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Referee #1

Evidence, reproducibility and clarity

Summary:

This manuscript by Lan et al. addresses the still incompletely resolved question as to how branching morphogenesis of the embryonic mammary epithelium is regulated at the molecular and cellular level. Using (combinatorial) primary explant cultures of wildtype and genetically engineered mouse embryos, in which the authors have developed a unique expertise over many years, together with imaging and RNAseq analyses, they (i) show that the timing of epithelial branching is dictated by the biological age of the epithelium, but that an epithelial-mesenchymal interaction is required to bestow branching ability on the mammary epithelium somewhere between E13.5 and E16.5, (ii) seek to determine if and how lineage and cell proliferation affect branching, (iii) show that while salivary mesenchyme can promote growth (i.e. branching density) of the E16.5 mammary epithelium, the mode of branching (i.e. lateral branching vs tip-clefting) is an intrinsic property of the mammary epithelium, (iv) use transcriptomics to identify genes that are likely to control either mammary- or salivary gland specific growth and/or branching patterns, (v) hypothesize that low levels of WNT signaling in the mammary gland mesenchyme (due to relatively high expression of WNT signaling inhibitors) are responsible for mammary specific branching, (vi) show that hyperactivation of WNT/CTNNB1 signaling in the mesenchyme indeed induces hyperbranching, (vii) identify Eda and Igf1 as putative mediators and paracrine signaling factors that regulate branching of the mammary epithelium upon secretion from the mesenchyme downstream of WNT/CTNNB1 signaling and (viii) show that mammary gland branching is impaired in Igfr1 null embryos.

Major comments:

1. Overall, this is a solid study that is well controlled and technically of high quality. The materials and methods should allow follow up and replication by others and the transcriptomic data have been made available via NCBI GEO. I think the authors convincingly demonstrate points (i), (iii), (iv) and (vi) and (viii). I have some questions regarding (ii), (v) and (vii) and (viii) that I will pose below.
2. Re: (ii): The authors try to study the link between basal cell fate and branching. They use position of the cells (which they describe clearly and which is a good choice), since they cannot use specific markers due to the fact that the basal and luminal linages have not yet segregated at this point. This part of the manuscript is not the most straightforward to follow. The most obvious experiment would have been to focus on the location of the cells and their associated cell cycle profile - but the authors themselves have just recently published a pre-print (their REF #54, now also out in JCB) that is an in-depth study of the link between cell proliferation + cell motility and branching, but this only becomes apparent in the discussion. In that sense, Fig2 of the current manuscript is less novel, although it is nice to see that it holds up in a slightly different analysis. Instead of focusing on the cell cycle markers, the authors turn to a K14-Eda mouse model - which shows precocious branching and a temporary reduction in K8 expression. They also analyze Eda-KO embryos. Quite frankly, I find the authors' reasoning difficult to follow here and I cannot deduce how these experiments really address the question at hand (i.e. how lineage and cell proliferation affect branching), so I hope they can rewrite this section of the paper to make the arguments more clear and easy to follow for the reader who, at this point, knows little about Eda. For example, the authors present the argument that K14-Eda mice show a transient reduction in K8 expression - but we don't know if that also really means a (temporary?) change in (future?) luminal cell fate. In fact, since Eda later also makes an appearance as a candidate factor to be secreted by the mesenchyme together with Igf1, I wonder if their K14-Eda data would not be better suited to underscore that point instead and if the authors should perhaps eliminate this section altogether and just refer to their prior work in REF #45. If the authors think the current data add something more, than they need to be more explicit about this (and then also introduce the link to REF #45 in the results section).
3. Re: (v): Do the authors have any WNT/CTNNB1 target genes that they can include in their transcriptomics analysis to show that the WNT/CTNNB1 signaling levels are indeed lower in the mammary mesenchyme? Axin2 comes to mind, but there are some other negative feedback targets that are often induced across tissues, e.g. Rnf43 and/or Znrf3 and/or Sp5?E.g. to include in FIg6E?
4. Re: (vii) and (viii): The authors convincingly show the phenotype of the Igfr1 KO mice, but I hope the authors concur that an epithelial only Igfr1 KO (or alternatively a mesenchymal only Igf1 KO, or epithelial/mesenchymal recombination experiments with WT vs IGFR1 null or IGF1 null tissue, or experiments with small molecule inhibitors of IGF1/IGFR1 signaling) would have given more solid mechanistic evidence regarding the presumed paracrine effect of IGF1 signaling. I am not asking the authors to perform another mouse experiment or even generate or use these conditional strains, but if the authors agree, then I do think this would merit some attention in the discussion section. See also my comments regarding Eda in point 1.

Minor comments:

• A few minor spelling/grammar errors, including a couple of "the"s missing (first line of the abstract, and also preceding "Majority" in line 148.
• Line 517-518: please also include the details for the Eda mice.
• 1f spelling error: separation

Referees cross-commenting

Having read all three review reports I think they are pretty much in agreement, with shared questions about the inclusion/meaning/discussion of the lineage specification data and also agreement about the overall technical solidity of the data and this approach.

I gather that reviewer #2 asks for more controls than myself or reviewer #3 and while I think all of their points are valid, in principle, I don't think all of these are required. I should add that I am inclined to trust the authors on their ability to separate mesenchyme and epithelium as they have been developing and optimising this system over many years.

Significance

General assessment:

This is a carefully executed study in which an impressive amount of (combinatorial) embryonic mammary tissue explant experiments are combined with quantitative imaging and transcriptomics analysis.

The main limitations of the work lie in the fact that the investigation of a potential link between branching and the cell cycle is not entirely novel, as the authors themselves recently published an nice pre-print (now also out in JCB) describing similar analyses. In addition, the mechanistic link between WNT/CTNNB1 signaling in the mesenchyme and the paracrine signaling activities of the presumed downstream effectors EDA and IGF, while plausible, is not yet complete. The work also does not yet addresses what exactly the branching identity is that is bestowed upon the mammary epithelium between E13.5 and E16.5 and how this then becomes an intrinsic (epigenetic?) feature of the mammary gland.

Advance:

This work provides more insight into the embryonic branching of the mammary gland - a stage of mammary gland development that is still poorly understood and that is, in general, understudied. In part, the work confirms prior work in the literature (their REF #19) regarding mammary and salivary gland tissue recombination experiments. It supplements this with a more elaborate time series of heterochronic and heterologous epithelium/mesenchyme explant cultures, using genetically engineered (and fluorescently labeled) mouse tissues to allow better and quantitative imaging. The transcriptomic analysis of different mesenchyme populations is also informative and allows the researchers to propose a putative mechanism for why the mammary gland branches differently from the salivary gland. The advance is both technical and functional, as well as conceptual, with some advance in terms of mechanism.

Audience: This works should appeal to mammary gland biologists interested in the molecular and cellular mechanisms of (early) mammary gland development, as well as to a broader community of developmental biologists studying branching morphogenesis in tissues such as lung, kidney and salivary gland.

My expertise:

WNT signaling and mammary gland biology, at the intersection of developmental, stem cell and cancer 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

Summary:

In this study, Hwang et al. develop an inducible Cas9 hiPSC line and perform with it a pooled CRISPR knockout screen using a custom sgRNA library to identify novel genes involved in human primordial germ cell like cell (hPGCLC) differentiation in vitro. Thereby they find the AKT coactivator TCL1A to be important in the proliferation/survival of hPGCLCs after specification.

Specific Comments:

1.) p.7-p.8: "Using the MAGeCK algorithm (Li et al, 2014) to call hits on merged replicates, 25 genes scored as significantly depleted from the AG+ population at p < 0.05. Among the top hits was SOX17, and near-hits included TFAP2C, both of which are well-known drivers of the hPGCLC state (Fig. S2E)."

When looking at Table S3, it appears that only 2 genes were significantly depleted (P < 0.05) in replicate 1, 23 in replicate 2 and 10 genes when rep 1 and rep 2 were analyzed together. The essential germ cell genes SOX17 and TFAP2C were not significantly depleted in replicate 1 and only TFAP2C but not SOX17 was depleted significantly in replicate 2. Also the main hits discussed in this paper, METTL7 and TCL1A were not significantly depleted in replicate 1 and only METTL7 but not TCL1A was significantly depleted in replicate 2. This indicates that replicate 1 might not have been robust enough to reliably detect depleted genes and that TCL1A was not among the significant hits. A potential explanation could be that not enough cells have been used to ensure a sufficient representation of sgRNAs to provide significant results in a depletion screen. Ideally the screen would need to be repeated to provide another informative replicate, or the authors should at least correct the sentences above and openly state that their hits are only based on one replicate of the screen and that the list of their hits might therefore not be fully reliable. Also the statement on page 8 that "the screen was both technically and biologically successful" might need to be toned down.

2.) p.8 and Fig. 2E: The authors do not clearly describe, what are the 25 top hits in PGCLC(+) and PGCLC(-) cells and how they were chosen (Score, p-value or fold change), which they compared in the gene set enrichment analysis to the RNA-Seq data.

3.) Fig. S3I-K: The authors mention in the text on p. 9 a significant reduction in hPGCLC induction efficiency for both TCL1A and METTL7A KO cells, but they do not provide statistics and do not mention, how many biological replicates have been used. As hiPSCs generally show a high clone to clone variability in hPGCLC induction efficiency, results from a single KO clone can not be considered as a reliable result. The authors should provide results from additional wt and KO clones (they are showing in S3E multiple for each gene) to ensure reliable effects, especially for METTL7A KO cells, where the reduction in PGCLC induction efficiency is more modest and might not be significant (Fig. S3I). Another way of validating the phenotype would be to use individual control, TCL1A and METTL7A sgRNAS from the screen and compare induction efficiencies with or without DOX-induced Cas9 expression.

4.) Fig. 3F, Supp Tables S4, S5, S6: It is not clearly described, what was the criteria to define DEGs for the GO term analysis of TCL1A KO cells, as more genes have been used than the relatively few significant DEGs reported in Table S4. Furthermore, only FDRs or otherwise adjusted p-values (not raw p-values as done in the figure and tables) should be used to determine significantly enriched GO terms. Also no representative gene names are displayed in Fig.3F, as stated in the figure legend.

5.) Fig.4: p-AKT and p-mTOR signaling are represented as the mechanism, by which TCLA1 KO affects hPGCLC maintenance/proliferation. It is not clear from the presented data, what is meant with biological triplicates (different germ cell inductions, different subclones) mentioned in the figure legend. As some of the effects observed are quite small (e.g. p-mTOR differences in 4E, cell cycle differences in 4J), biological replicates with a different KO clone should be performed (see point 3). Otherwise it is hard to judge how robust the data and conclusions derived are.

CROSS-CONSULTATION COMMENTS

Apart from my points regarding the weakness in statistical confidence I agree with the other reviewers that it needs to be shown whether the effect of TCL1A KO is based on a general proliferation defect of the entire aggregation body or if the effect is really hPGCLC-specific.

Significance

The study is the first CRISPR screen performed during hPGCLC differentiation and provides a proof of principle for a useful tool to allow dissection of gene regulatory networks during human germ cell development. Overall this is a technical advancement and an ambitious study and will generate interest in the human germ cell field. Generally it is easy to follow but could be improved in the description of some of the methodology (points 2+4). Overall the study suffers from weaknesses in the statistical robustness, as the screen itself did not provide many significant hits (major point 1) and the follow up was only performed using a single KO clone (points 3+5). Therefore adding replicates would be necessary to strengthen the confidence in the drawn conclusions.

Reviewers' relevant expertise: in vitro germ cell differentiation, pluripotency, CRISPR screening

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Referee #2

Evidence, reproducibility and clarity

The authors conducted a custom CRISPR screening including 422 coding-genes in hPGC-like cells (hPGCLCs) to identify genes important to hPGCLC. Based on the screen, they found two candidates, TCL1A and METTL7A, that regulate hPGCLC specification. They concluded that TCL1A, an AKT coactivator, is critical for hPGCLC specification through regulating AKT-mTOR signaling. Unfortunately, we found that the evidences for the key conclusions are not quite convincing. Reasons are as below:

1. The results to demonstrate the key role of TCL1A on hPGCLC specification is not convincing. Fig. 3B, C & D. the cell number per aggregate is also significantly reduced in TCL1A KO (2843/20.7% =13734) compared to that in WT cells (545/16.4%=3323). Despite that, the percentage of AG+ cells per aggregate is significantly, but not dramatically decreased in TCL1A KO (20.7%) vs WT (16.4%) cells. Thus, the effect of TCL1A KO may not be specific on the AG+ cells, but on the whole aggregate.
2. The overall effect of METTL7A KO on hPGCLC development is too moderate to conclude it as a key regulator for hPGCLC specification.

Significance

a CRISPR screening for key regulator for human germline cell apecification was not reported before.

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Referee #1

Evidence, reproducibility and clarity

In this manuscript, the authors performed CRISPR/Cas9-based screening to identify genes involved in human germ cell development. Using human PGCLC system, the authors found that sgRNAs targeting TCL1A and METTL7A genes were enriched in non-PGCLC population. Gene-disruption of each gene resulted in a significant reduction in PGCLC differentiation. Moreover, TCL1A-knockout PGCLCs failed to proliferation during PGCLC induction, possibly due to attenuation of AKT signaling. Further analyses showed that protein synthesis and cell-cycle progression, especially in S-phase, were impaired in TCL1A-knockout PGCLCs. Thus, the authors provided remarks on successful identification of genes functionally important for human PGCLC differentiation and the importance of translational control in human germ line.

This manuscript demonstrates a genetic screening for genes involved in hPGCLC differentiation. Although the number of genes targeted by sgRNAs were limited (422 genes), it is still valuable to show such genetic screening can be applied to the hPGCLC system. Overall, statements and data in the manuscript are convincing, except for following points, and the novelty is sufficient for publication. It would be further improved, considering following points with additional experiment, if feasible.

1. A major concern in this manuscript is whether TCL1A function is specifically involved in hPGC development or generally important for other cell type. As AKT signaling plays multiple roles on many cell contexts, this is important to verify the author's conclusion. For example, is there any defect in proliferation of TCL1A-knockout iPS lines? The authors should quantify the doubling rate of TCL1A-knockout iPS cells, the number of iMeLCs yielded, and the cell number included in the aggregates. Looking at Figure S3K and K, the total number of the cells in the aggregates seems lower in TCL1A-knockout aggregates than in WT.

2. Related to the comment above, the author should add a statement describing expression pattern and level of TCL1A and METTL7A in tissue. Are they preferentially expressed in the germ line, or generally expressed in a broad range of tissue?

3. The quantification of pAKT and p-mTOR is vague. The authors should quantify in a different way. Although the author claimed that Western blot analysis was not able to detect pAKT and p-mTOR in PGCLCs, there are a number of reports that detect these proteins. As an advantage of PGCLC system is to handle a large number of cells in culture, the authors should perform rigorously the quantification.

4. In the abstract, there is a statement "demonstrate the importance of translational control in human reproduction". Isn't this too general? Is it a new finding? With critical examination for cell-specificity of the translational control by TCL1A as described above, this should be refined.

Significance

As authors performed CRISPR/Cas9-based screening to identify genes involved in human germ cell development using human PGCLC system, and then successfully isolated TCL1A and METTL7A genes that are previously known as drives for PGCLC induction. Therefore, from both technological and scientific viewpoints, there is a significant advance shown in this manuscript.

Transparent Peer Review

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Reply to the reviewers

Response to Reviewer comments

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

__Summary __

The manuscript by Parker et al addresses the important question of how different organisms have evolved pre-messenger RNA systems that are either more or less complex. This question underlies the evolution of complex organisms and the genome adaptation of simple organisms to their specific environments, so is an important question to answer. This manuscript now provides the underlying molecular mechanisms of how 5' splice site sequence preference may have evolved which is both an interesting and exciting advance for the field. 

We thank the reviewer for these kind comments.

__Major comments __

__This manuscript builds on the previous work from this group where they identified the role of adenosine N6 methylation (m6A) of the U6 small nuclear RNA (snRNA) of the spliceosome by METTL16 as being important for 5' splice site selection. This work led to the speculation that loss of a METTL16 ortholog, or potentially other splicing factors, in some species could contribute to an evolutionary change in 5' splice site sequence preference. Here the authors now use the power of phylogenetics, interspecies association mapping and the available spliceosome structures to provide convincing conclusions that 5' splice site sequence preferences in the extensive number of organisms examined correlate with the presence of the U6 snRNA methyltransferase METTL16 and the splicing factor SNRNP27K. __

__An analysis of METTL16 conservation was first carried out by comparing the METTL16 methyltransferase domain (MTD) in 29 diverse eukaryotic species. All the METTL16 orthologs were found to have either one or two globular domains. Three domain types were identified and compared in detail. What was not clear from this analysis was the functional significance of orthologs having either one or two domains. __

We identified several species, including Drosophila melanogaster, whose METTL16 orthologs do not contain a VCR domain. However, in this study we do not draw specific conclusions about the functional significance of orthologs having different domain topologies.

__In addition, while this analysis provides important new information on the domain structure of METTL16 orthologs, especially where these domains had not been identified previously, the link between this section of the results and the following sections is not that apparent. __

We agree that there is a significant difference in approach between the first section of the Results and the following sections. However, we are keen to keep this part of the manuscript because it provides an orthogonal line of evidence suggesting that the ancestral role of METTL16 in eukaryotes is specifically the methylation of U6 snRNA.

__Next novel bioinformatics pipelines were developed to compare both introns and orthologous groupings of protein coding genes between 227 Sacchromycotina genomes as well as 13 well-annotated eukaryote genomes. First, the 5' splice site sequence preference was compared and clearly indicates that the +4 position has the greatest variation in preferences within the Sacchromycotina. The ability to now compare a large number of genomes has provided novel information on the evolution of the 5' splice site sequence and the conclusion that there is more complexity to the 5' splice site in fungi that previously recognized. While it is apparent why only the 5' splice site signal was investigated here, with its relationship to the U6 snRNA and METTL16, it seems a shame the other splice site sequences were not analyzed using this novel pipeline. In any case, the complexity of the 5' splice site +4 position now allows, for the first time, interesting interspecies association studies. __

We have now included the variance plots for 3’SS motifs (analogous to the 5’SS variance plots shown in Figure 2B) as Figure 2 supplementary figure 4A, and a traitgram for 3’SS -3C to U ratio as Figure 2 supplementary figure 4B. We have included a short section of text in the Results section to describe these additional findings.

__With ____the 5' splice site +4 variation identified, the next step was to determine the underlying molecular mechanisms that dictate the evolution of the various sequence preferences. Some obvious players here are the U1 and U6 snRNAs which directly interact with the 5' splice site during splicing. However, no association was found between these snRNAs and the 5' splice site +4 sequence. __

__The powerful interspecies association mapping was then used to determine whether the presence or absence of METTL16 ortholog or a splicing factor correlated with the 5' splice site +4 sequence variation. Interestingly, a clear association was found between METTL16 and the 5' splice site +4 position; METTL16 presence was associated with +4A at the 5' splice site and METTL16 absence was associated with +4U at the 5' splice site. This is an exciting and significant finding. __

We thank the reviewer for these comments on the importance of this study.

__Interestingly, the next most significant association with the 5' splice site +4 position was with SNRNP27K. This result makes sense as in the cryo-EM structure of the pre-B spliceosome complex the C-terminal domain of SNRNP27K is found near the region of the U6 snRNA that will interact with the 5' splices site. Absence of SNRNP27K was associated with an increased preference for +4U at the 5' splice site. Now the real power of the interspecies association mapping was demonstrated by investigating whether any association could be determined specifically within the C-terminus of SNRNP27K. Significantly, the methionine 141 position in SNRNP27K was found to be associated with the +4 position of the 5' splice site. This finding fits nicely with previous studies where mutation of M141 caused a shift in 5' splice site selection away from +4A 5' splice sites, to 5' splice sites without +4A. What is not clear is whether M141 is conserved or invariant between all the species that were compared? __

M141 is not completely conserved across the species that were compared for the SNRNP27K C-terminus analysis. We did not test positions with very strong sequence conservation, because without variation in both the genotype and phenotype it is not possible to test for an association. We have rephrased the relevant Results and Methods sections to make this point clearer. In addition, we have incorporated a sequence logo to illustrate the degree of conservation of each position in the SNRNP27K C-terminal domain as Figure 5 -figure supplement 1A. Finally, we have included an additional box-plot to illustrate the finding that species which have lost SNRNP27K or have only lost the Methionine equivalent to human SNRNP27K position 141, show a similar preference for +4U at 5’ SSs. This is now included as Figure 5 - figure supplement 1B.

Overall, this result reveals the power of the interspecies association approach and provides interesting and exciting information on the molecular determinants of 5' splice site evolution. 

We are grateful to the reviewer for these comments.

__The final analysis was to investigate the interaction potentials of the U5 and U6 snRNAs with the 5' splice site in the Sacchromycotina genomes and try to relate this to species with fewer introns and less alternative splicing. Species with low intron numbers and low splicing complexity were revealed to have weaker U5 and U6 anti-correlation potentials and favor +4U at the 5' splice site. On the other hand, species with high intron number and presumably higher splicing complexity featured anti-correlated U5 and U6 snRNA interaction potentials and favored +4A 5' splice sites. This extensive analysis provides novel information on the interactions and splice site properties of species with simple and complex splicing. Again, I see why there is emphasis on the 5' splice site here but a similar analysis with the U2 snRNA and the branch site could also be informative. __

We absolutely agree that inter-species association mapping could be applied to other splicing signal phenotypes including 3’ splice sites and intron branchpoints. Accordingly, we raise this subject in the final section of the Discussion. However, branchpoint sequences are challenging to predict with genomic data. Because preliminary analyses suggest independent variation in these other splicing signal phenotypes, we feel a separate focused study is required to properly explain (and substantiate) even the analytical approaches involved. We hope the reviewer would agree that incorporating U2 snRNA and branchpoint variation analyses into this manuscript as well, could detract from the clarity of the conceptual advances that we make here.

__Minor comments __

__Should the Title include SNRNP27K? __

We have included SNRNP27K into the revised title.

Should the title specify that it is the evolution of only the 5’ splice site sequence preference being studied here? 

Because apostrophes in titles can compromise some scholarly online search engines (https://insights.uksg.org/articles/10.1629/uksg.534), we would prefer not to include 5’ in the title.

Include information on intron number and 5’ splice site interaction potential of U5 and U6 snRNA in the Summary? 

We thank the reviewer for this suggestion. We have updated the Summary to include our findings on U5 and U6 interaction potential in species with reduced intron number.

__Figure 1C is not referred to in the text? __

We apologise for this oversight. We have added references to figure 1C in the appropriate Results section.

Page 8, line 5 – better to say “splicing signal phenotypes”. 

We have amended this statement on Page 8 and at other places in the text where related phrasing was made.

__What are the other points on Figure 3B? What is the next point below SNRNP27K? Is it U2A’? __

The other points on Figure 3B represent Orthofinder orthogroups which contain human orthologs that are known components of the spliceosome. The list of spliceosomal components was taken from Sales-Lee et al. 2021. The third most significant point is indeed the orthogroup containing the human ortholog of U2A’. As we state in the text, however, the correlation of U2A’ with the 5’SS+4 A to U ratio phenotype is no longer significant once METTL16 presence/absence is controlled for, indicating that the correlation of U2A’ with the +4A phenotype is likely explained by similarity in the patterns of gene loss of U2A’ and METTL16.

__The second paragraph of the Discussion is vague and lacks a reference. “we could also identify an association with a methionine residue in the conserved C-terminal domain of SNRNP27K orthologs.” There are a few methionines in the C-terminus, which one? Please reference the statement “transcriptome analysis of C. elegans SNRP-27 M141T mutants..” __

We apologise for the lower quality of writing in this section of the Discussion. We have updated the text, made the statements about the SNRNP27K C-terminus less ambiguous, and added the relevant citations as appropriate.

Reviewer #1 (Significance (Required)): 

Overall, this is a well written and clearly presented study that provides some key molecular information on the splicing factors involved in the evolution of 5’ splice sites and shows the power of interspecies association studies. Some important conceptual principles have now been defined for the field going forward. 

With thank the reviewer for this kind comment on the importance of this work.

__The question remains as to whether METTL16 and SNRNP27K are the sole determinants of 5’ splice site preference evolution at +4? __

We cannot say for certain that METTL16 and/or SNRNP27K determine the 5’SS +4 phenotype – only that they are correlated with it. In our response to reviewer 3, and in a new Discussion section, we have detailed some of the scenarios that could explain these correlations. We also cannot rule out whether there are changes in the presence/absence (or domain/sequence-level changes) of other, untested proteins that correlate with the 5’SS +4 phenotype and we allude to this in the final section of the Discussion.

One splicing factor that immediately comes to mind is Prp8 where there is extensive evidence for involvement in splice site selection and is clearly in the right location throughout splicing to be involved. This question should at least be discussed but Prp8 would also be a very interesting candidate for the interspecies association mapping. 

Prp8 is a core component of spliceosomes and is conserved throughout the Saccharomycotina. For this reason, we were unable to associate splicing phenotypes with Prp8 presence or absence variation at the level of orthogroups. However, we revisited this question posed by the reviewer. Our experience with inter-species association mapping, so far, indicates it works well with orthogroup presence/absence or when straightforward amino acid substitutions can be detected in conserved and hence alignable protein sequence domains. We analysed the conserved U6 snRNA-interacting region of the Prp8 linker domain, which maps close to the 5’ splice site in cryo-EM models, using the profile HMM PF10596 available from Pfam. We found that the majority of this domain was extremely highly conserved with variation in only a few species and positions. The strongest correlation with the +4A to U ratio phenotype was at position 58, which is conserved as a Glycine in all but 8 species (6 Dipodascaceae, 2 CUG-Ser1), that also tend to have a stronger preference for +4A. However, examination of the species contributing to this result (and to similar results at other positions) indicated that in the 6 Dipodascaceae species, this change is part of a larger deletion or replacement that makes the whole linker region align poorly to the model. Hence, the G58 position itself may not be specifically important for the +4 phenotype. Although the wholesale loss or replacement of the U6 snRNA-interacting region in these species is potentially interesting, these larger scale structural changes in a small number of species are difficult to interpret. Therefore, to maintain the focus of the manuscript and the clear links to METTL16 and SNRNP27K that have orthogonal support, we have decided not to add these results to the manuscript but present them here (Figure not available on biorXiv commenting window).

Also, as mentioned previously, only the 5’ splice site was investigated here and the manuscript could become a more substantial piece of work if the other splice sites were included in some way. 

We agree that it will be exciting to apply this approach to other splicing signal phenotypes and in other phylogenetic clades with emerging tree-of-life-scale genomics data. We have included variation in 3’ splice sites in the revised manuscript. As the first of its kind, this study should pioneer a wider use of this approach, by us and others, to understand the mechanisms and functions of molecular interactions not only in splicing but in other areas of biology too.

__The obvious audience here are those directly in the splicing field but the overall principles are relevant for evolutionary biologists and those studying organismal complexity. __

We thank the reviewer for recognising the broad importance of this work.

My expertise is in yeast and human splicing mechanisms. I do not have the expertise to critically evaluate the bioinformatic pipelines but they were clearly explained and presented. 

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

In their manuscript, Parker et al. investigate the evolutionary patterns of splice site preference, focusing on the A/U ratio at position A+4 on the 5´ splice site. Building upon prior studies in S. pombe and A. thaliana, the authors establish a strong correlation between this preference and the co-evolution of the METTL16 U6 snRNA methyltransferase. Furthermore, through inter-species association mapping, they identify the involvement of the splicing factor SNRNP27K in altered A/U ratios and highlight the significance of the residue Met-141 in SNRNP27K for this function. Overall, the paper effectively presents impactful new findings on the evolution of METTL16, U6 snRNA, and splicing.

We thank the reviewer for these kind comments on the importance of our study.

The computational analyses employed in this study are situated outside our field of expertise, preventing us from offering a comprehensive evaluation of the methodology’s appropriateness and rigor. Nonetheless, the identification of METTL16 through the authors’ methods, which aligns with previous research in S. pombe and A. thaliana, lends support to the validity of their approach. Notably, the close proximity between SNRNP27K and the methylated A43 residue in U6 snRNA within the spliceosome, particularly near Met-141, is an impressive finding. Previous studies have shown that a mutation at position M141T affects splicing at +4A introns, thus providing robust validation for their methods.

We thank the reviewer for these kind comments on our work.

The data presented in this study furnish crucial insights into the role of METTL16, U6 snRNA methylation, and splice site recognition. The authors expand upon recent observations that the “vertebrate conserved region” exists in non-vertebrates, despite the absence of primary sequence homology. These results will serve as a valuable guide for future molecular investigations into U6 snRNA methylation and its mechanisms in splicing. Furthermore, the implications of this paper extend to human evolution, as the plasticity in splicing is an essential factor in the evolution of developmental complexity.

We thank the reviewer for these kind comments.

Minor suggestions for improvement:

1. __ Given the significance of the interaction between U6 snRNA and the intron for understanding the data, it would be beneficial to include a figure illustrating the RNA-RNA base-pairing interactions between U6 snRNA and the 5´ splice site. This addition is particularly important if the paper is intended for publication in a journal with a general readership.__  We thank the reviewer for this excellent suggestion. We have included this as Figure 3A.

__ Similarly, the section on U1 snRNA would be more comprehensible with the inclusion of U1 RNA-RNA intron diagrams and improved descriptions of both the figures and the assay. Despite being negative data in the supplement, clarifying this section is essential. As currently written, it is challenging to follow.__ 

We agree that this section is difficult to follow. We have updated the text to improve the readability and included a figure of U1 snRNA:5’SS basepairing as Figure 3 – figure supplement 1A.

__ Whenever possible, consider increasing the figure and font sizes to enhance readability for readers.__ 

We agree that some of the more complex figures can be difficult to read when embedded into a Word document/pdf. We hope that providing high-resolution figures for reading online will mitigate this.

__ In the text, there is no reference to Figure 1C.__ 

We apologise for this oversight. We have resolved this issue with the appropriate references in the Results text.

__ In Figure 5B, the y-axis in the top panel is labelled “species,” but the legend only mentions U5/6p as the y-axis. Please revise the legend to include the appropriate information.__ 

We apologise for the confusion caused by our poorly written legend for this plot. We have updated the legend so that the text clearly refers to either the scatter plot or the marginal histograms.

Reviewer #2 (Significance (Required)):

The data presented in this study furnish crucial insights into the role of METTL16, U6 snRNA methylation, and splice site recognition. The authors expand upon recent observations that the “vertebrate conserved region” exists in non-vertebrates, despite the absence of primary sequence homology. These results will serve as a valuable guide for future molecular investigations into U6 snRNA methylation and its mechanisms in splicing. Furthermore, the implications of this paper extend to human evolution, as the plasticity in splicing is an essential factor in the evolution of developmental complexity.

We are grateful to the reviewer for these kind comments on the importance of this work.

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

In this manuscript, Parker et al present a nice exploration of the evolutionary and mechanistic relationships between 5′ splice site consensus sequences, intron numbers and METTL16/SNRNP27K. By performing inter-species association mapping in Saccharomycotina species, they found that a T in position +4 is strongly associated with the absence of METTL16 (and/or in some cases SNRNP27K or mutations in it). They also provide solid structural modelling data in support of this association.

In general, I think this is a very nice manuscript. I only have a few comments, which could be addressed by rewording specific parts and/or improving the current figures.

We are grateful to the reviewer for the kind comments on this work.

1) As the authors acknowledge, a key issue that cannot be fully resolved in this study is causality between the different events investigated. Overall, the authors are careful about this, but there are some exceptions that should be corrected. Probably the most important is in the abstract, where they write: “We conclude that variation in concerted processes of 5’ splice site selection by U6 snRNA is crucial to evolutionary change in splicing complexity”. I suggest they write something more open (and correct), such as: “We conclude that variation in concerted processes of 5’ splice site selection by U6 snRNA is associated with evolutionary changes in splicing complexity”. Similarly, other plausible scenarios should be discussed in the corresponding Discussion section.

We agree with the reviewer that it is not possible to infer the causal relationship between METTL16 absence and 5’SS+4 preference change from the current data. We, therefore, apologise for failing to be more careful in the Summary and Introduction. We have reworded these statements to better reflect what we can currently say about the evolutionary relationship between METTL16 and 5’SS sequence preference.

