liver cell line-derived organoids. Using live cell imaging and LSM microscopy, binculeation was consistently observed in two independent cell line systems, at frequencies seen in human liver and sensitive to pharmacological inhibition (GSK3i) and genetic manipulation (E2F7 & E2F8 editing). The findings presented are in line with earlier data, largely gathered studying rodents. The data is convincing and robust indicating that these systems can be used to study cause and consequences of polyploidy in human hepatocytes.

      1. While the authors do suggest that they provide a mechanisms how polyploidy is initiated in human hepatocytes undergoing endomitosis, ie. loss of membrane association of membrane-anchoring proteins at the midbody (e.g. Anillin, RacGAP1), I do feel that the data provided is rather descriptive and does not address a particular mechanism that may account for loss of membrane anchoring. As such, the title is making a too strong point, as, in my point of view, it associates with loss of membrane anchorage, but may not drive endomitosis. Whether this is a "passive" process in response to changes in physical forces and tension, or regulated via signalling intermediates to initiate regression of the cleavage furrow is not addressed experimentally (mislocalizing these proteins on a larger scale). Discussion seems warranted.

      We agree with the reviewer that our mechanistic insights into the molecular mechanisms of endomitosis are limited, and we cannot currently prove that the loss of membrane-anchoring drives endomitosis. We have therefore toned down this conclusion and changed the title to “Binucleated human hepatocytes arise through late cytokinetic regression during endomitosis M phase”. Furthermore, we have expanded the Discussion to reflect on the gaps in knowledge and speculate about possible molecular mechanisms of endomitosis, see pages 12-16 (in particular, lines 404-423, lines 433-443, and 445-472.

      I do not see the need for additional experiments, as I believe the data is robust and introduces an interesting new model where the role of ploidy can be studied in human hepatocytes ex vivo. However, if the authors wish to extend their studies and document further similarities with pathways engaged in rodents, some E2F7/8 targets relevant for ploidy control such as Anillin or PIDDosome components, or, maybe MDM2 processing for p53 activation, could be tested in wt and E2F mutant cell lines.

      Unfortunately, we have not been able to look at E2F7/8 targets and their expression in E2F mutant Hep-Orgs. We performed qPCRs for some cytokinesis regulators such as Ect2, RacGap1 and Mklp1 in Hep-Orgs, however these genes are so lowly expressed that we can hardly detect them. This is likely because these transcripts are only expressed in a short period of the cell cycle during S/G2 phase, whereas the vast majority of cells in Hep-Orgs are in G1. Therefore, differences in gene expression are very difficult (if not impossible) to detect by qPCR. We also tried to perform single molecule FISH on Hep-Orgs, which would allow us to quantify lowly expressed transcripts in single cells, however despite that the smFISH stainings work well on cholangiocyte organoids and intestinal organoids, we could not get good signals in Hep-Orgs. Taken together, we are unable at this point to look into downstream targets of E2F7/8.

      A minor suggestion is to clarify the term M-CDK activity in the introduction, as it may not be fully intuitive to all readers; similarly, ploidy reversal is still controversial in the field, but it is stated as a given fact.

      Thank you for these suggestions, we have clarified the term M-CDK on page 3, lines 60-61, and have rephrased the sentence on ploidy reversal on page 3, lines 81-82.

      Reviewer #1 (Significance (Required)):

      Polyploidy at the cellular and nuclear level is a key feature of hepatocytes albeit the physiological significance of the process is not entirely clear. Increased ploidy has been linked to cancer resistance in the liver, but may pose a threat to hepatocyte survival under conditions of repeated compensatory proliferation cycles. Curiously, during normal regeneration after single surgical intervention liver regeneration is not compromised, even though it may recover faster starting when starting from higher ploidy levels. Mechanistically, most data has been generates studying rodents where it is documented that the proliferation behaviour changes around the time of weaning in mice when hepatocytes start to fail cytokinesis and undergo endomitosis, leading to cellular and nuclear polyploidy. In rodents, insulin signalling / AKT appears involved as is the E2F network and p53, activated by the caspase-2-PIDDosome.

      The model system introduced here will allow mechanistic studies in human organoids and help to increase our understanding of this process in steady state and under conditions of stress.


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

      Summary:

      Polyploid cells arise within various human tissues by multiple different mechanisms. Here, Darmasaputra et al present a study of one such mechanism, endomitosis, in liver cells using fetal-derived human hepatocyte organoids. In this model, they demonstrate that binucleated cells arise through the late regression of the cytokinetic furrow prior to abscission. They identify a rare event in cytokinetic cells - loss of midbody association with the plasma membrane - that could explain the cytokinesis failure observed in a proportion of these cells. Finally, they show that loss of Wnt signalling increases the number of binucleation events in a manner that depends on E2F7 and E2F8, similar to what has been observed in murine hepatocytes.

      Major comments:

      This is a compelling and well-presented study. The data presented are high quality, the experiments are well described and controlled and the conclusions are convincing. I am particularly impressed by the technical effort that the authors must have put into obtaining high quality live and IF images of dividing cells within organoids and their careful documentation of what are very rare mitotic events. In addition, the manuscript is extremely well written and I found it a pleasure to read.

      1. I do not think that there are additional experiments that are essential to justify the conclusions of the paper. However, I do have suggestions that I think would strengthen this work and increase its significance. As is, the authors present findings in two different areas: the documentation of cytokinesis failure in hepatocyte organoids and the role of Wnt and E2F7/8 on binucleation. It would be really nice if the two parts could be linked. For example, the authors could examine cell divisions in the organoids without Wnt either live or fixed and show that they have a higher proportion of cells undergoing cytokinetic regression or with membrane-midbody attachment defects. Alternatively, they could look at whether the expression levels of key cytokinetic genes are changed in the Wnt and E2F7/8 organoids. As I said, these experiments are not required for or the publication of this work and I will leave it up to the authors to decide if they have the time or capacity to add additional data.

      We thank the reviewer for this suggestion. Unfortunately, despite substantial effort, we have been unable to perform successful live imaging of Hep-Orgs under CHIR99021 removal conditions: these organoids become very sensitive to live imaging and they also proliferate very slowly. We have tried to look at the expression of cytokinetic genes by qPCR, however these experiments were inconclusive (see also our response to reviewer #1, point 2). Thus, we cannot rule out that the increase in binucleation that we see upon CHIR99021 removal is not due to increased endomitosis, but rather occurs independently, for example by an increased survival rate of binucleated cells upon WNT removal. We have now discussed this issue and explained the limitations of our study in the discussion, pages 14-15, lines 451-460.

      Finally, before publication, the authors should discuss further the mechanisms by which loss of membrane attachment during cytokinesis could occur - there is quite a lot of literature in this area on the role of RacGAP1 and Ect2 in membrane attachment that is not discussed, particularly from the lab of Mark Pentronczki (eg Kotynkova 2026 PMID: 27926870, Lekmotsev PMID: 23235882). It's surprising that the authors haven't mentioned (or looked at) Ect2 at all, especially since Ect2 levels have been shown to control polyploidy in cardiomyocytes (Liu 2019 PMID: 31597755). This at least warrants some discussion.

      We thank the reviewer for pointing us to these articles. We have elaborated the discussion to include the work on rodent and human cardiomyocytes, and to explain why we think that there is no defect in ECT2 and RhoA signaling in human hepatocytes undergoing endomitosis, see pages 13-14, 404-423 and 433-443.

      Minor comments:

      Table 1 would be more striking as a graphical representation. I appreciate that the n numbers in the regressed cells means that statistical comparisons is not possible, but some kind of colour coding or graph would make this part clearer

      We agree that Table 1 was difficult to read – we now show the data schematically in a new figure, Fig.4.

      It's not clear what the difference between Hep-Org 1 and Hep-Org 2 are. Are these from different donors?

      Indeed Hep-Org1 and Hep-Org2 are from different donors. We have clarified this in the text, see page 5, lines 131-133.

      Reviewer #2 (Significance (Required)):

      This study is an important technical development in that it reports a new system to study in depth cell biology of liver endomitosis in non-transformed and, crucially, human 3D hepatocyte organoids. The findings reported using this system are potentially interesting although they could be further developed if they were mechanistically linked together (see major comments). This work is likely to be highly interesting to scientists studying cell division, cytokinesis and hepatocyte biology. It also has wider implications for liver biology and particularly liver regeneration. Additionally, given the role of polyploidisation in many different tissues, it will likely be of interest to scientists studying polyploidy and endomitosis more generally.

      My area of expertise is in cytokinesis and cell division in general, although not specifically in hepatocytes. I am not an expert in organoids.


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

      In this manuscript, Darmasaputra and colleagues took advantage of human hepatocyte organoids (Hep-Org) to investigate the formation of binucleated cells that naturally occurs in liver. So far, the mechanism of hepatocyte binucleation has been studied in rodents, where binucleated hepatocytes arise upon weaning through an insulin/akt pathway that inhibits furrow contraction in a fraction of cells (Ref. 21, 22). In addition, it is known that E2F7 and E2F8 downstream of the Wnt signaling repress the expression in mouse hepatocytes of several key cytokinetic proteins (AuroraB, Mklp1, Ect2, Racgap1) and thereby promote binucleation (Ref. 23).

      Advances:

      As seen in vivo, the authors first show that a fraction (5-15%) of cells are binucleated in two independently derived human Hep-Orgs. Live cell imaging reveals that binucleation is not due to furrow ingression defects after anaphase but rather arises from post-furrowing intercellular bridge regression. Fixed data suggest that the cytokinetic midbody formed normally but lost its anchorage to the bridge membrane. Activation of the Wnt signaling resulted in a modest but significant increase in the proportion of binucleated cells (4.5 to Major comments

      1. An outstanding question is whether human Hep-Orgs represent a bona-fide model to study the process of human liver binucleation. The absence of cholangiocytes, vascularization, other cell types and physiological hormones etc. might impact on the mechanism of binucleation, which is the main focus of this study. Since the mechanism of binucleation in human Hep-Orgs appears radically different from what has been reported in vivo in rodents, the authors should reproduce the lack of furrow ingression in mouse Hep-Orgs (that they were able to generate in Ref. 44). This could be done in fixed cells as in Fig. 3. Alternatively, they could use live cell imaging and chemical dyes such as SiR-Tubulin and Cell Mask to label microtubules and the plasma membrane, respectively, without the need of creating genome-edited reporter lines.

      The mechanism of endomitosis that we observe in human hepatocyte organoids is indeed different from what has been observed in mouse hepatocytes. Unfortunately, mouse Hep-Orgs are more difficult to generate as they require a two-step perfusion protocol from live mice (described in Hu et al., 2018). Additionally, mouse Hep-Orgs do not survive freezing, so to be able to perform the suggested experiments, we would need to generate new mouse Hep-Org lines. As our collaborators are currently not performing any experiments with mouse livers, we would need to request an ethical permit to generate these organoids, which would take several months. We have seriously considered this option, however due to the substantial investment in time and resources, we feel these experiments would be more suited for a follow-up study.

      To nonetheless better clarify the differences between what has been observed in rodents, and what we see in the Hep-Orgs, we have added a paragraph in the discussion, see pages 14-15 lines 433-460.

      The videos acquired in Fig. 2 contain much more information than presented. The authors should measure the rate of furrow ingression, the extend of spindle elongation, the time of MT severing and the time of furrow/bridge regression after cytokinesis onset. All these parameters are important since spindle elongation and furrow ingression are altered in rodents. Is this also the case in human Hep-orgs? Furthermore, the spindle seems very different (bent bridges) in endomitotic compared to canonical cytokinesis (Fig. 2A). Finally, the authors should provide more time points during the time of furrow regression to better show how this phenomenon occurs. It seems, based on fixed images, that the midbody stays attached to the plasma yhmembrane in an asymmetric manner (i.e. does not fully detach, contrary to what is stated in the text). 3D reconstructions in fixed cells and a further characterization of the movies would clarify this point.

      We thank the reviewer for this suggestion. Although there are some technical limitations that pose some restrictions (explained below), we have extended our analyses where possible. In our live imaging, we use 5-minute time intervals with 4 mm z-slices, which allows a delicate balance between having enough frames in M phase, and imaging for at least 48 hours, which is required to catch enough divisions. We are unable to image with smaller time intervals or smaller z-slices, as this leads to phototoxicity. Nonetheless, using these settings, we can get an indication of the rate of furrow ingression, time of severing and the time of furrow regression:

      • We find that the time of furrowing onset and the rate of furrow ingression is very similar between canonical M phases and endomitosis M phases: we have now added this data in the results section, page 7, lines 192-199 and Fig. 2D.
      • The time of cytokinetic regression is more variable between endomitoses events, and can range between 30 minutes and 2,5 hours. We have also added this information to page 7, lines 199-202and Fig. 2E
      • The time of MT severing is similar between endomitosis M phases, as we show in Fig. 2C
      • Unfortunately, we cannot accurately measure the extent of spindle elongation, as the divisions occur in 3D and our Z resolution is not good enough. Regarding the observation that the spindle looks different in the endomitosis example in Fig. 2A: we have quantified how often we observe bent midzones in endomitosis versus canonical M phases, and this occurs in 60% of canonical (n=12/20) and 83% of endomitosis M phases (n=15/18). We have now added this information in the results section, page 6, lines 1862-185.
      • We have quantified how often we see the midbody remaining attached to one side of the plasma membrane versus fully detaching: we find that in 6 out of 9 late stage endomitotic regressions, the membrane is detached from both sides, and in 3 out of 9, it remains attached to one side. We have added this information to the results section, page 8 line 249-251.

        DAPI staining is not sensitive enough to detect thin chromatin bridges. To rule out that post-furrowing regression is not merely due to the present of DNA bridges, the authors should confirm their results with LAP2b staining (see PMID 19203582).

      To exclude the presence of ultrafine DNA bridges during anaphase, we have performed a staining for RIF1, a factor that localizes to ultrafine DNA bridges in anaphase and is required for their resolution (Hengeveld et al, 2015, PMID: 26256213). In early anaphase, we find many RIF1-positive thread-like structures, as has been described before in other non-transformed and non-stressed cells. However, in late anaphase and telophase, we never observe these fibers (n=57/57), suggesting that they are fully resolved and are not the cause of cytokinetic regression. We have added this data to the results section, see page 8, lines 226-234, and Fig. S1.

      The authors shows that binucleation results from defective anchorage of the bridge membrane to the midbody, but the molecular mechanism remains elusive and should be further probed. In Fig. 3, there is no obvious changes in the investigated markers. Are the intensities of RACGAP1, Anillin, CIT-K reduced in regressing cells? Are ECT2, activated (phospho) Myosin II, CEP55/ESCRT-III, (activated) AuroraB and MKLP1 normally localized/concentrated? ECT2, AuroraB and MKLP1 are regulated by E2F7/8 (Ref. 23) and AuroraB inactivation after bridge formation leads to late regression (PMID 19203582).

      We agree with the reviewer that the molecular mechanism by which midbodies lose their attachment to the membrane is currently unclear. We do not see any clear differences in the intensities of RACGAP1, Anillin, or CIT-K in cells undergoing endomitotic regression. We also do not expect large differences in localization or abundancies of ECT2, AuroraB or MKLP1, because if this were the case, you would expect differences in early cytokinesis in endomitosis, such as a delay or a slower rate of furrow ingression. We did perform additional IF experiments to investigate the localization of SEPT9, a septin that is expressed in human hepatocytes and that has essential functions in membrane anchorage during cytokinesis. Although we find that SEPT9 exhibits more variable localizations than RACGAP1, Anillin, and CIT-K, we find that in the majority of endomitotic regressions, it is also absent from the regressed membrane (n=5/7 cells). We have added this data to the results section on page 9, and in the figures Fig. 3C and Fig.4C.

      The results of Fig. 4F indicate that the increased proportion of binucleated cells upon CHIR99021 removal depends on E2F7/8. Without live cell imaging (or FISH experiments) the authors cannot conclude that conclude that the increase in endomitosis is dependent on E2F7/8. A decrease in binucleation could indeed not imply a reduced occurrence of endomitosis. For instance, it is possible that E2F7/8 KO induces the formation of mononucleated 4n cells due to early mitotic failure. This issue should be clarified.

      The reviewer raises an important point. Unfortunately, we were unable to generate E2F7/8 KO lines containing fluorescent nuclear and membrane markers, which would allow us to perform live-imaging and confirm that these organoids perform less endomitosis. As an alternative, we tried to use SiR-Tubulin dyes for live imaging, but even at very low concentrations these dyes are toxic for the organoids. To exclude the possibility that E2F7/8 KO induces the formation of mononucleated 4n cells, we have measured the DNA content in wildtype, E2F7 and E2F8 lines, and found that the distribution of ploidies is very similar between these lines, both in normal growth conditions as well as upon removal of CHIR99021 (see the new supplemental figure, Fig. S3). We thus think it is unlikely that E2F7/8 KO induces the formation of mononucleated 4n, however it remains possible that the differences in percentage of binucleated cells arise independently of endomitosis. We have now toned down our conclusions on the function of WNT signaling and E2F7/8 in endomitosis, and discussed alternative explanations for our findings in the discussion, see page 14, lines 451-460.

      Binucleation increases with age both in humans and rodents. Could this feature be mimicked in the human Hep-Org by leaving the organoids longer in culture? (optional but would reinforce the value of the model).

      We do not see an increase in binucleation percentages in organoids that are kept longer in cultures, and we have now also tested the effect of growing the organoids in a “differentiation medium”, which was previously described to give rise to more mature hepatocyte gene expression (Hu et al. 2018), however we see no significant differences in the percentages of binucleated cells per organoid. We have now included this data, as well as our analyses of the effect of insulin in the growth medium (see our response to point 12 below) in the results section on page 11 lines 341-353 and we further discuss this point in the Discussion, pages 12-13, lines 389-397.

      Minor comments

      The results of Table 1 are based on very few fixed cells (3 to 6). The authors should consider increasing the number of regressing cells.

      We are aware that the number of endomitotic regressions is very low. Unfortunately, it is extremely challenging to catch these events by IF: cells in Hep-Orgs cycle very slowly (they divide once every ±50 hours), and thus very few cells are in M phase at any given moment (only 1 or 2 cells per organoid) – the chance that this cell is then also in telophase is even lower, and then only ± 5% of the telophase are actually undergoing endomitosis. Due to technical limitations of the organoid IF staining protocol, it is not trivial to scale up these experiments, making it very difficult to find more than 3-5 endomitotic regressions per condition. Despite the low numbers of endomitotic regressions that we have identified, we find that RacGAP1, Anillin and CIT-K localize in a very similar manner in cells undergoing endomitosis. For SEPT9, we see a little bit more variation in the localizations, but also here the majority of cells in undergoing endomitosis have lost SEPT9 membrane association on the regressed membrane (see Fig. 4C).

      Is WNT signaling modified by E2F7/8 mutations? To conclude that "WNT signaling inhibits binucleation in an E2F7/8-dependent manner", the authors should check that E2F7/8 KO does not impair the increase of WNT signaling upon CHIR99021 removal.

      We had not thought of this option, but it is indeed possible that E2F7/8 influences the ability of cells to respond to CHIR99021 removal. WNT regulators are not known to be targets of E2F7 or E2F8 in mice (see PMIDs: 22180533, 18194653, and 23064264), however as we have not analyzed the gene expression changes in E2F7 or E2F8 mutant organoids, we cannot exclude the possibility that CHIR99021 has different effects in E2F7/E2F8 knock-out cells. We now discuss this possibility in the discussion, page 15, lines 459-460.

      Please provide movies of the cells presented in Fig. 2A.

      We have included movies of these cells, see Supplemental Movie 1 and Supplemental Movie 2.

      1. Removal of CHIR99021 induces major shape changes and lumen formation (rather than "exhibited some morphological changes" as stated). Could the author speculate on this?

      WNT signaling is likely important for many aspects of hepatocyte growth and differentiation, and it is possible that upon CHIR99021 removal, Hep-Orgs are starting to differentiate and become more secretory, which would explain why they start forming larger lumens. We now discuss this in more detail in the final part of the results section, see page 11 lines 341-353, and in the discussion, page 15 lines 462-472.

      1. Fig. 4: Why do the authors use the cell line-1 that has the lowest level of binucleation in this experiment? Would the results be the same in cell line 2? (optional)

      We perform most experiments in Hep-Org line 1 because this line is easier to maintain in culture, and we have been unable to generate CRISPR knock-outs in Hep-Org line 2.

      1. Would insulin increase the proportion of binucleated cells, as in rodents? (optional)

      We have tested this, but do not see a difference in the percentage of binucleated cells when we either increase or decrease the concentration of insulin in the growth medium. We have now added this data in the results section, see page 11, lines 347-350 and Fig. 5J.

      Reviewer #3 (Significance (Required)):

      Strengths and limitations:

      The manuscript is well written, easy to follow, and the quality of the data is overall high. A clear strength of this study is the use of state-of-the-art human hepatocyte organoids and genome editing (to generate reporter lines and to KO E2F7/8). This allows the authors to address the mechanism of binucleation in a human context. Interestingly, it revealed both similarities (e.g. E2F7/8 depends for binucleation) and striking mechanistic differences (e.g. post-furrowing regression) between rodent and human systems. The study is rather descriptive -which is fine- but deeper mechanistic insights would strengthen the conclusions of the manuscript. For instance, "our results identify how human hepatocytes inhibit cell division in endomitosis" appears as an overstatement since the molecular reason of midbody anchorage defects remains elusive.

      We thank the reviewer for their kind words. Unfortunately, we have been unable to gain deeper mechanistic insights into the molecular mechanism of membrane regression in endomitosis. We have therefore toned down our conclusions, see the new concluding sentence in the abstract, page 2, lines 35-36.

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      Referee #3

      Evidence, reproducibility and clarity

      In this manuscript, Darmasaputra and colleagues took advantage of human hepatocyte organoids (Hep-Org) to investigate the formation of binucleated cells that naturally occurs in liver. So far, the mechanism of hepatocyte binucleation has been studied in rodents, where binucleated hepatocytes arise upon weaning through an insulin/akt pathway that inhibits furrow contraction in a fraction of cells (Ref. 21, 22). In addition, it is known that E2F7 and E2F8 downstream of the Wnt signaling repress the expression in mouse hepatocytes of several key cytokinetic proteins (AuroraB, Mklp1, Ect2, Racgap1) and thereby promote binucleation (Ref. 23).

      Advances:

      As seen in vivo, the authors first show that a fraction (5-15%) of cells are binucleated in two independently derived human Hep-Orgs. Live cell imaging reveals that binucleation is not due to furrow ingression defects after anaphase but rather arises from post-furrowing intercellular bridge regression. Fixed data suggest that the cytokinetic midbody formed normally but lost its anchorage to the bridge membrane. Activation of the Wnt signaling resulted in a modest but significant increase in the proportion of binucleated cells (4.5 to <8% or 3 to <6% depending on the subfigures). This increase depended on the presence of E2F7 and E2F8. This study represents the first description of binucleation in a human organoid context.

      Major comments

      1. An outstanding question is whether human Hep-Orgs represent a bona-fide model to study the process of human liver binucleation. The absence of cholangiocytes, vascularization, other cell types and physiological hormones etc. might impact on the mechanism of binucleation, which is the main focus of this study. Since the mechanism of binucleation in human Hep-Orgs appears radically different from what has been reported in vivo in rodents, the authors should reproduce the lack of furrow ingression in mouse Hep-Orgs (that they were able to generate in Ref. 44). This could be done in fixed cells as in Fig. 3. Alternatively, they could use live cell imaging and chemical dyes such as SiR-Tubulin and Cell Mask to label microtubules and the plasma membrane, respectively, without the need of creating genome-edited reporter lines.
      2. The videos acquired in Fig. 2 contain much more information than presented. The authors should measure the rate of furrow ingression, the extend of spindle elongation, the time of MT severing and the time of furrow/bridge regression after cytokinesis onset. All these parameters are important since spindle elongation and furrow ingression are altered in rodents. Is this also the case in human Hep-orgs? Furthermore, the spindle seems very different (bent bridges) in endomitotic compared to canonical cytokinesis (Fig. 2A). Finally, the authors should provide more time points during the time of furrow regression to better show how this phenomenon occurs. It seems, based on fixed images, that the midbody stays attached to the plasma membrane in an asymmetric manner (i.e. does not fully detach, contrary to what is stated in the text). 3D reconstructions in fixed cells and a further characterization of the movies would clarify this point.
      3. DAPI staining is not sensitive enough to detect thin chromatin bridges. To rule out that post-furrowing regression is not merely due to the present of DNA bridges, the authors should confirm their results with LAP2b staining (see PMID 19203582).
      4. The authors shows that binucleation results from defective anchorage of the bridge membrane to the midbody, but the molecular mechanism remains elusive and should be further probed. In Fig. 3, there is no obvious changes in the investigated markers. Are the intensities of RACGAP1, Anillin, CIT-K reduced in regressing cells? Are ECT2, activated (phospho) Myosin II, CEP55/ESCRT-III, (activated) AuroraB and MKLP1 normally localized/concentrated? ECT2, AuroraB and MKLP1 are regulated by E2F7/8 (Ref. 23) and AuroraB inactivation after bridge formation leads to late regression (PMID 19203582).
      5. The results of Fig. 4F indicate that the increased proportion of binucleated cells upon CHIR99021 removal depends on E2F7/8. Without live cell imaging (or FISH experiments) the authors cannot conclude that conclude that the increase in endomitosis is dependent on E2F7/8. A decrease in binucleation could indeed not imply a reduced occurrence of endomitosis. For instance, it is possible that E2F7/8 KO induces the formation of mononucleated 4n cells due to early mitotic failure. This issue should be clarified.
      6. Binucleation increases with age both in humans and rodents. Could this feature be mimicked in the human Hep-Org by leaving the organoids longer in culture? (optional but would reinforce the value of the model).

      Minor comments

      1. The results of Table 1 are based on very few fixed cells (3 to 6). The authors should consider increasing the number of regressing cells.
      2. Is WNT signaling modified by E2F7/8 mutations? To conclude that "WNT signaling inhibits binucleation in an E2F7/8-dependent manner", the authors should check that E2F7/8 KO does not impair the increase of WNT signaling upon CHIR99021 removal.
      3. Please provide movies of the cells presented in Fig. 2A.
      4. Removal of CHIR99021 induces major shape changes and lumen formation (rather than "exhibited some morphological changes" as stated). Could the author speculate on this?
      5. Fig. 4: Why do the authors use the cell line-1 that has the lowest level of binucleation in this experiment? Would the results be the same in cell line 2? (optional)
      6. Would insulin increase the proportion of binucleated cells, as in rodents? (optional)

      Significance

      Strengths and limitations:

      The manuscript is well written, easy to follow, and the quality of the data is overall high. A clear strength of this study is the use of state-of-the-art human hepatocyte organoids and genome editing (to generate reporter lines and to KO E2F7/8). This allows the authors to address the mechanism of binucleation in a human context. Interestingly, it revealed both similarities (e.g. E2F7/8 depends for binucleation) and striking mechanistic differences (e.g. post-furrowing regression) between rodent and human systems. The study is rather descriptive -which is fine- but deeper mechanistic insights would strengthen the conclusions of the manuscript. For instance, "our results identify how human hepatocytes inhibit cell division in endomitosis" appears as an overstatement since the molecular reason of midbody anchorage defects remains elusive.

      Audience:

      broad, basic research.

      Field of expertise:

      cell biology of cytokinesis

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      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      Polyploid cells arise within various human tissues by multiple different mechanisms. Here, Darmasaputra et al present a study of one such mechanism, endomitosis, in liver cells using fetal-derived human hepatocyte organoids. In this model, they demonstrate that binucleated cells arise through the late regression of the cytokinetic furrow prior to abscission. They identify a rare event in cytokinetic cells - loss of midbody association with the plasma membrane - that could explain the cytokinesis failure observed in a proportion of these cells. Finally, they show that loss of Wnt signalling increases the number of binucleation events in a manner that depends on E2F7 and E2F8, similar to what has been observed in murine hepatocytes.

      Major comments:

      This is a compelling and well-presented study. The data presented are high quality, the experiments are well described and controlled and the conclusions are convincing. I am particularly impressed by the technical effort that the authors must have put into obtaining high quality live and IF images of dividing cells within organoids and their careful documentation of what are very rare mitotic events. In addition, the manuscript is extremely well written and I found it a pleasure to read.

      I do not think that there are additional experiments that are essential to justify the conclusions of the paper. However, I do have suggestions that I think would strengthen this work and increase its significance. As is, the authors present findings in two different areas: the documentation of cytokinesis failure in hepatocyte organoids and the role of Wnt and E2F7/8 on binucleation. It would be really nice if the two parts could be linked. For example, the authors could examine cell divisions in the organoids without Wnt either live or fixed and show that they have a higher proportion of cells undergoing cytokinetic regression or with membrane-midbody attachment defects. Alternatively, they could look at whether the expression levels of key cytokinetic genes are changed in the Wnt and E2F7/8 organoids. As I said, these experiments are not required for or the publication of this work and I will leave it up to the authors to decide if they have the time or capacity to add additional data.

      Finally, before publication, the authors should discuss further the mechanisms by which loss of membrane attachment during cytokinesis could occur - there is quite a lot of literature in this area on the role of RacGAP1 and Ect2 in membrane attachment that is not discussed, particularly from the lab of Mark Pentronczki (eg Kotynkova 2026 PMID: 27926870, Lekmotsev PMID: 23235882). It's surprising that the authors haven't mentioned (or looked at) Ect2 at all, especially since Ect2 levels have been shown to control polyploidy in cardiomyocytes (Liu 2019 PMID: 31597755). This at least warrants some discussion.

      Minor comments:

      • Table 1 would be more striking as a graphical representation. I appreciate that the n numbers in the regressed cells means that statistical comparisons is not possible, but some kind of colour coding or graph would make this part clearer
      • It's not clear what the difference between Hep-Org 1 and Hep-Org 2 are. Are these from different donors?

      Significance

      This study is an important technical development in that it reports a new system to study in depth cell biology of liver endomitosis in non-transformed and, crucially, human 3D hepatocyte organoids. The findings reported using this system are potentially interesting although they could be further developed if they were mechanistically linked together (see major comments). This work is likely to be highly interesting to scientists studying cell division, cytokinesis and hepatocyte biology. It also has wider implications for liver biology and particularly liver regeneration. Additionally, given the role of polyploidisation in many different tissues, it will likely be of interest to scientists studying polyploidy and endomitosis more generally.

      My area of expertise is in cytokinesis and cell division in general, although not specifically in hepatocytes. I am not an expert in organoids.

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      Referee #1

      Evidence, reproducibility and clarity

      The study provides insights into how polyploidization via endomitosis may arise in human hepatocytes by studying fetal liver cell line-derived organoids. Using live cell imaging and LSM microscopy, binculeation was consistently observed in two independent cell line systems, at frequencies seen in human liver and sensitive to pharmacological inhibition (GSK3i) and genetic manipulation (E2F7 & E2F8 editing). The findings presented are in line with earlier data, largely gathered studying rodents. The data is convincing and robust indicating that these systems can be used to study cause and consequences of polyploidy in human hepatocytes.

      While the authors do suggest that they provide a mechanisms how polyploidy is initiated in human hepatocytes undergoing endomitosis, ie. loss of membrane association of membrane-anchoring proteins at the midbody (e.g. Anillin, RacGAP1), I do feel that the data provided is rather descriptive and does not address a particular mechanism that may account for loss of membrane anchoring. As such, the title is making a too strong point, as, in my point of view, it associates with loss of membrane anchorage, but may not drive endomitosis. Whether this is a "passive" process in response to changes in physical forces and tension, or regulated via signalling intermediates to initiate regression of the cleavage furrow is not addressed experimentally (mislocalizing these proteins on a larger scale). Discussion seems warranted.

      I do not see the need for additional experiments, as I believe the data is robust and introduces an interesting new model where the role of ploidy can be studied in human hepatocytes ex vivo. However, if the authors wish to extend their studies and document further similarities with pathways engaged in rodents, some E2F7/8 targets relevant for ploidy control such as Anillin or PIDDosome components, or, maybe MDM2 processing for p53 activation, could be tested in wt and E2F mutant cell lines.

      A minor suggestion is to clarify the term M-CDK activity in the introduction, as it may not be fully intuitive to all readers; similarly, ploidy reversal is still controversial in the field, but it is stated as a given fact.

      Significance

      Polyploidy at the cellular and nuclear level is a key feature of hepatocytes albeit the physiological significance of the process is not entirely clear. Increased ploidy has been linked to cancer resistance in the liver, but may pose a threat to hepatocyte survival under conditions of repeated compensatory proliferation cycles. Curiously, during normal regeneration after single surgical intervention liver regeneration is not compromised, even though it may recover faster starting when starting from higher ploidy levels. Mechanistically, most data has been generates studying rodents where it is documented that the proliferation behaviour changes around the time of weaning in mice when hepatocytes start to fail cytokinesis and undergo endomitosis, leading to cellular and nuclear polyploidy. In rodents, insulin signalling / AKT appears involved as is the E2F network and p53, activated by the caspase-2-PIDDosome. The model system introduced here will allow mechanistic studies in human organoids and help to increase our understanding of this process in steady state and under conditions of stress.

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      Reply to the reviewers

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

      Deletion of CerS4 in the entire mouse epidermis throughout development via the K14-Cre results in enlarged sebaceous glands and perturbed HFSC molecular phenotype. There is low or no expression of CD34, a known marker of the HFSCs along with apparent reduction of several other HFSC markers and acquisition of a more differentiated cell phenotype in these cells. Interestingly, skin and hair follicles seem to remain normal otherwise up to advanced age, though this contradicts the notion that HFSC were indeed affected at the functional level. The data does not demonstrate 'gradual decline' in the HFSC compartment, as claimed by the authors, but rather seem to indicate that the adult HFSC compartment is not properly established in its molecular signatures. Organoid cultures document defects in HFSC, which included reduced proliferation in the CerS4 KO cells. Lipid composition in plasma membranes was also affected by the CerS4 KO. Associated with this, Wnt signal transduction is also affected according to experiments that enhance the strength of wnt signals via a specific small molecular agonist of the pathway. Finally, the authors discover a resemblance of the mouse KO immune-phenotype, with human atopic dermatitis. The study is likely of interest to a specialized readership in skin biology and dermatology and adds to previous studies on CerS4 in skin that erroneously placed its role in the sebaceous gland. [The authors here demonstrate that deletion of CerS4 in the sebaceous glands via SCD3-Cre led to no phenotype, contradicting the previous assessment that CerS4 is important in sebaceous glands.] The study would need to be corrected in a few of its interpretations regarding stem cells to better match the data, as indicated below. *

      We thank the reviewer for the constructive comments that will help us to improve the manuscript. In particular, it is clear that we have not been sufficiently clear in the data presentation.

      Firstly, contrary to what the reviewer states, the CerS4epi-/- mice have a very strong hair follicle phenotype that results in complete hair loss. Also the epidermis is not normal as an inflammatory phenotype develops later, after the hair follicle architecture and function has been disrupted. Thus, there are clear functional consequences to the hair follicle and epidermis that arise from the dysfunction of the HFSC compartment. We will edit the manuscript and add photodocumentation of the macroscopic phenotype to ensure clarity.

      We fully agree with the reviewer that the initial phenotype is inability to establish the adult hair follicle stem cell niche, as shown by the single cell sequencing data and as also stated in the manuscript title. We will further edit the manuscript to clarify this conclusion. Importantly, however, some hair follicle stem cells are generated but these become gradually depleted. So there is a dual phenotype: an inability to efficiently establish and maintain the hair follicle stem cell population. We will clarify this in the text.

      Finally, we want to emphasize that the main finding of this manuscript is that hair follicle stem cells contain a unique lipid profile and perturbing this profile by deleting CerS4 leads to profound defects in stem cell fate regulation through Wnt. This is a completely new finding that has implications far beyond dermatology.

      Major revisions: Fig1B - the data seems to simply shows that bulge cells express less or no CD34 and not that ' CerS4epi-/- mice showed reduced HFSC numbers'; the primary FACS data should be shown somewhere too.

      Outer bulge hair follicle stem cells are defined as a population of cells that expresses CD34 and integrin-a6. The quantifications in Fig 1B show the quantitative FACS analyses of the size of this population and indicate less CD34+/integrin-a6+ cells in CerS4epi-/- epidermis. The mean fluorescence intensity of CD34 and integrin-a6 was not reduced in these CerS4epi-/- stem cells. This FACS analysis therefore allows the conclusion that there are less CD34+/integrin-a6+ cells in CerS4epi-/- epidermis. We will include the original FACS plot data to support this notion and the quantifications.

      The conclusion that stemness is affected, and HFSCs lose their normal gene expression signature is at more convincing after looking at other HFSC markers down the road in the paper. However, in the absence of functional assays that would demonstrate stem cell function is lacking and seeing that hair follicles are maintained and grow in long-term, the notion that stem cells are lacking in these conditions is not supported by the data.

      We appreciate that the reviewer finds the marker gene analysis convincing. To assay stem cell functionality, we have used the organoid assays (spheroid formation is classical, widely used assay for stemness). Using these functional assays we observe impaired self-renewal of stem cells (Fig. 3D), enhanced differentiation (Fig. 3I), and altered Wnt responsiveness (Fig. 5 E, F), all indicative of stem cell dysfunction and explaining the in vivo phenotypes of altered stem cell differentiation and inability to establish and maintain the stem cell population.

      In the revised manuscript we will also include measurements of stem cell self-renewal in vivo using BrdU incorporation and provide more detailed description on the hair loss phenotype of the mice to further strengthen this conclusion.

      *The conclusion after figure 2: "Collectively, these data indicate that CerS4-deficiency triggers ... ... gradual depletion of the quiescent HFSC compartment." There is no data showing gradual depletion of the quiescent HFSC compartment. We would need to see a gradual activation of HFSCs with over proliferation to conclude this. There is some data albeit not always convincing (see NFAC1 staining in Fig. 5C) indicating loss of markers associated with quiescence but there is no data indicating 'gradual' loss of markers. *

      We agree with the reviewer that showing gradual activation of the HFSCs in vivo is important to conclude loss of quiescence. We will include in situ stainings of in vivo BrdU labeling and quantify proliferation in the hair follicle bulge stem cell region. Preliminary data of P47 mice already shows a clear increase in BrdU+ cell in the stem cell compartment in CerS4epi-/- skin . Further analysis at P21 will be carried out during the revision.

      *Minor revisions: *

      • Figure 1C legend - please spell out what are the abbreviations for the different subpopulations; please show these populations as % as opposed to absolute numbers. *

      We will edit the Figure 1C legend for clarity and express the populations as %.

      *

      *

      *Figure 1D - please make it clear in the cartoon what the different sub-populations listed are; *

      We will edit the cartoon for clarity.

      Is OB1 a CD34- HFSC population?

      The outer bulge 1 (OB1) is a population of cells that expresses hair follicle stem cell markers, including CD34. We will clarify this in the legend.

      Fig. 3B - the colors of the legend do not match the colors in the data so it is confusing as to which one is which!

      We will alter the colors to match the data and thank the reviewer for pointing this out.

      Fig 5C - the differences in NFATc1 are not visible in the images shown

      We apologize for the suboptimal quality of these images and will replace them with higher resolution images to more clearly demonstrate the difference.

      *

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

      The manuscript authored by Peters et al. titled "Sphingolipid metabolism orchestrates the establishment of the adult hair follicle stem cell niche to control skin homeostasis" elucidates the critical role of ceramide synthase 4 (CerS4) in the epidermal stem cell niche, particularly in regulating hair follicle bulge stem cells (HFSCs). Using epidermal specific CerS4 knockout mice as an in vivo model and hair follicle organoid culture as an ex vivo model, the authors conducted a comprehensive analysis, which includes cutting edge approaches such as scRNA-seq, proteomics, and lipidomics. The results highlight CerS4's function in the establishment/maintenance of the HFSC niche, as absence of CerS4 changes HFSCs' number and differentiation state. Potential underlying mechanisms identified include altered membrane lipid profiles and Wnt signaling responsiveness. Possible link to a chronic inflammatory skin disease, atopic dermatitis, is also implicated. The data presented are generally of high quality, and the work is significant as it uncovers a new regulator of HFSC fate with mechanistic connection to lipid metabolism. *

      We thank the reviewer for the positive assessment of our work and finding it to be of high quality and significance. We further appreciate the constructive comments that will further help us to improve the manuscript.

      *However, some issues were identified, most of them having to do with in vivo characterization and data interpretation:

      *

      *Major: 1. The in vivo HFSC phenotype can be better characterized. "Collective, these data show that CerS4 in HFSCs is essential to establish the adult stem cell compartment and to assure lineage fidelity." - this statement premature based on order of the data shown. Also the trajectory difference shown in Figure 2A is not striking. Subclustering out the relative cell subsets and redo the analysis might help to tease out the difference. Additional experiments such as lineage tracing would be useful to support the notion that there is lineage fidelity issue in the mutant - though it is understood that this is quite involved and may lie outside the scope of the current study. Are bulge cells in the mutant proliferative? - the authors should consider in vivo Edu labelling experiment or the like to assess the quiescence/proliferation of the bulge cells. Finally, analyzing hair follicles at earlier stages might help to clarify when and where the bulge and sebaceous gland changes start - is possible that aberrant divergence of bulge/sebaceous fates occur prior to the establishment of a stable bulge fate? *

      We thank the reviewer for suggesting additional analyses of the single cell sequencing data. We have performed subclustering of the relevant populations for the trajectory analyses to more clearly demonstrate the altered lineage trajectories. We will include these new analyses in the manuscript. Importantly, the in vitro organoids show abnormal differentiation (Fig. 3H, 3I, Supplementary Fig. 2G), closely resembling the in vivo phenotypes, thereby strengthening the conclusion of cell-autonomously altered lineage trajectories of the hair follicle stem cells.

      We will further preform in vivo BrdU labeling as suggested. These experiments have already been initiated and preliminary data show increased proliferation in the bulge stem cell region of CerS4epi-/- mice in older mice (P47). The data will be included to emphasize long term loss of quiescence in the stem cell compartment in CerS4epi-/- mice.

      Understanding the early development of bulge and sebaceous fates is indeed an interesting question. This will be addressed by detailed analyses of stem cell fate at early stages (P17-P21) using key markers of stem cell state and sebaceous linages (CD34, Krt15, Lhx2, Nfatc1, SCD1 and FASN).

      Finally, we have initiated lineage tracing experiments using the stem cell-specific Lgr5-Cre to conclusively demonstrate that Cers4-deletion leads to altered routing of hair follicle stem cells into upper hair follicle and sebaceous gland fates. This notion is supported by the preliminary analyses of these experiments. We will finalize these analyses and include them in the manuscript.

      *2. The exclusion of IFE contribution is not backed up by data. Figure 6D - model emphasizes HFSC involvement in atopic dermatitis, but this could be due to epidermal barrier defect. Barrier defect could already be present even though IFE morphology appears normal. Maybe TEWL is measured at the time of analysis and shows no change - if so, this data should be included. HFSC changes might contribute but the involvement of IFE cannot be excluded. The conclusion that "CerS4 expression was restricted to the hair follicle" is not supported by data. IFE expression is apparent in Figure S1C. Along this line, there is also an apparent expansion of IFE basal II in the mutant (Figure 1C). *

      We acknowledge that we have not been clear enough with the evidence that allowed us to exclude the involvement of an IFE-mediated barrier defect in the early skin inflammation phenotype. To address a potential barrier defect early on, we have performed careful analysis of TEWL. In Peters at al., 2020 we demonstrate no changes in TEWL at P0, a reduced TEWL at P21 and an increased TEWL in adult CerS4epi-/- mice starting only at P33. The reduction of the TEWL in adolescent CerS4epi-/- mice (P21) is likely linked to an increased production of sebaceous lipids lubricating the skin surface at this time point (Peters et al., 2020). Thus, defects in the hair follicle stem cell compartment, present at adolescence (P21) arise prior to defects in the adult (P33) IFE barrier function. We will clarify this in the manuscript.

      Cers4 expression is overall low in skin, as is typical for enzymes. In situ stainings of Cers4mRNA (Fig.S1C) indeed show a sparse signal also in the IFE. This signal is also detected in CerS4-/- sections, although the KO skin cannot be conclusively used to control background as these mice were generated by deletion of exon 3 only, and Cers4 RNAscope probes might detect remnant Cers4 RNA in these mice. Importantly, our data on FACS sorted basal cells of the IFE shows no substantial Cers4 mRNA expression in IFE progenitors (Fig. S1D) and no mRNA is detected in the IFE in the single cell sequencing. Thus, while we cannot fully exclude low levels of CerS4 expression in the IFE, the levels are substantially lower than in the HFSC and SG compartments, and the phenotype, including the slight expansion of the IFE basal II population, is very minor compared to the hair follicle phenotype. However, to avoid overinterpreting our data, we will carefully edit the conclusions to be less strong on the involvement of the IFE. Furthermore, we will perform hair follicle stem cell lineage tracing experiments as outlined in resspose to the previous point to strengthen the conclusion on the hair follicle stem cell-autonomous phenotype.

      3. Figure 1 - single cell analysis was done using only 2 pairs of mice, and data in E lack statistical assessment. At the very least, data for individual pairs should be shown in supplemental data to ensure that changes are consistent in both mutant mice rather than being dominated by dramatic alteration in only 1 mutant mouse.

      We naturally have rigorously analyzed the replicates to ensure that the phenotype is consistently present in both. We will include the separate analysis of the mice to document this and include statistical analysis.

      Minor: 1. CerS4SCD3-/+ nomenclature is mis-leading.

      We will edit this for clarity

        1. Figure 2- "Furthermore, we observed expansion of the inner bulge identity marker Krt6 protein expression into outer bulge stem cells and along the infundibulum in CerS4epi-/- hair follicles, whereas in control mice Krt6 was restricted to the inner bulge (Fig. 2C)." - Krt6 staining is presented in Fig 2D, not 2C. *

      We thank the reviewer for pointing out this mistake that will correct.

        1. Figure 3C - size of the organoids should be quantified with statistics. The images shown do not support the statement that "Strikingly, CerS4epi-/- organoids showed altered morphology characterized by smaller size and loss of cohesion of peripheral cells from the organoid clusters (Fig. 3C), ...".*

      We will include quantifications.

        1. Section titled "CerS4 regulates HFSC differentiation in a stem cell autonomous manner": "CD34- integrin- a6+ cells, which based on extensive transcriptome and marker expression analyses represent a mixture of HFSCs, hair follicle outer root sheath (ORS) cells and inner bulge cells (collectively termed non-HFSCs)." - shouldn't the CD34- integrin- a6+ population also contain IFE stem/progenitor cells? Are hair follicles micro-dissected out for FACS? *

      The hair follicles are not micro-dissected out for FACS, and the entire basal cell population is initially isolated. However the organoid culture conditions speficically promote the expansion of the hair follicle linage, whereas cells of the IFE are not expanded and long term maintained as extensively documented in previous publications using this organoid system (see for example Kim et al., Cell Metabolism 2020; Chacon-Martinez EMBOJ 2016).

      *5. Figure 5D - please provide the working concentration of Chir99021. *

      We will provide the working concentration.

      *6. Figure 5F - explain what arrows mean in legends. *

      We will define the arrows.

        1. Figure 6A - no significant changes in Th2 and ILC2 were observed at a 95% confidence interval. Increasing mouse number will help to increase statistical power*.

      We agree with the reviewer and acknowledge that this experiment was unfortunately underpowered. We will repeat it with a larger cohort.

        1. Additional Wnt target genes such as Axin 2 should be looked at.*

      We thank the reviewer for this suggestion, we will include analyses of additional Wnt target genes.

        1. The increased BMP signaling and decreased Nfatc1 expression are seemingly contradictory.*

      We apologize for the lack of clarity here. Single cell sequencing showed increased BMP-signaling of outer bulge cell cells to inner bulge cells on mRNA level (Figure S4A). No alteration in BMP signaling was detected within the outer bulge stem cell compartment (Figure 5A). Nfatc1 protein expression was analyzed in the upper bugle (Figure 5C). The data indicate no differential gene expression of ligand receptor pairs mediating BMP-signaling within the outer bulge. A decrease in Nfact1 protein expression (Fig. 5C) together with an increased proliferation (see above) and loss of label retention (Peters et al., 2015) indicates loss of quiescence in this compartment. This data does not contradict an increased BMP signaling in the inner bulge (Figure S4A). An increase in BMP signaling in the inner bulge is in line with reduced inner bulge cell cluster detected in CerS4epi-/- skin via single cell sequencing, likely contributing to the hair loss observed. We will edit this paragraph to make this more clear.

        1. Paragraph starting with "It is interesting to note that ceramide availability was shown to regulate Wnt signaling in Drosophila through strong effects on recycling endocytosis of the receptors (Pepperl et al., 2013)." Is redundant in the manuscript.*

      We apologize for the accidental duplication of this paragraph and thank the reviewer for noticing this mistake.

      *

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

      The authors created CerS4 mutant mice to test the role of sphingolipids in hair follicle stem cells (HFSCs) and the hair cycle. This work extends previous studies that show that loss of this enzyme leads to defects in the hair cycle and eventually hair loss. In this study the authors look early on in the course of the deletion in an attempt to understand why loss of this enzyme leads to the phenotype described previously. They use single cell profiling, proteomics, and in situ imaging to pinpoint issues in the stem cell niche that drive phenotypes and propose novel interactions between sphingolipid metabolism, Wnt signaling, and inflammation in regulation of HFSC homeostasis. The data are nicely presented, and the text is well written. The conclusions are clearly defined.*

      We thank the reviewer for the positive assessment of our work and finding it well written and presented. We further appreciate the constructive comments that will further help us to improve the manuscript.

      *While the data are clearly presented, there are numerous issues that are confusing to this reviewer. In addition, some of the phenotypes described are subtle, and thus do not make a convincing case.

      1, In figure 1C, the cell proportion analysis suggests there are no OBII or SG in WT. I am not sure how this could be possible. In addition, there appears to be almost no sebaceous cells in either, but the mutant supposedly has much larger sebaceous glands (in Fig 2). In Fig S1I, there is no change in bulge cells? In Fig 1B, there is less HFSCs in the mutant than in the WT, but in 1C, there is more OBI in the mutant. The results in Fig 1B and C are confusing. Also, the schematic in Fig 1 is hard to read, the authors should color code the text with the image.*

      It is important to emphasize that the single cell RNA sequencing was carried out at P19 when the bulge stem cell compartment only starts to be established. This explains why only few bulge stem cells are detected at this point. Nevertheless, the OBII and SG cluster is visible also in the wt in Figure 1D. We will include subclustering of the relevant subpopulations to make these populations more clearly visible also in the wt. We will also edit the labels for clarity.

      Mature sebocytes are very large cells, and inherent to the single cell sequencing workflows these large cells are excluded from the sequencing libraries. Importantly, we do not detect a change in bulge stem cells in a mouse line in which CerS4 was specifically deleted only in sebocytes (Figure S1I). This analysis was carried out to exclude a sebocyte intrinsic effect on the hair follicle stem cell state and fate. The data does not contradict Fig. 1, as data in Fig. 1 was generated using a different mouse line in which CerS4 is deleted in the entire epidermal stem cell population using K14Cre. We will edit the manuscript to make this more clear.

      Data presented in Fig 1B and C focus on two different aspects. Fig 1B shows the inefficient establishment and maintenance of CD34+/integrin-a6+ bulge hair follicle stem cells. The quantification is based on FACS analyses of cells expressing these cell surface molecules/stem cell markers. Fig 1C shows the quantification of the various cell states based on single cell RNA expression and subsequent clustering of the control and CerS4epi-/- epidermal cells together. The “outer bulge” cluster was annotated based on these cells expressing hair follicle stem cell markers. While the CerS4epi-/- epidermis shows increased number of cells in this cluster, the expression of all key stem cell genes (CD34, Sox9, Krt15, Lhx2) is reduced in CerS4epi-/- outer bulge 1 compartment compared to control. Thus, while this “outer bulge” population is expanded in the KO, the stem cell properties of this population are clearly attenuated, as defined by decreased expression of key stem cell transcription factors and increased expression of differentiation genes. We will clarify this in the revised version of the manuscript and also rename this cluster “outer bulge-like” to highlight that these cells are not necessarily bona fide stem cells and might not express high levels of CD34+/integrin-a6+ protein.

      *2, In Figure 5, the signaling chart shows a strong upregulation of non-canonical Wnt signaling in the mutant bulge. Canonical Wnt signaling appears to be unchanged between wt and ko. Thus, it is not clear why the authors came to the conclusion that Wnt signaling is induced in the mutant. They further show expression of Lef1 and Nfatc1, but these are not typical markers used to denote canonical wnt activation, as implied. In fact, the data in Fig S4B suggest the induction of Lef1 and Tcf4 is actually very subtle. Instead, the authors should use nuclear b-catenin or transcriptional targets such as Axin or CyclinD. The authors should in fact explore the observation of Wnt5, as that appears to be the most dramatic change. In addition, the authors should use an ontological analysis with the single cell data from the tissue in the same manner that they did for organoids to take another look at molecular consequences of loss of CerS4. *

      We agree with the reviewer that further analysis of canonical and non-canonical Wnt signaling will strengthen this conclusion. In our experience, nuclear b-catenin is very difficult to detect in the skin even when Wnt is highly active, but we will investigate Axin2 and CyclinD1 expression. We will also investigate Wnt5a signaling by analyzing its expression as well as its downstream target genes. We will further perform additional ontological analyses from the single cell sequencing data to strengthen the conclusions on the signaling alterations.

      * 3, The authors suggest that much of the phenotype is due to inflammation. In Fig 6A, they showed analysis of CD45 cells in the skin. However, the only change was a very subtle change in Th2 cells, while no other CD45+ cells were altered.*

      We agree with the reviewer and acknowledge that this experiment was unfortunately underpowered. We will repeat these analyses with a larger cohort.

      4, The authors showed upregulation of Immune response in Fig 6C, but then in Fig S2, the genes downregulated are also related to immune response...how do the authors reconcile this?

      We apologize for this confusion. Importantly, keratinocyte-intrinsic downregulation of homeostatic immune modulating activity is a key driver of allergic disorders, like atopic dermatitis. This barrier intrinsic immune modulation is distinct from immune cell-mediated inflammation. There is a strong overlap of genes constituting the term “Inflammatory abnormality of the skin” (Human phenotype ontology terms) Fig 6C and “Immune system process” (GOBP terms) Fig S2F. To name some, i.e. Adam-, ALOX-, ASXL- family members are annotated by both terms. Mutations in these genes are known to cause skin diseases associated with immune dysregulation but are likewise known to regulate immune responses.

      Data in Figure 6C shows enrichment of this term from both up and downregulated proteins in the CerS4epi-/- condition compared to control, indicating that proteins involved in “Inflammatory abnormality of the skin” are dysregulated in CerS4epi-/- organoids. Data in Figure S2F shows the downregulation of these proteins in CerS4epi-/- organoids compared to control. We will clarify this in the text and figure legends.

      5, The author propose that the phenotype in CerS4 null mice is due to disruption of the stem cell Niche. However, the authors have not shown evidence for such an effect through any in situ analysis. The single cell approaches are valuable, but in that case the niche is dissociated. The organoid work is also nice, but not exactly a stem cell niche either. The authors should instead test their hypothesis through an in situ analysis.

      We have used the term niche to describe the cellular interactions between stem cells and the other niche resident cells such as the Krt6+ inner bulge cells that have been analyzed here. We will edit the conclusions for clarity. We will further include additional immunofluorescence analyses of the bulge compartment in situ, as suggested (including markers for quiescence and activation).

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      Referee #3

      Evidence, reproducibility and clarity

      The authors created CerS4 mutant mice to test the role of sphingolipids in hair follicle stem cells (HFSCs) and the hair cycle. This work extends previous studies that show that loss of this enzyme leads to defects in the hair cycle and eventually hair loss. In this study the authors look early on in the course of the deletion in an attempt to understand why loss of this enzyme leads to the phenotype described previously. They use single cell profiling, proteomics, and in situ imaging to pinpoint issues in the stem cell niche that drive phenotypes and propose novel interactions between sphingolipid metabolism, Wnt signaling, and inflammation in regulation of HFSC homeostasis. The data are nicely presented, and the text is well written. The conclusions are clearly defined.

      While the data are clearly presented, there are numerous issues that are confusing to this reviewer. In addition, some of the phenotypes described are subtle, and thus do not make a convincing case.

      1. In figure 1C, the cell proportion analysis suggests there are no OBII or SG in WT. I am not sure how this could be possible. In addition, there appears to be almost no sebaceous cells in either, but the mutant supposedly has much larger sebaceous glands (in Fig 2). In Fig S1I, there is no change in bulge cells? In Fig 1B, there is less HFSCs in the mutant than in the WT, but in 1C, there is more OBI in the mutant. The results in Fig 1B and C are confusing. Also, the schematic in Fig 1 is hard to read, the authors should color code the text with the image.
      2. In Figure 5, the signaling chart shows a strong upregulation of non-canonical Wnt signaling in the mutant bulge. Canonical Wnt signaling appears to be unchanged between wt and ko. Thus, it is not clear why the authors came to the conclusion that Wnt signaling is induced in the mutant. They further show expression of Lef1 and Nfatc1, but these are not typical markers used to denote canonical wnt activation, as implied. In fact, the data in Fig S4B suggest the induction of Lef1 and Tcf4 is actually very subtle. Instead, the authors should use nuclear b-catenin or transcriptional targets such as Axin or CyclinD. The authors should in fact explore the observation of Wnt5, as that appears to be the most dramatic change. In addition, the authors should use an ontological analysis with the single cell data from the tissue in the same manner that they did for organoids to take another look at molecular consequences of loss of CerS4.
      3. The authors suggest that much of the phenotype is due to inflammation. In Fig 6A, they showed analysis of CD45 cells in the skin. However, the only change was a very subtle change in Th2 cells, while no other CD45+ cells were altered.
      4. The authors showed upregulation of Immune response in Fig 6C, but then in Fig S2, the genes downregulated are also related to immune response...how do the authors reconcile this?
      5. The author propose that the phenotype in CerS4 null mice is due to disruption of the stem cell Niche. However, the authors have not shown evidence for such an effect through any in situ analysis. The single cell approaches are valuable, but in that case the niche is dissociated. The organoid work is also nice, but not exactly a stem cell niche either. The authors should instead test their hypothesis through an in situ analysis.

      Significance

      The authors created CerS4 mutant mice to test the role of sphingolipids in hair follicle stem cells (HFSCs) and the hair cycle. This work extends previous studies that show that loss of this enzyme leads to defects in the hair cycle and eventually hair loss. In this study the authors look early on in the course of the deletion in an attempt to understand why loss of this enzyme leads to the phenotype described previously. They use single cell profiling, proteomics, and in situ imaging to pinpoint issues in the stem cell niche that drive phenotypes and propose novel interactions between sphingolipid metabolism, Wnt signaling, and inflammation in regulation of HFSC homeostasis. The data are nicely presented, and the text is well written. The conclusions are clearly defined.

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      Referee #2

      Evidence, reproducibility and clarity

      The manuscript authored by Peters et al. titled "Sphingolipid metabolism orchestrates the establishment of the adult hair follicle stem cell niche to control skin homeostasis" elucidates the critical role of ceramide synthase 4 (CerS4) in the epidermal stem cell niche, particularly in regulating hair follicle bulge stem cells (HFSCs). Using epidermal specific CerS4 knockout mice as an in vivo model and hair follicle organoid culture as an ex vivo model, the authors conducted a comprehensive analysis, which includes cutting edge approaches such as scRNA-seq, proteomics, and lipidomics. The results highlight CerS4's function in the establishment/maintenance of the HFSC niche, as absence of CerS4 changes HFSCs' number and differentiation state. Potential underlying mechanisms identified include altered membrane lipid profiles and Wnt signaling responsiveness. Possible link to a chronic inflammatory skin disease, atopic dermatitis, is also implicated. The data presented are generally of high quality, and the work is significant as it uncovers a new regulator of HFSC fate with mechanistic connection to lipid metabolism.

      However, some issues were identified, most of them having to do with in vivo characterization and data interpretation:

      Major:

      1. The in vivo HFSC phenotype can be better characterized. "Collective, these data show that CerS4 in HFSCs is essential to establish the adult stem cell compartment and to assure lineage fidelity." - this statement premature based on order of the data shown. Also the trajectory difference shown in Figure 2A is not striking. Subclustering out the relative cell subsets and redo the analysis might help to tease out the difference. Additional experiments such as lineage tracing would be useful to support the notion that there is lineage fidelity issue in the mutant - though it is understood that this is quite involved and may lie outside the scope of the current study. Are bulge cells in the mutant proliferative? - the authors should consider in vivo Edu labelling experiment or the like to assess the quiescence/proliferation of the bulge cells. Finally, analyzing hair follicles at earlier stages might help to clarify when and where the bulge and sebaceous gland changes start - is possible that aberrant divergence of bulge/sebaceous fates occur prior to the establishment of a stable bulge fate?
      2. The exclusion of IFE contribution is not backed up by data. Figure 6D - model emphasizes HFSC involvement in atopic dermatitis, but this could be due to epidermal barrier defect. Barrier defect could already be present even though IFE morphology appears normal. Maybe TEWL is measured at the time of analysis and shows no change - if so, this data should be included. HFSC changes might contribute but the involvement of IFE cannot be excluded. The conclusion that "CerS4 expression was restricted to the hair follicle" is not supported by data. IFE expression is apparent in Figure S1C. Along this line, there is also an apparent expansion of IFE basal II in the mutant (Figure 1C).
      3. Figure 1 - single cell analysis was done using only 2 pairs of mice, and data in E lack statistical assessment. At the very least, data for individual pairs should be shown in supplemental data to ensure that changes are consistent in both mutant mice rather than being dominated by dramatic alteration in only 1 mutant mouse.

      Minor:

      1. CerS4SCD3-/+ nomenclature is mis-leading.
      2. Figure 2- "Furthermore, we observed expansion of the inner bulge identity marker Krt6 protein expression into outer bulge stem cells and along the infundibulum in CerS4epi-/- hair follicles, whereas in control mice Krt6 was restricted to the inner bulge (Fig. 2C)." - Krt6 staining is presented in Fig 2D, not 2C.
      3. Figure 3C - size of the organoids should be quantified with statistics. The images shown do not support the statement that "Strikingly, CerS4epi-/- organoids showed altered morphology characterized by smaller size and loss of cohesion of peripheral cells from the organoid clusters (Fig. 3C), ...".
      4. Section titled "CerS4 regulates HFSC differentiation in a stem cell autonomous manner": "CD34- integrin- a6+ cells, which based on extensive transcriptome and marker expression analyses represent a mixture of HFSCs, hair follicle outer root sheath (ORS) cells and inner bulge cells (collectively termed non-HFSCs)." - shouldn't the CD34- integrin- a6+ population also contain IFE stem/progenitor cells? Are hair follicles micro-dissected out for FACS?
      5. Figurer 5D - please provide the working concentration of Chir99021. Figure 5F - explain what arrows mean in legends.
      6. Figure 6A - no significant changes in Th2 and ILC2 were observed at a 95% confidence interval. Increasing mouse number will help to increase statistical power.
      7. Additional Wnt target genes such as Axin 2 should be looked at.
      8. The increased BMP signaling and decreased Nfatc1 expression are seemingly contradictory.
      9. Paragraph starting with "It is interesting to note that ceramide availability was shown to regulate Wnt signaling in Drosophila through strong effects on recycling endocytosis of the receptors (Pepperl et al., 2013)." Is redundant in the manuscript.

      Significance

      The work uncovers a new regulator of HFSC fate with mechanistic connection to lipid metabolism and development signaling. The same group previously reported epidermal and hair cycling phenotypes of the same mutant mice, but this work now identifies a specific defect in HFSCs and present evidence for cellular, molecular and biochemical changes. Linking stem cell regulation to lipid metabolism is conceptually novel, and should have a broad audience. However, the study does have some limitations, such as lack of definitive evidence that CerS4 function in HFSCs is responsible for all the defects reported here, and that lipid alterations have a causal relationship with altered Wnt signaling.

      My expertise is in skin biology, stem cell control, and developmental signaling.

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      Referee #1

      Evidence, reproducibility and clarity

      Deletion of CerS4 in the entire mouse epidermis throughout development via the K14-Cre results in enlarged sebaceous glands and perturbed HFSC molecular phenotype. There is low or no expression of CD34, a known marker of the HFSCs along with apparent reduction of several other HFSC markers and acquisition of a more differentiated cell phenotype in these cells. Interestingly, skin and hair follicles seem to remain normal otherwise up to advanced age, though this contradicts the notion that HFSC were indeed affected at the functional level. The data does not demonstrate 'gradual decline' in the HFSC compartment, as claimed by the authors, but rather seem to indicate that the adult HFSC compartment is not properly established in its molecular signatures. Organoid cultures document defects in HFSC, which included reduced proliferation in the CerS4 KO cells. Lipid composition in plasma membranes was also affected by the CerS4 KO. Associated with this, Wnt signal transduction is also affected according to experiments that enhance the strength of wnt signals via a specific small molecular agonist of the pathway. Finally, the authors discover a resemblance of the mouse KO immune-phenotype, with human atopic dermatitis. The study is likely of interest to a specialized readership in skin biology and dermatology and adds to previous studies on CerS4 in skin that erroneously placed its role in the sebaceous gland. [The authors here demonstrate that deletion of CerS4 in the sebaceous glands via SCD3-Cre led to no phenotype, contradicting the previous assessment that CerS4 is important in sebaceous glands.] The study would need to be corrected in a few of its interpretations regarding stem cells to better match the data, as indicated below.

      Major revisions:

      Fig1B - the data seems to simply shows that bulge cells express less or no CD34 and not that ' CerS4epi-/- mice showed reduced HFSC numbers'; the primary FACS data should be shown somewhere too. The conclusion that stemness is affected, and HFSCs lose their normal gene expression signature is at more convincing after looking at other HFSC markers down the road in the paper. However, in the absence of functional assays that would demonstrate stem cell function is lacking and seeing that hair follicles are maintained and grow in long-term, the notion that stem cells are lacking in these conditions is not supported by the data.

      The conclusion after figure 2: "Collectively, these data indicate that CerS4-deficiency triggers ... ... gradual depletion of the quiescent HFSC compartment." There is no data showing gradual depletion of the quiescent HFSC compartment. We would need to see a gradual activation of HFSCs with over proliferation to conclude this. There is some data albeit not always convincing (see NFAC1 staining in Fig. 5C) indicating loss of markers associated with quiescence but there is no data indicating 'gradual' loss of markers.

      Minor revisions:

      Figure 1C legend - please spell out what are the abbreviations for the different subpopulations; please show these populations as % as opposed to absolute numbers.

      Figure 1D - please make it clear in the cartoon what the different sub-populations listed are;

      Is OB1 a CD34- HFSC population?

      Fig. 3B - the colors of the legend do not match the colors in the data so it is confusing as to which one is which!

      Fig 5C - the differences in NFATc1 are not visible in the images shown

      Significance

      Deletion of CerS4 in the entire mouse epidermis throughout development via the K14-Cre results in enlarged sebaceous glands and perturbed HFSC molecular phenotype. There is low or no expression of CD34, a known marker of the HFSCs along with apparent reduction of several other HFSC markers and acquisition of a more differentiated cell phenotype in these cells. Interestingly, skin and hair follicles seem to remain normal otherwise up to advanced age, though this contradicts the notion that HFSC were indeed affected at the functional level. The data does not demonstrate 'gradual decline' in the HFSC compartment, as claimed by the authors, but rather seem to indicate that the adult HFSC compartment is not properly established in its molecular signatures. Organoid cultures document defects in HFSC, which included reduced proliferation in the CerS4 KO cells. Lipid composition in plasma membranes was also affected by the CerS4 KO. Associated with this, Wnt signal transduction is also affected according to experiments that enhance the strength of wnt signals via a specific small molecular agonist of the pathway. Finally, the authors discover a resemblance of the mouse KO immune-phenotype, with human atopic dermatitis. The study is likely of interest to a specialized readership in skin biology and dermatology and adds to previous studies on CerS4 in skin that erroneously placed its role in the sebaceous gland. [The authors here demonstrate that deletion of CerS4 in the sebaceous glands via SCD3-Cre led to no phenotype, contradicting the previous assessment that CerS4 is important in sebaceous glands.]

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      Reply to the reviewers

      Manuscript number: RC-2023-02132R

      Corresponding author(s): Halyna, Shcherbata

      Point-by-point description of the revisions

      We would like to sincerely thank the reviewers for the positive evaluation of our work, careful reading of our manuscript, and helpful suggestions. In the revised version of our manuscript, we have introduced the proposed changes and added the new data based on the suggested experiments to address the reviewers’ concerns. We hope that this modified version of the manuscript is now acceptable for publication.

      • *

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

      Summary Elucidating the cellular and molecular mechanisms underlying age-related neurodegeneration remains a key challenge for neurobiologists. In this manuscript, Mariana Tsap and colleagues in the team of Halyna Shcherbata focus on the function of the neuropathy target esterase NTE/Swiss Cheese (Sws) in the Drosophila brain. The authors use an elegant combination of genetics, light and electron microscopy, RT-qPCR and GS-MS mass spectrometry to determine the complex role of Sws in cellular blood brain barrier (BBB) integrity, the brain inflammatory response and fatty acid metabolism. The study provides a detailed characterisation as to how the loss of sws affects glial cell morphology in the BBB revealing abnormal membrane accumulations and tight junctions, and in consequence causing permeability issues. Importantly, they observed the upregulation of antimicrobial peptides in the brain, indicative of neuroinflammation, as well as of fatty acids, equally connected with the inflammatory response.

      Major comments

      The study provides a detailed and comprehensive characterization of the sws mutant phenotype, and in particular the role of this gene in blood-brain barrier forming glia.

      The study connects neurodegeneration and inflammation, but also makes a particular point about "inflammaging". However, the age contribution has not been studied in detail. Indeed, the flies analyzed are 15 days old (according to the Material and Methods section, with the exception of Figure 1 where flies are 30 days old), and hence have not been compared with younger or older flies to make a point of age as evoked in the abstract, introduction or discussion. The authors should either add experiments comparing differently aged flies or de-emphasize this point to a brief consideration in the discussion. Instead, it would be very helpful to provide concise information about the current knowledge concerning the inflammatory response in the Drosophila brain. We thank the reviewer for raising this point. The decision to use 15-day-old flies was made due to the high mortality of swsmutants after two weeks and because age-dependent character of sws neurodegeneration has been previously well described. As the reviewer suggested, now we also included old animals in our experiments to show a connection between age-dependent neurodegeneration and inflammation. We measured and compared the mRNA levels of expression of the antimicrobial peptides (AMPs) Attacin A, Cecropin A, and Diptericin in the heads of 15- and 30-day-old sws loss-of-function mutants, in the heads of flies that had sws downregulation only in SPG cells (moody>swsRNAi) and in the heads of flies expressing NTE/SWS in SPG cells in sws mutant background. We found that the expression levels of the antimicrobial peptides are increased in the age-dependent manner in the tested mutants. In addition, we found that the expression of NTE/SWS in SPG in sws mutant background reduces inflammatory response in aging animals (see Figure 5D). Also, as the reviewer suggested, we provide brief information on the current understanding of the inflammatory response in the Drosophila brain in the Introduction and Results sections.

      Related to this point, the authors convincingly show that sws is required in surface glia using rescue experiments. Nevertheless, all experiments rely on drivers and mutants that could cause the emergence of phenotypes during development. Thus, to strengthen the causative link between the breakdown of the BBB and the neuroinflammatory response, it would be helpful to consider an acute knock-down in adults after BBB formation has been completed. To strengthen the causative link between the breakdown of the BBB and the neuroinflammatory response during adulthood, we performed qPCR analysis and measured the mRNA levels of the antimicrobial peptides Attacin A, Cecropin A, and Diptericin in the heads of flies with sws downregulation in glia cells induced after the blood-brain barrier was formed using the Gal80ts tool. We found that sws downregulation in glial cells during adulthood, after the BBB is formed, leads to the increased inflammatory response (new Supplementary Figure 4E).

      To test the brain permeability barrier, the study uses a 10 KDa dextran permeability assay. Almost 25% of brain in controls show a leaky barrier. It would be helpful to describe the causes for this relatively high occurrence. The observed relatively high occurrence of a leaky barrier phenotype in our control group may be attributed to our experimental procedure. We injected flies peritoneally and waited for over 12 hours before dissecting their brains for the permeability assay. Typically, such analyses are conducted after shorter periods, often around 2 hours. Additionally, we used Dextran with the smallest molecular weight (10kDa). The blood-brain barrier (BBB) is not 100% impermeable, and small molecules can gradually enter the brain over time. Recent studies have shown that this entry could be facilitated by endocytosis (Artiushin et al, 2018), which could partially explain the presence of Dextran 10kDa in control brains. Considering this, using a larger Dextran (70kDa) in our experiments could have been more accurate. Importantly, we always compared mutants and controls that underwent identical treatment, dissection, and analysis. We conducted experiments in multiple biological replicates to accurately assess the significance of the differences between mutants and controls. Therefore, we are confident that the differences we observed between controls and mutant flies in the BBB permeability are significant. We included all relevant numbers and statistics for these experiments in Supplementary Table 4.

      An important point in the study concerns the increase of free fatty acids as cause of the inflammatory response. The measurements were based on measurements of whole heads, which could include the hemolymph and fat body within the head in addition to brain. However, the causative relationship remains unclear and the question why a leaky blood brain barrier would increase the free fatty acid levels in the body or brain remains mainly an observation at the descriptive level. Here, it would be helpful to design an experiment, which could test the causative links or to modify the interpretation in scheme 6D and adjust the wording in the text. We agree that the causative relationship between a leaky blood-brain barrier and increased free fatty acid levels in the body or brain is currently an observation at the descriptive level and that it would be important to investigate the correlation between a leaky blood-brain barrier, inflammation, and increased free fatty acid levels in greater detail in future studies. In the modified manuscript, we have changed the scheme in Figure 5G and adjusted the wording in the text.

      Related to this, how do the levels of AMP caused by a leaky BBB would compare to an elicited neuroinflammation by the presence of bacteria? The neuroinflammatory response can be accompanied by macrophage entry into the brain following AMP induction. Could the authors detect this response (which could be envisioned as manipulations include pupal development, provided macrophages would persist into adulthood)? This would make a strong point regardless of the outcome. We thank the reviewer for suggesting this excellent experiment. To detect macrophage entry into the mutant brains, we used antibodies (NimC1) and srp(Hemo)>mCherry that label the macrophage cells. We found macrophages in the larval and adult sws mutant brains and also in adult brains upon downregulation of sws in SPG cells (Figure 5E-F and Supplementary Figure 4F-IG. These data additionally support our hypothesis that a leaky BBB in sws mutants induces neuroinflammation, which is accompanied by macrophage entry into the brain following AMP expression.

      Expression of sws is determined using sws-Gal4 driving membrane-tethered GFP. As sws is expressed very widely and classical Gal4 lines tend to be active in the BBB, it is important to provide the exact information about the nature of this driver. We appreciate the reviewer for bringing this to our attention. We have now included information about the line we used to express transgenes in a sws-dependent manner. Specifically, we utilized the y*w*P{GawB}swsNP4072/FM7c line (Kyoto Stock Center 104592), which was generated using the Gal4 enhancer trap element P{GawB} insertion strategy.

      The Material and Methods section should contain a proper Quantification and Statistical analysis section. In the Figures, it would be helpful to refer to the Table reporting sample numbers. As the reviewer suggested, we have now included a Quantification and Statistical analysis section in the Materials and Methods. Additionally, we ensured that all figure legends include a reference to the corresponding tables reporting sample numbers and statistics.

      In Figure 5, it would be important to indicate sample numbers, the nature of the error bar, and show data points together with columns. We agree with the reviewer that it is important to report all sample numbers and statistics. We generated a new Supplementary Table 1 for all qRT-PCT data, and Supplementary Tables 5 containing all "n" values and corresponding p-values. In the Figure Legends, we denoted the type of error bars and deviations, included p-values, and referred to the relevant tables for comprehensive numerical data.

      Minor comments

      On page 8, cell death is visualized using "the apoptotic marker Cas3". It should be Caspase-3. Moreover, it is not clear whether this antibody (directed against vertebrate Caspase-3) recognizes indeed Caspase-3 in Drosophila? This should be formulated more carefully. As the reviewer correctly noted, the Caspase-3 antibody is designed for human Caspase-3. While it has been employed in Drosophila apoptosis research, its specificity for Caspase-3 in Drosophila is unclear. Given the very well-documented apoptosis in sws mutants (Kretzschmar et al, 1997; Muhlig-Versen et al, 2005) and the non-focus on neuronal cell death in this research, we have opted to exclude this information from the supplementary figure. We appreciate the reviewer for bringing this to our attention and for the valuable suggestion.

      On Page 9 (3rd paragraph), the authors report that they "want to understand what signaling pathway is activated." However, the described experiments do not lead to a signaling pathway, but conclude that an antiflammatory response is evoked. This should thus be reworded. Thank you for pointing this out. In the revised version, we state that we wanted to understand whether the compromised brain barrier in sws mutants triggers the activation of any cellular stress pathways, including apoptosis, ferroptosis, oxidative stress, ER stress, and inflammation.

      Figure 1 reports the expression pattern and phenotype of sws; thus, the title of the figure should be extended. Thank you for the suggestion. We have updated the title of Figure 1 to more accurately reflect its content. The revised title is now: NTE/SWS is expressed in Drosophila brain and its loss leads to severe neurodegeneration.

      Concerning the description of phenotypes, the authors use the term "clumps", but it is not clear what this entails (e.g., Page 6, or Figure 6). For the reader, it is also necessary to refer to original studies of moody to understand the septate junction phenotype represented in the figure. As the reviewer suggested, we changed the word “clumps” to “clusters”. We also agree with the reviewer’s recommendation to cite the original work on Moody to acknowledge previous research and enhance the understanding of moody phenotypes. We have now included the relevant citations in the manuscript.

      **Referees cross-commenting**

      I fully agree with the comments of the other two reviewers, as they were complementary and overlapping with mine (e.g. the contribution of age).

      Reviewer #1 (Significance (Required)):

      This study provides a detailed cellular and functional characterization of the swiss cheese phenotype in the blood-brain barrier so far not reported in previous studies, including the team's own earlier publications (e.g., Kretzschmar et al., 1997; Melentev et al., 2021 and Ryabova et al., 2021). Furthermore, it uses cutting-edge technology to provide links to neuroinflammation and neurodegeneration, Previous studies explored neuroinflammation in the brain of Drosophila by challenging the organism with bacteria to mount an inflammatory response (Winkler et al., 2021). Intriguingly, this current study provides evidence, that a leaky blood brain barrier alone could lead to an inflammatory response, and that in turn, treatment with anti-inflammatory agents could reduce the cellular defects in glia and in consequence neurodegeneration. This represents an important conceptual advance that will be of wide interest to neurobiologists interested in glial biology, neuroinflammation and neurodegeneration in Drosophila and in vertebrates. One possible limitation of the study may be that while complex cellular processes have been pinpointed, some of the causative links of the BBB with neuroinflammation remain unexplored, in particular the aspect of elevated free fatty acids/antimicrobial peptides.

      We appreciate the reviewer's recognition of the conceptual significance of our study, revealing that a leaky blood-brain barrier alone can induce an inflammatory response, with subsequent treatment using anti-inflammatory agents and the importance of these findings for neurobiologists. We also thank the reviewer for thorough examination and insightful suggestions. Given that prior studies have demonstrated the induction of neurodegeneration by the overactivation of innate immune-response pathways, especially elevated expression of antimicrobial peptides (Cao et al, 2013), our new experimental data showing increased levels of antimicrobial peptides in aging flies with a defective BBB further strengthen the connection between the BBB, AMPs and neuroinflammation. This link is even more enhanced by the rescue experiments and the detection of macrophage entry in the mutant brains. We trust that the implemented revisions, accompanied by supplementary experimental data, enhance the suitability of our manuscript for publication.

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

      The manuscript by Tsap et al describes a role of NTE/SWS in forming the BBB in Drosophila. Disruption of the BBB in SWS mutants and knockdown flies results in morphological changes of the glia forming the BBB, increased brain permeability, altered lysosomes, and an upregulation of innate immune genes. The experiments to show a function of SWS in surface glia and the resulting changes in permeability are well supported by the experiments and the statistics appears appropriate.

      The authors also show changes in innate immune genes and some fatty acids and that similar changes are found in another mutant affecting the BBB. They discuss that these changes are a consequence of the disruptions of the BBB but also that these changes induce changes in the BBB. To address this and confirm that the changes in immune genes and fatty acids is a consequence of the altered BBB, they should include experiment expressing SWS in the surface glia and measure if that normalizes these changes. Another major aspect that should be addressed is the effect of aging. As the authors point out, loss of SWS causes age-dependent phenotypes (shown by the author and others) and with the exception of figure 3F, the age isn't even mentioned in any of the other figures. Furthermore, at least some of the experiments should be done at different ages to determine whether the phenotype is progressive; this includes the permeability assays and the measurements of immune genes (the latter could also support whether changes in the immune genes affect the BBB or vice versa the BBB changes cause the upregulation of immune genes).

      As the reviewer suggested, in order to establish a connection between age-dependent correlation between neurodegeneration and inflammation, we analyzed the mRNA expression levels of antimicrobial peptides in the heads of both 15- and 30-day-old sws loss-of-function mutants, as well as in flies with sws downregulation specifically in SPG cells (moody>swsRNAi). We found that the expression levels of the antimicrobial peptides are increased in the age-dependent manner in the tested mutants (Figure 5D, red and orange bars). Following the reviewer’s recommendation, we also performed an experiment where we expressed NTE/SWS in the surface glia in a sws mutant background (sws1; moody>sws, rescue). We measured mRNA levels of Attacin A, Cecropin A, and Diptericin in the heads of 15- and 30-day-old flies (Figure 5D, blue bars). The results showed that the levels of all three AMPs were not significantly different or slightly upregulated in the heads of “rescue” animals compared to Oregon R controls (Figure 5D, compare green and blue bars, and see Supplementary Table 1). Importantly, the levels of all AMPs were significantly lower in the heads of 30-day-old rescue animals than in the heads of the same age sws1mutants (Figure 5D, compare red and blue bars, green stars, see also Supplementary Table 1). These findings further support our hypothesis that sws deficit in the surface glia induces an immune response in age-dependent manner.

      We did not conduct the Dextran permeability assay in older flies because approximately 90% of the 15-day-old flies with swsderegulation already exhibited impaired permeability of the BBB. This suggests that the phenotype is quite severe and may not show significant age-dependent progression. Moreover, older mutant flies were extremely weal, and it is likely that they would not have survived the peritoneal injection procedure.

      Lastly, the authors claim that septate junctions are defective in sws mutants. However, this should be confirmed by EM studies (which the authors have already done) besides immunohistochemistry which doesn't provide enough resolution.

      As the reviewer suggested, for a more detailed detection of septate junctions, we conducted additional electron microscopy experiments. The images included in Figure 6D-F show irregular aggregates and disruptions in the structures of septate junctions and membranes in sws mutants compared to controls. Additionally, we display the appearance of tight junctions in moody mutants (Supplementary Figure 5E-F), which look dramatically different compared to sws junctions and, as previously described, appear overgrown.

      Reviewer #2 (Significance (Required)):

      A role of SWS in maintaining the BBB and what consequences this has provides another insight how this protein (and its homolog NTE) affects brain health. Although a function of SWS in glia (as well as in neurons) has previously been described, changes in the surface glia and the BBB is a novel aspect. However, the causative role of SWS on some of the described consequences (see above) should be confirmed. Although the manuscript can add to a better understanding of the connection between disruptions of the BBB and neurodegenerative diseases, which is of interest for a broader field of researchers, the discussion of the results is quite speculative.

      We appreciate the recognition of the novelty of this work and its potential contribution of our manuscript to a better understanding of the connection between disruptions of the BBB and neurodegenerative diseases. We thank the reviewer for the constructive feedback and hope that introduced changes, along with additional experimental data that address the concerns raised, strengthen the proposed role of sws in the formation of tight junctions in the BBB and its age-dependent maintenance.


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

      Summary: The study of the formation and maintenance of the blood-brain barrier (BBB) is a growing field of study, partly due to its strong link with neurological disorders. The BBB depends on the role of multiple cell types and mechanisms. Mutations in the conserved phospholipase NTE/SWS can lead to neurodegeneration, and previous work from the authors shows that SWS loss leads to abnormal glial morphology. In this work, authors use Drosophila to further study this phenotype, showing that SWS is mostly expressed in the BBB-related glia and that its loss leads to abnormal BBB permeability, increased inflammatory response and neural cell death. Interestingly, authors observed a dependence for the BBB-defective phenotype on aging, with important implications for SWS/NTE and neurodegeneration. Overall, the work represents a clear advance in the poorly explored role of NTE/SWS in neurodegeneration, with a broad impact on the understanding of BBB maintenance. This work shows a combination of multiple and appropriate experimental approaches, including confocal microscopy, EM, RT-qPCR, or gas chromatography-mass spectrometry among others.

      Major comments:

      The use of sws1 and sws1/sws4 transheterozygous animals, together with the use of sws RNAi is a solid approach to validate that the reported phenotypes are due to SWS loss. Using these models, the authors performed a convincing structural analysis of the subperineurial glia phenotype, and showed that it is accompanied by a defective BBB, inflammation and neuronal cell death. The key conclusions are properly supported by the data. However, there are some claims in the text that are not supported by any data in the Figures, but only qualifications. This needs to be fixed:

      -Page 6, third paragraph:

      "...we specifically downregulated sws in the nervous system using the double driver line that allows downregulation of sws in glia and neurons (repo, nSyb-Gal4, Suppl. Fig. 2C-Cʹ). Since these animals had the same disorganized structure of brain surface as the loss-of-function mutant..." Supp. Fig. 2C-C' only shows expression of CD8:GFP and nlacZ reporters by repo and nSyb-Gal4, but there is no data showing sws RNAi expression by these drivers.

      We thank the reviewer for noticing these referencing mistakes. We have corrected the references to the expression patterns of the glial and/or neuronal Gal4 drivers (Supplementary Figure 1D, E and F). Bar graph in Supplementary Figure 1C shows RT-qPCR analysis of sws mRNA levels from flies with glial and/or neuronal sws downregulation (repo>swsRNAi, nSyb>swsRNAiand repo, nSyb>swsRNAi), and the images of mutant brains in Supplementary Figure 2 and Figure 2A-C show the surface glia phenotypes in these mutants.

      "...Moreover, downregulation of sws in all glial cells (repo>swsRNAi) resulted in the same phenotype. At the same time, upon sws downregulation in neurons,... (Suppl. Fig. 4)..." Suppl. Fig. 4 only shows nsyb>swsRNAi data but not repo>swsRNAi

      We show now both repo>swsRNAi and nSyb>swsRNAi (Supplementary Figure 2C and 2E, respectively).

      -Page 6, fourth paragraph:

      "Importantly, expression of Drosophila or human NTE in these glia cells rescued this phenotype (Fig. 2H)"

      In addition to the indicated quantifications, it is essential to show some representative data showing the phenotype when Drosophila or human NTE are expressed in glial cells of sws mutant animals. We agree with the reviewer that it is important to show the rescue phenotypes. We have included images of the brain surface of sws mutants that have Drosophila or human NTE expressed in glial cells (Figure 2D and Supplementary Figure 2F).

      -Page 9, last paragraph: "We found that in moody mutants, the surface glia phenotype analyzed using CoraC as a marker could also be suppressed by NSAID and rapamycin (Fig. 5A)." In addition to the indicated quantifications, it is essential to show some representative data showing the phenotype with and without treatments.

      We appreciate the reviewer's suggestion, and as recommended, we have included representative data showing the phenotype with and without treatments in Supplementary Figure 4C-D.

      A more detailed analysis of two aspects of the data would clearly improve the manuscript, whose findings are a bit superficial in the current state:

      • The exact mechanism by which BBB permeability leads to brain inflammation remains unknown. Authors show that accumulation of polyunsaturated fatty acids (known to regulate inflammation) occurs in sws-depleted animals. However, they only observed a correlation between this phenotype and the inflammatory response, while is not clear whether the accumulation of polyunsaturated fatty acids causes inflammation in this model or is a consequence of it. An attempt to rescue the accumulation of polyunsaturated fatty acids (i.e., knocking down a required enzyme for their production) in sws mutants might help to understand this. Also, the fact that the defective BBB phenotype observed in either sws KO and glia-specific KD can only be partially rescued by the use of inflammation inhibitors, suggests that other pathways are involved.

      We agree with reviewer that since the use of inflammation inhibitors only partially rescue the defective BBB phenotype in swsmutants, it implies the involvement of additional pathways. While our data reveal a correlation between the accumulation of polyunsaturated fatty acids and the inflammatory response, whether this accumulation causes inflammation in our system remains to be studied. We have revised the text to ensure that this explanation is clearly stated without overemphasis.

      • While the differences between the phenotypes caused by sws or moody loss are well characterized, it would be key for this work to further study the mechanisms by which sws controls septate junctions. The authors propose the organization of lipid rafts, but some experiments in that direction to check this hypothesis. For example, can authors reproduce the septate junction phenotype of sws mutant (Fig. 6C) by using a different approach to induce defective lysosomes in subperineurial glia?

      We appreciate the reviewer's suggestion for such an insightful experiment. To investigate whether the septate junction phenotype observed in sws mutants can be replicated in mutants with defective lysosomes in subperineurial glia, we downregulated several key lysosomal genes in SPG cells: moody>DysbRNAi, moody>Npc1aRNAi, moody>PldnRNAi, andmoody>spinRNAi (Supplementary Figure 6A-E). We were happy to see that downregulation of any of these genes resulted in abnormal formation of SJs and membrane organization in SPG cells. These additional experiments strongly support our hypothesis that lysosomal control of membrane homeostasis significantly impacts the appearance of SJs. Thank you for this excellent idea.

      The attempt of the proposed approaches above should require about 3-6 months of investment, with limited economic effort, given the availability and diversity of lines found in the existing stock centres such as Bloomington or Vienna.

      The data is presented very clearly, and the methods are adequately detailed, and the experiments and statistical analysis are adequate.

      Minor comments:

      Prior studies are referenced appropriately, but there is a case that should be addressed. On Page 3, first paragraph, regarding the sentence: "However, the molecular mechanisms underlying inflammaging remain unclear". I recommend specifying what is known and what is unknown in the field. Ideally describing (briefly) the knowledge about lipids, inflammaging and neurodegeneration, which are the specific topics of the research. Otherwise, the current sentence is too vague, while there is a lot of work published about it.

      As the reviewer suggested we have extended the first part of our introduction to briefly describe how inflammaging is connected with the BBB, fatty acid metabolism and lysosomal functions.

      The text and figures are clear and accurate. The logic of the experiments and the results are exposed very clearly (for example, the Suppl. Tables are very helpful). There are a few minor issues, however, that should be addressed:

      • Page 4, first paragraph: regarding the sentence: "For various obvious reasons, humans are not ideal subjects for age-related research.", I recommend specifying the main reasons (i.e. life cycle, ethical issues, etc.?).

      Thank you, the main reasons are specified now.

      • I would recommend moving the text "For various obvious reasons...disrupted upon ageing." From its current position to just before "Drosophila melanogaster is an excellent...". This would keep a better logic in the text by explaining NTE first and later introducing the models to study its function. Presenting then Drosophila.

      Thank you, done.

      • To support the sentence "Together, Drosophila satisfies...neurodegeneration during aging", instead of citing so many papers, I recommend citing just one current review about it, since the amount of literature supporting the claim is huge and should not be limited to a few "random" articles. An alternative might be indicating that the lab has used Drosophila for this aim before, and then citing the examples from the literature.

      Thank you for this suggestion, now we referenced few recent reviews and referred to our previous work on the topic.

      • Page 4, second paragraph: if NTE/SWS is going to be used as a synonym for NTE/SWS loss of function (or other type) model, it needs to be specified. Otherwise, refers to the proteins and sentences like "NTE/SWS has been shown to result in lipid droplet accumulation..." are misleading. Thank you for the suggestion; we have now specified that NTE/SWS is used as a synonym for the SWS protein in Drosophila and corrected this throughout the manuscript.

      • Page 4, last paragraph: the first time that "BBB" is used, its meaning should be specified. And three lines below use "BBB" instead of blood-brain barrier.

      Thank you, corrected.

      **Referees cross-commenting**

      I agree with the comments provided by the other reviewers. They are well reasoned and cover some aspects of the work that I did not see. Regarding the main issue, the three revisions point at the same direction, that is the limited analysis about the mechanism underlying the phenotypes.

      Reviewer #3 (Significance (Required)):

      • Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field. This work represents a substantial advance in the understanding of NTE/SWS function in the context of neurodegeneration, and opens potential approaches to treat related disorders (they successfully use anti-inflammatory compounds to ameliorate some of the key phenotypes). However, the findings are a bit superficial in terms of mechanisms, and further analysis (see major comments) would notably improve the significance of the manuscript. This should be realistic and suitable, given the advantages of the Drosophila model and the availability of tools.

      • Place the work in the context of the existing literature.

      The role of SWS in regulating lysosomal function is potentially supported by NTE-deficient mice data (Akassoglou et al., 2004; Read et al., 2009), where different types of neurons show similar dense bodies containing concentrically laminated and multilayered membranes than those observed in this work in Drosophila sws mutant. Potentially, the rest of the work has a translation to mammals, which is supported by the fact that ectopic expression of NTE rescues some of the key phenotypes described in the manuscript.

      • State what audience might be interested in and influenced by the reported findings. Neuroscience in general, since the study of BBB and neurodegeneration has a clear general interest in the whole field.

      • Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. Drosophila; Neurodegeneration; Hereditary Spastic Paraplegia; Alzheimer's disease; Motor neurons; Microglia; Endoplasmic reticulum; Mitochondria.

      Lipid metabolism is the part of the manuscript where I have less expertise to evaluate, only having general knowledge about it.

      We appreciate the positive evaluation of our work, the careful reading, and the valuable suggestions provided by the reviewer, including recommendations for additional experiments and changes in the text. We believe that the implemented changes, combined with the new experimental data, have improved the manuscript, making it ready for publication.

      References

      Artiushin G, Zhang SL, Tricoire H, Sehgal A (2018) Endocytosis at the Drosophila blood-brain barrier as a function for sleep. Elife 7

      Cao Y, Chtarbanova S, Petersen AJ, Ganetzky B (2013) Dnr1 mutations cause neurodegeneration in Drosophila by activating the innate immune response in the brain. Proc Natl Acad Sci U S A 110: E1752-1760

      Kretzschmar D, Hasan G, Sharma S, Heisenberg M, Benzer S (1997) The swiss cheese mutant causes glial hyperwrapping and brain degeneration in Drosophila. J Neurosci 17: 7425-7432

      Muhlig-Versen M, da Cruz AB, Tschape JA, Moser M, Buttner R, Athenstaedt K, Glynn P, Kretzschmar D (2005) Loss of Swiss cheese/neuropathy target esterase activity causes disruption of phosphatidylcholine homeostasis and neuronal and glial death in adult Drosophila. J Neurosci 25: 2865-2873

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      Referee #3

      Evidence, reproducibility and clarity

      Summary:

      In this manuscript the authors are interested in understanding how fission yeast respond to a Nitrogen Signaling Factor (NSF) that has previously been shown to allow Leucine auxotrophs to grow in the presence of Leucine when Nitrogen Catabolite Repression (NCR) is triggered by the presence of a high quality Nitrogen source such as Ammonium Chloride (NH4Cl).

      The authors begin with a screen to identify genes that affect the ability of wild type cells grown near cells with leucine auxotrophy to enhance or abolish NCR phenotype. They screened the non-essential gene deletion library which they manipulate so that it only contains a leucine auxotrophy (unlike the original gene deletion library which contains additional auxotrophies). They identify 137 genes whose deletion allows growth of Leu auxotrophs in the presence of Leucine and Ammonia without the presence of WT cells. These genes are required for NCR. They further identify 203 genes which do not bypass NCR even in the presence of wild type cells, and are thus important for bypassing NCR in the presence of WT cells.

      They then conduct a second screen to identify which of these genes are important for bypassing NCR in response to the Synthetic NSF, 10(R)-hydroxy-8(Z)-octadecenoic acid, by looking for genes which grow in the presence of leucine when ammonia is not present, but do not grow in the presence of leucine when ammonia is present, even when NSF is added. This second screen identifies 117 strains carrying deletions in a gene set enriched for genes related to cellular respiration and mitochondria. They then show that the NSF bypass of NCR is linked to respiration by showing that it is abolished in the presence of the respiration inhibitor Antimycin A, that growth in low levels of glucose can bypass NCR in the absence of NSF< and that cells supplemented with NSF have a higher oxygen consumption rate.

      To gain insight into how the cell responds to NSF, the authors then gather RNA expression data from cells grown in high ammonium concentrations following treatment with NSF relative to a negative control treated only with Methanol (the vehicle into which NSF is dissolved). They argue that the gene expression pattern resembles gene expression data from cells undergoing respiration in glycerol relative to cells undergoing fermentation in glucose. They show that the upregulated genes relate to trehalose synthesis, detoxification of Reactive Oxygen Species, and cellular fusion and the downregulated genes are related to cellular adhesion and flocculation.

      They validate their RNA-seq measurements by showing that the two most highly induced and two most highly repressed genes respond to NSF addition in a dose dependent manner and do not respond oleic acid which is chemically similar to NSF. The most highly responsive gene they identify is an uncharacterized gene, SPBPB2B2.01, which they suggest naming "NSF-responsive amino acid transporter 1" (nrt1). They also show that the nrt1 response is dependent on the culture density, and that the response is present (though the magnitude varies) in YES and in EMM under varying nitrogen concentrations, and that yfp driven by the nrt1 promoter is induced by NSF.

      The authors then investigate the 8 transcription factors that were present in their list of genes required for NSF-mediated adapted growth. They note that Hsr1 was the only one of these transcription factors, indeed the only gene, that was a hit in their screen for NSF-mediated adapted growth and whose expression was induced upon NSF treatment. To see if the activity of the other transcription factors changed in response to NSF treatment, the authors then gathered ChIP-seq data using 6 of these transcription factors as targets for IP. They saw that for Hsr1 and Php3, targets that had increased RNA-seq expression showed an increase in promoter occupancy while for Hsr1, Php3, Adn2, and Atf1, genes that had decreased RNA-seq expression showed a decrease in promoter activity.

      Finally the authors attempt to identify the mode of action of NSF by generating a functionalized NSF with an alkyne tag (AlkNSF) which they then use as a probe to identify NSF binding partners. They first show that AlkNSF does allow bypass of NCR, although at 30-fold higher concentration. Also AlkNSF induces nrt1 expression in a dose dependent manner, although the expression saturates at a lower level and requires a much higher concentration for induction. They then look for proteins that co-purify with AlkNSF compared to a control that was pre-incubated with NSF which was expected to compete off AlkNSF. The only significant protein they saw was Ayr1, which was not identified in their screen and which did not abrogate NSF bypass of NCR when deleted independantly. They saw that Ayr1 deletion actually increases the response of nrt1 and mei2 targets to NSF, and speculate that Ayr1 metabolises NSF and reduces the cell's ability to respond to NSF to bypass NCR.

      They then repeat the affinity purification / mass spec protocol in an Ayr1 delete cells to identify other interaction partners, this time incubating with a higher concentration of NSF, and also comparing to an experiment using Alkeyne Oleic Acid as a control for non-specific binding. The top two specific hits from this assay are Hmt2 and Gst3. NSF was still able to rescue NCR in gst3 deletes, indicating that it was not relevant for the phenotype. Cells lacking hmt2 did not grow in EMM, but did grow in YES when not supplemented with ammonium and when supplemented with ammonium did not grow, and addition of NSF did not rescue growth. They also see that nrt1 and mei2 gene induction in response to NSF is abolished when hmt2 is deleted. They then argue that hmt2, a sulfide:quinone oxidoreductase localized in the inner membrane of mitochondria is a direct target of NSF that triggers a switch to respiratory metabolism and allows bypass of NCR.

      Below are comments that I think ought to be addressed prior to publication (Major comments)

      1. In line 70, the authors state that "S. pombe cells rely on their own BCAA synthesis to sustain growth" when grown alongside Leucine when ammonium is supplied in the media. If prototrophs can inhibit NCR via NSFs in neighboring auxotrophic cells on the same plate, couldn't they also inhibit NCR within their own colony? How do we know that prototrophic cells grown in high quality nitrogen sources along with, say leucine, are not taking up leucine? The fact that leucine auxotrophs cannot grow in high quality nitrogen sources when leucine is present does not imply that wild type cells must use be synthesizing BCAAs rather than importing them. In a recent paper (Kamrad et al Nat. Microbiol. 2023, https://www.nature.com/articles/s41564-022-01304-8), it was shown that S. cerevisiae cells grown in lysine and in high concentrations of ammonium uptake lysine rather than synthesize it as lysine concentrations in the media are increased. I am aware via unpublished results that this is the case for Leucine as well. I would be surprised if the same isn't true in S. pombe. The authors should caveat or remove this assertion.
      2. It is important for the authors to put their observation linking respiration to rescue from NCR in context with findings from a closely related study (Chiu et al 2022) which included some authors from this manuscript and which the authors cite. In that paper, it was shown that the siderefore ferrichrome can also rescue NCR in fission yeast. That paper stated "It is likely that ferrichrome increased mitochondrial activity, which enabled efficient utilization of glucose downstream of the glycolytic pathway" based on experiments in different concentrations of glucose. This evidence seems to support the link between respiration and rescue from NCR proposed by the authors of this manuscript. The authors should acknowledge this closely related and earlier work as it strengthen's the case they are trying to make. They could even test if ferrichrome addition makes cells sensitive to antimycin A (as in fig 1E), but that extra experiment would be optional in my opinion.
      3. In figure 1B for the second screen I do not understand what the photos represent. For the photos, two rows are meant to have no NH4 and also no NSF and the label on that image makes no mention of Leucine supplementation. In the diagram there are two rows that have NH4 and leucine and one row that has no NH4 but does have leucine. I assume the diagram is correct and the labels on the images are incorrect.
      4. It would be important for the authors to put their observation linking respiration to rescue from NCR in context with findings from Chiu et al 2022 which the authors cite. In that paper, it was shown that the siderefore Ferrichrome can also rescue NCR in fission yeast which the authors site which found that a siderephore rescues NCR. Also the authors of that paper stated "It is likely that ferrichrome increased mitochondrial activity, which enabled efficient utilization of glucose downstream of the glycolytic pathway." based on experiments in different concentrations of glucose. This evidence seems to support the link between respiration and rescue from NCR proposed by the authors of this manuscript.
      5. In line 133. The authors state that the 29 mutants that didn't grow under Leucine supplementation either without NH4CL or with NH4Cl whether or not NSF was present were "related to EMM Growth, leucine uptake, or utilization of ammonium as the sole nitrogen source." The first two make sense, but I can't see why a a strain with deletion of a gene related to utilization of ammonium as a sole nitrogen source wouldn't grow when supplemented with leucine. In fact for all the leucine auxotrophs in the screen, if one was to try to grow them with ammonium as the sole nitrogen source they would not grow, so it isn't clear that this screen can identify genes responsible for utilization of ammonium as a sole nitrogen source. The authors should clarify or remove this point.
      6. 203 strains are important for avoidance of NCR (because in the presence of Ammonium and Leucine, as well as a WT strain, they cannot grow). Of these 57 strains can't grow in the presence of a WT strain but they can grow in the presence of NSF. The authors conclude in line 138 that these strains are "likely to respond to a transmissible signal that is different from NSF". This is confusing because deletion of these genes still does allow cells to respond to NSF, however when these cells are growing in the presence of wild type cells (which in their model are releasing NSF), the cells don't grow. I am confused about the nature of the transmissible signal that the authors suggest. It would appear that when these genes are deleted and grown next to a wild type cell which sends the alternative signal and the NSF, the other transmissible signal would inhibits the ability of NSF to release NCR (as NSF can still rescue the gene). It is not clear how the other transmissible signal would work when the gene is present as it is clearly not necessary to rescue growth.

      A simpler explanation might be that there was contamination in the second screen, or that there was a threshold effect - perhaps in the first screen the strains grew just below a threshold and in the second screen it grew just above that level.

      The authors should clarify their interpretation for these strains, and acknowledge any alternative technical explanations.<br /> 7. The authors' efforts to removed confounding effects that might stem from additional auxotrophic alleles made the screen more convincing. However, Fig 1E, 1F, 5B, and 5E were done with EMM+Leu+Ade+Ura, while the initial strain was just done in the presence of additional Leucine. It is unclear why this was done from the text and captions, but I assume it was because they used a strain that was ade- and ura- in addition to being leu-. Given that they had strains without these additional mutations, this seems like a strange choice. The authors should acknowledge that there are possible confounding effects of adding adenine and uracil to the media, and, if they did have additional metabolic deletions, acknowledge that that could possibly be confounding.<br /> 8. Fig 1E, it appears that cells can grow without NSF in the presence of ammonium and additional amino acids after 10 days (although NSF is required for growth at 5 days). This is not a problem for the screen as that was taken at 5-6 days, but it appears as though NSF does not rescue growth so much as speed it up. The authors should acknowledge this when describing the phenotype. It also argues for a quantitative time course growth experiment to compare growth over the course of 10 days with and without NSF, although this would not be necessary to the paper's main argument.<br /> 9. In line 191 and 192, the authors suggest that the "downregulation of flocculation/adhesion related genes by NSF could serve to avoid undesirable mating during growth". If this is the case, I don't understand why mating genes and cellular fusion genes would be upregulated. What do the authors mean by undesirable mating? Wouldn't flocculation increase desirable mating as well? If all mating is undesirable, wouldn't upregulation of mating and cellular fusion genes be detrimental? 10. The authors mention that trehalose is an antioxidant, for which they reference Malecki 2019, however that paper shows no direct evidence of trehalose functioning as an antioxidant under respiratory conditions. It only shows that some trehalose synthesis genes are upregulated when cells are grown under glucose. The authors should identify primary literature to back this statement up, or soften the wording. Also trehalose is known to be a storage metabolite (which is mentioned in Malicki et al 2019, but not in this manuscript). In fact work in budding yeast has show that trehalose can be a shared metabolite that can be produced by respiring cells and used as a fermentable carbon source in communities of budding yeast cells that consist of fermenting and non-fermenting cells (Varahan et al, eLife 2019 https://doi.org/10.7554/eLife.46735). It seems that this role should be considered as an alternative explanation for the induction of trehalose in respiratory cells.<br /> 11. Line 208: The stimulatory effect of NSF on NRT1 decreased with cell density, thus cell density is likely to be an important factor in terms of gene expression. The methods section, text and figure captions do not mention the density at which cells were inoculated/harvested for RNA-seq and other experiments. If that density was more than OD 0.1, then this would be inconsistent with the measurements from Fig 3. Also in fig 3D, The culture density is not mentioned in the figure or the caption, even though the text suggests that for that experiment cells were grown at low density (Lines 212-213). The authors should provide information on density for their experiments in order for them to be reproducible, as they show it is a key factor. 12. In suggesting a name for NRT1 (NSF-responsive amino acid transporter 1), the authors assume that the gene has a role in amino acid transmembrane transport, but they have no experiments showing this phenotype. They mention that it is Inferred from homology with other amino acid transporters. I presume this name has already been approved by Pombase and is not provisional, but it seems that including phenotypes inferred from homology, rather than from experiments is unwise. Do the authors have any other direct evidence that this is a bona fide Amino Acid Transporter? Perhaps a name like "NSF-responsive gene" would be more appropriate.

      Related to this, it appears that the expression level of Nrt1 may be very low (see Fig S2B in which the scale of the RNA-seq track is very small [-1,1] and the amount of expression is very small even when NSF is added). Looking at Fig 2A, the total transcript abundance did not appear to be very low in terms of counts per million (over 100) is this a discrepancy in fig S2B? Perhaps the large fold change is the result of counts very close to zero in the control condition? Also in Fig 3 the nrt1 expression levels did not appear to be especially low and they appeared repeatable. Is the RNA-seq data shown in fig S2B for nrt1 a fluke or am I misinterpreting it? <br /> 13. To show that their Chip-seq worked, the authors showed specific examples of Chip-seq reads for target genes Line 240, "Previously determined target genes of these TFs were significantly enriched in our data set, demonstrating that the experiment has worked (Figure S2A)." Is the significance here, the threshold from fig S2B? If so that threshold should be clearly stated here in the text. If it is the fact that asn1 shows up as "Fil1 bound" is strange as there are no genes that had significant changes in ChIP-seq signals for fig S2B. If there is another threshold the authors should describe it. While some of the examples they showed were convincing (e.g. php3-flag for the php3 regulated gene gln1 and the increased reads for srw1 for the reb1 target srw1), there were some targets that didn't seem to be especially enriched for their designated transcription factor. For example, the gene trx1 which was identified as an Hsr1 binding target had some binding from Hsr1, but more from Php3 and equivalent amounts for many of the other transcription factors. A clear description of how genes are chosen to be significant in the text, alongside references/selection criteria the authors used to select the specific genes shown should be provided to improve reproducability. <br /> 14. In lines 244-246 the authors state that "These differences in TF occupancy were positively correlated with target gene expression changes. That is, individual genes that were upregulated by NSF tended to be more strongly bound by the TFs, whereas downregulated genes were less occupied by the respective TFs (Figure 4A)." This is far from a general trend. The trend is not there for reb1 and fil1. In fact fil1 looks to the eye like it shows a decrease in occupancy for genes with increased expression, and I worry that the authors did a one sided test for significance that would have missed this, although the variability of the genes that don't change in this case is very high, so there could be no significant effect. The authors elaborate on some of the detail in following statements, but they should soften or remove this statement.

      Related to this, in line 254, the authors state: "These results imply that NSF exposure rewires the recipient cell's transcriptional program, for which the TFs Atf1, Adn2, Adn3, Fil1, Hsr1, Php3, Php5, and Reb1 are indispensable (Table S3)." While I am convinced from the RNA-seq evidence and some of the chip-seq evidence that NSF exposure rewires cell's transcriptional program, I am not convinced that the 8 transcription factors they mention are indespensable for rewiring the transcriptional program. While they may be indespensible for the phenotype itself, Reb1, and Fil1 show no no siginificant enrichment in occupancy of upregulated or downregulated targets (Fig 4A) and, along with Atf1, Reb1, and Fil1, have very few genes in which ocupancy is changed significantly (Fig S2B), while no chip-seq experiments were shown for Php5 and Adn3.

      The more specific summary of the data (Lines 250-253) from Fig S2B describing how hsr1 and adn2 have the strongest effects of the transcription factors required for NSF-mediated NCR bypass is a much stronger message for this section. 15. In line 335, the authors state that "in contrast to other communication systems, NSF does not induce noticeable changes in S. pombe's morphology", referring to changins in mating, filamentation, and bacterial biofilm formation. However they do show very clearly that NSF does cause a large decrease in expression in flocculation/adhesion genes. The fact that they do not see a change in morphology is likely due to the fact that the lab strain in the conditions used for this assay do not flocculate. We have recently identified conditions and strains which do exhibit flocculation in this preprint [https://www.biorxiv.org/content/10.1101/2023.12.15.571870v2]. It is likely that if they had a strain and conditions that did flocculate addition of NSF would break up flocculation and thus change the morphology based on their evidence. The authors should remove or caveat this point.<br /> 16. Line 270 Fig 5B: The concentration of NH4Cl listed in the text (374mM) does not match the concentration shown on the figure (748mM). I assume this is a typo but it should be corrected prior to publication.

      Also I have several minor comments to help improve the manuscript.

      m1: Lines 66-70- state that "uptake of the branched-chain amino acids (BCAA) isoleucine (Ile), leucine (Leu), and valine (Val) is suppressed in the presence of high-quality nitrogen sources such as ammonium or glutamate, because the expression of transporters or permeases that are needed for the uptake of poorer nitrogen sources are down regulated (Zhang et al, 2018)." This reference is for S. cerevisiae and is a review. The authors should cite original results in S. pombe if possible, and if that is not available, alert the reader that this result is from a different species.

      m2: It is unclear from the methods section how the images taken for the screens were analyzed. Were they analayzed and scored by hand, or using custom image analysis software. Either way, when publishing the authors should publish the scores for each deletion mutant in their screen. If there was custom image analysis, the authors should mention in their methods the cutoffs which they used to score growth, and consider plotting the data as a supplement so readers can get a sense of how sensitive the screen was.

      m3: The authors identify 137 mutants that did not require NSF signaling to bypass NCR and claimed these genes were required for NCR. It would be helpful and give more confidence in this screen to demonstrate the extent to which the genes identified in this study overlap with any previous genes required for NCR, and whether there was any GO-term enrichment in this set.

      m4: It would be interesting if the authors could speculate a bit in their discussion on why mitochondrial respiration counteracts NCR. Is there something about cells undergoing respiration that would make it easier for them to use BCAAs than to produce them, or conversely something about fermenting cells that makes it easier for them to produce BCAAs rather than importing them?

      m5: It is unclear why Figure 1F has 'MP biomedicals TM' listed in the figure. It doesn't seem to be listed in the caption or the methods. Is this different media than in other experiments? If so, the authors should add that information to the methods or the caption.

      m6: In Line 160, positively influenced is strange wording, do the authors mean "induced"?

      m7: In the section on gene expression change upon exposure to NSF, the authors use a + after each gene name. My understanding is that that notation is meant to refer to strains with the wild type genotype of that gene, and not the gene itself. Shouldn't the gene be italicised in lower case to represent the gene? See: Lera-Ramirez et al 2023 https://doi.org/10.1093/genetics/iyad143.

      m8: In Fig 2A, genes are displayed on a plot that depicts level vs log2FC, but a comparison between the fold change and p-value would be more useful, and I believe DESeq2 should provide an adjusted p-value for these genes. A related issue is that it appears as though there were no biological replicates, though there was data gathered at different time points. In these genome wide experiments, replicates can give confidence to data and help distinguish true change from intrinsic variability of expression in specific genes. Though the authors did qPCR to validate specific results, it would have improved the quality of their systems-level data to have replicates for these and other key experiments (Chip-seq, affinity purification and even the screen).

      m9: Supp Fig S1: To show that similar gene expression profiles exist for other time points, it would be more convincing to show Log fold change 2h vs 4h and 2h vs 6h and show correlation, or else to make a heat map with all genes to see that genes that go up in one condition go up in the other conditions. It is not clear if the red and blue colors are defined for the 2h dataset and then mapped onto the 4 and 6h dataset, or if they are independently assigned for each plot.

      m10: Mbx2 is a key transcription factor related to flocculation and adhesion genes, and its expression is correlated with expression of its targets. If this transcription factor's expression levels decreased in response to NSF, that might strengthen and help explain the decrease in expression the authors observe in flocculation/adhesion genes when cells encounter NSF. If it it does not change, it might also be interesting for readers interested in these phenotypes.

      m11: In Fig 3D, The notation for the Ammonium concentrations for EMM and YES are inconcistent (+ vs parentheses), also the units (mM from the caption) are not on the figure, but the abbreviation "N" is which is confusing and inconsistent with the other plots in which NH4CL is not abbreviated. Additionally, the caption lists additional nutrients in the media for the EMM conditions (Leu, Ade, Ura) which ought to also be listed.

      m12: In lines 233-235, the authors say "One possibility is that they remain bound to their target genes but become activated or deactivated by NSF directly, or posttranslational modification, such as phosphorylation in the case of Atf1". I don't think the authors intend this, but this sentence could be taken to mean that Atf1 has been shown to be phorphorylated by NSF in the reference they site. I think the authors should clarify, i.e. by saying "..such as phophorylation which is known to regulate activity of Aft1 in response to oxidative and osmotic stress [Lawrence et al 2009]".

      m13: In Fig 4B and Fig S2A, there are grey and colored tracks for the chip-seq (- and + NSF), but they are very difficult to see. If grey is in front it is hard to tell how close the colored peak wehn the colored peak is lower. For example, grey is in front for pex7 while color is in front for yhb1. Could the authors add some transparancy so that the data for both conditions could be seen at once? Also there is little information on the control. My assumption for the input(ChIP) sample was that it was cross-linked and sonicated but not immunoprecipitated, but it is not clear what conditions it was in. I would assume it was done without NSF treatment in WT cells, but those details should be added in the caption or methods. In particular, in the input there is a large spike for Gsf2. Do the authors have any explanation for this and does it have anything to do with that gene's NSF responsiveness?

      m14: The authors might consider putting something like Fig S2B (or even a corresponding volcano plot) as a main figure for Fig 4 in addition to the other two panels, as the individual examples from fig 4B are nice to see, but do not give a broad overview of the data.

      m15: In line 348, the wording "Would score" might be better replaced by "would be identified."

      Significance

      Assessment:

      In general I find the authors arguments compelling and their experiments convincing. The initial and follow on screens were well designed and the authors linked respiration and the action of NSF in a convincing way. The analysis of RNA-seq data was also convincing, especially regarding the decreased expression of flocculation and adhesion genes, and the follow up of specific targets gives confidence in the data (though see Major point 12 below regarding the naming and expression levels of nsf1). The identification of hmt2 as a functional target of NSF was compelling and rigorous, and the authors offer an interesting hypothesis to connect this to respiration that could form the basis of future studies.

      At times I thought that some of the interpretation of the results was hard to follow, poorly worded, or off the mark (see comments below). The presentation of the CHiP seq data also felt incomplete, though the influence of Hsr1 and Adn2 on expression of NSF1 targets was convincing. The genome wide assays (RNA-seq, CHiP seq, screen and pull-down/mass spec) could have done with replicates which would have improved statistics and reliability of the results presented for those experiments, although for key messages, the authors followed up with convincing targeted experiments.

      The study represents an advance on recent work in NCR in fission yeast in linking this with the broad metabolic switch between fermentation and respiration, and in that sense makes this of interest to a broader swathe of the microbiology community, outside those interested in metabolic regulation in microbes. In addition to being of interest to applied researchers interested in producing metabolites with yeast and other microbes, the link to cell signaling and, via flocculation and adhesion genes, to microbial multicellular-like phenotypes would make this work of interest to those interested in microbial communities.

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      Referee #2

      Evidence, reproducibility and clarity

      This paper uses the model system Schizosaccharomyces pombe to investigate how the oxylipin nitrogen signaling factor functions to send signals and adapt the metabolism upon a change in nutrients in the environment. Combining genome-wide screens, RNA-sequencing and chemical biology, the authors find that the nitrogen signaling factor triggers a change from fermentation to a respiratory metabolism, through a direct interaction with a mitochondrial oxidoreductase Hmt2.

      Major comments:

      Overall, the manuscript lacks readability and coherence. Quite a lot of genes/TFs and proteins are mentioned, it is difficult to find a coherent story and clear overview and connection between these subparts. The manuscript would benefit from a general proposed scheme/working mechanism in the discussion and streamlining the results and data into a single biological storyline.

      Several statements or results are not sufficiently clear, elaborated or nuanced. The paper would benefit from more explanation and discussion.

      In the discussion section, the authors are not consistently referencing figures.

      179-181: 'GO enrichment analysis of the 92 downregulated genes' but on line 167, it is '74 downregulated genes' that are mentioned. It is unclear where this difference in number of downregulated genes comes from. Similarly, for the upregulated genes. '156 genes' are mentioned on line 181 but only '98' on line 167.

      189: The statement that the downregulation of flocculation could serve to avoid mating, though sounding logical, is undermined by the finding that mating-related processes are upregulated in the experiment. I find this statement rather speculative

      247-249: The statement is too broad, the effects are visible for maybe 3 TFs, the others don't seem to make a difference in occupancy. Also, why are these two highlighted genes of importance (pex7+, yhb1+), this is the first and last time they are mentioned?

      254-256: The statement that these TFs are indispensable may be too strong. Right before, the authors showed that most of these TFs don't change occupancy (and especially Fil1 and Reb1 do not show a correlation with up- and down-regulated genes, nor does Fil1 in FigS2B show a changed ChIP-seq signal).

      365: 'independently of the carbon source'. As far as we can see, all experiments were performed using glucose as the carbon source, so this statement seems too strong as there is no clear proof for this. This could be an easy extra experiment to perform these tests on media with other carbon sources than glucose?

      Fig1E: It is not clear if the experiment was performed with the Wild-Type or a deletion strain. In the case of the WT, colonies grew in the media not containing NSF but in Fig5E and Fig5I, the WT did grow in the media not containing NSF. It could be more relevant to plate out 1 colony like in the second screen. Thus, unless different strains were used for both experiments, the results seem inconsistent with each other, which is not mentioned in the manuscript.

      Fig1E, Fig5B, Fig5E, and Fig5I: For these experiments, different nitrogen concentrations were used depending on the media, but this has not been addressed/mentioned in the manuscript.

      Minor comments:

      53-57: I would like more elaboration on why CCR and NCR are important for virulence of human pathogens or relevant for industrial applications, and link back to this in the discussion. Otherwise, it is superfluous to include this in the introduction.

      108: Does having a h- library have any impact on the outcome compared to the original h+ library?

      170: Why would only one of the 117 NSF-linked genes change expression in the RNA-sequencing experiment? Any explanation as to why the expression remains unchanged for the 116 other NSF-linked genes?

      212: Please elaborate the discussion of these results. I understand the point that at low cell densities, the cells do not produce NSF as much, and thus adding NSF induces nrt1+. However, the added value of testing this in different media is unclear, especially when the results of strength of increase in nrt1+ show the opposite trend for the two different media between low and high nitrogen content.

      216: Why was the ADH1+ promoter chosen as a 'negative control'?

      284-288: Fig5E: To test whether AYR1 is indeed metabolizing NSF (and thus supporting this statement), an overexpression strain of AYR1 could be made to see if it grows on the EMM + NH4Cl without NSF added.

      385: 'NSF would not strictly revoke NCR only, but also CCR': the authors should try to provide experimental evidence, citation(s), or clearly state it to be a hypothesis. This comment links back to the major comment on line 365.

      405: typo: strains were validation, should be 'validated'

      644: typo: '+' sign not in superscript

      Fig1G: Could the differences in OCR be due to differences in growth rate or remaining glucose? It could for instance be that the culture in the control condition grew less fast, thus still having glucose and therefore still in fermentative metabolism. Showing or mentioning growth rates, nutrient concentrations could help to strengthen this finding.

      Fig2A: The top two 'most' upregulated genes (nrt1 and mei2) were taken along for additional experiments. However, one gene with a significant upregulation labeled in red on the left seemingly shows stronger induction than the second gene (mei2). Why was this gene not taken along?

      Fig2C: the x-axis label is not immediately clear to the reader.

      Fig4B: typo: 'non treatmentt'

      Significance

      This manuscript advances our understanding of nitrogen signaling pathways and nitrogen catabolite repression in the model organism S. pombe. Specifically, it shows how a nitrogen signaling factor functions to send signals and adapt the metabolism upon a change in nutrients and reveals that this nitrogen signaling factor triggers a change from fermentation to a respiratory metabolism. These findings are relevant for the broad fields of applied microbiology, signal transduction and metabolic regulation. Relevant literature is appropriately cited, although the links with Crabtree repression in S. cerevisiae are perhaps not fully supported.

      This manuscript was reviewed by experts with expertise in S. cerevisiae, Crabtree effect, respiration-fermentation balance, adaptation to changing environments.

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      Referee #1

      Evidence, reproducibility and clarity

      Summary

      We have now reviewed the manuscript by the groups of Dr. Bühler and Dr Yashiroda entitled: "Nitrogen signaling factor triggers a respiration-like gene expression program". We have enjoyed the topic, the experiments and the science behind it all. The authors study here one part of the fission yeast 'quorum sensing'-like mechanism of counteracting NCR, mediated by the small molecule NSF: they identify pathways required to respond to NSF, and more specifically determine the mechanism by which NSF counteracts NCR: triggering respiration. This is a very interesting manuscript, with nicely executed experiments, and the topic is of great interest. Regarding the major comments, they are specific to the current data. The minor comments are questions raised in light of the present set of data, which should be appropriate for future research and future manuscripts.

      Major comments

      1. Consistency with the numbers of mutants/genes should be improved. Line 119: 203 genes, 206 in 4th datasheet of Table S1; line 139: 117 mutants but 119 analyzed for GO analysis (1st datasheet in Table S2); lines 179 and 181: where are these numbers (92 down and 156 up) coming from? (compare with 74 and 98 in line 167) (maybe they come from the merge of 2, 4 and 6 h, but it is not indicated).
      2. Lists of genes up- and down-regulated from the RNA seq data should be provided. GO terms are not useful. Add supplementary table, please.
      3. Comparing the transcriptomic response to that of Malecki et al 2020 in response to Antimycin A (EMBO Rep. 21:e50845) would be useful.
      4. The optical densities and whether NCR has been induced has to be clearly specified in each experiment. For instance, RNA seq data. Line 165: for the transcriptome experiment, NSF is added or not to low density cells (not indicated in results, figure legend nor materials and methods). Should addition of NSF to wild-type strain en MM trigger the same transcriptomic changes?
      5. Fig. 1G: Addition of NSF can enhance oxygen consumption at any cell density? And in prototrophs? And without NCR? Add in figure legend that this has been done at OD600 of 0.01.
      6. Fig. 1 E and F: why 14 d after growth there is not growth at 2% glucose in panel F, but it is 10 d after in panel E? What is EMM Biomedical?
      7. Fig. 2BC: Venn diagrams should be more useful to demonstrate overlap withn the Malecki data.
      8. Fig. 4A: not very useful
      9. Is Hsr1 required for some of the RNA seq changes upon NSF addition? Same with other TFs
      10. Line 287: '...it is tempting to speculate that Ayr1 dampens adaptive responses by metabolizing NSF'. Calculating MEC for NSF in delta ayr1 and in cells over-expressing Ayr1 would be required to confirm this speculation. According to Pombase, cells lacking Ayr1 have their respiratory functions compromised (no growth in galactose, glycerol...), why is so? The opposite should be expected, if NSF-mediated respiration is enhanced in this background.
      11. Regarding the two pull-down experiments, one to identify Ayr1 and the second Hmt2, why different negative controls are used? Is addition of NSF to WCE prior to pull-down also used in the second experiment (with delta ayr1 and AlkOle)?
      12. The data regarding Hmt2 is very interesting. As for delta ayr1, delta hmt2 cells cannot grow in glycerol nor galactose according to Pombase. Is the result shown in Fig. 5J (lack of NSF-dependent activation of nrt1 and mei2 in delta hmt2) a consequence of the absence of the NSF receptor, or is it due to the lack of respiration of this background? Is delta hmt2 really auxotrophic for Cys? Why? In this background, H2S should be enhanced, and Cys and Met biosynthesis improved. In fact, in one manuscript these cells grow fine in SG minimal media (Mol Microbiol 01 42:29), while another report indicates they are auxotrophic for Cys (Genes to Cells 2016, 21:530).
      13. M&M: regarding RNA isolation and sequencing: add info about OD of cultures, genotype (leu1-32?), growth media; also, number of replicates and filtering (fold-change used, Q value...)
      14. M&M, ChIP seq: same as above. Also, MACS2 can be used for the unbiased identification of bona fide TF targets, by using a quantification tool reporting percentage of occupancy upstream the TSS (callpeak function).

      Minor comments

      1. Who triggers NCR? Analysis of 137 genes in Figure 1b.
      2. Synthesis of NSF: how is it regulated, where does it come from?
      3. NCR impairs import of BCAA. How are the aa importers such as Cat1 or Agp3 eliminated from the plasma membrane? Transporter internalization, degradation, transcriptional repression... And how does NSF block the NCR regarding aa uptake? Or aa usage?
      4. How can enhanced respiration by NSF counteract all of the above? How can now leu1-32 cells grow?
      5. Addition of NSF to any cell type would do the same, enhance respiratory rates? With or without previous NCR? Should this signaling molecule also drive different respiratory rates in a cell density-independent manner regarding glucose catabolite repression?

      Significance

      Within this manuscript, the authors study a cell-to-cell communication process, by which nitrogen catabolite repression can be counteracted by a small molecule called NSF. Specifically, the authors demonstrate here that NSF up-regulates respiratory metabolism as a mechanism to overcome the repression of amino acid internalization, which was blocked by excess nitrogen. This is a wonderful manuscript, with splendid data, on a very interesting topic.

  2. Feb 2024
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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:

      In this manuscript the authors study a unique membraneless organelle (MLO) in the developing germline of the wasp (Nasonia vitripennis) and highlights the differences with polar granules, homologous membraneless assemblies formed in the Drosophila germline. They identify that in contrast to Drosophila, the wasp utilises an alternatively spliced isoform of the conserved RNA Helicase, Vasa, where the longer isoform harbours FG-repeats characteristic of nucleoporins. Additionally, they observe striking differences in the assembly of the perinucelar 'nuage' where the nuage components are heavily enriched at the anterior half as a mechanism to effectively silence transposon activity in the anterior nurse cells which are characterised by a high degree of DNA double strand breaks. In the course of oogenesis to embryogenesis, the authors observe that the oosome is dynamic and conserved germ plasm proteins (Osk, Vas, Tud) transition from diffuse distribution (in the oocytes) to a dense Tud shell surrounding there oosome filled with Osk-Vas granules (in the embryo). <br /> While the study provides insights into a novel germline condensate, there are some key questions which need to addressed to support publication.

      Major Comments:

      1. Nasonia expresses two distinct Vasa isoforms differing by 96 amino acids close to the N-terminus. The authors claim that the 96 amino acid insertion is FG-rich and intrinsically disordered providing experimental evidence with Circular Dichroism of the purified 96-amino acid fragment. However the amino acid sequence of the remaining N-terminal region upstream of the folded RecA domain is low complexity with an apparent over-representation of G, R, D, N as well as several FG repeats. Any computational disorder prediction tool (such as, IUPred, D2P2, etc) can be used to predict the sequence disorder of the entire N-terminus. Therefore, it is unclear why the authors claim that the 96 amino acid insertion exclusively confers special advantages and contribute to mesh-like properties to the oosome. Does the Long isoform provide specific advantages? This needs to be addressed. "Computational analysis predicted two alternatively spliced Nv-vas mRNAs, that should result in 92.3 kD and 82 kD proteins ": Please explain the analysis and tools used in methods. Fig. 1d : Please discuss the source and identity of the multiple non-specific bands of the RT-PCR experiment in the figure legends. Fig. 1f : For ease of readers, it is recommended to label the figure panels with stages as well as proteins probed.
      2. Are there sequence similarities between the novel 57-residue NTD of Nv-Osk and the Drosophila NTD (138 amino acid long) present exclusively in Drosophila Long Oskar?
        • Fig. 2c : Consider including corresponding micrographs of the oocyte oosome imaged with AiryScan.
        • Fig 2d,e : Is Osk-GFP cytoplasmic or form peri-nuclear condensates? Is Vasa-mCherry nuclear or cytoplasmic or both? Please include DAPI channels and consider drawing outlines of the cell membrane.
        • Are these S2 cell images completely representative of the localisation patterns of Osk and Vas in the cells or do the authors only observe other phenotypic classes as well? If yes, please include the different classes observed with relevant statistics.
      3. The differential assembly of the 'nuage' between anterior and posterior nurse cells is intriguing and well addressed. The higher degree of nuage assembly coincides with higher amount of DSBs in anterior nurse cells. Is this a cause or a consequence? Exposure to mutagens can induce DSBs uniformly in all nurse cells; will this lead to up regulation of nuage assembly uniformly in all nurse cells?
      4. Dynamic sub-compartmentalization of Tudor to the periphery of the embryonic oosome suggests remodelling of the proteins components post-fertilization.
        • Can the authors perform live-imaging to track oosome dynamics from oogenesis to embryogenesis using FP tagged-germ plasm components? This would provide valuable insights into the assembly mechanism of this giant membraneless organelle.
        • Fig. 4 a, b: Line profiles required to show redistribution of Tudor. What do the three panels per condition indicate? What makes the authors conclude that the Tudor shell is "fibrillar" in nature? Is there any evidence?
      5. Maternal mRNAs form homotypic clusters in Drosophila germ granules (Treck et al., 2015). Where do the maternal mRNAs localise in the oosome? In case they are recruited by Oskar (in line with Drosophila germ granules assembly model), are they diffusely distributed in the oocyte oosome and do they redistribute in the Osk-Vas granules that form at the core of the embryonic oosome? RNA in situ hybridization with a few maternal mRNAs can be done to understand how RNAs are distributed within this giant condensate.
      6. The 'dense-shell liquid core' architecture of the oosome as proposed by the authors lacks any concrete proof. The migration of the nuclei (lines 342-345) can be facilitated by changes in physical properties of the Tudor shell in that particular embryonic stage, promoted in turn by key PTMs, for instance. Moreover, there is no evidence that the core oosome has liquid-like properties. In absence of live imaging and FRAP data, the 'dense-shell liquid core' architecture can not be addressed.

      Minor Comments:

      Line 40: "small spherical or amorphous cytoplasmic granules"; the terms "spherical" and "amorphous" have very different implications-one is for shape and the other indicates molecular organization. Consider re-phrasing.

      Lines 55-57: mention embryonic stages as the Tud re-organization within oosome is a dynamic process.

      Line 63: Is this really addressed in the manuscript?

      Lines 95-97: What about Long Oskar in Drosophila? There is a 138 amino acid extension 5' of the LOTUS domain.

      Line126: "proteome of the oosome". Proteome analysis would require isolation of the oosome followed by mass spectrometric identification of constituent proteins. Here the authors investigate the conserved germ plasm proteins and not the whole proteome. Please re-phrase accordingly.

      Lines 308-310: "protein-free channels or cavities"- how do the authors know that they are protein free by probing for only three proteins? Consider re-phrasing.

      Significance

      The study describes a giant membraneless organelle in the developing wasp germline by developing an important set of tools and reagents necessary to study this novel organelle in greater depths in future. Experiments are well designed and validations of the tools developed are adequately carried out. However, the study is largely descriptive and the suggested experiments need to be performed to provide deeper insights into the significance of the work.

      Considering the existing resources on assembly of germ granules by liquid-liquid phase separation, the 'oosome' represents another class of germ granules whose mechanism of assembly, dynamics and physical properties appear to be distinct from Drosophila polar granules as well as P-granules in C. elegans. Therefore, the work is significant in the fields of condensate biology and germline development as further studies focussing on the oosome can elucidate not only the molecular principles underlying oosome assembly but also address the plasticity in assembly of homologous MLOs across evolution.

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      Referee #2

      Evidence, reproducibility and clarity

      Summary

      In this study, Kharel et al use endogenous antibodies to characterize the dynamics of germ granule components throughout development in the wasp Nasonia vitripennis. The authors observe several key differences in Nasonia germ granules as compared to the more well-studied germ granules of Drosophila. Kharel et al describe a novel isoform of the conserved granule component Vasa, which in Nasonia contains an FG domain. The authors use super-resolution microscopy to describe a core/shell architecture for the oosome, the single large germ granule that forms in the oocyte cytoplasm. Additionally, the authors find that a subset of Nasonia nurse cells have comparatively higher levels of perinuclear nuage which they hypothesize is related to high levels of DNA double strand breaks. The authors propose that these observed differences in conserved germ granule components may support the unique demands of germ granules in Nasonia.

      Major comments

      1. In many instances the authors make strong statements that are not directly supported by the presented data. For example, in the Abstract (line 62) the authors write "Our results point to the high degree of plasticity in the assembly of membraneless organelles, which adapt to specific developmental needs of different organisms, and suggest that novel molecular features of conserved proteins result in the unique architecture of the oosome in the wasp." Indeed, the authors have described several differences between germ granules in Drosophila versus Nasonia, but they have not presented data indicating that these differences are functionally relevant. They have also not shown that these differences result in the unique architecture of the oosome. The authors may of course speculate about the functional significance of their observations in the Discussion (emphasizing that certain statements are speculative), but should tone down or limit such statements in the Abstract and Results.

      A few more examples of over interpreted data:

      a. In line 111 of the Results the authors write: "Our data suggest that the Nv-Tud shell provides mechanical stability to contain a less dense oosome core during its migration in the early embryo." The authors have only observed an enrichment of Nv-Tud at the periphery of the oosome, which is not quantified. The authors have not performed experiments to test whether this enrichment is required for oosome integrity, or whether the core of the oosome is less dense.

      b. In line 113 of the Results, the authors state: "Nasonia egg chambers have distinct subset of nurse cells in anterior that show evidence of double-strand DNA breaks and assemble higher amounts of perinuclear nuage than their posterior counterparts, indicating a higher demand for anterior nurse cells to silence transposable elements." Indeed, a subset of nurse cells have strikingly higher levels of nuage, and a subset have significantly higher levels of gH2Av staining. However, a link between high levels of nuage and a need to silence transposable elements seems speculative.

      c. In line 421, the authors summarize their conclusions: "the assembly of the oosome...relies on the combination of highly conserved components...as well as a suite of novel features, including a novel Nv-Vas isoform, an unusual shell of Nv-Tud protein demarcating the edges of the oosome, and unusual distribution of nuage in the ovary." As the data presented in this study is largely descriptive, the authors have not directly tested whether any of these features are required for oosome assembly. 2. Throughout the study, the authors often show single western blots or representative images. To determine reproducibility, the authors should quantify their data whenever possible or indicate the number of independent experiments used to generate a figure. Sample size should be included in the Legends.

      Some examples:

      a. In Figure 1a, the authors show that the short Nv-Vas isoform is decreased in the embryo. How many times was this western performed, and is the short isoform always similarly decreased in the embryo?

      b. In Figure 1d, the authors use RT-PCR to show that multiple vas RNA isoforms are present in ovaries, but only the long isoform is detected in embryos. How many times was the RT-PCR performed and how reproducible was this result? Also, there appears to be a third major RNA species present in ovaries, do the authors think this is relevant?

      c. In Figure 2d, Nv-Osk forms granules when expressed in S2 cells. What fraction of S2 cells expressing Nv-Osk had granules?

      d. In Figures 4 and 6, the authors should quantify core versus shell enrichment for Nv-Tud and other germ granule components (see Major comment 3 below). 3. A main finding of this study is that Nv-Tud forms a fibrillar shell by concentrating at the periphery of the oosome. The authors propose that this shell "fulfills the role of a membrane" (line 371) to protect the integrity of the oosome. This model is based on a handful of images, some of which are not entirely convincing. For example, Nv-Tud does not appear to form a shell in the middle image of Figure 4b. In order to strengthen their model, the authors should quantify the enrichment of different germ granule components in the core versus shell of Nasonia oosomes. Optionally, the authors could directly test a role for Tud in oosome integrity by observing the fate of the oosome core components following tud mutation or RNAi.

      Minor comments

      1. It might be helpful to add the protein structure for Drosophila Vasa for comparison in Figure 1c. Similarly, Drosophila Oskar could be added to Figure 2b.
      2. The authors mis-reference Extended Data Fig 3 as Extended Data Fig 2 (starting in line 198).
      3. In the Figures throughout, it would be helpful to label each panel with the antibodies used. Relatedly, in both the Figures and text the authors should always clarify whether they used antibodies recognizing the long Nv-Vas isoform or the entire Nv-Vas. Also make sure to include MWs for all blots.
      4. For Extended Data Fig. 3d, I'm not sure that migration of an in vitro transcribed Osk "confirms" that the NTD is responsible for the higher molecular weight of Nasonia Osk. Is this experiment is needed?
      5. In Figure 2e, the authors don't observe recruitment of Nv-Vas to Nv-Osk granules in S2 cells, leading to the proposal that "contrary to Drosophila, Nv-Osk does not directly recruit or associate with Nv-Vas in Nasonia" (line 231). It's possible that Nv-Osk is necessary but not sufficient to recruit Nv-Vas, and the authors might consider directly testing this by RNAi depletion of Osk in Nasonia.
      6. The authors should mention and discuss the high level of gH2Av staining in the oocyte nucleus (Figure 3b). Has this been reported before?
      7. The authors find strong gH2Av staining in anterior nurse cells, leading them to write in line 277: "indicating that the same population of nurse cells that assemble high amounts of nuage, shows high level of DSBs." While it is likely that this is the same population, without co-staining of germ granules and gH2Av in the same egg chmaber the authors cannot conclude that this is the same population of cells.
      8. In Figure 3a, the authors note that Nv-Osk is produced in the cytoplasm of nurse cells, where it assembles into granules. It might be worthwhile to use osk RNAi as a control to make sure that the granular Osk signal in their IF is specific.
      9. Unless I've missed it, the authors never reference Extended data Figures 6a and b in the text.
      10. The authors write in line 362: "The spherical shape of these granule, point to their liquid characteristics and their formation inside the oosome core via liquid-liquid phase separation mechanism." Spherical shape alone is not sufficient to conclude liquid-like character or assembly via LLPS.

      Referees cross-commenting

      I might clarify that analyzing maternal RNA localization should be optional (Reviewer 3 Major Comment 5).

      Significance

      In this study Kharel et al use endogenous antibodies to observe the dynamics of conserved germ granule components in Nasonia. This approach allowed the authors to uncover several key differences between germ granules in Nasonia versus Drosophila. While these differences have the potential to be of interest to the specialized germ cell community, the data presented in this study are largely descriptive and not quantified. Therefore, the functional relevance of these differences remains uncertain.

      The finding that a subset of nurse cells have high levels of nuage is quite striking. Furthermore, the authors write in line 405: "The occurrence of DSBs in a distinct population of nurse cells in any organisms has not been reported before to our knowledge." Therefore, this population of nurse cells may be unique to Nasonia and would be of interest to be explored further in future studies. The authors could use granule mutants to test their hypothesis that high levels of nuage are required to silence transposable elements.

      A main goal of this study is to compare germ cell assembly between Nasonia and Drosophila, and thereby identify how unique features of Nasonia contribute to germ granule dynamics and function. Indeed, the oosome is quite unique as an enormous, solitary granule (though perhaps reminiscent of a Balbiani body?), and how it maintains integrity is an open question. The authors propose that Nv-Tud acts as a shell to stabilize the oosome, which would be remarkable for such a large germ granule. This finding could be of interest to a broader field of condensate researchers. Therefore, future studies should directly test whether Nv-Tud is required for oosome integrity. Finally, it would be helpful to the reader to more fully discuss direct comparisons between Nasonia and Drosophila germ granule components. For example, the authors should comment on what is known about isoforms of Drosophila Vasa, and whether Drosophila Vasa may have the potential to be alternatively spliced.

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      Referee #1

      Evidence, reproducibility and clarity

      The manuscript entitled "Dynamic protein assembly and architecture of the large solitary membraneless organelle during germline development in the wasp Nasonia vitripennis" by Kharel et al. aims to examine structural features of the wasp oosome. Specifically, the authors look at the expression of the Vasa and Oskar protein isoforms, their accumulation in the oosome and nuage during oogenesis and early embryogenesis and aim to understand possible functional roles of the structure of these organelles in female germline development.

      However, several conclusions in this paper are not fully supported by the data and some of the experiments need additional experimentation and controls. Below I am listing my concerns (listed in the order they appear in the manuscript):

      Major concerns:

      Lane 141: Extended Data Fig. 1b: Control demonstrating that CIP treatment worked. Lack of change could be due to the enzyme not working.

      Lane 149: To demonstrate a differential splicing pattern the authors need to show PCR using primers spanning the intron that is retained or spliced out. These PCR products should also be quantified using qRT-PCR. The authors should explain the multitude of bands on the PCR gel - the gel presented by the authors is not convincing and shows issues with annealing efficiency (non-specificity) of primers.

      Lane 168-169: "we detected Nv-Vas outside the oosome, distributed in the embryos' cytoplasm (Fig. 1g)." The authors should show a control of the embryo/oocyte stained the same way but without the primary antibody to evaluate background fluorescence in the staining. The images should be quantified and imaged/displayed using the same imaging and normalization parameters as the one shown in Fig. 1g.

      Lane 171: Data showing the result of this mass spec experiment is not shown.3

      Lane 181: Extended Data Fig. 2: This graph is hard to interpret. A control is missing that shows how a curve of the structured protein or an FG-repeat containing fragment of the nucleoporin would look like. As it stands now, it is just a curve that cannot be interpreted by someone who has never used CD spectroscopy to study IDRs.

      Lane 202-203: "The Nv-osk mRNA 3' RACE mapping was consistent with the previously identified 3'-end of Nv-osk mRNA indicating that Nv-Oskis not extended at its C-terminus." Data for this is not shown in this manuscript.

      Lane 204: "However, 5'-end mapping revealed that Nv-osk RNA starts at more than 800 bps upstream of previously predicted Nv-osk transcription start site (Extended Data Fig. 2c)." The authors show a schematic which is not data. Instead, they should show raw dat.

      Lane 213-215: "in addition to major 51 kD band, a less intense ~100 kD band is detected, suggesting the formation of Osk dimers (Extended Data Fig. 3e) consistent with previous finding that LOTUS domain of Nv-Osk dimerizes" The authors are (presumably) running denaturing PAGE gels and they add beta-mercaptoethanol to the samples before they load them on the gel. Therefore, dimerization should not be detected on the gel. The band the authors see must be a contaminant.

      Lane 231: "that, contrary to Drosophila, Nv-Osk does not directly recruit or associate with Nv-Vas in Nasonia (Fig. 2e)." The authors cannot make this conclusion. It is possible that Osk and Vasa interact directly but that one of the proteins requires a post-translational modification for this interaction and this modification does not happen in S2 cells on Nasonia proteins.

      Lane 237: Lack of these specific amino acids in Nasonia proteins does not support the argument that Nasonia Osk and Vasa do not interact. Perhaps changes in amino acids in Vasa are compensated by changes in amino acids in Oskar.

      Lane 243: "co-expressed in S2 cells, fail to form granules (Fig. 2e). Overall, our data suggest that while Nv- Osk has the intrinsic ability to condense into spherical granules..." If the expression of Vasa is not high enough, then Vasa will not phase separate in S2 cells. It is possible that both proteins phase separate but at different critical concentrations, which would explain the lack of granule formation of Vasa in S2 cells.

      Lane 286: "transposon-related gene in Nasonia ovaries, we found no evidence that transposable elements are selectively upregulated in anterior nurse cells (Extended Data Fig. 5b), suggesting that high assembly of anterior nuage is needed to effectively silence transposable elements despite the prevalence of DSBs in anterior" This is an overstatement and incorrect interpretation. Since the staining is not mutually exclusive, the authors can conclude that there is no correlation between dsDNA breaks, nuage and transposon expression and that therefore nuage is not required for the regulation of transposon expression or dsDNA formation. Regardless, the data is correlative and existence of direct connection has not been tested. Lane 293: Control of IF staining without the primary antibody is missing to evaluate background fluorescence in the staining. The images should be quantified and imaged/displayed using the same imaging and normalization parameters. Also, the authors should do a western on oocytes that do not yet form germplasm to demonstrate Oskar protein expression in early oocytes.

      Lane 311: There is no data demonstrating that the oosome has migrated - just two images of an oosome in embryos of different ages. The developmental changes (progression) of the embryo are also not evident. The data currently presented are not evidence of migration. The authors should avoid interpretations connected with migration using the data correctly presented.

      Lane 314: the evidence that Tudor makes a shell is weak and only displayed in an image co-stained for Tud and Osk in Figure 4b. Co-staining of Tud and Vasa in the same panel does not display the shell convincingly. More data is needed to show a shell.

      Lane 314: There is no data showing that the shell is fibrillar.

      Lane 341-345: The authors overinterpret the data. Germ plasm is a cytoplasm and everything in a cell moves through the cytoplasm. This is not in itself evidence of a liquid nature of the oosome.

      Lane 363: Round granule shape is consistent with LLPS but is not evidence for it. The authors should fix their statement.

      Minor concerns:

      Lane 95: Statement" In particular, we provide evidence for the presence of a novel N-terminal segment of Nasonia Oskar (Nv-Osk) adjacent to the conserved LOTUS domain that is absent in other insect Osk proteins." Is not true as written. The Drosophila melanogaster (D mel) Oskar has a N-terminal extension which forms the Long Oskar isoforms. In fact, what the authors report here is that Nosonia Oskar protein is a lot more similar to the D mel Oskar than previously reported by the authors, and that both organisms express long and short Oskar isoforms that with very similar protein structures. The authors should correct their statement.

      Lane 134: Where is this data shown (Subsequently, we were able to confirm Nv-Vas identity of both IP-ed proteins with mass spectrometry.)- no mass spec data is reported in this manuscript

      Lane 171: " ass spectrometry..." is missing an M.

      Lane 200: Extended Data Fig 2b is referencing the wrong figure panel.

      In general, western blots are missing molecular weight standards.

      Lane 265: Tudor is not a component of nuage in D mel.

      Significance

      Overall, I found this manuscript interesting. It provided new insights in the expression of Vasa and Oskar and as well as new models of how these two proteins are regulated and how they accumulate in the oosome. Some of the features, like the newly identified N-terminal extension of Nasonia Oskar protein, appear to be shared with those of Drosophila melanogaster Oskar. This is an important finding because it indicates that mechanism by which Osk functions in the female germline might be conserved in insects.

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      Reply to the reviewers

      Manuscript number: RC-2023-02270

      Corresponding author(s): Usha Vijayraghavan

      General Statements

      We thank all three Reviewers for their thorough assessment of our manuscript and their constructive feedback and comments.

      Point-by-point description of the revisions

      This section is mandatory. *Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. *

      Reviewer #1

      We are encouraged by the very positive comments made on the significance of our study that it provides convincing insights on alternative modes of nuclear positioning and division which is an important question in cell biology. We also took all possible suggestions to improve the interpretation of our results, have also added some newer data to address the constructive points raised by the reviewer.

      Major comments:

      1. A) I am concerned about the lethal phenotype caused by slu7 deprivation. Slu7 deficiency causes defective nuclear positioning at the bud in late G2. This phenotype per se should not cause defective mitosis, so slu7 deficiency may also be interfering with other aspects of mitosis which might indeed impinge on cell viability.

      Response: Our data indeed show Slu7 knockdown has severe growth defect when grown on non-permissive media (YPD) where a two-fold difference in O.D. was seen by 12 hours (Supplementary figure 2.B).