The correlation between METTL16 absence and 5'SS+4 sequence preference change could most likely be explained by one of several scenarios: (a) sudden loss of METTL16 causes a rapid necessity to change 5'SS sequence preferences. This is unlikely as such rapid change without widespread corresponding 5'SS changes would likely impose a high fitness cost. (b) Changes in 5'SS sequence preference occur first, driven by some other selective pressure, until there is no longer a benefit to retaining the METTL16 gene. (c) Gradual changes in the expression or catalytic efficiency of METTL16 reduce the stoichiometry of U6 snRNA m6A modification, which permits gradual change in 5'SS+4 sequence preference until complete loss of the METTL16 no longer imposes a major fitness cost. As we suggest in the Discussion, future work could examine this question by determining whether the METTL16 orthologs found in Zygosaccharomyces and Eremothecium species, which have altered their 5'SS+4 preference to a U, are expressed and functional. We have updated the Discussion to include a new section that addresses these scenarios.

2) I do not agree with the statement that "The extent of alternative splicing is the best genomic predictor of developmental complexity". To start with, there are many ways to quantify "extent of alternative splicing" and there are also different types of alternative splicing that might have different prevalence and biological impact. Then, this claim is usually related with exon skipping, which is tightly linked with intron length, and that is likely a better prediction of complexity (yet clearly not causative). My concern is: to what extent has this claim been formally and properly assessed by comparing splicing prevalence with other genomic features, such as intergenic region length, intron length, or average distance between enhancer-promoter interactions (arguably the most relevant predictor, in light of many other studies)? Moreover, I found it a bit misleading to frame the work presented in this study as directly related with developmental (or even splicing) complexity. The work is very interesting on its own, and I doubt their findings on +4 position preference in Saccharomycotina has anything to do with developmental complexity (as the Abstract and Introduction seem to imply). 

On reflection, we agree with the reviewer. Some of our framing of the text isn’t balanced with other studies on the scaling of alternative splicing with developmental complexity. We have edited the Summary and Introduction sections accordingly and cited other references that broaden the consideration of this subject. We are grateful to the reviewer for this suggestion because the changes we make improve the focus of the manuscript since our findings relate more to splicing simplification than to an understanding of increased developmental complexity.

__3) I found Figure 2 and its associated supplementary figure very difficult to follow. I suggest the authors try to improve it and make it clearer. Also, other trees summarizing the results might be helpful. __

We apologise for the complexity of these figures. We opted to show phylogenetic trees with phenotypes plotted on the y axis, rather than simply trait histograms or box-plots, because the underlying structure of the tree is important for demonstrating that multiple independent changes in the 5’SS phenotype have occurred in the Saccharomycotina. We have tried to improve the comprehensibility of the figures in the following ways: (a) We have added 5’SS sequence motifs to the x-axis of figure 2B to make what the plot represents clearer, (b) as suggested by the reviewer, we have created a pruned tree showing the 5’SS motifs of a selection of Saccharomycotina species, which demonstrates that the changes in 5’SS+4 position preferences seen in S. cerevisiae and C. albicans are likely to be a result of convergent evolution. We have added this tree as Figure 2 - figure supplement 3.

__4) I also found the Results section corresponding to Figure 5B a bit confusing. I would argue (as I think the authors do) that there are two main patterns here: below 500 introns, there is no association, while above 500 introns there is an increasingly negative association (correlation). I think it would help to more explicitly distinguishing these two patterns. Then, for the intron-poor species: is the correlation (or lack of) for species with a T or an A in position +4 different? __

We do indeed think that there are two patterns here, as indicated by the reviewer. In the previous version of the manuscript, we separated species into those having an overall preference for A at the +4 position, and those having +4U. By showing regression lines for these two classes, rather than for the general relationship between intron number and U5/6rho, we somewhat imply that the switch in +4 base preference might be causing the loss of correlation between U5/6rho and intron number. However, since essentially all species with a 5'SS +4U preference are intron poor, it seems more likely that these trends are the result of a loss of the negative correlation between intron number and U5/6rho in intron poor species, as suggested by the reviewer. To address this issue, we have replaced the regression lines on Figure 6B with a single loess (locally estimated scatterplot smoothing) regression line for all species and updated the text to make it clearer that we think loss of U5/6rho and +4A preference are separate traits of intron poor species. Although this is not exactly what the reviewer requested, we hope that it satisfies their issue with the analysis.

__Reviewer #3 (Significance (Required)): __

__This is a very interesting study that sheds light on an intriguing evolutionary pattern: the change in consensus sequence at position +4 of the 5' splice site. This topic is relevant since it is closely associated with intron loss and splicing efficiency and evolution. __

We thank the reviewer for the kind and constructive comments on this study.

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity):

Summary

The manuscript by Parker et al addresses the important question of how different organisms have evolved pre-messenger RNA systems that are either more or less complex. This question underlies the evolution of complex organisms and the genome adaptation of simple organisms to their specific environments, so is an important question to answer. This manuscript now provides the underlying molecular mechanisms of how 5' splice site sequence preference may have evolved which is both an interesting and exciting advance for the field.

We thank the reviewer for these kind comments.

Major comments

This manuscript builds on the previous work from this group where they identified the role of adenosine N6 methylation (m6A) of the U6 small nuclear RNA (snRNA) of the spliceosome by METTL16 as being important for 5' splice site selection. This work led to the speculation that loss of a METTL16 ortholog, or potentially other splicing factors, in some species could contribute to an evolutionary change in 5' splice site sequence preference. Here the authors now use the power of phylogenetics, interspecies association mapping and the available spliceosome structures to provide convincing conclusions that 5' splice site sequence preferences in the extensive number of organisms examined correlate with the presence of the U6 snRNA methyltransferase METTL16 and the splicing factor SNRNP27K. 

An analysis of METTL16 conservation was first carried out by comparing the METTL16 methyltransferase domain (MTD) in 29 diverse eukaryotic species. All the METTL16 orthologs were found to have either one or two globular domains. Three domain types were identified and compared in detail. What was not clear from this analysis was the functional significance of orthologs having either one or two domains.

We identified several species, including Drosophila melanogaster, whose METTL16 orthologs do not contain a VCR domain. However, in this study we do not draw specific conclusions about the functional significance of orthologs having different domain topologies.

In addition, while this analysis provides important new information on the domain structure of METTL16 orthologs, especially where these domains had not been identified previously, the link between this section of the results and the following sections is not that apparent.

We agree that there is a significant difference in approach between the first section of the Results and the following sections. However, we are keen to keep this part of the manuscript because it provides an orthogonal line of evidence suggesting that the ancestral role of METTL16 in eukaryotes is specifically the methylation of U6 snRNA.

Next novel bioinformatics pipelines were developed to compare both introns and orthologous groupings of protein coding genes between 227 Sacchromycotina genomes as well as 13 well-annotated eukaryote genomes. First, the 5' splice site sequence preference was compared and clearly indicates that the +4 position has the greatest variation in preferences within the Sacchromycotina. The ability to now compare a large number of genomes has provided novel information on the evolution of the 5' splice site sequence and the conclusion that there is more complexity to the 5' splice site in fungi that previously recognized. While it is apparent why only the 5' splice site signal was investigated here, with its relationship to the U6 snRNA and METTL16, it seems a shame the other splice site sequences were not analyzed using this novel pipeline. In any case, the complexity of the 5' splice site +4 position now allows, for the first time, interesting interspecies association studies.

We have now included the variance plots for 3’SS motifs (analogous to the 5’SS variance plots shown in Figure 2B) as Figure 2 supplementary figure 4A, and a traitgram for 3’SS -3C to U ratio as Figure 2 supplementary figure 4B. We have included a short section of text in the Results section to describe these additional findings.

With the 5' splice site +4 variation identified, the next step was to determine the underlying molecular mechanisms that dictate the evolution of the various sequence preferences. Some obvious players here are the U1 and U6 snRNAs which directly interact with the 5' splice site during splicing. However, no association was found between these snRNAs and the 5' splice site +4 sequence. 

The powerful interspecies association mapping was then used to determine whether the presence or absence of METTL16 ortholog or a splicing factor correlated with the 5' splice site +4 sequence variation. Interestingly, a clear association was found between METTL16 and the 5' splice site +4 position; METTL16 presence was associated with +4A at the 5' splice site and METTL16 absence was associated with +4U at the 5' splice site. This is an exciting and significant finding.

We thank the reviewer for these comments on the importance of this study.

Interestingly, the next most significant association with the 5' splice site +4 position was with SNRNP27K. This result makes sense as in the cryo-EM structure of the pre-B spliceosome complex the C-terminal domain of SNRNP27K is found near the region of the U6 snRNA that will interact with the 5' splices site. Absence of SNRNP27K was associated with an increased preference for +4U at the 5' splice site. Now the real power of the interspecies association mapping was demonstrated by investigating whether any association could be determined specifically within the C-terminus of SNRNP27K. Significantly, the methionine 141 position in SNRNP27K was found to be associated with the +4 position of the 5' splice site. This finding fits nicely with previous studies where mutation of M141 caused a shift in 5' splice site selection away from +4A 5' splice sites, to 5' splice sites without +4A. What is not clear is whether M141 is conserved or invariant between all the species that were compared?

M141 is not completely conserved across the species that were compared for the SNRNP27K C-terminus analysis. We did not test positions with very strong sequence conservation, because without variation in both the genotype and phenotype it is not possible to test for an association. We have rephrased the relevant Results and Methods sections to make this point clearer. In addition, we have incorporated a sequence logo to illustrate the degree of conservation of each position in the SNRNP27K C-terminal domain as Figure 5 -figure supplement 1A. Finally, we have included an additional box-plot to illustrate the finding that species which have lost SNRNP27K or have only lost the Methionine equivalent to human SNRNP27K position 141, show a similar preference for +4U at 5’ SSs. This is now included as Figure 5 - figure supplement 1B.

Overall, this result reveals the power of the interspecies association approach and provides interesting and exciting information on the molecular determinants of 5' splice site evolution.

We are grateful to the reviewer for these comments.

The final analysis was to investigate the interaction potentials of the U5 and U6 snRNAs with the 5' splice site in the Sacchromycotina genomes and try to relate this to species with fewer introns and less alternative splicing. Species with low intron numbers and low splicing complexity were revealed to have weaker U5 and U6 anti-correlation potentials and favor +4U at the 5' splice site. On the other hand, species with high intron number and presumably higher splicing complexity featured anti-correlated U5 and U6 snRNA interaction potentials and favored +4A 5' splice sites. This extensive analysis provides novel information on the interactions and splice site properties of species with simple and complex splicing. Again, I see why there is emphasis on the 5' splice site here but a similar analysis with the U2 snRNA and the branch site could also be informative.

We absolutely agree that inter-species association mapping could be applied to other splicing signal phenotypes including 3’ splice sites and intron branchpoints. Accordingly, we raise this subject in the final section of the Discussion. However, branchpoint sequences are challenging to predict with genomic data. Because preliminary analyses suggest independent variation in these other splicing signal phenotypes, we feel a separate focused study is required to properly explain (and substantiate) even the analytical approaches involved. We hope the reviewer would agree that incorporating U2 snRNA and branchpoint variation analyses into this manuscript as well, could detract from the clarity of the conceptual advances that we make here.

Minor comments

Should the Title include SNRNP27K?

There is certainly a case that the title should include SNRNP27K. Our aim was to make the title as short and informative as possible without too many acronyms that need explaining. Since the clearest correlation is with METTL16 and this has broader implications for understanding the role of this enzyme not only in splicing but in possibly modifying other RNA targets too, we think not including SNRNP27K is a suitable compromise. In addition, retaining the current title simplifies the tracking of the manuscript from pre-print through to journal publication.

Should the title specify that it is the evolution of only the 5’ splice site sequence preference being studied here?

Because apostrophes in titles can compromise some scholarly online search engines (https://insights.uksg.org/articles/10.1629/uksg.534), we would prefer not to include 5’ in the title.

Include information on intron number and 5’ splice site interaction potential of U5 and U6 snRNA in the Summary?

We thank the reviewer for this suggestion. We have updated the Summary to include our findings on U5 and U6 interaction potential in species with reduced intron number.

Figure 1C is not referred to in the text?

We apologise for this oversight. We have added references to figure 1C in the appropriate Results section.

Page 8, line 5 – better to say “splicing signal phenotypes”.

We have amended this statement on Page 8 and at other places in the text where related phrasing was made.

What are the other points on Figure 3B? What is the next point below SNRNP27K? Is it U2A’? 

The other points on Figure 3B represent Orthofinder orthogroups which contain human orthologs that are known components of the spliceosome. The list of spliceosomal components was taken from Sales-Lee et al. 2021. The third most significant point is indeed the orthogroup containing the human ortholog of U2A’. As we state in the text, however, the correlation of U2A’ with the 5’SS+4 A to U ratio phenotype is no longer significant once METTL16 presence/absence is controlled for, indicating that the correlation of U2A’ with the +4A phenotype is likely explained by similarity in the patterns of gene loss of U2A’ and METTL16.

The second paragraph of the Discussion is vague and lacks a reference. “we could also identify an association with a methionine residue in the conserved C-terminal domain of SNRNP27K orthologs.” There are a few methionines in the C-terminus, which one? Please reference the statement “transcriptome analysis of C. elegans SNRP-27 M141T mutants..”

We apologise for the lower quality of writing in this section of the Discussion. We have updated the text, made the statements about the SNRNP27K C-terminus less ambiguous, and added the relevant citations as appropriate.

Reviewer #1 (Significance):

Overall, this is a well written and clearly presented study that provides some key molecular information on the splicing factors involved in the evolution of 5’ splice sites and shows the power of interspecies association studies. Some important conceptual principles have now been defined for the field going forward.

With thank the reviewer for this kind comment on the importance of this work.

The question remains as to whether METTL16 and SNRNP27K are the sole determinants of 5’ splice site preference evolution at +4?

We cannot say for certain that METTL16 and/or SNRNP27K determine the 5’SS +4 phenotype – only that they are correlated with it. In our response to reviewer 3, and in a new Discussion section, we have detailed some of the scenarios that could explain these correlations. We also cannot rule out whether there are changes in the presence/absence (or domain/sequence-level changes) of other, untested proteins that correlate with the 5’SS +4 phenotype and we allude to this in the final section of the Discussion.

One splicing factor that immediately comes to mind is Prp8 where there is extensive evidence for involvement in splice site selection and is clearly in the right location throughout splicing to be involved. This question should at least be discussed but Prp8 would also be a very interesting candidate for the interspecies association mapping.

Prp8 is a core component of spliceosomes and is conserved throughout the Saccharomycotina. For this reason, we were unable to associate splicing phenotypes with Prp8 presence or absence variation at the level of orthogroups. However, we revisited this question posed by the reviewer. Our experience with inter-species association mapping, so far, indicates it works well with orthogroup presence/absence or when straightforward amino acid substitutions can be detected in conserved and hence alignable protein sequence domains. We analysed the conserved U6 snRNA-interacting region of the Prp8 linker domain, which maps close to the 5’ splice site in cryo-EM models, using the profile HMM PF10596 available from Pfam. We found that the majority of this domain was extremely highly conserved with variation in only a few species and positions. The strongest correlation with the +4A to U ratio phenotype was at position 58, which is conserved as a Glycine in all but 8 species (6 Dipodascaceae, 2 CUG-Ser1), that also tend to have a stronger preference for +4A. However, examination of the species contributing to this result (and to similar results at other positions) indicated that in the 6 Dipodascaceae species, this change is part of a larger deletion or replacement that makes the whole linker region align poorly to the model. Hence, the G58 position itself may not be specifically important for the +4 phenotype. Although the wholesale loss or replacement of the U6 snRNA-interacting region in these species is potentially interesting, these larger scale structural changes in a small number of species are difficult to interpret. Therefore, to maintain the focus of the manuscript and the clear links to METTL16 and SNRNP27K that have orthogonal support, we have decided not to add these results to the manuscript but present them here (Figure not available on biorXiv commenting window).

Also, as mentioned previously, only the 5’ splice site was investigated here and the manuscript could become a more substantial piece of work if the other splice sites were included in some way.

We agree that it will be exciting to apply this approach to other splicing signal phenotypes and in other phylogenetic clades with emerging tree-of-life-scale genomics data. We have included variation in 3’ splice sites in the revised manuscript. As the first of its kind, this study should pioneer a wider use of this approach, by us and others, to understand the mechanisms and functions of molecular interactions not only in splicing but in other areas of biology too.

The obvious audience here are those directly in the splicing field but the overall principles are relevant for evolutionary biologists and those studying organismal complexity.

We thank the reviewer for recognising the broad importance of this work.

My expertise is in yeast and human splicing mechanisms. I do not have the expertise to critically evaluate the bioinformatic pipelines but they were clearly explained and presented.

Reviewer #2 (Evidence, reproducibility and clarity):

In their manuscript, Parker et al. investigate the evolutionary patterns of splice site preference, focusing on the A/U ratio at position A+4 on the 5´ splice site. Building upon prior studies in S. pombe and A. thaliana, the authors establish a strong correlation between this preference and the co-evolution of the METTL16 U6 snRNA methyltransferase. Furthermore, through inter-species association mapping, they identify the involvement of the splicing factor SNRNP27K in altered A/U ratios and highlight the significance of the residue Met-141 in SNRNP27K for this function. Overall, the paper effectively presents impactful new findings on the evolution of METTL16, U6 snRNA, and splicing.

We thank the reviewer for these kind comments on the importance of our study.

The computational analyses employed in this study are situated outside our field of expertise, preventing us from offering a comprehensive evaluation of the methodology’s appropriateness and rigor. Nonetheless, the identification of METTL16 through the authors’ methods, which aligns with previous research in S. pombe and A. thaliana, lends support to the validity of their approach. Notably, the close proximity between SNRNP27K and the methylated A43 residue in U6 snRNA within the spliceosome, particularly near Met-141, is an impressive finding. Previous studies have shown that a mutation at position M141T affects splicing at +4A introns, thus providing robust validation for their methods.

We thank the reviewer for these kind comments on our work.

The data presented in this study furnish crucial insights into the role of METTL16, U6 snRNA methylation, and splice site recognition. The authors expand upon recent observations that the “vertebrate conserved region” exists in non-vertebrates, despite the absence of primary sequence homology. These results will serve as a valuable guide for future molecular investigations into U6 snRNA methylation and its mechanisms in splicing. Furthermore, the implications of this paper extend to human evolution, as the plasticity in splicing is an essential factor in the evolution of developmental complexity.

We thank the reviewer for these kind comments.

Minor suggestions for improvement:

1. Given the significance of the interaction between U6 snRNA and the intron for understanding the data, it would be beneficial to include a figure illustrating the RNA-RNA base-pairing interactions between U6 snRNA and the 5´ splice site. This addition is particularly important if the paper is intended for publication in a journal with a general readership.

We thank the reviewer for this excellent suggestion. We have included this as Figure 3A.

1. Similarly, the section on U1 snRNA would be more comprehensible with the inclusion of U1 RNA-RNA intron diagrams and improved descriptions of both the figures and the assay. Despite being negative data in the supplement, clarifying this section is essential. As currently written, it is challenging to follow.

We agree that this section is difficult to follow. We have updated the text to improve the readability and included a figure of U1 snRNA:5’SS basepairing as Figure 3 – figure supplement 1A.

1. Whenever possible, consider increasing the figure and font sizes to enhance readability for readers.

We agree that some of the more complex figures can be difficult to read when embedded into a Word document/pdf. We hope that providing high-resolution figures for reading online will mitigate this.

1. In the text, there is no reference to Figure 1C.

We apologise for this oversight. We have resolved this issue with the appropriate references in the Results text.

1. In Figure 5B, the y-axis in the top panel is labelled “species,” but the legend only mentions U5/6p as the y-axis. Please revise the legend to include the appropriate information.

We apologise for the confusion caused by our poorly written legend for this plot. We have updated the legend so that the text clearly refers to either the scatter plot or the marginal histograms.

Reviewer #2 (Significance):

The data presented in this study furnish crucial insights into the role of METTL16, U6 snRNA methylation, and splice site recognition. The authors expand upon recent observations that the “vertebrate conserved region” exists in non-vertebrates, despite the absence of primary sequence homology. These results will serve as a valuable guide for future molecular investigations into U6 snRNA methylation and its mechanisms in splicing. Furthermore, the implications of this paper extend to human evolution, as the plasticity in splicing is an essential factor in the evolution of developmental complexity.

We are grateful to the reviewer for these kind comments on the importance of this work.

Reviewer #3 (Evidence, reproducibility and clarity):

In this manuscript, Parker et al present a nice exploration of the evolutionary and mechanistic relationships between 5′ splice site consensus sequences, intron numbers and METTL16/SNRNP27K. By performing inter-species association mapping in Saccharomycotina species, they found that a T in position +4 is strongly associated with the absence of METTL16 (and/or in some cases SNRNP27K or mutations in it). They also provide solid structural modelling data in support of this association.

In general, I think this is a very nice manuscript. I only have a few comments, which could be addressed by rewording specific parts and/or improving the current figures.

We are grateful to the reviewer for the kind comments on this work.

1) As the authors acknowledge, a key issue that cannot be fully resolved in this study is causality between the different events investigated. Overall, the authors are careful about this, but there are some exceptions that should be corrected. Probably the most important is in the abstract, where they write: “We conclude that variation in concerted processes of 5’ splice site selection by U6 snRNA is crucial to evolutionary change in splicing complexity”. I suggest they write something more open (and correct), such as: “We conclude that variation in concerted processes of 5’ splice site selection by U6 snRNA is associated with evolutionary changes in splicing complexity”. Similarly, other plausible scenarios should be discussed in the corresponding Discussion section.

We agree with the reviewer that it is not possible to infer the causal relationship between METTL16 absence and 5’SS+4 preference change from the current data. We, therefore, apologise for failing to be more careful in the Summary and Introduction. We have reworded these statements to better reflect what we can currently say about the evolutionary relationship between METTL16 and 5’SS sequence preference.

The correlation between METTL16 absence and 5'SS+4 sequence preference change could most likely be explained by one of several scenarios: (a) sudden loss of METTL16 causes a rapid necessity to change 5'SS sequence preferences. This is unlikely as such rapid change without widespread corresponding 5'SS changes would likely impose a high fitness cost. (b) Changes in 5'SS sequence preference occur first, driven by some other selective pressure, until there is no longer a benefit to retaining the METTL16 gene. (c) Gradual changes in the expression or catalytic efficiency of METTL16 reduce the stoichiometry of U6 snRNA m6A modification, which permits gradual change in 5'SS+4 sequence preference until complete loss of the METTL16 no longer imposes a major fitness cost. As we suggest in the Discussion, future work could examine this question by determining whether the METTL16 orthologs found in Zygosaccharomyces and Eremothecium species, which have altered their 5'SS+4 preference to a U, are expressed and functional. We have updated the Discussion to include a new section that addresses these scenarios.

2) I do not agree with the statement that "The extent of alternative splicing is the best genomic predictor of developmental complexity". To start with, there are many ways to quantify "extent of alternative splicing" and there are also different types of alternative splicing that might have different prevalence and biological impact. Then, this claim is usually related with exon skipping, which is tightly linked with intron length, and that is likely a better prediction of complexity (yet clearly not causative). My concern is: to what extent has this claim been formally and properly assessed by comparing splicing prevalence with other genomic features, such as intergenic region length, intron length, or average distance between enhancer-promoter interactions (arguably the most relevant predictor, in light of many other studies)? Moreover, I found it a bit misleading to frame the work presented in this study as directly related with developmental (or even splicing) complexity. The work is very interesting on its own, and I doubt their findings on +4 position preference in Saccharomycotina has anything to do with developmental complexity (as the Abstract and Introduction seem to imply).

On reflection, we agree with the reviewer. Some of our framing of the text isn’t balanced with other studies on the scaling of alternative splicing with developmental complexity. We have edited the Summary and Introduction sections accordingly and cited other references that broaden the consideration of this subject. We are grateful to the reviewer for this suggestion because the changes we make improve the focus of the manuscript since our findings relate more to splicing simplification than to an understanding of increased developmental complexity.

3) I found Figure 2 and its associated supplementary figure very difficult to follow. I suggest the authors try to improve it and make it clearer. Also, other trees summarizing the results might be helpful. 

We apologise for the complexity of these figures. We opted to show phylogenetic trees with phenotypes plotted on the y axis, rather than simply trait histograms or box-plots, because the underlying structure of the tree is important for demonstrating that multiple independent changes in the 5’SS phenotype have occurred in the Saccharomycotina. We have tried to improve the comprehensibility of the figures in the following ways: (a) We have added 5’SS sequence motifs to the x-axis of figure 2B to make what the plot represents clearer, (b) as suggested by the reviewer, we have created a pruned tree showing the 5’SS motifs of a selection of Saccharomycotina species, which demonstrates that the changes in 5’SS+4 position preferences seen in S. cerevisiae and C. albicans are likely to be a result of convergent evolution. We have added this tree as Figure 2 - figure supplement 3.

4) I also found the Results section corresponding to Figure 5B a bit confusing. I would argue (as I think the authors do) that there are two main patterns here: below 500 introns, there is no association, while above 500 introns there is an increasingly negative association (correlation). I think it would help to more explicitly distinguishing these two patterns. Then, for the intron-poor species: is the correlation (or lack of) for species with a T or an A in position +4 different? 

We do indeed think that there are two patterns here, as indicated by the reviewer. In the previous version of the manuscript, we separated species into those having an overall preference for A at the +4 position, and those having +4U. By showing regression lines for these two classes, rather than for the general relationship between intron number and U5/6rho, we somewhat imply that the switch in +4 base preference might be causing the loss of correlation between U5/6rho and intron number. However, since essentially all species with a 5'SS +4U preference are intron poor, it seems more likely that these trends are the result of a loss of the negative correlation between intron number and U5/6rho in intron poor species, as suggested by the reviewer. To address this issue, we have replaced the regression lines on Figure 6B with a single loess (locally estimated scatterplot smoothing) regression line for all species and updated the text to make it clearer that we think loss of U5/6rho and +4A preference are separate traits of intron poor species. Although this is not exactly what the reviewer requested, we hope that it satisfies their issue with the analysis.

Reviewer #3 (Significance):

This is a very interesting study that sheds light on an intriguing evolutionary pattern: the change in consensus sequence at position +4 of the 5' splice site. This topic is relevant since it is closely associated with intron loss and splicing efficiency and evolution. 

We thank the reviewer for the kind and constructive comments on this study.

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 this manuscript, Parker et al present a nice exploration of the evolutionary and mechanistic relationships between 5′ splice site consensus sequences, intron numbers and METTL16/SNRNP27K. By performing inter-species association mapping in Saccharomycotina species, they found that a T in position +4 is strongly associated with the absence of METTL16 (and/or in some cases SNRNP27K or mutations in it). They also provide solid structural modeling data in support of this association.

In general, I think this is a very nice manuscript. I only have a few comments, which could be addressed by rewording specific parts and/or improving the current figures.

1. As the authors acknowledge, a key issue that cannot be fully resolved in this study is causality between the different events investigated. Overall, the authors are careful about this, but there are some exceptions that should be corrected. Probably the most important is in the abstract, where they write: "We conclude that variation in concerted processes of 5' splice site selection by U6 snRNA is crucial to evolutionary change in splicing complexity". I suggest they write something more open (and correct), such as: "We conclude that variation in concerted processes of 5' splice site selection by U6 snRNA is associated with evolutionary changes in splicing complexity". Similarly, other plausible scenarios should be discussed in the corresponding Discussion section.
2. I do not agree with the statement that "The extent of alternative splicing is the best genomic predictor of developmental complexity". To start with, there are many ways to quantify "extent of alternative splicing" and there are also different types of alternative splicing that might have different prevalence and biological impact. Then, this claim is usually related with exon skipping, which is tightly linked with intron length, and that is likely a better prediction of complexity (yet clearly not causative). My concern is: to what extent has this claim been formally and properly assessed by comparing splicing prevalence with other genomic features, such as intergenic region length, intron length, or average distance between enhancer-promoter interactions (arguably the most relevant predictor, in light of many other studies)? Moreover, I found it a bit misleading to frame the work presented in this study as directly related with developmental (or even splicing) complexity. The work is very interesting on its own, and I doubt their findings on +4 position preference in Saccharomycotina has anything to do with developmental complexity (as the Abstract and Introduction seem to imply).
3. I found Figure 2 and its associated supplementary figure very difficult to follow. I suggest the authors try to improve it and make it clearer. Also, other trees summarizing the results might be helpful.
4. I also found the Results section corresponding to Figure 5B a bit confusing. I would argue (as I think the authors do) that there are two main patterns here: below 500 introns, there is no association, while above 500 introns there is an increasingly negative association (correlation). I think it would help to more explicitly distinguishing these two patterns. Then, for the intron-poor species: is the correlation (or lack of) for species with a T or an A in position +4 different?

Significance

This is a very interesting study that sheds light on an intriguing evolutionary pattern: the change in consensus sequence at position +4 of the 5' splice site. This topic is relevant since it is closely associated with intron loss and splicing efficiency and evolution.

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Referee #2

Evidence, reproducibility and clarity

In their manuscript, Parker et al. investigate the evolutionary patterns of splice site preference, focusing on the A/U ratio at position A+4 on the 5´ splice site. Building upon prior studies in S. pombe and A. thaliana, the authors establish a strong correlation between this preference and the co-evolution of the METTL16 U6 snRNA methyltransferase. Furthermore, through inter-species association mapping, they identify the involvement of the splicing factor SNRNP27K in altered A/U ratios and highlight the significance of the residue Met-141 in SNRNP27K for this function. Overall, the paper effectively presents impactful new findings on the evolution of METTL16, U6 snRNA, and splicing.

The computational analyses employed in this study are situated outside our field of expertise, preventing us from offering a comprehensive evaluation of the methodology's appropriateness and rigor. Nonetheless, the identification of METTL16 through the authors' methods, which aligns with previous research in S. pombe and A. thaliana, lends support to the validity of their approach. Notably, the close proximity between SNRNP27K and the methylated A43 residue in U6 snRNA within the spliceosome, particularly near Met-141, is an impressive finding. Previous studies have shown that a mutation at position M141T affects splicing at +4A introns, thus providing robust validation for their methods.

The data presented in this study furnish crucial insights into the role of METTL16, U6 snRNA methylation, and splice site recognition. The authors expand upon recent observations that the "vertebrate conserved region" exists in non-vertebrates, despite the absence of primary sequence homology. These results will serve as a valuable guide for future molecular investigations into U6 snRNA methylation and its mechanisms in splicing. Furthermore, the implications of this paper extend to human evolution, as the plasticity in splicing is an essential factor in the evolution of developmental complexity.

Minor suggestions for improvement:

1. Given the significance of the interaction between U6 snRNA and the intron for understanding the data, it would be beneficial to include a figure illustrating the RNA-RNA base-pairing interactions between U6 snRNA and the 5´ splice site. This addition is particularly important if the paper is intended for publication in a journal with a general readership.
2. Similarly, the section on U1 snRNA would be more comprehensible with the inclusion of U1 RNA-RNA intron diagrams and improved descriptions of both the figures and the assay. Despite being negative data in the supplement, clarifying this section is essential. As currently written, it is challenging to follow.
3. Whenever possible, consider increasing the figure and font sizes to enhance readability for readers.
4. In the text, there is no reference to Figure 1C.
5. In Figure 5B, the y-axis in the top panel is labeled "species," but the legend only mentions U5/6p as the y-axis. Please revise the legend to include the appropriate information.

Significance

The data presented in this study furnish crucial insights into the role of METTL16, U6 snRNA methylation, and splice site recognition. The authors expand upon recent observations that the "vertebrate conserved region" exists in non-vertebrates, despite the absence of primary sequence homology. These results will serve as a valuable guide for future molecular investigations into U6 snRNA methylation and its mechanisms in splicing. Furthermore, the implications of this paper extend to human evolution, as the plasticity in splicing is an essential factor in the evolution of developmental complexity.

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Referee #1

Evidence, reproducibility and clarity

Summary

The manuscript by Parker et al addresses the important question of how different organisms have evolved pre-messenger RNA systems that are either more or less complex. This question underlies the evolution of complex organisms and the genome adaptation of simple organisms to their specific environments, so is an important question to answer. This manuscript now provides the underlying molecular mechanisms of how 5' splice site sequence preference may have evolved which is both an interesting and exciting advance for the field.

Major comments

This manuscript builds on the previous work from this group where they identified the role of adenosine N6 methylation (m6A) of the U6 small nuclear RNA (snRNA) of the spliceosome by METTL16 as being important for 5' splice site selection. This work led to the speculation that loss of a METTL16 ortholog, or potentially other splicing factors, in some species could contribute to an evolutionary change in 5' splice site sequence preference. Here the authors now use the power of phylogenetics, interspecies association mapping and the available spliceosome structures to provide convincing conclusions that 5' splice site sequence preferences in the extensive number of organisms examined correlate with the presence of the U6 snRNA methyltransferase METTL16 and the splicing factor SNRNP27K.

An analysis of METTL16 conservation was first carried out by comparing the METTL16 methyltransferase domain (MTD) in 29 diverse eukaryotic species. All the METTL16 orthologs were found to have either one or two globular domains. Three domain types were identified and compared in detail. What was not clear from this analysis was the functional significance of orthologs having either one or two domains. In addition, while this analysis provides important new information on the domain structure of METTL16 orthologs, especially where these domains had not been identified previously, the link between this section of the results and the following sections is not that apparent.

Next novel bioinformatics pipelines were developed to compare both introns and orthologous groupings of protein coding genes between 227 Sacchromycotina genomes as well as 13 well-annotated eukaryote genomes. First, the 5' splice site sequence preference was compared and clearly indicates that the +4 position has the greatest variation in preferences within the Sacchromycotina. The ability to now compare a large number of genomes has provided novel information on the evolution of the 5' splice site sequence and the conclusion that there is more complexity to the 5' splice site in fungi that previously recognized. While it is apparent why only the 5' splice site signal was investigated here, with its relationship to the U6 snRNA and METTL16, it seems a shame the other splice site sequences were not analyzed using this novel pipeline. In any case, the complexity of the 5' splice site +4 position now allows, for the first time, interesting interspecies association studies.

With the 5' splice site +4 variation identified, the next step was to determine the underlying molecular mechanisms that dictate the evolution of the various sequence preferences. Some obvious players here are the U1 and U6 snRNAs which directly interact with the 5' splice site during splicing. However, no association was found between these snRNAs and the 5' splice site +4 sequence.

The powerful interspecies association mapping was then used to determine whether the presence or absence of METTL16 ortholog or a splicing factor correlated with the 5' splice site +4 sequence variation. Interestingly, a clear association was found between METTL16 and the 5' splice site +4 position; METTL16 presence was associated with +4A at the 5' splice site and METTL16 absence was associated with +4U at the 5' splice site. This is an exciting and significant finding.

Interestingly, the next most significant association with the 5' splice site +4 position was with SNRNP27K. This result makes sense as in the cryo-EM structure of the pre-B spliceosome complex the C-terminal domain of SNRNP27K is found near the region of the U6 snRNA that will interact with the 5' splices site. Absence of SNRNP27K was associated with an increased preference for +4U at the 5' splice site. Now the real power of the interspecies association mapping was demonstrated by investigating whether any association could be determined specifically within the C-terminus of SNRNP27K. Significantly, the methionine 141 position in SNRNP27K was found to be associated with the +4 position of the 5' splice site. This finding fits nicely with previous studies where mutation of M141 caused a shift in 5' splice site selection away from +4A 5' splice sites, to 5' splice sites without +4A. What is not clear is whether M141 is conserved or invariant between all the species that were compared? Overall, this result reveals the power of the interspecies association approach and provides interesting and exciting information on the molecular determinants of 5' splice site evolution.

The final analysis was to investigate the interaction potentials of the U5 and U6 snRNAs with the 5' splice site in the Sacchromycotina genomes and try to relate this to species with fewer introns and less alternative splicing. Species with low intron numbers and low splicing complexity were revealed to have weaker U5 and U6 anti-correlation potentials and favor +4U at the 5' splice site. On the other hand, species with high intron number and presumably higher splicing complexity featured anti-correlated U5 and U6 snRNA interaction potentials and favored +4A 5' splice sites. This extensive analysis provides novel information on the interactions and splice site properties of species with simple and complex splicing. Again, I see why there is emphasis on the 5' splice site here but a similar analysis with the U2 snRNA and the branch site could also be informative.

Minor comments

Should the Title include SNRNP27K?

Should the title specify that it is the evolution of only the 5' splice site sequence preference being studied here?

Include information on intron number and 5' splice site interaction potential of U5 and U6 snRNA in the Summary?

Figure 1C is not referred to in the text?

Page 8, line 5 - better to say "splicing signal phenotypes".

What are the other points on Figure 3B? What is the next point below SNRNP27K? Is it U2A'?

The second paragraph of the Discussion is vague and lacks a reference. "we could also identify an association with a methionine residue in the conserved C-terminal domain of SNRNP27K orthologs." There are a few methionines in the C-terminus, which one? Please reference the statement "transcriptome analysis of C. elegans SNRP-27 M141T mutants.."

Significance

Overall, this is a well written and clearly presented study that provides some key molecular information on the splicing factors involved in the evolution of 5' splice sites and shows the power of interspecies association studies. Some important conceptual principles have now been defined for the field going forward.

The question remains as to whether METTL16 and SNRNP27K are the sole determinants of 5' splice site preference evolution at +4? One splicing factor that immediately comes to mind is Prp8 where there is extensive evidence for involvement in splice site selection and is clearly in the right location throughout splicing to be involved. This question should at least be discussed but Prp8 would also be a very interesting candidate for the interspecies association mapping.

Also, as mentioned previously, only the 5' splice site was investigated here and the manuscript could become a more substantial piece of work if the other splice sites were included in some way.

The obvious audience here are those directly in the splicing field but the overall principles are relevant for evolutionary biologists and those studying organismal complexity.

My expertise is in yeast and human splicing mechanisms. I do not have the expertise to critically evaluate the bioinformatic pipelines but they were clearly explained and presented.

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Reply to the reviewers

Reviewer #1*. This is a good paper dealing with gap of our knowledge in understanding reason of ICB failures. Subject being difficult it is expected that the design and content of such experiment will be complex.But the authors forget practicality of readers attention and making paper apear interesting. They need to organise and may be classify the varied information in such a way that reader can find a rhythm in excavating data more easily. It appears confusing at time, so they may try to make it more simple. In this way they may concentrate more on methods and classify results too. A thorough revision is suggested, to make it consize. *

__Authors’ answer: __We thank the Reviewer for his positive evaluation and constructive feedback. We appreciate the complexity of single-cell RNA-sequencing analyses. In order to simplify our manuscript, our revised manuscript now focuses on the transitional states of tumor-resident and circulating T cells found in ovarian cancer patients. Our study is timely as it is the first to report the developmental relationship of TILs in ovarian cancer. We substantially edited our manuscript to make it clear that our findings suggest a gradual acquisition of the exhaustion program initiated by effector-like cells (cluster CD8_GZMH) that eventually gives rise to more terminal states with features of tissue residency and chemotaxis (clusters CD8_CCL4, CD8_XCL1, and CD8_CXCL13). We also include new analyses revealing the presence and proportion of these T cell states in different cancer patients (New Fig. 4A-B), and how these T cell states associate with clinical responses to immune checkpoint blockade (ICB). We hope the Reviewer will find our revised manuscript easier to read.

Reviewer #2. I think the first half of the article, in which the GZMH-CD8 cluster is considered to be in an intermediate state of transition to exhaustion, is interesting, and I feel that the single-cell seq and TCR data are well analyzed to make the point. On the other hand, I feel that the latter part of the paper may not be anything more than a hypothesis. In particular, the part claiming that it is related to prognosis or applicable to the prediction of the effect of ICB is insufficient, since their gene signature is not described in detail and the contents of the Figure are not mentioned in the manuscript. In the latter part, the effects of GPR184 and 25-HC, or the effects of IL21, would require experiments to verify (to verify whether the addition of chemokine or the inhibition of the receptor changes the specific CD8 population).

Author’s answer: Thank you for discussing the limitation of the signature employed. We agree with the reviewer’s comment. Old Figure 5 has been removed from the revised manuscript.

Reviewer #2. Minor point: In particular, there is little mention of Figure 5 in the text, making it difficult to understand.

Author’s answer: Thank you for your comment. As we previously discussed, we have removed Figure 5 from the revised manuscript. The method used to generate the signature was found to be inappropriate.

Reviewer #2. The latter part is difficult to understand. To begin with, it is already known that ovarian cancer does not contribute much to ICB, so what does it mean to analyze the CD8 population, which is known as a marker of ICB response in other carcinomas, as an indicator? Especially for clinicians like us, it is hard to imagine that the results will lead to clinical trials that will attempt to sort out the population that ICB is favored in.

Author’s answer: Although immune checkpoint blockade has demonstrated limited effectiveness against ovarian cancer, subset analyses suggest superior efficacy for some patients and according to subtype. Combination anti-PD-1/CTLA-4 therapy for instance achieved response rates up to 31% (Zamarin et al., 2020), and superior benefit for single agent PD-1 blockade has been reported in clear cell ovarian cancer. Moreover, encouraging clinical results have recently been reported in studies exploring combinations with PARP and VEGF inhibitors. As example, interim analysis of the phase 3 DUO-O trial (NCT03737643) showed a statistically significant and clinically meaningful improvement in PFS in patients with newly diagnosed advanced ovarian cancer without a BRCA1/2 mutation (Harter et al., 2023).

Our study aimed to better understand how ovarian tumor-infiltrating T cells acquire their exhaustion program after migrating from the periphery and whether these mechanisms are unique or shared amongst cancer types. Recent studies in other cancer types had shown the dynamics of T cells and demonstrated the clonal replacement of intratumoral T cells after ICB and emphasized the role of peripheral clones in this process (Wu et al., 2020; Yost et al., 2019). In lung cancer, it has been proposed a transitional state between precursor and terminally differentially cells (Gueguen et al., 2021). Our study demonstrates, for the first time in ovarian cancer, the presence of similar transitional states of CD8 T cells. Our revised manuscript also now includes new data revealing that pre-effector GZMK- and intermediary GZMH-expressing CD8 cells are better biomarkers of ICB response than terminally differentiated XCL1 and CXCL13 expressing CD8 T cells (New Figure 4). Altogether, our study provides important and novel insights on the development of tumor-infiltrating T cells in ovarian cancer patients, which may serve to better select ovarian cancer patients for ICB therapy.

Reviewer #2. Since the first half of the study is very interesting, we feel that it is more important to confirm the mechanism of exhaustion from the blood via the intermediate (GZMH_CD8), including functional experiments. Also, as a clinician, we are very interested in the perspective of whether some of the fractions identified in this study are different in proportion in different patients and whether they correlate with the clinical course of the disease since the study only analyzed a sample of 5 patients.

Author’s answer: We thank the reviewer for proposing to extend our analysis. As suggested, our revised manuscript now includes new analyses which reveals the different proportions of our identified T cells states in different cancer patients (New Figure 4). We further investigated whether these T cell states associate with clinical responses and observed that pre-effector GZMK- and intermediary GZMH-expressing CD8 T cells are better biomarkers of ICB response than terminally exhausted XCL1- and CXCL13-expressing CD8 T cells (New Figure 4).

Reviewer #3. Question 1: Whether the distribution patterns of CD4+ and CD8+ T cell clusters in Figure 1B were comparable among the 5 patient samples? Whether the proportion of five types of clones in Figure 3C are comparable among the 5 patient samples?

Author’s answer: Thank you for the question. We included the results to answer these questions in the supplementary material (fig. S1C-D). For each patient, we calculated the proportion of a cluster among T cells in the blood or tumor. As observed in the boxplot (fig. S1C), the proportion of some subsets were higher in certain patients, such as the higher proportion of CD8_GZMK in the tumor of patient p09454. A recent study classified patients’ tumors based on the spatial distribution of CD8 T cells and performed scRNA-seq to identified cell subsets enriched in the groups inflamed/infiltrated (characterized by the distribution of CD8 T cells within the tumor epithelium), excluded (infiltrating CD8 T cells are restricted to the tumor stroma) or desert (T cells are not present or have low frequency) (Hornburg et al., 2021). Interestingly, this subset of CD8_GZMK cells were enriched in desert tumors, suggesting that the difference we observed in our dataset might reflect the spatial distribution of CD8 T cells in patient p09454. Regarding the TCR-seq data, the frequency of the five types of clones was different among patients. To show this data, we included a barplot (fig. S2D), showing for example, a higher proportion of tumor-expanded clones in patient p10329.

Reviewer #3. Question 2: In Figure S2C, only a very small number of cells in the CD8-GZMK K-22 population. Are these cells representative? Do they generally exist in multiple samples or only in one sample?

Author’s answer: Thank you for your comment. The subcluster k_22 indeed has a smaller number of cells compared to other subclusters. Nevertheless, the K_22 cluster was found in every patient and in every healthy donor. To clarify, we edited our revised manuscript to include a statement that cluster k_22 was composed of fewer cells compared to other clusters.

Reviewer #3. Question 3: In the Fig.S6 legend, the authors stated "Our results suggest the differentiation of cluster CD8-GZMK into the effector-like subset CD8-GZMH." However, there seems to be no corresponding analysis in the main text to support this conclusion.

Author’s answer: We appreciate your attention to this statement. We agree the results of our study doesn’t sustain this statement and so we have excluded it in the revised manuscript.

Reviewer #3____. Question 4: Is there more detailed clinical information that can be provided for the 5 patients included in the study? Per the methods all patients were receiving debulking surgery and were treatment naïve, but did they differ in stage, age, comorbidities, etc.?

Author’s answer: Thank you for your comment on this. We have included a table with clinical information on the stage, age, and menopause status of the five patients.

Reviewer #3. Question 5: Were any cells included for sequencing from adjacent 'normal' tissue uninvolved with tumor (these samples are from surgical debulking of primary tumors, which may include such areas of non-involved tissue.) While shared TCR clonotypes between blood and intratumoral T cells strongly suggests the tumor-resident populations are recruited from the blood, the degree of sharing with normal tissue-resident T cells would be of interest as well.

Author’s answer: Thank you for your comment. Samples were provided for sc-RNA-seq after pathology review and validation of tumor histology. We did not perform sc-RNA-seq on normal adjacent tissue (NAT) We agree this would be interesting as a follow up study, since in other cancer types (renal, colon and lung) it has been demonstrated that T clones expanded in the tumor and NAT are also present in peripheral blood (Wu et al., 2020).

Reviewer #3. Question 6: Very little is discussed about HGSOC itself in the main text (eg clinical background, prior literature on the composition of infiltrating immune populations and potential reasons for at best modest poor responses to IO) until the first sentence of the discussion. As the entirety of the new data produced in this study is from HGSOC tumors there should be more focus on this tumor type and conversation with the prior literature on it (mainly from prior studies on the immune environment of HGSOC). Further, how distinct do the authors suspect the cell populations found in their study to be to ovarian as opposed to other epithelial tumor types?

Author’s answer: Thank you for the suggestion. We now included more background information on immunotherapy of HGSOC. Specifically, we added the following paragraph in our introduction: “In ovarian cancer, the presence of both T and B cells improves patients' survival (Nelson, 2015; Nielsen et al, 2012). They are usually organized in lymphoid aggregates ranging from a small group of cells to a well-organized TLS (Kroeger et al, 2016). Organized TLSs correlate with better survival, such as observed in patients treated with ICB. Although immunotherapy has demonstrated limited effectiveness against ovarian cancer, subsets of patients may thus benefit from ICB. In support of this, combination anti-PD-1/CTLA-4 therapy can achieve response rates above 30% (Zamarin et al., 2020), and encouraging clinical results have recently been reported when combining ICB with with PARP and VEGF inhibitors (Harter et al., 2023)”.

Reviewer #3. Question 7: Were the signature genes used for analysis in figure 5 remove chosen in a formal, unbiased manner, or simply hand-picked as representative of the respective cell types? This information is not provided in the supplement.

Author’s answer: Another reviewer has also expressed similar concerns. The genes selected to represent cell types were chosen manually, which we acknowledge is not the best method for defining a signature. As a result, we have decided to exclude Figure 5 from the manuscript under review. We believe an unbiased approach is more suitable for characterizing the cell network proposed in our study.

Reviewer #3. Question 8: While the NicheNet analysis of potential interactions among lymphocyte populations raises some strong hypotheses, it would be interesting to extend the interaction analysis to all CD45+ populations, given the sequencing was done on CD45+ immune cells.

Author’s answer: Thank you for suggesting analysis. We have included the results of cell interaction including all CD45+ cells (fig. S3). We observed CD40L as one of the top predicted ligands highly expressed in CD4_CXCL13 subset mediating a response in subsets of antigen-presenting cells, such as B cells (cluster B), plasma cells (cluster PC_2), and plasmacytoid dendritic cells (cluster pDC). Interestingly, this result also support the hypothesis of Tfh-like cells (cluster CD4_CXCL13) coordinating the action of intratumoral immune cells involved in the antitumor immune response.

Reviewer #3. Question 9: A sample size of 5 patients is relatively small for current single cell RNAseq studies of human tumor patients.

Author’s answer: We agree with the reviewer that a sample size of 5 patients is relatively small. Thus, to validate our results in other patients, we included in the reviewed manuscript the analysis of scRNA-seq of 47 patients across10 cancer types (dataset from (Zheng et al., 2021). As demonstrated in figure 3 and figure 5, we could identify subsets of CD8 and CD4 T cells from our ovarian cancer patients in those 10 cancer types dataset.

Reviewer #3.____ Minor

*1. In lines 96-97, "CD8-GZMB" was mentioned twice in the description. *

2. In line 126, this section did not discuss residency markers, yet a conclusion about residency was made in this sentence.

Author’s answer: We appreciate you bringing these errors to our attention. We fixed them in the updated version of the manuscript.

References:

Gueguen, P., Metoikidou, C., Dupic, T., Lawand, M., Goudot, C., Baulande, S., … Amigorena, S. (2021). Contribution of resident and circulating precursors to tumor-infiltrating CD8 T cell populations in lung cancer. Science Immunology, Vol. 6, p. eabd5778. doi:10.1126/sciimmunol.abd5778

Harter, P., Trillsch, F., Okamoto, A., Reuss, A., Kim, J.-W., Rubio-Pérez, M. J., … Aghajanian, C. (2023). Durvalumab with paclitaxel/carboplatin (PC) and bevacizumab (bev), followed by maintenance durvalumab, bev, and olaparib in patients (pts) with newly diagnosed advanced ovarian cancer (AOC) without a tumor BRCA1/2 mutation (non-tBRCAm): Results from the randomized, placebo (pbo)-controlled phase III DUO-O trial. Journal of Clinical Orthodontics: JCO, 41(17_suppl), LBA5506–LBA5506.

Hornburg, M., Desbois, M., Lu, S., Guan, Y., Lo, A. A., Kaufman, S., … Wang, Y. (2021). Single-cell dissection of cellular components and interactions shaping the tumor immune phenotypes in ovarian cancer. Cancer Cell. doi:10.1016/j.ccell.2021.04.004

Wu, T. D., Madireddi, S., de Almeida, P. E., Banchereau, R., Chen, Y.-J. J., Chitre, A. S., … Grogan, J. L. (2020). Peripheral T cell expansion predicts tumour infiltration and clinical response. Nature. doi:10.1038/s41586-020-2056-8

Yost, K. E., Satpathy, A. T., Wells, D. K., Qi, Y., Wang, C., Kageyama, R., … Chang, H. Y. (2019). Clonal replacement of tumor-specific T cells following PD-1 blockade. Nature Medicine. doi:10.1038/s41591-019-0522-3

Zamarin, D., Burger, R. A., Sill, M. W., Powell, D. J., Jr, Lankes, H. A., Feldman, M. D., … Aghajanian, C. (2020). Randomized Phase II Trial of Nivolumab Versus Nivolumab and Ipilimumab for Recurrent or Persistent Ovarian Cancer: An NRG Oncology Study. Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology, 38(16), 1814–1823.

Zheng, L., Qin, S., Si, W., Wang, A., Xing, B., Gao, R., … Zhang, Z. (2021). Pan-cancer single-cell landscape of tumor-infiltrating T cells. Science, 374(6574), abe6474.

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Referee #3

Evidence, reproducibility and clarity

Below are some questions as well as suggestions for revision and to strengthen the manuscript.

Major:

1. Whether the distribution patterns of CD4+ and CD8+ T cell clusters in Figure 1B were comparable among the 5 patient samples? Whether the proportion of five types of clones in Figure 3C are comparable among the 5 patient samples?
2. In Figure S2C, only a very small number of cells in the CD8-GZMK K-22 population. Are these cells representative? Do they generally exist in multiple samples or only in one sample?
3. In the Fig.S6 legend, the authors stated "Our results suggest the differentiation of cluster CD8-GZMK into the effector-like subset CD8-GZMH." However, there seems to be no corresponding analysis in the main text to support this conclusion.
4. Is there more detailed clinical information that can be provided for the 5 patients included in the study? Per the methods all patients were receiving debulking surgery and were treatment naïve, but did they differ in stage, age, comorbidities, etc.?
5. Were any cells included for sequencing from adjacent 'normal' tissue uninvolved with tumor (these samples are from surgical debulking of primary tumors, which may include such areas of non-involved tissue.) While shared TCR clonotypes between blood and intratumoral T cells strongly suggests the tumor-resident populations are recruited from the blood, the degree of sharing with normal tissue-resident T cells would be of interest as well.
6. Very little is discussed about HGSOC itself in the main text (eg clinical background, prior literature on the composition of infiltrating immune populations and potential reasons for at best modest poor responses to IO) until the first sentence of the discussion. As the entirety of the new data produced in this study is from HGSOC tumors there should be more focus on this tumor type and conversation with the prior literature on it (mainly from prior studies on the immune environment of HGSOC). Further, how distinct do the authors suspect the cell populations found in their study to be to ovarian as opposed to other epithelial tumor types?
7. Were the signature genes used for analysis in figure 5 chosen in a formal, unbiased manner, or simply hand-picked as representative of the respective cell types? This information is not provided in the supplement.
8. While the NicheNet analysis of potential interactions among lymphocyte populations raises some strong hypotheses, it would be interesting to extend the interaction analysis to all CD45+ populations, given the sequencing was done on CD45+ immune cells.
9. A sample size of 5 patients is relatively small for current single cell RNAseq studies of human tumor patients.

Minor

1. In lines 96-97, "CD8-GZMB" was mentioned twice in the description.
2. In line 126, this section did not discuss residency markers, yet a conclusion about residency was made in this sentence.

Significance

In this manuscript titled "Predicting Developmental Relationships of Tumor-Resident and Circulating T Cells in Ovarian Cancer," Carneiro and colleagues employed single-cell transcriptomics and T cell receptor profiling of immune cells sorted from paired peripheral blood and tumor tissue in a small cohort of ovarian cancer patients to investigate the developmental relationships of T cell populations and their potential interactions. They identified a possible differentiation pathway involving GZMH-expressing CD8+ T cells that progresses towards tissue residency and exhaustion. The researchers suggested the effector function of intermediate GZMH-expressing CD8+ T cells could be sustained through interaction with CXCL13-expressing CD4+ Tfh-like cells. Moreover, they proposed that CD4+ Tfh-like cells could attract GPR183-expressing pre-effector GZMK-expressing CD8+ T cells and plasmacytoid dendritic cells via the production of 7α,25 dihydroxycholesterol (7α,25-HC). Ultimately, the study hypothesized that CD4+ Tfh-like cells expressing IL-21 among other molecules might enhance antitumor immunity against ovarian tumors by coordinating the actions of multiple immune populations. Strengths of the study include detailed, combined analysis of inferred developmental trajectories via shared TCR clonotypes across tissue as well as potential crosstalk between cellular populations, as well as association of signature genes with clinical outcomes. Weaknesses include a small number of patients and the dataset being limited only to single cell RNAseq and thus providing descriptive findings without functional validation or perturbation.

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Referee #2

Evidence, reproducibility and clarity

Summary: This study used single-cell transcriptomics and T cell receptor profiling to identify the developmental relationships of T cell populations in ovarian cancer patients. The researchers proposed a model of differentiation pathway that showed how an intermediate GZMH-expressing CD8 T cell subset progressively reinforces exhaustion and tissue residency programs towards terminally exhausted cells. Then they also focus on the nature of TPEX, dual-expanded clone, which is considered an important indicator for the efficacy of ICB, and argue that it is strongly related to GPR183, 25-OHC, and IL21. Based on the analysis of clinical samples, they argue that their proposed gene signature may also be prognostically relevant and predictive of ICB efficacy.

Major comment: I think the first half of the article, in which the GZMH-CD8 cluster is considered to be in an intermediate state of transition to exhaustion, is interesting, and I feel that the single-cell seq and TCR data are well analyzed to make the point. On the other hand, I feel that the latter part of the paper may not be anything more than a hypothesis. In particular, the part claiming that it is related to prognosis or applicable to the prediction of the effect of ICB is insufficient, since their gene signature is not described in detail and the contents of the Figure are not mentioned in the manuscript. In the latter part, the effects of GPR184 and 25-HC, or the effects of IL21, would require experiments to verify (to verify whether the addition of chemokine or the inhibition of the receptor changes the specific CD8 population).

Minor point: In particular, there is little mention of Figure 5 in the text, making it difficult to understand.

Significance

It is interesting to note that the authors simultaneously analyze immune cells in the blood and in the tumor, and examine in detail what is characteristic of the blood, what is characteristic of the tumor, and what is seen in both. And it is very interesting that they specifically proposes an intermediate group that is recruited from the blood to the tumor and is in the process of becoming exhausted. I am sure there are many studies on TILs and TLSs, but this study would be helpful to understand how they are concentrated locally (near the tumor) in comparison with immune cells in the blood as well.

However, the latter part is difficult to understand. To begin with, it is already known that ovarian cancer does not contribute much to ICB, so what does it mean to analyze the CD8 population, which is known as a marker of ICB response in other carcinomas, as an indicator? Especially for clinicians like us, it is hard to imagine that the results will lead to clinical trials that will attempt to sort out the population that ICB is favored in.

Since the first half of the study is very interesting, we feel that it is more important to confirm the mechanism of exhaustion from the blood via the intermediate state, including functional experiments. Also, as a clinician, we are very interested in the perspective of whether some of the fractions identified in this study are different in proportion in different patients and whether they correlate with the clinical course of the disease, since the study only analyzed a sample of 5 patients.

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Referee #1

Evidence, reproducibility and clarity

This is a good paper dealing with gap of our knowledge in understanding reason of ICB failures. Subject being difficult it is expected that the design and content of such experiment will be complex.But the authors forget practicality of readers attention and making paper apear interesting.

They need to organise and may be classify the varied information in such a way that reader can find a rhythm in excavating data more easily.

It appears confusing at time, so they may try to make it more simple.

In this way they may concentrate more on methods and classify results too.

A thorough revision is suggested, to make it consize.

Significance

This is a good paper dealing with gap of our knowledge in understanding reason of ICB failures. Subject being difficult it is expected that the design and content of such experiment will be complex.But the authors forget practicality of readers attention and making paper apear interesting.

They need to organise and may be classify the varied information in such a way that reader can find a rhythm in excavating data more easily.

It appears confusing at time, so they may try to make it more simple.

In this way they may concentrate more on methods and classify results too.

A thorough revision is suggested, to make it consize.

Transparent Peer Review

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Referee #3

Evidence, reproducibility and clarity

In the manuscript entitled "Aurora A mediated new phosphorylation of RAD51 is observed in Nuclear Speckles", the authors unveil the Serine S97 as a novel phosphorylation site of the RAD51 recombinase and that this phosphorylation is mediated by the Aurora A kinase using a set of in vitro and in cellulo experiments. The authors also describe this phosphorylation being in the nucleus specifically in nuclear speckles where mRNA maturation and splicing occurs suggesting a role of RAD51 in the latter. The confocal microscopy images provided to test this hypothesis are convincing. However, using confocal images as well, the authors claim that RAD51 phosphorylated at S97 foci do not colocalize with the DNA damage marker -H2AX, hence a function not related to DNA damage, however the data provided does not fully support this statement. In this study, Alaouid et al, utilize mutants of RAD51 that alter S97 phosphorylation to further study its function and provide data that support RAD51 as an RNA binding protein. Overall, the manuscript shows some interesting observations that are worth pursuing however the in vitro and in cellulo results are not aligned, lack some controls, and many points should be reconsidered.

Major comments:

• Are the key conclusions convincing?

Not as stated.

Fig. 1A. The authors conclude that pS97-RAD51 favors RAD51 strand invasion capacity using the D-loop assay. Indeed, the S97D phosphomimic increased the D-loop activity 2.5-fold compared to WT RAD51. However, the S97A mutant, which is the non-phosphorylated form also increased the D-loop activity by 2-fold compared to WT (figure 1C). So, the phosphorylation or the absence of it seem to promote strand invasion. So, what is the role of the phosphorylation? There is no discussion about this. Besides, no representative image of the D-loop assay is shown, this is very important as these experiments need to be run with the relevant controls to be meaningful.

Fig. 1D. The polymerization rate of RAD51 is probably irrelevant for its function in the absence of DNA. What do they want to get at with this assay?

In figure 2B, the authors conclude that RAD51 phosphorylation at S97 is dynamically regulated throughout the cell cycle. Indeed, the pS97-RAD51 is well observed in asynchronous cells, and the double thymidine block time course experiment followed by PI staining shows the oscillation of the pS97-RAD51 from G1 to G2/M stage. The authors quantified the ratio of pS97-RAD51/total RAD51 to conclude this. However, it would be more accurate to also divide the above over the intensity of the loading control (tubulin) because in figure 3A for example, they quantified the ratio of pS97-RAD51/tubulin but did not consider the levels of RAD51 in their quantifications.

In figure 3B, the authors state that pS97-RAD51 is decreased after CPT treatment and that the pS97-RAD51 foci do not localize with the DNA damage marker -H2AX. The signal of gH2AX is already weird as it does not change from Ctrl to CPT conditions (especially in HCC1806 cells). A pre-extraction of soluble protein with CSK should be used to then look at the co-localization, with the pan-staining of the two signals is difficult to draw any conclusions of colocalization. Nevertheless, the signal of RAD51 seems equal in all conditions in the images shown and it does not seem to be reduced after CPT.

In figure 4A, the authors show that Aurora A is responsible for the S97-RAD51 phosphorylation in cellulo. Indeed, the use of an Aurora A inhibitor reduces the pS97-RAD51 signal, however, this is only true in one cell line (HCC1806) but no effect was observed in HeLa cells. Is this effect cell-specific?

The authors find that RAD51 binds both DNA and RNA and measure the affinities of the RAD51 bearing the S97D and S97A mutations. S97D shows the highest affinity for ssDNA and RNA in Fig. 7A, B, however the opposite is true for dsDNA in Fig 7C, D. All three forms of RAD51 bind RNA although with different affinities however no error bars are shown. The description of the results does not seem accurate. Importantly, these data should somehow correlate/be discussed with respect to the D-loop assay performed in Fig. 1. The authors conclude that the binding to RNA is reduced in S97D-RAD51 suggesting that the pRAD51 that they observe at nuclear speckles would be probably not associated with RNA at these nuclear speckles, right? this goes against their idea of this phosphorylated form being related to RNA splicing... - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

The manuscript seems to be in early days and requires lots of editing, rewriting to relate the in vitro and in cell data and make a coherent story - Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.

The authors performed chromatin fractionation to determine the correct localization of the pS97-RAD51 and looked for the phosphorylated form by western blots. But then they confirmed the finding using immunofluorescence. I think it would be more convincing and consistent if the authors do a pre-extraction before the use the antibody because as such, they would be indeed confirming the localization of the protein they are looking at that is specifically in the nucleus.

As well, in order to test the specificity of the pS97-RAD51 antibody they generated, a simple treatment of the lysates with phosphatases would be a good control for the specificity of their antibody These and the critics mentioned above need to be address. - 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.

This manuscript is not ready for submission - Are the data and the methods presented in such a way that they can be reproduced?

Yes. However, the legends of the images are way too concise. - Are the experiments adequately replicated and statistical analysis adequate?