      We agree with the reviewer that defective mitosis, arises from several aspects of cell cycle including those in mitosis. The data we present show G2 arrest, small-budded cells with unsegregated nuclei and large-budded cells with segregated nuclei, all which do not progress through cell cycle phases and contribute to the severe growth defect. Further, GO enrichment analysis of deregulated pathways on knockdown of Slu7 support the above findings as various cell cycle related pathways are abnormal in their expression levels. In this study, we have focused on an in depth analysis of the role of Slu7 in a particular window and uncover how it controls nuclear position for progress G2-M phase cell cycle progression. The likely targets and mechanisms by which Slu7 regulates other phases of the cell cycle which needs similar other deeper investigations in future. Our detailed analysis of nuclear movement in Slu7 knockdown cells grown in YPD for 12 hours showed no nuclear movement (Supplementary figure 3B) which is the terminal phenotype. To examine events that lead to nuclear mispositioning phenotype we investigated the dividing slu7kd cells grown in non-permissive media for only 6 hours; under these conditions Slu7 protein is still detected at lower amount (Supplementary figure 1D). From the studies of nuclear position, mitotic spindle position and dynein distribution in mother and daughter cell, we propose that in the dividing cells, the nucleus does not experience enough force to move inside the daughter bud during mitosis. Further, we delineate the role of Slu7 in the splicing of transcripts for PAC1 encoding a protein whose homolog in S. cerevisiae has a proven role in nuclear migration. In live imaging of slu7kd cells that show nuclear segregation at the start of live imaging, new bud was not formed till the end of 60 minutes, implying that are arrested after transition to mitosis. We could speculate a role for Slu7 through regulation of genes involved in mitotic exit or cytokinesis.

      1. B) Supp. Fig4 shows defective mitosis in TBZ, so TBZ may be exacerbating defective mitosis of slu7-deficient cells.

      __Response: __Studies with yeast and mammalian model systems have revealed that the mobility and repair of damaged DNA are compromised upon disruption of microtubules (Wu et al, 2008; Chung et al, 2015; Lottersberger et al, 2015; Lawrimore et al, 2017; Oshidari et al, 2018; Laflamme et al, 2019). These data point to reasons why the mutants in DNA damage checkpoint genes are sensitive to TBZ. In this context, we observed that CnSlu7 knockdown is also sensitive to MMS stress (shown below). In addition, recent work on human Slu7 in Hela cell lines has elucidated the its role in the maintenance of genome integrity by preventing the formation of R-loops (Jiménez et al, 2019). We suggest that TBZ may exacerbate the defective mitosis of Slu7 depleted cells, however, whether it is particular only to mitosis or to the other cellular processes where the microtubules are involved needs further investigation.

      Throughout the figures it can be observed uneven chromosome/nuclear segregation in cells deprived of slu7, however, these mitotic defects have not been mentioned or explored in depth. From Supp Figure 3C it can be inferred that CENP-A segregation is uneven. Is this correct? Is CENP-A-GFP segregation normal?

      __Response: __ It should be noted that in Cryptococcus, the kinetochore remains unclustered during the early phase of cell cycle, cluster to a single punctum at the end of G2 phase and then de-cluster at the end of mitosis. Since this is a highly dynamic process, its technically challenging to measure the intensity CENP-A in mother and daughter cell. In the fixed cell imaging or live imaging data, there are no appreciable differences in intensity of the GFP signal of the tagged proteins (H4 and CENPA). The uneven chromosome/nuclear segregation observed in certain panels images presented are due to technical issues in that particular stack while generating the montage. This has been re-examined and we infer that there are no major differences in the signals from GFP-H4 and GFP - CENPA through mitosis.

      Additionally, taking the cue from the reviewer’s comment, we examined the likelihood of improper chromosome segregation by evaluating if there are any appreciable cell populations that are aneuploid. We revisited our flow cytometry data, we found no significant difference in the population of aneuploid cells between the knockdown strain and wildtype strain grown in non-permissive condition for 12 hours. This data was assessed again in new experiments where we also analyzed by flow cytometry the ipl1 mutant where aneuploidy is reported (Varshney et al, 2019). It has been reported in Cryptococcus neoformans that aneuploid cells are resistance to anti-fungal drug fluconazole. Preliminary experiments showed that slu7kd cells were sensitive to fluconazole and in this assay were similar to wildtype cells. Hence, we speculate that chromosome segregation is normal in Slu7 depleted cells.

      If chromosome segregation is altered upon slu7 deprivation, this might also explain the drop in cell viability and slow growth rates of this condition.

      __Response: __ From live microscopy imaging and flow cytometry data, we believe that the chromosome segregation is normal in Slu7 depleted cells. Dilution spotting in permissive media after growth in non-permissive media revealed that slu7kd cells resumed growth without losing viability, indicating the arrest phenotype associated with the depletion of Slu7 is largely reversible and does not cause chromosome mis-segregation (figure is now added to manuscript as supplementary figure 2D). Prolonged arrest at various cell cycle phase might lead to cell death and hence drop in cell viability.

      The manuscript will improve if authors analyse chromosome segregation for example, by showing time-lapse images of chromosome dynamics during mitosis.

      __Response: __Chromosome dynamics during the mitotic phase is given below. We observe that the chromosome segregation is equal in both mother and daughter bud. The uneven chromosome/nuclear segregation observed in certain panels images presented in original manuscript were due to technical issues while generating the montage.

      The authors perform an RNA seq comparing wild-type cells with slu7 deficiency and detect changes in gene expression, however, they do not explore from this data the percentage of un-spliced introns genome-wide which might be very informative, even more than changes in gene expression, which many of them, might be an indirect consequence of Slu7 deficiency. Authors should re-analyze the RNA seq data looking for unprocessed mRNAs and provide information about the overall impact of slu7 in intron processing.

      __Response: __ A very detailed bioinformatic analysis of the impact on slu7 on global transcriptome and splice pattern, is an ongoing study in the laboratory. The findings are indeed giving good leads which are being validated by further experiments using mini-gene exon-intron constructs. These studies are extensive and form a future manuscript identifying and characterizing intronic features which predispose an intron towards Slu7 dependency. Therefore, it falls outside the scope for this study on the cell biological role of Slu7 on mitosis, specifically nuclear position to ensure faithful mitotic segregation.

      Minor comments:

      __ __1. "Previous studies of slu7 mutants in S. cerevisiae and the conditional knockdown of its S. pombe homolog". Consider replacing homolog with Ortholog.

      Response: The suggestion is well taken, and the word “homolog” has been replaced with word “ortholog”.

      1. A) Taking these results together, we conclude that the inability of the conditional mutant to grow in the non-permissive media is due to impaired progression through the G2-M phase of the cell cycle. Is the G2/M delay the cause of the slow growth phenotype of the Slu7 deficiency?

      Response: From the live microscopy, we note that even when the budding index for mitosis has been reached the nucleus in slu7kd cells is still in the mother cell and spends more time here rather than reaching the bud or bud neck. We present G2/M delay as ONE of the reasons for the slow growth of Slu7 depleted cells. Although we have showed that Slu7 depletion does not activate MAD2 dependent Spindle Assembly Checkpoint, we have not investigated the activation of other cell cycle checkpoints such as G2 DNA damage checkpoint. These are potential new leads as we infer from our RNA seq datasets that CHK1, TEL1, BDR1 and RAD51 show increased expression in Slu7 knockdown condition when compared to wildtype. It is therefore reasonable to conclude that Slu7 might play a role at various cell cycle phases through direct or indirect effect on genes involved in these phases. Delayed positioning of the nucleus during G2/M is one of the major effects that is investigated in depth in this study.

      1. B) If so, growth defects of slu7 deficiency could be suppressed by ectopic expression of G2/M activators.

      Response: We have not tested this possibility, but we predict that expression of G2/M activators would at best offer only partial rescue the growth defect of Slu7 depleted cells since multiple pathways are adversely affected in cells depleted of Slu7.

      In this line of investigation, we have tested the consequences of PAC1 overexpression, as PAC1 expression levels and splicing are affected by loss of Slu7. We report a partial rescue of nuclear position defect during mitosis, yet these cells were arrested at cytokinesis. Further, the unavailability of an array of suitable auxotrophic (or other) markers in this model system makes it technically challenging to do rescue experiments by overexpression of multiple candidate downstream genes.

      Supp Figure 3C, remove the drawing on the right. Adjust times relative to panels.

      Response: The drawing has been removed and the time points have been adjusted.

      1. Tracking the nucleus in wild-type cells with a small bud showed that the nucleus moved into the daughter bud, divided into two, and one-half migrated to the mother bud (Supplementary Figure 3B, top row).

      Please replace the sentence: "one-half" with "one of the daughter nuclei". Additionally, as this nuclear positioning occurring during late mitosis is due to spindle elongation, I would not use the term migrated but "positioned" or "moved". Nuclear movement into the bud, which is referred to as "moved", can indeed be named "migrated".

      Response: The word “migrated” in the above sentence has been replaced with the word “moved”.

      1. Indicates in Figure 2B the marker used (GFP-H4), as in Fig Supp 3B.

      Response: The marker has been indicated in the figure.

      1. Nuclear division initiates in the bud, and one of the divided nuclei with segregated chromosomes migrates back to the mother cell (Figure 2B, top panel, wildtype, quantified in Figure 2C grey bar).

      As mentioned before, I would not name this, nuclear migration as it is the result of spindle elongation, and it can be confusing or misleading for non-expert readers.

      Response: The word “migrate” in the above sentence has been replaced with the word “move”.

      1. These two conclusions should be revised and described in temporal/sequential order.
      2. Thus, we identify that the depletion of CnSlu7 severely affects the temporal and spatial sequence of events during mitosis, particularly nuclear migration and division.
      3. Together, these results confirmed that without affecting the kinetochore clustering, depletion of Slu7 affects nuclear migration during the G2 to mitotic transition in Cryptococcus neoformans.

      Response: We thank the reviewer for bringing out the clarity in the concluding statements. These has now been revised to read as follows:

      “Together, these results confirm that without affecting the kinetochore clustering, depletion of Slu7 affects nuclear movement during the G2 to mitotic transition in Cryptococcus neoformans. Thus, we identify that the depletion of CnSlu7 severely affects the temporal and spatial sequence of events during mitosis, particularly nuclear migration, and division.”

      1. In slu7d cells, in cells with small buds, numerous cMTs were nucleated from the MTOCs, and as the cell cycle progressed, they organized to form the unipolar mitotic spindle (Figure 3A, slu7kd GFP-TUB1 panel, time point 55 mins).

      Please, revise whether the term unipolar mitotic spindle is correct here.

      Response: The word unipolar has been removed.

      1. I suggest including page and line numbers in the manuscript to facilitate revision.

      Response: We regret missing out this formatting guideline. The Page and line numbers have provided.

      Reviewer #2

      We are thankful by the very positive comments on the significance of our work, its novelty and findings being of broad interest to microbiology; splicing; cell cycle and cell division communities. We respond to all comments raised below.

      1. The authors test the Mad2-dependent spindle assembly checkpoint and show that it is not relevant for slu7-depletion. This is as expected if the defect is in nuclear positioning. They could test other checkpoint pathways that would monitor nuclear positioning in budding yeasts. Perhaps they have considered this: Bub2, Bfa1, Tem1, Lte1 mutants? I don't think this experiment is essential for publication, but it could strongly support their model.

      Response: We appreciate the comment on other checkpoints operating during mitosis. However, we have not done these experiments to examine role of components that arrest mitosis (Bub2, Tem1 etc.) in response to spindle or kinetochore damage. We hope the reviewer appreciates that this line of work would require the generation of bub2Δ strain and extensive characterization for their role in checkpoint in Cryptococcus before it can be brought into strains compromised for Slu7.

      __ Minor comments:__ 1. in Figure 3, Dyn1-GFP is imaged and in many of the cells in which Slu7 is depleted, nothing (or very little) can be seen. It is later argued that this is an indirect effect, due to defects in Pac1 and associated functions. Have the authors attempted a Dynein western blot (the 3xGFP tag should be quite sensitive)? It would be good to demonstrate that the Dynein motor complex hasn't simply fallen apart and Dynein been degraded in the slu7-depletion.

      Response: A study in S. cerevisiae has reported the dynein expression does not change in pac1Δ cells (Lee et al., 2003). Since the molecular weight of CnnDYN1 along with the tag is 630kDa, we did attempt the very challenging experiment of western blot to check for the expression levels this very large protein in wildtype and slu7kd cells. Based on the reviewer’s suggestion, we have attempted dot blot of protein lysates from wild type and from slu7kd cells probed with anti GFP antibody for estimating DYN-GFP levels. Untagged WT H99 strain was used as negative control. The same blot was stripped and re-probed for PSTAIRE which served as a loading control. This experiment revealed that dynein levels are same in both wildtype and slu7kd cells.

      in Figure 7: have any intronless genes been tested for rescue of the post-mitotic delay/arrest? This is not necessary for publication, but if any have been tested already, they could be listed here.

      Response: We have not tested intronless genes for their role in the rescue of post mitotic delay/arrest. From the RNA seq data, we observed that most of the genes involved in mitotic exit network (MEN) and cytokinesis were highly expressed in slu7kd cells as compared to the wildtype indicating and indirect role for Slu7 in their expression level. So, we had validated three candidates MOB2, CDC12 and DBF2 by qRT PCR (Supplementary 7.D) and found they were upregulated in slu7kd cells and hence speculate that deregulation of these transcript could contribute to the post mitotic arrest in slu7kd.

      In SFig2C legend make it clear that these cells are HU arrested at time zero. Are the cells in glucose or galactose during HU treatment.?

      Response: We regret the lack of clarity in the legend and the required details have been added. The cells were initially grown in non-permissive media for 2 hours to deplete Slu7 and then HU was added to the non-permissive media and the cell were allowed to grow for 4 hours.

      in SFig4, the TBZ sensitivity isn't very convincing as the slu7kd strain is struggling to grow at all on YPD.

      Response: We agree with the reviewer comment on the growth of slu7kd cells on media YPD containing TBZ. TBZ may exacerbate the defective mitosis of Slu7 depleted cells, however whether it pertains only to mitosis or any cellular processes where microtubules are involved requires further investigation.

      In SFig5 legend the volcano plot needs to be better explained. What are the dashed lines etc. ?

      Response: We regret missing these details on the volcano plot which has now been added to the legend.

      __Reviewer #3 __

      We appreciate the views that our work provides strong evidence to support out conclusions that Cryptococcus neoformans Slu7 controls mitotic progression by efficient splicing of cell cycle regulators and cytoskeletal elements. We have taken all comments of the reviewer into account to revise our manuscript with additional data, and by improving the presentation. The key additional data are summarized below.

      Major comments:

      1) The authors claimed that CnSlu7 is the most divergent among the fungal homologs and closer to its human counterpart (Fig. 1A, Supplementary Fig 1A). -Just based on the phylogenetic tree including limited members, as in Supplementary Fig. 1, it cannot be concluded that CnSlu7 is closer to its human counterpart since the basidiomycete yeast such as C. neoformans itself is more closely positions to humans compared to the ascomycete yeasts S. cerevisiae and Sch. pombe in phylogenetic tree analysis. It is strongly recommended to include other fungal species from the Basidiomycota, such as Ustilago maydis, in phylogenetic analysis in Supplementary Fig. 1. - Conservation analysis among diverse eukaryotes is more meaningful data that the conservation withing the fungi group, so that it is recommended that the data of Fig. 1 A would be replaced with the revised Supplementary Fig 1. -The analysis data on amino acid identities among Slu7 homologues should be presented to support the claim.

      Response: We agree with the reviewer that our data would be better served by an improved analysis of the phylogenetic relationship between various Slu7 homologs. We have therefore reconstructed the phylogenetic tree by including other fungal groups. This is presented here and also in the revised manuscript Supplementary Figure 1A. These data too, show that Cryptococcus (deneoformans and neoformans) Slu7 is the most diverged among its homologs from various fungal species with its closest homologs being other pathogens Puccinia graminis and Ustilago maydis.

      2) Despite that CnSlu7 is the main key subject, the comparative analysis of CnSlu7 to the previously reported Slu7 homologues, in the aspect of functional domain organization, is not provided in the present manuscript. - It was reported that Slu7 contains the four motifs that control its cellular localization and canonical function as a splicing factor, such as a nuclear location signal, a zinc knuckle motif, four stretches of leucine repeats and a lysine-rich domain. Notably, human Slu7 protein is 204 amino acids longer than S. cerevisiae homolog with only 24% identity in the zinc knuckle motif (Molecular Biology of the Cell Vol. 15, 3782-3795). Thus, it is strongly recommended to provide additional information on the conserved and diverged features of CnSlu7 compared to other Slu7 homologs as a part of revised Figure.

      Response: The multiple sequence alignment of Cryptococcus neoformans Slu7 with its fungal and higher eukaryote homologs such as human Slu7 and plant Slu7 proteins revealed that only the CCHC zinc finger motif is highly conserved. We do not detect conservation in the nuclear localization signal, stretch of leucine repeats and lysine rich domain except for leucine 3 stretch near the C terminal. This additional information is presented in revised Figure 1A.

      3) The manuscript clearly demonstrated that one of key targets of Slu7-mediated splicing is PAC1 in C. neoformans. Considering, Pac1 is also conserved from S. cerevisiae to human, it could be speculated that the defect of Slu7 can affect nuclear migration in other fungal species and human cells by inefficient splicing of PAC1, despite striking differences in their nuclear position during cell division. Please discuss this possibility or provide the qRT-PCR analysis data of PAC1 homologs in the available fungal Slu7 mutant strains.

      Response: Cell cycle arrest phenotypes of splicing factor mutants (studied largely in budding and fission yeast) results from inefficient pre-mRNA splicing of cell cycle-related genes. Slu7 is a well characterized second step splicing factor in S. cerevisiae where in vitro splicing assays with ACT1 minigene transcripts with a modified single intron showed ScSlu7 is dispensable for splicing when the branchpoint to 3'SS distance is less than seven nucleotides in the mini transcript (Brys and Schwer, 1996). In fission yeast we reported the effects of metabolic depletion of Slu7, which is an essential gene (Banerjee et al., 2013) and showed unexpectedly that in addition to BrP to 3'SS distance new intronic features contributors of dependency of fission yeast intron containing transcripts on Slu7 functions. The work also showed in multi-intronic transcripts its role is intron-specific and thus the candidate gene/ transcript is likely to be to dependent on Slu7 by virtue of the intronic features and not its biological function. In this study a splicing dependent role of CnSlu7 in cell cycle progression is investigated where based on a strong nuclear mis-positioning phenotype we narrowed on PAC1 transcripts as one of targets. We show PAC1, encoding a cytoskeletal factor, has introns dependent on CnSlu7 for efficient splicing and show partial rescue of nuclear position in strain complemented with expression of an intronless PAC1 gene. In this scenario, while it is likely that in other species where PAC1 exon-introns nucleotide sequences are similar to that in Cryptococcus a role for Slu7 may be predicted, for validation by other experimentalists.

      Interestingly, PAC1 in S. cerevisiae is an intronless gene and its homolog is not annotated in S. pombe. In human cell lines, knockdown of Slu7 by siRNA resulted in metaphase arrest by inefficient splicing of soronin – which is crucial in sister chromatid cohesion and correct spindle assembly, according to recent research in human cell lines (Jiménez et al., 2019).

      Hence the roles of splicing factor in cell cycle is through splicing of targets involved in cell cycle wherein the targets regulated by splicing factor may or may not be conserved in other species.

      Minor comments:

      General points 1) Provide information on the marker sizes in the data of qRT-PCR analysis presented in Figures 5 and 6, and Supplementary Fig 2A.

      Response: We regret the omission of this technical data and have corrected the same by providing the marker sizes in all the figures.

      2) Please unify the format of gene names. Some genes were written with superscript of "+", such as CLN1+ and PAC1+ in Fig. 4. What does "+" mean in the gene names?

      Response: We have taken the suggestion to carefully review the nomenclature of genes and their expressed transcripts as is typical for Cryptococcus neoformans. To depict the wildtype form of transcript we had used +. Thus CLN1+ was used to denote Cyclin 1 cellular transcript from expressed from its own locus without any modification of promoter or the intronic features.

      3) Supplementary Figure 1 C: Please correct "Slu7KD" 6 hrs YPD to "slu7kd" 6 hrs YPD.

      Response: This error has been corrected.

      4) Supplementary Figure 2A: What do "mRNA" and "No RT29X/", respectively, indicate?

      Response: The mRNA indicates the spliced form across any intron after intron is spliced out, so denotes exon-exon sequences in the mRNA. The reactions marked as “No RT 29 X” denote semi- quantitative PCR performed on DNase treated RNA sample, without reverse transcription to generate the cDNA. These reactions were done to confirm that there is no genomic DNA present in the RNA sample used for reverse transcription reaction of the cellular transcripts. Some of these details are now included in the Supp Fig 2A legend.

      5) Supplementary Figure 4C: Please provide brief explanation in the text on why the authors employed mad2Δ slu7kd cells.

      Response: In Page 8, line 6, we had provided the rationale for generating and studying mad2Δ slu7kd strain. This is recapitulated below:

      “To investigate whether Slu7 knockdown triggers the activation of spindle assembly checkpoint (SAC), we generated a strain with conditional slu7kd in cells with mad2Δ allele and the GFP-H4 nuclear marker.”

      6) Supplementary Figure 6D legend: Please correct the description of "slu7kd SH:Slu7 FL" from "expressing intronless PAC1" to "expressing full length of SLU7".

      Response: The error in the legend is regretted and this has been corrected.

      7) Supplementary Figure 7D: The authors confirmed that MOB2, CDC12, and DFB1 were expressed at higher levels in slu7kd when compared to wildtype. Please briefly explain in the text why the expression level of these genes in slu7kd was mentioned.

      Response: slu7kd cells expressing intronless Pac1 arrest post nuclear division. Revisiting our transcriptomic data, we found that genes involved in mitosis exit network and cytokinesis, such as DFB1, MOB2, CDC12, BUD4, and CHS2, were deregulated in slu7kd when compared to wildtype. We confirmed the same by performing qRT PCRs for three candidates, MOB2, DBF1 and CDC12 and that these transcript were expressed at high levels in knockdown when compared to wildtype.

      8) The species name should be written as abbreviation after the first mention. For example, please correct Cryptococcus neoformans to C. neoformans throughout manuscript.

      Response: The suggestion is well taken, and the required edits have been made throughout the text.

      9) Please unify the format of paper titles listed in References.

      Response: This formatting error is regretted and corrected to have all references in a single format.

      10) No page information for Hoffmann et al (2010) in References.

      Response: This omission is corrected.

      11) Update the information on the published journal of Chatterjee et al. (2021) in References.

      Response: This omission is regretted and is now corrected.

      12) Information on the authors, title, published journal and pages should be provided for the papers (Yadav and Sanyal, 2018; Sridhar et al., 2021) in Supplementary Table 1, which were not included in the main Reference list.

      Response: The references are now added to the main list.

      References used for addressing the reviewer’s comments:

      1. Chung DKC, Chan JNY, Strecker J, Zhang W, Ebrahimi-Ardebili S, Lu T, Abraham KJ, Durocher D, Mekhail K (2015) Perinuclear tethers license telomeric DSBs for a broad kinesin- and NPC-dependent DNA repair process. Nat Commun doi:10.1038/NCOMMS8742.
      2. Jiménez M, Urtasun R, Elizalde M, Azkona M, Latasa MU, Uriarte I, Arechederra M, Alignani D, Bárcena-Varela M, Alvarez-Sola G et al (2019) Splicing events in the control of genome integrity: Role of SLU7 and truncated SRSF3 proteins. Nucleic Acids Res 47: 3450–3466. doi:10.1093/nar/gkz014.
      3. Laflamme G, Sim S, Leary A, Pascariu M, Vogel J, D’Amours D (2019) Interphase Microtubules Safeguard Mitotic Progression by Suppressing an Aurora B-Dependent Arrest Induced by DNA Replication Stress. Cell Rep 26: 2875-2889.e3. doi:10.1016/J.CELREP.2019.02.051.
      4. Lawrimore J, Barry TM, Barry RM, York AC, Friedman B, Cook DM, Akialis K, Tyler J, Vasquez P, Yeh E et al (2017) Microtubule dynamics drive enhanced chromatin motion and mobilize telomeres in response to DNA damage. Mol Biol Cell 28: 1701–1711. doi:10.1091/MBC.E16-12-0846.
      5. Lee WL, Oberle JR, Cooper JA (2003) The role of the lissencephaly protein Pac1 during nuclear migration in budding yeast. J Cell Biol. doi:10.1083/jcb.200209022.
      6. Lottersberger F, Karssemeijer RA, Dimitrova N, De Lange T (2015) 53BP1 and the LINC Complex Promote Microtubule-Dependent DSB Mobility and DNA Repair. Cell 163: 880–893. doi:10.1016/J.CELL.2015.09.057.
      7. Oshidari R, Strecker J, Chung DKC, Abraham KJ, Chan JNY, Damaren CJ, Mekhail K (2018) Nuclear microtubule filaments mediate non-linear directional motion of chromatin and promote DNA repair. Nat Commun doi:10.1038/S41467-018-05009-7.
      8. Varshney N, Som S, Chatterjee S, Sridhar S, Bhattacharyya D, Paul R, Sanyal K (2019) Spatio-temporal regulation of nuclear division by Aurora B kinase Ipl1 in Cryptococcus neoformans. PLoS Genet doi:10.1371/journal.pgen.1007959.
      9. Wu G, Zhou L, Khidr L, Guo XE, Kim W, Lee YM, Krasieva T, Chen PL (2008) A novel role of the chromokinesin Kif4A in DNA damage response. Cell Cycle 7: 2013–2020. doi:10.4161/CC.7.13.6130.
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      Referee #3

      Evidence, reproducibility and clarity

      Summary:

      The manuscript by Krishnan et al. reports the key role of a RNA splicing factor CnSlu7 in mitotic progression during the cell cycle of Cryptococcus neoformans, an intron-rich human pathogenic yeast. Using a conditional knockdown strategy and a time-lapse live imaging analysis of C. neoformans cells expressing a set of fluorescently tagged cell cycle markers (GHF-H4, GFP-CENPA, and GFP-TUB1), the authors clearly demonstrated the defective nuclear movement and cell division during mitosis under Slu7 depletion conditions. The global transcriptome analysis of the Slu7 knockdown strain revealed the downregulation of transcripts encoding several cell cycle regulators and cytoskeletal factors for nuclear migration, including PAC1. The requirement of PAC1 splicing by CnSlu7 for nuclear migration was validated by the rescue of nuclear migration defects in the CnSlu7 knockdown cells complemented with an intron-less PAC1 minigene, although the PCA1 complementation did not recover cell division defects. Based on their findings, the authors conclude that Slu7 ensures nuclear positioning during mitotic progression through RNA splicing in C. neoformans.

      Major comments:

      Overall, the manuscript provides a set of evident strongly supporting its conclusion that Slu7 controls cell cycle mitotic progression by efficient mRNA splicing of several cell cycle regulators and cytoskeletal factors in C. neoformans. However, there are a few points to be clarified and complemented by providing additional informatic analysis data and explanations in more detail.

      1. The authors claimed that CnSlu7 is the most divergent among the fungal homologs and closer to its human counterpart (Fig. 1A, Supplementary Fig 1A).
        • Just based on the phylogenetic tree including limited members, as in Supplementary Fig. 1, it cannot be concluded that CnSlu7 is closer to its human counterpart since the basidiomycete yeast such as C. neoformans itself is more closely positions to humans compared to the ascomycete yeasts S. cerevisiae and Sch. pombe in phylogenetic tree analysis. It is strongly recommended to include other fungal species from the Basidomycota, such as Ustilago maydis, in phylogenetic analysis in Supplementary Fig. 1.
        • Conservation analysis among diverse eukaryotes is more meaningful data that the conservation withing the fungi group, so that it is recommended that the data of Fig. 1 A would be replaced with the revised Supplementary Fig 1.
        • The analysis data on amino acid identities among Slu7 homologues should be presented to support the claim.
      2. Despite that CnSlu7 is the main key subject, the comparative analysis of CnSlu7 to the previously reported Slu7 homologues, in the aspect of functional domain organization, is not provided in the present manuscript.
        • It was reported that Slu7 contains the four motifs that control its cellular localization and canonical function as a splicing factor, such as a nuclear location signal, a zinc knuckle motif, four stretches of leucine repeats and a lysine-rich domain. Notably, human Slu7 protein is 204 amino acids longer than S. cerevisiae homolog with only 24% identity in the zinc knuckle motif (Molecular Biology of the Cell Vol. 15, 3782-3795). Thus, it is strongly recommended to provide additional information on the conserved and diverged features of CnSlu7 compared to other Slu7 homologs as a part of revised Figure 1 or Supplementary Figure 1.
      3. The manuscript clearly demonstrated that one of key targets of Slu7-mediated splicing is PAC1 in C. neoformans. Considering, Pac1 is also conserved from S. cerevisiae to human, it could be speculated that the defect of Slu7 can affect nuclear migration in other fungal species and human cells by inefficient splicing of PAC1, despite striking differences in their nuclear position during cell division. Please discuss this possibility or provide the qRT-PCR analysis data of PAC1 homologs in the available fungal Slu7 mutant strains.

      Minor comments:

      General points

      1. Provide information on the marker sizes in the data of qRT-PCR analysis presented in Figures 5 and 6, and Supplementary Fig 2A.
      2. Please unify the format of gene names. Some genes were written with superscript of "+", such as CLN1+ and PAC1+ in Fig. 4. What does "+" mean in the gene names?
      3. Supplementary Figure 1 C: Please correct "Slu7KD" 6 hrs YPD to "slu7kd" 6 hrs YPD.
      4. Supplementary Figure 2 A: What do "mRNA" and "No RT29X/", respectively, indicate?
      5. Supplementary Figure 4C: Please provide brief explanation in the text on why the authors employed mad2Δ slu7kd cells.
      6. Supplementary Figure 6D legend: Please correct the description of "slu7kd SH:Slu7 FL" from "expressing intronless PAC1" to "expressing full length of SLU7".
      7. Supplementary Figure 7D: The authors confirmed that MOB2, CDC12, and DFB1 were expressed at higher levels in slu7kd when compared to wildtype. Please briefly explain in the text why the expression level of these genes in slu7kd was mentioned.
      8. The species name should be written as abbreviation after the first mention. For example, please correct Cryptococcus neoformans to C. neoformans throughout manuscript.
      9. Please unify the format of paper titles listed in References.
      10. No page information for Hoffmann et al (2010) in References.
      11. Update the information on the published journal of Chatterjee et al. (2021) in References.
      12. The information on the authors, title, published journal and pages should be provided for the papers (Yadav and Sanyal, 2018; Sridhar et al., 2021) in Supplementary Table 1, which were not included in the main Reference list.

      Referees cross-commenting

      The slu7 deficiency would generate massive defects in intron processing, thus causing an overall alteration of gene expression. However, I agree with the reviewers #1 and # 2 that additional analysis on specifically focusing on (i) chromosome segregation and (ii) checkpoint pathways other than Mad2 could strengthen their conclusions on the key roles of Slu7 in nuclear position and cell division.

      Significance

      As a splicing factor necessary for the correct selection of 3 splice sites, Slu7 (Splicing factor synergistic lethal with U5 snRNA 7) strongly impacts the expression of diverse genes involved in various essential cellular functions. The Slu7 homologs have been intensively studied in the model yeast systems and human cell lines, revealing Slu7 as a pleiotropic factor with a holistic function at different levels of gene expression regulation in various cellular processes. This work presents advanced findings on a pivotal role of Slu7 in controlling nuclear migration and cell cycle progression, uncovering the molecular mechanism of a Slu7-dependent cell cycle mitotic progression in C. neoformans.

      Considering that Slu7 is a general splicing factor, the depletion of Slu7 would affect diverse cellular functions besides nuclear migration and cell cycle progression. Thus, further studies on other physiological defects by Slu7 depletion in the human pathogenic fungi, C. neoformans, particularly such as the altered expression of virulence-associated genes under stress conditions mimicking host environments, can provide intriguing information on the possible involvement of splicing factors in regulating the virulence of pathogenic fungi.

      My expertise is the protein secretion and glycosylation in various yeast species, including C. neoformans.

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      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      This manuscript reports the effects of depleting the Slu7 splicing factor in Cryptococcus neoformans. Mitotic defects are apparent, in particular in positioning the nucleus with cells struggling to get this into the bud (daughter) before chromosome segregation. The manuscript is well written, logically presented and the data of high quality. I suggest minor modifications and a few additional experiments that could be attempted.

      Major comments:

      • Are the key conclusions convincing? Yes. Splicing is clearly perturbed. Pac1 is likely to be one of the targets, as expression of an intronless minigene rescues the spindle positioning defect in the slu7 depleted cells. Importantly, other defects are still apparent (late mitotic delay/block) and so growth is not rescued. This is not surprising, as the expression of hundreds of genes are affected by Slu7-depletion.
      • the authors test the Mad2-dependent spindle assembly checkpoint, and show that it is not relevant for the slu7-depletion. This is as expected if the defect is in nuclear positioning. They could test other checkpoint pathways that would monitor nuclear positioning in budding yeasts. Perhaps they have considered this: Bub2, Bfa1, Tem1, Lte1 mutants? I don't think this experiment is essential for publication, but it could strongly support their model.
      • 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? Yes.

      Minor comments:

      • in Figure 3, Dyn1-GFP is imaged and in many of the cells in which Slu7 is depleted, nothing (or very little) can be seen. It is later argued that this is an indirect effect, due to defects in Pac1 and associated functions. Have the authors attempted a Dynein western blot (the 3xGFP tag should be quite sensitive)? It would be good to demonstrate that the Dynein motor complex hasn't simply fallen apart and Dynein been degraded in the slu7-depletion.
      • in Figure 7: have any intronless genes been tested for rescue of the post-mitotic delay/arrest? This is not necessary for publication, but if any have been tested already they could be listed here.
      • In SFig2C legend make it clear that these cells are HU arrested at time zero. Are the cells in glucose or galactose during HU treatment.?
      • in SFig4, the TBZ sensitivity isn't very convincing as the slu7kd strain is struggling to grow at all on YPD. In SFig5 legend the volcano plot needs to be better explained. What are the dashed lines etc. ?
      • 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? A few are listed above.

      Significance

      This manuscript will be of broad interest to the microbiology; splicing; cell cycle and cell division communities. The links between splicing and cell division is a novel area of research in Cryptococcus.

      I am an expert in mitotic regulation in yeast. Not a splicing expert.

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      Referee #1

      Evidence, reproducibility and clarity

      Summary

      In this work, Vishnu Priya Krishnan et al., show that deprivation of the Slu7 splicing factor severely compromises the viability of Cryptococcus neoformans. The authors show convincingly that slu7 deprivation leads to G2/M arrest, defective nuclear migration to the bud, and improper nuclear positioning at the bud neck during mitosis. Authors correlate this phenotype with defective mRNA processing of the Pac1 gene, which in S. cerevisiae is required to target dynein to the plus end of microtubules and ensures nuclear migration during mitosis. Consistently, expression of an intron-less Pac1 mRNA partially rescued nuclear positioning defects of slu7 deficiency. The data showing the involvement of slu7 in mRNA intron processing is convincing.

      Despite partially correcting nuclear positioning, expression of intron-less pac1 gene does not complement at all slu7 deficiency, suggesting that the lethality of slu7 lack of function is not caused by the nuclear positioning defects described here and it might arise from either deregulation of other specific factors as the authors suggest, to an overall unbalance of gene expression, or other reasons yet unknown.

      Major comments:

      -I am concerned about the lethal phenotype caused by slu7 deprivation.Slu7 deficiency causes defective nuclear positioning at the bud in late G2. This phenotype per se should not cause defective mitosis, so slu7 deficiency may also be interfering with other aspects of mitosis which might indeed impinge on cell viability. Supp. Fig4 shows defective mitosis in TBZ, so TBZ may be exacerbating defective mitosis of slu7-deficient cells. Throughout the figures it can be observed uneven chromosome/nuclear segregation in cells deprived of slu7, however, these mitotic defects have not been mentioned or explored in depth. From Supp Figure 3C it can be inferred that CENP-A segregation is uneven. Is this correct? Is CENP-A-GFP segregation normal? If chromosome segregation is altered upon slu7 deprivation, this might also explain the drop in cell viability and slow growth rates of this condition. The manuscript will improve if authors analyze chromosome segregation for example, by showing time-lapse images of chromosome dynamics during mitosis.

      The authors perform an RNA seq comparing wild-type cells with slu7 deficiency and detect changes in gene expression, however, they do not explore from this data the percentage of un-spliced introns genome-wide which might be very informative, even more than changes in gene expression, which many of them, might be an indirect consequence of Slu7 deficiency. Authors should re-analyze the RNAseq data looking for unprocessed mRNAs and provide information about the overall impact of slu7 in intron processing.

      Minor comments: -"Previous studies of slu7 mutants in S. cerevisiae and the conditional knockdown of its S. pombe homolog"

      Consider replacing homolog with Ortholog.

      -Taking these results together, we conclude that the inability of the conditional mutant to grow in the non-permissive media is due to impaired progression through the G2-M phase of the cell cycle.

      Is the G2/M delay the cause of the slow growth phenotype of the Slu7 deficiency? If so, growth defects of slu7 deficiency could be suppressed by ectopic expression of G2/M activators.

      -Supp Figure 3C, remove the drawing on the right. Adjust times relative to panels.

      -Tracking the nucleus in wild-type cells with a small bud showed that the nucleus moved into the daughter bud, divided into two, and one-half migrated to the mother bud (Supplementary Figure 3B, top row).

      Please replace the sentence: "one-half" with "one of the daughter nuclei". Additionally, as this nuclear positioning occurring during late mitosis is due to spindle elongation, I would not use the term migrated but "positioned" or "moved". Nuclear movement into the bud, which is referred to as "moved", can indeed be named "migrated".

      -Indicates in Figure 2B the marker used (GFP-H4), as in Fig Supp 3B.

      -Nuclear division initiates in the bud, and one of the divided nuclei with segregated chromosomes migrates back to the mother cell (Figure 2B, top panel, wildtype, quantified in Figure 2C grey bar).

      As mentioned before, I would not name this, nuclear migration as it is the result of spindle elongation, and it can be confusing or misleading for non-expert readers.

      -These two conclusions should be revised and described in temporal/sequential order. 1. Thus, we identify that the depletion of CnSlu7 severely affects the temporal and spatial sequence of events during mitosis, particularly nuclear migration and division. 2. Together, these results confirmed that without affecting the kinetochore clustering, depletion of Slu7 affects nuclear migration during the G2 to mitotic transition in Cryptococcus neoformans.

      -In slu7d cells, in cells with small buds, numerous cMTs were nucleated from the MTOCs, and as the cell cycle progressed, they organized to form the unipolar mitotic spindle (Figure 3A, slu7kd GFP-TUB1 panel, time point 55 mins).

      Please, revise whether the term unipolar mitotic spindle is correct here.

      -I suggest including page and line numbers in the manuscript to facilitate revision.

      Significance

      Understanding different strategies of nuclear positioning and division is an important question in cell biology. The model organism used in this study, Cryptococcus neoformans, performs a mode of division that is different from S. cerevisiae, as the nucleus migrates to the bud in late G2 and later to the bud-neck, whereas in S cerevisiae the nucleus remains in the mother cell during G2 before its positioning to the bud-neck prior mitosis. In both cases, proper nuclear positioning at the bud neck ensures DNA-nuclear segregation between the mother and the daughter cells by elongating the intranuclear mitotic spindle. Thus, understanding this alternative mode of nuclear positioning and division is a relevant problem in the field.

      Strength

      The demonstration of the involvement of slu7 in mRNA intron processing is convincing and the suppression of nuclear positioning defects of slu7 deficiency by expressing an intron-less Pac1 gene provides evidence that indeed, as in S. cerevisiae, both dynein and Pac1 also play a critical role in nuclear positioning in Cryptococcus neoformans.

      Limitation

      The authors get to the problem of nuclear positioning by using the deficiency of the intron processing factor, slu7. Deficiency of slu7 is lethal possibly due to massive defects in intron processing and an overall deregulation of gene expression. However, the authors of this study analyze slu7 deficiency in a short window of time followed slu7 switch-off and describe some of the phenotypes resulting from this condition.

      The result presented in this study might be useful for a specialized audience. The suggested genome-wide analysis of intron processing defects and a better analysis of chromosome segregation during mitosis under slu7 deficiency might be useful to increase the impact of this study and reach a greater audience.

      My expertise.

      I have been working in nuclear positioning in the fission yeast and have made some contributions to this field by generating a procedure to displace the nucleus within the cell. This approach allowed us to study forces and mechanisms responsible for nuclear positioning. I have also recently made key contributions to the field of nuclear mechanics, by describing how interphase microtubules contribute to cohesin loading, and the field of nuclear division, by describing mechanisms of spindle disassembly and nuclear partitioning in the fission yeast.

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      Reply to the reviewers

      REPLY TO REVIEWERS

      Reviewer #1

      __Evidence, reproducibility and clarity: __Interesting results from exposing human brain organoids to FGF8 include suggestions that FGF8 contributes to the anterior to posterior patterning of the neocortex, as previously reported in mouse. Good, varied methods with reproducibility described well in the methods section. It would improve the reader's experience however to cite numbers of organoids used in specific experiments/assays in the main text.

      Response: We thank the Reviewer for the positive assessment of our study, and we agree that citing the number of organoids per experimental approach would better allow the readers to appreciate the intrinsic variability of organoid protocols. We will include the number of organoids per experiment both in figure legends and in Materials and Methods as a summary table.

      ....Organoids do not develop individual neocortical areas. To approach this issue of area identity, however, the authors compared control and FGF8-treated organoids against an existing dataset of transcriptomes of human fetal brains that separated pre-frontal, motor, somatosensory, and visual areas. This seems a good idea, but results showed both treated and untreated organoids alike expressed genes characteristic of somatosensory and pre-frontal cortical regions (anterior and midlevel areas) apparently suggesting that exogenous FGF8 had little effect. Because the previous dataset was not the authors' work, however, and because a comparison between organoids and actual human tissue is hard to interpret, this whole section is probably only confusing to include.

      Response: We would like to clarify to the reviewer that the effect of FGF8 on antero-posterior area identity is only partial in our organoid system, suggesting that different doses or temporal windows of FGF8 treatment may be necessary to achieve a stronger modulation of area identity genes. We agree with the Reviewer that, due to this partial effect, the transcriptomic comparison with fetal brain areas might be confusing for readers. Therefore, we plan to move this type of data to the Supplementary Material. We thank the Reviewer for bringing this to our attention.

      The authors further stress a dorsal/ventral effect in FGF8-treated organoids. The population of ventral telencephalic interneurons, produced in the lateral ganglionic eminence in mice, expand in the human organoids at the expense of glutamatergic neurons of the dorsal telencephalon. This may be consistent with the loss of ventral telencephalic structures in FGF8-deficient mice. The authors suggest that FGF8 expansion of interneurons is a novel finding not previously seen in animal research and may point to a human-specific characteristic. Readers may believe this part of the paper requires more support, just because multiple studies of FGF8 have not revealed this action. Overall, this paper would benefit from shortening, and by statements that some of the results suggest, but do not guarantee, particular conclusions.

      Response: We agree with the reviewer that before stating that FGF8-induced expansion of interneurons in dorsal telencephalic territories is a human-specific characteristic, more support in mouse studies would need to be performed. However, as suggested by reviewer 2 below, there is some evidence that ventral interneuron markers, such as ASCL1 and DLX2, are expressed in the dorsal telencephalon of the early fetal human cerebral cortex, even if at much lower levels than in the ventral telencephalon, and that individual human cortical progenitors can generate both excitatory neurons and inhibitory interneurons in culture. Thus, FGF8 might promote an intrinsic capacity of dorsal cortical neurons to induce the generation of ventral interneurons, which would indeed be a human (or maybe primate)-specific trait. We plan to better discuss this issue in the revised version of the manuscript.

      Significance

      The paper is for a fairly specialized audience interested in the development of the cerebral cortex, but also has interest regarding developmental human brain defects

      Response: Although the manuscript sounds upon first reading specific to a specialized audience interested in cortical development, we believe that the strength of our human organoid system is the formation of regionalized organoids including brain regions other than the cortex. Moreover, considering the increasing attention on brain organoids in general, and the lack of information on the action of FGF8 during human cortical development, we are confident that this study will attract a broader audience.

      Interesting results from exposing human brain organoids to FGF8 include suggestions that FGF8 contributes to the anterior to posterior patterning of the neocortex, as previously reported in mouse. Good, varied methods with reproducibility described well in the methods section. It would improve the reader's experience however to cite numbers of organoids used in specific experiments/assays in the main text.

      Response: We thank again the reviewer for acknowledging the potential of our study. As previously mentioned, we agree that providing information about the number of organoids used will enhance the statistical analysis. This will definitely be added in a revised version.

      Reviewer #2

      Evidence, reproducibility and clarity

      ……However, organoid technology offers a solution to this and the present study presents an elegant approach to addressing how FGF8 signalling directs both anterior/posterior and dorsal/ventral identity in neural progenitors and their offspring in human development. This has both biological and clinical relevance has the study demonstrates how FGF8 may be a key regulator of expression of susceptibility genes for neurodevelopmental conditions. The methods and approach are described clearly and in great detail and it serves as an exemplar for how studies like this might be pursued in the future. Likewise, the results are presented logically, using excellent figures with clear descriptions of the findings. It is positively entertaining to read and very thought provoking. We don't have any major issues with the conclusions.

      Response: We sincerely appreciate the reviewer’s enthusiastic and thoughtful feedback. The positive remarks on the clarity and detail of our methods and results are very encouraging, and we are pleased that the reviewer found our study both entertaining and thought-provoking.

      We have some minor issues over presentation and interpretation that we would like the authors to consider.

      1) Developmental staging. It is stated that the organoids have reached a developmental stage equivalent to 16.5 GW based on expression of key genes such as CRYAB. Firstly, we would prefer an unambiguous way of stating age such as post-conceptional age. It is never clear what gestational weeks exactly means (post-menstrual, post-ovulatory?). Secondly, in several figures, UMAPs generated from the organoids are presented alongside representative mouse brain sections from E13.5 which is equivalent to about 11 post conceptional weeks in human. Although we find the mouse sections helpful, perhaps the potential discrepancy in developmental stage should be pointed out.

      Response: We agree with the reviewer that the staging of human organoids in vitro can be very tricky. We will clarify this issue by using post-conceptional weeks (PCW) instead of gestational weeks in the revised version of the manuscript. It is true, that schematic representations of brain sections of mouse telencephalon of around E13.5 were used in the paper, but the idea was to choose an age where dorsal and ventral territories are clearly separated during embryogenesis to highlight the expression of the different genes. We will change the schematics to make sure they can be better compared with scRNA-seq data and will highlight that they represent early mid-gestation stages of mouse embryos.

      2) Dorso-ventral patterning. Firstly, we wondered why VGLUT2 was used as a marker for dorsal identity when it is generally regarded as being expressed by subcortical neurons, e.g. thalamus and midbrain, whereas VGLUT1 is the standard marker for cortical neurons :https://doi.org/10.1016/j.tins.2003.11.005? Potentially, VGLUT2 expression may be more an indicator of mid/hindbrain identity than cortical identity. Is there any evidence for VGLUT2 expression by cortical cells in development? Also, MASH1 (more correctly called ASCL1) is not exclusively ventral, having shown to be expressed in a subset of intermediate progenitor cells for glutamatergic neurons in rodent doi:10.1093/cercor/bhj168 and particularly human doi: 10.1111/joa.12971. We are surprised that the recent evidence that human cortical progenitors do have capacity to generate GABAergic neurons 10.1038/s41586-021-04230-7; 10.1101/2023.11.06.565899 is not mentioned in this section as perhaps FGF8 doesn't so much ventralise progenitor cells as promote an inherent property. This might explain why MGE-like identity is not observed, whereas LGE/CGE like is, as it has already been shown that MGE-like gene expression by dorsal progenitors is very much less likely than LGE/CGE like expression 10.1038/s41586-021-04230-7; DOI 10.1007/s00429-016-1343-5

      Response: We fully agree and thank the reviewer for bringing to our attention this interesting discussion and pointing to our confusion between VGLUT1 and VGLUT2 expression profiles. After checking our scRNA-seq data, we realized that the Reviewer is absolutely correct about the issue of using VGLUT2 as a dorsal telencephalic marker, as it is expressed in both dorsal and ventral cells. In contrast, VGLUT1 appears to be more specific for neocortical (dorsal) neurons (see UMAP images below). Moreover, it perfectly fits with our results showing a downregulation of VGLUT1 in dorsal glutamatergic neurons.

      We are currently conducting additional staining experiments to support this point. Specifically, our plan includes:

      • Performing immunostaining assays to validate the expression patterns of VGLUT2 in dorsal cortical neurons, notably triple VGLUT2/TRB1/CTIP2 and double VGLUT2/SATB2 stainings, to be added in Supplementary material. This will allow to confirm the use of VGLUT2 as a dorsal marker.
      • Performing additional immunostainings involving VGLUT1, either juxtaposed with GAD67 to assess dorso-ventral neuronal balance or in conjunction with dorsal cortical markers to examine co-expression. This new analysis will be quantified using AI and integrated into Figure 4. Notably, these experiments will provide a comprehensive understanding of the expression patterns of VGLUT1 and VGLUT2 in the dorsal or ventral telencephalon and will further elucidate their utility as markers for specific neuronal populations in human brain organoids.

      Furthermore, and importantly, we fully agree with the reviewer that human dorsal cortical progenitors do have the ability to generate GABAergic neurons, even if at lower efficiency than glutamatergic neurons, and that FGF8 might promote this inherent property in human organoids. This new discussion and the new references suggested by the reviewer will significantly contribute to our data interpretation about LGE/MGE development. Therefore, we intend to incorporate them into the revised version of the text. Again, thank you to the reviewer for these insightful suggestions.

      3) MEA recordings. The presentation of electrophysiological data is quite simple. Detection of spikes is claimed therefore representative traces of the spikes should be included and these can be easily generated with the Maxwell system software. It isn't clear how many times the experiments were repeated and there is no statistical analysis. For example, in the text they state on page 15 'Notably, WNTi+FGF8 organoids showed lower spike frequency (firing rate) and amplitude'. The amplitude difference is 43uV vs 41uV; we doubt this is significantly different. Threshold for detecting burst firing appears to be different between Figure 5C and 5d. Why? Shouldn't it be the same? The axonal tracking analysis in fig 5E/F needs more explanation. How many axons were tracked? Is there any statistical analysis beyond means and standard deviation?

      Response: We agree with the Reviewer that the presentation of our electrophysiological data need further improvement. We are currently repeating key recordings on four additional samples coming from two different batches, which will allow us to conduct a better statistical analysis.

      In detail, we plan to:

      • Extract representative traces of spikes from the Maxwell software, which will be included as Supplementary material. Footprints of action potentials will be extracted using the in-built analysis tool available in the software.
      • Perform axon tracking analysis on three control and three FGF8-treated samples coming from two distinct batches of organoids. Recordings and analyses will be conducted over a period of two weeks to monitor the growth of axonal tracts, enabling us to perform statistical analysis and observe the temporal evolution of axonal growth. Furthermore, placing the threshold for detecting bursts in the network analysis at different levels in control or treated samples seems to be a routine procedure in this MEA system. Indeed, while the user can set a fixed multiplying factor (that is, of course, the same for both control and treated samples), it is the software that multiplies such factor by the basal average activity of the sample. In this way, bursts can be detected as synchronized activity emerging from the basal one, which, of course, varies in every sample. We plan to better explain this point in the Materials and Methods section, and we thank the reviewer for raising this lack of clarity.

      4) Anterior/posterior patterning. Returning to the subject of cortical GABAergic neurons, it has been proposed that the prefrontal cortex contains a relatively higher proportion of GABAergic neurons, although the mechanism for this has not been elucidated (see https://doi.org/10.1111/joa.13055 and references therein). Might higher anterior FGF8 specifying cortical progenitors to produce GABA neurons have a role in this?

      Response: We thank the reviewer for citing this very interesting review. It is highly possible that FGF8 normally expressed anteriorly might have a role in inducing distinct GABAergic subtypes, such as Calretinin+ interneurons, which have been found to be more abundant in frontal cortices of the developing human fetal brain. Our organoids are too early in terms of developmental age to verify whether interneuron subtypes such as CalR+ are more or less represented, but we will definitely add this very interesting point to our discussion in the revised version.

      5) Nomenclature. As this study principally presents data on mRNA expression levels it might be preferable to use italicised capitals for all gene names (except where referring to mouse genes). Also, common names are used in places and standard gene names in others, e.g. COUPTF1 is referred to NR2F1 but VGLUT1 is not referred to SLC17A7 (also see above re MASH1). It would be good to see everything standardised.

      Response: We appreciate the Reviewer for highlighting these discrepancies. We will standardize gene names both in the text and figures accordingly.

      Significance

      This study involves a very imaginative use of organoids combined with a variety of approaches to test if fundamental principles of forebrain development, particularly cell specification and regional patterning, that we have learnt from mouse models are relevant to human brain development. It also has clinical relevance as it explores potential disruptions to development that leader to diseases of higher cognition, such as autism of schizophrenia. It is a very accessible manuscript that should have broad appeal. It makes several incremental additions to the field and points the way to future experiments in this area.

      Response: We sincerely thank the Reviewer's insightful comments and positive assessment of our study.

      __Reviewer #3 __

      __Evidence, reproducibility and clarity: __

      In the manuscript "FGF8-mediated gene regulation affects regional identity in human cerebral organoids" the authors used FGF8 to change cellular fate in human brain organoids. The experiments are well-performed and the authors used well-established protocols to generate brain organoids. The results clearly show that FGF8 addition induces an increase of diencephalon/midbrain markers (OTX2, EN2), suggesting that long-term FGF8 treatment can induce also posterior regional identities. These data are reinforced also by scRNAseq highlighting a possible mix of cellular identity.

      Response: We thank the reviewer for this encouraging report about our study highlighting the significance of our findings.

      Main concern:

      1. The authors should start using FGF8 at later stages than day 19-21, in trying to maintain the forebrain identity.

      Response: As the Reviewer correctly pointed out, the temporal window of FGF8 treatment seems of pivotal importance for the final outcome of regional identity acquisition. Indeed, while early treatment with FGF8 at day 5 disrupts FOXG1 expression in organoids, as demonstrated in Supplementary Figure 1, our first attempts at adding FGF8 at day 15 resulted in poor regulation of the major FGF8-target gene NR2F1. However, we noticed that high expression of FOXG1 was still maintained, supporting forebrain identity. We fully agree with the reviewer that it is worth treating organoids with FGF8 at later stages to test whether forebrain identity becomes enriched while midbrain one is reduced, which would highlight an FGF8-dependent dosage of forebrain identity acquisition. To this purpose, we have already started additional experiments to assess the effect of delayed FGF8 treatment on forebrain markers and FGF-target genes, such as ETV1, SPRY4, DUSP6, ETV4 and ETV5, but also on representative midbrain markers. Importantly, we will treat the same batch of organoids with the same amount of FGF8 but at different times to be able to compare the different treatments in parallel. We plan to incorporate these supplementary analyses into the Supplementary material to provide a more comprehensive characterization of the efficiency time windows of FGF8.

      In detail, we plan to structure these additional experiments as follows:

      • We will culture in parallel neural progenitors (cortical induction protocol, with XAV-939 as a WNT inhibitor) that will be treated with 100 ng/ML FGF8 starting at day5 (early treatment), at day10 (normal treatment) or at day 20 (late treatment).
      • Each condition will require at least n=6 organoids.
      • Samples will be cultured until day 30.
      • At day 30, we will fix n=3 organoids per condition to be processed by immunostaining, and harvest n=3 organoids per condition for RNA extraction and Real Time RT-PCR analysis.
      • By immunostaining, we will measure the number of FOXG1+ cells as a read-out of telencephalic identity and the intensity of NR2F1 staining to evaluate FGF8 action.
      • By RT-PCR, we will measure the expression level of the following regional identity markers and FGF8 target genes: FOXG1, EN2, OTX2, NR2F1, ETV1, SPRY4, DUSP6, ETV4 and ETV5. This experimental setup will allow us to further detail the efficiency of distinct temporal windows for FGF8 treatment and their effects on cell identity and FGF target gene modulation. However, based on the first data we already obtained, we expect poor FGF target gene modulation upon late FGF8 treatment. This is why we believe that the temporal window we selected for our study already represents an optimal compromise between maintaining high levels of FOXG1 while effectively modulating FGF8 targets in human organoids.

      To verify the identity of the neurons in the organoids the authors should check their ability to make projections in immunodeficient mice. Human iPSC-derived cortical neurons establish subcortical projections in the mouse brain after transplantation and the location of the different neuronal projections could reveal the rosto-caudal identity of the cortical neurons.

      Response: We agree with the reviewer that in general conducting in vivo transplants of human organoids offers an interesting approach to testing the identity of differentiated neurons by tracking their projections. However, we believe that due to the multi-regional character of FGF8-treated organoids (which includes also midbrain-like neurons), their transplant into the neocortex would be of difficult interpretation and would not reveal the precise rostrocaudal identity of transplanted human cortical neurons, as requested by the reviewer. Furthermore, this would almost constitute an entire project on its own, given the technical challenges associated with such experimental approaches. We think that our thorough scRNA sequencing analysis is powerful enough for assessing cell identity, as supported by the majority of organoid studies investigating cell identity through scRNA-seq without resorting to transplantation. In our study, the scRNA-seq analysis was subsequently validated by several steps of immunostainings, a simple but fundamental corroborative control approach that is sometimes overlooked in similar studies. Finally, we would like to emphasize that reviewers #1 and 2 found our complementary approaches (molecular, cellular, and functional) appropriate, well-performed, logical and reproducible.

      Significance:

      The proposed protocol is useful to generate brain organoids with mixed cell populations from different regions of the brain (forebrain, midbrain, hindbrain). However, has limited applications since is not clear whether the proposed structures have some kind of organization.

      Response: We agree with the Reviewer that each protocol comes with its own limitations and that a careful characterization of the proportion of different regional domains could definitively improve the significance and applicability of our protocol. To this aim, we are now using artificial intelligence-mediated detection of cortical versus midbrain-like domains in control and FGF8-treated organoids, to further improve the characterization of distinct cellular populations and quantify the extent of their domains in multi-regional organoids. These data will be added in Figure 3.

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      Referee #3

      Evidence, reproducibility and clarity

      In the manuscript "FGF8-mediated gene regulation affects regional identity in human cerebral organoids" the authors used FGF8 to change cellular fate in human brain organoids. The experiments are well-performed and the authors used well-established protocols to generate brain organoids. The results clearly show that FGF8 addition induces an increase of diencephalon/midbrain markers (OTX2, EN2), suggesting that long-term FGF8 treatment can induce also posterior regional identities. These data are reinforced also by scRNAseq highlighting a possible mix of cellular identity.

      Main concern:

      • The authors should start using FGF8 at later stages than day 19-21, in trying to maintain the forebrain identity.
      • To verify the identity of the neurons in the organoids the authors should check their ability to make projections in immunodeficient mice. Human iPSC-derived cortical neurons establish subcortical projections in the mouse brain after transplantation and the location of the different neuronal projections could reveal the rosto-caudal identity of the cortical neurons.

      Significance

      The proposed protocol is useful to generate brain organoids with mixed cell populations from different regions of the brain (forebrain, midbrain, hindbrain). However, has limited applications since is not clear whether the proposed structures have some kind of organization.

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      Referee #2

      Evidence, reproducibility and clarity

      Almost everything we know about development of functional arealisation and cell specification in the telencephalon comes from studies in mouse, but it is important to compare our mouse models with human if we wish to understand the origins of our more evolved cognition and of neurodevelopmental diseases. Some work using transcriptomics and histology has already been done in this area, but directly studying mechanisms of guided differentiation is more difficult because of the accessibility issues surrounding live human fetal tissue and cells. However, organoid technology offers a solution to this and the present study presents an elegant approach to addressing how FGF8 signalling directs both anterior/posterior and dorsal/ventral identity in neural progenitors and their offspring in human development. This has both biological and clinical relevance has the study demonstrates how FGF8 may be a key regulator of expression of susceptibility genes for neurodevelopmental conditions. The methods and approach are described clearly and in great detail and it serves as an exemplar for how studies like this might be pursued in the future. Likewise, the results are presented logically, using excellent figures with clear descriptions of the findings. It is positively entertaining to read and very thought provoking. We don't have any major issues with the conclusions.

      We have some minor issues over presentation and interpretation that we would like the authors to consider.

      1. Developmental staging. It is stated that the organoids have reached a developmental stage equivalent to 16.5 GW based on expression of key genes such as CRYAB. Firstly, we would prefer an unambiguous way of stating age such as post-conceptional age. It is never clear what gestational weeks exactly means (post-menstrual, post-ovulatory?). Secondly, in several figures, UMAPs generated from the organoids are presented alongside representative mouse brain sections from E13.5 which is equivalent to about 11 post conceptional weeks in human. Although we find the mouse sections helpful, perhaps the potential discrepancy in developmental stage should be pointed out.
      2. Dorso-ventral patterning. Firstly, we wondered why VGLUT2 was used as a marker for dorsal identity when it is generally regarded as being expressed by subcortical neurons, e.g. thalamus and midbrain, whereas VGLUT1 is the standard marker for cortical neurons :https://doi.org/10.1016/j.tins.2003.11.005? Potentially, VGLUT2 expression may be more an indicator of mid/hindbrain identity than cortical identity. Is there any evidence for VGLUT2 expression by cortical cells in development? Also, MASH1 (more correctly called ASCL1) is not exclusively ventral, having shown to be expressed in a subset of intermediate progenitor cells for glutamatergic neurons in rodent doi:10.1093/cercor/bhj168 and particularly human doi: 10.1111/joa.12971. We are surprised that the recent evidence that human cortical progenitors do have capacity to generate GABAergic neurons 10.1038/s41586-021-04230-7; 10.1101/2023.11.06.565899is not mentioned in this section as perhaps FGF8 doesn't so much ventralise progenitor cells as promote an inherent property. This might explain why MGE-like identity is not observed, whereas LGE/CGE like is, as it has already been shown that MGE-like gene expression by dorsal progenitors is very much less likely than LGE/CGE like expression 10.1038/s41586-021-04230-7; DOI 10.1007/s00429-016-1343-5
      3. MEA recordings. The presentation of electrophysiological data is quite simple. Detection of spikes is claimed therefore representative traces of the spikes should be included and these can be easily generated with the Maxwell system software. It isn't clear how many times the experiments were repeated and there is no statistical analysis. For example, in the text they state on page 15 'Notably, WNTi+FGF8 organoids showed lower spike frequency (firing rate) and amplitude'. The amplitude difference is 43uV vs 41uV; we doubt this is significantly different. Threshold for detecting burst firing appears to be different between Figure 5C and 5d. Why? Shouldn't it be the same? The axonal tracking analysis in fig 5E/F needs more explanation. How many axons were tracked? Is there any statistical analysis beyond means and standard deviation?
      4. Anterior/posterior patterning. Returning to the subject of cortical GABAergic neurons, it has been proposed that the prefrontal cortex contains a relatively higher proportion of GABAergic neurons, although the mechanism for this has not been elucidated (see https://doi.org/10.1111/joa.13055 and references therein). Might higher anterior FGF8 specifying cortical progenitors to produce GABA neurons have a role in this?
      5. Nomenclature. As this study principally presents data on mRNA expression levels it might be preferable to use italicised capitals for all gene names (except where referring to mouse genes). Also, common names are used in places and standard gene names in others, e.g. COUPTF1 is referred to NR2F1 but VGLUT1 is not referred to SLC17A7 (also see above re MASH1). It would be good to see everything standardised.

      Significance

      This study involves a very imaginative use of organoids combined with a variety of approaches to test if fundamental principles of forebrain development, particularly cell specification and regional patterning, that we have learnt from mouse models are relevant to human brain development. It also has clinical relevance as it explores potential disruptions to development that leader to diseases of higher cognition, such as autism of schizophrenia. It is a very accessible manuscript that should have broad appeal. It makes several incremental additions to the field and points the way to future experiments in this area.

    4. 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

      Interesting results from exposing human brain organoids to FGF8 include suggestions that FGF8 contributes to the anterior to posterior patterning of the neocortex, as previously reported in mouse. Good, varied methods with reproducibility described well in the methods section. It would improve the reader's experience however to cite numbers of organoids used in specific experiments/assays in the main text.

      Full review

      During mouse embryonic development FGF8 protein disperses through the neocortical primordium in an anterior/posterior (A/P) gradient, regulating patterned expression of specific transcription factors (TFs) as the first step in generating the neocortical area map. More specifically, FGF8 upregulates area patterning genes expressed anteriorly and downregulates those expressed posteriorly. Both actions lead to the formation of the area map in mouse neocortex.

      The authors of this paper investigate whether FGF8 and its downstream TFs play a similar patterning role in the human brain, a very significant question. A series of experiments assess effects of exogenous FGF8 on human brain organoids in regulating relevant genes using RTPCR, in situ hybridization, and, most convincingly, single cell RNA-Seq. Results for both neuroepithelial cells and neurons indicate appropriate upregulation of "anterior" cortical patterning genes, such as Pax6, alongside knock-down of "posterior" genes including Nr2f1 and Fgfr3. Surprisingly, expression of Emx2, another powerful gene implicated in the formation of posterior neocortex, shows only a slight, though significant, decrease in expression.

      Organoids do not develop individual neocortical areas. To approach this issue of area identity, however, the authors compared control and FGF8-treated organoids against an existing dataset of transcriptomes of human fetal brains that separated pre-frontal, motor, somatosensory, and visual areas. This seems a good idea, but results showed both treated and untreated organoids alike expressed genes characteristic of somatosensory and pre-frontal cortical regions (anterior and midlevel areas) apparently suggesting that exogenous FGF8 had little effect. Because the previous dataset was not the authors' work, however, and because a comparison between organoids and actual human tissue is hard to interpret, this whole section is probably only confusing to include.

      The authors further stress a dorsal/ventral effect in FGF8-treated organoids. The population of ventral telencephalic interneurons, produced in the lateral ganglionic eminence in mice, expand in the human organoids at the expense of glutamatergic neurons of the dorsal telencephalon. This may be consistent with the loss of ventral telencephalic structures in FGF8-deficient mice.<br /> The authors suggest that FGF8 expansion of interneurons is a novel finding not previously seen in animal research and may point to a human-specific characteristic. Readers may believe this part of the paper requires more support, just because multiple studies of FGF8 have not revealed this action.

      Overall, this paper would benefit from shortening, and by statements that some of the results suggest, but do not guarantee, particular conclusions.

      Significance

      The paper is for a fairly specialized audience interested in the development of the cerebral cortex, but also has interest regarding developmental human brain defects

      Interesting results from exposing human brain organoids to FGF8 include suggestions that FGF8 contributes to the anterior to posterior patterning of the neocortex, as previously reported in mouse. Good, varied methods with reproducibility described well in the methods section. It would improve the reader's experience however to cite numbers of organoids used in specific experiments/assays in the main text.

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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

      Bianca Köhler and colleagues investigate the influence of miR-200c on cancer cell migration through a series of in vitro and in vivo experiments. After inducing miR-200c overexpression in MDA-MB 231 cells with doxycycline treatment, the researchers observe a reduction in metastases when these cells are implanted into mice. Using live imaging analysis, the authors found that MCF7 cells lacking miR-200c display increased mobility compared to wildtype cells, particularly at low cell density. Conversely, MDA-MB 231 cells with miR-200c overexpression show decreased mobility, irrespective of cell density in culture. Scratch assays show a diminished invasive capacity of MDA-MB 231 cells with heightened miR-200c expression. This finding aligns with results from transwell assays, where wildtype MCF7 cells exhibit reduced migration compared to MCF7 cells lacking miR-200c. In examining the impact of miR-200c on single-cell migration, a micropattern assay with two square islands connected by a thin bridge reveals a decrease in both transition frequency and transition speed of migrating MDA-MB-231 cells upon miR-200c expression.

      In summary, this study provides a comprehensive exploration of the effects of miR-200c on cancer cell migration in various experimental contexts, offering insights into potential therapeutic implications.

      The manuscript exhibits clear and articulate writing, coupled with well-explained experiments. To enhance its value, a more thorough characterization of miR-200c's mechanism of action, validation of its targets, and a more detailed analysis of in vivo metastases would be beneficial.

      The manuscript's novelty appears limited, as the role of miR-200c as a tumor suppressor and its association with decreased metastatic potential in breast cancer cells have been previously documented (Klicka et al., Front Oncol 2022; Ljepoja et al., Plos One 2019). Highlighting unique contributions or contextualizing findings within existing literature would strengthen the manuscript's distinctiveness.

      Comments to the authors: I recommend integrating these suggestions into the manuscript to enhance its scientific rigor and relevance.

      Metastases Characterization:

      Consider providing histological images illustrating the distribution of cancer cells in metastatic organs. This visual representation could offer readers valuable insights into the nature and characteristics of metastases arising from MDA-MB 231 cells.

      Tumor Growth Impact:

      Address the potential impact of tumor growth on metastatic dissemination by correcting for variations in primary tumor size when quantifying metastases in vivo. Accounting for this variable will strengthen the reliability and interpretation of the results.

      Control Experiments:

      Strengthen the experimental design by including a scrambled miRNA sequence as a control. This addition will contribute to a more robust comparison, ensuring observed effects are specifically attributed to miR-200c.

      Target Validation for Mechanistic Insights:

      Improve the understanding of miR-200c's mechanism of action by validating some of its natural targets. This step will provide a more solid foundation for interpreting experimental outcomes and unraveling the intricacies of miR-200c function.

      Clinical Correlation:

      Explore the possibility of correlating miR-200c expression with the progression of specific tumor diseases in patients. This potential correlation could contribute valuable clinical insights to the manuscript.

      Translational Potential:

      Once natural targets of miR-200c are validated, explore the translational potential by investigating whether these targets can be targeted by available drugs. Testing these drugs in tumor mouse models would further assess their efficacy and potential clinical applications.

      Significance

      In summary, this study provides a comprehensive exploration of the effects of miR-200c on cancer cell migration in various experimental contexts, offering insights into potential therapeutic implications.

      The manuscript exhibits clear and articulate writing, coupled with well-explained experiments. To enhance its value, a more thorough characterization of miR-200c's mechanism of action, validation of its targets, and a more detailed analysis of in vivo metastases would be beneficial.

      The manuscript's novelty appears limited, as the role of miR-200c as a tumor suppressor and its association with decreased metastatic potential in breast cancer cells have been previously documented (Klicka et al., Front Oncol 2022; Ljepoja et al., Plos One 2019). Highlighting unique contributions or contextualizing findings within existing literature would strengthen the manuscript's distinctiveness.

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      Referee #2

      Evidence, reproducibility and clarity

      In this manuscript, Kohler et al analyze the impact of miR200c on cell motility in vitro and breast cancer metastasis in mouse models. The they show that miR200c represses metastasis to several different organs and propose that reduced motility is a significant cause of this. The experiments are generally sound and well performed. However, the insight gained with the study does not go much beyond what is already known about miR200c function in breast cancer. The experimental tools used in the study could provide the opportunity to reveal novel insights into the role of miR200c in metastasis. However, the investigators did not take full advantage of this and thus we are left with findings that are rather predictable based on the current literature. Details below.

      Major points:

      1. The primary weakness of this study is limited novelty. miR200c has been shown to regulate migration and invasion of breast cancer cells in several previous studies, and this includes analysis using the same breast cancer cell lines that Kohler et al use in the current study, MCF7 and MDA-MB-231 (Jurmeister et al Mol Cell Bio 2012; Zhang et al Genet Mol Res 2017) and a study by the same group (Ljepoja et al Plos One 2019). Moreover, previous studies have also shown that miR200c represses metastasis in two different claudin low triple negative breast cancer models, MDA-MB-231 and genetically-engineered p53 null transplantable model (Simpson et al Genes 2022, Knezevic et al Oncogene 2016). Of note, Kohler et al do analyze metastases not only in lungs, but also in liver, brain and spleen and this could be a source of novel insights depending on the scientific questions. Is the miR200c mediated repression of metastasis caused by the same mechanisms in all these organs, or is it context dependent? What about molecular mediators downstream of miR200c?
      2. The authors focus primarily on migration issues as the potential cause of miR200c mediated repression of metastasis. However, there is significant literature on the role of miR200c in cancer progression. miR200c has been associated with multiple cellular functions, including regulation of epithelial mesenchymal transition (EMT) by repressing key EMT transcription factors ZEB1 and ZEB2. EMT regulation of course may suggest an effect on cell motility, but also several other functions, such as stem cell activity, plasticity, survival under stress and many more. Indeed, in a clinical setting some may question the importance of migration, considering that breast cancer cells disseminate from the primary tumor early in the process and upon diagnosis the cells are likely already lodged in secondary organs. Therefore, it is probable that cell functions such as survival under stress, proliferation and plasticity would be of even higher importance compared to cell motility. I would think that miR200c functional studies need to go beyond cell motility to generate additional insights into its role in metastasis and reveal potentially actionable targets.
      3. The investigators use a dox inducible system to express miR200c in MDA-MB-231 mammary tumors in mice. The mice were treated with dox to induce miR200c when the tumors reached 200 mm3 in size. This is a rather early induction of miR200c and may not address the ability of miR200c to repress actively growing metastatic lesions. I think these experiments should also be done by waiting longer before miR200c induction. What happens if the tumors are allowed to grow to 500 mm3 or 750 mm3? This would really test the ability of miR200c to inhibit overt metastasis.

      Minor points:

      1. Although in some figures the plots/graphs show individual data points, this is not always the case. All box plots and bar graphs should show individual data points (biological replicates).
      2. Representative histological examples of the metastases in Figure 1C-1D should be shown.
      3. Presentation of the data in Figure 2C-2F is confusing. Statistics are also missing.

      Significance

      Although the study is technically sound, it suffers from limited novelty. Overall conclusions are predictable from previous studies. Of note, this study does provide somewhat more detailed analysis of migratory regulation by miR200c in cancer cells compared to previous reports. However, the study's advance is still quite modest.

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      Referee #1

      Evidence, reproducibility and clarity

      Summary: in this manuscript, Kohler and coworkers describe the role of miR-200c in preventing breast cancer cell migration in vitro and metastasis in vivo (using sub cutaneous injections of human breast cancer cell lines in nude mice). The novelty of this manuscript resides in the in vivo work, as the role of miR-200c in preventing cell migration and EMT in vitro is widely established (and recognised in this manuscript).

      Major comments:

      • the authors need to measure miR-200c expression in their experimental systems. Here they described a DOX-inducible system to express miR-200c in MDA-MB-231 cells and they used KO MCF7 cells, but the levels of miR-200c are not reported at all in the manuscript. It is essential to show that DOX treatment induces miR-200c expression both in vitro and in vivo.
      • the experiments presented in figure 4 do not contain the appropriate controls. In all the other figures, inducible MDA-MB-231 cells are presented, in the presence and absence of DOX. However, in this figure WT MDA-MB-231 cells are compared with the inducible variant in the presence of DOX. All the experiments in this figures need to be repeated with the inducible cells in the absence of DOX
      • in the would healing experiments (figure 3), both KO and induction of miR-200c result in increased migration (which is not consistent with the rest of the data shown in the paper). This point should be explained more clearly in the discussion. In addition, the behaviour of the cells in the absence of DOX (figure 3G) seems very different in the control vs miR-200c cells (figure 3E) - this issue needs to be addressed in the discussion, as it could suggest that other factors independent of miR-200c expression might contribute to the difference between the 2 cell lines.
      • in some instances, the authors draw conclusions from data that are not statistically significant, as in supplementary figure S2A and B, in relation to which the authors state 'both analysis were additionally validated... by crystal violet staining', but the quantifications show no significant differences
      • all the migration experiments in vitro are in 2D. This should be highlighted as a limitation of this study. In addition, it is not appropriate to describe migrating cells as 'invasive', when this was not assessed in the experiment.

      Minor comments:

      • it is not clear what the difference between figure 4 A and B is
      • it would be good to better clarify the rational behind and the physiological relevance of the confined cell motility experiment
      • the authors measured differences in tumour volume it vivo, therefore it would be useful to assess cell proliferation in vitro as well. This is also important as proliferation can impact the cell migration assays used in this study.
      • MCF7 cell migration is minimal, making it difficult to draw meaningful conclusions from these experiments. Longer migration times might be helpful here
      • I was not able to open the supplementary videos, so I cannot comment on them.

      Significance

      General assessment: the strongest aspect of the study is the characterisation of the role of miR-200c expression in metastasis formation. However, the study lacks several controls. In my opinion, the in vivo work should be expanded, as the in vitro is mostly a confirmation of previous work. The data seem to hint to potential effect in organo-tropism, which warrant further investigation.

      Advance: the in vivo work is novel, extending the knowledge of miR200c role in metastasis, while most of the in vitro work is incremental or confirmatory.

      Audience: cancer biology researchers will mostly be interested in this work. There is potential for translational implications, but this needs to be strengthen.

      I am a cancer cell biologist, expert in cancer cell migration and invasion. Most of my expertise is in 2D and 3D in vitro models, but I am also very familiar with mouse breast cancer models. I don't have sufficient expertise to comment on the analysis of the confined cell motility assay.

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      Reply to the reviewers

      We appreciate the positive and constructive comments of the reviewers on our paper. Below please find our point-by-point response to their comments.

      Reviewer #1:

      Main comments:

      1) The expression levels of many genes, including some major TFs (like CEBPa or HNF4) in isolated primary hepatocytes greatly differ from that in normal liver. This is due to the disruption of cell-cell contacts. For this reason, single nuclei sequencing is more reliable and it is the preferred method. It is not indicated how many biological replicates were used and what level of variability was observed between different preparations.

      We thank the reviewer for pointing out the immediate response of hepatocytes to dissociation, including in expression of CEBPa or HNF4 (this reviewer) and stress-related genes (reviewer 3), which we were aware of.

      Unfortunately, however no perfect method exists to explore only hepatocytes in the context of the liver and single nuclei RNA-seq, which was not available at the start of our study, also has its limitations (e.g. substantial ambient RNA contamination, a lower median number of genes detected and potential for biases and higher doublet rates due to increased amplification steps (PMID: 34515767)).

      Importantly, in our current study, we were interested in exploring gene regulatory networks in hepatocytes by the combination of RNA-seq and ATAC-seq. In our hands, data that we obtained from single cell ATAC-seq was far too shallow and noisy to predict gene regulatory networks. Hence, we needed to rely on pure populations of hepatocytes to perform our studies with bulk ATAC-seq, for which we optimized perfusion and subsequent density gradient centrifugation. While we succeeded in obtaining a very pure hepatocyte population, we agree with the reviewer that due to dissociation-associated changes the results that we obtain might not fully reflect the events happening in hepatocytes in the liver.

      To address this issue brought up by reviewer 1 and 3, i) we will better indicate our rationale within the manuscript, and the limitations as indicated by both reviewer 1 and 3; ii) to provide an overview of potential changes that were induced by the perfusion procedure that we applied, we will compare the hepatocyte RNA-seq transcriptomes that we obtained with in vivo liver RNA-seq, with specific attention to transcription factors and stress-related genes (see reviewer 3, point 1); iii) we will better separate in the figures data obtained from hepatocytes versus data obtained from liver (see also point 2 from this reviewer).

      Additionally, we will indicate how many replicated were used, and the level of variability between different preparations (donors).

      2) The regulome studies involved analysis of ENCODE data sets (ChIP-seq), while the RNA-seq data were obtained in the current work. Due to the different source of the data (e.g primary hepatocytes used for ENCODE consortia members and this study) differences are expected. In the present study the cells were FACS-sorted immediately after isolation, while the ones used to produce ENCODE data sets were not subjected to sorting and were also probably cultured. This limits the accuracy of comparisons. Furthermore, the authors should indicate exactly which ENCODE data-sets were used.

      It is also unusual to observe broad distribution of the ATF3, JUND and EGR1 ChIP-seq reads over the PCK1 gene or the Alb gene (Fig S3). Peaks called by MACS should be indicated. Have the authors verified this distribution, e.g by ChIP-PCR or other means? It is quite unlikely that binding motifs are present all over the gene bodies. Is it possible that these factors interact with elongating RNA Pol-II complexes? What is the situation in other actively transcribing gene bodies?

      In the first paragraph of this comment, the reviewer rightfully points out that we use data from different sources in the first part of our study: scRNA-seq and ATAC-seq from perfusion-obtained hepatocytes (this study) and ENCODE ChIP-seq data which, in contrast to what the reviewer seems to assume, is obtained from liver (as profiled by ENCODE).

      We did choose to use ChIP-seq data from liver tissue to corroborate our findings in isolated hepatocytes in the tissue of origin (largely composed of hepatocytes). Indeed, the near perfect co-localization of HNF4A and ATF3/EGR1 in liver tissue and the enrichment of corresponding DNA motifs in our ATAC-seq data strongly suggests interaction between bZIP family members and hepatocyte-specific transcription factors (including HNF4A) and hence support our conclusion.

      To further address this issue, we will better separate the data obtained from hepatocytes versus data obtained from liver in the figures and include additional data for liver if available (see also point 1 from this reviewer). Additionally, we will indicate exactly which ENCODE datasets were used (see table below). Where relevant, we will explicitly mention the limitations/confounding factors of our analysis.

      EGR1-liver ChIP-seq

      ENCODE Project Consortium

      ENCFF389LQC, ENCFF132PDR

      JUND-liver ChIP-seq

      ENCODE Project Consortium

      ENCFF215GBK, ENCFF978CPC

      ATF3-liver ChIP-seq

      ENCODE Project Consortium

      ENCFF522PUA, ENCFF094LXX

      HNF4A-liver ChIP-seq

      ENCODE Project Consortium

      ENCFF302XOK, ENCFF500ZBE

      FOXA1-liver ChIP-seq

      ENCODE Project Consortium

      ENCFF765EAP, ENCFF945VNK

      CTCF-liver ChIP-seq

      ENCODE Project Consortium

      ENCFF002EXB

      RAD21-liver ChIP-seq

      ENCODE Project Consortium

      ENCFF643ZXX, ENCFF171UDL

      EGR1- K562 ChIP-seq

      ENCODE Project Consortium

      ENCFF000PZK, ENCFF000PZP

      JUND- K562 ChIP-seq

      ENCODE Project Consortium

      ENCFF000YSC, ENCFF000YSE

      ATF3- K562 ChIP-seq

      ENCODE Project Consortium

      ENCFF000PWC, ENCFF000PWA

      With respect to the second paragraph: We obtained these liver tissue ChIP-seq profiles from ENCODE, in which these have gone through thorough validation procedures. Furthermore, we do observe very similar patterns with a complementary, but independent approach, ATAC-seq in hepatocytes. Hence, we do not think that further validation by ChIP-qPCR will have much added value.

      We will follow the advice of the reviewer by i) indicating MACS peaks in our examples, ii) check whether ChIP-seq peaks in coding regions are typical for these datasets. If not, we will show better examples. If they are, we will are investigate potential motifs present in gene bodies, iii) investigate literature for a possible link between these factors and elongating RNA Pol-II complexes; and iv) investigate actively transcribing gene bodies

      3) The synergism between AP1 and HNF4 is based on RNA and ChIP data in Primary hepatocytes. The main evidence for the synergism are co-binding of the two factors and the regulome profiles in the individual cells. In ICOs where both factors are expressed at high levels ChIP-seq data are not available and the potential binding distribution is estimated by the presence of binding motifs in ATAC-seq positive areas. Considering the concern described in point 2, it is important to obtain ChIP-seq data in ICOs too.

      We would like to point out that, we make the central observations on overlapping regulatory modules in perfusion-derived hepatocytes, the ChIP-seq data to show co-binding of AP-1 and other factors with HNF4A (Fig 2c-f; Fig S3c-e) is all based on liver tissues. By showing this in the tissue or origin, we feel we provide sufficient evidence for the (potential) interplay between these factors in the liver, making ChIP-seq in ICOs redundant and beyond the scope of this study.

      In addition, more direct experimental evidence for the synergism is needed. For example, demonstrating the synergism between HNF4 and some AP1 factors in specific genes by co-transfection experiments.

      With regards to the potential synergy between HNF4 and AP1 in adult hepatocytes: previous studies have shown an essential role for c-Jun (part of AP1) in normal hematogenesis, with hepatocytes being rounded and detached in c-Jun KO mice (PMID: 8371760). This clearly shows the critical role of c-Jun in liver development and support to a potential interaction with HNF4 factors.

      Yet, we agree with the reviewers that co-transfection (or knock down) experiments would be an elegant means to further support our conclusion. Unfortunately, however, PHHs are refractory to transfection making this experiment nearly impossible. Hence, instead we will tone down our statements about cooperation between these factors, instead referring to overlapping regulatory modules and co-binding as we observe.

      4) Transcriptome comparisons between primary hepatocytes and intrahepatic cholangiocyte organoids (ICO) or ICOs cultured in hepatocyte differentiation medium (DM-ICO) were performed before (Ref. 6). These cells were derived from the same donor. In the current study ICOs were obtained from a biobank, thus they were from different donors. Differences between the expression patterns of primary cells and EM-IOC and DM-IOC organoid cultures are expected even if they derived from the same donor. In Ref.6 it is clearly demonstrated that DM-IOCs closely mimic many, but not all aspects of the liver phenotype. The present paper therefore provides only incremental new knowledge about the usefulness of organoid cultures in general. On the other hand, the scRNA-seq data with cells from the organoids point to the lack of zonation, which is an important new information, not analysed in Ref.6

      We agree with the reviewer that the EM-ICOs and DM-ICOs have been well characterized in the ground-breaking works Reference 6. Indeed, in Figure 5d of Reference 6, it is shown that DM-ICOs display more comparable expression profile to hepatocytes than EM-ICOs. However, there are also clear differences between hepatocytes and DM-ICOs, indicating incomplete differentiation of the later. In our study, we now make the important observation that the differentiation potential of ICOs at least in part depends on the expression of ELF3 (Figure 3B).

      To address this issue, we will put emphasis on the findings in Ref 6, and we will put our observations in better perspective in relation to Ref 6.

      5) In the methods section the description of ICO culture conditions are very epigrammatic. It refers to previously published protocols but also mentions the addition of BMP7 in the first round of culturing without explaining why was this important. It would be useful if the authors describe exactly the culture conditions they used. Were the ICOs from the biobank established under culture conditions described in Ref 6 or by previous protocols?

      We apologize for this being unclear. We will include this information in the revised manuscript.

      6) The results about ELF3 function are interesting and convincing. This is a novel finding and may worth to perform a global transcriptome analysis and some immunostainings with specific markers in siELF3 cells to further strengthen its regulatory role in cholangiocyte-hepatocyte conversion.

      We agree with the reviewer. To follow this up, we will perform RNA-seq during differentiation of ICOs towards hepatocytes, with and without siRNA-mediated ELF3 knockdown. This will further reveal the precise regulatory role of ELF3 in during hepatocyte differentiation.

      Reviewer #2:

      Comments:

      1) Hepatocyte nuclear factors do not form a transcription factor (TF) family, they are from different TF families: the nuclear receptor, homeobox, and forkhead TF (super)families.

      We thank the reviewer for pointing the mistakes in points 1 to 6 with regards to the naming of protein and protein families in our manuscript, we apologize for these inaccuracies. We will correct these naming and references, and check for any further inconsistencies.

      2) AP-1 is not a TF family either. It is basically a heterodimer of FOS and JUN (sub)family members, which are part of the bZIP (super)family such as C/EBPs and ATF3, which latter is related to JDP2.

      We will adapt this.

      3) EGR1 is not a bZIP protein, it is a zinc finger protein from the EGR family. Was the motif of EGRs enriched? Only the motif of C/EBPs is shown on Fig. 2D.

      We will adapt this. We will also analyze whether the motif of EGRs is enriched

      4) RAD21 is not a TF, it is part of the Cohesin ring, which is associated to the insulator-binding CTCF.

      We will adapt this.

      5) EP300 (Fig. 2A) and PPARGC1A (Fig. 3B) are not TFs, they are co-regulators, basically co-activators, which can interact with several TFs. EP300 is otherwise not so specific, its presence in the chromatin is one of the major active enhancer marks.

      We will adapt this.

      6) DNA sequence motifs are typically not specific for a single TF, rather for a TF (sub)family, so based on a motif, it is usually not possible to identify a certain TF (Fig. 3F). Are there other nuclear receptors, SOX or ETS proteins that can bind to the identified motifs? (For example, FLI1 and several other ETS proteins can bind to the motif of ELF3/EHF, or there are several DR1-binding nuclear receptor dimers like HNF4/HNF4 or PPAR/RXR.)

      We agree with the reviewer. We will analyze this and adapt the manuscript according to our findings.

      &) Although the manuscript is easy to follow and understand, it needs to be checked for grammar.

      We have asked a native speaker to proofread and adapt the manuscript.

      Reviewer #3:

      1) It is well known that perfusion of primary hepatic tissues (mice and human) results in immediate genetic responses, which will be captured right away in the performed RNASeq analysis. Stress pathways are upregulated and will normalize when the cells are put in culture for a couple of days. (Not too long, as they then undergo EMT and de-differentiate into non-parenchyma cells.) These responses can influence the expression profiles observed.

      We thank the reviewer for this comment. Please see how we will address this concern in our reply to reviewer 1, issue 1, who raised a very similar point.

      2) Why were the organoid cultures not differentiating properly into hepatocytes using different media cocktails (EM versus DM)? They seem to maintain cholangiocyte features, which questions the culture conditions used.

      We thank the reviewer for the chance to clarify this important point. We like to stress that we do use the standard differentiation protocol as published (which we will also better detail in our material methods) and it does lead to differentiation towards hepatocyte like cells (both morphologically and gene expression-wise). However, what is not highlighted in previous publications, but broadly observed in the field, is that this differentiation is far from being complete and that the extent to which proper differentiation occurs varies between organoids from different donors. In our study, we now make the important observation that the differentiation potential of ICOs at least in part depends on the expression of ELF3 (Figure 3B).

      3) The authors found the up-regulation of the AP-1 family proteins such as ATF3 and EGR1 which are known to induce apoptosis/cell death. Hepatic organoids are often found to have the un-intended necrotic core development which is caused by the oxygen diffusion matter and this issue is highly likely relevant to the size of the organoids. So, it would be advisable to specify the size of hepatic organoids (i.e., diameter) and check the necrosis-related genes.

      To follow-up on this comment of the reviewer: We will measure the size of our organoids. These organoids indeed are typically hollow inside and hence we will check the expression of necrosis related genes and adjust our conclusions accordingly.

      4) The KD approach with ELF3 in the ICOs is a good way forward, however only a minor number of hepatocellular genes are recovered, questioning the central role of ELF3 in driving the hepatocellular program. Functional assays, such as albumin release, bile acid production and CYP450 response should be coupled with the gene expression analysis.

      In line with the response to reviewer 1 (point 6) we will perform RNA-seq to better characterize ELF3 KD-associated genes expression changes including genes typical and functionally relevant for hepatocyte function (e.g. albumin release and bile acid secretion)

      5) The manuscript should be supplemented by adding the statement regarding the specific reason why a different set of donors was selected for two transcriptomics. The authors used three different donors for scRNA-seq and other two donors for the ATAC-seq. It seems better if all five donors were used for both transcriptomics analyses to reduce the inconsistent proportion of primary human hepatocytes (PHHs) from each donor. In addition, the donors which are selected should have identical genetic backgrounds for in-depth analysis of PHHs. The various backgrounds such as age, sex and ethnicity cause the transcriptional and translational heterogeneity. The authors need to explain the criteria on the selection of the donors.

      We do agree with the reviewer that ideally all experiments are performed on the same set of donors. However, PHHs are obtained from surgical margins and hence provide a very limited source, leading to different experiments being performed on different donors. Importantly, the replicates for each experiment type have been obtained from multiple donors enabling us to capture common rather than donor specific expression/chromatin accessibility signatures.

      Within the revised manuscript, we will include a paragraph on the criteria on the selection of the donors, and why a different set of donors was selected for two transcriptomics. Also, we will provide information with respect to the background of the donors.

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      Referee #3

      Evidence, reproducibility and clarity

      In this study the authors aimed at characterizing the differences between primary human hepatocytes and hepatic organoids derived from human intrahepatic cholangiocytes (ICO), which can differentiate into hepatocytes, using scRNA-seq and ATAC-seq approaches. Their goal was to identify gene regulatory signatures that differ between the two models and to single out transcription factors that could drive hepatocellular functionality. They found the AP-1 family members to be associated with increased hepatic function together with known hepatocyte identity markers, such as HNF4A, FOXA1 and FOXA2. In ICOs they observed an increase of ELF3, which represent cholangiocyte-like features. KD of this factor induced the expression of known hepatocellular marker genes, such as ALB, CYP3A4, TTR, GC, and GLUL, indicating ELF3 may function as a barrier in hepatocyte differentiation.

      Although this is an interesting approach to decipher, which transcription factors are involved in the development of proper human related hepatic organoids, it requires a more thorough analysis and ideally an improvement in the culture conditions to support their claims.

      1. It is well known that perfusion of primary hepatic tissues (mice and human) results in immediate genetic responses, which will be captured right away in the performed RNASeq analysis. Stress pathways are upregulated and will normalize when the cells are put in culture for a couple of days. (Not too long, as they then undergo EMT and de-differentiate into non-parenchyma cells.) These responses can influence the expression profiles observed.
      2. Why were the organoid cultures not differentiating properly into hepatocytes using different media cocktails (EM versus DM)? They seem to maintain cholangiocyte features, which questions the culture conditions used.
      3. The authors found the up-regulation of the AP-1 family proteins such as ATF3 and EGR1 which are known to induce apoptosis/cell death. Hepatic organoids are often found to have the un-intended necrotic core development which is caused by the oxygen diffusion matter and this issue is highly likely relevant to the size of the organoids. So, it would be advisable to specify the size of hepatic organoids (i.e., diameter) and check the necrosis-related genes.
      4. The KD approach with ELF3 in the ICOs is a good way forward, however only a minor number of hepatocellular genes are recovered, questioning the central role of ELF3 in driving the hepatocellular program. Functional assays, such as albumin release, bile acid production and CYP450 response should be coupled with the gene expression analysis.
      5. The manuscript should be supplemented by adding the statement regarding the specific reason why a different set of donors was selected for two transcriptomics. The authors used three different donors for scRNA-seq and other two donors for the ATAC-seq. It seems better if all five donors were used for both transcriptomics analyses to reduce the inconsistent proportion of primary human hepatocytes (PHHs) from each donor. In addition, the donors which are selected should have identical genetic backgrounds for in-depth analysis of PHHs. The various backgrounds such as age, sex and ethnicity cause the transcriptional and translational heterogeneity. The authors need to explain the criteria on the selection of the donors.

      Significance

      General assessment: This study used two powerful transcriptomics methods. The liver zonation was considered in the analysis which is reasonable. Limitations are related to cell culture conditions and lack of validations.

      Advance: This study extends the knowledge in human in vitro model system (mostly technical, but also clinical field).

      Audience: The audience from the basic and clinical research will be interested in this study.

      The field of expertise: Liver metabolism, pathophysiology of liver diseases, pre-clinical investigation

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      Referee #2

      Evidence, reproducibility and clarity

      Comments:

      1. Hepatocyte nuclear factors do not form a transcription factor (TF) family, they are from different TF families: the nuclear receptor, homeobox, and forkhead TF (super)families.
      2. AP-1 is not a TF family either. It is basically a heterodimer of FOS and JUN (sub)family members, which are part of the bZIP (super)family such as C/EBPs and ATF3, which latter is related to JDP2.
      3. EGR1 is not a bZIP protein, it is a zinc finger protein from the EGR family. Was the motif of EGRs enriched? Only the motif of C/EBPs is shown on Fig. 2D.
      4. RAD21 is not a TF, it is part of the Cohesin ring, which is associated to the insulator-binding CTCF.
      5. EP300 (Fig. 2A) and PPARGC1A (Fig. 3B) are not TFs, they are co-regulators, basically co-activators, which can interact with several TFs. EP300 is otherwise not so specific, its presence in the chromatin is one of the major active enhancer marks.
      6. DNA sequence motifs are typically not specific for a single TF, rather for a TF (sub)family, so based on a motif, it is usually not possible to identify a certain TF (Fig. 3F). Are there other nuclear receptors, SOX or ETS proteins that can bind to the identified motifs? (For example, FLI1 and several other ETS proteins can bind to the motif of ELF3/EHF, or there are several DR1-binding nuclear receptor dimers like HNF4/HNF4 or PPAR/RXR.)
      7. Although the manuscript is easy to follow and understand, it needs to be checked for grammar.

      Significance

      Haoyu Wu and his colleagues investigated the gene regulatory mechanisms contributing to human hepatocyte differentiation and maintenance integrating scRNA-seq, ATAC-seq, and ChIP-seq data and applying knock-down experiments. They differentiated the hepatocytes of the individual liver zones, identified the "lineage-determining" transcription factors of hepatocytes and intrahepatic cholangiocyte organoids, showed the co-localization of hepatocyte-specific and other, e.g., AP-1 transcription factors, and showed that the knock-down of ELF3 enhances hepatocyte characteristics. Although several findings and conclusions of the manuscript are available from the literature in some form, and some results could be interpreted better, this manuscript provides a novel insight in liver biology with results useful to the field. After thorough revision, this reviewer recommends the manuscript for publication.

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      Referee #1

      Evidence, reproducibility and clarity

      In this manuscript Wu et al., present results from a comparative analysis of transcriptomes of primary hepatocytes and organoid cultures derived from intrahepatic cholangiocytes. The authors also performed scRNA-seq and ATAC-seq experiments. Using SCENIC R computational tool and ENCODE ChIP-seq data they performed regulon analysis. The main findings of the paper are the following: 1) The cell-to-cell heterogeneity of primary hepatocytes are mainly due to their zonal expression patterns within porto-central axis. 2) AP1 family of factors (JUN, FOS, ATF3 and others) co-occupy gene regulatory regions bound by HNF4 and the associated transcriptome profiles suggest that AP1 factors cooperate with liver-specific factors to regulate hepatic genes. 3) Different sets of transcription factors are active in primary hepatocytes and intrahepatic cholangiocyte organoids that were differentiated in vitro to hepatocyte-like cells. 4) Identification of ELF3 as a factor required for cholangiocyte to hepatocyte conversion. The findings are interesting, although in many cases are expected. There are some issues that need to be addressed.

      Main comments:

      1. The expression levels of many genes, including some major TFs (like CEBPa or HNF4) in isolated primary hepatocytes greatly differ from that in normal liver. This is due to the disruption of cell-cell contacts. For this reason, single nuclei sequencing is more reliable and it is the preferred method. It is not indicated how many biological replicates were used and what level of variability was observed between different preparations.
      2. The regulome studies involved analysis of ENCODE data sets (ChIP-seq), while the RNA-seq data were obtained in the current work. Due to the different source of the data (e.g primary hepatocytes used for ENCODE consortia members and this study) differences are expected. In the present study the cells were FACS-sorted immediately after isolation, while the ones used to produce ENCODE data sets were not subjected to sorting and were also probably cultured. This limits the accuracy of comparisons. Furthermore, the authors should indicate exactly which ENCODE data-sets were used. It is also unusual to observe broad distribution of the ATF3, JUND and EGR1 ChIP-seq reads over the PCK1 gene or the Alb gene (Fig S3). Peaks called by MACS should be indicated. Have the authors verified this distribution, e.g by ChIP-PCR or other means? It is quite unlikely that binding motifs are present all over the gene bodies. Is it possible that these factors interact with elongating RNA Pol-II complexes? What is the situation in other actively transcribing gene bodies?
      3. The synergism between AP1 and HNF4 is based on RNA and ChIP data in Primary hepatocytes. The main evidence for the synergism are co-binding of the two factors and the regulome profiles in the individual cells. In ICOs where both factors are expressed at high levels ChIP-seq data are not available and the potential binding distribution is estimated by the presence of binding motifs in ATAC-seq positive areas. Considering the concern described in point 2, it is important to obtain ChIPs-seq data in ICOs too. In addition, more direct experimental evidence for the synergism is needed. For example, demonstrating the synergism between HNF4 and some AP1 factors in specific genes by co-transfection experiments.
      4. Transcriptome comparisons between primary hepatocytes and intrahepatic cholangiocyte organoids (ICO) or ICOs cultured in hepatocyte differentiation medium (DM-ICO) were performed before (Ref. 6). These cells were derived from the same donor. In the current study ICOs were obtained from a biobank, thus they were from different donors. Differences between the expression patterns of primary cells and EM-IOC and DM-IOC organoid cultures are expected even if they derived from the same donor. In Ref.6 it is clearly demonstrated that DM-IOCs closely mimic many, but not all aspects of the liver phenotype. The present paper therefore provides only incremental new knowledge about the usefulness of organoid cultures in general. On the other hand, the scRNA-seq data with cells from the organoids point to the lack of zonation, which is an important new information, not analysed in Ref.6
      5. In the methods section the description of ICO culture conditions are very epigrammatic. It refers to previously published protocols but also mentions the addition of BMP7 in the first round of culturing without explaining why was this important. It would be useful if the authors describe exactly the culture conditions they used. Were the ICOs from the biobank established under culture conditions described in Ref 6 or by previous protocols?
      6. The results about ELF3 function are interesting and convincing. This is a novel finding and may worth to perform a global transcriptome analysis and some immunostainings with specific markers in siELF3 cells to further strengthen its regulatory role in cholangiocyte-hepatocyte conversion.

      Referees cross-commenting

      I fully agree with the comments of Reviewer 2. Addressing them would clearly improve the paper. I also fully agree with Reviewer 3. In my opinion, special emphasis should be put on addressing point 1, 3, 4 and 5. Properly addressing these points would also answer at least partially my concerns (Reviewer 1) described in point 1, 2, 3 and 6. I would recommend the authors focus on the above issues.

      Significance

      Strengths: combines scRNA-seq with regulome analysis to identify synergism between different classes of transcription factors.

      Weaknesses: The data sets come from different sources. Key conclusions drawn from computational analysis are not validated experimentally. Comparing expression patterns of primary cells with those of organoid cultures is risky due to a number of technical limitations.

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

      Learn more at Review Commons


      Reply to the reviewers

      We appreciate the time and effort that you and the reviewers have dedicated to providing your valuable feedback on our manuscript. Those comments are all valuable and very helpful for revising and improving our paper, as well as the importance guiding significance to our researches. We have highlighted the changes in yellow within the manuscript.

      *Here is a point-by-point response to the reviewers’ comments and concerns. *

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

      The provided document, titled "Camel Milk Affects Serum Metabolites by Modulating the Intestinal Microflora," is an extensive research paper. My summary covers the first 44 pages of the total 63 pages. The document begins with a standard review commons manuscript notice and provides contact information for the Review Commons office.

      The research focuses on the effects of camel milk on serum metabolites and the intestinal microflora. It starts with a detailed introduction to the topic, outlining the crucial role of gut microbes in human health and the influence of various factors like diet, genetics, and environment on these microbes. The paper emphasizes the nutritional richness of camel milk and its potential as a functional food, particularly its impact on gut microbiota and host metabolism.

      Initial sections of the paper discuss the research methodologies, including the study's keywords, abstract, and introduction. The abstract highlights the study's significant findings, such as the presence of various beneficial bacteria in sour camel milk, the inter- and intra-species transportation of microbiomes, and the impact of camel milk on the gut microflora and serum metabolites of type 2 diabetic rats.

      The introduction further delves into the composition of the human gut microbiota and the shaping factors of the adult gut microbiome. It also examines the role of diet in modulating gut microbiota and the potential health benefits of dairy products, with a particular focus on camel milk.

      Subsequent sections present detailed research findings, including the results of microbial composition and source analysis in camel milk, the composition and changes of rat gut microbiota under camel milk regulation, and the effects of camel milk-regulated gut microbiota on metabolism in rats. The research also explores the interspecies transfer of microbes using camel milk as a vector and analyzes the gut microbiota in people consuming camel milk.

      The paper further discusses the endophytic flora of camel edible desert plants and their possible influence on the camel's gut microbiota. The discussion section integrates the findings, offering insights into the potential health benefits of camel milk and its probiotic qualities. It also compares the effects of camel milk with other dairy products and discusses its role as a vector for beneficial microbes.

      Materials and methods used in the study are detailed towards the end of the summarized portion, describing sample collection and processing, the experimental setup for rats, and data processing and analysis techniques.

      Reviewer #1 (Significance (Required)):

      The paper continues with detailed research findings, including the microbial composition in camel milk, the impact on the gut microflora of rats and humans, and the serum metabolism effects.

      There's a focus on how camel milk, as a vector, can transfer beneficial microbes between species, influencing gut microbiota and host metabolism.

      The paper compares the effects of camel milk with other dairy products, emphasizing its unique health benefits and its role in transferring beneficial microbes.

      It discusses various bacteria found in camel milk and their potential health benefits.

      The research findings extend to understanding how camel milk affects human gut microbiota, with studies on pastoral herders who consume camel or bovine milk.

      Author response: We thank you for your approval and constructive and valuable feedback from you and other reviewers.

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

      summary:

      The authors introduce a study assessing the bacterial flora of sour fermented camel milk and its capability to introduce beneficial species into consumer's gut. They further tested the potential of its nutrients and species for beneficial effects on type 2 diabetic (t2d) rats. They claim that t2d rats fed with high-dose camel whey reveal a microbiota closer to that of healthy rats rather than that of other t2d rats not receiving the camel whey treatment. Further they claim that this effect is due to the presence of Eubacterium limnetica that was exclusively found in the gut microflora of rats taking camel milk and producing MtcB protein. They conclude that camel milk may have the potential to be functional food.

      Overall, I think the approach of looking into camel milk and its microbiota is of broad interest, as it is food consumed traditionally by many tribes and in several countries. However, to me the presentation of the findings, the data and the analysis is often unprecise and confusing.

      For example, the MtcB protein they claim to be the mechanism of reducing the risk for t2d in the abstract is mentioned only once in the whole study and there only as a finding of another study (cited). According to my understanding the abstract should contain the main findings of the study, rather than some side-finding from other studies happens to match with the study results. I assume the authors have plenty of results from their sequencing data and metabolomics that they could mention in the abstract.

      In the text the authors mention the analysis of the microbial composition and source analysis of camel milk, the analysis of the gut microbiota of young camels, the composition, and changes of rat gut microbiota under the regulation of camel milk, the structure and changes of gut microbiota in people taking camel milk and the analysis of the endophytic flora of camel edible desert plants. And this just quoting the headers in the results section. Why is that not represented/mentioned in the abstract? Instead the authors focus on the t2d rats and the MtcB mechanism they fail to present.

      Further the authors are sloppy when it comes to typos and preciseness. For example, in the abstract they talk first about sour camel milk, then whey and then milk again.

      I suggest a major restructuring/rewriting and if necessary partial reanalysing of the results and the conclusions.

      It would be good to have an overview figure combining the work done, also stating the number of samples for each experiment.

      __Author response: __Thank you very much for your nice suggestion on our manuscript, we applied some restructuring to our manuscript and the changes were highlighted in yellow.

      Major comments:

      1) Please make sure all raw data (sequences and filtering/assembly results) are deposited in public databases, like NCBI, ENA or else.

      __Author response: __The corresponding data is available as Mendeley Data, V1, https://doi.org/10. 17632/4w8n8n96tc.1, some datasets with bigger size uploaded failed owing to internet problem. The full version could be offered in other approaches if requested.

      2) Please state briefly for each dataset analysed, which sequencing method was used, how many samples were collected and how many were pooled for the sequencing runs:

      AmpliAeq, whole metagenome HiSeq, MiSeq?

      __Author response: __Sample and dataset information for sequence was supplied in Supplementary Table 9 and 12. Sequencing library was prepared following Illumina library preparation instructions, and sequenced using Illumina Miseq platform at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China) with pair-end (PE) 150 bp reads.

      3) Page14 line283:

      F082? What is it? A strain, species or a sample?

      Please state clearly in the text.

      Also please avoid using abbreviations where possible and if you have to use them, please define.

      __Author response: __When applying diversity analysis at the specie level, a species annotated as unclassified_g_norank_f_F082 was found abundant in camel feces in Darbancheng.

      4) Page14 line307:

      "These evidenced that camel milk was a vector transferring microbes from the female camel to their cubs."

      Yes, that may be likely, but 16S amplicon-seq cannot provide evidence. Evidence would be strain similarity confirmed by SNP's or the like. So please state that this is speculative or show appropriate evidence.

      __Author response: __We completely agree that SNP’s is better evidence for this point and thank you. Microbial diversity analysis was a main part of initial design, and our limited sample couldn’t meet the needs of diversity and SNPs in the same time. There also were reports which used 16S based methods to trace the microbes source(Du et al., 2022; El-Mokdad, 2014; Wang et al., 2018).

      5) Page15 line322 ff:

      "Besides, using raw milk was not effective in type 2 diabetic rat model, so we chose camel whey and bovine whey as the diet of type 2 diabetic rats in follow-up experiments"

      Data/evidence? How is it different from whey on a nutrient perspective, as whey was more effective? Any explanation for this difference? And the bovine whey, what species did it contain? Can they be transferred regarding the processing of whey prior to application?

      __Author response: __This is an interesting and valuable question. We prepared raw milk and whey for the pre-test, then directly turned to validate the function of whey. Maybe we will investigate the composition difference in the future. The whey was prepared using the following protocol: Centrifuge fresh milk for 20 mins at 5000 r/min, discard the fat, and precipitate and obtain the middle layer of skim milk. After 20 mins in a 40 ℃ water bath, adjust the pH to 4.6 with 10% glacial acetic acid, and store in a 4°C refrigerator, overnight. Then, the skim milk was centrifuged at 8000 r/min for 20 min, repeated twice, and the middle whey fraction was collected. The centrifuged whey was poured into a petri dish and sealed. It was frozen at -80°C for 12 hours and then pierced with a sterile toothpick on the petri dish and then freeze-dried to get whey powders. A speculation was the preparing progress of whey played an important role in their functional difference. A comprehensive comparison of camel raw milk, camel whey, bovine raw milk, and whey will be an interesting point and we may investigate it shortly.

      6) Page17 line366ff:

      "Taking the number of microbes involved in this pathway, 8001 species were noted in the high-dose camel whey group, 3447 in the positive drug group, and only 1467 in the diabetics." How many species were present in the rats initially? Was species abundance different in the first place, or did they get lost, or came from the camel whey?

      __Author response: __The rats were fed with broad-spectrum antibiotics for 2 weeks, which ensured the same species abundance in the beginning.

      7) Page17 line369 ff:

      "It indicated that these microbes might resist the high glucose environment of the host through the synthesis and metabolism of their amino acids, and the effect of high-dose camel milk was more effective than that of metformin"

      -> How high was the glucose level in the rat gut? Or were there any obvious physiological changes in the t2d model rats that are characteristic for such a high-glucose environment? Please explain.

      __Author response: __This is an interesting and critical question. We didn’t measure the glucose level in the rat gut directly because we had to make sure other related characterizations worked properly. Besides, we thought camel milk could regulate microbial community, and further influence the blood sugar level, which was more representative in our sight. Blood sugar level is supplied in Fig.4O and Supplementary Table 11.

      8) The resolution/quality of the figures is low and the labelling often small. So not all text is readable.

      __Author response: __We adjusted the figures in the manuscript and offered additional independent picture files. Additionally, it seemed caused by the PDF merge progress, please check the pictures in .docx or .png files for details.

      9) Page19 line400 ff:

      What serum metabolites were analysed and why? Please write an intro-sentence to make it easier for the reader.

      Please write more precise what methods were used. Maybe I missed it, but I didn't find it in the methods part as well (Page40/41).

      __Author response: __The rats fed high-dose camel whey or metformin showed similar improvement in serum metabolite imbalance and were closer to normal. Caproylcarnitine, taurodeoxycholic acid, acetylcarnitine, creatinine, linoleic acid, and tridecanoic acid were detected as upregulated; 2-deoxyuridine, cyclohexylamine, L-pipecolic acid, LysoPC(18:0), uracil, caprylic acid, cholesterol sulfate, L-citrulline, pelargonic acid, and phenol downregulated. Carnitine supplementation, due to its key role in lipid metabolism and antioxidant effects, may effectively manage Type 2 Diabetes by addressing fatty acid metabolism dysregulation and oxidative stress(Bene, Hadzsiev, & Melegh, 2018). Studies have shown that taurodeoxycholic acid can enhance the effect of insulin and reduce blood sugar levels by regulating endoplasmic reticulum stress, and have potential in the treatment of diabetes(Xing, Zhou, Wang, & Xu, 2023). Low serum creatinine is associated with the development of T2D(Song, Hong, Sung, & Lee, 2022). Increased linoleic acid consumption was recommended for the prevention of T2D(Henderson, Crofts, & Schofield, 2018). The uridine is phosphorylated into uracil, which is converted to 2-deoxyuridine. Then 2-deoxyuridine is further converted to thymine with thymidine phosphorylase, the expression of thymidine phosphorylase was lost or considerably reduced when the organism suffered nephropathy and the high concentration of thymidine is a cause of DNA impairment, which is related to diabetes and diabetic nephropathy(Spinazzola et al., 2002; Szabo et al.; Xia, Hu, Liang, Zou, Wang, & Luo, 2010). L-Pipecolic acid are associated with higher incidence of T2D(Razquin et al., 2019). A research showed LysoPC(16:0) and (18:0) may mediated a fast progression of diabetic kidney disease(Yoshioka et al., 2022). Cholesterol sulfate is the most abundant known sterol sulfate in human plasma, and it plays a significant role in the control of glucose metabolism, which contribute to the pathogenesis of insulin resistance and the resultant development of diabetes(Shi et al., 2014; Zhang et al., 2022). L-citrulline supplementation might improve glucose homeostasis, some lipid factors and inflammatory markers in overweight and obese patients with T2D(Azizi, Mahdavi, Mobasseri, Aliasgharzadeh, Abbaszadeh, & Ebrahimi-Mameghani, 2021). T2D mellitus is associated with increased total plasma free fatty acid and modulating its concentration is the mechanism of some fibrates and statins drugs(I. S. Sobczak, A. Blindauer, & J. Stewart, 2019). Most of these metabolites have been reported as causes of T2D or consequences of T2D progress, some have been designed as therapeutic target.

      The serum metabolites were carried out using Agilent 1290 Infinity UHPLC system equipped with a HILIC column. The mobile phase of the optimized method consisted of (A) water with 25 mM ammonium acetate and 25 mM ammonia; and (B) acetonitrile (ACN). The following gradient elution was used: 5% A at 0-1min; 5-35% A at 1-14 min; 35-60% A at 14-16 min; 60% A at 16-18 min ; 60-5% A at 18-18.1 min and 5% A at 18.1-23 min. The flow rate was 0.3 mL/min, injection volume 2 μL, and column temperature was 25 ℃. Triple TOF 5600 mass spectrometer was applied for mass spectrometer analysis. The condition was used as following: Ion Source Gas1:60,Ion Source Gas2:60,Curtain gas:30,source temperature:600℃,IonSapary Voltage Floating ± 5500 V. TOF MS scan m/z range:60-1000 Da,product ion scan m/z range:25-1000 Da,TOF MS scan accumulation time 0.20 s/spectra, product ion scan accumulation time 0.05 s/spectra.MS/MS was gathered by information dependent acquisition (IDA) using high sensitivity mode, Declustering potential:±60 V, Collision Energy:35±15 eV, and IDA was set as Exclude isotope within 4 Da, Candidate ions to monito per cycle: 6. The methods part was complemented.

      Minor comments:

      1) Page1, line56-58 ff

      Please phrase more clearly:

      "This study specified that the transportation of microbiome happened both intra- and inter-species and played a principal role in the formation of progeny gut microflora."

      While the content is mostly comprehensible, there is a need for rephrasing and correction of language also in the following text.

      __Author response: __As suggested by the reviewer, we have rephrased and modified the abstract part.

      2) Page14 line300 ff:

      There is no need to show the OTU numbers in the text, please provide your results as a table in the supplements and refer to it in the text.

      Author response: We deleted OTU numbers in the manuscript and added the corresponding table in supplementary file.

      3) Page15 line328: Please check for typos, it is Shannon index, not Shanno.

      __Author response: __The corresponding correction was applied in the manuscript.

      4) Page16 line334:

      Please mention the number, age and sex of the rats used and how many groups you had in your experiments.

      __Author response: __SPF-grade male rats weighing 180-220 g were used for our related experiments. The detailed information is available in Supplementary Material (Supplementary Table 11-13).

      5) The headlines should logically structure the paper:

      For example, the authors have two very similar sections in the results part: "Composition and changes of rat gut microbiota under the regulation of camel milk" and "Analysis of the composition of gut microbiota in rats". Those can be combined or stated more concise.

      Also, other headlines improvement to make it easier for the reader to follow.

      __Author response: __We adjusted this part in the manuscript according to the reviewer’s suggestion.

      Reviewer #2 (Significance (Required)):

      I do think the study is of broad interest and relevance. However, the presentation of the analysis and data needs major revision. Especially it is lacking clarity on what was done for which samples and how the authors draw their conclusions. Also, I think that abstract and main text have a different focus. I would suggest to the authors to concentrate on their findings in abstract and text and state precisely what was done and what they found.

      __Author response: __Thank you very much for your recognition of our manuscript.

    2. 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 introduce a study assessing the bacterial flora of sour fermented camel milk and its capability to introduce beneficial species into consumer's gut. They further tested the potential of its nutrients and species for beneficial effects on type 2 diabetic (t2d) rats. They claim that t2d rats fed with high-dose camel whey reveal a microbiota closer to that of healthy rats rather than that of other t2d rats not receiving the camel whey treatment. Further they claim that this effect is due to the presence of Eubacterium limnetica that was exclusively found in the gut microflora of rats taking camel milk and producing MtcB protein. They conclude that camel milk may have the potential to be functional food.

      Overall, I think the approach of looking into camel milk and its microbiota is of broad interest, as it is food consumed traditionally by many tribes and in several countries. However, to me the presentation of the findings, the data and the analysis is often unprecise and confusing. For example, the MtcB protein they claim to be the mechanism of reducing the risk for t2d in the abstract is mentioned only once in the whole study and there only as a finding of another study (cited). According to my understanding the abstract should contain the main findings of the study, rather than some side-finding from other studies happens to match with the study results. I assume the authors have plenty of results from their sequencing data and metabolomics that they could mention in the abstract. In the text the authors mention the analysis of the microbial composition and source analysis of camel milk, the analysis of the gut microbiota of young camels, the composition, and changes of rat gut microbiota under the regulation of camel milk, the structure and changes of gut microbiota in people taking camel milk and the analysis of the endophytic flora of camel edible desert plants. And this just quoting the headers in the results section. Why is that not represented/mentioned in the abstract? Instead the authors focus on the t2d rats and the MtcB mechanism they fail to present. Further the authors are sloppy when it comes to typos and preciseness. For example, in the abstract they talk first about sour camel milk, then whey and then milk again.

      I suggest a major restructuring/rewriting and if necessary partial reanalysing of the results and the conclusions.

      It would be good to have an overview figure combining the work done, also stating the number of samples for each experiment.

      Major comments:

      1. Please make sure all raw data (sequences and filtering/assembly results) are deposited in public databases, like NCBI, ENA or else.
      2. Please state briefly for each dataset analysed, which sequencing method was used, how many samples were collected and how many were pooled for the sequencing runs: AmpliAeq, whole metagenome HiSeq, MiSeq?
      3. Page14 line283: F082? What is it? A strain, species or a sample? Please state clearly in the text. Also please avoid using abbreviations where possible and if you have to use them, please define.
      4. Page14 line307: "These evidenced that camel milk was a vector transferring microbes from the female camel to their cubs." Yes, that may be likely, but 16S amplicon-seq cannot provide evidence. Evidence would be strain similarity confirmed by SNP's or the like. So please state that this is speculative or show appropriate evidence.
      5. Page15 line322 ff: "Besides, using raw milk was not effective in type 2 diabetic rat model, so we chose camel whey and bovine whey as the diet of type 2 diabetic rats in follow-up experiments" Data/evidence? How is it different from whey on a nutrient perspective, as whey was more effective? Any explanation for this difference? And the bovine whey, what species did it contain? Can they be transferred regarding the processing of whey prior to application?
      6. Page17 line366ff: "Taking the number of microbes involved in this pathway, 8001 species were noted in the high-dose camel whey group, 3447 in the positive drug group, and only 1467 in the diabetics." How many species were present in the rats initially? Was species abundance different in the first place, or did they get lost, or came from the camel whey?
      7. Page17 line369 ff: "It indicated that these microbes might resist the high glucose environment of the host through the synthesis and metabolism of their amino acids, and the effect of high-dose camel milk was more effective than that of metformin"
      8. How high was the glucose level in the rat gut? Or were there any obvious physiological changes in the t2d model rats that are characteristic for such a high-glucose environment? Please explain.
      9. The resolution/quality of the figures is low and the labelling often small. So not all text is readable.
      10. Page19 line400 ff: What serum metabolites were analysed and why? Please write an intro-sentence to make it easier for the reader. Please write more precise what methods were used. Maybe I missed it, but I didn't find it in the methods part as well (Page40/41).

      Minor comments:

      1. Page1, line56-58 ff Please phrase more clearly: "This study specified that the transportation of microbiome happened both intra- and inter-species and played a principal role in the formation of progeny gut microflora." While the content is mostly comprehensible, there is a need for rephrasing and correction of language also in the following text.
      2. Page14 line300 ff: There is no need to show the OTU numbers in the text, please provide your results as a table in the supplements and refer to it in the text.
      3. Page15 line328: Please check for typos, it is Shannon index, not Shanno.
      4. Page16 line334: Please mention the number, age and sex of the rats used and how many groups you had in your experiments.
      5. The headlines should logically structure the paper: For example, the authors have two very similar sections in the results part: "Composition and changes of rat gut microbiota under the regulation of camel milk" and "Analysis of the composition of gut microbiota in rats". Those can be combined or stated more concise. Also, other headlines improvement to make it easier for the reader to follow.

      Significance

      I do think the the study is of broad interest and relevance. However, the presentation of the analysis and data needs major revision. Especially it is lacking clarity on what was done for which samples and how the authors draw their conclusions. Also I think that abstract and main text have a different focus. I would suggest to the authors to concentrate on their findings in abstract and text and state precisely what was done and what they found.

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

      Learn more at Review Commons


      Referee #1

      Evidence, reproducibility and clarity

      The provided document, titled "Camel Milk Affects Serum Metabolites by Modulating the Intestinal Microflora," is an extensive research paper. My summary covers the first 44 pages of the total 63 pages. The document begins with a standard review commons manuscript notice and provides contact information for the Review Commons office.

      The research focuses on the effects of camel milk on serum metabolites and the intestinal microflora. It starts with a detailed introduction to the topic, outlining the crucial role of gut microbes in human health and the influence of various factors like diet, genetics, and environment on these microbes. The paper emphasizes the nutritional richness of camel milk and its potential as a functional food, particularly its impact on gut microbiota and host metabolism.

      Initial sections of the paper discuss the research methodologies, including the study's keywords, abstract, and introduction. The abstract highlights the study's significant findings, such as the presence of various beneficial bacteria in sour camel milk, the inter- and intra-species transportation of microbiomes, and the impact of camel milk on the gut microflora and serum metabolites of type 2 diabetic rats.

      The introduction further delves into the composition of the human gut microbiota and the shaping factors of the adult gut microbiome. It also examines the role of diet in modulating gut microbiota and the potential health benefits of dairy products, with a particular focus on camel milk.

      Subsequent sections present detailed research findings, including the results of microbial composition and source analysis in camel milk, the composition and changes of rat gut microbiota under camel milk regulation, and the effects of camel milk-regulated gut microbiota on metabolism in rats. The research also explores the interspecies transfer of microbes using camel milk as a vector and analyzes the gut microbiota in people consuming camel milk.

      The paper further discusses the endophytic flora of camel edible desert plants and their possible influence on the camel's gut microbiota. The discussion section integrates the findings, offering insights into the potential health benefits of camel milk and its probiotic qualities. It also compares the effects of camel milk with other dairy products and discusses its role as a vector for beneficial microbes.

      Materials and methods used in the study are detailed towards the end of the summarized portion, describing sample collection and processing, the experimental setup for rats, and data processing and analysis techniques.

      Significance

      The paper continues with detailed research findings, including the microbial composition in camel milk, the impact on the gut microflora of rats and humans, and the serum metabolism effects. There's a focus on how camel milk, as a vector, can transfer beneficial microbes between species, influencing gut microbiota and host metabolism. The paper compares the effects of camel milk with other dairy products, emphasizing its unique health benefits and its role in transferring beneficial microbes. It discusses various bacteria found in camel milk and their potential health benefits. The research findings extend to understanding how camel milk affects human gut microbiota, with studies on pastoral herders who consume camel or bovine milk.

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

      Learn more at Review Commons


      Reply to the reviewers

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

      DBF4 and DRF1 knockout cells were generated and used to separate DBF4- and CDC7-dependent from DRF1- and CDC7-dependent activities. DBF4- and CDC7-dependent activities at replication forks were independent of DRF1. These include the replication timing pattern, replication fork velocity, DNA damage signaling. DBF4 is required to recruit CDC7 to active replication forks. The study is in large part exceptional.

      The inclusion of quantitation for a modest bandshift on CDC7 in figure 2 (30% vs 50% reduced) is not justified given the abundance of the main band and our knowledge of the lack of linearity of western blot quantitation. This should be removed.

      We thank the reviewer for evaluating our manuscript and for the positive feedback.

      In the revised manuscript we have removed the quantification of the bandshift related to CDC7 autophosphorylation in mitotic cells which was reported in Figure 1E. We recognise that the quantification may not be accurate although performed using semiquantitative near-infrared scanning technology. Importantly the experiment was performed three times with almost identical results.

      The only significant weakness in the paper is the explanation of the replication timing analyses in Figure 3. I don't understand what the differences between the plots equate to in terms of timing. I understand the replication of these regions that diverge is either early or late, but their were only two fractions of cells - 2N-3N and 3N-4N (the cells are "normal"). If this is the case, isn't the readout binary? a sequence either replicates in S phase between 2N and 3N or in S phase between 3N and 4N. Why are the differences so small? Are they only evident in a small population of cells? If that is the case, then what does the difference really mean? I think the description of these data needs to be precise.

      The replication timing experiments were performed with a well-established and reliable protocol (Ryba et al., 2011, https://doi.org/10.1038/nprot.2011.328). Asynchronous cells are labelled with a short pulse of BrdU, and sorted in two fractions, early and late S-phase, as described in Hiratani et al., 2008, Ryba et al., 2010, Hadjadj et al, 2016 and 2020 (https://doi.org/10.1371/journal.pbio.0060245) (https://doi.org/10.1101/gr.099655.109, https://doi.org/10.1016/j.gdata.2016.07.003, https://doi.org/10.1093/nargab/lqaa045).

      This method does not take into account the variation in the DNA copy number (2N vs 4N) between replicated and non-replicated parts of the genome (S/G1 ratio) as in Siefert et al., 2017 (https://doi.org/10.1101/gr.218602.116).

      The profiles depict the average replication timing of a population of 20,000,000 cells; thus, the readout is not binary.

      Replication timing profiles display the log ratio between early and late replicated fractions along the chromosome. Early replicated regions show positive log ratios and late replicated regions show negative ratios. The differential analysis performed with the START-R suite allows the comparison of the profiles (Ctrl vs either CDC7i-treated or DBF4-deficient cells). The genomic regions with altered timing are shown in green or in purple below the profiles, showing advanced and delayed regions, respectively.

      Importantly, the differences in replication timing are expressed with log ratio, that explains why the profiles are varying from -2 (very late replicating regions) and +2 (very early replicating regions). The differences we observed in Figure 3 are representative of two experiments, each composed of two technical replicates that are highly reproducible.

      To better describe the data, we have modified the text in the results section with the words in bold, as below: “These two neo-synthesized DNA fractions were then hybridised on human whole genome microarrays, as previously described. The log ratio between early and late replicated fractions was calculated and visualised for the whole genome.” We also changed the labelling of the replication profiles in Figure 3 and former Figure S3 (now Figure S4) by adding Log2 (Early/Late) to intensity and added two new sentences to the figure legend 3.“____Replication timing profiles display the log ratio between early and late replicated fractions along the chromosome. Positive log ratios correspond to early replicated regions whereas negative ratios correspond to late replicated regions.”

      Reviewer #1 (Significance (Required)):

      I think this paper is a significant advance that should be published. CDC7 is a critical kinase and identifying its co-factor at the replication fork is important both for our understanding of mechanisms of DNA replication and the impact of CDC7 kinase inhibitors in the clinic. I think the majority of the experiments are well designed and the results are unambiguous and precisely described.

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

      CDC7 is a master cell cycle kinase with essential functions in DNA replication and important roles in the DNA damage response. For its functions, CDC7 relies on a regulatory factor, DBF4, which is essential in many species but not in human cells as a consequence of the presence of a second DBF4-related factor, DRF1. In this work, Göder and colleagues study the relative relevance of these regulatory proteins in CDC7 roles. Their study reveals DBF4 as the major regulatory subunit both in DNA replication, DNA damage checkpoint and fork dynamics. The objective of the study is highly relevant to understand an essential cell cycle kinase with potential applications in cancer therapies, the experiments are well performed and the conclusions are "in principle" sound.

      We thank this reviewer for the time and attention in evaluating the manuscript, for the positive feedback and for indicating key points for improvement and discussion.

      The major handicap of the study is the absence of western blots showing the elimination of DBF4 and DRF1 in the edited cell lines due to the lack of specific antibodies. The authors have generated homozygous mutations that lead to premature stop codons behind critical CDC7 domains. However, as they mention, it is not possible to fully exclude some proteins arising from internal start sites or exon skipping events with residual (functional or altered, and not necessarily residual) activity. This is not unexpected, especially for essential proteins. This would not be a major handicap if the study were focused in a specific factor because it would only question the impact of but not the affected function, but it aims to compare the relative effect of two defective genes. In this case, it is essential to confirm that both genes are eliminated, at least to the same degree.

      We agree with the reviewer that it would be valuable to confirm the effect of the mutations by immunoblotting.

      Over the years we have had multiple attempts at generating sensitive antibodies against both DBF4 and DRF1, using recombinant proteins and synthetic peptides. We also tested several commercially available anti-DBF4 and anti-DRF1 antibodies. While often we were able to detect overexpressed proteins, the detection of endogenous levels has been particularly challenging especially in non-transformed cells, such MCF10A.

      Nevertheless, with an anti-DBF4 serum we obtained from the Diffley lab, which was generated against the C-terminus fragment of hDBF4, we managed to detect endogenous full length DBF4 in parental but not in the DBF4-KO cells (this blot is now included as supplementary Fig S1B). Even with this reagent the detection levels are low and multiple non-specific immunoreactive bands are present, making the detection of DBF4 particularly challenging across the experiments. Interestingly, while DBF4 is no longer detectable in DBF4-11, one the two clones used in this work , we detect a new immunoreactive band of approximately 55kDa in the other clone DBF4-30. We reckon that this may be the result of mRNA translation from the next downstream methionine. In this case this aberrant protein would lack the N domain and most of the M domain, involved in CDC7 binding and activation, and thus this fragment is very likely not functional.

      Importantly, most results in this study were obtained using both DBF4-11 and DBF4-30 clones with indistinguishable results. Only the replication timing experiments were done using a single clone DBF4-11, in which DBF4 protein is not detected.

      We had less success with the direct detection of DRF1. As also suggested by reviewer #3, to screen the clones after genome editing, we originally performed IP-western experiments. We used an anti-DRF1 mAb and unrelated IgG for the immunoprecipitations and an anti-CDC7 antibody as a probe in western blotting. We detected an immunoreactive band above the background at the expected molecular weight for CDC7 when the immunoprecipitation was performed with extracts from parental cells (as well as in a clone obtained with a different sgRNA, targeting DRF1 Exon1 and never used in this study) but not when the immunoprecipitation was performed with extracts from the DRF1- 5 and DRF1-7 clones used in the study. These original co-IPs are credible although not particularly pretty and importantly the result was confirmed in a more convincing experiment in the DRF1-5 clone.

      These new data are now included in the resubmission in Figure S1. So, while the detection of the CDC7 regulatory subunits still remains particularly difficult, we can now provide evidence that their expression is altered in the engineered cell lines used in the study.

      The computational analysis in Figure 1C is consistent with the major conclusion about the primary regulatory role of DBF4 in replication, but it is insufficient to validate the specific phenotypes addressed in the study.

      The figure reports the effects of targeting single genes with multiple sgRNA (4 to 8 according to the library used) on proliferation rate/fitness measured after multiple days in more than 1000 screens across many different human cell types. Loss of fitness can be due either to a direct problem with DNA replication or with other cellular processes.

      We agree with the reviewer that the analysis in Fig 1C is consistent with the phenotypes shown in the study. Particularly it is consistent with the lack of a major defect of DRF1-deficient cells in DNA replication, and it strongly indicates an essential role for CDC7 which was somehow challenged by Suski and co-workers (see also below).

      Indeed, there is a result that is hard to understand if the edited cell lines are defective in the expression of the regulators, specially DRF1. Figure S2D-E shows no synergistic defect in DNA synthesis when the second regulator is knock down with specific siRNAs, not even DRF1 defective cell lines treated with a siDBF4 that reduces its expression 10 times. Also, it is not clear why the defects, specially in DBF4-defective cell lines, are less severe than in cells treated with an inhibitor that causes a partial inhibition of CDC7. If it is due to the expression of DRF4, a siRNA against DRF4 should cause more severe defects.

      Yes, we did not detect synergy or additive effect on the rate of DNA replication when targeting both DBF4 and DRF1 by multiple approaches. This was also for us an unexpected result, that we examined to the best of our capabilities.

      The lack of the expected synergy in the replication assays could be explained in multiple ways and could be of biological or technical nature such as 1) residual low levels of DBF4/DRF1 proteins remaining in the cells upon either CRISPR/Cas9 or siRNA targeting, 2) alternative mechanisms of kinase activation by a different, yet unidentified protein, 3) minimal residual enzymatic activity of hCdc7 kinase not requiring an activating subunit.

      We performed further computational analysis using the dataset of the DepMap project, assessing if the effect of targeting DBF4 on fitness may be dependent on the levels of DRF1 expression. In several instances, when dealing with paralogues the gene effect of knocking out one of the paralogues directly correlates with the expression levels of the second, a phenomenon known as paralogue buffering (De Kegel et al. 2019 https://doi.org/10.1371/journal.pgen.1008466 ).

      In the case of DBF4 and DRF1, this correlation is minimal (plot below: X and Y axes are DRF1 expression levels and DBF4 gene effect respectively, Pearson's correlation = 0.12) so that there are ~ 470 other genes whose expression is more correlated with DBF4 essentiality. Furthermore, by stratifying cell lines according to whether DBF4 was essential or not and then looking at DBF4B (DRF1) expression, we failed to see significant association (graph below).

      Thus, this analysis reinforces the idea that if cooperation between DBF4 and DRF1 exists, it is particularly difficult to demonstrate. To date the interplay between DBF4 and DRF1 is only indicated by the partial impairment on MCM2 phosphorylation and CDC7 autophosphorylation observed in the individual KOs and by the fact that we were unable to obtaining viable double KO mutant clones. We recognise that the latter is a negative result and double KO may be generated in other cellular models or with different strategies.

      We are happy to include the above computational analysis in a revised manuscript and to expand the discussion on the essentiality of CDC7, DBF4 and DRF1.

      The effects of directly inhibiting CDC7 with 10 microM XL413 (concentration used in this study) are indeed stronger than DBF4 KO / depletion on both DNA synthesis (Fig 2A-B) and MCM2 phosphorylation (Fig 4A and Fig 5A).

      We and others have previously shown that CDC7 inhibition by XL413 causes a dose dependent decrease in MCM2 phosphorylation and DNA synthesis. Importantly in the experiments where XL413 was titrated on MCF10A cells from 0.3 microM to 80 microM, we demonstrated that these parameters are uncoupled and that doses that are ~20-fold higher are required to cause a strong impediment of DNA synthesis compared to the dose required to cause full MCM2 dephosphorylation (Rainey et al. 2017 https://doi.org/10.1021/acschembio.7b00117 ).

      DBF4 deficiency only partially affects MCM2 phosphorylation thus it is comparable to very low doses of XL413, that we can estimate to be in the range between 1 and 2 microM.

      Minor points

      • Title in Pag 12. "DBF4 mediates the majority of CDC7 functions in the replication stress response". In this section the authors address only the role of CDC7 in checkpoint signalling but not in other processes related to the replication stress response.

      We agree and we have modified the title of this section accordingly.

      • Figure 2. "EdU incorporation in late S-phase/ per cell" is clearer

      We have modified the label of this figure.

      • Right panels in Figures 3A and 3B are duplicated

      We sincerely apologise for the mistake occurred while assembling the figure. The figure has been corrected, and shows that the changes in the replication timing with the CDC7i or with DBF4-KO are indeed similar but not identical.

      **Referees cross-commenting**

      I am aware of the difficulty to sort out the detection problem, a major handicap of the work. Immunoprecipitation as suggested by rev. 3 might be an interesting possibility. The results should be published, in any case, as they are well performed and try to answer a relevant question. But, if finally the authors fail to detect the proteins, they should make clear in the paper the limitation of their conclusions by the possibility that the expression of the regulators is not completely eliminated or could be altered. Indeed, the apparent contradiction with Suski's results raised by Rev 3 might be discussed in this context.

      We appreciate the reviewer’s recognition of the technical problems we have encountered. We are glad that we now are in a position to provide evidence of impairment of DBF4 and DRF1 expression in the engineered cells (discussed above and reported in new Figure S1 and S2).

      Also, it is important to explain the lack of synergism when combining the edited mutations with siRNAs.

      In a revised manuscript we will explain the potential reasons why lack of synergism either doesn’t exist or is not observed, as discussed above.

      Reviewer #2 (Significance (Required)):

      In summary, the work is relevant and interesting, but the lack of controls about the effect of the edition rises important concerns about the conclusions. It is evident from the acknowledgment section that the authors have tried without success to generate specific antibodies. An alternative possibility would be 1) to get similar results with at least two clones addressing different exons (actually, only one clone was used for DRF1 in most cases) and 2) show synergistic effects for the more important phenotypes in edited cells transfected with efficient siRNAs. This is particularly important for DRF1-defective cells, which show no phenotypes except for an increase in micronuclei. If DBF4 is not essential because the complementary activity of DRF1, impairment of DBF4 expression with siRNAs in DRF1 deficient cells should cause synergistic defects at least in DNA replication and cell viability.

      We hope we have satisfactory addressed this reviewer’s comments, by providing experimental evidence of the impairment of DBF4 and DRF1 expression/function in the engineered cells and several points for discussion addressing the lack of obvious synergy between DBF4 and DRF1.

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

      Summary Assembly of the CMG helicase during DNA replication initiation is regulated by the DBF-Dependent Kinase known as CDC7 (or DDK), which also plays roles at DNA replication forks during elongation. In vertebrates, DDK has two regulatory subunits called DBF4 and DRF1. Until now, the division of labour between these two activators of CDC7 was poorly understood in mammalian cells. To address this issue, the authors used CRISPR-Cas9 to edit the DBF4 and DRF1 genes in immortalised human breast cells (MCF10A), thereby truncating key domains of the DBF4 and DRF1 proteins. The DBF4-deficient and DRF1-deficient lines are viable, whereas the double mutant was unobtainable and likely inviable, as reported previously by the authors for knockout of CDC7 in MCF10A cells. The authors compare the DBF4-deficient and DRF1-deficient lines with the CDC7 inhibitor XL413, providing evidence that DBF4 has the major role in supporting CDC7 activity in MCF10A cells compared to DRF1, in terms of DNA replication, origin firing, fork progression, and checkpoint activation. Curiously, DRF1 appears to be more important in preventing the formation of micronuclei - another phenotype seen upon inhibition of CDC7 kinase activity.

      Major comments: The data are of high quality and the key conclusions are convincing, although it is unfortunate that the authors were not able to monitor the level of DBF4 and DRF1 by immunoblotting to validate their edited cell lines. The authors previously reported using immunoprecipitation of CDC7, DBF4 and DRF1 (Tenca et al, 2007, 10.1074/jbc.M604457200) to monitor DDK subunits in HeLa cells, which would presumably have been helpful here in MCF10A cells. Nevertheless, the DNA sequence of the edited clones indicates frameshift mutations that lead to premature STOP codons, and the various phenotypes reported in this manuscript are consistent with loss of DBF4 / DRF1 function as described.

      We thank the reviewer the time an effort in carefully assessing the manuscript, and with his/her positive assessment.

      We have now included experimental evidence indicating that DBF4 expression is deficient in the DBF4 KO cells used in this study and that the interaction with DRF1 and CDC7 is deficient in the DRF1-KO cells using the same Co-IP strategy previously reported in Hela cells. Please see also the response to reviewer #2 to the same point.

      Minor comments: 1. The authors should discuss their data in the context of the recent study by Suski et al (https://doi.org/10.1038/s41586-022-04698). The latter study reported that knockout of DBF4 in mouse fibroblasts impairs proliferation but is not lethal, in agreement with the present manuscript, but Suski et al also argue that CDC7 is dispensable for DNA replication in mammalian cells due to redundancy with CDK1.

      The requirement for CDC7 kinase activity for genome duplication in mammalian cells has become a contentious point of debate. CRISPR screens in more than 1000 cell lines indicate that CDC7 is a core essential gene required for proliferation (DepMap.org). Clearly human cells can clearly withstand reduced CDC7 activity, and several proteins contribute both positively and negatively to the effectiveness of CDC7 inhibition in DNA replication and cell proliferation e.g. RIF1 depletion, ATR inhibition, PTBP1 mutation. (Hiraga et al. 2017 https://doi.org/10.15252/embr.201641983 ; Rainey et al. 2020 https://doi.org/10.1016/j.celrep.2020.108096 : Jones et al. 2021 https://doi.org/10.1016/j.molcel.2021.01.004 ; Göder et al. 2023 https://doi.org/10.1016/j.isci.2023.106951).

      Specifically CDK1-phosphporylatyon of RIF1 was shown to disrupt RIF1/PP1 interaction and PP1’s ability to counteract CDC7-dependnet phosphorylation of the MCM complex (Moiseeva et al. 2019 https://doi.org/10.1073/pnas.1903418116 ; Jones et al. 2021 https://doi.org/10.1016/j.molcel.2021.01.004). Thus increased CDK1 activity can be helpful in dealing with low levels of CDC7 kinase.

      Suski et al argue that CDC7 is dispensable for DNA replication in human cells based on acute degradation of CDC7 or by its inhibition using an “Shokat type” analogue sensitive CDC7 allele. However, another study showed that DNA replication is not completed using the same approach and the same analogue sensitive allele (Jones et al. 2021 https://doi.org/10.1016/j.molcel.2021.01.004). In mouse embryonic stem cells, the Masai group had previously shown that CRE-Lox mediated inactivation of mDBF4 leads to a strong decrease of DNA synthesis and that mDBF4, like mCDC7 is essential for cell ES cells viability (Kim et al, 2002 https://doi.org/10.1093/emboj/21.9.2168 and Yamashita 2005 https://doi.org/10.1111/j.1365-2443.2005.00857.x ). Intriguingly mDRF1 has yet not been identified nor characterised. In our opinion, the simplest explanation to reconciliate the different reports is that human and mouse CDC7 are indeed required for DNA replication and for cell proliferation, but the phenotype of the most severe effects of its inhibition requires the complete loss of function of the kinase and may be delayed in time. We are happy to add these considerations in the discussion section of the revised manuscript.

      1. Some discussion of the increased frequency of micronuclei in DRF1-deficient cells compared to DBF4-deficient lines would be useful (c.f. Figure 1F-G).

      In the discussion we have suggested that the increase of micronucleated cells in the DRF1 deficient clones “could be consistent with a (DRF1) specific but not yet identified function in chromosome segregation, in the fine-tuning of DNA replication or the DNA repair process”. Of interest, CDC7 kinase was recently involved in modulating ATR function in cytokinetic abscission, and impairment of this process can lead to increase frequency of micro nucleated cells (Luessing et al. 2023 https://doi.org/10.1016/j.isci.2022.104536 ). It is possible that this new role of CDC7 could be dependent on DRF1, an hypothesis at present purely speculative, that we will be testing in the future. We are happy to add these considerations to the discussion section of the revised manuscript.

      1. It would be helpful to present actual p values in Figure 2, rather than asterisks.

      Asterisks report the range in which the p values fall into, which currently is specified in the legend. These can be substituted with actual numbers in the figures, and we will comply with the requirement of the journal in which the manuscript will be accepted.

      Reviewer #3 (Significance (Required)):

      The main strength of this manuscript is the exploration of the division of labour between DBF4 and DRF1 in human cells, regarding the roles of CDC7 kinase during DNA replication initiation, fork progression and checkpoint control. A limitation would be the failure to monitor the level of DBF4 and DRF1 in the CRISPR-edited cell lines, whilst it is also possible that the relative roles of DBF4 and DRF1 might vary in different cell types.

      Previous studies of DNA replication in Xenopus egg extracts (e.g. Takahashi et al, 2005: doi: 10.1101/gad.1339805) indicated that DRF1 is the dominant activator of CDC7. In contrast, past work from the current authors (Tenca et al, 2007, 10.1074/jbc.M604457200) indicated that DBF4 is the major partner of CDC7 in human HeLa cells, at least at the level of promoting MCM2 phosphorylation (the only parameter monitored in the previous study, whereas the present manuscript goes much deeper into the various roles of CDC7 in DNA replication control and focusses on the role of CDC7 at replication forks and in checkpoint control).

      This study should be of interest to those studying chromosome replication, checkpoints and genome integrity. It should also interest those with a more clinical perspective, due to the potential importance of CDC7 kinase inhibitors as anti-cancer agents.

      My own expertise is in the field of chromosome replication.

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      Referee #3

      Evidence, reproducibility and clarity

      Summary

      Assembly of the CMG helicase during DNA replication initiation is regulated by the DBF-Dependent Kinase known as CDC7 (or DDK), which also plays roles at DNA replication forks during elongation. In vertebrates, DDK has two regulatory subunits called DBF4 and DRF1. Until now, the division of labour between these two activators of CDC7 was poorly understood in mammalian cells. To address this issue, the authors used CRISPR-Cas9 to edit the DBF4 and DRF1 genes in immortalised human breast cells (MCF10A), thereby truncating key domains of the DBF4 and DRF1 proteins. The DBF4-deficient and DRF1-deficient lines are viable, whereas the double mutant was unobtainable and likely inviable, as reported previously by the authors for knockout of CDC7 in MCF10A cells. The authors compare the DBF4-deficient and DRF1-deficient lines with the CDC7 inhibitor XL413, providing evidence that DBF4 has the major role in supporting CDC7 activity in MCF10A cells compared to DRF1, in terms of DNA replication, origin firing, fork progression, and checkpoint activation. Curiously, DRF1 appears to be more important in preventing the formation of micronuclei - another phenotype seen upon inhibition of CDC7 kinase activity.

      Major comments:

      The data are of high quality and the key conclusions are convincing, although it is unfortunate that the authors were not able to monitor the level of DBF4 and DRF1 by immunoblotting to validate their edited cell lines. The authors previously reported using immunoprecipitation of CDC7, DBF4 and DRF1 (Tenca et al, 2007, 10.1074/jbc.M604457200) to monitor DDK subunits in HeLa cells, which would presumably have been helpful here in MCF10A cells. Nevertheless, the DNA sequence of the edited clones indicates frameshift mutations that lead to premature STOP codons, and the various phenotypes reported in this manuscript are consistent with loss of DBF4 / DRF1 function as described.

      Minor comments:

      1. The authors should discuss their data in the context of the recent study by Suski et al (https://doi.org/10.1038/s41586-022-04698). The latter study reported that knockout of DBF4 in mouse fibroblasts impairs proliferation but is not lethal, in agreement with the present manuscript, but Suski et al also argue that CDC7 is dispensable for DNA replication in mammalian cells due to redundancy with CDK1.
      2. Some discussion of the increased frequency of micronuclei in DRF1-deficient cells compared to DBF4-deficient lines would be useful (c.f. Figure 1F-G).
      3. It would be helpful to present actual p values in Figure 2, rather than asterisks.

      Significance

      The main strength of this manuscript is the exploration of the division of labour between DBF4 and DRF1 in human cells, regarding the roles of CDC7 kinase during DNA replication initiation, fork progression and checkpoint control. A limitation would be the failure to monitor the level of DBF4 and DRF1 in the CRISPR-edited cell lines, whilst it is also possible that the relative roles of DBF4 and DRF1 might vary in different cell types.

      Previous studies of DNA replication in Xenopus egg extracts (e.g. Takahashi et al, 2005: doi: 10.1101/gad.1339805) indicated that DRF1 is the dominant activator of CDC7. In contrast, past work from the current authors (Tenca et al, 2007, 10.1074/jbc.M604457200) indicated that DBF4 is the major partner of CDC7 in human HeLa cells, at least at the level of promoting MCM2 phosphorylation (the only parameter monitored in the previous study, whereas the present manuscript goes much deeper into the various roles of CDC7 in DNA replication control and focusses on the role of CDC7 at replication forks and in checkpoint control).

      This study should be of interest to those studying chromosome replication, checkpoints and genome integrity. It should also interest those with a more clinical perspective, due to the potential importance of CDC7 kinase inhibitors as anti-cancer agents.

      My own expertise is in the field of chromosome replication.

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      Referee #2

      Evidence, reproducibility and clarity

      CDC7 is a master cell cycle kinase with essential functions in DNA replication and important roles in the DNA damage response. For its functions, CDC7 relies on a regulatory factor, DBF4, which is essential in many species but not in human cells as a consequence of the presence of a second DBF4-related factor, DRF1. In this work, Göder and colleagues study the relative relevance of these regulatory proteins in CDC7 roles. Their study reveals DBF4 as the major regulatory subunit both in DNA replication, DNA damage checkpoint and fork dynamics. The objective of the study is highly relevant to understand an essential cell cycle kinase with potential applications in cancer therapies, the experiments are well performed and the conclusions are "in principle" sound.

      The major handicap of the study is the absence of western blots showing the elimination of DBF4 and DRF1 in the edited cell lines due to the lack of specific antibodies. The authors have generated homozygous mutations that lead to premature stop codons behind critical CDC7 domains. However, as they mention, it is not possible to fully exclude some proteins arising from internal start sites or exon skipping events with residual (functional or altered, and not necessarily residual) activity. This is not unexpected, especially for essential proteins. This would not be a major handicap if the study were focused in a specific factor because it would only question the impact of but not the affected function, but it aims to compare the relative effect of two defective genes. In this case, it is essential to confirm that both genes are eliminated, at least to the same degree. The computational analysis in Figure 1C is consistent with the major conclusion about the primary regulatory role of DBF4 in replication, but it is insufficient to validate the specific phenotypes addressed in the study. Indeed, there is a result that is hard to understand if the edited cell lines are defective in the expression of the regulators, specially DRF1. Figure S2D-E shows no synergistic defect in DNA synthesis when the second regulator is knock down with specific siRNAs, not even DRF1 defective cell lines treated with a siDBF4 that reduces its expression 10 times. Also, it is not clear why the defects, specially in DBF4-defective cell lines, are less severe than in cells treated with an inhibitor that causes a partial inhibition of CDC7. If it is due to the expression of DRF4, a siRNA against DRF4 should cause more severe defects.