In Fig. 2B, the authors performed a double thymidine block followed by a time course release to track cell cycle progression of the cells and phosphorylation of RAD51 at S97. They do not indicate the biological replicates they performed. There are no error bars in the estimated KD shown in Fig.7.

Minor comments:

• Specific experimental issues that are easily addressable.

The authors conclude that the S97 is specifically phosphorylated by the Aurora A kinase. How? Have they looked at other documented kinases known to phosphorylate RAD51?

In figure 6 the authors overexpress HA-tagged RAD51 proteins corresponding to WT, S97D and S97A mutants in cells and label them for immunofluorescence. Maybe it would be better to downregulate the endogenous RAD51 to discard possible combined effects.

In figure - Are prior studies referenced appropriately?

The authors show in their manuscript that RAD51 protein CAN interact with RNA in vitro, a finding not previously described to my knowledge. However, a recent study entitled "RAD51-dependent recruitment of TERRA lncRNA to telomeres through R-loops, Nature, 2020" provides in vitro data showing the binding of RAD51 to TERRA, a LncRNA, which I think would be worth mentioning their manuscript.

The authors should mention previous contributions in the field especially when it comes to RAD51 in the HR pathway post DNA damage, which is quite documented and updated. For example, in this section of the introduction, "RAD51 is a recombinase protein implicated in the strand exchange mechanism during the DSB repair by the Homologous Recombination (HR) pathway. In the absence of DNA Damage (DD), RAD51 is predominantly cytoplasmic and translocates to the nucleus during the DNA Damage Response (DDR) to manage HR repair. As it needs the undamaged sister chromatid as a template, the HR repair pathway occurs mainly in the late S, G2 phases of the cell cycle. However, it has been documented that HR repair can also occur during G1 and early S phases, and in this case, the undamaged template used for the repair could be the homologous chromosome or an RNA transcript2". This statement is definitely worth more references.

The same problem is recurrent in the rest of the introduction; therefore, it needs to be updated and better referenced. - Are the text and figures clear and accurate?

The text needs a lot of editing to accurately describe the results, see for example: "The resulting KD evaluation shows that the S97D mutant had a dsDNA binding affinity lower to that of the WT (a KD of 2.26 μM for the S97D-RAD51 vs a KD of 0.38 μM for the WT RAD51). Concerning, the S97A mutant comparison to the WT RAD51, we observed modified association and dissociation curves that resulted in an identical affinity to dsDNA (a KD of 0.33 μM for the S97A-RAD51 vs a KD of 0.38 μM for the WT RAD51). We can conclude that in our in vitro conditions, the Ser97 phosphorylation has a high impact on RAD51 affinity for DNA by dividing its affinity by 5.8." Besides, the figures are of low quality and should be more carefully crafted and presented. Some experiments (such as the D-loop) are not represented in the figures.<br /> - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

Using a different representation for the graphs would be a plus (also see previous comments)

Referees cross-commenting

I think the other reviewers and I have raised very important and complementary points that will help the authors improve the quality of the manuscript substantially.

Significance

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.

The discovery of a new phosphorylation site in RAD51 (S97) by Aurora A is potentially interesting for the field of the maintenance of genome stability as it could broaden the understanding of how such an important recombinase may be regulating the maintenance of genome integrity throughout the cell cycle. Also, the idea of RAD51 being involved in splicing and mRNA maturation seems very attractive and a very important conceptual advance. However, given the premature status of the text and the figures, the manuscript falls short to show convincing evidence. - Place the work in the context of the existing literature (provide references, where appropriate).

Many works are highlighting the role of RNA binding proteins as an integral part of the DNA damage response. In addition, a wealth of evidence in the literature suggest that many DNA repair proteins are RNA binding proteins, and that RNA is an important player in the DDR. The possible finding that RAD51 interacts with RNA and localize to nuclear speckles possibly acting in splicing is very interesting and attractive. How is Aurora A involved in this, what is the trigger, and whether RAD51 is binding RNA at these sites is still unclear. - State what audience might be interested in and influenced by the reported findings.

Labs working in genome integrity mechanisms and the crosstalk between transcription and DNA repair would be interested. - Define your field of expertise with a few keywords to help the authors contextualize your point of view.

Genome Instability, homologous recombination

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Referee #2

Evidence, reproducibility and clarity

Summary

Homologous recombination is central to stabilizing the genome where Rad51 recombinase plays a pivotal role. Authors found unexpected localization of Rad51 to nuclear speckles. This localization is associated with a novel phosphorylation site of Rad51 at Ser97, which is phosphorylated by Aurora A. Because nuclear speckles are where RNA maturation occurs, authors argue for the possible involvement of Rad51 in modulating splicing, a previously unsuspected role for this important recombinase.

Major points:

1. The discoveries made in this paper heavily rely on the Phospho-S97 specific antibody (PS97 antibody). The biggest concern of this reviewer is that the validation of this material is not rigid enough. The specificity of this antibody against PS97 is validated only by PS97 peptide competition. The outcome is not convincing either; the PS97 signal seems quite resistant to Si-RAD51 in Fig2A. Furthermore, in Fig2B, PSer97 signal seems rather constant throughout the cell cycle while Rad51 signal fluctuates.

These observations make this reviewer wonder if the authors are really detecting the phosphorylation of Rad51 with this material (i.e., PSer97 antibody).

I suggest the authors validate this antibody by doing the following experiments:

1-1. Do phosphatase treatment to see if the western blotting signal depends on phospho-S97.

1-2. Do competition experiments using the non-phospho peptide (i.e., the same polypeptides carrying a regular unmodified Ser at 97).

1-3. Try western blotting using purified Rad51 proteins, one treated with AuroraA and another without the treatment.

1-4. Do western blotting with cell extract from the cell line producing Rad51-S97A, S97D and compare with wild-type Rad51.

1. P.10, line 4 The purity of the purified protein should be included (Rad51 and two other mutant proteins) by showing CBB-stained SDS-page gel.
2. P. 10, line 7 (Fig1C). D-loop assay with Rad51 and its mutants. The actual data should be presented with the actual D-loop formation efficiency. Comparison with wild type value is not enough.
3. Fig5AB There are lots of PSer97 signals that do not even overlap with DAPI (Fig5A) or Sc35 (Fig5B). How do authors explain that? Also, quantification needs to be done regarding colocalization between PSer97 and Sc35.
4. Fig5D I do not know what to look for here. At least authors should employ proper negative controls such as siRad51 extract and WCE supplemented with PSer peptides.
5. Fig6AB Quantification of the results needs to be presented. This reviewer is wondering if there is any explanation regarding the difference in the localization of overproduced HA-Rad51 between HeLa and HCC1806; HA-Rad51 goes into a nucleus in HeLa while it stays in the cytoplasm in HCC1806. Any explanation?

Minor points:

1. Please include line numbers.
2. P.2, line 11 Could you cite the literature showing Rad51 is predominantly cytoplasmic?
3. P.10, line 15 The authors are not measuring the polymerization rate here. The title is misleading.
4. Fig2A What do NT and Si-Sc stand for? How come Pser97 signal is resistant to Si-RAD51?
5. Fig2B P-Rad51/Rad51 ratio graph does not have error bars, making it difficult to assess its reproducibility.

Referees cross-commenting

I am pretty much in agreement with the comments/criticisms raised by the other two reviewers.

Significance

If Rad51 is indeed involved in RNA maturation, that will be a very novel and exciting discovery. The observations presented in this work, however, seem a bit too inconclusive to support the idea, at least, to this reviewer.

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Referee #1

Evidence, reproducibility and clarity

This paper by Alaouid et al. describes the role of Aurora A-mediated RAD51 phosphorylation in RNA metabolism in the sub-nuclear organelle such as Nuclear Speckles (NS). By the combination of biochemistry and cell biology methods, the authors showed that Aurora A phosphorylates Ser97 of human RAD51 in vitro. The antibody against the phosphor-Ser97 RAD51 seems to recognize NS. Moreover, RAD51 binds not only DNA, but also RNA in vitro. These suggest the role of RAD51 in RNA processing in NS. Moreover, the authors analyzed the biochemical properties of a phosphor-mimetic version of RAD51 (RAD51-S97D) and a phosphor-defective version (RAD51-S97A) and the effect of the over-expression of these mutants in NS dynamics in a cell. The idea of the link to RAD51 in RNA processing in a specific nuclear organelle sounds very interesting and opens a new area of DNA damage response (DDR). However, this paper did not show any functional evidence on the link between RAD51 phosphorylation and RNA processing in NS. Moreover, there are lots of technical issues in the results reported in the manuscript. In some experiments, the authors have to check the reproducibility and be careful about statistics. More importantly, the specificity of the anti-PSer97-RAD51 antibody raised in this study was not properly evaluated in vivo, which makes it hard to interpret the results using this antibody such as western blotting and immuno-fluorescent analyses.

Major comments:

1. Because of the poor description, it is hard to evaluate the content. This manuscript needs a more detailed description of the results in a scientifically valid way.
2. Please describes the basic biochemical activities (ssDNA (Figure, dsDNA binding, and ATP hydrolysis activities) of mutant RAD51 proteins used in this study; RAD51-S97A and RAD51-S97D proteins. See also minor comments in this respect.
3. It is essential to check the localization signal of PS97 signal in cells with RAD51 depletion by siRNA. Alternatively, the authors used chicken DT40 RAD51 cKO cells (Sonoda et al. EMBO J. 1998) to check the specificity of the antibody (RAD51 is conserved between humans and chicken, and the antibody seems to work in DT40).
4. Data not shown: Please show the data in Supplemental Figures or deposit it in a public database.
5. Please cite original references to cite the previous results.
6. Please make a single composite Figure.

Minor comments:

1. Page 4, the second paragraph, line 1: Please add the reference number of Chabot et al. (4).
2. Page 4, last sentence, DNA/RNA binding activity: For the binding of RAD51 in the presence of ATP, Mg2+ ion or divalent ion is essential. However, there is no description on how much concentration of the divalent ion was used in the assay.
3. Page 10, the first paragraph, line 4: Please show a Coomassie gel of purified RAD51, RAD51-S97A, and RAD51-S97D proteins.
4. Figure 1C, D-loop assay: Please show the gel of the products in this assay. It would be nice to show the kinetics of the reactions by these RAD51 mutant proteins. Or the effect of a different RAD51 concentration was tested.
5. Page 10, the third paragraph, line 1: Please explain what is "BS3"; how this chemical stabilizes the oligomer and the references related to the drug.
6. P values: Please describe the method to calculate the value in Figure legends.
7. Figure 1D: Since this assay cannot quantitatively measure the oligomerization status of RAD51, the authors' claims are not convincing. Electron microscopic observation, which is the best, and/or ultra-centrifugation or gel filtration would be recommended to see the difference in the oligomeric status of the RAD51.
8. Figure 2A: This result is not convincing. Although siRNA for RAD51 largely decreases the amount of RAD51 in cell lysates (bottom, ~80%), a modest decrease of the signal is seen for Phospho-Ser97-RAD51 (top, ~50%)). The authors need to explain this discrepancy. More importantly, this phosphorylation is mediated by Aurora A kinase. It is important to show the signals detected with this antibody decrease in the treatment of the Aurora A inhibitor or siRNA for Aurora A subunits. The inhibition experiments shown in Figure 4A are not convincing because the effect of the inhibitor is very small.
9. Figure 2B: How did the authors determine each stage of G1, S, G2, and M phases (bottom right graph)? There are no markers of the S phase in western blots such as Cyclin A. Moreover, FACS analysis would be recommended.
10. Figure 2B, graphs: Please add error bars of quantification of the bands by doing multiple experiments to support the authors' claim on the increase of RAD51 S97 phosphorylation from G1/S to G2/M transition.
11. Figure 2C top, fractionation assay: Please include a western blot of RAD51 as a control like the ones in the middle.
12. Figure 2D top: Please include images of RAD51 as a control.
13. Page 12, first paragraph, line 2: Please show representative images of immunostaining of different cell lines in the Supplementary Figure and quantify the size of the foci. Do show all the data in either main Figures or Supplemental Figures without "data not shown".
14. Figure 3A: Please explain gammaH2AX blot in either text or legend.
15. Page 12, the second paragraph, line 8, data not shown: Please show the data in Supplemental Figure.
16. Page 12, the third paragraph, line 3: The authors need to explain what is the gammaH2AX to readers.
17. Figure 3B and C: Please check BRCA1/2 or RPA32 (or other DNA repair center markers) localization rather than gammaH2AX for the marker for DNA damage focus. As shown in these figures, gammaH2AX signals spread over the DSB sites, make it difficult to check the colocalization. Why number and intensity of gammaH2AX signals are so different between B and C? In Figure 3C, did the authors use non-treated cells?
18. Figure 3B, western blots: The top panel is over-exposed.
19. Page 12 last paragraph-page 13 first paragraph: The short summary is not necessary. These sentences should be moved to Discussion.
20. Figure 4A: Please include any positive marker for the Aurora-A inhibition such as histone H3S10-phosphorylation.
21. Figure 4B: Did Aurora A overexpression induce any cell cycle arrest? If it induces G2/M arrest, this increased phosphorylation is simply due to the arrest (in Figure 2B, the authors showed an increase of the phosphorylation in G2/M phase).
22. Figure 4B pSer97-RAD51/RAD51 ratio: This reviewer is not convincing the quantification. What is the dynamic range of this western? Do they try different cell lysate volumes to adjust constant RAD51 signals to compare the pSer97-RAD51 signals?
23. Page 13, third paragraph, lines 2-3 and Figure 4B left graph: Is this statistically significant? Please show what statistical method was used here (show it in Legend).
24. Figure 5B, PlaB treatment: The Images show a decreased focus number of PSer97-RAD51. This is more obvious than the formation of larger foci. The authors need a more precise description of the result in the text.
25. Figure 5C: Please show the position of the full-length of RAD51 protein by an arrow. The position of RAD51 and pS97 are different-pS97 signal migrates faster than the RAD51 (opposed to the result in Figure 1A).
26. Figure 5D, IE: What is "NIP"?
27. Figure 5D, IP: Where is a band of Sc-35? In IP fraction (bottom), there is little band corresponding with the band in lysates. Three thick band are not specific.
28. Figure 5E, page 14 last sentence, "improved this experiment": Without the quantification, the authors do not conclude this.
29. Figure 5 experiments: It is not clear why the improvement of Rad51-IP by RNA treatment could explain the role of pSer97-RAD51 points out the RAD51-binding to RNA. Rather the opposite interpretation would be possible. If pSer97-RAD51 is tightly bound to an RNA-containing nuclear structure, the authors may try chromatin fractionation with RNAase treatment.
30. Figure 6: Please quantify the number and size of Nuclear speckles in different conditions.
31. Figure label of B and D: "B" and "D" should be placed on the graph for RNA binding.
32. Page 15-16, DNA/RNA binding assay: Please indicate the length of DNA/RNA in the text. Moreover, it is well established that ATP analogs modulate RAD51-binding to DNA. It is important for the authors to check the effect of ATP and ADP et on DNA/RNA.
33. Page 16, the second paragraph: In this paragraph, the authors mentioned about "ds"DNA rather than ssDNA described above. Which is true?
34. Supplemental Figure 1: Please explain what the purple circle means. Moreover, how this result shows the phosphorylation of Ser97. The two spectra look very different. Do they have any other phosphorylation?

Referees cross-commenting

I also agree with the other two reviewers. My concern is that we need a re-review of the revised version. I am not familiar with how the Review Common works. Hope that the journal will take care of the re-reviewing after the authors address our concerns on this paper

Significance

This paper may offer a new idea in the biology of nuclei by providing a possible link between proteins involved in homologous recombination such as RAD51 and RNA processing in subnuclear compartments, which is regulated by Aurora A-phosphorylation.

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field. This paper might provide a possible link of RAD51 protein involved in homologous recombination with RNA processing in subcompartments in nuclei.
• Place the work in the context of the existing literature (provide references, where appropriate). The concept on the role of RAD51 in nuclear RNA processing sounds interesting.
• State what the audience might be interested in and influenced by the reported findings. The results in the paper are of interest to researchers who work on DNA damage response and DNA repair as well as RNA metabolism.
• Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. I am a researcher on DNA damage response and DNA repair but is not working of RNA biology.

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Referee #3

Evidence, reproducibility and clarity

This manuscript reports the interaction between poorly characterized FAM104 proteins to ubiquitin-dependent segregase VCP. VCP functions in protein and organelle quality control as well as in extraction of ubiquitylated proteins from chromatin to regulate DNA repair, replication and transcription. In addition, VCP mutations are causative for several human neurological disorders. The authors demonstrate that FAM104 proteins promote the nuclear localization of VCP and that their loss causes impaired growth and hypersensitivity to chemical inhibition of VCP. They show that FAM104 proteins bind to VCP directly via a non-canonical helical motif and model the interaction with AlphaFold Miner, which allowed the identification of critical amino acids that mediate the interaction, which was then validated in vivo and in vitro.

The conclusions are supported with well-designed experiments and data of high quality, manuscript is written in a clear and precise way.

Minor points

• P3: The authors write that mutations in VCP are causative for cancer. This should be rephrased.
• P3: I would suggest to add a reference to the new study that also shows that VCP is also exploited by bacteria rand not only viruses (
• Could the authors better illustrate the difference between FAM104A and B, and provide some explanations of why A seems to interact better with VCP compared to B. Is it just matter of higher expression of FAM104A in the cells where the interaction has been tested?
• The authors should quantify the IF results in Figure 4 and include the quantification in the main figure
• UBXN2B interaction with FAM104A was found in HT affinity-MS (Huttlin et al) and Y2H (Luck et al) studies. Can the authors validate this interaction of UBXN2B with FAM104 proteins? This would help to understand whether FAM104 interacts mainly with nuclear adaptors.

Significance

The results presented in this manuscript will be of interest to the borad field of protein quality control and lay the foundation to study the functions of FAM104 proteins in chromatin-associated degradation.

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Referee #2

Evidence, reproducibility and clarity

In their manuscript ‚FAM104 proteins promote the nuclear localization of p97/VCP' Maria Körner, Susanne Meyer, and coauthors describe the identification of FAM104 proteins as cofactors of p97/VCP, a central factor in ubiquitin-mediated cellular proteolytic processes. Function as p97/VCP cofactors has not previously been clearly attributed to FAM104 proteins.

The initial observation that FAM104 proteins interact directly with p97/VCP in yeast two-hybrid assays is confirmed by in vitro pulldown experiments with recombinantly purified proteins as well as in lysates of cultured mammalian cells. Using truncated proteins and structure predictions, the interaction interface of p97/VCP and FAM104 proteins is further narrowed down to single amino acids of a characteristic C-terminal alpha helix in FAM104. Overall, these interaction studies are technically sound and include meaningful control conditions to postulate FAM104 proteins as p97/VCP binders. Subsequent functional analyses using colocalization studies and cellular fractionation suggest that FAM104 proteins determine the nuclear/chromatin-associated fraction of p97/VCP. Based on this observation, the authors speculate that FAM104 proteins are of particular importance given the established nuclear/chromatin-associated processes involving p97/VCP activity. This hypothesis is supported by the observation that FAM104A knockout cells exhibit an impaired growth phenotype that is exacerbated in the presence of a p97/VCP inhibitor and in combination with a DNA damage trigger.

Points of concern:

1. The authors hypothesize that FAM104 proteins enhance the nuclear/chromatin-associated function of p97/VCP by sequestering it from the cytosol into nuclear/chromatin. In the corresponding experiments, overexpression of FAM104 species (Figures 4 and 5) in otherwise unperturbed cells is used. Because recruitment of p97/VCP to client proteins is thought to depend in large part on ubiquitylation, it is unclear how overexpression of FAM104 is sufficient to enhance nuclear/chromatin localization of VCP. Is nuclear/chromatin localization accompanied by changes in ubiquitylation and/or turnover of the corresponding proteins? In other words, does enhanced localization also correlate with increased activity, or could the enhanced nuclear/chromatin association also be explained by inhibited/captured p97/VCP?
2. The authors link the function of FAM104 proteins in nuclear targeting of p97/VCP to the absence of a unique NLS peptide. Therefore, it would be interesting to determine whether the appearance of FAM104 proteins at the evolutionary level correlates with the strength/presence of NLS peptides in p97/VCP and/or its cofactors UFD1/NPL4/FAF1/UBXN3. Do FAM104 proteins compensate for the loss of NLS peptides in p97/cofactor complexes?
3. Re 2) It remains unclear whether FAM104 proteins are responsible for the mere sequestration of p97/VCP in the nucleus or whether FAM104 proteins also contribute to process/client specificity in other ways. In this context, the authors could investigate a possible compensation of the reduced nuclear targeting of p97/VCP in FAM104 knock-out cells by fusion with an efficient cNLS peptide. Does this compensate for both nuclear/chromatin localization and growth/drug sensitivity?
4. Re 3) How does overexpression of FAM104 alter drug sensitivity compared to knock-out cell lines (Figure 7)?
5. Is there experimental evidence on how FAM104 proteins can bind p97/VCP to chromatin in this context and the proposed targeting of p97/VCP to the nucleus/chromatin? Does FAM104 mRNA/protein expression increase when p97/VCP-mediated processes are disrupted (e.g., in the presence of p97/VCP inhibition or DNA damage)? Are FAM104 protein levels stabilized under these conditions? Are FAM104 proteins differentially regulated (e.g., in terms of localization) under these conditions? Figure 3A suggests that FAM104 proteins may have a different function in relation to p97/VCP protein levels: FAM104A iso1/2 have lower p97/VCP protein levels than FAM104A iso5 and B iso3. The authors suggest that this is due to the solubility of p97/VCP. It should be clarified whether lower solubility equates to increased chromatin association.
6. It remains unclear whether a FAM104-dependent shift in nuclear/chromatin-associated p97/VCP could also be a secondary compensatory effect versus functional impairment in FAM104 overexpression/depletion. The authors might include this in their discussion.

Significance

In summary, the author's conclusion that FAM104 proteins represent a previously underappreciated class of p97/VCP cofactors is well supported. Given the versatile and important role of p97/VCP and cellular protein homeostasis pathways, this finding is of interest to a broad audience. However, the functional role of FAM104 proteins in p97/VCP biology remains unclear. Therefore, the authors need to further elaborate the physiological contribution of FAM104 proteins to p97/VCP function in additional experiments. The suggestions are largely based on modifications of experiments already performed in this manuscript.

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Referee #1

Evidence, reproducibility and clarity

Summary:

The manuscript submitted by Korner et al. presents data regarding the interaction of p97 with FAM104 protein family. This part of the manuscript is performed by Y2H as well as in-vitro and in-vivo pull-down assays. After molecular mapping and characterizations, the authors continue and address the role of FAM104-p97 interaction on nuclear localization of p97 as well cell health in respect to p97 dependent activity. 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.

Major comments:

• Are the claims and the conclusions supported by the data or do they require additional experiments or analyses to support them?

Claims concerning the mapping of FAM104 and p97 (Figures 1&2) are generally well concluded. Yet, minor issues concerning Fig2D (FAM104Aiso1 cdel26) as well as Figure 2E (p97-deltaN pull down) lack of interaction-are not supported by the presented data (both show weak interactions). Claims concerning nuclear/cytosol p97 distribution impact upon FAM104 manipulations (over-expression or KO) need to be further evaluated by additional methodologies. For example, the distribution impact using the FAM104 mutants in 4B should be evaluated by cell fractionation experiments (as performed in figure 5). Cell fractionation performed for FAM104A isoforms 1&2 should be performed on isoforms 5&3, the fact that they are expressed at lower levels has no impact, as the evaluation is on p97 and they were able to show in figure 3A an impact on p97 levels. Impact on distribution performed in Figure 6 using FAM104 KO cells should also include cell fractionation experiments in order to enable clear conclusion regarding FAM104 impact on p97 nuclear distribution.

Also, statistics presented are somewhat problematic at several points. In figure S4C the ** difference between vector and deNLS mutant make no sense (I think they should have been non-significant). Figure 7 make no sense to compare WT and KO cells (in panels b&C) if their original growth was different. One should compare the differences in respect to the drug concentration in each cell type. Also, it may be useful for statistical purposes to evaluate cell numbers rather than growth% and this may enable to obtain better statistical significances. - 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.

The suggested experiments are all in reasonable time frame. - Are the data and the methods presented in such a way that they can be reproduced?

Y2H is not explained at all in methods, furthermore, it would be useful to present in a table the entire list of p97 interactome obtained in this screen. - Are the experiments adequately replicated and statistical analysis adequate?

See comments above

Minor comments:

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

Previous reports regarding FAM104 interaction with p97 have been reported in two papers (PMID 32296183 sup. Table9 therein and PMID 32814053 S2 therein) this has not been stated at all. Furthermore, no data concerning previous knowledge of FAM104 is referred to in the introduction. - Are the text and figures clear and accurate?

The text is written well and one can easily follow<br /> - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

See major suggestion above

Referee cross-commenting

It seems reviewer #2 concerns are also situated close to our comments regarding nuclear function of FAM104 on p97 function. Reviewers 3 comment regarding UBXN2B possible tertiary complex with p97 and FAM104 should be attempted as it would help put p97 function in a slightly more specific context

Significance

Provide contextual information to readers (editors and researchers) about the novelty of the study, its value for the field and the communities that might be interested.

The following aspects are important:

• 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? The authors deal with a specific interaction of p97 with FAM104 protein family. While this interaction has been previously reported, their mapping of domains required for interaction is new. Conclusions regarding the additional binding partners of the FAM104-p97 complex would require additional double affinity and mass-spectrometry identifications (as well as possible substrates identification).
• 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,...). The study advances the repertoire of p97 adaptors and interacting domains.
• 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? The suitable audience would be p97 basic researchers
• 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. p97 role in protein quality control and cellular homeostasis.

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Reply to the reviewers

Manuscript number: RC-2023-01991

Corresponding author(s): Chaitanya A. Athale

1. General Statements [optional]

*We are grateful to the editors sending our manuscript out to review, and the reviewers for the careful reading and critical comments. In the following sections we describe our plan for revisions that will address the comments of the reviewers. We have added these in a point-wise manner. In summary most of the comments are addressable with additional experiments, simulations and data analysis. These will indeed serve to strengthen the findings without altering the fundamental findings. However, we would require upto 90 days to make these changes. *

Description of the planned revisions

Reviewer #1 Evidence, reproducibility and clarity

Summary: This work combines in-vitro experiments and numerical modeling to study the dynamics ofmicrotubules, driven by molecular motors. In this bottom-up approach, molecular motors areimmobilized on the surface and microtubule filaments are anchored to the surface from one end. The dynamics results in "beating like" motion of the anchored microtubules. The authors establish aphase diagram of the different dynamical patterns of "beating like" motions by varying the molecular motor density and the length of the microtubule anchored to the surface. They use a numerical framework that captures the observed patterns.

Our response: We are grateful to the reviewer for the careful reading and agree with the summary of our work. In the following sections we detail how we plan to address the specific comments.

Major comments:

1. Overall the experiments and results are well described and claims are supported by the data.

Both experimental and numerical methods are presented in a way that they can be reproduced.

Our response: We are grateful for the reviewer’s assessment about our findings and presentation of the results.

Minor comments:

1. A key feature of beating cilia is the asymmetry of the beat pattern (fast stroke and slow recovery). It might be interesting to use the kymographs or the Phy vs time analysis to see whether or not this feature exists in this simplified experimental model.

Our response: We agree with the reviewer that it could be of interest to examine whether the dynamics of the tip-angle phi (φ) shows a difference between the strokes at onset and return, to compare to the fast-slow asymmetry observed in cilia. This will be approached in two ways:

1) We will obtain more data from more fields of view

2) Use the time-derivative of the tip-angle, phi (φ) dynamics to examine whether the onset and return strokes are asymmetric and how this compares to ciliary dynamics.

3) We will also analyze the tangent angle to the contour, psi (ψ) plots with time (y-axis) and MT length (x-axis).

A qualitative analysis of a few time-series suggests indeed that the onset v/s return stroke of the ‘beating’ is likely to be asymmetric in the manner qualitatively distinct from cilia and flagella, that appear to be symmetric. This would suggest we avoid the term flagella-like to describe the dynamics.

2. Also, the beating frequency is very low (mHz) compared to real cilia/flagella (~Hz). Would it be possible to use the model to predict which parameter would need to be tuned to reach more

physiologically relevant beating frequencies?

Our response: We agree that the oscillations we observe have a frequency thousand fold lower as compared toflagella and cilia and have highlighted this in our discussion. When we modified motor velocity and stall forces, we found only a marginal increase in frequency of oscillations by a factor of 2-5, but not 10-fold or more. We also attempted in simulations to mimic kinesin-like properties. However we do not see a dramatic improvement. This suggests an involvement of higher-order organization of the filament. Indeed we plan to perform simulations that test the following scenarios not already tested:

1) the role of microtubule bundling factors resulting in 2-, 3-, and higher order complexes of MTs

2) varying the bending rigidity of the microtubules within ranges of what may be experimentally feasible with differences reported for taxol and GMPCPP filaments

3) altering the duty ratio of the motor

These will be in the nature of “what if” simulations that could provide the basis of future experimental design to test such predictions. This comment is similar to one by the other reviewers.

Significance

This study is part of the field of in-vitro reconstitution, from a minimal set of components, that aims to reproduce a biological function to identify and understand the minimal physical/biophysical mechanisms underlying a function. This study might be of interest for the people who address questions of the self-organization of cytoskeletal elements in minimal systems.

Our response: We agree with the assessment of the reviewer of the significance of the study and the readership that might be most interested in this work.

*The main limitation of this study relies on the claim of reproducing a flagella-like motion. Indeed, the frequency of the described oscillations is in the mHz range while the frequency of cilia is in the range of few Hz to tens of Hz. This suggests that the mechanism at play in such a reconstituted system is not the one that drives beating in real cilia/flagella. Yet, this limitation also applies to other studies in the field (Vilfan et al. 1999, Guido et al. 2022 ...). *

Our response: We agree with the reviewer that the 10^3 to 10^4 difference in oscillation frequency with that observed in cilia is striking. Indeed our claim was limited to the wavelike nature of the oscillation of the free end of a clamped microtubule driven by molecular motors producing a buckling instability, release and re-engagement of motors. Therefore it is evident we are missing many components in our minimal system as compared to cilia. However, we would like to emphasize for now that the beating is only qualitatively comparable to cilia and flagella. So far we have not compared the two waveforms. As a part of our revision plan, we aim to objectively describe the quantitativeaspects that could strengthen our claim of a similarity or lack thereof in wave-forms.

Indeed this limitation is also observed in the work of Vilfan et al. (2019) and Guido et al. (2022). However, we believe with changes to the experimental setup and a robust and tractable model we have improved on these studies.

References:

Vilfan A, Subramani S, Bodenschatz E, Golestanian R, Guido I (2019). Flagella- like Beating of a Single Microtubule. Nano Lett 19(5), 3359–3363.

Guido I, Vilfan A, Ishibashi K, Sakakibara H, Shiraga M, Bodenschatz E, Golestanian R, Oiwa K (2022). A synthetic minimal beating axoneme. Small e2107854.

My second concern is that the added value with regards to state of art is not clearly explicit. I'm thinking about the work of the Isabelle Guido's team where they have more complex reconstituted systems (a pair of 2 microtubules); or the work of Pascal Martin's lab where the design of the system allows to capture more complex mechanisms such as myosin density waves, which result infrequency beat of 0.1Hz.

Our response: We agree that the advances of our study can be highlighted. In the following points we highlight the value added to prior art:

1. In previous work, MT bundles have been shown to produce synchronized base-to-tip oscillations in vitro driven by kinesin in presence of crowdants (Sanchez et al., 2011??). However, the study lacked control over MT length,, something we have addressed in our study.

2. Cilia reconstitution with MT length and motor density control (Sasaki et al., 2018) are closer to control of the system but because of the complexity it is hard to distinguish what effect emerged from which componen.

3. The generation of a bending wave driven by outer dynein arm (ODA) combined with pairs of MTs nucleated from Chlamydomonas axonemal fragments (Guido et al., 2022) was probably a close mimic of a minimal system; it not only lacked ??lacked variation in motor density and length but failed to show oscillations, with S-shaped buckling patterns observed.

As a result it is reasonable to state that this work is a distinct improvement on previous work. In some senses it provides a consistency check on the previous results and at the other with a model and novel order-parameter an opportunity to improve our understanding.

References:

1. Vilfan A, Subramani S, Bodenschatz E, Golestanian R, Guido I (2019). Flagella-like Beating of a Single Microtubule. Nano Lett 19(5), 3359–3363.

2. Sanchez T, Welch D, Nicastro D, Dogic Z (2011). Cilia-like beating of active microtubule bundles. Science 333(6041), 456–9.

3. Sasaki R, Kabir AMR, Inoue D, Anan S, Kimura AP, Konagaya A, Sada K, Kakugo A (2018). Construction of artificial cilia from microtubules and kinesins through a well-designed bottom-up approach. Nanoscale 10(14), 63236332.

4. Guido I, Vilfan A, Ishibashi K, Sakakibara H, Shiraga M, Bodenschatz E, Golestanian R, Oiwa K (2022). A synthetic minimal beating axoneme. Small e2107854.

Reviewer #2 Evidence, reproducibility and clarity Summary:

The authors use a modified version of conventional gliding assays to induce microtubule bending, buckling, looping and cyclic beating (which they term "flagella-like") via clamping the plus ends of gliding microtubules to the surface. They find that the pattern of motion depends on different factors such as microtubule length and motor density. They build a simple computational model that predicts transitions between microtubule motion patterns depending on these parameters.

Our response: We agree with the assessment of the reviewer summarizing our work in terms of the approach taken and the inferences.

Major comments:

- Overall, the experimental data is extremely sparse. As far as I can see, there are only two replicas for the lower motor density. It is not clear to me how the authors define the boundaries in the

experimental phase diagram in Fig. 7. To build a phase diagram - where one axis corresponds to the motor density - on just two experiments is not convincing. I would need to see more experiments covering a larger range of motor densities and at least three replica per condition.

Our response: The comment refers to Fig. 7, whose purpose was to answer the question- can we test the phase diagram predicted in simulations by comparing to experiment? The answer was provided with representative data, in order to demonstrate that the model is qualitatively validated.

The reviewer is asking for a systematic experimental test that rigorously demonstrates such a match between simulation and experiment. To this end, the phase diagram may not be the ideal form for such a test. We will attempt to examine the beating frequency and wave-transition in line with a comment by reviewer #3, as a measure of experiment-theory validation.

We agree with the reviewer that our data could be enriched with replicates, with more densities of the motor. We will then analyze all the experimental data using common metrics to compare to simulations.

- It is not clear to me why the proportion of pinned vs. free microtubule segments should affect the beating pattern. I would expect that the free microtubule segment does not "feel" the length of the clamped segment, if it is indeed fixed all along its length and unable to move / bend. The simulations use only two anchor points at the pinned tip. The segment in between the anchor points bends, which could affect how the free microtubule segment behaves. To support the claim that it is indeed the proportion of the lengths of the pinned vs. free segments and not simply the length of the free segment alone that influence the beating pattern, I would expect to

(1) see the corresponding and thoroughly quantified experimental data that verifies this simulation-based prediction. Fig. 5C is based on only three microtubules and it is not clear how long the segments are.

(2) the entire pinned segments in the simulation should be fixed. This should also be compared to experimental data, where the lengths of the free segments are the same and only the lengths of the pinned segments

vary.

Our response: Originally the intention of comparing pinned length changes was based on experimental design, in which we incubated biotinylated tubulin to obtain longer or shorter clamped plus-ends. The contrast between a point-pinning and a longer segment is based on beam bending and buckling theory, corresponding to the difference between a swivelling point of immobilization (pinning) and a clamped end (clamped). However, we agree with the reviewer that beyond the pining scenario, once a segment is pinned the only thing really driving the beating is the free length. To address the specific comment we aim to add simulation calculations that will include a fixed clamp and increasing free length demonstrating that the primary driver in changing dynamics (so long as a segment is clamped) is the free length.

(1) To address the question of experimental comparison we will examine more data with increasing free segment lengths for the same density of motors and plot the dynamics, as well as characterize the oscillations with frequency estimation.

(2) This relates to the earlier part of this comment and we aim to re-run the filament clamped segment simulations to make it consistent with expectation and theory from related papers in the field, with only the free-segment length varied.

- In relation to my previous comments: I would expect a direct comparison between the simulation-based prediction that the beating pattern changes with microtubule length and motor density in a quantitative manner, where all pinned microtubules observed experimentally are analyzed. The figures are often based on single observations.

Our response: The experimental phase diagram had representative beating MTs, as compared to simulations. We agree that showing more statistics on these patterns could help. We aim to perform more experiments and analyze more data, which will be systematically plotted to make statistically relevant inferences of patterns as a function of density and length of MT.

- The authors report that the pinned microtubules typically undergo 2-3 cycles of beating. This

number is very low, and I am hesitant to call it "flagella-like" cyclic beating. Is this due to the dynein motors being much slower than e.g. kinesis? To confirm this and support the generality claimed by the authors, I would like to see experiments with a different, faster motor. If other motors are not readily available to the authors, this would imply a substantial amount of time and effort though.

Our response: The slower velocity of yeast cytoplasmic dynein is indeed one the contributing factors for the slow oscillations seen. In preliminary experiments with kinesin we indeed see a faster oscillation, but still in the 10 mHz range. These experiments will be added to the revised manuscript.

- Please perform statistical analysis of the experimental data.

Our response: Most of the data, while statistical, is not being compared for means (e.g. simulation v/s experiment). However we will analyze the frequency as a function of length and density and examine differences based on standard statistical tests.

Minor comments:

- Number of replicates and samples should be indicated in the figures.

Our response: With additional analyzed data and new experiments we will have more datasets and

Significance

- The approach to clamp the plus ends of gliding microtubules in order to induce buckling, bending and beating is elegant and should be easily transferable to other groups who may be interested in this method, since it is straightforward to adapt conventional gliding assays to induce pinning.

Our response: We agree with this assessment of the reviewer.

- The study could potentially be interesting to an audience studying flagella-like systems. Since the system is simple and based on in vitro components with defined parameters, it could serve as a basis for studying more complex systems or testing the influence of particular proteins associated with flagella. However, I do not see a major advance regarding our understanding of flagella or similar structures based on the manuscript. In combination with the model, I see it majorly as a useful tool, providing methodological advance. It would be desirably to make the computational model available to the public.

Our response: We agree that this system of minimal in vitro components could in future be made more complex in a step-wise manner. Once the manuscript is accepted after review, we have intended to make the code available in OpenSource. The source code of Cytosim already is OpenSource and can be downloaded here: https://gitlab.com/f-nedelec/cytosim.

- The computational model seems useful and straightforward to me, yet my background is purely experimental and I cannot judge the model in detail.

Our response: The computational model is indeed straightforward, and is based on a set of C++ codes that are OpenSource and those with a computational training have tested it in multiple studies both by us and other labs.

- In my view, the most important limitation of the manuscript is its lack of thorough experimental data to support the claims made by the authors. In its current state, the manuscript seems rather preliminary and I see the need for significant additional experimental evidence.

Our response: We plan to take the reviewers criticism on board and perform new experiments, analyses and simulations to address this gap of additional experiments. These experiments we believe will go to strengthen the manuscript, but not fundamentally alter the result.

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

-Summary:

*This manuscript reports experimental in vitro gliding assays demonstrating bending oscillations when single microtubules are anchored at their plus end and compressed beyond a buckling threshold by dynein molecular motors immobilized on a solid substrate. Together with numerical simulations based on the well-established Cytosim software, the authors identify three main classes of motile behavior under the control of microtubule length and motor density: aperiodic fluctuations (flapping), periodic beating with bending traveling waves over at least part of the filament length, and looping behaviors where the microtubule can curl on itself near its free tip. The authors claim that these movements are reminiscent of the beating movements of eukaryotic cilia and flagella and may provide useful information of the mechanism underlying the oscillatory instability. *

Our response: We are grateful to the reviewer for a careful reading and have in the following sections outlined our plan for revision in response to the specific comments.

*- Major comments: *

1. The observed oscillations show only a few cycles (up to only 4, but often 2-3 (Fig. 1-2)) and are in addition very noisy. Oscillations thus appear to happen only transiently, i.e. do not show a dynamic steady state on timescale much larger than the oscillation period. Demonstrating the emergence of true (and stable) regular oscillations thus remains a challenge, in contrast to the authors' claim. The large variability of behavior from filament to filament (as seen in SV3), as well as in a single filament over time, also makes it difficult to achieve a robust quantitative description of these movements (see below).

Our response: We have observed at times 4 and at times more cycles but we believe this is limited by the fact that mechanical pulling on the streptavidin-biotin linkage could result in occasional detachment of the filament from the surface. Stable oscillations of the form that the reviewer is pointing to may not emerge due to practical challenges and may require an alternative experiment such as optical tweezer to clamp the filament for a longer period. This is currently beyond the scope of the study, but could be attempted in future.

Regarding the variability, we are aiming to analyze more data that has already been recorded and is also being acquired. These additional datapoints will allow for more representative statistics. The variability should tell us more about the nature of the system. We will estimate frequency of oscillations as a parameter for comparison along with our order parameter (span). This is similar to the comment by reviewer #2.

2. Overall, the amount of experimental control seems relatively limited, for there is systematic variation of microtubule length (free or pinned) and only two motor densities have been explored.

Our response: We will address this shortcoming by performing more experiments, with a few more motor densities of intermediate value. This will be supplemented with additional data analysis.

• *One wonders why the motor density has not been more extensively varied and what determines the range of densities that can be achieved. What happens if the density gets larger than 50/µm^2? Do the filaments fail to remain anchored? Is buckling still permitted at high motor density? *

Our response: The range of densities are obtained after the experiment, since this is not a patterning system. At times the density is either too low, and the filaments do not beat, or too high and they detach. This results in only two reported densities, less than perhaps desirable as pointed out by the reviewer. Now that we know what densities work, we aim for a fine-grained scan in the same range expected to produce regular oscillations.

We will titrate the motors to obtain intermediate densities in the range that we have already found to result in stable oscillations with between 4-5 periods and hope to address this question.

• *Important fundamental issues remain here unfortunately untouched in experiments and are also only qualitatively discussed in simulations (bottom of p11 and Fig. 4), namely the dependence of the frequency and wavelength of wave-like beating as a function of motor density and microtubule length. These limitations result from a lack of control over the microtubule lengths and that only two motor densities have been tested. Using the natural variability in length of the anchored filaments may be potentially used to study length effects but then a relatively large amount of data will be required to reliably conclude that filaments ensembles of different mean lengths reliably show different behaviors. Similarly, I do not see where in the data one can see that increasing motor density actually controls the oscillation frequency, as concluded from simulation data (but not analyzed quantitatively). *

Our response: We plan to systematically analyze the frequency, which we have already demonstrated we can measure. The dependence on MT length and density will be tested and added as additional data. We will perform experiments with more motor densities to address that aspect too. We will also run additional simulations and compare outputs. This will help to address the comment and is in line with suggestions by the other reviewers too.

3. The authors repeatedly claim that the movements they observe are "flagella-like". However, the comparison remains vague as there is no quantitative assessment of the similarity or dissimilarity between the movements observed here and biological beating of flagella or cilia (e.g. using data in Riedel-Kruse et al HSFP Journal 2007. DOI:10.2976/1.2773861 as a reference).

Our response: We have compared frequency of oscillations from previous literature but find them to be extremely disparate – by a factor of 1,000. We will use the suggested references to find geometric properties that could test our claim of flagella-like in terms either of waveforms, symmetry of beating or the dynamics or tip-behavior.

• *What does it mean to resemble flagellar beating? It would be desirable to be more explicit/quantitative and not be ashamed to point to differences (could be event more instructive) as well as to similarities. Note that oscillations of the tangent angle in flagella of the bull sperm are nearly sinusoidal, and are thus smooth, with no snaps (Riedel-Kruse et al HSFP 2007), thus challenging the claimed resemblance between bending oscillations in this work and the flagellar beat. *

Our response: This is similar to the previous point. We agree that a quantitative comparison between the dynamics we observe of single filaments and of bonafide flagella, could strengthen the findings of this manuscript. We will use multiple metrics such as the tangent angle-with time of the free end, and the average angle along the flagella (as reported by Riedel-Kruse et al.) to make a more concrete comparison.

• *In my opinion, the authors should tone done the resemblance of their system with cilia and flagella and be much more quantitative about the detailed features of the observed movements in their in-vitro assay. *

Our response: We will take the reviewers comment on board and discuss the work in the absence of the flagellar connection since indeed there is no direct link so far- our comparison with flagella-like systems will be moved to the discussion section with a qualitative comparison of waveforms as this reviewer and others have suggested.

• *In the present gliding assay, motors produce compressive tangential forces on the microtubule, which can result in buckling and thus in an elastic load applied by the filament to the motor with a component perpendicular to the filament. Instead, flagellar motors produce force dipoles that result in neighboring-filament sliding which is then converted in bending of the filament bundle as a result of elastic constrains. Symmetries of the problem thus seem very different. It is also worth noting that many (but not all) models of the flagellar beat actually assume a constant inter-filament distance so that there is no effective normal force acting on the motors to detach them, yet faithfully reproduce beating waveforms (e.g. Camalet and Jülicher New J of Phys (2000) DOI: 10.1088/1367-2630/2/1/324; Riedel-Kruse et al HSFP J (2010)). More generally, whether the present study provides any useful information to inform our current understanding of the flagellar beat is not clear to me and the authors' claim that it may be the case is not motivated enough. Accordingly, the statement (P19) "qualitative transitions (...) expected from not just the minimal but even the potentially complex flagellum" is not justified. *

Our response: This distinction will be more elaborately discussed in the revised discussions section and similar to the previous point, we will avoid reference to flagella-like behavior.

4. I could not find a detailed statistical account of the total number of filaments that was used for the paper, how many fell in the four classes of movement (swiveling, fluctuations, beating, and looping) identified by the authors, and whether the population in each class could actually be controlled experimentally, e.g. by varying motor density or microtubule length. This gave the unfortunate impression that the conclusions were based on cherry picking, which is troublesome considering the large variability in behavior between filaments and the ambition of the authors to provide a state diagram of the dynamics (Fig. 7). To reach clear conclusions, one parameter must be changed while the others remain fixed. For instance, to discuss the effects of the pinned length, one would like to fix the total microtubule length (but then the free length varies) or vary the pinned length with constant free length (thus changing the total microtubule length). I understand that this might be difficult (in experiments), but the authors should then acknowledge these limitations and mitigate their conclusions. In principle, if the yield of the experiment (number of anchored filaments per slide) were sufficient, one could to address these issues by classifying the filaments in ensembles of a given properties (e.g. same total length by variable pinned length). To reach this goal, there is a need to obtain a sufficiently large quantity of data. The reader gets an estimate on the order of 10 usable filaments per slide (video SV3 and inset in Fig. 2D), with only a few replicates (4 experiments at 46/µm^2 and 2 experiments at 27/µm^2). The authors talk about "representative filaments" throughout the text but there is no detail about the ensemble of filaments that show a given behavior and the number of filaments that are used to reach a given conclusion is not given. Length distributions for the free and pined ends of the microtubules, for the maximal amplitude of tangent-angle oscillations, and other measures that characterize the microtubule movements (curvature, wave speed) ought to be given, provided that enough data has been collected to compute reliable ensemble averages.

Our response: For now we have only considered the average behavior with the dynamics observed from multiple fields of view, combined in terms of MT lengths and motor densities. Since Fig. 7 was meant to be representative and therefore a qualitative comparison with simulation predictions, replicates were not added. However, in response to reviewer’s question, we will analyze more data and add it in the supplementary material, in order to support the statistical validity of our claims- that are not based on purely selective evidence.

*5. The effect of motor density on beating properties, in particular frequency, is discussed in simulations but not clearly demonstrated in experiments. One cannot conclude that experiments confirm the prediction of the theory in this respect. *

Our response: Currently we have used a novel metric for the type of oscillation and pattern, the span-parameter (S). However, this was meant to capture large qualitative changes observed in experiment and simulation in terms of patterns.

In response to this comment, we will also analyze the dominant frequency of filaments using FFT on the tip-angles from multiple conditions of MT length and motor density. The scaling of frequency with length and motor density will be compared to simulation predictions. The comparison will then allow an additional quantitative comparison between experiment and simulation.

*- Minor comments: *

6. More extensive quantitative analysis of the waveform of oscillation (noisy sinusoid vs. sawtooth or relaxation oscillations?) and bending wave propagation (speed and curvature vs position along the filament) is needed. In particular, it is claimed that the filaments "snap" and thus evince a "recovery stroke" (e.g. p7). I agree that snaps are evident in some of the videos, and are expected at low motor density. However, I would expect the movements to get smoother at higher motor density, as shown in simulations (looping regime). In any case, one could use the analysis of the tip or (better) tangent angle as a function of time to assess whether 'snaps' indeed occur; due to noise, snapping behavior is not so clear in the data provided in Fig. 1D-E.

Our response: We agree with the reviewer that “snap-back” movement arising from potentially low motor density scenarios changes when the motor density is increased to a more smooth motion. We have observed this, and will characterize it quantitatively to make this point more clear. The tip-dynamics will be analyzed for velocity and symmetry to make this point more apparent.

*7. Because the tips of the microtubules are "sticky" due to their biotinylated tips, I wonder whether the histogram of gliding velocity of the microtubules that are not anchored is modified, i.e shifted toward lower velocities, as compared to that of bare gliding microtubules. This is assuming that a majority of the microtubules are equipped with biotinylated "heads"; this information ought to be provided in the Methods if, as the author claim, the biotinylated tips can be visualized. Analysis of gliding velocities (e.g. in video SV3) could potentially reveal the enhanced interaction between the microtubules and the surface. *

Our response: We will analyze the instantaneous gliding velocity and test the hypothesis that some filaments may be transiently immobile, while others may move unhindered at typical gliding assay velocities (50 to 80 nm/s).

*8. Demonstrating that the anchoring strategy has actually improved the chance to anchor a microtubule, as compared to random anchoring to surface defects that occur naturally in gliding assays, would be welcome. *

Our response: We will analyze the frequency histogram of gliding assay velocities and compare them to the filament-oscillation scenario with biotinylated filaments. We expect to see a zero-velocity mode in the clamped filament scenario and only transient (and therefore less frequent) pinned or clamped filaments. This is already our qualitative observation but we will seek to quantify it.

*9. The simulations should be analyzed more quantitatively and extensively to study how motor density and microtubule length affect the wavelength and frequency of oscillations in the wave-like beating regime, going beyond what can be achieved experimentally. In particular, one could compute the speed of the bending waves, asses how it varies during wave progression from base to tip of the microtubule, describe the increase in the magnitude of tangent-angle and curvature oscillation as a function of curvilinear abscissa. *

Our response: We have now analyzed the frequency and amplitude of filament oscillations in simulations. This will in the next step be used to look for trends as a function of MT length and motor density. We hope indeed to look beyond what experimentally achievable ranges might be, including measuring the propagation of the bending wave along the contour as suggested by the reviewer.

*- Suggestions to help improving the presentation: *

*1. First section of the results (p5-7): this section is full of methological details that get in the way of the description of the actual result (Fig. 1). I would suggest moving these details (e.g. there is not need here to explain how the motors are attached to the substrate, which you use cytoplasmic yeast dynein, and other details). *

Our response: We will rewrite the manuscript to improve the clarity and move the methods to the section dedicated to the methodology.

*2. The top of P9 could also be moved to Discussion section. *

Our response: We will move the page 9 text referred to into the discussion.

*3. P12-13: I also find that the Results section mixes results with discussion, which is not very effective. I would again move elements of discussion (here associated with bending energies) to the Discussion section and focus on results only. *

Our response: We have done so due perhaps to a requirement from an earlier round of reviews. However, we will be happy to separate results from discussion- for example the reference to bending energies.

*4. Throughout the result section: Move any comparison to actual flagellar dynamics to a dedicated section in Discussion. *

Our response: The flagellar discussion will be moved out of the results section entirely unless we invoke the analysis of bonafide flagella.

5. P12: doesn't the increase of the clamped length reduce the length of the free length, moving in the state diagram toward regions of shorter filaments. One wonders whether the clamped length really matter as long as the filament is clamped near the plus end. I would naively expect that it is the free-filament length that maters rather than the total length or the faction of the filament that is clamped.

Our response: We agree with the reviewer with one caveat- filaments pinned at one end (point pinning) are distinct from those with long segments clamped. However, the reviewer is correct in pointing out cases where filaments have a substantial clamp, the free length is more important. We will revise our figures and results section to clarify this.

*6. Figure 4: this figure shows very interesting simulation data that, in my opinion could be much more extensively studied. In particular, one could plot the oscillation frequency, the bending-wave speed, and wavelength as a function of the filament length and the motor density. Also, to characterize the beating waveform more in detail, it would be worth computing how the magnitude of tangent-angle oscillation increases with the curvilinear abscissa for representative examples of waveforms in the three regimes (see again in Riedel-Kruse et al HSFP 2007. DOI: 10.2976/1.2773861 or Pochitaloff et al Nat Phys 2022 DOI: 10.1038/s41567-022-01688-8). *

Our response: We have performed fourier series analysis to obtain dominant frequencies. This will indeed be applied to the simulations in Fig. 4 in order to examine the rich dynamics, as well as provide a point of quantitative comparison to exepriments.

*7. Figure 5: the way to display the data in A-B (simulations) and C-D (experiments) does not allow for an easy comparison between simulations and experiments. I would use beating patterns and kymographs of the tangent angle for both. *

Our response: We are in the process of revising Fig. 5 in order to examine the effect of free MT length on oscillations and will put experimental and simulation analyses that match each other in the nature of the analysis. The analysis itself will be elaborated to include aspects such as average tangent angle as a function of arc-length (Riedel-Kruse et al., 2007) along with frequency.

*8. Figure 6: the way to present the experimental beating patterns is no so clear (thick colored lines). I would recommend showing black lines resulting from automatic tracking of the microtubule. *

Our response: The data in Fig. 6 is raw data projected in order to provide a picture within the limits of magnification. In order to address this comment we will project the tracked contour of the filament and that will result in a finer and better resolved image.

*9. Legend of Fig. S1: the panels (D) and (E) of the figure are not called properly. *

Our response: We will rectify the issue of sub-figure callouts.

*10. Fig. S3: use the same scale in the different panels of (a) and (b) to allow for an easier comparison. It would also be nice to show videos of the simulated motion. *

Our response: The current differences were in order for visual clarity and the modified axis values are mentioned. We will revise Fig. S3 simulation outputs where filaments are projected on the same axis for consistency.

*11. Fig. S4: Hard to read, in particular the motors are not visible. Would be better to have the patterns in black on a white background. The panels look like screen shots. *

Our response: The unbound motors have been deliberately made invisible for clarity. We can provide a figure update with the motors made visible again.

*12. Fig.S5: indicate in the title that this figure deals with results of simulations. The legend refers to color bars but the figure is in grey scale. *

Our response: Colorbar is indeed in grayscale. The legend entry will be modified to read “grayscale bar”.

*Reviewer #3 (Significance (Required)): *

*The motile phenomena reported here are qualitatively already well known in the field. Indeed, anyone who has performed a gliding assay, with microtubules or actin filaments has probably seen undulating or spiraling filaments accidentally anchored on surface defects. Accordingly, the topic has already been somewhat adressed in previous publications (e.g. Bourdieu et al Phys Rev Lett 1995; Sekimoto et al Phys rev Lett 1995; Vilfan et al Nanoletter 2019). As a matter of fact, microtubules anchored on defects in standard gliding assay can show oscillations very similar to those shown here. However, the lack of control over filament anchoring has precluded a systematic experimental study of the oscillatory filament dynamics. It is worth noting that ther bottom-up approaches have used filament bundles instead of single filaments, either with microtubules and kinesin motors (Sanchez et al Science 2011) or actin filaments and myosin motors (Pochitaloff et al Nature Phys 2022). These assays evince more regular oscillations (over tens of cycles) and waveforms that more closely resemble those of eukaryotic flagella than reported here. *

Our response: We agree with this summary of our work, and will highlight the possible reasons why it differs from the work of Pochitaloff et al.

*Here, the authors have developed an experimental strategy to increase the chance of anchoring single filaments' plus end to the substrate, potentially allowing for more control of the experimental conditions that lead to the emergence of oscillations (but see my criticisms above). Anchoring is made more likely, because short segments of biotinylated tubulin are added to the end of bare microtubules to make them stick to the substrate, which has been functionalized with streptavidin. A similar protocol had been reported before in the literature to study buckling of single microtubules by single kinesin motors (Gittes et al Biophys J 1996), but is here used at larger motor densities on the substrate. There is unfortunately no quantification of the success of the approach. *

Our response: We propose to perform more experiments and analyze the data more quantitatively using multiple measures described in the literature and cited by this reviewer. We believe these changes will adequately address the concerns.

*The comparison of the experimental data to Cytosim simulations is, to my knowledge, novel and a clear asset of the work, although this comparison could be more effective, as detailed above. *

Our response: We will add a more complete quantitative comparison to supplement the already provided qualitative comparison to address the comments.

*The emergence of periodic wave-like beating oscillations in motor-filament systems is a classical problem in biophysics. This problem is particularly relevant in the context of eukaryotic cilia and flagellar beating in biology. The audience for the present work is thus potentially broad, although the simplistic and artificial nature of the in-vitro system, with only one microtubule, will probably appeal more to biophysicists and theoretical physicists than biologists. *

Our response: We appreciate the effort of this reviewer to evaluate our work. We however believe that the relevance of this work could extend beyond purely biophysics and theoretical physics as claimed by the reviewer.

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Referee #3

Evidence, reproducibility and clarity

Summary:

This manuscript reports experimental in vitro gliding assays demonstrating bending oscillations when single microtubules are anchored at their plus end and compressed beyond a buckling threshold by dynein molecular motors immobilized on a solid substrate. Together with numerical simulations based on the well-established Cytosim software, the authors identify three main classes of motile behavior under the control of microtubule length and motor density: aperiodic fluctuations (flapping), periodic beating with bending traveling waves over at least part of the filament length, and looping behaviors where the microtubule can curl on itself near its free tip. The authors claim that these movements are reminiscent of the beating movements of eukaryotic cilia and flagella and may provide useful information of the mechanism underlying the oscillatory instability.

Major comments:

1. The observed oscillations show only a few cycles (up to only 4, but often 2-3 (Fig. 1-2)) and are in addition very noisy. Oscillations thus appear to happen only transiently, i.e. do not show a dynamic steady state on timescale much larger than the oscillation period. Demonstrating the emergence of true (and stable) regular oscillations thus remains a challenge, in contrast to the authors' claim. The large variability of behavior from filament to filament (as seen in SV3), as well as in a single filament over time, also makes it difficult to achieve a robust quantitative description of these movements (see below).

2. Overall, the amount of experimental control seems relatively limited, for there is systematic variation of microtubule length (free or pinned) and only two motor densities have been explored.

a) One wonders why the motor density has not been more extensively varied and what determines the range of densities that can be achieved. What happens if the density gets larger than 50/µm^2? Do the filaments fail to remain anchored? Is buckling still permitted at high motor density?

b) Important fundamental issues remain here unfortunately untouched in experiments and are also only qualitatively discussed in simulations (bottom of p11 and Fig. 4), namely the dependence of the frequency and wavelength of wave-like beating as a function of motor density and microtubule length. These limitations result from a lack of control over the microtubule lengths and that only two motor densities have been tested. Using the natural variability in length of the anchored filaments may be potentially used to study length effects but then a relatively large amount of data will be required to reliably conclude that filaments ensembles of different mean lengths reliably show different behaviors. Similarly, I do not see where in the data one can see that increasing motor density actually controls the oscillation frequency, as concluded from simulation data (but not analyzed quantitatively).

1. The authors repeatedly claim that the movements they observe are "flagella-like". However, the comparison remains vague as there is no quantitative assessment of the similarity or dissimilarity between the movements observed here and biological beating of flagella or cilia (e.g. using data in Riedel-Kruse et al HSFP Journal 2007. DOI: 10.2976/1.2773861 as a reference).

a) What does it mean to resemble flagellar beating? It would be desirable to be more explicit/quantitative and not be ashamed to point to differences (could be event more instructive) as well as to similarities. Note that oscillations of the tangent angle in flagella of the bull sperm are nearly sinusoidal, and are thus smooth, with no snaps (Riedel-Kruse et al HSFP 2007), thus challenging the claimed resemblance between bending oscillations in this work and the flagellar beat.

b) In my opinion, the authors should tone done the resemblance of their system with cilia and flagella and be much more quantitative about the detailed features of the observed movements in their in-vitro assay.

c) In the present gliding assay, motors produce compressive tangential forces on the microtubule, which can result in buckling and thus in an elastic load applied by the filament to the motor with a component perpendicular to the filament. Instead, flagellar motors produce force dipoles that result in neighboring-filament sliding which is then converted in bending of the filament bundle as a result of elastic constrains. Symmetries of the problem thus seem very different. It is also worth noting that many (but not all) models of the flagellar beat actually assume a constant inter-filament distance so that there is no effective normal force acting on the motors to detach them, yet faithfully reproduce beating waveforms (e.g. Camalet and Jülicher New J of Phys (2000) DOI: 10.1088/1367-2630/2/1/324; Riedel-Kruse et al HSFP J (2010)). More generally, whether the present study provides any useful information to inform our current understanding of the flagellar beat is not clear to me and the authors' claim that it may be the case is not motivated enough. Accordingly, the statement (P19) "qualitative transitions (...) expected from not just the minimal but even the potentially complex flagellum" is not justified.

1. I could not find a detailed statistical account of the total number of filaments that was used for the paper, how many fell in the four classes of movement (swiveling, fluctuations, beating, and looping) identified by the authors, and whether the population in each class could actually be controlled experimentally, e.g. by varying motor density or microtubule length. This gave the unfortunate impression that the conclusions were based on cherry picking, which is troublesome considering the large variability in behavior between filaments and the ambition of the authors to provide a state diagram of the dynamics (Fig. 7). To reach clear conclusions, one parameter must be changed while the others remain fixed. For instance, to discuss the effects of the pinned length, one would like to fix the total microtubule length (but then the free length varies) or vary the pinned length with constant free length (thus changing the total microtubule length). I understand that this might be difficult (in experiments), but the authors should then acknowledge these limitations and mitigate their conclusions. In principle, if the yield of the experiment (number of anchored filaments per slide) were sufficient, one could to address these issues by classifying the filaments in ensembles of a given properties (e.g. same total length by variable pinned length). To reach this goal, there is a need to obtain a sufficiently large quantity of data. The reader gets an estimate on the order of 10 usable filaments per slide (video SV3 and inset in Fig. 2D), with only a few replicates (4 experiments at 46/µm^2 and 2 experiments at 27/µm^2). The authors talk about "representative filaments" throughout the text but there is no detail about the ensemble of filaments that show a given behavior and the number of filaments that are used to reach a given conclusion is not given. Length distributions for the free and pined ends of the microtubules, for the maximal amplitude of tangent-angle oscillations, and other measures that characterize the microtubule movements (curvature, wave speed) ought to be given, provided that enough data has been collected to compute reliable ensemble averages.

2. The effect of motor density on beating properties, in particular frequency, is discussed in simulations but not clearly demonstrated in experiments. One cannot conclude that experiments confirm the prediction of the theory in this respect.

Minor comments:

1. More extensive quantitative analysis of the waveform of oscillation (noisy sinusoid vs. sawtooth or relaxation oscillations?) and bending wave propagation (speed and curvature vs position along the filament) is needed. In particular, it is claimed that the filaments "snap" and thus evince a "recovery stroke" (e.g. p7). I agree that snaps are evident in some of the videos, and are expected at low motor density. However, I would expect the movements to get smoother at higher motor density, as shown in simulations (looping regime). In any case, one could use the analysis of the tip or (better) tangent angle as a function of time to assess whether 'snaps' indeed occur; due to noise, snapping behavior is not so clear in the data provided in Fig. 1D-E.