      Minor points

      • Title in Pag 12. "DBF4 mediates the majority of CDC7 functions in the replication stress response". In this section the authors address only the role of CDC7 in checkpoint signalling but not in other processes related to the replication stress response.
      • Figure 2. "EdU incorporation in late S-phase/ per cell" is clearer
      • Right panels in Figures 3A and 3B are duplicated

      Referees cross-commenting

      I am aware of the difficulty to sort out the detection problem, a major handicap of the work. Immunoprecipitation as suggested by rev. 3 might be an interesting possibility. The results should be published, in any case, as they are well performed and try to answer a relevant question. But, if finally the authors fail to detect the proteins, they should make clear in the paper the limitation of their conclusions by the possibility that the expression of the regulators is not completely eliminated or could be altered. Indeed, the apparent contradiction with Suski's results raised by Rev 3 might be discussed in this context. Also, it is important to explain the lack of synergism when combining the edited mutations with siRNAs.

      Significance

      In summary, the work is relevant and interesting, but the lack of controls about the effect of the edition rises important concerns about the conclusions. It is evident from the acknowledgment section that the authors have tried without success to generate specific antibodies. An alternative possibility would be 1) to get similar results with at least two clones addressing different exons (actually, only one clone was used for DRF1 in most cases) and 2) show synergistic effects for the more important phenotypes in edited cells transfected with efficient siRNAs. This is particularly important for DRF1-defective cells, which show no phenotypes except for an increase in micronuclei. If DBF4 is not essential because the complementary activity of DRF1, impairment of DBF4 expression with siRNAs in DRF1 deficient cells should cause synergistic defects at least in DNA replication and cell viability.

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      Referee #1

      Evidence, reproducibility and clarity

      DBF4 and DRF1 knockout cells were generated and used to separate DBF4- and CDC7-dependent from DRF1- and CDC7-dependent activities. DBF4- and CDC7-dependent activities at replication forks were independent of DRF1. These include the replication timing pattern, replication fork velocity, DNA damage signaling. DBF4 is required to recruit CDC7 to active replication forks.

      The study is in large part exceptional. The inclusion of quantitation for a modest bandshift on CDC7 in figure 2 (30% vs 50% reduced) is not justified given the abundance of the main band and our knowledge of the lack of linearity of western blot quantitation. This should be removed.

      The only significant weakness in the paper is the explanation of the replication timing analyses in Figure 3. I don't understand what the differences between the plots equate to in terms of timing. I understand the replication of these regions that diverge is either early or late, but their were only two fractions of cells - 2N-3N and 3N-4N (the cells are "normal"). If this is the case, isn't the readout binary? a sequence either replicates in S phase between 2N and 3N or in S phase between 3N and 4N. Why are the differences so small? Are they only evident in a small population of cells? If that is the case, then what does the difference really mean? I think the description of these data needs to be precise.

      Significance

      I think this paper is a significant advance that should be published. CDC7 is a critical kinase and identifying its co-factor at the replication fork is important both for our understanding of mechanisms of DNA replication and the impact of CDC7 kinase inhibitors in the clinic. I think the majority of the experiments are well designed and the results are unambiguous and precisely described.

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      Reply to the reviewers

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

      This research article describes genetic identification and expression analyses of six Ephrin type-B receptor 4 (EPHB4) variants identified in patients with dilated cardiomyopathy (DCM). Variants were identified Variants were identified in a cohort of 573 patients enrolled through the multicenter DZHK-TORCH (TranslatiOnal Registry for CardiomyopatHies) study and the Institute for Cardiomyopathies Heidelberg registry. Expression of downstream molecules, CAV1 and CD36, was assessed in human cardiac tissues by immunohistochemistry. EPHB4 cardiac expression was assessed using recently published single-cell/nucleus RNA sequencing data (Nicin et al 2022) incorporating siRNA-seq data from two other studies (healthy cardiac tissue, Litvinukova et al 2020) and (hypertrophic/aortic stenosis, Nicin et al. 2020).

      We thank the reviewer for the recommendations that have improved our manuscript.

      Major Comments:

      1. Details of identified truncating RBM20 and TTN variants must be provided. These should be integrated into Table 1 alongside each co-occurring EPHB4 variant. List whether the TTN truncating variant is located in the A-band and whether these variants would be adjudicated as pathogenic/likely pathogenic, variant of uncertain significance by ACMG and/or similarly refined DCM criteria (Morales et al. 2020, Circ-Genom Precis Med).

      Details of the truncating RNM20 and TTN have been provided in the new supplementary table 1. As indicated in the table both mutations are pathogenic, and thus, most probable the cause for the disease in these patients. In case of TTN this is a truncating variant and is located in the M-band in exon 358, which is annotated with a PSI in DCM of 100% in cardiodb.org. The fact that these mutations are most probably the cause for DCM in these patients has been included in the discussion section and reads as follows:

      Although it is most probable that in the case of the patients carrying TNN and RNM20 variants this would be the cause of the disease, this study further supports, the importance of EPHB4 regulating CD36 caveolar trafficking to the membrane, whether this happens in endothelial cells or cardiomyocytes, maintaining cardiac homeostasis in humans and its implication on DCM

      1. Discuss co-occurrence of multiple EPHB4 variants in two patients (DCM1, DCM3) and identification of 2 EPHB4 variants in more than one proband.

      As shown in Figure 1A, the detected variants are found in multiple domains of the protein, hence no clear hotspot is detected. We did not yet investigate on the exact mechanisms of action, however, when we compare the two patients with multiple EPHB4 variants, the average LVEF (echo) is 17.5 compared to 38,67 for the remaining 4 patients with only one EPHB4 variant and 35,17 for the six non-EPHB4 variant-carriers. Although the sample number only allows for a semi-quantitively analysis, it still hints at a possible EPHB4-variant effect, which certainly needs verification in a larger cohort.

      Since we do not postulate the detected variants as independently disease-causing, and we also did not explicitly filter for very rare variants, it is not surprising that we find two variants in multiple patients. As stated above, we did not investigate this further, but evidence is growing that compound heterozygosity is playing a role in heritable diseases. It will be interesting to analyze e.g. phasing (Hofmeister et al., Nature Genetics, 2023) or additive (biallelic) effects, which have come to attention also in cardiomyopathies recently (Lipov et al., Nature Cardiovascular Research, 2023).

      This fact has now been included in the manuscript, both in the results and in the discussion. It reads as follows:

      Interestingly, two of the analysed patients present more than one variant of EPHB4 and we could identify the same variant in more than one patient (Table 1)

      (…)

      Nevertheless, two of the patients carrying one benign or likely benign also carry another variant classified as likely pathogenic or of uncertain significance (Table 1) and interestingly, the average LVEF of the two patients with multiple EPHB4 variants is 17.5 compared to 38,67 for the remaining 4 patients with only one EPHB4 variant and 35,17 for the six non-EPHB4 variant-carriers. Although the sample number only allows for a semi-quantitively analysis, it still hints at a possible EPHB4-variant effect, which certainly needs verification in a larger cohort.

      1. Three of the six variants (p.Lys635Asn, Val113Ile, Glu890Asp) are classified as Clinvar Benign/Likely Benign. Additionally, p.Glu890Asp has been identified in 50 homozygotes in gnomAD non-Finnish European population. These data cast doubt on the pathogenicity of these variants. These classifications, as well as VUS classification of p.Pro79Leu, should be listed in Table 1. The authors should reconcile the benign/likely benign Clinvar classifications with their presented evidence for pathogenicity in the discussion.

      We have now included the ACMG classification in Table 1. Similar to the Clinvar classification, some of the variants are classified benign or likely benign. Still, the fact that the patients that carry them also carry another variant and that the histological findings are similar among the patients carrying an EPHB4 variant and different to those that don’t and the enriched presence of EPHB4 variants in the DCM population support our hypothesis that the Eph-ephrin signalling pathway plays a role in the development of DCM.

      Nevertheless, we agree with the reviewer that the fact that some of these variants have been classified as benign, and the presence of mutations in other genes already related to DCM like TNN or RMM20 may suggest that the EPHB4 mutations may not be the only cause for the disease but rather have an additive effect. As a consequence, we have toned down our conclusions and the discussion reads now as follows:

      Finally, although not as the main disease cause, this study not only supports the role of EPHB4 in the heart, but it also corroborates the importance of CD36 and CAV1 for the cardiac health, and has the potential to improve diagnosis and risk stratification tools for DCM. In addition, as other genes crucial for fatty acid transport may be involved in cardiac disease, this study may help identify new diagnostic or therapeutic targets.

      1. CD36 and CAV1 expression are not quantified. Qualitatively, it is difficult to confirm CD36 reduction in DCM and disruption in EPHB4 variant samples as imaging parameters are not specified and do not appear to be standardized across treatments. Clearly state (either in the figure legend or in the methods) whether identical imaging parameters were used across panels 1C-1E. Note any differences in these parameters.

      We have now quantified the two IHC. It is very clear that the total CD36 is significantly reduced in both groups when compared to the healthy donor (Figure for the reviewer 1A). In case of CAV1 this is not so evident, although the signal seems reduced this is not significant (Figure for the reviewer 1B). These new data have been included in the figure of the manuscript.

      Figure for the reviewer 1. Quantification of (A) CD36 and (B) CAV1 in the immunohistochemistry analysis of patients biopsies. Data shown as mean ± SEM. (A) P value was calculated using one sample one sample Wilcoxon test for DCM and one sample t test for DCM EPHB4. Both cohorts where compared to the mean of HD. P value < 0.05 was considered significant. (B) P value was calculated with one sample t test for both cohorts. P value < 0.05 was considered significant.

      All the images have been taken in the same conditions. The observed difference in the background is due to the disease conditions of the DCM samples. Furthermore, the apparent reduced number of capillaries observed in the DCM patients are caused by the hypertrophic state of the cardiomyocytes in the diseased state. These are bigger and thus, less cells and capillaries appear per picture. The parameters have been included in the methods and read as follow:

      Immunohistochemistry was imaged in a Leica Stellaris confocal microscope. All images were obtained with 63x magnification and the same laser and gain intensities. Images were acquired using the software LAS X (Leica, version 4.4) and quantified using the Volocity Software (Quorum Technologies, version 6.5.1)

      1. Why was EPHB4 membrane localization not assessed or reported?

      We agree with the reviewer that this would be a very interesting point. Unfortunately, we had very limited amount of material and we did not have a proper working antibody.

      1. A key finding of the manuscript is that all six variants produce similar histological impacts on CAV1 and CD36 expression, denoting downstream impacts of EPHB4 genetic disruption. There is no granular data presented to support this claim. Additional discussion is also required to address how the authors anticipate variants in functionally distinct domains on either side of the plasma membrane to similarly impact downstream expression of CAV1/CD36. Mapping to available crystal structures in the Protein Data Bank (PDB) may be insightful to determine which variants may be most likely to have an impact on heterotetramer formation or to exert dominant negative effects on receptor function.

      As an appendix to this revision we have included a figure with representation images of all biopsies analysed to support our claim.

      The whole protein structure is not solved and only some individual domains are present in the Protein Data Bank making difficult to analyse the effect on the tetramer without crystallising the whole protein.

      1. Study limitations are not discussed and are significant. 5 of the 6 samples were from male patients, there are limitations to analyses of non-diverse patient ancestry, there is uncertainty regarding pathogenic contributions of variants in established DCM genes in 2/6 patients, data is limited to expression-only analyses highlighting need for additional functional modeling in cell or animal based systems.

      We have now included a limitation sections that includes all the points raised by the reviewer. It reads as follows:

      Although this study offers valuable insights to the potential implication of the Eph-ephrin signalling pathway in the development of DCM it has some limitations that need to be discussed. Despite finding increased presence of EPHB4 variants in the DCM population when compared to the healthy population, analysis of the identified variants in using different classifications (CADD and ACMG) not always predicted pathogenicity for these variants. For this reason, further experiments should be performed to determine the effect of every variant.

      It is also important to note that given the lower number of patients analysed these are not age and gender matched. The EPHB4 carrying DCM patients were younger than the DCM patients carrying a wild type EPHB4 sequence and mainly male. Finally, no biomaterial nor genetic testing from family related patients is available.

      1. Language used in conclusions overstates study findings ["our results confirm a crucial role of the Eph-ephrin signaling pathway in DCM" (page 3), "this study not only confirms the crucial role of EPHB4 in the heart..." (page 8)]. Change to "suggest" or "support".

      We have revised our discussion according to the limitations discussed in the previous remark and these words have been corrected.

      Major Methods Comments:

      1. DCM diagnostic criteria (clinical and imaging) for inclusion in the DZHK-TORCH study and the Institute for Cardiomyopathies Heidelberg registry should be stated or referenced. Likewise, describe and/or reference DCM exclusion criteria. State any relevant differences in DCM enrolment criteria for the two registries.

      We have now included our inclusion criteria in the methods and include two references to support this. The paragraph reads as follows:

      The criteria to be included in the study was reduced left ventricular ejection fraction (LVEF) <50% validated either with two independent image techniques or at two different time points with the same imaging technique. Furthermore, patients should include left ventricular dilation (LVEDD) >117% corrected with age and body surface according to the Henry-Formel formula (LVEDD= 45,3 * BSA1/3 – 0,03*Age –7,2). In both cases the heart were analysed either by echocardiography or magnetic resonance tomography (MRT)

      1. Describe how the final cohort of 573 DCM patients was reached. (All patients with DCM in the DZHK-TORCH study/Heidelberg registry? All patients with available exome data meeting QC standards and having available cardiac tissue?).

      From the 573 DCM patients, 100 have been recruited as part of the DZHK-TORCH registry and have been genome sequenced. Further 62 genomes and 411 exomes have been sequenced from patients of the cohort from the Institute for Cardiomyopathies (ICH) at the Heidelberg University Hospital.

      From this cohort, we selected 6 patients with and 6 without an EPHB4 variant and received heart tissue slides from the pathology department.

      1. State whether any family/segregation data is available for these patients.

      DCM4 has a mother and aunt (mother’s sister) who are also affected by CMP. In case of DCM6, the mother was also diagnosed with CMP. Unfortunately, no further biomaterial nor genetic testing of those individuals is available. This has been included in the new limitation sections as described above.

      1. Description of genetic testing methods are inadequate. Describe how genetic analyses were completed for each study/registry and how results were filtered/quality controlled. If sequencing methods were different across registries, state which patients were tested by which methods. If any testing was gene-targeted rather than whole exome/genome, list the specific DCM genes tested.

      All data has been sequenced using Illumina paired-end technology with either 2x100bp or 2x150bp. Exome enrichment was achieved using SureSelect Human All Exon V6 Target Enrichment (Agilent Genomics) was used. Bioinformatics analysis pipeline was based on “Best Practices Guideline” from the Genome Analysis Toolkit (GATK) (https://gatk.broadinstitute.org/hc/en-us). Besides the analysis for EPHB4, we assessed further genes associated with cardiomyopathies (ACTC1, ACTN2, ALPK3, BAG3, CRYAB, CSRP3, DES, DMD, DSC2, DSG2, DSP, FLNC, GLA, HCN4, HRAS, JPH2, JUP, KRAS, LAMP2, LDB3, LMNA, MIB1, MYBPC3, MYH7, MYL2, MYL3, MYPN, NEXN, PKP2, PLN, PRDM16, PRKAG2, PTPN11, RAF1, RBM20, RYR2, SCN5A, SHOC2, TAZ, TMEM43, TNNC1, TNNI3, TNNT2, TPM1,TTN, TTR, VCL).

      This is information has been included in the methods section.

      1. Provide additional detail for human cardiac biopsies. Was the same chamber/tissue biopsied in all samples? Is an endomyocardial biopsy available for all 573 patients included in this study? If not, were additional EPHB4 variants identified in patients without biopsy samples?

      All biopsies investigated are from left-ventricular tissue, accessed during cardiac catheterization.

      We did find additional, mainly non-coding variants in the cohort. However, as the focus on the study was on the histological analysis of the CD36 and CAV1 expression, we did restrict our analysis to our selected samples as described in the response to comment 2.

      1. Describe the source of the healthy control biopsy, alongside brief clinical detail establishing suitability as a control. Did DCM controls carry variants in known DCM genes (including truncating variants in RBM20 or TTN)? How were DCM controls selected?

      The healthy control biopsy was kindly donated by Prof. Dettmeyer from the University Gießen. This is a postmortem sample with unrelated cause of death. Cardiac biopsy was examined to discard any pathological alterations. This sample originates from a 27 years old female, and thus ideal as a healthy sample. This information has been included in the methods.

      1. List statistical analyses and associated experiments. (Page 5).

      Statistical tests have been included in the figure legend of each experiment. This reads as follows:

      (B) EPHB4 variant allelle frequency analysis. Each variant is compared in a paired wise manner between the two population. P value was calculated with a paired one-tailed Student’s t test comparing the frequencies of the different variants in the two populations.

      And

      (F) Quantification of CD36 and CAV1 expression in the immunohistochemistry analysis of patients biopsies. Data shown as mean ± SEM. In the case of CD36, P value was calculated using one sample one sample Wilcoxon test for DCM and one sample t test for DCM EPHB4. P value < 0.05 was considered significant. In the case of CAV1, P value was calculated with one sample t test for both cohorts. P value < 0.05 was considered significant. In both cases, the cohorts where compared to the mean of HD.

      1. List microscopes/equipment and software used to complete immunohistochemistry experiments. Describe imaging parameters to facilitate comparisons between treatments in Figure 1C-E.

      Immunohistochemistry was imaged in a Leica Stellaris confocal microscope. All images were obtained with 63x magnification and the same laser and gain intensities. Images were acquired using the software LAS X (Leica, version 4.4) and quantified using the Volocity Software (Quorum Technologies, version 6.5.1)

      This paragraph has now been included in the methods section.

      1. Please reword the following passage, which is almost verbatim to the same passage in Nicin et al. 2022.

      Page 4

      **"In brief, a combination of two human snRNA-seq datasets was used. Data from healthy cardiac tissue from the septum of 14 individuals in the Litvinukova et al. study and data from location-matched hypertrophic cardiac tissues from five patients with aortic stenosis."

      Nicin et al. 2022 (https://doi.org/10.1038/s44161-022-00019-7)**

      "Two human snRNA-seq datasets were used: data from healthy cardiac tissue from the septum of 14 individuals in the Litvinukova et al. study and data from location-matched hypertrophic cardiac tissues from five patients with aortic stenosis."

      We have reworded the paragraph in the methods sections. Now it reads as follows:

      Healthy cardiac tissue data was derived from the cardiac septum of 14 individuals 15. Subsequently, it was integrated with data from the septum of hypertrophc cardiac tissue from 5 patients with aortic stenosis 16.

      Minor Comments:

      1. Results: List source for Non-Finnish European Control cohort (gnomAD) (Page 5).

      The Non-Finnish European Control cohort (gnomAD) was obtained from https://gnomad.broadinstitute.org/. This information has been included in the methods section.

      1. Discussion: "all DCM patients" (page 6) requires clarification.

      We have made clear that this refers to the patients analysed in this study. The new sentence reads as follows:

      Furthermore, our results stress the importance of the endothelial CD36 in the onset of cardiac disease as all DCM patients analysed by immunohistochemistry show a downregulation of CD36 in the endothelium and warrant a more detailed assessment of genes involved in vascular function20

      1. Discussion: Define acronyms. CSF, IL4, LPS (Page 7)

      We have defined the acronyms in the discussion. The new sentence reads as follows:

      CD36 expression is upregulated by the nuclear hormone transcription factor Peroxisome Proliferator-Activated Receptor-Gamma (PPAR-ɣ), cerebrospinal fluid (CSF) cytokines and Interleukin-4 (IL4). In the other hand, lipopolysaccharides (LPS) and dexamethasone downregulate its expression In microvascular endothelial cells, CD36 is downregulated by lysophosphatidic acid.

      1. Table 1. Table is confusingly arranged. It would make more sense to organize the table by cDNA/AAchange to better correspond to Figure 1A. List the impacted protein domain for each variant in a separate column. It is also unclear how DCM allele frequencies were calculated as the reported number of patients (DCM1-6) carrying each variant do not universally correspond to the listed allele frequencies (see AFs of 0.0052 and 0.0208). Clarification should be added to the legend so it is clear to the reader how these frequencies were determined

      In case of the EPHB4 variants table, we agree with the reviewer and to make the table more understandable we have removed the first three columns, which are the same for all variants. This information has been included in the table legend. Nevertheless, this information has been kept in the new Supplementary table 1 that contains the variants on the other DCM causing genes.

      Regarding the calculation of the allele frequency we made by dividing the number of alleles found in the population by the total number of alleles in the population. This information has been included in the methods.

      We want to note that we performed a mistake in the original table. We had calculated the frequencies by dividing the number of alleles by the number of individuals in the population. We have now corrected both Table 1 and Figure 1B.

      1. Figure 1B. Add variant labels. Indicate relevant p-values for each variant. It is unclear to which comparison the p = 0.024 belongs. State in legend that 2 variants were omitted (presumably due to absence from gnomAD)

      No variants were omitted in the representation of Figure 1B. Some of them have the same allele frequency in the DCM population and thus, the individual data points appear overlapping. The variants that were not detected in the genomAD population were considered as 0 for the representation and for the analysis.

      For the comparison with P=0.024 (now corrected to 0.0011) between the two groups we have performed a one tail paired t test comparing the frequencies in both populations. The information regarding the test has been included in the figure legend and included in the methods section as indicated above.

      1. Figure 1E. Add label to indicate which EPHB4 variant is depicted.

      The DCM sample from which the images originates is now indicated in Figure 1E.

      <br /> Referees cross-commenting****

      As is, this manuscript is not ready for publication. Our comments are in complete alignment. Like the other reviewer, I also emphasize the need for other DCM genes tested to be listed. I also reiterate that any similarly worded passages to other published material must be corrected

      Reviewer #1 (Significance): This study presents genetic and expression data on a novel DCM gene candidate (EPHB4) from a European cohort of 573 DCM patients. This work is of interest as much of genetic DCM remains unexplained and identification of novel genes and pathways will be critical to advance understanding of the disease and to develop novel treatments. Reported data will be of greatest interest to cardiovascular practitioners and translational/basic researchers working with genetic heart disease/DCM. The fact that cardiac tissue was available for histological analyses for all six patients is an asset. There are considerable weaknesses to the paper, as written. There is a lack of detail in the included genetic methods and results. While the premise of the study is intriguing, additional detail is required for identified TTN and RBM20 truncating variants and additional discussion is needed to resolve confusion regarding reported allele frequencies and benign/likely benign Clinvar classifications. Because study design is restricted to genetic and expression analyses, reported data do not address possible pathogenic mechanisms. Overall, there is insufficient data presented to confirm a role for EPHB4 in causing DCM. Manuscript-specific (as-opposed to study specific) weaknesses include insufficient methods detail, a lack of clarity in the presented genetic and expression data (particularly Figure 1), insufficiently described study limitations, and overstated study conclusions. These scientific and manuscript issues will need to be addressed for the manuscript to be suitable for publication.

      Reviewer fields of expertise: cardiovascular genetics, DCM.

      Insufficient expertise to evaluate statistical methods.

      Reviewer #2 (Evidence, reproducibility and clarity):<br /> I reviewed a paper by Luxan et al. describing EPHB4 variants as a novel disease gene for dilated cardiomyopathy (DCM).

      The short report is interesting, however, not enough evidence is given to convince me EPHB4 is indeed a novel disease gene for DCM. More work is needed before this can be published.

      Major points:

      1. Genetics: two individuals have EPHB4 variants together with DCM causing TTN tv or RBM20 variants. Which other DCM genes were excluded for the remaining four cases? GnomAD MAF of 0.008748404 suspiciously high.

      So overall the small case number makes it hard to judge whether these are truly pathogenic variants.<br /> Could the authors attempt co-segregation of DCM with EPHB4 variant in families?

      Unfortunately we do not have family information from these patients. We have included this in the new limitation sections in the discussion that reads as follows:

      Although this study offers valuable insights to the potential implication of the Eph-ephrin signalling pathway in the development of DCM it has some limitations that need to be discussed. Despite finding increased presence of EPHB4 variants in the DCM population when compared to the healthy population, analysis of the identified variants in using different classifications (CADD and ACMG) not always predicted pathogenicity for these variants. For this reason, further experiments should be performed to determine the effect of every variant.

      It is also important to note that given the lower number of patients analysed these are not age and gender matched. The EPHB4 carrying DCM patients were younger than the DCM patients carrying a wild type EPHB4 sequence and mainly male. Finally, no biomaterial nor genetic testing from family related patients is available.

      1. Only CADD tools was used for pathogenicity, several tools should be used. Is the structure solved? Structural predictions on the consequences of the variants should be done.

      We have now included the ACMG classification in Table 1. As discussed above in the comments of Reviewer 1, some of the variants are classified as benign or likely benign. For this reason we have now toned down our conclusion suggesting that the EPHB4 may not be sufficient to trigger DCM but act as modifiers. This is supported by the fact that the histological analysis revealed that the patients carrying EPHB4 variants are similar among themselves and different to the other patients. Furthermore, our hypothesis is also supported by the fact that those patients carrying benign or potentially benign variants also carry another variant and the fact that they even have lower LVEF. The new classification has been included in the results and discussion sections and it reads as follows:

      Nevertheless, the classification of the variants according to the American College of Medical Genetics (ACMG) 25 suggests that two of the variants are benign, two likely benign, one likely pathogenic and one variant of uncertain significance (Table1). Nevertheless, two of the patients carrying one benign or likely benign also carry another variant classified as likely pathogenic or of uncertain significance (Table 1) and interestingly, the average LVEF of the two patients with multiple EPHB4 variants is 17.5 compared to 38,67 for the remaining 4 patients with only one EPHB4 variant and 35,17 for the six non-EPHB4 variant-carriers. Although the sample number only allows for a semi-quantitively analysis, it still hints at a possible EPHB4-variant effect, which certainly needs verification in a larger cohort.

      And

      Our analysis identified several variants in EPHB4 enriched in a cohort of DCM patients. According to the CADD score prediction, all these variants have a deleterious potential. Nevertheless, the ACMG classified some of the variants as benign or potentially benign. Also the fact, that one variant has identified in two non-related patients suggests that this variant may be benign for the protein. Nevertheless, two of the patients carrying a benign or potentially benign variant also carried another potentially pathogenic or of uncertain significance. During Eph-ephrin signalling, the binding of the ligand induces Eph receptor heterotetramers to initiate the signalling via Eph–Eph cis interactions30. Thus, variant EPHB4 molecules could have a dominant negative effect on these heterotetramers, and while maybe not completely abrogating its function, reducing the functionality of the heterotetramers. This observation could explain why the presence of one variant copy in the DCM patients of our cohort would be sufficient to reduce the activity of the Eph-ephrin signalling pathway. Although this shows that some of the variants may indeed not be the sole cause for DCM it shows that the Eph-ephrin signalling pathway, and in particular EPHB4 may be important for the development of DCM.

      Only parts of the protein have been resolved and present in the Protein Data Base.

      1. The microscopy Figure 1C-E is not convicing. Only one sample shown while 6 were available/investigated. I would not be comfortable to identify cardiomyocytes/endothelial cells from these sections

      As an appendix to this document, we included figures with images obtained from all the analysed patients. These were not included on the original figure for space reasons.

      These sections are perfect to identify cardiomyocytes and endothelial cells in cardiac tissue. First, endothelial cells, that form the microvasculature are labelled with ULEX, a well known marker of endothelial cells. Secondly, cardiomyocytes are really big cells easy to score for their size and location between the capillaries in the heart. Other cells present in the heart, like fibroblasts, macrophages, or pericytes would also be located in the space left in between cardiomyocytes but would need to be labelled for visualization. We believe that our interpretation of the immunohistochemistry pictures is correct.

      1. Functional work is needed to understand the interplay between EPHB4, CAV1 and CD36. Such as transfecting mutant EPHB4 into cells and probing for altered localisation/attachment of binding partners, most likely in endothelial - cardiomyocyte co-culture systems.

      Our study is based in our previous murine study in which we showed that the deletion of EphB4 or its ligand ephrinB2 would induce a phenotype similar to DCM in mice. At the molecular level, defects in the Ephb4 are linked to compromised caveolar function and reduced CAV1 phosphorylation, which involves the kinase Src, a known mediator of Eph receptor signalling. In the healthy heart, caveolar transport is required for the membrane translocation and correct function of fatty acid translocase FAT/CD36, which mediates the uptake of fatty acids. The objective of this follow up study was to study whether we could identify EPHB4 mutations in DCM patients. As seen in the results we have observed that there is an enrichment of EPHB4 variants in the DCM population. We think that the previous study supports our conclusions and hope that the reviewer agrees with us. Nevertheless, we agree with the reviewer that functional assays could be performed with every variant. We have included this in the new limitation sections of the manuscript described above.

      Minor points:

      1. Figure 1B does not make sense

      Figure 1B confirms the enrichment of EPHB4 mutations in the DCM population. We have corrected the labelling to make this clearer. We have now labelled the figure “EPHB4 variant allele frequency in control and DCM population”.

      1. Statistics: Which tests were performed, if normality tests were applied, which one was used?

      The tests used for every comparison are included in the figure legend. In case of EPHB4 variant allele frequency, we performed a paired one-tailed Student’s t test comparing the frequencies of the different variants in the two populations. In case of the CD36 and CAV1 quantifications, we performed a two-tailed one sample t test. In this case, we compare the expression of CD36 and CAV1 to an hypothetical healthy population with mean equal 1 as que have used this value for normalization.

      1. Please do not use contractions, e.g. 'can't' in discussion section

      Contractions have been removed from the manuscript.

      <br /> Referees cross-commenting****

      Overall I agree with the other reviewer on the points raised.

      Reviewer #2 (Significance): Description of EPHB4 as a novel DCM gene is of interest, but the current data are not convincing enough to make this statement.

      Mechanistic work on the interplay of endothelial cells and cardiomyocytes and consequences of EPHB4 variants would make it a very compelling story.

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

      The authors of this manuscript studied the prevalence of a population of Ephrin type-B receptor 4 (EPHB4) in a cohort of 573 DCM patients and found six new EPHB4 variants, possibly pathogenic based on the Combined Annotation Dependent Depletion (CADD) score and population frequency. Moreover, the authors perform immunofluorescence (IF) and histologic analysis on 6 EPHB4 variant carrying DCM patients, 6 DCM patients with wild type EPHB4 and one healthy control biopsy and found dysregulation of Caveolin 1 (CAV1) and CD36 (which are implicated in fatty acid transport in endothelial cells and cardiomyocytes) in both groups of DCM patients.

      Major comments:

      • Additional experiments are necessary to prove the hypothesis: for example, co-IF staining with endothelial markers should be provided. IF should be supported by western blots and qPCR.

      The objective of this study was to explore whether we could identify EPHB4 mutants in a DCM cohort. Interestingly we have shown that EPHB4 mutations are enriched in the DCM population when compared to the general population. Nevertheless, we agree with the reviewer that a more in depth mechanistic study would improve the significance of the study. We have included a limitations section that reads as follows:

      Although this study offers valuable insights to the potential implication of the Eph-ephrin signalling pathway in the development of DCM it has some limitations that need to be discussed. Despite finding increased presence of EPHB4 variants in the DCM population when compared to the healthy population, analysis of the identified variants in using different classifications (CADD and ACMG) not always predicted pathogenicity for these variants. For this reason, further experiments should be performed to determine the effect of every variant.

      It is also important to note that given the lower number of patients analysed these are not age and gender matched. The EPHB4 carrying DCM patients were younger than the DCM patients carrying a wild type EPHB4 sequence and mainly male. Finally, no biomaterial nor genetic testing from family related patients is available.

      • The DCM samples with wild type EPHB4, have no CD36: the mechanism by which a mutation in another gene could affect the Eph-ephrin signaling pathway should be at least discussed.

      These patients do not have any mutation on EPHB4. Based in the literature and the previous murine study show that the Eph-ephrin signaling pathway is upstream of CD36. For these reasons we believe that our observation that shows that CD36 expression is reduced in all DCM patients confirms the important role of CD36 in cardiac homeostasis and the development of DCM. We further, as indicated in the discussion, other genes crucial for fatty acid transport may be involved in cardiac disease and thus, this study may help identify new diagnostic or therapeutic targets.

      • The authors should discuss and possibly prove the correlation between mutant EPHB4 and CD36 and CAV1 expression and localization in endothelial cells vs cardiomyocytes and explain the mechanistic implications of co-localization of CAV1 with CD36.

      In a previous study we showed that the deletion of EphB4 or its ligand ephrinB2 would induce a phenotype similar to DCM in mice. At the molecular level, defects in the Ephb4 are linked to compromised caveolar function and reduced CAV1 phosphorylation, which involves the kinase Src, a known mediator of Eph receptor signalling. In the healthy heart, caveolar transport is required for the membrane translocation and correct function of fatty acid translocase FAT/CD36, which mediates the uptake of fatty acids. We have expanded the introduction to explain the relationship between these molecules. It reads as follows:

      Mechanistically, EPHB4 deficient endothelial cells are characterized by compromised caveolar function and reduced Caveolin 1 (CAV1) phosphorylation. EPHB4 is required for the phosphorylation of CAV1 at Tyr-149. The phosphorylation of CAV1 promotes the release of caveolae from the plasma membrane10. Caveolae are required for the correct membrane translocation of the fatty acid translocase FAT/CD3611 and fatty acids are used by cardiomyocytes to obtain about 50% to 70% of their energy12. Absence of CD36 in cardiomyocytes reduces fatty acid uptake by the cardiac muscle cells13 and accelerates the progression from compensated hypertrophy to heart failure14. Finally, some cardiomyopathies a causally related to defects in the synthesis of the proteins required for fatty acid uptake in the heart15.

      • The available snRNAseq raw data are from normal subjects and aortic stenosis patients who are different from DCM patients. A better dataset would be the one from Reichart D, et al. Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies. Science 2022.

      The single nucleus RNA sequencing data was used in an exploratory manner to study whether EPHB4 would also be expressed in cardiomyocytes. We did not perform any study on gene expression comparing the two groups. We believe that the use of this dataset is justified. We hope that the reviewer agrees with us.

      • Furthermore, the link between the analysis done on the published snRNA seq datasets and the authors' own data is not clearly explained.

      As we stated above and in the methods, we have used the single nucleus RNA sequencing to explore whether cardiomyocytes express EPHB4. The sentence in the methods reads as follows:

      The single-nucleus-RNA-sequencing data set generated in the paper by Nicin et al.14 was used to explore EPHB4 expression in human cardiac cells

      • DCM1 and DCM 3 carry 2 EPHB4 variants: please describe if the phenotype was more severe.

      As discussed above in the response to reviewer 1, the two patients with multiple EPHB4 variants present an average LVEF (echo) of 17.5 compared to 38,67 for the remaining 4 patients with only one EPHB4 variant and 35,17 for the six non-EPHB4 variant-carriers. Although the sample number only allows for a semi-quantitively analysis, it still hints at a possible EPHB4-variant effect, which certainly needs verification in a larger cohort.

      This information has been included in the manuscript and reads as follows:

      and interestingly, the average LVEF of the two patients with multiple EPHB4 variants is 17.5 compared to 38,67 for the remaining 4 patients with only one EPHB4 variant and 35,17 for the six non-EPHB4 variant-carriers. Although the sample number only allows for a semi-quantitively analysis, it still hints at a possible EPHB4-variant effect, which certainly needs verification in a larger cohort.

      • Provide p values on suppl table 1. The 2 groups are not matched by age and maybe gender, and this could affect the histological findings.

      We have not performed any comparison between the two groups in the characteristics shown in supplementary table 1. Nevertheless, we agree with the reviewers that the fact that the patients are not matched in age and gender is a limitation to our study. We have acknowledged this in the new included limitations section that is mentioned above.

      • Please discuss why in the DCM population the EPHB4 variant is enriched as compared with controls. Causal role? Modifiers?

      The deletion of EphB4 and its ligand ephrin-B2 induce DCM in mouse. The objective of this study was to determine whether there would be mutations in EPHB4 associated to DCM. We agree with the reviewer that in depth mechanistic studies both in vivo and in vitro would be required to determine the exact role of the here identified mutations in the development of DCM. This has been acknowledged in the new limitations sections and indicated in the discussion of the results as follows:

      Finally, this study not only supports the crucial role of EPHB4 in the heart, but it also corroborates the importance of CD36 and CAV1 for the cardiac health, and has the potential to improve diagnosis and risk stratification tools for DCM. Nevertheless, whether mutations in EPHB4 are causative or modifiers of the disease should be further studied. In addition, as other genes crucial for fatty acid transport may be involved in cardiac disease, this study may help identify new diagnostic or therapeutic targets.

      • The data and the methods are presented in such a way that they could be reproduced however,

      We thank the reviewer for the positive comment on our methods section.

      • At least 2 more healthy controls should be included, and the DCM groups should be matched by gender and age.

      Healthy donor biopsies are very rare and difficult to obtain. Although we agree with the reviewer that this could strengthen our study, we cannot add more healthy biopsies. We hope the reviewer understands this.

      As stated above, we have included a limitation section in the manuscript discussing the issue with the gender and age.

      • The causal mutation of the DCM patients should be provided.

      Only 35% of DCM cases have been related to mutations in genes encoding cytoskeletal, sarcomere or nuclear envelope proteins. In our case, the DCM patients that we use do not carry a variant in any of the DCM known genes. We have now expanded the methods sections explaining the inclusion criteria for the DCM patients including this issue:

      The criteria to be included in the study was reduced left ventricular ejection fraction (LVEF) <50% validated either with two independent image techniques or at two different time points with the same imaging technique. Furthermore, patients should include left ventricular dilation (LVEDD) >117% corrected with age and body surface according to the Henry-Formel formula (LVEDD= 45,3 * BSA1/3 – 0,03*Age –7,2). In both cases the heart were analysed either by echocardiography or magnetic resonance tomography (MRT).

      Minor comments:

      • I would explain in more detail the interactions among EPHB4, CD36 and CAV1 in the introduction, as the readers may not be familiar with this pathway.

      We have completed the introduction expanding the paragraph where the relationship between EPHB4, CD36 and CAV1 is presented. It now reads as follows:

      Mechanistically, EPHB4 deficient endothelial cells are characterized by compromised caveolar function and reduced Caveolin 1 (CAV1) phosphorylation. EPHB4 is required for the phosphorylation of CAV1 at Tyr-149. The phosphorylation of CAV1 promotes the release of caveolae from the plasma membrane10. Caveolae are required for the correct membrane translocation of the fatty acid translocase FAT/CD3611 and fatty acids are used by cardiomyocytes to obtain about 50% to 70% of their energy12. Absence of CD36 in cardiomyocytes reduces fatty acid uptake by the cardiac muscle cells13 and accelerates the progression from compensated hypertrophy to heart failure14. Finally, some cardiomyopathies a causally related to defects in the synthesis of the proteins required for fatty acid uptake in the heart15.

      • Panel B in Fig 1 shows 4 variants and not 6.

      All variants are shown in the panel As stated in the response to reviewer 1, it the fact that some variants have the same value that induces to think that only four are shown. The variants that do not appear in the genomAD have been considered 0 for this analysis.

      • IF in Fig 1: make sure that control and DCM are at the same magnification.

      Both control and DCM are at the same magnification. The reason why it looks different is the DCM phenotype. Cardiomyocytes are hypertrophic in the in the disease samples giving the impression that they are shown in a higher magnification.

      • The authors analyze snRNA seq data from available datasets and not from their own patients: so, the paragraph title in the method section should be changed as it is misleading.

      We have changed the title of this section of the methods. We have labelled it now “Analysis of single-nucleus-RNA-sequencing”.

      Reviewer #3 (Significance): Despite the main focus of the manuscript is EPHB4, dysregulation of CD36 and its interaction with CAV1 seem to be a common mechanism in the pathogenesis of all DCM. The significance of these findings is higher than the role of EPHB4 alone and should be improved.<br /> Metabolic abnormalities, mainly affecting the fatty acid metabolism, have been described as causes or modifiers of DCM pathogenesis but in my knowledge the role of EPHDB4, CD36 and CAV 1 have not been studied in human tissues. The discovery of the mechanisms through which dysregulation of metabolism is induced by DCM genetic mutations would be an advance in the field. However, the paper in the present form is not going to have a significant impact. There is no clear connection between the sets of experiments and more mechanistic experiments should be provided to prove causality. This may take months or even years depending on the availability of human tissues and resources.

      The type of audience interested in this research are mainly translational scientists mainly in the field of genetic cardiomyopathies. Furthermore, the elucidation of the metabolic effects of genetic mutations on DCM evolution may be of interest in the field of heart failure in general.

      The focus of my research is genetic and molecular pathogenesis of cardiomyopathies.

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      Referee #3

      Evidence, reproducibility and clarity

      Summary:

      The authors of this manuscript studied the prevalence of a population of Ephrin type-B receptor 4 (EPHB4) in a cohort of 573 DCM patients and found six new EPHB4 variants, possibly pathogenic based on the Combined Annotation Dependent Depletion (CADD) score and population frequency. Moreover, the authors perform immunofluorescence (IF) and histologic analysis on 6 EPHB4 variant carrying DCM patients, 6 DCM patients with wild type EPHB4 and one healthy control biopsy and found dysregulation of Caveolin 1 (CAV1) and CD36 (which are implicated in fatty acid transport in endothelial cells and cardiomyocytes) in both groups of DCM patients.

      Major comments:

      • Additional experiments are necessary to prove the hypothesis: for example, co-IF staining with endothelial markers should be provided. IF should be supported by western blots and qPCR.
      • The DCM samples with wild type EPHB4, have no CD36: the mechanism by which a mutation in another gene could affect the Eph-ephrin signaling pathway should be at least discussed.
      • The authors should discuss and possibly prove the correlation between mutant EPHB4 and CD36 and CAV1 expression and localization in endothelial cells vs cardiomyocytes and explain the mechanistic implications of co-localization of CAV1 with CD36.
      • The available snRNAseq raw data are from normal subjects and aortic stenosis patients who are different from DCM patients. A better dataset would be the one from Reichart D, et al. Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies. Science 2022.
      • Furthermore, the link between the analysis done on the published snRNA seq datasets and the authors' own data is not clearly explained.
      • DCM1 and DCM 3 carry 2 EPHB4 variants: please describe if the phenotype was more severe.
      • Provide p values on suppl table 1. The 2 groups are not matched by age and maybe gender, and this could affect the histological findings.
      • Please discuss why in the DCM population the EPHB4 variant is enriched as compared with controls. Causal role? Modifiers?
      • The data and the methods are presented in such a way that they could be reproduced however,
      • At least 2 more healthy controls should be included, and the DCM groups should be matched by gender and age.
      • The causal mutation of the DCM patients should be provided.

      Minor comments:

      • I would explain in more detail the interactions among EPHB4, CD36 and CAV1 in the introduction, as the readers may not be familiar with this pathway.
      • Panel B in Fig 1 shows 4 variants and not 6.
      • IF in Fig 1: make sure that control and DCM are at the same magnification.
      • The authors analyze snRNA seq data from available datasets and not from their own patients: so, the paragraph title in the method section should be changed as it is misleading.

      Significance

      Despite the main focus of the manuscript is EPHB4, dysregulation of CD36 and its interaction with CAV1 seem to be a common mechanism in the pathogenesis of all DCM. The significance of these findings is higher than the role of EPHB4 alone and should be improved.

      Metabolic abnormalities, mainly affecting the fatty acid metabolism, have been described as causes or modifiers of DCM pathogenesis but in my knowledge the role of EPHDB4, CD36 and CAV 1 have not been studied in human tissues. The discovery of the mechanisms through which dysregulation of metabolism is induced by DCM genetic mutations would be an advance in the field. However, the paper in the present form is not going to have a significant impact. There is no clear connection between the sets of experiments and more mechanistic experiments should be provided to prove causality. This may take months or even years depending on the availability of huma tissues and resources.

      The type of audience interested in this research are mainly translational scientists mainly in the field of genetic cardiomyopathies. Furthermore, the elucidation of the metabolic effects of genetic mutations on DCM evolution may be of interest in the field of heart failure in general.<br /> The focus of my research is genetic and molecular pathogenesis of cardiomyopathies.

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      Referee #2

      Evidence, reproducibility and clarity

      I reviewed a paper by Luxan et al. describing EPHB4 variants as a novel disease gene for dilated cardiomyopathy (DCM).

      The short report is interesting, however, not enough evidence is given to convince me EPHB4 is indeed a novel disease gene for DCM. More work is needed before this can be published.

      Major points:

      1. Genetics: two individuals have EPHB4 variants together with DCM causing TTN tv or RBM20 variants. Which other DCM genes were excluded for the remaining four cases? GnomAD MAF of 0.008748404 suspiciously high.<br /> So overall the small case number makes it hard to judge whether these are truly pathogenic variants.<br /> Could the authors attempt co-segregation of DCM with EPHB4 variant in families?
      2. Only CADD tools was used for pathogenicity, several tools should be used. Is the structure solved? Structural predictions on the consequences of the variants should be done.
      3. The microscopy Figure 1C-E is not convicing. Only one sample shown while 6 were available/investigated. I would not be comfortable to identify cardiomyocytes/endothelial cells from these sections
      4. Functional work is needed to understand the interplay between EPHB4, CAV1 and CD36. Such as transfecting mutant EPHB4 into cells and probing for altered localisation/attachment of binding partners, most likely in endothelial - cardiomyocyte co-culture systems.

      Minor points:

      1. Figure 1B does not make sense
      2. Statistics: Which tests were performed, if normality tests were applied, which one was used?
      3. Please do not use contractions, e.g. 'can't' in discussion section

      Referees cross-commenting<br /> Overall I agree with the other reviewer on the points raised.

      Significance

      Description of EPHB4 as a novel DCM gene is of interest, but the current data are not convincing enough to make this statement.

      Mechanistic work on the interplay of endothelial cells and cardiomyocytes and consequences of EPHB4 variants would make it a very compelling story.

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      Referee #1

      Evidence, reproducibility and clarity

      Summary:

      This research article describes genetic identification and expression analyses of six Ephrin type-B receptor 4 (EPHB4) variants identified in patients with dilated cardiomyopathy (DCM). Variants were identified Variants were identified in a cohort of 573 patients enrolled through the multicenter DZHK-TORCH (TranslatiOnal Registry for CardiomyopatHies) study and the Institute for Cardiomyopathies Heidelberg registry. Expression of downstream molecules, CAV1 and CD36, was assessed in human cardiac tissues by immunohistochemistry. EPHB4 cardiac expression was assessed using recently published single-cell/nucleus RNA sequencing data (Nicin et al 2022) incorporating siRNA-seq data from two other studies (healthy cardiac tissue, Litvinukova et al 2020) and (hypertrophic/aortic stenosis, Nicin et al. 2020).

      Major Comments:

      1. Details of identified truncating RBM20 and TTN variants must be provided. These should be integrated into Table 1 alongside each co-occurring EPHB4 variant. List whether the TTN truncating variant is located in the A-band and whether these variants would be adjudicated as pathogenic/likely pathogenic, variant of uncertain significance by ACMG and/or similarly refined DCM criteria (Morales et al. 2020, Circ-Genom Precis Med).
      2. Discuss co-occurrence of multiple EPHB4 variants in two patients (DCM1, DCM3) and identification of 2 EPHB4 variants in more than one proband.
      3. Three of the six variants (p.Lys635Asn, Val113Ile, Glu890Asp) are classified as Clinvar Benign/Likely Benign. Additionally, p.Glu890Asp has been identified in 50 homozygotes in gnomAD non-Finnish European population. These data cast doubt on the pathogenicity of these variants. These classifications, as well as VUS classification of p.Pro79Leu, should be listed in Table 1. The authors should reconcile the benign/likely benign Clinvar classifications with their presented evidence for pathogenicity in the discussion.
      4. CD36 and CAV1 expression are not quantified. Qualitatively, it is difficult to confirm CD36 reduction in DCM and disruption in EPHB4 variant samples as imaging parameters are not specified and do not appear to be standardized across treatments. Clearly state (either in the figure legend or in the methods) whether identical imaging parameters were used across panels 1C-1E. Note any differences in these parameters.
      5. Why was EPHB4 membrane localization not assessed or reported?
      6. A key finding of the manuscript is that all six variants produce similar histological impacts on CAV1 and CD36 expression, denoting downstream impacts of EPHB4 genetic disruption. There is no granular data presented to support this claim. Additional discussion is also required to address how the authors anticipate variants in functionally distinct domains on either side of the plasma membrane to similarly impact downstream expression of CAV1/CD36. Mapping to available crystal structures in the Protein Data Bank (PDB) may be insightful to determine which variants may be most likely to have an impact on heterotetramer formation or to exert dominant negative effects on receptor function.
      7. Study limitations are not discussed and are significant. 5 of the 6 samples were from male patients, there are limitations to analyses of non-diverse patient ancestry, there is uncertainty regarding pathogenic contributions of variants in established DCM genes in 2/6 patients, data is limited to expression-only analyses highlighting need for additional functional modeling in cell or animal based systems.
      8. Language used in conclusions overstates study findings ["our results confirm a crucial role of the Eph-ephrin signaling pathway in DCM" (page 3), "this study not only confirms the crucial role of EPHB4 in the heart..." (page 8)]. Change to "suggest" or "support".

      Major Methods Comments:

      1. DCM diagnostic criteria (clinical and imaging) for inclusion in the DZHK-TORCH study and the Institute for Cardiomyopathies Heidelberg registry should be stated or referenced. Likewise, describe and/or reference DCM exclusion criteria. State any relevant differences in DCM enrolment criteria for the two registries.
      2. Describe how the final cohort of 573 DCM patients was reached. (All patients with DCM in the DZHK-TORCH study/Heidelberg registry? All patients with available exome data meeting QC standards and having available cardiac tissue?).
      3. State whether any family/segregation data is available for these patients.
      4. Description of genetic testing methods are inadequate. Describe how genetic analyses were completed for each study/registry and how results were filtered/quality controlled. If sequencing methods were different across registries, state which patients were tested by which methods. If any testing was gene-targeted rather than whole exome/genome, list the specific DCM genes tested.
      5. Provide additional detail for human cardiac biopsies. Was the same chamber/tissue biopsied in all samples? Is an endomyocardial biopsy available for all 573 patients included in this study? If not, were additional EPHB4 variants identified in patients without biopsy samples?
      6. Describe the source of the healthy control biopsy, alongside brief clinical detail establishing suitability as a control. Did DCM controls carry variants in known DCM genes (including truncating variants in RBM20 or TTN)? How were DCM controls selected?
      7. List statistical analyses and associated experiments. (Page 5).
      8. List microscopes/equipment and software used to complete immunohistochemistry experiments. Describe imaging parameters to facilitate comparisons between treatments in Figure 1C-E.
      9. Please reword the following passage, which is almost verbatim to the same passage in Nicin et al. 2022.

      Page 4<br /> "In brief, a combination of two human snRNA-seq datasets was used. Data from healthy cardiac tissue from the septum of 14 individuals in the Litvinukova et al. study and data from location-matched hypertrophic cardiac tissues from five patients with aortic stenosis."

      Nicin et al. 2022 (https://doi.org/10.1038/s44161-022-00019-7)<br /> "Two human snRNA-seq datasets were used: data from healthy cardiac tissue from the septum of 14 individuals in the Litvinukova et al. study and data from location-matched hypertrophic cardiac tissues from five patients with aortic stenosis."

      Minor Comments:

      1. Results: List source for Non-Finnish European Control cohort (gnomAD) (Page 5).
      2. Discussion: "all DCM patients" (page 6) requires clarification.
      3. Discussion: Define acronyms. CSF, IL4, LPS (Page 7)
      4. Table 1. Table is confusingly arranged. It would make more sense to organize the table by cDNA/AAchange to better correspond to Figure 1A. List the impacted protein domain for each variant in a separate column. It is also unclear how DCM allele frequencies were calculated as the reported number of patients (DCM1-6) carrying each variant do not universally correspond to the listed allele frequencies (see AFs of 0.0052 and 0.0208). Clarification should be added to the legend so it is clear to the reader how these frequencies were determined
      5. Figure 1B. Add variant labels. Indicate relevant p-values for each variant. It is unclear to which comparison the p = 0.024 belongs. State in legend that 2 variants were omitted (presumably due to absence from gnomAD)
      6. Figure 1E. Add label to indicate which EPHB4 variant is depicted.

      Referees cross-commenting

      As is, this manuscript is not ready for publication. Our comments are in complete alignment. Like the other reviewer, I also emphasize the need for other DCM genes tested to be listed. I also reiterate that any similarly worded passages to other published material must be corrected

      Significance

      This study presents genetic and expression data on a novel DCM gene candidate (EPHB4) from a European cohort of 573 DCM patients. This work is of interest as much of genetic DCM remains unexplained and identification of novel genes and pathways will be critical to advance understanding of the disease and to develop novel treatments. Reported data will be of greatest interest to cardiovascular practitioners and translational/basic researchers working with genetic heart disease/DCM. The fact that cardiac tissue was available for histological analyses for all six patients is an asset. There are considerable weaknesses to the paper, as written. There is a lack of detail in the included genetic methods and results. While the premise of the study is intriguing, additional detail is required for identified TTN and RBM20 truncating variants and additional discussion is needed to resolve confusion regarding reported allele frequencies and benign/likely benign Clinvar classifications. Because study design is restricted to genetic and expression analyses, reported data do not address possible pathogenic mechanisms. Overall, there is insufficient data presented to confirm a role for EPHB4 in causing DCM. Manuscript-specific (as-opposed to study specific) weaknesses include insufficient methods detail, a lack of clarity in the presented genetic and expression data (particularly Figure 1), insufficiently described study limitations, and overstated study conclusions. These scientific and manuscript issues will need to be addressed for the manuscript to be suitable for publication.

      Reviewer fields of expertise: cardiovascular genetics, DCM.

      Insufficient expertise to evaluate statistical methods.

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      Reply to the reviewers

      Revision summary.

      Additional new data.

      • CYPA expression levels in Scrm Vs KO Vs R55A isogenic cell lines as new Fig 1C.
      • ATR signaling: western blot analysis of HU-induced p-CHK1 (S345) in Scrm, KO and R55A isogenic cell lines as new Suppl Fig 1B.
      • MRN expression: western blot analysis of expression of NBS1, MRE11, RAD50 and MCM2 is Scrm, KO and R55A isogenic cell lines as new Suppl Fig 7A.
      • NBS1 subcellular fractionation: western blot analysis of NBS1 from whole cell extract Vs cytoplasmic extract Vs nuclear extract comparing expression/distribution in Scrm, KO and R55A isogenic cell lines, as new Suppl Fig 7B.
      • CYPA immunofluorescence (IF) staining on untreated and HU treated U2OS, as new Suppl Fig 7C.
      • CYPA immunofluorescence (IF) staining on untreated and HU treated U2OS following pre-extraction, as new Suppl Fig 7D.
      • DepMap Project Score Cancer Gene Dependency cell survival (“fitness”) following PPIA/CYPA-KO in breast carcinoma cell lines mapped against BRCA2 status, as a new Suppl Table 5.
      • DepMap Project Score Cancer Gene Dependency cell fitness following PPIA/CYPA-KO in Neuroblastoma cell lines, as a new Suppl Spreadsheet 4.
      • DepMap Project Score Cancer Gene Dependency cell fitness following PPIA/CYPA-KO in Multiple Myeloma cell lines, as a new Suppl Spreadsheet 4.
      • DepMap Project Score Cancer Gene Dependency cell fitness following PPIA/CYPA-KO in Chronic Myelogenous Leukaemia cell lines, as a new Suppl Spreadsheet 4.

      Revised and/or additional text.

      The Abstract, Introduction, Materials & Methods, Results and Discussion have been amended as necessary, to facilitate the issues raised by the Reviewers.

      Reviewer #1: We thank this reviewer for their understanding and appreciation of our CYPA study as espoused by their comprehensive summary of the content, importance, and potential implications of our work; “The manuscript presents clear and comprehensive data, demonstrating the profound impact of CYPA on DNA repair.” Furthermore, we very much appreciate their robust and complementary words regarding the significance of our work and its wide appeal; “The significance of this study is twofold: it adds a new layer to our understanding of DNA repair mechanisms and, importantly, it could point the way to novel therapeutic strategies for cancer. It will spark interest from molecular biologists to clinicians and pharmaceutical researchers.”

      Query:

      It's surprising to find that the loss of CYPA abolished HU-induced NBS1 foci, as the MRE11 interactive domain of NBS1 should remain intact in CYPA deficient conditions and the N-terminus of NBS1 is dispensable for ATM activation (Kim et al., 2017; Stracker and Petrini, 2011). A more detailed mechanistic explanation of this phenotype would be appreciated. The authors should check the subcellular localization of NBS1 and the stability of MRN in wildtype and CYPA KO cells. Additionally, including the kinetics of NBS1 foci formation using multiple timepoints in wildtype and CYPA KO cells after damage will further support the observation.

      RESPONSE:

      Regarding NBS1 foci formation, we note that rather than abolish HU-induced NBS1 foci formation, CYPA loss (through KO) and/or inhibition (through p.R55A) in fact results in a “…spontaneously elevated yet unresponsive amount of NBS1 foci/cells when compared to scrambled” (see original Fig 9A legend and associated Results section text). We have reinforced this observation in the revised Results section entitled ‘CYPA influences NBS1 and MDC1 foci formation’ and in the Discussion section. We do describe a kinetic impairment of RAD51 foci formation in the CYPA-engineered lines up to 16hrs post HU-treatment (Fig 6D). Our mechanistic working model is that CYPA interacts directly with NBS1 via a Pro residue within the short linking peptide between the FHA and BRCT1, and that this likely influences the relative dynamic positioning of the FHA with BRCA1-BRCT2, at least following acute HU treatment; replication fork stalling, likely biased towards ATR-dependent signaling initially, rather than that of ATM. The relative positioning of these functional domains can impact MRN function, and we discuss this possible mechanism in the section entitled ‘CYPA and the MRN complex’, with reference to the detailed structure-function analyses and complementary DDR activation models described by<br /> - Williams, R.S., et al., Nbs1 flexibly tethers Ctp1 and Mre11-Rad50 to coordinate DNA double-strand break processing and repair. Cell, 2009. 139(1): p. 87-99.<br /> and<br /> - Lloyd, J., et al., A supramodular FHA/BRCT-repeat architecture mediates Nbs1 adaptor function in response to DNA damage. Cell, 2009. 139(1): p. 100-11.<br /> and<br /> - Rotheneder, M., et al., Cryo-EM structure of the Mre11-Rad50-Nbs1 complex reveals the molecular mechanism of scaffolding functions. Mol Cell, 2023. 83(2): p. 167-185.e9.

      The N-terminal FHA-BRCT region of NBS1 does indeed influence MRN recruitment and HRR execution, a point we highlight in the section entitled ‘CYPA influences NBS1 and MDC1 foci formation’, with reference to the seminal original observations of<br /> - Sakamoto, S., et al., Homologous recombination repair is regulated by domains at the N-<br /> and C-terminus of NBS1 and is dissociated with ATM functions. Oncogene, 2007. 26(41): p.6002-6009<br /> and<br /> - Tauchi, H., et al., The forkhead-associated domain of NBS1 is essential for nuclear foci formation after irradiation but not essential for hRAD50-hMRE11-NBS1 complex<br /> DNA repair activity. J Biol Chem, 2001. 276(1): p. 12-15.<br /> and<br /> - Zhao, S., W. Renthal, and E.Y. Lee, Functional analysis of FHA and BRCT domains of NBS1 in chromatin association and DNA damage responses. Nucleic Acids Res, 2002. 30(22): p. 4815-22.<br /> and<br /> - Cerosaletti, K.M. and P. Concannon, Nibrin forkhead-associated domain and breast cancer C-terminal domain are both required for nuclear focus formation and phosphorylation. J Biol Chem, 2003.<br /> 278(24): p. 21944-21951.

      HU-unresponsive NBS foci (indicative of MRN dysfunction) and MDC1 foci formation are consistent with the DNA-R (i.e., DR-GFP reporter systems: Fig 3A-C and impaired RAD51 foci formation: Fig 6D) and resection-related phenotypes (Fig 6A-B) we report here and are also consistent with the relative resistance to HU-induced killing we report for CYPA-KO and CYPA-R55A cells (Fig 11A and as reported by Manthey, K.C., et al., NBS1 mediates ATR-dependent RPA hyperphosphorylation following replication-fork stall and collapse. J Cell Sci, 2007. 120(Pt 23): p. 4221-9).

      At the reviewer’s request we include additional novel experimental data showing that MRN expression is stable and equivalent in control, CYPA-KO and CYPA-R55A cells (Suppl Fig 7A). We also provide evidence that NBS1 subcellular distribution (via extract fractionation) is not altered upon CYPA loss and/or inhibition (Suppl Fig 7B).

      Query:

      The authors showed that the interaction between CYPA and MRN didn't change after HU treatment. The authors should also include co-localization analysis of CYPA and NBS1 after HU.

      RESPONSE:

      At the reviewer’s suggestion we undertook a series of IF analyses concerning endogenous CYPA (i.e., +/- HU, +/- pre-extraction). We found that endogenous CYPA failed to form foci following HU thereby precluding CYPA-NBS1 foci co-localization analysis (Suppl Fig 7C-D).

      Query:

      The paper demonstrated that BRCA2 knockdown cells were sensitive to CsA. The authors should also examine CsA sensitivity in BRCA2 deficient cancer cells. In addition, the authors could elaborate more on their criteria for selecting cancers for CYPA inhibition, whether it is based on high genomic instability or an addiction to HRR for survival.

      RESPONSE:

      Despite repeated attempts we have been unable to successfully routinely culture the TNBC suspension line HCC1599 (BRCA2 c.4154_5572del1419 and p.K1517fs*23), consistent with its reported ~5 days population doubling time. Although not a tumour line per se, we also failed to effectively culture the FANC-D1 patient FB line HSC62 (BRCA2 c.8488-1 G>A (IVS19-1G>A)) to enable survival analysis. We provide new quantification analysis of the CsA survival on the H1299 conditional shBRCA2 line (Fig 11E). Additionally, we include a comprehensive new analysis of cell survival (“fitness”) of a range of breast carcinoma cell lines following PPIA/CYPA-KO, extracted from DepMap Project Score Cancer Gene Dependency portal (https://score.depmap.sanger.ac.uk/), and also specify the BRCA2 status of each line. Interestingly, we find that reduced BRCA2 copy number is more commonly associated with loss of fitness following PPIA/CYPA loss (Suppl Table 5). We also include similar cell line fitness datasets for each of the cancers for whom we demonstrate elevated sensitivity to CYPAi (i.e., Neuroblastoma, Multiple Myeloma and CML) (Suppl Spreadsheet 4). Fascinatingly, PPIA/CYPA loss clearly results in loss of fitness in most of these cancer cell lines. Collectively, these new independent comprehensive datasets support our argument that targeting CYPA in select cancer scenarios shows impact in the preclinical setting and may represent an effective new strategy.

      The unifying features of the cancers showing elevated sensitivity to CYPAi are indeed high genomic instability, denoted by elevated RS and hence a dependency upon replication fork protection machinery. This would be consistent with the observed lethality of our CYPA-panel to shBRCA2, siXRCC3 and siRAD51C. The cancers are additionally characterised by aberrantly elevated HRR (i.e. an addiction to/dependency on HRR). This would be consistent with the observed lethality of our CYPA-panel to siCtIP, siRAD52, siXRCC3, and siRAD51C. At the Reviewer’s request we have reinforced and better clarified this point in the section Potential rational applications of CYPA inhibition in select cancers and in the Discussion.

      Reviewer #2:

      We thank this reviewer for their positive and supportive comments concerning our work; “Authors have quite conclusively explored the interaction between NBS1 and cyclophilinA as well as the putative proline residue important for this interaction.” We appreciate the constructive feedback concerning the range of consequences/impacts of CYPA impairment and we concur with their contention that “This manuscript will have broad interest from groups working on genomic stability, immunology as well as cancer therapy.”; a general view also voiced by Reviewer #1.

      We do stress that whilst other prolyl isomerases have previously been linked to DNA repair (e.g., most notably the Parvulin family member PIN1), this is the first time that CYPA has been directly implicated in DNA repair, and the first time CYPA has been shown to directly interact with a known DNA-R protein (i.e. NBS1).

      We believe that the comprehensive CYPA-BioID we describe is worthy of report and should serve as a very useful starting point for additional studies concerning CYPA biology, which is undoubtedly complex. The interactome will also function as a useful tool in helping dissect the clinically significant wider biological consequences of CYPA inhibition. Our interactome findings demonstrate that CYPA may influence DNA-R via multiple, and not necessarily mutually exclusive, routes. We do not argue that CYPA’s role in DNA-R is exclusively via NBS1/MRN. This is clearly demonstrated by our validation of CYPA interactions via co-IP with endogenous CYPA with proteins including PCNA, 53BP1, CHAMP1 and ILF2-3 complex (Fig 5). These are completely novel observations that furthermore reinforce the validity and efficacy of our experimental approach in leveraging the CYPA-BioID to provide new biological insight into this druggable prolyl cis-trans isomerase.

      Query:

      Authors show delayed S-phase transit along with reduced replication speed indicating replication stall. However, authors have not discussed how cyclophilinA might regulate replication (other than hypothesizing regarding altered dynamism of FHA-BRCT). It is conceivable that it could be an indirect effect on cellular metabolism or if authors believe it could be due to direct disruption to core replication machinery or signaling. In this regard, it will be helpful to see if there is shortening of (premature entry) G1 phase and comment on the status of the associated G1/S checkpoint.

      RESPONSE:

      The reviewer makes a very interesting and astute observation concerning the DNA replication phenotypes we report following CYPA loss and/or inhibition. The bases of these phenotypes are likely multifactorial, and we have revised the associated Discussion text to reflect this. Specifically, we highlight the elevated and unresponsive NBS1 and MDC1 foci seen in the CYPA-KO lines (Fig 9. i.e., persistent protein-DNA complexes) and dependence upon fork protection factors (XRCC3, RAD51C, BRCA2: Fig 11). We also report that a range of DNA replication factors are found in the CYPA-BioID (Fig 5A). Untangling the functional significance of these putative interactions would involve further study. Are they direct/indirect interactors? If direct, are they prolyl isomerase substrates or chaperone clients or regulated by liquid-liquid phase separation (LLPS)? Similarly, the CYPA-BioID throws-up an extensive set of RNA binding factors (Suppl Table 2), many of whom may conceivably contribute to the replication–transcription fork conflicts/collisions under conditions of CYPA-dysfunction. As this is the first comprehensive report of the cellular impacts of CYPA loss and inhibition, we thought it worth reporting the DNA replication associated phenotypes specifically to demonstrate the pleiotropic impact of loss and inhibition of this particular prolyl isomerase, to underscore its significance/importance. Although we have indeed found cell cycle phase transition impairments in our CYPA-KO and CYPA-R55A cells (for both G1-S and G2-M), these constitute additional studies requiring more thorough molecular-mechanistic characterization. We chose to focus on DNA repair for this first manuscript, as the CYPA-NBS1 interaction was the physical relationship for which we have assembled the most detailed and interconnected datasets, to-date. We do intend to pursue the cell cycle work as it too is derived from our CYPA-BioID (Suppl Spreadsheet 1), and we have already validated some of those relevant interactions by CYPA co-IP, but this is very much a work-in-progress. With this manuscript we’re endeavoring to tread a fine line by showcasing a wide range of cellular phenotypes resultant from CYPA loss and inhibition, but then also showing a deeper level of characterisation with at least one relevant interactor known to function in a range of DNA-R pathways wherein we’ve found impairments and dependencies.

      Query:

      In connection to this, it will also be interesting to see if the ATR/Chk1 signaling axis is intact in CYPA KO cells with or without additional DNA damage compared to WT.

      RESPONSE:

      At the reviewer’s request we include new data showing that HU-induced ATR-dependent CHK1 phosphorylation is normal in CYPA-KO and CYPA-R55A cells, and that ATR does not appear to be spontaneously activated in the absence of replication stress in these cells (Suppl Fig 1B).

      Query:

      Authors show that the P112 residue of NBS1 is important for the binding of cyclophilinA. What is the status of interaction among components of the MRN complex in CYPAKO cells and P112G NBS1? Further, what are the authors' thoughts on rescue experiments and whether P112G containing NBS1 to perform resection function.

      RESPONSE:

      We include new data showing normal expression of MRN components and normal subcellular localisation of NBS1 in the CYPA-KO and CYPA-R55A cells (Suppl Fig 7A-B). Regarding the interaction status of P112G, we show that this fails to co-IP endogenous CYPA when transiently expressed in HEK293 cells, in marked contrast to WT-NBS1 (Fig 8A). Furthermore, we show that ablation of another FHA Pro residue (P64) does not impair co-IP with endogenous CYPA under similar conditions, suggesting P112G is unique in this regard. Our recombinant protein interaction work demonstrates that CYPA-Step directly interacts with a HIS-(FHA-BRCT1) peptide and that P112G abolishes this interaction (Fig 8B). Regarding rescue experiments, we’ve found that stable overexpression of NBS1 can be neomorphic, resulting in resistance to certain DNA damaging agents, thereby complicating cell-based rescue analyses. We stress that along with our engineered KO and R55A (isomerase-dead) lines we have employed the well-known CYPAi Cyclosporin A (CsA) to reproduce several of the DNA-R related phenotypes (e.g., Fig 1, Fig 3, Fig 6, Fig 10, Fig 11). To further examine impacts upon resection specifically, a logical approach would be to engineer P112G into a full-length recombinant (baculoviral produced) human MRN complex for in vitro kinetic assessment using various labelled DNA substrates. But we think that this specialist and not insignificant undertaking is outside the scope of our report of the extensive cellular consequences of CYPA loss and dysfunction and it’s potential (pre)clinical significance with regards CYPAi repurposing.

      Query:

      What are the protein levels of MRN, RAD51 etc. in CYPAKO cells? It will be important control to delineate the effects of CYPA on global transcription and translation vs specific and direct effect on end-resection. Can overexpression of NBS1 rescue the observed resection and focus phenotypes?

      RESPONSE:

      Basal levels of RAD51 foci/cell are comparable between Scrm and both CYPA-KO and R55A cells (Fig 6D). We also find comparable levels of MRN components between these lines (Suppl Fig 7A). Importantly, we observe the pRPA/resection defect following an acute (up to 3hrs) treatment with CsA; conditions unlikely to grossly impair translation to an extent that would result in reduced expression of the relevant DNA-R proteins. Furthermore, microarray based transcriptomic analyses of these isogenic lines did not show evidence of a global impact upon transcription following CYPA-KO or R55A, nor was there evidence of reduced expression of any genome stability/DNA-R genes. We did not include this negative data so as to maintain the focus on the functional link with DNA repair.

      Reviewer #3: This critically negative review is myopic, unbalanced, self-contradictory and frustratingly mis-represents some of our key findings. The dismissive tone of the text unnecessarily and unprofessionally crosses into the pejorative (“Either evidence is lacking or experiments were not performed in a convincing way”). The stark contrast between this review and the summations of Reviewer #1 and Reviewer #2 serve to highlight this hyper-negative approach.

      It is very frustrating that this reviewer describes our findings as “…an interesting story…”, that “…the identification of NBS1 as a novel substrate of CYPA is significant” , that the “..manuscript may provide new insight…”, and that “…the role of CYPA in DNA repair is fairly well described using its inhibitor or KO cells”, and yet then concludes by stating “… the current manuscript suffers lack of evidence to support the main conclusion”. This is self-contradictory and unbalanced. Again, the contrast with Reviewer #1 and Reviewer #2 in this regard is stark.

      Major critical theme no. 1.

      Expression of CYPA-R55A: “…vastly different…”

      RESPONSE.

      This reviewer dismisses the entirety of the R55A model cell line work based upon the apparent “…vastly different…” expression levels of the reconstituted lines. This is an overstatement of the situation and notably not an issue for either Reviewer #1 or Reviewer #2. Nonetheless, we have replaced the original CYPA blot in Fig 1C with a clearer and more representative depiction of expression levels between the engineered lines and control. Importantly, the pRPA/resection work, siRAD52 and siXRCC3 dependency work were all corroborated/reproduced using the CYPA PPI inhibitor Cyclopsorine A (CsA). The plurality of our complementary approaches showing the influence of CYPA upon DNA-R is minimised and/or ignored by this Reviewer. Although not shown in this study, we find that the R55A cells are selectively sensitive to DNA cross-linker melphalan, in contrast to the CYPA-KO cells. Although we don’t yet understand the basis of this observation, this clearly indicates that R55A expression is a valid model in our hands and is not a like-for-like mimic of CYPA-KO simply because of reduced expression. We appreciate the reviewer could not know this.

      Major critical theme no. 2.

      CYPA-NBS1 work: “Another major concern is that the evidence to support that NBS1 is the major substrate of CYPA is lacking since all the experiments were performed with the CYPA mutant or CsA treatment.”

      RESPONSE:

      We do not claim that NBS1 is ”… the major substrate of CYPA.” . We do not claim that all the DNA-R deficits we have identified are specifically a consequence of impaired NBS1 function. These are misrepresentations of our findings and how we’ve presented and discussed them. This Reviewer ignores our comprehensive CYPA-BioID, and specifically our discussion pertaining to the DNA-R and Replication factors found therein (section entitled ‘CYPA Interacting protein partners’ and Fig 5A). We explicitly discuss the fact that “A recurring theme amongst these CYPA interactors is that all are involved in end-resection” whilst also demonstrating CYPA co-IP with 53BP1, CHAMP1 and ILF2-3 (Fig 5C-E). In the ‘Discussion’ section we describe a “homesostatic role for CYPA in genome stability”, including possible contributions to controlling LLPS of well-known DNA-R factors and the fact that several mitotic, kinetochore, centrosomal and spindle proteins are found in the CYPA-BioID.

      Major critical theme no. 3.

      A major repeated criticism levelled by this reviewer as a basis for dismissing the entirety our findings is that we have failed to demonstrate that the catalytic activity of CYPA is required for DSB repair.

      • Their conclusion should be supported by additional key experiments to prove that the catalytic activity of CYPA is indeed required for DSB repair…

      • Another major concern is that the evidence to support that NBS1 is the major substrate of CYPA is lacking since all the experiments were performed with the CYPA mutant or CsA treatment.

      • One major weakness of this study is that it focuses on characterizing the interaction between CYPA and NBS1, then jumps into a conclusion that the catalytic activity of CYPA is required for DSB repair based on its direct interaction with NBS1

      RESPONSE:

      As this criticism is repeated, the impression created, and no doubt intended, is that the manuscript is irreparably flawed (“…major weakness…”). This is an over-simplification and a misdirection. It’s notable that this critique isn’t raised in such a manner by either Reviewer #1 or Reviewer #2. This is likely because any modest inferences we made concerning the possible role of CYPA catalytic isomerase activity were based on a combination of differing but complementary approaches. Firstly, we routinely used the p.R55A engineered CYPA variant, although this Reviewer regards our use of this as invalid. This longstanding peptidyl prolyl isomerase (PPI)-dead mutant model has frequently been employed to invoke the catalytic function of CYPA. The mutant was originally proposed and characterized as catalytically-dead using the in vitro chymotrypsin-coupled prolyl isomerase assay using N-succinyl-AAPF-p-nitroanilide as a substrate as far back as 1992 (Zydowsky, L.D., et al., Active site mutants of human cyclophilin A separate peptidyl-prolyl isomerase activity from cyclosporin A binding and calcineurin inhibition. Protein Science, 1992. 1(9): p.1092-1099). In addition, we routinely use Cyclopsorin A (CsA), the longstanding clinically relevant CYPA PPI inhibitor, and we also use a different and more potent CYPA PPI inhibitor, namely NIM811 (N-methyl-4-isoleucine-cyclosporine) for the DR-GFP reporter assays of individual DNA-R pathway function (i.e.’ NHEJ, HRR and SSA).

      With regards to our findings concerning CYPA-NBS1 interaction, in the Discussion section we clearly state that mechanistic analyses of prolyl isomerase on the dynamism of NBS1 FHA-BRCT would require specialist approaches outside the scope of this manuscript, as the manuscript is firmly within the realm of cellular biology. This is ignored by this Reviewer. Specifically, we state that “A regulated cis-trans isomerisation of the E111-P112 peptide bond could conceivably dynamically alter the relative positioning of the FHA domain with the tandem BRCTs of NBS1 (Fig 7C-D). This may then impact on these domains’ abilities to dynamically interact with their respective phospho-threonine (for FHA) and phospho-serine (BRCT) containing targets, consequently likely shaping/impacting NBS1 recruitment dynamics and/or plasticity of its interactome [120-122]. Demonstrating this hypothesis would require additional structural analysis using techniques such as 2D-NMR which is outside the scope of this manuscript.”

      Minor comments: 1.

      Fig. 1E; is the survival between KO and R55A statistically significant? If so, do the authors have an explanation? Why is the reconstitution of R55A more toxic than KO alone?

      RESPONSE:

      Yes, R55A is slightly more sensitive compared to KO for this endpoint. The irony that this observation runs contrary to the Reviewer’s dismissal of the R55A model line is not lost on us (Major critical theme no. 1). As is well-known for PARP1, inhibition is not equivalent to absence. A possible speculative explanation is that the R55A isomerase-dead could have additional dominant impacts compared to the KO situation. Nonetheless, we suspect this Reviewer would object to such speculation in the absence of ever more data.

      Minor comments: 2.

      In Fig. 3D, the NHEJ activity of CsA- or NIM811-treated cells is significantly downregulated in comparison to control, which raises the possibility of the pleiotropic effect of CYPA inhibition. The authors should discuss this issue.

      RESPONSE:

      Not necessarily indicative of a pleiotropic effect if one accepts that absence of a protein is not always biologically equivalent to the presence of an inhibited version the same protein. Of note, we do see somewhat reduced NHEJ following siCYPA (Fig 3A), something not mentioned by this Reviewer. Furthermore, we explicitly discuss and show interaction between CYPA and 53BP1, CHAMP1 and ILF2-3 complex, all players in NHEJ and in the intricate balance between NHEJ and resection-mediated recombination directed repair pathways.

      Minor comments: 3.

      In Figure 8A, since the expressions of Flag-NBS1 WT, P112G, and P64G are very different, the conclusion that the isomerization of CYPA is essential for NBS1 cannot be supported. Given the variation of input levels, it appears that the P64G mutation actually enhances the interaction with endogenous CYPA. Is this reproducible? This co-IP result may need to be quantified from independent sets for statistical analysis.

      RESPONSE:

      We do not claim that “…isomerization of CYPA is essential for NBS1…”. Fig 8A data is derived from a transient transfection. Whilst there is some variation in expression, we do not make any precise quantitative conclusions from these co-IPs. Nonetheless, FLAG-NBS1-P112G clearly interacts less with endogenous CYPA in this system. Importantly, and ignored by this Reviewer, the associated recombinant protein work shown in Fig 8B clearly confirms that NBS1-P112G is profoundly compromised in its ability to interact with CYPA.

      Minor comments: 4.

      A defect in DSB repair generally hypersensitizes cells to DNA replication stress, including HU. In this regard, resistance of the CYPA KO (or R55A cells) to HU is interesting, but it may be due to the nonspecific effect of the CYPA loss in multiple DNA damage signaling and repair processes. Alternatively, cell cycle may be affected nonspecifically, rendering cells resistant to replication-associated genotoxic stress. This needs to be addressed further. Analysis of overall cell cycle profile may be required.

      RESPONSE:

      Resistance to HU is likely multifactorial and cell cycle transition kinetics may be relevant here. That is why we linked the DNA replications phenotypes to this discussion in the section entitled “Impaired CYPA function reveals novel genetic dependencies/vulnerabilities”. A comprehensive analysis of cell cycle profile and phase transits is outside the scope of the current manuscript (see response to Reviewer #2).<br /> Impaired HU-induced pRPA has been linked to HU-resistance via NBS1 previously: Manthey, K.C., et al., NBS1 mediates ATR-dependent RPA hyperphosphorylation following replication-fork stall and collapse. J Cell Sci, 2007. 120(Pt 23): p. 4221-9.

      Minor comments: 5.

      Text not to mention Abstract is too dense. The manuscript will benefit a lot from extensive editing and rearrangement of figures to make the story more succinct for journal submission.

      RESPONSE:

      The Reviewer’s view concerning a lack of succinctness is not shared by Reviewer #1 and Reviewer #2. We have endeavored to draft a concise and accessible manuscript, the main body of which comes in at just over 23x sides of A4 (including Materials & Methods). Considering we guide the reader through 12x multipart figures, 5x supplementary tables and 8x supplementary figure, we believe we have achieved succinctness. Nonetheless, we will of course take direction from the appropriate journal editorial team regarding house style and format.

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      Referee #3

      Evidence, reproducibility and clarity

      In this manuscript, O'Driscoll and colleagues identify the role of cyclophilin A (CYPA), a peptidyl-prolyl cis-trans isomerase, in promoting DNA repair. They propose that the catalytic activity of CYPA is required for the action of the MRE11-RAD50-NBS1 (MRN) complex and thus double-strand break (DSB) repair. This study originated from their previous finding that cyclosporin A (CsA) induces replication-associated DNA breakage and genome instability in LIG4 syndrome patient fibroblasts. As CsA is an inhibitor of the CYPA, the authors reasoned that the negative effect of CsA in DNA repair results from its inhibition of CYPA and presumably its essential downstream substates in DNA repair. Using CRISPR/Cas-based U2OS knockout cells, they showed that the catalytic activity of CYPA is necessary for homology-directed repair. Series of BioID-proximity interactome analysis, biochemical studies (e.g., co-immunoprecipitation), and AIphaFold-derived structural determination revealed that CYPA directly interacts with the MRN complex, specifically through the Pro112 of NBS1, and its catalytic activity is required for damage-induced NBS1 foci formation, which all together led to the conclusion that the MRN complex is a direct substrate of CYPA and that CYPA controls DNA end resection and DSB repair via isomerization of NBS1.

      This is an interesting story as it reveals a new role of prolyl isomerization, which is mediated by CYPA, in promoting DSB repair. The identification of NBS1 as a novel substrate of CYPA is significant, and the manuscript may provide new insight into how prolyl isomerization of NBS1 regulates the function of the MRN complex that is engaged in DNA end resection during DSB repair. However, the authors' major claim that CYPA controls DSB repair via the MRN complex is not substantiated by the data provided at its current form. Either evidence is lacking or experiments were not performed in a convincing way. Their conclusion should be supported by additional key experiments to prove that the catalytic activity of CYPA is indeed required for DSB repair and NBS1 is a major substrate of CYPA, through which CYPA regulates DNA end resection at the stalled DNA replication fork.

      Major comments

      1. The authors reconstituted the CYPA knockout (KO) cells with WT or a catalytic mutant (R55A) for the structure-function analysis. However, re-expression levels of CYPA are vastly different between WT vs. R55A, R55A being expressed at much lower levels (not near to endogenous CYPA) (Fig. 1C). Consequently, the loss-of-function phenotypes of R55A may be simply explained by its inadequate reconstitution, thus failing to complement KO phenotypes. For instance, the lack of pRPA2 S4/S8 induction in R55A cells may be just due to the insufficient expression of R55A, thus resulting in the same phenotype as KO. Additionally, the R55A cells were compared to parental cells, not to the WT-reconstituted cells for the majority of functional analysis, so it is not clear whether WT is able to complement the KO phenotype in their system (Figs. 1, 2, 6, 9, 10, and 11). Whether the catalytic activity of CYPA is indeed responsible for the phenotypes of DNA repair deficiency is not supported. The authors should compare the phenotypes between WT- vs. R55A-reconstitued cells side-by-side for the key experiments. Ideally, expression of WT and R55A should be similar in KO cells to exclude the possibility that the R55A phenotypes merely result from insufficient mutant expression rather than true loss of catalytic activity.
      2. Another major concern is that the evidence to support that NBS1 is the major substrate of CYPA is lacking since all the experiments were performed with the CYPA mutant or CsA treatment. Whether the NBS1 P112G isomerization-defective mutant indeed exhibits a defect in DNA repair similarly to the CYPA mutant is not shown. For instance, one key experiment would be to test whether the P112G mutant fails to form damage-inducible NBS1 foci formation.
      3. In Figure 7A, the authors showed that the interaction between CYPA and NBS1 is dependent on the isomerization activity of CYPA. It should be checked whether the CYPA R55A mutant fails to interact with NBS1 in contrast to WT to support the main conclusion that NBS1 is controlled by the isomerization activity of CYPA.
      4. OPTIONAL) One major weakness of this study is that it focuses on characterizing the interaction between CYPA and NBS1, then jumps into a conclusion that the catalytic activity of CYPA is required for DSB repair based on its direct interaction with NBS1. How the isomerization of NBS1 affects its localization, stability, and/or function is not addressed. At its current form, the functional link between NBS1 isomerization and stalled fork processing is weak. Elucidating how the catalytic activity of CYPA controls the action of the MRN complex via the isomerization of NBS1 will add significant impact on the manuscript. Otherwise, the story fails to fully support the description of its title.

      Minor comments

      1. Fig. 1E; is the survival between KO and R55A statistically significant? If so, do the authors have an explanation? Why is the reconstitution of R55A more toxic than KO alone?
      2. In Fig. 3D, the NHEJ activity of CsA- or NIM811-treated cells is significantly downregulated in comparison to control, which raises the possibility of the pleiotropic effect of CYPA inhibition. The authors should discuss this issue.
      3. In Figure 8A, since the expressions of Flag-NBS1 WT, P112G, and P64G are very different, the conclusion that the isomerization of CYPA is essential for NBS1 cannot be supported. Given the variation of input levels, it appears that the P64G mutation actually enhances the interaction with endogenous CYPA. Is this reproducible? This co-IP result may need to be quantified from independent sets for statistical analysis.
      4. A defect in DSB repair generally hypersensitizes cells to DNA replication stress, including HU. In this regard, resistance of the CYPA KO (or R55A cells) to HU is interesting, but it may be due to the nonspecific effect of the CYPA loss in multiple DNA damage signaling and repair processes. Alternatively, cell cycle may be affected nonspecifically, rendering cells resistant to replication-associated genotoxic stress. This needs to be addressed further. Analysis of overall cell cycle profile may be required.
      5. Text not to mention Abstract is too dense. The manuscript will benefit a lot from extensive editing and rearrangement of figures to make the story more succinct for journal submission.

      Referees cross-commenting

      I agree with concerns on the pleiotropic effect of CYPA KO, which exhibit many distinct phenotypes in DNA repair and replication fork stability.

      Significance

      While establishing a new link between CYPA-dependent prolyl isomerization and DSB repair is significant, the current manuscript suffers lack of evidence to support its main conclusion. Specifically, although the role of CYPA in DNA repair is fairly well described using its inhibitor or KO cells, whether its isomerization activity is indeed essential and whether NBS1 is the major target for its action in DSB repair is not clear. Existence of many other targets cannot be excluded. Whether the role of CYPA is specific to replication-associated DSB repair processes or can be generally applicable to homologous recombination in any DSB repair is not shown. The role of MRN in stalled fork processing and in response to DSBs could be different, but how CYPA would modulate these distinct processes is not addressed. As such, the manuscript is targeting more specialized audience, but if the link between CYPA and the MRN complex can be further elaborated, including how isomerization affects the function of NBS1 (e.g., using the isomerization-defective NBS1 mutant), it could reach out to broader readership.

      My field of expertise includes DNA replication stress and replication-associated repair processes including stalled fork processing and recovery. I am familiar with most of the genetic, cellular, and biochemical experiments presented in the manuscript. I do not have significant expertise on the structural analysis of protein-protein interactions.

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      Referee #2

      Evidence, reproducibility and clarity

      The current manuscript by Bedir et al. explores the role of cyclophilin A in DNA repair, particularly homologous recombination. Authors show that the absence of cyclophilin A or loss of PP1 activity affects end-resection via direct interaction with NBS1. Authors have conducted a series of experiments to confirm their findings. While the findings are interesting, further discussion/ experiments mentioned below will perhaps assure readers with respect to pointed direct vs consequence facilitated indirectly through global cellular effects of CYPA.

      1. Authors show delayed S-phase transit along with reduced replication speed indicating replication stall. However, authors have not discussed how cyclophilinA might regulate replication (other than hypothesizing regarding altered dynamism of FHA-BRCT). It is conceivable that it could be an indirect effect on cellular metabolism or if authors believe it could be due to direct disruption to core replication machinery or signaling. In this regard, it will be helpful to see if there is shortening of (premature entry) G1 phase and comment on the status of the associated G1/S checkpoint.
      2. In connection to this, it will also be interesting to see if the ATR/Chk1 signaling axis is intact in CYPA KO cells with or without additional DNA damage compared to WT.
      3. Authors show that the P112 residue of NBS1 is important for the binding of cyclophilinA.
      4. What is the status of interaction among components of the MRN complex in CYPAKO cells and P112G NBS1? Further, what are the authors' thoughts on rescue experiments and whether P112G containing NBS1 to perform resection function.
      5. What are the protein levels of MRN, RAD51 etc. in CYPAKO cells? It will be important control to delineate the effects of CYPA on global transcription and translation vs specific and direct effect on end-resection. Can overexpression of NBS1 rescue the observed resection and focus phenotypes?

      Significance

      Current study highlights the role of cyclophilin A or in large peptidyl-prolyl cis- trans isomerases activity in DNA repair. Although this is not the first study showing the relevance of cyclophilin A in DNA repair, they do highlight its role in homologous recombination and DNA repair. Authors have quite conclusively explored the interaction between NBS1 and cyclophilinA as well as the putative proline residue important for this interaction.

      One of the drawbacks of the study is the pleotrophic effects of CyclophilinA. This needs to be at least discussed. Authors themselves observe induction of DSBs, replication stall, reduced NHEJ, SSA as well as HR efficiencies. Taken together, the effects of CyclophilinA even on resection could be a combination of both direct and indirect effects.

      This manuscript will have broad interest from groups working on genomic stability, immunology as well as cancer therapy. I have expertise in NHEJ, mammalian replication and replication-stress response.

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      Referee #1

      Evidence, reproducibility and clarity

      In this manuscript, the authors reveal a previously unexplored role of CYPA in DNA repair, particularly in the context of cells sensitive to the CsA. The authors' multi-faceted approach involved using CRISPR/Cas9-engineering, siRNA, BioID, co-immunoprecipitation, and specific DNA repair investigations. They suggest that CYPA, through its PPI activity, plays an active role in DNA repair, specifically in DNA end resection. They also demonstrate that inhibition or loss of CYPA results in impaired HRR following DNA replication fork stalling. Furthermore, the authors associate the loss and inhibition of CYPA with certain genetic vulnerabilities, suggesting potential therapeutic applications by exploiting CYPA PPI inhibition to selectively target cancer cells with characteristic genomic instability.

      The manuscript presents clear and comprehensive data, demonstrating the profound impact of CYPA on DNA repair. It would be suitable for publication after addressing the following points:

      1. It's surprising to find that the loss of CYPA abolished HU-induced NBS1 foci, as the MRE11 interactive domain of NBS1 should remain intact in CYPA deficient conditions and the N-terminus of NBS1 is dispensable for ATM activation (Kim et al., 2017; Stracker and Petrini, 2011). A more detailed mechanistic explanation of this phenotype would be appreciated. The authors should check the subcellular localization of NBS1 and the stability of MRN in wildtype and CYPA KO cells. Additionally, including the kinetics of NBS1 foci formation using multiple timepoints in wildtype and CYPA KO cells after damage will further support the observation.
      2. The authors showed that the interaction between CYPA and MRN didn't change after HU treatment. The authors should also include co-localization analysis of CYPA and NBS1 after HU.
      3. The paper demonstrated that BRCA2 knockdown cells were sensitive to CsA. The authors should also examine CsA sensitivity in BRCA2 deficient cancer cells. In addition, the authors could elaborate more on their criteria for selecting cancers for CYPA inhibition, whether it is based on high genomic instability or an addiction to HRR for survival.

      Significance

      The significance of this study is twofold: it adds a new layer to our understanding of DNA repair mechanisms and, importantly, it could point the way to novel therapeutic strategies for cancer. It will spark interest from molecular biologists to clinicians and pharmaceutical researchers.

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      Reply to the reviewers

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

      Redhardt and colleagues describe a structure of the voltage and Ca-activated Slo1 channel in complex with an auxiliary subunit, γ1. In complex with γ1, Slo1 adopts an open state that closely resembles previous open state structures. Of γ1, only the single membrane-spanning helix, which binds to the periphery of the Slo1 VSD, is resolved. There, it establishes several interactions with Slo1 that authors propose may favor adoption of the open state, potentially explaining how γ1 can shift I-V profile of Slo1 to be activated at more negative membrane potentials. The interactions described fit well with existing mutagenesis analyses.

      While this report provides a first glimpse of how γ1 can bind to Slo1, its impact will be minimal. It describes a single structural snapshot and there are no functional analyses presented. Additional analyses would be helpful in understanding of how γ1 can regulate Slo1 channels.

      We thank the reviewer for their honest judgment. We agree that validating the structure by biochemical and/or functional data would have significantly strengthened the manuscript. However, we are convinced that our structural data alone already provides significant novel understanding of the assembly of the Slo1-γ1 complex and regulation of Slo1 by γ1. Thus, we feel that publication of this manuscript is justified by the high importance of Slo channels and our data will have an impact in the field.

      __Major comments: __ 1. The authors propose several models for how γ1 regulates Slo1, yet none of them are experimentally evaluated. For example, on page 8, it is written that "we propose that the combination of three different principles, namely shape complementarity, covalent anchoring and lowering the resting state potential by a positively charged intracellular stretch, act in concert to stabilize an active VSD conformation in the Slo1-γ1 complex." This is a testable hypothesis and one that should be experimentally evaluated to better understand regulation by γ1.

      We agree with the reviewer that experimental validation of this hypothesis would have been an asset. Nevertheless, we think that our structural data in context of previous functional data e.g. from Li et al. 2015,2016) and also in comparison with the other two manuscripts on the same topic which have been published while this manuscript was under review, allows us to draw conclusions about the mechanism of γ1-mediated activation of Slo1. We have now, however, toned down some of the earlier statements and changed parts of our interpretations in light of the novel findings by Yamanouchi et al. and Kallure et al.

      The authors analysis of the extracellular domain of γ1 is incomplete. The only presented structure was performed with C4 symmetry imposed, in which extracellular domains were largely lost. The authors propose that these domains are dynamic and that their dynamism would enable simultaneous binding of both γ and b subunits, as occurs in cells. A more thorough analysis of the dynamics and well as potential asymmetric conformations should be performed to better understand how these domains interact with Slo1.

      We completely agree with the reviewer that a thorough analysis of the extracellular domain is important and thank the reviewer for their valuable suggestions. We had attempted such analysis already from the beginning, but were not successful. More specifically, we have attempted reconstructions with lower symmetry (C2 and C1) from the beginning or by symmetry relaxation after initial C4 reconstruction. Also, we tested different masking and signal subtraction strategies in combination with different global and local refinements, as well as symmetry expansion and 3D classification. Unfortunately, none of these strategies led to a better resolved LRR module.

      We now think that in comparison with Kallure et al. and Yamanouchi et al., the ice in our sample was thinner, which allowed us to reach higher resolution in the core particle (Slo1 and γ1 TM helix), but at the cost of the γ1 LRRs being denatured or at least distorted by the air-water interface.

      The refinement statistics suggest that the model was incompletely refined. This reviewer was not provided with the map or models, but the validation report lists a clashscore of 9 and 5.7% of the rotamers as being outliers, both of which are high for the reported resolution of the structure. It is also strange that the Q-score varied between different γ1 protomers. Why are the four protomers not identical when the map is 4-fold symmetric? The authors should carefully inspect their model to insure that it is as correct as possible.

      We thank the reviewer for pointing this out, and while the values for clashscores and rotamers were not outside the range of values typically found in many other cryo-EM structures, we agree that there was still some room for improvement. We have worked on this and could lower the values to a clashscore of 7.0 and 1.8 % rotamer outliers.

      The difference in Q-score is also something not too uncommon since, while the map is indeed C4-symmetric, during model refinement the NCS restraints are not completely preventing small deviations between the protomers. We have now also successfully attempted to minimize these differences further.

      Reviewer #1 (Significance (Required)):

      The impact of this report is limited. Functional analyses will be necessary to uncover precisely how gamma subunits regulate Slo1 channels.

      We thank the reviewer for this honest statement, but respectfully disagree. While additional functional analyses would have certainly boosted the impact, we are certain that our structural data and their interpretation will be very valuable for the field, because they provide (as stated by Reviewer 3) new insights into the regulation of Slo channel activity by the γ subunits and suggest (as stated by reviewer 2) a novel mechanism of activation of voltage-gated ion channels..

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

      Summary This study presents a high resolution cryo-EM study of a voltage-gated Ca++-dependent K+ channel in the presence of a gamma1 subunit. Analysis of the structure and sequence alignments suggest a novel mechanism of activation of voltage-gated ion channels.

      __Major comments __ The major issue in this paper is that it is only a structural biology paper. There is no structure-function relationship study, no functional studies of mutants that could validate -or not- the inferred underlying mechanism. Even though the authors have identified good candidates for mutations (e.g. p. 6) they have not attempted to validate their importance experimentally. As a result, reading their discussion is somewhat frustrating and full of assumptions, as indicated by sentences (p.7) like

      "a possible mechanism... might be... which would make... more likely".

      "... which might act ... seems important... might indicate... might lower... likely most pronounced... could be responsible..."

      "... might play an important role... does not allow a certain conclusion..."

      We completely agree with the reviewer that the paper would have been much stronger if we would have been able to perform biochemical or functional assays testing mutations in the binding interface. However, this would have unfortunately been beyond the scope of the project. We are nevertheless confident that our structural data will be of value for the field, also in context of the two structure-function papers that have been published since which confirm and validate our data and provide the link to function.

      __Minor comments which could be confidently addressed __ The Introduction contains no description of the state-of-the-art in the field concerning the available structures in the same system or similar ones. Hence, it is difficult to judge for people outside the field if the novelty. is incremental or significant.

      We have adjusted the introduction to explicitly mention previously published structural data on the Slo channels.

      References 10 and 42 (eLife) lacj some details.

      We have adjusted said references accordingly.

      __Reviewer #2 (Significance (Required)): ______


      Significance general assessment As it turns out, at least two papers in exactly the same field just appeared: -one in Molecular Cell by a Japanese group, which is much more developed and contains functional tests and structure-function relationships, in addition to beautiful structures (available on-line early December) https://www.sciencedirect.com/science/article/pii/S1097276523009218

      -one in biorxiv, deposited yesterday https://www.biorxiv.org/content/biorxiv/early/2023/12/20/2023.12.20.572542.full.pdf

      Advances wrt known results See above. As a result of these new papers in Mol Cell and biorxiv, I think the authors should reconsider submitting their article elsewhere, perhaps for a more specialized audience.

      We agree with the reviewer that in light of the other two publications which both were published a while after we deposited our preprint on biorxiv and while the manuscript was under review, the uniqueness of our data is somewhat lowered. However, since our data is overall in large agreement with these two other publications, but we report a structure at significantly higher resolution and from a different species (indeed the first Slo1 structure from rabbit, a model organism of BK channel characterization in the last decades), we are confident that our data are still very valuable for the field and qualify for publication in one of the affiliate journals of Review Commons. After all, the fact that three papers reporting very similar data were published within a few weeks (plus another preprint reporting structures of a Slo channel, but unrelated to γ subunits) illustrates the importance for understanding the regulation of this essential ion channel and the impact of all structural data enhancing this understanding, and independent confirmation by three different labs is something very valuable to the community.

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

      "This manuscript by Redhardt et al. presents the cryo-EM structure of the Slo K+ channel from rabbits in conjunction with its auxiliary subunit, γ1, and proposes a mechanistic model for regulating channel activation. "This manuscript by Redhardt et al. presents the cryo-EM structure of the Slo K+ channel from rabbits in conjunction with its auxiliary subunit, γ1, and proposes a mechanistic model for regulating channel activation. The Slo channel, also known as the large-conductance calcium-activated potassium channel or BK channel, is an ion channel type found in various cell membranes, including neurons, muscle cells, and other tissue types. Its key features encompass Ca2+ activation, voltage dependence, and regulation by auxiliary subunits. Different auxiliary subunits have been shown to modulate channel functions distinctly; notably, the γ1 subunit enables channel activation at lower voltages compared to the wild-type channel. This manuscript offers a structural-functional framework that enhances our comprehension of how Slo channels are regulated by auxiliary subunits, such as gamma and beta subunits. While the structure of Slo channels in complex with the beta subunit is understood, the binding and interaction of the gamma subunit with the channels remain elusive due to the absence of corresponding structures. Along these lines, the presented structure here indeed provides new insights into the regulation of Slo channel activity by the gamma subunit. However, there are some important questions below that should be addressed."

      1. In Figure 1D panel, the calcium ions appear to be indistinct, likely due to the figure's low resolution. The authors are recommended to enhance the figure quality and consider a better positioning to effectively illustrate the ions.

      We have adjusted the coloring of calcium ions Fig. 1D to increase their visibility.

      It would be beneficial for the readers if the authors provided detailed methodology explaining how they arrived at the 7% and 11% coexpression, aiding in the complex formation. Additionally, it would be informative to know the observed shift in the size exclusion chromatography (SEC) profile of Slo1-Y1 compared to apo Slo1.

      We have arrived at these concentrations of the respective viruses by empirically testing ranges between 3 % and 15 %. We have now added a sentence to the manuscript to explain this.

      Is there any rationale behind initially purifying using strep affinity followed by His affinity?

      The idea behind using a dual-affinity protocol is to ensure that all purified complexes contain at least one copy of Slo1 and one copy of γ1. Using the Strep tag first allows to remove most contaminants already in the first step, due to its higher specificity compared to the His tag. We have added a sentence to the methods section to explain this.

      Regarding the Slo1 tetramer with gamma subunit binding, are there other classes where one, two, or three gamma subunits are bound to Slo1? Or is there only one class where all protomers of Slo1 are occupied by the gamma subunit? How do these classes appear when refined in C1 symmetry? Are there classes displaying C1 or C2 symmetry, or is the four-fold symmetry preserved across all refined classes?"

      We exclusively observe complexes with four γ1 subunits. This is also in agreement with the other two recent publications reporting Slo1-γ1 complex structures, but could in principle be an artifact of artificial overexpression. Also when we refine the particles in C1, we retain C4 symmetry and do not observe any classes with C2 or C1 symmetry.

      The authors utilized nearly 1.9 million particles to reconstruct the final class, resulting in a high resolution. Is such a large number of particles truly necessary to achieve high resolution in this context?

      The large number of particles is not strictly necessary, i.e. we could obtain similar quality by using fewer particles. In the end, we have now further classified down to ~827k particles, which very slightly improved the resolution and quality of the map.

      Authros mentioned that F273 of γ1 forms pi-stacking interactions, it remains unclear with which components of the channel these interactions occur.

      F273 forms (slightly distorted) T stacking interactions with F164 in S2 and F187 in S3. We now changed the sentence in the manuscript to mention the residues that line the hydrophobic pocket to make it more clear which elements contribute to the interaction with F273.

      The authors propose that the disulfide bond between the γ subunit and Slo1 could play a crucial role in their interaction. Was there any observation of a covalent linkage in SDS page analysis? Furthermore, how would this interaction be affected if either cysteine C253 of gamma1 or C141 on the channel were mutated or neutralized?"

      We have run all our SDS-PAGE experiments under reducing conditions, thus destroying any disulfide bridges that might have been present in the complex. We have now, however obtained a slightly better defined reconstruction (as pointed out in our answer to point 5 raised by this reviewer) where we do not see as clear continuous density anymore between the two cysteine side chains. Thus, we have removed the cystine bond from the final model and have adjusted text and figures accordingly. We still think that it might be more than coincidence that those two side chains come into such close proximity, though, and still discuss the possibility of a cystine bridge in the manuscript.

      Author's state that "The presence of several immobile positive charges on the intracellular side in close proximity to the VSD as in the case of the Slo1-γ1 complex is likely to locally lower the resting state potential and repulse the gating charges, thereby reducing the energy to overcome for the VSD to transition to the active conformation." Authors need to be little more elaborative here as it is not clear what authors mean repulse of gating charges.

      We have expanded our description of the proposed repulsive effect of the positive charges in the manuscript and in addition also discuss the additional role of the charges in stabilizing the Ca2+-bound conformation of the gating ring as proposed by Yamanouchi et al.

      Probably beyond this study but I was wondering whether it is possible that Beta and gamma subunit can together assemble as heteromers to form a cage-like structure with contribution from both.

      We agree with the reviewer that this is an interesting question which we have also thought about and one which should be tested, but as the reviewer already mentioned, this would go beyond the present study and should be subject to an independent follow-up investigation.

      Are there any specific lipids observed within the structure that could potentially contribute to the functional conformation or stability of the complex?"

      Given the high resolution of our structure, we observe a number of ordered lipid and detergent molecules, most of which were located at similar positions as in previous structures of Slo channels. Besides those molecules clustering in the deep cleft between neighboring voltage-sensor domains, we also observe lipid densities close to the binding site of γ1 on the distal side of the VSD. However, as their relevance for γ1 binding is unclear, we don’t discuss them in the manuscript. In general, of course, we agree with the reviewer that lipids can have a large impact on the function of membrane proteins.

      It would be interesting to see if the kink in the gamma subunit is entirely neutralized through mutations of proline and glycine, how these alteration might impact the assembly of the mutated gamma subunit with the channel. The authors should provide insights into whether this mutated form of the gamma subunit assembles effectively with the channel and whether there are functional consequences associated with this alteration.

      As shown by Kallure et al., substituting P270 in the kink by serine (the native residue at this position in γ3) strongly diminished the ability of γ1 to associate with Slo1 in vitro, demonstrating the importance of the kink and providing a rationale for the observed differences in the potency of the TM helices of γ1 and γ3 in Slo1 activation.

      It would be generally beneficial for the authors to provide functional insights that can support the physiological relevance of this kink in the gamma subunit. Understanding the potential consequences of this mutation and its implications for the assembly and function of the channel complex will offer valuable insights into the physiological role of the kink.

      We absolutely agree with the reviewer that functional insights on the relevance of the kink would be very valuable, but we think that the available experimental data together with the natural sequence differences in γ1-γ4 and the correlation with their physiological activity are very clear indications that the kink is relevant. However, future follow-up studies that prove this beyond any doubt would be valuable.

      Is it known that binding of beta or gamma subunit can impact the subsequent binding of beta and gamma to channels. If it is, it need to be discussed briefly in the discussion part.

      This is, to the best of our knowledge, not known. The only existing data that suggests co-presence of beta and gamma subunits on Slo1, reported in Gonzalez-Perez et al., 2015, stems from electrophysiological experiments and does not reveal anything about hierarchy and temporal order of binding events.

      Reviewer #3 (Significance (Required)):

      The Slo channel, also known as the large-conductance calcium-activated potassium channel or BK channel, is an ion channel type found in various cell membranes, including neurons, muscle cells, and other tissue types. Its key features encompass Ca2+ activation, voltage dependence, and regulation by auxiliary subunits. Different auxiliary subunits have been shown to modulate channel functions distinctly; notably, the γ1 subunit enables channel activation at lower voltages compared to the wild-type channel. This manuscript offers a structural-functional framework that enhances our comprehension of how Slo channels are regulated by auxiliary subunits, such as gamma and beta subunits. While the structure of Slo channels in complex with the beta subunit is understood, the binding and interaction of the gamma subunit with the channels remain elusive due to the absence of corresponding structures. Along these lines, the presented structure here indeed provides new insights into the regulation of Slo channel activity by the gamma subunit.

      We thank the reviewer for this positive assessment of the data and agree that our structural data, also when regarded together with the complementary manuscripts by Kallure et al. and Yamanouchi et al., provides significant new insight into the assembly and activity of γ subunits.

    2. 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

      "This manuscript by Redhardt et al. presents the cryo-EM structure of the Slo K+ channel from rabbits in conjunction with its auxiliary subunit, γ1, and proposes a mechanistic model for regulating channel activation.

      "This manuscript by Redhardt et al. presents the cryo-EM structure of the Slo K+ channel from rabbits in conjunction with its auxiliary subunit, γ1, and proposes a mechanistic model for regulating channel activation.

      The Slo channel, also known as the large-conductance calcium-activated potassium channel or BK channel, is an ion channel type found in various cell membranes, including neurons, muscle cells, and other tissue types. Its key features encompass Ca2+ activation, voltage dependence, and regulation by auxiliary subunits. Different auxiliary subunits have been shown to modulate channel functions distinctly; notably, the γ1 subunit enables channel activation at lower voltages compared to the wild-type channel. This manuscript offers a structural-functional framework that enhances our comprehension of how Slo channels are regulated by auxiliary subunits, such as gamma and beta subunits. While the structure of Slo channels in complex with the beta subunit is understood, the binding and interaction of the gamma subunit with the channels remain elusive due to the absence of corresponding structures. Along these lines, the presented structure here indeed provides new insights into the regulation of Slo channel activity by the gamma subunit. However, there are some important questions below that should be addressed."

      1. In Figure 1D panel, the calcium ions appear to be indistinct, likely due to the figure's low resolution. The authors are recommended to enhance the figure quality and consider a better positioning to effectively illustrate the ions.
      2. It would be beneficial for the readers if the authors provided detailed methodology explaining how they arrived at the 7% and 11% coexpression, aiding in the complex formation. Additionally, it would be informative to know the observed shift in the size exclusion chromatography (SEC) profile of Slo1-Y1 compared to apo Slo1.
      3. Is there any rationale behind initially purifying using strep affinity followed by His affinity?
      4. Regarding the Slo1 tetramer with gamma subunit binding, are there other classes where one, two, or three gamma subunits are bound to Slo1? Or is there only one class where all protomers of Slo1 are occupied by the gamma subunit? How do these classes appear when refined in C1 symmetry? Are there classes displaying C1 or C2 symmetry, or is the four-fold symmetry preserved across all refined classes?"
      5. The authors utilized nearly 1.9 million particles to reconstruct the final class, resulting in a high resolution. Is such a large number of particles truly necessary to achieve high resolution in this context?
      6. Authros mentioned that F273 of Y1 forms pi-stacking interactions, it remains unclear with which components of the channel these interactions occur.
      7. The authors propose that the disulfide bond between the Y subunit and Slo1 could play a crucial role in their interaction. Was there any observation of a covalent linkage in SDS page analysis? Furthermore, how would this interaction be affected if either cysteine C253 of gamma1 or C141 on the channel were mutated or neutralized?"
      8. Author's state that "The presence of several immobile positive charges on the intracellular side in close proximity to the VSD as in the case of the Slo1-γ1 complex is likely to locally lower the resting state potential and repulse the gating charges, thereby reducing the energy to overcome for the VSD to transition to the active conformation." Authors need to be little more elaborative here as it is not clear what authors mean repulse of gating charges.
      9. Probably beyond this study but I was wondering whether it is possible that Beta and gamma subunit can together assemble as heteromers to form a cage-like structure with contribution from both.
      10. Are there any specific lipids observed within the structure that could potentially contribute to the functional conformation or stability of the complex?"
      11. It would be interesting to see if the kink in the gamma subunit is entirely neutralized through mutations of proline and glycine, how these alteration might impact the assembly of the mutated gamma subunit with the channel. The authors should provide insights into whether this mutated form of the gamma subunit assembles effectively with the channel and whether there are functional consequences associated with this alteration.
      12. It would be generally beneficial for the authors to provide functional insights that can support the physiological relevance of this kink in the gamma subunit. Understanding the potential consequences of this mutation and its implications for the assembly and function of the channel complex will offer valuable insights into the physiological role of the kink.
      13. Is it known that binding of beta or gamma subunit can impact the subsequent binding of beta and gamma to channels. If it is, it need to be discussed briefly in the discussion part.

      Significance

      The Slo channel, also known as the large-conductance calcium-activated potassium channel or BK channel, is an ion channel type found in various cell membranes, including neurons, muscle cells, and other tissue types. Its key features encompass Ca2+ activation, voltage dependence, and regulation by auxiliary subunits. Different auxiliary subunits have been shown to modulate channel functions distinctly; notably, the γ1 subunit enables channel activation at lower voltages compared to the wild-type channel. This manuscript offers a structural-functional framework that enhances our comprehension of how Slo channels are regulated by auxiliary subunits, such as gamma and beta subunits. While the structure of Slo channels in complex with the beta subunit is understood, the binding and interaction of the gamma subunit with the channels remain elusive due to the absence of corresponding structures. Along these lines, the presented structure here indeed provides new insights into the regulation of Slo channel activity by the gamma subunit.

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

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      Referee #2

      Evidence, reproducibility and clarity

      Summary

      This study presents a high resolution cryo-EM study of a voltage-gated Ca++-dependent K+ channel in the presence of a gamma1 subunit.

      Analysis of the structure and sequence alignments suggest a novel mechanism of activation of voltage-gated ion channels.

      Major comments

      The major issue in this paper is that it is only a structural biology paper. There is no structure-function relationship study, no functional studies of mutants that could validate -or not- the inferred underlying mechanism. Even though the authors have identified good candidates for mutations (e.g. p. 6) they have not attempted to validate their importance experimentally. As a result, reading their discussion is somewhat frustrating and full of assumptions, as indicated by sentences (p.7) like "a possible mechanism... might be... which would make... more likely". "... which might act ... seems important... might indicate... might lower... likely most pronounced... could be responsible..." "... might play an important role... does not allow a certain conclusion..."

      Minor comments which could be confidently addressed

      The Introduction contains no description of the state-of-the-art in the field concerning the available structures in the same system or similar ones. Hence, it is difficult to judge for people outside the field if the novelty is incremental or significant.

      References 10 and 42 (eLife) lack some details.

      Significance

      Significance general assessment

      As it turns out, at least two papers in exactly the same field just appeared:

      Advances

      wrt known results

      See above.

      As a result of these new papers in Mol Cell and biorxiv, I think the authors should reconsider submitting their article elsewhere, perhaps for a more specialized audience.

    4. 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

      Redhardt and colleagues describe a structure of the voltage and Ca-activated Slo1 channel in complex with an auxiliary subunit, 1. In complex with 1, Slo1 adopts an open state that closely resembles previous open state structures. Of 1, only the single membrane-spanning helix, which binds to the periphery of the Slo1 VSD, is resolved. There, it establishes several interactions with Slo1 that authors propose may favor adoption of the open state, potentially explaining how 1 can shift I-V profile of Slo1 to be activated at more negative membrane potentials. The interactions described fit well with existing mutagenesis analyses. While this report provides a first glimpse of how 1 can bind to Slo1, its impact will be minimal. It describes a single structural snapshot and there are no functional analyses presented. Additional analyses would be helpful in understanding of how 1 can regulate Slo1 channels.

      Major comments:

      1. The authors propose several models for how 1 regulates Slo1, yet none of them are experimentally evaluated. For example, on page 8, it is written that "we propose that the combination of three different principles, namely shape complementarity, covalent anchoring and lowering the resting state potential by a positively charged intracellular stretch, act in concert to stabilize an active VSD conformation in the Slo1-γ1 complex." This is a testable hypothesis and one that should be experimentally evaluated to better understand regulation by 1.
      2. The authors analysis of the extracellular domain of 1 is incomplete. The only presented structure was performed with C4 symmetry imposed, in which extracellular domains were largely lost. The authors propose that these domains are dynamic and that their dynamism would enable simultaneous binding of both  and  subunits, as occurs in cells. A more thorough analysis of the dynamics and well as potential asymmetric conformations should be performed to better understand how these domains interact with Slo1.
      3. The refinement statistics suggest that the model was incompletely refined. This reviewer was not provided with the map or models, but the validation report lists a clashscore of 9 and 5.7% of the rotamers as being outliers, both of which are high for the reported resolution of the structure. It is also strange that the Q-score varied between different 1 protomers. Why are the four protomers not identical when the map is 4-fold symmetric? The authors should carefully inspect their model to insure that it is as correct as possible.

      Significance

      The impact of this report is limited. Functional analyses will be necessary to uncover precisely how gamma subunits regulate Slo1 channels.

    1. 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

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

      The coupling between cell polarity and cell cycle progression is an important aspect of symmetric and asymmetric cell division. Although there are several examples of cell cycle kinases phosphorylating polarity proteins, it has been difficult to assess the importance of these on cell division due to the strong and pleiotropic effects of manipulating these kinases. Here, the authors generate an analogue-sensitive allele of cdk1 in flies to tackle this question in neuroblasts (NBs) and sensory organ precursors (SOPs), two well characterised examples of asymmetric cell divisions. They show that partial Cdk1 inhibition (which still allows cell cycle progression) does not block Bazooka (PARD3 in mammals) polarization in NBs, but prevents coalescence of the Baz crescent, which has previously been shown to be an actomyosin-based process. They further identify a Cdk1 consensus site on Baz (S180) for which they generate a phospho-specific antibody, allowing them to show that this site is specifically phosphorylated in dividing NBs and SOPs. Although mutations at this site do not recapitulate the effect of Cdk1 on Baz coalescence, they do delay Miranda polarization in NBs and affect lateral inhibition and asymmetric cell division of SOPs. Finally, the authors show that human PARD3 can also be phosphorylated by Cyclin B/Cdk1 in vitro.

      Major comments:

      • Figure 2A: it would be good to show that polarization of Baz::GFP in consecutive divisions is maintained in cdk1as2 animals in the absence of 1-NA-PP1. We now show in Fig S2B a panel with two consecutive divisions of a cdk1as2 neuroblast in the absence of 1-NAP-PP1, followed by a third division in the presence of 1-NAP-PP1. The neuroblast shows high levels of Baz polarization in the two first divisions.

      • The interpretation of the observed SOP phenotypes is complicated by the uneven expression of the pnr-GAL4 driver and the fact that it is expressed in epithelial cells rather than just SOPs. The authors could express their control and mutant Baz constructs under the control of neurP72-GAL4. It is not likely they would be able to deplete endogenous Baz as they have done in NBs, as neurP72-GAL4 is expressed too late to deplete most proteins before SOP division, but they could at least look at localization of the mutants and any possible gain-of-function phenotypes.

      Following this suggestion, we have recombined Neur-GAL4 with UAS-delta RNAi to attempt to deplete both endogenous Baz::mScarlet and Delta while expressing our Baz::GFP constructs specifically in SOPs. Baz::mScarlet depletion was surprisingly efficient considering, as the reviewer points out, the late timing of Neur-GAL4 expression. However, the adult flies did not present any sensory organs transformations, perhaps because Delta might not be as efficiently depleted. We can at least rule out dominant-negative effects.

      We thank the reviewer for his constructive feedback and as suggested, we now extensively analysed the localisation of the Baz-S180 mutants in SOPs and found significant defects. We describe these observations in a new Figure 6. Briefly, we observed that the Baz phosphomutants have localisation defects during the pIIa cell division but not the pI cell division. We also observed a very surprising mosaicism of expression of our UASz-driven constructs within the SOP lineage that allowed us to make a few interesting observations which should be of interest to SOP specialists. Briefly, mosaic expression of Baz::GFP within the SOP lineage allowed to analyse the relative contributions of pIIa and pIIb/pIIIb to different Baz cortical pools and revealed an unexpected cell non-autonomous mechanism controlling pIIb division orientation. We describe these findings in a new associated supplemental figure.

      The authors speculate that Baz phosphorylation during lateral inhibition may be the reason for the observed excess specification of SOPs in the S180 mutants. This could easily be tested by looking at their antibody staining at earlier stages in the notum. Following this suggestion (also coming from Reviewer #2), we have stained nota between around 8h APF. We observed that patches of cells of the early notum display a strong Baz-pS180 phospho-signal. These patches partially overlap with the Delta-positive stripes in which lateral inhibition occurs (as described for example in (Corson et al., 2017), consistent with the possibility that Baz-S180 phosphorylation does somehow regulate lateral inhibition.

      These new experiments clearly show that Baz can be phosphorylated on S180 in cells that do not divide asymmetrically. This led us to change the title.

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

      Cell polarization in dividing cells, including stem cells, is typically coupled such that polarity can inform the architecture, orientation, and/or asymmetry during cell division. In Drosophila neural stem cells (neuroblasts/SOP), Par polarity is coupled to the cell cycle, but the nature of this coupling remains unclear. In this work, Loyer and colleagues report on impacts of CDK1 inhibition on Bazooka/Par3 localization and basal fate determinant localization. They provide evidence for a novel phosphorylation site that appears unique to asymmetrically dividing cells and may be involved in regulation of asymmetric division. Finally, they show that CDK1 can, at least in principle, phosphorylate human Par3 in vitro.

      Overall, the major claims of the abstract appear supported by the experimental work; however, we think the title overstates the overall conclusions that can be drawn from the work.

      Major comments:

      • The major claim of the paper is the role of specific phosphorylation of S180 in asymmetrically dividing cells in polarization and sensory organ formation, which relies heavily on interpretation of S180A/D phosphomutants. The experiments are carefully performed and quantified, and are consistent with the conclusions drawn. However, we wondered if it possible that the phenotypes are not linked to phosphorylation (the authors acknowledge this in the Discussion)? In other words could the A/D mutants simply be weak Baz mutants? This could this potentially explain the extra-SOP phenotype if Baz function is generally altered, especially given that it is difficult to rationalise a role for SOP-specific phosphorylation in the processes that specify SOP cells in the precursor epithelial cells. The authors speculate that these early precursors may exhibit also phosphorylation, but this isn't examined. Chasing this down seems key to support the core titular claim of the paper. Following this suggestion (also coming from Reviewer #1), we have stained nota around 8h APF. We observed that patches of cells of the early notum display a strong Baz-pS180 phospho-signal. These patches partially overlap with the Delta-positive stripes in which lateral inhibition occurs (as described for example in Corson et al., 2017). This result is presented in Fig. 5H. As would be the case for any phosphomutant, this does not strictly rule out that the S180A and S180D could simply be weak Baz mutants, but it strongly supports the possibility that the lateral inhibition defects observed in these mutants result from defective Baz-S180 phosphorylation.

      • Implicit in the core message of the paper is the elucidation of CDK1 regulation of polarity and specifically Baz. However, the connection between CDK1 and S180 (and Baz regulation overall) is relatively tenuous in this work. First, the S180A mutant does not phenocopy CDK1 inhibition with respect to basal determinant phenotypes, though obviously CDK1 may be more pleiotropic. Second, whether the CDK1 inhibition phenotype is linked to any effect on Baz/PAR behaviour is not really explored. Third, they do not test whether S180 phosphorylation is CDK1-dependent. We fully agree with these comments. We cannot think of any way of addressing the first two points, which would require fully inhibiting CDK1 and somehow maintaining neuroblasts in mitosis to examine how it impacts Baz localisation. We tried to arrest neuroblasts in mitosis and block the proteasome as this at least in HeLa cells led to persistence of mitosis when CDK1 was inhibited (Skoufias et al., 2007). However, neuroblasts arrested in mitosis by proteasome inhibition slipped out of mitosis.

      However, concerning the third point, we now provide evidence showing that, at least in vitro, Drosophila BazS180 is phosphorylated by CDK1 (see below).

      The method for quantifying domain signal only references prior work and should be described in this work. From our search of the cited reference, it appears to be peak signal intensity at a user specified point on the cortex. While this does not undermine the core findings as presented, it may not capture additional features that may be informative (domain size, fluorescence distribution, total signal etc.). For example domain coalescence would imply smaller, brighter domains, but similar total protein amounts, which appears to be the case from images, but isn't quantified per se. We now describe our method for quantifying average signal intensity in the middle of the Baz crescents. We agree that quantifying additional features to check whether they are affected by partial CDK1 inhibition would be interesting. However, doing so requires determining exactly where Baz crescents start and end. As Baz crescent edges in neuroblasts often end in a gradient rather than a sharp edge (Hannaford et al., 2018), we are not sure to be able to confidently do so in every case with the image quality of our dataset: we prioritised limiting photobleaching to accurately quantify the levels of endogenously expressed Baz rather than obtaining very sharp and high contrast images. This is further complicated by the fact that, depending on the depth of neuroblasts within the tissue and the orientation of their division relative to the imaging plane, the signal intensity of Baz crescents is quite variable, preventing a simple thresholding approach to arbitrarily determine the limits of crescents based on signal intensity. In short, accurately determining the size of crescents is very challenging.

      The phosphospecific antibody signal is relatively weak, leading to relatively low signal to noise, which could compromise the ability to detect phospho-S180 in non-asymmetrically dividing cells or generally in cells in which Baz is not polarised and thus signal would be diffused around the cell rather than concentrated. Similar caveats could also apply to the lack of signal in interphase cells, where Baz may be less enriched at the cortex and not polarized. We are inclined to believe the authors conclusions, particularly given their examination of multiple cell types and tissues. However, it is a potential caveat as it may be most visible in polarised cells where it is asymmetrically enriched. We thank the reviewer for pointing this out. Given the fact that Baz levels at the neuroepithelial cells adherens junctions are similar, we are confident that Baz-S180 is phosphorylated in dividing neuroblasts but not in non-mitotic epithelial cells, which is at least consistent with our new finding that CDK1 phosphorylates Baz-S180 in vitro. However, we agree that we cannot strictly rule out that Baz-S180 is phosphorylated but below a detection threshold in mitotic neuroepithelial cells as cortical Baz levels decrease in these cells.

      We have also gathered new data showing that, in the early notum, Baz-S180 is detected in epithelial cells that are not dividing asymmetrically, definitely ruling out the notion that Baz-S180 is strictly ACD-specific. We have changed the title of the paper accordingly, toned down the mention of apparently ACD-specific Baz-S180 phosphorylation in the abstract and now describe and discuss the fact that the apparent ACD-specificity of Baz-S180 phosphorylation is context-specific.

      Examination of in vitro phosphorylation of human Par3D (Figure 6) seems out of place and does not add much. It is human, not Bazooka. They reveal 30 sites, 18 of which in both replicates, but most are not obvious CDK sites and the S180 equivalent site is missing. None of these sites is validated in vivo, at least in this work.

      We fully agree with these comments. We initially attempted to purify both full length Baz and human PARD3 but only managed to purify small amounts of PARD3, which is why our analysis was limited to human PARD3. To circumvent these difficulties, we instead purified a smaller N-terminal fragment of Baz and PARD3, which was successful for both proteins and gave us much higher quantities of sample for analysis. Using two different approaches (Western blot with our phospho-specific antibody on Baz and targeted mass spectrometry on Baz and PARD3), we now show in a new Figure 7 that CDK1 phosphorylates Baz-S180 and PARD3-S187 in vitro.

      Minor comments: Figure 1: Uses metaphase arrested cells, presumably colcemid, but colcemid is only noted in Figure 2. We now mention Colcemid in the legend of Figure 1. - Figure 2A: Scale bar is truncated. We have corrected this. - Figure 2A: Example images of control neuroblasts could be useful to readers. We now show control neuroblasts in Figure 2A. - Figure 2G' vs H': Because G' has two panels and H' has only one, we often confused the PKC and Mira box plots when comparing to Numb. Perhaps Mira could be in a separate sub panel or be more closely juxtaposed with Numb? The quantification of the Mira signal is now right next to Numb. - Whereas both Numb/Mira were examined in CDK1(as), only Mira is reported for the S180A/D experiments. Is there a Numb phenotype as well?

      We actually co-stained Numb and Miranda in the dataset that we analysed in the S180A/D experiments shown in Fig 4E, F. We did not analyse Numb localisation in the first version we submitted because of a penetration issue of the Numb antibody: the Numb signal fades extremely fast as we image deeper in the tissue, causing large difference of signal intensity even within a single cell. This prevents us from performing any meaningful quantitative measurement of the Numb signal like the one we did in Fig. 2H, K, for which we did not encounter this issue. All our further immunostaining experiments with this antibody have had the same problem since then, even after using Triton concentrations up to 4% for permeabilization.

      Nonetheless, following the reviewer’s question, we have at least performed a simple qualitative analysis of Numb localisation in this experiment. We observed that Numb localised to the basal pole in most cases in controls and Baz phosphomutants, but localised uniformly at the cortex in half the cases where Miranda showed very low levels of polarisation in metaphase in BazS180D mutants. This Numb localisation defect suggests a loss of function of the PAR complex whereas, intriguingly, the Miranda localisation defect suggests a gain of function of the PAR complex. These new observations are described in Fig. 4G-H’.

      • The discussion of the notch / Baz phenotypes (Figure 5) is rather complicated and a bit difficult to follow. We agree with this, we have rewritten this part. This is further simplified by our new observation that Baz-S180 is phosphorylated in the early notum during lateral inhibition.

      • Figure 5A: captions should indicate that RFP RNAi is depleting Baz. We have modified the figure accordingly.

      • Box plots are used, but not described. i.e. outliers seem to be marked, but criteria unclear. Mean vs median, etc. We now describe boxplots in the legend in the first instance they are used (Fig 2A’), and in the material and methods
      • Some grammatical mistakes:
      • Title: neuroblast (no 's'),
      • Page 1: Cell fate difference(s?) in the resulting daughter cells
      • Page 4: (As) CDK1 inhibition with 10 μM 1-NA-PP1 prevents neuroblasts from cycling and causes metaphase- arrested neuroblasts to slip out of mitosis. (Reword)
      • Page 6: increased levels of basal fate(no 's') determinants

      We have corrected these mistakes.

      Reviewer #2 (Significance (Required)):

      The links between cell cycle and cell polarity are clearly important and remain poorly understood. Hence, the work addresses key conceptual/mechanistic questions relevant to our fundamental understanding of stem cell biology and regulation of polarity and asymmetric cell division. In our opinion, there are clearly some interesting observations in the manuscript, the experiments are performed carefully, and the data are generally well described. That said, overall, the work seems somewhat premature.

      The direct impact of CDK1 on Baz behaviour remains somewhat unclear. The authors do a good job of limiting the concentration of inhibitor to decouple effects of cell cycle progression from CDK1 levels per se, but this does potentially impact the strength of the phenotypes they can detect and hence the observed phenotypes are relatively minor. Note that driving cells out of mitosis with stronger CDK1 inhibition clearly impacts Baz localization, so the 'real' effect of CDK1 inhibition on Baz could be stronger than reported here. It is also unclear whether the phenotypes observed are directly linked to CDK1 regulation of PAR polarity or an indirect effect of cell cycle control of other processes. The authors' suggestion that it could be related to defects in cortical actin organization, which is known to be cell cycle controlled, seems most likely, but neither this or other models are explored further. We agree but are not aware of any experiment that would allow testing full inhibition of CDK1 on membrane-bound Baz in mitotic neuroblasts. As mentioned above in our response to reviewer #1 we tried to arrest neuroblasts in mitosis and block the proteasome as this at least in HeLa cells led to persistence of mitosis when CDK1 was inhibited (Skoufias et al., 2007). However, neuroblasts arrested in mitosis by proteasome or Colcemid or both slipped out of mitosis upon inhibition of CDK1.

      We agree it would be interesting to study how CDK1 affects the actomyosin network in neuroblasts but feel that this is somewhat beyond the scope of the manuscript.

      Using phosphospecific antibodies, they report on a novel putative CDK1 phosphorylation site, but aside from looking like a consensus CDK1 site, whether this site is CDK1 dependent is not examined. Notably, the corresponding phosphomutants have modest effects and don't obviously account for the CDK1 inhibition phenotype, leaving it somewhat unclear whether it is under cell cycle regulation. We now provide a new figure 7 to address this point. As mentioned already above, using two different approaches (Western blot with our phospho-specific antibody on Baz and targeted mass spectrometry on Baz and PARD3 using), we now show in a new Figure 7 that CDK1 phosphorylates Baz-S180 and PARD3-S187 in vitro. Again, we cannot identify any experiment that would allow us testing whether S180 Baz is a direct target of CDK1 in vivo. The fact that we now report significant defects on Baz localisation in pIIa divisions, strongly suggests functional relevance and CDK1 seems a plausible kinase based on the new in vitro results.

      The observation that S180 phosphorylation appears unique to asymmetrically dividing cells is very curious, but this observation is not followed up extensively. Again phenotypes of phosphomutants are quite modest, and while one can propose models to rationalise the phenotypes observed, these models are not fully explored. As mentioned above, we now show that Baz-S180 phoshorylation is not strictly ACD-specific and changed the title accordingly. We also have new data showing that the S180 phosphomutants of Baz have localisation defects in mitotic pIIa divisions (new figure 6). Therefore, this phosphorylation event on Baz can be linked to Baz’s cortical localisation and interestingly shows context dependency.

      The findings that human Par3D can be phosphorylated by CDK1 in vitro do not add much particularly as they obtain a very large number of putative sites raising questions of specificity, the sites are not validated, and an S180 equivalent site was not identified. We agree that this has been a weakness which we feel we have addressed. We paste here the answer already provided above when replying to reviewer #1.

      We initially attempted to purify both full length Baz and human PARD3 but only managed to purify small amounts of PARD3, which is why our phospho-proteomics analysis was limited to human PARD3. To circumvent these difficulties, we instead purified a smaller N-terminal fragment of Baz and PARD3, which was successful for both proteins and gave us much higher quantities of sample for analysis. Using two different approaches (Western blot with our phospho-specific antibody on Baz and phosphor proteomics on Baz and PARD3 using mass spectrometry), we now show in a new Figure 7 that CDK1 phosphorylates Baz-S180 and PARD3-S187 in vitro.

      References

      CORSON, F., COUTURIER, L., ROUAULT, H., MAZOUNI, K. & SCHWEISGUTH, F. 2017. Self-organized Notch dynamics generate stereotyped sensory organ patterns in Drosophila. Science, 356.

      HANNAFORD, M. R., RAMAT, A., LOYER, N. & JANUSCHKE, J. 2018. aPKC-mediated displacement and actomyosin-mediated retention polarize Miranda inDrosophilaneuroblasts. eLife, 7__,__ 166.

      SKOUFIAS, D. A., INDORATO, R. L., LACROIX, F., PANOPOULOS, A. & MARGOLIS, R. L. 2007. Mitosis persists in the absence of Cdk1 activity when proteolysis or protein phosphatase activity is suppressed. J Cell Biol, 179__,__ 671-85.

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      Referee #2

      Evidence, reproducibility and clarity

      Cell polarization in dividing cells, including stem cells, is typically coupled such that polarity can inform the architecture, orientation, and/or asymmetry during cell division. In Drosophila neural stem cells (neuroblasts/SOP), Par polarity is coupled to the cell cycle, but the nature of this coupling remains unclear. In this work, Loyer and colleagues report on impacts of CDK1 inhibition on Bazooka/Par3 localization and basal fate determinant localization. They provide evidence for a novel phosphorylation site that appears unique to asymmetrically dividing cells and may be involved in regulation of asymmetric division. Finally, they show that CDK1 can, at least in principle, phosphorylate human Par3 in vitro.

      Overall, the major claims of the abstract appear supported by the experimental work; however, we think the title overstates the overall conclusions that can be drawn from the work.

      Major comments:

      1. The major claim of the paper is the role of specific phosphorylation of S180 in asymmetrically dividing cells in polarization and sensory organ formation, which relies heavily on interpretation of S180A/D phosphomutants. The experiments are carefully performed and quantified, and are consistent with the conclusions drawn. However, we wondered if it possible that the phenotypes are not linked to phosphorylation (the authors acknowledge this in the Discussion)? In other words could the A/D mutants simply be weak Baz mutants? This could this potentially explain the extra-SOP phenotype if Baz function is generally altered, especially given that it is difficult to rationalise a role for SOP-specific phosphorylation in the processes that specify SOP cells in the precursor epithelial cells. The authors speculate that these early precursors may exhibit also phosphorylation, but this isn't examined. Chasing this down seems key to support the core titular claim of the paper.
      2. Implicit in the core message of the paper is the elucidation of CDK1 regulation of polarity and specifically Baz. However, the connection between CDK1 and S180 (and Baz regulation overall) is relatively tenuous in this work. First, the S180A mutant does not phenocopy CDK1 inhibition with respect to basal determinant phenotypes, though obviously CDK1 may be more pleiotropic. Second, whether the CDK1 inhibition phenotype is linked to any effect on Baz/PAR behaviour is not really explored. Third, they do not test whether S180 phosphorylation is CDK1-dependent.
      3. The method for quantifying domain signal only references prior work and should be described in this work. From our search of the cited reference, it appears to be peak signal intensity at a user specified point on the cortex. While this does not undermine the core findings as presented, it may not capture additional features that may be informative (domain size, fluorescence distribution, total signal etc.). For example domain coalescence would imply smaller, brighter domains, but similar total protein amounts, which appears to be the case from images, but isn't quantified per se.
      4. The phosphospecific antibody signal is relatively weak, leading to relatively low signal to noise, which could compromise the ability to detect phospho-S180 in non-asymmetrically dividing cells or generally in cells in which Baz is not polarised and thus signal would be diffused around the cell rather than concentrated. Similar caveats could also apply to the lack of signal in interphase cells, where Baz may be less enriched at the cortex and not polarized. We are inclined to believe the authors conclusions, particularly given their examination of multiple cell types and tissues. However, it is a potential caveat as it may be most visible in polarised cells where it is asymmetrically enriched.
      5. Examination of in vitro phosphorylation of human Par3D (Figure 6) seems out of place and does not add much. It is human, not Bazooka. They reveal 30 sites, 18 of which in both replicates, but most are not obvious CDK sites and the S180 equivalent site is missing. None of these sites is validated in vivo, at least in this work.

      Minor comments:

      • Figure 1: Uses metaphase arrested cells, presumably colcemid, but colcemid is only noted in Figure 2.
      • Figure 2A: Scale bar is truncated
      • Figure 2A: Example images of control neuroblasts could be useful to readers.
      • Figure 2G' vs H': Because G' has two panels and H' has only one, we often confused the PKC and Mira box plots when comparing to Numb. Perhaps Mira could be in a separate sub panel or be more closely juxtaposed with Numb?
      • Whereas both Numb/Mira were examined in CDK1(as), only Mira is reported for the S180A/D experiments. Is there a Numb phenotype as well?
      • The discussion of the notch / Baz phenotypes (Figure 5) is rather complicated and a bit difficult to follow.
      • Figure 5A: captions should indicate that RFP RNAi is depleting Baz.
      • Box plots are used, but not described. i.e. outliers seem to be marked, but criteria unclear. Mean vs median, etc.

      Some grammatical mistakes:

      • Title: neuroblast (no 's'),
      • Page 1: Cell fate difference(s?) in the resulting daughter cells
      • Page 4: (As) CDK1 inhibition with 10 μM 1-NA-PP1 prevents neuroblasts from cycling and causes metaphase- arrested neuroblasts to slip out of mitosis. (Reword)
      • Page 6: increased levels of basal fate(no 's') determinants

      Significance

      The links between cell cycle and cell polarity are clearly important and remain poorly understood. Hence, the work addresses key conceptual/mechanistic questions relevant to our fundamental understanding of stem cell biology and regulation of polarity and asymmetric cell division. In our opinion, there are clearly some interesting observations in the manuscript, the experiments are performed carefully, and the data are generally well described. That said, overall, the work seems somewhat premature.

      1. The direct impact of CDK1 on Baz behaviour remains somewhat unclear. The authors do a good job of limiting the concentration of inhibitor to decouple effects of cell cycle progression from CDK1 levels per se, but this does potentially impact the strength of the phenotypes they can detect and hence the observed phenotypes are relatively minor. Note that driving cells out of mitosis with stronger CDK1 inhibition clearly impacts Baz localization, so the 'real' effect of CDK1 inhibition on Baz could be stronger than reported here. It is also unclear whether the phenotypes observed are directly linked to CDK1 regulation of PAR polarity or an indirect effect of cell cycle control of other processes. The authors' suggestion that it could be related to defects in cortical actin organization, which is known to be cell cycle controlled, seems most likely, but neither this or other models are explored further.
      2. Using phosphospecific antibodies, they report on a novel putative CDK1 phosphorylation site, but aside from looking like a consensus CDK1 site, whether this site is CDK1 dependent is not examined. Notably, the corresponding phosphomutants have modest effects and don't obviously account for the CDK1 inhibition phenotype, leaving it somewhat unclear whether it is under cell cycle regulation.
      3. The observation that S180 phosphorylation appears unique to asymmetrically dividing cells is very curious, but this observation is not followed up extensively. Again phenotypes of phosphomutants are quite modest, and while one can propose models to rationalise the phenotypes observed, these models are not fully explored.
      4. The findings that human Par3D can be phosphorylated by CDK1 in vitro do not add much paritcularly as they obtain a very large number of putative sites raising questions of specificity, the sites are not validated, and an S180 equivalent site was not identified.

      In summary, the individual findings of this work are interesting and generally solid. Each could be followed up to provide mechanistic insight into cell cycle- or cell type-dependent regulation of Par polarity. However, in their current state, the results seem more like a loosely connected set of observations.

      Expertise: Cell polarity and asymmetric cell division

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      Referee #1

      Evidence, reproducibility and clarity

      The coupling between cell polarity and cell cycle progression is an important aspect of symmetric and asymmetric cell division. Although there are several examples of cell cycle kinases phosphorylating polarity proteins, it has been difficult to assess the importance of these on cell division due to the strong and pleiotropic effects of manipulating these kinases. Here, the authors generate an analogue-sensitive allele of cdk1 in flies to tackle this question in neuroblasts (NBs) and sensory organ precursors (SOPs), two well characterised examples of asymmetric cell divisions. They show that partial Cdk1 inhibition (which still allows cell cycle progression) does not block Bazooka (PARD3 in mammals) polarization in NBs, but prevents coalescence of the Baz crescent, which has previously been shown to be an actomyosin-based process. They further identify a Cdk1 consensus site on Baz (S180) for which they generate a phospho-specific antibody, allowing them to show that this site is specifically phosphorylated in dividing NBs and SOPs. Although mutations at this site do not recapitulate the effect of Cdk1 on Baz coalescence, they do delay Miranda polarization in NBs and affect lateral inhibition and asymmetric cell division of SOPs. Finally, the authors show that human PARD3 can also be phosphorylated by Cyclin B/Cdk1 in vitro.

      Major comments:

      1. Figure 2A: it would be good to show that polarization of Baz::GFP in consecutive divisions is maintained in cdk1as2 animals in the absence of 1-NA-PP1.
      2. The interpretation of the observed SOP phenotypes is complicated by the uneven expression of the pnr-GAL4 driver and the fact that it is expressed in epithelial cells rather than just SOPs. The authors could express their control and mutant Baz constructs under the control of neurP72-GAL4. It is not likely they would be able to deplete endogenous Baz as they have done in NBs, as neurP72-GAL4 is expressed too late to deplete most proteins before SOP division, but they could at least look at localization of the mutants and any possible gain-of-function phenotypes.
      3. The authors speculate that Baz phosphorylation during lateral inhibition may be the reason for the observed excess specification of SOPs in the S180 mutants. This could easily be tested by looking at their antibody staining at earlier stages in the notum.

      Significance

      This work advances our knowledge of the coupling between the cell cycle and cell polarity during cell division, and shows that Baz/PARD3 receives inputs from Cdk1 that is specific to asymmetrically dividing cells. The reagents generated here (cdk1as2 and phospho-specific antibody) will also be of interest to the field. The data are convincing and well documented. This work should be of broad interest to the stem cell and developmental biology fields. Above are a few suggestions to improve the manuscript.

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      Reply to the reviewers

      Point-by-point response to reviewers’ comments:

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

      Major comments: 1. Previous studies using HDR and donor templates have shown that mutating the PAM sites in donor templates can enhance repair efficiencies. It would be helpful to add a discussion about the fact that SpRY does not have a PAM sequence that could be mutated and the potential consequences on repair efficiency.

      We find that one mismatch in the target sequence (i.e. albino wt v. albino[b4]) is enough to completely abolish activity of SpRY. We have stated this more clearly in the manuscript.

      It is also unclear how the template for the induction of mutations in kcnj13 was chosen. From the experiment with SpRY it seems that an HDR template equivalent to the sequence of the sgRNA target strand was most efficient, while in this experiment the alternative strand was used. An explanation should be added to the text.

      Oligonucleotides corresponding to both DNA strands were tested, only one of them yielded positive results. We do not know the mechanistic basis for this finding, but amended the manuscript accordingly.

      Minor comments: 1. It is not directly evident what the difference between the OP2 and OP2* sgRNA is. A short explanation would help clarify this and make it easier for the reader to understand.

      OP2 (now re-named: U6) targets the wild type sequence, whereas OP2* (now: U6*) targets the albino[b4] sequence, which has one mutation leading to a premature stop codon. As this mutation is in the target region, we need adapt the sgRNA accordingly. We have stated this in the text more clearly now.

      Similarly, it would be helpful to add the length of the different donor templates to Figure 2.

      We have added the lengths of the oligonucleotides (in nt) to Fig.2.

      While the PAM sequences and their difference between guides is discussed for two of them (OP2 and U5), it would be helpful to add the PAM sequences for all guides to Table 1 or figure 1.

      We have added a table with all target sites including PAM sequences.

      For people who are unfamiliar with the obelix phenotype/pigment pattern, it would be helpful to add a picture of an obelix mutant to Figure 4, so they would know what the phenotype would look like and how obvious it would be.

      We have added a panel showing an obelix mutant fish to Fig.4.

      Reviewer #2:

      While every new and improved method to generate stable allele swap lines is greatly needed in the community, the results are not sufficient to convince me that the new version is leading to better success than previous methods. While they found one successful founder event, a single one is not enough to calculate efficiencies. Could just be luck that they got one. It is already known that HDR is very locus-specific, so maybe the locus they chose is such a locus.

      This comment is difficult to address; while we found that the improved HDR method we present in the paper leads to better success for the repair of the albinob4 mutation and the one specific allele exchange we performed, we, of course, agree that one founder event is not enough to calculate efficiencies. However, we would like to maintain that one founder will in almost all cases be better than none. We also think that the locus we chose, kcnj13, is not a particularly lucky one yielding positive results easily, because it used to be refractory to editing following published protocols for a long time.

      Overall, the paper suffers from the problem that the authors initially set out to investigate a specific genetic mutation in zebrafish but, upon observing that the resultant mutant exhibited no discernible phenotype, they shifted their focus towards refining and showcasing their methodological approach. This dual identity results in a study that, while informative, lacks the comprehensive exploration typical of dedicated research papers or the focused, technical depth one might expect from methodological publications.

      Overall, we feel that there might be a slight misunderstanding here. The reviewer states that ‘… the paper suffers from the problem that the authors initially set out to investigate a specific genetic mutation in zebrafish but, upon observing that the resultant mutant exhibited no discernible phenotype, they shifted their focus…’, which is quite the opposite of what actually lead to the writing of the manuscript. We had already suspected that the single amino acid difference in the protein sequence between the two sister species might not be responsible for the observed functional divergence of the gene. We had also already found allele-specific differences in expression levels in hybrids, which make cis-regulatory evolution more likely. So, the null-hypothesis of our experiments was that both protein sequences would be functionally equivalent. However, as we had difficulties with the allele exchange due to low HDR efficiencies we needed to improve the method before we could definitively show this.

      We have re-written some parts of the manuscript to make it clearer that we do not claim to have invented a method for HDR that is superior to all previously published ones. Rather, we think that we offer a variation of these published methods, which other researchers, struggling with low editing efficiencies (as we did), might want to try. What we do show in the manuscript is that the addition of an aNLS to Cas9 or SpRY leads to an increase in the efficiency in the generation of albino k.o. alleles and in HDR to repair the albinob4 mutation (see Fig. 3). If this will also be the case when editing other genes in the zebrafish genome needs to be investigated, but is clearly beyond the scope of this manuscript. We investigated one other locus in the zebrafish genome and could get one founder fish for the allele exchange in kcnj13, as opposed to zero we obtained with previously tried methods (conventional Cas9 with long or short donor-DNAs, prime editing). One advantage of ’our method’ is the simplicity of implementation. The Cas9 and SpRY proteins are easy to express in E. coli and the purification using two affinity tags is highly efficient resulting in samples of sufficient purity and high enough concentration for immediate use in injection experiments. So, we think that other researchers could easily try out the aNLS tagged proteins without changing much else of the protocols they usually employ for genome editing in zebrafish.

      Reviewer #3:

      Major comments: • The Cas9SpRY has been previously analyzed for the efficiency in zebrafish (Liang et al, Nat Comm 2022). This becomes only clear after reading the discussion. A comparison of these previously published SpRYCas9 proteins containing the bpNLS is missing, also a comparison of the efficiencies. The same locus (Albino) has been used in the study, are the guides identical? This study has not efficiently put the results in perspective of published results of the afore mentioned paper. And it seems that addition of the aNLS is not providing any benefit, which is good to know for the community.

      We have added information to the introduction making it clear that the SpRY protein has previously been used in zebrafish. We also expanded the discussion and added more details comparing our results to previously published ones. However, this comparison is not always easy because the evaluation methods are different, sequencing v. phenotypic read-out. While the addition of the aNLS to the SpRY protein did not significantly enhance the (already high) k.o. efficiency for the albino locus, it did result in a significant boost of the repair efficiency of the albino[b4] mutation (see Fig.3C). Therefore, we think that the general statement it ’is not providing any benefit’ might not be entirely accurate. We think that the use of SpRY could be beneficial in some instances, but it must be assessed one a case-by-case basis.

      • The HDR numbers is relying on 1 germline founder fish and might not be representative. More loci and higher numbers would be desirable.

      We completely agree with the reviewer on this point. However, we feel that this is beyond the scope of this manuscript; we are looking forward to seeing other labs using the aNLS tagged proteins and finding out about their experiences.

      • The allele exchange in Obelix is an interesting approach to use HDR but should be explained a little bit more. The motivation behind this experiments rains unclear.

      We have added some information on obelix to provide more context

      minor points: • All y axes require a labeling: % of what?!

      We have changed the labels to % of larvae.

      • When showing the specific classes of phenotpes the reader would benefit if the classes were written directly into the fish picture rather than using B, C, D, etc...

      We have added this information directly to the pictures.

      • OP2 should be called U6 to avoid unnecessary confusion, or is there anything special about it, why does it have another name?