2. Because the tips of the microtubules are "sticky" due to their biotinylated tips, I wonder whether the histogram of gliding velocity of the microtubules that are not anchored is modified, i.e shifted toward lower velocities, as compared to that of bare gliding microtubules. This is assuming that a majority of the microtubules are equipped with biotinylated "heads"; this information ought to be provided in the Methods if, as the author claim, the biotinylated tips can be visualized. Analysis of gliding velocities (e.g. in video SV3) could potentially reveal the enhanced interaction between the microtubules and the surface.

3. Demonstrating that the anchoring strategy has actually improved the chance to anchor a microtubule, as compared to random anchoring to surface defects that occur naturally in gliding assays, would be welcome.

4. The simulations should be analyzed more quantitatively and extensively to study how motor density and microtubule length affect the wavelength and frequency of oscillations in the wave-like beating regime, going beyond what can be achieved experimentally. In particular, one could compute the speed of the bending waves, asses how it varies during wave progression from base to tip of the microtubule, describe the increase in the magnitude of tangent-angle and curvature oscillation as a function of curvilinear abscissa.

Suggestions to help improving the presentation:

1. First section of the results (p5-7): this section is full of methological details that get in the way of the description of the actual result (Fig. 1). I would suggest moving these details (e.g. there is not need here to explain how the motors are attached to the substrate, which you use cytoplasmic yeast dynein, and other details).

2. The top of P9 could also be moved to Discussion section.

3. P12-13: I also find that the Results section mixes results with discussion, which is not very effective. I would again move elements of discussion (here associated with bending energies) to the Discussion section and focus on results only.

4. Throughout the result section: Move any comparison to actual flagellar dynamics to a dedicated section in Discussion.

5. P12: doesn't the increase of the clamped length reduce the length of the free length, moving in the state diagram toward regions of shorter filaments. One wonders whether the clamped length really matter as long as the filament is clamped near the plus end. I would naively expect that it is the free-filament length that maters rather than the total length or the faction of the filament that is clamped.

6. Figure 4: this figure shows very interesting simulation data that, in my opinion could be much more extensively studied. In particular, one could plot the oscillation frequency, the bending-wave speed, and wavelength as a function of the filament length and the motor density. Also, to characterize the beating waveform more in detail, it would be worth computing how the magnitude of tangent-angle oscillation increases with the curvilinear abscissa for representative examples of waveforms in the three regimes (see again in Riedel-Kruse et al HSFP 2007. DOI: 10.2976/1.2773861 or Pochitaloff et al Nat Phys 2022 DOI: 10.1038/s41567-022-01688-8).

7. Figure 5: the way to display the data in A-B (simulations) and C-D (experiments) does not allow for an easy comparison between simulations and experiments. I would use beating patterns and kymographs of the tangent angle for both.

8. Figure 6: the way to present the experimental beating patterns is no so clear (thick colored lines). I would recommend showing black lines resulting from automatic tracking of the microtubule.

9. Legend of Fig. S1: the panels (D) and € of the figure are not called properly.

10. Fig. S3: use the same scale in the different panels of (a) and (b) to allow for an easier comparison. It would also be nice to show videos of the simulated motion.

11. Fig. S4: Hard to read, in particular the motors are not visible. Would be better to have the patterns in black on a white background. The panels look like screen shots.

12. Fig.S5: indicate in the title that this figure deals with results of simulations. The legend refers to color bars but the figure is in grey scale.

Significance

• The motile phenomena reported here are qualitatively already well known in the field. Indeed, anyone who has performed a gliding assay, with microtubules or actin filaments has probably seen undulating or spiraling filaments accidentally anchored on surface defects. Accordingly, the topic has already been somewhat adressed in previous publications (e.g. Bourdieu et al Phys Rev Lett 1995; Sekimoto et al Phys rev Lett 1995; Vilfan et al Nanoletter 2019). As a matter of fact, microtubules anchored on defects in standard gliding assay can show oscillations very similar to those shown here. However, the lack of control over filament anchoring has precluded a systematic experimental study of the oscillatory filament dynamics. It is worth noting that ther bottom-up approaches have used filament bundles instead of single filaments, either with microtubules and kinesin motors (Sanchez et al Science 2011) or actin filaments and myosin motors (Pochitaloff et al Nature Phys 2022). These assays evince more regular oscillations (over tens of cycles) and waveforms that more closely resemble those of eukaryotic flagella than reported here.

• Here, the authors have developed an experimental strategy to increase the chance of anchoring single filaments' plus end to the substrate, potentially allowing for more control of the experimental conditions that lead to the emergence of oscillations (but see my criticisms above). Anchoring is made more likely, because short segments of biotinylated tubulin are added to the end of bare microtubules to make them stick to the substrate, which has been functionalized with streptavidin. A similar protocol had been reported before in the literature to study buckling of single microtubules by single kinesin motors (Gittes et al Biophys J 1996), but is here used at larger motor densities on the substrate. There is unfortunately no quantification of the success of the approach.

• The comparison of the experimental data to Cytosim simulations is, to my knowledge, novel and a clear asset of the work, although this comparison could be more effective, as detailed above.

• The emergence of periodic wave-like beating oscillations in motor-filament systems is a classical problem in biophysics. This problem is particularly relevant in the context of eukaryotic cilia and flagellar beating in biology. The audience for the present work is thus potentially broad, although the simplistic and artificial nature of the in-vitro system, with only one microtubule, will probably appeal more to biophysicists and theoretical physicists than biologists.

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Referee #2

Evidence, reproducibility and clarity

Summary:

The authors use a modified version of conventional gliding assays to induce microtubule bending, buckling, looping and cyclic beating (which they term "flagella-like") via clamping the plus ends of gliding microtubules to the surface. They find that the pattern of motion depends on different factors such as microtubule length and motor density. They build a simple computational model that predicts transitions between microtubule motion patterns depending on these parameters.

Major comments:

• Overall, the experimental data is extremely sparse. As far as I can see, there are only two replicas for the lower motor density. It is not clear to me how the authors define the boundaries in the experimental phase diagram in Fig. 7. To build a phase diagram - where one axis corresponds to the motor density - on just two experiments is not convincing. I would need to see more experiments covering a larger range of motor densities and at least three replica per condition.

• It is not clear to me why the proportion of pinned vs. free microtubule segments should affect the beating pattern. I would expect that the free microtubule segment does not "feel" the length of the clamped segment, if it is indeed fixed all along its length and unable to move / bend. The simulations use only two anchor points at the pinned tip. The segment in between the anchor points bends, which could affect how the free microtubule segment behaves. To support the claim that it is indeed the proportion of the lengths of the pinned vs. free segments and not simply the length of the free segment alone that influence the beating pattern, I would expect to (1) see the corresponding and thoroughly quantified experimental data that verifies this simulation-based prediction. Fig. 5C is based on only three microtubules and it is not clear how long the segments are. (2) the entire pinned segments in the simulation should be fixed. This should also be compared to experimental data, where the lengths of the free segments are the same and only the lengths of the pinned segments vary.

• In relation to my previous comments: I would expect a direct comparison between the simulation-based prediction that the beating pattern changes with microtubule length and motor density in a quantitative manner, where all pinned microtubules observed experimentally are analyzed. The figures are often based on single observations.

• The authors report that the pinned microtubules typically undergo 2-3 cycles of beating. This number is very low, and I am hesitant to call it "flagella-like" cyclic beating. Is this due to the dynein motors being much slower than e.g. kinesis? To confirm this and support the generality claimed by the authors, I would like to see experiments with a different, faster motor. If other motors are not readily available to the authors, this would imply a substantial amount of time and effort though.

• Please perform statistical analysis of the experimental data.

Minor comments:

• Number of replicates and samples should be indicated in the figures.

Significance

• The approach to clamp the plus ends of gliding microtubules in order to induce buckling, bending and beating is elegant and should be easily transferable to other groups who may be interested in this method, since it is straightforward to adapt conventional gliding assays to induce pinning.

• The study could potentially be interesting to an audience studying flagella-like systems. Since the system is simple and based on in vitro components with defined parameters, it could serve as a basis for studying more complex systems or testing the influence of particular proteins associated with flagella. However, I do not see a major advance regarding our understanding of flagella or similar structures based on the manuscript. In combination with the model, I see it majorly as a useful tool, providing methodological advance. It would be desirably to make the computational model available to the public.

• The computational model seems useful and straightforward to me, yet my background is purely experimental and I cannot judge the model in detail.

• In my view, the most important limitation of the manuscript is its lack of thorough experimental data to support the claims made by the authors. In its current state, the manuscript seems rather preliminary and I see the need for significant additional experimental evidence.

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Referee #1

Evidence, reproducibility and clarity

Summary:

This work combines in-vitro experiments and numerical modeling to study the dynamics of microtubules, driven by molecular motors. In this bottom-up approach, molecular motors are immobilized on the surface and microtubule filaments are anchored to the surface from one end. The dynamics results in "beating like" motion of the anchored microtubules. The authors establish a phase diagram of the different dynamical patterns of "beating like" motions by varying the molecular motor density and the length of the microtubule anchored to the surface. They use a numerical framework that captures the observed patterns.

Major comments:

Overall the experiments and results are well described and claims are supported by the data. Both experimental and numerical methods are presented in a way that they can be reproduced.

Minor comments:

A key feature of beating cilia is the asymmetry of the beat pattern (fast stroke and slow recovery). It might be interesting to use the kymographs or the Phy vs time analysis to see whether or not this feature exists in this simplified experimental model.

Also, the beating frequency is very low (mHz) compared to real cilia/flagella (~Hz). Would it be possible to use the model to predict which parameter would need to be tuned to reach more physiologically relevant beating frequencies ?

Significance

This study is part of the field of in-vitro reconstitution, from a minimal set of components, that aims to reproduce a biological function to identify and understand the minimal physical/biophysical mechanisms underlying a function. This study might be of interest for the people who address questions of the self-organization of cytoskeletal elements in minimal systems.

The main limitation of this study relies on the claim of reproducing a flagella-like motion. Indeed, the frequency of the described oscillations is in the mHz range while the frequency of cilia is in the range of few Hz to tens of Hz. This suggests that the mechanism at play in such a reconstituted system is not the one that drives beating in real cilia/flagella. Yet, this limitation also applies to other studies in the field (Vilfan et al. 1999, Guido et al. 2022 ...).

My second concern is that the added value with regards to state of art is not clearly explicit. I'm thinking about the work of the Isabelle Guido's team where they have more complex reconstituted systems (a pair of 2 microtubules); or the work of Pascal Martin's lab where the design of the system allows to capture more complex mechanisms such as myosin density waves, which result in frequency beat of 0.1Hz.

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Reply to the reviewers

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

The manuscript describes that simultaneous inhibition of LOXL2 and BRD4 reduces proliferation of TNBC in vitro and reduces growth in vivo.

This observation is followed by extensive mechanistic studies that suggest physical interaction between LOXL2 and short isoform of BRD4-MED1. Inferences from Chip-seq analyses suggest that this interaction is involved in regulation of multiple transcriptional programs. Authors focus on differential activation of DREAM complex, to claim that this interaction "is fundamental for proliferation of TNBC". The manuscript is very well written and mechanistic inferences are based on a set of sophisticated epigenetic analyses and bioinformatical inferences. The phenotypic effects from LoxL2 inhibition by itself, or in combination with BRD4 inhibition are relatively modest. These modest effects, as well as many of the reported changes in gene expression are clearly inconsistent with the frequently used adjectives as "dramatic", "fundamental", "deeply affected", "drastically hampered" etc. Given the modest phenotypic effects, many of the key claims and conclusions are not supported by the data.

We thank the reviewer for appreciating our work, defining the manuscript as well-written, and saying that it comprises extensive mechanistic studies as well as sophisticated epigenetic analysis.

We apologize if some of our statements seemed exaggerated. In this revised version, we revisited some of our conclusion to moderate them.

Moreover, we took the reviewer's criticism as an opportunity to strengthen our findings. In the revised version of the manuscript, we included an additional TNBC PDX (PDX-127), and results from this experiment clearly reinforce our claims (Fig. 6D and Fig. EV9E-F). In this new in vivo experiment, we selected a PDX model in which the expression of BRD4L is not detectable, while BRD4S is clearly expressed. Therefore, the treatment with JQ1 would specifically affect the activity of BRD4S, making the treatment selective. Additionally, we reduced by half the dose of JQ1 administrated to limit the effect of BRD4S inhibition alone on tumor growth. The combinatorial treatment (JQ1+PXS) induced a clear superior effect in this setting as compared with single-agent treatments. In addition to this, we discarded that the observed growth reduction is not the result of the sole inhibition of LOXL2, which could affect FAK/Src activity or extracellular Collagen crosslinking. In conclusion, our data show that the combinatorial inhibition of LOXL2 and BRD4S is effective in reducing tumor proliferation in TNBC in vivo models, independently of the inhibition of BRD4S and of other pathways known to be regulated by LOXL2.

Specifically:

1) It is unclear why authors generalize their conclusions to TNBC. Figure 1B demonstrates synergy for 1/3 cell lines, which is chosen for the follow up study. Even for MDA231, the synergy is confined to low concentrations of BRD4i (S1c). While MDA231 cell line is frequently used in experimental studies of TNBC, it is quite dissimilar to majority of clinical TNBC, and contains mutant RAS, which is rare in this disease.

The synergistic effect is observed in MDA-MB-231 cells because only this cell line expresses both BRD4S and LOXL2. Indeed, in Fig. 1C we show that MDA-MB-468 cells do not express LOXL2, while BT549 only express minimal BRD4 levels.

To corroborate this hypothesis, in the revised version of the manuscript we added:

1. A new cell line (Cal51) expressing the same LOXL2 and BRD4 levels (Fig. EV8C) but showing greater resistance to JQ1 than MDA-MB-231 (Fig. EV8D). Also, in this cell line, we could show that the combinatorial treatment had a superior effect on cell viability than the single agents’ treatment (Fig. EV8E).
2. A western blot panel of different TNBC PDXs shows that the majority of them express medium to high levels of both BRD4S and LOXL2 proteins, as is the case of MDA-MB-231 (Fig. EV9E) and Cal51 (Fig. EV8C). This result suggests that the combinatorial treatment could be used in the majority of TNBC patients as they are expected to express both BRD4S and LOXL2.
3. Finally, as explained above, we performed another in vivo choosing a PDX that expresses BRD4S (but not BRD4L) and LOXL2 (PDX-127) (Fig. 6D and Fig. EV9E-F). Also, in this new model, we could observe that the combinatorial inhibition had a superior effect than single treatments.

   2) In vivo, the effect appears to be modest even in the MDA231 model, selected for evidence of synergy in vitro. In vivo, the combination appears to have an additive effect. Tumor growth rates are reduced, but no shrinkage is occurring. In the PDX model, LOXL2i does not have an effect as a monotherapy, while modestly enhancing the impact of BRD4i. These results are at odds with the claim of the interaction being fundamental for proliferation.

We agree with the reviewer that the combinatorial inhibition appears to have an additive effect in vivo using the MDA-MB-231 model.

1. For that reason, we have now performed the in vivo PDX experiment mentioned above (PDX-127; Fig. 6D and Fig. EV9E-F) in which we decreased the dose of JQ1 by half to avoid strong tumor growth effect due to BRD4 inhibition alone. In this new experiment, the synergistic effect is evident. While single-agent treatment showed a very moderate effect (0% or 20% tumor growth reduction for LOXL2 and JQ1, respectively), the combinatorial treatment showed a 50% reduction in tumor volume, further supporting our conclusions.
2. We also performed either BRD4 or MED1 pull-down experiments in the presence of PXS and JQ1. We show that upon PXS treatment, the interaction between LOXL2 and BRD4S is maintained while the interaction with MED1 is reduced (Fig. 5A-C). However, in the presence of JQ1, the interaction between LOXL2 and MED1 is maintained while BRD4S-LOXL2 and BRD4S-MED1 interactions are impaired (Fig. 5D-F). These new results explain why monotherapy does not have a sufficient effect in vivo and set the rationale for the use of the combinatorial treatment. We believe that these new results corroborate our initial findings and we hope to have been able to satisfy the reviewer comments.

3) No analysis of cell proliferation was shown in vivo. Authors should have performed BrdU or KI67 staining to support the claim. For in vitro analyses, authors also used indirect assays for proliferation. PI staining by itself does not have sufficient resolution to clearly capture modest effects that authors demonstrate. BrdU-PI double staining would have been much more useful.

We appreciate the reviewer’s comment. In the revised manuscript we have added Ki67 and H3S10p staining in the tumor samples for the new in vivo PDX experiment (Fig. 6E and Fig. EV10A-C). We show that the combinatorial treatment significantly induces a reduction of both proliferation markers, which is in agreement with a reduced tumor volume. Regarding the in vitro analysis, we did not only use PI staining to show a reduced proliferation state but also H3S10p staining (Fig. 4B) and an SLBP1 fluorescent reporter MDA-MB-231 cell line (Fig. 4D, Fig. EV6B, E, and Movie EV). In the revised version of the manuscript, we included a new FACS-PI analysis (Fig. 4A, C) to better represent the effects we see on the cell cycle.

Minor points:

Dose dependent decrease in phosphorylated H3 is not at all obvious from eyeballing the data in S1A; the only effect that I see is a modest reduction at the highest concentration of the inhibitor. Authors need to quantify the results to support the claim.

We agree with the reviewer and we apologize for the misinterpretation. We have changed the revised manuscript as follows: “The selective LOXL2 inhibitor PXS-538224 (hereafter, PXS) efficiently reduced the levels of oxidized histone H3 (H3K4ox) in MDA-MB-231 cells at 40 μM (Fig. EV6C), indicating an efficient inhibition of LOXL2 catalytic activity in the nucleus.”

Most of breast cancer cell lines are derived from metastatic disease, including pleural effusion, thus the point that because MDA231 cell line is derived from pleural effusion, it is metastatic does not have sufficient logical foundation.

Many publications have shown the high metastatic capacity of MDA-MB-231 (e.g. https://doi.org/10.1016/j.bbabio.2011.04.015, doi: 10.1038/s41467-017-01829-1), which are therefore used as TNBC metastatic model. The scope of the analysis reported in Fig. 6C was just to show whether any of the used treatments could reduce the metastatic capacity of this cell line. We believe we do not overstate the results but just report them as they are.

How is loss of cell-cell junction in vitro consistent with LOXL2 role in modulating ECM? There is no evidence of ECM production in MDA231 in vitro. On the other hand, this loss is associated with EMT.

We thank the reviewer for identifying this mistake. In the revised manuscript we changed the text as follows: “Gene set enrichment analysis (GSEA) revealed that LOXL2 KD induced upregulation of processes involved in cell morphology, secretion, membrane trafficking, and cell differentiation, with cell-cell junction being one of the most significantly affected pathways (Fig. EV5E). These results agree with the role of LOXL2 in regulating epithelial-to-mesenchymal transition, corroborating the high quality of our dataset.”

Reviewer #1 (Significance (Required)):

Discovery and characterization of LOXL2-BRD4 interaction is advancing the ever-deepening understanding of molecular mechanisms of regulation of gene expression. The studies and analyses appear to be sufficiently rigorous and reported with clarity, and the claimed discovery of the biological interaction between LOXL2 and BRD4 is well supported. However, given the magnitude of the reported (rather than claimed) effects of this interaction, and concerns about generalizability of authors conclusions, it is not clear how these results are promising for the development of new therapies in TNBC. Moreover, in contrast to luminal BC, there is no clear evidence for utility of cytostatic drugs in constraining TNBC. Therefore, biological and clinical significance of the authors discovery is unclear and claims in this regard appear to be overblown

We thank the reviewer for stating that our analysis is rigorous and reported with clarity. We really took the criticisms as an opportunity to strengthen our findings, as explained above.

For the newly presented in vivo PDX model, we performed immunohistochemistry of Ki67, H3S10p and Cleaved Caspase 3 to check whether the reduction of tumor volume observed in the combinatorial treatment was a result of a cytotoxic and/or a cytostatic effect (Fig. 6E and Fig. EV10A-C). As shown in the figure, the combination of the two inhibitors induced a superior decrease of Ki67, H3S10p, and a clear increase of Cleaved Caspase 3. Therefore, these new data indicate that the combinatorial treatment does not only have a cytostatic effect but also cytotoxic, suggesting a clinical exploitability for the treatment of TNBC patients.

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

In their study, Pascual-Reguant et al. show that combined inhibition of BRD4 and LOXL2 can synergize to restrict triple-negative breast cancer (TNBC) proliferation. BRD4 and LOXL2 are transcription regulators that can read and write epigenetic information, respectively. The authors employ three distinct breast cancer cell lines and mouse models with cell line-derived xenografts, and they show that combined inhibition of BRD4 and LOXL2 can be superior to single BRD4/LOXL2 inhibition in these model systems. In an attempt to identify a connection between BRD4 and LOXL2, the authors find that the two proteins can bind to each other. The authors performed most of the experiments in the breast cancer cell line MDA-MB-231. To assess the impact of LOXL2-inhibition on transcription, the authors assessed changes of the transcriptome in MDA-MB-231 cells following LOXL2 knockdown. They found that genes related to cell differentiation and morphology were upregulated, while genes related to the cell cycle were downregulated. ChIP-seq data of BRD4 showed that BRD4 can bind to cell cycle gene promoters and that this binding was enhanced upon loss of LOXL2. The authors found that LOXL2 and BRD4 interacted with the transcriptional cell cycle regulators B-MYB, FOXM1, and LIN9, which are components of the MYB-MuvB-FOXM1 (MMB-FOXM1) complex that is known to promote the expression of late cell cycle genes with important functions during mitosis. The authors conclude that LOXL2/BRD4 interact with each other and with the MMB-FOXM1 complex to drive the expression of cell cycle genes and cell proliferations. Vice versa, they conclude that inhibition of LOXL2/BRD4 reduces cell proliferation through inhibiting the expression of cell cycle genes.

Major:

• The data and methods are presented well. The experiments are adequately replicated and analyzed. However, except for the first section, all experiments were performed using only one cell line. It is important to validate key findings in at least a second cell line.

We thank the reviewer for valuing our work.

To address the reviewer’s comment, in the revised manuscript we added an additional cell line (Cal-51), that expresses similar levels of LOXL2 and BRD4 as compared to MDA-MB-231 (Fig. EV8C). Even though this cell line is clearly more resistant to JQ1 than the MDA-MB-231 cell line (Fig. EV8D), the combinatorial treatment is significantly more effective as compared with single agents’ treatment (Fig. EV8E).

Moreover, we have also performed an additional in vivo experiment using another TNBC PDX (PDX-127) that expresses LOXL2 and BRD4S, but not BRD4L. Given that JQ1 can inhibit both BRD4 isoforms, this in vivo system allowed us to demonstrate that the tumor antiproliferative capacity of the combinatorial treatment is due to the simultaneous inhibition of LOXL2 and BRD4S (rather than BRD4S and L) (Fig. 6D and Fig. EV9E-F).

• There appears to be a misunderstanding of the concept of cell cycle-dependent gene regulation by the DREAM complex and its related factors. Early (G1/S) cell cycle genes contain E2F promoter motifs, while late (G2/M) cell cycle genes contain CHR promoter motifs. The DREAM complex can bind both, while RB-E2F and MuvB recognize only E2F and CHR motifs, respectively. B-MYB and FOXM1 bind to MuvB and regulate late cell cycle genes, but they do not bind to early cell cycle genes. Given this concept, the authors' rationale to connect BRD4/LOXL2 through MuvB/B-MYB/FOXM1 with E2F promoter sequences and early cell cycle genes and the subsequent conclusions must be corrected.

We thank the reviewer for their expert explanation. We corrected our conclusion in the revised version of the manuscript following the reviewer’s comment.

• I felt that the suggested functional connection between LOXL2/BRD4 and DREAM is not strongly supported by the authors' data. Figure S6E: A similarity score of Fig. EV6E: We agree with the reviewer that a similarity score of Fig. 4E: We thank the reviewer for this comment. The performed pulldown showed that BRD4S, LOXL2, and MED1 interact with Lin9 and B-Myb, but not with FOXM1, thus FOXM1 itself is an internal negative control of the pulldown. Additionally, BRD4L does not show the same interaction pattern as BRD4S, LOXL2, and MED1, again acting as an internal negative control. We, therefore, believe that the pulldown is properly controlled and that the observed interaction is trustful. We furthermore agree with the reviewer that it would be interesting to characterize the interactions between the DREAM complex and BRD4S, LOXL2, and MED1. However, we believe that the dissection of these interactions at the mechanistic levels would require a deeper study, which can be a project in itself that we aim to explore in the future. For example, it would be interesting to investigate whether either the inhibition or the downregulation of LOXL2 and/or BRD4S specifically impairs the formation of the DREAM complex or the recruitment of specific DREAM complex subunits, as well as how these effects impair the DREAM complex chromatin binding. We are afraid that the suggested pulldowns would not be sufficient to answer these questions, which would require extensive cross-interaction studies in either BRD4/LOXL2 and BRD4+LOXL2 inhibition or downregulation followed by ChIP-seq and transcriptomics for all the conditions. We believe that the provided data, together with the functional characterization (both, in vitro and in vivo), of the phenotypes triggered by BRD4S and LOXL2 inhibition make a strong case for our manuscript and leave out of scope the suggested experiments. We hope the reviewer will understand our explanation and will appreciate that we are planning to pursue this further in the future.

Fig. 3: We thank the reviewer for this important comment. The ChIP-seq technique very often does not provide exhaustive results due to sequencing depth limits and antibody performance. We believe that the fraction of DREAM target genes found in our dataset as bound by BRD4S is not exhaustive and that the analysis proposed by the reviewer would not lead to clear conclusive results. However, we understand the importance of verifying that DREAM target genes whose promoter is bound by BRD4 are indeed downregulated when LOXL2 is inhibited. To give an answer to this question, in the revised manuscript we added gene expression analysis of selected DREAM target genes upon treatment with JQ1, PXS their combination. We could successfully show that both JQ1 and PXS treatment impairs the transcription of the selected DREAM target genes, however, the combinatorial treatment almost shut down their expression, in agreement with our hypothesis (Fig. 5J).

• The authors state that it is surprising to find that LOXL2 can promote target gene transcription because it is rather known as a transcriptional repressor. To this point, the authors should perform standard analyses using their RNA-seq and ChIP-seq data. Compare differential expression of genes that are bound by BRD4S/L/S+L and genes not bound by BRD4. Perform motif search and enrichment analyses for transcription factor and co-factor binding data (public ChIP-seq repositories). Such analyses may suggest what gene sets are up- and downregulated by LOXL2 through BRD4S/L and what other factors could be involved in LOXL2-dependent up- and downregulation of gene transcription.

We thank the reviewer for this valuable comment that certainly provides the rationale for a follow-up project. However, we believe that the proposed study goes beyond the scope of our work at this moment.

Minor:

• I felt that background information on the BRD4 isoforms was missing. The short and long isoforms of BRD4 should be introduced briefly.

We agree with the reviewer. In the revised manuscript, we addressed this by presenting BRD4 isoforms in the introduction part of the manuscript.

• Given that BRD4 inhibition is known to activate p53 (e.g., PMID 23317504 and 33431824) and p21 (PMID 31265875), the authors should discuss the p53 status of their cell lines (largely mutant). In general, I felt that the authors could better cite and discuss the current literature on BRD4 and LOXL2.

We appreciate the comment of the reviewer regarding p53. Given the fact that p53 is mutant in MDA-MB-231, we believe that the proliferation defect observed with the combinatorial treatment may be due to the activation of alternative cytostatic or cytotoxic signaling cascades, independently of P53 activation. We have now briefly mentioned this point in the manuscript discussion.

• It was unclear to me why the authors did not actually test experimentally whether their predicted interaction models 2 or 4 are likely true (Figure 2E+G).

We understand the reviewer’s comment. The fact that JQ1 treatment almost abrogates the interaction between LOXL2 and BRD4S strongly suggests that models 1 and 3 are likely wrong, therefore pointing towards models 2 and 4 as the correct ones. To test whether models 2 and 4 are indeed the correct models we are now performing extensive mutagenesis studies, which are producing preliminary results suggesting indeed that models 2 and 4 are correct. The reason why we did not include this study in the current manuscript, is that we started a parallel line of investigation aimed at identifying residues fundamental for the interaction that can be exploited in compound screening campaigns to identify molecules able to block the described interaction and thus cancer proliferation. Publishing these preliminary results at this stage could jeopardize the drug discovery campaign and we hope that the reviewer will understand our constraints.

• The transcription of cell cycle genes depends on the cell cycle (i.e., reduced cell cycle entry correlates with reduced cell cycle gene expression). Given that the authors showed LOXL2 inhibition reduce MDA-MB-231 cell proliferation, they should note that reduced expression of cell cycle-related genes is expected upon LOXL2 knockdown.

We understand the reviewer’s comment. We believe that we provide sufficient data supporting our hypothesis that LOXL2 controls the expression of cell cycle genes at the transcriptional level together with BRD4S. In addition, the sole inhibition of LOXL2 has practically no effect on tumor proliferation in vivo but largely enhances the antiproliferative effect of low-dose JQ1 (Fig. 6D). We hope these clarifications would satisfy the reviewer.

• The authors specify in their discussion that their data show a function of LOXL2/BRD4 in the cell cycle interphase, while there were no experiments that support that specific conclusion. At least it is unclear to me why the authors rule out a function in mitosis?

We thank the reviewer for this comment. We referred to interphase genes because these are the early cell cycle genes, while mitotic genes are the late ones. We do not discard a possible function for BRD4S and LOX2 regulating mitotic progression, however, we believe this would be a consequence of dysregulated G1-S-G2 gene expression, rather than a direct transcriptional effect. This conclusion derives from the fact that while we observe interactions between LOXL2, BRD4S, and MED1 with Lin9 and B-Myb, these are not fully conserved with FOXM1, which is typically required for the transcription of mitotic genes. To avoid confusion, we have now anyway removed the word “interphase” from the text.

• I felt that the first part of the manuscript (combination of BRD4 and LOXL2 inhibitors in TNBC) was a bit uncoupled from the functional studies on LOXL2 and its connection to BRD4. The transition between these parts and the final discussion on why the joint control of cell cycle genes by LOXL2/BRD4 may be important for the synergistic effect of LOXL2/BRD4 inhibitors. To this point, the authors' model was not clear to me.

We really appreciate the reviewer’s comment. To better connect the functional studies with the clinical significance of the proposed combinatorial treatment, we restructured the manuscript. In the revised version, the use of the combinatorial treatment is shown in Figure 6. Moreover, to better explain why we focused all the studies on BRD4 and LOXL2, we also included data from the Cancer Cell Line Encyclopedia (CCLE)-associated chemotherapeutics sensitivity (Fig. 1A and Fig. EV1) showing that LOXL2 expression levels can predict the response to BRD4 inhibition, suggesting a functional interaction between BRD4 and LOXL2 and the possibility to exploit it for therapeutical purposes. We believe that these data set the rationale to further explore the connection between LOXL2 and BRD4, both at the mechanistic and functional levels.

Reviewer #2 (Significance (Required)):

The study by Pascual-Reguant et al. shows that inhibitors of BRD4 and LOXL2 can be combined to achieve better efficacy in reducing proliferation of breast cancer cell lines and breast tumor growth in xenograft models. They provide strong evidence for a functional interaction between LOXL2 and BRD4 and investigate their common transcriptional targets. Intriguingly, some evidence points towards a direct regulation of the DREAM complex and its cell cycle gene targets.

The findings are novel and can be the basis for further research on TNBC combination therapy using BRD4 and LOXL2 inhibitors. The link to the DREAM complex is preliminary.

The study is of interest for a basic research audience with some translational aspects.

I reviewed this manuscript as a researcher in gene regulatory mechanisms, with cell cycle genes as one focus area. I have no expertise in the computational modeling of protein-protein interactions and I am no expert for breast cancer.

We thank the reviewer for the positive comments. We also would really like to thank the reviewer for their criticism, which, we believe, contributed to a new and improved manuscript version.

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

Summary:

In this manuscript, Laura Pascual-Reguant et al. identified a novel role of the LOXL2 oxidase in sustaining cell cycle progression through a so far uncharacterized gene-activating function is mediated by the BRD4S epigenetic reader and exerted on key DREAM-target genes in TNBC. Moreover, the authors showed that combinatorial treatment of TNBC with LOXL2- and BRD4-specific inhibitors result in a tremendous anti-tumorigenic effect. For all findings, they leveraged in vitro and in vivo settings as well as high-throughput sequencing approaches. However, the following points should be addressed and explained.

Major points:

-The authors on their working hypothesis propose that dual inhibition of BRD4 and LOXL2 is a novel strategy for curing TNBC. For my taste, just because both targets are quite promising for TNBC, the jump to this combinatorial treatment is kind of abrupt. Knowing the difficulty and time-/financial- investment, authors could optionally perform a mass spectrometry analysis on nuclei lysates with LOXL2 pull down to identify physical interactors. Due to the augmented resources and analysis of raw data, authors may necessitate a generous revision period (approx. 4 months for starters). By that, this can provide a more unbiased approached to look at nucleus-specific gene-regulatory functions and particularly at epigenetic readers. It would be also interesting to see if LOXL2 interacts with other members of the BRD family. Selecting BRD4 and no other members of the bromodomain family cannot be the only choice given that other BRD members can also interact with several of these mediator subunits.

We thank the reviewer for the suggestion and we agree with the fact that the rationale for combining BRD4 and LOXL2 inhibitors was not sufficiently argued in the first version of the manuscript. For that reason, in the revised manuscript, we added new data to explain why we explored this topic. In particular, to better explain why we focused all the studies on BRD4 and LOXL2, we included data from the Cancer Cell Line Encyclopedia (CCLE)-associated chemotherapeutics sensitivity (Fig. 1A and Fig. EV1) showing that LOXL2 expression levels can predict the response to BRD4 inhibition (but not to other approved chemotherapeutic drug), suggesting a functional interaction between BRD4 and LOXL2 and the possibility to exploit it for therapeutical purposes. Moreover, we restructured the manuscript to make the story more linear, explaining first the functionality of BRD4S-LOXL2 interaction at the molecular and cellular levels, and then presenting the in vivo systems in the last part of the manuscript.

We agree with the reviewer that it may be interesting to explore whether LOXL2 interacts with other BRD family members. However, given the prominent role of BRD4 in promoting cancer proliferation, we believe that understanding the relevance of BRD4S-LOXL2 interaction in TNBC is, per se, of great interest and provide a novel mechanistic understanding of how TNBC proliferation is controlled at the transcription level. In the specific case of TNBC, it has been shown that BRD4S has an oncogenic effect, while BRD4L is an oncosuppressor. In the manuscript, we now showed that LOXL2 downregulation sensitizes cells to JQ1 treatment (Fig. 1D). Additionally, while the downregulation of BRD4L does not have any additional effect on cell treated with PXS, the downregulation of BRD4S sensitize them to LOXL2 inhibition (Fig. EV8B). These results, once again, indicate the relevance of studying the functional interaction between BRD4S and LOXL2.

-LOXL enzymes have been shown to promote collagen and fibronectin assembly, thereby sustaining the pro-survival effect of the ITG5A/FN1/FAK/SRC signaling cascade and shielding TNBC cells against chemotherapy treatment (32415208). Did authors observe if LOXL2 loss or inhibition decreased the active status of FAK and SRC, which are well known to promote G1-S transition (25381661)?

Probably the cell cycle defects upon LOXL2 loss may also partially arise from the impairment of this cascade.

We really appreciate the reviewer’s suggestions. In the revised version of the manuscript, we checked FAK and Src activation status in tumor samples from one of our in vivo experiments (Fig. EV10D). We did not observe any difference in phospho-FAK or phospho-Src upon treatment either with PXS, JQ1, or their combinations, suggesting that alterations in the activity of these factors were not driving the observed proliferation defects.

-Authors exclusively use JQ1 as a BRD4 inhibitor. As JQ1 may have an unspecific effect on BRD2 as well, authors should consider reproducing key experiments with siControl- and siBRD4-treated cells and increasing doses of PSX as well as repeating the JQ1 dose response assay in Figure 1B using siRNA-mediated silencing of LOXL2. Given that both players are part of the same complex, silencing of one and inhibition of the other should sensitize cells compared to their control counterparts.

We agree with the reviewer and we addressed this comment in the revised manuscript. In particular, we have added two additional experiments:

• We transduced MDA-MB-231 cells with isoform-specific shBRD4s (shBRD4L and shBRD4S) (Fig. EV5H) and checked cell sensitivity to PXS treatment (Fig. EV8B). As explained also above, we observed that only when the short isoform of BRD4 was downregulated cells displayed higher sensitivity to PXS treatment. This result corroborates that BRD4S and LOXL2 are required for TNBC proliferation.

• We transduced MDA-MB-231 cells with shLOXL2 and assessed JQ1 sensitivity (Fig. 1D). We showed that upon LOXL2 downregulation, cells became more sensitive to JQ1 treatment, again corroborating the fact that TNBC proliferation requires BRD4S and LOXL2.

-Moreover, in Figures 1G and S3D the differential sensitivity of low and high LOXL2 cell lines is unclear. Do authors know if any of these growth kinetic lines represent one of the tested cell lines in Figure 1A-B? Authors should provide respective legends. In addition, authors should take advantage of their homemade data given that they have already selected a panel of TNBC cell lines with various LOXL2 expression at basal state (Figure 1A) for which dose response assays have been performed (Figure 1B). Therefore, I would perform an IC50 graph for JQ1 (without PSX treatment) using the existing data from Figure 1B.

We apologize if our representation was confusing. In the revised manuscript we have changed the sensitivity plots (Fig. 1A and Fig. EV1) to make them easier to grasp. Additionally, in Figure 1A we included the analysis of CCLE cell lines stratified based on their LOXL2 expression levels. This analysis showed that LOXL2 expression levels could overall predict the response to BETi treatment. As suggested by the reviewer, we also plotted the IC50 of the 3 cell lines tested. However, their JQ1 sensitivity curves did not show any difference that could be attributed to their different LOXL2 levels. Our speculation is that only 3 cell lines do not provide a sufficient size to reach a meaningful conclusion, which, in contrast, can be achieved by comparing the CCLE BETi sensitivity.

-In Figure 2D, the pull-down assay is inconclusive, as the molecular weight for each construct is not mentioned. I would probably add this information also in all performed western blots. Also, the overexpression of the BD1/BD2-mutated and especially the BD1/BD2-lacking construct is unclear if it still interacts with LOXL2, probably because of the lack of molecular weight reference of each band. Therefore, the authors should make this pull-down assay more descriptive regarding the size of the bands. Also, BD1 mutagenesis at N140 was shown to dislodge the binding of JQ1 to BRD4 (24497639), which implies that BD1 mutagenesis or overexpression of the BD1-deficient construct should abrogate the interaction of LOXL2 with BRD4, reminiscent to the abrogated interaction of BRD4/LOXL2 upon JQ1 that binds to both BDs (Figure 2F). And, what happens if a BD2-deficient construct is expressed?

We thank the reviewer for spotting this distraction. We apologize for this and in the revised version of the manuscript we included molecular weights for all western blots.

We acknowledge that BD1 mutagenesis displaces JQ1 binding, however, we respectfully disagree that because of this BD1-N140 mutant should not bind to LOXL2. Our docking analysis indeed showed that none of the poses is impaired either by BD1 or BD2 mutagenesis (Fig. EV4D). The fact that JQ1 disrupts the interaction between BRD4S and LOXL2 (Fig. 2F, G) is not due to the fact that they compete for the same binding residue, but rather for the space occupied by JQ1 inside the AcK binding pocket of either BD1 or BD2, which impedes proper binding to LOXL2. Our pulldown data indeed showed that mutant BD1 and BD2 retain the ability to bind to LOXL2 (Fig. 2C), as predicted by the docking.

We did not try to express constructs either lacking BD1 or BD2 and we cannot speculate what could happen to the BRD4S-LOXL2 interaction in this scenario. Even though this experiment could help dissect the interaction between LOXL2 and BRD4S, we decided to rather perform mutagenesis of specific residues that have been predicted to be important for the interaction. The reason why we did not include this study in the current manuscript, is that we started a parallel line of investigation aimed at identifying residues fundamental for the interaction that can be exploited in compound screening campaigns to identify molecules able to block the described interaction and thus cancer proliferation. Publishing these preliminary results at this stage could jeopardize the drug discovery campaign and we hope that the reviewer will understand our constraints.

-If authors support that BRD4S is the predominant isoform driving the expression of DREAM-targets, this means that DREAM-targets are mainly bound by BRD4S, relying on Figure 3E-F. However, based on the author's ChIPseq tracks in Figure 3H, DREAM targets such as EZH2 and HMGB2 are co-occupied by both BRD4 isoforms at the basal state on their promoter region. Also, especially for EZH2 and PLK4, authors should set to 'group auto-scale' both conditions in a smaller scale range for ChIPseq- and RNAseq tracks, although I do not these two genes as good candidates representing your analysis. Therefore, authors should initially show all genes (e.g in a table format) that enrich the 'DREAM-targets' signature and select for a greater panel of genes (like for AURKB and HMGB2) demonstrating a preferential occupancy of the BRD4S at their promoter region. Finally, authors are recommended to perform a ChIP-qPCR on these genomic regions at basal state (no LOXL2 silencing) to validate the predominant occupancy of BRD4S and the low/absent occupancy of BRD4L at these genomic sites.

We apologize for the confusion. To make the figure more understandable, we now scaled all the panels to the same scale and highlighted in grey the promoter region of each selected DREAM target gene. As the reviewer can appreciate, none of these genes is bound by BRD4L in basal conditions (Fig. 3F).

To better characterize the differential binding, following the reviewer’s suggestion, we performed ChIP-qPCR using Ab2 (which recognizes both BRD4 isoforms), in cells either downregulated for BRD4L or BRD4S with isoform-specific shRNAs (Fig. EV5H). Results showed that only the downregulation of BRD4S reduced the binding of Ab2 to the promoter of the selected DREAM target genes (Fig. 3D), corroborating our hypothesis and validating our ChIPseq strategy.

-Authors in Figure 3G should select an equal-sized population of randomly chosen non-DREAM-target genes, otherwise, the comparison of log2FC difference between these two gene cohorts is unreliable and difficult to make. Mann-Whitney test should also be performed.

We thank the reviewer for this suggestion, which was added to the revised version of the manuscript (Fig. 3E, lower panel).

-Authors should repeat the cell cycle analysis (Figure 4A) as the number of cells subjected to flow cytometry is quite discrepant between the conditions. Also, it is not clear if the experiment was performed in at least biological triplicates (although in the respective legend, it is stated so). If performed in biological triplicates, authors should make a new graph where each cell cycle phase cell population differs between the two conditions. Moreover, the difference in cell cycle defects in LOXL2-inhibited cells (Figure 4C) is indifferent compared to their control counterpart. Therefore, authors should address these inconsistencies.

We thank the reviewer for the suggestion. In the revised version of the manuscript, we represent the cell cycle also as a bar plot with statistical analysis (Fig. 4A, C). Even though the number of cells was the same across conditions, the sub-G1 population of the LOXL2 KD cells may have distorted the profile of the cell cycle. To avoid misinterpretations, we repeated the analysis in the revised version of the manuscript. Statistical analysis supports that LOXL2 inhibition or downregulation has a significant effect on cell cycle progression (Fig. 4A, C, right panel).

-Furthermore, authors should explain what was the rational selecting a mediator subunit and specifically MED1 as a possible interacting partner of LOXL2 and BRD4s since MED12 and MED24 were also highly essential (Figure 4F).

We selected MED1 as a Mediator Complex proxy. In our essentiality analysis MED 1, 9, 10, 12, 15, 16, 19, 23, 24, 25 score as significant, suggesting a functional interaction between LOXL2 and the Mediator Complex, rather than a specific subunit. MED1 has been previously described as a BRD4 partner and it is often used in immunofluorescence to visualize transcriptional foci, which made it the best candidate for follow-up study in our project.

-Moreover, do authors also observe this functional relationship of LOXL2 and BRD4S in cell cycle progression in other breast cancer subtypes presenting a high proliferation index e.g HER2+?

Presumably, the author's proposed mechanism applies to a wide panel of breast cancer entities, for which, only key experiments could be performed.

We thank the reviewer for the suggestion. We hypothesized that other cancer types expressing LOXL2 and BRD4S could also benefit from the combinatorial treatment. Indeed, the CCLE drug sensitivity panel in Fig. 1A comprises cancer cell lines of different origins, not just TNBC, and corroborates that the relationship between LOXL2 expression levels and BRD4 sensitivity exist also beyond TNBC. Even though it is important to experimentally verify this hypothesis, we decided to pursue it in the future to broaden the applicability of the proposed strategy in preclinical settings.

-Authors in Figure 5H represent LOXL2 and BRD4s as integral chromatin looping factors together with MED1 at promoter and enhancer regions. However, this illustration is an overrepresentation of their finding because authors did not address the differential occupancy of BRD4S upon LOXL2 loss in DREAM-target-specific enhancer regions. If they wish to do so, they may use the RANK ORDERING OF SUPER-ENHANCERS (ROSE) package to call for super-enhancer regions in the proximity of DREAM-targets and confirm similar results as for their TSS-proximal sites.

We thank the reviewer for the useful suggestion. In the new version of the manuscript, we have simplified the representation, which now does not show super-enhancers. However, following the reviewer’s suggestion, we performed super enhancer analysis using ROSE. Results showed that BRD4S binds to super-enhancers more than BRD4L, including DREAM target gene super-enhancers. Additionally, while LOXL2 KD did not alter the binding of LOXL2 to DREAM target gene super-enhancers, it decreased the binding of BRD4S to them (Fig. EV7D, E). Overall, these data are in agreement with our hypothesis that BRD4S together with LOXL2 controls the expression of DREAM target genes.

-In the current manuscript, authors did not address the translational relevance of their proposed mechanism in the context of conventional therapies. Knowing that several BRD-specific compounds currently undergo clinical trials, authors should address if LOXL2 low (MDAMB468) and high (BT549) cells demonstrate a differential sensitivity to increasing doses of chemotherapy, in the presence or absence of BRD4. By doing that, LOXL2 apart from being a therapeutic target could be also used as a prognostic marker to stratify patients and achieve better response to standard therapies.

We really appreciate the reviewer’s suggestion and we think this is a fundamental point. In the new version of the manuscript, we have performed further analysis using a greater panel of chemotherapeutic agents from the CCLE sensitivity database. We now show that LOXL2 low-expressing cells show significantly more sensitivity to BETi treatments, but not to conventional chemotherapeutic agents (e.g. doxorubicin, Olaparib, 5-fluorouracil, paclitaxel, etc.) (Fig. 1A and Fig. EV1), which set the rationale to further explore the functional relationship between BRD4 and LOXL2.

Minor points:

-In Figure 1D, the authors should convert the y-axis to a logarithmic scale to better represent the differences between JQ1, PXS, and combo. Also, One-way Anova should be performed between JQ1, PXS and combo.

We don’t understand the reviewer’s suggestion since Fig. 1D (Fig. 6B, right panel in the revised version) is a tumor picture for which the y-axis cannot be converted to a logarithmic scale.

-In Figure S6F, authors did not show the sensitivity of LOXL2 low and high cell lines for BRD4 KO. If LOXL2-proficient cells are less sensitive to JQ1, based on Figure 1B, authors should consider showing something similar from the gene essentiality database.

We agree with the reviewer and we apologize for this mistake. We have included the sensitivity of LOXL2 low and high cell lines for BRD4 KO and also for MYC KO (Fig. EV6G).

-Authors failed to discuss the work from Ozge Saatci et al (PMID: 32415208) regarding LOXL2 in TNBC and ECM reorganization as well as in other cancer entities (PMID: 35428659) in the context of ECM remodeling. Authors should realize that these published works and the current ones are not conflicting but complement each other.

We thank the reviewer for the suggestion. In the revised version of the manuscript, we discussed this work.

Reviewer #3 (Significance (Required)):

SIGNIFICANCE

The conception and findings are of enlightening significance for TNBC therapy, especially given the lack of targeted therapies in this particularly aggressive breast cancer subtype. Hence, I posit this work as highly relevant for the cancer epigenetics research community interested in characterizing unknown factors that facilitate the gene-activating function of epigenetic readers in health and disease.

My field of expertise is to uncover epigenetic vulnerabilities responsible for transcriptional plasticity driving drug tolerance in aggressive forms of breast cancer.

We would like to take the opportunity to thank the reviewer for the relevant suggestions. We strongly believe the revised version of the manuscript has been substantially improved by addressing the comments the reviewer made.

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Referee #3

Evidence, reproducibility and clarity

Summary:

In this manuscript, Laura Pascual-Reguant et al. identified a novel role of the LOXL2 oxidase in sustaining cell cycle progression through a so far uncharacterized gene-activating function is mediated by the BRD4S epigenetic reader and exerted on key DREAM-target genes in TNBC. Moreover, the authors showed that combinatorial treatment of TNBC with LOXL2- and BRD4-specific inhibitors result in a tremendous anti-tumorigenic effect. For all findings, they leveraged in vitro and in vivo settings as well as high-throughput sequencing approaches. However, the following points should be addressed and explained.

Major points:

• The authors on their working hypothesis propose that dual inhibition of BRD4 and LOXL2 is a novel strategy for curing TNBC. For my taste, just because both targets are quite promising for TNBC, the jump to this combinatorial treatment is kind of abrupt. Knowing the difficulty and time-/financial- investment, authors could optionally perform a mass spectrometry analysis on nuclei lysates with LOXL2 pull down to identify physical interactors. Due to the augmented resources and analysis of raw data, authors may necessitate a generous revision period (approx. 4 months for starters). By that, this can provide a more unbiased approached to look at nucleus-specific gene-regulatory functions and particularly at epigenetic readers. It would be also interesting to see if LOXL2 interacts with other members of the BRD family. Selecting BRD4 and no other members of the bromodomain family cannot be the only choice given that other BRD members can also interact with several of these mediator subunits.
• LOXL enzymes have been shown to promote collagen and fibronectin assembly, thereby sustaining the pro-survival effect of the ITG5A/FN1/FAK/SRC signaling cascade and shielding TNBC cells against chemotherapy treatment (32415208). Did authors observe if LOXL2 loss or inhibition decreased the active status of FAK and SRC, which are well known to promote G1-S transition (25381661)? Probably the cell cycle defects upon LOXL2 loss may also partially arise from the impairment of this cascade.
• Authors exclusively use JQ1 as a BRD4 inhibitor. As JQ1 may have an unspecific effect on BRD2 as well, authors should consider reproducing key experiments with siControl- and siBRD4-treated cells and increasing doses of PSX as well as repeating the JQ1 dose response assay in Figure 1B using siRNA-mediated silencing of LOXL2. Given that both players are part of the same complex, silencing of one and inhibition of the other should sensitize cells compared to their control counterparts.
• Moreover, in Figures 1G and S3D the differential sensitivity of low and high LOXL2 cell lines is unclear. Do authors know if any of these growth kinetic lines represent one of the tested cell lines in Figure 1A-B? Authors should provide respective legends. In addition, authors should take advantage of their homemade data given that they have already selected a panel of TNBC cell lines with various LOXL2 expression at basal state (Figure 1A) for which dose response assays have been performed (Figure 1B). Therefore, I would perform an IC50 graph for JQ1 (without PSX treatment) using the existing data from Figure 1B.
• In Figure 2D, the pull-down assay is inconclusive, as the molecular weight for each construct is not mentioned. I would probably add this information also in all performed western blots. Also, the overexpression of the BD1/BD2-mutated and especially the BD1/BD2-lacking construct is unclear if it still interacts with LOXL2, probably because of the lack of molecular weight reference of each band. Therefore, the authors should make this pull-down assay more descriptive regarding the size of the bands. Also, BD1 mutagenesis at N140 was shown to dislodge the binding of JQ1 to BRD4 (24497639), which implies that BD1 mutagenesis or overexpression of the BD1-deficient construct should abrogate the interaction of LOXL2 with BRD4, reminiscent to the abrogated interaction of BRD4/LOXL2 upon JQ1 that binds to both BDs (Figure 2F). And, what happens if a BD2-deficient construct is expressed?
• If authors support that BRD4S is the predominant isoform driving the expression of DREAM-targets, this means that DREAM-targets are mainly bound by BRD4S, relying on Figure 3E-F. However, based on the author's ChIPseq tracks in Figure 3H, DREAM targets such as EZH2 and HMGB2 are co-occupied by both BRD4 isoforms at the basal state on their promoter region. Also, especially for EZH2 and PLK4, authors should set to 'group auto-scale' both conditions in a smaller scale range for ChIPseq- and RNAseq tracks, although I do not these two genes as good candidates representing your analysis. Therefore, authors should initially show all genes (e.g in a table format) that enrich the 'DREAM-targets' signature and select for a greater panel of genes (like for AURKB and HMGB2) demonstrating a preferential occupancy of the BRD4S at their promoter region. Finally, authors are recommended to perform a ChIP-qPCR on these genomic regions at basal state (no LOXL2 silencing) to validate the predominant occupancy of BRD4S and the low/absent occupancy of BRD4L at these genomic sites.
• Authors in Figure 3G should select an equal-sized population of randomly chosen non-DREAM-target genes, otherwise, the comparison of log2FC difference between these two gene cohorts is unreliable and difficult to make. Mann-Whitney test should also be performed.
• Authors should repeat the cell cycle analysis (Figure 4A) as the number of cells subjected to flow cytometry is quite discrepant between the conditions. Also, it is not clear if the experiment was performed in at least biological triplicates (although in the respective legend, it is stated so). If performed in biological triplicates, authors should make a new graph where each cell cycle phase cell population differs between the two conditions. Moreover, the difference in cell cycle defects in LOXL2-inhibited cells (Figure 4C) is indifferent compared to their control counterpart. Therefore, authors should address these inconsistencies.
• Furthermore, authors should explain what was the rational selecting a mediator subunit and specifically MED1 as a possible interacting partner of LOXL2 and BRD4s since MED12 and MED24 were also highly essential (Figure 4F).
• Moreover, do authors also observe this functional relationship of LOXL2 and BRD4S in cell cycle progression in other breast cancer subtypes presenting a high proliferation index e.g HER2+? Presumably, the author's proposed mechanism applies to a wide panel of breast cancer entities, for which, only key experiments could be performed.
• Authors in Figure 5H represent LOXL2 and BRD4s as integral chromatin looping factors together with MED1 at promoter and enhancer regions. However, this illustration is an overrepresentation of their finding because authors did not address the differential occupancy of BRD4S upon LOXL2 loss in DREAM-target-specific enhancer regions. If they wish to do so, they may use the RANK ORDERING OF SUPER-ENHANCERS (ROSE) package to call for super-enhancer regions in the proximity of DREAM-targets and confirm similar results as for their TSS-proximal sites.
• In the current manuscript, authors did not address the translational relevance of their proposed mechanism in the context of conventional therapies. Knowing that several BRD-specific compounds currently undergo clinical trials, authors should address if LOXL2 low (MDAMB468) and high (BT549) cells demonstrate a differential sensitivity to increasing doses of chemotherapy, in the presence or absence of BRD4. By doing that, LOXL2 apart from being a therapeutic target could be also used as a prognostic marker to stratify patients and achieve better response to standard therapies.

Minor points:

• In Figure 1D, the authors should convert the y-axis to a logarithmic scale to better represent the differences between JQ1, PXS, and combo. Also, One-way Anova should be performed between JQ1, PXS and combo.
• In Figure S6F, authors did not show the sensitivity of LOXL2 low and high cell lines for BRD4 KO. If LOXL2-proficient cells are less sensitive to JQ1, based on Figure 1B, authors should consider showing something similar from the gene essentiality database.
• Authors failed to discuss the work from Ozge Saatci et al (PMID: 32415208) regarding LOXL2 in TNBC and ECM reorganization as well as in other cancer entities (PMID: 35428659) in the context of ECM remodeling. Authors should realize that these published works and the current ones are not conflicting but complement each other.

Significance

Minor points:

• In Figure 1D, the authors should convert the y-axis to a logarithmic scale to better represent the differences between JQ1, PXS, and combo. Also, One-way Anova should be performed between JQ1, PXS, and combo.
• In Figure S6F, the authors did not show the sensitivity of LOXL2 low and high cell lines for BRD4 KO. If LOXL2-proficient cells are less sensitive to JQ1, based on Figure 1B, authors should consider showing something similar from the gene essentiality database.
• Authors failed to discuss the work from Ozge Saatci et al (PMID: 32415208) regarding LOXL2 in TNBC and ECM reorganization as well as in other cancer entities (PMID: 35428659) in the context of ECM remodeling. Authors should realize that these published works and the current ones are not conflicting but complement each other.

Significance

The conception and findings are of enlightening significance for TNBC therapy, especially given the lack of targeted therapies in this particularly aggressive breast cancer subtype. Hence, I posit this work as highly relevant for the cancer epigenetics research community interested in characterizing unknown factors that facilitate the gene-activating function of epigenetic readers in health and disease.

My field of expertise is to uncover epigenetic vulnerabilities responsible for transcriptional plasticity driving drug tolerance in aggressive forms of breast cancer.

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 their study, Pascual-Reguant et al. show that combined inhibition of BRD4 and LOXL2 can synergize to restrict triple-negative breast cancer (TNBC) proliferation. BRD4 and LOXL2 are transcription regulators that can read and write epigenetic information, respectively. The authors employ three distinct breast cancer cell lines and mouse models with cell line-derived xenografts, and they show that combined inhibition of BRD4 and LOXL2 can be superior to single BRD4/LOXL2 inhibition in these model systems. In an attempt to identify a connection between BRD4 and LOXL2, the authors find that the two proteins can bind to each other. The authors performed most of the experiments in the breast cancer cell line MDA-MB-231. To assess the impact of LOXL2-inhibition on transcription, the authors assessed changes of the transcriptome in MDA-MB-231 cells following LOXL2 knockdown. They found that genes related to cell differentiation and morphology were upregulated, while genes related to the cell cycle were downregulated. ChIP-seq data of BRD4 showed that BRD4 can bind to cell cycle gene promoters and that this binding was enhanced upon loss of LOXL2. The authors found that LOXL2 and BRD4 interacted with the transcriptional cell cycle regulators B-MYB, FOXM1, and LIN9, which are components of the MYB-MuvB-FOXM1 (MMB-FOXM1) complex that is known to promote the expression of late cell cycle genes with important functions during mitosis. The authors conclude that LOXL2/BRD4 interact with each other and with the MMB-FOXM1 complex to drive the expression of cell cycle genes and cell proliferations. Vice versa, they conclude that inhibition of LOXL2/BRD4 reduces cell proliferation through inhibiting the expression of cell cycle genes.

Major:

• The data and methods are presented well. The experiments are adequately replicated and analyzed. However, except for the first section, all experiments were performed using only one cell line. It is important to validate key findings in at least a second cell line.
• There appears to be a misunderstanding of the concept of cell cycle-dependent gene regulation by the DREAM complex and its related factors. Early (G1/S) cell cycle genes contain E2F promoter motifs, while late (G2/M) cell cycle genes contain CHR promoter motifs. The DREAM complex can bind both, while RB-E2F and MuvB recognize only E2F and CHR motifs, respectively. B-MYB and FOXM1 bind to MuvB and regulate late cell cycle genes, but they do not bind to early cell cycle genes. Given this concept, the authors' rationale to connect BRD4/LOXL2 through MuvB/B-MYB/FOXM1 with E2F promoter sequences and early cell cycle genes and the subsequent conclusions must be corrected.
• I felt that the suggested functional connection between LOXL2/BRD4 and DREAM is not strongly supported by the authors' data. Figure S6E: A similarity score of <0.7 is poor support for a 'consensus E2F sequence' and indicates very limited specificity. Figure 4E: IP with BRD4 and LOXL2 is missing as important control. A chromatin-binding control is missing that does not bind to DREAM/LOXL2/BRD4. To test for binding to the actual DREAM complex, the authors should include E2F4 and p130 in their IPs and western blots, perhaps following LOXL2 inhibition/knockdown. Figure 3: The authors' ChIP-seq data indicate that only a fraction of DREAM targets is bound by BRD4. To provide more evidence that LOXL2/BRD4 may be directly involved in regulating DREAM targets, the authors should compare the differential regulation of BRD4-bound DREAM targets upon LOXL2 knockdown with DREAM targets which are not bound by BRD4. If LOXL2/BRD4 acted in a direct manner on those targets, one would expect that loss of LOXL2 affected their transcription more strongly than the other DREAM targets which are affected only indirectly. Such an analysis can be performed readily using the available data.
• The authors state that it is surprising to find that LOXL2 can promote target gene transcription because it is rather known as a transcriptional repressor. To this point, the authors should perform standard analyses using their RNA-seq and ChIP-seq data. Compare differential expression of genes that are bound by BRD4S/L/S+L and genes not bound by BRD4. Perform motif search and enrichment analyses for transcription factor and co-factor binding data (public ChIP-seq repositories). Such analyses may suggest what gene sets are up- and downregulated by LOXL2 through BRD4S/L and what other factors could be involved in LOXL2-dependent up- and downregulation of gene transcription.

Minor:

• I felt that background information on the BRD4 isoforms was missing. The short and long isoforms of BRD4 should be introduced briefly.
• Given that BRD4 inhibition is known to activate p53 (e.g., PMID 23317504 and 33431824) and p21 (PMID 31265875), the authors should discuss the p53 status of their cell lines (largely mutant). In general, I felt that the authors could better cite and discuss the current literature on BRD4 and LOXL2.
• It was unclear to me why the authors did not actually test experimentally whether their predicted interaction models 2 or 4 are likely true (Figure 2E+G).
• The transcription of cell cycle genes depends on the cell cycle (i.e., reduced cell cycle entry correlates with reduced cell cycle gene expression). Given that the authors showed LOXL2 inhibition reduce MDA-MB-231 cell proliferation, they should note that reduced expression of cell cycle-related genes is expected upon LOXL2 knockdown.
• The authors specify in their discussion that their data show a function of LOXL2/BRD4 in the cell cycle interphase, while there were no experiments that support that specific conclusion. At least it is unclear to me why the authors rule out a function in mitosis?
• I felt that the first part of the manuscript (combination of BRD4 and LOXL2 inhibitors in TNBC) was a bit uncoupled from the functional studies on LOXL2 and its connection to BRD4. The transition between these parts and the final discussion on why the joint control of cell cycle genes by LOXL2/BRD4 may be important for the synergistic effect of LOXL2/BRD4 inhibitors. To this point, the authors' model was not clear to me.

Significance

The study by Pascual-Reguant et al. shows that inhibitors of BRD4 and LOXL2 can be combined to achieve better efficacy in reducing proliferation of breast cancer cell lines and breast tumor growth in xenograft models. They provide strong evidence for a functional interaction between LOXL2 and BRD4 and investigate their common transcriptional targets. Intriguingly, some evidence points towards a direct regulation of the DREAM complex and its cell cycle gene targets.

The findings are novel and can be the basis for further research on TNBC combination therapy using BRD4 and LOXL2 inhibitors. The link to the DREAM complex is preliminary.

The study is of interest for a basic research audience with some translational aspects.

I reviewed this manuscript as a researcher in gene regulatory mechanisms, with cell cycle genes as one focus area. I have no expertise in the computational modeling of protein-protein interactions and I am no expert for breast cancer.

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Referee #1

Evidence, reproducibility and clarity

The manuscript describes that simultaneous inhibition of LOXL2 and BRD4 reduces proliferation of TNBC in vitro and reduces growth in vivo. This observation is followed by extensive mechanistic studies that suggest physical interaction between LOXL2 and short isoform of BRD4-MED1. Inferences from Chip-seq analyses suggest that this interaction is involved in regulation of multiple transcriptional programs. Authors focus on differential activation of DREAM complex, to claim that this interaction "is fundamental for proliferation of TNBC". The manuscript is very well written and mechanistic inferences are based on a set of sophisticated epigenetic analyses and bioinformatical inferences. The phenotypic effects from LoxL2 inhibition by itself, or in combination with BRD4 inhibition are relatively modest. These modest effects, as well as many of the reported changes in gene expression are clearly inconsistent with the frequently used adjectives as "dramatic", "fundamental", "deeply affected", "drastically hampered" etc. Given the modest phenotypic effects, many of the key claims and conclusions are not supported by the data.