      We have changed OP2 to U6, as requested. The naming was completely due to historic reasons, there is nothing special about this target site / sgRNA.

      • Differences in efficiency could potentially attributed to the PAM sequence as discussed. Please list the different PAM sequences and discuss in more detail. Why are so many gRNAs not efficient in the KO approach (Figure1)?

      We added a table with the different target sites and the corresponding PAM sequences.

      While we cannot provide a satisfactory explanation for the low efficiencies of five from six sgRNAs in our experiments, we notice that in the published data from Liang et al., 2022, a sizeable proportion of the tested sgRNAs with the SpRY protein also show low efficiency or no activity at all (see Fig. 2B, Liang et al., 2022, https://doi.org/10.1038/s41467-022-31034-8). This phenomenon is likely to be locus-specific and more data will be needed to come to a mechanistic understanding. We also do acknowledge that there is the possibility that our assay, the albino mutant phenotype in larvae, is likely not as sensitive as sequencing-based approaches. For one, we rely on the bi-allelic k.o. of the target gene, and we only assess a small proportion of all larval cells. However, we think that our approach with a phenotypic read-out is still valid, as it will reflect the practical requirements for an HDR method in many laboratories, where low efficiencies will result in no or weak and variable F0 phenotypes and in very low probabilities for germ-line transmission, which in most cases researchers will want to avoid.

      • Line 217: correct co.injected to co-injected

      done

      The scientific advancement is not clear. Readers would benefit if the advancement can be worked out better. Most readers would like to decide if it is worth changing their Cas9 design for genome editing in zebrafish and what efficiencies to expect.

      We have modified the manuscript to better convey the scientific advancement it presents. We think it lies mainly in the fact that no other changes to the design of genome editing experiments is required, but to exchange the Cas9 protein usually employed for the aNLS tagged proteins. Both proteins, aNLS tagged Cas9 or SpRY, can easily be produced and purified in the lab following standard protocols. In less than one week enough protein for several hundred or thousands of injection experiments can be purified and aliquoted. We suggest that everybody uses their tried and tested method to produce knock-in alleles, and, as long as it works for them, don’t change it. If, however, the efficiencies are too low to get the desired allele, it will be very quick and simple to try our method. This is what we wanted to demonstrate with the editing of the obelix locus. In all cases we can envisage identifying one founder fish will be considerably better than not finding a single one.

      Reviewer #4:

      Major

      1. The authors use a mutated version of the widely used Cas9 protein from Streptococcus pyogenes, SpRY which basically does not rely on a PAM motif adjacent to the sgRNA target site. While this has certain advantages which are properly described, lowering stringency also comes with disadvantages, i.e. enhanced off target site activity. While assessing these is of the scope of the paper, these considerations should be properly discussed. Under which circumstances do the authors suggest to use SpRY and at which the conventional Cas9 or TALENs?

      This is an important point and we have expanded on this. We think that SpRY offers a possibility to target sites that are not accessible to conventional Cas9, but it should not be expected to work as well as Cas9 for all loci (see also Liang et al., 2022 Fig.2). Whether the reduced stringency leads to more off-target effects is unclear; we did not experience higher rates of deformations or mortality in the injected larvae. This is, admittedly, a very crude measure for potential off-target effects, but is also in good accordance with the findings of Liang et al., 2022. In contrast to this, all labs that produce their own Cas9 protein could easily switch to the aNLS tagged version. It does not seem to have any disadvantages.

      The authors designed 6 guides against slc42a2/alb according to the text and to Fig1 U1-U5+OP. Table 1 contains 16 sequences fitting these criteria. Which ones where used? Why are they named differently (U vs OP)? What method was used to design them? Does their design include PAM requirements? Have these guides been used previously and confirmed to work efficiently using CAS9? If the authors intend to provide an improved method that can widely and easily be adopted by other labs, they should put special emphasis in describing the procedure properly possibly including a supplemental figure detailing the workflow.

      We have added a table with the target sites and the corresponding PAMs (see response to reviewer #1). The oligonucleotides shown in Table 1, which is now Table 2, are the ones used to generate the plasmid templates for the in vitro transcription of the sgRNAs.

      The naming of the target sites, which was solely due to ’historic’ reasons, has been changed to U1 - U6.

      They were designed (basically by hand) to allow in vitro transcription with T7 RNA polymerase (i.e. 5’ with GG), to have a G/C content of 50 - 65% and to represent a variety of different PAM sequences, that should potentially result in high activity (according to the data published by Walton et al., 2020 DOI: 10.1126/science.aba8853).

      These sgRNAs could not be tested with Cas9 as they lack the PAM (NGG) required for activity of this protein.

      We think that the main advantage of ’our’ method lies in the fact that aNLS-Cas9 (and aNLS-SpRY) can easily incorporated into the experimental procedures and workflows already in place in other laboratories. There is no need to follow exactly our protocol, eg. regarding sgRNA production or target site selection. We think that we showed that SpRY can be as effective as conventional Cas9, but not for all target sites, and that the addition of an aNLS sequence to Cas9 or SpRY is beneficial for genome editing in zebrafish, even when the aNLS is not combined with a myc-tag, as is the case shown by Thumberger et al., 2022, i.e. hei-tag.

      The authors use a recessive pigment mutant (albino) to validate and quantify precise genome editing by HDR applying their toolbox. This is very clever and probably the most robust readout possible. The authors found that adding an aNLS to CAS9 and SpRY improves rescue efficiency, possibly also for germ line transmission. The authors should compare their efficiency for accurate editing with that of other papers in the field to allow for a better comparison.

      We have now included a more detailed comparison of our results with previously published data in the discussion. However, this comparison is not always easy because the evaluation methods are different, sequencing v. phenotypic read-out. In terms of accuracy of the methods, we found that the majority of the HDR events we detected were associated with additional mutations. Some of these were possibly due to synthesis errors in the donor oligonucleotides, which might be alleviated by different purification methods. Other mutations, however, most likely occurred during cellular repair of dsDNA breaks and are therefore not easily avoided, unless double strand breaks are avoided, which would be the case if base editors are used. However, with base editors it is so far not possible to introduce every possible DNA change, making HDR methods still useful.

      Minor:

      1. Fig.1A: Please indicate orientation of the gene

      done

      Line 168: ... tested sperm... à Method not explained in the methods section

      The sperm samples extracted from anaesthetized males were used in exactly the same way as larvae were in other genotyping experiments; as is mentioned in the methods section. We have re-phrased this section a bit to make it clearer that we used larvae or sperm in exactly the same way for genotyping.

      Kcnj13 editing. Explain obelix pigment phenotype to the non expert reader in pigmentation possibly illustrating D. aesculapii. This is a very powerful method allowing such comparisons, however it is not properly explained.

      We have added some information on the obelix phenotype and included a panel of a mutant zebrafish in Fig.4.

      Line 130: 'hei-tag' not properly explained

      The hei-tag, published by Thumberger et al., 2022, consists of a myc-tag, a flexible linker and an aNLS in exactly that order. We have added some more details on the hei-tag to the text.

      The co-editing of a restriction site for later identification of the edited allele is clever. However precise editing should be performed carefully and include splice site prediction algorithms to avoid enabling ectopic splice sites by silent mutagenesis. Also, an example of the analysis would be benefitial to Fig.4 or in the supplement.

      We agree that this is an important point. We originally designed the edit in a way that would not result in the generation of a strong ectopic splice site by avoiding the creation of AG or GT di-nucleotide sequences.

      We now also performed analysis with spliceator (http://www.lbgi.fr/spliceator/), a splice site prediction tool using convolutional neural networks, which confirmed that no ectopic splice site should be generated.

      We could include this into a supplementary figure, if deemed necessary.

      The manuscript is well written, the data are presented in an accessible way and the results look convincing. The work clearly shows a path to improvement of a fundamental method of gene editing in zebrafish and other species and clearly provides essential data on the topic. However, some aspects of the work are not properly described for the non-expert. Given the nature of the work which aims to improve an important, established method a more precisely described workflow in form of a table and workflow chart would certainly help the reader to focus on the essentials of the procedure.

      As mentioned above, we think that it will be easy for other labs to incorporate our improvements into their existing protocols by exchanging normal Cas9 for aNLS-Cas9 or aNLS-SpRY. There should not be the need to strictly follow our protocols, e.g., for target site selection or sgRNA synthesis. The proteins can easily be expressed in bacteria and purified by standard methods using the His- and Strep-tags, as we published previously for conventional Cas9 (Podobnik et al. 2023).

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      Referee #4

      Evidence, reproducibility and clarity

      In this manuscript, Dorner, Stratmann et al. developed a new variant of the homologous directed repair mediated genome editing technique in zebrafish using modified Cas9 proteins. They focus on the SpRY Cas9 protein variant, which offers a more relaxed PAM requirement for gene targeting. The requirement of a PAM has particularly hampered the feasabilty of HDR in the zebrafish model as the genomic sites of interest often do not meet the PAM requirements for conventional Cas9. Their improved method enhances the versatility of CRISPR/Cas methods in zebrafish, a crucial model organism in biomedical research. The authors also demonstrate that integrating an artificial nuclear localization signal (aNLS) into Cas9 variants not only improves gene knockout efficiency but also boosts homology-directed repair (HDR) frequency. This advancement allows for more precise genetic modifications, including single base pair changes, offering significant potential for research and other applications in genetics.

      The manuscript is well written, the data are presented in an accessible way and the results look convincing. The work clearly shows a path to improvement of a fundamental method of gene editing in zebrafish and other species and clearly provides essential data on the topic. However, some aspects of the work are not properly described for the non-expert. Given the nature of the work which aims to improve an important, established method a more precisely described workflow in form of a table and workflow chart would certainly help the reader to focus on the essentials of the procedure.

      Major comments:

      1. The authors use a mutated version of the widely used Cas9 protein from Streptococcus pyogenes, SpRY which basically does not rely on a PAM motif adjacent to the sgRNA target site. While this has certain advantages which are properly described, lowering stringency also comes with disadvantages, i.e. enhanced off target site activity. While assessing these is of the scope of the paper, these considerations should be properly discussed. Under which circumstances do the authors suggest to use SpRY and at which the conventional Cas9 or TALENs?

      2. The authors designed 6 guides against slc42a2/alb according to the text and to Fig1 U1-U5+OP. Table 1 contains 16 sequences fitting these criteria. Which ones where used? Why are they named differently (U vs OP)? What method was used to design them? Does their design include PAM requirements? Have these guides been used previously and confirmed to work efficiently using CAS9? If the authors intend to provide an improved method that can widely and easily be adopted by other labs, they should put special emphasis in describing the procedure properly possibly including a supplemental figure detailing the workflow.

      3. The authors use a recessive pigment mutant (albino) to validate and quantify precise genome editing by HDR applying their toolbox. This is very clever and probably the most robust readout possible. The authors found that adding an aNLS to CAS9 and SpRY improves rescue efficiency, possibly also for germ line transmission. The authors should compare their efficiency for accurate editing with that of other papers in the field to allow for a better comparison.

      Minor comments:

      1. Fig.1A: Please indicate orientation of the gene

      2. Line 168: ... tested sperm...  Method not explained in the methods section

      3. Kcnj13 editing. Explain obelix pigment phenotype to the non expert reader in pigmentation possibly illustrating D. aesculapii. This is a very powerful method allowing such comparisons, however it is not properly explained.

      4. Line 130: 'hei-tag' not properly explained

      5. The co-editing of a restriction site for later identification of the edited allele is clever. However precise editing should be performed carefully and include splice site prediction algorithms to avoid enabling ectopic splice sites by silent mutagenesis. Also, an example of the analysis would be benefitial to Fig.4 or in the supplement.

      Significance

      The manuscript is well written, the data are presented in an accessible way and the results look convincing. The work clearly shows a path to improvement of a fundamental method of gene editing in zebrafish and other species and clearly provides essential data on the topic. However, some aspects of the work are not properly described for the non-expert. Given the nature of the work which aims to improve an important, established method a more precisely described workflow in form of a table and workflow chart would certainly help the reader to focus on the essentials of the procedure.

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      Referee #3

      Evidence, reproducibility and clarity

      The manuscript "efficient genome editing using modified Cas9 Proteins in zebrafish" by Dorner et al. is using the modified SpRY Cas9 protein with the addition of an artificial nuclear localization sequence (aNLS) and compares its efficiency in the generation of making KO animals with other Cas9 proteins and its use to generate a HDR mediated KI in zebrafish. The paper shows that the SpPY Cas9 works efficiently and that addition of aNLS can increase the HDR mediated efficiency in one locus.

      Major comments:

      • The Cas9SpRY has been previously analyzed for the efficiency in zebrafish (Liang et al, Nat Comm 2022). This becomes only clear after reading the discussion. A comparison of these previously published SpRYCas9 proteins containing the bpNLS is missing, also a comparison of the efficiencies. The same locus (Albino) has been used in the study, are the guides identical? This study has not efficiently put the results in perspective of published results of the afore mentioned paper. And it seems that addition of the aNLS is not providing any benefit, which is good to know for the community.

      • The HDR numbers is relying on 1 germline founder fish and might not be representative. More loci and higher numbers would be desirable.

      • The allele exchange in Obelix is an interesting approach to use HDR but should be explained a little bit more. The motivation behind this experiments rains unclear. minor points:

      • All y axes require a labeling: % of what?!

      • When showing the specific classes of phenotpes the reader would benefit if the classes were written directly into the fish picture rather than using B, C, D, etc...

      • OP2 should be called U6 to avoid unnecessary confusion, or is there anything special about it, why does it have another name?

      • Differences in efficiency could potentially attributed to the PAM sequence as discussed. Please list the different PAM sequences and discuss in more detail. Why are so many gRNAs not efficient in the KO approach (Figure1)?

      • Line 217: correct co.injected to co-injected

      Significance

      The scientific advancement is not clear. Readers would benefit if the advancement can be worked out better. Most readers would like to decide if it is worth changing their Cas9 design for genome editing in zebrafish and what efficiencies to expect.

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      Referee #2

      Evidence, reproducibility and clarity

      The manuscript: Efficient genome editing using modified Cas9 proteins in zebrafish by Dorner and Stratmann et al. provides a putative improved method of modifying single base pairs in the genome of zebrafish through homology-directed repair. The authors use a modified Cas9 protein called SpRY in zebrafish. The SpRY protein has fewer restrictions on the PAM sequence it requires, which broadens its genome targeting potential. The paper presents experiments on zebrafish using SpRY for efficient genome editing. However, not all target sites are equally efficient, and the authors suggest that individual sequences may need to be evaluated on a case-by-case basis.

      The paper also explores the benefits of using an optimized artificial nuclear localization signal (aNLS) for the Cas9 protein, which significantly increases genome editing efficiency in zebrafish. Using this improved method, the researchers demonstrate precise editing of the kcnj13 gene in zebrafish to match the sequence found in Danio aesculapii, their closest sister species. The edited zebrafish do not show any visible phenotypic changes, suggesting that the Kcnj13 proteins from both species are functionally equivalent.

      While every new and improved method to generate stable allele swap lines is greatly needed in the community, the results are not sufficient to convince me that the new version is leading to better success than previous methods. While they found one successful founder event, a single one is not enough to calculate efficiencies. Could just be luck that they got one. It is already known that HDR is very locus-specific, so maybe the locus they chose is such a locus.

      Significance

      Overall, the paper suffers from the problem that the authors initially set out to investigate a specific genetic mutation in zebrafish but, upon observing that the resultant mutant exhibited no discernible phenotype, they shifted their focus towards refining and showcasing their methodological approach. This dual identity results in a study that, while informative, lacks the comprehensive exploration typical of dedicated research papers or the focused, technical depth one might expect from methodological publications.

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      Referee #1

      Evidence, reproducibility and clarity

      Summary:

      The manuscript "Efficient genome editing using modified Cas9 proteins in zebrafish" by Dorner et al. describes the utility of combining Cas9 variants with an alternative NLS to improve the efficiency of induction of single base pair changes in zebrafish through HDR. The authors confirm findings from previous studies, that the SpRY variant of Cas9 can be used in zebrafish to induce knockouts at efficiencies similar to Cas9 and additionally show the ability of SpRY to induce point mutations via HDR. They further confirm other studies that showed that the addition of an artificial NLS can significantly increase targeting efficiency of Cas9 in zebrafish. They extend their studies to show that the increased efficiency through addition of this alternative NLS also enhances HDR mediated induction of single base-pair changes using donor templates for both Cas9 variants. Most conclusions of the paper are well supported by the presented data and the experiments are explained in sufficient detail for replication. The paper could benefit from a few modifications/additions to the text to clarify a few details.

      Major comments:

      Previous studies using HDR and donor templates have shown that mutating the PAM sites in donor templates can enhance repair efficiencies. It would be helpful to add a discussion about the fact that SpRY does not have a PAM sequence that could be mutated and the potential consequences on repair efficiency. It is also unclear how the template for the induction of mutations in kcnj13 was chosen. From the experiment with SpRY it seems that an HDR template equivalent to the sequence of the sgRNA target strand was most efficient, while in this experiment the alternative strand was used. An explanation should be added to the text.

      Minor comments:

      1. It is not directly evident what the difference between the OP2 and OP2* sgRNA is. A short explanation would help clarify this and make it easier for the reader to understand.

      2. Similarly, it would be helpful to add the length of the different donor templates to Figure 2.

      3. While the PAM sequences and their difference between guides is discussed for two of them (OP2 and U5), it would be helpful to add the PAM sequences for all guides to Table 1 or figure 1.

      4. For people who are unfamiliar with the obelix phenotype/pigment pattern, it would be helpful to add a picture of an obelix mutant to Figure 4, so they would know what the phenotype would look like and how obvious it would be.

      Significance

      General assessment: Strength of the study are the use of multiple, independent injection experiments for each group to test guide and repair efficiency. Clear presentation of methods which will allow replication of experiments and also production of reagents. While the study clearly shows that SpRY does work for HDR mediated repair, only one specific repair template design (single stranded oligo) was tested. This study could be enhanced through testing of additional HDR template designs and a direct comparison of repair efficiency between Cas9 and SpRY.

      Advance: This study does provide a minor advance in our understanding of how the efficiency of Cas9 and its variants can be optimized and how these modifications can enhance repair efficiency. The use of the SpRY variant in zebrafish as well as the enhancement of Cas9 efficiency through the use of the aNLS has been shown before (Liang et al. 2022, Thumberger et al. 2022). Novelties in this study are the use of SpRY for HDR mediated repair and the improvement of the repair efficiency through the addition of the aNLS to SpRY and Cas9.

      Audience: The methods described in this paper will be of interest to the zebrafish and Medaka communities as well as people using HDR mediated repair for the induction of mutations.

      Expertise: I am a geneticist who has worked with the zebrafish model for over 20 years and uses CRISPR/Cas for genome editing in zebrafish routinely.

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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

      Genome-wide association studies (GWAS) were used to identify potential risk variants associated with amyotrophic lateral sclerosis (ALS), and a specific variant of GGNBP2 has emerged as a critical player, exhibiting increased expression, and prompting the authors to investigate its role in the disease progression.

      The study, focusing on Drosophila Ggnbp2 (dGgnbp2) in motor neurons, revealed crucial insights into its function. Loss-of-function experiments underscored the necessity of dGgnbp2 in motor neuron synaptic development. Strikingly, introducing a human transgene fully restored these phenotypes, demonstrating functional conservation between humans and flies. Contrary to expectations, overexpression of dGgnbp2 resulted in severe locomotor defects in adult flies, mirroring aspects of ALS pathology, suggesting a tight regulation for this protein in the control of NMJ function.

      The authors also suggest a role of the gene in regulating autophagy, as RNA-seq showed abnormalities in the expression levels of genes involved in autophagy when dGGNPB2 was mutated. Finally, they described a potential molecular mechanism through which GGNBP2 may regulate autophagy and that is by controlling phospholipid levels specifically PI(3)P.

      Understanding the cellular mechanisms, the study suggests dGgnbp2's role in regulating autophagy, a process frequently impaired in ALS, and both overexpression and depletion of dGgnbp2 led to altered levels of phosphorylated lipid PI(3)P, a vital component of autophagosomes. Add PI3K This comprehensive investigation provides compelling evidence that Ggnbp2 plays a pivotal role in motor neurons, exerting regulatory control over a cellular process commonly compromised in ALS. These findings also provide insights into the functional implications of the GGNBP2 variant and also open new avenues for potential therapeutic crucial pathways like autophagy and InR, offering a promising direction in ALS treatment.

      Major:

      The experiments outlined in this paper, which elucidate the function of the Ggnbp2 in the neuromuscular junction (NMJ), are compelling and crucial for characterizing a novel gene implicated in ALS. However, my primary concern revolves around the demonstration of the influential role of the Ggnbp2 in regulating autophagy and its responsiveness to insulin signaling.

      Indeed, the author should better analyze and also genetically demonstrate an interaction between Ggnbp2 and components of the insulin signaling pathway. For instance, analyzing PTEN (utilizing available mutants) could enhance the understanding of the pathway linking Ggnbp2 downstream of PIP2.

      The connections drawn in the paragraph regarding autophagy (paragraph title: dGgnbp2 is linked to autophagy in motor neurons) might be a bit tenuous for the described observations. In the end it seems to only suggest a link to autophagy without explicitly asserting that it drives autophagy. The authors have overlooked providing a clear explanation or speculation on the correlation between GGNBP2's regulation of autophagy and its impact on synaptic development. A more explicit emphasis, then, on whether a loss-of-function or gain-of-function is more pertinent to human disease is necessary.

      The authors should take advantage of the available Drosophila lines to elucidate the relative dependence of the autophagic flux controlled by Ggnbp2 and macroautophagy, using mutants or RNAi lines for Atg1, Atg5, and potentially Atg6/beclin, as these factors have been demonstrated to be relevant in neurodegenerative diseases, including ALS and Parkinson's.

      Furthermore, alternative approaches for testing InR activation exist, such as the widely employed tPH-GFP method (Britton et al., 2002) that could be used to implement the activation of Akt in NMJ.

      The observation that dGgnbp2 serves specific functions in the cytoplasm of motor neurons is particularly interesting, and further investigation to better understand this function would be valuable. Additionally, is this soluble form also identified in humans?

      Minor:

      Line 113-119: This does not seem relevant to the study. This is not discussed or investigated anywhere else in this work. However, I understand and appreciate the intent.

      Line 135-138/Figure 2L: The authors do not address the non-significant "continuous" data.

      Line 191: Define the age of young animals.

      Line 192: Why did the authors change to OK371-Gal4 promoter in the experiments in Figure 4.

      Line 192: The authors need to specify how young were the animals.

      Line 202: Is the human GGNBP2 expressed with OK6-Gal4 able to rescue the reduced motility of the d Ggnbp2null flies?

      Line 223: Typo, "to the" is repeated.

      Referees cross-commenting

      The comments I read are all feasible and in line with what I also suggest, and I accept them. What is not clear is how much time the authors need if they reply to all, which, of course, depends on how much deeper they decide to go to complete the characterization of GGNBP2 in autophagy and the relevance of InR/TOR signaling. This will also depend on the journal they decide for their final submission.

      Significance

      This study outlined in this paper rests on a robust experimental design and yields conclusive results. It shows strong evidence of a role of the GGNBP2 gene in ALS pathology. It provides clear evidence of a synaptic development defect as well as a locomotor dysfunction in mutants, building on its relevance in human pathology. It solidly proves a functional conservation between flies and humans. It then suggests a potential role in regulating autophagy. However, further experiments demonstrating the actual interaction between GGNBP2 and class I and III PI3K is needed to fully elucidate the mechanisms through which GGNBP2 controls autophagy.

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      Referee #2

      Evidence, reproducibility and clarity

      Kerwin et al. conducted a study on the function of dGgnbp2 and its role in motoneurons. There are some general oversights that make the paper less robust than it could be. Firstly, the connection between autophagy dysregulation and the autophagic defects shown in the last figures is not clear. Combining these two parts would add more value to the paper. Secondly, the actual connection to ALS - made by the authors throughout the study - is not very strong. The only link with ALS is mentioned at the beginning when it is stated that Futsch is a target of TDP-43 and later when the authors mention that autophagy is a key dysregulated pathway in ALS. Although this is true, there is no strong connection to ALS pathology. It would have been appropriate to measure TDP-43 mislocalization in the animals and see whether the Futsch decrease observed in both null and OE models is related to it, or whether TDP-43 aggregates.

      Figure 2: Although the results presented in Fig S3R-X suggest a possible reduction in dGgnbp2 protein, it would be more reliable to validate the knockout strategy used for this figure with a PCR or a WB. The same comment applies to Figure 3.

      Figure 5H: Why aren't the results with dGgnbp2 OE shown in the locomotion sets, but rather a het null + GGNBP2OE is reported? This does not match the groups represented in the previous panels of the same figure.

      Line 223 typo: In motor neurons, it was localized to the cytoplasm

      Figure 6: I suggest performing N/C fractionation and WB probing for V5 to better characterize protein localization. This data is relevant given results in the next figure.

      Figure 6I:To claim dGgnbp2 function is cytoplasmic, data on mutant alone needed (not in null background).

      Figure 7: The volcano plot shows that the over expression system and the insertion only exhibit similar genes, which suggests that most of the observed changes are due to the insertion alone. As we do not have a clear understanding of GGNBP2's function in the nucleus, we need more precise data on over expression.

      Figure 8: Autophagy experiments are very interesting, despite the lack of crucial data. While it is evident that autophagy dysregulation occurs due to dGgnbp2 dysregulation, it is unclear whether it is a direct cause of the pathology. This assumption can only be confirmed by conducting a few experiments. Firstly, auto-Nagy defects should be measured in rescue models such as the one presented in figure 5. Secondly, treatment should be administered to restore autophagic flux, such as rapamycin or Torin1, as these drugs are known to help in cases of autophagy dysregulation. Another experiment that could be conducted is the overexpression of key autophagic proteins, such as Atg8.

      Significance

      This study is unique as few studies have focused on this protein and none on its role in motor neurons. The experiments were well-conducted, with the proper controls in place. The authors clearly demonstrate the significance of balanced protein levels for proper synapsis development and optimal motor neuron performance. The study also evaluated RNA dysregulation in different models used in the previous section of the paper. The authors found that autophagy was one of the dysregulated pathways. They characterized the autophagic defects in these cells.

      The study would be of interest to a specialized audience since its potential translational implications.

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      Referee #1

      Evidence, reproducibility and clarity

      In this paper, Kerwin et al. investigate the role of the GGNBP2 in synaptic morphology and autophagy in motor neurons. Using Drosophila, the authors performed functional studies of GGNBP2, a putative nuclear protein which has been linked to ALS through GWAS. Through creating clean mutants using CRISPR, the authors found that the null mutants of the fly homolog of GGNBP2 (CG2182, a previously uncharacterized gene which they propose to name Ggnbp2) are viable and fertile, but exhibit motor defects in adult flies accompanied by synaptic phenotypes in the larval neuromuscular junction (NMJ). In addition, the authors show that overexpression of Ggnbp2 also cause behavioral and NMJ defects, which is significant for ALS studies since the variant associated with this condition seems to increase the levels of GGNBP2 based on eQTL studies. Interestingly, the human GGNBP2 was able to rescue the fly LOF mutant phenotypes, suggesting that they have conserved molecular functions. Surprisingly, while mammalian GGNBP2 has been suggested to function as a transcription factor and gain and loss of this gene seems to mildly alter the transcriptome in flies, the authors showed that majority of the endogenously expressed fly Ggnbp2 protein is found in the cytoplasm and that the predicted nuclear localization signal (NLS) is not required for its function in motor neurons. Finally, the authors performed some additional experiments to propose a functional link between this gene and autophagy, focusing on its potential regulation of PI(3)P and genetic interaction with a fly ortholog of TBK1, which have also been linked to ALS in human.

      Overall, I feel this work addresses an important question in the field and the genetics experiments have been conducted with rigor. This study somewhat lacks mechanistic insights (e.g. how does Ggnbp2 regulate PI(3)P and motor neuron function?) but there are a number of novel findings (e.g. first generation and characterization of the null mutant of Ggnbp2 in flies, showing that it's predicted NLS is not important) that makes this paper provide value to the literature and community in its current form. While I have several major and minor issues that I would like to see addressed the authors, I would be generally in favor of this paper to be published in an appropriate journal that targets readers with interests in human neurological disorders and Drosophila biology.

      Major Points

      Major #1: In Figs 5, 6 and S3, the authors demonstrated significant rescue of Ggnbp2 null phenotypes by overexpressing fly Ggnbp2 or human GGNBP2 protein using the GAL4/UAS system. However, data shown in Fig 3 and elsewhere reveals that overexpression of fly Ggnbp2 results in smaller bouton numbers and larger boutons. Regarding this...

      1A: Does overexpression of human GGNBP2 in a wild-type background show similar NMJ and motor behavioral defects as fly Ggnbp2?

      1B: It is quite surprising that the authors were able to rescue the null mutant NMJ phenotype using GAL4/UAS (in this case OK6-GAL4) system considering that overexpression of this protein seems to have a strong effect using this driver as well. Is this because they used the UAS-dGgpnb2::V5 as a heterozygous in FigS3, which is a condition in which the overexpression phenotype is not seen? If so, the genotype of FigS3 (and Fig3) should be matched with FigS4 (otherwise, it looks like the authors used homozygous of the UAS in FigS3).

      Major #2: To assess adult fly locomotor performance, the authors employed the negative geotaxis assay to measure their climbing activity (Fig4). While the data show that the flies with LOF or GOF of Ggnbp2 have age-dependent defects, it is possible that the effect is developmental, especially for the overexpression paradigm. Considering that ALS is considered to be an adult onset neurodegenerative disease, it would be valuable if the authors can perform a conditional overexpression study of Ggnbp2[OE-EPgy2] using the Gal80[ts] system in which the fly Ggnbp2 that is overexpressed post-developmentally (i.e. overexpression of this protein induced only after eclosion) can also have an age-dependent motor defect. Considering that the authors do not perform any synaptic studies in adults (i.e. all NMJ experiments are performed in the larva), such experiments will increase the value of this work in the context of ALS research.

      Major #3: The authors generated several of UAS-fly Ggnbp2 (V5 tagged with or without the NLS) and UAS-human GGNBP2 (Myc tagged). Regarding these...

      3A: Other than in Fig6A, the authors do not show their expression pattern in motor neurons. It would appreciate if the authors can provide an immunostaining image of the all three proteins in the cell body and neurons of flies when expressed using OK6 or OK371. This way, the readers can appreciate whether the human and fly proteins behave similarly, and whether the deletion of the predicted NLS alters the subcellular localization of the protein. I acknowledge that it may be already difficult to observe the wild-type Ggnbp2 in the nucleus so one may not see a major difference but it would be important to document these.

      3B: Considering that the Ggnbp2::V5 seems to show a punctate pattern, may be interesting to see if this signal overlaps with the Atg8a, PIP2 and 2xFYVE::GFP in the cell body or in the synapse.

      Minor points

      Minor #1: In line 62, "Given that 75% of genes..." needs a minor correction, as 77% is the the number of gene that is mentioned in the cited reference (77%). Perhaps the authors can say "Given that about 75% of genes...".

      Minor #2: In line 266, the title of this section is "dGgnbp2 is linked to autophagy in motor neurons" but the author only shows data regarding the genetic interaction between Ggnbp2 and ik2 (official gene name is IKKε in FlyBase) in this section. Although IKKε and its mammalian homolog TBK1 is known to regulate autophagy, these are kinases that are involved in other processes (e.g. cell proliferation, cell death, cell polarity) so the title is a bit of an overstatement. Since the connection to autophagy is more directly shown in subsequent sections, I would recommend modifying the title of this section (e.g. "dGgnbp2 genetically interacts with IKKε, an ortholog of mammalian TBK1"". Also, note that IKKε is orthologous to both TBK1 and IKBKE so this may need to be clearly mentioned in the text.

      Minor #3: In line 282, the loss-of-function (lof) allele for ik2[1] requires proper reference that experimentally showed that this is indeed a lof allele. Also, please change the 'ik2' nomenclature to 'IKKε' to match with the latest official gene name.

      Minor #4: In FigS2, can the author show where the predicted NLS of the fly protein is that they deleted in Fig6E so the readers can see how conserved this region is between the fly and human proteins?

      Minor #5: I personally feel that the section regarding "RNA-seq analysis of Ggnbp2" is a bit out of place. Currently, this follows the section that says Ggnbp2 is does not function in the nucleus, so it doesn't make much sense to perform RNA-seq experiment for something that you think primarily works in the cytoplasm if the goal of this assay was to find direct mechanistic targets. Perhaps the authors can consider showing moving this section to before the "dGgnbp2 functions in the cytoplasm of motor neurons" (and place Fig7 before Fig6) so you can use the fact that you didn't see much dramatic gene expression changes in the LOF/GOF mutants as a rationale of why you decided to question its nuclear requirements. Just a suggestion, but this may make your paper flow better.

      Significance

      Overall, I feel this work addresses an important question in the field and the genetics experiments have been conducted with rigor. This study somewhat lacks mechanistic insights (e.g. how does Ggnbp2 regulate PI(3)P and motor neuron function?) but there are a number of novel findings (e.g. first generation and characterization of the null mutant of Ggnbp2 in flies, showing that it's predicted NLS is not important) that makes this paper provide value to the literature and community in its current form. While I have several major and minor issues that I would like to see addressed the authors, I would be generally in favor of this paper to be published in an appropriate journal that targets readers with interests in human neurological disorders and Drosophila biology.

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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

      In this manuscript, the authors reveal the genetic basis for why two different null alleles of Fasiclin II (Fas2), a member of the Igg superfamily of cell surface proteins, result in very different phenotypes in the follicular epithelia of the developing Drosophila egg chamber. One null allele - Fas2G0336 - results in rare occurrences of follicular cells being found outside of and apical to the plane of the epithelia in mutant clones, whereas the other null allele - Fas2EB112 - results in frequent occurrences of cells apical to the plane of the epithelia in mutant clones. Using recombination, they map a second mutation on the Fas2EB112 chromosome and demonstrate that it is a known allele of another Igg superfamily protein member - Neuroglian (Nrg). Thus, the severe phenotypes associated with only one of the two Fas2 null alleles can be explained by the additional absence of Nrg function, supporting previous studies that, in the follicular epithelia, the functions of Fas2 and Nrg are overlapping and compensatory.

      The authors fully support this finding by several carefully done experiments, all of which are thoroughly described and nicely illustrated in the figures in the main body of the paper, with helpful information provided in the supplemental figures. Indeed, the authors explore a number of possible explanations for the phenotypic differences with the two null Fas2 alleles and their conclusion of there being a known mutation in Nrg on one of the two null chromosomes is supported by several independent approaches. No additional experiments are necessary, and the findings should be easily reproducible by others using the reagents described in the study.

      Minor point: On the second page of the results, the last paragraph starts with "The second chromosome" in the first sentence. This is a bit confusing - could be considered chromosome 2, when the authors do not mean chromosome 2. It would be better to refer to this as "The other chromosome generated by recombination".

      Referees cross-commenting

      The other two reviewers have picked up some minor issues that should be addressed by the authors (quantitation of the Western, labels on all figure panels, etc). These changes would definitely improve the manuscript and should be done. I'm not convinced that the overall findings are important for a significant part of the Drosophila community - seems more of a specialty audience who needs to know that there is a second mutation in Neuroglian on one of the Fas2 null chromosomes that are available through the stock centers.

      Significance

      The findings are particularly relevant to anyone who has used the Fas2EB112 allele for their studies or who plans to do so. Otherwise, it serves as a cautionary tale to all to examine and report phenotypes using multiple different alleles as a control for what other mutations may also exist on mutant chromosomes of interest.

      I am a Drosophila developmental biologist who uses most of the same tools used in this manuscript on a regular basis. I am also quite familiar with the experimental system used for this work.

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      Referee #2

      Evidence, reproducibility and clarity

      Epithelial integrity is fundamental to organ function and development. There are mechanisms to reintegrate cells that divide outside of the cell layer that depend on cell adhesion. In many cases, including the Drosophila follicular epithelium, this adhesion and reintegration is dependent on partially redundant functions of the IgCAMs Fas2, Fas3, and Neruoglian (Nrg).

      Here, Finegan et al have identified discrepancies in phenotypic strength between two null alleles of Fas2 and show that this is due to an additional mutation in Nrg on the phenotypically stronger chromosome (likely due to a submission of a double mutant rather than a single mutant to the stock center, as this Nrg allele seems to be the same aberration as the Nrg14 null alle used in this study as well). Overall, the data is sound and of interest to people working with these genes in the adhesion field, but not of a broader interest. Over passages the paper is lengthy (such as a description of recombinations separating the mutations (or not) on p5 or the extensive description of the Nrg splice variants on p7.

      Points to address:

      Major:

      Fig 1C and Fig 4B: Why do the shRNAs used for Fas2 and Nrg have stronger phenotypes than the mutants? As clones were used, the argument of adaptation is harder to make. Specificity of shRNAs may have to be shown in a mutant background. Therefore, actually, this is particularly puzzling/worrisome in case of Fig. 4B where Nrg RNAi is stronger than the Nrg14 null allele (i.e. e(Fas2)mut) background.

      P8/Fig 3F Western blot: Despite description of quantification of blots in methods, nothing is quantified, and the arguments of dosage compensation thus cannot be made. Comes up again in the discussion. Furthermore, would the resolution of the blot allow distinction of Nrg180-YFP from Nrg167-YFP to really exclude that only one of them is expressed from the tagged locus?

      Discussion: Similarly, Mannheim Fas2EB112 has a lower average number of...., though this difference is not significant. Thus, is does not have a lower average!

      Discussion: Sentence ending in '...that E(Fas2)mut is suppressed' is confusing. Suppressed with repressed to what by what?

      Minor:

      • P2 second paragraph: insert 'Drosophila' before 'follicular epithelium'.
      • P4: Dr. Riechmann's first name is misspelled.
      • P8 last line: Fig. X should be Fig. 4A.
      • P12, legend of Fig. 2: description of panel B missing.
      • Tables are supplementary and should be labeled as such in the methods.
      • Fig. S3C: the non-disjunction aspect is not straight forward to see in the figure (e.g. XXY genotype and its correlation to eye shape from balancers).

      Significance

      Overall, the data is sound and of interest to people working with these genes in the adhesion field, but not of a broader interest.

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      Referee #1

      Evidence, reproducibility and clarity

      This manuscript reports an intriguing genetic puzzle and its solution that is very relevant to Drosophila researchers studying the Immunoglobulin-superfamily cell adhesion molecules (IgCAMs) Fasciclin 2 (Fas2) and Neuroglian (Nrg), homologs of vertebrate NCAM and L1-CAM, respectively. In their earlier work, the authors described the roles of these IgCAMs in the Drosophila follicle epithelium, where Fas2 and Nrg are required for cell reintegration after mitosis. During cell division, errors in spindle positioning can cause newly born cells to get displaced from the epithelial sheet. Such apically extruded cells normally re-integrate with high efficiency into the epithelium. As the authors previously showed through genetic studies in the Drosophila follicle epithelium, mutations in Fas2 and Nrg act synergistically to disrupt reintegration, leading to the accumulation of extruded ("popped out") cells. A puzzle arose when the authors compared the phenotypes of two different presumed protein-null alleles of Fas2 (Fas2(EB112) and Fas2(G0336)), which showed different strengths of epithelial cell reintegration defects. They systematically examined the phenotypes of Fas2(G0336) and two different fly strains carrying the Fas2(EB112) allele and discovered that the more severe defects seen in one of the Fas2(EB112) strains are due to the presence of an additional mutation in Nrg on the same chromosome. Intriguingly, they identified the mutation in the Nrg locus as the previously characterized Nrg(14) allele. This suggests that the Fas2 Nrg double mutant chromosome did not arise naturally through random appearance of a second-site mutation, but that it was generated intentionally and then apparently got mixed up with the Fas2(EB112) strain (however, the authors do not comment on this point). The authors spared no effort to resolve this genetic puzzle in a clear and convincing manner. The used clever genetics, genome sequencing and polytene chromosome preparations to unveil the Nrg mutation as Nrg(14). The results are very clearly documented, and the text is well written, almost in the style of a criminal investigation. I have only minor comments to be addressed by the authors before the manuscript should be published. p. 5: " The second chromosome that we generated through recombination did not demonstrate decreased anti-Fas2 immunoreactivity or the presence of popped-out cells (Figure 2A,B)..." The latter finding is surprising, as the authors previously showed that the Nrg(14) mutation leads to an increase in the number of popped out cells (Cammarota et al. 2020). They discuss this issue later in the text, but the reason for this discrepancy remains unclear. In the same context, p. 9: " Consistent with this, we find that E(Fas2)mut does not increase the number of popped-out cells in Nrg knockdown tissue (Figure 4B)." But Fig. 4B shows that Nrg knockdown increases the number of popped out cells in E(Fas2) mutant clones. Assuming that Nrg14 is a true null allele, this result would suggest that the effect of Nrg knockdown on the frequency of popped out cells is an RNAi artifact (off-target effect)? The authors should comment on this issue.

      Fig. 3F: The Nrg(167) band in the Fas2(EB112) Mannheim lane is stronger than in the control (w1118), suggesting that Nrg(167) expression is upregulated when Fas2 levels are reduced. Please comment.

      The authors refer to the enhancer of Fas2 mutation interchangeably as e(Fas2) and E(Fas2). As I understand, the mutation is recessive, and should therefore be referred to as e(Fas2).

      p. 4: "Both Fas2EB112 (Grenningloh, Rehm, and Goodman 1991) and Fas2G0336 are thought to be protein null (Bergstralh, Lovegrove, and St Johnston 2015)." The authors should explain why these mutations are "thought to be protein null". They show that Nrg immunoreactivity is lost in Nrg(14) mutants, and likewise for Fas2. If both anti-Fas2 (1D4) and anti-Nrg antisera detect all isoforms of the respective proteins, the authors should state this clearly and modify their rather vague statement on p. 4 ("thought to be protein null").

      Fig. 4C: Please add labels to indicate the gene locus (Fas2, Nrg) analyzed in each panel.

      Fig. 4D: The chromosomes shown are from heterozygous flies carrying the respective mutation in trans to the w1118 X-chromosome. Correct genotypes should be indicated.

      For the genome sequencing, what was the exact genotype of the flies that were sequenced? Hemizygous (lethal) embryos or heterozygotes? If DNA from heterozygotes was analyzed, how were short reads assigned to one of the parental (mutation-bearing or wild-type) chromosomes?

      p. 8/9: "Figure X".

      Figure legends: scale bars are in µm, not µM.

      Referees cross-commenting

      I agree that the results are important for a specialty audience concerned with the specific mutant strains described here.

      Significance

      Although the manuscript does not report a conceptual advance, the findings are very important for a significant part of the Drosophila community, particularly those studying Fas2 and Nrg. These proteins are involved in development of the nervous system, in synapse formation, as well as in epithelial morphogenesis and barrier formation. The Fas2(EB112) mutant has been widely used in at least 37 publications (dating back to 1991), several of which will need to be revisited in the light of the new findings reported here. This reviewer is a cell and developmental biologist with expertise in Drosophila genetics.

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      Reply to the reviewers

      We would like to sincerely thank both reviewers for taking the time to examine our work, for the cogent points they have raised, and their constructive attitude aimed at improving our manuscript.

      Reviewer #1

      • Single-cell RNAseq (Fig. 1B) and in situ (Fig. 3D) results both indicate that SNHG7 is broadly expressed in multiple epidermal layers but more enriched in the spinous layer. Although most assays, such as colony formation and Ki67 staining, did not specifically examine the role of SNHG7 in the spinous layer, the raft culture experiment seemed to indicate specific reduction of the spinous layer (Fig. 3H), which was more prominent than basal defects. The authors should examine the defects more carefully in the raft culture system by using basal, spinous and granular markers. It is possible that SNHG7 functions to maintain limited cell proliferation while restrict premature differentiation. In addition, they should perform serial passage experiments to distinguish whether overexpression of SNGH7 can indeed confer self-renewal in long-term experiments.*

      We have included staining of a range of epidermal markers in the raft cultures (ITGB1, K14, K10 and IVL) in the revised manuscript (Fig. S6B). We do not observe major changes in the distribution of any of the differentiation markers.

      In terms of serial passage, we have cultured SNHG7-overexpressing or control cells for multiple passages until their growth capacity was exhausted. The SNHG7-overexpressing cells grew for approximately seven more passages than the control cells. We have added this information to the revised manuscript (Fig. S6L).

      • The main proposed mechanism is the sequestration of miR34 by SNHG7. While miR34 is well known for its function in inhibiting cell proliferation, the ability of coding or noncoding RNA to sequestrate miRNAs is highly dependent on the stability and copy number of these RNAs. Since they have single-cell data with UMI information, they should estimate the copy number of SNHG7 in epithelial cell populations, and this could provide a range for the "buffering" capacity of SNHG7. They should also examine, ideally by in situ hybridization, the expression patterns of miR34 in human vs mouse skin. While miR34 expression can be induced by p53 activation, it is possible that its expression varies in different species. It'll be interesting to determine whether the lack of miR34 expression in mouse keratinocyte or mouse skin could explain the insensitivity of mouse keratinocytes to SNHG7. Finally, to further demonstrate the competition between SNHG7 and miR34 targets, they can use a heterologous luciferase reporter system with a canonical miR34 targeting site in the 3'UTR and quantify luciferase activities with or without SNHG7 (or SNHG7 mut34 variant). This assay could quantify the impact of SNHG7 on individual miR34 targets.*

      We will include the analysis of the scRNAseq data to estimate the copy number of SNHG7 in the epidermal populations.

      We will also perform in situ hybridization staining for miR-34 in human and mouse epidermis as well as mouse keratinocytes.

      Finally, we will carry out the luciferase reporter experiments.

      Reviewer #2

      Major comments:

      1) The premise of the study relies on the observation that SNHGs have low levels of sequence conservation. Indeed the authors aim to prove that biological functions can be identified even in the absence of evolutionary conservation. However, the extent of evolutionary conservation strongly depends on the phylogenetic scale at which it is analyzed. Here, the authors evaluate sequence conservation using PhastCons and PhyloP scores determined using alignments of human and 99 other vertebrate species. These scores reflect the extent of long-term sequence conservation. At this scale, only a small percentage of the human genome can be considered to be "conserved". It is thus not surprising that SNHG and other lncRNAs are not conserved at this scale, even if they carry some biological functions in the human genome. Here, it would be useful to redo the sequence conservation analyses using PhastCons and PhyloP scores computed on less distant species. Pre-computed scores exist for alignments containing human and other mammalian species, mainly primates (UCSC genome browser). It would also be good to provide comparisons of sequence conservation levels on the snoRNA genes and on the non-snoRNA parts of SNHGs. In addition to protein-coding genes, pseudogenes and lncRNAs, it would be good to add a perfectly neutral control for the sequence conservation in Figure 1C - for example, flanking intergenic regions for SNHGs. It might also be a good idea to analyze the GC content of SNHGs compared to other lncRNAs, since GC content can be correlated with sequence conservation levels, in particular in noncoding regions.

      Importantly, the SNHG selected for detailed investigation (SNHG7) appears to be more conserved than the bulk of human lncRNAs, given that it is found in another primate and in mouse. It would be interesting to analyze in details what sequence features of this lncRNAs are conserved among species - for example, are the SNHG7 splice sites and promoter regions conserved? Are the snoRNA genes always located in the introns?

      The reviewer raises very good points. We have added the conservation data of snoRNA genes (all or SNHG-resident, both significantly more conserved than SNHGs or lncRNA), and a “true neutral” control (we used the introns of 10,000 randomly sampled genes) to our PhastCons analysis (Fig.1C). We also added a conservation analysis of the promoters (defined as the 500 bp upstream of the transcription start site) of coding genes, pseudogenes, lncRNA and SNHGs (Fig, S1B). We have now performed all our conservation analyses using both PhastCons scores generated from the 100-vertebrate alignment and PhastCons scores generated from the 30-mammals (28 primate) alignment (Fig. S1E-G). We do not detect any marked difference between the two alignment sets. We have also added a comparison of the GC content in lncRNA, SNHGs, coding genes and introns (Fig.S1C).

      Due to the nature of the PhyloP scores, the 30-mammal PhyloP track (phyloP30) would be unsuitable to detect additional conservation in the primate lineage using the thresholding analysis we employed in Fig. 1E. The PhyloP track gives base-wise p-values for conservation (positive values) or accelerated evolution (negative values). Using alignments of genomes that are overall more similar to each other (as in the 30-mammal alignment set) makes it more difficult to distinguish between conserved and neutrally evolving regions, because even segments that are not under constraint will look relatively similar due to the evolutionary proximity of the species in the set. For the same reason this alignment set is quite sensitive to accelerated evolution, as it contains many relatively similar genomes it the alignment.

      This causes the PhyloP30 scores to be very asymmetrical around zero: the conservation (positive) scores never reach 2 (p-value of 0.01) in the whole track (not even coding regions of very well-conserved genes), while acceleration scores can reach very significant values, down to -20. Conversely, the PhyloP100 track (used in Fig.1E) is quite symmetrical around 0 and is thus better suited for the purposes of the analysis in Fig.1E, which are to detect both conserved and accelerated portions of SNHGs. We have however also inspected the PhyloP30 track manually and do not observe any clear evidence of presence of additional conserved elements in SNHG7. We have added all conservation tracks for SNHG7 to Fig. 3A.

      While lncRNA orthologs can be identified by using a combination of sequence conservation, conserved synteny with surrounding genes and in some cases conserved gene structure, SNHG orthologs can additionally be identified by the embedded (conserved) intronic snoRNA sequence, which makes them easier to find even when the transcript sequence bears no similarity across species. The mouse SNHG7 sequence, for example, does not match with human SNHG7 even using the least stringent BLAST parameters. The monkey sequence is similar enough to match with the human in the 3’ of the gene, but the intron-exon structure of the 5’ is completely different. We agree with the reviewer’s assessment, however, when it comes to identification of SNHG orthologs in more evolutionary distant species, closer to the root of the vertebrate clade.

      Regarding splice sites, they are often conserved among lncRNA in general (gene structure conservation occurs more frequently than sequence conservation, see Ulitsky, Nat Rev Genet, 2016). In the case of SNHG7 the structure of the gene appears conserved in the mouse (though this annotation has likely not been fully confirmed experimentally), and in the monkey based on genome alignments. However, our RACE experiments show that the 5’ end of SNHG7 in the monkey has a radically different splicing pattern when compared to human, so it is difficult to assess splicing conservation in the absence of full isoform characterization.

      2) I am not perfectly convinced by the enrichment of miRNA target genes among the genes that are downregulated upon SNHG knockdown. The methods do not clearly explain how this enrichment is calculated. What is the background used for this enrichment analysis? In Figure 5C, we see that the genes predicted to be targeted by the top 10 microRNAs tend to have negative fold changes in the differential expression analysis (downregulation following knockdown). However, from Figure 5A it seems that the great majority of significantly differentially expressed (DE) genes have negative fold changes. How do the miRNA target genes differ from all other DE genes? What proportions of all predicted miRNA target genes (expressed in keratinocytes) are DE following knockdown, and how does this compare with the target genes of other miRNAs?

      We have added a description of the statistical test used by MIENTURNET for the enrichment analysis to the methods section. More details can be found in the original publication. The significance of the enrichment is calculated by performing a hypergeometric test using as background the total number of miRNA-target interactions in the database and the total interactions the individual miRNA being tested engages in.

      Figure 5C only includes the genes we used in our enrichment analysis (i.e. the significantly downregulated genes, not all DE genes) and it’s meant to show the extent of downregulation exhibited by the targets of the most significantly enriched miRNAs within this group of genes.

      The reviewer is correct in pointing out that the imbalance between downregulated and upregulated genes (which we now further highlight in the plots in Fig. 5A-B) will tend to skew any group of genes towards having a relatively large number of downregulated genes. However, we found this bias to be particularly strong in the case of our candidate miRNAs. We now show this in volcano plots for validated targets of the candidate miRNAs and a control miRNA (Fig. S8E). In a similar way, when looking at the cumulative distributions of the fold changes of all predicted targets for a certain miRNA and comparing it to the fold change cumulative distribution of all other genes, our candidate miRNAs displayed a more pronounced shift towards downregulation than the control miR-21-5p (which we now added in Fig. S8F).

      3) If keratinocyte RNA-seq data is available for other species (for example mouse), it would be interesting to test whether the high expression levels of SNHG7 and the other analyzed SNHGs are also conserved in the other species.

      We will include the RNA-seq data, if available.

      Minor comments:

      1) The AD (atopic dermatitis) abbreviation should be explained the first time it is mentioned in the text.

      We thank the reviewer for pointing out the missing abbreviation, we have now added it.

      2) More details are needed regarding the MIENTURNET analyses in the methods and in the main text

      We have added more details about the statistics involved to the methods (see above).

      *3) Figure 5C, it is not clear how to interpret the color code for the boxplot. Does this represent the median or mean FDR of the target genes? Are only genes with FDRThe genes included in the enrichment analysis are all downregulated genes with an adjusted p-value (or FDR adjustment after the Wald test) adj”. The color scale in Fig 5C reports the significance of the enrichment for targets of the single miRNAs within the significantly downregulated genes list (FDR adjustment after the hypergeometric test), not the significance of the downregulation itself. FDR values are also used for all other enrichment analyses (GO terms, REACTOME Pathways). We apologise to the reviewer for the confusion, we have now modified the text and figures to make this clearer.

      4) Figure 6D, I am not sure how to the D panel. Do the gray rectangles represent the exonic length of the SNHGs? Do the dots correspond to the positions of the miRNA target sites? Here, a more quantitative comparison with the extent of sequence conservation of miRNA binding sites in SNHGs, other lncRNAs and in protein-coding genes would be perhaps better suited.

      The grey rectangles in Fig. 6D represent the total exonic length of the SNHGs (basically all exons are “stitched together” head to tail irrespective of the actual isoforms) and the dots represent the positions of the miRNA binding sites within this “maximum exonic coverage”. Since not all individual isoforms are analysed it is possible that some additional miRNA sites can be created at alternatively spliced junctions, however we would estimate the number of such sites to be small. We have added this caveat to the methods section.

      The degree of conservation that is estimated by TargetScan to underlie a functional MRE in coding genes is taken into account in this analysis, as sites within SNHGs that pass this threshold are highlighted with yellow borders in the figure. We have now added a plot of the distribution of Branch length scores for MREs in SNHGs and the distribution of Branch length scores for MREs in a random sample of 250 Coding genes UTRs (Fig. S9E). A similar comparison for lncRNA is more challenging as the data is not readily available and is likely to be confounded by the nuclear localisation of a majority of lncRNA species.

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      Referee #2

      Evidence, reproducibility and clarity

      Summary

      The manuscript submitted by M. Vietri Rudan and co-authors presents a functional analysis of a specific class of long non-coding RNA transcripts, namely the small nucleolar RNA host genes (SNHGs). These genes are defined by the fact that snoRNA molecules are embedded within their loci, often in the SNHGs introns. The rationale presented by the authors for studying this specific class of lncRNA genes is the fact that they display very low levels of evolutionary sequence conservation (even compared to the generally low conserved lncRNA transcripts) and that they are expressed at remarkably high levels (contrary to most lncRNA genes, which are very weakly expressed). The overarching goal of this study thus appears to be determining whether functional transcripts can exist in the absence of evolutionary conservation.

      The authors study SNHGs in the human keratinocytes model system. They analyze the expression levels of SNHGs in skin affected by atopic dermatitis and psoriasis, compared to normal skin. They identify several SNHGs that are differentially expressed between diseased and normal skin, and which are also detected at strong expression levels in single cell RNA-seq assays of human keratinocytes. The authors use knockdown assays to investigate the potential roles of these SNHGs in keratinocytes and show that the knockdown of each of 5 selected SNHGs results in a loss of clonogenicity.

      The last part of the manuscript focuses on the functional characterization of SNHG7, chosen because it is dysregulated in both atopic dermatitis and psoriasis and because its knockdown strongly affects clonogenicity. Additional assays showed that SNHG7 knockdown results in a reduced rate of proliferation and an increase in the fraction of differentiating cells. To ensure that the effects of the knockdown are not simply due to the absence of the snoRNA molecules embedded in the SNHG7 locus, the authors overexpressed the spliced form of SNHG7 (which lacks the snoRNA genes), successfully rescuing the cellular phenotype. They also verified that the knockdown does not affect the abundance of the corresponding snoRNA molecules.

      To propose a potential mechanism for the involvement of SNHG7 in keratinocyte proliferation, the authors investigated its capacity to act as a miRNA "decoy". They searched for an enrichment of miRNA binding sites among the genes that are downregulated following SNHG7. They identified several miRNAs which are predicted to target SNHG7 as well as (a substantial fraction of) the genes that are downregulated following SNHG7 knockdown. The transfection of two of these miRNAs (miR-193-3p and miR-34-5p) has a negative effect on keratinocyte proliferation, supporting the authors's hypothesis that SNHG7 may act via "sponging" these miRNAs, thereby positively contributing to the control of the expression of the other miRNA target genes. Consistent with this hypothesis, the authors show that overexpression of a SNHG7 mutant sequence that lacks the miRNA binding sites is not able to rescue the knockdown phenotype.

      However, this hypothesis is not supported (or at leat not further reinforced) by the evolutionary analysis performed by the authors. They were able to identify homologues for SNHG7 in another primate species (night monkey) and in the mouse. Transfection of the human SNHG7 sequence was able to increase clonogenicity in night monkey cells, but not in mouse cells. Given that miR-34 is also present in mouse and was previously shown to affect keratinocyte proliferation, it is not clear why the human SNHG7 sequence is not able to act as a miRNA sponge in this species. Likewise, only a slight effect on clonogenicity is observed upon SNHG7 transfection in night monkey. The authors conclude (correctly, in my view) that further investigations are needed to confirm the potential functions of SNHG7.

      Overall, I find that this study is interesting and carefully conducted. Nevertheless, I have several comments that I hope can improve this manuscript.

      Major comments:

      1. The premise of the study relies on the observation that SNHGs have low levels of sequence conservation. Indeed the authors aim to prove that biological functions can be identified even in the absence of evolutionary conservation. However, the extent of evolutionary conservation strongly depends on the phylogenetic scale at which it is analyzed. Here, the authors evaluate sequence conservation using PhastCons and PhyloP scores determined using alignments of human and 99 other vertebrate species. These scores reflect the extent of long-term sequence conservation. At this scale, only a small percentage of the human genome can be considered to be "conserved". It is thus not surprising that SNHG and other lncRNAs are not conserved at this scale, even if they carry some biological functions in the human genome. Here, it would be useful to redo the sequence conservation analyses using PhastCons and PhyloP scores computed on less distant species. Pre-computed scores exist for alignments containing human and other mammalian species, mainly primates (UCSC genome browser). It would also be good to provide comparisons of sequence conservation levels on the snoRNA genes and on the non-snoRNA parts of SNHGs. In addition to protein-coding genes, pseudogenes and lncRNAs, it would be good to add a perfectly neutral control for the sequence conservation in Figure 1C - for example, flanking intergenic regions for SNHGs. It might also be a good idea to analyze the GC content of SNHGs compared to other lncRNAs, since GC content can be correlated with sequence conservation levels, in particular in noncoding regions.

      Importantly, the SNHG selected for detailed investigation (SNHG7) appears to be more conserved than the bulk of human lncRNAs, given that it is found in another primate and in mouse. It would be interesting to analyze in details what sequence features of this lncRNAs are conserved among species - for example, are the SNHG7 splice sites and promoter regions conserved? Are the snoRNA genes always located in the introns? 2. I am not perfectly convinced by the enrichment of miRNA target genes among the genes that are downregulated upon SNHG knockdown. The methods do not clearly explain how this enrichment is calculated. What is the background used for this enrichment analysis? In Figure 5C, we see that the genes predicted to be targeted by the top 10 microRNAs tend to have negative fold changes in the differential expression analysis (downregulation following knockdown). However, from Figure 5A it seems that the great majority of significantly differentially expressed (DE) genes have negative fold changes. How do the miRNA target genes differ from all other DE genes? What proportions of all predicted miRNA target genes (expressed in keratinocytes) are DE following knockdown, and how does this compare with the target genes of other miRNAs? 3. If keratinocyte RNA-seq data is available for other species (for example mouse), it would be interesting to test whether the high expression levels of SNHG7 and the other analyzed SNHGs are also conserved in the other species.

      Minor comments:

      1. The AD (atopic dermatitis) abbreviation should be explained the first time it is mentioned in the text.
      2. More details are needed regarding the MIENTURNET analyses in the methods and in the main text
      3. Figure 5C, it is not clear how to interpret the color code for the boxplot. Does this represent the median or mean FDR of the target genes? Are only genes with FDR<5% included in this analysis?
      4. Figure 6D, I am not sure how to the D panel. Do the gray rectangles represent the exonic length of the SNHGs? Do the dots correspond to the positions of the miRNA target sites? Here, a more quantitative comparison with the extent of sequence conservation of miRNA binding sites in SNHGs, other lncRNAs and in protein-coding genes would be perhaps better suited.

      Significance

      Overall, this study is highly relevant in the field of lncRNA functionality and evolution. It presents evidence for a potential involvement in the regulation of cell proliferation for SNHGs, a role that appears to be independent of the snoRNAs produced by these loci. This study reinforces the current body of work suggesting that lncRNAs and other noncoding transcripts can sometimes function as miRNA "decoy" targets. This study will be of interest for a specialized audience, oriented towards understanding lncRNA biological functions.

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      Referee #1

      Evidence, reproducibility and clarity

      Vietri Rudan and colleagues present an interesting study to examine the function and mechanism of small nucleolar RNA Host Gene 7 (SNHG7) in human keratinocytes. The key findings are that a widely expressed SNHG7, a long noncoding RNA hosting two snoRNAs in the introns, promotes keratinocyte proliferation and inhibits differentiation likely by sequestrating miR34a from its targets. The experiments are generally well-executed with proper controls. Notably, they leveraged human, night monkey and mouse keratinocytes to reveal primate specific functions of SNHG7 in a miR34 dependent manner. I have a few comments and suggestions that should be addressed to further strengthen the study.

      1. Single-cell RNAseq (Fig. 1B) and in situ (Fig. 3D) results both indicate that SNHG7 is broadly expressed in multiple epidermal layers but more enriched in the spinous layer. Although most assays, such as colony formation and Ki67 staining, did not specifically examine the role of SNHG7 in the spinous layer, the raft culture experiment seemed to indicate specific reduction of the spinous layer (Fig. 3H), which was more prominent than basal defects. The authors should examine the defects more carefully in the raft culture system by using basal, spinous and granular markers. It is possible that SNHG7 functions to maintain limited cell proliferation while restrict premature differentiation. In addition, they should perform serial passage experiments to distinguish whether overexpression of SNGH7 can indeed confer self-renewal in long-term experiments. Based on these results, they may need to refine their hypothesis/conclusion whether SNHG7 functions primarily on stem cell self-renewal or transiently maintain proliferation in transitioning cells.
      2. The main proposed mechanism is the sequestration of miR34 by SNHG7. While miR34 is well known for its function in inhibiting cell proliferation, the ability of coding or noncoding RNA to sequestrate miRNAs is highly dependent on the stability and copy number of these RNAs. Since they have single-cell data with UMI information, they should estimate the copy number of SNHG7 in epithelial cell populations, and this could provide a range for the "buffering" capacity of SNHG7. They should also examine, ideally by in situ hybridization, the expression patterns of miR34 in human vs mouse skin. While miR34 expression can be induced by p53 activation, it is possible that its expression varies in different species. It'll be interesting to determine whether the lack of miR34 expression in mouse keratinocyte or mouse skin could explain the insensitivity of mouse keratinocytes to SNHG7. Finally, to further demonstrate the competition between SNHG7 and miR34 targets, they can use a heterologous luciferase reporter system with a canonical miR34 targeting site in the 3'UTR and quantify luciferase activities with or without SNHG7 (or SNHG7 mut34 variant). This assay could quantify the impact of SNHG7 on individual miR34 targets.

      Significance

      This study reveals a potential function and mechanism of primate specific noncoding RNA for its role in modulating gene expression and cellular functions in the skin. It provides a new paradigm for identifying molecular functions of poorly conserved RNAs.

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      Reply to the reviewers

      Manuscript number: #RC-2023-02281

      Corresponding author(s): Maurizio Molinari

      Point-by-point description of the revisions

      This section is mandatory. *Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. *

      • *

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

      In this manuscript from Fasana et al., the authors present data that investigates potential compensatory degradation pathways for misfolded glycoproteins in the ER - postulating that the ER-to-lysosome associated degradation (ERLAD) pathway becomes employed in the absence of a path for substrates to reach the ER-associated degradation (ERAD) mechanism. Using the classic ERAD substrate alpha1-antitrypsin NHK variant (NHK), the authors first demonstrate that pharmacologically preventing access of NHK to ERAD either with KIF (early) or PS-341 (late) elevates the number of LAMP-1 positive endolysosomes also immunoreactive for NHK (via HA), similar to what is observed for the ATZ variant that forms polymers in the ER (Fig 2). The authors next use shRNAs that silence essential ERAD factors (EDEM1, OS-9) involved in glycan recognition to demonstrate comparable enrichment of NHK in endolysosomes through genetic disruption (Fig 3). Next, the authors employ FAM134B-deficient MEFs to demonstrate the requirement for this ER-phagy receptor when ERAD is unavailable (Fig 4). Reconstituting FAM134B-/- MEFs treated with KIF/PS-341 + Baf, with a full length FAM134B rescue plasmid restores endolysosomal accumulation of NHK while a FAM134B-∆LIR does not, providing supporting evidence for substrate rerouting to ERLAD. Finally, the authors use knockouts of Atg7 and Atg13 to demonstrate dependence on LC3 lipidation and independence from macro-ERphagy (Fig 6), that points towards a pathway that is like that used to remove ATZ polymers. From these data, the authors conclude that ERLAD is increasingly engaged for substrate degradation when ERAD is impaired.

      MAJOR COMMENTS 1. All assays rely on quantification of the NHK-HA substrates by microscopy. Would it be possible for the authors to also include biochemical analysis of NHK - potentially including data assessing its changing abundance and glycosylation state?

      To consider this, and other comments, the new submission includes biochemical data (pulse-chase analyses) on NHK (new panels A-D in Fig. 2) and on BACE457delta, an additional ERAD substrate (new Fig. 6). Please also refer to Comment 3.

      In Figure 3D, the knockdown of OS-9.1/2 is modest compared to that of EDEM1 (Fig 3A). Moreover, there is only data from single shRNAs presented. Could the authors please at least include another shRNA to confirm and demonstrate whether the targeting to ERLAD is accordingly scaled to loss of access to ERAD (based on the degree of OS-9 or EDEM1 remaining)?

      __The reviewer is right. The phenotype (i.e., lysosomal delivery of NHK, Figs. 3B, 3C) is quite modest upon EDEM1 silencing. However, one has to consider that in contrast to OS9 lectins, EDEM1 is an enzyme, and residual protein may partially facilitate NHK de-mannosylation and access to the ERAD pathways and therefore reduce the ERLAD contribution for NHK clearance in these cells. Moreover, cells also express EDEM2 and 3 that may partially compensate the loss of EDEM1. __

      While degradation is implied, it is not specifically demonstrated at any point in the manuscript. Perhaps the authors might include some demonstration of NHK stabilization in one of the figures via a translational shutoff or pulse-chase assay.


      __In the new submission, we show biochemical analyses (pulse-chase) that reveal the decay of radiolabeled NHK (Fig. 2A, lanes 1-3) and BACE457delta (Fig. 6A, lanes 1-3), the inhibition by PS341 (lanes 4, 5) and by KIF (lanes 8, 9), and the intervention of lysosomal enzymes when ERAD is inhibited (lanes 6, 7 and 10, 11). Moreover, we confirm that the protein delivered to the endolysosome is eventually degraded by performing a Bafilomycin washout experiment (new Fig. 2J-2O). __

      10-30% of NHK-HA positive endolysosomes are detected even with Baf alone (e.g. Fig 2E)? Does this mean that Baf impairs ERAD to some extent since or is it evidence for continuous ERLAD involvement when ERAD is intact? If so, how much is its contribution?

      Pulse-chase analyses (new Fig. 2D) and published data show that BafA1 or chloroquine do not inhibit clearance of the ERAD substrates NHK and BACE457delta (e.g., Liu et al 1999, Molinari et al 2002, references in the manuscript). A basal level of endolysosomal delivery between the 20 and 30% as quantified with LysoQuant is observed in all experiments (Figs. 2I, 2O, 3C, 3F, 4C, 4K, 5H, 6G, 6O), which have been performed in 3 different cell lines (3T3, HEK293, MEF). We measure similar basal levels also when ER-phagy is monitored on quantification of lysosomal delivery of endogenous ER marker proteins (e.g., CNX), possibly to be ascribed to constitutive ER phagy that controls physiologic ER turnover.


      An accounting of how much ERLAD is contributing to NHK degradation with or without ERAD impairment is not really present.. Effectively, how much degradation capacity is ERLAD making up? These would be interesting data to include if possible as they would speak to the "division of labour" for ER substrate degradation its potentially dynamic nature.

      The biochemical analyses show the contribution of ERLAD on NHK (new Figs 2B, 2C, grey zones) and BACE457delta (new Figs. 6B,C, grey zones) clearance, when ERAD is dysfunctional.

      MINOR COMMENTS 1. In Figure 4, an increase is observed for the rescue of FAM134B-/-MEFs with WT FAM134B that is 50% greater that of WT MEFs, suggesting that its availability might be rate limiting. Could the authors compare the relative levels of FAM134B for the WT and KO-rescue MEFs to address this possibility?

      __The referee is right in assuming that FAM134B, expressed at low levels in these cells, is limiting. We now show the levels of endogenous FAM134B and of recombinant FAM134B in WB (new Fig. 4A). __

      In Figures 1 and 6, the terms siOS9 and siEDEM1 are used but Figure 3 shows data from shRNAs and not siRNAs.

      We apologize for the mistake. We have corrected this in the new Figures 1 and 7.

      Samples from Figure 3 treated with Baf but this is not indicated in the figure or figure legend.


      We have corrected this, thank you.

      VCP/p97 inhibitors typically stabilize ERAD glycoprotein substrates better than proteasome inhibitors do. Is the same degree of endolysosomal targeting present ?


      __For the convenience of the reviewer (we did not put these data in the new manuscript). In our experiments, the p97 inhibitor DBeQ is less efficient in deviating NHK to the endolysosomal degradative compartments, if compared with KIF (see below). At higher doses, DBeQ also inhibits other AAA-ATPases (e.g., VPS4, which plays a role in certain types of autophagy). This, or other cross-reactivities of DBeQ could explain the moderate capacity to activate ERLAD pathways as a response of ERAD inhibition, if compared with the phenotypes observed when ERAD is inhibited with KIF or PS341. __

      Reviewer #1 (Significance (Required)):

      Deconvolution of the different pathways taken by misfolded proteins to escape the ER is of great interest not only to the ER community but also represents consequences to consider for those interested in therapeutics involving UPS inhibition. While concise, this manuscript does a good job of trying to demonstrate the principal of substrate rerouting and the prioritisation of degradation pathways. Overall, the manuscript is well written, the experiments presented are performed to a sufficient standard, the data are lean but of good quality, and the appropriate statistical analyses have mostly been included where necessary and are described. The Methods and Materials is brief but describes the experiments that have been performed. The manuscript is brief in its results and would obviously benefit from additional complementary assays that would strengthen and broaden the authors arguments for rerouting. But too their credit, the authors do not grossly overstate their findings and merely present the culmination of a set of experiments to answer a single question - what happens to a misfolded glycoprotein substrate when ERAD is impaired. This is a key question with broad implications.

      While their limited data clearly demonstrates an acquired dependence on ERLAD, one can't help but wonder how broadly these findings hold true, as only a single glycoprotein substrate example is used.

      We have now added a complete set of experiments (imaging + biochemical to monitor clearance of the model polypeptides by pulse-chase analyses) performed with a second ERAD substrate (BACE457delta, Fig. 6). These data fully recapitulate the results obtained with NHK.


      Moreover, it is not clear what percentage ERLAD contributes to overall NHK degradation (with or without ERAD) as the total NHK amount remaining is not assessed or measured.


      Pulse-chase analyses (new Fig. 2D) and published data (e.g., Liu et al 1999, Molinari et al 2002, references in the manuscript) show that BafA1 or chloroquine do not inhibit clearance of the ERAD substrates NHK and BACE457delta. The biochemical analyses now show the contribution of ERLAD on NHK (new Figs 2B, 2C, grey zones) and BACE457delta (new Figs. 6B,C, grey zones) clearance, when ERAD is dysfunctional.

      Nevertheless, the manuscript is an advancement of understanding of the fate of substrates unable to access ERAD and raises many future questions of interdependency between the ERAD and ERLAD pathways. The data just need a bit of shoring up.

      Expertise - ERAD, UPS, protein quality control

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

      The endoplasmic reticulum (ER) is a crucial site for protein synthesis and folding within the cell, and strict protein quality control is essential for maintaining ER homeostasis. In this context, ER-associated degradation (ERAD) and the unfolded protein response (UPR) play pivotal roles. Recent researches have highlighted the significance of ER-phagy in protein quality control. In this manuscript, the authors demonstrate the role of FAM134B in degrading misfolded proteins such as ATZ through the ER-phagy pathway when the ERAD pathway is obstructed. This work partially addresses a prominent issue in the field, unveiling the interconnections between different regulatory pathways in maintaining ER homeostasis.

      Major issues: 1: In a multitude of experiments, the authors employed Bafilomycin A1 (BafA1) to block the fusion between autophagosomes and lysosomes, attempting to demonstrate that the clearance of misfolded proteins mediated by FAM134B is independent of autolysosomes. However, in Figure 4, the lack of rescue of FAM134B knockout by overexpressing FAM134B△LIR suggests a dependence on the interaction between FAM134B and LC3. The conclusions drawn before and after appear contradictory.

      We apologize if our explanations were unclear. We have now modified the text and performed new experiments to clarify these issues.

      __The inhibitor of the V-ATPase BafA1 is used here to inhibit the activity of lysosomal hydrolases and to accumulate undegraded material in the LAMP1-endolysosomes (note that these endolysosomes also display RAB7 at their limiting membrane) (Fregno et al 2018, Forrester et al 2019, Fregno et al 2021, …). __

      __In Figs. 2A-2D, we now monitor the lack of NHK stabilization by cell exposure to BafA1 (Fig. 2D), which correlates with lack of accumulation of NHK in the LAMP1-positive compartment (e.g., Fig. 2F, 2J, and quantifications in 2I and 2O). The biochemical data also show that BafA1 stabilizes NHK in cells where ERAD has been inactivated with PS341 or KIF (Fig. 2A, lanes 6, 7, 10, 11 and grey zones in Figs. 2B and 2C), which correlates with accumulation of NHK in LAMP1-positive organelles (Figs. 2G, 2H, 2I, 2K, 2M, 2O). __

      __In Figs. 2J-2O, we have now added panels showing that NHK clearance from the LAMP1-positive endolysosome lumen is restored upon BafA1 washout. __

      Importantly, the involvement of the lipidation machinery, of the ER-phagy receptor FAM134B and of the LC3-binding function of FAM134B (the LIR), does not necessarily imply the involvement of autophagosomes in the process under investigation, as the comment by the referee seems to suggest. For example, both the clearance from the ER of ATZ polymers and of mutant forms of procollagen rely on the LC3 lipidation machinery and on the LC3-binding function of FAM134B, but ERLAD of ATZ polymers does not rely on autophagosomes intervention (new Fig. 1B, arrow 1 and Fregno et al 2018), whereas ERLAD of procollagen relies on intervention of autophagosomes (new Fig. 1B, arrow 2 and Forrester et al 2019).

      2: Some Western blot data are insufficient to substantiate the author's conclusions. For instance, in Figure 5D, the ATG7 KO line is inadequately supported

      The WB show____s the absence of ATG7 in the ATG7-KO cells (a well-established cell line generated in the lab of Masaaki Komatsu (____Komatsu M, et al. J Cell Biol 169: 425-434_) and used in many_ laboratories, including our lab in Fumagalli et al 2016, Fregno et al 2018, Fregno et al 2021, Loi et al 2019, Kucinska et al 2023). We agree with the reviewer that the anti-Atg7 shows cross-reactions. We have now added a WB showing the lack of LC3 lipidation in the Atg7-KO cells exposed to nutrient deprivation (new Fig. 5D).

      3: The author employed Lamp1 antibody for lysosomal staining in cells and observed a significant abundance of lysosomes in some experiments, as depicted in Figure 2C, 2D, 4I, etc. Is the phenomenon of lysosomes extensively filling the entire cell a common occurrence? Is it indicative of a normal physiological state?

      There may be variations depending on the cell type used for the experiments. In the new version of the manuscript, we now present imaging data for 3 cell lines (NIH 3T3 with stable expression of NHK and ATZ (Figs. 2E-2H), MEF (Figs. 2J-2N, 4, 5, 6) and HEK293 with transient expression of ERAD clients (Figs. 3).

      Minor issues: 1: Some immunofluorescence experimental data are unclear. Please request the authors to replace these with more distinct images, as seen in Figure 3B and 3E.


      We hope that the quality of the new images will be considered sufficient for publication.

      2: Some expressions appear to be questionable. For instance, the necessity of utilizing endolysosomes requires clarification.

      For the use of endolysosomes (lysosome would be incorrect in our opinion to indicate these LAMP1/RAB7-positive degradative organelles), we now refer to the papers by Bright et al ____Endolysosomes Are the Principal Intracellular Sites of Acid Hydrolase Activity_ Curr Biol 2016, and the original definition by Huotari and Helenius _Endosome maturation EMBO J 2011 (Introduction, page 2).

      3: Some writing lacks precision, such as referring to FAM134B as FAM134.

      __Corrected, thank you____ __ Reviewer #2 (Significance (Required)):

      o General assessment: o Advance: provide an meaningful evidence that how two degradative pathways are coordinated in maintaining ER homeostasis. o Audience: cell biologist o Reviewer's expertise: autophagy, vesicle trafficking, organelle biolgy Reviewer #3 (Evidence, reproducibility and clarity (Required)):

      In their study, Fasana and colleagues investigate protein quality control in the ER. Specifically, they test whether folding-incompetent proteins that are normally cleared by ER-associated degradation (ERAD) can also be targeted for degradation by direct vesicular transport from the ER to lysosomes in case ERAD is blocked. They show that blocking ERAD pharamacologically or genetically indeed leads to re-rerouting of an ERAD model substrate (the NHK variant of alpha-antitrypsin) to lysosomes and that this pathway requires the reticulon-like protein FAM134B, the ability of FAM134B to interact with the ubiquitin-like protein LC3 and the machinery for LC3 lipidation.

      The paper is, for the most part, easy to follow. There are, however, a few minor issues and I think the authors could do more to connect their work with similar studies in the literature. Accordingly, I have some general and specific suggestions to make the manuscript more accessible for the reader.

      General suggestions

      1. To avoid confusion, it would be helpful to more clearly distinguish between vesicular transport to endolysosomes and autophagy. Previous work by the authors has defined a trafficking pathway from the ER to endolysosomes that appears to rely on conventional vesicle-mediated transport (Fregno et al, EMBO J 2018). This pathway delivers material from the ER lumen to the lumen of endolysosomes, which are both topologically equivalent to the extracellular space. Hence, this pathway is distinct from autophagy, which is the transport of cytoplasmic components to endolysosomes and thus the transport of material from intracellular to extracellular space. This distinction is particularly important as both vesicular ER-to-lysosome transport and autophagy of the ER involve LC3 and FAM134B, which is typically referred to as an ER-phagy receptor. To make this less confusing, it may be helpful to explain that FAM134B appears to be a multifunctional molecule that can function as a receptor for macroautophagy but also in the vesicular transport pathway studied here. In addition, it would be helpful to point out that LC3 appears to also have roles unrelated to autophagosome formation.

      The reviewer is referring to the original definition of ERLAD to describe the mechanisms of clearance of ATZ polymers (Fregno et al 2018). The definition of ERLAD has now been expanded and is given, for example, in Klionsky DJ, et al (2021) Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition). Autophagy 17: 1-382 and is explained in detail in our recent review Rudinskiy M, Molinari M (2023) ER-to-lysosome-associated degradation in a nutshell: mammalian, yeast, and plant ER-phagy as induced by misfolded proteins. Febs Letters: 1928-1945.

      __Notably, the acronym ERAD for ER-associated degradation has originally been used to describe ____the proteasomal clearance from the ER of misfolded pro-alpha factor in a reconstituted yeast system in McCracken AA, Brodsky JL (1996) Assembly of ER-associated protein degradation in vitro: dependence on cytosol, calnexin, and ATP. The Journal of cell biology 132: 291-298. Only later on, the acronym has been used as an umbrella term that now covers all the pathways that control proteasomal clearance of misfolded proteins from the ER. A short historical excursus is presented in the new introduction to better explain these issues. __

      It is well established that LC3 and the LC3 lipidation machinery have functions that go beyond macroautophagy (which involves double membrane autophagosomes). Micro-autophagy (or micro-ER-phagy to remain on the topic of our paper) is an example of autophagic pathway relying on ER-phagy receptor that engage LC3, on the LC3 lipidation machinery, without involving autophagosomes. This is schematically represented in the new Fig. 1B.

      Several recent papers that appear relevant to the present study are not mentioned. In particular, Sun et al., Dev Cell 2023 (PMID: 37922908) appears worthy of discussion, as does Gonzalez et al., Nature 2023 (PMID: 37225996).

      Thank you. Both papers are not directly linked to our study addressing the intervention of ERLAD pathways when ERAD activity is impaired. In particular the work of Gonzales et al describes post-translational modification of ER-phagy receptors for their activation. The Sun et al paper is not really related to the topic covered in our manuscript, but we cite it as an alternative pathway that removes ATZ from the ER (page 8).

      Specific suggestions

      1. Abstract: The abstract begins with "About 40% of the eukaryotic cell's proteome is synthesized ... in the ER." Similar statements can be found in many papers and purportedly reflect common knowledge. However, it is unclear where the figure of 'about 40%' comes from. It would be proper to provide a reference and demonstrate that giving such a fairly precise estimate is supported by experimental data. Alternatively, the statement could be modified to avoid being precise than is justified.

      No reference is allowed in the abstract. We therefore modified the sentence as suggested by the reviewer.

      1. p2: "The ER is site of gene expression in nucleated cells and ... native proteins to be delivered at their site of activity ...". There is something missing at the beginning of this sentence. Also, it should be 'delivered to their site of activity', not 'delivered at'.

      Thank you

      1. p2: "... by mechanistically distinct ER-phagy pathways collectively defined as ER-to-lysosome-associated degradation ERLAD." This statement suggests that all pathways subsumed under the term ERLAD are ER-phagy pathways, which I believe is misleading (see comment above on the distinction between autophagy and vesicular transport pathway).

      See point 1.

      1. p2: "KIF selectively ...". Please spell out KIF and explain what kind of compound it is.

      Thank you, we changed to “_The alkaloid kifunensine (KIF) is a cell permeable selective inhibitor of the members of the glycosyl hydrolase 47 family of a____1,2-mannosidases_”____ __ 5. p3: "Notably, ERAD inhibition delays, rather than blocking degradation of ERAD clients ...". Please correct, for example: Notably, ERAD inhibition delays rather than blocks degradation of ERAD clients ...

      Thank you

      Figures 2 - 5: The number of quantified cells is given but it is not clear if experiments were done once or in biological replicates. Please indicate this in the figure legends.

      __N is now given for all panels in the corresponding figure legends.____ __ 7. p4: "To verify if ERAD inactivation ..." sounds odd. Less ambiguous would be 'To test whether' or 'To ask if'.

      Thank you

      1. p7, beginning of discussion: Please correct "delivered at" to 'delivered to'.

      Thank you

      Reviewer #3 (Significance (Required)):

      This is a concise and convincing manuscript with a clear message. The idea that proteins that cannot be processed by ERAD can be eliminated by other means, for instance by autophagy, is not new. Similarly, the FAM134B- and LC3-dependent pathway for ER-to-lysosome transport has been described by the authors before (Fregno et al, EMBO J 2018). Furthermore, the study exclusively relies on microscopy and does not attempt to tackle new mechanistic questions. Still, this study presents a definite functional advance in our understanding of the interplay of various ER quality control pathways.

      The findings presented here will be of interest mainly to molecular cell biologists working on protein quality control and organelle homeostasis. However, given the disease-relevance of misfolded proteins, and alpha-antitrypsin in particular, the impact of this study may eventually go beyond basic research and may also interest translational researchers.

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      Referee #3

      Evidence, reproducibility and clarity

      In their study, Fasana and colleagues investigate protein quality control in the ER. Specifically, they test whether folding-incompetent proteins that are normally cleared by ER-associated degradation (ERAD) can also be targeted for degradation by direct vesicular transport from the ER to lysosomes in case ERAD is blocked. They show that blocking ERAD pharamacologically or genetically indeed leads to re-rerouting of an ERAD model substrate (the NHK variant of alpha-antitrypsin) to lysosomes and that this pathway requires the reticulon-like protein FAM134B, the ability of FAM134B to interact with the ubiquitin-like protein LC3 and the machinery for LC3 lipidation.

      The paper is, for the most part, easy to follow. There are, however, a few minor issues and I think the authors could do more to connect their work with similar studies in the literature. Accordingly, I have some general and specific suggestions to make the manuscript more accessible for the reader.

      General suggestions

      1. To avoid confusion, it would be helpful to more clearly distinguish between vesicular transport to endolysosomes and autophagy. Previous work by the authors has defined a trafficking pathway from the ER to endolysosomes that appears to rely on conventional vesicle-mediated transport (Fregno et al, EMBO J 2018). This pathway delivers material from the ER lumen to the lumen of endolysosomes, which are both topologically equivalent to the extracellular space. Hence, this pathway is distinct from autophagy, which is the transport of cytoplasmic components to endolysosomes and thus the transport of material from intracellular to extracellular space. This distinction is particularly important as both vesicular ER-to-lysosome transport and autophagy of the ER involve LC3 and FAM134B, which is typically referred to as an ER-phagy receptor. To make this less confusing, it may be helpful to explain that FAM134B appears to be a multifunctional molecule that can function as a receptor for macroautophagy but also in the vesicular transport pathway studied here. In addition, it would be helpful to point out that LC3 appears to also have roles unrelated to autophagosome formation.
      2. Several recent papers that appear relevant to the present study are not mentioned. In particular, Sun et al., Dev Cell 2023 (PMID: 37922908) appears worthy of discussion, as does Gonzalez et al., Nature 2023 (PMID: 37225996).

      Specific suggestions

      1. Abstract: The abstract begins with "About 40% of the eukaryotic cell's proteome is synthesized ... in the ER." Similar statements can be found in many papers and purportedly reflect common knowledge. However, it is unclear where the figure of 'about 40%' comes from. It would be proper to provide a reference and demonstrate that giving such a fairly precise estimate is supported by experimental data. Alternatively, the statement could be modified to avoid being precise than is justified.
      2. p2: "The ER is site of gene expression in nucleated cells and ... native proteins to be delivered at their site of activity ...". There is something missing at the beginning of this sentence. Also, it should be 'delivered to their site of activity', not 'delivered at'.
      3. p2: "... by mechanistically distinct ER-phagy pathways collectively defined as ER-to-lysosome-associated degradation ERLAD." This statement suggests that all pathways subsumed under the term ERLAD are ER-phagy pathways, which I believe is misleading (see comment above on the distinction between autophagy and vesicular transport pathway).
      4. p2: "KIF selectively ...". Please spell out KIF and explain what kind of compound it is.
      5. p3: "Notably, ERAD inhibition delays, rather than blocking degradation of ERAD clients ...". Please correct, for example: Notably, ERAD inhibition delays rather than blocks degradation of ERAD clients ...
      6. Figures 2 - 5: The number of quantified cells is given but it is not clear if experiments were done once or in biological replicates. Please indicate this in the figure legends.
      7. p4: "To verify if ERAD inactivation ..." sounds odd. Less ambiguous would be 'To test whether' or 'To ask if'.
      8. p7, beginning of discussion: Please correct "delivered at" to 'delivered to'.

      Significance

      This is a concise and convincing manuscript with a clear message. The idea that proteins that cannot be processed by ERAD can be eliminated by other means, for instance by autophagy, is not new. Similarly, the FAM134B- and LC3-dependent pathway for ER-to-lysosome transport has been described by the authors before (Fregno et al, EMBO J 2018). Furthermore, the study exclusively relies on microscopy and does not attempt to tackle new mechanistic questions. Still, this study presents a definite functional advance in our understanding of the interplay of various ER quality control pathways.

      The findings presented here will be of interest mainly to molecular cell biologists working on protein quality control and organelle homeostasis. However, given the disease-relevance of misfolded proteins, and alpha-antitrypsin in particular, the impact of this study may eventually go beyond basic research and may also interest translational researchers.

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      Referee #2

      Evidence, reproducibility and clarity

      The endoplasmic reticulum (ER) is a crucial site for protein synthesis and folding within the cell, and strict protein quality control is essential for maintaining ER homeostasis. In this context, ER-associated degradation (ERAD) and the unfolded protein response (UPR) play pivotal roles. Recent researches have highlighted the significance of ER-phagy in protein quality control. In this manuscript, the authors demonstrate the role of FAM134B in degrading misfolded proteins such as ATZ through the ER-phagy pathway when the ERAD pathway is obstructed. This work partially addresses a prominent issue in the field, unveiling the interconnections between different regulatory pathways in maintaining ER homeostasis.

      Major issues:

      1. In a multitude of experiments, the authors employed Bafilomycin A1 (BafA1) to block the fusion between autophagosomes and lysosomes, attempting to demonstrate that the clearance of misfolded proteins mediated by FAM134B is independent of autolysosomes. However, in Figure 4, the lack of rescue of FAM134B knockout by overexpressing FAM134B△LIR suggests a dependence on the interaction between FAM134B and LC3. The conclusions drawn before and after appear contradictory.
      2. Some Western blot data are insufficient to substantiate the author's conclusions. For instance, in Figure 5D, the ATG7 KO line is inadequately supported
      3. The author employed Lamp1 antibody for lysosomal staining in cells and observed a significant abundance of lysosomes in some experiments, as depicted in Figure 2C, 2D, 4I, etc. Is the phenomenon of lysosomes extensively filling the entire cell a common occurrence? Is it indicative of a normal physiological state?

      Minor issues:

      1. Some immunofluorescence experimental data are unclear. Please request the authors to replace these with more distinct images, as seen in Figure 3B and 3E.
      2. Some expressions appear to be questionable. For instance, the necessity of utilizing endolysosomes requires clarification.
      3. Some writing lacks precision, such as referring to FAM134B as FAM134.

      Significance

      • General assessment:
      • Advance: provide an meaningful evidence that how two degradative pathways are coordinated in maintaining ER homeostasis.
      • Audience: cell biologist
      • Reviewer's expertise: autophagy, vesicle trafficking, organelle biolgy
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      Referee #1

      Evidence, reproducibility and clarity

      In this manuscript from Fasana et al., the authors present data that investigates potential compensatory degradation pathways for misfolded glycoproteins in the ER - postulating that the ER-to-lysosome associated degradation (ERLAD) pathway becomes employed in the absence of a path for substrates to reach the ER-associated degradation (ERAD) mechanism. Using the classic ERAD substrate alpha1-antitrypsin NHK variant (NHK), the authors first demonstrate that pharmacologically preventing access of NHK to ERAD either with KIF (early) or PS-341 (late) elevates the number of LAMP-1 positive endolysosomes also immunoreactive for NHK (via HA), similar to what is observed for the ATZ variant that forms polymers in the ER (Fig 2). The authors next use shRNAs that silence essential ERAD factors (EDEM1, OS-9) involved in glycan recognition to demonstrate comparable enrichment of NHK in endolysosomes through genetic disruption (Fig 3). Next, the authors employ FAM134B-deficient MEFs to demonstrate the requirement for this ER-phagy receptor when ERAD is unavailable (Fig 4). Reconstituting FAM134B-/- MEFs treated with KIF/PS-341 + Baf, with a full length FAM134B rescue plasmid restores endolysosomal accumulation of NHK while a FAM134B-∆LIR does not, providing supporting evidence for substrate rerouting to ERLAD. Finally, the authors use knockouts of Atg7 and Atg13 to demonstrate dependence on LC3 lipidation and independence from macro-ERphagy (Fig 6), that points towards a pathway that is like that used to remove ATZ polymers. From these data, the authors conclude that ERLAD is increasingly engaged for substrate degradation when ERAD is impaired.

      Major comments:

      1. All assays rely on quantification of the NHK-HA substrates by microscopy. Would it be possible for the authors to also include biochemical analysis of NHK - potentially including data assessing its changing abundance and glycosylation state?
      2. In Figure 3D, the knockdown of OS-9.1/2 is modest compared to that of EDEM1 (Fig 3A). Moreover, there is only data from single shRNAs presented. Could the authors please at least include another shRNA to confirm and demonstrate whether the targeting to ERLAD is accordingly scaled to loss of access to ERAD (based on the degree of OS-9 or EDEM1 remaining)?
      3. While degradation is implied, it is not specifically demonstrated at any point in the manuscript. Perhaps the authors might include some demonstration of NHK stabilization in one of the figures via a translational shutoff or pulse-chase assay.
      4. 10-30% of NHK-HA positive endolysosomes are detected even with Baf alone (e.g. Fig 2E)? Does this mean that Baf impairs ERAD to some extent since or is it evidence for continuous ERLAD involvement when ERAD is intact? If so, how much is its contribution?
      5. An accounting of how much ERLAD is contributing to NHK degradation with or without ERAD impairment is not really present.. Effectively, how much degradation capacity is ERLAD making up? These would be interesting data to include if possible as they would speak to the "division of labour" for ER substrate degradation its potentially dynamic nature.

      Minor comments:

      1. In Figure 4, an increase is observed for the rescue of FAM134B-/-MEFs with WT FAM134B that is 50% greater that of WT MEFs, suggesting that its availability might be rate limiting. Could the authors compare the relative levels of FAM134B for the WT and KO-rescue MEFs to address this possibility?
      2. In Figures 1 and 6, the terms siOS9 and siEDEM1 are used but Figure 3 shows data from shRNAs and not siRNAs.
      3. Samples from Figure 3 treated with Baf but this is not indicated in the figure or figure legend.
      4. VCP/p97 inhibitors typically stabilize ERAD glycoprotein substrates better than proteasome inhibitors do. Is the same degree of endolysosomal targeting present

      Significance

      Deconvolution of the different pathways taken by misfolded proteins to escape the ER is of great interest not only to the ER community but also represents consequences to consider for those interested in therapeutics involving UPS inhibition. While concise, this manuscript does a good job of trying to demonstrate the principal of substrate rerouting and the prioritisation of degradation pathways. Overall, the manuscript is well written, the experiments presented are performed to a sufficient standard, the data are lean but of good quality, and the appropriate statistical analyses have mostly been included where necessary and are described. The Methods and Materials is brief but describes the experiments that have been performed. The manuscript is brief in its results and would obviously benefit from additional complementary assays that would strengthen and broaden the authors arguments for rerouting. But too their credit, the authors do not grossly overstate their findings and merely present the culmination of a set of experiments to answer a single question - what happens to a misfolded glycoprotein substrate when ERAD is impaired. This is a key question with broad implications.

      While their limited data clearly demonstrates an acquired dependence on ERLAD, one can't help but wonder how broadly these findings hold true, as only a single glycoprotein substrate example is used. Moreover, it is not clear what percentage ERLAD contributes to overall NHK degradation (with or without ERAD) as the total NHK amount remaining is not assessed or measured. Nevertheless, the manuscript is an advancement of understanding of the fate of substrates unable to access ERAD and raises many future questions of interdependency between the ERAD and ERLAD pathways. The data just need a bit of shoring up.

      Expertise - ERAD, UPS, protein quality control

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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

      The authors used hIPSCs to generate spheroids capable of elongation when cultured in KSR and exposed to BMP4. After examining all three developmental lineages of these treatments, the spheroids were embedded in different hydrogels to restrict movement and observed how this affected elongation and lineage differentiation. This manuscript was difficult to review because of the the style of the writing, the sometimes confused narrative of results, the problematic statistics and questionable interpretation of the literature. Authors should actively address the issues presented below with a significant overhaul of the text and presentation.

      Overall comments

      Major concerns - The body of the manuscript should be re-written to offer a coherent narrative that delivers a clear and condensed message . In fact, it was quite surprising given the well written and concise format of the introduction. However, there is some confusion about the interpretation of the first reference (https://doi.org/10.1038/s41586-020-2383-9) in which it was already presented that BMP4 treatment did not induce elongation in a hIPSC-derived gastruloid model. This is not to say that there is anything wrong with repeated experiments and different results, but the results from this reference were interpreted as if BMP4 treatment had induced elongation. The use of the methodology present in this manuscript as opposed to the validated model of using Wnt agonism to induce elongation is not convincingly justified. The results themselves have potential if reworded and condensed but in their current format they are not convincing. Statistics have substantial problems. According to the methodology, only one-way ANOVAs were used, when many of the circumstances would call for t-tests (if parametric) or at least mention the normality tests used to justify the ANOVAs. There is no clear mention of the number of independent differentiations and only one cell line was used. As a result of this, and the state of the statistics and interpretation of the data, the conclusions presented in this paper are inconclusive or misrepresented. The article should be re-written in a coherent scientific style, including not writing in the first person/active voice, and addressing the grammatical errors mentioned below.

      Minor concerns - Throughout the methods there are issues with inconsistent notation, e.g. acronyms aren't always in brackets (HBSS, PBS, KSR), units are sometimes spaced from the value (10ng/mL or 10 µg/mL), units are incorrectly written (u instead of µ). There are also typographical errors such as basic grammar (capital letters and full stops), double spacing, typos, strange sentence construction, as well as interchangeable use of commas and semi colons when listing antibodies. These issues were not confined to the methods, but were particularly noticeable there, and so the whole manuscript requires thorough proofreading. Positive comments - The introduction was well written and concise, the images were mostly clear and easy to interpret, illustrating a result even if not directly the one described.

      Specific Comments

      Introduction - Comments

      The introduction was well written and easy to follow. However, certain aspects should be refined in order to highlight the argument as to why the mechanical forces and environment are of importance to lineage determination in hIPSCs. For example, the paragraph describing 2D micropattern cultures could be reduced or integrated into the introduction of 3D gastruloid models. In its place, further exploration of examples of mechanical force's impact on stem cell/embryonic differentiation, both in vitro and in vivo, would be beneficial (perhaps including the geometric shape aspect mentioned in the 2D micropattern paragraph here instead). This would emphasise the necessity for investigation of environmental forces on 3D in vitro differentiation, tying it back to the first paragraph's broader developmental questions. Currently, it lacks the reiteration of the overarching purpose of this investigation.

      Materials and Methods - Comments

      hIPSC culture - The paper suggests that only one hIPSC line was used for this research; considering the variability innate to each stem cell line and their differentiation capabilities, at least two cell lines should be used. Please reference that stem cell validation was conducted by HipSci. It is concerning that antibiotics were used for tissue culture on such a short protocol and should not be used in future. Similarly, were these hIPSCs tested regularly for mycoplasma? Reference briefly the method in which hIPSCs were passaged and what range of passage number was used.

      Spheroids derivation from hIPSCs - There is no mention of hIPSC confluency upon differentiation. Based on the brief 4 minutes of Accutase exposure, colonies would either be small to achieve single cell dissociation (which is not in the best interest of hIPSC colonies) or that single cell dissociation was not achieved. Seeding density is also close to double seeding density for currently circulating gastruloid protocols (see https://doi.org/10.1242/dev.150391) with no explanation as to why this cell count was chosen. Make mention of whether or not they were fed during the initial 48 hours. There is also no reference to how many independent differentiations were executed and therefore replicability is of significant concern considering the use of an unvalidated protocol.

      Gastrulation-like induction of 3D hIPSCs - Difficult to follow timeline of treatments without reference to Figure 1 and therefore requires a rewrite for clarity. In addition, media 3 and 4 are formatted differently from 1 and 2, making it more confusing. Do not rely on Figure 1 to explain the treatment course, it should be clear in the methodology.

      Live Imaging - No need to state each media, particularly if it is out of numerical order as described previously. Can be written as "Live hIPSC spheroids were imaged for 96 hours....". Also include magnification and time frame of each hour, e.g. between 48 and 96 hours. Immunofluorescence staining - Other than the grammatical errors referenced above, as there are numerous in this paragraph in particular, the catalogue number for each antibody should also be supplied. Considering the number of antibodies, perhaps this would be best supplied as a supplemental table. No mention either here or previously as to how non-encapsulated spheroids were mounted and if cleared.

      Results - Comments

      As mentioned previously, the results are written in a style which is not sufficiently rigorous for a scholarly article and should therefore be edited to reflect the standard expected quality. BMP4 signalling induces axial elongation in 3D gastrulation-like models -

      Figure 1 - Nice and clean diagram but unnecessarily large, could be shrunk and placed at the top of Figure 2. Also is lacking key methodological details e.g. seeding density, reference to media changes in time line, etc.

      An example of a statement that lacks rigor and specificity is the following: "We used defined medium conditions that provided consistent shape variation in spheroid morphology. E8 medium promotes self-renewing conditions, while KSR BMP4 triggers differentiation [31,32]". Self-renewing conditions of what? Differentiation of what? Into what cells?

      These statements are too vague and remain without connection to the research This kind of issues are unfortunately recurrent throughout the manuscript. They are easily rectifiable with concise text rather than expecting the reader to search through references. "Consistent with our previous results..." - not referenced. Mention of size is brief in text and instead description of results is found in Figure 2 legend.

      Figure 2 - Although Figure 2.A and 2.B are clear images, Figure 2.B is unnecessary and doesn't add anything to the message. Figure 2.C: The statistics for this table are hard to believe, except between E8 and KSR BMP4, due to the spread of the data. Change references to "size" to "sphericity", as size would arguably be better investigated using area as a metric, again be precise in choice of language. There isn't even a description of what Figure 2.D is portraying, nor error bars or notation of statistical testing.

      Figure 3 - Figure 3.A Writing on scale bars is too small to be useful and unnecessary if mentioned in the legend. The images highlight the issue with the size/sphericity issue, although the images themselves are reasonably clear and will highlighted (if slightly overexposed and not cleared). The title of this figure is also misleading - E8 BMP4 is not emulating gastruloid development, and the gastruloid-like entity of KSR BMP4 has yet to be validated. A more appropriate title would be "Exposure to BMP4 in spheroid and elongated spheroid culture increases SOX17 expression". There is no mention of how cells were counted in methods and considering the variable fluorescence observed in Figure 3.A OCT4 for E8, this could easily be misconstrued. Inappropriate dictation of p value, should only be reporting the alpha. Much like the similar issue with sphericity, the error bars in Figure 3.E in particular make it difficult to believe the statistical significance achieved. Overall it seems inappropriate to focus solely on endodermal lineage and leave ectoderm and mesoderm to supplementals, when classically axial elongation in gastruloids is punctuated not just by SOX17 but also by BRACH expression throughout the extended region. This suggests that the authors may not have sufficiently evaluated the literature referenced. The justification provided by the authors for choosing SOX17 reinforces this fact by declaring that SOX17 is expressed during early development, as if SOX2 and BRACH isn't! Most concerningly, claims of SOX2's absence in E8 media spheroids as if to be a positive should actually be worrisome, considering SOX2 is a Yamanaka factor. Arguably, without further validation, this result undermines the foundation of this work.

      PEG-peptide hydrogel encapsulation disturbs SOX17 patterning - The interchangeable use of "control" and E8 makes for difficult reading. Although no further substantial issues were taken with Figure 4 that had not already been addressed (scale bars, overexposure), the final comment of this section is simply inaccurate: "Overall, this suggests that embedding hiPSCs in a confining environment blocks morphogenesis, and despite the addition of BMP4, this was not sufficient to enable SOX17 expression.". It does not define that the hIPSCs in this case are spheroids and determines this assumption based off data in Figure 6.B and Figure 6.C which could have been easily integrated into Figure 4. Rather than comparing non-deg PEG to deg-PEG, in order to make this statement, it is necessary to compare the non-embedded spheroids to the embedded spheroids. There is also reference to a Figure 3.C. that does not exist.

      Modulating PEG-peptide degradability promotes SOX17 expression - This section had similar issues to the one above, predominantly flitting between Figure 5 and 6 when it could have been condensed. The microscope images are also particularly poor, with high background in the 488 channel, overexposure for Hoechst and incomplete light penetrance in the centre for both E8 and E8 BMP4. Despite the lack of methodological explanation of how counting was conducted, these aspects are still likely to have had significant impact on cell count regardless of how the count was conducted. The last comment of this section is again questionable, as there is no definitive comparison as to what the deg-PEG is improving upon with regards to SOX17 expression.

      Biochemical cues regulate morphogenesis via cell proliferation and cellular tension - There is no explanation as to why the manuscript pivots away from hydrogels to look at proliferation and F-actin. It does not appear to benefit the overarching goal of this manuscript (i.e. investigating the impact of confinement on 3D hIPSC-derived elongation models), with proliferation investigations feeling like an afterthought and F-actin investigations being placed about 3 sections too late. It was surprising to see EdU to check cell proliferation in this manner; similar can and should be achieved by using KI67 staining. This was a significantly missed opportunity to do pulse-chase experiments to understand potential cell cycle changes, and suggests the experimental design was not thought through. However, it is more reasonable to examine the F-actin network as shown by the manuscript. Although the pipeline in Figure 7.D is an interesting take on quantifying F-actin staining, no statistical analysis was undertaken to confirm a link between conditions and F-actin, nor F-actin and SOX17 expression, despite what this manuscript suggests. This should be coupled with information prior to the introduction to hydrogels, and then re-evaluated in those confined to hydrogels.

      Overall these results need to be substantially edited for clarity, rigor and completeness. The narrative of the results is lost half way through, the statistics are questionable or non-existent and the logic behind certain experiments are debatable.

      Discussion - Comments

      To consider the models generated in this manuscript as gastruloids is misleading and inaccurate and should be replaced with something that reflects what was actually generated, e.g., BMP4-induced elongated spheroids. A quick search of key gastruloid papers, such as https://doi.org/10.1242/dev.113001, indicates how far detached the spheroids examined in this paper are, only sharing similar polarised SOX17 expression. In fact, the above referenced paper already examined aspects of classic gastruloid differentiation when exposed to BMP4, albeit using mESCs, and indicated that elongation only occurred in a proportion of the population. Similarly in the first reference which used hIPSCs specifically, https://doi.org/10.1038/s41586-020-2383-9, it was reported that BMP4 treatment did not induce elongation. At no point in this manuscript were these results discussed, which is concerning. Instead, this manuscript claims to have "robustly" concluded many of the results which have been questioned in detail above, with little reference to the variability across multiple differentiations or adequate statistical analysis. Noticeably they have also not mentioned their results on proliferation, which again makes the question of its relevance to the paper's aims.

      Significance

      The authors used hIPSCs to generate spheroids capable of elongation when cultured in KSR and exposed to BMP4. After examining all three developmental lineages of these treatments, the spheroids were embedded in different hydrogels to restrict movement and observed how this affected elongation and lineage differentiation. This manuscript was difficult to review because of the the style of the writing, the sometimes confused narrative of results, the problematic statistics and questionable interpretation of the literature. Authors should actively address the issues presented here with a significant overhaul of the text and presentation.

      Our expertise is in stem cell biology, 2D and 3D model systems, microscopy, and single cell analysis.

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      Referee #2

      Evidence, reproducibility and clarity

      Within the manuscript "Morphogen-driven human iPSCs differentiation in 3D in vitro models of gastrulation is precluded by physical confinement" by Alsehli et al, the authors aim to dissect the effects of biochemical cues and physical confinement using gastruloid models. Using this model, the authors find some indications that physical confinement prevents morphological changes and reduces lineage commitment of cells (as assayed by Sox 17).

      While the manuscript addresses an interesting and important question, I do not think that the setup and data as present in the manuscript provide conclusive insight in any of the questions studied. First of all, the authors use a very different system (BMP4 induction) as compared to mainstream conditions for gastruloid formation. Based on the images and movies within the manuscript, symmetry breaking and elongation seem to be very sub-optimal under the conditions used by the authors, which makes any further functional assaying highly challenging. Importantly, it remains unclear why the authors did not (at least) include mainstream conditions (Chiron pulse) within their assays for comparative purposes, I feel this is a missed chance. On top of that, KSR is known to be poorly compatible with gastrulation and further development, at least in mouse (https://pubmed.ncbi.nlm.nih.gov/35988542/), so it remains unclear why the authors include a KSR condition.

      Referees cross-commenting

      Like me, both other reviewers indicated (major) shortcomings of the current paper, and indicated potential directions for improvement. Both these other reviews are very balanced as well. Altogether, there are significant changes required for the manuscript, and it depends on the authors which direction they would like to take this manuscript. Hence, I do not know what else to conclude than that in the current format there too many shortcomings to be of added value to current literature (similar to reviewer 3, and in line w/ reviewer 1 but who is somewhat more mild in their evaluation). If the authors decide to move on with this story, this paper requires a re-evaluation of a much improved version.

      Significance

      Secondly, I am not convinced by the data quality and representation in the manuscript. As outlined above, symmetry breaking and elongation seem to be very sub-optimal. Also, Fig 4b and Fig 5b hardly show any visible SOX17, in particular also not in the deg-PEG E8 BMP4 condition. Yet, the authors claim high expression of SOX17 in this condition in Fig 6C, as well as large and significant differences between conditions. To my feeling, Fig 6C does not represent the Sox17 observations of the IF. Similarly, I am not convinced by the EdU staining in Fig 7A. Importantly, the authors base their conclusions on only a single cell line, very few spheroid of this cell line, and an unknown number of biological experimental replicated (which to me seems single experiments). Altogether, the setup and data lacks reliability and robustness.

      Currently, the efficiency of gastruloid formation is a important discussion in the field. Therefore, it is important to report on this in the current manuscript.

      Altogether, while the manuscript makes a few interesting observations, it is very preliminary and not-well worked out or validated. Without being more robust and conclusive, I do not think the manuscript is of much added value to current literature.

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      Referee #1

      Evidence, reproducibility and clarity

      Summary: This manuscript developed a BMP-based culturing protocol for gastruloid-like tissue that eexpresses markers from ectoderm, mesoderm, and endoderm. Through modulating the mechanical properties of extracellular environments, the expression of endodermal marker, SOX17, was found to correlate with the mechanical properties of the extracellular environment. However, the data presented only constitute a crude characterization of the cell lineages within the tissue and, therefore, the biological relevance of the gastruloid-like tissue, together with the associated discoveries, is not immediately evident.

      Major comments

      1. Extra explanation should be provided to justify why mechanical property of extracellular environments is a relevant/important factor for either early embryo development or gastruloid technology.
      2. (OPTIONAL) To demonstrate the impact of mechanical property of extracellular environments, the authors compared two different gels, a stiffer gel with non-significant stress relaxation, and a softer gel with non-trivial stress relaxation. However, such comparison can be somewhat non-intuitive since a variety of mechanical properties are modulated simultaneously between two groups, including both tissue stiffness and its time-dependency. Since it has been well established that both elasticity and viscoelasticity can affect cell behavior, respectively, I would suggest the authors consider adding an extra comparison between a stiff elastic gel and a soft elastic gel.

      Minor comments

      1. The author provided individual staining of SOX2, BRA and SOX17, it would be more helpful to co-stain these markers to demonstrate their relative spatial distribution.
      2. The quantification method for Fig. 7D&E seems missing from the method section, and more explanation for the method would be helpful. What is the area ratio between the inner and outer ROI? What does the y-axis number mean in Fig.7E?
      3. In the last 2nd paragraph of "Biochemical cues regulate morphogenesis via cell proliferation and cellular tension", it was mentioned that "spheroids cultured in E8 medium exhibited organised and tightly packed F-actin with a homogenous network orientation", yet in the next paragraph, it was claimed that "F-actin orientation in round spheroids in E8 medium is mostly distributed in the inner core". Aren't these statements contradictory? Also in this paragraph, it was mentioned "Whereas in KSR conditions, F-actin was distributed in the periphery without significant differences compared to KSR medium conditions", I assume the authors intended to say "KSR BMP4" here?
      4. The authors mentioned that "cells in the KSR BMP4 spontaneously elongate mirroring A-P elongation", yet based on the data presented, the elongation orientation appears more consistent with the D-V embryo axis?

      Significance

      This manuscript demonstrates a rudimentary investigation towards how mechanical properties of the extracellular environment may affect the marker expression within a gastruloid-like tissue. Such information may provide certain useful knowledge for the field of gastruloid. However, compared with the established gastruloid models in the field, the advantage of the tissue model developed in this study isn't very clear. Further, the physiological relevance of extracellular mechanics (and particularly, matrix viscoelasticity, which is studied in this manuscript) is not immediately evident.

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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 is a manuscript that focuses on understanding the function of BLTP2 protein in regulation of ciliation. BLTP family of proteins recently emerged as a lipid transporters in several contexts, such as formation and extension of autophagic membrane. The entire study is build on very intriguing observation that BLTP2 depletion leads to enhanced ciliation in RPE1 cells grown in the presence of serum. That makes BLPT2 a negative regulation of cilia formation that appears to mediate serum-dependent inhibition of ciliation in RPEs. Since molecular machinery governing serum-dependent inhibition of cilia formation remains poorly understood, this study does have a potentially high significance and interest. Unfortunately, most of the study (besides Figure 1) is done using Hela cells. It is a puzzling choice since Hela cells do not form cilia. Additionally, mots analyses are fairly descriptive and do not really lead to any specific hypothesis. As the result author's conclusion is very vague, specifically stating that "BLTP2 may suppress ciliogenesis by altering the lipid dynamics and/or densities of unidentified integral membrane proteins that suppress ciliogenesis". Thus, as it stands, this study does not really lead to new insights in BLPT2-dependent regulation of cilia formation.

      Few specific other comments are listed below.

      1. Figure 1. Two different individual siRNAs for each target should be used (unless authors show rescues) to minimize the possibility of off target effects.
      2. Figure 2-4. Not quite sure what was the rationale to study BLTP2 localization in HeLa cells instead of RPE1. Considering that the main focus of this manuscript is ciliation, one would want to see extensive analysis of localization of BLPT2 in RPE1 cells.
      3. The key to this manuscript (considering its focus on ciliation) would be to look at BLPT2 dynamics in the RPE1 cells in the presence and absence of serum, especially during ciliary vesicle and cilia formation. Instead, authors do most of their analysis in HeLa cells that do not even form cilia.

      Significance

      This is a manuscript that focuses on understanding the function of BLTP2 protein in regulation of ciliation. BLTP family of proteins recently emerged as a lipid transporters in several contexts, such as formation and extension of autophagic membrane. The entire study is build on very intriguing observation that BLTP2 depletion leads to enhanced ciliation in RPE1 cells grown in the presence of serum. That makes BLPT2 a negative regulation of cilia formation that appears to mediate serum-dependent inhibition of ciliation in RPEs. Since molecular machinery governing serum-dependent inhibition of cilia formation remains poorly understood, this study does have a potentially high significance and interest. Unfortunately, most of the study (besides Figure 1) is done using Hela cells. It is a puzzling choice since Hela cells do not form cilia. Additionally, mots analyses are fairly descriptive and do not really lead to any specific hypothesis. As the result author's conclusion is very vague, specifically stating that "BLTP2 may suppress ciliogenesis by altering the lipid dynamics and/or densities of unidentified integral membrane proteins that suppress ciliogenesis". Thus, as it stands, this study does not really lead to new insights in BLPT2-dependent regulation of cilia formation.

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      Referee #2

      Evidence, reproducibility and clarity

      The manuscript by Parolek at al demonstrates the role of Bridge-like lipid transfer protein family member 2 (BLTP2) as a negative regulator of ciliogenesis in cultured retinal pigmental epithelial (RPE-1) cells. Based on genetic interaction of BLTP2 with another ciliogenesis negative regulator, WDR44, a RAB11 effector, the authors mechanistically study the regulation of cilia by these proteins. The authors nicely show Hela cell specific colocalization of BLTP2 and WDR44 in the ER-tubular endosome network membrane contact sites (ER-TEN MCS). They demonstrate that the C-terminus of BLTP2 is necessary for localization to the TEN. They also find that the WDR44 network to be present in higher proportion of Hela cells lacking BLTP2. Interestingly, BLTP2 and WDR44 also localize at tips of GFP-Rab8 and GFP Rab10 tubular membrane network in Hela cells. However, RPE-1 cells do not possess WDR44- and BLTP2-associated tubules, so the context of the TEN with the ciliogenesis phenotype in RPE cells, if any, is presently unclear. The rigor and reproducibility of the presented experiments is high and the presented results are novel for cilia, membrane trafficking, memembrane contact sites and lipid transfer fields. Overall, the authors suggest that BLTP2 and WDR44 are common components of a pathway that suppresses ciliogenesis in serum-fed RPE-1 cells.

      Major comments

      How general are the effects of BLTP2 on ciliogenesis? Effects on ciliogenesis in other cells would consolidate the current results in RPE-1 cells.

      Are the effects on ciliogenesis in RPE cells mediated by the role of BLTP2 and WDR44 in TEN network shown in Hela cells? If not, can the authors demonstrate the subcellular localization of these proteins with respect to ciliogenesis, and optionally if possible with the Rab8-Rabin8-Rab11 cascade? For eg., WDR44 knockdown has been shown to increase peri-centrosomal localization of Rabin8 in serum-fed conditions. Does BLTP2 knockdown have similar effects?

      The authors show that the C-term of BLTP2 is necessary for its recruitment into TEN network, irrespective of WDR44 in Hela cells. Does the C-term of BLTP2 also regulate ciliogenesis?

      Optional: Interactions between BLTP2 and WDR44 are currently unclear other than their colocalization. Can the authors further address if there are close physical interactions between these proteins and/or Rab11?

      Minor comments

      Fig 3C. In merge/inset: please check the white bar.

      If possible, show rescue of ciliogenesis phenotype from BLTP2 knockdown or knockout.

      Significance

      The roles of lipid transfer proteins in ciliogenesis are currently unknown. By showing the function of BLTP2 in ciliogenesis, the authors suggest the possibility of lipid transfer between the ER and the endo-lysosomal network in regulating ciliogenesis pathways. The results showing co-localization of BLTP2 and WDR44 in ER-tubular endosome network membrane contact sites (ER-TEN MCS) is nicely done and the effects on TEN upon WDR44 loss is also very intriguing. Recent papers suggest a role of WDR44 in ciliogenesis and in ciliopathies. The current data will be of broad interest to readers in ciliogenesis, intracellular trafficking, and lipid transport fields. From my own expertise in cilia biology, I think the results are exceptionally novel but needs more context to further solidify the role of BLTP2 in ciliogenesis.

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      Referee #1

      Evidence, reproducibility and clarity

      Summary

      This manuscript by Parolek and Burd addresses the role of the evolutionarily conserved Bridge-like lipid transfer protein 2 (BLTP2) VPS13 family member in negatively regulating ciliogenesis. BLTP proteins are thought to mediate the transfer of lipids between a variety of different organelles, and while BLTP2 loss-of-function in plants and multicellular organism including flies and mice has been connected to various phenotypes, the role of human BLTP2 is poorly understood. In the current study, the authors initially used the Cancer Dependency Map Portal to find a very high mutual co-dependency between the BLTP2 gene and WDR44, a previously well-established negative regulator of primary ciliogenesis. This led the authors to ask whether BLTP2 (similar to WDR44) affects ciliogenesis and indeed they demonstrated that knock-down of either protein in serum-containing RPE1 cells (conditions that normally do not facilitate robust cilia formation) led to an increased percentage of ciliated cells. The authors next addressed the localization of human BLTP2, finding it on ER membranes as well as in linear/tubular structures that correlate with ER subdomains, at least in HeLa cells. Moreover, BLTP2 localization overlapped with that of WDR44. The authors then demonstrated that in BLTP2 knockout cell lines a significantly greater percentage of cells displayed a robust tubular endosome network than in wild-type cells. Finally, the authors show that both BLTP2 and WDR44 tend to localize to the tips of the endocytic tubular network, suggesting that these proteins may localize to contact sites between the ER and (tubular) endosomes, and further, that these contact sites may be required for primary ciliogenesis.

      Major Comments

      This is an interesting manuscript that addresses a poorly understood protein, and potentially provides a novel connection between ER-recycling endosome contact and ciliogenesis. The experimentation is well executed, and the presented data are clear. The strengths of the manuscript lie in partially unveiling new function for BLTP2, functionally associating BLTP2 with WDR44, and the potentially novel relationship between ER-endosome contact sites and ciliogenesis. Moreover, the tubular network of endosomes (which has been primarily implicated in recycling), remains an incompletely understood organelle and this manuscript suggests a new role for it. The weaknesses lie in the preliminary nature of the studies (which in the current form are largely correlative/speculative), and the somewhat descriptive nature of the study. For example, while the proposed connection between ER-endosome contacts, TEN, and cilia is intriguing, there is little attempt to address how such contact sites and TEN might affect ciliogenesis. Developing these ideas would greatly increase the significance of the findings, which as presented are mainly correlative. Other key questions include whether these proteins affect functions previously attributed to tubular endosomes, such as receptor recycling and endocytosis? What is the function of the TEN in maintenance or generation of ER contact sites? There is some literature suggesting that TEN serve in the sorting and/or fission process that might separate Rab5 anterograde transport from Rab4 recycling endosomes, but this is not addressed in the context of the current manuscript. How do ER contact sites and TEN impact ciliogenesis at a molecular level? How might a lipid transfer protein affect primary ciliogenesis? Is the TEN network connected to lipid transfer? Reports hold that PI4,5P2, PI4P, PA and other lipids might be enriched in the TEN; are these (or other lipids in the TEN) affected by BLTP2? In addition, while BLTP2 and WDR44 are linked by localization (and their mutual co-dependency), little attempt has been made to understand how these proteins function together. Do they physically interact? Are Rab8/10 responsible for their recruitment to the tips of endosomes?

      Minor comments:

      Could endogenous Rab proteins be used to address localization of BLTP2 and WDR44 to tubule tips?

      Could the authors please explain how the R=0.61 mutual co-dependency was arrived at? This reviewer used the portal website to find an R value of 0.58. Admittedly these numbers are both very high and the difference between them not significant, but nonetheless they are not identical.

      Significance

      The novelty of this study is that it identifies a new player, BLTP2, involved in the regulation of primary ciliogenesis. Since ciliogenesis impacts so many physiological events and underlies over 100 distinct ciliopathgies, there is clear significance in identifying new proteins that regulate this process (even if hundreds have already been identified). Perhaps the most (potentially) novel finding is the relationship between the ER contact sites, the tubular network of endosomes and ciliogenesis. Few papers have made any connection between tubule generation and ciliogenesis, with the exception of Insinna et al. (Nat Comm., 2019), a paper reporting that the tubular endosome scaffold MICAL-L1 is required for ciliogenesis (Xie et al., J. Cell Sci., 2019), and the recent Biorxiv manuscript by Ott and colleagues suggesting that tubules allow formation of "deconstructed" cilia, none of these connect ciliogenesis to ER contact sites. The limitations of the study are the preliminary nature; as noted, while the individual experiments are clear, substantial data that clearly connect ER contact sites, tubular endosomal networks and ciliogenesis remain largely uncharacterized in this study. In terms of the audience, if a more tangible relationship between ER contact sites/TEN and cilia could be derived, the study would be cross-disciplinary and of interest to a wide audience.

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      1. General Statements [optional]

      Response: We would like to thank both reviewers for their insightful comments. We have addressed most comments in the transferred manuscript and are willing to perform additional experiments to respond to some remaining points, as detailed in the following sections.

      1. Description of the planned revisions

      Insert here a point-by-point reply that explains what revisions, additional experimentations and analyses are planned to address the points raised by the referees.

      Reviewer #1:

      Fig. 5, It would also be interesting to explore the involvement of IFN-I receptors (IFNAR1 vs IFNAR2) by dissecting IFN-α from IFN-β responses.

      Response: Our understanding is that IFNAR1 and IFNAR2 form a heterodimer, which can be activated by both IFN-α and IFN-β. It is thus difficult to dissect the role of individual receptors or cytokines from each other. However, to confirm that IFN-α and IFN-β are both acting through the IFNAR1 receptor to prime for IL-1b activation and release in human neutrophils, we will perform additional experiments by treating neutrophils isolated from healthy individuals with both cytokines individually (as opposed to using them synergistically as in the current manuscript) and blocking their effects by a commercial IFNAR1 blocking antibody. 

      Reviewer #2:

      - The authors are encouraged to specify the number of independent experiments conducted. For mouse model studies, it is recommended to include results that are either representative of, or aggregated from, a minimum of two independent experiments to ensure robustness of the data.

      Response: We did three independent animal experiments in total. The first two experiments involved two time points (2 and 4 days post infection) with different downstream experiments: The first experiment was used for the detection of viral loads by PCR as well as IHC-based quantification of viral antigen and neutrophil influx into the lungs (Exp1, new suppl. Fig 6) while the second experiment (Exp2) was used to isolate neutrophils from the lungs in order to assess neutrophil caspase1 activity and to obtain samples for RNAseq (new Fig.7 A-D). The third experiment (Exp3) was to perform anti-IFNAR and isotype treatments for infected mice; here, all animals were at day 2 post infection. For this experiment we prepared lung samples for IHC and PCR (new suppl Fig. 7) and isolated neutrophils for the assessment of caspase1 activity and for PCR assays (new Fig. 7E-G). We have now improved the text and supplementary Table S2 to indicate these separate experiments more clearly.  In our experience, this approach, i.e. making use of the lungs of oe animals for the determination of several parameters, is of benefit not only because we can directly compare these parameters in a given animal and can thereby reduce the number of animals used for the project (following the 3R principles).

      However, in order to increase sample size and to respond to the various issues raised by the reviewer regarding our mouse work, we have decided to undertake another mouse infection experiment to analyze the effect of the anti-IFNAR treatment on viral loads by assaying for viral titers in the lung sample (which will hopefully directly answer the reviewer’s concerns raised below regarding the effect of anti-IFNAR treatment on viral replication). We will also confirm the negative effect of anti-IFNAR treatment on the expression of IFN-responsive genes by measuring OAS2 mRNA levels by PCR in the lungs of the anti-IFNAR treated as compared to isotype-treated mice. Finally, we will isolate neutrophils from the lungs to repeat the experiment showing the effect of anti-IFNAR treatment on neutrophil inflammasome activity as shown in Fig 7. E-G and will take a sample each for the histological and immunohistological analysis to complement the other tests.

      • The authors are advised to employ more quantitative methods, such as flow cytometry, to measure neutrophil recruitment in mice. Additionally, it should be clarified how many tissue sections from each mouse were assessed for every experimental condition to ensure the reproducibility and statistical validity of the results. 

      Response: While we are not aware that flow cytometry can be considered as a “more quantitative method” than morphometry, we agree that it is an alternative, i.e. complementary quantitative method. Furthermore, we feel that direct quantification of isolated Ly-6G+ neutrophils which are obtained from homogenized lung tissue by magnetic beads (as we have done for some mouse experiments of the current manuscript) is another quantitative approach and a method comparable to flow cytometry. Therefore, we are willing to repeat the mouse infection experiments and quantify the isolated neutrophils in parallel to IHC-based morphometry in order to determine the robustness of our morphometrical neutrophil quantification but are not inclined to undertake flow cytometry, in particular since this would not allow the assessment of all other relevant parameters in the same lung.

      The reviewer asked for information regarding the number of tissue sections that were assessed from each mouse. In our opinion, for quantitative purposes (i.e. morphometry), it is more meaningful to determine the total tissue area that is examined, as different pathologists take different approaches to trim the lung for histological examination (cross sections vs. longitudinal section of a lobe). In our study we examined a tissue area of 19.5 ± 6 mm2 for each lung, which is stated now also in the revised manuscript.

      Revised manuscript, methods section, line 307:

      “The average total tissue area used for the quantification was 19.5 ± 6 mm2”.

      • The authors need to address discrepancies in their text regarding the effects of anti-IFNAR1 blockade on viral titers and neutrophil recruitment in SARS-CoV-2 infected mice. While they state there is no change, Supplementary Figure 5D suggests increased SARS-CoV-2 NP staining with anti-IFNAR1 treatment, and there appears to be a lack of quantitative data on lung neutrophils to substantiate the claim that neutrophil recruitment remains unaffected. It is necessary for the authors to provide a more detailed explanation or additional data to resolve these inconsistencies *

      Response: We did not observe any significant differences in the antigen expression between anti-IFNAR treated and isotype-treated mice. The lack of differences in viral loads was also shown by PCR (suppl Fig. 6B). However, since we are suggesting to repeat the anti-IFNAR experiment which will also include the quantification of viral titers in lung tissue with and without anti-IFNAR treatment, we will gain further insight whether and how IFN-I activity could regulate infection kinetics. We will also repeat the quantification of neutrophils in the lungs of anti-IFNAR and isotype-treated mice by IHC-based morphometry as well as by determining the number of isolated LY-6G+ neutrophils. 

      • The authors should demonstrate the effectiveness of anti-IFNAR1 blockade in mice by providing evidence of sustained inhibition of IFN-I signaling throughout the duration of the experiment to validate the treatment protocol used. 

      Response: We feel the observed inhibition of inflammasome-related pathways by anti-IFNAR treatment strongly argues that blockade of IFNAR activity was successful during the 2 day time course of the direct experiment (Exp3). However, the reviewer’s comment is valid since we have not shown the effect of anti-IFNAR treatment on specific IFN-induced genes. Therefore, we will repeat the anti-IFNAR treatment in infected mice and confirm its negative effect on the expression of IFN-responsive genes by detecting the expression of OAS2 mRNA in lung samples by PCR (OAS2 is one of the mostly upregulated genes by SARS-CoV-2 infection based on our neutrophil transcriptomics analysis). We will also assess whether the treatment directly affects the levels of infectious virus by quantifying viral titers in lung tissue.

      *Referee Cross-Commenting*

      • I agree with Reviewer#1 about trying to dissect the role of IFNAR-1 vs IFNAR-2. Authors partially look at this in the in vivo mice experiments using the anti-IFNAR1 blocking Ab, but it would reinforce the study to see if this holds with human cells. 

      Response: To confirm that IFN-α and IFN-β are both acting through the IFNAR1 receptor to prime for IL-1b activation in human neutrophils, we will perform additional experiments by treating neutrophils isolated from healthy individuals with both cytokines individually (as opposed to using them synergistically as done for the current manuscript) and blocking their effects by a commercial IFNAR1 blocking antibody. 

      The study presents an investigation into the role of neutrophils and inflammasome formation in COVID-19 pathology, contributing to the field with transcriptomic profiling of neutrophils from varying severity of patient cases and a SARS-CoV-2 mouse model. A significant IFN-I gene signature in severe cases was confirmed, and differences in inflammasome response were identified, adding to our understanding of disease mechanisms.

      Strengths of the paper include the comprehensive analysis of neutrophil maturation states and the novel insights into the priming of inflammasome activation by IFN-I. However, limitations were noted in the purity of samples for RNAseq analysis and the lack of conclusive in vivo evidence for the direct role of IFN-I in neutrophil inflammasome priming. The study's implications suggest potential avenues for targeted therapies, but the authors were advised to moderate their conclusions without stronger in vivo evidence and to clarify the potential therapeutic implications of their findings.

      Additional suggestions for improvement include the use of more quantitative methods like flow cytometry for neutrophil recruitment measurements, clarification on experimental replication, and resolving discrepancies in data presentation regarding anti-IFNAR1 blockade effects. Furthermore, the paper would benefit from discussing the relevance of autoantibodies against IFN-I in the context of their findings and from exploring the causal relationship between inflammasome patterns and disease severity.

      Response: We would like to thank the reviewer for highly impactful comments. As suggested, we have redone the RNAseq analysis including only samples of higher neutrophil content, with similar conclusions as those previously made, and have amended the discussion based on the reviewer’s comments. Furthermore, to address the remaining questions raised by the reviewer, we will undertake the following additional animal experiments:

      • Five groups of animals (n = 4);  

      • PBS-inoculated animals 

      • Infected with SARS-CoV-2 for 2 days, treated with isotype 
      • Infected with SARS-CoV-2 for 2 days, treated with anti-IFNAR
      • Infected with SARS-CoV-2 for 2 days 
      • Infected with SARS-CoV-2 for 4 days 

      • Measurements from lung tissue  

      • Quantification of LY-6G neutrophils by morphometry 

      • RT-PCR for OAS2 mRNA (assessment of the successful blockade of IFN-I signaling by IFNAR antibody) 
      • Viral titers by quantification of infectious virus in cell culture (assessment of the successful blockade of IFN-I signaling by IFNAR antibody) 

      • Isolation of LY-6G neutrophils from lung tissue 

      • Quantification of the number of isolated LY-6G neutrophils 

      • Repeating measurement of caspase1 activity 
      • Repeating RT-PCR for caspase1 and IL-1b mRNA

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

      Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. If no revisions have been carried out yet, please leave this section empty.

      Reviewer #1:

      IFN-I promotes immune responses to diverse viruses. Some of them have evolved to dampen IFN-I responses in order to weaken or delay antiviral responses. A number of studies support the idea that this could be the case of SARS-CoV-2 (0.1038/s41586-022-04447-0, 10.1016/j.it.2021.02.003, 10.1038/s41467-022-34895-1, to cite a few). The authors should refer to some of these studies to counterbalance the statements of increased IFN-I response in severe COVID-19 patients in some parts of the manuscript, such as in the Discussion.

      Response: This is a good point and we added discussion on this topic.

      Revised manuscript, discussion section, between lines 634-648:

      “It should be noted that several SARS-CoV-2 encoded proteins have been shown to inhibit IFN-I signaling (60). However, no evidence suggests that neutrophils can be infected by SARS-CoV-2 and therefore it seems unlikely that such direct virus mediated effects could play a role in the observed neutrophil unresponsiveness to IFN-I.  

      The dualistic nature of the IFN-I response in COVID-19 has been recognized previously. It seems that a strong initial IFN-I response to SARS-CoV-2 is more likely to result in asymptomatic or mild COVID-19 whereas a decreased initial IFN-I activity, due to e.g. genetic defects or increased levels of IFN-I autoantibodies, can lead to more severe COVID-19 (61). This initial beneficial effect of IFN-I is probably due to its ability to limit viral replication at early stages of the infection. However, at later stages of the disease IFN-I can be detrimental by promoting inflammatory pathways instead of direct antiviral effects (62). Thus, similarly to the IFN-I response in general, the role of neutrophil inflammasomes in development and severity of COVID-19 might be dualistic in nature with an initial protective effect while damaging when sustained for prolonged periods.”

      1. Rashid F, et al. Roles and functions of SARS-CoV-2 proteins in host immune evasion [preprint]. Front Immunol. 2022;13. https://doi.org/10.3389/fimmu.2022.940756.
      2. da Silva RP, et al. Circulating Type I Interferon Levels and COVID-19 Severity: A Systematic Review and Meta-Analysis. Front Immunol. 2021;12. https://doi.org/10.3389/fimmu.2021.657363.
      3. Smith N, et al. Defective activation and regulation of type I interferon immunity is associated with increasing COVID-19 severity. Nat Commun. 2022;13(1). https://doi.org/10.1038/s41467-022-34895-1.

      In Fig 5, the authors stimulate PMNs from healthy controls in vitro with IFN-I and use mainly IL-1b as a readout for neutrophil priming. The authors should analyse whether IFN-I-mediated priming ultimately leads to NETosis, given the relevance of NETs to COVID-19 pathology (10.1016/j.tips.2023.06.007), which is acknowledged by the authors in the Introduction.

      Response: We agree that NETosis is a potential outcome of neutrophil activation. This is in part why we assayed for the release of MPO, which can be used as a marker of NETosis, in the ex vivo activated PMNs. However, while a clear increase in MPO levels was observed in response to nigericin treatment, no increase was seen with IFN-I or LPS treatments alone in COVID-19 or HC PMNs (Fig. 4C). We slightly modified the text to make it clearer that MPO served to detect PMN degranulation and NETosis in our study. 

      Revised manuscript, results section, lines 440-444:

      “However, the release of myeloperoxidase (MPO), used as a marker of degranulation and/or NETosis, in response to nigericin was similar between COVID-19 PMNs and HC PMNs, and therefore the observed diminished IL-1β release by COVID-19 PMNs is not due to general cellular inertia but may be specific to the ex vivo induced inflammasome pathway.”

      In Methods (Histology and immunohistochemistry), the authors mention that histone H3 is a NET marker and use this in Supp Fig 5 to support evidence of NETosis. The authors should state which antibody clone/company was used. Histone H3 is expressed in high levels by non-NETotic neutrophils. Citrullinated histone H3 (CitH3), on the other hand, is detectable by few commercially available antibodies and can be used as a NET marker in conjunction with other markers such as DNA staining (10.1084/jem.20201129).

      Response: For immunohistochemical detection of NETosis, we have used the following antibody: rabbit anti-histone H3 (citrulline R2 + R8 + R17; Abcam). We have provided a reference to a publication of a co-author (Schmid AS, et al. Antibody-based targeted delivery of interleukin-4 synergizes with dexamethasone for the reduction of inflammation in arthritis. Rheumatology (United Kingdom). 2018;57(4):748–755. Doi: 10.1093/rheumatology/kex447) which includes this information and fully describes the staining protocol. We admit that our labelling of the figure and the text was misleading by stating that the used antibody was anti-histone H3 instead of indicating that an antibody detecting citrullinated form of histone H3 was used. We have therefore relabeled Supplementary Fig. 7 and rewritten the text to indicate this more clearly.

      In the publication kindly referred to by the reviewer, the following antibody was used: rabbit anti-histone H3 (H3Cit; Abcam; cat. ab5103; 1:500) in immunofluorescence, where DAPI fluorescence served to highlight the DNA. We generally work with immunohistochemistry instead of immunofluorescence as it allows better alignment with histopathological features. However, we have now applied the anti-H3cit antibody in a fluorescence protocol, using the same tissues and antibody as shown in the immunohistochemistry image of suppl. Fig7, to indicate that the used antibody works equally well in immunofluorescence and immunohistochemistry.

      In the PDF version of this revision there is a figure plate that shows: NET IHC, showing abundant expression in the lumen of a bronchiole (top) and NET IF, showing part of a bronchiole with NET (green) and nuclei (DAPI; blue) and a closer view (bottom) with NET expression in a cell with the nuclear morphology of a neutrophil (arrowhead).

      In Fig 8, the authors show that neutrophils migrate to the lungs of infected animals. This finding is showed in many previous studies and does not seem to favour the structure of the manuscript. Insteand, it seems it would fit a Supp Fig better, or a portion of the following figure.

      Response: We are aware that neutrophil recruitment into the lungs with SARS-CoV-2 infection has been shown previously. However, this was so far not done in the model that we have used, mouse-adapted SARS-CoV-2 infection in wild type (BALB/C) mice in which the infection is short-lived and wanes off after 4 days (Gawish et al., 2022). We are happy to move this figure plate to the Supplements as Reviewer #2 shares this opinion. In the revised manuscript, it now features as Supplementary Fig. 6.

      Reviewer #2:

      Major points:

      -Figure 2A: for this RNAseq analysis, the authors claim that "This analysis also demonstrated that cells in the LDG fraction were predominantly immature neutrophils, meanwhile PMNs were composed of mainly mature neutrophils (Figure 2A)". Nevertheless, there are 2 samples in the "Severe COVID-19" group that show a fraction of neutrophils {less than or equal to}0.6, which indicates low levels of purity. In addition, there is one "PMN" sample with high LDG fraction (around 40%). Authors should remove from this analysis samples with such a low purity since the big fraction ({greater than or equal to}40%) of contaminating cells could introduce a bias in this group. Are the differences observed still present in the absence of these low-purity samples?

      Response: For Figure1 of the original manuscript, we first performed the analyses including all the samples, and after assessing their purity, included only the samples with highest purity in the following figures. However, we followed the reviewer’s recommendation and redefined the purity of the samples as >65% of total neutrophils, independent of their maturity. Of note, unlike the reviewer suggests, we did not remove the one “PMN” sample with high degree of immaturity, since PMNs and LDGs are defined based on their isolation method and not their degree of maturity. Along these lines, we have decided to move the new unsupervised heatmap and present it together with the RNA deconvolution plot as supplementary Figure 1. Therefore, Figure 1 now contains the samples with high purity based on the redefined criteria, with PCA in panel A, pathway analyses in panel B (PMN vs LDG) and interferon-related genes heatmap in panel C. We also redid suppl Fig. 2 to include samples with the redefined criteria and modified the results text accordingly.

      Revised manuscript, results section, lines 333-380:

      “Unsupervised RNA-seq analysis reveals an antiviral gene expression signature of circulating neutrophils in COVID-19 that is strongly influenced by maturity

      With our recent findings on increased frequencies of low-density granulocytes (LDGs, isolated from the PBMC fraction) during COVID-19 and their likely relevant role in disease progression (7), we sought to understand in more detail how the transcriptomic profile of LDGs differs from their higher “normal” density counterpart, the circulating polymorphonuclear cells (PMNs) (31), typically consisting mainly of mature neutrophils. Neutrophils isolated from different cohorts comprised three PMN groups (severe COVID-19, mild COVID-19, and healthy controls), and one LDG group. Initial deconvolution of the RNA sequencing (RNA-seq) data allowed us to gain a comprehensive understanding of the cellular composition within PMN and LDG fractions and verified that most cells present in the samples were neutrophils (Supplementary Figure 1A). This analysis also demonstrated that cells in the LDG fraction were predominantly immature neutrophils, meanwhile PMNs were composed of mainly mature neutrophils.

      The samples with predominant neutrophil cell populations were selected for subsequent gene expression analysis (neutrophils ≥ 65 %). The high variance in gene expression between PMNs and LDGs was confirmed by principal component analysis (PCA) (Figure 1A), which revealed that the gene expression patterns of COVID-19 LDGs differed from those of all PMNs regardless of the patients’ disease state. Functional enrichment analyses through gene overrepresentation (ORA) and gene-set enrichment analyses (GSEA) (Figure 1B) compared PMNs with LDGs from severe COVID-19 patients. The most statistically significant result was an overrepresentation of the NOD-like receptor signaling pathway in PMNs in contrast with LDGs, highlighting that the different neutrophil fractions have a distinct inflammatory profile. This was supported by GSEA, where the most obvious increases in fold changes were the enrichment of the interferon signaling pathways. Another relevant difference was the cell cycle and DNA replication pathways, identified by both ORA and GSEA, which supported our previous findings suggesting LDGs to be predominantly immature cells (7). Furthermore, a heatmap of selected type I IFN (IFN-I) related genes confirmed a robust IFN-I gene signature in severe COVID-19 PMNs, while LDGs from severe COVID-19 distinctively lacked this signature (Figure 1C). Unsupervised clustering analysis, namely Iterative Clustering and Guide Gene Selection (ICGS) using the AltAnalyze software, supported these findings by identifying the top 118 differentially expressed (DE) genes, including several IFN-related genes (Supplementary Fig. 1B). Similarly to the selected samples included in Figure 1, this analysis classified the samples into two major clusters: a first one containing all isolated LDG samples, and a second one comprising all isolated PMN samples. The former cluster consisted of neutrophil antimicrobial and granule marker genes (e.g. DEFA3, DEFA4, SERPINB10, CTSG), while in the latter cluster the most significantly upregulated genes in the PMNs from severe COVID-19 subgroup were mainly interferon inducible (e.g. IFI44L, IFI6, GBP3, IRF7). These differences were supported by a detailed gene analysis (Supplementary Fig. 2A).

      Inflammasomes are activated in severe COVID-19 PMNs, but not directly by SARS-CoV-2

      Looking more closely into PMN fractions, pathway analyses identified the inflammasome related NOD-like and RIG-like receptor signaling pathways among the most significantly overrepresented pathways, differentially expressed in severe COVID-19 PMNs versus HC PMNs (Figure 2A and Supplementary Fig. 2B-C) or mild COVID-19 PMNs (Figure 2B and Supplementary Fig. 2D, E). However, mild COVID-19 PMNs did not significantly differ from HC PMNs in their inflammatory profile (Supplementary Fig. 2F).”

      Finally, to respond to the reviewer’s specific question concerning whether the observed differences are still present in the absence of the newly defined low-purity samples, we can conclude that the results continue to highlight the differences we had previously described (increased cell cycle and metabolism-related pathways in LDGs and a distinct IFN-I signature in severe COVID-19 PMNs). 

      - While the in vitro data suggest that IFN-I may prime the inflammasome response in neutrophils, in vivo evidence remains inconclusive. The systemic blockade of IFNAR1 with antibodies in infected mice does not confirm that IFN-I directly primes neutrophil inflammasomes, as other cells could initially sense IFN-I and subsequently produce neutrophil-activating stimuli. In the absence of in vivo experiments utilizing conditional IFNAR1 knockout models, such as Mrp8-Cre x IFNAR1 fl/fl mice, the authors should consider moderating the stated significance of these findings in the discussion about the limitations of the study.

      Response: We agree with the reviewer on this point. Thus, we modified the “limitations of study” paragraph in the discussion.

      Revised manuscript, discussion section, lines 674-677:

      “Furthermore, the observed inhibitory effects on neutrophil inflammasome activity by IFNAR blockade does not exclude the possibility that IFN-I could promote neutrophil inflammasome formation by indirect effects such as stimulating the release of pro-inflammatory cytokines by other cell types.” 

      - Given the reports of life-threatening COVID-19 infections occurring in conjunction with autoantibodies against type I IFNs (DOI: 10.1126/science.abd4585), the authors should explore how this intersects with their findings. A discussion is needed on whether patients with such autoantibodies may exhibit inflammasome activation patterns similar to the severe cases in this study, which could provide valuable insights into patient stratification and treatment approaches.

      Response: This is a good point, thank you. Based on our data it is unlikely that patients with IFN-I autoantibodies or genetic defects in the production of IFN-I would show significant neutrophil inflammasome activation. Like with IFN-I response in general, neutrophil inflammasomes can probably be either protective or damaging to the host, depending on the context and durability of the response. We have discussed this topic further in the revised manuscript, in response to this concern and the first point of reviewer 1.

      Revised manuscript, discussion section, lines 639-648:

      “The dualistic nature of the IFN-I response in COVID-19 has been recognized previously. It seems that a strong initial IFN-I response to SARS-CoV-2 is more likely to result in asymptomatic or mild COVID-19 whereas a decreased initial IFN-I activity, due to e.g. genetic defects or increased levels of IFN-I autoantibodies, can lead to more severe COVID-19 (61). This initial beneficial effect of IFN-I is probably due to its ability to limit viral replication at early stages of the infection. However, at later stages of the disease IFN-I can be detrimental by promoting inflammatory pathways instead of direct antiviral effects (62). Thus, similarly to the IFN-I response in general, the role of neutrophil inflammasomes in development and severity of COVID-19 might be dualistic in nature with an initial protective effect while damaging when sustained for prolonged periods.” 

      - The authors need to delve deeper into whether the inflammasome patterns observed in severe COVID-19 cases are a contributing factor to the disease's progression or a result of the infection's severity, thereby clarifying the causality in their discussion.

      Response: This is an important aspect of the study and we agree that the relationship between neutrophil inflammasome activity and disease severity could be highlighted better. However, understanding causality by analyzing clinical patient samples is difficult due to the typical lack of patient samples from the early phase of the disease. Hospitalization and thereby patient sample collection typically occurs when the patients are already experiencing the peak of symptomatic phase of the disease. To highlight the link between neutrophil inflammasome formation and disease severity more clearly, we have marked the statistically significant correlations between inflammasome activation and disease severity parameters by an asterisk in the correlation plot (Fig. 5) and added text in the discussion accordingly.

      Revised manuscript, discussion section, lines 649-654:

      “Our study demonstrated a strong association between PMN caspase1 activity and plasma levels of calprotectin, a marker of neutrophil activation. Additionally, increased disease severity, as assessed by the WHO ordinal scale, was significantly linked to PMNs being less responsive to ex vivo IFN-induced inflammasome activation, which is suggestive of prior in vivo inflammasome activation. Thus, these results suggest that neutrophil inflammasomes play a potential role in disease severity rather than being protective in COVID-19.” 

      This point links to the previous comment by the reviewer regarding the role of IFN-I in disease severity. We have added text in the discussion highlighting the dual nature of the IFN-I response and neutrophil inflammasome activation in COVID-19 disease severity (see response above).     

      -Authors should clarify if and how their findings may lead to any therapeutic advantage for severe COVID-19 patients.

      Response: The text has been adapted accordingly, and more details have been added into the revised manuscript.

      Revised manuscript, discussion section, lines 685-687:

      For example, pharmacologically targeting the inflammasome pathway in neutrophils with novel inhibiting molecules, may help mitigate the exaggerated inflammatory response observed in severe cases.”

      Reference added: Mangan, M. S., Olhava, E. J., Roush, W. R., Seidel, H. M., Glick, G. D., & Latz, E. (2018). Targeting the NLRP3 inflammasome in inflammatory diseases. Nature reviews Drug discovery, 17(8), 588-606.

      Minor points:

      - Authors should increase the font in all the figures as most of them are difficult to be read

      Response: Thank you for your suggestion. The font sizes have been increased, but their size will ultimately depend on the requirements of the journal where is the work will be published.

      Thank you for your suggestion. The font sizes have been increased, but their size will ultimately depend on the requirements of the journal where the work will be published.

      - Authors should better clarify how the choice for statistics tests was conducted "depending on sample distribution and the number of groups analyzed" in the Methods.

      Response: We added additional details to the methods.

      Revised manuscript, methods section, lines 329-331:

      “To elaborate, nonparametric tests like Mann-Whitney and Kruskall-Wallis were employed when the data violated assumptions of normality, while ANOVA tests were applied when the data met parametric assumptions”. 

      Referee Cross-Commenting*

      -I agree with Reviewer#1 with adding relevant references about the evolution of some viruses, including SARS-COV-2, in evading type I IFN response.

      Response: We added this information into the manuscript.

      Revised manuscript, discussion section, lines 635-638:

      “It should be noted that several SARS-CoV-2 encoded proteins have been shown to inhibit IFN-I signaling. However, no evidence suggests that neutrophils can be infected by SARS-CoV-2 and therefore it seems unlikely that such direct virus mediated effects could play a role in the observed neutrophil unresponsiveness to IFN-I".   

      Reference added: Rashid F, et al. Roles and functions of SARS-CoV-2 proteins in host immune evasion [preprint]. Front Immunol. 2022;13.

      -I agree with Reviewer#1 about Figure 8 not delivering a novel message. I also suggest to move this to the supplementary section.

      Response: We have moved the figure plate to the Supplements. 

      1. 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 #2

      Evidence, reproducibility and clarity

      The authors of this study seek to examine the role of neutrophils, particularly their inflammasome formation potential, in the pathophysiology of COVID-19. They conducted transcriptomic profiling of neutrophils from both mild and severe COVID-19 patients, as well as SARS-CoV-2 infected mice, and compared these profiles to non-infected healthy controls. Their analysis confirmed a prominent IFN-I gene signature in severe cases previously reported by others. Furthermore, they observed that neutrophils from severe COVID-19 patients have an altered response to inflammasome activation and that IFN-I can serve as a priming stimulus for neutrophil inflammasomes, a finding further supported by a COVID-19 mouse model. Last, in this study the authors revealed that in severe COVID-19, LDGs show gene upregulation indicating immaturity, while PMNs exhibit enhanced pathogen-responsive NLR signaling.

      Major points:

      • Figure 2A: for this RNAseq analysis, the authors claim that "This analysis also demonstrated that cells in the LDG fraction were predominantly immature neutrophils, meanwhile PMNs were composed of mainly mature neutrophils (Figure 2A)". Nevertheless, there are 2 samples in the "Severe COVID-19" group that show a fraction of neutrophils {less than or equal to}0.6, which indicates low levels of purity. In addition, there is one "PMN" sample with high LDG fraction (around 40%). Authors should remove from this analysis samples with such a low purity since the big fraction ({greater than or equal to}40%) of contaminating cells could introduce a bias in this group. Are the differences observed still present in the absence of these low-purity samples?

      • While the in vitro data suggest that IFN-I may prime the inflammasome response in neutrophils, in vivo evidence remains inconclusive. The systemic blockade of IFNAR1 with antibodies in infected mice does not confirm that IFN-I directly primes neutrophil inflammasomes, as other cells could initially sense IFN-I and subsequently produce neutrophil-activating stimuli. In the absence of in vivo experiments utilizing conditional IFNAR1 knockout models, such as Mrp8-Cre x IFNAR1 fl/fl mice, the authors should consider moderating the stated significance of these findings in the discussion about the limitations of the study.

      • The authors are encouraged to specify the number of independent experiments conducted. For mouse model studies, it is recommended to include results that are either representative of, or aggregated from, a minimum of two independent experiments to ensure robustness of the data

      • The authors are advised to employ more quantitative methods, such as flow cytometry, to measure neutrophil recruitment in mice. Additionally, it should be clarified how many tissue sections from each mouse were assessed for every experimental condition to ensure the reproducibility and statistical validity of the results.

      • The authors need to address discrepancies in their text regarding the effects of anti-IFNAR1 blockade on viral titers and neutrophil recruitment in SARS-CoV-2 infected mice. While they state there is no change, Supplementary Figure 5D suggests increased SARS-CoV-2 NP staining with anti-IFNAR1 treatment, and there appears to be a lack of quantitative data on lung neutrophils to substantiate the claim that neutrophil recruitment remains unaffected. It is necessary for the authors to provide a more detailed explanation or additional data to resolve these inconsistencies

      • The authors should demonstrate the effectiveness of anti-IFNAR1 blockade in mice by providing evidence of sustained inhibition of IFN-I signaling throughout the duration of the experiment to validate the treatment protocol used.

      • Given the reports of life-threatening COVID-19 infections occurring in conjunction with autoantibodies against type I IFNs (DOI: 10.1126/science.abd4585), the authors should explore how this intersects with their findings. A discussion is needed on whether patients with such autoantibodies may exhibit inflammasome activation patterns similar to the severe cases in this study, which could provide valuable insights into patient stratification and treatment approaches

      • The authors need to delve deeper into whether the inflammasome patterns observed in severe COVID-19 cases are a contributing factor to the disease's progression or a result of the infection's severity, thereby clarifying the causality in their discussion.

      • Authors should clarify if and how their findings may lead to any therapeutic advantage for severe COVID-19 patients.

      Minor points:

      • Authors should increase the font in all the figures as most of them are difficult to be read

      • Authors should better clarify how the choice for statistics tests was conducted "depending on sample distribution and the number of groups analyzed" in the Methods.

      Referee Cross-Commenting

      • I agree with Reviewer#1 with adding relevant references about the evolution of some viruses, including SARS-COV-2, in evading type I IFN response.

      • I agree with Reviewer#1 about trying to dissect the role of IFNAR-1 vs IFNAR-2. Authors partially look at this in the in vivo mice experiments using the anti-IFNAR1 blocking Ab, but it would reinforce the study to see if this holds with human cells.

      • I agree with Reviewer#1 about Figure 8 not delivering a novel message. I also suggest to move this to the supplementary section.

      Significance

      • The study presents an investigation into the role of neutrophils and inflammasome formation in COVID-19 pathology, contributing to the field with transcriptomic profiling of neutrophils from varying severity of patient cases and a SARS-CoV-2 mouse model. A significant IFN-I gene signature in severe cases was confirmed, and differences in inflammasome response were identified, adding to our understanding of disease mechanisms.

      • Strengths of the paper include the comprehensive analysis of neutrophil maturation states and the novel insights into the priming of inflammasome activation by IFN-I. However, limitations were noted in the purity of samples for RNAseq analysis and the lack of conclusive in vivo evidence for the direct role of IFN-I in neutrophil inflammasome priming. The study's implications suggest potential avenues for targeted therapies, but the authors were advised to moderate their conclusions without stronger in vivo evidence and to clarify the potential therapeutic implications of their findings.

      • Additional suggestions for improvement include the use of more quantitative methods like flow cytometry for neutrophil recruitment measurements, clarification on experimental replication, and resolving discrepancies in data presentation regarding anti-IFNAR1 blockade effects. Furthermore, the paper would benefit from discussing the relevance of autoantibodies against IFN-I in the context of their findings and from exploring the causal relationship between inflammasome patterns and disease severity.

      • The study is of relevance to immunologists specializing in viral infections and researchers focused on neutrophil biology.

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      Referee #1

      Evidence, reproducibility and clarity

      • IFN-I promotes immune responses to diverse viruses. Some of them have evolved to dampen IFN-I responses in order to weaken or delay antiviral responses. A number of studies support the idea that this could be the case of SARS-CoV-2 (0.1038/s41586-022-04447-0, 10.1016/j.it.2021.02.003, 10.1038/s41467-022-34895-1, to cite a few). The authors should refer to some of these studies to counterbalance the statements of increased IFN-I response in severe COVID-19 patients in some parts of the manuscript, such as in the Discussion.

      • In Fig 5, the authors stimulate PMNs from healthy controls in vitro with IFN-I and use mainly IL-1b as a readout for neutrophil priming. The authors should analyse whether IFN-I-mediated priming ultimately leads to NETosis, given the relevance of NETs to COVID-19 pathology (10.1016/j.tips.2023.06.007), which is acknowledged by the authors in the Introduction. It would also be interesting to explore the involvement of IFN-I receptors (IFNAR1 vs IFNAR2) by dissecting IFN-a from IFN-b responses.

      • In Methods (Histology and immunohistochemistry), the authors mention that histone H3 is a NET marker and use this in Supp Fig 5 to support evidence of NETosis. The authors should state which antibody clone/company was used. Histone H3 is expressed in high levels by non-NETotic neutrophils. Citrullinated histone H3 (CitH3), on the other hand, is detectable by few commercially available antibodies and can be used as a NET marker in conjunction with other markers such as DNA staining (10.1084/jem.20201129).

      • In Fig 8, the authors show that neutrophils migrate to the lungs of infected animals. This finding is showed in many previous studies and does not seem to favour the structure of the manuscript. Instead, it seems it would fit a Supp Fig better or a portion of the following figure.

      Significance

      By conducting transcriptomics analyses, Cabrera LE et al. elucidate the inflammasome formation in neutrophils during SARS-CoV-2 infection. The authors have found a strong IFN-I signature in neutrophils from severe COVID-19 patients and show that IFN-I functions as a priming stimulus for neutrophil inflammasome.

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      1. General Statements

      We thank the reviewers for their excellent work that greatly improved our work. We are very content that reviewer #1 considered our work to be “novel, interesting and important for understanding the mitochondrial biology of PD”. This reviewer also valued our work as “a significant advancement” and suggested further study of the relationship of CISD1 (dimerization) to general mitophagy/autophagy. We addressed this in the already transferred revision (version 1, v1).

      Also reviewer #2 considered our work to be “an exciting and well-executed piece of research focusing on the defects in iron homeostasis observed in Parkinson's disease which a wide audience will appreciate”. This reviewer had a very specific suggestion on how to improve our manuscript which makes a lot of sense and is feasible. As the suggested experiments include fly breeding and behavioral analysis, these experiments will be included in the second revision to be uploaded as soon as possible (version 2, v2).

      Finally, reviewer #3 gathered that parts of our results “are confirmatory to recently published work” but also appreciated that our results established that iron-depleted apo-Cisd is an important determinant of toxicity which has not been shown before. I would like to comment here, that in contrast to the paper mentioned by this reviewer, our contribution includes data from dopaminergic neurons obtained from human patients suffering from familial Parkinson’s disease that demonstrate the same increase in apo-Cisd levels as the flies. This reviewer mainly suggested that the manuscript would be improved by a more balanced discussion of the strengths and weaknesses of the study and more circumspection in interpretation of data which we did in the revised version of our manuscript. We also added data on the expression levels of Cisd and apo-Cisd in transgenic flies as also suggested.

      2. Description of the planned revisions

      Reviewer #1 (Evidence, reproducibility and clarity):

      Summary: The manuscript focuses on mitochondrial CISD1 and its relationship to two Parkinson's disease (PD) proteins PINK1 and Parkin. Interestingly, CISD1 is a mitochondrial iron sulfur binding protein and an target of Parkin-mediated ubiquitinylation. Disruption of iron metabolism and accumulation of iron in the brain has long since been reported in PD but the involvement of iron sulfur binding is little studied both in vivo and in human stem cell models of PD. This work addresses the relationship between CISD1 and two mitochondrial models of PD (PINK1 and Parkin) making use of in vivo models (Drosophila), PINK1 patient models (iPSC derived neurons) and Mouse fibroblasts. The authors report a complex relationship between CISD1, PINK1 and Parkin, where iron-depleted CISD1 may illicit a toxic gain of function downstream of PINK1 and Parkin.

      Major comments:

      The conclusions are overall modest and supported by the data. One question remains unaddressed. Is mitochondrial CISD1 a downstream target that specifically mediates PINK1 and Parkin loss of function phenotypes or are the phenotypes being mediated because CISD1 is downstream of mitophagy in general?

      It would be interesting to know what happens to CISD1 (dimerization?) upon initiation of mitophagy in wild type cells? Would dissipation of mitochondrial membrane potential be sufficient to induce changes to CISD1 in wild type cells or PINK1 deficient cells? Since iron chelation is a potent inducer of mitophagy (Loss of iron triggers PINK1/Parkin-independent mitophagy. George F G Allen, Rachel Toth, John James, Ian G Ganley. EMBO Reports (2013)14:1127-1135) it would be useful to show one experiment addressing the role of CISD1 dimerization under mitochondrial depolarizing and non-depolarizing conditions in cells.

      Based on the overall assumption of the reviewer that our work is “novel, interesting and important for understanding the mitochondrial biology of PD” and “a significant advancement” we understand the word “modest” here as meaning “not exaggerated”. To address this question, we studied CISD1 dimerization in response to more classical activators of mitophagy namely FCCP and antimycin/oligomycin which had no significant effect on dimerization suggesting that this phenotype is more pronounced under iron depletion. These data are shown in the new Fig. 2c.

      Alternatively, the authors should discuss the topic of mitophagy (including PINK1-parkin independent mitophagy), the limitation of the present study not being able to rule out a general mitophagy effect and previous work on the role of iron depletion on mitophagy induction in the manuscript.

      The data and the methods are presented in such a way that they can be reproduced.

      The experiments are adequately replicated and statistical analysis is adequate.

      Minor comments:

      Show p values even when not significant (ns) since even some of the significant findings are borderline < p0.05.

      Here, I decided to leave it as it is, because the figures became very cluttered and less easy to understand. Borderline findings are however indicated and mentioned in the text.

      Because the situation for CISD1 is complicated (overexpression, different models etc.) it would be helpful if in the abstract the authors could summarize the role. E.g. as in the discussion that iron-depleted CISD1 could represent a toxic function.

      The abstract has been completely rewritten and now mentions the potential toxic function of iron-depleted CISD1.

      If there is sufficient iron (accumulation in PD) why would CISD1 be deactivated? Perhaps that could be postulated or discussed in a simplified way?

      We actually think that apo-CISD1 without its iron/sulfur cluster is incapable of transferring its Fe/S cluster to IRP1 and IRP2. This then results in increased levels of apo-IRP1/2 and subsequent changes that lead to iron overload. Such a sequence of events would place CISD1 upstream of the changes in iron homeostasis observed in PD and models of PD. This is now discussed in more detail.

      In the methods section both reducing and non-reducing gel/Western blotting is mentioned but the manuscript only describes data from blots under reducing conditions. Are there blots under non-reducing conditions that could be shown to see how CISD1 and dimerized CISD1 resolve?

      We now show these blots as supplemental data in new supplemental Figure 2.

      In the results section, PINK1 mutant flies, it is said that the alterations to CISD1 (dimerization) are analogous to the PINK1 mutation patient neurons. The effect is seen in old but not young flies. Since iPSC-derived neurons are relatively young in the dish, would one not expect that young flies and iPSC-derived neurons have similar CISD1 phenotypes? Could the authors modify the text to reflect that? or discuss the finding in further context.

      We only studied one time point in PINK1 mutation patient neurons and controls. It would indeed be interesting whether neuronal aging (as far as this can be studied in the dish) would result in increased CISD1 dimerization. This is now discussed.

      Reviewer #1 (Significance):

      The strengths of this work are in the novelty of the topic and the use of several well established in vivo and cell models including patient-derived neurons. The findings discussed in the text are honest and avoid over-interpretation. The findings are novel, interesting and important for understanding the mitochondrial biology of PD.

      We thank the reviewer for their kind words.

      Limitations include the lack of strong phenotypes in the CISD1 models and the lack of robust, sustained and consistent increase in CISD1 dimers in the patient and fly models (just significant because of variability). The relationship of CISD1 (dimerization) to general mitophagy/autophagy is not shown here.

      We do not completely agree with the assumption that all CISD1 models lack a strong phenotype. At least the CISD1-deficient fibroblasts exhibit a strong phenotype consisting of fragmented mitochondria and increased oxidative stress. The lack of a strong phenotype in Cisd-deficient flies could actually hint to a potential compensatory mechanism that could also protect the Pink1 mutant x Cisd-deficient double-knockout flies. It is correct that the increase in CISD1/Cisd dimers in the PD models are not overwhelming but – as also mentioned by the reviewer – this could be increased in “older” cultures. This is now discussed in more detail. As suggested by the reviewer, we have now added experiments that study the relationship between CISD1 dimerization and conventional mitophagy as described above.

      There is a significant advancement. So far researchers were able to describe the importance of iron metabolism in PD (For example refer to work from the group of Georg Auburger such as PMID 33023155 and discussion of therapeutic intervention such as reviewed by Ma et al. PMID: 33799121) but few papers describe involvement of iron sulfur cluster proteins specifically (such as Aconitase) in relation to PINK1 and parkin (these are cited). The fact that CISD1 is a protein of the mitochondrial outer membrane makes it particularly interesting and further studies looking more closely at the interaction of CISD1 with mitochondrial proteins associated with PD will be of interest.

      We thank the reviewer for pointing out these excellent publications. Key et al present an enormous wealth of data on protein dysregulation of wildtype and Pink1-/- fibroblast cell lines upon perturbation of the iron homeostasis (Key et al, 2020). Both cell lines exhibit a downregulation of CISD1 levels upon iron deprivation with the agent 2,2′ -Bipyridine possibly as a compensatory mechanism to limit the toxic gain of function of iron-depleted CISD1. The other paper, Ma et al. is a recent review on changes in iron homeostasis in PD and PD models (Ma et al, 2021). Both papers are now cited in the manuscript.

      This paper describes CISD1 as a new and relevant player in PINK1 and Parkin biology. Further work could lead to exploration of whether CISD1 could be a therapeutic target, considering its role in maintaining mitochondrial redox and mitochondrial health. This is of particular interest to mitochondrial biologists and pre-clinical research in PD.

      This preprint was reviewed by three scientists whose research focus in the mitochondrial biology underlying Parkinson's disease. The group has a special interest in the functions of the mitochondrial outer membrane. We work with several cell models of Parkinson's disease and work with patient donated samples. We do not have expertise in Drosophila models of PD nor the quantification of iron described in the manuscript.

      Reviewer #2 (Evidence, reproducibility and clarity):

      Summary: In the paper entitled 'Mitochondrial CISD1 is a downstream target that mediates PINK1 and Parkin loss-of-function phenotypes', Bitar and co-workers investigate the interaction between CISD1 and the PINK1/Parkin pathway. Mutations in PINK1 and PARKIN cause early onset Parkinson's disease and CISD1 is a homodimeric mitochondrial iron-sulphur binding protein. They observed an increase in CISD1 dimer formation in dopaminergic neurons derived from Parkinson's disease patients carrying a PINK1 mutation. Immuno-blots of cells expressing CISD1 mutants that affects the iron sulphur cluster binding and as well as cells treated with iron chelators, showed that the tendency of CISD1 to form dimers is dependent on its binding to iron-sulphur clusters. Moreover, the Iron-depleted apo-CISD1 does not rescue mitochondrial phenotypes observed in CISD1 KO mouse cells. Finally, In vivo studies showed that overexpression of Cisd and mutant apo-Cisd in Drosophila shortened fly life span and, using a different overexpression model, apo-Cisd caused a delay in eclosion. Similar as patient derived neurons, they observed an increase in Cisd dimer levels in Pink1 mutant flies. Additionally, the authors showed that double mutants of Cisd and Pink1 alleviated all Pink1 mutant phenotypes, while double mutants of Prkn and Cisd rescued most Prkn mutant phenotypes.

      Major comments:

      1) The authors observed an increase in the levels of Cisd dimers in Pink1 mutant flies and removing Cisd in Pink1 mutant background rescues all the mutant phenotypes observed in Pink1 mutant flies, suggesting that the Cisd dimers are part and partial of the Pink1 mutant phenotype. The authors also generated a UAS_C111S_Cisd fly which can overexpress apo-Cisd. Overexpression of the C111S_Cisd construct with Tub-Gal4 showed a developmental delay. Since apo-Cisd forms more dimeric Cisd, my question is: does the strong overexpression (e.g. with Tub-Gal4) of the C111S_Cisd in wild type flies shows any of the Pink1 mutant phenotypes? If not, the authors should mention this and elaborate on it.

      We thank the reviewer for their comments. In fact, we only observed very few flies ecclosing after overexpression of wildtype Cisd or C111S Cisd using the strong tubP-Gal4 driver during development. We considered these very few flies to be escapees (also indicated by the rather low induction of Cisd mRNA suggesting compensatory downregulation) and only used them to conduct the analysis shown in Figure 4c-e. This is now mentioned in more detail in the manuscript.

      2) Figure 6g: Shows the TEM pictures of the indirect flight muscles of Pink1 mutant flies and Pink1, Cisd double mutants. To me, the Picture of Pink1 mutant mitochondria is not very convincing. We expect swollen (enlarged) mitochondria with disrupted mitochondrial matrix. However, this is not clear in the picture. Moreover, in my opinion, Figure6 g, is missing an EM Picture of the Cisd mutant indirect flight muscles.

      We now show exemplary pictures from Pink1 mutant and DKO in a higher magnification which better demonstrate the rounded Pink1 mutant mitochondria and the disrupted cristae structure. EM pictures of all four genotypes in different magnifications are now shown in new supplemental Figure 6.

      3) OPTIONAL: The authors suggest that most probably apo-Cisd, assumes a toxic function in Pink1 mutant flies and serves as a critical mediator of Pink1-linked phenotypes. If this statement is correct, we can hypothesize that increasing apo-Cisd in Pink1 mutant background should worsen the pink1 mutant defects.

      Therefore, I suggest overexpressing Cisd1 wild type (and/or C111S Cisd) in pink1 mutant flies, as pink1 is on the X chromosome, and mild overexpression of Cisd1 with da is not lethal, these experiments could be done in 3-4 fly crosses and hence within 1.5 - 2 months.

      We have set up this experiment and will report in the second revision (v2) of our manuscript.

      Since Pink1 mutant flies contain higher levels of endogenous Cisd dimers, we can expect that overexpression of wild type Cisd will result in an even stronger increase of dimers. If these dimers indeed contribute to Pink1 mutant phenotypes we can expect that overexpression of Cisd will result in a worsening of the Pink1 mutant phenotypes.

      We have set up this experiment and will report in the second revision of our manuscript.

      Minor Comments:

      -) In the Introduction (Background) there are some parts without references:

      E.g., there is not a single reference in the following part between

      'However, in unfit mitochondria with a reduced mitochondrial membrane potential ...&... compromised mitochondria safeguards overall mitochondrial health and function.'

      We thank the reviewer for pointing out this flaw. We have now added a suitable reference to the introduction.

      -) In the introduction there is some confusion about the nomenclature used in the article: e.g. following comments are made in the text: Cisd2 (in this publication referred to as Dosmit) or fly Cisd2 (in this publication named MitoNEET).

      However, the names Dosmit and MitoNEET do not appear in the manuscript (except in references)

      The literature and nomenclature for CISD1 are indeed confusing. We have now revised the introduction.

      -) Figure 1: I am not sure why some gels are shown in this figure. The two last lanes of figure 1c are redundant and Figure 1c' which is also not mentioned in the text, is also a repetition of figure 1c.

      The blots in 1c and 1c’ represent all data points (different patients and different individual differentiations) shown in the quantification in 1d. This is now explained better in the revised manuscript.

      -) The authors mention in material and methods that T2A sites are used at the C-terminus of CISD1 to avoid tagging of CISD1. However, this is not entirely true as T2A will leave some amino acids (around 20) after the self-cleaving and therefore CISD1 will be tagged.

      This is indeed true and we have now changed the wording in the revised manuscript.

      -) In figure 5 P1 is used to abbreviate Pink1 mutants, however P1, to me, refers to pink1 wild type. It would be clearer to abbreviate Pink1 mutants as P1B9 in the graphs as B9 is the name of the mutant pink1 allele.

      We thank the reviewer for pointing out this flaw. We have now altered Fig. 5 to be clearer.

      -) In figure 7: Parkin is abbreviated both as Prkn and as Park

      We thank the reviewer for pointing out this flaw, we indeed mixed up both names because it is complicated. The gene symbol is Prkn, the fly line is called Park25. We have now clarified this in the text and Fig. 7.

      -) I suggest changing the title. Recently an article (Ham et al, 2023 PMID: 37626046) was published showing similar genetic interactions between Pink1/Prkn and Cisd. However, the article of Ham et al, 2023 was focused on Pink1/Prkn regulation of ER calcium release, while this article is more related to iron homeostasis. I suggest that the title shows this distinction.

      This is indeed a very good suggestion. We have now altered the title to “Iron/sulfur cluster loss of mitochondrial CISD1 mediates PINK1 loss-of-function phenotypes”.

      Reviewer #2 (Significance):

      In general, this is an exciting and well-executed piece of research focusing on the defects in iron homeostasis observed in Parkinson's disease which a wide audience will appreciate. Very recently, a similar genetic interaction between Cisd and Pink1/Prkn in flies was published (Ham et al, 2023 PMID: 37626046) however, from a different angle. While, Ham et al focused on the role of Pink1/Prkn and Cisd in IP3R related ER calcium release, this manuscript approaches the Pink1/Prkn - Cisd interaction from an iron homeostasis point of view. Since, iron dysregulation contributes to the pathogenesis of Parkinson's disease, the observations in this manuscript are relevant for the disease. Hence, the work is sufficiently novel and deserves publication. However, additional experiments are suggested to strengthen the authors' conclusions.

      We thank the reviewer for their kind words. As mentioned above, these additional experiments are on their way and will be included in version 2 of our revised manuscript (v2).

      I work on Drosophila models of Parkinson's disease

      Referees cross-commenting

      I agree with the reviewer number 1 that it would be interesting to investigate CISD1 dimerisation status during mitophagy.

      As mentioned above, we now studied CISD1 dimerization in response to more classical activators of mitophagy namely FCCP and antimycin/oligomycin which had no significant effect on dimerization suggesting that this phenotype is more pronounced under iron depletion. These data are shown in the new Fig. 2c.

      Reviewer #3 (Evidence, reproducibility and clarity):

      Here the authors provide evidence that Cisd is downstream of Parkin/Pink1 and suggest that the levels of apo-Cisd correlate with neurotoxicity. The data presented generally supports the conclusions of the authors and will be useful to those in the field. The manuscript would be improved by a more balanced discussion of the strengths and weaknesses of the study and more circumspection in interpretation of data.

      We thank the reviewer for their comments aimed to improve our manuscript. We have now discussed the strengths and weaknesses of our study in more detail.

      Introduction. While iron has been implicated in Parkinson's disease, it is an overstatement to say that disruption in iron metabolism contributes significantly to the pathogenesis of the disease.

      There is certainly a plethora of data implicating perturbed iron homeostasis in PD as also pointed out by reviewer #1. We have tried to tone down our wording in the text and added a recent review on the topic (Ma et al, 2021) as also suggested by reviewer #1.

      Introduction. The discussion of the various names for Cisd2 is important, but confusing as written. Specifically, the use of "this" makes the wording unclear.

      We thank the reviewer for pointing out this flaw. We have altered the wording in the introduction.

      Methods. It would be preferable to use heterozygous driver lines or a more similar genetic control rather than w-1118.

      The exact controls were indeed not well explained in the Methods section, this has been corrected in the revised version. In brief, homozygous driver and UAS lines were indeed used in Fig. 4, this will be addressed in the second revision of our manuscript together with the experiments reviewer #2 suggested. The data shown in Fig. 5, 6, and 7 all used w1118 as control because all other fly strains are on the same genetic background.

      Page 10. It appears that the PINK1 lines have been described previously. The authors should clarify this point and ensure that the new data presented in the current manuscript (presumably the mRNA levels, Fig. 1a) is indicated, as well as data that is confirmatory of prior findings (Fig. 1b).

      Yes, these PINK1 lines have been described previously as pointed out in the manuscript. The original paper did not quantify the PINK1 mRNA levels shown in Fig. 1a. The blots shown in Fig. 1b are from new differentiations and have also not been shown before but confirm findings published in Jarazo et al. (Jarazo et al, 2022). This has been clarified in the revised version of our manuscript.

      Fig. 3 legend. There is a typographical error, "ne-way ANOVA."

      We thank the reviewer for pointing out this flaw. This has been corrected in the revised version.

      Page 15. The nature of the Pink1-B9 mutant should be specified.

      We now added a supplemental Figure 1 that depicts the specific mutation in these flies.

      Fig. 4. Levels of mutant and wild type Cisd should be compared in transgenic flies.

      We now added a quantification of mutant and wildtype Cisd levels to the new Figure 4d.

      Fig. 5b,d. The striking change seems to be the decrease in dimers in young Pink1 mutant animals, not the small increase in dimers in the older Pink1 mutants.

      It is always difficult to find a “typical” picture that reflects all changes observed in quantitative data. This Figure actually shows a decrease of total Cisd levels in young flies in Fig. 5c but no difference of the dimer/monomer ratio in Fig. 5d.

      Fig. 5f. Caution should be used in interpreting the results. Deferiprone has toxicity to wildtype flies (trend) and may simply be making sick Pink1 mutants sicker.

      There is certainly a tendency for wildtype flies to thrive less in food containing deferiprone. To make this more obvious, we have now added the exact p value (0.0764, which we don’t consider borderline but a tendency) to this figure and mention this fact in the text.

      Fig. 5e. The data are hard to interpret. The number of animals is very small for a viability study and the strains are apparently in different genetic backgrounds, though this is not clearly specified. The experiment in Supplementary Fig. 1 appears better controlled and supports the Pink1 data; however, a similar concern pertains to Fig. 7. The authors may thus wish to be more circumspect in their interpretation, especially of the Parkin data.

      In Fig 5e we quantified total iron levels and the Fe3+/Fe2+ ratio using capillary electrophoresis-inductively coupled plasma mass spectrometry (CE-ICP-MS). Although indeed not so many flies were used in this quantification, the results are highly significant. If the reviewer was referring to Fig. 5f, we agree that this experiment was not well (to be honest, even wrongly explained) which we corrected in the revised version of this manuscript. We thank the reviewer for pointing out this flaw.

      Reviewer #3 (Significance):

      The major significance of the study is in putting downstream of Parkin/Pink1 (largely confirmatory to recently published work) and suggesting that the levels of apo-Cisd are an important determinant of toxicity. The work will be of interest to those in the field.

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

      The changes already carried out and included in the transferred manuscript (v1) are indicated above in bold orange. All changes pending on ongoing experiments to be included in the second revision of the manuscript are indicated above in bold magenta.

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

      All changes suggested by the reviewers were addressed (v1) or will be addressed (v2).

      References

      Jarazo J, Barmpa K, Modamio J, Saraiva C, Sabaté-Soler S, Rosety I, Griesbeck A, Skwirblies F, Zaffaroni G, Smits LM, et al (2022) Parkinson’s Disease Phenotypes in Patient Neuronal Cultures and Brain Organoids Improved by 2-Hydroxypropyl-β-Cyclodextrin Treatment. Mov Disord 37: 80–94

      Key J, Sen NE, Arsović A, Krämer S, Hülse R, Khan NN, Meierhofer D, Gispert S, Koepf G & Auburger G (2020) Systematic Surveys of Iron Homeostasis Mechanisms Reveal Ferritin Superfamily and Nucleotide Surveillance Regulation to be Modified by PINK1 Absence. Cells 9

      Ma L, Gholam Azad M, Dharmasivam M, Richardson V, Quinn RJ, Feng Y, Pountney DL, Tonissen KF, Mellick GD, Yanatori I, et al (2021) Parkinson’s disease: Alterations in iron and redox biology as a key to unlock therapeutic strategies. Redox Biol 41: 101896

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      Referee #3

      Evidence, reproducibility and clarity

      Here the authors provide evidence that Cisd is downstream of Parkin/Pink1 and suggest that the levels of apo-Cisd correlate with neurotoxicity. The data presented generally supports the conclusions of the authors and will be useful to those in the field. The manuscript would be improved by a more balanced discussion of the strengths and weaknesses of the study and more circumspection in interpretation of data.

      • Introduction. While iron has been implicated in Parkinson's disease, it is an overstatement to say that disruption in iron metabolism contributes significantly to the pathogenesis of the disease.

      Introduction. The discussion of the various names for Cisd2 is important, but confusing as written. Specifically, the use of "this" makes the wording unclear.<br /> - Methods. It would be preferable to use heterozygous driver lines or a more similar genetic control rather than w-1118.<br /> - Page 10. It appears that the PINK1 lines have been described previously. The authors should clarify this point and ensure that the new data presented in the current manuscript (presumably the mRNA levels, Fig. 1a) is indicated, as well as data that is confirmatory of prior findings (Fig. 1b).<br /> - Fig. 3 legend. There is a typographical error, "ne-way ANOVA."<br /> - Page 15. The nature of the Pink1-B9 mutant should be specified.<br /> - Fig. 4. Levels of mutant and wild type Cisd should be compared in transgenic flies.<br /> - Fig. 5b,d. The striking change seems to be the decrease in dimers in young Pink1 mutant animals, not the small increase in dimers in the older Pink1 mutants.<br /> - Fig. 5f. Caution should be used in interpreting the results. Deferiprone has toxicity to wildtype flies (trend) and may simply be making sick Pink1 mutants sicker.<br /> - Fig. 5e. The data are hard to interpret. The number of animals is very small for a viability study and the strains are apparently in different genetic backgrounds, though this is not clearly specified. The experiment in Supplementary Fig. 1 appears better controlled and supports the Pink1 data; however, a similar concern pertains to Fig. 7. The authors may thus wish to be more circumspect in their interpretation, especially of the Parkin data.

      Significance

      The major significance of the study is in putting downstream of Parkin/Pink1 (largely confirmatory to recently published work) and suggesting that the levels of apo-Cisd are an important determinant of toxicity. The work will be of interest to those in the field.

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      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      In the paper entitled 'Mitochondrial CISD1 is a downstream target that mediates PINK1 and Parkin loss-of-function phenotypes', Bitar and co-workers investigate the interaction between CISD1 and the PINK1/Parkin pathway. Mutations in PINK1 and PARKIN cause early onset Parkinson's disease and CISD1 is a homodimeric mitochondrial iron-sulphur binding protein. They observed an increase in CISD1 dimer formation in dopaminergic neurons derived from Parkinson's disease patients carrying a PINK1 mutation. Immuno-blots of cells expressing CISD1 mutants that affects the iron sulphur cluster binding and as well as cells treated with iron chelators, showed that the tendency of CISD1 to form dimers is dependent on its binding to iron-sulphur clusters. Moreover, the Iron-depleted apo-CISD1 does not rescue mitochondrial phenotypes observed in CISD1 KO mouse cells. Finally, In vivo studies showed that overexpression of Cisd and mutant apo-Cisd in Drosophila shortened fly life span and, using a different overexpression model, apo-Cisd caused a delay in eclosion. Similar as patient derived neurons, they observed an increase in Cisd dimer levels in Pink1 mutant flies. Additionally, the authors showed that double mutants of Cisd and Pink1 alleviated all Pink1 mutant phenotypes, while double mutants of Prkn and Cisd rescued most Prkn mutant phenotypes.

      Major comments:

      1. The authors observed an increase in the levels of Cisd dimers in Pink1 mutant flies and removing Cisd in Pink1 mutant background rescues all the mutant phenotypes observed in Pink1 mutant flies, suggesting that the Cisd dimers are part and partial of the Pink1 mutant phenotype. The authors also generated a UAS_C111S_Cisd fly which can overexpress apo-Cisd. Overexpression of the C111S_Cisd construct with Tub-Gal4 showed a developmental delay. Since apo-Cisd forms more dimeric Cisd, my question is: does the strong overexpression (e.g. with Tub-Gal4) of the C111S_Cisd in wild type flies shows any of the Pink1 mutant phenotypes? If not, the authors should mention this and elaborate on it.
      2. Figure6 g: Shows the TEM pictures of the indirect flight muscles of Pink1 mutant flies and Pink1, Cisd double mutants. To me, the Picture of Pink1 mutant mitochondria is not very convincing. We expect swollen (enlarged) mitochondria with disrupted mitochondrial matrix. However, this is not clear in the picture. Moreover, in my opinion, Figure6 g, is missing an EM Picture of the Cisd mutant indirect flight muscles.
      3. OPTIONAL: The authors suggest that most probably apo-Cisd, assumes a toxic function in Pink1 mutant flies and serves as a critical mediator of Pink1-linked phenotypes. If this statement is correct, we can hypothesize that increasing apo-Cisd in Pink1 mutant background should worsen the pink1 mutant defects.

      Therefore, I suggest overexpressing Cisd1 wild type (and/or C111S Cisd) in pink1 mutant flies, as pink1 is on the X chromosome, and mild overexpression of Cisd1 with da is not lethal, these experiments could be done in 3-4 fly crosses and hence within 1.5 - 2 months.

      Since Pink1 mutant flies contain higher levels of endogenous Cisd dimers, we can expect that overexpression of wild type Cisd will result in an even stronger increase of dimers. If these dimers indeed contribute to Pink1 mutant phenotypes we can expect that overexpression of Cisd will result in a worsening of the Pink1 mutant phenotypes.

      Minor Comments:

      1. In the Introduction (Background) there are some parts without references:<br /> E.g., there is not a single reference in the following part between<br /> 'However, in unfit mitochondria with a reduced mitochondrial membrane potential ...&... compromised mitochondria safeguards overall mitochondrial health and function.'
      2. In the introduction there is some confusion about the nomenclature used in the article: e.g. following comments are made in the text: Cisd2 (in this publication referred to as Dosmit) or fly Cisd2 (in this publication named MitoNEET).<br /> However, the names Dosmit and MitoNEET do not appear in the manuscript (except in references)
      3. Figure 1: I am not sure why some gels are shown in this figure. The two last lanes of figure 1c are redundant and Figure 1c' which is also not mentioned in the text, is also a repetition of figure 1c.
      4. The authors mention in material and methods that T2A sites are used at the C-terminus of CISD1 to avoid tagging of CISD1. However, this is not entirely true as T2A will leave some amino acids (around 20) after the self-cleaving and therefore CISD1 will be tagged.
      5. In figure 5 P1 is used to abbreviate Pink1 mutants, however P1, to me, refers to pink1 wild type. It would be clearer to abbreviate Pink1 mutants as P1B9 in the graphs as B9 is the name of the mutant pink1 allele.
      6. In figure 7: Parkin is abbreviated both as Prkn and as Park
      7. I suggest changing the title. Recently an article (Ham et al, 2023 PMID: 37626046) was published showing similar genetic interactions between Pink1/Prkn and Cisd. However, the article of Ham et al, 2023 was focused on Pink1/Prkn regulation of ER calcium release, while this article is more related to iron homeostasis. I suggest that the title shows this distinction.

      Referees cross-commenting

      I agree with the reviewer number 1 that it would be interesting to investigate CISD1 dimerisation status during mitophagy.

      Significance

      In general, this is an exciting and well-executed piece of research focusing on the defects in iron homeostasis observed in Parkinson's disease which a wide audience will appreciate. Very recently, a similar genetic interaction between Cisd and Pink1/Prkn in flies was published (Ham et al, 2023 PMID: 37626046) however, from a different angle. While, Ham et al focused on the role of Pink1/Prkn and Cisd in IP3R related ER calcium release, this manuscript approaches the Pink1/Prkn - Cisd interaction from an iron homeostasis point of view. Since, iron dysregulation contributes to the pathogenesis of Parkinson's disease, the observations in this manuscript are relevant for the disease. Hence, the work is sufficiently novel and deserves publication. However, additional experiments are suggested to strengthen the authors' conclusions.<br /> I work on Drosophila models of Parkinson's disease

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      Referee #1

      Evidence, reproducibility and clarity

      Summary:

      The manuscript focuses on mitochondrial CISD1 and its relationship to two Parkinson's disease (PD) proteins PINK1 and Parkin. Interestingly, CISD1 is a mitochondrial iron sulfur binding protein and an target of Parkin-mediated ubiquitinylation. Disruption of iron metabolism and accumulation of iron in the brain has long since been reported in PD but the involvement of iron sulfur binding is little studied both in vivo and in human stem cell models of PD. This work addresses the relationship between CISD1 and two mitochondrial models of PD (PINK1 and Parkin) making use of in vivo models (Drosophila), PINK1 patient models (iPSC derived neurons) and Mouse fibroblasts. The authors report a complex relationship between CISD1, PINK1 and Parkin, where iron-depleted CISD1 may illicit a toxic gain of function downstream of PINK1 and Parkin.

      Major comments:

      • The conclusions are overall modest and supported by the data. One question remains unaddressed. Is mitochondrial CISD1 a downstream target that specifically mediates PINK1 and Parkin loss of function phenotypes or are the phenotypes being mediated because CISD1 is downstream of mitophagy in general?<br /> It would be interesting to know what happens to CISD1 (dimerization?) upon initiation of mitophagy in wild type cells? Would dissipation of mitochondrial membrane potential be sufficient to induce changes to CISD1 in wild type cells or PINK1 deficient cells?

      • Since iron chelation is a potent inducer of mitophagy (Loss of iron triggers PINK1/Parkin-independent mitophagy. George F G Allen, Rachel Toth, John James, Ian G Ganley. EMBO Reports (2013)14:1127-1135) it would be useful to show one experiment addressing the role of CISD1 dimerization under mitochondrial depolarizing and non-depolarizing conditions in cells.

      • Alternatively, the authors should discuss the topic of mitophagy (including PINK1-parkin independent mitophagy), the limitation of the present study not being able to rule out a general mitophagy effect and previous work on the role of iron depletion on mitophagy induction in the manuscript.

      • The data and the methods are presented in such a way that they can be reproduced.<br /> The experiments are adequately replicated and statistical analysis is adequate.

      Minor comments:

      • Show p values even when not significant (ns) since even some of the significant findings are borderline < p0.05.

      • Because the situation for CISD1 is complicated (overexpression, different models etc.) it would be helpful if in the abstract the authors could summarize the role. E.g. as in the discussion that iron-depleted CISD1 could represent a toxic function.

      • If there is sufficient iron (accumulation in PD) why would CISD1 be deactivated? Perhaps that could be postulated or discussed in a simplified way?

      • In the methods section both reducing and non-reducing gel/Western blotting is mentioned but the manuscript only describes data from blots under reducing conditions. Are there blots under non-reducing conditions that could be shown to see how CISD1 and dimerized CISD1 resolve?

      • In the results section, PINK1 mutant flies, it is said that the alterations to CISD1 (dimerization) are analogous to the PINK1 mutation patient neurons. The effect is seen in old but not young flies. Since iPSC-derived neurons are relatively young in the dish, would one not expect that young flies and iPSC-derived neurons have similar CISD1 phenotypes? Could the authors modify the text to reflect that? or discuss the finding in further context.

      Significance

      • The strengths of this work are in the novelty of the topic and the use of several well established in vivo and cell models including patient-derived neurons. The findings are discussed in the text are honest and avoid over-interpretation. The findings are novel, interesting and important for understanding the mitochondrial biologyof PD.
      • Limitations include the lack of strong phenotypes in the CISD1 models and the lack of robust, sustained and consistent increase in CISD1 dimers in the patient and fly models (just significant because of variability). The relationship of CISD1 (dimerization) to general mitophagy/autophagy is not shown here.
      • There is a significant advancement. So far researchers were able to describe the importance of iron metabolism in PD (For example refer to work from the group of Georg Auburger such as PMID 33023155 and discussion of therapeutic intervention such as reviewed by Ma et al. PMID: 33799121) but few papers describe involvement of iron sulfur cluster proteins specifically (such as Aconitase) in relation to PINK1 and parkin (these are cited). The fact that CISD1 is a protein of the mitochondrial outer membrane makes it particularly interesting and further studies looking more closely at the interaction of CISD1 with mitochondrial proteins associated with PD will be of interest.
      • This paper describes CISD1 as a new and relevant player in PINK1 and Parkin biology. Further work could lead to exploration of whether CISD1 could be a therapeutic target, considering its role in maintaining mitochondrial redox and mitochondrial health. This is of particular interest to mitochondrial biologists and pre-clinical research in PD.
      • This preprint was reviewed by three scientists whose research focus in the mitochondrial biology underlying Parkinson's disease. The group has a special interest in the functions of the mitochondrial outer membrane. We work with several cell models of Parkinson's disease and work with patient donated samples. We do not have expertise in Drosophila models of PD nor the quantification of iron described in the manuscript.
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      Reply to the reviewers

      1. General Statements [optional]

      __We thank all the reviewers for their time and their constructive criticism, based on which we will revise our manuscript. All our responses are indicated in red. __

      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)): __

      The manuscript by Nguyen and Cheng is investigating the timing and mechanism of cessation of neuroblasts in the pupal optic lobe. Previous studies by several groups have determined the spatial and temporal factors required for the neuroepithelial to neuroblast transition and neuroblast to neural/glycogenesis in third instar larvae such that neuroblasts are eliminated. The mechanism of elimination of neuroblasts in the VNC or mushroom bodies have been investigated, but the mechanism(s) and the timing of elimination of medulla neuroblasts has not been investigated. The authors suggest that medulla neuroblasts are eliminated via a combination of mechanisms including apoptosis, prospero induced size symmetric terminal differentiation and a switch to gliogenesis by gcm expression. Expression of Tailless also was found to affect the timing of medulla neuroblast termination. They also ruled out several mechanisms such as ecdysone pulses.

      Major comments

      Clearly written and logical flow to experiments and results not over interpreted.

      Clearly show that the neuroblast number and size decrease (12 to 18 hrs) and are eliminated by 30 hours

      Figure 2a Marking of the Neuroepithelium. Would be more convincing if shown by PatJ expression and is clonal analysis. While the following panels use PatJ in clones suggesting are NE and NBs present it is more difficult to put into the context in the higher magnification images (Figure 2 D- M) and the Miranda expression in F' seems to be the entire lobe and it is not clear if would be any NE which does not agree with what is shown in panel A.

      We will perform clonal analysis using MARCM to show that the elimination of medulla NBs (marked by Dpn) is accompanied by the depletion of NE (marked by PatJ). For Figure 2 D, E, I, L, we will change the images to the whole lobes to clearly show the shift in the NE-NB transition upon Notch OE/KD.

      Is difficult to see the neuroblasts in Figure 2 D D" and E. The figure does not match what is stated in the results in that the neuroblasts are difficult to observe. If the point is that there is fewer NE cells and more neuroblasts then this is hard to see. It has been previously shown that with Notch RNAi clones prematurely extrude form the NE (Egger 20210; Keegan 2023) and could be expressing more Neuroblast markers but this is not visible in the panels as shown. Are the images single focal plane or maximum projections? Imaging more deeply in the brain or viewing in cross section would account for these possibilities. The possibility that are more neuroblasts but not all at the surface of the OL should be addressed as this could also alter the overall results.

      Figure 2 is key to first point of the paper so needs to be addressed.

      The images are single focal plane of the superficial layer of the medulla. We will specify this information in the figure legends. We will include cross-section of the notch RNAi clones to show the delamination of precocious NBs.

      Minor comments

      Why express volume of DPN in clone volume. Would make the point more clear and more strong be to express as number of NB in the 3-D volume of the clone. This measurement occurs in several figures.

      We will redo the quantification as suggested.

      Use of Miranda to mark NBs is unclear in Figure 2. Perhaps more clear in B&W.

      We will redo the staining with Dpn instead of Mira to mark medulla NBs. Figures will be presented in B&W as suggested.

      Make clear in figures (or figure legend) if single focal plane or projections.

      We will do so.

      It is unclear what percentage of NB the Gal4 line eyR16F10 are expressed in. Veen 2023 state that the GAL4 is also expressed in neurons and at different levels whether deeper within the brain or superficially on the surface of the brain. At 16 APF it is expressed but it is not clear whether it is in all cells at a low level or only within a few cells

      We will further characterize the expression of eyR16F10-GAL4 in the pupal medulla as suggested.

      Some RNAi lines referenced as previously validated and other are not. For example: EcR, Oxphos, Med27, Notch need references or confirmation of specificity to the intended target (qRT)

      We will perform RT-qPCR to validate the use of UAS-med27 RNAi. For RNAi stocks such as UAS-EcR RNAi, UAS-Atg1 RNAi, UAS-notch RNAi that have been previously used in other publications, we will provide appropriate references.

      At least 2 animals per genotype were used. While I appreciate the technical difficulty of working in pupae this seems a bit low in terms of number of samples and data would be more robust with more numbers.

      Any experiments in which less than 3 animals were used, we will redo the experiments.

      Reviewer #1 (Significance (Required)):

      This provides mechanism and timing for the elimination of neuroblasts (NE to NB) that arise from the medulla. As these are most similar to mammalian brain development (Radial glial to NSC) this information provides more context to interpret the formation of glial and neurons in the adult optic lobe given the effect on timing and mechanisms of elimination.

      This paper would be of interest to developmental biologist who work with Drosophila or mice who are looking at neural development. An understanding of how neural diversity is achieved and the mechanisms behind this that can be dysfunctional in terms of etiology of neural diseases. Is a well done study for the most part that would be improved by clarifying some data and provided more replicates for robustness of the data.

      I am a developmental biologist working with Drosophila in larval and adult neural development.

      __Reviewer #2 (Evidence, reproducibility and clarity (Required)): __

      Lineages of neural stem cells are of great interest to understand how many neural types are generated. They produce very diverse neurons, often in a highly stereotyped series. However, they must terminate their life when the animal becomes functional or if neurons need time to become mature before birth.

      In the Drosophila optic lobes, neural stem cells are produced over a period of several days by a wave of neurogenesis that transforms a neuroepithelium into neural stem cells that undergo a series of temporal patterning steps. It has been reported that they finish their life when a symmetric division generates glial cells. The authors however analyze the end of a particular lineage, that of the latest born neural stem cells of the medulla.

      The paper shows that neural stem cells stop being produced when the neuroepithelium is consumed. But how do the latest born neural stem cells stop their lineage?

      The results show that they do so by several means, which is quite unexpected: they may die from apoptosis, or autophagy, by becoming glioblasts or by a terminal symmetric division.

      There are no major issues affecting the conclusions

      • The paper shows that the end of production of neural stem cells occurs the neuroepithelium is completely transformed. The experiments performed by the authors are fine and show that, if the transition is delayed, neural stem cells terminate their life later, and vice versa. However, the lifespan of the neural stem cells is not affected by the timing of the transition. Therefore, these experiments do not tell us how neural stem cells terminate their life, which is the central question of the study. The discussion should be written accordingly and the title and the model in Fig 6 modified to reflect the importance of the end of life of the stem cells, the main theme of the paper.

      We agree that our said experiments did not elucidate how NBs terminate at the end of neurogenesis. Nevertheless, our aim is to show that the timing of NB termination in the medulla is dependent on the timing of the NE-NB transition.

      In Supplementary Figure 1, we showed that factors previously shown to be involved in NB termination in other lineages did not play similar roles in the medulla NBs. Thus, we think that NB termination in the medulla is likely regulated at the levels of the NE, but not the NBs themselves. Although we have briefly mentioned this in our manuscript, we hope by conducting the experiments suggested by the reviewer (see below), we can subsequently modify our model in Figure 6 and our discussion.

      • The authors talk about Pros-dependent symmetric division and gliogenic switch as two separate processes, but these may be two sides of the same phenomenon. Tll+ gcm+ neural stem cells undergo Pros-dependent cell cycle exit, generating glial progeny. If the authors agree with this, could they update their model (and discussion) to reflect the fact that gliogenic switch occurs via a Pros-dependent symmetric division, and these are not two separate processes independently contributing to the depletion of the neural stem cell pool? Ideally, a triple staining between Dpn, Pros, and gcm would show that the symmetrically dividing cells seen by the authors are committed to the glial fate.

      We will further test how gliogenesis is affected in pros RNAi clones. The results may shed light on whether Pros-mediated symmetric division is required for Gcm-mediated gliogenesis in the medulla. Regarding the model, we have summarized our findings and suggestions in Figure 5K, however, we will integrate this information into our final model.

      In Figure 5C, we showed that at 12h APF, there are Dpn+ NBs in the medulla that expressed both Pros and Gcm, suggesting that it is very likely that Pros is upstream of Gcm to induce the glial cell fate switch of the medulla NBs.

      • Why were Notch RNAi experiments assessed for the presence of neural stem cells at P12 and gcm RNAi experiments at P24? Given that most optic lobe neural stem cells disappear between P12-18, a subtle effect of gcm RNAi may have been missed. Do the authors have data for gcm RNAi at P12?

      We hypothesized that the timing of NE-NB transition affects the timing of NB termination in the medulla. Because Notch KD was previously shown to induce precocious NE-NB transition in the OL, meaning that medulla NBs are born prematurely, we expected that this manipulation will lead to a corresponding premature elimination of the NBs. In contrast, gcm RNAi which inhibits the switch into the glial cell fate of the NBs, is expected to prolong the neurogenic phase of the NBs, and thereby, their persistence by 24h APF when WT NBs are eliminated.

      • The authors should acknowledge that the inhibition of either apoptosis or autophagy alone may not be fully sufficient to prevent the death of NBs. In mushroom body neural stem cells, both processes must be inhibited simultaneously to produce a strong effect on their survival (Pahl et al. 2019, PMID 30773368).

      We will add this information in our discussions.

      • There is an important missing point that should be addressed: is there a specific point in time when all neural stem cells must stop their lineage wherever they are in the temporal series and either die or divide symmetrically? One possibility that is not discussed is that most neural stem cells end their life through a gliogenic symmetric division while those that were generated late must stop en route and die by apoptosis and/or autophagy. This would solve the strange diversity of end-of-life, which could be easily addressed by identifying the temporal stage of the neural stem cells that undergo apoptosis

      We agree that it would be of interest to understand how there are diverse mechanisms by which medulla NBs terminate during pupal development. To address if temporal progression is involved in apoptosis of the medulla NBs, we will first characterize the expression of some temporal TFs (e.g., Ey, Slp, Tll) at 12h APF when we found a subset of medulla NBs undergo apoptosis in the wildtype animals.

      Minor suggestions:

      We agree with these minor modifications.

      • Line 46: Specify that there are 8 type II neural stem cells in each hemisphere*.

      • The statement in lines 181-182 that "cell death, and not autophagy, makes a minor contribution to..." should be replaced with "apoptosis, and not autophagy," as autophagy is also a type of cell death.

      • The authors should adjust the logic of the section "Medulla neuroblasts terminate during early pupal development": Describe the wild-type pattern first (the decrease in the number of neural stem cells and their size with age) and then describe the perturbations aimed at disrupting the number and the size of neural stem cells

      • Line 151 should refer to Fig. 2I-K, not Fig. 2J-K.

      **Referees cross-commenting**

      How can NBs die by different mechanisms?? This might only happen is they are in a different states, an issue that is not addressed.

      it has been shown that optic lobe NBs end their life by a symmetric, gliogenic last division at the end of the last temporal window, and not by PCD.

      It is likely, and the authors do hint at it, that NBs only die by PCD when they prematurely interrupt the temporal series in early pupation when neurons synchronously start undergoing maturation.

      I believe that the authors should explain this, if this is indeed their model, and show that NBs die while still in early temporal windows.

      Reviewer #2 (Significance (Required)):

      Lineages of neural stem cells are of great interest to understand how many neural types are generated. They produce very diverse neurons, often in a highly stereotyped series. However, they must terminate their life when the animal becomes functional or if neurons need time to become mature before birth.

      In the Drosophila optic lobes, neural stem cells are produced over a period of several days by a wave of neurogenesis that transforms a neuroepithelium into neural stem cells that undergo a series of temporal patterning steps. It has been reported that they finish their life when a symmetric division generates glial cells. The authors however analyze the end of a particular lineage, that of the latest born neural stem cells of the medulla.

      The paper shows that neural stem cells stop being produced when the neuroepithelium is consumed. But how do the latest born neural stem cells stop their lineage?

      The results show that they do so by several means, which is quite unexpected: they may die from apoptosis, or autophagy, by becoming glioblasts or by a terminal symmetric division.

      There are no major issues affecting the conclusions

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

      Summary

      In this manuscript, the authors address the timing and mechanisms responsible for the termination of medulla neuroblasts in Drosophila visual processing centres, also known as optic lobes. Through time course experiments the authors demonstrate the medulla NBs are completely eliminated by 30h APF during early pupal development. By manipulating the Notch signalling pathway as well as proneural genes such as lethal of scute, the authors show that altering the NE-NB transition is sufficient to change the timing of NB termination. In contrast, ecdysone signalling and components of the mediator complex, known to terminate proliferation of central brain NBs, are not required for the termination of medulla NBs. Medulla NBs sequentially express a variety of temporal transcription factors to promote cellular diversity, however, the authors demonstrate that altering temporal factors such as Ey, Sco or Hth, does not affect the timing of the medulla NBs termination. Interestingly however overexpression of the transcription factor tailless can cease medulla NB termination via the conversion of type I to type II NB fate. They further go on to show the importance of the differentiation factor, Prospero, in promoting the differentiation of medulla NBs as well as terminating medulla neurogenesis during pupal development. Finally, in addition to differentiation, the authors show another mechanism responsible for the cessation of neurogenesis which is the commencement of gliogenesis. Through manipulation of the neurogenic to gliogenic switch by knockdown or overexpressing the glial regulatory gene, gcm, the authors show that even though the downregulation of gcm is is not sufficient to induce NB persistence, gcm overexpression can cause premature termination of NBs.

      Major comments:

      • Are the key conclusions convincing?

      Yes, the key conclusions are convincing with proper controls, quantifications and statistical analyses.

      • Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

      The conclusion that temporal transcription factors (TTF) do not affect the timing of medulla NB termination is somewhat preliminary. The authors investigated a simplified temporal series including Homothorax, Eyeless, Sloppy-paired, Dichaete and Tailless. However, there are additional temporal factors that have not been examined for their potential involvement in medullar NB termination. Previous reports have identified several other temporal factors that play a role in medulla TTF cascade, such as, SoxNeuro (SoxN) and doublesex-Mab related 99B (Dmrt99B) that start their expression in the NE similar to Hth, however, Dmrt99B is likely to be repressed much later than Hth (Li, Erclik et al. 2013, Zhu, Zhao et al. 2022). At this point, it remains challenging to completely rule out the possibility that other temporal factors play a role in medullar NB termination or have redundant functions in regulating the timing of medulla NB cessation. It is suggested to tone down this claim and provide a brief discussion on alternative possibilities, citing relevant papers on the functions of other temporal factors in medullar NBs.

      We agree.

      • 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.

      Loss of pros by RNAi caused the formation of ectopic NBs and the NBs persist even at 24h APF. Do these NBs persist at 30h or 48h APF? Does overexpression of Pros result in early termination of medulla NBs?

      We will do these experiments in clones as suggested.

      • Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

      Yes, I believe the suggested experiments are realistic in terms of time and resources, with an estimation of 3 months to complete the experiments.

      • 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 experiments are straight forward and were performed with proper controls, supported by quantifications and proper statistical analyses. However, there is no mention about how many replicates were used.

      We will add this information in our Material and Methods section.

      Minor comments:

      1. The authors use the eyR6F10-Gal4 driver in certain experiments. The eyR6F10-Gal4 driver is however expressed only in a subset of medulla NBs. Can the authors comment on what percentage of medulla NBs is the driver expressed in? We will characterize this.

      Does the EGFR signalling pathway or JAK/STAT pathway affect the timing of termination of medulla NBs? Experiments are not necessary. The author can speculate on their roles.

      We will modify our discussion accordingly.

      Figure 1C has a p value of only 0.03 (*) but shows a strong reduction in the number of Dpn+ cells from 12h to 18h, etc. Is this correct? Also, is the p value the same for the comparison between 12h and 24h as well as 12h and 30h APF?

      Yes. P-values showed no significant differences between 28-24h and 24-30h APF.

      The controls in figure 2B and to some extent figure 2H show one major outlier (much higher than the other brain lobes in the control). Will the removal of this outlier affect the significance/ p-value of the experiment?

      No, removing the outliers do not change the statical results.

      In figure 2B what is the p-value between 12h and 18h APF? Is it *** as well?

      No, it’s not significant.

      Line 84 of the introduction introduces Tll, Gcm and Pros for the first time in the manuscript and should be written out in full.

      We will change this.

      • 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?

      Quite a few of data mentioned in the manuscript have been described as data not shown. I think it would be nice to show quantifications or representative images in the supplementary figures.

      We will add the data which was previously not shown.

      Reviewer #3 (Significance (Required)):

      Since the mechanisms by which medulla NBs are terminated are currently unknow, this is an important and interesting study to understand how medulla neuroblasts in the optic lobe are terminated. The balance between stem cell maintenance and differentiation is critical for proper brain development and the results presented in this paper are impactful. Furthermore, Drosophila melanogaster is an excellent model to study stem cell niches and neuroblast temporal patterning. The authors provide key mechanisms namely cell death, Pros-mediated differentiation and the gliogenic switch that contribute to a better understanding of how the NB progenitor pool can be terminated in the Drosophila OL, which is largely supported by the data.

      • Place the work in the context of the existing literature (provide references, where appropriate).

      So far, most work in this field has focused on the regulation of the temporal factors to promote the progression of the TTF transcriptional cascade and thereby diversity of the neural progenitors (Li, Erclik et al. 2013, Naidu, Zhang et al. 2020, Ray and Li 2022, Zhu, Zhao et al. 2022). Furthermore, work on pathways such as EGFR and Notch signalling that allows the proneural wave to progress and subsequently induce neuroblast formation in a precise and orderly manner have also been studied (Yasugi, Umetsu et al. 2008, Yasugi, Sugie et al. 2010). Here, considering previous literature, the authors move one step forward to determine how and when these neuroblast progenitors cease proliferation during development thus providing mechanisms for the regulation of the neuroepithelial stem cell pool, its timely conversion into NSCs and the switch from neurogenesis to gliogenesis thus providing important implications for brain size determination and function.

      • State what audience might be interested in and influenced by the reported findings.

      Stem cell research, neurobiologists and developmental biologists.

      • Define your field of expertise

      Stem cells, developmental biology

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      Referee #3

      Evidence, reproducibility and clarity

      Summary

      In this manuscript, the authors address the timing and mechanisms responsible for the termination of medulla neuroblasts in Drosophila visual processing centres, also known as optic lobes. Through time course experiments the authors demonstrate the medulla NBs are completely eliminated by 30h APF during early pupal development. By manipulating the Notch signalling pathway as well as proneural genes such as lethal of scute, the authors show that altering the NE-NB transition is sufficient to change the timing of NB termination. In contrast, ecdysone signalling and components of the mediator complex, known to terminate proliferation of central brain NBs, are not required for the termination of medulla NBs. Medulla NBs sequentially express a variety of temporal transcription factors to promote cellular diversity, however, the authors demonstrate that altering temporal factors such as Ey, Sco or Hth, does not affect the timing of the medulla NBs termination. Interestingly however overexpression of the transcription factor tailless can cease medulla NB termination via the conversion of type I to type II NB fate. They further go on to show the importance of the differentiation factor, Prospero, in promoting the differentiation of medulla NBs as well as terminating medulla neurogenesis during pupal development. Finally, in addition to differentiation, the authors show another mechanism responsible for the cessation of neurogenesis which is the commencement of gliogenesis. Through manipulation of the neurogenic to gliogenic switch by knockdown or overexpressing the glial regulatory gene, gcm, the authors show that even though the downregulation of gcm is is not sufficient to induce NB persistence, gcm overexpression can cause premature termination of NBs.

      Major comments:

      • Are the key conclusions convincing?

      Yes, the key conclusions are convincing with proper controls, quantifications and statistical analyses. - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

      The conclusion that temporal transcription factors (TTF) do not affect the timing of medulla NB termination is somewhat preliminary. The authors investigated a simplified temporal series including Homothorax, Eyeless, Sloppy-paired, Dichaete and Tailless. However, there are additional temporal factors that have not been examined for their potential involvement in medullar NB termination. Previous reports have identified several other temporal factors that play a role in medulla TTF cascade, such as, SoxNeuro (SoxN) and doublesex-Mab related 99B (Dmrt99B) that start their expression in the NE similar to Hth, however, Dmrt99B is likely to be repressed much later than Hth (Li, Erclik et al. 2013, Zhu, Zhao et al. 2022). At this point, it remains challenging to completely rule out the possibility that other temporal factors play a role in medullar NB termination or have redundant functions in regulating the timing of medulla NB cessation. It is suggested to tone down this claim and provide a brief discussion on alternative possibilities, citing relevant papers on the functions of other temporal factors in medullar NBs. - 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.

      Loss of pros by RNAi caused the formation of ectopic NBs and the NBs persist even at 24h APF. Do these NBs persist at 30h or 48h APF? Does overexpression of Pros result in early termination of medulla NBs? - Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

      Yes, I believe the suggested experiments are realistic in terms of time and resources, with an estimation of 3 months to complete the experiments. - 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 experiments are straight forward and were performed with proper controls, supported by quantifications and proper statistical analyses. However, there is no mention about how many replicates were used.

      Minor comments:

      1. The authors use the eyR6F10-Gal4 driver in certain experiments. The eyR6F10-Gal4 driver is however expressed only in a subset of medulla NBs. Can the authors comment on what percentage of medulla NBs is the driver expressed in?
      2. Does the EGFR signalling pathway or JAK/STAT pathway affect the timing of termination of medulla NBs? Experiments are not necessary. The author can speculate on their roles.
      3. Figure 1C has a p value of only 0.03 (*) but shows a strong reduction in the number of Dpn+ cells from 12h to 18h, etc. Is this correct? Also, is the p value the same for the comparison between 12h and 24h as well as 12h and 30h APF?
      4. The controls in figure 2B and to some extent figure 2H show one major outlier (much higher than the other brain lobes in the control). Will the removal of this outlier affect the significance/ p-value of the experiment?
      5. In figure 2B what is the p-value between 12h and 18h APF? Is it *** as well?
      6. Line 84 of the introduction introduces Tll, Gcm and Pros for the first time in the manuscript and should be written out in full.

      7. 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?

      Quite a few of data mentioned in the manuscript have been described as data not shown. I think it would be nice to show quantifications or representative images in the supplementary figures.

      Significance

      Since the mechanisms by which medulla NBs are terminated are currently unknow, this is an important and interesting study to understand how medulla neuroblasts in the optic lobe are terminated. The balance between stem cell maintenance and differentiation is critical for proper brain development and the results presented in this paper are impactful. Furthermore, Drosophila melanogaster is an excellent model to study stem cell niches and neuroblast temporal patterning. The authors provide key mechanisms namely cell death, Pros-mediated differentiation and the gliogenic switch that contribute to a better understanding of how the NB progenitor pool can be terminated in the Drosophila OL, which is largely supported by the data.

      • Place the work in the context of the existing literature (provide references, where appropriate).

      So far, most work in this field has focused on the regulation of the temporal factors to promote the progression of the TTF transcriptional cascade and thereby diversity of the neural progenitors (Li, Erclik et al. 2013, Naidu, Zhang et al. 2020, Ray and Li 2022, Zhu, Zhao et al. 2022). Furthermore, work on pathways such as EGFR and Notch signalling that allows the proneural wave to progress and subsequently induce neuroblast formation in a precise and orderly manner have also been studied (Yasugi, Umetsu et al. 2008, Yasugi, Sugie et al. 2010). Here, considering previous literature, the authors move one step forward to determine how and when these neuroblast progenitors cease proliferation during development thus providing mechanisms for the regulation of the neuroepithelial stem cell pool, its timely conversion into NSCs and the switch from neurogenesis to gliogenesis thus providing important implications for brain size determination and function. - State what audience might be interested in and influenced by the reported findings.

      Stem cell research, neurobiologists and developmental biologists. - Define your field of expertise

      Stem cells, developmental biology

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      Referee #2

      Evidence, reproducibility and clarity

      Lineages of neural stem cells are of great interest to understand how many neural types are generated. They produce very diverse neurons, often in a highly stereotyped series. However, they must terminate their life when the animal becomes functional or if neurons need time to become mature before birth.

      In the Drosophila optic lobes, neural stem cells are produced over a period of several days by a wave of neurogenesis that transforms a neuroepithelium into neural stem cells that undergo a series of temporal patterning steps. It has been reported that they finish their life when a symmetric division generates glial cells. The authors however analyze the end of a particular lineage, that of the latest born neural stem cells of the medulla. The paper shows that neural stem cells stop being produced when the neuroepithelium is consumed. But how do the latest born neural stem cells stop their lineage?

      The results show that they do so by several means, which is quite unexpected: they may die from apoptosis, or autophagy, by becoming glioblasts or by a terminal symmetric division.

      There are no major issues affecting the conclusions

      • The paper shows that the end of production of neural stem cells occurs the neuroepithelium is completely transformed. The experiments performed by the authors are fine and show that, if the transition is delayed, neural stem cells terminate their life later, and vice versa. However, the lifespan of the neural stem cells is not affected by the timing of the transition. Therefore, these experiments do not tell us how neural stem cells terminate their life, which is the central question of the study. The discussion should be written accordingly and the title and the model in Fig 6 modified to reflect the importance of the end of life of the stem cells, the main theme of the paper.
      • The authors talk about Pros-dependent symmetric division and gliogenic switch as two separate processes, but these may be two sides of the same phenomenon. Tll+ gcm+ neural stem cells undergo Pros-dependent cell cycle exit, generating glial progeny. If the authors agree with this, could they update their model (and discussion) to reflect the fact that gliogenic switch occurs via a Pros-dependent symmetric division, and these are not two separate processes independently contributing to the depletion of the neural stem cell pool? Ideally, a triple staining between Dpn, Pros, and gcm would show that the symmetrically dividing cells seen by the authors are committed to the glial fate.
      • Why were Notch RNAi experiments assessed for the presence of neural stem cells at P12 and gcm RNAi experiments at P24? Given that most optic lobe neural stem cells disappear between P12-18, a subtle effect of gcm RNAi may have been missed. Do the authors have data for gcm RNAi at P12?
      • The authors should acknowledge that the inhibition of either apoptosis or autophagy alone may not be fully sufficient to prevent the death of NBs. In mushroom body neural stem cells, both processes must be inhibited simultaneously to produce a strong effect on their survival (Pahl et al. 2019, PMID 30773368).
      • There is an important missing point that should be addressed: is there a specific point in time when all neural stem cells must stop their lineage wherever they are in the temporal series and either die or divide symmetrically? One possibility that is not discussed is that most neural stem cells end their life through a gliogenic symmetric division while those that were generated late must stop en route and die by apoptosis and/or autophagy. This would solve the strange diversity of end-of-life, which could be easily addressed by identifying the temporal stage of the neural stem cells that undergo apoptosis

      Minor suggestions:

      • Line 46: Specify that there are 8 type II neural stem cells in each hemisphere*.
      • The statement in lines 181-182 that "cell death, and not autophagy, makes a minor contribution to..." should be replaced with "apoptosis, and not autophagy," as autophagy is also a type of cell death.
      • The authors should adjust the logic of the section "Medulla neuroblasts terminate during early pupal development": Describe the wild-type pattern first (the decrease in the number of neural stem cells and their size with age) and then describe the perturbations aimed at disrupting the number and the size of neural stem cells
      • Line 151 should refer to Fig. 2I-K, not Fig. 2J-K.

      Referees cross-commenting

      How can NBs die by different mechanisms?? This might only happen is they are in a different states, an issue that is not addressed. it has been shown that optic lobe NBs end their life by a symmetric, gliogenic last division at the end of the last temporal window, and not by PCD. It is likely, and the authors do hint at it, that NBs only die by PCD when they prematurely interrupt the temporal series in early pupation when neurons synchronously start undergoing maturation. I believe that the authors should explain this, if this is indeed their model, and show that NBs die while still in early temporal windows.

      Significance

      Lineages of neural stem cells are of great interest to understand how many neural types are generated. They produce very diverse neurons, often in a highly stereotyped series. However, they must terminate their life when the animal becomes functional or if neurons need time to become mature before birth.

      In the Drosophila optic lobes, neural stem cells are produced over a period of several days by a wave of neurogenesis that transforms a neuroepithelium into neural stem cells that undergo a series of temporal patterning steps. It has been reported that they finish their life when a symmetric division generates glial cells. The authors however analyze the end of a particular lineage, that of the latest born neural stem cells of the medulla.

      The paper shows that neural stem cells stop being produced when the neuroepithelium is consumed. But how do the latest born neural stem cells stop their lineage?

      The results show that they do so by several means, which is quite unexpected: they may die from apoptosis, or autophagy, by becoming glioblasts or by a terminal symmetric division.

      There are no major issues affecting the conclusions

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      Referee #1

      Evidence, reproducibility and clarity

      The manuscript by Nguyen and Cheng is investigating the timing and mechanism of cessation of neuroblasts in the pupal optic lobe. Previous studies by several groups have determined the spatial and temporal factors required for the neuroepithelial to neuroblast transition and neuroblast to neural/glycogenesis in third instar larvae such that neuroblasts are eliminated. The mechanism of elimination of neuroblasts in the VNC or mushroom bodies have been investigated, but the mechanism(s) and the timing of elimination of medulla neuroblasts has not been investigated. The authors suggest that medulla neuroblasts are eliminated via a combination of mechanisms including apoptosis, prospero induced size symmetric terminal differentiation and a switch to gliogenesis by gcm expression. Expression of Tailless also was found to affect the timing of medulla neuroblast termination. They also ruled out several mechanisms such as ecdysone pulses.

      Major comments

      Clearly written and logical flow to experiments and results not over interpreted. Clearly show that the neuroblast number and size decrease (12 to 18 hrs) and are eliminated by 30 hours

      Figure 2a Marking of the Neuroepithelium. Would be more convincing if shown by PatJ expression and is clonal analysis. While the following panels use PatJ in clones suggesting are NE and NBs present it is more difficult to put into the context in the higher magnification images (Figure 2 D- M) and the Miranda expression in F' seems to be the entire lobe and it is not clear if would be any NE which does not agree with what is shown in panel A.<br /> Is difficult to see the neuroblasts in Figure 2 D D" and E. The figure does not match what is stated in the results in that the neuroblasts are difficult to observe. If the point is that there is fewer NE cells and more neuroblasts then this is hard to see. It has been previously shown that with Notch RNAi clones prematurely extrude form the NE (Egger 20210; Keegan 2023) and could be expressing more Neuroblast markers but this is not visible in the panels as shown. Are the images single focal plane or maximum projections? Imaging more deeply in the brain or viewing in cross section would account for these possibilities. The possibility that are more neuroblasts but not all at the surface of the OL should be addressed as this could also alter the overall results. Figure 2 is key to first point of the paper so needs to be addressed.

      Minor comments

      Why express volume of DPN in clone volume. Would make the point more clear and more strong be to express as number of NB in the 3-D volume of the clone. This measurement occurs in several figures. Use of Miranda to mark NBs is unclear in Figure 2. Perhaps more clear in B&W. Make clear in figures (or figure legend) if single focal plane or projections. It is unclear what percentage of NB the Gal4 line eyR16F10 are expressed in. Veen 2023 state that the GAL4 is also expressed in neurons and at different levels whether deeper within the brain or superficially on the surface of the brain. At 16 APF it is expressed but it is not clear whether it is in all cells at a low level or only within a few cells Some RNAi lines referenced as previously validated and other are not. For example: EcR, Oxphos, Med27, Notch need references or confirmation of specificity to the intended target (qRT) At least 2 animals per genotype were used. While I appreciate the technical difficulty of working in pupae this seems a bit low in terms of number of samples and data would be more robust with more numbers.

      Significance

      This provides mechanism and timing for the elimination of neuroblasts (NE to NB) that arise from the medulla. As these are most similar to mammalian brain development (Radial glial to NSC) this information provides more context to interpret the formation of glial and neurons in the adult optic lobe given the effect on timing and mechanisms of elimination.

      This paper would be of interest to developmental biologist who work with Drosophila or mice who are looking at neural development. An understanding of how neural diversity is achieved and the mechanisms behind this that can be dysfunctional in terms of etiology of neural diseases. Is a well done study for the most part that would be improved by clarifying some data and provided more replicates for robustness of the data. I am a developmental biologist working with Drosophila in larval and adult neural development.

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      Reply to the reviewers

      Rebuttal for Review Commons to:

      “A specific innate immune response silences the virulence of Pseudomonas aeruginosa in a latent infection model in the Drosophila melanogaster host”

      We thank the reviewers for their careful scrutiny of our manuscript. We believe that we have addressed satisfactorily the points raised by the reviewers and that our revised manuscript is definitely improved. Our replies below are in blue and use a distinctive font.

      Reviewer #1

      __Evidence, reproducibility and clarity __

      This works describes a latent Drosophila intestinal infection, which spreads systemically, with a direct systemic Drosophila infection using a common laboratory strain of Pseudomonas aeruginosa. The major observation of this study is that P. aeruginosa can cause a latent infection via its passage through the gut (as opposed to being injected). In doing so it exhibits cell rounding (instead of elongation), reduced cell motility, loss of O5-antigen, antibiotic resistance, ability to cross the intestinal barrier and circulate in the hemolymph and infiltrate the host tissue underneath the cuticle. In addition, latent infection bacteria induce all brunches of the systemic response: the Imd pathway, phagocytosis, and the melanization cascade. Moreover, the melanization pathway protects the host from a secondary systemic infection with various types of bacterial and fungal microbes.

      An issue that needs to be clarified is the sensitivity of P. aeruginosa virulence to its biochemical environment. The authors note that. For example, liquid bacterial culture in BHI induces the latent form of bacteria. So the growth conditions and the infection media play a major role in the infection process. They authors need to clarify further the effect of media and infection vehicles, sucrose (high/low), LB, and BHI (as well as temperature) on the latent phenotype.

      Temperature is definitely an important parameter and bacteria appear to be somewhat more virulent at 25°C. This point is now addressed in the Material and Methods section (lines 675-679) and in Fig. S6I.

      As regards the influence of the composition of the infection solution, it does not seem to be a critical parameter that we have described in the context of continuous feeding on the bacterial solution (Limmer et al., PNAS, 2011). In preliminary experiments, we had tried LB or BHB medium to grow the bacteria and this did not make any difference (see Panel A below for LB [BHB used in our experiments]). As regards the sucrose concentration to the infection solution, we have tried two concentrations and did not observe any difference as regards the establishment of the latent infection. (see panel B below for 50 mM sucrose [100mM used in our experiments]). Of note, P. aeruginosa does not grow on sucrose solution alone. However, a latent infection was still established upon feeding the flies with PAO1 in sucrose alone, albeit likely with a mildly increased virulence, in the absence of any BHB medium (see panels C-D) below.

      A) Comparison of LB vs. BHB B) Establishment of latent infection with 50mM sucrose

      C) Establishment of a latent infection with a sucrose-only bacterial solution D) Colonization of host tissues by PAO1 ingested in a sucrose-only bacterial solution Minor issues: -Lines 579-581> How were the PAO1GFP/RFP constructed (details are needed)

      Done; please, see lines 641-643.

      -Figure 1D and other figures > CFUs given as Log2 are unconventional. One cannot easily deduce the burden unless e.g. translate 2e10 to ~1000 and 2e30 to ~10e9 CFUs.

      True, but bacterial titer increases by a factor of two at each division cycle. Even though we have previously used a Log10 representation, we now prefer using a Log2 representation. This representation has also been used by other authors in the field, e.g., Duneau et al., eLife, 2019.

      -Figire S1DB (now S1C)> "but from the outside of the gut". The given experiment does not prove that statement.

      This issue has been already dealt with in the Nehme et al. PLoS Pathogens 2007 article, as cited in the manuscript. We further provide in Fig. S1B pictures documenting the presence of bacteria associated with visceral muscles. Finally, we also show that the gut lumen is essentially cleared of bacteria after a period of feeding on a sucrose solution or gentamicin. Hence, most bacterial colonies originate from the outer layer of the gut. We clarify the issue in the text (lines 154-158).

      -Lines 146-7 > data are missing in support to the statement.

      We have now added Fig. S1B to document that the gentamicin treatment does work, as actually does feeding on sucrose solution alone, as previously documented in Limmer et al., 2011 (Fig. S2B). Of note, we cannot exclude that a few bacteria remain, especially in the crop, but those would be at very low titer. Please, see also reply to Reviewer 2.

      -Figure S1C > The effect of injury seems to be huge, and may account for much/most of the differences observed (including those between latent and active infection). This is further supported by Figure4A, injury may account for gut collapse and/or systemic stress.

      It is well known that injury alone induces the systemic IMD pathway response 6 hours after injury but largely subsides by 24 hours. The point of Fig. S1C is that the level of induction reached during latent infection is very low as compared to that observed during a systemic infection, here obtained for reference with an Escherichia coli injection and to a lesser extent with a PBS injection. In our latent infection model, we do not perform any injury, except as noted by the reviewer in Fig. 4: the effects of an experimental injury are observed only while the bacteria are crossing the intestinal barrier and hardly any effect is observed when the injury is performed on day 10 (Fig. S4B).

      -Figure S1D > How was "fated to die" assessed?

      The fluorescent flies were sorted out and their subsequent survival was monitored. As compared to nonfluorescent flies from the same batch, they died within two days of sorting them.

      -Figure 3B/10th day > Average line is misplaced.

      We thank the reviewer for pointing out this problem. The line is not the average but the median. We have now added a precise description of the bars to all the figure legends.

      -Lines 382-5 > what is the evidence of gut damage (or the absence of it)? How do the bacteria escape the gut?

      The absence of major gut damages has been documented in Limmer et al, PNAS, 2011. How the bacteria escape the gut remains an open question (intracellular and/or paracellular route).

      -Lines437-442 > The distinction between dormant P. aeruginosa in the fly tissues and persister cells (upon antibiotic treatment) cannot be justifies on the basis of relative bacterial numbers in the two systems. The extent of resistance to antibiotics though my serve that purpose.

      In our latent infection model, most of the bacteria that have crossed the gut barrier become dormant and are associated with tissues, except at the beginning of the infection. In contrast, when a bacterial culture is treated with antibiotics, most of the bacteria are killed by the treatments and only a few ones persist, likely because of an inactive metabolism. Thus, the induction of dormancy in our latent infection model does not rely on the selection of a few metabolically-inactive bacteria able to withstand an immune response or an antibiotic treatment.

      Significance

      The study is a significant advance to our knowledge. Notwithstanding further explanations, it provides a solid basis of understanding active versus dormant bacteria. It further establishes a mode of intestinal to systemic infection as a tool for further explorations.

      Reviewer #2

      Evidence, reproducibility and clarity

      Summary: In this study, Chen and colleagues investigated a new latent infection model for Pseudomonas aeruginosa using Drosophila melanogaster as a host. First, the authors established a new model for latent Pseudomonas infection. The key feature of this model is the translocation of P. aeruginosa from the gut to the hemolymph and the colonization of fly tissues by the dormant bacteria. Bacteria that translocated from the gut appeared strikingly different in morphology and resistance to antibiotics compared to bacteria that were directly injected. Next, the authors suggest that melanization but not the Imd pathway or hemocytes are necessary to promote dormancy and colonization of fly tissues. Finally, flies with latent P. aeruginosa infection exhibit improved survival after secondary infections in a melanisation-dependent manner. The study reports an interesting model for latent infection, provides insights into the host factors promoting latency and describes some of the consequences of such latent infection for the host. However, some of the conclusions are not fully supported by the data and need further experimental evidence.

      Major comments: 1. The latent infection model requires some clarifications. First, temperature. Could the authors explain why they used 18 {degree sign}C and could low temperature contribute to the establishment of dormancy?

      As shown in Fig.S6I, the latent infection model is less compelling at 25°C in terms of survival curves, which may reflect an increased rate of spontaneous reactivation of the virulence, a phenomenon we have not studied at 25°C. In another manuscript in preparation (Lin et al.), we actually show that a small heat shock does contribute to reactivation of the bacteria, an issue that is outside of the scope of the present study. Please, see also reply to reviewer 1.

      Second, the use of gentamycin. How does gentamicin affect PAO1 outside the gut? From Fig.1C It looks like the cfus in the hemolymph diminished rapidly after gentamicin treatment (around day 3), suggesting the potential effect of the antibiotic. Once the bacteria have crossed the gut and entered the hemolymph, they could still be affected by feeding flies the antibiotic. Is there a possibility that gentamicin treatment is a stress factor that could trigger or facilitate the transition to dormancy? The authors could test this experimentally either by omitting the antibiotic and assessing dormancy or by feeding injected flies with gentamycin and scoring dormancy.

      We had actually tested the issue about the potential role of gentamicin outside of the gut compartment. We have thus fed flies on different concentrations of gentamicin and monitored the survival of those flies to the injection of PAO1 bacteria (please, see Figure below). When flies were feeding on the highest concentration of gentamicin tested, 32 mg/mL, they were succumbing fast to the PAO1 challenge, but not as fast as nontreated positive control PAO1 injected flies. The use of lower concentrations (16, 8, and 4 mg/mL) led to a progressively stronger protection from PAO1 injection that inversely correlated with the gentamicin dose. We interpret the data with high gentamicin concentrations as an indication that gentamicin at such concentrations is likely directly toxic to the flies, an issue that could be experimentally tested but is not relevant to this study. Interestingly, lower doses led to a much-decreased protection from PAO1 (2mg/mL) to no protection at the dose we use to establish latent infection (100 µg/mL). Thus, these data show that gentamicin can pass the gut barrier when provided at high concentrations, down to 2 mg/mL. However, there is no proof of such a passage at the dose we use. In keeping with this latter possibility, we made a control experiment in which the gentamicin treatment step was replaced by simply feeding on the sucrose solution: the bacterial titer decreased in the hemolymph at the same rate as for gentamicin-treated flies (new Fig. S1F), demonstrating that ingested gentamicin does not contribute to the decreased titer. Rather, the likely depletion of the “source”, that is PAO1 in the gut lumen, best accounts for this phenomenon.

      We have now cited references which document a lack of permeability of the gut barrier to ingested gentamicin in vertebrate animals (lines 130-133).

      As regards the possibility that gentamicin acts as a stress factor on bacteria, our data do not support this possibility, as a latent infection is established in the absence of gentamicin by just feeding the flies on a sucrose solution. We had previously reported that flies fed with P. aeruginosa for up to three days do not succumb within the next two weeks when they are fed on a sterile sucrose solution after having ingested the bacterial solution (Limmer et al., PNAS, 2011; Fig. 1C). Under the conditions of two days of PAO1 ingestion, we document in novel Fig. S1G that the carcass is equally well colonized under these conditions.

      Figure: impact of gentamicin ingestion at diverse concentrations on the survival of injected PAO1 bacteria. The ingested antibiotics can act on bacteria present in the hemocoel at concentrations over 2 mg/mL and not at that used in our experiments (100 µg/mL).

      Does melanization really induce the dormant state of the bacteria? I am not sure the provided data fully support this claim. Addressing these questions might provide a stronger evidence: Fig. 2 A-F: What causes the morphological changes of the bacteria? Melanization or the passage through the gut? Do authors see the same changes in bacteria retrieved from PO-deficient mutant flies? Fig. 2G: Do the authors see the same resistance of PAO1 that colonized PO mutant flies to antibiotics?

      In a novel Fig. S4, we now document comprehensively the physiological state of PAO1 bacteria fed to PO-deficient flies. We find that these bacteria are susceptible to antibiotics treatment as they can be rescued from death by the injection of antibiotics on day 3 (Fig. S4A-B). Second, they show a mixed phenotype in terms of colony morphology (Fig. S4C) and bacterial morphology and cell wall properties: even though most bacteria appeared to have kept a rounded morphology, they predominantly (about 75%) expressed the O5-LPS antigen. We interpret these data in terms of a slower transition to virulence than in a septic injury model. Melanization thus strongly contributes to the establishment of latency, even though it is likely that other factors contribute to the establishment of dormancy, but at best provide a minor contribution.

      How do PO mutants behave after PAO1 injection? Are they similarly more susceptible?

      PPO1-PPO2 mutants are not more susceptible to PAO1 injection than wt controls (new Fig. S3C).

      Fig. 3F: PPO1 is believed to be the fast-acting PPO, whereas PPO2 is deployed later in infection.

      This statement is based on experimental data gained on larvae, not adults. It is not really clear whether the about 10% adult hemocytes that express PPO2 actually contain crystals, in as much as the adult may be better oxygenated than larvae that grow in a hypoxic environment (description by the laboratory of Prof. Jiwon Shim of a role for PO in respiration at the latest EDRC meeting).

      How does the Western blot look for PPO1? Will it show an early induction of melanization that could drive the change into the dormant state?

      We provide below a characterization of the PPO antibody we use by Western blot analysis. This antibody had originally been raised by the late Dr. Hans-Michael Müller against a PPO from mosquito cell lines, hence explaining its cross-reaction to both * Drosophila PPO1 and PPO2 (Muller, H.M., Dimopoulos, G., Blass, C., and Kafatos, F.C. (1999)). A hemocyte-like cell line established from the malaria vector Anopheles gambiae expresses six prophenoloxidase genes. J Biol Chem 274*, 11727-11735.). It follows that at least one PO is partially cleaved at day 2 and that both are fully cleaved by day6 of the establishment of the latent infection (Fig. 3F, Fig. S3F).

      Figure: characterization of the antibody raised against A. gambiae PPO

      Alternatively, the induction of melanization could also be measured with an L-DOPA test.

      This experiment is not needed given the explanation provided above.

      Fig. 3E: Melanization prevents the growth of PAO1 adhering to tissues, as shown in Fig. 3E. One can see higher levels of cfus in the carcass in PO deficient flies compared to wt flies. However, after, 5 days, there is no difference in the cfus of wt and mutant flies anymore. If the growth inhibition was melanization mediated, would we not expect a consistent growth of bacteria in PO mutants? How to explain the drop in cfus in PO deficient mutants?

      This observation is difficult to account for and the explanations we can put forward at this stage are somewhat speculative. It appears that bacteria found in the tissues in PO-deficient flies have a morphology found in in vitro culture and within the gut, which does not correlate with virulence but also not with the avirulence state since they are LPS O5 positive. Given the shallow survival curves, we envision that there is a progressive release of bacteria from the tissue and then quick proliferation in the hemolymph in a few flies that would then die, but at a frequency too low to reliably ascertain in our hemolymph titer data, with a few flies displaying a high titer (Fig. 3D). By day5, the decreased titer in the carcass may reflect the progressive depletion of tissue-associated bacteria as they progressively become planktonic.

      Fig. 5D: How do PAO1 bacteria react to Levofloxacin treatment? Do they still go into the dormant state? Do they still attach to tissues? The authors should show that Levofloxacin treatment leads to the same dormant state as gentamycin before interpreting the results of this experiment.

      Taken together, our data yield a mixed result. When levofloxacin was fed for two days to latently-infected flies, we found that colonization was not altered (Fig. S2D’), in contrast to a septic injury model in which injected bacteria were susceptible to the ingested antibiotics (Fig. S2D”). Following the reviewer’s query, we have further monitored survival and bacterial colonization in the levofloxacin ingestion model. Fig. S2D had already demonstrated that ingested levofloxacin protects the flies from injected PAO1. Fig. S6F shows that the double mutant PO bacteria are protected from ingested PAO1 by the ingestion of this antibiotics. When we monitored the bacterial burden, we found for both wild-type and double PO mutant flies that the bacteria had been cleared in some 50% of the flies. The exact interpretation of the wild-type data is not straightforward. On the one hand, the colonizing bacteria may have become susceptible to the antibiotics even though they remained dormant. On the other hand, they might have been reactivated in their virulence and thus become secondarily susceptible to the antibiotics. For the double PO mutants, the 40% bacteria remaining may witness the mixed bacterial state of PAO1 in these mutants, as documented in Fig. S4. Nevertheless, the important point is that bacteria are unlikely to contribute to the demise of secondarily infected flies since they have been cleared in at least 50% of the flies, yet the secondarily challenged flies become susceptible only when the relevant melanization genes are affected. The nonPAO1-infected controls succumb faster to the infection than infected ones: the protection against secondary infections is provided by the activation of the melanization cascade by colonizing PAO1 bacteria, even if the colonization is transient in the levofloxacin treatment.

      We have altered the main text to reflect these novel data: lines 387-403.

      Minor comments:

      Lines 68-72. Mechanisms that are listed are not specific against Gram-negative bacteria but rather general. Please correct.

      We are of course aware of this. If it is general, it also applies to Gram-negative bacteria that are the focus of this article. Actually, an earlier version of the manuscript just mentioned the IMD pathway, hence the reference to Gram-negative bacteria. However, the Toll pathway is also required in the host defense against some Gram-negative pathogens such as P. aeruginosa. We have now deleted “Gram-negative” in this corrected version.

      Line 95. In - as?

      We are not sure we understand this comment. We have now added a reference documenting that P. aeruginosa can be found in rotting fruits (line 97).

      Lines 182-187. Some background information is needed. What is O5 LPS antigen? What motivated the authors to look at it specifically?

      The O-antigen is a long-chain polysaccharide motif that constitutes the outermost part of the cell wall. It varies according to the strain. We have added a couple of references that refer to O-antigen (line 198). We had actually already found out this result (unpublished) with the Serratia marcescens Db11 O-antigen (O18) that was not found in bacteria that had crossed the gut. The loss of the O5 antigen changes the surface of the bacterium and likely its interactions with tissues and/or the immune system. In the case of Serratia, we suspect that the loss of its O-antigen allows the bacterium to be phagocytosed in an eater-dependent manner.

      Fig. 3C: Why PPO1 and Hayan and PPO1,2 and Sp7 are compared but not mutant vs wild type?

      The reason is that it was obviously significant. We have now added the comparisons to wild-type in the revised figure.

      How precise is estimation of bacteria in the carcass?

      Even though it is not possible to measure how precise these measures are, they are nevertheless reproducible making us confident that they provide an estimate of the rough number of these bacteria found associated to tissues.

      How do the authors prevent dissemination of the bacteria during dissection? I wonder if some bacteria might by lost during the dissection (when removing the gut and ovaries) or if you carry over some bacteria from the hemolymph into the carcass measurement? How to make sure, that the bacteria you recover were really adherent and were not leftover from the hemolymph?

      It is not possible to prevent dissemination as we cannot fix the tissues and bacteria if we make cfu counts. However, the finding that bacteria are found in the hemolymph only for the first three days, with a distinct morphology from tissue-associated bacteria, and not at later time points make us confident that this is not an issue, which suggests that the bacteria are rather tightly attached to the tissues. As regards contamination of tissues by hemolymph, it is also not an issue since the hemolymph titers are so low. However, when the bacteria are actively proliferating to high levels, this is a legitimate concern.

      I am also curious how the differences in the cfu levels between whole fly and carcass can be explained (Fig. 1D). After day 5 there are almost no bacteria left in the hemolymph, however, if you compare cfus in the whole fly vs. the carcass, one can see that the whole fly cfus are rising from day 4 onwards. Where do these bacteria come from if not from the hemolymph?

      To assess the statement of the reviewer, we now have included the numerical values of the medians of the bacterial burdens displayed in Fig. 1D. There is no increased bacterial burden in whole flies between days 5 to 12; however, the titer is increased at days 15 and 22. Whether this slight increase is biologically relevant is questionable given the spread of the data (see also reply to previous point on the precision of measures). We cannot rigorously exclude that there might be a low-level proliferation of colonizing bacteria late in the latent infection, which has been observed in specific conditions of reactivation of dormant bacteria (Lin et al., in preparation).

      Fig. S4D: If the protection to secondary PAO1 infection is not mediated via Imd or phagocytosis, is it mediated via melanization? How do melanization mutants (increased or decreased) respond to PAO1 secondary infection?

      We have performed the experiment (Fig. S6A-B) and found that the protection was abrogated. As noted in the main text, the interpretation is however difficult since the bacteria are no longer in a dormancy state in the PPO mutants.

      Significance

      This study suggests that host factors, particularly specific immune responses, could drive the latent infections. Hence, besides bacterial mechanisms that received significant attention, we should not underestimate the host's contribution to promoting the latent state in bacteria.

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      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      In this study, Chen and colleagues investigated a new latent infection model for Pseudomonas aeruginosa using Drosophila melanogaster as a host. First, the authors established a new model for latent Pseudomonas infection. The key feature of this model is the translocation of P. aeruginosa from the gut to the hemolymph and the colonization of fly tissues by the dormant bacteria. Bacteria that translocated from the gut appeared strikingly different in morphology and resistance to antibiotics compared to bacteria that were directly injected. Next, the authors suggest that melanization but not the Imd pathway or hemocytes are necessary to promote dormancy and colonization of fly tissues. Finally, flies with latent P. aeruginosa infection exhibit improved survival after secondary infections in a melanisation-dependent manner. The study reports an interesting model for latent infection, provides insights into the host factors promoting latency and describes some of the consequences of such latent infection for the host. However, some of the conclusions are not fully supported by the data and need further experimental evidence.

      Major comments:

      1. The latent infection model requires some clarifications. First, temperature. Could the authors explain why they used 18 {degree sign}C and could low temperature contribute to the establishment of dormancy? Second, the use of gentamycin. How does gentamicin affect PAO1 outside the gut? From Fig.1C It looks like the cfus in the hemolymph diminished rapidly after gentamicin treatment (around day 3), suggesting the potential effect of the antibiotic. Once the bacteria have crossed the gut and entered the hemolymph, they could still be affected by feeding flies the antibiotic. Is there a possibility that gentamicin treatment is a stress factor that could trigger or facilitate the transition to dormancy? The authors could test this experimentally either by omitting the antibiotic and assessing dormancy or by feeding injected flies with gentamycin and scoring dormancy.
      2. Does melanization really induce the dormant state of the bacteria? I am not sure the provided data fully support this claim. Addressing these questions might provide a stronger evidence: Fig. 2 A-F: What causes the morphological changes of the bacteria? Melanization or the passage through the gut? Do authors see the same changes in bacteria retrieved from PO-deficient mutant flies? Fig. 2G: Do the authors see the same resistance of PAO1 that colonized PO mutant flies to antibiotics? How do PO mutants behave after PAO1 injection? Are they similarly more susceptible?
      3. Fig. 3F: PPO1 is believed to be the fast-acting PPO, whereas PPO2 is deployed later in infection. How does the Western blot look for PPO1? Will it show an early induction of melanization that could drive the change into the dormant state? Alternatively, the induction of melanization could also be measured with an L-DOPA test.
      4. Fig. 3E: Melanization prevents the growth of PAO1 adhering to tissues, as shown in Fig. 3E. One can see higher levels of cfus in the carcass in PO deficient flies compared to wt flies. However, after, 5 days, there is no difference in the cfus of wt and mutant flies anymore. If the growth inhibition was melanization mediated, would we not expect a consistent growth of bacteria in PO mutants? How to explain the drop in cfus in PO deficient mutants?
      5. Fig. 5D: How do PAO1 bacteria react to Levofloxacin treatment? Do they still go into the dormant state? Do they still attach to tissues? The authors should show that Levofloxacin treatment leads to the same dormant state as gentamycin before interpreting the results of this experiment.

      Minor comments:

      Lines 68-72. Mechanisms that are listed are not specific against Gram-negative bacteria but rather general. Please correct.

      Line 95. In - as?

      Lines 182-187. Some background information is needed. What is O5 LPS antigen? What motivated the authors to look at it specifically?

      Fig. 3C: Why PPO1 and Hayan and PPO1,2 and Sp7 are compared but not mutant vs wild type? How precise is estimation of bacteria in the carcass? How do the authors prevent dissemination of the bacteria during dissection? I wonder if some bacteria might by lost during the dissection (when removing the gut and ovaries) or if you carry over some bacteria from the hemolymph into the carcass measurement? How to make sure, that the bacteria you recover were really adherent and were not leftover from the hemolymph? I am also curious how the differences in the cfu levels between whole fly and carcass can be explained (Fig. 1D). After day 5 there are almost no bacteria left in the hemolymph, however, if you compare cfus in the whole fly vs. the carcass, one can see that the whole fly cfus are rising from day 4 onwards. Where do these bacteria come from if not from the hemolymph?

      Fig. S4D: If the protection to secondary PAO1 infection is not mediated via Imd or phagocytosis, is it mediated via melanization? How do melanization mutants (increased or decreased) respond to PAO1 secondary infection?

      Significance

      This study suggests that host factors, particularly specific immune responses, could drive the latent infections. Hence, besides bacterial mechanisms that received significant attention, we should not underestimate the host's contribution to promoting the latent state in bacteria.

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      Referee #1

      Evidence, reproducibility and clarity

      This works describes a latent Drosophila intestinal infection, which spreads systemically, with a direct systemic Drosophila infection using a common laboratory strain of Pseudomonas aeruginosa. The major observation of this study is that P. aeruginosa can cause a latent infection via its passage through the gut (as opposed to being injected). In doing so it exhibits cell rounding (instead of elongation), reduced cell motility, loss of O5-antigen, antibiotic resistance, ability to cross the intestinal barrier and circulate in the hemolymph and infiltrate the host tissue underneath the cuticle.

      In addition, latent infection bacteria induce all brunches of the systemic response: the Imd pathway, phagocytosis, and the melanization cascade. Moreover, the melanization pathway protects the host from a secondary systemic infection with various types of bacterial and fungal microbes.

      An issue that needs to be clarified is the sensitivity of P. aeruginosa virulence to its biochemical environment. The authors note that. For example, liquid bacterial culture in BHI induces the latent form of bacteria. So the growth conditions and the infection media play a major role in the infection process. They authors need to clarify further the effect of media and infection vehicles, sucrose (high/low), LB, and BHI (as well as temperature) on the latent phenotype.

      Minor issues:

      • Lines 579-581> How were the PAO1GFP/RFP constructed (details are needed)
      • Figure 1D and other figures > CFUs given as Log2 are unconventional. One cannot easily deduce the burden unless e.g. translate 2e10 to ~1000 and 2e30 to ~10e9 CFUs.
      • Figire S1D > "but from the outside of the gut". The given experiment does not prove that statement.
      • Lines 146-7 > data are missing in support to the statement.
      • Figure S1C > The effect of injury seems to be huge, and may account for much/most of the differences observed (including those between latent and active infection). This is further supported by Figure4A, injury may account for gut collapse and/or systemic stress.
      • Figure S1D > How was "fated to die" assessed?
      • Figure 3B/10th day > Average line is misplaced.
      • Lines 382-5 > what is the evidence of gut damage (or the absence of it)? How do the bacteria escape the gut?
      • Lines437-442 > The distinction between dormant P. aeruginosa in the fly tissues and persister cells (upon antibiotic treatment) cannot be justifies on the basis of relative bacterial numbers in the two systems. The extent of resistance to antibiotics though my serve that purpose.

      Significance

      The study is a significant advance to our knowledge.

      Notwithstanding further explanations, it provides a solid basis of understanding active versus dormant bacteria.

      It further establishes a mode of intestinal to systemic infection as a tool for further explorations.

  3. Jan 2024
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      Reply to the reviewers

      1. General Statements [optional]

      All four reviewers have positive comments on the paper. We totally agree with their comments, and proposed controls and experiments. Most of them are already introduced in the present text and several new figures added, as we had the controls/experiments proposed. Few others are now being done and we hope to have the complete set of experiments ready in 2-3 months.

      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

      Most comments of this reviewer have already been done and included in the transferred manuscript, except for part of the first comment:

      1.1 b. Is it possible that the loss of function of Wengen on its own has a phenotype? If so, that would suggest that Wgn in addition to its role in regeneration might be implicated in pro-survival processes in homeostatic conditions?

      This issue is very important to understand the differential role of Wgn and Grnd. First of all, Wengen knock out (wgnKO; Andersen et al., 2015) is viable in homozygosis. However, in this paper we have focused on inducible mutants. Therefore, we have now crossed the flies to get the genotype hh-Gal UAS RNAi wgn and we will check for apoptotic phenotype, as suggested. This will take us few weeks of work.

      Reviewer #2 Most comments have been already carried out and included in the transferred manuscript, except these ones:

      *2.3. Aside from wgn, other RNAi experiments are not validated through independent RNAi lines. I suggest expanding the Supplemental Figures to reproduce a few key findings with independent RNAi lines. *

      We have recently received a set of independent RNAi line to repeat the experiments for Traf1, Traf2, Ask1 from Bloomington Stock Center. And We did not do it before mainly because we wanted to focus on wgn and grnd. However, we agree with the Reviewer 2 and we will do the experiments. Another RNAi from VDRC for grnd and Tak1 have been ordered. These experiments will take about 2 months from the crosses to the analysis of results (some flies still to arrive, and many crosses will be done at 17ºC).

      *2 4. In Figure 1E, the authors show that wgn RNAi enhances cell death caused by hh>egr. What is missing here is a wgn RNAi control without hh>egr. Is there any cell death caused by the loss of wgn alone (without hh>egr)? *

      This control is now in progress. Expected to have it complete in 2 weeks.

      *2.5. If wgn RNAi causes some degree of cell death, is the observed effect with hh>egr a significant genetic interaction, or merely additive? *

      The result from the previous comment will help us to respond this point.

        1. Is the wgn-p38 pathway sufficient to block egr induced cell death? The authors could test this by having hh>egr in the licT1.1 background. The authors have a more complex experiment in Figure 3, where licT1.1 is introduced into the hh>egr, wgn RNAi background. However, testing the effect of licT1.1 without wgn would establish a more direct relationship between egr and wgn-p38. *

      We have set the crosses for the experiment hh>egr and licT1.1 as suggested. The results will be included in the new version of the manuscript. 1 month.

      Reviewer #3

      All comments already carried out and included in the transferred manuscript. See next sections.

      __Reviewer #4 __

      Major comments:

      *4.3 In Figure 5, the cells expressing Rpr appeared to be pulled/extruded basally as expected. It would be beneficial to quantify Wgn and Grnd signals along cross-sections and provide higher magnification images of domain boundaries to illustrate differences in TNFR localization and levels. ** The micrographs for Grnd Figure 5B,D, F capture substantial signal from the peripodial epithelium where the salE/Pv> driver is likely not active? *

      We will do a thorough quantification of high-resolution stacks of images and include higher magnification of the analyzed stacks. To this aim, we need some more weeks to collect the images of each genotype, processed and quantify them. We propose to do have this work done in two months.

      *4.4 The non-autonomous induction of Wgn seems stronger when facing dying Rpr overexpressing cells simultaneously depleted of Eiger compared to Rpr OE alone. Should this be a reproducible, could the authors discuss potential reason for this observation? *

      It is difficult to respond this question, without quantification. The quantification suggested in the previous point, will allow us to state if Wgn is more accumulated in rpr +egr than rpr alone. Therefore, the previous point will tell us if there are significant differences and if, so it will help us to discuss it.

      Timing: The entire plan can be executed in 2-3 month.

      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.

      __Reviewer #1 __

      1.1 a- *The result in Fig1.H is somehow surprising. How does the overexpression of Egr induce caspase activation in the absence of its receptor Grnd? *

      The results of Fig. 1H, in which egr+grndRNAi+wgnRNAi results in high apoptosis indicates that wgn down regulation compromises survival even in the absence of grnd. The reviewer correctly points that “How does the overexpression of Egr induce caspase activation in the absence of its receptor Grnd?”.

      There is evidence that Eiger is involved in the regulation of the pro-apoptotic gene head involution defective (hid) in primordial germ cells (Maezawa 2009 Dev. Growth Differ., 51 (4) (2009), pp. 453-461) and in the elimination of damaged neurons during development (Shklover et al., 2015). Moreover, Eiger is necessary for HID stabilization and regulates HID-induced apoptosis independently of JNK signaling (Shklover et al., 2015). Therefore, in our discs egr activation in the absence of grnd and wgn can still result in apoptosis because of the absence of wgn’s survival signal and, presumably, activation of hid.

      We have introduced this issue in the text as:

      “To check for epistasis between grnd and wgn, we activated hh> egrweak and knocked down both TNFRs. We found high levels of cell death compared to wgn RNAi alone (Fig. 1H and 1I), which demonstrates that wgn down-regulation is dominant over grnd. This is surprising as it is generally assumed that Egr interacts with Grnd to induce apoptosis via JNK, which in turn activates the proapoptotic gene hid (Andersen et al., 2015; Diwanji & Bergmann, 2020; Fogarty et al., 2016; Igaki et al., 2002; Moreno, Yan, et al., 2002; Sanchez et al., 2019; Shlevkov & Morata, 2012). Interestingly, Egr is necessary for HID stabilization and can regulate HID-induced apoptosis independently of JNK (Shklover et al., 2015). Therefore, cells egrweak that downregulate grnd and wgn can still be eliminated because the lack of both Wgn-survival signal and the pro-apoptotic Grnd/JNK signal could result in an alternative pathway of apoptosis.”

      *1.2- In Fig.6, it would be relevant to include wengen inactivation within the domain where rpr is expressed to show that wengen is not required autonomously for regeneration (sal>rpr + wgn RNAi). What is the phenotype of the adult wing of sal-lexA>rpr + nub-gal4 >wgn RNAi animals.? *

      We have already added a new figure (Fig. S4C) containing this data. As shown, both wgnRNAi alone and wgn RNAi + rpr do not show relevant anomalies and regenerate normally. Therefore, we conclude that wgn is not autonomously required for regeneration.

      The adult wings sal-lexA>rpr + nub-gal4 >wgn RNA result in a strong aberration, as regeneration is inhibited. This experiment has been also added in another figure (Fig. S4B) it is done.

      *1.4 Minor- In fig.1I, it is surprising that knockdown of neither Grnd nor dTRAF2 significantly affects Egr-induced apoptosis *

      After applying a One-Way ANOVA test to compare all the groups against all the groups in fig. 1B no significative differences were detected between Control and RNAi grnd or RNAi dTRAF2 (p>0,05). But if we apply a Student’s T test, which is less restrictive, we obtain, indeed, significative differences:

      Control vs. RNAigrnd p=9,48x10-7

      Control vs. RNAi dTRAF2 p=2,47x10-7

      We have now added in the text:

      “Note that when egrweak cells downregulated dTRAF2 or grnd the cell death area ratio is slightly lower than egrweak alone (Fig. 1I), comfirming that dTRAF2 and Grnd contribute to apoptosis in egrweak cells.”

      *1.5 Minor The ability of the wing disc to regenerate has been associated with the induction of a developmental delay mediated by Dilp8. Are the authors observing this developmental delay is the case of sal-lexA>rpr + Ap-gal4 >wgn RNAi or sal-lexA>rpr + Ci-Gal4>wgn RNAi *

      The developmental delay due to Dilp8 has been observed by many laboratories, indeed. The question of the reviewer is relevant because if there is no delay in pupariation, regeneration could be compromised not because regeneration has been affected but because after pupariation regeneration is impeded.

      However, delay in pupariation has been found in our experiments. Usually for 11hrs of heat shock (to induce apoptosis) we found 1-2 days of delay.

      We have added the following text:

      “The ability of the wing disc to regenerate after genetic ablation has been associated with the induction of a developmental delay (Colombani et al., 2012; Garelli et al., 2012; Jaszczak et al., 2015; Katsuyama et al., 2015; Smith-Bolton et al., 2009). All genotypes analyzed in figure 6 showed a similar developmental delay of 1-2 days (at 17ºC) after genetic ablation in comparison to the animals of the same genotype in which no genetic ablation was induced, i.e. developed continuously at 17ºC (Fig. S4A). After the adults emerged, the wings were dissected, and regeneration was analyzed.”

      *1.7 Minor - The investigation of the evolutionary origin of TNFR in drosophila included in Fig.2 is cutting a bit the flow of the results. *

      The evolutionary origin starts now with a sentence that can smoothen the flow and few changes in that paragraph have been made:

      “Opposing roles between proteins of the TNFR superfamily suggests that they have an ancient origin and have followed divergent evolutionary paths. To track the differences observed between grnd and wgn, we decided to investigate the evolutionary origin of these two Drosophila genes.”

      *1.8 Minor The authors could explain in more details the double transactivation system for non-fly specialists. *

      The entire section has been re-written in Material and Methods.

      *1.9 Minor - It can be interesting to include and/or discuss these few references: *

      *PLoS Genet. 2019 Aug; 15(8): e1008133. ** PLoS Genet. 2022 Dec 5;18(12):e1010533. FEBS Lett. 2023 Oct;597(19):2416-2432. *

      *Curr Biol. 2016 Mar 7;26(5):575-84. *

      *Nat Commun. 2020 Jul 20;11(1):3631. **

      *

      All these references, and few others, have been introduced in the text.

      __Reviewer #2 __ *2. 1. The authors find that wgn RNAi enhances hh>egr-induced apoptosis. They validate the results with two independent RNAi lines in Figure S1. However, Figure S1 is missing a control without wgn RNAi, and therefore, the results are difficult to assess. *

      Fig S1A now contains this control.

        1. Are the two independent wgn RNAi lines targeting different regions of the coding sequence? *

      As the regions targeted by the 2 RNAi’s are different, see below, we have included in the text:

      “This observation was corroborated with an independent RNAi-wgn strain targeting a different region in the coding sequence (Fig. S1A and S1B). “

      Bloomington BL55275 (dsRNA-HMCO3962)

      VDRC GD9152 (dsRNA-GD3427)

      *2.7. In Figure 4, the authors show that egr expression induces ROS and performs anti-oxidant experiments. This part could be strengthened if they show that the ROS sensor signal disappears after Sod::Cat expression. *

      We had done this experiment and there is a definitively drop in Mitosox in discs in which the weak allele of egr is active. We have included this new image in Figure 4G and in the text.

      *2.8. How effective is egr RNAi? In Figure 5E, F, the authors knock down egr and obtain negative results. Based on this, the authors argue that Wgn localization occurs through an egr-independent mechanism. Drawing strong conclusions based on a negative result with egr RNAi is not a good practice since one cannot rule out residual egr activity that mediates the effect (of course , because there is cell death as well, death cells express egr). I suggest either finding ways to completely abolish egr function, or tone down the conclusion. *

      We have used ‘after knocking down eiger’ instead of in the ‘absence’ or ‘abolish’ eiger.

        1. Figure 6 shows that wgn RNAi aggravates the reaper phenotype. What's missing is a control that expresses wgn RNAi but not reaper. *

      Control experiments using the UAS-wgnRNAi in the absence of rpr are now shown in figure S4C.

      Reviewer #3 ____ 3.1.Minor Fig 6C-E would need a control disc without induced apoptosis (ie wildtype disc) stained for phospho-p38 as a baseline comparison. This is important to judge the significance of the remaining phospho-p38 in panel E where wgn is knocked down. The authors write ** " However, after knocking down wgn, phosphorylated p38 in the wing pouch ** surrounding the apoptotic cells was abolished (Fig. 6E)." *Depending on the amount of phospho-p38 in control discs, this may need to be rephrased to "strongly reduced" instead of "abolished". *

      A control disc stained with P-p38 has been added in Figure 6.

      We have changes ‘abolished’ by ‘strongly reduced’.

      * 3.2. This sentence in the Intro needs fixing because TNFa doesn't transduce the signal from TNFR to Ask1 since it's upstream of TNFR: "TNFα can transduce the TRAF-mediated signal from TNFR to Ask1 to modulate its activity (Hoeflich et al., 1999; Nishitoh et al., 1998, p. 0; Obsil & Obsilova, 2017; Shiizaki et al., 2013)." *

      We have rephrased this sentence by:

      “TNFα binds to TNFRs which in turn interact with TRAFs to transduce the signal to Ask1 to modulate its activity”.

      *3.3a In the results section, the authors start by ectopically overexpressing Eiger. Are there conditions where Eiger expression is induced in the wing? If yes, it would be helpful for the reader to mention that this system with the genetically GAL4-induced expression of Eiger aims to phenocopy one of these conditions. *

      Eiger ectopic expression has been induced in the wing to generate apoptosis. This is a common technique in Drosophila, and the Reviewer3 is right that a sentence should be useful for the reader.

      A sentence has been introduced at the beginning of the results section:

      “Ectopic expression of egr in Drosophila imaginal discs results in JNK-dependent apoptosis (Brodsky et al., 2004; Igaki et al., 2002; Moreno, Yan, et al., 2002).”

      *3.3b Fig 2C is not very self-explanatory: it is worth writing out what Hsa (H. sapiens), Bla and Sco stand for (there is plenty of space). *

      We have re-designed figure 2 to make it more self-explanatory.

      *3.4. This sentence is confusing: ** " ...Wgn localization were due to ROS or to the expression of egr, we used RNAi to knock down egr in the apoptotic cells and found that reduced Egr/TNFα had no effect on Wgn localization (Fig. 5E, 5F)." The authors may want to specify that Wgn is still accumulated even without Egr. ("No effect" is unclear). *

      This sentence has been modifies as:

      “Wgn localization were due to ROS or to the expression of egr, we used RNAi to knock down egr in the apoptotic cells and found that Wgn accumulation was not altered by the knocking down Egr/TNFα (Fig. 5E, 5F). “

      *3.5 Comment. It discovers that Wengen is activated by ROS. In fact, since Wengen binds TNF with an affinity that is several orders of magnitude lower than Grindelwald, and since Wengen is not even located at the cell membrane, these data call into question whether Wengen is a TNF receptor, or a ROS receptor? Could the authors comment on this ? Could it be that the results obtained in the past showing that Wengen is activated by TNF were actually due to TNF inducing apoptosis, leading to production of ROS, leading to activation of Wengen?

      *

      We totally agree with Reviewer#3. We have added a final paragraph in the discussion section.

      “We speculate that the subcellular location of Wgn and Grnd may contribute to the different functions of both receptors. Grnd is more exposed at the apical side of the plasma membrane, which makes this receptor more accessible for ligand interactions (Palmerini et al., 2021). Wgn, embedded in cytoplasmic vesicles, is less accessible to the ligand and could be more restricted to being activated by local sources of signaling molecules, such as ROS. In contrast to initial reports (Kanda et al., 2002; Kauppila et al., 2003), los-of-function of wgn does not rescue Egr-induced apoptosis in the Drosophila eye (Andersen et al., 2015), which supports our observation in the wing that Wgn is not required for Egr-induced apoptosis. Instead, Egr-induced apoptosis generates ROS which target intracellular Wgn to foster a cell survival program of cells close to the apoptotic zone.”

      __Reviewer #4 __

      *4.1 b Are phospho-p38 levels increased in cells expressing Egr[weak]? *

      We have the results of these experiments. To respond to this point, a new figure has been added (Fig. S4) in which we show the P-p38 levels are increased (non-autonomously) in egrw, as previously found for reaper. In addition, we show that egrw + activation of p35 and egrw + activation of Sod1::Cat results in strong reduction of P-p38. This indicates that P-p38 is stimulated by the ROS produced by apoptotic cells.

      The text now:

      “It is worth noting that cells egrw induce phosphorylation of p38 in neighboring cells (Fig. S4A) and that, as previously found for rpr (REF), depends on ROS generated by egrw apoptotic cells (Fig. S4B, C).”

      *4.2 In Figure 4C it appears that the Dcp-1 positive cells move apically rather than basally. Including nuclear staining would be very informative allowing assessment of tissue morphology. ** The authors focus on the pouch region of the wing imaginal disc, where phenotypes are strong and obvious. However, the hh-Gal4 driver also affects posterior cells in the hinge and notum, where the effects of Eiger[weak] overexpression seem weaker (e.g., minimal to no MitoSox signal in hinge and notum posterior cells). Could the authors explain this observation? *

      Point 1: Actually, cells move more basally, though some move more apical as well. Depending on the section cells the image could be confusing. To solve that, we show now a plane on these discs at apical and a plane basal. Both high magnifications. There one can see that there is more concentration of pyknotic nuclei basally. We have added this observation in a new supplementary figure (Fig. S3) and the corresponding text in page 5: “Apoptotic cells in egrweak are characterized by pyknotic nuclei and are positive for Dcp1. These cells tend to concentrate in the basal side of the epithelium, although some are scattered apically (Fig. S3). Accumulation of Wgn was observed in healthy anterior cells adjacent to both apical and basal egrweak cells (Fig. 4, Fig. S3A, B).”

      Point 2 Comment on MitoSOX in notum: At the stages of the imaginal discs used in this study, almost all notum cells are anterior compartment. The hh positive cells in notum much less abundant, therefore most of the staining was found in the posterior compartment of the wing pouch.

      *4.5 Figure 6 C-E. Does WgnRNAi potentiates and GrndRNAi suppress Rpr-induced apoptosis similarly to their effects when knocked down in Eiger[weak]OE cells? *

      The areas controlled by salE/Pv >rpr (dotted lines) are full of pycnotic nuclei, which indicates concentration of apoptotic cells in all genotypes shown.

      Thus, in the conditions generated here, apoptosis is not inhibited and grnd RNAi does not interfere with the activation of P-p38. In wgn knock down, phospho-p38 is strongly inhibited, indicating the importance of wgn in phosphorylation of p38.

      To clarify this point, we have added in the text: “Note that rpr-induced apoptosis is not suppressed after knocking down grnd or wgn.” Also in the figure legend we added: “White lines in the confocal images outline the salE/Pv-LHG,LexO-rpr dark area full of pyknotic nuclei of apoptotic cells.”

      4.6 The activation of p38 following salE/Pv>rpr-mediated ablation as shown by immunostaining is noteworthy. While loss Grnd knockdown leads to phospho-p38 signal enrichment around the rpr-expressing cells, WgnRNAi results in reduced phospho-p38 signal in the wing pouch but also beyond the nub-expression domain. Do salE/Pv>rpr nub>WgnRNAi cells still generate ROS?

      So far there is no evidence of Wengen as a ROS scavenger. We have evidence that ROS (using MitoSox probe) are produced in egrweak + Wgn RNAi cells. Thus, the inhibition of wgn expression does not block ROS production. A new figure shows this observation (Figure S4A).

      4.7 Are ROS responsible for the long-range signaling and p38 activation, referring to authors' previous work Santabarbara-Ruiz et al., 2019, PLoS Genet 15(1): e1007926. https://doi.org/10.1371/journal. pgen.1007926, Figure 5G?

      ROS are responsible for p38 activation as shown in a new figure (Fig. S4). In this new figure egrweak is activated in hh, and p38 is most of cells in the posterior compartment, and also anterior. However, after blocking apoptosis or ROS production, this P-p38 is reduced.

      4.8 Minor I propose rephrasing the description of "UAS-Egr[weak] transgene, a strain that produces a reduced Egr/TNFα activity". It could imply a loss of function strain rather than a transgene that causes mild/moderate Egr overexpression.

      The sentence has been rephrases as suggested (End of the first paragragraph in results section).

      *4.9 Minor. I recommend the authors to revise the charts for improved clarity in genotype representation. For example, in Figure 1I, the label "control-GFP" might be misleading. It would be beneficial to specify that "control" refers to Eiger[weak] alone with other manipulations being done simultaneously with Eiger[weak] overexpression. *

      All charts have been revised.

      4.10 Minor. Additionally, considering that individuals with color blindness may struggle to differentiate between red and green colors, I strongly suggest using a color-blind-friendly palette, especially in Figure 4A, C, G, and Figure 4A, C, E." ** All images have been revised for color blind code.

      • 11 Minor. Providing detailed information regarding the reagents used in the study, such as Catalogue Numbers or RRIDs, is beneficial for enhancing reproducibility. *

      We have added the RRID and Cat #. If no ID was available, we added the reference or contact.

      4.12 This reviewer points two limitations that we are now trying to solve:

      *Limitations: *

      *Quality of the imaging – higher magnification images and quantification would enhance the study. ** The summarizing model may contain excessive speculations that lack support from the data or references to the existing literature. *

      Quality of imaging. We have now an extra supplemental figure with higher magnifications. Extra higher magnifications will be included in the next version as well as quantification, as exposed for the Revision Plan points 4.3 and 4.4.

      Model: We have re-written the paragraph on the model, introduced references and drop some speculations. We hope the current version will be more convincing for the reader.

      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.

      Reviewer 1

      *1.3. Is the overexpression of Wengen sufficient to increase tissue regeneration? *

      The suggestion of the reviewer is a key point in regeneration biology: how to accelerate regeneration?

      We have demonstrated that Wengen is upstream the Ask1-p38 axis that drives regeneration. The reviewer wonders if Wengen overexpression can result in increase in regeneration. In a previous work we have demonstrated that p38 activation is key for regeneration but its overexpression can be deleterious (Esteban-Collado et al., 2021). Only in discs that sensitized for low p38 (starvation, low Akt, Ask1S83A mutant), the overexpression rescues regeneration. Therefore, the levels of the Wgn-Ask1-p38 have to be very tightly controlled. An excess will be deleterious. We are aware of the importance of the question, but at this point we do not have the technology to finely control Wgn-Ask1-p38 levels to do this experiment.

      1.6 Minor - It possible to test the induction of apoptosis in a wgn null mutant background to see if the phenotype is even stronger than the one observed with RNAi (the wgn RNAi is induced at the same time than egr or rpr overexpression).

      Flies wgnKO survive, but they gave us problems when carrying transgenes for our design of genetic ablation. Indeed, we tried to generate wgnKO carrying Gal4+tubGal80+eigerweak without success.

      In addition, the reason we have used an inducible mutant is because it allows us to work in time and space without altering expression in other cell types beyond wing discs. Wgn is required in other organs during development like gut, trachea and axon growth, etc.., and thus, we ensure the affected cells belong to the tissue analyzed.

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      Referee #4

      Evidence, reproducibility and clarity

      The study by Florenci Serras and colleagues presents compelling evidence highlighting distinct functions of the two Drosophila TNFRs, Wengen (Wgn) and Grindewald (Grnd) in developing imaginal epithelia. The study shows that while Grnd-dTraf2-Tak1 module controls apoptosis in Eiger (Egr)-dependent manner, Wgn-dTraf1-Ask1 promotes survival likely via p38 signaling independent of Egr. Their phylogenetic analysis underscores the ancient origin of both receptors while revealing their divergent evolutionary path, manifested by markedly different CRD sequences. Moreover, Wgn shows higher degree of similarity to mammalian TNFRs. Using functional genetics and confocal imaging of immunostained wing imaginal discs, the authors confirm the differential localization of Wgn and Grnd in imaginal cells, consistent with several recent studies. Interestingly, they demonstrate distinct responses between Grnd that is internalized upon Eiger[weak] overexpression from the plasma membrane, and Wgn, which cytoplasmic levels decrease in Eiger[weak] OE cells but become enriched in neighboring wild type cells. The non-autonomous accumulation of Wgn required ROS but not Eiger production by dying cells. Finally, employing an elegant double-driver lexA/lexO and Gal4/UAS system, enabling independent gene manipulation in specific domains of the wing imaginal discs, the authors established the essential role of Wgn, but not Grnd, in the regenerative response to apoptosis, including the occurrence of phosphorylated p38.

      Major comments:

      The conclusion regarding the protective role of p38 in response to Egr[weak] should be supported by a p38 knockdown experiment. Are phospho-p38 levels increased in cells expressing Egr[weak]?

      In Figure 4C it appears that the Dcp-1 positive cells move apically rather than basally. Including nuclear staining would be very informative allowing assessment of tissue morphology. The authors focus on the pouch region of the wing imaginal disc, where phenotypes are strong and obvious. However, the hh-Gal4 driver also affects posterior cells in the hinge and notum, where the effects of Eiger[weak] overexpression seem weaker (e.g., minimal to no MitoSox signal in hinge and notum posterior cells). Could the authors explain this observation?

      In Figure 5, the cells expressing Rpr appeared to be pulled/extruded basally as expected. It would be beneficial to quantify Wgn and Grnd signals along cross-sections and provide higher magnification images of domain boundaries to illustrate differences in TNFR localization and levels. The micrographs for Grnd Figure 5B,D, F capture substantial signal from the peripodial epithelium where the salE/Pv> driver is likely not active?

      The non-autonomous induction of Wgn seems stronger when facing dying Rpr overexpressing cells simultaneously depleted of Eiger compared to RprOE alone. Should this be a reproducible, could the authors discuss potential reason for this observation?

      Figure 6 C-E. Does WgnRNAi potentiates and GrndRNAi suppress Rpr-induced apoptosis similarly to their effects when knocked down in Eiger[weak]OE cells? The activation of p38 following salE/Pv>rpr-mediated ablation as shown by immunostaining is noteworthy. While loss Grnd knockdown leads to phospho-p38 signal enrichment around the rpr-expressing cells, WgnRNAi results in reduced phospho-p38 signal in the wing pouch but also beyond the nub-expression domain. Do salE/Pv>rpr nub>WgnRNAi cells still generate ROS? Are ROS responsible for the long-range signaling and p38 activation, referring to authors' previous work Santaba ́rbara-Ruiz et al., 2019, PLoS Genet 15(1): e1007926. https://doi.org/10.1371/journal. pgen.1007926, Figure 5G?

      Minor comments:

      I propose rephrasing the description of "UAS-Egr[weak] transgene, a strain that produces a reduced Egr/TNFα activity". It could imply a loss of function strain rather than a transgene that causes mild/moderate Egr overexpression.

      I recommend the authors to revise the charts for improved clarity in genotype representation. For example, in Figure 1I, the label "control-GFP" might be misleading. It would be beneficial to specify that "control" refers to Eiger[weak] alone with other manipulations being done simultaneously with Eiger[weak] overexpression. Additionally, considering that individuals with color blindness may struggle to differentiate between red and green colors, I strongly suggest using a color-blind-friendly palette, especially in Figure 4A, C, G, and Figure 4A, C, E."

      Providing detailed information regarding the reagents used in the study, such as Catalogue Numbers or RRIDs, is beneficial for enhancing reproducibility.

      Significance

      This is a very solid study that uncovers unique roles of Drosophila TNFRs in regulating imaginal cell behaviors crucial for tissue regeneration. It expands our knowledge on processes controlled by TNFR-mediated signaling, highlighting the potential for ligand-independent regulation. The study nicely complements recent findings by several laboratories (Letizia et al., 2023; Loudhaief et al., 2023; Palmerini et al., 2021). Beyond its contribution to fundamental biology, the study has biomedical implication for regenerative medicine. It emphasizes the necessity of balancing TNFR activities, downstream signaling and their dependence on ligands, providing important insights for the development of receptor agonists or antagonists. The findings are relevant to audience interested in developmental and regenerative biology, gene evolution.

      Strengths: functional genetics revealing distinctive roles for the two TNFRs in Drosophila and their dependency on ligand in the paradigm of tissue regeneration.

      Limitations: quality of the imaging - higher magnification images and quantification would enhance the study. The summarizing model may contain excessive speculations that lack support from the data or references to the existing literature.

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      Referee #3

      Evidence, reproducibility and clarity

      Summary:

      TNF receptors have a broad range of possible function, from inducing apoptosis to promoting cell survival and proliferation. How this works is not completely understood. Drosophila has two TNF receptors, Wengen and Grindelwald. This manuscript nicely shows that Grindelwald is pro-apoptotic while Wengen promotes cell survival and proliferation. Strikingly, if TNF is expressed in Drosophila tissue, knockdown of the receptor Wengen leads to elevated levels of apoptosis, clearly showing its cell-protective function. Interestingly, the authors find that Wengen is activated by ROS produced by neighboring dying cells - regardless of whether they are dying due to TNF signaling or not - and that Wengen then activates p38 downstream to mediate a regenerative response.

      Major comments:

      Overall the conclusions are interesting, clear and convincing. The data are of very good quality. I only have a few minor comments below.

      Minor comments:

      1. Fig 6C-E would need a control disc without induced apoptosis (ie wildtype disc) stained for phospho-p38 as a baseline comparison. This is important to judge the significance of the remaining phospho-p38 in panel E where wgn is knocked down. The authors write " However, after knocking down wgn, phosphorylated p38 in the wing pouch surrounding the apoptotic cells was abolished (Fig. 6E)." Depending on the amount of phospho-p38 in control discs, this may need to be rephrased to "strongly reduced" instead of "abolished".
      2. This sentence in the Intro needs fixing because TNFa doesn't transduce the signal from TNFR to Ask1 since it's upstream of TNFR: "TNFα can transduce the TRAF-mediated signal from TNFR to Ask1 to modulate its activity (Hoeflich et al., 1999; Nishitoh et al., 1998, p. 0; Obsil & Obsilova, 2017; Shiizaki et al., 2013)."
      3. In the results section, the authors start by ectopically overexpressing Eiger. Are there conditions where Eiger expression is induced in the wing? If yes, it would be helpful for the reader to mention that this system with the genetically GAL4-induced expression of Eiger aims to phenocopy one of these conditions.
      4. Fig 2C is not very self-explanatory: it is worth writing out what Hsa (H. sapiens), Bla and Sco stand for (there is plenty of space).
      5. This sentence is confusing: " ...Wgn localization were due to ROS or to the expression of egr, we used RNAi to knock down egr in the apoptotic cells and found that reduced Egr/TNFα had no effect on Wgn localization (Fig. 5E, 5F)." The authors may want to specify that Wgn is still accumulated even without Egr. ("No effect" is unclear).

      Significance

      This manuscript makes several important discoveries:

      1. it clearly shows that one TNF receptor, Grindelwald, is mainly pro-apoptotic, while the other, Wengen, is mainly pro-survival. This provides a mechanistic explanation for the dual role of the TNF, Eiger.
      2. It discovers that Wengen is activated by ROS. In fact, since Wengen binds TNF with an affinity that is several orders of magnitude lower than Grindelwald, and since Wengen is not even located at the cell membrane, these data call into question whether Wengen is a TNF receptor, or a ROS receptor? Could the authors comment on this ? Could it be that the results obtained in the past showing that Wengen is activated by TNF were actually due to TNF inducing apoptosis, leading to production of ROS, leading to activation of Wengen?
      3. It was previously shown that damage, for instance in the fly intestine, induces production of ROS, which then activates p38, leading to a proliferative/regenerative response. This manuscript provides a missing mechanistic link, showing that the ROS activates Wengen, which in turn activates p38. This thereby completes the mechanistic chain of events from damage to the regenerative response.

      Hence, overall, this is a very interesting study. It will be of interest for a broad audience of people studying TNF signaling, stress signaling and stress response, tissue damage and repair, and regeneration.

      My expertise: Drosophila, growth, signaling

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      Referee #2

      Evidence, reproducibility and clarity

      The Drosophila genome encodes a single TNFa ortholog, eiger (egr), and two TNF Receptros (TNFR), wengen (wgn) and grindelwald (grnd). While egr overexpression can cause apoptosis, the authors here report that wgn and grnd have opposing roles in cell death and survival. Specifically, the authors show evidence that grnd promotes cell death in response to egr expression, while wgn promotes cell survival through the p38 MAP Kinase pathway. They further show that apoptotic cells have high levels of ROS, which activates the wgn-p38 axis for tissue regeneration, independent of egr.

      Overall, the manuscript is well written. At the same time, there are some technical concerns and missing controls that need to be addressed. Below are a few specific comments for the authors' consideration:

      Major Comments

      1. The authors find that wgn RNAi enhances hh>egr-induced apoptosis. They validate the results with two independent RNAi lines in Figure S1. However, Figure S1 is missing a control without wgn RNAi, and therefore, the results are difficult to assess.
      2. Are the two independent wgn RNAi lines targeting different regions of the coding sequence?
      3. Aside from wgn, other RNAi experiments are not validated through independent RNAi lines. I suggest expanding the Supplemental Figures to reproduce a few key findings with independent RNAi lines.
      4. In Figure 1E, the authors show that wgn RNAi enhances cell death caused by hh>egr. What is missing here is a wgn RNAi control without hh>egr. Is there any cell death caused by the loss of wgn alone (without hh>egr)?
      5. If wgn RNAi causes some degree of cell death, is the observed effect with hh>egr a significant genetic interaction, or merely additive?
      6. Is the wgn-p38 pathway sufficient to block egr induced cell death? The authors could test this by having hh>egr in the licT1.1 background. The authors have a more complex experiment in Figure 3, where licT1.1 is introduced into the hh>egr, wgn RNAi background. However, testing the effect of licT1.1 without wgn would establish a more direct relationship between egr and wgn-p38.
      7. In Figure 4, the authors show that egr expression induces ROS and performs anti-oxidant experiments. This part could be strengthened if they show that the ROS sensor signal disappears after Sod::Cat expression.
      8. How effective is egr RNAi? In Figure 5E, F, the authors knock down egr and obtain negative results. Based on this, the authors argue that Wgn localization occurs through an egr-independent mechanism. Drawing strong conclusions based on a negative result with egr RNAi is not a good practice since one cannot rule out residual egr activity that mediates the effect. I suggest either finding ways to completely abolish egr function, or tone down the conclusion.
      9. Figure 6 shows that wgn RNAi aggravates the reaper phenotype. What's missing is a control that expresses wgn RNAi but not reaper.

      Significance

      There is now a detailed understanding of mammalian TNFRs, which play pro-apoptotic and non-apoptotic roles depending upon the context. Previous studies had also reported that TNFR1 respond to ROS. By comparison, our understandings of the two TNFRs in Drosophila remain rudimentary. The two receptors have different loss-of-function phenotypes, some of which may be independent of egr signaling. The major significance of this work is in delineating the distinct behaviors of the two Drosophila TNFRs, centering around their pro-apoptotic, or pro-survival properties.

      Audience: This study will draw the interest of Drosophila geneticists, those interested in Reactive Oxygen Species and cell death, and evolutionary biologists.

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      Referee #1

      Evidence, reproducibility and clarity

      Tumor necrosis factor (TNF)-α stands out as a remarkably conserved pro-inflammatory cytokine that plays crucial roles in immunity, tissue repair, and cellular homeostasis. The Drosophila TNF-TNF receptor (TNFR) system, known for its simplicity, combined with a versatile genetic toolkit, has been instrumental in unraveling the intricate mechanisms governing both the physiological and pathological functions mediated by TNF. Recently, the fly TNFR Wengen has been described to have ligand independent functions in maintaining tissue homeostasis and tracheal remodeling. The current manuscript describes a novel TNF/Egr-independent function of Wengen in regulating tissue regeneration in imaginal discs. The authors identify both the upstream regulator (ROS) and the downstream signaling pathway through Ask1/p38 MAPK. The data presented are solid and support an interesting model where ROS emanating from damaged tissue triggers Wgn-dependent signaling in adjacent cells to promote regeneration. Few points could be addressed:

      Major points:

      • The result in Fig1.H is somehow surprising. How does the overexpression of Egr induce caspase activation in the absence of its receptor Grnd? Is it possible that the loss of function of Wengen on its own has a phenotype? If so, that would suggest that Wgn in addition to its role in regeneration might be implicated in pro-survival processes in homeostatic conditions?
      • In Fig.6, it would be relevant to include wengen inactivation within the domain where rpr is expressed to show that wengen is not required autonomously for regeneration (sal>rpr + wgn RNAi). What is the phenotype of the adult wing of sal-lexA>rpr + nub-gal4 >wgn RNAi animals?
      • Is the overexpression of Wengen sufficient to increase tissue regeneration?

      Minor points:

      • In fig.1I, it is surprising that knockdown of neither Grnd nor dTRAF2 significantly affects Egr-induced apoptosis
      • The ability of the wing disc to regenerate has been associated with the induction of a developmental delay mediated by Dilp8. Are the authors observing this developmental delay is the case of sal-lexA>rpr + Ap-gal4 >wgn RNAi or sal-lexA>rpr + Ci-Gal4>wgn RNAi
      • It possible to test the induction of apoptosis in a wgn null mutant background to see if the phenotype is even stronger than the one observed with RNAi (the wgn RNai is induced at the same time than egr or rpr overexpression).
      • The investigation of the evolutionary origin of TNFR in drosophila included in Fig.2 is cutting a bit the flow of the results.
      • The authors could explain in more details the double transactivation system for non-fly specialists.
      • It can be interesting to include and/or discuss these few references:

      PLoS Genet. 2019 Aug; 15(8): e1008133.

      PLoS Genet. 2022 Dec 5;18(12):e1010533.

      FEBS Lett. 2023 Oct;597(19):2416-2432.

      Nat Commun. 2020 Jul 20;11(1):3631.

      Curr Biol. 2016 Mar 7;26(5):575-84.

      Significance

      The understanding of the mechanistic interplay between TNFR in integrating TNF-dependent and independent signals to stimulate distinct downstream responses lays the foundation for investigating whether these insights can be generalized to other members within the TNFR superfamily in all organisms. This work is relevant for a large audience of researchers working in the field of inflammation and TNFR.

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      Reply to the reviewers

      We thank the reviewers for their reading of our manuscript, which we believe has led to substantial improvements.

      To aid clarity, we have split Fig. 1 into three separate figures.

      For convenience, we have put all major changes in the text in blue.

      Reviewer #1

      Evidence, reproducibility and clarity

      Summary: Hui et al. tackle a crucial question in biology: what factors influence the preference for carbon sources in yeasts?

      They reveal that the growth rate on palatinose exceeds that on glucose,

      The above statement is incorrect --- we think the reviewer may have confused sugars.

      despite palatinose utilization being repressed in the presence of glucose. Consequently, the favored carbon source does not necessarily align with the one supporting the fastest growth rate. The study also delves into potential regulatory mechanisms governing carbon source preference and dismisses certain existing theories, such as the general carbon flux sensing mechanism proposed by Okano et al. [25].

      Major comments: None

      Minor comments:

      The authors suggest that a higher growth rate implies a higher glycolytic flux (l63), a crucial assumption underpinning their interpretation of the absence of a ``general carbon flux sensing mechanism' (l65). To substantiate this significant conclusion, they could calculate the extracellular uptake fluxes (based on the time-course concentrations of biomass and substrates).

      This suggestion is a good one, but unfortunately the number of data points in the new Fig. 3 are insufficient to estimate the uptake flux reliably.

      To address whether glycolytic flux increases, we have added a new paragraph to the introduction explaining how all the sugars we consider feed upper glycolysis, providing either its first or second metabolite. We therefore think it highly likely that any differences in growth rate are generated by differences in glycolytic flux. Indeed, Hackett et al., 2016, showed that the glycolytic flux increases with growth rate when they changed extracellular glucose concentrations. We now include this reference in the Discussion.

      The accumulation of certain by-products is known to be toxic, reducing cellular growth rate (e.g., acetate DOI: 10.1038/srep42135, ethanol DOI: 10.1016/B978-0-12-040308-0.50006-9, etc.), while they can also enhance growth under specific conditions (e.g., acetate DOI: 10.15252/embj.2022113079). Considering this is crucial to rule out certain hypotheses, such as the possibility that a by-product produced during growth on the first carbon source would not modulate growth on the second carbon source, potentially influencing the growth rate differentially in each phase. Although the authors use mutant strains to eliminate the role of some C2 compounds (acetate and ethanol), alternative pathways could be implicated in the (co-)utilization of these by-products. This aspect should be discussed, and ideally, the authors could quantify the time-course concentrations of by-products to assess their potential role.

      We agree with the reviewer that extracellular acetate and ethanol may inhibit growth, although budding yeast might be less sensitive than E. coli, the subject of most of the studies provided.

      Nevertheless, we think it unlikely that these chemicals modify the decision-making we see. First, the icl1Δ mutant we tested is unable to consume ethanol (Fernandez et al., 1992) or acetate (Lee et al., 2011) --- we now include these references in the SI --- and yet has wild-type behaviour (Fig. S2D). Second, we observe that isomaltase expression strongly decreases in the presence of galactose when we grow cells in a microfluidic device (Fig. S4), just like it does in batch culture (Fig. 3A), even though the constant flow of medium through the device removes any chemicals the cells excrete.

      The general flux-sensing regulatory mechanism proposed by Okano et al. [25], which has been dismissed by this study, has recently been questioned, as discussed in DOI: 10.15252/embj.2022113079. This aspect should be included in the discussion.

      Okano et al. studied E. coli while we study budding yeast. We therefore have shown that the understanding for that organism does not transfer to our eukaryotic example. We suspect that control in budding yeast combines both flux-sensing and specific regulation, as we say in the discussion, and so we consider our results to build on those of Okano et al.

      Significance

      Strengths & limitations: The work is robust, and the experiments in the study have been appropriately designed and conducted. The primary question of this study has been tackled using a combination of experimental and computational methods to thoroughly assess various regulatory and functional aspects. However, there are gaps in the data that could enhance key conclusions, notably the absence of glycolytic flux measurements. Moreover, further evidence is needed to substantiate the assertion that by-products do not play a role in carbon source preference.

      Advance: This study represents a significant step forward in comprehending the nutritional strategy of microbes. The authors demonstrate that the preferred carbon source may not necessarily be the one supporting the fastest growth rate. Furthermore, they dismiss certain theories that have been proposed to explain the growth strategy of microbes on mixed carbon sources.

      Audience: By addressing a fundamental question in life science, this work is important in the field of biology in general and of particular interest in systems biology, biotechnology, synthetic biology, and health. Consequently, it will be of interest to a broad audience.

      Reviewer #2

      Evidence, reproducibility and clarity

      Summary: The authors have used microtiter plates to produce growth profiles on combinations of different sugars. From this data they have evaluated whether the sugars are co-consumed or if there is a preference for either sugar, seen as a diauxic shift. They found diauxie between galactose and the disaccharide palatinose, but co-consumption between palatinose and fructose. They further used strains with perturbations in their GAL regulon to attempt to explain this discrepency.

      Major comments:

      I unfortunately found a large portion of the present manuscript unintelligable.

      Firstly, figures were incorrect to the point I could not dechiffre them: Figure 2A-C have black solid and dashed lines in the legend that are not found in the graph, instead there are orange and blue dashed lines in the graph with no legends. Figure 4C has no description of the y-axis. The growth rates in Figure 1C are very hard to follow, and there are definitely local maxima in both the blue and green profiles that are not being discussed (at 15-20 h). I cannot evaluate the conclusions drawn from the data until these issues have been resolved.

      We apologise for the difficulties experienced by this reviewer.

      The black lines in the old Fig. 2's legend, now Fig. 4, explain the different styles used: dashed lines are for single sugars regardless of their concentration and full lines are for mixtures regardless of their concentration. We now explicitly say this in the caption.

      We have fixed the missing label in what is now Fig. 6C and have moved the statement that we are showing two biological replicates for each set of concentrations earlier in Fig. 2's caption.

      We now explore the meaning of the shoulder for the fructose-palatinose mixture in Fig. 2B in the Discussion. This point is not a local maximum, unlike the case for diauxie, because the growth rate always decreases. The shoulder for the glucose-palatinose mixture was likely an artefact generated by measurement noise at low ODs because it was not present when we repeated the experiment. We now use that data for Fig. 2A & B. We also include a new Fig. S5 showing that there are sucrose-palatinose concentrations too that have a similar shoulder.

      Secondly, the language in the Results and Discussion sections is confusing. Alternating between present and imperfect tense as well as active and passive form makes it hard to distinguish the authors own results from literature findings (Results are usually written in passive, imperfect tense). Examples are found on lines 24, 29, 37-38, 59, 84, 131, and 165.

      We have made both sections flow more smoothly with substantial re-writing. As before, we cite all results that are not our own.

      The authors also do not consider the differences and similarities in catabolic pathways for assimilation of galactose, fructose and palatinose. Even if they do not see a reason to continue that as a possible explanation for the co-consumption between fructose and palatinose a discussion of why it is disregarded would not be out of place here.

      A good point, and we now state in the Introduction that all the sugars we study feed upper glycolysis.

      Significance

      There is some novelty to the authors findings, but I would argue it is being overstated in the present manuscript. Some examples of studies looking at catabolite repression, the main cause of diauxie, of sugars other than glucose can be found in: Simpson-Lavy and Kupiec (2019), Gancedo (1998), Prasad and Venkatesh (2008) and Borgstrom et al (2022).

      We strongly disagree with this statement. The papers cited do not address, as we do, the co-consumption between two sugars neither of which is glucose. Where they study two sugars, they always study glucose.

      Simpson-Lavy and Kupiec, 2019, investigate the interaction between acetate and ethanol, neither of which are sugars. Further, they are not independent carbon sources because cells convert ethanol into acetate when catabolising ethanol.

      Gancedo, 1998, is a review of glucose repression and describes how glucose represses the expression of genes for other sugars. Although Gancedo mentions ``galactose repression', this repression is of genes encoding enzymes for gluconeogenesis and the TCA and glyoxylate cycles, not of other sugar regulons, our subject.

      Prasad and Venkatesh, 2008, also focus on glucose and the well studied diauxie between glucose and galactose.

      Borgstrom et al., 2022, focus too on glucose and growth on glucose and xylose in recombinant strains. The standard laboratory strains we study have not be artificially engineered to consume xylose. They do mention that galactose causes repression of TPS1, which encodes an enzyme that synthesises the storage carbohydrate trehalose. This repression is again not of a sugar catabolic regulon, our subject.

      I would not say that the field would be significantly advanced by the publication of this manuscript, and the authors have themselves not explained the application of futhering the understanding palatinose metabolism in yeast. As mentioned above, the catabolite repression potential of galactose is already known, it just hasn't been shown for palatinose specifically before.

      We again strongly disagree. Our findings are novel. The reviewer did not provide any evidence for galactose repression of other sugar regulons, which is not widely recognised as we emphasised in the Discussion. We believe that the reviewer has confused the known "galactose repression' of gluconeogenic or TCA-cycle genes with our new report of repression of other sugar regulons in the presence of the sugar catabolised by the regulon.

      I would recommend a complete rewrite of the manuscript as presented, with a lower stated novelty, clearer language and comprehensible figures.

      Reviewer #3

      Evidence, reproducibility and clarity

      Summary: Microbes grow at different growth rates in different carbon sources. When more than one carbon sources are present in the media microbes often show a preference over certain carbon sources, and 'non-preferred' carbons sources are used only when the preferred carbon source is exhausted in the media, this process called diauxic shift.

      Why microbes exhibit such utilization preference over certain carbon sources, is an interesting question in microbiology and evolutionary biology, and the molecular mechanisms that enable microbes to preferentially use one carbon over another is worth investigating. It is intuitive to think that microbes will prefer to use a carbon source that confers maximum growth rate, but when tested experimentally it has been often observed that a carbon source in which microbes grow at sub optimal growth rate is actually preferentially used.

      Although the reviewer states that "it has been often observed that a carbon source in which microbes grow at sub optimal growth rate is actually preferentially used“, we are unaware of this work and would appreciate references, particularly for budding yeast. The most systematic study we know, in E. coli by Aidelberg et al., 2014 --- reference 13, concludes that "the faster the growth rate, the higher the sugar on the hierarchy“, the opposite behaviour.

      In this study authors demonstrate that budding yeast prefer to use galactose over palatinose, but not over sucrose or fructose where all three sugars can support faster growth rate compared to palatinose. Authors presented data where preferential galactose use and diauxic shift is observed in the growth curve when galactose and palatinose or glucose and palatinose combinations were used.

      No diauxic shift was observed in the growth curve when fructose-palatinose, or sucrose-palatinose combination were used. In fructose-palatinose and sucrose-palatinose combinations growth curves agree more with co-utilization strategies. Authors used transcriptomics and genetic perturbations to decipher the molecular mechanism of such preferential carbon use, and reports preference of galactose over palatinose is achieved by preventing positive feedback of MAL regulon, which encodes the genes for palatinose catabolism. We found this observation is interesting and the molecular mechanism of such preferential carbon use is nicely described in this paper. We also find claims authors made are well supported by experiments. Although catabolite repression and diauxic transitions are known in yeast, and authors also pointed out such previous references, but preferential use of a slower carbon source, i.e. galactose over at least one other fast-growing carbon is interesting enough for publication. We would like to support the publication of this article, but we have major concerns about the data analysis and data presentation. Authors must address our concerns which are mentioned below.

      Major comments:

      1. This study mainly hinges on growth rate measurements, but we found growth rates are not properly represented in the figures. Growth curves are always shown in linear scale, which makes it almost impossible to compare fast and slow growth when presented in same plot. All growth curves must be shown on log scale.

      We have changed all growth curves to log2 scale, following New et al., 2014, rather than Monod's choice of linear scale that we had originally.

      Our conclusions are unaffected.

      1. Growth rates of the Yeast strain growing individual single carbon sources (galactose, palatinose, sucrose and fructose) should be shown as a figure panel and t-test should be performed to conclude if the individual growth rates are significantly different or not.

      We already showed these growth rates in their own panel in Fig. 1B. Following the reviewer's suggestion, we have now added their statistical significance to the caption.

      1. Growth phase, lag phase, diauxic shift and post shift growth should be clearly shown in figure 2 and 4, each phase should be clearly marked, carbons used in each phase should be mentioned on the plot. Also, the growth curve must be plotted using log scale.

      Although we have changed all growth curves to log scale, we decided against include this additional labelling for two reasons. First, we are presenting evidence that some of the growth we observe is diauxic and labelling the curves as diauxic before we discuss this evidence undermines that discussion. Second, any further labels would clutter the figures, and we believe would hinder rather than help the reader.

      Instead we changed the colour scheme and the boldness of the diauxic growth curves in Fig. 2, which we hope the reviewer agrees adds the clarity they felt was missing.

      1. Authors has taken in account that MAL12 gene overexpression causes long lag when cells need to switch to maltose from glucose, and shown deletion of IMA1 decreases the lag with subsequent 2% growth rate increase in palatinose. How significant is this increase?

      We have confirmed the statistical significance through a t-test and added the results to the caption of Fig. 6C.

      1. Authors have an interesting observation that in sucrose-palatinose and fructose palatinose combinations, most probably co utilization of the carbons is taking place. Authors should discuss this in more details. In galactose-palatinose scenario intracellular galactose-based repression of gal80 and subsequent lack of feed forward of the Mal regulon is expected to stop co-utilization of palatinose. As authors have RNA seq data, can they make predictions for other carbon pairs, where sequential utilization can occur based on their model?

      We agree and have added more discussion of the fructose- and sucrose-palatinose mixtures to the Discussion and a new figure, Fig. S5.

      Our RNAseq data reveals the difference in gene expression caused by an active versus an inactive GAL regulon. In Fig. S11, we show that the hexose transporters HXT2 and HXT7 are down regulated in 0.1% fructose when the GAL regulon is active, perhaps implying that cells are able to prioritise galactose over other hexoses. Nevertheless, to predict if particular carbon sources are therefore favoured, we would need to know whether cells use specific hexose transporters to drive growth on different carbon sources, which has been little investigated.

      Minor comments:

      1. In figure 5, authors attempted to summarize the model, which is informative, but it will be more useful for non-specific reader if a cell-based cartoon, with transports on surface and catabolic enzymes inside is also added.

      We have re-designed Fig. 5, now Fig. 7, following this suggestion and agree it improves clarity.

      In this schematic diagram, switch from galactose (blue line) to red line (palatinose) shows a mixed color zone, it's a bit confusing, as this represents a bi-stable state. Authors should clearly comment on possibility of biostability while discussing their proposed mechanism.

      In the new figure, this part has been removed.

      1. The author may want to put their work in the context of other recent observations that bacteria do not try to maximize their growth rates in many conditions. Fast growth is often associated with expansive tradeoffs, and a carbon source which confers fast growth rate may confer selective disadvantage. Thus, there are evolutionary benefits of sub-optimal growth, which could be discussed in the manuscript. In this regard a recent study (bioRxiv (2023) doi:10.1101/2023.08.22.554312.) has established the link between resource allocation strategies, growth rates and tradeoffs, which may be taken in account while discussing. Are there any known tradeoffs, when galactose is used over palatinose and which is not the case sucrose or fructose?

      This is an interesting reference looking at growth on a single carbon source. We are unaware of similar tradeoffs relevant to our study. For example, we see little evidence for a constraint on the proteome because in a strain with a constitutively active GAL regulon there is no change in phenotype if we delete the genes for the three highly expressed GAL enzymes (Fig. S6B). Nevertheless and as we state in the penultimate paragraph of the Discussion, we agree that such a constraint must exist, although perhaps this constraint is ecological.

      Referees cross-commenting

      As other reviewers pointed out, this study has merit and addressed interesting questions, but needed to be written well in a more understandable form, we agree with this assessment. Also figures must be made much clearer, as all of the reviewers pointed out. In summary, this is an interesting study, but needs some work before publication.

      Significance

      General assessment: Strength and limitations:

      This study addressed an interesting question regarding resource preference and growth rate optimization in microbes. This is an important question in the field. Study is well designed and claims are backed up with experimental results. One of the limitations of the study is lack of predictability. Authors explained the mechanism for one pair of carbon sources, but how applicable that will be in general is not clear.

      We would argue that one of our important findings is to demonstrate that the scientific community is missing the information needed to make such predictions. We provide a counter example to the generally accepted belief that accurate predictions can be made using growth rates. Our work poses the question: what then are the physiological variables required to predict how a cell will consume a pair of carbon sources?

      Advance: This study helps to advance our knowledge. Their observation regarding preferential utilization of a carbon source which supports slower growth over a carbon source which can support faster growth, and the molecular mechanism provided will help researchers to understand resource allocation strategies better.

      Audience: Microbiology, systems biology, evolutionary biology, fermentation and bio process engineering research.

      Reviewer expertise: Biochemistry, systems biology, metabolic strategies and tradeoffs in microbes, microbial ecology.

    2. 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

      Review of the paper by Yu Huo et al.

      Summary:

      Microbes grow at different growth rates in different carbon sources. When more than one carbon sources are present in the media microbes often show a preference over certain carbon sources, and 'non-preferred' carbons sources are used only when the preferred carbon source is exhausted in the media, this process called diauxic shift. Why microbes exhibit such utilization preference over certain carbon sources, is an interesting question in microbiology and evolutionary biology, and the molecular mechanisms that enable microbes to preferentially use one carbon over another is worth investigating. It is intuitive to think that microbes will prefer to use a carbon source that confers maximum growth rate, but when tested experimentally it has been often observed that a carbon source in which microbes grow at sub optimal growth rate is actually preferentially used. In this study authors demonstrate that budding yeast prefer to use galactose over palatinose, but not over sucrose or fructose where all three sugars can support faster growth rate compared to palatinose. Authors presented data where preferential galactose use and diauxic shift is observed in the growth curve when galactose and palatinose or glucose and palatinose combinations were used.

      No diauxic shift was observed in the growth curve when fructose-palatinose, or sucrose-palatinose combination were used. In fructose-palatinose and sucrose-palatinose combinations growth curves agree more with co-utilization strategies. Authors used transcriptomics and genetic perturbations to decipher the molecular mechanism of such preferential carbon use, and reports preference of galactose over palatinose is achieved by preventing positive feedback of MAL regulon, which encodes the genes for palatinose catabolism. We found this observation is interesting and the molecular mechanism of such preferential carbon use is nicely described in this paper. We also find claims authors made are well supported by experiments. Although catabolite repression and diauxic transitions are known in yeast, and authors also pointed out such previous references, but preferential use of a slower carbon source, i.e. galactose over at least one other fast-growing carbon is interesting enough for publication. We would like to support the publication of this article, but we have major concerns about the data analysis and data presentation. Authors must address our concerns which are mentioned below.

      Major comments:

      1. This study mainly hinges on growth rate measurements, but we found growth rates are not properly represented in the figures. Growth curves are always shown in linear scale, which makes it almost impossible to compare fast and slow growth when presented in same plot. All growth curves must be shown on log scale.
      2. Growth rates of the Yeast strain growing individual single carbon sources (galactose, palatinose, sucrose and fructose) should be shown as a figure panel and t-test should be performed to conclude if the individual growth rates are significantly different or not.
      3. Growth phase, lag phase, diauxic shift and post shift growth should be clearly shown in figure 2 and 4, each phase should be clearly marked, carbons used in each phase should be mentioned on the plot. Also, the growth curve must be plotted using log scale.
      4. Authors has taken in account that MAL12 gene overexpression causes long lag when cells need to switch to maltose from glucose, and shown deletion of IMA1 decreases the lag with subsequent 2% growth rate increase in palatinose. How significant is this increase?
      5. Authors have an interesting observation that in sucrose-palatinose and fructose palatinose combinations, most probably co utilization of the carbons is taking place. Authors should discuss this in more details. In galactose-palatinose scenario intracellular galactose-based repression of gal80 and subsequent lack of feed forward of the Mal regulon is expected to stop co-utilization of palatinose. As authors have RNA seq data, can they make predictions for other carbon pairs, where sequential utilization can occur based on their model?

      Minor comments

      1. In figure 5, authors attempted to summarize the model, which is informative, but it will be more useful for non-specific reader if a cell-based cartoon, with transports on surface and catabolic enzymes inside is also added.

      In this schematic diagram, switch from galactose (blue line) to red line (palatinose) shows a mixed color zone, it's a bit confusing, as this represents a bi-stable state. Authors should clearly comment on possibility of biostability while discussing their proposed mechanism. 2. The author may want to put their work in the context of other recent observations that bacteria do not try to maximize their growth rates in many conditions. Fast growth is often associated with expansive tradeoffs, and a carbon source which confers fast growth rate may confer selective disadvantage. Thus, there are evolutionary benefits of sub-optimal growth, which could be discussed in the manuscript. In this regard a recent study (bioRxiv (2023) doi:10.1101/2023.08.22.554312.) has established the link between resource allocation strategies, growth rates and tradeoffs, which may be taken in account while discussing. Are there any known tradeoffs, when galactose is used over palatinose and which is not the case sucrose or fructose?

      Referees cross-commenting

      As other reviewers pointed out, this study has merit and addressed interesting questions, but needed to be written well in a more understandable form, we agree with this assessment. Also figures must be made much clearer, as all of the reviewers pointed out. In summary, this is an interesting study, but needs some work before publication.

      Significance

      General assessment: Strength and limitations: This study addressed an interesting question regarding resource preference and growth rate optimization in microbes. This is an important question in the field. Study is well designed and claims are backed up with experimental results. One of the limitations of the study is lack of predictability. Authors explained the mechanism for one pair of carbon sources, but how applicable that will be in general is not clear.

      Advance: This study helps to advance our knowledge. Their observation regarding preferential utilization of a carbon source which supports slower growth over a carbon source which can support faster growth, and the molecular mechanism provided will help researchers to understand resource allocation strategies better.

      Audience: Microbiology, systems biology, evolutionary biology, fermentation and bio process engineering research.

      Reviewer expertise: Biochemistry, systems biology, metabolic strategies and tradeoffs in microbes, microbial ecology.

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

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      Referee #2

      Evidence, reproducibility and clarity

      Summary: The authors have used microtiter plates to produce growth profiles on combinations of different sugars. From this data they have evaluated whether the sugars are co-consumed or if there is a preference for either sugar, seen as a diauxic shift. They found diauxie between galactose and the disaccharide palatinose, but co-consumption between palatinose and fructose. They further used strains with perturbations in their GAL regulon to attempt to explain this discrepency.

      Major comments: I unfortunately found a large portion of the present manuscript unintelligable.

      Firstly, figures were incorrect to the point I could not dechiffre them: Figure 2A-C have black solid and dashed lines in the legend that are not found in the graph, instead there are orange and blue dashed lines in the graph with no legends. Figure 4C has no description of the y-axis. The growth rates in Figure 1C are very hard to follow, and there are definitely local maxima in both the blue and green profiles that are not being discussed (at 15-20 h). I cannot evaluate the conclusions drawn from the data until these issues have been resolved.

      Secondly, the language in the Results and Discussion sections is confusing. Alternating between present and imperfect tense as well as active and passive form makes it hard to distinguish the authors own results from literature findings (Results are usually written in passive, imperfect tense). Examples are found on lines 24, 29, 37-38, 59, 84, 131, and 165.

      The authors also do not consider the differences and similarities in catabolic pathways for assimilation of galactose, fructose and palatinose. Even if they do not see a reason to continue that as a possible explanation for the co-consumption between fructose and palatinose a discussion of why it is disregarded would not be out of place here.

      Significance

      There is some novelty to the authors findings, but I would argue it is being overstated in the present manuscript. Some examples of studies looking at catabolite repression, the main cause of diauxie, of sugars other than glucose can be found in: Simpson-Lavy and Kupiec (2019), Gancedo (1998), Prasad and Venkatesh (2008) and Borgstrom et al (2022).

      I would not say that the field would be significantly advanced by the publication of this manuscript, and the authors have themselves not explained the application of futhering the understanding palatinose metabolism in yeast. As mentioned above, the catabolite repression potential of galactose is already known, it just hasn't been shown for palatinose specifically before.

      I would recommend a complete rewrite of the manuscript as presented, with a lower stated novelty, clearer language and comprehensible figures.

    4. 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: Hui et al. tackle a crucial question in biology: what factors influence the preference for carbon sources in yeasts? They reveal that the growth rate on palatinose exceeds that on glucose, despite palatinose utilization being repressed in the presence of glucose. Consequently, the favored carbon source does not necessarily align with the one supporting the fastest growth rate. The study also delves into potential regulatory mechanisms governing carbon source preference and dismisses certain existing theories, such as the general carbon flux sensing mechanism proposed by Okano et al. [25].

      Major comments: None

      Minor comments:

      • The authors suggest that a higher growth rate implies a higher glycolytic flux (l63), a crucial assumption underpinning their interpretation of the absence of a "general carbon flux sensing mechanism" (l65). To substantiate this significant conclusion, they could calculate the extracellular uptake fluxes (based on the time-course concentrations of biomass and substrates).
      • The accumulation of certain by-products is known to be toxic, reducing cellular growth rate (e.g., acetate DOI: 10.1038/srep42135, ethanol DOI: 10.1016/B978-0-12-040308-0.50006-9, etc.), while they can also enhance growth under specific conditions (e.g., acetate DOI: 10.15252/embj.2022113079). Considering this is crucial to rule out certain hypotheses, such as the possibility that a by-product produced during growth on the first carbon source would not modulate growth on the second carbon source, potentially influencing the growth rate differentially in each phase. Although the authors use mutant strains to eliminate the role of some C2 compounds (acetate and ethanol), alternative pathways could be implicated in the (co-)utilization of these by-products. This aspect should be discussed, and ideally, the authors could quantify the time-course concentrations of by-products to assess their potential role.
      • The general flux-sensing regulatory mechanism proposed by Okano et al. [25], which has been dismissed by this study, has recently been questioned, as discussed in DOI: 10.15252/embj.2022113079. This aspect should be included in the discussion.

      Significance

      Strengths & limitations: The work is robust, and the experiments in the study have been appropriately designed and conducted. The primary question of this study has been tackled using a combination of experimental and computational methods to thoroughly assess various regulatory and functional aspects. However, there are gaps in the data that could enhance key conclusions, notably the absence of glycolytic flux measurements. Moreover, further evidence is needed to substantiate the assertion that by-products do not play a role in carbon source preference.

      Advance: This study represents a significant step forward in comprehending the nutritional strategy of microbes. The authors demonstrate that the preferred carbon source may not necessarily be the one supporting the fastest growth rate. Furthermore, they dismiss certain theories that have been proposed to explain the growth strategy of microbes on mixed carbon sources.

      Audience: By addressing a fundamental question in life science, this work is important in the field of biology in general and of particular interest in systems biology, biotechnology, synthetic biology, and health. Consequently, it will be of interest to a broad audience.

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

      Learn more at Review Commons


      Reply to the reviewers

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

      This well done and interesting paper examining the connection between TXNIP and GDF15. The main thrust is that TXNIP upregulation chemotherapies, such as Oxa, results in an a down regulation of GDF15 early in tumorigenesis. Later in tumorigenesis, TXNIP upregulation is less pronounced, elevating GFP15 resulting in a blockage of tumor suppressive immune responses. Generally the work is convincing. For example, it's clear that TXNIP is up regulated by Oxa in an ROS and MondoA-dependent manner. Likewise its quite clear TXNIP loss reads to an upregulation of GDF15. However, it's also quite clear that Oxa suppresses GDF15 in a manner that appears to be completely independent of TXNIP. The writing in the paper implies strongly that there is a mechanistic connection between TXNIP and GDF15, but no experiments investigate this possibility.

      We feel this is very fair and is reflective of a) perhaps an overemphasis of the TXNIP knockout observation and supportive tissue data, which suggests a relationship but not a mechanistic understanding b) an underemphasis of the data in Figure 3 that shows a decrease in GDF15 after oxaliplatin treatment in TXNIP knockout lines.

      We have addressed these concerns in several ways:

      1. We have carried out knockdown experiments using siRNA for ARRDC4, which we felt, given its regulation by MondoA and ROS, and homology to TXNIP, may also regulate GDF15. This was found to be the case and may explain the data in Figure 3. At the very least it shows that other factors involved in oxidative stress management may have similar impacts – a form of functional redundancy. Lines 553-559 “Finally, given our previous data (Figure S4) we looked to assess the role of ARRDC4 on GDF15 expression. In the absence of oxaliplatin, knocking down ARRDC4 in DLD1 and HCT15 cells drove an increase in GDF15. When challenged with oxaliplatin, both ARRDC4 and TXNIP expression increased and GDF15 decreased. When the ARRDC4 knockdown was challenged TXNIP increased further and GDF15 decreased further (Figure S6G-J). Given the common regulatory pathways and homology between TXNIP and ARRDC4, and their similar functional roles, we suggest these data are evidence of redundancy within this system. “

      We have included some context in the discussion:

      Lines 930-933: “Further support for both TXNIP and ARRDC4’s role in regulating GDF15 after the induction of ROS comes from a pan cancer meta-analysis assessing the impact of metformin (which has been reported to inhibit ROS) on gene expression. Here the top two downregulated genes were TXNIP and ARRDC4 and the top four upregulated genes were DDIT4, CHD2, ERN1 and GDF1572

      We have tempered the text:

      Lines 522-524 “It is important to note however that here we saw clear evidence that TXNIP was not solely responsible for the downregulation of GDF15 post oxaliplatin treatment, with decreased levels seen in knockout lines (Figure 3C-G, S5E).”

      Lines 926-929 “It must be stressed that these data do not place TXNIP as the sole regulator of GDF15, for example ARRDC4 can also be seen to regulate GDF15. We envisage TXNIP as one of a number of ROS-dependent GDF15 regulators, with this redundancy potential evidence of the importance of this regulatory framework.”

      We have carried out additional analysis detailed in the discussion and in Figure S12 which suggests TXNIP impacts MYC function, as reported elsewhere (detailed below). For ease, the key paper can be accessed through this link https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3001778

      Lines 934-956: “The main shortcoming of this paper is the lack of mechanistic understanding linking TXNIP to GDF15. There are 650 transcription factors that have been shown, or are predicted, to bind to GDF15 promoter and/or enhancer regions. By assessing our list of differentially expressed genes (Suppl. Table 1-2) for the presence of these factors we identified 6 GDF15 binding TFs that show significantly decreased expression after oxaliplatin treatment in both cell lines (ATF4, MYC, SREBF1, PHB2, HBP1, KLF9). There was only one, MYC, that was downregulated by oxaliplatin treatment (validated; Figure S12A), and with this downregulation partially being rescued in a matched TXNIP knockout line (Figure S12B). We then observed that c-myc has been shown or is predicted to bind to promoter/enhancer regions of the top five transcriptomic and proteomic differentials in TXNIP knockout lines, including TXNIP itself (apart from C16orf90). Even with c-myc’s promiscuity (binds to 10-20% of all promoters/enhancers) this may be suggestive of a specific relationship. Finally, when looking at the correlations between these 6 TFs and TXNIP and GDF15 in the TCGA COAD dataset, MYC has the greatest and most significant negative correlation to TXNIP (r=-0.4631 p=1.42e-28) and the greatest and most significant positive correlation to GDF15 (r=0.4653 p=7.32e-29). ATF4 and PHB2 are the other TFs in the list, that show the same significant trends (Figure S12C), and therefore may play a role in the TXNIP-independent oxaliplatin-dependent regulation of GDF15. Further exploration of these additional TFs is outside the scope of the current manuscript.

      MYC’s role in bridging from TXNIP to GDF15 is further supported by a recent paper which shows that TXNIP is “a broad repressor of MYC genomic binding” and that “TXNIP loss mimics MYC overexpression”73. Furthermore, the inter-dependent regulatory relationship between MondoA, TXNIP, and MYC has been seen in a variety of models74, whilst the impact of NAC on MYC-dependent pathways has been seen in lymphoma75. These studies lend credence to the idea that MYC is the most likely TXNIP-regulated TF that regulates GDF15 in our systems.”

      It seems equally likely that TXNIP and GDF15 represent independent parallel pathways. Even if TXNIP is a direct regulator of GDF15, it's also clear that other "factors" up or down-regulated by Oxa also contribute to the regulation of GDF15. These are not explored and even though TXNIP is highly regulated genes shown Figure 2 that are not identified or discussed that may also be contributing to GDF15 regulation.

      As mentioned above, the new data suggests that at least one other factor, ARRDC4, can regulate GDF15 (changes upon oxaliplatin treatment) and that MYC is a potential mechanistic bridge between TXNIP and GDF15. Whilst assessing for the transcription factor that may link TXNIP and GDF15 we found an additional 5 TXNIP-independent factors (ATF4, PHB2, SREBF1, HBP1, KLF9) that bind to GDF15 promoter/enhancer regions and are downregulated post-oxaliplatin treatment. When looking at correlations between these factors and GDF15 in the TCGA COAD dataset, ATF4 and PHB2 correlate most closely with GDF15 (when removing MYC) and so we would cautiously suggest that these may be the most pertinent. This data is now included.

      Further, the experiments treating PBMCs with conditioned media contain other cytokines/factors, in addition to GDF15, that likely also contribute the observed effects on the different immune cells understudy. The conditioned media from GDF15 knock out cells are a good experiment, but the media is not rigorously tested to see what other cytokines/factors might have also been depleted.

      The TXNIP knockout media is the same as that analysed by mass spec and the protein array, however as the reviewer states there is no analysis (excluding assessing for the presence or absence of GDF15) on the double knockout supernatant or over-expression supernatant. The text has been corrected as follows:

      Lines 675-679. “In light of other secreted factors being seen to be regulated by TXNIP (Figure 3A-B), we included double knockouts (TXNIP and GDF15 knockout; GTKO) as well as an overexpression system (GDF15a) to test for GDF15 specific effects. However, we do not know the impact of knocking out or overexpressing GDF15 on the broader secretome.”

      Perhaps a GDF15 complementation experiment would help here.

      We felt that the association between GDF15 and Treg induction is reasonably well established in the literature, and so once we saw that the supernatant from our GDF15 overexpression system (+/- CD48 blockade) complemented what has already been demonstrated, we were encouraged. However we needed more – hence the TCGA data and IHC staining.

      Finally, even if completely independent, a TXNIP/GDF15 ratio does seem to have utility in determining chemo-therapeutic response.

      We agree – we feel that conceptually this may be the most interesting part of the project and is an example of what can be done with these tools.

      Other major points: 1. Please label the other highly regulated genes shown in Fig 2A and B. Might they also explain some of the underlying biology. This could be on the current figures or in a supplement, though the former is preferred.

      Many thanks – we have done this.

      Please address why the TXNIP induction is so much less in patient-derived organoids vs. cell line spheroids (Fig S2). By the western blots, TXNIP inductions in the organoids looks quite modest. Further, the text is quite cryptic and implies that the "upregulation" is similar in both organoids and spheroids.

      You are absolutely correct. Many apologies, the wording has changed:

      Lines 320-323 “In both models we observed the upregulation of TXNIP mRNA (Figure S2E-H) and TXNIP protein (Figure S2I-L) after oxaliplatin treatment, with spheroids showing greater responsiveness. This difference is most likely due to culturing conditions or differences in the number and location of cycling cells.”

      We have two possible explanations. Firstly the media in which the organoids are cultured contains a lower glucose concentration than that used for the spheroids. As per some of our new data (Figure S3 – later in the rebuttal), the upregulation of TXNIP after oxaliplatin is glucose dependant, with lower concentrations resulting in less of a differential. Secondly, while restricted to the periphery, the Ki67 signal in DLD1 spheroids is quite pronounced indicating that, within the outer zone, many cells (probably the majority) are in the S/G1/G2 phase of the cell cycle at any given point in time (figure below this text).

      This is not the case for the organoids, where the Ki67 (and pCDK1) signal is quite weak, and only sporadic in the outer layer. So we believe that there are many more rapidly cycling cells in the most drug-exposed layer of spheroids when compared to the comparable region in organoids. As the spheroid cells are likely cycling more rapidly, they would also be expected to be more adversely affected by the drug within the finite drug treatment window. Indeed, these spheroids grow large, and quite quickly. If the organoid cells are cycling more slowly and if, within the cell layer most exposed to drug, these cycling cells are less abundant, then the TXNIP response may well be subdued in organoids when compared with spheroids.

      We have decided to not include the above (full) explanation and figure within the new draft, as we feel it may distract from the central message. However do let ourselves and the editor know if you disagree.

      What was the rationale of performing the MS experiment on control and TXNIP KO DLD1 cells in the absence of oxaliplatin? The other experiments in Fig 3 clearly show that Oxa can repress GDF15 even in the absence of TXNIP, which implicates other pathways. ARRDC4? Or something else? This needs to be addressed.

      We adopted this approach because of the order in which the assays occurred and technical issues surrounding the use of post-oxaliplatin treated supernatant. By the time we moved to the proteomics we had already identified, and validated, GDF15 as our number one candidate (initially from the protein array), in terms of response to oxaliplatin and dependence on TXNIP. This led us to the next stage of the project – to assess the environmental impacts of this factor in vitro before validation in situ. To do this, aware of the issue of contaminated recombinant GDF15, we decided early on to use cell line supernatant. We carried out some pilot studies on immune cells using supernatant from oxaliplatin treated cell lines and we had several technical issues (difficulty in determining the correct controls, immune cell death…). This changed the emphasis to using supernatant from knockout models rather than knockout and treated models. Before we began these assays in earnest we wanted to assess exactly what was enriched in TXNIP knockout supernatant and so we turned to proteomics. When this further validated GDF15, we then generated GDF15 and TXNIP/GDF15 knockouts to further elucidate GDF15’s role specifically.

      With regards the other pathways, as you correctly predicted, ARRDC4 also appears to regulate GDF15 – many thanks for helping with this line of enquiry. Please see earlier in the rebuttal for more details and the data.

      The data in 3J with the MondoA knockdown is not convincing. The knockdown is weak and TXNIP goes down a smidge. Agree that GDF15 goes up

      We agree. We have re-run this and pooled the densitometry data – see new figure below (Panel 3J).

      Minor points 1. Line 79. The "loss" of TXNIP/GDF15 axis is confusing. It's really loss of TXNIP and upregulation of GDF15, right?

      Absolutely - corrected to responsiveness.

      Lines 144-147: “Intriguingly, multiple models including patient-derived tumor organoids demonstrate that the loss of TXNIP and GDF15 responsiveness to oxaliplatin is associated with advanced disease or chemotherapeutic resistance, with transcriptomic or proteomic GDF15/TXNIP ratios showing potential as a prognostic biomarker.”

      Please provide an explanation for the different stages in tables 1 and 2. This will likely not be clear to non-clinicians.

      Many thanks. The following has been added at the bottom of the second table.

      Lines 304-309: “The TNM staging system stands for Tumor, Node, Metastasis. T describes the size of the primary tumor (T1-2; 5cm). N describes the presence of tumor cells in the lymph nodes (N0; no lymph nodes. N1-3 >0). M describes whether there are any observable metastases (M0; no metastases. M1; metastases). The clinical stage system is as follows: I/II; the tumor has remained stable or grown, but hasn’t spread. III/IV; the tumor has spread, either locally (III) or systemically (IV).”

      Line 231 should probably read ...cysteine (NAC), a reactive oxygen species inhibitor,

      Many thanks - corrected

      Line 247, should be RT-qPCR I think.

      Many thanks - corrected

      Lines 343-345. I don't quite understand the wording. Does this mean to say that 675 soluble proteins were not changed between the condition media from both cell populations?

      Yes, exactly this. We have removed as this is superfluous and confusing.

      The data in FigS1 B and C don't seem to reach the standard p value of > 0.05

      Very true – we have rewritten the text to make sure the reader knows there is no significance.

      Lines 269-271. “High levels of both the protein (significantly) and the transcript (not significantly) were seen to be associated with favourable prognosis (Figure 1G,H and S1B,C).”

      **Referee Cross-Commenting**

      cross comment regarding referees 2 and 3 above. I'm am convinced that TXNIP is at least contemporaneously upregulated with GDF15 downregulation. However, the strong implication from the writing is that TXNIP regulates GDF15 directly. I agree with the comment above that exploring mechanisms may be open-ended especially as TXNIP has been implicated in gene regulation by several different mechanism. I'd be satisfied with a more open-minded discussion of potential mechanisms by which TXNIP may repress GDF15 and the possibility of other parallel pathways that likely contribute to GDF15 repression.

      Many thanks, this is a generous and understanding approach. As described above we have carried out extra analysis and have found 6 differentially regulated transcription factors which have been shown to bind GDF15 promoter or enhancer regions with 1 of these, MYC, being significantly affected in the TXNIP knockout cell lines, which in combination with supportive literature suggests a degree of TXNIP dependence. We have also identified ARRDC4 as an additional regulator of GDF15 – again please see above.

      Reviewer #1 (Significance (Required)):

      This is an interesting contribution but the mechanistic connection between GDF15 and TXNIP is relatively weak. That said, even as independent variables they do seem to have utility in predicting therapeutic response.

      Many thanks for the comment – we concur. We have reanalysed our data looking for relevant transcription factors (those that bind GDF15 promoter / enhancer regions) finding MYC as the most likely bridge. Please see above.

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

      The manuscript by Deng et al. investigates a mechanistic link between TXNIP and GDF15 expression and oxaliplatin treatment and acquired resistance. They observe an upregulation in TXNIP expression in the tumors of patients who have previously received chemotherapy. They demonstrate oxaliplatin-driven MondoA transcriptional activity is what underlies the induction of TXNIP. They further demonstrate that TXNIP is a negative regulator of GDF15 expression. Together, oxaliplatin induces MondoA activity and TXNIP expression, resulting in a downregulation of GDF15 expression and consequently decreased Treg differentiation.

      Major Comments

      1. The authors suggest that TXNIP induction and GDF15 downregulation are a common effect of chemotherapies; however, the mechanistic studies were limited to oxaliplatin. The authors should clarify this point through further investigation using other commonly used CRC chemotherapies (5-FU, irinotecan, etc.),or through textual changes. To be clear, I think that the oxaliplatin results could potentially stand on their own but would require additional clarification. For example, regarding the patient samples analyzed in 1D and 4F, which patients received oxaliplatin? Could the analysis of publicly available molecular data be drilled down to just the patients who received oxaliplatin?

      Many thanks – this is an excellent point. Firstly, all the patients in 1D and 4F received oxaliplatin. Secondly, we have included new data looking at the impact of other chemotherapies (FOLRIRI, FU-5 and SN-38) on aspects of the study, ultimately finding that these processes (especially an anti-correlation between GDF15 and TXNIP changes upon chemo treatment) appear to be specific to oxaliplatin. These data have been added (Figure S11) and throughout the emphasis has been switched from chemotherapeutic treatment to oxaliplatin treatment.

      Lines 796-799: “To check if the pre-treatment GDF15/TXNIP ratio could be used for patients treated with FOLFIRI we performed the same analyses finding no significance (S11A-D). This oxaliplatin specificity was then confirmed by western blot analysis in DLD1 and HCT15 cells treated with 5-FU or SN38 (Figure S11E-F).

      Example of change of emphasis from ‘chemotherapy’ to ‘oxaliplatin’ – lines 139-142: “Here, in colorectal adenocarcinoma (CRC) we identify oxaliplatin-induced Thioredoxin Interacting Protein (TXNIP), a MondoA-dependent tumor suppressor gene, as a negative regulator of Growth/Differentiation Factor 15 (GDF15).”

      The data demonstrating the induction of MondoA transcriptional activity and TXNIP expression in response to oxaliplatin treatment is quite convincing. The data regarding ROS induction of TXNIP is interesting, especially in light of other studies arguing that ROS limits MondoA activity (PMID: 25332233). Given this apparent disparity, I think that this study could really be strengthened by also investigating other potential mechanisms of oxaliplatin induction of MondoA. In particular, given many studies arguing for direct nutrient-regulation of MondoA, the authors should address the potential for oxaliplatin regulation of glucose availability and a potential glucose dependence of oxaliplatin-induced TXNIP. 2

      In line with the previous point, since MondoA activity and TXNIP expression are sensitive to glucose levels, the authors should investigate oxaliplatin-regulation of TXNIP under physiological glucose levels. No need to replicate everything, just key experiments.

      We feel these are excellent point and really help the piece – many thanks. We have carried out assays around these points suggested and have included the findings in the new draft – see below.

      Lines 332-339: “As such, we went back to first principles and assessed the impact of different concentrations of glucose on TXNIP induction +/- oxaliplatin treatment, finding a concentration dependent effect (Figure S3A). Intriguingly, high glucose alone was able to induce increased TXNIP expression. We then assessed if oxaliplatin treatment drove an increase in glucose uptake, with this seen at concentrations >10mM (Figure S3B). Next, to investigate the impact of glucose metabolism, and consequent ROS generation, on TXNIP induction we treated cells with Antimycin A, an inhibitor of oxidative phosphorylation, finding a complete block in oxaliplatin-induced TXNIP (Figure S3C).”

      The authors did a good job of linking TXNIP and GDF15 in untreated conditions; however, the data arguing for oxaliplatin regulation of GDF15 through TXNIP is less clear. For example, in 3B-H, oxaliplatin treatment reduces GDF15 approximately to the same extent in the NTC and TKO cells, potentially in line with a mechanism of downregulation that doesn't involve TXNIP.

      A very salient point and completely in line with the other reviewers. We have carried out a few additional analyses mentioned previously in this letter. The most pertinent for this specific point are the experiments around ARRDC4, where we found evidence to suggest that, like TXNIP, it regulates GDF15.

      Minor Comments

      1. The presentation of data in Figure 5 is confusing. A-B include raw cell numbers, whereas C-F show "normalized proliferation." What does this mean? And how was the normalization done?

      Apologies for this. Legend test has been corrected to “Normalised proliferation (normalised to MFI from control: i.e. cells treated with supernatant from NTC cells) on gated CD3+CD8+ or CD3+CD4+ cells is shown. n=6. (G-H) Normalised IFNg concentrations (normalised to MFI from control: i.e. cells treated with supernatant from NTC cells) in the supernatant of cells from C-F.” (lines 727-729).

      **Referee Cross-Commenting**

      cross-comment regarding reviewer #1

      I agree with the referee that the link between TXNIP and GDF15 is weak, though as I mentioned before, this is particularly true in the context of oxaliplatin-regulation of TXNIP. I agree that given all the presented data, it is likely that oxaliplatin-regulation of TXNIP and GDF15 are independent. In my opinion, the referee brought up all valid concerns, but this is by far the biggest concern that I share.

      We agree that this is the weakest aspect of the paper, however our new analyses plus supportive literature, suggests that the relationship between TXNIP and GDF15 may be mediated by MYC (please see above)

      cross-comment regarding reviewer #3

      The major concern that this referee addresses is whether another transcription factor supersedes the proposed MondoA/TXNIP induction in regulating GDF15 expression in later stage CRC. In my opinion, this another other concerns of the referee are all valid, but still I remain unconvinced that TXNIP induction underlies the oxaliplatin-regulation of GDF15. I think fleshing out that aspect of the study would potentially help the authors tease apart how this potential MondoA-TXNIP-GDF15 axis is dysregulated later in CRC progression.

      This is a great discussion. Interestingly enough, c-myc is seen at higher levels in late stage CRC (Hu X, Fatima S, Chen M, Huang T, Chen YW, Gong R, Wong HLX, Yu R, Song L, Kwan HY, Bian Z. Dihydroartemisinin is potential therapeutics for treating late-stage CRC by targeting the elevated c-Myc level. Cell Death Dis. 2021 Nov 5;12(11):1053. Doi: 10.1038/s41419-021-04247-w. PMID: 34741022; PMCID: PMC8571272.), is seen as an important factor in resistance, and as this review argues, is driven by stress (Saeed H, Leibowitz BJ, Zhang L, Yu J. Targeting Myc-driven stress addiction in colorectal cancer. Drug Resist Updat. 2023 Jul;69:100963. Doi: 10.1016/j.drup.2023.100963. Epub 2023 Apr 20. PMID: 37119690; PMCID: PMC10330748.). So it is very plausible that the partial TXNIP-mediated regulation of myc in early / sensitive CRCs that we may be observing, and has been reported recently (TXNIP loss expands Myc-dependent transcriptional programs by increasing Myc genomic binding Lim TY, Wilde BR, Thomas ML, Murphy KE, Vahrenkamp JM, et al. (2023) TXNIP loss expands Myc-dependent transcriptional programs by increasing Myc genomic binding. PLOS Biology 21(3): e3001778. https://doi.org/10.1371/journal.pbio.3001778) is lost in late stage / resistant CRCs. If this is the case, in effect what we would have observed is the loss of a stress-associated method (TXNIP) of controlling c-myc activity. What makes our collective lives difficult is that, as reported “this expansion of Myc-dependent transcription following TXNIP loss occurs without an apparent increase in Myc’s intrinsic capacity to activate transcription and without increasing Myc levels.” (TXNIP loss expands Myc-dependent transcriptional programs by increasing Myc genomic binding Lim TY, Wilde BR, Thomas ML, Murphy KE, Vahrenkamp JM, et al. (2023) TXNIP loss expands Myc-dependent transcriptional programs by increasing Myc genomic binding. PLOS Biology 21(3): e3001778. https://doi.org/10.1371/journal.pbio.3001778)

      Reviewer #2 (Significance (Required)):

      Generally speaking the experiments are well controlled and the findings are significant and novel. Though the link between MondoA activity and ROS could be strengthened, and the data could be validated under more physiological settings. Further, the authors should clarify their interpretations so as to not overstate the findings.

      Many thanks for the comments. We have taken onboard the need for more physiological settings and have included varying levels of glucose to reflect concentrations in different environments. We have repeated the siMondoA work in 3J strengthening the conclusions wrt its impact on TXNIP and GDF15 expression (see above).

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

      In this well-written manuscript, the authors show that chemotherapy increases a MondoA-dependent oxidative stress-associated protein, TXNIP, in chemotherapy-responsive colorectal cancer cells. They show that TXNIP negatively regulates GDF-15 expression. GDF-15, in turn, correlates with the presence of T cells (Treg), and inhibits CD4 and CD8 T cell stimulation. In advanced disease and chemo-resistant cancers, upregulation of TXNIP and downregulation of GDF-15 appear to get lost. Based on a somewhat smallish data set, the authors suggest that the pre-treatment GDF-15/TXNIP ratio can predict responses to oxaliplatin treatment. This is a very interesting, novel finding. In general, the quality of the experiments and the data are high and the conclusions appear sound. Still, there are a number of aspects that should still be improved:

      The observed loss of the ROS - MondoA - TXNIP - GDF15 axis in chemoresistant and/or metastatic tumors implies that another transcription factor or pathway becomes dominant upon tumor progression. As this switch would be key to better understanding the mechanism underlying the prognostic role of the TXNIP/GDF15 ratio, the authors should at least do data mining followed by ChEA or Encode (or other) analysis to identify transcription factors or pathways that become activated in late-stage/metastatic CRC cells. There is a high likelihood that a transcription factor or pathway involved in GDF-15 upregulation in cancer (e.g. p53, HIF1alpha, Nrf2, NF-kB, MITF, C/EBPß, BRAF, PI3K/AKT, MAPK p38, EGR1) supersedes the inhibitory effect of the MondoA-TXNIP axis. As it stands, the proposed loss of function of the ROS - MondoA - TXNIP - GDF-15 axis is far less convincing than almost all other aspects of the study.

      An extremely fair point. We adopted a similar approach to that suggested – as mentioned above, we looked at TFs that bind to GDF15 promoter/enhancer regions and then looked at the presence of these in our transcriptomic data – specifically any evidence of change post oxaliplatin treatment. We found 6 such TFs that were decreased post-oxaliplatin treatment. We then looked for any evidence of TXNIP dependence in these TFs by comparing post-oxaliplatin treatment across NTC and TXNIP knockout lines, when we did this we found only one GDF15 promoter/enhancer binding TF was significantly changed: MYC. We then looked at the relationship between MYC,TXNIP, and GDF15 against the other 5 ‘control’ TFs in the TCGA COAD dataset, we found that MYC showed the strongest correlations, in the ‘correct’ directions. This finding was further backed up in the literature where a TXNIP knockout in a breast cancer model drove c-myc-dependent transcription, whilst c-myc has been observed to increase in later stage CRC patients, is associated with cellular stress and resistance. The collective evidence therefore suggests that MYC is the factor that is initially at least partially regulated by TXNIP, before this regulation is lost in advanced / resistant disease. Continuing on this line, it is likely that the predictive GDF15/TXNIP ratio is at least in part, a measure of c-myc responsiveness to oxaliplatin. All the while we must bear in mind TXNIP-independent oxaliplatin-dependent regulation of GDF15, most likely ARRDC4, as described earlier in this document.

      Using pathway analysis software to compare our transcriptomic data from cell lines treated with/without oxaliplatin, the most likely pathways upstream of MYC/c-myc that are negatively affected by chemotherapy are BAG2, Endothelin-1, telomerase, ErbB2-ErbB3 and Wnt/B-catenin. When looking at the comparison of UTC and resistant lines’ transcripts there is only one key component of these pathways which is upregulated in both lines - ERBB3 – which has already been shown to be important in CRC metastasis and resistance (Desai O, Wang R. HER3- A key survival pathway and an emerging therapeutic target in metastatic colorectal cancer and pancreatic ductal adenocarcinoma. Oncotarget. 2023 May 10;14:439-443. doi: 10.18632/oncotarget.28421. PMID: 37163206; PMCID: PMC10171365.). It is highly speculative, but our data suggests the most likely pathway to supersede TXNIP in its (partial) regulation of MYC is the ErbB2-ErbB3 pathway.

      My further criticisms are mostly more technical:

      Figure 2 I-L: What was the extent of MondoA downregulation achieved by siRNA treatment? Could the effects also be seen with the small molecule mondoA inhibitor SBI-477 (or a related substance)?

      This experiment has been repeated. The pooled densiometric data is also now given (please see above).

      How do you explain the different GDF-15 levels between untreated non-target control cells (NTC) and TXNIP knock-down cells (TKO) in Figures 3C-F?

      The only way to interpret this is that there is a TXNIP-independent pathway regulating GDF15 expression after oxaliplatin treatment, as described this is most likely to be ARRDC4 - the text has been updated to:

      Lines 522-524: “It is important to note, however, that we saw clear evidence that TXNIP was not solely responsible for the downregulation of GDF15 post oxaliplatin treatment (Figure 3C-G, S6E).”

      In figures 3 E-G the dots for the individual measurements should be indicated. This would be more informative than just the bar graphs.

      Completed.

      Figure 4C,D and Table 3: Data on the role of GDF-15 in CRC are largely valedictory of previous work (e.g. Brown et al. Clin Cancer Res 2003, 9(7):2642-2650, Wallin et al., Br J Cancer. 2011 May, 10;104(10):1619-27). Therefore, the previous studies should be cited.

      Apologies for the oversight and many thanks – this is an excellent addition.

      Figure 5C-F: Please indicate in the figure legend how proliferation was assessed.

      Many thanks. This was noticed by another reviewer also. We have changed the text to include how the data was normalised: “(C-F) Labelled PBMCs were stimulated with anti-CD3 and anti-CD28 for 4 days in the presence of fresh supernatant from indicated cell lines, before being stained with anti-CD3 and anti-CD8 (C-D) or anti-CD4 (E-F) antibodies and measured by flow cytometry. Normalised proliferation (normalised to MFI from control: i.e. cells treated with supernatant from NTC cells) on gated CD3+CD8+ or CD3+CD4+ cells is shown. n=6. (G-H) Normalised IFNg concentrations (normalised to MFI from control: i.e. cells treated with supernatant from NTC cells) in the supernatant of cells from C-F.” (lines 724-730)

      Figure S8E-G: Please indicate the analysed parameters in the graphs. In Figure S8G, the legend just indicates that "aggression of tumour" is dichotomized and plotted. This clearly requires a better definition.

      Many thanks, this has been changed as per the below.

      Lines 862-868: “(E-G) Receiver operating characteristic (ROC) curves showing area under the curve and p values for the use of GDF15/TXNIP ratio in predicting origin of cell line (E; primary; DLD1, HCT15, HT29, SW48 [n=4] or secondary; DiFi, LIM1215 [n=2]), sensitivity to oxaliplatin (F; parental DLD1 (plus biological repeat), HCT15 [n=3] or resistant DLD1 (plus biological repeat), HCT15 [n=3]), aggression of tumor (G; non-aggressive; The authors propose a novel ROS - MondoA - TXNIP - GDF15 - Treg axis, where MondoA activation, TXNIP up- and GDF-15 downregulation enhance tumor immunogenicity. While this axis has been analyzed in some detail, GDF-15 is not only linked to induction of regulatory T cells. There has been a report showing that GDF-15/MIC-1 expression in colorectal cancer correlates with the absence of immune cell infiltration (Brown et al. Clin Cancer Res 2003, 9(7):2642-2650). The link between GDF-15 and immune cell exclusion has also been confirmed in other conditions, including different cancers (Kempf et al. Nat Med 2011, 17(5):581-588, Roth P et al. Clin Cancer Res 2010, 16(15):3851-3859, Haake et al. Nat Commun 2023, 14(1):4253). A key mechanism is the GDF-15 mediated inhibition of LFA-1 activation on immune cells. As the authors argue that the described pathways turns cold tumors hot in response to oxaliplatin-based chemotherapy, this GDF-15 dependent immune cell exclusion mechanism might be at least as relevant than induction of Treg. Likewise, inhibition of dendritic cell maturation by GDF-15 (Zhou et al. PLoS One 2013, 8(11):e78618) could explain why GDF-15high tumors are immunologically cold. Reviewed in 3

      The authors propose that the pathways discovered by them contributed to the "heating up" of the tumor microenvironment after oxaliplatin-based chemotherapy. The authors should thus look in their data sets for the presence of cytotoxic T cells and their possible correlation with TXNIP and GDF-15 levels.

      This is a wonderful explanation – many thanks. We have taken the opportunity to assess the impact of GDF15 expression on a variety of T cell markers (Figure S9). In this data a negative association between GDF15 and CD8 CTLs can clearly be seen, as predicted by the reviewer.

      Lines 712-717: “To assess if the GDF15-dependent presence of Tregs may be associated with a decrease in activated cytotoxic CD8 T cells, we interrogated the TCGA COAD dataset. We found that low GDF15 tumors carried significantly higher levels of CD8, CD69, IL2RA, CD28, PRF1, GZMA, GZMK, TBX21, EOMES and IRF4 (Figure S9); transcripts indicative of activated cytotoxic CD8 T cells. High GDF15 tumors were enrichment for FOXP3 and, interestingly, RORC (Figure S9). These data support the hypothesis that GDF15 induces Foxp3+ve Tregs which inhibit CD8 T cell proliferation and activation in the TME.”

      The paragraph on GDF-15 receptors needs to be corrected: The purported role of a type 2 transforming growth factor (TGF)-beta receptor in GDF-15 signalling had been due to a frequent contamination of recombinant GDF-15 with TGF-beta (Olsen et al. PLoS One 2017, 12(11):e0187349). There have been a number of screenings for GDF-15 receptors that have all failed to show an interaction between GDF-15 and TGF-beta receptors. Instead, only GFRAL was found in these large-scale screenings (Emmerson et al. Nat Med 2017, 23(10):1215-1219, Hsu et al. Nature 2017, 550(7675):255-259, Mullican et al. Nat Med 2017, 23(10):1150-1157, Yang et al. Nat Med 2017, 23(10):1158-1166). The one subsequent report that shows a link between GDF-15, engagement of CD48 on T cells and induction of a regulatory phenotype (Wang et al. J Immunother Cancer 2021, 9(9)) still awaits independent validation. Considering that CD48 lacks an intracellular signaling domain that would be critical for a classical receptor function, I recommend to be more cautious regarding the role of CD48 as GDF-15 receptor. Given the mechanism outlined by Wang et al. the word interaction partner might be more apt. Moreover, an anti-GDF-15 antibody would be a good control for the experiments involving an anti-CD48 antibody in Figure 5.

      Thank you so much for this concise and highly informative paragraph. We have changed the text to read:

      202-204: “As a soluble protein, GDF15 exerts its effects by binding to its cognate receptor, GDNF-family receptor a-like (GFRAL)44,45,46,47 or interaction partner, CD48 receptor (SLAMF2)43, with the latter still requiring additional verification.”

      We would have ideally included an anti-GDF15 antibody in the CD48 assay at the time but didn’t have the foresight. We have included the additional text to temper any conclusions.

      Lines 701-711: “Furthermore, when stimulating naïve CD4 T cells in the presence of GDF15 enriched supernatant we were able to both differentiate these cells into functional Tregs and also block the generation of this functionality using an anti-CD48 antibody (Figure 5M-N). However, it must be stressed that the binding and functional impacts of GDF15’s interaction with CD48 still require further verification.”

      Cell surface externalization of annexin A1 has been described as a failsafe mechanism to prevent inflammatory responses during secondary necrosis (PMID: 20007579). Thus, I am surprised that the authors list annexin A1 among the immune-stimulatory molecules exposed or released in response to chemotherapy-induced cell death (line 103). Please clarify!

      We agree – it shouldn’t be there!! Removed. Many thanks.

      **Referee Cross-Commenting**

      Regarding the cross-comment by referee 2: In my opinion, the data shown in Figure 3C-H clearly demonstrates that TXNIP can repress GDF-15 expression. I agree that there will likely be further regulators. The GDF-15 promoter is constantly regulated by a multitude of factors (which mostly induce transcription). As downregulation of GDF-15 in response to oxaliplatin is the opposite of the frequently described induction of GDF-15 upon chemotherapy, net effects may always be "smudged" by contributions from different pathways (e.g. by cell stress due to siRNA transfection). Therefore, I believe that the data are as good as it will get. Accordingly, I would not force the authors to further amplify the observed effect.

      Many thanks for your understanding – yes, GDF15 has >650 TFs that bind its promoter/enhancer regions – a number we found rather daunting. Happily your comments and those of the other reviewers inspired us to dig and we now have data that is supportive of MYC’s and ARRDC4’s involvement – detailed throughout this reply.

      cross comment regarding referee #1: I share the general assessment of the referee and recognize the very detailed mechanistic analysis. To further support the moderate effects of the MondoA knockdown, a small molecule inhibitor like SBI-477 might be useful. (I had already suggested using this inhibitor to support these data.)

      Many thanks for the suggestion. We opted to increase the number of siRNA repeats instead – with the data included in Figure 3J (above).

      Still, my view on the potential relevance of oxaliplatin-induced, TXNIP-independent downregulation of GDF-15 differs from that of referee 1. In the clinics, platinum-based chemotherapy is one of the strongest inducers of GDF-15 (compare Breen et al. GDF-15 Neutralization Alleviates Platinum-Based Chemotherapy-Induced Emesis, Anorexia, and Weight Loss in Mice and Nonhuman Primates. Cell Metabolism 32(6), P938-950, 2020.DOI:https://doi.org/10.1016/j.cmet.2020.10.023). I was thus surprised that the authors found a pathway, which leads to an outcome that an exactly opposite effect.

      This is fascinating that oxaliplatin drives this increase in GDF15 – we were unaware of this paper. Looking at figure 2(H-K), GDF15 is being produced from multiple non-diseased tissues after systemic chemotherapy – even at day 19 post-treatment – this suggests that wrt this study, systemic GDF15 could not be used as a readout of success or otherwise – which is extremely helpful! Thank you.

      Thus far, the only obvious reason for reduced GDF-15 secretion upon treatment with cytotoxic drugs was a reduction in tumor cell number due to cytotoxicity.

      Please do not discount this. This study was focused on the cells which survived oxaliplatin treatment – the cells which did not were discarded. Our view, given your input, would be a complex picture where in early stages systemic GDF15 goes up, due to off-target effects, but locally levels drop owing to cell death and this, and other, stress-related pathways in the remaining tumor cells.

      Still, the authors managed to convince me that the described pathway (ROS - MondoA - TXNIP - GDF-15) exists. (Here, I still largely concur with referee 1.) Moreover, as we have identified some factors required for GDF-15 biosynthesis that could easily interact with TXNIP, I find the proposed mechanism plausible.

      Extremely encouraging for us to hear!

      Nevertheless, as a downregulation of GDF-15 in response to chemotherapy is hardly ever observed in late-stage cancers, I believe that the observed switch in pathway activation between early- and late-stage cancers might be highly relevant - in particular, as there is so much evidence for platinum-based induction of GDF-15 in late-stage cancer patients. Emphasizing the divergent clinical observations (e.g. by Breen et al.) could thus help to put the finding into perspective.

      Very much agree. We did see this phenomenon in LIM1215 cells (Figure 6B) and the resistant lines we generated continually produced higher levels.

      Analysing TXNIP-independent mechanisms involved in the oxaliplatin-dependent repression of GDF-15, as suggested by referee #1, will require enormous efforts and resources, and may still turn out to be fruitless. Personally, I would thus be content if the authors just mentioned possible contributions from other pathways upon cancer progression. To me, the described pathway seems to be limited to early-stage cancers, and the actual finding that GDF-15 is downregulated is an interesting observation, irrespective of further involved pathways.

      Many thanks – this is extremely fair. Happily we have managed to make some tentative steps forward in highlighting the potential role of MYC, and the suggestion of redundancy wrt ARRDC4, but as you say, much more work needs to be done to fully understand these processes.

      cross comment regarding referee #2: I fully agree with the referee that activation of the pathway by further chemotherapeutic drugs could be a valuable addition. As Guido Kroemer´s lab has described oxaliplatin to induce a more immunogenic cell death compared to other platinum-based chemotherapies, even a rather limited comparison between oxaliplatin and cisplatin could be very interesting.

      Absolutely agree – extra data on this has been included in Figure S11, which is included earlier in this letter. We also uncovered a meta-analysis using metformin, which has been seen to inhibit ROS, where TXNIP and ARRDC4 are the top two downregulated transcripts whilst GDF15 appears in the top four upregulated. This may suggest that chemotherapeutic immunogenicity, at least through the presence or absence of GDF15, may in part be driven by ROS.

      Lines 930-933: “Further support for both TXNIP and ARRDC4’s role in regulating GDF15 after the induction of ROS comes from a pan cancer meta-analysis assessing the impact of metformin (which has been reported to inhibit ROS) on gene expression. Here the top two downregulated genes were TXNIP and ARRDC4 and the top four upregulated genes were DDIT4, CHD2, ERN1 and GDF1572 “

      Reviewer #3 (Significance (Required)):

      In general, this is a very interesting manuscript describing a cascade of events that may contribute to successful chemotherapy (which likely requires induction of an immune response against dying tumor cells.) The observation that this pathway is only active in early/non-metastatic cancer cells is striking. Unfortunately, the authors cannot explain inactivation of this pathway in later stage/ metastatic/ highly aggressive cancers. Understanding this switch could easily be the most important finding triggered by this report. Therefore, I highly recommend to make some effort in this direction. Strikingly, the authors find that disruption of TXNIP-mediated GDF-15 downregulation is strongly associated with worse prognosis. They also suggest that this ratio could indicate whether a patient will respond to oxaliplatin-based chemotherapy.

      This is again very fair – we have posited a potential mechanism for the loss of this switch elsewhere in this reply– one which involves a change in TXNIP-mediated MYC regulation and/or increased HER2-HER3 signalling – but although reasonable for a rebuttal (and publication in that context) we do not feel we have the evidence to include this within the full manuscript.

      Altogether, the findings described in manuscript are very novel and may have prognostic (or, in case of the presumed loss of the MondoA - TXNIP - GDF-15 pathway) therapeutic implications. Thus, the manuscript certainly fills various gaps and should be of major interest for cell biologists working on immunogenic cell death, or colorectal cancer, or MondoA, TXNIP or GDF-15. Still, due to its translational implications, it would also be worthwhile reading for a large number of researchers in the oncology field.

      We are very grateful for your kind comments.

      1 Sinclair, L. V., Barthelemy, C. & Cantrell, D. A. Single Cell Glucose Uptake Assays: A Cautionary Tale. Immunometabolism 2, e200029, doi:10.20900/immunometab20200029 (2020).

      2 Yu, F. X., Chai, T. F., He, H., Hagen, T. & Luo, Y. Thioredoxin-interacting protein (Txnip) gene expression: sensing oxidative phosphorylation status and glycolytic rate. J Biol Chem 285, 25822-25830, doi:10.1074/jbc.M110.108290 (2010).

      3 Wischhusen, J., Melero, I. & Fridman, W. H. Growth/Differentiation Factor-15 (GDF-15): From Biomarker to Novel Targetable Immune Checkpoint. Front Immunol 11, 951, doi:10.3389/fimmu.2020.00951 (2020).

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      Referee #3

      Evidence, reproducibility and clarity

      In this well-written manuscript, the authors show that chemotherapy increases a MondoA-dependent oxidative stress-associated protein, TXNIP, in chemotherapy-responsive colorectal cancer cells. They show that TXNIP negatively regulates GDF-15 expression. GDF-15, in turn, correlates with the presence of T cells (Treg), and inhibits CD4 and CD8 T cell stimulation. In advanced disease and chemo-resistant cancers, upregulation of TXNIP and downregulation of GDF-15 appear to get lost. Based on a somewhat smallish data set, the authors suggest that the pre-treatment GDF-15/TXNIP ratio can predict responses to oxaliplatin treatment. This is a very interesting, novel finding. In general, the quality of the experiments and the data are high and the conclusions appear sound. Still, there are a number of aspects that should still be improved:

      The observed loss of the ROS - MondoA - TXNIP - GDF15 axis in chemoresistant and/or metastatic tumors implies that another transcription factor or pathway becomes dominant upon tumor progression. As this switch would be key to better understanding the mechanism underlying the prognostic role of the TXNIP/GDF15 ratio, the authors should at least do data mining followed by ChEA or Encode (or other) analysis to identify transcription factors or pathways that become activated in late-stage/metastatic CRC cells. There is a high likelihood that a transcription factor or pathway involved in GDF-15 upregulation in cancer (e.g. p53, HIF1alpha, Nrf2, NF-kB, MITF, C/EBPß, BRAF, PI3K/AKT, MAPK p38, EGR1) supersedes the inhibitory effect of the MondoA-TXNIP axis. As it stands, the proposed loss of function of the ROS - MondoA - TXNIP - GDF-15 axis is far less convincing than almost all other aspects of the study.

      My further criticisms are mostly more technical:

      Figure 2 I-L: What was the extent of MondoA downregulation achieved by siRNA treatment? Could the effects also be seen with the small molecule mondoA inhibitor SBI-477 (or a related substance)?

      How do you explain the different GDF-15 levels between untreated non-target control cells (NTC) and TXNIP knock-down cells (TKO) in Figures 3C-F?

      In figures 3 E-G the dots for the individual measurements should be indicated. This would be more informative than just the bar graphs.

      Figure 4C,D and Table 3: Data on the role of GDF-15 in CRC are largely valedictory of previous work (e.g. Brown et al. Clin Cancer Res 2003, 9(7):2642-2650, Wallin et al., Br J Cancer. 2011 May, 10;104(10):1619-27). Therefore, the previous studies should be cited.

      Figure 5C-F: Please indicate in the figure legend how proliferation was assessed.

      Figure S8E-G: Please indicate the analysed parameters in the graphs. In Figure S8G, the legend just indicates that "aggression of tumour" is dichotomized and plotted. This clearly requires a better definition.

      The authors propose a novel ROS - MondoA - TXNIP - GDF15 - Treg axis, where MondoA activation, TXNIP up- and GDF-15 downregulation enhance tumor immunogenicity. While this axis has been analyzed in some detail, GDF-15 is not only linked to induction of regulatory T cells. There has been a report showing that GDF-15/MIC-1 expression in colorectal cancer correlates with the absence of immune cell infiltration (Brown et al. Clin Cancer Res 2003, 9(7):2642-2650). The link between GDF-15 and immune cell exclusion has also been confirmed in other conditions, including different cancers (Kempf et al. Nat Med 2011, 17(5):581-588, Roth P et al. Clin Cancer Res 2010, 16(15):3851-3859, Haake et al. Nat Commun 2023, 14(1):4253). A key mechanism is the GDF-15 mediated inhibition of LFA-1 activation on immune cells. As the authors argue that the described pathways turns cold tumors hot in response to oxaliplatin-based chemotherapy, this GDF-15 dependent immune cell exclusion mechanism might be at least as relevant than induction of Treg. Likewise, inhibition of dendritic cell maturation by GDF-15 (Zhou et al. PLoS One 2013, 8(11):e78618) could explain why GDF-15high tumors are immunologically cold.

      The authors propose that the pathways discovered by them contributed to the "heating up" of the tumor microenvironment after oxalilatin-based chemotherapy. The authors should thus look in their data sets for the presence of cytotoxic T cells and their possible correlation with TXNIP and GDF-15 levels.

      The paragraph on GDF-15 receptors needs to be corrected: The purported role of a type 2 transforming growth factor (TGF)-beta receptor in GDF-15 signalling had been due to a frequent contamination of recombinant GDF-15 with TGF-beta (Olsen et al. PLoS One 2017, 12(11):e0187349). There have been a number of screenings for GDF-15 receptors that have all failed to show an interaction between GDF-15 and TGF-beta receptors. Instead, only GFRAL was found in these large-scale screenings (Emmerson et al. Nat Med 2017, 23(10):1215-1219, Hsu et al. Nature 2017, 550(7675):255-259, Mullican et al. Nat Med 2017, 23(10):1150-1157, Yang et al. Nat Med 2017, 23(10):1158-1166). The one subsequent report that shows a link between GDF-15, engagement of CD48 on T cells and induction of a regulatory phenotype (Wang et al. J Immunother Cancer 2021, 9(9)) still awaits independent validation. Considering that CD48 lacks an intracellular signaling domain that would be critical for a classical receptor function, I recommend to be more cautious regarding the role of CD48 as GDF-15 receptor. Given the mechanism outlined by Wang et al. the word interaction partner might be more apt. Moreover, an anti-GDF-15 antibody would be a good control for the experiments involving an anti-CD48 antibody in Figure 5.

      Cell surface externalization of annexin A1 has been described as a failsafe mechanism to prevent inflammatory responses during secondary necrosis (PMID: 20007579). Thus, I am surprised that the authors list annexin A1 among the immune-stimulatory molecules exposed or released in response to chemotherapy-induced cell death (line 103). Please clarify!

      Referee Cross-Commenting

      Regarding the cross-comment by referee 2: In my opinion, the data shown in Figure 3C-H clearly demonstrates that TXNIP can repress GDF-15 expression. I agree that there will likely be further regulators. The GDF-15 promoter is constantly regulated by a multitude of factors (which mostly induce transcription). As downregulation of GDF-15 in response to oxaliplatin is the opposite of the frequently described induction of GDF-15 upon chemotherapy, net effects may always be "smudged" by contributions from different pathways (e.g. by cell stress due to siRNA transfection). Therefore, I believe that the data are as good as it will get. Accordingly, I would not force the authors to further amplify the observed effect.

      cross comment regarding referee #1: I share the general assessment of the referee and recognize the very detailed mechanistic analysis. To further support the moderate effects of the MondoA knockdown, a small molecule inhibitor like SBI-477 might be useful. (I had already suggested using this inhibitor to support these data.) Still, my view on the potential relevance of oxaliplatin-induced, TXNIP-independent downregulation of GDF-15 differs from that of referee 1. In the clinics, platinum-based chemotherapy is one of the strongest inducers of GDF-15 (compare Breen et al. GDF-15 Neutralization Alleviates Platinum-Based Chemotherapy-Induced Emesis, Anorexia, and Weight Loss in Mice and Nonhuman Primates. Cell Metabolism 32(6), P938-950, 2020.DOI:https://doi.org/10.1016/j.cmet.2020.10.023). I was thus surprised that the authors found a pathway, which leads to an outcome that an exactly opposite effect. Thus far, the only obvious reason for reduced GDF-15 secretion upon treatment with cytotoxic drugs was a reduction in tumor cell number due to cytotoxicity. Still, the authors managed to convince me that the described pathway (ROS - MondoA - TXNIP - GDF-15) exists. (Here, I still largely concur with referee 1.) Moreover, as we have identified some factors required for GDF-15 biosynthesis that could easily interact with TXNIP, I find the proposed mechanism plausible. Nevertheless, as a downregulation of GDF-15 in response to chemotherapy is hardly ever observed in late-stage cancers, I believe that the observed switch in pathway activation between early- and late-stage cancers might be highly relevant - in particular, as there is so much evidence for platinum-based induction of GDF-15 in late-stage cancer patients. Emphasizing the divergent clinical observations (e.g. by Breen et al.) could thus help to put the finding into perspective. Analysing TXNIP-independent mechanisms involved in the oxaliplatin-dependent repression of GDF-15, as suggested by referee #1, will require enormous efforts and resources, and may still turn out to be fruitless. Personally, I would thus be content if the authors just mentioned possible contributions from other pathways upon cancer progression. To me, the described pathway seems to be limited to early-stage cancers, and the actual finding that GDF-15 is downregulated is an interesting observation, irrespective of further involved pathways.

      cross comment regarding referee #2: I fully agree with the referee that activation of the pathway by further chemotherapeutic drugs could be a valuable addition. As Guido Kroemer´s lab has described oxaliplatin to induce a more immunogenic cell death compared to other platinum-based chemotherapies, even a rather limited comparison between oxaliplatin and cisplatin could be very interesting.

      Significance

      In general, this is a very interesting manuscript describing a cascade of events that may contribute to successful chemotherapy (which likely requires induction of an immune response against dying tumor cells.) The observation that this pathway is only active in early/non-metastatic cancer cells is striking. Unfortunately, the authors cannot explain inactivation of this pathway in later stage/ metastatic/ highly aggressive cancers. Understanding this switch could easily be the most important finding triggered by this report. Therefore, I highly recommend to make some effort in this direction. Strikingly, the authors find that disruption of TXNIP-mediated GDF-15 downregulation is strongly associated with worse prognosis. They also suggest that this ratio could indicate whether a patient will respond to oxaliplatin-based chemotherapy.

      Altogether, the findings described in manuscript are very novel and may have prognostic (or, in case of the presumed loss of the MondoA - TXNIP - GDF-15 pathway) therapeutic implications. Thus, the manuscript certainly fills various gaps and should be of major interest for cell biologists working on immunogenic cell death, or colorectal cancer, or MondoA, TXNIP or GDF-15. Still, due to its translational implications, it would also be worthwhile reading for a large number of researchers in the oncology field.

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      Referee #2

      Evidence, reproducibility and clarity

      The manuscript by Deng et al. investigates a mechanistic link between TXNIP and GDF15 expression and oxaliplatin treatment and acquired resistance. They observe an upregulation in TXNIP expression in the tumors of patients who have previously received chemotherapy. They demonstrate oxaliplatin-driven MondoA transcriptional activity is what underlies the induction of TXNIP. They further demonstrate that TXNIP is a negative regulator of GDF15 expression. Together, oxaliplatin induces MondoA activity and TXNIP expression, resulting in a downregulation of GDF15 expression and consequently decreased Treg differentiation.

      Major Comments

      1. The authors suggest that TXNIP induction and GDF15 downregulation are a common effect of chemotherapies; however, the mechanistic studies were limited to oxaliplatin. The authors should clarify this point through further investigation using other commonly used CRC chemotherapies (5-FU, irinotecan, etc.), or through textual changes. To be clear, I think that the oxaliplatin results could potentially stand on their own but would require additional clarification. For example, regarding the patient samples analyzed in 1D and 4F, which patients received oxaliplatin? Could the analysis of publicly available molecular data be drilled down to just the patients who received oxaliplatin?
      2. The data demonstrating the induction of MondoA transcriptional activity and TXNIP expression in response to oxaliplatin treatment is quite convincing. The data regarding ROS induction of TXNIP is interesting, especially in light of other studies arguing that ROS limits MondoA activity (PMID: 25332233). Given this apparent disparity, I think that this study could really be strengthened by also investigating other potential mechanisms of oxaliplatin induction of MondoA. In particular, given many studies arguing for direct nutrient-regulation of MondoA, the authors should address the potential for oxaliplatin regulation of glucose availability and a potential glucose dependence of oxaliplatin-induced TXNIP.
      3. In line with the previous point, since MondoA activity and TXNIP expression are sensitive to glucose levels, the authors should investigate oxaliplatin-regulation of TXNIP under physiological glucose levels. No need to replicate everything, just key experiments.
      4. The authors did a good job of linking TXNIP and GDF15 in untreated conditions; however, the data arguing for oxaliplatin regulation of GDF15 through TXNIP is less clear. For example, in 3B-H, oxaliplatin treatment reduces GDF15 approximately to the same extent in the NTC and TKO cells, potentially in line with a mechanism of downregulation that doesn't involve TXNIP.

      Minor Comments

      1. The presentation of data in Figure 5 is confusing. A-B include raw cell numbers, whereas C-F show "normalized proliferation." What does this mean? And how was the normalization done?

      Referee Cross-Commenting

      cross-comment regarding reviewer #1

      I agree with the referee that the link between TXNIP and GDF15 is weak, though as I mentioned before, this is particularly true in the context of oxaliplatin-regulation of TXNIP. I agree that given all the presented data, it is likely that oxaliplatin-regulation of TXNIP and GDF15 are independent. In my opinion, the referee brought up all valid concerns, but this is by far the biggest concern that I share.

      cross-comment regarding reviewer #3

      The major concern that this referee addresses is whether another transcription factor supersedes the proposed MondoA/TXNIP induction in regulating GDF15 expression in later stage CRC. In my opinion, this another other concerns of the referee are all valid, but still I remain unconvinced that TXNIP induction underlies the oxaliplatin-regulation of GDF15. I think fleshing out that aspect of the study would potentially help the authors tease apart how this potential MondoA-TXNIP-GDF15 axis is dysregulated later in CRC progression.

      Significance

      Generally speaking the experiments are well controlled and the findings are significant and novel. Though the link between MondoA activity and ROS could be strengthened, and the data could be validated under more physiological settings. Further, the authors should clarify their interpretations so as to not overstate the findings.

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      Referee #1

      Evidence, reproducibility and clarity

      This is well done and interesting paper examining the connection between TXNIP and GDF15. The main thrust is that TXNIP upregulation chemotherapies, such as Oxa, results in an a down regulation of GDF15 early in tumorigenesis. Later in tumorigenesis, TXNIP upregulation is less pronounced, elevating GFP15 resulting in a blockage of tumor suppressive immune responses. Generally the work is convincing. For example, it's clear that TXNIP is up regulated by Oxa in an ROS and MondoA-dependent manner. Likewise its quite clear TXNIP loss reads to an upregulation of GDF15. However, it's also quite clear that Oxa suppresses GDF15 in a manner that appears to be completely independent of TXNIP. The writing in the paper implies strongly that there is a mechanistic connection between TXNIP and GDF15, but no experiments investigate this possibility. It seems equally likely that TXNIP and GDF15 represent independent parallel pathways. Even if TXNIP is a direct regulator of GDF15, it's also clear that other "factors" up or down-regulated by Oxa also contribute to the regulation of GDF15. These are not explored and even though TXNIP is highly regulated genes shown Figure 2 that are not identified or discussed that may also be contributing to GDF15 regulation. Further, the experiments treating PBMCs with conditioned media contain other cytokines/factors, in addition to GDF15, that likely also contribute the observed effects on the different immune cells understudy. The conditioned media from GDF15 knock out cells are a good experiment, but the media is not rigorously tested to see what other cytokines/factors might have also been depleted. Perhaps a GDF15 complementation experiment would help here. Finally, even if completely independent, a TXNIP/GDF15 ratio does seem to have utility in determining chemo-therapeutic response.

      Other major points:

      1. Please label the other highly regulated genes shown in Fig 2A and B. Might they also explain some of the underlying biology. This could be on the current figures or in a supplement, though the former is preferred.
      2. Please address why the TXNIP induction is so much less in patient-derived organoids vs. cell line spheroids (Fig S2). By the western blots, TXNIP inductions in the organoids looks quite modest. Further, the text is quite cryptic and implies that the "upregulation" is similar in both organoids and spheroids.
      3. What was the rationale of performing the MS experiment on control and TXNIP KO DLD1 cells in the absence of oxaliplatin? The other experiments in Fig 3 clearly show that Oxa can repress GDF15 even in the absence of TXNIP, which implicates other pathways. ARRDC4? Or something else? This needs to be addressed.
      4. The data in 3J with the MondoA knockdown is not convincing. The knockdown is weak and TXNIP goes down a smidge. Agree that GDF15 goes up

      Minor points

      1. Line 79. The "loss" of TXNIP/GDF15 axis is confusing. It's really loss of TXNIP and upregulation of GDF15, right?
      2. Please provide an explanation for the different stages in tables 1 and 2. This will likely not be clear to non-clinicians.
      3. Line 231 should probably read ...cysteine (NAC), a reactive oxygen species inhibitor,
      4. Line 247, should be RT-qPCR I think.
      5. Lines 343-345. I don't quite understand the wording. Does this mean to say that 675 soluble proteins were not changed between the condition media from both cell populations?
      6. The data in FigS1 B and C don't seem to reach the standard p value of > 0.05

      Referee Cross-Commenting

      cross comment regarding referees 2 and 3 above. I'm am convinced that TXNIP is at least contemporaneously upregulated with GDF15 dowregulation. However, the strong implication from the writing is that TXNIP regulates GDF15 directly. I agree with the comment above that exploring mechanisms may be open-ended especially as TXNIP has been implicated in gene regulation by several different mechanism. I'd be satisfied with a more open-minded discussion of potential mechanisms by which TXNIP may repress GDF15 and the possibility of other parallel pathways that likely contribute to GDF15 repression.

      Significance

      This is an interesting contribution but the mechanistic connection between GDF15 and TXNIP is relatively weak. That said, even as independent variables they do seem to have utility in predicting therapeutic response.

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      Reply to the reviewers

      We are sincerely thankful to all reviewers for their work and constructive comments that allowed us to improve the quality of the present manuscript. We are very pleased to announce that we were able to tackle all the raised concerns (except the reporter assays which is a focus of future research for our laboratory, see below), and would like to briefly mention here three major improvements:

      1) We have crossed our data in frog with available human ATAC-Seq datasets. We have followed a similar approach to the one we employed in Xenopus, by “subtracting” human osteoblastic ATAC-Seq peaks with human liver, heart and lung. This cross-species validation strategy led to the identification of osteoblast-specific NFRs in human that compare very well to the Xenopus osteoblastic regulatory landscape (new Fig 6). 2) We have included ChIP-Seq data that was performed by Patricia Hanna, a former PhD student from our laboratory, in collaboration with Laurent Sachs and Nicolas Buisine (these three researchers were incorporated as new co-authors). We were planning to publish this ChIP-Seq separately but find that it contributes very well to this manuscript (modified Fig 4, new Fig 7). 3) We have included in situ hybridization analyses on frog and shark performed by David Muñoz, a former PhD student from our laboratory, in collaboration with Melanie Debiais-Thibaud and Catherine Boisvert (these three researchers were incorporated as new co-authors). This data ends nicely the manuscript by providing a biological dimension and by strengthening our evolutionary model (See new Fig 7).

      We hope that our responses match the quality criteria of Review Commons and of its affiliated journals, thank you very much once again and kind regards, Sylvain Marcellini

      Point-by-point description of the revisions:

      Reviewer #1 (Evidence, reproducibility and clarity (Required)): Summary: The paper investigates the genetic mechanisms driving osteoblast differentiation in Xenopus tropicalis, shedding light on bone diseases and early skeletal evolution. Through ATAC-seq analysis, the study identifies osteoblast-specific regulatory regions, confirming their role as osteogenic transcriptional enhancers. A substantial number of these enhancers are conserved in humans, potentially offering insights into skeletal disorders. Additionally, the research highlights an evolutionary perspective by revealing shared regulatory elements between Xenopus tropicalis and the elephant shark, suggesting an ancient origin for mineralized tissues in vertebrates.

      Major comments:

      Methodology of this paper is kinda vague and the paper seems to be fragmented and not logically organized in a linear fashion.

      Reply: We have improved the methodology section. We provide the accession numbers for all raw sequencing datasets generated for this study have been submitted and linked to the NCBI BioProject database (page 27). The paper has been almost completely rewritten and the figures substantially modified. There are now less figure which contain more information presented in a friendly fashion. The logic of the paper is as follows: -Identification of enhancers and promoters (Figs 1 and 2) -Characterization of their nucleotide sequence and TFBSs (Fig 3) -Validation with RNA-Seq and ChIP-Seq (Fig 4) -Global sequence conservation (Fig 5) -Cross validation with ATAC-Seq in human (Fig 6) -Evolutionary model (Fig 7).

      Authors could provide evidentiary support that the control tissues are non-mineralized (and exp tissues are) by simple calcein staining. Mineralization occurs during tadpole stage, and calcification of heart and lung tissue in amphibians is not well understood. This will strengthen the attestation of these tissues as controls and provide a useful diagram for exactly what tissues were used.

      Reply: We have performed Alizarin reg staining on larval skull, liver, heart and lung and show that, like in mammals, only the calvaria is mineralized (see page 6 and new Supporting Information 1).

      There appears to be no mention of osteocytes or other cell types. What measures were taken to ensure that osteoblasts are the principal cell type being described? The reference for bone tissue extraction refers to a cell culture technique in which it is likely no osteocytes would prevail.

      Reply: This is an important point to clarify because osteoblasts and their osteocytic progeny harbour a completely different function, physiology and gene expression profile. Our laboratory has studied frog osteocytes in details (Fritz et al, 2018), and we have added the following sentence “Of note, this extraction procedure does not harvest osteocytes that lie embedded within the bone matrix, allowing us to exclusively study osteoblasts. As controls, we also included larval liver, heart and lung following the criteria that they are nonmineralized (Supporting information 1) and unrelated to skeletal tissues”. See page 6.

      Minor comments:

      Data on conservation of mentioned transcription factors could be easily added (NFAT, etc.)

      Reply: We have performed extensive protein alignments showing broad conservation of the osteogenic transcription factors for which we detected binding site enrichment in osteoblast-specific enhancers (see page 10 and new Supporting Information 7).

      The data presentation is poor, especially figure 2 and figure 4.

      Reply: Following the reviewer’s advice these figures have been eliminated and replaced by Figures 2B and 2C, which, we believe, present the same information in a much clearer and friendly fashion.

      Line 115-117: "By focusing on annotated Xt transcription start sites (TSSs), we found that the ATAC-Seq NFR and mononucleosome signals form two distinct clusters," it would be helpful to briefly explain the significance of these two clusters. What does it indicate about the regulatory regions associated with TSSs?

      Reply: We have clarified this point by being more explicit: “The first cluster is composed of 5,949 promoters harbouring a robust NFR located immediately upstream of the TSS and flanked by two well-positioned nucleosomes (Fig 1B, left panel), likely corresponding to expressed genes. By contrast, the second cluster contains 16,947 promoters showing weak NFR and diffuse mononucleosome signals (Fig 1B, right panel), and is probably enriched in transcriptionally repressed genes or genes expressed at low levels”. See Page 6.

      Line 133-139: When discussing hierarchical clustering and the similarity of NFR landscapes between different tissues, you could provide a sentence or two to speculate on the potential biological implications. For instance, why might heart and lung tissues exhibit more similarity in NFR landscapes compared to osteoblasts and liver?

      Reply: This is an interesting point to raise because there is data in the literature supporting our findings. We have modified the following sentence on page 7: “Hierarchical clustering showed that the landscape of the NFRs from heart and lung are more similar to each other than to osteoblasts or liver, which is true both for TSS and non-TSS regions (Fig 1D) and which parallels data obtained in mouse [10]”. Our novel analysis with human ATAC-Seq data also leads to the same finding (Page 13): “Available human liver, heart and lung ATAC-Seq datasets were retrieved, and hierarchical clustering confirmed a higher similarity for heart and lung, and that the osteoblast sample substantially differs from the three other tissues (Supporting information 11), similarly to the situation in frog (Fig 1D) and mouse [10]”.

      Line 134: To enhance clarity, you might consider using phrases like "Figure 3A" and "Figure 3B" instead of "Compare Fig 3A and B" to directly refer to the figures in the text.

      Reply: This has been corrected has we have deeply improved the figures. See “Globally, the Pearson correlation coefficient was much higher for TSS than non-TSS peaks (Fig 1D), a finding consistent with previous studies showing that, between distinct cell types, histone marks are largely invariable at promoters while they display highly context-dependent patterns at enhancers [6, 7].” on page 7.

      Line 142-144: Please consider briefly explaining why you chose liver, heart, and lung tissues as controls. What specific characteristics or functions of these tissues make them suitable for this comparative analysis?

      Reply: We now mention “As controls, we also included larval liver, heart and lung following the criteria that they are nonmineralized (Supporting information 1) and unrelated to skeletal tissues.” on page 6.

      When discussing the potential function of osteoblastic enhancers in cartilaginous fish, you might briefly mention the role of cartilage in these organisms and how these enhancers may have evolved to regulate cartilage-related processes.

      Reply: We agree with the reviewer that this is an exciting point which is of high interest for our laboratory (see for instance our review, Cervantes et al, 2017). However, as we feel that the manuscript is already quite long and has many references, we preferred not to discuss this point and to simply focus on the osteoblast/odontoblast aspect of skeletal evolution.

      Ensure that the formatting of your methods section is consistent. For example, consistently use italics for software/tool names (e.g., "SAMtools") and follow a standard format for listing parameters or options used in software/tools.

      Reply: We have corrected these points.

      Reviewer #1 (Significance (Required)): The paper's significance lies in its elucidation of osteoblast-specific regulatory regions in Xenopus tropicalis. By characterizing these regions and connecting them to specific genes and pathways, the study advances our understanding of osteogenesis. Additionally, the identification of conserved elements across vertebrates provides insights into the deep evolutionary origins of skeletal features, offering a unique perspective on vertebrate evolution. However, one of the main limitations of the study is the lack of extensive experimental validation for the identified regulatory regions, leaving a gap in confirming their functionality.

      Reply: Thank you very much again for your helpful and constructive comments. As a functional validation, at least from the chromatin perspective, we have incorporated ChIP-Seq data (Fig 4) with four key histone marks present at active promoters (H3K4me3), active enhancers (H3K4me1), and at active chromatin (H3K27Ac) and repressed chromatin (H3K27me3). This ChIP-Seq was already available in our laboratory (thereby explaining the incorporation of three new co-authors, Dr Hanna, Dr Sachs and Dr Buisine), but we were planning to incorporate it in a different manuscript. However, we feel that it is important to include it in the present paper. Another functional validation lies in the identification of 138 conserved osteogenic enhancers harbouring a NFR both in frog and human (Fig 6). We do not intend to incorporate reporter assays at this stage, as this is a future direction of research for our laboratory, together with CRISPR mutagenesis.

      Reviewer #2 (Evidence, reproducibility and clarity (Required)): In this study, Hector Castillo and the coauthors conducted ATAC-seq and RNA-seq analyses across several cell types in Xenopus tropicalis (Xt) to identify regulatory elements specific to osteoblasts. They explored the evolutionary conservation of the osteoblast regulatory elements across species. Their research encompassed the identification of osteoblast-specific regulatory elements through cross-tissue analysis, offering comprehensive insights into tissue-specific regulatory elements. These insights included cell-type-specific chromatin accessibility, biological functions predicted by gene ontology analysis, and potential transcriptional regulators associated with these regions. The cross-species analysis unveiled partial conservation of osteoblast-specific regulatory regions between the Xt and the human genome, with the shared genomic regions being linked to osteoblast-related genes. Additionally, the enriched transcription factors were identified in these regions. The study further explored comparative analyses involving multiple species, providing evolutionary insights into the gene regulatory mechanisms underlying osteoblast identity and pathology.

      Major comment All the cross-species analyses in this study were primarily based on sequence conservation. However, since human osteoblast ATAC-seq data, as well as ChIP-seq and Hi-C data, are publicly available (PMID: 35906483), conducting a direct comparative analysis between Xenopus tropicalis (Xt) osteoblast ATAC-seq and human osteoblast ATAC-seq could provide more concrete evidence regarding the conservation of chromatin-accessible regions between these two species. This additional analysis has the potential to significantly strengthen the conclusions drawn in the study.

      Reply: We are thankful to the reviewer for this insightful comment that dramatically improved the scope of our work. We have indeed incorporated available ATAC-Seq experiments performed on human osteoblasts (SRR12933513 and SRR12933514), liver (SRR21927033 and SRR21927032), heart (SRR21927531 and SRR21927534) and lung (SRR21927095 and SRR21927098). This is explained on pages 13-14 (results), pages 19-20 (discussion) and pages 22-24 (methods). Hence, we have uncovered 138 conserved enhancers that display an osteoblast-specific NFR both in frog and human (see new Fig 6). As the reviewer states, we believe that our conclusions have been significantly strengthened, allowing us to reformulate the manuscript title which now vehiculates a more functional message. Also, thanks to this comment, we were able to propose a more attractive title for our work: “Cross-validation of conserved osteoblast-specific enhancers illuminates bone diseases and early skeletal evolution”.

      Minor comment 1 The authors made use of "annotated human enhancers" in their study; however, the specific definition or source of this annotation was not provided in the manuscript. It is crucial that the authors clarify the criteria or source used for annotating human enhancers to ensure transparency and allow readers to better understand the basis of their analyses and conclusions.

      Reply: The reviewer is correct. These “annotated human enhancers” have now completely been eliminated for the study and replaced by the analysis shown in Fig 6 (and see our reply to the previous comment).

      Minor comment 2 In relation to the association studies conducted between Xenopus tropicalis (Xt) osteoblast enhancers and genes related to human bone diseases, it's important for the authors to express their statements with caution. While the putative target genes may be potentially regulated by shared regulatory elements between Xt and humans, there exists no direct evidence demonstrating that these regulatory regions are the causative factors behind these diseases. It's worth noting that there are several other open chromatin regions in proximity to these putative target genes. As a result, the shared genomic regions may or may not have a direct relationship with human diseases. To establish a substantial linkage, more in-depth analyses would be required to provide evidence of a pathological connection.

      Reply: This is an important point, on page 14 we now state “While the osteoblast-specific regulatory regions reported here might not be directly involved in the aetiology of the aforementioned diseases, their identification considerably improves our understating of the transcriptional control of these genes”.

      Minor comment 3 In lines 394 to 397, the authors assert that the enrichment of TWIST1/2 transcription factor binding sites (TFBS) at Xenopus tropicalis (Xt) osteogenic enhancers is a novel finding. However, this claim lacks clarity regarding the novelty of this discovery, given that they reference previous literature (reference 42) that has already demonstrated the involvement of TWIST1/2 in osteoblast differentiation. The authors should provide a more precise explanation of how their specific findings related to TWIST1/2 TFBS enrichment contribute to existing knowledge or differ from previous studies to clarify the novelty of their results.

      Reply: We now provide a clearer explanation by mentioning “In this respect, the reported enrichment in TWIST1/2 TFBS (Fig 3 and Supporting information 5) represents the first evidence that TWIST proteins might control the timing of osteoblastic differentiation through binding to hundreds of osteogenic enhancers, a possibility that could be confirmed by ChIP-Seq” on page 19.

      Minor comment 4 Depositing the NGS data, including ATAC-seq and RNA-seq datasets, in a public database would be a valuable contribution to the research community.

      Reply: Yes, this data has now been made available, see pages 26-27: “Data Availability. The raw sequencing datasets generated for this study have been submitted and linked to the NCBI BioProject database with the following accession numbers: PRJNA1011469 (ATAC-seq), PRJNA1021677 (RNA-seq), and PRJNA1056467 (ChIP-seq)”.

      Reviewer #2 (Significance (Required)): The comparative analysis of ATAC-seq among different cell types in Xenopus tropicalis (Xt) provides a broad perspective on cell-type-specific chromatin accessible regions, which is a notable strength of the study. It's worth highlighting that, as far as known, this study represents the first report of ATAC-seq in Xt osteoblasts. However, it's important to acknowledge that the overall message of the study is consistent with previous findings in mammals. For example, the observation that non-transcription start site (TSS) regions were more cell-type-specific, correlating with cell-type distinct gene expressions, aligns with findings in mammalian systems. Additionally, many of the osteoblast regulators predicted from the data are already known osteogenic factors in mammals. The cross-species analysis provides valuable insights into the evolutionary aspects of putative enhancers in osteoblasts. The study identifies conserved gene regulatory regions and putative transcription factors associated with these genomic regions, shedding light on their potential roles in gene regulation. Moreover, the identification of conserved regions possibly linked to human skeletal diseases is a noteworthy aspect of the research, showcasing its strengths. However, it's essential to acknowledge a potential limitation related to this aspect of the study: the analyses conducted so far have been descriptive, primarily focusing on DNA sequence conservation. Given that several osteoblast ATAC-seq datasets from different species are publicly available, a more direct comparison between the Xt dataset and these other datasets could provide a deeper understanding of enhancer conservation and evolution. This study offers valuable resources for researchers in the field of skeletal biology and evolution. The comprehensive analysis of osteoblast-specific regulatory elements in Xenopus tropicalis, along with insights into their conservation and potential roles in human skeletal diseases, provides a foundation for further investigations in this area. Additionally, the evolutionary insights offered by the cross-species analysis contribute to the growing body of knowledge in evo-devo studies, shedding light on the evolution of gene regulatory mechanisms related to osteoblast identity. These resources and insights can serve as a valuable reference and guide for future research endeavors in both bone biology and evolutionary developmental biology. This reviewer specializes in the study of gene regulatory mechanisms in skeletal development and metabolism, primarily utilizing mouse and human tissues.

      Reply: Thank you very much again for your helpful and constructive comments.

      Reviewer #3 (Evidence, reproducibility and clarity (Required)): Summary Starting with ATAC-seq on the Xenopus tropicalis (Xt) genome, the authors tried to identify regulatory regions, which were evolutionally conserved and critical for osteoblasts, through computational approaches. They obtained profiles of the nucleosome-free regions (NFRs), i.e., open chromatin regions, in bone, liver, heart, and lung of Xt. The NFRs contain TSS-associated regions (TSS regions) and non-TSS regions. They then identified tissue-specific NFRs. Tissue-specific NFRs were predominantly located in introns and intergenic regions, and the trend was more highlighted in non-TSS regions. Regarding osteoblast-specific NFRs, non-TSS regions were associated with genes related to osteoblasts. Osteoblast-specific TSS- and non-TSS regions were enriched with motifs of osteoblast-related transcription factors (TFs), including Smad, AP-1, TEAD, Runx2, Nfic, Twist, and Nfat. By integrating ATAC-seq data with RNA-seq data, they found that osteoblast-specific NFRs were associated with transcriptionally active genes. When inter-species conservation of the Xt tissue-specific NFRs was analyzed, osteoblast-specific ones were well conserved in human, chick, and Callorhinchus milii (elephant shark). The authors further identified human homologous regions to Xt osteoblast-specific NFRs, which were enriched with binding motifs of osteoblast-related TFs, proposing putative osteogenic enhancers associated with skeletal diseases. Lastly, they identified a set of Xt osteoblast-specific NFRs that were conserved with the human, chick, and elephant shark genomes. The putative target genes of NFRs are enriched with osteogenesis-related TFs. Based on these data, they propose that evolutionary origins of osteoblast and odontoblasts are common, given that elephant shark is a cartilaginous fish, where bone is absent but odontoblast is present.

      Major comments A major critical concern on this work is that their findings and claim fully rely on bioinformatic analyses. Bioinformatic prediction should be verified by wet-type experiments. Otherwise, it is quite difficult to draw definitive conclusions. In particular, it remains to be verified if the "putative enhancers" that they computationally identified have actual enhancer activities in in-vivo contexts. ATAC-seq alone identifies open chromatin regions on the genome and is not enough to define the location of enhancers and their activities. The authors need to perform ChIP-seq for enhancer marks and reporter assays for enhancer activities, in order to verify their prediction on at least several key regions they propose.

      Reply: We have taken very seriously the reviewer´s comments and have incorporated three major experimental validations that go beyond bioinformatic analyses: -ChIP-Seq data on 4 key histone marks, previously performed in our laboratory, performed on Xenopus primary osteoblasts (see Fig 4). -Available human ATAC-Seq data for osteoblasts and control tissues (see new Fig 6). -In situ hybridization on elephant shark dental plates (see new Fig 7). We therefore have deeply modified the whole manuscript and now propose a more attractive title for our work: “Cross-validation of conserved osteoblast-specific enhancers illuminates bone diseases and early skeletal evolution”. We were not able to incorporate Reporter assays because (i) these experiments are lengthy, (ii) the current manuscript is already quite extensive and (iii) this is a major future research focus of our laboratory.

      Minor comments Line 146: Fig S2 is unlikely to be provided.

      Reply: We would like to keep this data available for readers, former Fig S2 is now “Supporting Information 3”.

      Lines 158 to 163 and Fig. 4: GO analysis was performed only on non-TSS peaks. What about TSS peaks?

      Reply: We now state on page 8 “Due to the low number of regions, no significant results were obtained with lung-specific non-TSS ATAC-Seq peaks, or with any category of TSS”.

      Line 269: In the text, the authors describe that 48 osteoblast-specific TSS peaks are aligned to corresponding regions on the human genome. However, Fig. S7 shows 46 peaks are aligned. Please double-check.

      Reply: This discrepancy has now been corrected.

      Lines 289 to 296, Figs. 8, and S11: Although TRPS1 appears in Fig. S11, the authors did not mention it in the main text and Fig. 8. Why is the gene specifically excluded from the explanation?

      Reply: This omission has now been corrected and now trps1 appears in Fig 6C, in Supporting Information 12, and is mentioned in the abstract and at pages 13-14 “Some cross-validated osteoblastic promoters and enhancers are located at loci of genes involved in skeletal diseases (See Supporting information 12 and Ref. [49]), such as osteoarthritis (adam12), osteoporosis (etv1), geroderma osteodysplasticum (gorab), keipert syndrome (gpc4), buschke-Ollendorff syndrome (lemd3), cleidocranial dysplasia (runx2) and trichorhinophalangeal syndrome type I (trps1).”.

      Reviewer #3 (Significance (Required)): - This work is potentially interesting, not just leading to identification of regulatory regions critical for osteoblast biology, but also providing evolutionary insight into bone development. However, as mentioned, lack of validation of bioinformatic prediction is a major weakness of this work. This work's concept would engage the interest in the field of bone development and skeletal transcriptional programs. However, the reviewer is not sure how much this work engages general interest. - Expertise of the reviewer is mammalian skeletal development, particularly focusing on gene regulatory networks and epigenome during the process.

      Reply: Thank you very much again for your helpful and constructive comments.

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      Referee #3

      Evidence, reproducibility and clarity

      Summary

      Starting with ATAC-seq on the Xenopus tropicalis (Xt) genome, the authors tried to identify regulatory regions, which were evolutionally conserved and critical for osteoblasts, through computational approaches. They obtained profiles of the nucleosome-free regions (NFRs), i.e., open chromatin regions, in bone, liver, heart, and lung of Xt. The NFRs contain TSS-associated regions (TSS regions) and non-TSS regions. They then identified tissue-specific NFRs. Tissue-specific NFRs were predominantly located in introns and intergenic regions, and the trend was more highlighted in non-TSS regions. Regarding osteoblast-specific NFRs, non-TSS regions were associated with genes related to osteoblasts. Osteoblast-specific TSS- and non-TSS regions were enriched with motifs of osteoblast-related transcription factors (TFs), including Smad, AP-1, TEAD, Runx2, Nfic, Twist, and Nfat. By integrating ATAC-seq data with RNA-seq data, they found that osteoblast-specific NFRs were associated with transcriptionally active genes. When inter-species conservation of the Xt tissue-specific NFRs was analyzed, osteoblast-specific ones were well conserved in human, chick, and Callorhinchus milii (elephant shark). The authors further identified human homologous regions to Xt osteoblast-specific NFRs, which were enriched with binding motifs of osteoblast-related TFs, proposing putative osteogenic enhancers associated with skeletal diseases. Lastly, they identified a set of Xt osteoblast-specific NFRs that were conserved with the human, chick, and elephant shark genomes. The putative target genes of NFRs are enriched with osteogenesis-related TFs. Based on these data, they propose that evolutionary origins of osteoblast and odontoblasts are common, given that elephant shark is a cartilaginous fish, where bone is absent but odontoblast is present.

      Major comments

      A major critical concern on this work is that their findings and claim fully rely on bioinformatic analyses. Bioinformatic prediction should be verified by wet-type experiments. Otherwise, it is quite difficult to draw definitive conclusions. In particular, it remains to be verified if the "putative enhancers" that they computationally identified have actual enhancer activities in in-vivo contexts. ATAC-seq alone identifies open chromatin regions on the genome and is not enough to define the location of enhancers and their activities. The authors need to perform ChIP-seq for enhancer marks and reporter assays for enhancer activities, in order to verify their prediction on at least several key regions they propose.

      Minor comments

      Line 146: Fig S2 is unlikely to be provided. Lines 158 to 163 and Fig. 4: GO analysis was performed only on non-TSS peaks. What about TSS peaks? Line 269: In the text, the authors describe that 48 osteoblast-specific TSS peaks are aligned to corresponding regions on the human genome. However, Fig. S7 shows 46 peaks are aligned. Please double-check. Lines 289 to 296, Figs. 8, and S11: Although TRPS1 appears in Fig. S11, the authors did not mention it in the main text and Fig. 8. Why is the gene specifically excluded from the explanation?

      Significance

      • This work is potentially interesting, not just leading to identification of regulatory regions critical for osteoblast biology, but also providing evolutionary insight into bone development. However, as mentioned, lack of validation of bioinformatic prediction is a major weakness of this work. This work's concept would engage the interest in the field of bone development and skeletal transcriptional programs. However, the reviewer is not sure how much this work engages general interest.
      • Expertise of the reviewer is mammalian skeletal development, particularly focusing on gene regulatory networks and epigenome during the process.
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      Referee #2

      Evidence, reproducibility and clarity

      In this study, Hector Castillo and the coauthors conducted ATAC-seq and RNA-seq analyses across several cell types in Xenopus tropicalis (Xt) to identify regulatory elements specific to osteoblasts. They explored the evolutionary conservation of the osteoblast regulatory elements across species. Their research encompassed the identification of osteoblast-specific regulatory elements through cross-tissue analysis, offering comprehensive insights into tissue-specific regulatory elements. These insights included cell-type-specific chromatin accessibility, biological functions predicted by gene ontology analysis, and potential transcriptional regulators associated with these regions.

      The cross-species analysis unveiled partial conservation of osteoblast-specific regulatory regions between the Xt and the human genome, with the shared genomic regions being linked to osteoblast-related genes. Additionally, the enriched transcription factors were identified in these regions. The study further explored comparative analyses involving multiple species, providing evolutionary insights into the gene regulatory mechanisms underlying osteoblast identity and pathology.

      Major comment

      All the cross-species analyses in this study were primarily based on sequence conservation. However, since human osteoblast ATAC-seq data, as well as ChIP-seq and Hi-C data, are publicly available (PMID: 35906483), conducting a direct comparative analysis between Xenopus tropicalis (Xt) osteoblast ATAC-seq and human osteoblast ATAC-seq could provide more concrete evidence regarding the conservation of chromatin-accessible regions between these two species. This additional analysis has the potential to significantly strengthen the conclusions drawn in the study.

      Minor comment 1

      The authors made use of "annotated human enhancers" in their study; however, the specific definition or source of this annotation was not provided in the manuscript. It is crucial that the authors clarify the criteria or source used for annotating human enhancers to ensure transparency and allow readers to better understand the basis of their analyses and conclusions.

      Minor comment 2

      In relation to the association studies conducted between Xenopus tropicalis (Xt) osteoblast enhancers and genes related to human bone diseases, it's important for the authors to express their statements with caution. While the putative target genes may be potentially regulated by shared regulatory elements between Xt and humans, there exists no direct evidence demonstrating that these regulatory regions are the causative factors behind these diseases. It's worth noting that there are several other open chromatin regions in proximity to these putative target genes. As a result, the shared genomic regions may or may not have a direct relationship with human diseases. To establish a substantial linkage, more in-depth analyses would be required to provide evidence of a pathological connection.

      Minor comment 3

      In lines 394 to 397, the authors assert that the enrichment of TWIST1/2 transcription factor binding sites (TFBS) at Xenopus tropicalis (Xt) osteogenic enhancers is a novel finding. However, this claim lacks clarity regarding the novelty of this discovery, given that they reference previous literature (reference 42) that has already demonstrated the involvement of TWIST1/2 in osteoblast differentiation. The authors should provide a more precise explanation of how their specific findings related to TWIST1/2 TFBS enrichment contribute to existing knowledge or differ from previous studies to clarify the novelty of their results.

      Minor comment 4

      Depositing the NGS data, including ATAC-seq and RNA-seq datasets, in a public database would be a valuable contribution to the research community.

      Significance

      The comparative analysis of ATAC-seq among different cell types in Xenopus tropicalis (Xt) provides a broad perspective on cell-type-specific chromatin accessible regions, which is a notable strength of the study. It's worth highlighting that, as far as known, this study represents the first report of ATAC-seq in Xt osteoblasts. However, it's important to acknowledge that the overall message of the study is consistent with previous findings in mammals. For example, the observation that non-transcription start site (TSS) regions were more cell-type-specific, correlating with cell-type distinct gene expressions, aligns with findings in mammalian systems. Additionally, many of the osteoblast regulators predicted from the data are already known osteogenic factors in mammals.

      The cross-species analysis provides valuable insights into the evolutionary aspects of putative enhancers in osteoblasts. The study identifies conserved gene regulatory regions and putative transcription factors associated with these genomic regions, shedding light on their potential roles in gene regulation. Moreover, the identification of conserved regions possibly linked to human skeletal diseases is a noteworthy aspect of the research, showcasing its strengths. However, it's essential to acknowledge a potential limitation related to this aspect of the study: the analyses conducted so far have been descriptive, primarily focusing on DNA sequence conservation. Given that several osteoblast ATAC-seq datasets from different species are publicly available, a more direct comparison between the Xt dataset and these other datasets could provide a deeper understanding of enhancer conservation and evolution.

      This study offers valuable resources for researchers in the field of skeletal biology and evolution. The comprehensive analysis of osteoblast-specific regulatory elements in Xenopus tropicalis, along with insights into their conservation and potential roles in human skeletal diseases, provides a foundation for further investigations in this area. Additionally, the evolutionary insights offered by the cross-species analysis contribute to the growing body of knowledge in evo-devo studies, shedding light on the evolution of gene regulatory mechanisms related to osteoblast identity. These resources and insights can serve as a valuable reference and guide for future research endeavors in both bone biology and evolutionary developmental biology.

      This reviewer specializes in the study of gene regulatory mechanisms in skeletal development and metabolism, primarily utilizing mouse and human tissues.

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      Referee #1

      Evidence, reproducibility and clarity

      Summary:

      The paper investigates the genetic mechanisms driving osteoblast differentiation in Xenopus tropicalis, shedding light on bone diseases and early skeletal evolution. Through ATAC-seq analysis, the study identifies osteoblast-specific regulatory regions, confirming their role as osteogenic transcriptional enhancers. A substantial number of these enhancers are conserved in humans, potentially offering insights into skeletal disorders. Additionally, the research highlights an evolutionary perspective by revealing shared regulatory elements between Xenopus tropicalis and the elephant shark, suggesting an ancient origin for mineralized tissues in vertebrates.

      Major comments:

      Methodology of this paper is kinda vague and the paper seems to be fragmented and not logically organized in a linear fashion. Authors could provide evidentiary support that the control tissues are non-mineralized (and exp tissues are) by simple calcein staining. Mineralization occurs during tadpole stage, and calcification of heart and lung tissue in amphibians is not well understood. This will strengthen the attestation of these tissues as controls and provide a useful diagram for exactly what tissues were used. There appears to be no mention of osteocytes or other cell types. What measures were taken to ensure that osteoblasts are the principal cell type being described? The reference for bone tissue extraction refers to a cell culture technique in which it is likely no osteocytes would prevail.

      Minor comments:

      Data on conservation of mentioned transcription factors could be easily added (NFAT, etc.) The data presentation is poor, especially figure 2 and figure 4. Line 115-117: "By focusing on annotated Xt transcription start sites (TSSs), we found that the ATAC-Seq NFR and mononucleosome signals form two distinct clusters," it would be helpful to briefly explain the significance of these two clusters. What does it indicate about the regulatory regions associated with TSSs? Line 133-139: When discussing hierarchical clustering and the similarity of NFR landscapes between different tissues, you could provide a sentence or two to speculate on the potential biological implications. For instance, why might heart and lung tissues exhibit more similarity in NFR landscapes compared to osteoblasts and liver? Line 134: To enhance clarity, you might consider using phrases like "Figure 3A" and "Figure 3B" instead of "Compare Fig 3A and B" to directly refer to the figures in the text. Line 142-144 :Please consider briefly explaining why you chose liver, heart, and lung tissues as controls. What specific characteristics or functions of these tissues make them suitable for this comparative analysis? When discussing the potential function of osteoblastic enhancers in cartilaginous fish, you might briefly mention the role of cartilage in these organisms and how these enhancers may have evolved to regulate cartilage-related processes. Ensure that the formatting of your methods section is consistent. For example, consistently use italics for software/tool names (e.g., "SAMtools") and follow a standard format for listing parameters or options used in software/tools.

      Significance

      The paper's significance lies in its elucidation of osteoblast-specific regulatory regions in Xenopus tropicalis. By characterizing these regions and connecting them to specific genes and pathways, the study advances our understanding of osteogenesis. Additionally, the identification of conserved elements across vertebrates provides insights into the deep evolutionary origins of skeletal features, offering a unique perspective on vertebrate evolution. However, one of the main limitations of the study is the lack of extensive experimental validation for the identified regulatory regions, leaving a gap in confirming their functionality.

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      Reply to the reviewers

      1. General Statements [optional]

      We would like to extend our warmest thanks to the reviewers for their constructive comments and strong support for our study.

      2. Point-by-point description of the revisions

      Reviewer #1:

      Table

      1. It would be nice to have a table of isoform, dose, promoter, enhancer and other conditions tested and the brief summary of phenotype as Table.

      We thank the reviewer for this valuable suggestion and have now included a summary Table (Table 1) cited in the last result section.

      Discussion

      1. This experiment was done on knockout condition but in real patient different form of mutant protein will exist in retinal tissue. Authors indicated that co‐expression of short and long form of FAM161A worked better to rescue function. How would authors cope with interfering endogenous mutant protein in real patients?

      We thank the reviewer for raising this interesting point. Most mutations described so far are nonsense or frameshift mutations common to both long and short isoforms which, consequently, are not present at the protein level (Beryozkin et al 2020, doi.org/10.1038/s41598-020-72028-0, Matsevich et al 2022, doi.org/10.1016/j.xops.2022.100229). Thus, we don’t expect to have an imbalance between the remaining functional alleles and the therapeutic ones. However, we cannot exclude the discovery of missense mutations and the effect of such allele would have to be molecularly evaluated to determine if gene replacement is limited for this specific condition. This question could be assessed in cellular models by co-expression of both mutated and WT-tagged proteins or in organoid models.

      1. Related to the first question, the expression of these retinal structural proteins will be different in mice and human. How would authors optimize the vector for human patient gene therapy?

      Aware that the 60% homology between the human and mouse protein could cause important limitations for the evaluation of the vector in the mouse model, we are continuing the validation of our vectors in human retina organoïds. We plan to test both the reliable localization of the human isoforms in WT organoid and the rescue of structural photoreceptor defects of FAM161A-deficient human organoids. In parallel, vector-derived expression will also be validated in non-human primates.

      Reviewer #2:

      Scotopic and photopic ERG were performed to study retinal function. However, mouse behavior tests such as optomotor response should be employed to confirm vision restoration.

      In our hand, we didn’t notice a significant modification of the optomotor response between 4 and 16 weeks (for figure on visual acuity changes with age in Fam161atmb/tmb mice (n=6-9), see uploaded word document), and consequently of the estimated visual acuity, in Fam161atmb/tmb mice at 3.5 months corresponding to the endpoint of our study (see figure below). In a separate study to this work, we are thus conducting a follow-up long term gene therapy study to be able to complete the functional analysis of the gene therapy rescue with the optomotor response at age with significant decreased visual acuity in untreated mice compared to WT. We will have to wait at least 6 months to expect to see a difference between groups.

      The immunostaining in Figure 3 has some noise. Filtering the blocking solution before use could improve the quality of the staining.

      We thank the reviewer for this suggestion. The blocking solution was already filtered and the limited success of the mouse FAM161A staining is due to the imperfect recognition of anti-human FAM161A antibodies to the mouse protein.

      In Figure 5f, the data of wildtype mice should be included for comparison.

      As noted by reviewer 3, in Fig5 F, the plain gray horizontal line surrounded by the 2 dotted ones are referring to the mean +/- SEM of the WT value respectively. We added “WT” on the right of the graph to highlight the plain line.

      The cited paper, such as 'Garafalo AV, Cideciyan AV, Heon E, Sheplock R, Pearson A, WeiYang Yu C, Sumaroka A, Aguirre GD, and Jacobson SG. Progress in treating inherited retinal diseases: Early subretinal gene therapy clinical trials and candidates for future initiatives. Prog Retin Eye Res. 2020;77(100827),' should be an original research paper, not a review article.

      As noted by reviewer 3, we think appropriate to cite this review which is a complete reference to the different gene therapy approaches developed for inherited retinal diseases.

      Major:

      Fig 1A‐B. Do hTERT‐RPE1 cells endogenously express FAM161A? This set of images lacks a negative control (i.e., no transfected RPE1 cells). Western blot of FAM161A is recommended, similar to Fig 1C.

      We previously showed that hTERT-RPE1 cells express FAM161A in the basal body of the centriole (Di Gioia 2015), but we recognized that it is not apparent in Figure 1A and B, probably due to a limitation of the antibody reactivity which labeled only overexpressed proteins. We thus performed additional experiments using the human ARPE19 cell line to demonstrate endogenous FAM161A expression in untransfected cells and to perform a Western blot from human transfected cells. We observed that in untransfected cells FAM161A labeling is weak and is only revealed in the centriole labeled by centrin after a long exposure time (Figure 1A). When FAM161A HS or HL is overexpressed the FAM161A labeling is present in the cell body, very strong, and is observed with short exposure time (Figure 1A). We also extracted protein from untransfected and HS- or HL-transfected ARPE-19 cells to identify the FAM161A protein by Western blot (Figure 1B). Thus, we added the negative control and a western blot from human cells to answer reviewer comments.

      Fig 1C. The authors noted in the discussion that HS isoform is more abundant than HL isoform from human retinal extract. Although this is from 661W, a mouse photoreceptor cell line, it seems this is aligned with the notion. To echo with the last comment, I am curious to see if under the same transfection, the HS isoform is preferentially expressed in hTERT‐RPE1 cells.

      We do not think that transfection experiment is sufficient to prove that HS is preferentially express than HL. Even if we transfect the same amount of DNA, we would need an internal control for transfection to allow relative quantification of the protein expression after transfection. However, we performed an additional experiment in human RPE cells using the ARPE-19 cell line which is more efficiently transfected than hTERT-RPE1 in our hands. As shown in Figure 1B, we observed again more abundant expression of HS in these human transfected cells. However, we cannot exclude difference in transfection efficiency between HL and HS conditions that could explain the difference in the final amount of FAM161A protein.

      Fig 3 and Fig 5: low mag WT images of FAM161A are the same. But higher mag images (presumably selected from ROIs in low mag) are not the same. Please make sure of no duplication images.

      We are facing technical limits with the labeling of the mouse Fam161A. The antibodies available have limited affinity for the mouse Fam161A protein. While we were able to perform Uex-M from mouse tissue samples (flatmount retina) to study Fam161A expression in the connecting cilium (Mercey et al PLoS Biol 2022), it was more challenging to obtained low magnification picture from mouse retina sections. We propose to show in Figure 3 mouse Fam161A expression obtained from retina section and keep the low magnification from a flatmount for the figure 5. Thus, there will be no duplication of images as recommended by the reviewer.

      Fig 4H. HS+HL combo, and HL alone, showed almost a polarized quantification, quite variable. Can the authors speculate the reason?

      Despite the fact that injections are targeting similar retinal region in treated animals, there is still variation in the localization and extend of the gene transfer due to the surgical success. Indeed, the area of retinal detachment is hard to control in the mouse as of the quality of re-attachment. Moreover, the effective dose may lightly vary when some viral particles might be loss due to reflux. One would need to treat a larger number of eyes to really conclude that HS alone would be less variable than HL alone or HS+HL. However, we could also speculate that HS+HL and HL treatments being more efficient to rescue connecting cilium length compared to HS alone (Fig 5F) could, in the best injected eyes, have a better ONL thickness rescue than the limited ONL rescue induced by HS treatment.

      Also can the authors comment on if there is any associated notable inflammation especially in high tier dosage (10^11 GC)?

      We didn’t follow inflammation directly by fundus examination or OCT imaging following injection. However, despite the high dose used in our successful conditions (10E11 GC/eye), we didn’t notice any differences in the general mouse welfare after injection compare to lower doses. Systemic administration of Rimadyl (carprofen) was however adapted to each mouse during the 24 hrs post-surgery. In comparison to other groups with lower vector doses, no particular emergence of inflammatory cells or damages were observed by histology.

      Can the authors comment on the difference in the injection time, PN14‐15 in this study vs. PN24‐29 in their previous study? Have the authors attempted to treat the older mice with the optimized vector?

      The gene therapy study using the mouse cDNA was performed before establishing the time course of connecting cilia disruption in the Fam161atmb/tmb mouse (Mercey et al. 2022). Following the observation that CC develop similarly to healthy animal up to postnatal day 10, we decided to treat the mouse earlier for the second gene therapy study using human proteins. Nonetheless, the action of the vector occurred when the cilium is already disorganized as we expect expression of the WT Fam161A from 2 weeks post-injection. We are now testing treatments at different ages, including PN28, to determine the therapeutic window and if the optimal conditions (dose, ratio) may vary with the age at treatment.

      Can the authors speculate on why IRBP‐GRK1 human FAM161A did not realize functional rescue (Fig 2) as it did with mouse FAM161A (previous work)?

      Our hypothesis to explain the absence of functional rescue following IRBP-GRK1 vector injection is that the difference in human protein distribution compared to the mouse protein in the mouse retina could impact the function of the photoreceptor by interfering with physiological process such as transport. As mentioned in our discussion: “overexpression of these proteins could saturate the transport system impacting the cellular processes”.

      As mentioned in the discussion, there is only 60% of homology between human and mouse proteins which could induce a major impact on protein localization and function. Post-translational modification which are also known to be crucial for modulating connecting cilium addressing (Rao et al. 2016) could also differ and impact both human protein distribution and function (for example 3 cysteines in the human protein sequence could be palmytoylated (C359, C366, C367) and are absent in the mouse sequence). Moreover, the exact role of the human long and short isoforms are unknown and their adaptability to the mouse system not yet identified. Further studies should be performed to understand the consequence of such differences on the function and to unravel the function of both long and short human isoforms in the retina.

      Minor:

      While the manuscript is overall well communicated, there are areas requiring further proofread. For example, in the Abstract section, "In 15 years" should be "For 15 years", "14‐days FAM161atm1b/tm1b mice" should be "14‐day old". In the Introduction, "... suggesting that protein miss‐localization" should be "mis‐localization". In the last paragraph before Discussion, "(iii) the restauration of CC..." should be "restoration", etc.

      We corrected these errors and carefully proofread the whole manuscript to avoid typing mistakes.

      I recommend the authors to use a table to summarize different promoters, titers and key findings (e.g., expression level, localization) used and refer back to each figure.

      We thank the reviewer for this valuable suggestion and have now included a summary Table (Table 1) cited in the last result section.

      Scale bars on all figures, or every set of images.

      We added scale bars on figures containing microscopic images.

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      Referee #3

      Evidence, reproducibility and clarity

      This manuscript led by Arsenijevic and Chang is an important technical development to the ocular gene therapy space, and touches on the important aspect of structural protein restoration by gene therapy, that is, the precise control of localization and subsequent functional realization. Overall the manuscript is well written, and the experiments are technically sound, with limitations acknowledged.

      To briefly summarize, the authors wanted to understand precise control of FAM161A expression and connecting cilium (CC) restoration. They built on, and extended their previous work that showed limited structural and functional rescue by photoreceptor expression of the longer isoform of mouse FAM161A in Fam161a KO driven by IRBP-GRK1 promoter. In the current work, the authors experimented with delivering human ortholog of FAM161A cDNA, short, or long, or both isoforms using newly devised, relatively weak promoters. The main readouts include retinal morphology (e.g., ONL thickness), ERG, and protein localization by IHC (e.g., correct location, no ectopic expression). It is worth noting that the authors highlighted the use of expansion microscopy technology to examine the connecting cilium (CC) organization and protein expression, which may minimize the use of TEM for CC structure determination and enable acceleration.

      My enthusiasm for recommending it for publication is high. Nonetheless, I have the following comments, hoping the authors could address to further improve the manuscript.

      Major:

      Fig 1A-B. Do hTERT-RPE1 cells endogenously express FAM161A? This set of images lacks a negative control (i.e., no transfected RPE1 cells). Western blot of FAM161A is recommended, similar to Fig 1C.

      Fig 1C. The authors noted in the discussion that HS isoform is more abundant than HL isoform from human retinal extract. Although this is from 661W, a mouse photoreceptor cell line, it seems this is aligned with the notion. To echo with the last comment, I am curious to see if under the same transfection, the HS isoform is preferentially expressed in hTERT-RPE1 cells..

      Fig 3 and Fig 5: low mag WT images of FAM161A are the same. But higher mag images (presumably selected from ROIs in low mag) are not the same. Please make sure of no duplication images.

      Fig 4H. HS+HL combo, and HL alone, showed almost a polarized quantification, quite variable. Can the authors speculate the reason? Also can the authors comment on if there is any associated notable inflammation especially in high tier dosage (10^11 GC)?

      Can the authors comment on the difference in the injection time, PN14-15 in this study vs. PN24-29 in their previous study? Have the authors attempted to treat the older mice with the optimized vector?

      Can the authors speculate on why IRBP-GRK1 human FAM161A did not realize functional rescue (Fig 2) as it did with mouse FAM161A (previous work)?

      Minor:

      While the manuscript is overall well communicated, there are areas requiring further proofread. For example, in the Abstract section, "In 15 years" should be "For 15 years", "14-days FAM161atm1b/tm1b mice" should be "14-day old". In the Introduction, "... suggesting that protein miss-localization" should be "mis-localization". In the last paragraph before Discussion, "(iii) the restauration of CC..." should be "restoration", etc.

      I recommend the authors to use a table to summarize different promoters, titers and key findings (e.g., expression level, localization) used and refer back to each figure.<br /> Scale bars on all figures, or every set of images.

      Referees cross-commenting

      To reviewer #2, Fig5f - WT data was shown as the gray horizontal line. I had the same question but then saw they noted in the legends. I think it is fine to cite the PRER review article to make their point.

      I agree with the comments addressed by Reviewer #1 and am glad we both raise the point of using table for summarization.

      Significance

      This well-drafted paper represents a technical development that could supplement current gene therapy strategies to certain ciliopathies. In this particular case, the authors chose FAM161A, a disease causal gene to retinitis pigmentosa-28 and encodes for a microtubule-associated ciliary protein involved in organizing the connecting cilium in photoreceptors. Of importance, the authors devised novel promoters to drive gene expression and took advantage of expansion microscopy for quickly examining cilia proteins and structures. Conceptually, the techniques developed in this manuscript could be applicable to several other inherited retinal dystrophies that share similar disease mechanisms.

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      Referee #2

      Evidence, reproducibility and clarity

      Arsenijevic et al. investigated the therapeutic function of the FCBR1-F0.4 promoter-driven expression of both the short and long isoforms of human FAM161A. The results showed that this method not only repaired the disorganized connecting cilium but also restored the appropriate expression and localization of other proteins in the connecting cilium, thus restoring retinal function. Additionally, the study systematically evaluated the AAV dose, different promoters, and FAM161A isoforms' effects on retinal survival and function. Overall, the study is novel and robust. Here are some suggestions that may help improve the manuscript:

      Scotopic and photopic ERG were performed to study retinal function. However, mouse behavior tests such as optomotor response should be employed to confirm vision restoration.

      The immunostaining in Figure 3 has some noise. Filtering the blocking solution before use could improve the quality of the staining.

      In Figure 5f, the data of wildtype mice should be included for comparison.

      The cited paper, such as 'Garafalo AV, Cideciyan AV, Heon E, Sheplock R, Pearson A, WeiYang Yu C, Sumaroka A, Aguirre GD, and Jacobson SG. Progress in treating inherited retinal diseases: Early subretinal gene therapy clinical trials and candidates for future initiatives. Prog Retin Eye Res. 2020;77(100827),' should be an original research paper, not a review article.

      Referees cross-commenting

      Agree with the comments addressed by Reviewer #1 and #3

      Significance

      Overall, the manuscript is clear and interesting. I suggest a major resion for the manuscript.

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      Referee #1

      Evidence, reproducibility and clarity

      The manuscript "Fine-tuning FAM161A gene augmentation therapy to restore retinal function" submitted by Arsenijevic et al., describes gene therapy for RP28 caused by mutation in FAM161A in human. The authors worked on Fam161a-dficient mice by testing different isoforms, dose, promoter and enhancers to control the expression level and localization of the protein to functionally rescue the mice to prevent blindness. The tight control of protein expression is required for mutation in genes coding structural proteins in the retina.

      The authors have clearly showed the optimized combination of conditions to restore function of Fam161atm1b/tm1b mice and also area of improvement to make.

      Comments

      Table

      1. It would be nice to have a table of isoform, dose, promoter, enhancer and other conditions tested and the brief summary of phenotype as Table.

      Discussion

      1. This experiment was done on knockout condition but in real patient different form of mutant protein will exist in retinal tissue. Authors indicated that co-expression of short and long form of FAM161A worked better to rescue function. How would authors cope with interfering endogenous mutant protein in real patients?
      2. Related to the first question, the expression of these retinal structural proteins will be different in mice and human. How would authors optimize the vector for human patient gene therapy?

      Significance

      This is an important and excellent work showing tight control of expression is required for future retinal gene therapy.

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      Reply to the reviewers

      1. General Statements [optional]

      We are thankful to the reviewers for the time and effort invested in assessing our manuscript and for their suggestions to improve it. We have now considered the points raised by them, carried out additional experiments, and modified the text and figures to address them. We feel that the new experiments and modifications have been able to solve all concerns raised by the reviewers and have improved the manuscript substantially, strengthening and extending our conclusions.

      The main modifications include:

      • We have extended the analysis of the overexpression strains to highly stringent conditions, which revealed a mild acidification defect for the strain overexpressing Oxr1. In addition, we have included in our analysis a strain in which both proteins are overexpressed, which resulted in a further growth defect.
      • We have analyzed the recruitment of Rtc5 to the vacuole under additional conditions: deletion of the main subunit of the RAVE complex RAV1, medium containing galactose as the sole carbon source and pharmacological inhibition of the V-ATPase. These experiments allowed us to strengthen and extend our conclusions regarding the requirements for Rtc5 targeting to the vacuole.
      • We have analyzed V-ATPase disassembly in intact cells, by addressing the localization to the vacuole of subunit C (Vma5) in glucose and galactose-containing medium. The results strengthen our conclusion that both Rtc5 and Oxr1 promote an in vivo state of lower V-ATPase assembly.
      • We have extended our analyses of V-ATPase function to medium containing galactose as a carbon source, since glucose availability is one of the main regulators of V-ATPase function in vivo. The results are consistent with what we observed in glucose-containing medium.
      • We have included a diagram of the structure of the V-ATPase for reference.
      • We have included a diagram and a paragraph describing Oxr1 and Rtc5 regarding protein length and domain architecture and comparing them to other TLDc domain-containing proteins.
      • We have made changes to the text and figures to improve clarity and accuracy, including a methods section that was missing. We include below a point-by-point response to the reviewers´ comments.

      2. Point-by-point description of the revisions

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

      __ __Suggestions:

      1. The authors observed that knockout of Rtc5p or Oxr1p does not affect vacuolar pH. If Rtc5p and Oxr1p both cooperate to dissociate V-ATPase, the authors may wish to characterize the effect of a ∆Rtc5p∆Oxr1p double knockout on vacuolar pH. The double mutant ∆rtc5∆oxr1 was already included in the original manuscript (the growth test is shown in Figure 5 B and the BCECF staining is shown in Figure 5C). This strain behaved like wt in both of these assays. Of note, what we observe for the deletion strains is increased assembly (Figure 5 D - G), so we expect that it would be hard to observe a difference in vacuole acidity or growth in the presence of metals.

      Therefore, we have now also included a strain with the double overexpression of Oxr1 and Rtc5. Since overexpression of the proteins results in decreased assembly, it is more likely that this strain will show impaired growth under conditions that strongly rely on V-ATPase activity. Indeed, we observed that the overexpression of Oxr1 alone resulted in a slight growth defect in media containing high concentrations of ZnCl2 and the double overexpression strain showed an even further defect (Figure 6 A and C).

      The manuscript would benefit from a well-labelled diagram showing the subunits of V-ATPase (e.g. in Figure 2D).

      We agree with the reviewer and we have now added a diagram of the structure of the V-ATPase labeling the different subunits in Figure 2B.

      The images of structures, especially in Figure 1-Supplement 1B, are not particularly clear and could be improved (e.g. by removing shadows or using transparency).

      We are thankful to the reviewer for this suggestion. To improve the clarity of the structures in Figure 1 C and Figure 1 – Supplement 1A, we are now presenting the different subunits in the structures with different shades of blue and grey.

      The authors should clearly describe the differences between Rtc5p and Oxr1p in terms of protein length, sequence identity, domain structure, etc.

      We are thankful for this suggestion and we have now included a diagram of the domain architecture and protein length of Rtc5 and Oxr1, comparing with two human proteins containing a TLDc domain in Figure 5A. In addition, we have added the following paragraph describing the features of the proteins.

      “Rtc5 is a 567 residue-long protein. Analysis of the protein using HHPred (Zimmermann et al., 2018), finds homology to the structure of porcine Meak7 (PDB ID: 7U8O, (Zi Tan et al., 2022)) over the whole protein sequence (residues 37-559). For both yeast Rtc5 and human Meak7 (Uniprot ID: Q6P9B6), HHPred detects homology of the C-terminal region to other TLDc domain containing proteins like yeast Oxr1 (PDBID: 7FDE), Drosophila melanogaster Skywalker (PDB ID: 6R82), and human NCOA7 (PDB ID: 7OBP), while the N-terminus has similarity to EF-hand domain calcium-binding proteins (PDB IDs: 1EG3, 2CT9, 1S6C6, Figure 5A). HHPred analysis of the 273 residue long Saccharomyces cerevisiae Oxr1, on the other hand, only detects similarity to TLDc domain containing proteins (PDB IDs: 7U80, 6R82, 7OBP), which spans the majority of the sequence of the protein (residues 71-273). The overall sequence identity between Oxr1 and Rtc5 is 24% according to a ClustalOmega alignment within Uniprot. The Alphafold model that we generated for Rtc5 is in good agreement with the available partial structure of Oxr1 (7FDE) (root mean square deviation (RMSD) of 3.509Å) (Figure 5 - S1 A), indicating they are structurally very similar, in the region of the TLDc domain. Taken together, these analyses suggest that Oxr1 belongs to a group of TLDc domain-containing proteins consisting mainly of just this domain like the splice variants Oxr1-C or NCOA7-B in humans (NP_001185464 and NP_001186551, respectively), while Rtc5 belongs to a group containing an additional N-terminal EF-hand-like domain and a N-myristoylation sequence, like human Meak7 (Finelli & Oliver, 2017) (Figure 5 A).”

      Minor:

      1. The "O" in VO should be capitalized. This has been corrected.

      In Figure 4 supplement 1, the labels "I", "S", and "P" should be defined.

      This has been clarified in the figure legend.

      Please clarify what is meant by "switched labelling"

      This refers to the SILAC vacuole proteomics experiments, for which yeast strains are grown in medium containing either L-Lysine or 13C6;15N2- L-Lysine to produce normal (‘light’) or heavy isotope-labeled (‘heavy’) proteins. This allows comparing two conditions. To increase the robustness of the comparisons, the experiments are done twice with both possible labeling schemes (condition A – light, condition B – heavy + condition A – heavy + condition B – light), which is commonly described as switched labeling or label switching.

      We have exchanged the original sentence in the manuscript for:

      “Performing the same experiments but switching which strain was labeled with heavy and light amino acids gave consistent results.”

      The meaning of the sentence "Indeed, this was the case for both of them" is ambiguous.

      We have now replaced this sentence with the following:

      “Indeed, overexpression of either Rtc5 or Oxr1 resulted in increased growth defects in the context of Stv1 deletion (Figure 7 H and I).”

      For Figure 1-Supplement 1B it is hard to see the crosslink distances.

      We have updated this figure to improve the visibility of the cross-links. In addition, we now include a supplemental table (supplemental table 5) with a list of the Cα- Cα distances measured for all the crosslinks we mapped onto high-resolution structures.

      The statement "The effects of Oxr1 are greater than those caused by Rtc5" requires more context. Is there a way of quantifying this effect for the reader?

      We agree that this sentence was too general and vague. The effects caused by one or the other protein depend on the condition and the assay. We have thus deleted this sentence, and we think it is better to refer to the description of the individual assays performed.

      The phrase "negative genetic interaction" should be clarified.

      We have included in the text the following explanation of genetic interactions:

      “A genetic interaction occurs when the combination of two mutations results in a different phenotype from that expected from the addition of the phenotypes of the individual mutations. For example, deletion of OXR1 or RTC5 has no impact on growth in neutral pH media containing zinc in a control background but improves the growth of RAV1 deletion strains (Figure 7 E and F), so this is a positive genetic interaction. On the other hand, overexpression of either Rtc5 or Oxr1 results in a growth defect in a background lacking Rav1 in neutral media containing zinc, a negative genetic interaction.”

      * * In the sentence "Isogenic strains with the indicated modifications in the genome where spotted as serial dilutions in media with pH=5.5, pH=7.5 or pH=7.5 and containing 3 mM ZnCl2", "where" should be "were".

      This has been corrected.

      Figure 2D: the authors should consider re-coloring these models, as it is challenging to distinguish Rtc5p from the V-ATPase.

      We have changed the coloring of this structure and added a diagram of the V-ATPase structure with the same coloring scheme to improve clarity.

      Reviewer #1 (Significance (Required)):

      The vacuolar protein interaction map alone from this manuscript is a nice contribution to the literature. Experiments establishing colocalization of Rtc5p to the vacuole are convincing, as is dependence of this association on the presence of assembled V-ATPase. Similarly, experiments related to myristoylation are convincing. The observed mislocalization of V-ATPases that contain Stv1p to the vacuole (which is also known to occur when Vph1p has been knocked out) upon knockout of Oxr1p is also extremely interesting. Overall, this is an interesting manuscript that contributes to our understand of TLDc proteins.

      We are thankful to the reviewer for their appreciation of the significance of our work, including the interactome map of the vacuole as a resource and the advances on the understanding of the regulation of the V-ATPase by TLDc domain-containing proteins.

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

      Major points:

      1. The evidence of Oxr1 and Rtc5 as V-ATPase disassembly factors is circumstantial. The authors base their interpretation primarily on increased V1 (but not Vo) at purified vacuoles from Oxr1- or Rtc5-deleted strains, which does not directly address disassembly. Of course, the results regarding Oxr1 confirm detailed disassembly experiments with the purified protein complex (PMID 34918374), but on their own are open to other interpretations, e.g. suppression of V-ATPase assembly. Of note, the authors emphasize that they provide first evidence of the in vivo role of Oxr1, but monitor V1 recruitment with purified vacuoles and do not follow V-ATPase assembly in intact cells. We are thankful to the reviewer for pointing this out. We did not want to express that the molecular activity of the proteins is the disassembly of the complex, as our analyses include in vivo and ex vivo experiments and do not directly address this. We rather meant that both proteins promote an in vivo state of lower assembly of the V-ATPase. We have modified the wording throughout the manuscript to be clearer about this.

      In addition, we have added new experiments to monitor V-ATPase assembly in intact cells, as suggested by the reviewer. Previous work has shown that in yeast, only subunit C leaves the vacuole membrane under conditions that promote disassembly, while the other subunits remain at the vacuole membrane (Tabke et al 2014). Our own experiments agree with what was published (Figure 3 D). We have thus monitored Vma5 localization to the vacuole under glucose or after shift to galactose containing media in cells lacking or overexpressing Rtc5 or Oxr1. We observed that cells overexpressing either TLDc domain protein show lower levels of Vma5 recruitment to the vacuole in glucose (Figure 6 D and E). Additionally cells lacking either Rtc5 or Oxr1 contain higher levels of Vma5 at the vacuole after 20 minutes in galactose medium (Figure 5 F and G). Thus, these results re-inforce our conclusions that Rtc5 and Oxr1 promote states of lower assembly.

      Oxr1 and Rtc5 have very low sequence similarity. It would be helpful if the authors provided more detail on the predicted structure of the putative TLDc domain of Rtc5 and its relationship to the V-ATPase - Oxr1 structure. Is Rtc5 more closely related to established TLDc domain proteins in other organisms?

      We have now included a diagram of the domain architecture of Rtc5 and Oxr1, and comparison to the features of other TLDc domain containing proteins in Figure 5 A, as well as a paragraph describing them:

      “Rtc5 is a 567 residue-long protein. Analysis of the protein using HHPred (Zimmermann et al., 2018), finds homology to the structure of porcine Meak7 (PDB ID: 7U8O, (Zi Tan et al., 2022)) over the whole protein sequence (residues 37-559). For both yeast Rtc5 and human Meak7 (Uniprot ID: Q6P9B6), HHPred detects homology of the C-terminal region to other TLDc domain containing proteins like yeast Oxr1 (PDBID: 7FDE), Drosophila melanogaster Skywalker (PDB ID: 6R82), and human NCOA7 (PDB ID: 7OBP), while the N-terminus has similarity to EF-hand domain calcium-binding proteins (PDB IDs: 1EG3, 2CT9, 1S6C6, Figure 5A). HHPred analysis of the 273 residue long Saccharomyces cerevisiae Oxr1, on the other hand, only detects similarity to TLDc domain containing proteins (PDB IDs: 7U80, 6R82, 7OBP), which spans the majority of the sequence of the protein (residues 71-273). The overall sequence identity between Oxr1 and Rtc5 is 24% according to a ClustalOmega alignment within Uniprot. The Alphafold model that we generated for Rtc5 is in good agreement with the available partial structure of Oxr1 (7FDE) (root mean square deviation (RMSD) of 3.509Å) (Figure 5 - S1 A), indicating they are structurally very similar, in the region of the TLDc domain. Taken together, these analyses suggest that Oxr1 belongs to a subfamily of TLDc domain-containing proteins consisting mainly of just this domain like the splice variants Oxr1-C or NCOA7-B in humans (NP_001185464 and NP_001186551, respectively) , while Rtc5 belongs to a subfamily containing an additional N-terminal EF-hand-like domain and a N-myristoylation sequence, like human Meak7 (Finelli & Oliver, 2017) (Figure 5 A).”

      The authors conclude vacuolar recruitment of Rtc5 depends on the assembled V-ATPase, based on deletion of different V1 and Vo domain subunits. However, these genetic manipulations likely cause a strong perturbation of vacuolar acidification; indeed, the images show drastically altered vacuolar morphology. To strengthen their conclusion, it would be helpful to show that Rtc5 recruitment is not blocked by inhibition of vacuolar acidification, and that conversely it is blocked by deletion of rav1.

      We are thankful to the reviewer for this insightful suggestion and we have now performed both experiments suggested. The experiment regarding rav1Δ is now Figure 3C, and we observed that this mutation also disrupts Rtc5 localization to the vacuole. In addition, we decided to include an experiment showing the subcellular localization of Rtc5 after shifting the cells to galactose containing medium for 20 minutes, as a physiologically relevant condition that results in disassembly of the complex (Figure 3D). We observed that under these conditions Rtc5 re-localizes to the cytosol. This result is particularly interesting given that in yeast only subunit C (but not other V1 subunits) re-localizes to the cytosol under these conditions. In addition, the experiment using Bafilomycin A to inhibit the V-ATPase shows that Rtc5 is still localized at the vacuole membrane under conditions of V-ATPase inhibition (Figure 3 F). Taken together these results allowed us to strengthen our original interpretation that Rtc5 requires an assembled V-ATPase for its localization and extend it to the fact that the V-ATPase does not need to be active.

      Reviewer #2 (Significance (Required)):

      This is an interesting paper that confirms and extends previous findings on TLDc domain proteins as a novel class of proteins that interact with and regulate the V-ATPase in eukaryotes. The title seems to exaggerate the findings a bit, as the authors do not investigate V-ATPase (dis)assembly directly and only phenotypically describe altered subcellular localization of the Golgi V-ATPase in Oxr1-deleted cells. A recent structural and biochemical characterization of Oxr1 as a V-ATPase disassembly factor (PMID 34918374) somewhat limits the novelty of the results, but the function of Oxr1 in regulating subcellular V-ATPase localization and the identification of a second potential TLDc domain protein in yeast provide relevant insights into V-ATPase regulation. This paper will be of interest to cell biologists and biochemists working on lysosomal biology, organelle proteomics and V-ATPase regulation.

      We thank the reviewer for the assessment of our work, and for recognizing the novel insights that we provide. Regarding the previous biochemical work on Oxr1 and the V-ATPase, we have clearly cited this work in the manuscript. In our opinion, our results complement and extend this article, showing that the function in disassembly is relevant in vivo. Additionally, this is only one of five major points of the article, the other four being

      • The interactome map of the vacuole as a resource
      • The identification of Rtc5 as a second yeast TLDc domain containing protein and interactor of the V-ATPase.
      • The identification of the role of Rtc5 in V-ATPase assembly.
      • The identification of the role of Oxr1 in Stv1 subcellular localization. We believe these additional points add important insights to researchers interested in lysosomes, the V-ATPase, intracellular trafficking and TLDc-domain containing proteins.

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

      Major comments

      __1) Re: A cross-linking mass spectrometry map of vacuolar protein interactions (results) __ While XL-MS is a very powerful method, it is a high-throughput approach and there should be some kind of negative control in these experiments. In cross-linking experiments, non-cross-linked samples are usually used as negative controls. What was the negative control in cross-linking mass-spectrometry experiments here? If there was no negative control, how the specificity of interactions was evaluated? Maybe the authors analyzed the dataset for highly improbable interactions and found very few of them?

      We fully agree that it is crucial to ensure the specificity of the interactions detected by XL-MS. To achieve this, one needs to control (1) the specificity of the data analysis (i.e. that the recorded mass spectrometry data are correctly matched to cross-linked peptides from the sequence database) and (2) the biological specificity (i.e. that the cross-linking captured natively occurring interactions).

      To ascertain that criterion (1) is met, cross-link identifications are filtered to a pre-defined false-discovery rate (FDR) – an approach that the XL-MS field adopted from mass spectrometry-based proteomics. As a result, low-confidence identifications (e.g. cross-linked peptides that are only supported by a few signals in a given mass spectrum) are removed from the dataset. FDR filtering in XL-MS is a rather complex matter as it can be done at different points during data analysis and the optimal FDR cut-off depends on the specific scientific question at hand (for more details see for example Fischer and Rappsilber, Anal Chem, 2017). Generally speaking, an overly restrictive FDR cut-off would remove a lot of correct identifications, thereby greatly limiting the sensitivity of the analysis. On the other hand, a too relaxed FDR cut-off would dilute the correct identifications with a high number of false-positives, which would impair the robustness and specificity of the dataset. While many XL-MS study control the FDR on the level of individual spectrum matches, we opted for a 2% FDR cut-off on the level of unique residue pairs, which is more stringent (see Fischer and Rappsilber, Anal Chem, 2017). Our FDR parameters are described in the Methods section (Cross-linking mass spectrometry of isolated vacuoles - Data analysis). Of note, we have made all raw mass spectrometry data publicly available through the PRIDE repository (https://www.ebi.ac.uk/pride/ ; accession code PXD046792; login details during peer review: Username = reviewer_pxd046792@ebi.ac.uk, Password = q1645lTP). This will allow other researchers to re-analyze our data with the data analysis settings of their choice in the future.

      To ascertain that criterion (2) is met, we mapped the identified cross-links onto existing high-resolution structures of vacuolar protein complexes. Taking into account the length of our cross-linking reagent, the side-chain length of the cross-linkable amino acids (i.e. lysines), and a certain degree of in-solution flexibility, cross-links can reasonably occur between lysines with a mutual Cα-Cα distance of up to 35 Å. Using this cut-off, the lysine-lysine pairs in the high-resolution structures we studied can be split into possible cross-linking partners (Cα-Cα distance 35 Å). Of all cross-links we could map onto high-resolution structures, 95.2% occurred between possible cross-linking partners. In addition, our cross-links reflect numerous known vacuolar protein interactions that have not yet been structurally characterized. These lines of evidence increase our confidence that our XL-MS approach captured genuine, natively occurring interactions. These analyses are described in more detail in the first Results sub-section (“A cross-linking mass spectrometry map of vacuolar protein interactions”).

      In addition, the high purity of vacuole preparation is critical. How was it assessed by the authors?

      We disagree that the purity of the vacuole preparation is critical for this analysis to be valid. The accuracy of the protein-protein interactions detected will depend on their preservation during sample preparation until the sample encounters the cross-linker, and the data analysis, as described above. The experiment would have been equally valid if performed on whole cell lysates without any enrichment of vacuoles, but the coverage of vacuolar proteins would have likely been very low. For this reason, we decided to use the vacuole isolation procedure to obtain better coverage of the proteins of this particular organelle. The use of the Ficoll gradient protocol (Haas, 1995) was based on that it is a protocol that yields strong enrichment of proteins annotated with the GO Term “vacuole” (Eising et al, 2019) and that it preserves the functionality of the organelle, as evidenced by its use for multiple functional assays (vacuole-vacuole fusion (Haas, 1995), autophagosome-vacuole fusion (Gao et al, 2018), polyphosphate synthesis by the VTC complex (Desfougéres et al, 2016), among others).

      2) Re: Rtc5 and Oxr1 counteract the function of the RAVE complex (results)

      Taken together, data, presented in this section of the manuscript, provide strong evidence that Rtc5 and Oxr1 negatively regulate V-ATPase activity, counteracting the V-ATPase assembly, facilitated by the activity of the RAVE complex. However, the complete deletion of the major RAVE subunit Rav1p was required to observe this effect in vivo in yeast. The other way to induce V-ATPase disassembly in yeast is glucose deprivation. It will be interesting to study if there is a synergistic effect between glucose deprivation and RTC5/OXR1 deletion on V-ATPase assembly, vacuolar pH, and growth of single oxr1Δ, rtc5Δ or double oxr1Δrtc5Δ mutants (OPTIONAL). Glucose deprivation is a more physiologically relevant condition than a deletion of an entire gene.

      We would like to point out that an effect on assembly is observed without deleting the RAVE complex: deletions of Oxr1 or Rtc5 resulted in increased V-ATPase assembly in vivo in the presence of glucose and of the RAVE complex (Figures 5 D and E). We have now also added the experiments showing that the overexpression strains have a mild growth defect under conditions that force cells to strongly rely on V-ATPase activity (Figures 6 A and C).

      Nevertheless, we agree that addressing the effect of changing the levels of Oxr1 and Rtc5 under low-glucose conditions is an interesting physiologically relevant question. We have now included growth assays and BCECF staining in medium containing galactose as the carbon source (Figures 5 – Supplement 1 B and C, and Figure 6 C and Figure 6- Supplement 1A). In addition, we have addressed the vacuolar localization of Vma5 in medium containing glucose or after shifting to medium containing galactose for 20 minutes, as a proxy for V-ATPase disassembly in intact cells (Figure 5 F and G, Figure 6 D and E). Taken together, these analyses reinforce our conclusions that both Rtc5 and Oxr1 promote an in vivo state of lower V-ATPase assembly, based on the following observations:

      • Higher localization of Vma5 to the vacuole after 20 mins in galactose in cells lacking Oxr1 or Rtc5 (Figure 5 F and G).
      • Lower localization of Vma5 to the vacuole in medium containing glucose in cells overexpressing Oxr1 or Rtc5 (Figure 6 D and E).
      • Growth defect of the strain overexpressing Oxr1 in medium containing galactose with pH = 7.5 and zinc chloride, with a further growth defect caused by additional overexpression of Rtc5 (Figure 6 C). 3) Re: Figure 6 - supplement 1. The title is relevant to panel D only, it should be renamed to reflect the results of the disassembly of V-ATPase in rav1Δ mutant strains, while results about the stv1Δ-based strains (Panel D) should be shown together with similar experiments in Figure 7 - supplement 2 for clarity.

      We have shifted the Panel D from the original Figure 6 – Supplement 1 to the main Figure (now Figure 7 – H and I). Regarding the title of the Figure, whether Supplemental Figures have titles or not will depend on the journal where the manuscript is published. For now, we have removed all titles from supplemental figures, as they are conceived to complement the main Figures.

      4) Re: Figure 7 - supplement 1, Panel A. The proper assay to show that Stv1-mNeonGreen is functional is to express it in double mutant vph1Δstv1Δ to see if the growth defect is reversed. In addition, the vph1Δ growth defect is not changed (improved or worsened) in the presence of Stv1-mNeonGreen, so it means that the expression of Stv1-mNeonGreen does not further compromise the V-ATPase function, but it does not mean that it improves its function.

      It is clear from the experiment suggested by the reviewer that they think that we have expressed Stv1-mNeonGreen from a plasmid. This was not the case, Stv1 was C-terminally tagged with mNeonGreen in the genome. It is thus the only expressed version in the strain. The experiment we have performed is thus equivalent to the one suggested by the reviewer, but for genomically expressed variants. For reference, the genotypes of all the strains used can be found in Supplemental Table 1.

      5) Re: Figure 7 - supplement 2. This figure should be combined with Fig. 6- suppl 1, panel D as also mentioned above. The figure seems to lack some labels, and conclusions are not accurate as discussed below. However, this data provides important additional information about relationships between isoform-specific subunits of V-ATPase Vph1 and Stv1 and both Rtc5 and Oxr1 and should be repeated if it is not done yet to have a better idea about these relationships.

      Panel B: Based on this picture, deletion of RTC5 has a negative genetic interaction with the deletion of VPH1, since double deletion mutant vph1Δ rtc5Δ grows worse than each individual mutant. Although it also means that there is no positive interaction, it is not the same.

      Indeed, there is a negative genetic interaction between the deletion of RTC5 and VPH1. We have replaced the growth tests in this figure (Figure 8 – Supplement 2 A in the new manuscript) to show this negative genetic interaction better. This effect is reproducible, as shown in the repetitions of the experiments.

      Panel C: Same as for panel B. Based on this picture, the deletion of OXR1 has a weak negative genetic interaction with the deletion of STV1, since double deletion mutant stv1Δ oxr1Δ grows worse than each individual mutant at 6 mM ZnCl2.

      Panel D: Same as for panels B and C. Based on this picture, deletion of RTC5 has a negative genetic interaction with the deletion of STV1, since double deletion mutant stv1Δ rtc5Δ grows worse than each individual mutant at 6 mM ZnCl2. There is no label in the middle panel (growth conditions) and no growth assay data in the presence of CaCl2.

      However, these results will be then in contradiction with the results from Figure 6 - Supplement 1, panel D, showing negative genetic interaction between the overexpression of Rtc5 or Oxr1 and deletion of Stv1, since both deletion and overexpression of Rtc5 or Oxr1 would have negative genetic interactions with Stv1.

      For both Panels C and D (Now Figure 8 - Supplement 2 B and C). The effect pointed out by the reviewer (slightly stronger growth defect for the double mutants than for the single mutants) is very mild. We have attempted to make it more evident by assessing growth in medium with higher and lower concentrations of zinc and this was not possible. This is in contrast with the very clear positive genetic interaction that we observe between the deletion of OXR1 and VPH1 (Now Figure 8 H). This is the reason that we decided to report the lack of a positive genetic interaction instead of the presence of a negative one, as we do not want to draw conclusions based on results that are borderline detectable.

      In addition, there is no label for the media in the middle panel, is it just YPAD pH=7.5, without the addition of any metals?

      Indeed, the media is YPAD pH=7.5, without the addition of any metals. The line drawn above several images based on this media indicated this. Since this form of labeling appears to be confusing, we have now replaced it and placed the label directly above the image.

      Why there is no growth assay in the presence of CaCl2, like in panels A and B?

      Every growth test shown in the manuscript was performed including growth in YPD pH=5,5 as a control of a permissive condition for lack of V-ATPase activity, and then in YPD pH=7,5 including a broad range of Zinc Chloride and Calcium chloride concentrations. From all these pictures, the conditions where the differences among strains were clearly visible were chosen to assemble the figures. Conditions that did not provide any information for that particular experiment were not included in the figure to avoid making them unnecessarily large and crowded.

      Re: Figure 7 - supplement 2, continued. How many times all these experiments were repeated? These experiments should be repeated at least 3 times, which is especially necessary for the experiments in panel C, because the effects are borderline. If results are reproducible and statistically significant, although small, the conclusion should be changed from "no positive genetic interactions" to "negative genetic interactions", which is more precise and informative.

      All growth tests shown in the manuscript were repeated at least three times for the conditions shown. We are thankful to the reviewer for pointing out that this was not mentioned, and we have added this to the methods section. We have assembled a file with all repetitions of the shown growth tests and added it at the end of this file. In doing so, these are already available for the public. These repetitions show that all effects reported are reproducible. We will then discuss with the editors of the journal where this manuscript is published about the necessity of including it with the final article.

      Regarding reporting the lack of a positive genetic interaction vs. a negative one, we have discussed this above. Shortly, for Panel B (Figure 8 – Supplement 2 A in the new manuscript) we have changed the conclusion to “negative genetic interaction” as adjusting the zinc chloride concentration allowed us to show this clearly and reproducibly, as shown by the repetitions of the experiments. For panels C and D (Now Figure 8 - Supplement 2 B and C), the effect is really mild and barely detectable, even when we tried a wide range of zinc chloride concentrations. For this reason, we would prefer to maintain the “no positive genetic interaction” conclusion.

      Re: Methods. There is no description of yeast serial dilution growth assay at all. In addition, why the specific media (neutral pH, in the presence of high concentrations of calcium or zinc) was used is not explained either in the results or methods. Appropriate references should be included, for example, PMID: 2139726, PMID: 1491236.

      We apologize for the oversight of the missing methods section, which we have now included.

      Regarding the explanation of the media used, the following section was already a part of the results section, before the description of the first growth test:

      “The V-ATPase is not essential for viability in yeast cells, and mutants lacking subunits of this complex grow similarly to a wt strain in acidic media. However, when cells grow at near-neutral pH or in the presence of divalent cations such as calcium and zinc, the mutants lacking V-ATPase function show a strong growth impairment (Kane et al, 2006).”

      We have now replaced this with the following, more complete version:

      “As a first approach for addressing the role of these proteins, we tested growth phenotypes related to V-ATPase function in strains lacking or overexpressing them. The V-ATPase is not essential for viability in yeast cells, and mutants lacking subunits of this complex grow similarly to a wt strain in acidic media, but display a growth defect at near-neutral pH the mutants (Nelson & Nelson, 1990). In addition, the proton gradient across the vacuole membrane generated by the V-ATPase energizes the pumping of metals into the vacuole, as a mechanism of detoxification. Thus, increasing concentrations of divalent cations such as calcium and zinc, generate conditions in which growth is increasingly reliant on V-ATPase activity (Förster & Kane, 2000; MacDiarmid et al, 2002; Kane, 2006).”


      MINOR COMMENTS

      Yeast proteins are named with "p" at the end, such as "Rtc5p".

      This nomenclature rule is falling into disuse during the last decades, as the use of capitals vs lowercase and italics allows to distinguish between genes proteins and strains (OXR1 = gene, Oxr1 = protein, oxr1Δ = strain). As an example, I include a list of the latest papers by some of the major yeast labs around the world, all of which use the same nomenclature as we do (in alphabetical order). This list even includes some work in the field of the V-ATPase.

      • Alexey Merz, USA. PMID: 33225520
      • Benoit Kornmann, UK. PMID: 35654841
      • Christian Ungermann, Germany. PMID: 37463208
      • Claudio de Virgilio, Switzerland. PMID: 36749016
      • Daniel E. Gottschling, USA. PMID: 37640943
      • David Teis, Austria. PMID: 32744498
      • Elizabeth Conibear, Canada. PMID: 35938928
      • Fulvio Reggiori, Denmark. PMID: 37060997
      • J Christopher Fromme, USA. PMID: 37672345
      • Maya Schuldiner, Israel. PMID: 37073826
      • Patricia Kane, USA. PMID: 36598799
      • Scott Emr, USA. PMID: 35770973
      • W Mike Henne, USA. PMID: 37889293
      • Yoshinori Ohsumi, Japan. PMID: 37917025 In addition, we would prefer to keep the nomenclature that we already use, to keep consistency with other published articles from our lab.

      Re: Introduction. In the introduction it should be indicated that Rtc5 was originally discovered as a "restriction of telomere capping 5", using screening of temperature-sensitive cdc13-1 mutants combined with the yeast gene deletion collection [PMID: 18845848]. A couple of sentences should be written about the RAVE complex and its role in V-ATPase assembly.

      We are thankful for this suggestion and we have now included both pieces of information in the introduction.

      *“The re-assembly of the V1 onto the VO complex when glucose becomes again available, is aided by a dedicated chaperone complex known as the RAVE complex, which also likely has a general role in V-ATPase assembly (Seol et al, 2001; Smardon et al, 2002, 2014).” *

      “In our cross-linking mass spectrometry interactome map of isolated vacuoles we found that the only other TLDc-domain containing protein of yeast, Rtc5, is a novel interactor of the V-ATPase. Rtc5 is a protein of unknown function, originally described in a genetic screen for genes related to telomere capping (Addinall et al, 2008)”

      Re: The TLDc domain-containing protein of unknown function Rtc5 is a novel interactor of the vacuolar V-ATPase (results)

      1) It is important to understand, that Oxr1 was co-purified before with the V1 domain of V-ATPase from a certain mutant strain, not wild-type yeast [PMID: 34918374]. It may explain why the authors did not identify it in their original protein-protein interactions screen here.

      The structural work on the V1 domain bound to Oxr1 (Khan et al, 2022) showed that the binding of Oxr1 prevented V1 from assembling onto the Vo. Since our experiments rely on the purification of vacuoles, they should contain mainly only V1 assembled onto the VO, and not the free soluble V1. This is likely the reason that we do not detect Oxr1, in addition to it being less abundant. We have clarified this now in the manuscript and added the fact that Oxr1 was co-purified with a V1 containing a mutant version of the H subunit.

      “In a previous study, Oxr1 was co-purified with a V1 domain containing a mutant version of the H subunit, and its presence prevented the in vitro assembly of this V1 domain onto the VO domain and promoted disassembly of the holocomplex (Khan et al., 2022). This is likely the reason why we do not detect Oxr1 in our experiments, which rely on isolated vacuoles and thus would only include V1 domains that are assembled onto the membrane. In addition, Oxr1 is less abundant in yeast cells than Rtc5 according to the protein abundance database PaxDb (Wang et al, 2015).”

      2) It is a wrong conclusion that because Rtc5 was co-purified with both V1 and V0 domain subunits it interacts with the assembled V-ATPase, this does not exclude a possibility that Rtc5 also interacts with separate V1 sector or separate V0 sector of V-ATPase.

      We agree with the reviewer that the co-purification of Rtc5 with both V1 and VO domain subunits does not necessarily mean that it interacts with the assembled V-ATPase. Thus, we have modified the text in this part to:

      “The fact that we can co-enrich Rtc5 both with Vma2 and with Vph1 indicates that it can interact either with both the VO and V1 domains or with the assembled V-ATPase.”

      However, other results throughout the manuscript can be taken into account to strengthen this idea:

      1. Rtc5 requires an assembled V-ATPase to localize to the vacuole membrane, and thus seems not to interact with free VO domains, which would be available when we delete V1 subunits or in medium containing galactose.
      2. Rtc5 becomes cytosolic in galactose-containing media. This would indicate that it also does not interact with free V1 domains, which are still localized to the vacuole membrane under these conditions. Taken together with the pull-downs, these results suggest that Rtc5 interacts with the assembled V1-VO V-ATPase. Thus, we have included the following sentence after Figure 3, which shows the subcellular localization experiments.

      *“Taking into account that Rtc5 is co-enriched with subunits of both the VO and V1 domain, and that it localizes at the vacuole membrane dependent on an assembled V-ATPase, we suggest that Rtc5 interacts with the assembled V-ATPase complex.” *

      Re: Figure 1, Panel C. Is it possible to show individual proteins in different colors for clarity?

      Panel D. How were cross-link distances measured? It is not obvious if you are not an expert in the field and it is not described in the methods.

      We have modified Figure 1 C and Figure 1 – Supplement 1B (now Figure 1 – Supplement 1 A) to present the different subunits in the structures with different shades of blue and grey.

      Furthermore, we have clarified the distance measurement approach in the methods section and in the legend of Fig 1D: “Ca-Ca distances were determined using the measuring function in Pymol v.2.5.2 (Schrodinger LLC).”

      __Re: Figure 1 - Supplement 1, __

      Panel A. What scientific information are we getting from this picture?

      This panel was just a visual representation of the complexity of the protein network we obtained. Indeed, there was no specific scientific message, so we have decided to remove this panel from the revised manuscript.

      Panel B. Why are these complexes shown separately from the complexes in Figure 1, panel C? Also, can individual proteins be colored differently here as well?

      We did not want to overload Fig 1C, so we decided to show some of the protein complexes in Fig 1 – Supplement 1B. The most important information is the histogram showing that 95% of the mapped cross-links fall within the expected length range, and this is shown in the main Figure (Figure 1D). As stated above, we have adjusted the subunit coloring in Figure 1 C to improve clarity.

      Re: Figure 3. It will be nice to show the localization of the untagged protein as well if antibodies are available (OPTIONAL).

      Unfortunately, there are no available antibodies for either Rtc5 or Oxr1. This hinders us from detecting the endogenous untagged proteins. We would like to point out that we have been very careful in showing which tagged proteins are functional (C-terminally tagged Rtc5) and which are not (C-terminally tagged Oxr1), so that the reader can know how to interpret the localization data.

      Re: Figure 4. Why different tags were used in panels A (GFP), C (msGFP2) and D

      (mNeonGreen)?

      In general, we prefer to use mNeonGreen as a tag for microscopy experiments because it is brighter and more stable, and msGFP2 as a tag for experiments involving Western blots because we have better antibodies available. There was a mistake in the labeling, and actually, all constructs labeled as GFP were msGFP2. We have now corrected this. Of note, we have tested the functionality of both tagged version (mNeonGreen and msGFP2).

      Panels B and C. Were Rtc5 fusions detected using anti-GFP antibodies?

      Indeed, Rtc5-msGFP2 was detected with an anti-GFP antibody. We have now indicated next to each Western blot membrane the primary antibody used. In addition, all antibodies are detailed in Supplemental Figure 3.

      The authors should have full-size Western blots available, not just cut-out bands, as some journals and reviewers require them for publication.

      For all western blots, we always showed a good portion of the membrane and not cut-out bands. The cropping was performed to avoid making figures unnecessarily large. The whole membranes are of course available and will be included in an “extended data file” if required by the journal.

      Re: Figure 4 - Supplement 1, Panel A. Does "-" and "+" mean -/+ Azido-Myr?

      Indeed. We have now added this label to the figure.

      Panel B. There is no blot with a membrane protein marker (Vam3 or Vac8), it should be included.

      We have replaced this western blot for a different repetition of this experiment in which a membrane protein marker was included. Of note, the two other repetitions of the experiment shown (Figure 4 – Supplement 1 panel C and Figure 4 panel C) also include both a membrane protein marker and a soluble protein marker.

      Re: Figure 5. The title does not describe all results in this figure and should be modified accordingly.

      The original data from Figure 5 is now separated into Figures 5 and 6 because of the additional experiments included during revisions. We have modified the Figure titles to be descriptive of the overall message of the Figures.

      Panel C. Statistical significance value for *** should be indicated in the legend.

      This has been indicated in the Figure legend.

      It is not clear how many times yeast growth assays were repeated. Usually, all experiments should be done in triplicates or more.

      All shown growth tests were performed at least three times for the conditions shown. We have now indicated this in the materials and methods section. In addition, we now provide in this response a file with all repetitions of growth tests, which will be appended to the article if deemed necessary by the editors.

      Re: Figure 5 - supplement 1. No title

      Re: Figure 5 - supplement 2. No title

      Whether the supplemental Figures should have a title or not will depend on the style of the journal where the manuscript is finally published. The current idea of the supplemental Figures is that they complement the corresponding main Figure. For this reason, we have removed all titles from supplemental Figures.

      Re: Figure 6. There is a typo on the second lane in the legend: "...the genome were", not "...the genome where".

      This has been corrected.

      Panel C. Why the analysis of BCECF vacuole staining of double mutants oxr1Δrav1Δ and rtc5Δrav1Δ is not shown? Was it done at all?

      We had not included this piece of data, as we thought that the genetic interaction of RTC5 and OXR1 and rav1Δ was sufficiently well supported with the included data (growth tests in combination with the deletion, growth tests in combination with the overexpression, vacuole proteomics in combination with overexpression, and BCECF staining in combination with the overexpression). Because of the request of the reviewer, we have now included this experiment as Figure 7 G.

      Re: Figure 6 - Supplement 2. Why were two different tags (2xmNG and msGFP2) used?

      We tried both tags to see if one of them would be functional. Unfortunately, they both resulted in non-functional proteins, as shown by the corresponding growth tests.

      Did the authors study N-terminally tagged Oxr1? Was it functional?

      We have tagged Oxr1 N-terminally, and this unfortunately resulted in a protein that was not completely functional. We show below the localization of N-terminally mNeon-tagged Oxr1, under the control of the TEF1 promoter. The protein appears cytosolic (Panel A) but is not completely functional (Panel B). The localization of Oxr1 had already been misreported by using a tagged version that we now show to be non-functional. For this reason, we preferred not to include this data in the manuscript, to avoid again including in the literature subcellular localizations that correspond to non-functional or partially functional proteins.

      Panel B. Results for the untagged TEF1pr-Oxr1 overexpression are not shown, thus tagged and untagged proteins can't be compared. Are they available? What is the promoter for the expression of 2xmNG fusion constructs?

      Oxr1-2xmNG was C-terminally tagged in the genome, which means that the promoter is the endogenous one, it was not modified. For this reason, the correct controls are a strain expressing Oxr1 at endogenous levels (the wt strain) and a strain lacking Oxr1. Both controls were included in the Figure, and in all repetitions made of this experiment. For reference, all the genotypes of the strains used are found in Supplemental Table 1.

      Re: Methods. Were vacuoles prepared differently for XL-MS and SILAC-based vacuole proteomics (there are different references) and why? Methods for XL-MS and quantitative SILAC-based proteomics can be placed together for clarity.

      The basis for the method of vacuole purification is the same, from (Haas, 1995). This reference was included in both protocols that include vacuole purifications. However, modifications of this method were performed to fit the crosslinking method (higher pH, no primary amines) or to fit the SILAC labeling (combination of two differentially labeled samples in one purification). The reference for the vacuole proteomics (Eising et al 2022) corresponds to a paper in which the SILAC-based comparison of vacuoles from different mutant strains was optimized, and includes not only the vacuole purification but the growth conditions and downstream processing of the vacuoles.

      Since both the SILAC-based vacuole proteomics and the XL-MS are multi-step methods, containing numerous parameters including the sample preparation, processing for MS, MS run and data analysis, we would prefer to keep them separate. We think this would allow a person attempting to reproduce these methods to go through them step by step.

      What is CMAC dye? Why was it used to stain the vacuolar lumen?

      We apologize for this oversight, we have included the definition of CMAC as 7-Amino-4-Chlormethylcumarin. It is a standard-used organelle marker for the lumen of the vacuole.

      Some abbreviations (TEAB, ACN) are not explained.

      We apologize for this oversight. We have now replaced these abbreviations with the full names of the compounds in the article.

      What is 0% Ficoll?

      We used the term 0% Ficoll, because this is the name given to the buffer in the original Haas 1995 paper on vacuole purifications. However, we agree that the term is misleading and we have now added the composition of the buffer (10 mM PIPES/KOH pH=6.8, 0.2 M Sorbitol).

      Reviewer #3 (Significance (Required)):

      The vacuolar-type proton ATPase, V-ATPase, is the key proton pump, that hydrolases ATP and uses this energy to pump protons across membranes. Amazingly, this proton pump and its function are conserved in eukaryotes from yeast to mammals. While V-ATPase structure and function have been studied for more than 30 years in various organisms, its regulation is not completely understood. The very recent discoveries of two new V-ATPase interacting proteins in yeast, first Oxr1 (OXidative Resistance 1), and now Rtc5 (Restriction of Telomere Capping 5), both the only two members of TLDc (The Tre2/Bub2/Cdc16 (TBC), lysin motif (LysM), domain catalytic) proteins in yeast, provide new insights in V-ATPase regulation in yeast, and because the interaction is conserved in mammals its relevance to mammalian V-ATPases regulation as well.

      TLDc proteins are best known for their role in protection from oxidative stress, in particular in yeast and in the nervous system in mammals. The discovery of the novel Rtc5-V-ATPase interaction points to the role of V-ATPase not only in protection from oxidative stress but also in restriction of telomere capping in yeast and most likely higher species. The studies of other species also highlight the possible conserved role of V-ATPase in lifespan determination and Torc1 signaling, mediated through these interactions. Thus, the discovery of this new functionally important interaction between the second TLDc family member in yeast, Rtc5, and V-ATPase will shed light on the molecular mechanisms of all these essential biological processes and pathways.

      In addition, because the authors performed a comprehensive proteomics protein-protein interaction study of the purified yeast vacuole it provides a valuable resource for all researchers who study vacuoles and/or related to them lysosomes.

      The follow-up functional studies using the rav1Δ strain clearly demonstrated that Rtc5 and Oxr1 disassemble V-ATPase and counteract the function of V-ATPase assembly RAVE complex in vivo in yeast. Thus, they are essentially the first discovered endogenous eukaryotic protein inhibitors of V-ATPase. Moreover, because the authors obtained the evidence that Oxr1 is the regulator of the specific subunit isoform of V-ATPase Stv1p in vivo in yeast, it suggests that different TLDc proteins may regulate different specific V-ATPase subunit isoforms in cell- and tissue-specific manner in higher eukaryotes. The mechanism of this isoform-specific regulation in yeast and other species needs further investigation in the future.

      Because of the conservation of the TLDc-V-ATPase interactions, all this information can be extrapolated to higher species, all the way to humans, in whom genetic mutations in various TLDc proteins are known to cause devastating diseases and syndromes.

      We are thankful to the reviewer for their positive comments about the significance of our work.

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      Referee #3

      Evidence, reproducibility and clarity

      Summary

      In this manuscript, the authors used a proteomics approach to comprehensively study yeast vacuole protein-protein interactions using cross-linking mass-spectrometry (XL-MS). They identified 16694 interactions between 2051 proteins. Many known vacuolar protein complexes were found and used as positive controls, confirming the high quality of the dataset, however, no negative controls were reported, and this issue is raised in the 'Major comments' section. The authors then focused on one particular previously unknown protein-protein interaction between the TLDc-domain containing protein of unknown function Rtc5 and the vacuolar-type proton ATPase, V-ATPase, which acidifies yeast vacuoles. The methods and results regarding Rtc5 discovery as a novel interactor of the V-ATPase, Rtc5 myristoylation, and its V-ATPase-dependent localization to the vacuole membrane are convincing. The authors then moved on to study the in vivo function of Rtc5 as well as Oxr1, the only other TLDc-domain-containing protein in yeast. Interestingly, they did not originally detect Oxr1 in their protein-protein interaction studies, apparently due to its very low abundance in yeast. However, they found that deletion of either RTC5 or OXR1 in vivo resulted in more assembled V-ATPase at the yeast vacuole and this effect was stronger in oxr1Δ cells. However, RTC5/OXR1 deletion or overexpression in parental yeast strains did not affect either vacuolar pH (a readout of functional V-ATPase) or yeast growth, including growth under specific conditions (neutral pH, in the presence of high concentrations of calcium or zinc), which is used to reveal a conditional lethal phenotype of unfunctional V-ATPase (the Vma− phenotype). Since they did not observe any in vivo phenotype in parental yeast strains, they subsequently studied the effects of RTC5/OXR1 deletion and overexpression in the 'sensitized' rav1Δ strain, lacking a specific assembly factor of V-ATPase, Rav1, one of the subunits of RAVE complex. In this strain, RTC5/OXR1 overexpression resulted in less acidic vacuolar pH and reduced growth of double mutant cells, compared to the single rav1Δ mutant. In addition, overexpression of Oxr1, but not Rtc5, caused disassembly of the V-ATPase in rav1Δ cells, noteworthy this effect was not detectable in the parent strain with intact Rav1p. Finally, they found that in oxr1Δ cells there is more Stv1 in the vacuole and concluded that Oxr1 is necessary for the retention of Stv1 containing V-ATPase at the vacuole. However, the mechanism seems to be complicated and remains to be elucidated. In summary, an impressive variety of methods from a technologically advanced XL-MS to classical yeast growth assays were used to identify Rtc5 interaction with V-ATPase and analyze its functional role in vivo in yeast, making the conclusions well justified overall.


      Major comments

      Re: A cross-linking mass spectrometry map of vacuolar protein interactions (results)

      While XL-MS is a very powerful method, it is a high-throughput approach and there should be some kind of negative control in these experiments. In cross-linking experiments, non-cross-linked samples are usually used as negative controls. What was the negative control in cross-linking mass-spectrometry experiments here? If there was no negative control, how the specificity of interactions was evaluated? Maybe the authors analyzed the dataset for highly improbable interactions and found very few of them? In addition, the high purity of vacuole preparation is critical. How was it assessed by the authors? All this is important to know to use this dataset as a reliable resource in the future.

      Re: Rtc5 and Oxr1 counteract the function of the RAVE complex (results)

      Taken together, data, presented in this section of the manuscript, provide strong evidence that Rtc5 and Oxr1 negatively regulate V-ATPase activity, counteracting the V-ATPase assembly, facilitated by the activity of the RAVE complex. However, the complete deletion of the major RAVE subunit Rav1p was required to observe this effect in vivo in yeast. The other way to induce V-ATPase disassembly in yeast is glucose deprivation. It will be interesting to study if there is a synergistic effect between glucose deprivation and RTC5/OXR1 deletion on V-ATPase assembly, vacuolar pH, and growth of single oxr1Δ, rtc5Δ or double oxr1Δrtc5Δ mutants (OPTIONAL). Glucose deprivation is a more physiologically relevant condition than a deletion of an entire gene.

      Re: Figure 6 - supplement 1. The title is relevant to panel D only, it should be renamed to reflect the results of the disassembly of V-ATPase in rav1Δ mutant strains, while results about the stv1Δ-based strains (Panel D) should be shown together with similar experiments in Figure 7 - supplement 2 for clarity.

      Re: Figure 7 - supplement 1, Panel A. The proper assay to show that Stv1-mNeonGreen is functional is to express it in double mutant vph1Δstv1Δ to see if the growth defect is reversed. In addition, the vph1Δ growth defect is not changed (improved or worsened) in the presence of Stv1-mNeonGreen, so it means that the expression of Stv1-mNeonGreen does not further compromise the V-ATPase function, but it does not mean that it improves its function.

      Re: Figure 7 - supplement 2. This figure should be combined with Fig. 6- suppl 1, panel D as also mentioned above. The figure seems to lack some labels, and conclusions are not accurate as discussed below. However, this data provides important additional information about relationships between isoform-specific subunits of V-ATPase Vph1 and Stv1 and both Rtc5 and Oxr1 and should be repeated if it is not done yet to have a better idea about these relationships. Panel B: Based on this picture, deletion of RTC5 has a negative genetic interaction with the deletion of VPH1, since double deletion mutant vph1Δ rtc5Δ grows worse than each individual mutant. Although it also means that there is no positive interaction, it is not the same. Panel C: Same as for panel B. Based on this picture, the deletion of OXR1 has a weak negative genetic interaction with the deletion of STV1, since double deletion mutant stv1Δ oxr1Δ grows worse than each individual mutant at 6 mM ZnCl2. In addition, there is no label for the media in the middle panel, is it just YPAD pH=7.5, without the addition of any metals? Why there is no growth assay in the presence of CaCl2, like in panels A and B? Panel D: Same as for panels B and C. Based on this picture, deletion of RTC5 has a negative genetic interaction with the deletion of STV1, since double deletion mutant stv1Δ rtc5Δ grows worse than each individual mutant at 6 mM ZnCl2. There is no label in the middle panel (growth conditions) and no growth assay data in the presence of CaCl2.

      Re: Figure 7 - supplement 2, continued. How many times all these experiments were repeated? These experiments should be repeated at least 3 times, which is especially necessary for the experiments in panel C, because the effects are borderline. If results are reproducible and statistically significant, although small, the conclusion should be changed from "no positive genetic interactions" to "negative genetic interactions", which is more precise and informative. However, these results will be then in contradiction with the results from Figure 6 - Supplement 1, panel D, showing negative genetic interaction between the overexpression of Rtc5 or Oxr1 and deletion of Stv1, since both deletion and overexpression of Rtc5 or Oxr1 would have negative genetic interactions with Stv1. In addition, apparently, there is no data about genetic interaction between the overexpression of Rtc5 or Oxr1 and the deletion of Vph1. All this needs clarification, therefore repeating these experiments is essential. In conclusion, while genetic interactions between RTC5/OXR1 and RAV1 are straightforward, they seem to be more complex with STV1/VPH1.

      Re: Methods. There is no description of yeast serial dilution growth assay at all. In addition, why the specific media (neutral pH, in the presence of high concentrations of calcium or zinc) was used is not explained either in the results or methods. Appropriate references should be included, for example, PMID: 2139726, PMID: 1491236.

      Minor comments

      Yeast proteins are named with "p" at the end, such as "Rtc5p".

      Re: Introduction. In the introduction it should be indicated that Rtc5 was originally discovered as a "restriction of telomere capping 5", using screening of temperature-sensitive cdc13-1 mutants combined with the yeast gene deletion collection [PMID: 18845848]. A couple of sentences should be written about the RAVE complex and its role in V-ATPase assembly.

      Re: The TLDc domain-containing protein of unknown function Rtc5 is a novel interactor of the vacuolar V-ATPase (results) 1) It is important to understand, that Oxr1 was co-purified before with the V1 domain of V-ATPase from a certain mutant strain, not wild-type yeast [PMID: 34918374]. It may explain why the authors did not identify it in their original protein-protein interactions screen here. 2) It is a wrong conclusion that because Rtc5 was co-purified with both V1 and V0 domain subunits it interacts with the assembled V-ATPase, this does not exclude a possibility that Rtc5 also interacts with separate V1 sector or separate V0 sector of V-ATPase.

      Re: Figure 1, Panel C. Is it possible to show individual proteins in different colors for clarity? Panel D. How were cross-link distances measured? It is not obvious if you are not an expert in the field and it is not described in the methods.

      Re: Figure 1 - Supplement 1, Panel A. What scientific information are we getting from this picture? Panel B. Why are these complexes shown separately from the complexes in Figure 1, panel C? Also, can individual proteins be colored differently here as well?

      Re: Figure 3. It will be nice to show the localization of the untagged protein as well if antibodies are available (OPTIONAL).

      Re: Figure 4. Why different tags were used in panels A (GFP), C (msGFP2) and D (mNeonGreen)? Panels B and C. Were Rtc5 fusions detected using anti-GFP antibodies? The authors should have full-size Western blots available, not just cut-out bands, as some journals and reviewers require them for publication.

      Re: Figure 4 - Supplement 1, Panel A. Does "-" and "+" mean -/+ Azido-Myr? Panel B. There is no blot with a membrane protein marker (Vam3 or Vac8), it should be included.

      Re: Figure 5. The title does not describe all results in this figure and should be modified accordingly. Panel C. Statistical significance value for *** should be indicated in the legend. It is not clear how many times yeast growth assays were repeated. Usually, all experiments should be done in triplicates or more.

      Re: Figure 5 - supplement 1. No title

      Re: Figure 5 - supplement 2. No title

      Re: Figure 6. There is a typo on the second lane in the legend: "...the genome were", not "...the genome where". Panel C. Why the analysis of BCECF vacuole staining of double mutants oxr1Δrav1Δ and rtc5Δrav1Δ is not shown? Was it done at all?

      Re: Figure 6 - Supplement 2. Why were two different tags (2xmNG and msGFP2) used? Did the authors study N-terminally tagged Oxr1? Was it functional? Panel B. Results for the untagged TEF1pr-Oxr1 overexpression are not shown, thus tagged and untagged proteins can't be compared. Are they available? What is the promoter for the expression of 2xmNG fusion constructs?

      Re: Methods. Were vacuoles prepared differently for XL-MS and SILAC-based vacuole proteomics (there are different references) and why? Methods for XL-MS and quantitative SILAC-based proteomics can be placed together for clarity. What is CMAC dye? Why was it used to stain the vacuolar lumen? Some abbreviations (TEAB, ACN) are not explained. What is 0% Ficoll?

      Referees cross-commenting

      I agree with both reviewers, although I think that it is a pretty novel finding because while I was familiar with Oxr1 data I did not realize until now that there is a second protein in yeast. I think it is because homology between Oxr1 and Rtc5 is really low. I also agree that they should study more about what happens with V0 subunits.

      Significance

      Field of expertise keywords:

      Protein-protein interactions, V-ATPase, TLDc

      The vacuolar-type proton ATPase, V-ATPase, is the key proton pump, that hydrolases ATP and uses this energy to pump protons across membranes. Amazingly, this proton pump and its function are conserved in eukaryotes from yeast to mammals. While V-ATPase structure and function have been studied for more than 30 years in various organisms, its regulation is not completely understood. The very recent discoveries of two new V-ATPase interacting proteins in yeast, first Oxr1 (OXidative Resistance 1), and now Rtc5 (Restriction of Telomere Capping 5), both the only two members of TLDc (The Tre2/Bub2/Cdc16 (TBC), lysin motif (LysM), domain catalytic) proteins in yeast, provide new insights in V-ATPase regulation in yeast, and because the interaction is conserved in mammals its relevance to mammalian V-ATPases regulation as well.

      TLDc proteins are best known for their role in protection from oxidative stress, in particular in yeast and in the nervous system in mammals. The discovery of the novel Rtc5-V-ATPase interaction points to the role of V-ATPase not only in protection from oxidative stress but also in restriction of telomere capping in yeast and most likely higher species. The studies of other species also highlight the possible conserved role of V-ATPase in lifespan determination and Torc1 signaling, mediated through these interactions. Thus, the discovery of this new functionally important interaction between the second TLDc family member in yeast, Rtc5, and V-ATPase will shed light on the molecular mechanisms of all these essential biological processes and pathways.

      In addition, because the authors performed a comprehensive proteomics protein-protein interaction study of the purified yeast vacuole it provides a valuable resource for all researchers who study vacuoles and/or related to them lysosomes.

      The follow-up functional studies using the rav1Δ strain clearly demonstrated that Rtc5 and Oxr1 disassemble V-ATPase and counteract the function of V-ATPase assembly RAVE complex in vivo in yeast. Thus, they are essentially the first discovered endogenous eukaryotic protein inhibitors of V-ATPase. Moreover, because the authors obtained the evidence that Oxr1 is the regulator of the specific subunit isoform of V-ATPase Stv1p in vivo in yeast, it suggests that different TLDc proteins may regulate different specific V-ATPase subunit isoforms in cell- and tissue-specific manner in higher eukaryotes. The mechanism of this isoform-specific regulation in yeast and other species needs further investigation in the future.

      Because of the conservation of the TLDc-V-ATPase interactions, all this information can be extrapolated to higher species, all the way to humans, in whom genetic mutations in various TLDc proteins are known to cause devastating diseases and syndromes.

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      Referee #2

      Evidence, reproducibility and clarity

      Using cross-linking proteomics, Klössel et al. identify the yeast TLDc domain protein Rtc5 as a novel interactor of yeast V-ATPase and characterize functions for Rtc5 and the TLDc domain protein Oxr1 in V-ATPase assembly and localization.

      Major points:

      1. The evidence of Oxr1 and Rtc5 as V-ATPase disassembly factors is circumstantial. The authors base their interpretation primarily on increased V1 (but not Vo) at purified vacuoles from Oxr1- or Rtc5-deleted strains, which does not directly address disassembly. Of course, the results regarding Oxr1 confirm detailed disassembly experiments with the purified protein complex (PMID 34918374), but on their own are open to other interpretations, e.g. suppression of V-ATPase assembly. Of note, the authors emphasize that they provide first evidence of the in vivo role of Oxr1, but monitor V1 recruitment with purified vacuoles and do not follow V-ATPase assembly in intact cells.
      2. Oxr1 and Rtc5 have very low sequence similarity. It would be helpful if the authors provided more detail on the predicted structure of the putative TLDc domain of Rtc5 and its relationship to the V-ATPase - Oxr1 structure. Is Rtc5 more closely related to established TLDc domain proteins in other organisms?
      3. The authors conclude vacuolar recruitment of Rtc5 depends on the assembled V-ATPase, based on deletion of different V1 and Vo domain subunits. However, these genetic manipulations likely cause a strong perturbation of vacuolar acidification; indeed, the images show drastically altered vacuolar morphology. To strengthen their conclusion, it would be helpful to show that Rtc5 recruitment is not blocked by inhibition of vacuolar acidification, and that conversely it is blocked by deletion of rav1.

      Significance

      This is an interesting paper that confirms and extends previous findings on TLDc domain proteins as a novel class of proteins that interact with and regulate the V-ATPase in eukaryotes. The title seems to exaggerate the findings a bit, as the authors do not investigate V-ATPase (dis)assembly directly and only phenotypically describe altered subcellular localization of the Golgi V-ATPase in Oxr1-deleted cells. A recent structural and biochemical characterization of Oxr1 as a V-ATPase disassembly factor (PMID 34918374) somewhat limits the novelty of the results, but the function of Oxr1 in regulating subcellular V-ATPase localization and the identification of a second potential TLDc domain protein in yeast provide relevant insights into V-ATPase regulation. This paper will be of interest to cell biologists and biochemists working on lysosomal biology, organelle proteomics and V-ATPase regulation.

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      Referee #1

      Evidence, reproducibility and clarity

      Klössel et al. explore the role of the TLDc domain-containing proteins Oxr1p and Rtc5p in Saccharomyces cerevisiae. They performed cross-linking mass spectrometry and detected the interaction of Rtc5p with V-ATPase. TLDc domains have previously been found to serve as V-ATPase interacting domains. The authors find that both Oxr1p and Rtc5p induce dissociation of V-ATPase in vivo, an activity that was previously established for Oxr1p in vitro. They propose that this activity counteracts the activity of the V-ATPase assembling RAVE complex. They also find that Oxr1p is necessary for late Golgi retention of the Golgi form of the V-ATPase (i.e. containing the Stv1p isoform of subunit a). It is a little surprising that Oxr1p binding to V-ATPase was not detected by the cross-linking mass spectrometry, although the authors argue that this absence may be owing to the abundance of the proteins, which sounds reasonable.

      Suggestions:

      1. The authors observed that knockout of Rtc5p or Oxr1p does not affect vacuolar pH. If Rtc5p and Oxr1p both cooperate to dissociate V-ATPase, the authors may wish to characterize the effect of a ∆Rtc5p∆Oxr1p double knockout on vacuolar pH.
      2. The manusript would benefit from a well-labelled diagram showing the subunits of V-ATPase (e.g. in Figure 2D).
      3. The images of structures, especially in Figure 1-Supplement 1B, are not particularly clear and could be improved (e.g. by removing shadows or using transparency).
      4. The authors should clearly describe the differences between Rtc5p and Oxr1p in terms of protein length, sequence identity, domain structure, etc.

      Minor:

      1. The "O" in VO should be capitalized.
      2. In Figure 4 supplement 1, the labels "I", "S", and "P" should be defined.
      3. Please clarify what is meant by "switched labelling"
      4. The meaning of the sentence "Indeed, this was the case for both of them" is ambiguous.
      5. For Figure 1-Supplement 1B it is hard to see the crosslink distances.
      6. The statement "The effects of Oxr1 are greater than those caused by Rtc5" requires more context. Is there a way of quantifying this effect for the reader?
      7. The phrase "negative genetic interaction" should be clarified.
      8. In the sentence "Isogenic strains with the indicated modifications in the genome where spotted as serial dilutions in media with pH=5.5, pH=7.5 or pH=7.5 and containing 3 mM ZnCl2", "where" should be "were".
      9. Figure 2D: the authors should consider re-coloring these models, as it is challenging to distinguish Rtc5p from the V-ATPase.

      Significance

      The vacuolar protein interaction map alone from this manuscript is a nice contribution to the literature. Experiments establishing colocalization of Rtc5p to the vacuole are convincing, as is dependence of this association on the presence of assembled V-ATPase. Similarly, experiments related to myristoylation are convincing. The observed mislocalization of V-ATPases that contain Stv1p to the vacuole (which is also known to occur when Vph1p has been knocked out) upon knockout of Oxr1p is also extremely interesting.

      Overall, this is an interesting manuscript that contributes to our understand of TLDc proteins.

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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

      In this manuscript, Grossmann et al. present a new potential pathway that regulates PLK4 levels in cells mediated by the CRL4^DCAF1 E3 ubiquitin ligase complex (CUL4A/B-DDB1-DCAF1). PLK4 plays a crucial role in centriole assembly acting as a master regulator of the centriole biogenesis and thus contributes to centriole number control. Centriole numbers need to be tightly regulated as deviations could lead to aneuploidy and potentially cancer. At the onset of centriole assembly in G1/S, PLK4 is focusing into a single point on each parental centriole together with STIL and SAS6 defining the site of procentriole formation. For this process to happen, PLK4 trans-phosphorylates itself creating a binding site for SCF^β-TrCP E3 ubiquitin ligase that targets PLK4 for ubiquitination and degradation by the proteasome. The authors identified by co-IP and mass spectrometry the CRL4DCAF1 E3 ubiquitin ligase complex as a potential regulator of PLK4. They show that CRL4^DCAF1 E3 ubiquitin ligase complex binds to PLK4 and targets it for degradation. Furthermore, the authors present data where knockdown of DCAF1 leads to increased levels of PLK4 and centriole amplification. Using AlphaFold and followed by IPs with PLK4 point-mutants, they propose that DCAF1 binds to the dimer of PLK4 at PB1-PB2 at a similar site where Cep192/Cep152 bind. Then, they move on to show that CRL4^DCAF1 E3 ubiquitin ligase complex ubiquitylates PLK4 predominantly in G2 phase. Lastly, they propose that DCAF1 regulates the interaction of PLK4 with STIL and that it is required to prevent premature centriole disengagement in G2 phase. The manuscript is written in a clear and concise manner while the experimental approaches are sound and well described. The experimental data are well presented with a good number of replicates in most cases. However, some of the conclusions are drawn from marginal differences in the data and without statistical tests (cases indicated in detail below). I believe that this work is of interest to the scientific community, but it would require revisions to address the following major and minor comments.

      Major comments:

      • The key finding of the paper is that PLK4 co-IPs with DCAF1 and DDB1 that are core components of CUL4A/B E3 ubiquitin ligase. However, the only evidence that this interaction between PLK4 and DCAF1 is direct relies on the ubiquitylation assay performed in E. coli. This experiment was performed only once, and no quantitation is performed (Fig 4A). Given that the components are overexpressed in this heterologous system, it is very plausible to have a non-specific interaction between the DCAF1-Acidic domain and PLK4-PB1-PB2 considering that native binders to this region (Cep192/Cep152) are absent. The PLK4-DCAF1 model that was generated with AlphaFold suggests that this interaction is plausible but stronger verification that the interaction is direct are necessary in this reviewer's point of view. This could be performed for instance by purifying proteins (or fragments of them) to test binding in vitro, or through IPs of full-length proteins from bacterial extracts. If the interaction between PLK4 and DCAF1 is indeed direct, then the authors would need to provide an explanation of the feasibility of this interaction given that the binding site is occupied by Cep192 or Cep152 at the centrioles. Based on the current knowledge, PLK4 is loaded to the centriole through the interaction with Cep192 which is then switched to interaction with Cep152. For the DCAF1 to be able to bind to PLK4 it would need to outcompete Cep152. Thus, in order to prove that DCAF1 can control PLK4 at the centrosome, evidence would need to be provided that this interaction is possible. If that is not the case, then the most likely alternative is that DCAF1 interactions with cytoplasmic pool of PLK4, thus only indirectly controlling the PLK4 levels at centrioles. A plausible alternative interpretation of the data provided would be that DCAF1-Acidic domain could bind weakly and perhaps non-specifically to PLK4 but in human cells the interaction is mediated through another component such as Cep152 or Cep192 (which are also present in the MS data). Based on the AlphaFold model, the authors introduced point mutations that abolish the PLK4-DCAF1 interaction, but this effect could just as easily be an indirect effect due to abolishing of the PLK4-Cep152/Cep192 interaction.
      • The authors state that DCAF1 depletion with siRNA or shRNA leads to increased level of PLK4 which triggers centriole overduplication. However, this statement is not entirely supported by the data provided. Firstly, in the western blots shown (Fig2A, 2D) the increase in PLK4 levels is hardly visible. Given that this is a key finding, stronger evidence would need to be provided. Furthermore, the quantification of the PLK4 levels upon siRNA mediated DCAF1 depletion are confusing as siDCAF1#2 leads to higher PLK4 levels than siDCAF1#1 despite being less effective in DCAF1 depletion (Fig 2A). More importantly, the quantification on the HeLa tet-on shDCAF1, that are used in many experiments, is missing an important statistical test (Fig 2D). Similarly, no statistical test is performed on the quantification of centriole numbers (Fig 2F) which puts to question the conclusion that "CRL4DCAF1 might function to keep PLK4 protein levels low, thus preventing centriole overduplication". Moreover, GFP-PLK4 levels shown in Fig 6A seem unaltered (if not lowered) upon DCAF1 depletion. Lastly, DCAF1 overexpression does not seem to decrease PLK4 levels as shown in Fig 6B. In that experiment, though, PLK4 is also overexpressed. In order to support the proposed function that CRL4DCAF1 keeps PLK4 levels low, it would be useful to also investigate whether overexpression of DCAF1 would lead to further decrease of PLK4 levels.
      • In page 7, the authors mention: "A premature onset of centriole duplication in the absence of DCAF1 should also result in increased numbers of already disengaged centrioles in G2 phase." This premise is not correct as it is inverted to the current knowledge. It is the premature disengagement that licences for premature centriole duplication (or as often stated as re-duplication) rather than the premature onset of centriole duplication that causes disengagement. This is also what the authors correctly state in the discussion. In the data presented (Fig 6C) the authors observe centriole disengagement upon DCAF1 depletion using expansion microscopy, but no re-duplication is visible in the images provided. This is contrary to the overduplication claim made earlier on (Fig 2F). As such, the data presented do not fully support the drawn conclusion that DCAF1 controls PLK4 levels in G2 to prevent unscheduled centriole duplication. The authors would also need to investigate whether the prolonged use of Cdk1 inhibitor RO-3306 to synchronise the cells in G2 in addition to DCAF1 depletion contributes to the centriole disengagement that is observed, considering that Cdk1-Cyclin B acts also on PLK4-STIL complex.
      • The mechanism proposed by the authors is that DCAF1 maintains PLK4 at low levels throughout G2 which prevents premature disengagement. Subsequently, low PLK4 levels prevent binding and activation of STIL impeding premature initiation of centriole duplication. However, this would not happen since centrioles remain engaged at this stage. Overall, some of the aspects of the proposed mechanism are not fully supported by the data presented. In addition, the proposed mechanism does not offer a suitable mechanistic explanation of how lower PLK4 levels by CRL4^DCAF1 mediated ubiquitylation and degradation prevent centriole disengagement.

      Minor comments

      • In Fig S2A authors need to indicate the expected size of the expressed protein. In its current form blot is difficult to be assessed. More specifically, it is unclear what is the result on the IP with the PLK4 fragment (1-879) since the more intense band in the input in not the same as in in the IP with Flag.
      • In Fig 1C, S2B, S3B, it would be helpful to have a summary of the interactions observed next to each construct. This is commonly represented with (-, +, ++, +++) depending on the amounts present in the IP.
      • In Fig 1D, even though not statistically significant, there seems to be a reduction in the IP of AA and PEST. Do the authors have some suggestion why that might be?
      • Authors used two different cell lines in the experiments presented in Fig2A and Fig 2B. Given that depletion of siDCAF5 is provided as a control of having no effect in the PLK4 levels I would expect to have the experiment performed on same cell line.
      • No statistical test is provided in the comparison on PLK4 levels upon siRNA treatment coupled with CHX (Fig 2C).
      • In the quantification of the PLK4 levels at the centrosomes (Fig 2E), it is not specified whether a background subtraction step was performed prior to the normalisation to the untreated control.
      • In the blot shown in Fig S3, no input is visible in the lane with expression of the Acidic domain.
      • Authors claim that both WD40 and acidic domain contribute to binding of PLK4 because WD40-Acidic is more efficient in binding PLK4 that Acidic domain alone. However, in the blot provided, WD40 alone does not interact with PLK4. Thus, the most likely explanation would be that Acidic domain is the major interactor and WD40 has only minor contribution or it offers a stabilisation role to the acidic domain.
      • Regarding the AlphaFold model provided, and in addition to the comments above, some further clarifications and controls would need to be provided. AlphaFold is a powerful tool but not without its caveats and needs to be used with caution. The authors need to provide a description on how they used AlphaFold to generate the model presented. Typically, AlphaFold produces 5 output models. At which site was DCAF1-Acidic domain positioned in the other output models? Based on what criteria the model shown was selected? Also, a confidence score for the model should be provided.
      • The authors compare their PLK4-DCAF1 AlphaFold model with the structure of PLK4-CEP192 complex but not with the PLK4-Cep152. What is the explanation for this? Given that Cep152 is reported to have higher affinity than Cep192 (Park SY et al., 2014) it would be important to be included in the comparisons performed.
      • The phrase "An overlay between the two structures revealed that ..." is not accurate as one is a merely a model. There are also other instances in the text that the model is referred to as 'structure' which is not correct.
      • Please provide a citation for "Poisson-Boltzmann solver (APBS)".
      • In Fig 3A ribbon representations are too small to see DCAF1 in the printout.
      • The mutations designed might affect the folding of the PBs and thus no interaction is observed. Authors could test how the mutations would affect PB1-PB2 and also design one or two mutants that are in the vicinity but not in the interaction interface to serve as true negative controls in addition to the PLK4-WT. Do these mutants localise to centrioles or also the interaction with Cep192/Cep152 is affected?
      • There is no statistical test in the quantification in Fig 3D, but it is not critical as the difference is very clear and certainly statistically significant.
      • Authors state that DCAF1 strongly interacts with PLK4 during interphase but only weakly in mitosis with quantification in Fig 5A but there is no statistical test.
      • Based on the data shown in Fig 5B, authors state that PLK4 is predominantly ubiquitylated by CRL4DCAF1 in G2 phase. However, in the blot shown, PLK4 seems to be in more abundance in G2 that might explain the apparent higher ubiquitylation. Furthermore, the experiment was performed once and no quantification of the ubiquitylation is performed. Lastly, there are no evidence that this apparent higher ubiquitylation in G2 is mediated by CRL4DCAF1.
      • In Fig 6A, STIL levels upon DCAF1 depletion seem to be lower, is there any potential explanation for that? No statistical test is performed for the STIL/GFP-PLK4 levels difference in siGL2 versus siDCAF1. The authors should provide a justification for over-expressing PLK4 in this experiment. Similarly, in Fig 6B, the authors use overexpression of both PLK4 and DCAF1 and no statistical test is performed.
      • Authors report in Fig 6C disengaged centrioles. How are disengaged centriole defined, is it based on a distance cut-off or loss of orthogonality? In the images provided, this reviewer's impression is that in the (+) Dox condition, there are two parental centrioles that have separated rather disengaged procentriole. Do the images come from the same cell?
      • Based on the data presented, would overexpression of PLK4 in G2 would result in centriole disengagement? This is something that the authors would optionally check.
      • The quantification of rootletin as an additional confirmation of centriole disengagement is puzzling to me as I would expect an increase rather than decrease of its levels. As centrioles disengage, a new link would need to form and thus the expected increase in its levels. However, new rootlet might form only later in mitosis. Also, given that the cells are synchronised in G2 the quantification is more complex. In late G2, centrioles separate in order to move to opposite poles to form the mitotic spindle. This would result in removal of the rootlet that might reflect the reduction the authors report. Ideally the quantification should be limited to cells in late G2 (that centrioles have separated) stained with Centrin 2 to allow for a quantification per centriole pair.
      • In the discussion, authors state "It is conceivable that increasing amounts of PLK4 during mitosis, when the interaction between CRL4DCAF1 and PLK4 is weak, might capture STIL from binding to CDK1 initiating the interaction between PLK4 and STIL". In mitosis CDK1-Cyclin B binds to STIL and prevents formation of the PLK4-STIL complex, thus inhibiting untimely onset of centriole biogenesis (Zitouni et al., 2016). In addition, the authors show that total PLK4 levels are low in mitosis (Fig 5A). The conclusion drawn are not in line with the current literature.
      • The addition of a graphical representation of the proposed mechanism would be beneficial to the readers.
      • A reference for the Ac.Tubulin antibody used is missing.
      • Please provide a citation for FiJi.

      Referees cross-commenting

      I find the comments by the other two reviewers to be valid, clear, insightful, and complementary to those made by this reviewer. There is a good convergence between the reviewers on the critical aspects in this manuscript that require attention. Following revisions this study will contribute to the understanding of regulatory mechanisms acting at the centrioles.

      Significance

      Centriole number control is an important aspect that is relevant not only to the centrosome research field but is also related to cilia, cells signaling, and cancer research. This work presents a novel pathway involved in the regulation of PLK4 levels in cells mediated by the CRL4^DCAF1 E3 ubiquitin ligase complex (CUL4A/B-DDB1-DCAF1). The authors present extensive data to characterise when and how DCAF1 interactions with PLK4 to lowers its levels through ubiquitination and subsequent degradation by the proteasome. However, the effects from various treatments are often minor. The study from Grossmann et al. comes to complement already known pathways of controlling centriole numbers, at G1/S through SCFβ-TrCP E3 ubiquitin ligase mediated PLK4 degradation, and in mitosis by CDK1-Cyclin B through STIL 'capturing' to block centriole reduplication. Given that certain aspects of the manuscript are revised, and an updated and more thorough mechanism is proposed and supported, it will contribute to the conceptual advancement or our understanding of centriole number control across the cell cycle. It could potentially also contribute to the ubiquitin research field of research, but it is hard for me to assess this as it is not my field of expertise.

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      Referee #2

      Evidence, reproducibility and clarity

      Polo-like kinase 4 (Plk4) is the master regulator of centriole assembly and previous studies have shown that its level must be tightly regulated to ensure the precise duplication of centrioles during each cell cycle. It is well documented that the abundance of Plk4 is regulated by E3 ubiquitin ligases and in particular the SCF-TrCp ubiquitin ligase. However, in the absence of SCF-TrCp mediated regulation, PLk4 is still ubiquitylated suggesting that other ubiquitin ligases function to regulate Plk4 levels. Here Grossman and colleagues identify the CUL4-DDB1-DCAF1 (CRL4DCAF1) E3 ubiquitin ligase as a regulator of Plk4 levels and show that it functions predominantly in G2 phase to prevent centriole assembly in M phase. They propose a model whereby SCF-TrCp and CRL4DCAF1 cooperate to control the levels of PLK4 at different points in the cell cycle.

      This study has the potential to yield some important and novel insights into the regulation of centriole assembly. However, in its current form the relationship between the increased Plk4 levels and the other effects described by the authors remain unclear. In particular, it is not clear to me that the small increase in Plk4 levels upon CRL4DCAF1 inhibition is responsible for the multipolar spindle phenotype. Nor is it clear how this increase in Plk4 is related to the premature disengagement defect. Finally, some of the experimental results could be made more convincing by including quantitation and/or additional controls. Major and minor issues are listed point-by-point below.

      Major issues

      Figure 2A and E. The authors report that depletion of DCAF-1 results in an increase in Plk4 levels. However, the actual increase is pretty small, about 1.5 fold for total levels (2A) and approximately 1.2 fold at centrosomes. How can the authors be sure this small increase in Plk4 levels is responsible for the multipolar spindle phenotype reported in figure 2F? It seems to me that CRL4DCAF1 could have other relevant substrates that are responsible for this defect. Related to this, can the authors show that the multipolar spindle phenotype is due to an overproduction of centrioles versus some other defect such as cytokinesis failure? Did the authors examine DCAF-1-depleted cells to if there are cell division defects that could explain the multipolar spindle defect?

      Do the authors know if DCAF1 is operating within the context of the CRL4DCAF1 complex to control Plk4 levels? I know they showed that the entire complex is bound to Plk4 in pull down experiments, but have they tried to deplete other components of CRL4DCAF1 to see if they have the same effect on Plk4 levels?

      Page 5 and Figure 3A. Th authors provide a model where the acidic domain of DCAF1 binds to a groove within the PB1-2 domain of Plk4. This is the same groove that binds CEP192, a protein that cooperates with Cep152 to recruit Plk4 to centrioles. Could it be that DCAF-1, at least in part, is competing with Cep192 and possibly cep152 for binding to Plk4? Thus, in the absence of DCAF1, Cep192 (and possibly Cep152) could recruit more Plk4. Can such a model be ruled out?

      Figure 4. I don't find the results of the in vitro ubiquitin assays all that compelling. Here the authors are fusing DCAF1 to the E2 enzyme and show that this synthetic construct can ubiquitylate Plk4. I wonder in such a system if any protein could be ubiquitylated simply by tethering a binding domain for that protein to an E2 enzyme. So, I guess this is a question of specificity. Is there a control the authors can do to demonstrate specificity in this system?

      Figure 5A and S5A. In figure 5A the authors use a flag-tagged Plk4 pulldown to show that DCAF1 strongly interacts with Plk4 during interphase and weakly during mitosis. In figure S5A, they perform the reverse experiment by pulling down endogenous DCAF1 and state that they obtained similar results. Looking at Figure S5A, this doesn't appear to be true. There is not much difference in the amount of Plk4 pulled down from interphase cells versus mitotic cells. The authors also do not indicate if any of the differences are significant.

      Figure 5B. The authors investigate the cell-cycle-dependent pattern of Plk4 ubiquitination by co-expressing Flag-Plk4, HA-ubiquitin, and Myc-DCAF1 in HEk293 cells followed by a series of Flag IPs from cells arrested at different points in the cell cycle. They claim based on the retarded migration of Plk4, that CRL4DCAF1 ubiquitylates Plk4 specifically during G2 phase. It's hard to make any firm conclusions without quantitation. Furthermore, it's impossible to know how much of the ubiquitylation at any given cell cycle stage is dependent on DCAF1. The correct experiment would have been to have a no DCAF1 control for each cell cycle stage and to quantitate the differences. Since ubiquitin is tagged with HA, would it not be possible to probe the immunoprecipitate with an anti-HA antibody followed by quantitation.

      Figures 6A and 6B. Why do the levels of Plk4 not respond to decreased or increased levels of DCAF1? In 6A for instance strong depletion of DCAF1 does not appear to affect the level of Plk4. Also, given that there is no change in Plk4 levels, the amount of STIL that is pulled down with PLK4 still increases upon DCAF1 knockdown. Does this mean that DCAF1 might function by directly inhibiting the Plk4-STIL interaction.

      Figure 6C The authors find that upon DCAF1 knockdown, centrioles prematurely disengage during G2. They attribute this effect to the increased levels of Plk4. Is there any evidence that increased Plk4 levels lead to premature disengagement? Isn't it possible that this defect is independent of the increase in Plk4 protein? Either the authors should provide evidence of this or offer the possibility that the premature disengagement defect arises independently of the effect on Plk4 levels.

      The authors should also consider exploring the possibility that CRL4DCAF1 functions semi-redundantly with the SCF. It would be interesting to see if there is a synergistic effect of knocking out both E3 ligases on Plk4 levels and centriole number. Such a finding would highlight the importance of the cooperative model the authors propose in this paper.

      Minor issues

      Page 5 typo: "in addition DCAF1 strongly binds to a WD40-acidic motif" I think you meant to say Plk4.

      Figure 4. The terms l.e. and s.e. should be explicitly defined.

      Many figures: Error bars are not defined. Do these represent SD or SE?

      SCF-TrCp is not the only known E3 ligase that controls Plk4 levels. For instance Erich Nigg's group showed some time ago that the E3 ubiquitin ligase Mindbomb (Mib1) also regulates Plk4. (CAjanek et al 2015 J. Cell Sci. 128: 1674-82). This should also be mentioned in the introduction in order to paint a more complete picture of what is known about E3-based regulation of Plk4.

      Significance

      If my criticisms can be successfully addressed, this study has the potential to provide significant new insight into how centriole number is controlled. At least two E3 ligases have already been described that regulate Plk4 levels. This manuscript would provide a third. In an of itself, the discovery of a third E3 involved in the regulation of PLK4 levels would not have a major effect on the field. However if the authors can demonstrate how these two E3s are coordinated to control centriole assembly during the cell cycle that would be a great interest to those studying centriole assembly.

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      Referee #1

      Evidence, reproducibility and clarity

      The CUL4-DDB1-DCAF1 E3 ubiquitin ligase complex regulates PLK4 protein levels to prevent premature centriole duplication

      Previously, it was thought that PLK4 is mainly regulated by autophosphorylation and degradation by the E3 ligase SCFSlimb/beta-TrCP in a phosphorylation dependent manner. In this manuscript by the Hoffmann group, the authors add an additional layer to the regulation of PLK4 as they identify the CRL4DCAF1 E3 ubiquitin ligase as a regulator of PLK4 that prevents PLK4 accumulation in G2 when beta-TrCP is low and therefore helps to restrict centrosome duplication to one event per cell cycle. More specifically, Grossmann et al. identified CRL4DCAF1 E3 ubiquitin ligase subunits in an immunoprecipitation mass spec approach. Using PLK4 kinase dead and phospho-mutants, they first show that CRL4DCAF1 binding is distinct from the SCFSlimb/beta-TrCP binding site. Depletion of DCAF1 leads to a modest increase in cellular PLK4 levels, PLK4 at centrosomes and cells with supernumerary centrosomes. Based on an IP experiments, they convincingly show that the acid C-terminus of DCAF1 interacts with PLK4 and they provide a model based on AlphaFold and analysis of mutations in the putative interaction interface how PLK4 and DCAF1 interact. They further provide evidences that DCAF1 directly ubiquitinates PLK4 in vitro. The interaction between DCAF1 and PLK4 is cell cycle dependent (peak in G2; Fig. 5) following the ubiquitination of PLK4. In Fig. 6 the authors analyze whether PLK4-STIL interaction is regulated by DCAF1. This is indeed the case and Fig. 6B likely indicates that DCAF1 functions as a competitive inhibitor for PLK4 and in this way blocks PLK4 binding to STIL. Finally, in Fig. 6C the authors analyze centrioles by expansion microscopy. The authors show mother-daughter centriole pair disengagement upon depletion of DCAF1 (on p. 7, bottom: "knockdown of DCAF1 leads to a significant higher number of disengaged centrioles"). This is similar to CEP57 depletion as shown by Kitagawa: JCB 2021 220: e202005153. Instead of analyzing centriole disengagement in further depth, the authors analyze in Fig. 6D centrosome separation, which is mechanistically quite distinct from centriole disengagement. Centrosome separation (mother-daughter pairs) in G2 is triggered by resolution of the rootletin linker through the action of the kinase Nek2A. Thus, Fig. 6 refers to two different events/mechanisms and it will be important to clarify whether DCFA1 depletion causes centriole disengagement or centrosome separation (e.g. by analyzing the centrin pattern and whether daughter centrioles mature). To my knowledge, there is no connection between PLK4/STIL and the centrosome linker. Thus, if DCFA1 regulates centrosome separation, Fig. 6 would be disconnected from the rest of the paper.

      Main points

      1. Fig. 2E: it would make sense to quantify the PLK4 signal at centrioles according to the cell cycle phase of the cell. G2 is probably the cell cycle phase when PLK4 is regulated by the CRL4DCAF1 E3 ubiquitin ligase.
      2. It is known that PLK4 has a function in cytokinesis (i.e.: https://doi.org/10.1073/pnas.181882011). Thus, there is the possibility that the supernumerary centrosomes observed in Fig. 2F result from a cytokinesis defect and not from centriole over-duplication. To address this, the authors can use procentriole marker Sas6, and show that a newly disengaged centriole should still posseses Sas6. When the premature onset of centriole duplication happens to those newly disengaed centrioles, both mother and daughter centriole in the pair should posses Sas6 since Sas6 removal only happens in upcoming mitosis.
      3. The authors suggest a competitive interaction between proteins DCAF1, PLK4 and STIL in Fig. 6A and Fig. 6B. However, they have not excluded direct binding of DCAF1 to STIL as an alternative explanation. Additionally, is the enhanced PLK4/STIL interaction in Fig. 6A G2 dependent?
      4. The quality of the expansion microscopy in Fig. 6C could be improved.
      5. The authors have to resolve whether Fig. 6C and D relate to centriole disengagement or centrosome separation and how this is connected to DCAF1, STIL and PLK4.

      Minor points

      1. P. 5: WD40-Acidic motif. This fragment needs to be described in the text and not just in Fig. S3.
      2. Fig. 2E: The authors analyze the phenotype by combining all data points from three experiments. It would be better to show the average of the three independent experiments and do the statistics on the three data points.
      3. Is the difference (> 4) in Fig. 2F significant?
      4. Fig. 3A-C is difficult to follow. It is too small and DCAF1 and CEP192 are very difficult to see. I am sure that there are simple ways to improve this figure.
      5. Define BP1 and BP2 in Fig. 3A. Does BP1 = PB1?
      6. P. 5. "the first helix (D1420-E1436) of DCAF1 positioned .... (add DCAF1).
      7. P. 20 Fig. 4B: 200 nm should be 200 nM.
      8. The authors may want to test additional PLK4 mutations that are not localized in the predicted interaction interface with DCAF1 to show that these mutations do not affect binding.
      9. In Fig. 4A the authors could IP GFP-PLK4 and show that a fraction of this protein carries His-Ubi conjugation using His antibodies.
      10. Difference in quantification of Fig. 6D is not significant,
      11. Fig. 4B (also Fig. 5B): Explain "l.e." and "s.e." in figure. Both blots are not the same (at least in case of Fig. 4B comparing the kDa numbers), thus l.e. = low exposure and s.e. = short exposure does not work. How was PLK4 detected in Fig. 4B?

      Referees cross-commenting

      I believe that all three reviewers have very similar concerns. I guess, everybody agrees that this manuscript, although potentialy very intresting, needs a substrainail amout of revision

      Significance

      The manuscript convincingly identifies CRL4DCAF1 E3 ubiquitin ligase as an PLK4 regulator and therefore is a very important contribution to the field. However, the impact of DCAF1 depletion is not too high. I therefore recommend double depletion of DCAF1 and SCFSlimb/beta-TrCP (not absolutely necessary but could increase impact). The interaction analysis of DCAF1 with PLK4 and the ubiquitination of PLK4 by the DCAF1 E3 ligase is convincing. I see a problems with the data in Fig. 6 that need to be revised.

      Thus, key experiments that should be done are Main points 2), 3) and 5). The revision of the manuscript will take 3-6 months.

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      Reply to the reviewers

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

      The manuscript develops the authors' previous work on the structure of the YeeE protein by presenting a co-structure with YeeD and investigating the role of certain key cysteine residues, especially C17 of YeeD. To this reviewer an entirely plausible mechanism for YeeD/E co-ordinated transport of thiosufate through the membrane and cleavage to sulfide and sulfite which are released into the cytoplasm is proposed on the basis of functional studies. The work is clearly described, the crystallography stats look good.

      Thank you very much for your highly positive comments. We sincerely appreciate them.

      Major comment: The 'cysteine relay' followed by a key role for C17 of YeeD in releasing a sulfide looks very plausible and makes the work of more general interest. An aspect that is not addressed is that of energetics. Moving thiosulfate into the cytoplasm as sulfide and sulfite means apparently that two negative charges net are generated in the cytoplasm for each thiosulfate taken up. This seems too simplistic (protons released as the bound sulfite is released b hydrolysis) but if thiosulfate were to be moved the whole way across there would be a divalent anion uniport which would work against the membrane potential negative inside (ie the main component of the protonmotive force). There is no mention in the paper of any pmf dependence and presumably the structure of YeeE shows no evidence of putative proton pathways? Some discussion of this and any wider implications could enhance the paper. In some ways the proposed transport scheme has some resemblance to Mitchells's old group translocation proposal for transport.

      Thank you for highlighting the significance of the 'cysteine relay.' We also believe that this aspect is likely to interest a broad readership. Regarding protons, YeeE does not have apparent proton pathways inside, and we currently do not have data on its dependence on the pmf. Investigating pmf dependence falls beyond the scope of this study, hence we plan to explore this in future research. We appreciate you for pointing out that the YeeE-YeeD is a reminiscence of Mitchell’s original proposal of group translocation. This is a very intriguing point, and we have now included a discussion of this, along with a relevant citation, in the Discussion section (lines 356-357).

      Reviewer #1 (Significance (Required)):

      The subject of thiosulfate transport (movement) into bacteria is arguably of interest only to a narrow group of bacterial biochemists. However, the contents of this manuscript ought to be of wider interest because the YeeD/E system described is unusual in doing more that catalysing transport alone. Whether the authors' description in their title of 'sophisticated' is an appropriate adjective I am not sure. The term 'cofactor' applied to YeeD seems 'odd' to this reviewer. It is not a cofactor in the usual sense eg NADH.

      We appreciate your comments. We have modified the title and avoided the unsuitable word 'cofactor' to describe YeeD.

      reviewer's expertise: bactrial energetics but little knowledge of sulfur metabolism


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

      Summary:

      The publication "Structure and function of a YeeE-YeeD complex for sophisticated thiosulfate uptake" by Ikei et al. shows the protein-protein interaction of a thiosulfate transporter YeeE and a sulfur transferase YeeD, a TusA-family protein. The transporter YeeE has been structurally characterized previously, without showing its functional activity in a purified reconstituted system. This experiment complementing the previous publication is provided here, furthermore proving the functionality of the transporter. These experiments were further extended by the characterization of the cytoplasmic acceptor protein. This acceptor was proven to be YeeD, by structural characterization and biolayer interferometry. The binding kinetics between YeeD and YeeE were measured, quantifying the binding affinity between the two proteins. Furthermore, the surface residues of YeeD were specified by amino acid exchange mutants. Thus, the structure and essential residues were characterized protein. The interaction of sulfur transferase YeeD with the thiosulfate transporter YeeE is a novelty to the field. This illuminates the first time a specific function of YeeD in thiosulfate assimilation.

      We appreciate your positive review and for recognizing the significance of our work in uncovering the functions of the YeeE and YeeD complex. We have addressed the following major and minor comments, thereby improving our manuscript. We appreciate the your constructive feedback.

      Major comments:

      I see the following major problem: The YeeD protein preparations used in the experiments contained several different protein species. Mass spectrometry showed the existence of the monomeric reduced protein, a TusA sulfinate and a TusA thiosulfonate. There is obviously an oxidation of cysteine to cysteine sulfinate, possibly due to the presence of oxygen as shown in Fig. 2D and stated in the text. The formation of sulfinates has to be avoided. This can be achieved by the use of stronger reducing agents or by purification under strict exlusion of oxygen. The formation of sulfenic, sulfinic and sulfonic acid on cysteines by oxidation has been reviewed by Ezraty et al 2017 Nat Rev Microbiol.

      To answer these points, we have extensively several experiments and analyses, and modified the text. In the mass spectrometry analysis of purified StYeeD, three major peaks are observed (Fig. 2D), but they do not necessarily reflect actual relative abundances due to the nature of mass spectrometry analysis. Therefore, we also analyzed the purified StYeeD by non-reducing SDS-PAGE, which showed very few molecular species with S-S bonds, with over 90% existing as YeeD-SH (Fig. S2D). We considered this level of purity sufficient for conducting biochemical analyses. Furthermore, although a small amount of YeeD-SO2- was observed, this would be inactive and thus not impact the activity of StYeeD because a similar irreversible modification product, NEM-modified StYeeD(WT), was inactive (Fig. S2G).

      We have also provided non-reducing SDS-PAGE results for each mutant StYeeD in Fig. S2F. All StYeeD mutants except for L45A showed a similar pattern to StYeeD(WT). Conducting experiments under anaerobic conditions is quite challenging in our laboratory facility, so we have displayed non-reducing SDS-PAGE profiles of all proteins used in order to avoid misunderstanding. We have also tried the purification in the presence of DTT, a stronger reducing agent, but the fraction of YeeD-SO2- was not significantly changed.

      In the revised version, mass spectrometry analyses were reperformed using DTT-reduced YeeD, resulting in more precise data (Fig. 2D–H). Based on these results and your valuable comments, we have rewritten the paragraph entitled 'T____hiosulfate decomposition activity of YeeD and its catalytic center residue' to represent the reduction/oxidation forms accurately. We have also cited the Nat. Rev. Microbiol. review in the text (line 185).

      In their in vitro assays, the authors use exceptionally high thiosulfate concentrations of 300 mM. This is so far from any physiologically relevant concentrations that strong doubt is shed the validity of any conclusions transferred from the in vitro to the in vivo situation.

      In the revised version, the mass spectrometry analysis was reperformed with a thiosulfate concentration of 500 µM, which is the same concentration of thiosulfate used in the thiosulfate decomposition experiments. To clarify this, we have included the thiosulfate ion concentrations in the legend of Fig 2.

      L247 and Fig5: The proposed mechanism cannot be true. Binding of thiosulfate to a reduced TusA protein is not possible without release of electrons. Where do these electrons go? In the proposed scheme, the number of electrons before and after the reaction steps is not equal (Fig. 5). A release of the sulfur atom between the cysteine sulfur atom and the oxidized sulfur atom is impossible.

      Thank you for your insightful comments. We have revised Fig. 5B to represent a better model. However, elucidating the electron pathway falls outside the scope of this study, and we cannot offer a definitive explanation. We have addressed this limitation in the Discussion section and highlighted it as a topic for future research.

      Have the authors checked whether TusA dimers are formed via disulfide bridges? If so, thiosulfate could resolve these disulfides leading to reduced TusA and thiosulfonated TusA (YeeD-S-S-YeeD + S2O32- → YeeD-S-S-SO3- + YeeD-S-).

      It cannot be excluded that the YeeD-S-SO3- species is a result of removal of sulfite from the YeeD-S-S2O3- species (possibly by transfer to another YeeD molecule) resulting in YeeD-S-S- oxidized by molecular oxygen to YeeD-S-SO3-.

      Upon answering to this comment, we have re-examined the gel filtration result using gel filtration markers. We found that a fraction of YeeD exists as dimers in solution, as shown in Fig. S2C. By performing non-reducing SDS-PAGE, it was shown that these YeeD dimers were not due to intermolecular disulfide bond (Fig. S2D). Following your valuable suggestion, we have introduced the possibility that YeeD can function as a dimer into our model, as presented in a box in Fig. 5B.

      Sulfide may be formed by a reaction of YeeD-S- with S2O32- to YeeD-S-SO3- and S2- or reaction of YeeD-S-S- with S2O32- to YeeD-S-S2O3- and S2-. As there is the formation of sulfinic acid that prevents clear conclusions, I suggest repeating the experiments on thiosulfate decomposition under anaerobic conditions to clarify the reaction mechanism. Anoxic buffers and strong reducing agents may prevent chemical oxidation.

      As described above, based on the non-reducing SDS-PAGE results (Fig. S2D), we believe that the low presence of oxidized species does not significantly affect our analysis. Moreover, the mass spectrometry analysis after DTT treatment yielded more precise results (Fig. 2D–H). As noted above, conducting experiments under anaerobic conditions is challenging in our facility, so we kindly request your understanding and consideration of the revisions made in this manuscript.

      Minor comments:

      In response to the minor comments, we have revised the manuscript.

      L58 What is the nature of the binding of the thiosulfate ion during the transport via YeeE. Is it covalently bound? Please comment in the text.

      In our previous study (Tanaka et al., Sci. Adv., 2020), we proposed that thiosulfate ions were transported via hydrogen bonds. Responding to your comment, we have included the explanation in the text and cited Tanaka et al., 2020 (lines 66-67).

      L76-L77 Is there a publication on the functionality of the Corynebacterium YeeD-YeeE fusion? The term "cofactor" does not apply to YeeD, which is a 9-kDa protein.

      Since the function of Corynebacterium YeeD-YeeE has not been reported, we have changed the sentence to "In some bacteria, such as Gram-positive Corynebacterium species, YeeE and YeeD are encoded as one polypeptide." We have also avoided the word "cofactor" in the revised text (lines 89-91).

      L114 YeeD was probably accidentally lowercased here as Yeed

      We have corrected this error (line 134).

      L119 Please specify what the negative control consisted of.

      We have elaborated on the conditions (lines 140-141).

      L120-122 In Fig 2c, the mutations E19A, K21A, E26A, D31A, E32A and D38A are still shown, but an explanation or description of the results is missing. The reason for investigation of these mutations should be stated in the text.

      We have added the requested mutation information (line 146).

      L137 If thiosulfate was not added before the MALDI-TOF, where did the sulfonate S-SO3 originate from? Is this an artifact formed during the heterologous production or purification? Please comment on this possibility in the text.

      We think that the -S-SO3- form arose during purification (Fig. 2D). The -S-SO3- form disappeared upon reduction by DTT (Fig. 2F). It is possible to consider it as an intermediate state in the catalytic cycle of YeeD. We commented on this in the section entitled "Thiosulfate decomposition activity of YeeD and its catalytic center residue."

      L144 Please state in the text whether these experiments were performed under aerobic or anaerobic conditions. The sulfinic acid is likely a product of a spontaneous chemical reaction with molecular oxygen.

      Thank you for your feedback. We have now included information about the aerobic conditions in the main text (line 166-167) and added comments regarding the mass spectrometry results at the end of the paragraph (lines 191-201).

      L148 It should be stated in the text whether YeeD in Fig2G was reduced with DTT as in Fig 2F or non-reduced as in Fig. 2D before thiosulfate was added. Only the reduced YeeD can yield conclusive results on the loading with sulfur, as there is already a thiosulfonate bound to the protein after purification.

      Thank you for pointing this out. For mass spectrometry analysis, data were re-obtained, and DTT-treated sample was used for the thiosulfate condition in this revised version. Furthermore, we performed mass spectrometry analysis for the hydrogen peroxide condition using DTT-treated sample. Figures were replaced with revised ones (Fig. 2D–H). The text in the section "Thiosulfat____e decomposition activity of YeeD and its catalytic center residue" was appropriately re-written. Detailed sample preparation is also described in MATERIALS AND METHODS section.

      L154 The YeeD used for measurement of sulfide formation must be reduced before the experiments. It is not stated in the text if this is the case. Also, the release of sulfide requires electrons. It should be commented where these electrons originate from.

      The sample in the purification process contains β-ME until just before the final column (gel filtration). As shown in Fig. S2D, more than 90% of the purified product is in a reduced state after gel filtration. For mass spectrometry analysis, data were re-obtained using DTT-treated samples, and the figures were replaced with new ones (Fig. 2D–H). Binding and activity measurements were conducted in the presence of β-ME. To avoid the confusion of the readers, the buffer conditions were included in the legends of both Fig. 2 and Fig. 4, along with the details in the MATERIALS AND METHODS section. Regarding electron origin, since the electron route remains unknown at this stage, we have added the explanation as a sentence in the Discussion section (lines 370-372).

      L159-160 If the mutation of the non-conserved YeeD cysteine inhibits growth, can anything be said about its function?

      Regarding the non-conserved Cys in EcYeeD, we added some sentences in the Discussion section (lines 393-397)

      L214 Is it possible to provide the Kd and KD values for the mutant proteins?

      The ka, kd and KD values the interactions between YeeE and YeeD proteins have been provided in Table 2. To provide these values for all the YeeD derivatives, the data was re-analyzed, and therefore, the value of the WT YeeD is slightly different from the original manuscript.

      L229 Stating a need of YeeD for thiosulfate uptake by YeeE is somewhat misleading as thiosulfate was also imported into liposomes by YeeE alone. Maybe state that YeeD is a required component for growth when thiosulfate is imported via YeeE.

      We have addressed the incorrect wording (lines 317-318).

      Reviewer #2 (Significance (Required)):

      The work of Ikei and colleagues significantly advances our understanding of thiosulfate import in Escherichia coli (E. coli) and prokaryotes in general. Sulfur metabolism as a field is generally considered to be underexplored, with a notable lack of biochemical and structural information on membrane transporters responsible for the movement of both inorganic and organic sulfur compounds. The mechanisms involved in sulfur transport are also relatively poorly understood.

      The proteins of the TusA family in E. coli exhibit distinct functions, although the precise function has only been determined for the canonical and namesake protein TusA. The discovered genetic evidence and the interaction of YeeE and YeeD adds significantly to our understanding of sulfur transfer reactions.

      The novelty of this reaction is of particular interest to researchers studying prokaryotic physiology, especially the synthesis of sulfur-containing cofactors such as coenzyme A (CoA), biotin, lipoate, thiamine, and iron-sulfur (FeS) clusters, as well as the biosynthesis of cysteine and methionine. In addition, recent findings related to the TusA family protein YeeD elucidate a novel mechanism for sulfur mobilization and transfer that will be of interest to researchers involved in the regulation of sulfur metabolism, sulfur dissimilation, and ecological studies focused on sulfur utilization. Thus, a wide range of studies could be influenced by this review.

      Areas of expertise include dissimilatory sulfur oxidation, sulfur transfer reactions, and protein-protein interactions.

      Thank you again for emphasizing the importance of our work. We also believe this study significantly advances the understanding of thiosulfate import in prokaryotes, shedding light on the underexplored field of sulfur metabolism. This has implications for various areas of study.

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

      The manuscript "Structure and function of a YeeE-YeeD complex for sophisticated thiosulfate uptake" by Ikei et al., reports the enzymatic characterization, transport capability and concerted function of YeeE and YeeD. Moreover, the authors report the crystal structures of two mutant variants of the complex.

      The present work fills an important gap in understanding thiosulfate uptake and the individual roles of the YeeE and YeeD proteins in this process. This Reviewer believes that the paper has the potential of becoming an important reference in the field. However, this Reviewer has two or three major comments, besides a couple of minor ones, that would like the authors to address.

      We appreciate your valuable comments. We have addressed both major and minor comments in our revisions, improving our manuscript.

      This Reviewer hypothesizes that some of the comments might derive from a poor understanding of the text, derived from the way the manuscript is written. So, this Reviewer urges the Authors to take these comments as positive feedback, and build on these to improve the manuscript (namely on English and grammar).

      We have diligently revised the manuscript, addressing your major concerns related to sulfide terminology and explanations in crystal structure analysis as below. These revisions have enhanced clarity, and a native English speaker has reviewed and refined our text for language and grammar.

      MAJOR CONCERNS

      1. There is no clue on the title and, more importantly, on the Abstract, to which microorganism the Authors are reporting this work. Only later one we are introduced to Spirochaeta thermophila, but this information should be front and center (at least in the Abstract);

      We recognize the importance of clearly indicating the microorganism in our work. In accordance with the comments, we have revised both the title and Abstract, ensuring that the species is clearly identified in the Abstract.

      Also, in the Abstract, the Authors only mention the 2.6 A resolution structure, leaving behind the 3.34 A one. This becomes very confusing, especially once one gets to the Results section (more comments below);

      We apologize for any confusion arising from the omission of the 3.34 A resolution structure in the Abstract. In the revised Abstract, we have included both the 2.60 A and 3.34 A resolution structures. As per your suggestion, we have also provided detailed information about the determination of these structures in the Results, minimizing potential confusion for readers (lines 217-233).

      The Authors mention in line 137 and Fig. 2D that a "sulfonate" moiety is formed at C17. However, cysteine sulfonation is an irreversible process, so how would the enzyme recover from this modification to allow turnover of the mechanism?;

      We apologize for the poorly written passage that led to confusion. This paragraph has been revised with the appropriate wording and a proper mention of the reduction and oxidation of the -SH group. We now use the appropriate terms, such as sulfinic acid (-S-O2-), sulfonic acid (-S-O3-), and perthiosulfonic acid (-S-SO3-) to describe the sulfur-related modification states. In contrast to sulfonic acid (-SO3-) formed by the oxidization of the cysteine residue that is an irreversible process, perthiosulfonic oxidization of cysteine residue (-S-SO3-) is a reversible process, as shown in (E. Doka et al., Sci Adv 6, eaax8358 (2020)). Therefore, the modified YeeD molecules should be able to recover to the original state.

      If the "sulfonylation" reported in line 137 and Fig. 2D is not a sulfonylation of the cysteine (because the peak disappears upon reduction with DDT as visible in Fig. 2F), but rather a sulfonylation of the cysteine-persulfide version of C17, this was already reported previously and should be referenced [PDB ID 5LO9, Brito et al. (2016) J Biol Chem 291: 24804-24818];

      Because there was a misleading statement, as replied above, we have rewritten this paragraph.

      The perthiosulfonic acid (-S-SO3-) in Fig.2D is different from this -S-S2O3- in Brito et al., (2016), but consistent with Fig. 2G. This point is included in the text and the suggested paper has been cited, as requested. (lines 191-193)

      Section "Crystal structure of the YeeE-YeeD complex" should be re-written. Not only it is confusing, but also undermines the tremendous amount of work done by the Authors. Please state clearle what was crystallized, how and why. Specify clearly the mutation introduced and complement Table 1 with this information;

      Thank you for these comments. The determination of the structures was certainly challenging. We have restructured the first part of the section entitled "Crystal structure of the YeeE-YeeD complex". We have included a comprehensive explanation of the crystallization process and the construction of YeeE-YeeD. Additionally, we have updated Table 1 to provide more detailed information on the two structures.

      Lines 403-407: are the crystallization conditions already cryo-protected or no cryo-protection was added before flash freezing? Please state clearly;

      In response to your feedback, we have added the missing information in MATERIALS AND METHODS section.

      Table 1:

      • Is the multiplicity of PDB ID 8K1R correct? Is it really 321?? If so, is there any radiation damage to the crystal? If not, how?? Fine-fine-slicing during data collection, big crystals with elliptical data collection?? Pleas elaborate;

      The multiplicity for PDB ID 8K1R is correct. We have provided detailed information on data collection in MATERIALS AND METHODS section.

      • There are water molecules in the structure so please report number of atoms and B-factors for waters ("Solvent"), and ligands (e.g., thiosulfate, or others, if any), separately;

      We have updated Table 1 to include the requested information.

      • Please provide validation statistics for the structures, namely, rotamer outliers, clashscore and MolProbity score.

      We have added the validation statistics to Table 1.

      MINOR CONCERNS

      1. Always reference paper and PDB ID for all structures. E.g., at line 181, only the paper is referenced;

      We have ensured that all structures are properly referenced with both the paper and the corresponding PDB ID (lines 246, 250).

      Remove "alpha" in line 199;

      We have removed the "alpha" (line 268).

      Add units to all concentrations. E.g., at lines 326 and 327, (w/V) and (V/V) are missing.

      We have incorporated concentration units, (w/v) or (v/v), for percentages in the appropriate locations.

      Reviewer #3 (Significance (Required)):

      The scientific rationale is robust and the experimental approach is adequate and provide support to the conclusion drawn. However, there are some questions this Reviewer would like to see clarified, namely on the data collection and processing of PDB ID 8K1R.

      We appreciate your feedback. These revisions enhance the clarity and accuracy of this manuscript.

    2. 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 "Structure and function of a YeeE-YeeD complex for sophisticated thiosulfate uptake" by Ikei et al., reports the enzymatic characterization, transport capability and concerted function of YeeE and YeeD. Moreover, the authors report the crystal structures of two mutant variants of the complex.

      The present work fills an important gap in understanding thiosulfate uptake and the individual roles of the YeeE and YeeD proteins in this process. This Reviewer believes that the paper has the potential of becoming an important reference in the field. However, this Reviewer has two or three major comments, besides a couple of minor ones, that would like the authors to address. This Reviewer hypothesizes that some of the comments might derive from a poor understanding of the text, derived from the way the manuscript is written. So, this Reviewer urges the Authors to take these comments as positive feedback, and build on these to improve the manuscript (namely on English and grammar).

      Major concerns

      1. There is no clue on the title and, more importantly, on the Abstract, to which microorganism the Authors are reporting this work. Only later one we are introduced to Spirochaeta thermophila, but this information should be front and center (at least in the Abstract);
      2. Also, in the Abstract, the Authors only mention the 2.6 A resolution structure, leaving behind the 3.34 A one. This becomes very confusing, especially once one gets to the Results section (more comments below);
      3. The Authors mention in line 137 and Fig. 2D that a "sulfonate" moiety is formed at C17. However, cysteine sulfonation is an irreversible process, so how would the enzyme recover from this modification to allow turnover of the mechanism?;
      4. If the "sulfonylation" reported in line 137 and Fig. 2D is not a sulfonylation of the cysteine (because the peak disappears upon reduction with DDT as visible in Fig. 2F), but rather a sulfonylation of the cysteine-persulfide version of C17, this was already reported previously and should be referenced [PDB ID 5LO9, Brito et al. (2016) J Biol Chem 291: 24804-24818];
      5. Section "Crystal structure of the YeeE-YeeD complex" should be re-written. Not only it is confusing, but also undermines the tremendous amount of work done by the Authors. Please state clearle what was crystallized, how and why. Specify clearly the mutation introduced and complement Table 1 with this information;
      6. Lines 403-407: are the crystallization conditions already cryo-protected or no cryo-protection was added before flash freezing? Please state clearly;
      7. Table 1:

      a. Is the multiplicity of PDB ID 8K1R correct? Is it really 321?? If so, is there any radiation damage to the crystal? If not, how?? Fine-fine-slicing during data collection, big crystals with elliptical data collection?? Pleas elaborate;

      b. There are water molecules in the structure so please report number of atoms and B-factors for waters ("Solvent"), and ligands (e.g., thiosulfate, or others, if any), separately;

      c. Please provide validation statistics for the structures, namely, rotamer outliers, clashscore and MolProbity score.

      Minor concerns

      1. Always reference paper and PDB ID for all structures. E.g., at line 181, only the paper is referenced;
      2. Remove "alpha" in line 199;
      3. Add units to all concentrations. E.g., at lines 326 and 327, (w/V) and (V/V) are missing.

      Significance

      The scientific rationale is robust and the experimental approach is adequate and provide support to the conclusion drawn. However, there are some questions this Reviewer would like to see clarified, namely on the data collection and processing of PDB ID 8K1R.

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

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      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      The publication "Structure and function of a YeeE-YeeD complex for sophisticated thiosulfate uptake" by Ikei et al. shows the protein-protein interaction of a thiosulfate transporter YeeE and a sulfur transferase YeeD, a TusA-family protein. The transporter YeeE has been structurally characterized previously, without showing its functional activity in a purified reconstituted system. This experiment complementing the previous publication is provided here, furthermore proving the functionality of the transporter. These experiments were further extended by the characterization of the cytoplasmic acceptor protein. This acceptor was proven to be YeeD, by structural characterization and biolayer interferometry. The binding kinetics between YeeD and YeeE were measured, quantifying the binding affinity between the two proteins. Furthermore, the surface residues of YeeD were specified by amino acid exchange mutants. Thus, the structure and essential residues were characterized protein. The interaction of sulfur transferase YeeD with the thiosulfate transporter YeeE is a novelty to the field. This illuminates the first time a specific function of YeeD in thiosulfate assimilation.

      Major comments:

      I see the following major problem: The YeeD protein preparations used in the experiments contained several different protein species. Mass spectrometry showed the existence of the monomeric reduced protein, a TusA sulfinate and a TusA thiosulfonate. There is obviously an oxidation of cysteine to cysteine sulfinate, possibly due to the presence of oxygen as shown in Fig. 2D and stated in the text. The formation of sulfinates has to be avoided. This can be achieved by the use of stronger reducing agents or by purification under strict exlusion of oxygen. The formation of sulfenic, sulfinic and sulfonic acid on cysteines by oxidation has been reviewed by Ezraty et al 2017 Nat Rev Microbiol. In their in vitro assays, the authors use exceptionally high thiosulfate concentrations of 300 mM. This is so far from any physiologically relevant concentrations that strong doubt is shed the validity of any conclusions transferred from the in vitro to the in vivo situation. L247 and Fig5: The proposed mechanism cannot be true. Binding of thiosulfate to a reduced TusA protein is not possible without release of electrons. Where do these electrons go? In the proposed scheme, the number of electrons before and after the reaction steps is not equal (Fig. 5). A release of the sulfur atom between the cysteine sulfur atom and the oxidized sulfur atom is impossible. Have the authors checked whether TusA dimers are formed via disulfide bridges? If so, thiosulfate could resolve these disulfides leading to reduced TusA and thiosulfonated TusA (YeeD-S-S-YeeD + S2O32- → YeeD-S-S-SO3- + YeeD-S-). It cannot be excluded that the YeeD-S-SO3- species is a result of removal of sulfite from the YeeD-S-S2O3- species (possibly by transfer to another YeeD molecule) resulting in YeeD-S-S- oxidized by molecular oxygen to YeeD-S-SO3-. Sulfide may be formed by a reaction of YeeD-S- with S2O32- to YeeD-S-SO3- and S2- or reaction of YeeD-S-S- with S2O32- to YeeD-S-S2O3- and S2-. As there is the formation of sulfinic acid that prevents clear conclusions, I suggest repeating the experiments on thiosulfate decomposition under anaerobic conditions to clarify the reaction mechanism. Anoxic buffers and strong reducing agents may prevent chemical oxidation.

      Minor comments:

      L58 What is the nature of the binding of the thiosulfate ion during the transport via YeeE. Is it covalently bound? Please comment in the text.

      L76-L77 Is there a publication on the functionality of the Corynebacterium YeeD-YeeE fusion? The term "cofactor" does not apply to YeeD, which is a 9-kDa protein.

      L114 YeeD was probably accidentally lowercased here as Yeed

      L119 Please specify what the negative control consisted of.

      L120-122 In Fig 2c, the mutations E19A, K21A, E26A, D31A, E32A and D38A are still shown, but an explanation or description of the results is missing. The reason for investigation of these mutations should be stated in the text.

      L137 If thiosulfate was not added before the MALDI-TOF, where did the sulfonate S-SO3 originate from? Is this an artifact formed during the heterologous production or purification? Please comment on this possibility in the text.

      L144 Please state in the text whether these experiments were performed under aerobic or anaerobic conditions. The sulfinic acid is likely a product of a spontaneous chemical reaction with molecular oxygen.

      L148 It should be stated in the text whether YeeD in Fig2G was reduced with DTT as in Fig 2F or non-reduced as in Fig. 2D before thiosulfate was added. Only the reduced YeeD can yield conclusive results on the loading with sulfur, as there is already a thiosulfonate bound to the protein after purification.

      L154 The YeeD used for measurement of sulfide formation must be reduced before the experiments. It is not stated in the text if this is the case. Also, the release of sulfide requires electrons. It should be commented where these electrons originate from.

      L159-160 If the mutation of the non-conserved YeeD cysteine inhibits growth, can anything be said about its function?

      L214 Is it possible to provide the Kd and KD values for the mutant proteins?

      L229 Stating a need of YeeD for thiosulfate uptake by YeeE is somewhat misleading as thiosulfate was also imported into liposomes by YeeE alone. Maybe state that YeeD is a required component for growth when thiosulfate is imported via YeeE.

      Significance

      The work of Ikei and colleagues significantly advances our understanding of thiosulfate import in Escherichia coli (E. coli) and prokaryotes in general. Sulfur metabolism as a field is generally considered to be underexplored, with a notable lack of biochemical and structural information on membrane transporters responsible for the movement of both inorganic and organic sulfur compounds. The mechanisms involved in sulfur transport are also relatively poorly understood.

      The proteins of the TusA family in E. coli exhibit distinct functions, although the precise function has only been determined for the canonical and namesake protein TusA. The discovered genetic evidence and the interaction of YeeE and YeeD adds significantly to our understanding of sulfur transfer reactions. The novelty of this reaction is of particular interest to researchers studying prokaryotic physiology, especially the synthesis of sulfur-containing cofactors such as coenzyme A (CoA), biotin, lipoate, thiamine, and iron-sulfur (FeS) clusters, as well as the biosynthesis of cysteine and methionine. In addition, recent findings related to the TusA family protein YeeD elucidate a novel mechanism for sulfur mobilization and transfer that will be of interest to researchers involved in the regulation of sulfur metabolism, sulfur dissimilation, and ecological studies focused on sulfur utilization. Thus, a wide range of studies could be influenced by this review.

      Areas of expertise include dissimilatory sulfur oxidation, sulfur transfer reactions, and protein-protein interactions.

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

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      Referee #1

      Evidence, reproducibility and clarity

      The manuscript develops the authors' previous work on the structure of the YeeE protein by presenting a co-structure with YeeD and investigating the role of certain key cysteine residues, especially C17 of YeeD. To this reviewer an entirely plausible mechanism for YeeD/E co-ordinated transport of thiosufate through the membrane and cleavage to sulfide and sulfite which are released into the cytoplasm is proposed on the basis of functional studies. The work is clearly described, the crystallography stats look good.

      Major comment: The 'cysteine relay' followed by a key role for C17 of YeeD in releasing a sulfide looks very plausible and makes the work of more general interest. An aspect that is not addressed is that of energetics. Moving thiosulfate into the cytoplasm as sulfide and sulfite means apparently that two negative charges net are generated in the cytoplasm for each thiosulfate taken up. This seems too simplistic (protons released as the bound sulfite is released b hydrolysis) but if thiosulfate were to be moved the whole way across there would be a divalent anion uniport which would work against the membrane potential negative inside (ie the main component of the protonmotive force). There is no mention in the paper of any pmf dependence and presumably the structure of YeeE shows no evidence of putative proton pathways? Some discussion of this and any wider implications could enhance the paper. In some ways the proposed transport scheme has some resemblance to Mitchells's old group translocation proposal for transport.

      Significance

      The subject of thiosulfate transport (movement) into bacteria is arguably of interest only to a narrow group of bacterial biochemists. However, the contents of this manuscript ought to be of wider interest because the YeeD/E system described is unusual in doing more that catalysing transport alone. Whether the authors' description in their title of 'sophisticated' is an appropriate adjective I am not sure. The term 'cofactor' applied to YeeD seems 'odd' to this reviewer. It is not a cofactor in the usual sense eg NADH.

      reviewer's expertise: bactrial energetics but little knowledge of sulfur metabolism

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      Reply to the reviewers

      1. General Statements We thank the Editors and the Reviewers for their time and constructive criticism, which has allowed us to improve our manuscript. All of our responses are indicated in blue font. Revision Figures for the Reviewers are included just below the response. The line numbers given here refer to those in the revised manuscript, where we have marked the changes in red.
      2. Description of the planned revisions If granted a full revision, we will experimentally address the following major points, which were raised by more than one Reviewer: ● Repeat experiment in Figure 4 C to assess statistical significance (Reviewer 1 and 3) ● Western blot analysis of HDV infected HLCs showing small and large delta antigens. We have already performed such an analysis on HLCs (see Revision Figure 2). In addition, we will perform a comparative analysis with common HDV infection models dHepaRG and Huh7-NTCP cells over time (Reviewers 2 and 3). ● Additional characterisation of the two HLC subpopulations at transcript and protein level (Reviewer 1 and 3). In addition, we planned to conduct the following experiments in response to the individual Reviewers: In response to Reviewer 1: We thank the Reviewer for their encouraging feedback on our model and for their helpful comments, allowing us to improve our manuscript. Figure 1: The observation of a denser subpopulation of hepatocytes more susceptible to HDV is interesting. Do you have more characterization of this cell subpopulation, by IFA, in term of hepatic maturation marker, known HDV host factors and particularly NTCP expression? We agree with the Reviewer that this is an interesting observation. We separated the two hepatocyte subpopulations to analyse the gene expression of the liver maturation markers NTCP and ALB by RT-qPCR (see Revision Figure 1A). Surprisingly, we found that the low-density population expressed higher levels of both ALB and NTCP, suggesting that they are more mature than the high-density population. In addition, we stained both markers by immunofluorescence and observed no apparent differences (see Revision Figures 1B & C). In contrast, the new host factor identified in our study, CD63, appeared to be more highly expressed in the high-density population compared to the low-density population (Fig. 6G). However, we cannot exclude the Revision Plan possibility that other factors play an additional role. As outlined in our response to Reviewer 3, we will separate the two populations and analyse the gene expression of other known HBV and HDV co-host factors to assess whether they play a role in addition to CD63 in conferring the higher susceptibility to HDV infection to the highly dense HLC population. Revision Figure 1: High-density HLCs population is not more mature than the low-density HLC population. (A) The low-density HLCs population was separated from the high-density HLC population by gentle dissociation. Total RNAs were isolated from both populations and Albumin and NTCP expression was analysed by RT-qPCR. (B & C) High-density HLCs (upper image) and low-density HLCs (bottom image) were stained with Albumin specific antibody. Shown are either images taken on an epifluorescence microscope (B) or single slices of confocal images acquired on a Airyscan confocal microscope (C). Fig 1B and C: Can a BLV control be included in the figure? Thank you for this suggestion, we will repeat the experiment for these panels and add BLV as control. Fig 1A-F: What is the overall level of NTCP between HLC, HepaRG, Huh7NTCP and HLCAAV- NTCP? Can NTCP and HDAg be stained simultaneously in your cells? This is an excellent question and we will compare the total NTCP levels between differentiated HepaRG, Huh7 NTCP, HLCs +/- AAV NTCP by Western blot analysis and immunofluorescence (IF) staining. Comparing NTCP expression in HLCs +/- AAV NTCP, we observed a strong upregulation of surface NTCP upon AAV transduction by IF staining (Figure 1D). Unfortunately, our initial attempts to simultaneously detect NTCP and HDAg were technically hampered. Since HDAg is mainly localised in the nuclei, we have to permeabilize the cells in a harsh manner, which interferes with the detection of membrane NTCP. The latter is further hampered by the availability of suitable anti-NCTP antibodies for IF staining. In our study, we used high doses of fluorescence-conjugated MyrB peptide to stain NTCP, but unfortunately it is very sensitive to the harsh permeabilization detergents mentioned above. However, since we have meanwhile optimised HDV infection, we will likewise try again to optimise the staining Revision Plan protocol. If we succeed, we will repeat the co-staining of NTCP and HDAg and include it in a revised manuscript. Figure 4: While the strategy is interesting, based on what has been previously shown for HCV in Wu et al., 2012, the lack of statistical data prevents the reader to really understand and see drastic difference in term of susceptibility to infection and level of expression of host genes. In panel C, is the difference between day 13 and 15 statistically significant? Same for panel D, day 17 vs 19?As a remark, day 19, the peak of susceptibility to HDV, seems to be also the peak of maturation, based on ALB RTqPCR (panel B). Thank you for this comment, and will perform another set of experiments allowing us to calculate statistical significance. The Reviewer correctly points out the correlation between HDV infection and hepatocyte maturity, which we find very intriguing. To identify potential host co- or restriction factors expressed in highly mature HLCs, we then performed the differential gene expression analysis (Figure 5). As shown in the new Figure 5A, GO analysis revealed that genes involved in pathways regulating viral entry into host cells were most significantly upregulated in mature HLCs and, as a probable consequence, they were more permissive to HDV infection. Indeed, among these factors, we identified CD63 as a novel host cofactor that renders mature HLCs susceptible to HDV infection (Figure 6). In response to Reviewer 2: We thank the Reviewer for their assessment of our study and for critically pointing out the increments over the previous study by Lange et al. We also appreciate their helpful suggestions, which allow us to improve the manuscript. The manuscript would benefit from a more detailed virological analysis, such as: •Determination of HDV genome and antigenome sequences and analysis of HDV editing. We thank the Reviewer for this comment. Accordingly, we will determine HDV genomes and antigenomes by Northern blot analysis and study HDV editing rates by sequencing in HDVinfected HLCs. •Analysis of HDV short and large antigens by western blot. We have already detected small and large HDAg in HDV-infected HLCs (see Revision Figure 2). To also satisfy Reviewer 3, we will additionally compare the S/L-HDAg ratios over time in HLCs, dHepaRGs, and Huh7-NTCP cells and include the results in a revised manuscript. Revision Figure 2: Detection of small and large delta antigen in HDV-infected HLCs. Mature HLCs were infected with HDV (MOI= 5 Int. Units/cell) and harvested 1 or 3 days post-infection. Cell lysates were analysed by Western blotting using antibodies against HDAg and b-actin. Revision Plan •Analysis of HBV-related virological parameters in monoinfected and co-infected cells. We agree with the Reviewer and we will include the characterisation of more HBV-related virological parameters in our mono- and co-infected HLCs. Accordingly, we will assess HBV cccDNA, RNA, and DNA by RT-qPCR, as well as released HBsAg and HBeAg via ELISA and add the results to the revised manuscript. In response to Reviewer 3: We thank the Reviewer for their positive evaluation, and we acknowledge their helpful comments, which will help us to improve our manuscript. Line 143: the authors describe two forms of HLCs (less and more confluent with differences regarding the susceptibility to HDV infection). The characteristics of the less and more confluent HLCs should be described in more detail-what is causative for the differences in susceptibility for HDV infection of these two forms? We thank the Reviewer for this comment. We likewise find this observation intriguing. As stated in our response to Reviewer 1, we have ruled out that NTCP and/or other mature markers such as ALB are differentially expressed between the two subpopulations. As one factor that could make a difference, we have identified CD63, which is highly expressed in the high-density HLC population and less so in the low-density HLC population (Figure 6G). Nevertheless, we will separate the two populations and analyse by RT-qPCR the expression of other known HBV and HDV host co-factors that may be additional factors governing the increased susceptibility of the highly dense HLC population. The statistical analyses should be improved: There are no p-values provided for the data presented in the supplement and a variety of figures lacks p-values We have added p-values to the Supplementary Figures (see revised Supplementary Fig. S2) and will repeat the experiments for Fig. 4 and Supplementary Fig. S1B and Fig S3 so that we can calculate the corresponding p-values. Kinetic of the infection: Here it would be interesting to see a comparative analysis by western blot investigating the ratio HBsAg/HDAg over the time in HLCs, HepaRGs and NTCP oe cells We thank the Reviewer for his comments. As stated in our response to Reviewer 2, we will perform this WB analysis to detect S/L-HDAg over time in infected HLCs, dHepaRG, and Huh7- NTCP cells. Line 157: What is the experimental evidence for the proper localization and functionality of the ectopically expressed NTCP in HLCs. Did the authors study the taurocholate transport after overexpression of NTCP? We thank the Reviewer for this comment. We analysed endogenous and ectopic NTCP expression by microscopy using a fluorescently conjugated peptide Atto-MyrB-565, which specifically binds to the ectodomain of human NTCP (Figure 2D) and found that both Revision Plan endogenously and ectopically expressed NTCP are located on the cell surface. To further confirm the correct localisation, we will perform NTCP co-staining with a cell membrane marker. We will also test the proper function of the ectopically expressed NTCP using a specific taurocholate transport assay as shown in our previous study (Ni et al, 2014, Gastroenterology). Line 169: The authors should include data comparing the number of double positive cells in HLCs, HepaRGs and Huh7NTCP o.e. expressing cells under the chosen experimental conditions We thank the Reviewer for this suggestion. We have already performed HBV/HDV co-infection of dHepaRG cells (Revision Figure 3) and we will perform the same experiment with Huh7-NTCP cells. Revision Figure 3: HBV/HDV co-infection of dHepaRG cells. Differentiated HepaRG were infected with HBV (MOI = 450 genome copies/cell) and HDV (MOI = 5). Cells were stained against HBV core (HBc), HDAg, and nuclei (DAPI) ten days p.i.. HBc- and HDAg-positive cells were counted using Cellprofiler imaging software to quantify HBV (pink) and HDV (green) single and co-infection (white) events. Images are representative of three independent differentiations. Line 291: expression analysis by RT-PCR is not sufficient. It will be important to study by CLSM if the identified factors are really present as proteins and properly localized. To satisfy this Reviewer, we will be happy to perform WB analysis of lysates from cells obtained at different stages of HLC differentiation to detect LDLR, LAMP1 and SR-B1 to further confirm our transcriptome analysis. As protein expression is easier to compare by WB analysis, we prefer this method to microscopic analysis. Regarding the role of CD63: what is the evidence for a direct role of CD63 for HDV entrycan the authors exclude that CD63 is relevant for targeting other factors to the surface? What is the impact of loss of CD63 on the functionality of the autophagosomal-MVB-EV system in HLCs? Since downregulation of CD63 before but not after impairs HDV infection, we conclude that CD63 is likely to be important for the early steps of the HDV life cycle, namely cell entry. Indeed, we speculate that CD63 may be critical for HDV trafficking to the vesicle, where fusion of the HBV glycoproteins is induced to allow capsid entry, based on the following observations: Although neither the precise site of HBV viral fusion nor the cues that induce fusion are currently fully understood, studies suggest that HBV can be co-transported with EGFR and NTCP to late endosomes for trafficking (Herrscher et al; 2020, Cells). We speculate that similar to what has been described for Lujo virus, CD63 may be involved in either HDV trafficking and/or virus fusion in the endosomal system (late endosome or lysosome) (Tominaga et al, 2014 Molecular cancer). Revision Plan CD63 is a ubiquitously expressed protein that localises to the endosomal system and, in its glycosylated form, to the cell surface. Non-glycosylated CD63 is not properly trafficked and aggregates at the nuclear periphery instead of the cell membrane (Tominaga et al., 2014, Molecular Cancer). According to the Western blot analysis in Figure 6, immature HLCs appear to express less glycosylated CD63 than mature HLCs. We will confirm the glycosylation by treating the cell lysates with PNGase F. Although AAV transduction enhanced CD63 expression of all three HLC stages tested (see new Supplementary Figure S6 in the revised manuscript), it only enhanced HDV infection of immature HLCs, in which the non-glycosylated form of CD63 appears to be the predominant form. To demonstrate that the glycosylated form of CD63 is involved in HDV entry, we will rescue WT CD63 in parallel with a glycosylation-deficient CD63 mutant (Yoshida et al., 2009, Microbiology and Immunology) in immature HLCs. We will also stain CD63 in both immature and mature HLCs to compare the subcellular localisation (plasma membrane/endosomes vs. nuclear membrane) of CD63 between the two stages.
      3. Description of the revisions that have already been incorporated in the transferred manuscript Based on the constructive comments by the Reviewers we already made the following changes, which are highlighted in red in the revised manuscript. In response to Reviewer 1: Fig 1B-C: the comparison with dHepaRG is very interesting, and confirms the validity of SC derived hepatocytes as a model for HDV infection. dHepaRG can be heterogeneous. Do you also see the same phenotype of enriched HDV infection within a denser subpopulations of dHepaRG We thank the Reviewer for their comment. Undifferentiated bipotent HepaRG cells are not permissive for HDV infection due to the lack of surface NTCP expression. Due to their bipotent nature and upon differentiation, two morphologically distinct populations become apparent: hepatocyte-like cells and biliary epithelial-like cells (McGill et al., 2010, Hepatology). As shown in the Figure 1 of the study by Mesnage et al. (2018, Molecular Toxicology), dense hepatocyte-like colonies are surrounded by clear epithelial cells corresponding to primitive biliary cells. In agreement with other studies, we only observe that the ALB-positive hepatocyte-like cells are permissive to HBV and HDV infection (Hantz et al., 2009, Journal of General Virology), highlighting their specific hepatic tropism and the cellular determinants required. Fig 1I is confusing. Was BLV assay also performed on the HLC infection (Day 0), or only during the titration assay in Huh7NTCP? We apologise for the confusion in this panel. BLV was only added during the titration assay on Huh7NTCP cells to confirm new and productive infections and to rule out carry-over. We have changed the order of Figures 1I - 1K to make this clearer and explain this better in the new results section (line 171-179) and figure legend (line 797-806). Revision Plan Fig 1K: x-axis is confusing... is it number of HBV, HDV and HBV/HDV positive cells? Or number of infected cells upon inoculation with HBV, HDV, or both? Please clarify. We apologise for this additional confusion caused in this panel. We infected HLCs with both HBV and HDV simultaneously and then counted the number of positive cells that were either single infected with HBV (pink cells/column), single infected with HDV (green cells/column) or double infected with both viruses (white cells/column). We have clarified this in the revised Results section (line 172-176) and in the revised Figure Legend (line 798-803). Figure 2: The AAV based vector to over express HBsAg is a very interesting tool, and the figure convincingly show production of HDV progeny viruses in HLC-AAV-HBsAg. Results shown are in agreement with previous studies based on hepatoma cell lines. We thank the Reviewer for this positive comment and we agree that AAVs represent interesting tools to genetically manipulate HLCs and other hepatocyte culture systems. Figure 2B: What is IU/ml? Infectious Unit? International Unit? Are units in Fig 1B, 2B and 2C the same? We apologise for the lack of clarity. In Figures 1B and 2C, IU corresponds to infectious units of HDV, whereas in Figure 2B, IU corresponds to international units for the assessment of secreted HBSAg levels in the supernatant. To make the difference clearer, we have changed the unit on the y-axis in Figure 2B and explicitly stated the abbreviations in the corresponding revised Figure Legends (lines 785, 786, 794, 795, 816, and 819). Figure 3: What is the overall number of transmission events observed in the co-culture setup? Can you visually observed viral spreading? Panel A shows only 1 event, making it hard to assess its efficiency. Titration assay in Fig 2C show production of up to 4-5 log of infectious HDV. But HLCs susceptibility to HDV infection may change during time... Thank you for your comment and for raising this important issue. Panel A clearly and visually demonstrates that extracellular spread of HDV had occurred in the HLCs system, as initially only WT and non-GFP positive HLCs were infected with HDV. After co-culture, the progeny of WT HLCs were able to infect GFP-HLCs (Figure 3A). The overall efficiency of HDV spread/transmission in HLC efficiency is shown in Figure 3C. If we allow spread to occur (DMSOtreated condition), the total number of HDV-positive HLCs grown in a 24-well plate is approximately 1000. When we block secondary infection of progeny with BLV and thus spread, we count only about 500 HDV-positive HLCs in a well. In general, spreading in HLCs (Figure 3C) is not as efficient as retitration to Huh7-NTCP (Figure 2C) for the following reasons: In Figure 2C, we wanted to have an estimation of the maximum amount of secreted infectious progeny from HDV-producing HLCs. To this end, we did not want the re-infection itself to be a major bottleneck and used the most susceptible model Huh7-NTCP and infected them under the best conditions, which includes the addition of 4% PEG and 2% DMSO in the culture medium. For our spread assay in HLCs, we cannot add PEG to the cells over the course of the experiment and we also wanted to be as physiological as possible. PEG significantly enhances HDV infection Revision Plan of HLCs (Supplementary Fig. S2) and Huh7-NTCP cells (Revision Figure 4), which is in agreement with previous studies (Michailidis et al., 2017, Scientific reports). In addition, as the Reviewer correctly points out, similar to other primary hepatocyte culture models, the HLC system deteriorates over time. However, we have found that HLCs can be cultured for up to 3 weeks. Nevertheless, we believe that the efficiency of HDV spread in HLCs is sufficient for drug testing (Fig. 3C & D). Revision Figure 4: PEG enhances HDV infection of Huh7-NTCP cells. Huh7- NTCP cells were infected with HDV (MOI= 5 Int. Units/cell) in the absence or presence of PEG. Cells were harvested on D5 pi and HDV genome copies were quantified by RT-qPCR. Figure 5: In panel A, GO pathways should be sorted based on significance, not Number of genes. In panel B-D, what is the scale of the heatmap on figure 5: change in CPM values, however log2, log10? Thank you for this comment, we have sorted the GO pathways based on significance (new Figure 5A). For panels B-D, we did not calculate the fold change in CPM values and they were not log transformed. Instead, we calculated the z-scores of the genes shown by comparing the expression level of a given gene (in CPM) in a given sample with the expression level of that gene across all samples. To avoid further confusion, we have added "z-score" to the new Figure 5. Figure 6: Do you have info about CD63 in other mature model, like dHepaRG and PHHs? Is CD63 also limiting in these models? Our data in Figure 6 suggest that CD63 may be a limiting factor for HDV infection of immature HLCs but not mature HLCs. Both dHepaRG cells and PHHs are mature hepatocyte models and therefore we speculate that CD63 is not rate limiting. However, we will investigate whether CD63 is rate-limiting in undifferentiated HepaRG cells. In response to Reviewer 2: Additional information that needs to be added, better explained, or corrected: The authors should explain why they used different MOIs depending on the genotype. In our previous study by Wang et al. 2021 J Hepatol, we found that the different HDV genotypes are heterogeneous in their ability to infect Huh7 NCTP cells. For example, as shown in Figure 4B of Wang et al. 2021 J Hepatol, GT 4 and 5 are less infectious than other genotypes. Based on the different infectious titres of the genotypes obtained on Huh7 NTCP cells, we then decided to use different MOIs for infection of our HLCs. The aim of the present study by Chi et al. was not to Revision Plan compare the different HDV genotypes, but to analyse whether they can all infect HLCs. In order to obtain similar infection efficiencies of our HLCs with the different genotypes, we used higher MOIs for those genotypes that were less infectious in Huh7-NTCP cells compared to those genotypes that were more infectious in Huh7-NCTP cells. We apologise for not making this sufficiently clear and have added this information to the results section (line 167-170) and the corresponding figure legend (line 796) of the revised manuscript. In Figure 1, it is unclear on which day the HCLs were infected by HDV and on which day they were transduced with AAV-NTCP. We apologise for the lack of clarity in the experimental design. We transduced HLCs with AAV two days before HDV infection to ensure sufficient ectopic NTCP expression on the day of HDV infection to study its effect on HDV entry. We have clarified this in the results section (line 153, 156) and in the figure legend (line 788) in the revised manuscript. It is not very clear if the authors used AAV serotype 6 consistently to transduce the cells. It would be valuable to show the transduction efficiency of AAV at different time points of HLC maturation, as it might also be affected and could explain some results. For example, in Figure 6H, why does AAV-CD63 transduction increase HDV infectivity at day15 but not at day 10? It would be interesting to repeat the anti-CD63 western blot after AAV-CD63 transduction. Thank you for this comment. Yes, we have consistently used AAV 6 due to its relatively broad tissue tropism (Verdera et al., 2020, Molecular Therapy) and we have clarified this information in the revised manuscript (see line 331). We agree with the Reviewer's concerns regarding the variable transduction efficiency. We have previously tested different AAV capsids and found that AAV6 transduced mature HLCs at high levels (Zhang et al., 2022, Hepatol Commun). In this study, we also performed Western blot analysis to confirm successful CD63 overexpression by AAV transduction at different stages of hepatocyte differentiation. As shown in new Supplementare Figure 6, although there were some differences in transduction efficiency, the majority of all cells at each stage of differentiation were successfully transduced to ectopically express CD63. The authors claim that by using AAV to express HBsAg, they are mimicking the expression of HBsAg from the integrated sequence rather than cccDNA. However, it is the opposite, as AAV genomes, like cccDNA, remain as episomes in the cells. Yes, the Reviewer is conceptually correct and we apologise for the incorrect wording. In principle, we aim to trans-complement HBsAg in a setting outside of HBV infection and thus mimic the expression of antigen from integrated cells, although AAVs of course remain mostly episomal. We have clarified this in the revised manuscript (see lines 188 & 378). In response to Reviewer 3: Line 217: the complete inhibition of cell to cell spread by myrcludex suggests that there is no spread by cell-cell contact. This should be discussed. Revision Plan Yes, there is no evidence of HDV spread by cell-cell contact because, as the Reviewer correctly points out, BLV treatment almost completely blocked HDV de novo infection (Figure 2D & E). To our knowledge, cell-to-cell spread has not been demonstrated for HDV. According to our own studies by Zhang et al, 2021/2022, Journal of Hepatology, HDV spreads either extracellularly (which can be blocked by BLV) or by cell division (discussed in lines 362). Since HLC are similar to primary human hepatocytes and do not divide in vitro, we believe that extracellular spread is the predominant mode of spread in HLC (line 365). Line 210ff:Is there any evidence for syncytia formation in this system? No, we have not observed syncytia formation. Since HDV has no glycoproteins, we would not expect syncytia to form. Line 42: secrete should be replaced by release We thank the Reviewer for pointing out the inaccuracy in our terminology. We have replaced "secrete" with "release" (line 42). Line 241: proteins are not expressed, genes are expressed Thank you, we agree and changed the wording accordingly (line 246).
      4. Description of analyses that authors prefer not to carry out In response to Reviewer 1: Fig 1B: Unit is confusing, using terms usually used for titration of infectivity, from the virus input point of view, not from the cellular point of view. Can you use % infected cells instead, or "HDV infection rate" like in Supp Fig 1B? We apologise for this confusion. For other viruses, such as but not limited to HCV or HEV, the most common method is to report focus forming units per ml (FFU/ml). HLCs do not divide and, in the absence of HBV S antigen, no cell-division mediated HDV spread can occur and only single infection events can be observed (hence infectious unit = IU/ml). Since differentiated, authentic hepatocyte culture models such as PHHs, HLCs or HepaRG cells are always characterised by strong cell heterogeneity, it is difficult to directly compare the overall percentage of infection with a homogeneous cell population such as Huh7-NTCP cells. Therefore, if the Reviewer allows us, we prefer to keep this unit in our main figures. However, and hopefully to the satisfaction of this Reviewer, we have also calculated the percentage of infected cells of this exact dataset and show it in the Supplementary figures (Suppl. Fig. S1 C). The proportion of infection efficiency comparing HLCs, dHepaRGs, and Huh7-NTCP cells does not differ when presented either as IU/ml or as percentage of infected cells.
    2. 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

      In their manuscript entitled " An HBV/HDV Infection Model Using Human Pluripotent Stem 1 Cell-Derived Hepatocyte- Like Cells for Virus Host Interactions and Antiviral Evaluation" describe the use of HLCs derived from hPSCs as infection model for analysis of HDV life cycle. The ms is well written and clearly structured. It is easy to follow the concept of the study. The ms addresses a relevant topic and could help to overcome limitations in the analysis of HDV life cycle. The authors perform in many points a detailed characterization of this experimental system but there are still a variety of open points which must be addressed:

      Specific points:

      Line 143: the authors describe two forms of HLCs (less and more confluent with differences regarding the susceptibility to HDV infection). The characteristics of the less and more confluent HLCs should be described in more detail-what is causative fir the differences in susceptibitly for HDV infection of these two forms? The statistical analyses should be improved: There are no p-values provided for the data presented in the supplement and a variety of figures lacks p-values Kinetic of the infection: Here it would be interesting to see a comparative analysis by western blot investigating the ratio HBsAg/HDAg over the time in HLCs, HepaRGs and NTCP oe cells

      Line 157: What is the experimental evidence for the proper localization and functionality of the ectopically expressed NTCP in HLCs. Did the authors study the taurocholate transport after overexpression of NTCP?

      Line 169: The authors should include data comparing the number of double positive cells in HLs, HepaRGs and NTCP o.e. expressing cells under the chosen experimental conditions

      Line 217: the complete inhibition of cell to cell spread by myrcludex suggests that there is no spread by cell-cell contact. This should be discussed.

      Line 210ff:Is there any evidence for syncytia formation in this system?

      Line 291: expression analysis by RT-PCR is not sufficient. It will be important to study by CLSM if the identified factors are really present as proteins and properly localized. Regarding the role of CD63: what is the evidence for a direct role of CD63 for HDV entry-can the authors exclude that CD63 is relevant for targeting other factors to the surface? What is the impact of loss of CD63 on the functionality of the autophagosomal-MVB-EV system in HLCs?

      Minor points:

      Line 42: secrete should be replaced by release Line 241: proteins are not expressed, genes are expressed

      Significance

      The manuscript describes the use of HLCs derived from hPSCs as infection model for analysis of HDV life cycle. The ms is well written and clearly structured. It is easy to follow the concept of the study.

      The ms addresses a relevant topic and could help to overcome limitations in the analysis of HDV life cycle. The authors perform in many points a detailed characterization of this experimental system but there are still a variety of open points which must be addressed.

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

      Learn more at Review Commons


      Referee #2

      Evidence, reproducibility and clarity

      In the present work, Chi et al. demonstrated that Hepatocyte-like cells (HCLs) derived from human pluripotent cells (hPCs) can be infected by HBV. The development of new HDV cellular models is of great value for understanding HDV biology and developing new treatments. However, the relevance of the present work is limited by a recent publication by Lange et al., in which they also showed that HCLs derived from hPCs can be infected by HDV, inducing the activation of the innate immune response, as previously demonstrated in cells and mice.

      The authors added new information to the work of Lange et al, including:

      • HLCs derived from human pluripotent cells can be infected by different HDV genotypes.
      • They proved that infectious HDV particles are formed.
      • They identified CD63 as a potential HDV coreceptor.

      The manuscript would benefit from a more detailed virological analysis, such as:

      • Determination of HDV genome and antigenome sequences and analysis of HDV editing.
      • Analysis of HDV short and large antigens by western blot.
      • Analysis of HBV-related virological parameters in monoinfected and co-infected cells.

      Additional information that needs to be added, better explained, or corrected:

      The authors should explain why they used different MOIs depending on the genotype.

      In Figure 1, it is unclear on which day the HCLs were infected by HDV and on which day they were transduced with AAV-NTCP.

      It is not very clear if the authors used AAV serotype 6 consistently to transduce the cells. It would be valuable to show the transduction efficiency of AAV at different time points of HLC maturation, as it might also be affected and could explain some results.

      For example, in Figure 6H, why does AAV-CD63 transduction increase HDV infectivity at day 15 but not at day 10? It would be interesting to repeat the anti-CD63 western blot after AAV-CD63 transduction.

      The authors claim that by using AAV to express HBsAg, they are mimicking the expression of HBsAg from the integrated sequence rather than cccDNA. However, it is the opposite, as AAV genomes, like cccDNA, remain as episomes in the cells.

      Significance

      In the present work, Chi et al. demonstrated that Hepatocyte-like cells (HCLs) derived from human pluripotent cells (hPCs) can be infected by HBV. The development of new HDV cellular models is of great value for understanding HDV biology and developing new treatments. However, the relevance of the present work is limited by a recent publication by Lange et al., in which they also showed that HCLs derived from hPCs can be infected by HDV. The authors added new information to the work of Lange et al, including:

      • HLCs derived from human pluripotent cells can be infected by different HDV genotypes.
      • They proved that infectious HDV particles are formed.
      • They identified CD63 as a potential HDV coreceptor.
    4. 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 the present manuscript, H Chi et al describe the infection of stem cell derived hepatocytes with HBV and HDV. They suggest that it could be used to validate antiviral treatment in a mature hepatocyte model. Moreover, they take advantage of the differentiation process of the cells to identify time points correlating with significant change in viral permissivity, and focus on one of these time points in an attempt to identify new host factors of HDV.

      Overall, the manuscript is well written and brings interesting information toward the establishement of an efficient HBV HDV coinfection model in stem cell derived hepatocytes. Particularly, comparison to dHepaRG, another model relying on in vitro differentiation and commonly used to study HBV and HDV infection, reveals the potential of stem cell derived hepatocytes. While the efficiency of co infection in the stem cell derived hepatocytes may seem low, the manuscript goes in the direction of helping establishing a new mature in vitro model of infection.

      Figure 1: The observation of a denser subpopulation of hepatocytes more susceptible to HDV is interesting. Do you have more characterization of this cell subpopulation, by IFA, in term of hepatic maturation marker, known HDV host factors and particularly NTCP expression?

      Fig 1B-C: the comparison with dHepaRG is very interesting, and confirms the validity of SC derived hepatocytes as a model for HDV infection. dHepaRG can be heterogeneous. Do you also see the same phenotype of enriched HDV infection within a denser subpopulations of dHepaRG?

      Fig 1B: Unit is confusing, using terms usually used for titration of infectivity, from the virus input point of view, not from the cellular point of view. Can you use % infected cells instead, or "HDV infection rate" like in Supp Fig 1B?

      Fig 1B and C: Can a BLV control be included in the figure?

      Fig 1A-F: What is the overall level of NTCP between HLC, HepaRG, Huh7NTCP and HLC-AAV-NTCP? Can NTCP and HDAg be stained simultaneously in your cells?

      Fig 1I is confusing. Was BLV assay also performed on the HLC infection (Day 0), or only during the titration assay in Huh7NTCP?

      Fig 1K: x-axis is confusing... is it number of HBV, HDV and HBV/HDV positive cells? Or number of infected cells upon inoculation with HBV, HDV, or both? Please clarify.

      Figure 2: The AAV based vector to over express HBsAg is a very interesting tool, and the figure convincingly show production of HDV progeny viruses in HLC-AAV-HBsAg. Results shown are in agreement with previous studies based on hepatoma cell lines.

      Figure 2B: What is IU/ml? Infectious Unit? International Unit? Are units in Fig 1B, 2B and 2C the same?

      Figure 3: What is the overall number of transmission events observed in the co-culture setup? Can you visually observed viral spreading? Panel A shows only 1 event, making it hard to assess its efficiency. Titration assay in Fig 2C show production of up to 4-5 log of infectious HDV. But HLCs susceptibility to HDV infection may change during time...

      Figure 4: While the strategy is interesting, based on what has been previously shown for HCV in Wu et al., 2012, the lack of statistical data prevents the reader to really understand and see drastic difference in term of susceptibility to infection and level of expression of host genes. In panel C, is the difference between day 13 and 15 statistically significant? Same for panel D, day 17 vs 19? As a remark, day 19, the peak of susceptibility to HDV, seems to be also the peak of maturation, based on ALB RTqPCR (panel B).

      Figure 5: In panel A, GO pathways should be sorted based on significance, not Number of genes. In panel B-D, what is the scale of the heatmap on figure 5: change in CPM values, however log2, log10?

      Figure 6: Do you have info about CD63 in other mature model, like dHepaRG and PHHs? Is CD63 also limiting in these models?

      Significance

      Overall, the manuscript brings interesting information toward the establishement of an efficient HBV HDV coinfection model in stem cell derived hepatocytes. Particularly, comparison to dHepaRG, another model relying on in vitro differentiation and commonly used to study HBV and HDV infection, reveals the potential of stem cell derived hepatocytes. While the efficiency of co infection in the stem cell derived hepatocytes may seem low, the manuscript goes in the direction of helping establishing a critical needed and long awaited mature in vitro model of HDV HBV infection.

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      Reply to the reviewers

      REVIEWER #1:

      The authors identify ZMYND8 as a bromodomain protein: is there evidence the actions described in this paper involve interaction of ZMYND8 with acetylated lysines? Does this mechanism play a role in ZMYND8's transcriptional regulatory activities?

      ZMYND8 is recruited to chromatin via its Bromo, PHD, and PWWP domains which recognize H3K4me1 and/or H3K14ac marks. Methyl marks on H3K4 are regulated by several lysine methyltransferases (e.g., MLL family and SETD1A/B) and demethylases (e.g., KDM5A-D) while H3K14ac is regulated by GCN5/PCAF, p300/CBP and/or Myst3. ZMYND8 also recruits histone deacetylases to chromatin including members of the highly conserved Nucleosome Remodeling and Deacetylase (NuRD) complex, HDAC1 and HDAC2. NuRD primarily deacetylates H3K27ac marks, however it is possible other acetyl moieties are affected by this complex.

      Using ChIP-seq, we now show that Zmynd8-cKO cardiomyocytes retain H3K27ac marks at misexpressed genes. Interestingly, while some of these genes have altered H3K27ac at their promoters (and therefore have full-length misexpressed transcripts; i.e., Casq1, Cdh16) other genes (e.g., Lamb3, Chst3) show changes in H3K27ac in the middle of the gene and this tracks with gene expression changes. We interpret this unusual transcript and H3K27ac pattern as evidence of potential ZMYND8-regulated intragenic enhancer elements. We include the following in our resubmission:

      1. Figure 5 which shows changes in H3K27ac levels at different genes, showing examples of genome browser tracks at the following genes Casq1, Cdh16, Camk1g, and Chst3.
      2. Supplemental Figure S5 showing H3K27ac and H3K27me3 marks at the cardiac myosin locus (i.e., Myh6 and Myh7) and surrounding genes in control and Zmynd8-cKO * We also show retention of H3K27ac at the Zmynd8 gene in Zmynd8-cKO cardiomyocytes, again supporting an autoregulatory mechanism of Zmynd8 *expression.
      3. An additional section in Results titled “H3K27 acetylation marks are retained at specific loci in Zmynd8-cKO cardiomyocytes”
      4. New “ChIP-seq and Analysis” section in Materials and Methods
      5. An updated model in Figure 6 that includes ZMYND8’s activities in modulating H3K27ac levels This first analysis on H3K27ac and H3K27me3 deposition in Zmynd8-cKO cardiomyocytes is not comprehensive and genome-wide analysis on these datasets will ultimately be performed in combination with additional datasets including ZMYND8 ChIP-seq from isolated cardiomyocytes. However, given the pertinence to ZMYND8’s transcriptional activities and in response to this reviewer’s critique, we include this pertinent H3K27ac and H3K27me3 ChIP-seq data.

      Given the newness of this model and multiple isoform issues, the authors should show the entire gel for the westerns in SFigure 1C.

      We now show the entire blots for all western blots in Supplementary Figure 1.

      Nuclear staining is in SFigure 1E (typo in text): most of the staining in the control is non-myocyte and non-nuclear, making the statement about IHC showing depletion less convincing for Nkx lines.

      We have fixed the typo in the text on page 5 line 128 and now correctly refer to this figure as Supplemental Figure S2. To better visualize nuclear ZMYND8 staining in this figure, we now show an adjusted image with increased contrast and brightness settings on both control and Zmynd8-cKO images and added arrowheads to indicate nuclei in the isolated cardiomyocytes. We also note that the flox sites only span the nuclear localization sequence for the protein so cytoplasmic ZMYND8 may still be present in Zmynd8-cKO cells.

      Regarding perinuclear ZMYND8 staining: am I accurate in observing the perinuclear staining is still present in the KO? What do the authors make of this?

      We do not observe perinuclear staining of ZMYND8 in KO cells. In Figure 1C, we believe the reviewer is observing potential staining in the cytoplasm, not perinuclear staining of ZMYND8 that we see in the control Myh6-CreTg/0 cardiomyocytes. We have added yellow arrowheads in Figure 1C to delineate perinuclear ZMYND8 staining we describe in the text.

      What is the protein amount in the Zmynd8fl/+ mice? Do the hearts upregulate the protein to compensate?

      We have added a gel in Supplemental Figure 1 that now shows protein isolated from Myh6-CreTg/0; Zmynd8fl/+ hearts and Myh6-CreTg/0 controls (Supplemental Figure 1C, right gel). It does not appear that Myh6-CreTg/0; Zmynd8fl/+ cardiomyocytes upregulate ZMYND8 to compensate for loss of one allele, as determined by Western blotting. However, our analysis shows differing ratios of the detected bands between conditional heterozygous mice, underscoring the need to further study the different ZMYND8 species present in cardiomyocytes. We state this in the results section (page 5, lines 123-124).

      Do the individual cardiomyocytes hypertrophy in the Zymnd8 cKO mice? Do they proliferate?

      Our analysis of cardiomyocyte morphology does reveal hypertrophy. The results we report include a new observation of variation in cell shape and are likely at least as sensitive as WGA staining which we find to be confounded by sectioning artifacts, cell identity, and position of the sections in the heart. We do not observe changes in H3S10ph staining between wild type and knockout hearts (data not shown) however we acknowledge further analysis of this may be warranted via other cell proliferation markers.

      Regarding this statement: "These results show that ZMYND8 is necessary to prevent the onset of contractile dysfunction that leads to heart failure and death." I think what the authors showed is that loss of ZMYND8 causes contractile dysfunction, heart failure and death.

      We acknowledge the difference in these statements and have now changed the text on page 7, lines 160-162 to “…these results show that loss of ZMYND8 from cardiomyocytes leads to contractile dysfunction, heart failure, and death.”

      The switch like up regulation of skeletal muscle genes is an interesting observation. Do the authors have any evidence how this works? Other studies with EZH2 are mentioned, and if ZYMND8 is in fact acting as a bromodomain, the mechanism might involve regulation of enhancer methylation/acetylation at K27. This is testable, certainly at the target genes the investigators have identified (Casq1 and Tnni2), by ChIP-PCR.

      As described above, we now include ChIP-seq data of H3K27ac and H3K27me3 marks in control and Zmynd8-cKO cardiomyocytes. As the reviewer suggests, there is retention of H3K27Ac marks in cKO cardiomyocytes, suggesting that ZMYND8 is necessary to recruit histone deacetylases to specific loci to remove acetyl moieties from H3K27. Regarding specific skeletal muscle genes, we do find a difference in histone acetylation at the promoter of the Casq1 gene and show this in Figure 5.

      The model in Figure 4C makes sense, but the authors do not present any data to support this molecular mechanism. If the authors ChIP for localization of TFs in KO vs control and/or examine histone marks, they could build support for this model, particularly since they have already identified target genes.

      We have now updated our model in Figure 6 to include ZMYND8’s role in modulating H3K27ac levels at target loci, leading to upregulation of mRNA transcripts. We add consideration of the implications of this in the Discussion.

      Reviewer #1 (Significance (Required)):

      The authors identify ZMYND8 as a bromodomain protein: is there evidence the actions described in this paper involve interaction of ZMYND8 with acetylated lysines? Does this mechanism play a role in ZMYND8's transcriptional regulatory activities? We include new data to demonstrate this. Please see above.

      REVIEWER #2:

      The study is reporting the role of ZMYND8 chromatin factor in the mouse heart. Mutations have been previously identified in genetic studies of atrioventricular septal defects and syndromic congenital cardiac abnormalities. Therefore the authors perform cardiomyocyte specific knockout of exon 4 (with the nuclear localisation signal) using Myh6 and Nkx2.5 cre. Full length protein seems to be removed from the nucleus. The knockout doesn't seem to affect embryonic development, but leads to hypertrophy and premature death. The authors perform transcriptome analysis and find 55 upregulated and 4 downregulated genes that are mainly related to contraction and ion transport. especially they find skeletal muscle proteins including fast-twitch troponin I upregulated. Tnni2 seems to be integrated into the sarcomeres, albeit the antibody staining is not in the expected location (see below). Shape of cardiomyocytes was apparently different, although this is seemingly not related to Tnni2 expression.

      Specific points: - ZMYND8 has been previously linked to atrioventricular septal defects, but the authors do not explore if this is the case also in their model; could the authors please expand

      We have not seen obvious septal defects in any Zmynd8-cKO mice. We now state this explicitly in the Results section on page 7, lines 159-160 and discuss this discrepancy from the observations in humans in our Discussion on page 12. The human study analyzing families carrying Zmynd8 mutations reported a variety of heart malformations in 7 of the 11 individuals. The septal defects observed in these individuals were not consistent and may be incidental to the molecular function of ZMYND8 within cardiomyocytes. One possibility is that these malformations are caused by stress during development, with Zmynd8 mutations sensitizing the heart to these defects. We acknowledge in the discussion that further analyses of septal defects in this knockout model could be useful in the future with more stringent stereoscopic techniques.

      • the initial section is difficult to follow. Especially, the authors seem surprised regarding the size of the bands. They should make clear what the expected band size should be after removal of exon 4 and if this doesn't fit, explore the reasons experimentally if possible.

      Rigorous analyses of the different Zmynd8 isoforms in cardiomyocytes will be a focus of future work as this may explain the mosaicism seen in cKO cardiomyocytes and the discrepancy between TNNI2 expression and cell shape (see below). We have reorganized the section and discuss potential explanations for our observed band sizes.

      • the authors explore the shape of the cardiomyocytes and find cells that are shorter and thicker. It would be meaningful to include other metrics including, sarcomere length, contractility measurements and calcium transients (especially in light of the change ion transporters).

      We agree that an investigation of the effects of the mutation and the skeletal muscle proteins on cellular contractility could be very interesting. Here we have contented ourselves with evaluating the effects at a physiological level through assessment of cardiac function.

      • it is unclear why Tnni2 stains for the M-band (where in fact should be no actin and troponin) and not a typical double band with the H zone excluded (see here for good staining example: https://www.biorxiv.org/content/10.1101/2020.09.09.288977v1.full.pdf). also the staining looks very fuzzy. can the authors provide evidence that the antibody is staining troponin I in skeletal muscle at the correct localisation to demonstrate the specificity of the antibody?

      We thank the reviewer for raising this point and do agree that there are instances where we observe TNNI2 staining colocalizing with MYOM1 staining. After closer examination of our images, we believe we do also see TNNI2 staining between M-lines and attribute this discrepancy to our antibody staining and/or biological differences between cells however, further analysis with better microscopy and immunostaining techniques is warranted. We have added an additional image to Figure 4A and have modified this results section on page 9, lines 217-222.

      • it is interesting why Tnni2 is detectable only in a subfraction of cells, but this remains unexplored. Could this e.g. be right vs left ventricular cardiomyocytes? or is this related to the remaining isoforms of ZMYND8? The authors should try to identify the source of this variability

      We agree that the TNNI2 mosaicism is an interesting phenotype and thank the reviewer for possible explanations. We favor the model of mosaicism being an effect of compensatory mechanisms by other ZMYND8 isoforms and discuss this in the discussion on page 8, line 228-229. This will be a focus of future work.

      • if Tnni2 is unrelated to the changes in hypertrophic phenotype of the cardiomyocytes, then the authors should aim to identify if one of the other differentially regulated proteins might be related (e.g. ion transporter). The experiments above might help to identify this

      We agree that identifying the causal agents of hypertrophy in this model would be interesting. It is however possible that we are simply seeing the expected effect of reduced contractility leading to hypertrophic compensation. Sorting this out will require additional mutant analyses and/or siRNA experiments all of which come with their own caveats and are outside of the scope of this initial analysis. Our aim for this manuscript was to report on the effects of ZMYND8 removal from cardiomyocytes. Additionally, it is certainly possible that phenotypes we report in this article are independent of the gene expression changes we have detected in the mutant and could be caused by other roles for ZMYND8 such as the DNA damage response. We include this possibility in our discussion.

      Reviewer #2 (Significance (Required)):

      Overall the manuscript is interesting in principle - it documents the role of a disease linked protein that hasn't been explored in the heart in detail, however at this point it seems premature and doesn't follow through on a solid detailed analysis.

      The change in transcription profiles and especially the upregulation of skeletal muscle isoforms is intriguing, but should be further explored. There seems a lack of hypothesis and instead the authors analyse Tnni2 and cell shape, but while the cell shape is different they don't find a correlation with Tnni2. so if the authors suggest that cell shape is important (as indeed might be), how is this regulated?

      Our goal for this initial paper is to describe the physiological and molecular phenotypes of the Zmynd8-cKO mouse model. It would be interesting to pursue a study directed at this question, perhaps of cell sorted "fat" and "thin" myocytes, but that would be beyond the scope of this report.

      The study could be of interest to cardiovascular researchers, but needs to be expanded on the points above.

      My expertise is in cardiovascular research

      REVIEWER #3:

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

      Summary:

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

      The authors found that Zmynd8-cKO mice develop dilated hearts, decreased cardiac function, and illegitimate expression of skeletal muscle genes. They concluded that ZMYND8 is necessary to maintain appropriate cardiomyocyte gene expression and cardiac function.

      Major comments:

      • Are the claims and the conclusions supported by the data or do they require additional experiments or analyses to support them? The claim that "Zmynd8 is dispensable for cardiac development" is not supported by the lethality of Zmynd8 D/D mice.

      We interpret our observation that viable Nkx2.5-CreTg/0; Zmynd8fl/fl mice are born and grow to adulthood as evidence that Zmynd8 is not necessary for establishment of the cardiac lineage. However, we do agree that labeling Zmynd8 as dispensable is not supported by the experiments using Zmynd8D/D mice. We hypothesize that the lethality of the Zmynd8D/D mice is due to early embryonic events since empty egg sacs were observed at E8.0, however we do agree that ZMYND8’s role in cardiac development cannot be assessed using this line. We state that empty yolk sacs are found in mother uteri 8 days after mating on page 4, lines 94-96.

      • Please request additional experiments only if they are essential for the conclusions. Alternatively, ask the authors to qualify their claims as preliminary or speculative, or to remove them altogether. The claim should be changed into "function of Zmynd8 in cardiac development can not be fully assessed in Zmynd8 D/D mice".

      We agree that the lethality of Zmynd8D/D * mice prevents any analysis of early embryonic roles for the establishment of the cardiac lineage. This is additionally confounded by the fact that other partial-length isoforms of Zmynd8* may still be present in our knockout model. We have modified our interpretation and have further discussed the potential role of ZMYND8 in early cardiac development on page 4, line 96.

      • If you have constructive further reaching suggestions that could significantly improve the study but would open new lines of investigations, please label them as "OPTIONAL". OPTIONAL: What about the phenotype of Nkx2-5 Cre mediated knockout of Zmynd8? Is it more severe than Myh6 Cre mediated knockout? At more earlier embryonic stage when cardiomyocytes are differentiated, are the skeletal muscle developmental genes ectopically upregulated in heart tube?

      This is an interesting observation and deserves further investigation. Our initial analysis of Nkx2.5-CreTg/0; Zmynd8fl/fl mice reveals that these mice do not die earlier than Myh6-CreTg/0; Zmynd8fl/fl mice or have a more severe phenotype. In fact, mice with Nkx2.5-Cre mediated cKO mice live longer than Myh6-Cre mediated cKO mice. We show that these mice do have ZMYND8 depleted from their cardiomyocyte nuclei and ectopically express TNNI2.

      This discrepancy in phenotype has been observed recently in mice lacking Kdm8 (Ahmed et al, 2023) and has been attributed to a lower efficiency of the Nkx2.5-Cre recombinase compared to Myh6-driven Cre.

      • Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated time investment for substantial experiments. Yes.

      • 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? Yes.

      Minor comments:

      • Specific experimental issues that are easily addressable. Have the female Zmynd8-cKO mice always died before their male siblings been pregnant with heart overload?

      All lifespan data are of non-pregnant females. All mice (i.e., both males and females) used in these analyses were not used for mating. We now explicitly say this in the mouse husbandry section of our Materials and Methods section.

      • Are prior studies referenced appropriately?

      This paper "De Novo ZMYND8 variants result in an autosomal dominant neurodevelopmental disorder with cardiac malformations" should be referenced.

      Thank you. We have referenced this paper (Dias et al. 2022) on page 3, line 61 as well as in the Discussion on page 9, line 211.

      • Are the text and figures clear and accurate? Description of "cardiomegaly, preventing a compact myocardium phenotype, heart enlargement and thinning of the ventricular" should be more accurate and professional. We have changed the following in the text:

      Page 6, line 150 “preventing a compact myocardium phenotype” to “during later stages of cardiac development” on

      Page 6, line 153 “heart enlargement” to “The heart weight of Zmynd8-cKO mice”

      Page 7, line 158 “thinning of the ventricular” to “dilated cardiomyopathy”

      • Do you have suggestions that would help the authors improve the presentation of their data and conclusions? GSEA analysis of RNA-seq can be used to show the enrichment of cardiac and skeletal genes.

      Because GSEA analysis requires at least three replicates per group to have the appropriate statistical power, we opted to show Gene Ontology analysis using DAVID software.

      Reviewer #3 (Significance (Required)):

      • General assessment: provide a summary of the strengths and limitations of the study. What are the strongest and most important aspects? What aspects of the study should be improved or could be developed? This study show that Zmynd8-cKO mice develop dilated hearts, decreased cardiac function, and illegitimate expression of skeletal muscle genes. However, the genes regulated by Zmynd8 during early developmental stage have not been identified and the functional mechanism of Zmynd8 during heart development remains unclear.

      • Advance: compare the study to the closest related results in the literature or highlight results reported for the first time to your knowledge; does the study extend the knowledge in the field and in which way? Describe the nature of the advance and the resulting insights (for example: conceptual, technical, clinical, mechanistic, functional,...). Genetic mutations of Zmynd8 have been identified in congenital heart diseases with cardiac structural defects. And this study further shows that dysfunction/weaker mutations of Zmynd8 as a reason for dilated cardiomyopathy with decreased function.

      • Audience: describe the type of audience ("specialized", "broad", "basic research", "translational/clinical", etc...) that will be interested or influenced by this research; how will this research be used by others; will it be of interest beyond the specific field? This study shows that dysfunction of Zmynd8 as a reason for dilated cardiomyopathy with decreased function. Researchers of "basic research" and "clinical" may be interested in this study.

      • Please define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. heart development, dilated cardiomyopathy, epigenetics

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      Referee #3

      Evidence, reproducibility and clarity

      Summary:

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

      The authors found that Zmynd8-cKO mice develop dilated hearts, decreased cardiac function, and illegitimate expression of skeletal muscle genes. They concluded that ZMYND8 is necessary to maintain appropriate cardiomyocyte gene expression and cardiac function.

      Major comments:

      • Are the claims and the conclusions supported by the data or do they require additional experiments or analyses to support them?

      The claim that "Zmynd8 is dispensable for cardiac development" is not supported by the lethality of Zmynd8 / mice. - Please request additional experiments only if they are essential for the conclusions. Alternatively, ask the authors to qualify their claims as preliminary or speculative, or to remove them altogether.

      The claim should be changed into "function of Zmynd8 in cardiac development can not be fully assessed in Zmynd8 / mice". - If you have constructive further reaching suggestions that could significantly improve the study but would open new lines of investigations, please label them as "OPTIONAL".

      OPTIONAL: What about the phenotype of Nkx2-5 Cre mediated knockout of Zmynd8? Is it more severe than Myh6 Cre mediated knockout? At more earlier embryonic stage when cardiomyocytes are differentiated, are the skeletal muscle developmental genes ectopically upregulated in heart tube? - Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated time investment for substantial experiments.

      Yes. - 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?

      Yes.

      Minor comments:

      • Specific experimental issues that are easily addressable.

      Have the female Zmynd8-cKO mice always died before their male siblings been pregnant with heart overload? - Are prior studies referenced appropriately?

      This paper "De Novo ZMYND8 variants result in an autosomal dominant neurodevelopmental disorder with cardiac malformations" should be referenced. - Are the text and figures clear and accurate?

      Description of "cardiomegaly, preventing a compact myocardium phenotype, heart enlargement and thinning of the ventricular" should be more accurate and professional. - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

      GSEA analysis of RNA-seq can be used to show the enrichment of cardiac and skeletal genes.

      Significance

      • General assessment: provide a summary of the strengths and limitations of the study. What are the strongest and most important aspects? What aspects of the study should be improved or could be developed? This study show that Zmynd8-cKO mice develop dilated hearts, decreased cardiac function, and illegitimate expression of skeletal muscle genes. However, the genes regulated by Zmynd8 during early developmental stage have not been identified and the functional mechanism of Zmynd8 during heart development remains unclear.
      • Advance: compare the study to the closest related results in the literature or highlight results reported for the first time to your knowledge; does the study extend the knowledge in the field and in which way? Describe the nature of the advance and the resulting insights (for example: conceptual, technical, clinical, mechanistic, functional,...). Genetic mutations of Zmynd8 have been identified in congenital heart diseases with cardiac structural defects. And this study further shows that dysfunction/weaker mutaions of Zmynd8 as a reason for dilated cardiomyopathy with decreased function.
      • Audience: describe the type of audience ("specialized", "broad", "basic research", "translational/clinical", etc...) that will be interested or influenced by this research; how will this research be used by others; will it be of interest beyond the specific field? This study shows that dysfunction of Zmynd8 as a reason for dilated cardiomyopathy with decreased function. Researchers of "basic research" and "clinical" may be interested in this study.
      • Please define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. heart development, dilated cardiomyopathy, epigenetics
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      Referee #2

      Evidence, reproducibility and clarity

      The study is reporting the role of ZMYND8 chromatin factor in the mouse heart. Mutations have been previously identified in genetic studies of atrioventricular septal defects and syndromic congenital cardiac abnormalities. Therefore the authors perform cardiomyocyte specific knockout of exon 4 (with the nuclear localisation signal) using Myh6 and Nkx2.5 cre. Full length protein seems to be removed from the nucleus. The knockout doesn't seem to affect embryonic development, but leads to hypertrophy and premature death. The authors perform transcriptome analysis and find 55 upregulated and 4 downregulated genes that are mainly related to contraction and ion transport. especially they find skeletal muscle proteins including fast-twitch troponin I upregulated. Tnni2 seems to be integrated into the sarcomeres, albeit the antibody staining is not in the expected location (see below). Shape of cardiomyocytes was apparently different, although this is seemingly not related to Tnni2 expression.

      Specific points:

      • ZMYND8 has been previously linked to atrioventricular septal defects, but the authors do not explore if this is the case also in their model; could the authors please expand
      • the initial section is difficult to follow. Especially, the authors seem surprised regarding the size of the bands. They should make clear what the expected band size should be after removal of exon 4 and if this doesn't fit, explore the reasons experimentally if possible.
      • the authors explore the shape of the cardiomyocytes and find cells that are shorter and thicker. It would be meaningful to include other metrics including, sarcomere length, contractility measurements and calcium transients (especially in light of the change ion transporters)
      • it is unclear why Tnni2 stains for the M-band (where in fact should be no actin and troponin) and not a typical double band with the H zone excluded (see here for good staining example: https://www.biorxiv.org/content/10.1101/2020.09.09.288977v1.full.pdf). also the staining looks very fuzzy. can the authors provide evidence that the antibody is staining troponin I in skeletal muscle at the correct localisation to demonstrate the specificity of the antibody?
      • it is interesting why Tnni2 is detectable only in a subfraction of cells, but this remains unexplored. Could this e.g. be right vs left ventricular cardiomyocytes? or is this related to the remaining isoforms of ZMYND8? The authors should try to identify the source of this variability
      • if Tnni2 is unrelated to the changes in hypertrophic phenotype of the cardiomyocytes, then the authors should aim to identify if one of the other differentially regulated proteins might be related (e.g. ion transporter). The experiments above might help to identify this

      Significance

      Overall the manuscript is interesting in principle - it documents the role of a disease linked protein that hasn't been explored in the heart in detail, however at this point it seems premature and doesn't follow through on a solid detailed analysis.

      The change in transcription profiles and especially the upregulation of skeletal muscle isoforms is intriguing, but should be further explored. There seems a lack of hypothesis and instead the authors analyse Tnni2 and cell shape, but while the cell shape is different they don't find a correlation with Tnni2. so if the authors suggest that cell shape is important (as indeed might be), how is this regulated?

      The study could be of interest to cardiovascular researchers, but needs to be expanded on the points above.

      My expertise is in cardiovascular research

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

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      Referee #1

      Evidence, reproducibility and clarity

      The authors identify ZMYND8 as a bromodomain protein: is there evidence the actions described in this paper involve interaction of ZMYND8 with acetylated lysines? Does this mechanism play a role in ZMYND8's transcriptional regulatory activities?

      Given the newness of this model and multiple isoform issues, the authors should show the entire gel for the westerns in SFigure 1C. Nuclear staining is in SFigure 1E (typo in text): most of the staining in the control is non-myocyte and non-nuclear, making the statement about IHC showing depletion less convincing for Nkx lines.

      Regarding perinuclear ZMYND8 staining: am I accurate in observing the perinuclear staining is still present in the KO? What do the authors make of this?

      What is the protein amount in the Zmynd8fl/+ mice? Do the hearts upregulate the protein to compensate?

      Do the individual cardiomyocytes hypertrophy in the Zymnd8 cKO mice? Do they proliferate?

      Regarding this statement: "These results show that ZMYND8 is necessary to prevent the onset of contractile dysfunction that leads to heart failure and death." I think what the authors showed is that loss of ZMYND8 causes contractile dysfunction, heart failure and death.

      The switch like up regulation of skeletal muscle genes is an interesting observation. Do the authors have any evidence how this works? Other studies with EZH2 are mentioned, and if ZYMND8 is in fact acting as a bromodomain, the mechanism might involve regulation of enhancer methylation/acetylation at K27. This is testable, certainly at the target genes the investigators have identified (Casq1 and Tnni2), by ChIP-PCR.

      The model in Figure 4C makes sense, but the authors do not present any data to support this molecular mechanism. If the authors ChIP for localization of TFs in KO vs control and/or examine histone marks, they could build support for this model, particularly since they have already identified target genes.

      Significance

      The authors identify ZMYND8 as a bromodomain protein: is there evidence the actions described in this paper involve interaction of ZMYND8 with acetylated lysines? Does this mechanism play a role in ZMYND8's transcriptional regulatory activities?

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      Reply to the reviewers

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

      In this manuscript, the authors report a novel and simple method to analyze the heterogeneity of various organelles. After imaging a large set of fluorescent-marker-labeled organelles, cluster analysis is adapted for illuminating the dynamics of organelles. Through this novel method, the authors are able to report organelle contact, which previously can only be observed by super-resolution imaging. This is method could significantly accelerate future discoveries at the cellular level. The manuscript is well written and has the potential be published in high-ranking journals, after a minor revision.

      To further demonstrate the unique power of this new method, the authors should test cells under known stimulation altering the dynamics of organelles. For instance, wortmannin can blocks the conversion from early endosomes to late endosomes. By doing that, the potential of this new method will be endorsed.

      Response:

      We thank Reviewer #1 for the positive comments. We will add an experiment using wortmannin to block the process of endocytosis at a specific stage, as part of the experiments analyzing the process of endocytosis.

      **Minor issue:** The authors should include more details about how to avoid signal crosstalk between adjacent fluorescent channels.

      Response:

      In the Methods section, we have added the following sentences to Lines 398-405.

      “In order to avoid signal crosstalk between adjacent fluorescence channels, eight fluorophores with distinct spectral distances were selected, and the samples were irradiated sequentially with lasers in the order from the longest wavelength, i.e., fluorescence from 646 to 731 nm was excited by a 640 nm laser, fluorescence from 569 to 634 nm was excited by a 561 nm laser, fluorescence from 494 to 554 nm was excited by a 488 nm laser, and fluorescence from 411 to 481 nm was excited by a 405 nm laser, as shown in Extended Data Fig. 1b.”

      Reviewer #1 (Significance (Required)):

      The comprehensive monitoring of organelle dynamics through the integration of multi-dimensional parameters can proficiently evaluate the condition and prognosticate the destiny of living cells in response to external stimulations. This new multi-dimensional assay reported in this manuscript represents a huge step towards this goal. Since this new method is simple and powerful, cell biologists will quickly start to use this new method for the study of subcellular dynamics.

      My lab is also developing a similar approach for organelles based on super-resolution imaging. I would like to congratulate the authors for this beautiful work.

      Response:

      We thank Reviewer #1 for the positive comment.

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

      The manuscript reports a multi-parametric particle-based method for analysis of organelles. The method aims to resolve heterogeneous populations of organelles involved in various cellular processes. They propose to isolate organelles labelled with multiple markers, after homogenization and sonification of the cells, and analyse the resulting particles by fluorescence microscopy using spectral imaging. Afterwards, the authors visualize and analyse the obtained data with dimension reduction techniques.

      Even though an interesting approach, the method and presented applications needs major improvisations before it can prove to be impactful for the field

      I note some possible improvement points below:

      • Initially, I think the current set of cell lines and labels should be extended also to include a wider set. The current limited set raises the question if the method authors report is also applicable to other cell lines, or if it only feasible with overexpressed markers. Including different cell lines with different labels would make the study more convincing and comprehensive.

      Response:

      We thank Reviewer #2 for this constructive comment. Regarding cell types, we will conduct experiments with HEK293T cells in addition to HeLa cells, labeling at least five different types of typical organelles. In our method, as shown in Figure 1a and 5a, we have already used not only overexpressed markers but also fluorescently labeled ligands (EGF-Alexa, transferrin-Alexa) and antibodies against endogenous proteins (anti-PMP70, anti-LAMP1), as well as direct labeling of cell membrane proteins (Alexa-NHS). Therefore, there are no significant limitations with respect to organelle labeling methods.

      • It is surprising that the authors explicitly list already the limitations of fluorescence microscopy and super-resolution microscopy in the second paragraph of their introduction, however present a method fully dependent on fluorescence labelling and imaging methods. Actually their approach takes away the spatial information of FM approaches, and further makes the approach prone to the limitations they state.

      They are also not fully fair about the limitation they state for Electron microscopy, as newly developed approaches (e.g. doi:10.1093/micmic/ozad067.1091;  doi:10.1126/science.aay3134) widely extend the limited field of view and sampling capacity of EM. I recommend the authors to state the potential advantage/superiority of the reported method rather than stating the unclear limitations of the existing powerful methods.

      Response:

      Regarding fluorescence microscopy, it appears that our description was inadequate and misled the reviewers. There is no problem with fluorescence microscopy itself. What we intended to convey was that “when attempting to detect individual organelles ‘in cells’, there are limitations in the resolution of fluorescence microscopy because organelles are densely packed”. We have added this to the text on Line 49. Also, we thank Reviewer #2 for informing us about the high-speed 3D electron microscopy. We have cited the indicated papers in the text at Lines 54-55 and mention that “except for the recently developed high-throughput electron microscopy”.

      • Most organelle markers the isolation of organelles are based on are overexpressed in the cells: endoplasmic reticulum (ER, mTagBFP2 (BFP)-SEC61B), mitochondria (GFP-OMP25 and SNAP-OMP25), and the Golgi (Venus-GS27). This raises significant questions about the native state relevance of the reported results, and how well they represent the endogenous processes.

      Response:

      We will add experiments analyzing the behavior of both endogenous and exogenous markers for the same organelles, for example, anti-LAMP1 antibody and VAMP7-GFP for lysosomes, and anti-PMP70 antibody and PEX16-GFP for peroxisomes.

      • For the application on endosomes, can the authors state what is the new information enabled by their method? They study the very trafficking of EGF and Transferrin, 2 widely used endosomal cargoes with very well characterized trafficking steps, and show they are trafficked through Rab5/7 and Rab11 positive endosomes, respectively. This recapitulates the existing information, however falls short in delivering new insight. The authors can use these cargoes for proof-of-concept, but I would recommend to extend their study with less exploited cargoes to represent the potential of the reported method to deliver new information.

      Response:

      We thank Reviewer #2 for the positive suggestion about the potential of our method to provide new information. However, to demonstrate new biological insights, it would take a lot of time and delay the provision of our methodology, so we would like to submit this manuscript as a Methods paper with the proof-of-concept data.

      Reviewer #2 (Significance (Required)):

      The significance of biochemical and cellular processes being spatially regulated cellular organelles, and the roles of specific organelles in diseases from cancer to neurodegeneration are continuously being discovered and appreciated. Therefore development of methods reporting on the structure and function of organelles is important to accelerate these studies. In the reported method, however, the ultrastructure (as in Fib 1b) and the spatial information of the cellular organelles are inherently lost. The method falls in between a biochemical and a microscopic approach, however the advantages are not clearly portrayed. I recommend the authors to carefully and explicitly state where their method would be the method of choice rather than a biochemistry, mass spectroscopy, or microscopy approach. The authors should critically consider such an experiment as a proof-of-concept case.

      Response:

      We thank Reviewer #2 for the valuable suggestion. We added the following to the Discussion (Lines 267-277).

      “A further potential application of our method would be to measure how the levels of key molecules in an organelle change during its differentiation or maturation. For example, the levels of PI4P and syntaxin 17 change during autophagosome maturation (Shinoda et al. eLife Preprint Review doi.org/10.7554/eLife.92189.1), which can be better demonstrated by this method using multiple markers for each stage of autophagosome formation and maturation, PI4P, and syntaxin17 because autophagosomes at different stages coexist in cells. In such cases, our single-particle analysis method, which examines the state of individual autophagosomes, would be more appropriate than biochemical methods that examine averages. In addition, it is difficult to quantitatively analyze many organelle structures in cells using fluorescence microscopy. Our particle-based analysis method can overcome this problem.”

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

      **Comments, suggestions, and questions**

      • I would like to start with a positive suggestion. The authors completely miss out on the opportunity to promote their approach by not relying on any type of fixation. In most multiplexing experiments, the first major challenge is to find antibodies that work well for imaging. The second challenge is then to find antibodies that work well under the same fixation conditions. The authors present a multiplexing approach that is completely independent of fixation. I suggest discussing this in the manuscript and promoting the approach in that regard.

      Response:

      We thank Reviewer #3 for pointing out the advantages of our method. We have added “Our method that is independent of fixation is advantageous for the optimization of the staining condition (Lines 298-299).

      • I am wondering what defines the ‘resolution’ of this approach. I assume it is a combination of the sonication time -the longer the cell is sonicated, the smaller the fragments are - and the density of particles on the coverslip. What are the limits here? How does this affect the UMAP analysis? I would encourage the authors to discuss this in the manuscript.

      Response:

      The particle density on a coverslip can be easily reduced by simply diluting the particles in a buffer solution. Therefore, there is no density limit, which is an advantage of a cell-free system. To improve the resolution within a single organelle, for example, to separate distinct subdomains, as the reviewer mentioned, we can prolong the sonication time to make the particles smaller. However, since this will reduce the signal-to-background ratio and destroy organelle contacts, we used the sonication conditions as mild as possible. To investigate organelle subdomains and fragile contacts, the sonication conditions need to be optimized carefully, which should affect the UMAP analysis, but we think that these will be future work.

      We do not think that prolonged sonication will affect the UMAP analysis because relative fluorescent signals of each particle would not change. However, as mentioned above, too strong sonication would worsen the signal-to-noise ratio, resulting in poor clustering.

      We have added the above discussion to the Discussion (Lines 288-293).

      “Also, to improve the resolution within a single organelle, for example, to separate distinct subdomains, we can prolong the sonication time to make the particles smaller. However, since this will reduce the signal-to-background ratio and may destroy organelle contacts, we used the sonication conditions as mild as possible. To investigate organelle subdomains and fragile contacts, the sonication conditions need to be optimized carefully.”

      • The only real control the authors present are the correlative light and electron microscopy (CLEM) three images in Figure 1b, which seems very minimalistic for a very central and essential control experiment. How many of these control images did the authors take? Is there possibly a second method for a control experiment to link the fluorescence readout to an organelle fragment (e.g., purification or pulldown)?

      Response:

      Since all the markers we used are well-established, we believe that there is no concern about the fluorescence readouts to the organelle fragments. We have cited the following papers in Lines 84-85.

      SEC61B: Rapoport, T. A., Jungnickel, B. & Kutay, U. Protein transport across the eukaryotic endoplasmic reticulum and bacterial inner membranes. Annu Rev Biochem 65, 271–303 (1996).

      OMP25: Horie, C., Suzuki, H., Sakaguchi, M. & Mihara, K. Characterization of signal that directs C-tail-anchored proteins to mammalian mitochondrial outer membrane. Mol Biol Cell 13, 1615–1625 (2002).

      GS27: Hay, J. C. et al. Localization, Dynamics, and Protein Interactions Reveal Distinct Roles for ER and Golgi SNAREs. J Cell Biol 141, 1489–1502 (1998).

      Fusella, A., Micaroni, M., Di Giandomenico, D., Mironov, A. A. & Beznoussenko, G. V. Segregation of the Qb-SNAREs GS27 and GS28 into Golgi Vesicles Regulates Intra-Golgi Transport. Traffic 14, 568–584 (2013).

      Although it is relatively easy to identify mitochondria-derived particles by EM based on their size and the presence of cristae-like structures (indeed we see many examples), it is more challenging for other organelles (because they appear simple vesicles). This is why we showed only mitochondria in Fig. 1b. Furthermore, the main purpose of this EM image is to show membrane contacts between the ER and mitochondria (related to Fig. 3).

      • Line 37-41: Could the authors please strengthen these statements with an appropriate citation (e.g., a review)?

      Response:

      We have cited the textbook Molecular Biology of THE CELL (the 6th edition, Chapter 12 and Chapter 13) in Lines 37 and 41.

      Response:

      We thank Reviewer #3 for notifying us of these important studies. We have rewritten the sentence on Lines 51-52 to read “Although multicolor imaging has been attempted with super-resolution microscopy (references of the indicated papers), it only partially solves the issue of resolution.”

      • The authors use spectral unmixing to overcome the limit of spectral multiplexing. While this has been demonstrated to work well for less than ten targets, it does not scale to multiplexing experiments with more than ten target species. I suggest that the authors discuss in the discussion part of the manuscript the potential of DNA-based multiplexed imaging, such as CODEX or DNA-PAINT, in combination with the presented approach.

      Response:

      In the Discussion (Lines 295-298), we have added the sentence “Current fluorescent particle detection uses spectral multiplexing, but this method has only been able to detect up to eight colors. Methods such as CODEX or DNA-PAINT with wide-field type illumination could significantly increase the number of targets”.

      Response:

      We thank Reviewer #3 for informing us. We have cited it in Line 72.

      • By using spectral unmixing for multiplexing, this method is limited to confocal due to spectral detection needs and therefore limited in throughput. It would be beneficial if it could work with wide-field type illumination. This could substantially increase the throughput, which is another reason why I think it would be important to discuss sequential multiplexing.

      Response:

      We agree with the Reviewer’s comment. We have added the discussion to Lines 295-298 as described in our response to Reviewer #3, Comment (6).

      • To image contact sites, the authors use split GFP. There have been discussions that split GFP might, in some cases, facilitate the process that is supposed to be measured, in this case, the formation of contact sites. I suggest using at transient version of split GFP, called split fast, for follow-up experiments in the authors’ next papers (https://www.nature.com/articles/s41467-019-10855-0).

      Response:

      We thank Reviewer #3 for providing this information. We will do it as suggested in the next paper.

      • Line 27 & 253: Please drop the term ‘intuitive’ or explain better what you mean by intuitive. For me, UMAP is certainly a very useful tool, but it is not at all what I would describe as intuitive.

      Response:

      We have deleted ‘intuitive’ in all seven places and rewritten them (Lines 27, 43, 58, 72, 180, 231, and 253).

      • Lastly, I want to mention that the authors state they used ChatGPT, DeepL, and DeepL Write for translation from Japanese to English. I appreciate their honesty.

      Response:

      We thank Reviewer #3 for the comment.

      Reviewer #3 (Significance (Required)):

      In the manuscript titled “Organelle Landscape Analysis Using a Multi-parametric-Based Method,” Kurikawa et al.present a method for multi-parametric, particle-based analysis of cellular organelles. After lysing cells, the fractions of the organelles are partially labeled with fluorescently tagged antibodies, while others are already tagged with fluorescent proteins, using six to eight spectrally different fluorescent dyes/proteins. These fractions are subsequently immobilized on a poly-L-lysine-coated coverslip. The authors use spectral unmixing to distinguish these markers. The6-8 multiplexed imaging data is then presented in two-dimensional UMAP space. The authors then use this approach to visualize seven major organelles, transitional sites of endocytic organelles, and contact sites between the endoplasmic reticulum and mitochondria using split GFP.

      The authors present, in my opinion, a conceptually new and interesting approach by combining spectral unmixing for imaging up to eight targets, with organelle fragment imaging, and presenting multidimensional data in two-dimensional Uniform Manifold Approximation and Projection (UMAP) space in this manuscript. They further validated this approach by linking the results of the experiments to results established or at least reported in the literature.

      In general, the manuscript is, in my opinion, a good fit for publication as it presents a conceptionally new approach and an interesting example of applying the UMAP approach, which might be of interest to a broader readership. Therefore, after an appropriate response to my comments, suggestions, and questions (see below), I would recommend this manuscript for publication.

      Response:

      We thank Reviewer #3 for the positive comment.

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      Referee #3

      Evidence, reproducibility and clarity

      Comments, suggestions, and questions

      • I would like to start with a positive suggestion. The authors completely miss out on the opportunity to promote their approach by not relying on any type of fixation. In most multiplexing experiments, the first major challenge is to find antibodies that work well for imaging. The second challenge is then to find antibodies that work well under the same fixation conditions. The authors present a multiplexing approach that is completely independent of fixation. I suggest discussing this in the manuscript and promoting the approach in that regard.
      • I am wondering what defines the 'resolution' of this approach. I assume it is a combination of the sonication time - the longer the cell is sonicated, the smaller the fragments are - and the density of particles on the coverslip. What are the limits here? How does this affect the UMAP analysis? I would encourage the authors to discuss this in the manuscript.
      • The only real control the authors present are the correlative light and electron microscopy (CLEM) three images in Figure 1b, which seems very minimalistic for a very central and essential control experiment. How many of these control images did the authors take? Is there possibly a second method for a control experiment to link the fluorescence readout to an organelle fragment (e.g., purification or pulldown)?
      • Line 37-41: Could the authors please strengthen these statements with an appropriate citation (e.g., a review)?
      • Line 51: The statement, "Super-resolution microscopy could partially solve the resolution problem, but it is currently limited to four-color imaging," is incorrect. Agasti et al. demonstrated up to nine target multiplexed super-resolved imaging with DNA-PAINT in 2017 (https://pubs.rsc.org/en/content/articlehtml/2017/sc/c6sc05420j). Additionally, two papers currently on Biorxiv demonstrate 12 target and 30 target multiplexed super-resolution imaging with FLASH-PAINT (https://www.biorxiv.org/content/10.1101/2023.05.17.541061v1.abstract) and SUM-PAINT (https://www.biorxiv.org/content/10.1101/2023.05.17.541210v1.abstract). Please cite these papers accordingly.
      • The authors use spectral unmixing to overcome the limit of spectral multiplexing. While this has been demonstrated to work well for less than ten targets, it does not scale to multiplexing experiments with more than ten target species. I suggest that the authors discuss in the discussion part of the manuscript the potential of DNA-based multiplexed imaging, such as CODEX or DNA-PAINT, in combination with the presented approach.
      • Regarding the spectral unmixing approach, please cite previous work described in the literature (e.g., https://www.nature.com/articles/nature22369, or earlier work).
      • By using spectral unmixing for multiplexing, this method is limited to confocal due to spectral detection needs and therefore limited in throughput. It would be beneficial if it could work with wide-field type illumination. This could substantially increase the throughput, which is another reason why I think it would be important to discuss sequential multiplexing.
      • To image contact sites, the authors use split GFP. There have been discussions that split GFP might, in some cases, facilitate the process that is supposed to be measured, in this case, the formation of contact sites. I suggest using a transient version of split GFP, called split fast, for follow-up experiments in the authors' next papers (https://www.nature.com/articles/s41467-019-10855-0 ).
      • Line 27 & 253: Please drop the term 'intuitive' or explain better what you mean by intuitive. For me, UMAP is certainly a very useful tool, but it is not at all what I would describe as intuitive.
      • Lastly, I want to mention that the authors state they used ChatGPT, DeepL, and DeepL Write for translation from Japanese to English. I appreciate their honesty.

      Significance

      In the manuscript titled "Organelle Landscape Analysis Using a Multi-parametric-Based Method," Kurikawa et al. present a method for multi-parametric, particle-based analysis of cellular organelles. After lysing cells, the fractions of the organelles are partially labeled with fluorescently tagged antibodies, while others are already tagged with fluorescent proteins, using six to eight spectrally different fluorescent dyes/proteins. These fractions are subsequently immobilized on a poly-L-lysine-coated coverslip. The authors use spectral unmixing to distinguish these markers. The 6-8 multiplexed imaging data is then presented in two-dimensional UMAP space. The authors then use this approach to visualize seven major organelles, transitional sites of endocytic organelles, and contact sites between the endoplasmic reticulum and mitochondria using split GFP.

      The authors present, in my opinion, a conceptually new and interesting approach by combining spectral unmixing for imaging up to eight targets, with organelle fragment imaging, and presenting multidimensional data in two-dimensional Uniform Manifold Approximation and Projection (UMAP) space in this manuscript. They further validated this approach by linking the results of the experiments to results established or at least reported in the literature.

      In general, the manuscript is, in my opinion, a good fit for publication as it presents a conceptionally new approach and an interesting example of applying the UMAP approach, which might be of interest to a broader readership. Therefore, after an appropriate response to my comments, suggestions, and questions (see below), I would recommend this manuscript for publication.

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      Referee #2

      Evidence, reproducibility and clarity

      The manuscript reports a multi-parametric particle-based method for analysis of organelles. The method aims to resolve heterogeneous populations of organelles involved in various cellular processes. They propose to isolate organelles labelled with multiple markers, after homogenization and sonification of the cells, and analyse the resulting particles by fluorescence microscopy using spectral imaging. Afterwards, the authors visualize and analyse the obtained data with dimension reduction techniques.

      Even though an interesting approach, the method and presented applications needs major improvisations before it can prove to be impactful for the field

      I note some possible improvement points below:

      • Initially, I think the current set of cell lines and labels should be extended also to include a wider set. The current limited set raises the question if the method authors report is also applicable to other cell lines, or if it only feasible with overexpressed markers. Including different cell lines with different labels would make the study more convincing and comprehensive.
      • It is surprising that the authors explicitly list already the limitations of fluorescence microscopy and super-resolution microscopy in the second paragraph of their introduction, however present a method fully dependent on fluorescence labelling and imaging methods. Actuallt their approach takes away the spatial information of FM approaches, and further makes the approach prone to the limitations they state. They are also not fully fair about the limitation they state for Electron microscopy, as newly developed approaches (e.g. doi:10.1093/micmic/ozad067.1091; doi: 10.1126/science.aay3134) widely extend the limited field of view and sampling capacity of EM. I recommend the authors to state the potential advantage/superiority of the reported method rather than stating the unclear limitations of the existing powerful methods.
      • Most organelle markers the isolation of organelles are based on are overexpressed in the cells: endoplasmic reticulum (ER, mTagBFP2 (BFP)-SEC61B), mitochondria (GFP-OMP25 and SNAP-OMP25), and the Golgi (Venus-GS27). This raises significant questions about the native state relevance of the reported results, and how well they represent the endogenous processes.
      • For the application on endosomes, can the authors state what is the new information enabled by their method? They study the very trafficking of EGF and Transferrin, 2 widely used endosomal cargoes with very well characterized trafficking steps, and show they are trafficked through Rab5/7 and Rab11 positive endosomes, respectively. This recapitulates the existing information, however falls short in delivering new insight. The authors can use these cargoes for proof-of-concept, but I would recommend to extend their study with less exploited cargoes to represent the potential of the reported method to deliver new information.

      Significance

      The significance of biochemical and cellular processes being spatially regulated cellular organelles, and the roles of specific organelles in diseases from cancer to neurodegeneration are continuously being discovered and appreciated. Therefore development of methods reporting on the structure and function of organelles is important to accelerate these studies. In the reported method, however, the ultrastructure (as in Fib 1b) and the spatial information of the cellular organelles are inherently lost. The method falls in between a biochemical and a microscopic approach, however the advantages are not clearly portrayed. I recommend the authors to carefully and explicitly state where their method would be the method of choice rather than a biochemistry, mass spectroscopy, or microscopy approach. The authors should critically consider such an experiment as a proof-of-concept case.

    4. 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

      In this manuscript, the authors report a novel and simple method to analyze the heterogeneity of various organelles. After imaging a large set of fluorescent-marker-labeled organelles, cluster analysis is adapted for illuminating the dynamics of organelles. Through this novel method, the authors are able to report organelle contact, which previously can only be observed by super-resolution imaging. This is method could significantly accelerate future discoveries at the cellular level. The manuscript is well written and has the potential be published in high-ranking journals, after a minor revision.

      To further demonstrate the unique power of this new method, the authors should test cells under known stimulation altering the dynamics of organelles. For instance, wortmannin can blocks the conversion from early endosomes to late endosomes. By doing that, the potential of this new method will be endorsed.

      Minor issue: The authors should include more details about how to avoid signal crosstalk between adjacent fluorescent channels.

      Significance

      The comprehensive monitoring of organelle dynamics through the integration of multi-dimensional parameters can proficiently evaluate the condition and prognosticate the destiny of living cells in response to external stimulations. This new multi-dimensional assay reported in this manuscript represents a huge step towards this goal. Since this new method is simple and powerful, cell biologists will quickly start to use this new method for the study of sub-cellular dynamics.

      My lab is also developing a similar approach for organelles based on super-resolution imaging. I would like to congratulate the authors for this beautiful work.

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      Reply to the reviewers

      1. General Statements We appreciate the insightful reviewer comments. Both reviewers alluded to the logical lack of connection between two themes in the original paper. Specifically, we showed that N-cad differentially regulates migration in different environments, and that leader and follower cells differ phenotypically, but did not connect the two themes. In this revised version, we've performed additional experiments and undertaken a comprehensive reorganization of both the manuscript and figures. The major changes are outlined below:

      2. Figure 4 A-C has been moved to Figure 6 F-H.

      3. Figure 5 has been moved to Figure S3 F-H.
      4. Figure 6 F has been moved to Figure 7 A.
      5. Figure 6 G-H have been moved to Figure 7 D-E.
      6. Figure 6 I-J have been moved to Figure S5 A-B.
      7. Figure 7 C-F have been moved to Figure S5 C-F.
      8. Added transcriptome profiling of control and N-cad-depleted cells and of leader and follower cells (Figures 6 E, S1 H and S4 C-D, Tables S2 and S3). We have incorporated additional figures (Figure 4 and 5 in the revised manuscript) to support the idea that the amount of N-cad at the cell surface is regulated by endocytic recycling, thereby stimulating glioma migration in the different local environments. Furthermore, our new findings showed that YAP1/TAZ regulates the surface level of N-cad during glioma migration (Figure 8). We trust that these additions contribute to the clarity and robust justification of our paper.

      Similar to other types of tumors, our findings revealed that pediatric high-grade gliomas migrate collectively, possibly contributing to a more aggressive invasion than single cells. In this study, we found that N-cad mediates this collective glioma migration. Interestingly, within these migrating groups, leader and follower cells dynamically interchange positions during migration, accompanied by changes their phenotypic characteristics. This suggests that differences in phenotypes, including N-cad recycling, proliferation and YAP activation, may be predominantly regulated by cell-extrinsic factors rather than being predetermined by genetic or epigenetic factors. Moreover, our new RNA-sequencing results indicate minimal difference between leader and follower cells, except for the upregulation of YAP response and wound healing migration genes in leader cells. Although genomic alterations still possibly encode the leader-follower exchange, our findings strongly suggest that the activation of YAP1 and glioma migration are regulated by the cellular context, specifically where cells are located within the group.

      Contrary to our initial findings suggesting a positive feedback loop between N-cad endocytosis and nuclear YAP1, our revised data indicates that nuclear YAP appears to be independent of N-cad. We observed that homotypic interactions with N-cad present in the surrounding environment, such as neurons (Figure 6 C-D) or N-cad extracellular domain-coated surface (Figure 7 B-C), did not affect nuclear YAP1. However, YAP1/TAZ depletion decreased N-cad expression and altered its localization at the surface (Figure 8). This leads us to propose a revised model where nuclear YAP1 stimulates surface N-cad, thereby facilitating the distinct modes of migration on ECM and neurons (Figure 8 I).

      1. Point-by-point description of the revisions

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

      In this manuscript, Kim and colleagues describe the role of N-Cadherin during pediatric glioma migration. They compare cell lines that have similar transcripts but different levels of N-Cadherin protein and find that N-Cadherin levels influence the route of migration - whether it be on ECM or other tissues. They also describe molecular feedback between N-Cadherin and YAP in leader vs follow cells of their systems. The data are clear, well presented, and convincing; and the conclusions described by the manuscript are mostly justified. My major criticism of the manuscript is that the line of questioning undertaken does not appear well justified. At many points, I was left asking "but why are they doing this?" and I could not understand the rationale for some of the experiments that were performed (even if they were performed well). The manuscript opens by validly describing how gliomas are highly invasive, poorly understood and that N-Cadherin was highly expressed in comparison to other adhesion proteins. This opened the path for the questions and experiments performed that contributed to Figures 1-3, which I thought were interesting. From there on, I found the logic of the story unclear and poorly justified. For example, I do not know why leader and follower cells were justified - when it had nothing to do with N-Cadherin which was the focus of the work prior. And then, having rightly concluded in Figure 4 that the data suggested that leader and follower cells dynamically exchange positions rather than being pre-determined, they went onto further figures focusing on differences between leader and follower cells, which left my quite confused. I am likewise confused by the model proposed in that, they authors describe that the difference between leader and follower cells contributes to a nuclear YAP/N-Cad endocytosis feedback loop that feeds into the speed of migration. Yet, the authors describe earlier that leader and follower cells frequently exchange positions, with no evidence that they are pre-determined. How do the authors square these seemingly conflicting points? And further, what is the relevance of this to understanding the differing modes of migration (on ECM or other tissues)? On this issue, I suggest authors re-consider whether the order of figures or logic of the story is appropriate (perhaps consider moving some figures to supplement?), and to clearly justify in the text the elements that are being addressed. Overall, I think the messaging, logic and justification could be use significant improvement; the experiments however are well performed, and the figures are very clear and nicely presented, and I don't have any qualms about them.

      We appreciate your insightful comments, recognizing the need for logical and justifiable improvements in certain sections of our previous manuscript. Please see Section 1, General Statements, for an explanation of changes made.

      Minor Comments

      1. Not required, but the authors may wish to consider putting t=0 pictures of the experiments in the supplement as supportive evidence for the circles of the initial seeding location they show in Fig 1.

      We provide the t=0 images in Figure S1 N and O.

      1. I assume the title of the second results section should say "migration speed" rather than "speed migration"

      The new title of the second results section is “N-cad stimulates and inhibits migration through intercellular homotypic interaction”.

      1. Fig. 4D - Are both example cell pictures leaders? If so, I'm not sure why two have been provided; I'm guessing the bottom set are supposed to be follower cells. If so, please label as appropriate. (And if not, a representative set of pictures from a follower cell should be provided).

      We have enhanced the clarity of the labels. We provide representative high magnification images of leader and follower cells. The updated figure can be found in Figure 5 A.

      1. Figure 5 Legend - the title of this figure is too definitive, and exaggerates further than the main text does, which was correct in saying that the experiments only suggest that N-Cadherin endocytosis might regulate the localisation of b-catenin and p120-catenin. Probably I would go further and say that there is no experimental evidence provided that even suggests that in the first place, and that this is a hypothesis that remains to be tested. The authors should inhibit endocytosis specifically (rather than just depleting N-Cad) and see the effect, to justify their conclusion.

      We appreciated your points and concerns. Following your earlier suggestion, we have moved the figure to the supplementary section (Figure S3 F-H). Moreover, we have addressed the reciprocal regulation of N-cad and catenins by knocking down p120-, β- or α-catenin. Our new findings showed that p120-, β- or α-catenin depletion decrease the amount of N-cad at the cell surface, not steady-state protein level, resulting in decreased migration on astrocytes but increased migration on ECM (see Figure 4). These findings support the idea that catenins play a role in glioma migration according to the environment by altering surface N-cad level. With that, we updated the figure title to “Catenins regulate N-cad surface levels to stimulate or inhibit migration.”

      Reviewer #1 (Significance (Required)):

      The manuscript provides a characterised of invasive glioma migration that was previously lacking. It also provides interesting observations related to the role of N-Cadherin for different modes of migration (on ECM or on tissues) that will be of interest for further exploration. It makes a good advance in terms of addressing a highly invasive cell type that has poor prognosis. I anticipate that now this initial characterisation has been performed, authors and others will be interested in gaining a deeper understanding as to how these two modes of migration are controlled, how there might be interplay between them and how such findings contribute to its highly invasive nature. I have expertise in collective cell migration and directed cell migration.

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

      Summary In the submitted manuscript, Kim et al. describe various aspects of N-cadherin function in the collective migration of PBT-05 cells, a pediatric high-grade glioma line, on laminin, 3D-matrigel, neurons or astrocytes. N-cadherin promotes the collective migration on neurons or astrocytes, whereas it suppresses the migration on laminin or 3D-matrigel. The authors also show that N-cadherin is actively internalized and recycled in the leader, but not follower, cells of the collective, which induce the nuclear accumulation of YAP/TAZ proteins. YAP/TAZ proteins are shown to regulate the collective migration.

      Thank you for the comments. Please see Section 1, General Statements, for a summary of changes made. Please also note that our new experiments failed to show that N-cad levels or traffic regulate YAP/TAZ nuclear accumulation. Rather, YAP/TAZ are regulated by cell density independent of N-cad, and YAP/TAZ regulate N-cad protein levels and traffic independent of changes in N-cad RNA levels

      Major comments

      1. In Fig. 1G, N-cadherin knockdown seems to affect the distribution of astrocytes. The authors should stain a marker for astrocytes, instead of actin, and the red alone images should be provided.

      Astrocytes were cultured for 4 days to generate 3D scaffolds before adding the glioma spheroid, essentially as described (Gritsenko et al., Histochem Cell Biol, 2017). Co-cultures were stained for human-specific vimentin (glioma) or actin (glioma and astrocytes) (see Figure 1 G and separate channels in new Figure S1 P). There do not appear to be major changes in astrocyte organization outside the migration front, but we lack a way to stain for astrocytes specifically and cannot visualize astrocytes under the glioma cells. It remains possible that astrocytes may be affected differently by contact with control and N-cad-deficient glioma cells. However, we added a new experiment, assaying migration on decellularized astrocyte ECM. While N-cad stimulated migration on astrocytes it inhibited migration on astrocyte ECM (Figures 1 I and J and S1 Q). Thus N-cad stimulates glioma migration on astrocyte cells and not their ECM.

      1. The colocalization between N-cadherin and Rab11 may not be high in Figs. 4F and S2B. It is unclear whether the majority of the internalized N-cadherin is recycled to the plasma membrane. In Fig. S2B, the internalized N-cadherin may be located mainly at the early endosomes before transported to the recycling endosomes (Is it 20 min after the N-cadherin antibody internalization?). First, the authors should analyze the colocalization between the N-cadherin and Rab11 at 30-40 min after the internalization. If the colocalization with Rab11 would be still low at that time point, some of the internalized N-cadherin might be degraded in the lysosomes. To test this possibility, the authors should analyze the colocalization between N-cadherin and LAMP1 under the treatment with a lysosome inhibitor.

      At steady state, N-cad co-localized better with Rab5 than with Rab11 or LAMP1 (Figure 5 C-D). In kinetics experiments, N-cad antibodies were internalized for 40 min. They colocalized better with Rab5 or EEA1 than with Rab11 or LAMP1. When we allowed recycling for an additional 20 min, the surface level of N-cad antibodies partially recovered in leader cells more than follower cells (see Figures 5 G and S3 D). We tested whether treatment with lysosomal inhibitors would increase co-localization of N-cad with Rab11 in recycling endosomes. Surprisingly, however, Chloroquine or Bafilomycin A1 decreased the amount of internalized N-cad antibody in leader and follower cells, and long-term treatment did not increase total N-cad levels. Therefore, the fate of internalized N-cad in follower cells remains unclear.

      1. When N-cadherin is depleted, dissociated single cells are increased, but these cells are not well characterized. A high magnification image of the dissociated single cells is required. In addition, the migration speed of the dissociated single cells should be measured.

      We didn’t quantify single cell migration because only a minority of cells separate from the collective even when N-cad is depleted. Therefore, we quantified migration directionality and speed for cells at or near the front of collective migration (Figure 2 D-I). We have updated the image of single cells, providing representative high-magnification images in Figure S1 N and O.

      1. In Fig. S2D, treatment with Pitstop-2 alone or Dyngo-4a alone is required. Dynamin is also involved in clathrin-independent endocytosis and N-cadherin is reported to be internalized via caveolin-1-mediated endocytosis as well as clathrin-mediated during neuronal migration. It would be better to clarify which type of endocytosis occurs in the leader cells.

      We have removed results showing inhibition of cell migration and N-cad endocytosis by Pitstop-2 and Dyngo-4a from the paper. Treatment with either chemical alone had much less effect on internalization or migration than adding both together (see figure below). This is hard to explain. Pitstop-2 should inhibit clathrin-coated pit formation and Dyngo-4a should inhibit clathrin and caveolin-mediated endocytosis. Caveolin-1 and 2 transcripts were not detected in our cells (Table S2). There may be some other form of clathin-independent endocytosis. Interpretation is also challenging since these inhibitors will inhibit endocytosis of many receptors, not just N-cad. Accordingly, we have removed these results in the revised manuscript.

      1. In Fig. 2, N-cadherin depletion disturbs the migration directionality. Is this a result from disruption of cell polarity? To test this, the position of centrosome or Golgi or lamellipodia in the leader cells should be analyzed. (OPTIONAL)

      We elected not to perform this analysis.

      1. I cannot understand the significance of Fig. 5F and 5G. If the authors would speculate that alpha- and beta-Catenins may transduce the intracellular signaling from the internalized N-cadherin, the authors should perform the knockdown experiments of the Catenins and analyze whether it may affect the nuclear accumulation of YAP/TAZ. (OPTIONAL)

      We agree. In the initial manuscript, we showed that N-cad depletion altered the localization of p120-, β-, and α-catenin (previously shown in Figure 5 F-G). For better clarity and logic, these figures have been moved to Figure S2 H in the revised manuscript. Additionally, to test whether catenins regulate N-cad and YAP1, we depleted p120-, β-, or α-catenin using shRNA. We found that downregulation of p120-, β-, or α-catenin decreased N-cad surface levels, consequently slowing migration on astrocytes and stimulating migration on laminin (Figure 4). In other words, depleting catenins altered migration in parallel with the changes in N-cad surface level. Catenin depletion also increased single-cell dissociation, reduced the crowding of leader and follower cells, and increased nuclear YAP1 (see figure below). These findings suggest that the main role of p120-, β-, or α-catenin is to regulate surface N-cad. Since this result does not support a role for catenins transducing an N-cad signal to YAP1, we have not included it in the paper.

      Minor comments

      1. The quantitative data is required in Fig. 5E.

      Quantitative data from three independent experiment are now presented in Figure S2 G.

      1. Vinculin is associated with the cadherin-catenin complex and it may not be a good loading control (Fig. 3C and 3L).

      The Western blot data has been updated and is now presented in new Figure 3 B and 3 F, with β-tubulin as a loading control.

      **Referees cross-commenting**

      I totally agree with the other Reviewers' comments and evaluation. As the reviewer-1 pointed out, I also think the experiments are well performed, but it would lack logic at least in part (see my comment-6). In addition, as the reviewer-3 pointed out, the linking mechanism of N-cadherin homophilic interaction with YAP/TAZ signaling is important to improve this manuscript

      We hope the revisions have improved the logical flow. We have also added new results showing that YAP/TAZ regulate N-cad protein levels and localization but not N-cad RNA. N-cad is not needed for cell density-dependent regulation of YAP1 localization. The model is shown in Figure 8 I.

      Reviewer #2 (Significance (Required)):

      Strength N-cadherin has multiple function in cancer and neuronal migration, and both positive and negative effects of N-cadherin on cancer cell migration have been reported. In this regard, different behaviors of N-cadherin in the leader and follower cells of the collective are interesting and may explain the controversial previous results.

      Limitation This study reveals various aspects of N-cadherin function in the collective migration of the glioma cell line, but it is unclear whether these findings are applied to pediatric high-grade gliomas in vivo.

      Thus, this study is a potentially important and informative to cell biologists and researchers in cancer biology, although this reviewer also found several weak points that should be improved.

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

      In this manuscript, the authors explore the role of N-cadherin in the migratory/infiltrative behavior of human pediatric brain tumor cells, in light of their surrounding microenvironment. Their in-depth phenotype analysis allows to document the behavior of migrating cells and revisit the concept of leading/follower migratory cells (somehow more commonly applied to endothelial cells). They suspected that the YAP/TAZ pathway might modulate N-cadherin endocytosis and vice versa, using imagery-based cell tracking.

      Major comments

      1. To control for co-culture models, migration should be evaluated on decellularized matrices from astrocyte and neuron cultures.

      We thank for your suggestion. We tested glioma migration on astrocyte-derived decellularized matrices. The mouse astrocytes we used are known to produce various extracellular matrices with a composition similar to Matrigel, except for laminin α5. (Gritsenko et al., J Cell Sci, 2018). N-cad shRNA cells migrated faster on decellularized ECM than control (Figure 1 I-J and S1 Q). This result agrees with N-cad depletion increasing migration on ECM but is opposite to migration on astrocytes.

      1. N-cadherin was stably knocked down with shRNA, which raises the question of adaptative/compensatory mechanisms. First, one could ask what happen in knockout conditions. Similarly, transient siRNA-mediated silencing might help to strengthen the findings. Second, is there any impact of Ncad knock down on alternate adhesive receptors (either cell-cell or cell-ECM). This should be verified with bulk RNAseq.

      Transient knockdown with N-cad siRNA also increased migration on laminin-coated surface (Figure S1 L-M). Unfortunately, N-cad depletion with siRNA was short-lived, precluding its use for long-term assays, like coculture with neurons or astrocytes. To test whether there is any impact of N-cad knockdown on alternative adhesion receptors, we performed RNA-Seq (Figure S1 H, Table S2). We found N-cad depletion did not alter expression of other cell-cell and cell-ECM adhesive receptors except CDH3 (2.8-fold increase compared with 7-fold decrease in CDH2). Integrin expression was unchanged.

      1. It would be interesting to evaluate the impact of N-cadherin/N-cadherin homotypic interactions on YAP/TAZ signaling, using for instance N-cad-coated surface.

      We observed that the homotypic interaction of N-cad with surrounding neurons and astrocytes did not hinder the accumulation of nuclear YAP1 in leader cells (Figure 6 C-D). To further support the idea that N-cad does not directly regulate YAP1 signaling, we have now measured YAP1 localization in cells migrating over N-cad ECD. The new data confirms that N-cad does not directly regulate YAP1 localization (Figure 7 B-C).

      1. along this line, the impact of mechanical cues (stiffness, 2D vs 3D) is not explored.

      We appreciate your suggestion. It is possible that different mechanical and cytoskeletal cues between leader and follower cells affect YAP1 signaling. In this study, we would like to focus more on the role of N-cad-mediated cell adhesions in YAP signaling.

      Minor comments

      1. Levels of N-cadherin expression in normal Astro and Neurons to compare with pediatric brain cancer cells (S1C)

      A new western blot analysis to show N-cad levels in DMG, PHGG and mouse cerebellar neurons and astrocytes has been added to Figure S1 F.

      1. Low versus high density culture conditions should be controlled and its further impact on the YAP/Ncad endocytosis route should be supported experimentally, or to be omitted from their proposed model.

      We previously used different size of micropattern discs to control low or high cell density. Smaller cell clusters, with more edge cells and hence fewer cell-cell interactions, had higher nuclear YAP1 (Figure 7 D-E). We have repeated this experiment, including N-cad ECD antibodies to measure N-cad endocytosis. Smaller cell clusters had higher N-cad antibody internalization (Figure 7 F). Together with our evidence that leader cells have higher YAP1 and more N-cad internalization than followers, and that YAP/TAZ knockdown inhibits N-cad internalization, these results high YAP/TAZ in leader cells regulates N-cad internalization.

      Reviewer #3 (Significance (Required)):

      This paper presents robust image analysis of human pediatric brain tumor migration in the context of the different microenvironment that they might encounter (matrices, neurons, astrocytes). This study brings new concepts on the way N-cadherin might contribute to tumor cell migratory behavior based on the nature of the interactions in which N-cadherin is involved. As a limitation, it remains unclear the mechanism by which N-cadherin endocytosis is driven.

      We now discuss the limitations of the study as follows:

      “The mechanisms by which YAP1 regulates N-cad levels and trafficking remain to be explored. YAP1 is widely expressed in human brain tumors and strongly associated poor survival. Leader cells expressed higher levels of YAP1-response and wound-healing gene transcripts, but transcript levels of N-cad and proteins known to regulate cadherin traffic, such as p120-catenin, Rab5/11 and Rac1, were similar. Therefore, N-cad is likely regulated at the level of protein synthesis or turnover. More endosomal N-cad recycled to the surface of leader than follower cells, implying that follower cells might divert more N-cad for lysosomal degradation, but our attempts to interfere with N-cad endocytosis or degradation specifically were unsuccessful. Further understanding of the mechanism and function of N-cad recycling for glioma cell migration will require cargo-specific ways to selectively regulate endocytosis and recycling”.

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      Referee #3

      Evidence, reproducibility and clarity

      In this manuscript, the authors explore the role of N-cadherin in the migratory/infiltrative behavior of human pediatric brain tumor cells, in light of their surrounding microenvironment. Their in-depth phenotype analysis allows to document the behavior of migrating cells and revisit the concept of leading/follower migratory cells (somehow more commonly applied to endothelial cells). They suspected that the YAP/TAZ pathway might modulate N-cadherin endocytosis and vice versa, using imagery-based cell tracking.

      Major comments:

      1. To control for co-culture models, migration should be evaluated on decellularized matrices from astrocyte and neuron cultures.
      2. N-cadherin was stably knocked down with shRNA, which raises the question of adaptative/compensatory mechanisms. First, one could ask what happen in knockout conditions. Similarly, transient siRNA-mediated silencing might help to strengthen the findings. Second, is there any impact of Ncad knock down on alternate adhesive receptors (either cell-cell or cell-ECM). This should be verified with bulk RNAseq.
      3. It would be interesting to evaluate the impact of N-cadherin/N-cadherin homotypic interactions on YAP/TAZ signaling, using for instance N-cad-coated surface.
      4. along this line, the impact of mechanical cues (stiffness, 2D vs 3D) is not explored.

      Minor comments:

      1. Levels of N-cadherin expression in normal Astro and Neurons to compare with pediatric brain cancer cells (S1C)
      2. Low versus high density culture conditions should be controlled and its further impact on the YAP/Ncad endocytosis route should be supported experimentally, or to be omitted from their proposed model.

      Significance

      This paper presents robust image analysis of human pediatric brain tumor migration in the context of the different microenvironment that they might encounter (matrices, neurons, astrocytes).

      This study brings new concepts on the way N-cadherin might contribute to tumor cell migratory behavior based on the nature of the interactions in which N-cadherin is involved.

      As a limitation, it remains unclear the mechanism by which N-cadherin endocytosis is driven.

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      Referee #2

      Evidence, reproducibility and clarity

      Summary

      In the submitted manuscript, Kim et al. describe various aspects of N-cadherin function in the collective migration of PBT-05 cells, a pediatric high-grade glioma line, on laminin, 3D-matrigel, neurons or astrocytes. N-cadherin promotes the collective migration on neurons or astrocytes, whereas it suppresses the migration on laminin or 3D-matrigel. The authors also show that N-cadherin is actively internalized and recycled in the leader, but not follower, cells of the collective, which induce the nuclear accumulation of YAP/TAZ proteins. YAP/TAZ proteins are shown to regulate the collective migration.

      Major comments

      1. In Fig. 1G, N-cadherin knockdown seems to affect the distribution of astrocytes. The authors should stain a marker for astrocytes, instead of actin, and the red alone images should be provided.
      2. The colocalization between N-cadherin and Rab11 may not be high in Figs. 4F and S2B. It is unclear whether the majority of the internalized N-cadherin is recycled to the plasma membrane. In Fig. S2B, the internalized N-cadherin may be located mainly at the early endosomes before transported to the recycling endosomes (Is it 20 min after the N-cadherin antibody internalization?). First, the authors should analyze the colocalization between the N-cadherin and Rab11 at 30-40 min after the internalization. If the colocalization with Rab11 would be still low at that time point, some of the internalized N-cadherin might be degraded in the lysosomes. To test this possibility, the authors should analyze the colocalization between N-cadherin and LAMP1 under the treatment with a lysosome inhibitor.
      3. When N-cadherin is depleted, dissociated single cells are increased, but these cells are not well characterized. A high magnification image of the dissociated single cells is required. In addition, the migration speed of the dissociated single cells should be measured.
      4. In Fig. S2D, treatment with Pitstop-2 alone or Dyngo-4a alone is required. Dynamin is also involved in clathrin-independent endocytosis and N-cadherin is reported to be internalized via caveolin-1-mediated endocytosis as well as clathrin-mediated during neuronal migration. It would be better to clarify which type of endocytosis occurs in the leader cells.
      5. In Fig. 2, N-cadherin depletion disturbs the migration directionality. Is this a result from disruption of cell polarity? To test this, the position of centrosome or Golgi or lamellipodia in the leader cells should be analyzed. (OPTIONAL)
      6. I cannot understand the significance of Fig. 5F and 5G. If the authors would speculate that alpha- and beta-Catenins may transduce the intracellular signaling from the internalized N-cadherin, the authors should perform the knockdown experiments of the Catenins and analyze whether it may affect the nuclear accumulation of YAP/TAZ. (OPTIONAL)

      Minor comments

      1. The quantitative data is required in Fig. 5E.
      2. Vinculin is associated with the cadherin-catenin complex and it may not be a good loading control (Fig. 3C and 3L).

      Referees cross-commenting

      I totally agree with the other Reviewers' comments and evaluation. As the reviewer-1 pointed out, I also think the experiments are well performed, but it would lack logic at least in part (see my comment-6). In addition, as the reviewer-3 pointed out, the linking mechanism of N-cadherin homophilic interaction with YAP/TAZ signaling is important to improve this manuscript

      Significance

      Strength

      N-cadherin has multiple function in cancer and neuronal migration, and both positive and negative effects of N-cadherin on cancer cell migration have been reported. In this regard, different behaviors of N-cadherin in the leader and follower cells of the collective are interesting and may explain the controversial previous results.

      Limitation

      This study reveals various aspects of N-cadherin function in the collective migration of the glioma cell line, but it is unclear whether these findings are applied to pediatric high-grade gliomas in vivo.

      Thus, this study is a potentially important and informative to cell biologists and researchers in cancer biology, although this reviewer also found several weak points that should be improved.

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      Referee #1

      Evidence, reproducibility and clarity

      Kim et al review

      In this manuscript, Kim and colleagues describe the role of N-Cadherin during pediatric glioma migration. They compare cell lines that have similar transcripts but different levels of N-Cadherin protein and find that N-Cadherin levels influence the route of migration - whether it be on ECM or other tissues. They also describe molecular feedback between N-Cadherin and YAP in leader vs follow cells of their systems. The data are clear, well presented, and convincing; and the conclusions described by the manuscript are mostly justified. My major criticism of the manuscript is that the line of questioning undertaken does not appear well justified. At many points, I was left asking "but why are they doing this?" and I could not understand the rationale for some of the experiments that were performed (even if they were performed well). The manuscript opens by validly describing how gliomas are highly invasive, poorly understood and that N-Cadherin was highly expressed in comparison to other adhesion proteins. This opened the path for the questions and experiments performed that contributed to Figures 1-3, which I thought were interesting. From there on, I found the logic of the story unclear and poorly justified. For example, I do not know why leader and follower cells were justified - when it had nothing to do with N-Cadherin which was the focus of the work prior. And then, having rightly concluded in Figure 4 that the data suggested that leader and follower cells dynamically exchange positions rather than being pre-determined, they went onto further figures focusing on differences between leader and follower cells, which left my quite confused.

      I am likewise confused by the model proposed in that, they authors describe that the difference between leader and follower cells contributes to a nuclear YAP/N-Cad endocytosis feedback loop that feeds into the speed of migration. Yet, the authors describe earlier that leader and follower cells frequently exchange positions, with no evidence that they are pre-determined. How do the authors square these seemingly conflicting points? And further, what is the relevance of this to understanding the differing modes of migration (on ECM or other tissues)? On this issue, I suggest authors re-consider whether the order of figures or logic of the story is appropriate (perhaps consider moving some figures to supplement?), and to clearly justify in the text the elements that are being addressed. Overall, I think the messaging, logic and justification could be use significant improvement; the experiments however are well performed, and the figures are very clear and nicely presented, and I don't have any qualms about them.

      Minor Comments

      • Not required, but the authors may wish to consider putting t=0 pictures of the experiments in the supplement as supportive evidence for the circles of the initial seeding location they show in Fig 1.
      • I assume the title of the second results section should say "migration speed" rather than "speed migration"
      • Fig. 4D - Are both example cell pictures leaders? If so, I'm not sure why two have been provided; I'm guessing the bottom set are supposed to be follower cells. If so, please label as appropriate. (And if not, a representative set of pictures from a follower cell should be provided).
      • Figure 5 Legend - the title of this figure is too definitive, and exaggerates further than the main text does, which was correct in saying that the experiments only suggest that N-Cadherin endocytosis might regulate the localisation of b-catenin and p120-catenin. Probably I would go further and say that there is no experimental evidence provided that even suggests that in the first place, and that this is a hypothesis that remains to be tested. The authors should inhibit endocytosis specifically (rather than just depleting N-Cad) and see the effect, to justify their conclusion.

      Significance

      The manuscript provides a characterised of invasive glioma migration that was previously lacking. It also provides interesting observations related to the role of N-Cadherin for different modes of migration (on ECM or on tissues) that will be of interest for further exploration. It makes a good advance in terms of addressing a highly invasive cell type that has poor prognosis. I anticipate that now this initial characterisation has been performed, authors and others will be interested in gaining a deeper understanding as to how these two modes of migration are controlled, how there might be interplay between them and how such findings contribute to its highly invasive nature.

      I have expertise in collective cell migration and directed cell migration.

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      Reply to the reviewers

      1. General Statements

      We appreciate the reviewers’ thoughtful feedback and thank them for their valuable suggestions to improve the manuscript. We have endeavored to respond to all their comments, with many of their concerns already incorporated in the manuscript. Validations for the additional experiments to be incorporated into the manuscript have been performed and show that all the plans outlined in Section 2 are highly feasible and will be added for the full revision. We believe that the incorporated and planned revisions contribute to a significant improvement on the original manuscript.

      2. Description of the planned revisions

      Reviewer 1

      Major comments:

      Point 3. p. 5. The authors do not describe any relationship to notch signaling. But notch signaling is the mechanism by which a sprout is selected. The CA phenotype shows no selection, and every sprout can continue migration. Did the authors check for any relationship between notch signaling c-Src activation? Does upregulation of C-Src downregulate notch?

      In previous unpublished results examining the impact of the loss of endothelial c-Src on notch signaling, we observed no alteration in DLL4 expression in the sprouting retina on postnatal day 5. Furthermore, no change in tip cell number was observed in mice with a loss of endothelial c-Src, suggesting c-Src depletion does not impact notch activity (Schimmel et al., Development, 2020, Figure 1M). We have started additional preliminary experiments performing immunostaining with a DLL4 antibody in migrating c-Src-CA cells to assess activation of notch signaling upon c-Src activation. We will continue these experiments for the full revision and will confirm the results via further analysis of notch activation by assessing DLL4 expression in the c-Src mutant cells using Western blot.

      Reviewer 2

      Major comments:

      Point 1. The authors have only used one type of vein endothelial cells from one single donor but they conclude that is effect is general for all endothelial cells. Endothelial cells are very heterogeneous, not only depending on their function and localization, vein, artery or capillary, but also between different organs and in disease (PMID: 22315715, PMID: 28775214, PMID: 31944177, PMID: 33514719). The authors, should either repeat some of the key experiments in other type of endothelial cells, maybe arterial or microvasculature cells which are commercially available or at least state that the observations presented in this manuscript apply to HUVECs and discuss whether this would also apply for other cell types.

      We agree it would be highly beneficial to assess whether c-Src-CA induces vascular expansion in other endothelial cell types. We have successfully transduced human arterial endothelial cells (HAEC) with empty vector and c-Src-CA lentivirus and are able to grow HAECs in 3D vessels. This demonstrates that introducing the c-Src constructs into other endothelial cells and putting them in 3D assays is highly feasible. We have also used human microvascular endothelial cells (HMVEC) in 3D vessels in previous studies (Schimmel et al., Clin Trans Immunol, 2021). Therefore, we will perform experiments introducing the full set of c-Src mutations in HAEC and/or HMVEC in 3D vessels for the revision to strengthen our findings.

      Reviewer 3

      Major comments:

      Point 1. "This was further supported by our observation that there were no changes in proliferation in c-Src mutant cells grown in a 2D monolayer". Figure 1A appears to have increased number of cells in the c-Src-CA condition compared to the control condition. Could the authors quantify the number of cells/area as they did for their 3D vessel model? This would reinforce the idea that the ballooning phenotype they observe is not due to differences in proliferation.

      We have started quantification on the number of cells per bead for the 3D bead sprouting experiments shown in Figure 1. We will complete this quantification for 3 independent experiments and the results will be added for the full revision.

      Point 2. Would be strengthened with analysis of another proliferation marker, such as EdU label, which is incorporated only during S phase of the cell cycle. Comparing ki67 staining and EdU staining would provide more insights. Also, using their 3D vessel model for this analysis would increase its relevance.

      We agree that showing proliferation in a 3D setting would be highly beneficial. We tested proliferation marker Ki67 in 3D vessels to ensure this analysis will be possible. We will perform full analysis of proliferation across c-Src mutations in 3D for the revision. We have started with BrdU labelling in 2D, and we will perform full analysis of proliferation with BrdU across c-Src mutations for the revision.

      Point 3. In Figure 1E', cells expressing the constitutively active form of cSrc appear to detach, giving the impression of cell death. Have the authors tested the viability/apoptosis of c-Src-CA cells, particularly in their 3D model?

      We agree that showing cell death in our model, especially in a 3D setting, would be highly beneficial. We have tested cell death marker Cleaved Caspase 3 (CC-3) in 3D vessels to ensure this analysis is feasible. We will perform full analysis of cell death across c-Src mutations in 3D for the revision.

      Point 4. "Therefore, reduction of endothelial cell-cell contacts in c-Src-CA cells may be due to elevated VE-cadherin phosphorylation and subsequent internalisation", "As reduction in cell-cell junction integrity has been shown to increase migratory capacity and sprouting angiogenesis [38], our data suggest that a balanced control of both cell-matrix and cell-cell junctions is essential for mediating migration." In general, it's not clear how constitutively active cSrc affects focal adhesions and cell-cell adhesion and how this is responsible for their ballooning phenotype. The role of the phosphorylation of the VE-Cadherin and cell-cell junctions in this process is not clear either. Further analysis of cell-cell junctions and focal adhesions (co-staining of phosphorylated paxillin and VE-Cadherin) and focal adhesions/fibronectin (like in figure 4C) in the context of cell migration (scratch wound assay) would provide important information to strengthen this notion of balanced control of both cell-matrix and cell-cell junctions.

      We will perform experiments on migrating cells in 2D, co-staining for p-paxillin and VE-cadherin, and p-paxillin and Fibronectin, to address the role of balanced cell-matrix and cell-cell junction adhesion, and how they influence Fibronectin deposition in migrating cells.

      Point 6. "Taken together, these results reveal that proteases produced by c-Src-CA cells are locally secreted at FAs but are membrane bound." The claim that proteases are membrane-bound is not convincingly demonstrated. Could the authors assess whether the constitutive form of cSrc activates the expression of specific genes encoding MMPs by qPCR? Or is it more a matter of the effect of c-Src on the transport of MMPs by microtubules?

      We would like to clarify the content of Figure 5, which presents two distinct sets of experiments supporting the assertion that the proteases under investigation are membrane-bound. Firstly, the transfer of conditioned medium from c-Src mutant cells demonstrated no degradation of fibronectin fibrils. Secondly, in the bead sprouting assay, a mixed culture of untransduced and c-Src-CA expressing cells was utilised. The results revealed that only c-Src-CA cells formed balloons, while untransduced cells sprouted normally right next to or sometimes even through a balloon.

      Recognising the need for a more in-depth understanding, we acknowledge the importance of analysing specific MMP gene expression. To this end, we have ordered qPCR primers for distinct MMPs, namely MMP2, MMP7, MMP9, and MT1-MMP. These forthcoming experiments are not only highly feasible but will also contribute valuable insights. The results of this gene expression analysis will be incorporated into the revision, shedding light on whether constitutively active c-Src induces MMP gene expression or influences MMP transport.

      Minor comments:

      Point 2. The lab already showed in a previous study that mice lacking c-Src specifically in endothelial cells have reduced blood vessel sprouting, leading to the expectation that the constitutively active form of cSrc would increase sprout number in the sprouting assay. Could the authors explain why the constitutively active form of cSrc induces this vascular ballooning and not an increase in the number of sprouts?

      In line with analysis to be performed on notch activity and DLL4 expression (Reviewer 1 point 3), we will provide additional discussion on the role of notch signalling and tip cell identity with the full revision.

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

      R____eviewer 1

      Major comments:

      Point 1. p5. Fig 1: The sentence that the dominant negative completely abrogated 'this' phenotype implies that the dominant negative was put into the same cells as the constitutively active mutation. 'Abrogated' means it stops the phenotype, and the phenotype in the sentence prior was constitutively active. It is more accurate to say that the dominant negative was not distinguishable from wild type, which is what the statistics show. No double transfection (DN-CA) was performed.

      We have changed the wording in the manuscript accordingly to ‘The c-Src-DN mutation showed no phenotype distinguishable from Ctrl (Fig 1A-D).’ on page 5.

      Point 2. p.5. Fig 1: the phenotype of the CA cells is fascinating. They expand far beyond their normal territory, but they are held together in a lacy bubble. To me, this looks like a different phenotype from the ballooning that might occur in an arteriovenous malformation in vivo, as in vivo malformations are continuously covered by cells. I understand why the authors might use the term ballooning but given that the cells expand without continuously touching each other, I do not think this is the correct term. Would blebbing, or radial migration in a lace-like discontinuous pattern describe it better?

      We have changed the phrasing from ‘ballooning morphology’ to ‘radial migration in a lace-like discontinuous pattern’ on page 5. For brevity, this has been referred to as ‘ballooning’ for the remainder of the manuscript, as noted on page 5.

      Point 4. The statistical methods are not described in the methods (GraphPad?). These need to be added. Are only significant comparisons plotted? In Fig 6 and 7 only pairwise statistics are shown. If all significant comparisons are plotted, then this means that the comparison between the rescued CA and the treated or untreated control is not significant. This can be thought of as a partial rescue towards a wild type, but it is definitely not a full rescue. None of the statistical comparisons in Figure 6 or 7 show significant comparisons to wildtype. This needs more discussion.

      We have now added additional clarification on statistical methods. Details on the statistical tests for each figure are mentioned in the figure legends. A general section on the statistical methods is now added to the methods section on page 18. Only significant comparisons are displayed in the graphs, but as mentioned by reviewer 2 (minor point 2), we have added additional information for transparency. Each of the different comparisons that were made, and their precise p value, have been compiled a table which has been added as Supplementary Table 1 to the manuscript.

      In Figures 6 and 7, we exclusively plotted pairwise comparisons to assess the impact of Marimastat treatment. As outlined in Supplementary Table 1, there is still a statistical significance when comparing Marimastat-treated c-Src-CA with either Marimastat-treated Ctrl or Marimastat-treated c-Src-WT. This suggests a partial rescue. For clarity, we kept only pairwise comparisons in the graphs, but discussed the partial rescue due to remaining significant difference between Marimastat-treated c-Src-CA and Ctrl or c-Src-WT cells in the results, referring to Supplementary Table 1 for p values. An important sidenote: c-Src-CA treated cells cannot exhibit complete rescue since they are initially seeded without Marimastat, and have already initiated ballooning by the time treatment commences.

      Point 5. Mmp activity is inferred, but not measured. This is a limitaion as the assumption is that marimostat acting through the expected pathway.

      Marimastat is one of the most commonly used broad spectrum MMP inhibitors, with potent activity against major MMPs, including MMP1, MMP3, MMP2, MMP9, MMP7 and MMP14. This is outlined in the existing reference (Rasmussen and McCann, 1997). We have adjusted phrasing to clarify the potency of Marimastat and have emphasised this is an MMP targeting drug which has been widely utilised in oncology clinical trials (page 8).

      Minor comments:

      Point 1. Fig 5D. The presentation of the data in this graph is difficult to understand. It is trying to show the proportion of mScarlet in sprouts or balloons a percentage of all the scarlet cells. It would be better to have all cells represented in one bar, distributed between sprout and balloon in that one bar. i.e., for the control and dominant negative, the bars would be all black and then for the CA it would be all white. The zero data points are confusing. A proportions graph should be investigated here.

      We have changed the graph in Figure 5D, which now represents the % of the outgrowth area, sprouts for Ctrl, c-Src-WT and c-Src-DN and balloon for c-Src-CA, that are mScarlet positive. Resulting in all black bars for Ctrl, c-Src-WT and c-Src-DN and all white bar for c-Src-CA, as the reviewer predicted.

      Point 2. The methods for vessel coverage for quantification in figs 1 and 7 are missing.

      We have added details of how quantification of vessel coverage in Figure 1 and 7 was performed to the methods section on page 17/18 as follow: ‘Microfluidic vessel coverage was measured by tracing any holes in the vessel wall (inverse of cell area marked by phalloidin) and dividing this by the total cell area per image.’

      Reviewer 2

      Minor comments:

      Point 1. Although the methods are well written and can be understood. To improve transparency, the authors should reduce the referring to other papers to describe the methods they perform and at least some kind of brief description should be included.

      We have added a brief description of the methods that included references to other papers; lentiviral transduction and microfluidic devices. More details about the lentivirus transduction were added on page 15 and a short description about the fabrication of the microfluidic devices was added on page 15/16.

      Point 2. The authors should report the real p value for their tests. Also, when the test is not significant.

      To provide more transparency about all of the different comparisons that were made and their precise p value, we have compiled a table listing all the p values and which is added as Supplementary Table 1 to the manuscript.

      Reviewer 3

      Minor comments:

      Point 3. In Figure 1A, it would be beneficial to include images from orthogonal views. Indeed, in the c-Src-CA condition, it's not clear whether the vascular ballooning observed represents a cluster of cells or an empty space between the bead and the endothelial cells. (Supp movie 1 helps, but it would be useful to add orthogonal views to the figure)

      For clarity, we have added single Z plane image for cross sectional views of the bead sprouts in Figure 1A to show that the c-Src-CA cells have an empty space inside the balloon, rather than being a big cluster of cells.

      Point 4. In Figure 1D, the method used to analyze sprout shape is not clear, especially for the c-Src-CA condition where the number of sprouts is close to 0. The figure legend indicates that this measurement corresponds to the shape of the sprouting area. Could the authors clarify and explain their quantification method?

      The shape of the sprouting area refers to the circularity index of the vascular area, measured by tracing the perimeter of the cell area in a minimum Z-projection of brightfield images and subtracting the area of the bead. For better clarity, we have adjusted the title of Figure 1D and Figure 6D to ‘Vascular area shape’ and added details of the quantification method in the methods section on page 17.

      Point 5. "however cells within the vessel still maintained some connections (Fig 1E')": The connections between cells are difficult to see in the images in Figure 1E'. Could the authors provide higher magnification images of the VE-cadherin staining to illustrate these connections between cells?

      For improved clarity, we have added high magnification images of the VE-cadherin channel only in black and white (Figure 1E’’) and indicated some of the maintained cell-cell connections in the c-Src-CA cells with black arrowheads.

      Point 6. "The reduction in migration correlated with an increase in FA size c-Src-CA expressing cells.": Could the authors give more explanation?

      We have adjusted phrasing to provide additional information (page 6/7) as follows: ‘The reduction in migration velocity in c-Src-CA cells coincides with an increase in FA size, number and density (Fig 2A-D). This suggests that the reduction of migration velocity is due to increased cellular adhesion via FAs.’

      Point 7. Could the authors widen the cell trajectory trace in Supplementary Figure 3A?

      We have adjusted the trajectory traces in Supplementary Figure 3A with wider lines for improved visibility.

      Point 8. it is very difficult to distinguish fibronectin fibrils on the images shown in figure 4C. it would be beneficial to change the images.

      We have enlarged the zoomed areas for better visibility of the focal adhesions and fibronectin degradation underneath those areas in the c-Src-CA cells. Additionally, arrows are added to indicate fibronectin fibrils.

      Point 9. "Treatment of ECs with Marimastat in a fibrin bead sprouting assay resulted in a rescue of the ballooning morphology observed in the c-Src-CA cells" Based on the images displayed in the figure and the associated quantifications, it still appears that c-Src-CA+Marimastat induces a vascular ballooning even if it is less pronounced than in the DMSO condition. Hence, it would be more accurate to describe the observed effect as a "partial rescue". In the microfabricated 3D vessel, in the figure 7A, cell-cell junctions still appear altered by c-Src-CA after the treatment with Marimastat, compared to the c-Src-WT-Marimastat, it would be more appropriate to talk about "partial rescue".

      We have changed ‘rescue’ to ‘partial rescue’ when referring to results in Figure 6 and 7 (page 8).

      Point 10. In Figure 6A, it seems that there is a decrease in the number of sprouts in the c-Src-DN condition compared to the control condition after the DMSO treatment, which is not observed in Figure 1, could the authors explain why?

      In Figure 1C, the number of sprouts is also reduced in the c-Src-DN condition compared to c-Src-WT, but this is not significant when compared to control (see Supplementary Table 1 for p values of all comparisons). However, it is true that the number of sprouts in the c-Src-DN condition is significantly reduced compared to both control and c-Src-WT upon DMSO treatment (Fig 6C). Reduction of sprouts in c-Src-DN cells was expected due to the dysfunctional kinase domain, as mentioned on page 5 and shown in reference 30 (Shvartsman, D.E., et al., J Cell Biol, 2007. 178(4): p. 675-86.). Why DMSO treatment seems to enhance the effects of dominant negative c-Src expression on sprouting behaviour remains unclear. However, DMSO has adverse effects on sprouting shown by reduction of sprouts in both control and c-Src-WT cells (comparing untreated condition in Fig 1C with DMSO treated condition in Fig 6C). We believe that DMSO treatment is an extra challenge for cells on top of c-Src-DN expression, which therefore display reduced sprouting compared to control and c-Src-WT.

      Point 11. There is no statistical paragraph in the method section.

      As pointed out by reviewer 1 and 2, we have now added a general section on the statistical methods to the method section on page 18. Additional details on the tests used for each specific graph can be found in the figure legends and Supplementary Table 1.

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

      Reviewer 3

      Major comments:

      Point 5. It is not clear how the constitutive activation of c-Src affects both cell-cell junction and focal adhesion morphology. Did the authors study signaling pathways downstream of c-Src such as the PI3K-AKT pathway?

      c-Src is well known to regulate a multitude of signalling pathways, which was definitively shown in analysis by Ferrando et al. using phosphoproteomics (Ferrando, I.M., et al., Mol Cell Proteomics, 2012. 11(8): p. 355-69.) In this manuscript, our primary emphasis is on elucidating the role of c-Src in governing cell-matrix adhesions and the degradation of the extracellular matrix. We delve into the nuanced connection between focal adhesions (FAs) and VE-cadherin through the actin framework in the discussion (see page 10). Additionally, we highlight that beyond its recognised direct targets in FAs and adherens junctions (AJs), c-Src exerts regulatory influence on these structures through its effects on the actin cytoskeleton.

      The PI3K/AKT pathway is implicated in the progression of vascular malformations in Hereditary Hemorrhagic Telangiectasia (HHT), where patients exhibit rapid vasculature expansion akin to the observed effects upon introducing the c-Src-CA mutation. In HHT, PTEN inhibition triggers heightened activity of VEGFA/VEGFR2 and subsequent AKT kinase activation. Although we have conducted preliminary analysis revealing elevated phospho-AKT, we contend that an in-depth examination of each signaling pathway perturbed downstream of c-Src-CA is beyond the current scope of this manuscript. Our future studies will specifically address this, providing a meticulous exploration of c-Src activity in HHT and its intricate interaction with the AKT pathway.

      Minor comments:

      Point 1: General comment: The authors have predominantly presented composite images with overlapping staining, making it challenging to differentiate between different labels. It would be beneficial if the authors could provide individual channel images along with a merge.

      Given the large numbers of multi-channel composite images, we believe it is not feasible to show each individual channel of every merged image in the manuscript. We have included individual channel images where we believe is appropriate. For example, p-paxillin Y118 (Figure 2), Fibronectin (Figure 4). We are happy to provide individual channel images for any image, where specifically requested, such as in Figure 1E’’ where VE-cadherin channel was added.

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      Referee #3

      Evidence, reproducibility and clarity

      Summary:

      In this study, Essebier et al., investigated the impact of constitutive activation of cSrc on endothelial cell behavior during vascular sprouting and homeostasis. The authors generated various mutant versions of cSrc to enable the expression of wild type cSrc, constitutively active cSrc, or cSrc with a dysfunctional kinase domain in HUVEC. They used a range of in vitro methods, including traditional 2D culture techniques and cutting-edge approaches like microfabricated vessels for 3D cell culture. They showed that the constitutive activation of c-Src resulted in a vascular ballooning phenotype both in a 3D angiogenic sprouting assay and in microfabricated blood vessels subjected to shear stress. The expression of this mutant form of c-Src was associated with an increase of focal adhesion size and number and an increase of extracellular matrix degradation. The vascular ballooning phenotype induced by constitutive activation of c-Src was partially rescued by the pharmacological inhibition of the matrix metalloproteinase (MMPs).

      Major:

      • "This was further supported by our observation that there were no changes in proliferation in c-Src mutant cells grown in a 2D monolayer".
        • Figure 1A appears to have increased number of cells in the c-Src-CA condition compared to the control condition. Could the authors quantify the number of cells/area as they did for their 3D vessel model? This would reinforce the idea that the ballooning phenotype they observe is not due to differences in proliferation.
        • Would be strengthened with analysis of another proliferation marker, such as EdU label, which is incorporated only during S phase of the cell cycle. Comparing ki67 staining and EdU staining would provide more insights. Also, using their 3D vessel model for this analysis would increase its relevance.
        • In Figure 1E', cells expressing the constitutively active form of cSrc appear to detach, giving the impression of cell death. Have the authors tested the viability/apoptosis of c-Src-CA cells, particularly in their 3D model?
      • "Therefore, reduction of endothelial cell-cell contacts in c-Src-CA cells may be due to elevated VE-cadherin phosphorylation and subsequent internalisation", "As reduction in cell-cell junction integrity has been shown to increase migratory capacity and sprouting angiogenesis [38], our data suggest that a balanced control of both cell-matrix and cell-cell junctions is essential for mediating migration." In general, it's not clear how constitutively active cSrc affects focal adhesions and cell-cell adhesion and how this is responsible for their ballooning phenotype. The role of the phosphorylation of the VE-Cadherin and cell-cell junctions in this process is not clear either.
        • Further analysis of cell-cell junctions and focal adhesions (co-staining of phosphorylated paxillin and VE-Cadherin) and focal adhesions/fibronectin (like in figure 4C) in the context of cell migration (scratch wound assay) would provide important information to strengthen this notion of balanced control of both cell-matrix and cell-cell junctions.
        • It is not clear how the constitutive activation of c-Src affects both cell-cell junction and focal adhesion morphology. Did the authors study signaling pathways downstream of c-Src such as the PI3K-AKT pathway?
      • "Taken together, these results reveal that proteases produced by c-Src-CA cells are locally secreted at FAs but are membrane bound." The claim that proteases are membrane-bound is not convincingly demonstrated. Could the authors assess whether the constitutive form of cSrc activates the expression of specific genes encoding MMPs by qPCR? Or is it more a matter of the effect of c-Src on the transport of MMPs by microtubules?

      Minor:

      • General comment: The authors have predominantly presented composite images with overlapping staining, making it challenging to differentiate between different labels. It would be beneficial if the authors could provide individual channel images along with a merge.
      • The lab already showed in a previous study that mice lacking c-Src specifically in endothelial cells have reduced blood vessel sprouting, leading to the expectation that the constitutively active form of cSrc would increase sprout number in the sprouting assay. Could the authors explain why the constitutively active form of cSrc induces this vascular ballooning and not an increase in the number of sprouts?
      • In Figure 1A, it would be beneficial to include images from orthogonal views. Indeed, in the c-Src-CA condition, it's not clear whether the vascular ballooning observed represents a cluster of cells or an empty space between the bead and the endothelial cells. (Supp movie 1 helps, but it would be useful to add orthogonal views to the figure)
      • In Figure 1D, the method used to analyze sprout shape is not clear, especially for the c-Src-CA condition where the number of sprouts is close to 0. The figure legend indicates that this measurement corresponds to the shape of the sprouting area. Could the authors clarify and explain their quantification method?
      • "however cells within the vessel still maintained come connections (Fig 1E')": The connections between cells are difficult to see in the images in Figure 1E'. Could the authors provide higher magnification images of the VE-cadherin staining to illustrate these connections between cells?
      • "The reduction in migration correlated with an increase in FA size c-Src-CA expressing cells.": Could the authors give more explanation?
      • Could the authors widen the cell trajectory trace in Supplementary Figure 3A?
      • it is very difficult to distinguish fibronectin fibrils on the images shown in figure 4C. it would be beneficial to change the images.
      • "Treatment of ECs with Marimastat in a fibrin bead sprouting assay resulted in a rescue of the ballooning morphology observed in the c-Src-CA cells" Based on the images displayed in the figure and the associated quantifications, it still appears that c-Src-CA+Marimastat induces a vascular ballooning even if it is less pronounced than in the DMSO condition. Hence, it would be more accurate to describe the observed effect as a "partial rescue". In the microfabricated 3D vessel, in the figure 7A, cell-cell junctions still appear altered by c-Src-CA after the treatment with Marimastat, compared to the c-Src-WT-Marimastat, it would be more appropriate to talk about "partial rescue".
      • In Figure 6A, it seems that there is a decrease in the number of sprouts in the c-Src-DN condition compared to the control condition after the DMSO treatment, which is not observed in Figure 1, could the authors explain why?
      • There is no statistical paragraph in the method section.

      Referees cross-commenting

      Agree that the comments of the reviews all seem reasonable. Since cultured EC do not retain very specialized characteristics, perhaps repeating experiments with many other ECs would not be helpful, but suggest some key experiments be performed with one other type of EC.

      Significance

      General assessment:

      The authors generated different mutant forms of c-Src and used them in innovative 3D endothelial cell culture models. The vascular ballooning phenotype induced by constitutive activation of c-Src is particularly interesting and impressive, especially as it can be reproduced in 2 different culture models. The model of cSrc inducing extracellular matrix degradation specifically at the level of focal adhesions is compelling, although it lacks rigorous support in the 3D model. Further analysis of signaling pathways downstream of c-Src would strengthen the work. The link and the necessity of a balance between cell adhesion and cell-cell junctions are mentioned and have started to be explored, particularly through the phosphorylation of Ve-Cadherin, and more in-depth analysis would strengthen this aspect of the work.

      Advance:

      This study provides new insight on the role of c-Src in vascular homeostasis and during sprouting angiogenesis and starts to explore cross-talk between EC cell junctions and focal adhesions. This study also provides new elements crucial for our understanding of vascular malformations and the implication of cell-adhesion to the extracellular matrix in this process. This study may lead to further investigations into the role of c-Src in tumor angiogenesis.

      Audience:

      Basic research / Specialized

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      Referee #2

      Evidence, reproducibility and clarity

      In this work, Essebier and colleagues have shown that the upregulation of c-Src in endothelial cells results in vascular dilation independently of growth factors or shear stress. The authors have shown that this effect is driven by alteration in the number of focal adhesion and the secretion of matrix metalloproteinases responsible for extracellular matrix remodeling as the inhibition of the MMPs rescues the observed effects.

      This is an elegant work, with well-designed experiments and nice images to illustrate them. Congratulations. Nevertheless, the results not really support the conclusions drawn by the authors. The authors have only used one type of vein endothelial cells from one single donor but they conclude that is effect is general for all endothelial cells. Endothelial cells are very heterogeneous, not only depending on their function and localization, vein, artery or capillary, but also between different organs and in disease (PMID: 22315715, PMID: 28775214, PMID: 31944177, PMID: 33514719).

      The authors, should either repeat some of the key experiments in other type of endothelial cells, maybe arterial or microvasculature cells which are commercially available or at least state that the observations presented in this manuscript apply to HUVECs and discuss whether this would also apply for other cell types. Minor. Although the methods are well written and can be understood. To improve transparency, the authors should reduce the referring to other papers to describe the methods they perform and at least some kind of brief description should be included.

      The authors should report the real p value for their tests. Also when the test is not significant.

      Referees cross-commenting

      I agree with reviewer #1. Description of the statistical methods should be described in the methods. I have nothing else to add to the comments from the other reviewers.

      Significance

      The work presented here by Essebier and colleagues is very well designed and performed. The main strength of the manuscript is the study of the molecular mechanism that regulate the relationship between cells and the extracellular matrix. This is not very well studied in the context of disease. Although all the assays have been performed elegantly, the main limitation of this study is that it has been performed in only one type of endothelial cell. For this reason, it is not possible to extrapolate the conclusions drawn to all endothelial cells like the authors do.

      This work advances our knowledge of endothelial cell biology and it will be of special interest for the vascular biology and development communities.

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      Referee #1

      Evidence, reproducibility and clarity

      The manuscript demonstrates the effects of overexpression of c-Src variants in HUVEC endothelial cells. The c-Src kinase interacts with cell adhesion machinery, and the manuscript dissects relationships downstream of c-Src with respect to cellular behavior. Transduced wild type, constituent active, dominant negative c-Src is assayed by sprouting in 3D using a bead system, growth of microfabricated vessels under oscillatory flow, focal adhesion analysis, migration analysis, ECM analysis, and by rescue with a matrix Metalloprotease inhibitor.

      Major comments:

      1. p5. Fig 1: The sentence that the dominant negative completely abrogated 'this' phenotype implies that the dominant negative was put into the same cells as the constitutively active mutation. 'Abrogated' means it stops the phenotype, and the phenotype in the sentence prior was constitutively active. It is more accurate to say that the dominant negative was not distinguishable from wild type, which is what the statistics show. No double transfection (DN-CA) was performed.
      2. p.5. Fig 1: the phenotype of the CA cells is fascinating. They expand far beyond their normal territory, but they are held together in a lacy bubble. To me, this looks like a different phenotype from the ballooning that might occur in an arteriovenous malformation in vivo, as in vivo malformations are continuously covered by cells. I understand why the authors might use the term ballooning but given that the cells expand without continuously touching each other, I do not think this is the correct term. Would blebbing, or radial migration in a lace-like discontinuous pattern describe it better?
      3. p. 5. The authors do not describe any relationship to notch signaling. But notch signaling is the mechanism by which a sprout is selected. The CA phenotype shows no selection, and every sprout can continue migration. Did the authors check for any relationship between notch signaling c-Src activation? Does upregulation of C-Src downregulate notch?
      4. The statistical methods are not described in the methods (GraphPad?). These need to be added. Are only significant comparisons plotted? In Fig 6 and 7 only pairwise statistics are shown. If all significant comparisons are plotted, then this means that the comparison between the rescued CA and the treated or untreated control is not significant. This can be thought of as a partial rescue towards a wild type, but it is definitely not a full rescue. None of the statistical comparisons in Figure 6 or 7 show significant comparisons to wildtype. This needs more discussion.
      5. Mmp activity is inferred, but not measured. This is a limitaion as the assumption is that marimostat acting through the expected pathway.

      Minor concerns:

      1. Fig 5D. The presentation of the data in this graph is difficult to understand. It is trying to show the proportion of mScarlet in sprouts or balloons a percentage of all the scarlet cells. It would be better to have all cells represented in one bar, distributed between sprout and balloon in that one bar. i.e., for the control and dominant negative, the bars would be all black and then for the CA it would be all white. The zero data points are confusing. A proportions graph should be investigated here.
      2. The methods for vessel coverage for quantification in figs 1 and 7 are missing.

      Referees cross-commenting

      The comments from the other reviewers seem reasonable.

      Significance

      The work is well executed and takes a mechanistic approach. The images are well put together and the movies significantly add to the manuscript. The phenotype describes highly unusual endothelial behavior, which is of interest, and an advance in the field for its novelty. Linking cSrc to downstream signalling including mmps and demonstrating a rescue is also novel and a strength. This is a conceptual advance in the relationship between a kinase and cell behaviour in 3D.

      Understanding this mechanism may be useful in understanding enlarged vessels in vascular malformations, although the direct relevance is not clear due to limitations of using cultured cells in artificial environments, lacking, for instance, support by secondary cells and ECM that might be contributed by support cells and perhaps modulate the phenotype.

      The audience would be specialized in the basic research community.

  4. Dec 2023
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      Reply to the reviewers

      The authors will submit a complete point-by-point response to the reviewer's comments when submitting a fully revised version of the manuscript

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      Referee #4

      Evidence, reproducibility and clarity

      This is a short report featuring an innovative proximity labeling approach to the identification of proteins enriched in distinct types of chromatin domains. The domains compared are centromeric heterochromatin and X-linked hyperactive chromatin in Drosophila cells. These are relatively well-described domains, thus serving as an excellent test for the targeting of biotinylation in the permeabilized nucleus via interaction of specific antibodies with ProteinA-Apex2 provided exogenously. In parallel with the signature chromatin proteins CID or MSL2 as baits, the authors also target proteins in proximity to specific histone tail PTMs. Taking the work one step further, they compare the recovery of proteins +/- pretreatment of nuclei with RNase. They conclude that in each case selective interactions are specifically lost with pre-treatment of RNase.

      Major comment:

      As mentioned above, the approach is innovative and raises the possibility of a simpler MS method to identify protein-protein interactions. The RNase result is also provocative. However, in each case the specificity of potentially novel results are not explored further. Thus, the work is of interest but clearly still preliminary.

      Significance

      Did the authors dig deeper into novel interactions without obtaining convincing validation? Did they conclude that the MS approach is worth pursuing further or not? Admittedly the RNase result is difficult to follow up, but additional discussion of prior related work as well as consideration of future experiments would help improve the manuscript.

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      Referee #3

      Evidence, reproducibility and clarity

      The manuscript entitled 'The role of RNA in the maintenance of chromatin domains as revealed by antibody mediated proximity labelling coupled to mass spectrometry' by Choudhury et al. describe a new method, which they termed AMPL-MS (Antibody mediated proximity labelling mass spectrometry). The technique is based on proximity labelling but uses antibodies instead of fusion proteins. They use this method to characterize chromatin domains containing specific signature proteins or histone modifications and focus on the composition of chromocenter as well as the chromosome territory containing the hyperactive X-chromosome in Drosophila. Last but not least they include data that show that RNA is involved in maintaining the integrity of chromatin domains by RNAse treatment and mass spec analysis. The technique works well and the results are very clear. I therefore expect that, in the right hands, it is very reproducible.

      There are a few points that the authors may want to address:

      1. Title 'The' role of RNA in the maintenance of chromatin domains as..., seems too much of a statement. The title is therefore an overstatement that needs to be fixed.
      2. Figure 1 In Figure 1 the authors show very convincingly that the methods works well in their hands. They report on 172 proteins that localized in proximity to CID containing centromeric chromatin but do not provide the list of proteins as far as I can tell. Especially the RNA binders should be named.
      3. Figure 2 Using the hyperactive X is very clever when addressing RNA function but it should be stated in the discussion that there may be certain aspects that are specific to the male x and that is impossible to discriminate general and specific effects uncovered by this method.
      4. Figure 3 The authors should state more clearly the new findings of this figure since it is not fully obvious from its current representation.
      5. Figure 4 These are certainly interesting data but the authors remain in the very descriptive state. This is fine for a methods paper but then, the authors should hypothesize more on what the results mean. Are certain RNA dependent factors specific or general and they then recruit a specific set of factors that fall off upon RNAse treatment as a secondary effect or because they bind RNA directly. I feel like there may be more information that they authors got get out of there data than what they currently provide.
      6. Discussion The authors state: 'While we have not identified the RNAs responsible for the formation of theses domains, we clearly observe that they do confer specificity for the domains as we observe very little overlap in the factors lost from the corresponding domains (Fig 4h). the 'specificity' is hard to determine since factors bound to these regions are different, and therefore different factors will fall off, regardless of whether the RBP are specific unless the RNA is involved in recruiting the factors specifically, which the authors have not shown. Therefore, this result is suggestive and interesting but the statement is too strong and not backed by their results.

      Significance

      Overall, this is an interesting method that has been used in the past to identify protein modifications with high quality antibodies available. The authors show here that the method can also be used to different nuclear proteins and detect changes in protein complex composition. As it is it is primarily a methods paper, and for that the results are very clear. Gain of new info is not large but it is a useful technique to continue research on this subjectand is a nice start of many new avenues into how RNA effects chromatin,

      My expertises are in epigenetics, chromatin biology, RNA and Drosophila genetics

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      Referee #2

      Evidence, reproducibility and clarity

      This manuscript by Choudhury et al. describes a new method for antibody-mediated proximity labeling and applies it in the cell nucleus. In short, nuclei are isolated, fix and permeabilized, proteins are labeled with primary antibodies, a bacterially expressed/purified protein-A-APEX2 fusion protein is added, conventional H2O2/biotin phenol labeling of proximate protein is performed, proteins are un-crosslinked and biotin-affinity captured for MS analysis. The application to nuclear proteins and results seems appropriate. The method is highly similar to and more complicated than prior methods as described in more detail below. I would focus the impact of this paper towards its biological results and not the novelty of the methods used.

      Prior methods that effectively accomplish the same outcome (fixed cells/tissues, antibodies and proximity labeling for AP-MS) have been published before. Perhaps most recently it was reinvented as the so called BAR method in PMID 29256494. That paper was cited here but incorrectly as BirA-related, which it is not. Of course that prior manuscript itself ignored prior methods from years back (2008, 2012, 2014, 2015, PMID 18495923, 22936677, 24706754, 25829300) using the same approaches of antibody targeted peroxidase for the same purposes of proximity labeling.

      This method seems a somewhat Rube Golderbergian approach to antibody-mediated proximity labeling, which has been performed previously in multiple reports. APEX/2was developed to function inside of living cells since HRP does not. The value of doing the proximity labeling in living cells was either to capture protein associations over time, as with BioID/TurboID, or to get snapshots of protein associations in living cells with APEX/2. HRP does however function quite well for proximity labeling outside of cells, or in fixed/permeabilized cells, as has been demonstrated in the prior methods/papers that are referenced above. Replacing commercially available secondary antibodies fused to HRP with homemade protein-A-fused to APEX2 seems counterintuitive and/or unnecessary.

      Could the authors explain the mechanisms that underly the reported enhanced sensitivity of AMPL-MS compared to conventional APEX2 in living cells. Is there something about the nuclear isolation that reduces interfering background, the loss of small soluble molecules in the nucleus after isolation and/or permeabilization that enhance the proximity labeling, penetration issues with the biotin-phenol in living cells, and/or something else?

      There seems to be the use of various controls based on the figures and legends, but they are not clearly described in the results or methods.

      All MS results should be provided, preferably in an Excel file format.

      Significance

      This manuscript by Choudhury et al. describes a new method for antibody-mediated proximity labeling and applies it in the cell nucleus. In short, nuclei are isolated, fix and permeabilized, proteins are labeled with primary antibodies, a bacterially expressed/purified protein-A-APEX2 fusion protein is added, conventional H2O2/biotin phenol labeling of proximate protein is performed, proteins are un-crosslinked and biotin-affinity captured for MS analysis. The application to nuclear proteins and results seems appropriate. The method is highly similar to and more complicated than prior methods as described in more detail below. I would focus the impact of this paper towards its biological results and not the novelty of the methods used.

      Prior methods that effectively accomplish the same outcome (fixed cells/tissues, antibodies and proximity labeling for AP-MS) have been published before. Perhaps most recently it was reinvented as the so called BAR method in PMID 29256494. That paper was cited here but incorrectly as BirA-related, which it is not. Of course that prior manuscript itself ignored prior methods from years back (2008, 2012, 2014, 2015, PMID 18495923, 22936677, 24706754, 25829300) using the same approaches of antibody targeted peroxidase for the same purposes of proximity labeling.

      This work may be of interest to investigators studying the nuclear proteins/structures to which the APML-MS was applied.

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      Referee #1

      Evidence, reproducibility and clarity

      Summary:

      This manuscript describes the application of a new variation of proximity (biotin) labelling (antibody mediated proximity labelling coupled to mass spectrometry, AMPL-MS). Combining protein- or histone variant-specific antibodies with a APEX2-proteinA fusion protein, they characterise the proteome of nuclear subdomains and demonstrate that RNA is important for the integrity of two tested domains, the Drosophila chromocenter and the chromosomal territory of the hyperactive X chromosome.

      Major comments:

      The vast majority the experimental results, statistical analysis, and conclusions drawn by the authors appear sound and are described in way that should allow reproduction (however, see my comments below for some suggestions for minor improvements). The authors rigorously test their method, using the Drosophila chromodomain as 'playground', before applying it to other chromosomal areas and histone variants/modifications. Besides providing proteomes of the targeted nuclear subcompartments, they show that RNase treatment of the cells radically changes the proteome(s) and conclude a role for RNA in the integrity of the corresponding compartments. This is shown by immunofluorescence staining as well as proteomic analysis of the biotinylated proteins. The images in figure 4b (and to lesser extent 4c) show an increased intensity and more diffuse labelling. Can the authors exclude that RNase treatment simply leads to an increase in accessibility for the biotin-phenol, hence a visibly higher biotinylation? Along these lines, have the authors maybe observed an increase in overall labelling/pulldown efficiency or for biotinylated proteins in their proteomic data?

      Minor comments:

      1. In figures 1a and 4a (as well as in the Methods section), the authors use the term 'biotin-tyramide' as labelling agent, but in the main text and figure legends 'biotin-phenol' is used. For clarity, only one term should be used.
      2. Figure 2a shows a magnified cell/nucleus in the last column. To what cells do the magnifications in this last column refer to? Maybe these cells could be boxed in the second last column?
      3. In figures 4b + c:, the figure legend mentions the individual rows as '(I)' and '(II)' but no such label seen in the corresponding panel(s).
      4. The Quantification method for co-localization (e.g. 1c and 2b) is insufficiently described to the reader (reference simply relates to Fiji package). What module/script within the Fiji package has been used?
      5. The RNase treatment is not described at all in the methods section or the supplementary information and should be added.
      6. The sentence on page 6 ('As expected, neither the targeted signature factor or proteins that mainly interact with them protein-protein interactions such as MSL1,3 and MOF for MSL2 or Cenp-C for Cid are not affected by RNAase treatment') should be rephrased as it is not comprehensible in the current form.

      Significance

      The findings in this manuscript advance our portfolio of proximity labelling techniques although this advancement is not a major step forward. As the authors state themselves, antibody-based proximity labelling has already been introduced, even in the context of chromosomal proteomes (e.g. Gan et al., 2022; https://doi.org/10.1016/j.gpb.2021.09.003). One major technical advance is the finding that modifications or protein variants can now reliably be targeted for proximity labelling, using their method. Furthermore, the number of cells that are required for proximity labelling and detection of biotinylated proteins could be significantly reduced compared to previous approaches (although this might simply be due to the use of a more advanced proximity labelling enzyme). I should state her that as I am not an expert in the field of chromatin domains, I cannot be certain if the proteomes and changes of proteomes the authors report are providing a significant increase in our knowledge on these domains, especially related to their individual functions.

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      Reply to the reviewers

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

      In the paper entitled GOT1 primes the cellular response to hypoxia by supporting glycolysis and HIF1α stabilization, Grimm and co-authors investigate the metabolic adaptations of cancer cells upon acute hypoxia. By measuring metabolite levels at early time points upon hypoxia, they observe the accumulation of lactate and depletion of aspartate, along with other TCA cycle metabolites. Importantly, they demonstrate that these metabolic changes are independent of the HIF alpha-dependent transcriptional response. The authors investigate the role of aspartate during these initial phases of hypoxia. To this aim, they characterize cells devoid of glutamate oxaloacetate transaminase (GOT1), in which aspartate accumulates and can no longer be used for replenishing NAD+ via the downstream conversion of oxaloacetate to malate, via malate dehydrogenase. These cells have lower cytosolic NAD+ which affects glycolytic flux through the rate-limiting, NAD+-dependent enzyme GAPDH. GOT1 KO cells have a decrease in glucose consumption, lactate secretion and metabolite levels downstream of GAPDH upon early hypoxia, however ATP levels and viability are only affected with additional lactate dehydrogenase (LDH) impairment. Finally, the authors demonstrate that GOT1 KO cells have higher alpha-ketoglutarate (aKG) levels during early hypoxia, which could contribute to higher prolyl-hydroxylation and subsequent degradation of HIF, regulating the transcriptional response mediated by transcription factor.

      * Major comments *

      1. The authors claim that they were unable to supplement cells with aspartate (Figure S3), (even though an increase of aspartate is instead observed in cells treated with sodium aspartate) and had to resort to the GOT1 knock-out model to "prevent aspartate from decreasing in hypoxia". This approach implicitly assumes that Got1 is the main driver of aspartate depletion upon hypoxia. However, although steady-state levels of aspartate are indeed higher in these cells, there is still a strong decrease upon hypoxia, which the authors acknowledge but merely ascribe to "attenuated production from glutamine". This seems an insufficient explanation, considering the very fast depletion upon hypoxia originally observed. The authors should provide further information regarding why aspartate is depleted in these conditions and consider other aspartate-consuming enzymes such as GOT2, ASNS, or even nucleotide biosynthesis and urea cycle enzymes. These observations could be made using the labeling experiments already acquired. In addition, to corroborate their hypothesis, the authors could supplement 13 C-aspartate at a supraphysiological concentration (i.e. 5-10 mM) to determine to what extent it is consumed by GOT1 or other pathways. > We thank the reviewer for this comment that helped us to recognise, in retrospect, that by focusing on GOT1ko as a means to rescue aspartate levels detracted from our main finding and extensive mechanistic insights into the role of GOT1 in sustaining the increase in glycolysis in early hypoxia. As we detail in our response to the Reviewer’s point 2, we have now re-written our results section to better clarify why we focused on GOT1 (lines 175-223 of the revised manuscript – please note that line numbering corresponds to the word document with the track changes off). However, we also agree that, because the motivation that led us to GOT1 was the counter-correlation between aspartate and lactate, expanding on the pathways that determine aspartate levels in hypoxia would be useful to the reader.

      2. To address the reviewer’s point, in revised Fig. S3E, we present new data where we incubated cells in normoxia or hypoxia for 3h in the presence of 1.5 mM 13C-aspartate. We opted for an intermediate aspartate concentration which was enough to observe intracellular labelling while minimising significant perturbation to cells. We found that the amount of labelled aspartate that accumulates intracellularly is not significantly different between normoxia and hypoxia. At the same time, we observe a vast depletion of unlabelled aspartate. We accept that aspartate labelling may not have reached isotopic steady state within the 3h time point we are confined to for our experiments. However, if increased consumption contributed significantly to aspartate depletion within this timeframe, the amount of labelled aspartate that accumulated would be lower in hypoxia compared to normoxia. Therefore, the data in Fig. S3E indicate that, at least within the timeframe of our experiments, the magnitude of aspartate consumption is not likely to increase to such an extent that could significantly contribute to the depletion in aspartate.

      We had, indeed considered other aspartate-consuming pathways, however, in light of the above results and our subsequent finding that GOT1 is needed for increased glycolysis, we did not pursue these investigations any further and focused on the role of GOT1 instead.

      • In revised Figure S3, and also in response to one of the Reviewer’s other comments below, we have now replotted the data from the experiment in the original manuscript to show both absolute and fractional isotopologue abundances of TCA intermediates from cells labelled with 13C-glucose or 13C-glutamine. Based on these re-plotted data, we find that the amounts of labelled intermediates from both labels decreases; the apparent decrease from glutamine appears greater than that from glucose, likely because glutamine labels more rapidly a greater fraction of TCA intermediates. Moreover, glutamate fractional labelling from glutamine decreases, but modestly increases from glucose over time in hypoxia compared to normoxia. These data raise the possibility that TCA intermediates are diverted to glutamate synthesis. However, as we point out in the revised text, the fact that only glutamine has reached an isotopic steady state by the end of the time course precludes us from making a more accurate quantitative statement and therefore we have refrained from further elaborating on these observations.

      Taking the above observations together, in the revised text we do not dismiss increased consumption as a factor in decreased aspartate levels and rather state that “within the timeframe tested, decreased production is a significant contributor to the low aspartate levels in early hypoxia.” (lines 187-188).

      In line with the previous comment, the conclusion that "GOT1 activity, rather than a decrease in aspartate concentration itself, is required to sustain the increase in glycolysis in early hypoxia." seems questionable, especially considering the failed aspartate supplementation. The authors suspect low expression of plasma membrane aspartate transporters as the reason and quote Garcia-Bermudez et al.2018 (PMID: 29941933). This paper contains ranked SLC1A2 mRNA expression data from the Cancer Cell Line Encyclopedia (CCLE). The authors may apply aspartate supplementation and "early hypoxia" to a cancer cell line expressing SLC1A2 or other aspartate transporters. Alternatively, they could try introducing the transporter by overexpression.

      > We concede that the way we phrased this statement was not ideal and has rightly led to the reviewer’s criticism. In particular, referring to a “decrease in aspartate concentration”, could mislead the reader into thinking that we were referring to the process of aspartate consumption, rather than the low aspartate levels themselves, which is what we aimed to explore. In the revised text, we now carefully make this distinction; we show new data (Figure S3G) supporting the idea that low aspartate levels are not necessary for increased lactate; we explain that, given the known role of the malate-aspartate shuttle in coordinating redox balance and potentially affecting glycolytic flux, the fact that aspartate didn’t appear to be limiting was surprising and we therefore asked whether GOT1, which depends on aspartate, had a role in the increased glycolysis in early hypoxia. Given that GOT1ko attenuated the increase in glycolysis we subsequently focused on the mechanism underlying this observation. In more detail:

      As Reviewer 2 noted in point 1 of their review, the increase in lactate became more apparent after 2 h, when aspartate levels had almost reached their minimum. This successive timing of abundance changes raised the possibility that low aspartate levels precede, and possibly drive, the increased lactate. Therefore, we sought to test whether this was the case by preventing depletion of aspartate in hypoxia with exogenous aspartate. We agree that, to address the comment of Reviewer 1 here, overexpression of an aspartate transporter would have been a good way to overcome poor aspartate uptake by MCF7 cells, however, at the time we initiated this study, SLC1A2 was not known as an aspartate transporter. We, therefore, cultured MCF7 cells for several weeks in media containing 0.5 mM aspartate (which is normally absent in our standard media formulation) because we expected that cells would adapt to take up more aspartate. We, thereby, obtained a derivative cell line that we called MCF7Asp. In new Figure S3G, we show that addition of 0.5 mM aspartate in the media of MCF7Asp cells largely prevented the decrease in intracellular aspartate seen in parental MCF7 cells after 3h in 1% O2; however, the increase in lactate was similar between MCF7 and MCF7Asp cells. These data are consistent with the idea that the low aspartate levels in hypoxia are not the likely cause for the increase in lactate.

      As the Reviewer notes in point 3 below, production of malate m+1 from 2H-glucose does not decrease below the levels found in normoxia (Fig. 4H), even though aspartate levels are depleted (Fig. 1C). Together with the fact that maintaining aspartate levels to near-normoxic levels does not further boost lactate levels (Figure S3G), these findings speak against the notion that the lack of increased GOT1-MDH1 flux is due to insufficient aspartate and are aligned with the idea that the malate-aspartate shuttle is saturated (PMID: 35973426, 21982705).

      • The observation that labelled m+1 malate produced from [4-2H]-glucose is similar in normoxia and hypoxia (Figure 4G), does not support the notion that GOT1-MDH axis is increased at low oxygen and seems to suggest that the depletion of aspartate observed in early hypoxia is unrelated to this axis. The authors should resolve this discrepancy.*

      > In our manuscript, we do not claim that the flux through the GOT1-MDH1 axis is increased but, instead, we emphasise the fact that, as the reviewer observed, malate labelling from 2H-glucose is unchanged (e.g. see text in our original manuscript - lines 519-522 of the revised version: “Importantly, a model where increased upper glycolysis due to the Pasteur effect overwhelms GAPDH capacity also elucidates the apparent increase in the reliance of glycolysis on GOT1-MDH1 in hypoxia, even though flux through this pathway is not elevated.”). As we also detail in our responses to comments 1 and 2, above, in the revised manuscript, we have re-written the discussion to better explain that the reliance on GOT1 in hypoxia is not driven by increased flux through this pathway (which is likely saturated as outline in our response to point 2, above), but rather from the increased demand imposed by the elevation in incoming glucose carbons due to the Pasteur effect (lines 504-531). This is akin to a situation where increased demand for a product drives its price up if the manufacturer does not boost production to increase supply. We hope that the reviewed discussion makes this clearer and addresses the reviewer’s comment.

      • The alpha-KG level regulation by Got1 and the subsequent HIF1alpha "priming" seem quite promising and likely the most novel part of the manuscript. However, further proof should be added to support this strong claim. First, aKG to succinate ratio, rather than aKG alone, is a better indicator of aKG-dependent dioxygenases activity. So. the authors should provide this measurement. *

      In line with the reviewer’s excellent suggestion, in the revised manuscript, we added new panel in Figure 6F (discussed in lines 457-458) that shows αKG levels alongside the corresponding αKG/succinate ratios. These data agree with our original interpretation that cofactor levels in GOT1ko cells favour increased dioxygenase activity.

      *Second, the authors should rule out the possibility that the differential hydroxylation of HIF is due to the redistribution of intracellular oxygen due to alterations in mitochondrial function. To do this, they could determine whether cytosolic oxygen levels differ in the two conditions. *

      The reviewer raises the interesting hypothesis that, given the decreased respiration in hypoxic GOT1ko cells, one could expect increased availability of oxygen that could contribute to the destabilisation of HIF1α. To the best of our knowledge, measuring absolute cytosolic O2 concentration, particularly in hypoxia, would require specialised equipment [e.g. phosphorescence lifetime imaging (PMID: 26065366), or phosphorescence quenching oxymetry (PMID: 21912692); unfortunately, we do not have access to such equipment. In the revised manuscript, we acknowledge the reviewer’s point with added new text in the discussion (lines 576-577).

      Finally, the authors could test whether α-ketoglutarate or 2-hydroxyglutarate supplementation affects HIF stability in their experimental conditions.

      > We thank the reviewer for this suggestion. In the revised manuscript (new Figure S6H and lines 453-455) we show that addition of DM-αKG, a cell-permeable form of αKG, to the media of MCF7 cells incubated at 1% O2, decreases HIF1α protein levels in a dose-dependent manner and, at the highest dose, to a degree comparable to that of GOT1ko cells.

      Minor comments:

      - The glycerol-3-phosphate shuttle is another means of re-oxidizing NADH and α-GP is indeed higher in GOT1 KO. According to this, in Fig 5C a clear increase in a-GP is observed in LDH KO cells. Would the phenotype be stronger upon additional GPD1 knockout or inhibition?

      > The main phenotype of combined LDHA/GOT1 inhibition is a deficit in ATP and decreased cell survival. While increased flux through GPD1 could, indeed, provide more NAD+, this would come at the expense of glucose carbons that would otherwise need to flow into lower glycolysis to produce ATP. Consistent with this idea, our data show that, even if GPD1 or other dehydrogenases reoxidise NADH, as would be the case in both the LDHAko and GOT1ko cells where α-GP is elevated, they are not sufficient to compensate for the decrease in LDH and GOT1 activity. Therefore, we did not pursue this hypothesis further.

      * - Aspartate and lactate levels appear unchanged in MDA-MB231 upon hypoxia. Can these changes be ascribed to a pseudohypoxic state? The authors should comment on this observation.*

      > In Figure S2A, we show that MDA-MB-231 cells have increased basal levels of HIF1α compared to the almost undetectable HIF1α seen in BT474 (same figure, adjacent panel) or MCF7 cells (Figure 2A). We, therefore, agree with the reviewer’s hypothesis that the attenuated changes in aspartate or lactate levels in MDA-MB-231 cells are likely due to a pseudohypoxic state. As this is speculative, we have refrained from elaborating on this point further in the manuscript.

      * - Figure S3B: The authors do not provide information on the length of hypoxia for these experiments. *> The data shown in original Figure S3B (new Fig. S3A-B) are a time course. Cells were incubated at 21% or 1% O2 with the respective isotope label for increasing lengths of time, with the longest time point shown (6h) being the longest time we incubated cells in hypoxia. If the reviewer meant another panel, the length of hypoxia would be 3h unless otherwise stated.

      - Glucose and glutamine isotopic labelling should be accompanied by graphs showing the total pool levels of these metabolites, and also the uptake of glucose and glutamine (and their specific isotopologue distribution). It would be important to show the isotopologue distribution of aKG in all the conditions tested, in particular, because of its proposed regulation by Got1.

      > In the revised manuscript, new Fig. S3 panels A-D, we now show absolute and fractional isotopologue distributions for TCA intermediates for both glucose and glutamine labelling. We have omitted showing αKG in this figure as we could not reliably quantify it in the glutamine-labelling experiment. Also, unfortunately, quantification of glutamine in our GC-MS datasets is not reliable due to conversion to 5-oxoproline.

      - Malate generated by MDH1 can be converted by ME1 into Pyruvate, which could be further processed by LDH. Have the authors measured this conversion in their dataset.

      > In the figure below we labelled cells with [U-13C]-glutamine for 3 h at 21% or 1% O2 and plotted the fractional labelling for all observable isotopologues in malate, pyruvate and lactate. These data show that there is minimal labelling in pyruvate and lactate (- Aspartate absolute levels across cell lines appear different. Is this due to differences in cell volume? Can the authors comment on this observation?

      > To address the reviewer’s hypothesis, we focused on MCF7 and MDA-MB-231, the two cell lines with the highest and lowest aspartate levels, respectively. The volume of MCF7 is approx. 19% higher than that of MDA-MB-231 (calculated based on cell size data from PMID: 31015463). Based on this calculation, and bearing in mind that cell volume is a good predictor of biomass content (PMID: 18595067), cell volume differences may contribute to, but cannot fully account for the one order of magnitude difference in aspartate abundance we see between these cell lines (Figures 1C and S1A).

      The cell lines we used in this manuscript (MCF7, BT474, MDA-MB-231, MCF10A) represent different breast cancer (or untransformed, in the case of MCF10A) cell types, with different oncogenic mutation content (PMID: 17157791, 22460905) and proliferation rates (PMID: 22628656); all these factors can be related to steady-state cellular metabolite levels (PMID: 31015463). In the figure below, we have plotted aspartate abundance data (from PMID: 31068703) in 928 cell lines of various origins. These data show that aspartate levels can differ as much as 2 orders of magnitude between cancer cell lines and about half an order of magnitude between MCF7 and MDA-MB-231 or BT474 (MCF10A was not present in this dataset); they also show that aspartate levels in the three cell lines rank in the same order as in our manuscript (MCF7>BT474>MDA-MB-231), although, it is unclear if cells in this dataset were also cultured in dialysed serum as in ours, so we cannot confidently compare the absolute aspartate measurements between our studies.

      In conclusion, we suspect that cell volume differences together with other factors, such as proliferation rates and metabolic network differences may account for the differences in intracellular aspartate levels.

      - Under hypoxia the contribution of glutamine (labelled fraction, Fig. S3) to TCA cycle intermediates decreases. However, this is not paralleled by an increase in the contribution of glucose, as also supported by an increase in the m+0 in the glutamine labeling but not in the glucose one. How do the authors explain this apparent inconsistency? Are there sources of unlabelled TCA cycle during the hypoxic experiment?

      > While glucose and glutamine are the major carbon sources in many cultured cancer cell lines, incl. MCF7 as indicated by the data in Figure S3A-D, other nutrients (such as amino acids, other than glutamine, and fatty acids) can also provide carbons at various points of the TCA cycle. The fact that fractional labelling of glutamate from glutamine is decreased in hypoxia would suggest that the source of decreased contribution of glutamine into the TCA is unlabelled glutamate. We can exclude uptake of exogenous glutamate, because all our metabolic measurements are performed with cells incubated in media without glutamate and supplemented with dialysed serum. However, we observe a modest increase in the fractional labelling from glucose into glutamate (Figure S3A). As glucose labelling into the TCA cycle is not at steady-state even after 5h, it is hard to assess whether, increased labelling from glucose suffices to explain the dilution of glutamine-derived labelling into glutamate a quantitative conclusion but it points to efflux of intermediates out of the TCA cycle (discussed in lines 181-183 of the revised manuscript).

      We thank the reviewer for their time and thoughtful comments that helped us improve the presentation of our work.

      **Referees cross-commenting**

      Referee 2 raises important questions that are in part aligned with referee 1 and are reasonable and doable is the time frame proposed. These are all important questions and comments to consolidate the central hypothesis of the work and I believe are required for publication.

      *

      Reviewer #1 (Significance (Required)):*

      Overall, this is an exciting and well-executed piece of work focusing on the early biochemical consequences of hypoxia that the wide metabolism/biochemistry audience will appreciate. While most of these observations are not entirely unexpected, the work brings a sufficiently novel perspective and insights to the field and deserves publication. However, some conclusions are not fully supported by the data and some additional experiments are suggested to bring clarification and strengthen the authors' conclusions.

      We are a lab expert in cancer metabolism.

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

      Summary ** This manuscript represents an interesting and novel description of the role of a cytosolic transaminase, glutamic-oxaloacetate transaminase 1 (GOT1) on both cytosolic redox (and therefore glycolysis through its functional linkage with malate dehydrogenase 1) and the availability of alpha-ketoglutarate for stabilisation of HIF1a in hypoxia. Some of the most interesting data are the evidence for increased cytosolic NAD+ regeneration through the combined action of LDHA (known) and GPD1 (less well-described increase in activity in hypoxia). The manuscript as a whole describes the multiple systems required for the early response to hypoxia, but the focus of the title and way the article is written do not entirely reflect this. For example, the title focuses on GOT1 as the enzymes whose activity is responsible for the early response to hypoxia. However, this is not reflected in some of the data - the deuteron labelling in particular - which shows that LDH and GPD1 are responsible for the biggest redox activity (i.e. support of glycolysis). A degree of reframing of the article may therefore be of benefit.

      We thank the reviewer for their constructive suggestions. In the revised manuscript, we have re-written the title and the relevant parts of the results section, and we have significantly re-structured the discussion section to reflect the fact that multiple enzyme systems, one of which is GOT1, converge to support the glycolytic increase and cell survival in early hypoxia. Furthermore, in our point-by-point responses, below, we highlight in detail how we have streamlined the way we present our results.

      *Major comments. *

      In Figure 1 C and D, the data suggest significant changes in the decrease in cellular aspartate between 1-2 hours, which then slow. This is followed by a change in lactate concentrations from 2 hours onwards, which is observed in the cells (D) and media (F). The rapid decrease in aspartate concentration suggests a relatively large change, which does not correspond to the later lack of alteration in deuteron labelling from d4-glucose (Figure 4H-J) in m+1 malate. This therefore suggests that the biggest determinant of decreased aspartate is not coupled to MDH1 activity directly. If the manuscript is focused on the relevance of GOT1 activity to the early hypoxic response, this should be better resolved. Given that this could undermine the strength of the case being made for GOT1 activity playing a significant role (through MDH1), could the authors perform the same experiments but in the GOT1KO cells to show how NADH is handled under these conditions by LDHA and GPD1? If the focus of the manuscript is shifted, these experiments would likely not be necessary.

      > We thank the reviewer for these comments, which, together with those by Reviewer 1, highlighted that the way we presented our results warranted improvement. First, we would like to clarify that by referring to a “decrease in aspartate concentration”, we may have misled the reader into thinking that we were referring to the process of aspartate consumption; rather we wanted to explore whether the low aspartate level itself could be causing the increase in lactate. This is because, as the Reviewer points out, the rate of lactate accumulation picked up after aspartate had almost reached its minimum. Furthermore, by not elaborating on the cause of decreased aspartate and by focusing on GOT1ko as a means to rescue aspartate levels implied a hypothesis whereby GOT1 was the main aspartate consumer, thereby detracting from our main finding and extensive mechanistic insights into the role of GOT1 in sustaining the increase in glycolysis in early hypoxia (regardless the contribution of GOT1 activity in the observed depletion of aspartate).

      In the revised text, we have re-written parts of the results section to better clarify these points (e.g. lines 175-223 - please note that line numbering corresponds to the word document with the track changes off). In summary, and as detailed below, we explore the glucose and glutamine data further and present new data with 13C-Asp, which, together support the idea that decreased aspartate in early hypoxia is largely attributable to decreased synthesis and, to a lesser extent, if at all, to increased degradation. We then explain that, given the known role of the malate-aspartate shuttle in coordinating redox balance and potentially affecting glycolytic flux, we asked whether GOT1, which depends on aspartate, still had a role in the increased glycolysis vis-à-vis the low aspartate levels in early hypoxia. Given that GOT1ko did attenuate the increase in glycolysis we subsequently focused on the mechanism underlying this observation. We have re-structured the discussion, to highlight that GOT1 is one the multiple systems required for survival in early hypoxia. We also explain that the reliance on GOT1 in hypoxia is not driven by increased flux through the GOT1-MDH1 axis (which is likely saturated), but rather from the increased demand imposed by the elevation in incoming glucose carbons due to the Pasteur effect (lines 504-531). A relatable situation is when increased demand for a product drives its price up if the manufacturer does not boost production to increase supply. We hope that the revised text better clarifies these points.

      Below, we detail the new experimental evidence/analyses we referred to above:

      • In revised Figure S3A-D, we have now replotted the data from the experiments in the original manuscript to show both absolute and fractional isotopologue abundances of TCA intermediates from cells labelled with 13C-glucose or 13C-glutamine. Based on these re-plotted data, we find that the amounts of labelled intermediates from both labels decreases; the apparent decrease from glutamine appears greater than that from glucose, likely because glutamine labels more rapidly a greater fraction of TCA intermediates. Moreover, glutamate fractional labelling from glutamine decreases, but modestly increases from glucose over time in hypoxia compared to normoxia. These data raise the possibility that TCA intermediates are diverted to glutamate synthesis. However, as we point out in the revised text, the fact that only glutamine has reached an isotopic steady state by 5h precludes us from making a more accurate quantitative statement and therefore we have refrained from further elaborating on these observations.

      • In revised Fig. S3E, we present new data where we incubated cells in normoxia or hypoxia for 3h in the presence of 1.5 mM 13C-aspartate. We found that the amount of labelled aspartate that accumulates intracellularly is not significantly different between normoxia and hypoxia. At the same time, we observe a vast depletion of unlabelled aspartate. We accept that aspartate labelling may not have reached isotopic steady state within the 3h time point we are confined to for our experiments. However, if increased consumption contributed significantly to aspartate depletion within this timeframe, the amount of labelled aspartate that accumulated would be lower in hypoxia compared to normoxia. Therefore, the data in Fig. S3E indicate that, at least within the timeframe of our experiments, the magnitude of aspartate consumption is not likely to increase to such an extent that could significantly contribute to the depletion in aspartate.

      Together with the data in Fig. S3A-D, these findings suggest that decreased aspartate in early hypoxia is to a great degree driven by decreased production.

      • The authors present data in Figure 1 and 3 using 2DG as a surrogate for glucose uptake. 2DG has been previously shown not to always be a surrogate for glucose uptake (Sinclair et al. Immunometabolism 2020). Given that this paper highlighted warns in particular about assuming SLC2A1 and SLC2A3 activities based on 2DG uptake, and that these two transporters are the major glucose transporters regulated by hypoxia, a cautious approach to these data is recommended. Assuming that 2DG uptake is a surrogate for glucose in this system (panel C), the effect of GOT1 appears to be at the level of glucose uptake even at 3 hours - it has been marked as being significant by the authors. This suggests that loss of GOT1 has an effect on glucose uptake prior to any transcriptional response is observed. Is the plasma membrane occupancy by the SLC2A1 or SLC2A3 been reduced after GOT1 KO? The same is true for Figure 1 - as intracellular aspartate and lactate and extracellular lactate is shown, could change in extracellular glucose not be presented as a direct measure?*

      The reviewer raises two points: (a) that using 2DG may not faithfully report transporter-mediated glucose uptake and (b) that, if our observations with 2DG are valid, they could point to the possibility that attenuation of glycolysis in GOT1ko cells may be attributable to effects in glucose uptake. In brief, we cannot use glucose measurements in media as an indicator of glucose uptake rates because we do not observe measurable glucose depletion from media within the relevant timeframe (3h) of our experiments.

      (a) Given that we did not have access to a set up for using radionuclides, we explored both 2DG-based and glucose depletion from media as potential means to assess glucose uptake. We found that, over 24h, MCF7 cells deplete glucose faster than cells incubated in normoxia for the same amount of time (figure below, A). The magnitude of this increase is similar to that we report using 2-DG (~3-fold, Fig. 1E and 3C). However, we observed only minimal depletion of glucose in the first 3-5 h of culturing cells with fresh media (figure below, B). This is perhaps not surprising given that studies that look at metabolite exchange rates (incl. glucose) typically sample over a period of one to several days rather than hours (e.g. PMID: 31015463, 22628656). In conclusion, we reasoned that detecting a positive change in signal (intracellular 2DG) would provide a more sensitive means than a decrease in extracellular glucose to enable assessment of glucose use within the early time-points that our manuscript is mainly concerned with.

      (b) Indeed, we were initially intrigued by the decrease in glucose uptake by GOT1ko cells as it could explain decreased lactate production. However, the upregulation of upstream glycolytic intermediates in GOT1ko cells in both normoxia and hypoxia (Figure 4A) together with the evidence of increased α-GP production from glucose (Figure 4K-L) suggested that, even if less glucose is taken up by GOT1ko cells, there is still a bottleneck at the GAPDH step that prevents maximal flow of glycolytic intermediates to lower glycolysis. We therefore did not pursue further the cause of decreased glucose uptake by GOT1ko cells at this stage.

      • The data shown in Figure 2D suggests that there is little change in overall contribution to citrate from glucose in hypoxia compared to normoxia, and that HIF1 is does not play a role in the hypoxic response at this point. However, the data presented are overall fractional labelling, and therefore do not focus on the main hypoxia-dependent point of control highlighted before this by the authors - pyruvate oxidation through PDH. Could the authors consider plotting m+2 isotopomer of citrate either alongside or instead of the total fractional label (which includes hypoxia-independent PC activity and cycling carbons). *

      We agree with the reviewer’s suggestion. In the revised manuscript, we added a new panel in Fig. 2D that shows the m+2 citrate isotopologue alongside the original fractional labelling data. This new panel is shown as a bar graph to enable the presentation of individual datapoints and statistical test results.

      Additionally, the experimental set-up means that average incorporation over the time shown is represented - i.e. the 3h timepoint is incorporation over the first two hours, while the 24 hour timepoint is averaged over the whole period. It is therefore likely under-representing the decrease in glucose contribution to citrate at 24 hours - the authors could point this out, or OPTIONALLY perform a more time-resolved experiment where flux over shorter periods is assessed for each of the timepoints (i.e. 0-1, 2-3, 5-6, 23-24).

      Indeed, we did consider a more time-resolved labelling experiment as the reviewer suggests, however, we decided against this approach as we were concerned that even if we pre-equilibrated the labelling media in hypoxia, it would be challenging to avoid perturbations associated with handling of the cells during addition of the isotopically labelled compound. The new panel in Fig. 2D that shows absolute citrate m+2 abundances should address this point, however, in the revised text (lines 162-164) we added new text that points out this issue.

      • Figure 3 data are key for the GOT1 theme of the manuscript, as the authors show that loss of GOT1 increases cellular aspartate in both normoxia and hypoxia - suggesting that GOT1 is an aspartate-consuming enzyme in both conditions. Indeed the magnitude of the change in aspartate after GOT1 knockdown appears similar in both conditions (Panel B). These are interesting data, as they contrast with a recently published study (Altea-Manzano et al. Molecular Cell 2022) suggesting that in respiration-deficient cells (a condition with parallels with hypoxia), GOT1 activity may be aspartate producing to supply aspartate to the mitochondria for GOT2. It would be important for the authors to discuss the differences between studies.*

      Following the reviewer’s suggestion, in the revised manuscript (lines 547-556), we have now expanded our previous discussion on the functions of GOT1 in cells with respiration defects.

      • Panel E shows data at 5 hours, while the rest of the panels here are a mix of 1 and 3h timepoints. Equally panel E also presents concentration, while D presents relative abundance of lactate - could a consistent approach to presenting the results be taken?*

      We agree. Taking into consideration that the data in this panel show one time point of the full time-course in Figure S3F, and to streamline the presentation of these data, in the revised manuscript, we have moved the time-course graph to the main figure.

      • In Figure S3, the authors show the lack of direct aspartate uptake, or supplementation through the use of an esterified form. OPTIONAL: they could consider using the expression of SLC1A3 (Tajan et al. Cell Metabolism 2018; Hart et al eLife 2023) to increase aspartate uptake in order to test their hypothesis. *

      We agree that, to address this point, overexpression of an aspartate transporter would have been a good way to overcome poor aspartate uptake by MCF7 cells, however, at the time we initiated this study, SLC1A2 was not known as an aspartate transporter. We, therefore, cultured MCF7 cells for several weeks in media containing 0.5 mM aspartate (which is normally absent in our standard media formulation) because we expected that cells would adapt to take up more aspartate. We, thereby, obtained a derivative cell line that we called MCF7Asp. In new Figure S3G, we show that addition of 0.5 mM aspartate in the media of MCF7Asp cells largely prevented the decrease in intracellular aspartate seen in parental MCF7 cells after 3h in 1% O2. However, the increase in lactate was similar between MCF7 and MCF7Asp cells. These data are consistent with the idea that the low aspartate levels in hypoxia are not the likely cause for the increase in lactate.

      *Figure S3B-E - the authors suggest based on these data that aspartate decrease in hypoxia is through decreased glutamine contribution. Indeed they could also interrogate the data further, as the defect is observed in glutamate, perhaps suggesting that glutamine metabolism through glutaminase is altered. *

      To address the Reviewer’s point, in revised Figure S3, we have now replotted the data from the experiment in the original manuscript to show both absolute and fractional isotopologue abundances of TCA intermediates from cells labelled with 13C-glucose or 13C-glutamine. We have elaborated on these results in our response to point 1, and we re-iterate our conclusions here for the Reviewer’s convenience: Based on these re-plotted data, we find that the amounts of labelled intermediates from both labels decreases; the apparent decrease from glutamine appears greater than that from glucose, likely because glutamine labels more rapidly a greater fraction of TCA intermediates. Moreover, glutamate fractional labelling from glutamine decreases but modestly increases from glucose over time in hypoxia compared to normoxia. These data raise the possibility that TCA intermediates are diverted to glutamate synthesis. However, as we point out in the revised text, the fact that only glutamine has reached an isotopic steady state by 5h precludes us from making a more accurate quantitative statement and therefore we have refrained from further elaborating on these observations.

      *Figure S3D and E - the authors show data from 3 hours of labelling, which is not at steady-state (observable from the timecourse also shown in B and C). To be able to compare the glucose and glutamine labelling, a timepoint in which (pseudo)steady-state is achieved would be better chose. *

      In the revised manuscript, this concern is now addressed by showing both absolute and relative isotopologue abundances for all available time points. We agree that quantitative comparison of labelling must be done at steady-state conditions, however, as we also point out in the revised text (lines 180-181), only glutamine reaches isotopic steady state by 5h whereas glucose hasn’t.

      Additionally, within the aspartate isotopomers arising from glutamine, there is an odd m+1 for aspartate not observed in the other proximal metabolites. Is this a technical defect or is there a biological reason for the significant fractional amount in normoxia?

      We thank the reviewer for pointing this irregularity, which we should have clearly identified as such during proofreading of the manuscript. Probed by the reviewer’s comment, we reviewed the corresponding data tables used to plot these data and found that M+1 had exactly the same values as M+0. We then inspected the original data and confirmed that this resulted from an error during the copying of the data from the R-script output data table to GraphPad Prism for plotting (the line containing the replicates for the m+0 isotopologue was pasted again in the line of the M+1 isotopologues). This issue is now obsolete, as, in the revised manuscript Fig S3 new panels A-D, we have replaced the fractional data with detailed absolute and fractional labelling showing all isotopologues. We apologise for this error.

      • Figure S6F - all samples from GOT1 KO cells have less actin - could an appropriately loaded western blot be presented?*

      In the revised manuscript, we added a new panel with the Ponceau (27/02/2018) staining of the same membrane used for immunoblotting. This staining shows equal loading between all lanes. It is unclear why despite equal loading, the actin signal differs between the two lines.

      • In Figure S5B, the authors present ATP data in wild-type control cells, and LDHA-KO with LDHA re-expression. These should be phenotypically similar, but clearly are not. It suggests that there is something not correct with the system being used.*

      As shown in the western blot of this figure, expression of exogenous LDH only reaches a fraction of endogenous levels, which likely explains the partial, albeit significant, rescue of the ATP depletion observed in the LDHAko cells. We have not been able to achieve higher LDH expression in our cell preparations that would enable us to address this point further.

      *

      *

      Minor comments

        • PHDs need iron, alpha-ketoglutarate, oxygen and critically ascorbate (Introduction page 2)*

          We thank the reviewer for highlighting this critical omission. In the revised manuscript, we have now added this information (line 58).

      * PDK1 phosphorylation of PDH leads to a reduction in pyruvate oxidation, rather than entry of glucose carbons to the TCA cycle (Introduction page 3)*

      We agree with the reviewer that our wording was not accurate, and, in the revised text, we have re-written this part (lines 72-74): “…[PDK1] catalyses the inhibitory phosphorylation of pyruvate dehydrogenase (PDH), leading to attenuated pyruvate oxidation and, consequently, decreased contribution of glucose-derived carbons into the tricarboxylic acid (TCA) cycle.

      * SLC25A51 has been identified as being required for NAD transport into the mitochondria (Kori et al. Science Advances 2020), so it is incorrect to say that the inner mitochondrial membrane is impermeable to this metabolite (page 7)*

      We agree that, in light of the Kori et al. study, the phrasing in our text presented an outdated view of pyridine nucleotide compartmentalisation. The data in Kory et al. support SLC25A51 as a mitochondrial NAD+ transporter, however, it is not clear if NADH is also a substrate. Furthermore, as the authors also point out, SLC25A51 has a relatively low affinity for NAD+ and therefore unlikely to interfere with the functions of the malate-aspartate shuttle. Taking all this into consideration, in the revised text (line 249), we acknowledge the existence of a low-affinity mitochondrial NAD+ transporter and retained the statement about impermeability specifically for NADH.

      * Figure S6D - authors shows a highly significant increase in the mRNA for EGLN3, which is a HIF1 target gene, as well as encoding PHD3, which acts to hydroxylate HIF1a alongside PHD2. This should be commented on in the text.*

      In the revised discussion (lines 577-578), we acknowledge that increased PHD3 (together with increased oxygen availability, related to Reviewer 1’s comment), may additionally contribute to HIF1α destabilisation. Please note that we have also added new data (Figure S6H) in response to Reviewer 1, where we show that exogenous αKG causes HIF1α destabilisation in hypoxia, further supporting the notion that boosting intracellular αKG, alone, can destabilise HIF1α.

      * Figure S5G - could it be made clear on the graph whether this is at 21% or 1% O2?*

      We thank the reviewer for pointing out this omission. We now state clearly both in the revised corresponding legend (line 937) and revised figure that these data are at 1% O2.

      • Figure 5I shows ATP level against % labelling of alpha-GP. It isn't clear whether this is abundance or fractional label, but if the latter this it potentially misleading, as if the concentration of alpha-GP increases as fractional label decreases, there is effectively no change. Could the authors extract the steady-state data from the analysis and use this to calculate amount of m+3 label instead of fraction? Similarly for Figure S1H showing fractional labelling of lactate from glucose. It is likely that the title of this graph is a typo, and that m+3 instead was meant. Additionally, measurement of fractional labelling does not demonstrate increased concentrations of the metabolite, but the glucose carbons making up this isotopomer in the pool.*

      For Figure 5I, we confirm that what we show is based on abundance of α-GP m+3 labelling from glucose and, in the revised manuscript (line 895), we amended the legend to clarify this important point.

      We concede that the way we had originally written this sentence, suggested that we derived our conclusion that increased lactate in media was due to increased glycolysis based solely on the fractional data in Fig. S1H. In the revised manuscript, we have re-phrased the relevant sentence (lines 136-137) to indicate that our conclusion is based on the fractional data, together with the total lactate data that we show in Fig. 1F.

      For all our GC-MS experiments we used ions that we detected reliably in all our experiments – in the case of lactate this is m/z 117. This is a 2-carbon fragment as indicated in the original legend; the molecular formula of the derivatised fragment is shown in Table S2. In the revised manuscript (line 671) we clarify that this fragment contains carbons 2 and 3 of lactate (which we concluded from experiments where labelling with 3,4-13C-glucose (which labels lactate at C1) led to partial decrease in this isotopologue); therefore changes in 117 m+2 indicate changes in glycolysis rather glycolysis and the PPP.

      * Figure S2G - the purpose of the measurement of cysteine is unclear; measurement of NAC directly within cells would be a clearer demonstration of its uptake, and to demonstrate direct contribution to antioxidant response would instead require measurement of cellular antioxidants rather than cysteine itself.*

      We agree with the reviewer’s comment that, ideally, we would have measured antioxidants, however, unfortunately our GC-MS experiments do not detect glutathione; we, therefore, opted to show cysteine as the best available proof that NAC was added to these cells from the same experiments where we measured aspartate and lactate.

      * There is no Figure S3F (page 6 of text)*

      In the original version of our manuscript we had awkwardly placed Figure S3F at the top right side of the figure due to space limitations, so, understandably, the reviewer may have missed it. In the revised manuscript, we have now moved this panel to the main Figure 3E, to also address the reviewer’s point 5, above (presentation of lactate data).

      * Figure 2E, lactate excretion into the media is presenting an odd profile, suggesting that between 3 and 6 hour there is uptake by cells. Equally, the 24 hour timepoint is being presented as p

      The overlap of the error bars arises from error propagation as we report the values at each time point relative to t=0h. The statistical difference we reported was calculated on the original values at 24 h alone, so to avoid this discrepancy we have opted for removing the results of this statistical test altogether.

      *

      Reviewer #2 (Significance (Required)):*

      * The data throughout this paper provide some strong evidence for an early and likely HIF-independent metabolic response - while this is understood, detailed studies have not been performed into the various redox balancing cytosolic pathways, which are presented here. The focus on GOT1 is also interesting and novel, but represents part of a larger overall picture presented, which is not reflected in the title.*

      * This is suitable for a relatively broad audience, as the phenotype is likely not cancer specific.

      *__Reviewer #3 (Evidence, reproducibility and clarity (Required)): __

      * Here, Grimm and colleagues investigate the immediate cellular response to hypoxia, prior to onset of HIF1a stabilization/activity. Consistent with established findings they describe that glycolysis is rapidly upregulated under hypoxia, in a HIF1 alpha independent manner, this correlates with an decreased aspartate levels. From this basis, they describe a key role for GOT1 activity in regulating the early hypoxic response, demonstrating its requirement for glycolysis, maintaining the NAD/NADH balance and - in combination with LDHA - maintaining ATP homeostasis in hypoxia. Finally they describe a role for GOT1 (though alpha KG depletion) in contributing to HIF1 alpha stabilization.*

      * In sum, the authors present a compelling study investigating the mechanistic basis of early response to hypoxia, placing GOT1 as a key metabolic regulator of this response. The question of how cell metabolically adapt in the short term to hypoxia is, in my view, an often overlooked area of investigation but clearly has importance across biology, not least in cancer biology - thus the area of investigation is topical. The authors conclusions are supported by their data, often in multiple cell lines and/or through orthologous methods. I would support publication of this study as is.*

      * Reviewer #3 (Significance (Required)):*

      * Significance is stated in my review above, an understudied area of investigation (early hypoxic responses) but clearly important since without a transient response, the long-term impact of HIF1 stress responses would not be possible*

      We thank the reviewer for their time assessing our manuscript and for their positive feedback.

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      Referee #3

      Evidence, reproducibility and clarity

      Here, Grimm and colleagues investigate the immediate cellular response to hypoxia, prior to onset of HIF1 stabilization/activity. Consistent with established findings they describe that glycolysis is rapidly upregulated under hypoxia, in a HIF1 alpha independent manner, this correlates with an decreased aspartate levels. From this basis, they describe a key role for GOT1 activity in regulating the early hypoxic response, demonstrating its requirement for glycolysis, maintaining the NAD/NADH balance and - in combination with LDHA - maintaining ATP homeostasis in hypoxia. Finally they describe a role for GOT1 (though alpha KG depletion) in contributing to HIF1 alpha stabilization.

      In sum, the authors present a compelling study investigating the mechanistic basis of early response to hypoxia, placing GOT1 as a key metabolic regulator of this response. The question of how cell metabolically adapt in the short term to hypoxia is, in my view, an often overlooked area of investigation but clearly has importance across biology, not least in cancer biology - thus the area of investigation is topical. The authors conclusions are supported by their data, often in multiple cell lines and/or through orthologous methods. I would support publication of this study as is.

      Significance

      Significance is stated in my review above, an understudied area of investigation (early hypoxic responses) but clearly important since without a transient response, the long-term impact of HIF1 stress responses would not be possible

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      Referee #2

      Evidence, reproducibility and clarity

      Summary

      This manuscript represents an interesting and novel description of the role of a cytosolic transaminase, glutamic-oxaloacetate transaminase 1 (GOT1) on both cytosolic redox (and therefore glycolysis through its functional linkage with malate dehydrogenase 1) and the availability of alpha-ketoglutarate for stabilisation of HIF1a in hypoxia. Some of the most interesting data are the evidence for increased cytosolic NAD+ regeneration through the combined action of LDHA (known) and GPD1 (less well-described increase in activity in hypoxia). The manuscript as a whole describes the multiple systems required for the early response to hypoxia, but the focus of the title and way the article is written do not entirely reflect this. For example, the title focuses on GOT1 as the enzymes whose activity is responsible for the early response to hypoxia. However, this is not reflected in some of the data - the deuteron labelling in particular - which shows that LDH and GPD1 are responsible for the biggest redox activity (i.e. support of glycolysis). A degree of reframing of the article may therefore be of benefit.

      Major comments

      1. In Figure 1 C and D, the data suggest significant changes in the decrease in cellular aspartate between 1-2 hours, which then slow. This is followed by a change in lactate concentrations from 2 hours onwards, which is observed in the cells (D) and media (F). The rapid decrease in aspartate concentration suggests a relatively large change, which does not correspond to the later lack of alteration in deuteron labelling from d4-glucose (Figure 4H-J) in m+1 malate. This therefore suggests that the biggest determinant of decreased aspartate is not coupled to MDH1 activity directly. If the manuscript is focused on the relevance of GOT1 activity to the early hypoxic response, this should be better resolved. Given that this could undermine the strength of the case being made for GOT1 activity playing a significant role (through MDH1), could the authors perform the same experiments but in the GOT1KO cells to show how NADH is handled under these conditions by LDHA and GPD1? If the focus of the manuscript is shifted, these experiments would likely not be necessary.
      2. The authors present data in Figure 1 and 3 using 2DG as a surrogate for glucose uptake. 2DG has been previously shown not to always be a surrogate for glucose uptake (Sinclair et al. Immunometabolism 2020). Given that this paper highlighted warns in particular about assuming SLC2A1 and SLC2A3 activities based on 2DG uptake, and that these two transporters are the major glucose transporters regulated by hypoxia, a cautious approach to these data is recommended. Assuming that 2DG uptake is a surrogate for glucose in this system (panel C), the effect of GOT1 appears to be at the level of glucose uptake even at 3 hours - it has been marked as being significant by the authors. This suggests that loss of GOT1 has an effect on glucose uptake prior to any transcriptional response is observed. Is the plasma membrane occupancy by the SLC2A1 or SLC2A3 been reduced after GOT1 KO? The same is true for Figure 1 - as intracellular aspartate and lactate and extracellular lactate is shown, could change in extracellular glucose not be presented as a direct measure?
      3. The data shown in Figure 2D suggests that there is little change in overall contribution to citrate from glucose in hypoxia compared to normoxia, and that HIF1 is does not play a role in the hypoxic response at this point. However, the data presented are overall fractional labelling, and therefore do not focus on the main hypoxia-dependent point of control highlighted before this by the authors - pyruvate oxidation through PDH. Could the authors consider plotting m+2 isotopomer of citrate either alongside or instead of the total fractional label (which includes hypoxia-independent PC activity and cycling carbons). Additionally, the experimental set-up means that average incorporation over the time shown is represented - i.e. the 3h timepoint is incorporation over the first two hours, while the 24 hour timepoint is averaged over the whole period. It is therefore likely under-representing the decrease in glucose contribution to citrate at 24 hours - the authors could point this out, or OPTIONALLY perform a more time-resolved experiment where flux over shorter periods is assessed for each of the timepoints (i.e. 0-1, 2-3, 5-6, 23-24).
      4. Figure 3 data are key for the GOT1 theme of the manuscript, as the authors show that loss of GOT1 increases cellular aspartate in both normoxia and hypoxia - suggesting that GOT1 is an aspartate-consuming enzyme in both conditions. Indeed the magnitude of the change in aspartate after GOT1 knockdown appears similar in both conditions (Panel B). These are interesting data, as they contrast with a recently published study (Altea-Manzano et al. Molecular Cell 2022) suggesting that in respiration-deficient cells (a condition with parallels with hypoxia), GOT1 activity may be aspartate producing to supply aspartate to the mitochondria for GOT2. It would be important for the authors to discuss the differences between studies.
      5. Panel E shows data at 5 hours, while the rest of the panels here are a mix of 1 and 3h timepoints. Equally panel E also presents concentration, while D presents relative abundance of lactate - could a consistent approach to presenting the results be taken?
      6. In Figure S3, the authors show the lack of direct aspartate uptake, or supplementation through the use of an esterified form. OPTIONAL: they could consider using the expression of SLC1A3 (Tajan et al. Cell Metabolism 2018; Hart et al eLife 2023) to increase aspartate uptake in order to test their hypothesis. Figure S3B-E - the authors suggest based on these data that aspartate decrease in hypoxia is through decreased glutamine contribution. Indeed they could also interrogate the data further, as the defect is observed in glutamate, perhaps suggesting that glutamine metabolism through glutaminase is altered. Figure S3D and E - the authors show data from 3 hours of labelling, which is not at steady-state (observable from the timecourse also shown in B and C). To be able to compare the glucose and glutamine labelling, a timepoint in which (pseudo)steady-state is achieved would be better chose. Additionally, within the aspartate isotopomers arising from glutamine, there is an odd m+1 for aspartate not observed in the other proximal metabolites. Is this a technical defect or is there a biological reason for the significant fractional amount in normoxia?
      7. Figure S6F - all samples from GOT1 KO cells have less actin - could an appropriately loaded western blot be presented?
      8. In Figure S5B, the authors present ATP data in wild-type control cells, and LDHA-KO with LDHA re-expression. These should be phenotypically similar, but clearly are not. It suggests that there is something not correct with the system being used.

      Minor comments

      1. PHDs need iron, alpha-ketoglutarate, oxygen and critically ascorbate (Introduction page 2)
      2. PDK1 phosphorylation of PDH leads to a reduction in pyruvate oxidation, rather than entry of glucose carbons to the TCA cycle (Introduction page 3)
      3. SLC25A51 has been identified as being required for NAD transport into the mitochondria (Kori et al. Science Advances 2020), so it is incorrect to say that the inner mitochondrial membrane is impermeable to this metabolite (page 7)
      4. Figure S6D - authors shows a highly significant increase in the mRNA for EGLN3, which is a HIF1 target gene, as well as encoding PHD3, which acts to hydroxylate HIF1a alongside PHD2. This should be commented on in the text.
      5. Figure S5G - could it be made clear on the graph whether this is at 21% or 1% O2?
      6. Figure 5I shows ATP level against % labelling of alpha-GP. It isn't clear whether this is abundance or fractional label, but if the latter this it potentially misleading, as if the concentration of alpha-GP increases as fractional label decreases, there is effectively no change. Could the authors extract the steady-state data from the analysis and use this to calculate amount of m+3 label instead of fraction? Similarly for Figure S1H showing fractional labelling of lactate from glucose. It is likely that the title of this graph is a typo, and that m+3 instead was meant. Additionally, measurement of fractional labelling does not demonstrate increased concentrations of the metabolite, but the glucose carbons making up this isotopomer in the pool.
      7. Figure S2G - the purpose of the measurement of cysteine is unclear; measurement of NAC directly within cells would be a clearer demonstration of its uptake, and to demonstrate direct contribution to antioxidant response would instead require measurement of cellular antioxidants rather than cysteine itself.
      8. There is no Figure S3F (page 6 of text)
      9. Figure 2E, lactate excretion into the media is presenting an odd profile, suggesting that between 3 and 6 hour there is uptake by cells. Equally, the 24 hour timepoint is being presented as p<0.01 for 4 replicates with error bars that cross the mean of one of the values. Could the authors possibly check that this is indeed the case?

      Significance

      The data throughout this paper provide some strong evidence for an early and likely HIF-independent metabolic response - while this is understood, detailed studies have not been performed into the various redox balancing cytosolic pathways, which are presented here. The focus on GOT1 is also interesting and novel, but represents part of a larger overall picture presented, which is not reflected in the title.

      This is suitable for a relatively broad audience, as the phenotype is likely not cancer specific.

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      Referee #1

      Evidence, reproducibility and clarity

      In the paper entitled GOT1 primes the cellular response to hypoxia by supporting glycolysis and HIF1α stabilization, Grimm and co-authors investigate the metabolic adaptations of cancer cells upon acute hypoxia. By measuring metabolite levels at early time points upon hypoxia, they observe the accumulation of lactate and depletion of aspartate, along with other TCA cycle metabolites. Importantly, they demonstrate that these metabolic changes are independent of the HIF alpha-dependent transcriptional response. The authors investigate the role of aspartate during these initial phases of hypoxia. To this aim, they characterize cells devoid of glutamate oxaloacetate transaminase (GOT1), in which aspartate accumulates and can no longer be used for replenishing NAD+ via the downstream conversion of oxaloacetate to malate, via malate dehydrogenase. These cells have lower cytosolic NAD+ which affects glycolytic flux through the rate-limiting, NAD+-dependent enzyme GAPDH. GOT1 KO cells have a decrease in glucose consumption, lactate secretion and metabolite levels downstream of GAPDH upon early hypoxia, however ATP levels and viability are only affected with additional lactate dehydrogenase (LDH) impairment. Finally, the authors demonstrate that GOT1 KO cells have higher alpha-ketoglutarate (aKG) levels during early hypoxia, which could contribute to higher prolyl-hydroxylation and subsequent degradation of HIF, regulating the transcriptional response mediated by transcription factor.

      Major comments

      1. The authors claim that they were unable to supplement cells with aspartate (Figure S3), (even though an increase of aspartate is instead observed in cells treated with sodium aspartate) and had to resort to the GOT1 knock-out model to "prevent aspartate from decreasing in hypoxia". This approach implicitly assumes that Got1 is the main driver of aspartate depletion upon hypoxia. However, although steady-state levels of aspartate are indeed higher in these cells, there is still a strong decrease upon hypoxia, which the authors acknowledge but merely ascribe to "attenuated production from glutamine". This seems an insufficient explanation, considering the very fast depletion upon hypoxia originally observed. The authors should provide further information regarding why aspartate is depleted in these conditions and consider other aspartate-consuming enzymes such as GOT2, ASNS, or even nucleotide biosynthesis and urea cycle enzymes. These observations could be made using the labeling experiments already acquired. In addition, to corroborate their hypothesis, the authors could supplement 13 C-aspartate at a supraphysiological concentration (i.e. 5-10 mM) to determine to what extent it is consumed by GOT1 or other pathways.
      2. In line with the previous comment, the conclusion that "GOT1 activity, rather than a decrease in aspartate concentration itself, is required to sustain the increase in glycolysis in early hypoxia." seems questionable, especially considering the failed aspartate supplementation. The authors suspect low expression of plasma membrane aspartate transporters as the reason and quote Garcia-Bermudez et al.2018 (PMID: 29941933). This paper contains ranked SLC1A2 mRNA expression data from the Cancer Cell Line Encyclopedia (CCLE). The authors may apply aspartate supplementation and "early hypoxia" to a cancer cell line expressing SLC1A2 or other aspartate transporters. Alternatively, they could try introducing the transporter by overexpression.
      3. The observation that labelled m+1 malate produced from [4-2H]-glucose is similar in normoxia and hypoxia (Figure 4G), does not support the notion that GOT1-MDH axis is increased at low oxygen and seems to suggest that the depletion of aspartate observed in early hypoxia is unrelated to this axis. The authors should resolve this discrepancy.
      4. The alpha-KG level regulation by Got1 and the subsequent HIF1alpha "priming" seem quite promising and likely the most novel part of the manuscript. However, further proof should be added to support this strong claim. First, aKG to succinate ratio, rather than aKG alone, is a better indicator of aKG-dependent dioxygenases activity. So. the authors should provide this measurement. Second, the authors should rule out the possibility that the differential hydroxylation of HIF is due to the redistribution of intracellular oxygen due to alterations in mitochondrial function. To do this, they could determine whether cytosolic oxygen levels differ in the two conditions. Finally, the authors could test whether α-ketoglutarate or 2-hydroxyglutarate supplementation affects HIF stability in their experimental conditions.

      Minor comments:

      • The glycerol-3-phosphate shuttle is another means of re-oxidizing NADH and α-GP is indeed higher in GOT1 KO. According to this, in Fig 5C a clear increase in a-GP is observed in LDH KO cells. Would the phenotype be stronger upon additional GPD1 knockout or inhibition?
      • Aspartate and lactate levels appear unchanged in MDA-MB231 upon hypoxia. Can these changes be ascribed to a pseudohypoxic state? The authors should comment on this observation.
      • Figure S3B: The authors do not provide information on the length of hypoxia for these experiments.
      • Glucose and glutamine isotopic labelling should be accompanied by graphs showing the total pool levels of these metabolites, and also the uptake of glucose and glutamine (and their specific isotopologue distribution). It would be important to show the isotopologue distribution of aKG in all the conditions tested, in particular, because of its proposed regulation by Got1.
      • Malate generated by MDH1 can be converted by ME1 into Pyruvate, which could be further processed by LDH. Have the authors measured this conversion in their dataset.
      • Aspartate absolute levels across cell lines appear different. Is this due to differences in cell volume? Can the authors comment on this observation?
      • Under hypoxia the contribution of glutamine (labelled fraction, Fig. S3) to TCA cycle intermediates decreases. However, this is not paralleled by an increase in the contribution of glucose, as also supported by an increase in the m+0 in the glutamine labeling but not in the glucose one. How do the authors explain this apparent inconsistency? Are there sources of unlabelled TCA cycle during the hypoxic experiment?

      Referees cross-commenting

      Referee 2 raises important questions that are in part aligned with referee 1 and are reasonable and doable is the time frame proposed. These are all important questions and comments to consolidate the central hypothesis of the work and I believe are required for publication.

      Significance

      Overall, this is an exciting and well-executed piece of work focusing on the early biochemical consequences of hypoxia that the wide metabolism/biochemistry audience will appreciate. While most of these observations are not entirely unexpected, the work brings a sufficiently novel perspective and insights to the field and deserves publication. However, some conclusions are not fully supported by the data and some additional experiments are suggested to bring clarification and strengthen the authors' conclusions.

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