Specifically:

1. It is unclear why authors generalize their conclusions to TNBC. Figure 1B demonstrates synergy for 1/3 cell lines, which is chosen for the follow up study. Even for MDA231, the synergy is confined to low concentrations of BRD4i (S1c). While MDA231 cell line is frequently used in experimental studies of TNBC, it is quite dissimilar to majority of clinical TNBC, and contains mutant RAS, which is rare in this disease.
2. In vivo, the effect appears to be modest even in the MDA231 model, selected for evidence of synergy in vitro. In vivo, the combination appears to have an additive effect. Tumor growth rates are reduced, but no shrinkage is occurring. In the PDX model, LOXL2i does not have an effect as a monotherapy, while modestly enhancing the impact of BRD4i. These results are at odds with the claim of the interaction being fundamental for proliferation.
3. No analysis of cell proliferation was shown in vivo. Authors should have performed BrdU or KI67 staining to support the claim. For in vitro analyses, authors also used indirect assays for proliferation. PI staining by itself does not have sufficient resolution to clearly capture modest effects that authors demonstrate. BrdU-PI double staining would have been much more useful.

Minor points:

1. Dose dependent decrease in phosphorylated H3 is not at all obvious from eyeballing the data in S1A; the only effect that I see is a modest reduction at the highest concentration of the inhibitor. Authors need to quantify the results to support the claim.
2. Most of breast cancer cell lines are derived from metastatic disease, including pleural effusion, thus the point that because MDA231 cell line is derived from pleural effusion, it is metastatic does not have sufficient logical foundation.
3. How is loss of cell-cell junction in vitro consistent with LOXL2 role in modulating ECM? There is no evidence of ECM production in MDA231 in vitro. On the other hand, this loss is associated with EMT.

Significance

Discovery and characterization of LOXL2-BRD4 interaction is advancing the ever-deepening understanding of molecular mechanisms of regulation of gene expression. The studies and analyses appear to be sufficiently rigorous and reported with clarity, and the claimed discovery of the biological interaction between LOXL2 and BRD4 is well supported. However, given the magnitude of the reported (rather than claimed) effects of this interaction, and concerns about generalizability of authors conclusions, it is not clear how these results are promising for the development of new therapies in TNBC. Moreover, in contrast to luminal BC, there is no clear evidence for utility of cytostatic drugs in constraining TNBC. Therefore, biological and clinical significance of the authors discovery is unclear and claims in this regard appear to be overblown.

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Reply to the reviewers

The authors show expression of the thyroid hormone transporter MCT8 in the human placenta. The MCT8-inhibiting compound sylchristine reduces the transfer of T4 from the maternal to the fetal side and accordingly reduces T4 degradation by DIO3. Since maternal thyroid hormones are relevant for neurodevelopment before the onset of fetal thyroid gland function, disruption of MCT8 transport, as occurs in the Allan-Herdon-Dudley syndrome, may contribute to the neurodevelopment failure present in these patients.

The results of the transfer experiments are clear and support the authors' conclusions.

We thank the reviewer for this positive statement.

Minor comments:

1. Line 71: please provide some references on the immaturity of the blood.brain barrier before 18 months. The endothelial cells may have tight junctions when the vessels sprout in the CNS. "Maturity" implies the full complement of the neurovascular unit, i.e., pericytes and astrocytes. So, please clarify this point, even if it does not contradict the experimental results showing the role of placental MCT8.

We acknowledge that there is debate when the human blood-brain barrier is regarded as mature. Tight junctions of endothelial cells are functional from week 14 in fetal development (Saili et al, DOI: 10.1002/bdr2.1180) and reach functionality comparable with adult blood-brain barrier from 18 weeks onwards (DOI: 10.1016/j.placenta.2016.12.005). A fully functional blood-brain barrier requires interaction with a range of cells, including pericytes, astrocytes, microglia and neurons (DOI: 10.1016/j.placenta.2016.12.005), which matures during the entire pregnancy (e.g. cortical astrocytes start to appear from 30 weeks onwards).

In our manuscript, we do not intend to overstate the relevance of our findings. Hence, in the revised manuscript, we changed the wording in lines 70-71 from ‘’mature’’ to ‘’functional’’. This avoids the discussion on when the human blood-brain barrier is mature, while conveying the message that the placental barrier is key in determining bioavailability of thyroid hormone for the fetal brain.

It is unclear if the partial effect of sylchristine on T4 transport means that MCT8 contribution is also partial and other transporters contribute.

We thank the reviewer for raising this point. Our in vitro data (Figure Expanded View 2) showed that at 10 µM concentration silychristin fully inhibits MCT8, agreeing with previous data by others (Johannes et al, DOI: 10.1210/en.2015-1933). As MCT8 is expressed at the apical membrane of the syncytiotrophoblasts which is in direct contact of maternal circulation, it can be inferred that T4 entering the placenta via MCT8 is fully inhibited. In our manuscript, we show that the application of silychristin on the maternal circulation leads to a 60% reduction of T4 accumulation at the fetal side, with the remaining 40% of fetal T4 corresponding to an absolute concentration of ~ 4 nM T4. Of note, we previously showed in the same placenta model that there is ~4 nM T4 endogenously present in the placenta (see Figure 3, DOI: 10.1089/thy.2022.0406). This endogenous placental T4 can be transferred to the fetal circulation; this latter process is not blocked by silychristin, which is only present in the maternal circulation. As adding silychristin results in only ~ 4 nM T4 appearing at the fetal side, equal to the endogenous concentration, it is likely that the contribution by other transporters is minimal.

To clarify this, we have added this in the Discussion of the revised manuscript (lines 117-120).

Lines 113-114. I missed the controls measuring TRIAC transport without sylchristine, or do the authors have strong reasons to assume that sylchristine does not affect TRIAC transport? If so, it should be stated.

We thank the reviewer for raising this question. No human TRIAC transporters have been published and, hence, we cannot exclude the possibility that silychristin may inhibit TRIAC transport. However, we previously showed that human MCT8 does not induce TRIAC uptake (Figure 7, DOI: 10.1089/thy.2019.0009), indicating that TRIAC transport is MCT8 independent. In a previous study, we tested the specificity of silychristin for the thyroid hormone transporters expressed in human term placenta (Figure 2 in DOI: 10.1089/thy.2021.0503)). Silychristin potently inhibited MCT8 with an IC50 of 0.12 µM and at a much higher concentration (10 µM) it also inhibited OATP1A2 by ~40% but none of the other transporters. However, OATP1A2 does not transport TRIAC (unpublished data). Therefore, we feel that silychristin is unlikely to have relevant effects on other placental thyroid hormone transporters that may facilitate TRIAC transport. Hence, we did not include experiments of TRIAC transport in the absence of silychristin.

Our aim was to provide a proof-of-concept that TRIAC is very efficiently transported across human placenta when MCT8 is inhibited. Should the reviewer insist to perform TRIAC transport in the absence of silychristin, we would be happy to do so.

In the revised manuscript, we have included this point as a limitation in our study (lines 146-151).

Reviewer #1 (Significance (Required)):

This study confirms the presence of MCT8 in the human placenta and adds additional data to demonstrate its functionality with experiments using placental perfusion.

We are pleased to see that the reviewer agrees that our data are a relevant addition to the field.

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

Short summary of findings:

The authors used silychristin to selectively block the thyroid hormone transporter MCT8 in perfused human placenta. This was done to model the MCT8 deficient placenta in the rare genetic condition called Allan Herndon Dudley Syndrome. They then showed that the thyroid hormone analogue TRIAC can still cross the placenta and may be a potential treatment to prevent some of the effects of thyroid hormone deficiency in the affected fetus.

Major comments:

The absence of binding proteins in the maternal circulation is an issue since protein bound thyroid hormones can also be taken up by trophoblasts. Additionally, the placenta produces and secretes transthyretin and albumin into the maternal circulation - was this taken into account?

We thank the reviewer for raising this point. We are aware of thyroid binding proteins such as transthyretin (TTR) (eg. DOI: 10.1016/j.placenta.2013.05.005; DOI: 10.1016/j.placenta.2012.01.006; DOI: 10.1210/jc.2009-0048). From such data, it has been established that the placenta secretes TTR. Also, it has been shown that the TTR-T4 complex can be internalized into Jeg3 cells. However, to our knowledge, there is no direct evidence showing that the TTR-T4 complex is transported across human placenta reaching the fetal circulation.

As we have mentioned in the response to the comment 2 of Reviewer 1, adding silychristin results in only ~ 4 nM T4 appearing at the fetal side, equal to the endogenous concentration present in the placenta. Therefore it is likely that the contribution by other transporters or transport mechanisms such as TTR-T4 is minimal.

A caveat to the abovementioned arguments is that our perfusion only lasted for 3 hours because longer perfusions will lead to loss of intactness of the placenta and, hence, less functionality. Therefore, it cannot be excluded that during longer exposures TTR might have a role.

Following this reviewer’s comment, we added this as a limitation to our model in the revised manuscript (lines 151-153).

Other studies have suggested that T4 cannot cross the placenta unless the type 3 deiodinase is blocked which differs from this study. This paper should be referenced and discussed.

We are aware of the study by Mortimer et al (DOI: 10.1210/jcem.81.6.8964859) that showed T4 could transport across human term placenta only when D3 was blocked by iopanoic acid. In our previous study (DOI: 10.1089/thy.2022.0406), we confirmed their findings in perfusion experiments with and without iopanoic acid on maternal-to-fetal T4 transfer (Figure 1), which we discussed in the discussion of our previous publication.

However, in that previous study we also found that transport of T4 in human term placenta is asymmetrical with fetal-to-maternal transfer being more rapid than maternal-to-fetal transfer. However, when adding albumin (BSA) to the fetal circulation (which was not done by Mortimer et al), we prevented re-uptake of T4 and were able to show fetal T4 accumulation in the absence of iopanoic acid. Therefore, we optimized the model by maintaining the physiological conditions in which the type 3 deiodinase is present.

Following the reviewer’s suggestion, we discussed this paper between lines 144-146.

How specific is the action of silychristin? Does it have effects on other thyroid hormone transporters that may facilitate TRIAC transport?

In a previous study, we tested the specificity of silychristin for the thyroid hormone transporters expressed in human term placenta (Figure 2 in DOI: 10.1089/thy.2021.0503). Silychristin potently inhibited MCT8 with an IC50 of 0.12 µM and at a much higher concentration 10 µM it also inhibited OATP1A2 by ~40%. However, OATP1A2 does not transport TRIAC (unpublished data). Therefore, we feel that silychristin is unlikely to have relevant effects on other placental thyroid hormone transporters that may facilitate TRIAC transport.

We have added discussion about this between lines 146-151.

Although TRIAC is able to cross the placenta, it is likely that it still would not be able to cross into the fetal brain making its use somewhat limited. Additionally, it has been suggested that TRIAC exposure may also be a neurodevelopmental risk ((Barez-Lopez et al., 2016) and (Yamauchi et al. 2022 TRIAC disrupts cerebral thyroid hormone action via a negative feedback loop and heterogenous distribution among organs. BioRXiv). This should be discussed.

We thank the reviewer for raising this important point. We would like to respectfully point out that TRIAC in different animal models for MCT8 deficiency has been able to restore abnormal brain development (DOI: 10.1210/me.2014-1135, DOI: 10.3390/ijms232415547, DOI: 10.1530/JOE-16-0323, DOI: 10.1242/dmm.027227).

Specifically, TRIAC administration between postnatal day 1 and 12 restored T3-dependent neural differentiation in the cerebral and cerebellar cortex in Mct8/Oatp1c1 double knockout mice, which represents a relevant mouse model recapitulating the neurological phenotype in patients with MCT8 deficiency (doi: 10.1210/me.2014-1135).

Barez-Lopez (2016) administered TRIAC to Mct8 single knock-out mice. As Oatp1c1 is a redundant T4 transporter in mice, brains of these animals are only mildly hypothyroid and do not recapitulate the severity of the phenotype seen in humans. Hence, we disagree with the conclusion of these authors as they utilized a non-optimal mouse model (DOI: 10.1210/jc.2012-3759). Yamauchi et al. (doi: 10.1016/j.isci.2023.107135) showed that TRIAC content in cerebral cortex did not increase after oral administration of TRIAC after postnatal day 21 in euthyroid and hypothyroid mice. Moreover, they utilized the same dose as T3 as comparison, while TRIAC should be dosed 10-times higher ( DOI: 10.1210/me.2014-1135). Using such a dose, it is very much understandable that TRIAC only affects the hypothalamus-pituitary-thyroid axis, but is insufficient to exert thyroid hormone action in the brain.

We would like to emphasize that there is >70-year experience with TRIAC in humans for other conditions. Neurotoxicity has never been observed. Currently, TRIAC is being studied in high dosages in young children with MCT8 deficiency. The study protocols have been approved by different Ethics Committees as well has been discussed with regulatory authorities.

In the revised manuscript, we have incorporated some information that there is sufficient data in different animal models showing that TRIAC is able to enter the brain.

The data for the control group was used in a previous publication - were the data collected at the same time? Ideally, the control vs silichrystin treated placental cotyledons should be from the same placental samples.

We agree with the reviewer that ideally the control and silychristin treated cotyledons should be matched from the same placenta. However, in practice, it is extremely difficult to realize this for many reasons. In our perfusion experiments, only ~30% of the perfusions succeeded as determined by the criteria of the quality controls (antipyrine and FITC-dextran). Moreover, using two cotyledons from one placenta is not feasible for different reasons (e.g. absence of two intact cotyledons due to damage during delivery; one cotyledon is intact during perfusion, whereas the other is not; one cotyledon has maternal antipyrine diffused to the fetal circulation whereas the other one is not. Therefore, due to practical obstacles and strict quality control criteria, it is not likely to obtain such data of these from different placentas.

Minor comments

T4 and TRIAC were prepared in 0.1N NaOH and silychristin in DMSO. Do NaOH or DMSO affect membrane transporters? Were vehicle controls used in the perfusion experiment?

We dissolved T4 and TRIAC in 0.1 N NaOH and silychristin in DMSO and added them to the perfusion buffer at a 1000 times dilution. For NaOH, it is commonly used in transport assays. Such NaOH and DMSO dilutions did not affect thyroid hormone transport in COS1 cells; therefore we did not include vehicle control DMSO in perfusion experiments.

Were the silichrystin vs control samples matched from the same placentas?

The silychristin and control samples were not matched from the same placentas for the reasons mentioned above.

In Figure 1C, why is there an increase in TRIAC on the maternal side between the first and second time points?

As we sometimes observed in our perfusion experiments with other compounds, at t=0 min (the first time point), the buffer is not aerated and still heterogeneous, leading to differences in the measured concentrations of the TRIAC. Therefore we also included t=6 min (the second time point) to get a more accurate starting concentration.

In figure 1C, TRIAC movement from maternal to fetal side in silichrystin treated placenta is shown but there is no data from untreated placenta? TRIAC transport may be reduced but we cannot tell without a control to compare it to. This should be included.

We thank the reviewer for raising this question, which is similar to comment 3 of Reviewer 1. Hence, we would like to refer to our response to the comment 3 of Reviewer 1.

Reviewer #2 (Significance (Required)):

This study is interesting and adds to the current gaps in the knowledge of transplacental thyroid hormone transport. There is still very limited information around how thyroid hormones cross the placenta despite many groups working on this over the years. However, the manuscript would be more interesting if the placental transporter for TRIAC was identified. There are several clinical trials already underway looking at how TRIAC therapy may be useful in this condition and it may even be detrimental. If TRIAC can cross the placenta its use may still be problematic since others have shown that it cannot cross the into the MCT8 deficient brain from the circulation and must be delivered directly into the brain (Barez-Lopez et al., 2019). This is a small study and is fairly limited however it would be interesting to those, like me, with an interest in endocrinology, placental biology and pregnancy.

Barez-Lopez, S., Grijota-Martinez, C., Liao, X.H., Refetoff, S. and Guadano-Ferraz, A., 2019. Intracerebroventricular administration of the thyroid hormone analog TRIAC increases its brain content in the absence of MCT8, PLoS One. 14, e0226017.

Barez-Lopez, S., Obregon, M.J., Martinez-de-Mena, R., Bernal, J., Guadano-Ferraz, A. and Morte, B., 2016. Effect of Triiodothyroacetic Acid Treatment in Mct8 Deficiency: A Word of Caution, Thyroid. 26, 618-26.

We are pleased to see that the reviewer agrees that our data are a relevant addition to the field. We have alluded to the discussion in the field in the revised manuscript (lines 129-132).

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Referee #2

Evidence, reproducibility and clarity

Short summary of findings:

The authors used silychristin to selectively block the thyroid hormone transporter MCT8 in perfused human placenta. This was done to model the MCT8 deficient placenta in the rare genetic condition called Allan Herndon Dudley Syndrome. They then showed that the thyroid hormone analogue TRIAC can still cross the placenta and may be a potential treatment to prevent some of the effects of thyroid hormone deficiency in the affected fetus.

Major comments:

The absence of binding proteins in the maternal circulation is an issue since protein bound thyroid hormones can also be taken up by trophoblasts. Additionally, the placenta produces and secretes transthyretin and albumin into the maternal circulation - was this taken into account?

Other studies have suggested that T4 cannot cross the placenta unless the type 3 deiodinase is blocked which differs from this study. This paper should be referenced and discussed.

How specific is the action of silychristin? Does it have effects on other thyroid hormone transporters that may facilitate TRIAC transport?

Although TRIAC is able to cross the placenta, it is likely that it still would not be able to cross into the fetal brain making its use somewhat limited. Additionally, it has been suggested that TRIAC exposure may also be a neurodevelopmental risk ((Barez-Lopez et al., 2016) and (Yamauchi et al. 2022 TRIAC disrupts cerebral thyroid hormone action via a negative feedback loop and heterogenous distribution among organs. BioRXiv). This should be discussed. The data for the control group was used in a previous publication - were the data collected at the same time? Ideally, the control vs silichrystin treated placental cotyledons should be from the same placental samples.

Minor comments

T4 and TRIAC were prepared in 0.1N NaOH and silychristin in DMSO. Do NaOH or DMSO affect membrane transporters? Were vehicle controls used in the perfusion experiment?

Were the silichrystin vs control samples matched from the same placentas?

In Figure 1C, why is there an increase in TRIAC on the maternal side between the first and second time points? In figure 1C, TRIAC movement from maternal to fetal side in silichrystin treated placenta is shown but there is no data from untreated placenta? TRIAC transport may be reduced but we cannot tell without a control to compare it to. This should be included.

Significance

This study is interesting and adds to the current gaps in the knowledge of transplacental thyroid hormone transport. There is still very limited information around how thyroid hormones cross the placenta despite many groups working on this over the years. However, the manuscript would be more interesting if the placental transporter for TRIAC was identified. There are several clinical trials already underway looking at how TRIAC therapy may be useful in this condition and it may even be detrimental. If TRIAC can cross the placenta its use may still be problematic since others have shown that it cannot cross the into the MCT8 deficient brain from the circulation and must be delivered directly into the brain (Barez-Lopez et al., 2019). This is a small study and is fairly limited however it would be interesting to those, like me, with an interest in endocrinology, placental biology and pregnancy.

Barez-Lopez, S., Grijota-Martinez, C., Liao, X.H., Refetoff, S. and Guadano-Ferraz, A., 2019. Intracerebroventricular administration of the thyroid hormone analog TRIAC increases its brain content in the absence of MCT8, PLoS One. 14, e0226017.

Barez-Lopez, S., Obregon, M.J., Martinez-de-Mena, R., Bernal, J., Guadano-Ferraz, A. and Morte, B., 2016. Effect of Triiodothyroacetic Acid Treatment in Mct8 Deficiency: A Word of Caution, Thyroid. 26, 618-26.

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 show expression of the thyroid hormone transporter MCT8 in the human placenta. The MCT8-inhibiting compound sylchristine reduces the transfer of T4 from the maternal to the fetal side and accordingly reduces T4 degradation by DIO3. Since maternal thyroid hormones are relevant for neurodevelopment before the onset of fetal thyroid gland function, disruption of MCT8 transport, as occurs in the Allan-Herdon-Dudley syndrome, may contribute to the neurodevelopment failure present in these patients. The results of the transfer experiments are clear and support the authors' conclusions.

Minor comments:

1. Line 71: please provide some references on the immaturity of the blood.brain barrier before 18 months. The endothelial cells may have tight junctions when the vessels sprout in the CNS. "Maturity" implies the full complement of the neurovascular unit, i.e., pericytes and astrocytes. So, please clarify this point, even if it does not contradict the experimental results showing the role of placental MCT8.
2. It is unclear if the partial effect of sylchristine on T4 transport means that MCT8 contribution is also partial and other transporters contribute.
3. Lines 113-114. I missed the controls measuring TRIAC transport without sylchristine, or do the authors have strong reasons to assume that sylchristine does not affect TRIAC transport? If so, it should be stated.

Significance

This study confirms the presence of MCT8 in the human placenta and adds additional data to demonstrate its functionality with experiments using placental perfusion.

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Reply to the reviewers

We appreciate the positive feedback from both reviewers and their critical comments, which will help us to improve the manuscript. Below, we provide a point-by-point response and how we propose to address their queries and comments.

As the laboratory is currently undergoing a major transition, we propose essential experiments that are realistic to perform under these circumstances. We are positive that we can address all the most critical points identified by the reviewers.

Suggestions for minor changes to the figures are already included.

We also include responses to questions the reviewers raise.

Reviewer #1 (Evidence, reproducibility and clarity):

Major comments:

1 - The authors assessed acridine orange incorporation in BECs upon LiverZap and concluded that LiverZap triggers hepatocyte-specific cell death without a bystander effect in adjacent cells (Figure 1 D-E). What happened to endothelial cells, which could also be affected either directly by ROS production in hepatocytes or indirectly by gross morphological changes in tissue organization?

Response:

The reviewer raises two excellent points:

(i) Bystander effect of hepatocyte-produced ROS on endothelial cells: the cell death analysis included in the manuscript, shows that Acridine Orange staining overlaps with hepatocyte _tg(fabp10a:dsRed) expression, but not with biliary tg(tp1:H2B-mCherry) indicating cell death is specific to hepatocytes. Moreover, singlet oxygen species as produced by LiverZap have been shown to have a very short half-life and short range of action, suggesting that neighbouring cells are unlikely affected (Liang et al., 2020).

PLAN: Investigate potential bystander effect in endothelial cells, by activating the LiverZap tool in livers expressing transgenic tg(kdrl:mcherry) marking the vascular network followed by live staining with Acridine Orange at 8 hours post illumination.

(ii) indirect effects of morphological tissue changes on endothelial cells: studying the tissue response of the vascular network to hepatocyte ablation would be very interesting. A separate and detailed study would be required to generate meaningful data and insights into said process. This could encompass for instance the use of the transgenic endothelial _tg(kdrl:mcherry) line for LiverZap experiments and parallel those in Figure 4A-S. Thus, it seems beyond the scope of this work.

NO CHANGES PROPOSED.

2 - The evaluation criteria for distinguishing mCherry and cells in imaging experiments should be clearly described in the methods section. The authors should also provide some quantitative data regarding the level of correlation between the mCherry hepatocytes and the BEC-derived hepatocytes strictly defined based on the TP1-H2B-EGFP lineage tracing, as the former was used as a surrogate marker for the latter in some experiments.

Response:

Here, we believe the reviewer refers to the Tp1:H2B-mCherry-based lineage tracing, since the tg(tp1:egfp) line has not been used for this purpose. Similar to previous studies in the regeneration field (e.g. Choi et al., 2014; He at al., 2014), we have used histone inheritance of Tp1:H2B-mCherry for short-term lineage tracing. Tp1:H2B-mCherry-based lineage tracing was assessed on the whole organ level, for which we will describe the quantification pipeline. Tp1:H2B-mCherrylow cells were identified as BEC-derived hepatocytes after severe hepatocyte ablation, as shown in Fig. 2A,C, correlating with hepatocyte marker tg(fabp10a:GFP) expression. Tp1high and Tp1low cell numbers were quantified for 12, 24, 48 and 72 hpi and can be added as supplementary information.

PLAN: Update the material and methods section and produce a more detailed description. This would include the following information: Whole-mounted livers of tg(tp1:H2B-mCherry) fish were stained for mCherry and imaged using an Leica SP8 confocal microscope. Image processing was carried out using the Imaris software. All mCherry-expressing cells in the liver were masked using the “spots” function, which allows quantification of signal intensity of all cells, represented by a sphere. Tp1high and Tp1low cells were identified using an automatically generated intensity threshold. Due to intensity differences with increasing imaging depth/z-position, segmented Tp1high cells were manually curated.

To showcase the analysis strategy, we propose to include an example showing original image data, semi-automated quantification at the surface and deep tissue levels, as well as the overall Tp1:H2B-mCherry intensities for all positive cells and specifically Tp1high cells for all z-positions of an entire liver (see data figure below). This example could be included as supplementary data. Likewise, cell number quantification for Tp1high and Tp1low across regeneration can be added to Fig. S2.

Fig. Quantification of Tp1:H2B-mCherryhigh cells. (A,B) 10 µm maximum intensity projections from whole mount stained tg(LiverZap);tg(tp1:H2B-mCherry) livers at 48 hpi: at the surface (A-A’) and deep in the liver (B-B’). Tp1high cells are identified by fluorescence intensity of segmented nuclei, outlined in yellow (A’ and B’). Graphs showing distribution of all Tp1:H2B-mCherry nuclei (C) and Tp1high nuclei (D) by fluorescence intensity and z-position (C). The intensity of all mCherry+ nuclei decreases with increasing z-position (C-D). The dotted line outlines the liver in A-B’.

3 - OPTIONAL: In the locally restricted ablation model, do hepatocytes located adjacent to the ROI proliferate and/or contribute to the regeneration of the injured region?

Response:

An important consideration, as highlighted by the reviewer, is whether neighbouring hepatocytes also contribute to regeneration following ROI ablation.

PLAN: To address this point, LiverZap ROI ablation will be followed by cell proliferation analysis using an EdU incorporation assay at 24 and 72 hpi. These time points are selected based on the proliferation results following global LiverZap ablation; see Fig. 2D-F. The experiment will be performed in a tg(tp1:H2B-mcherry); _tg(fabp10a:gfp)_background to distinguish proliferating GFP-positive hepatocytes, which are H2B-mCherry-negative, from LPC-derived hepatocytes that have inherited H2B-mCherry (Tp1low). The resulting insights may help to refine hypotheses regarding the process(es) stimulating the formation of new hepatocytes adjacent to the ablated region.

4 - OPTIONAL: Figure 4, A-S. It should be of significant interest if the authors could also analyze the BEC dynamics using the locally restricted hepatocyte ablation model, comparing those in the injured region (ROI) and the outside of the ROI.

Response:

We agree with the reviewer that this is the exciting next question, as it likely would provide insights into the cellular mechanism by which the biliary network is de- and re-constructed, as well as the mechanism by which BECs outside the ROI may initiate the LPC response to give rise to hepatocytes in a semi-systemic response. For this, the experimental set-up introduced in Fig.4J-P, in which BECs in the ROI are distinguished from adjacent ones by photoconversion, would be followed by extended live light-sheet microscopy of the regenerating liver. Due to the complexity, extent of the experiments and current unavailability of a light-sheet microscope, we would address this optional comment in future investigations.

NO CHANGES PROPOSED.

5A- Figure 4, T-V'. The data shown here for the changes in E-cadherin distribution is difficult to understand and interpret. The authors should provide magnified images and better description on how to distinguish the membranous (spotted signals?) and intracellular localization. Quantitative assessment should certainly be a plus, if possible.

Response:

We appreciate that it may be difficult to recognize the changes in E-Cadherin localisation, in particular at BEC membranes, given that there are intracellular puncta, and that E-Cadherin is expressed both in BECs and hepatocytes. We are convinced of the related data described in Figures 4 and S4, because the first experiment allowed quantification of the staining using both Tp1:H2B-mCherry to identify BECs and intestinal E-Cadherin for normalisation, which revealed a 51% E-Cadherin reduction at BEC cell membranes following injury. Unfortunately, the signal-to-noise ratio declined in consecutive experiments precluding further quantification although we could still observe a change in localisation. We tested alternative antibodies against E-Cadherin as well as optimized staining protocols, yet without success.

5B - OPTIONAL: In relation to the above point, it is this reviewer's candid impression that the very last part regarding the possible role of E-cadherin dynamics in regulating the biliary network remodeling is still preliminary compared to the remaining parts, thereby rather depreciating the value of the entire manuscript. Perhaps this part could be published separately, together with more functional evidence regarding the causal relationship between them (e.g., showing the effect of Ecadherin knockdown in hepatocytes on the biliary remodeling and the induction of the BECdependent regeneration program)

Response:

PLAN: Following this reviewer’s and reviewer 2’s comments and suggestions, we agree to remove the data on E-Cadherin. Loss of adhesion as a mechanism for adopting an LPC-state remains very exciting, future investigations with novel tools to monitor and modulate E‑Cadherin expression in BECs would thus be needed.

6 - Do zebrafish livers possess lobular structures with the portal-to-central vein axis and the metabolic zonation as typically observed in mammalian livers? As has been described in the manuscript, the "localized" injury patters in the mammalian livers usually occur at the sub-lobular structure levels (i.e., peri-portal region-restricted vs. peri-central region-restricted). Although the "localized" injury model described in this study using the zebrafish livers was indeed localized from the viewpoint of the entire organ (or the lobe), it still seemed much more "global" when considering those situations in the mammalian livers, so that the authors' claim that the former recapitulating the latter might be too exaggerated and somehow misleading. The authors should clarify and discuss this point in the manuscript.

Response:

The reviewer raises an important point, and it seems that our wording might not have been clear. In mammals, boundaries between injured and healthy tissue arise, because liver injuries frequently occur at the sub-lobular level. Although zebrafish livers are composed of metabolically diverse hepatocytes, a spatial arrangement comparable to mammalian zonation has so far not been identified (Morrison et al. 2022; Oderberg and Goessling, 2023). Yet, the liver lobes in the adult zebrafish have a central vein and periportal veins at the periphery of the organ, similar to the mammalian lobular organisation (Ota et al. 2022). Therefore, the scale of injury in the mammalian setting and the ROI-ablation model introduced in the current work differs. It, nevertheless, creates boundaries of healthy and injured liver tissue relevant for uncovering dynamic cellular processes mediating tissue repair in chronic liver disease. Importantly, with its suitability for advanced live imaging and optogenetic methods (e.g. photoconversion), LiverZap, complements mammalian models, in which this is still challenging. This offers therefore the powerful opportunity to employ LiverZap to screen for dynamic repair behaviours, which subsequently can be validated in a target approach in mammalian injury models.

PLAN: To describe the relevance of our ROI ablation paradigm for elucidating repair processes at the interface of injured and healthy tissue more precisely. We will further edit and clarify text to place the ROI ablation into the context of hepatic injuries at the sub-lobular level throughout the mammalian liver.

Minor comments:

7 - Figure 4. Panels D and G should correspond to the same one image and the way of labeling be changed (as in Figure 1G). Likewise, in panel J, the bars shown separately as "M" and "S" at 12 dpi should correspond to the same data, so that they should be unified as one bar.

Response:

Thank you for pointing this out, this is changed in the updated figures; panels Fig. 4D and I.

8 - Figure S3L. How was the ROI border defined? Perhaps the shape of the ROI should change significantly during regeneration due to dynamic tissue remodeling processes, thereby moving the position of the border as well.

Response:

The ROI border was defined as the interface between photoconverted and non-converted BECs. We concur with the reviewer’s notion that cell movement and rearrangement may occur during the regeneration process (see Fig. 4A-J), and the initially straight ROI border could consequently change during the regeneration process. Nevertheless, the border between photoconverted and non-converted BECs persists, serving as a landmark for the measurements shown in Figure S3L.

Fig.: Quantification strategy for determining the region exhibiting an LPC-response outside the ROI ablation region. The dashed line of the ROI indicates morphogenetic changes of the interface between photoconverted and nonconverted cells over time due to repair-related cell rearrangement.

PLAN: In the revised manuscript, we propose to include the below schematic as panel J to Figure S3. Moreover, we also suggest to change the solid line of the squares indicating the ROI area in figure panels 3C,G,O,P and S3D,H,K into a dashed line at the interface between photoconverted and non-converted tissue (see below figure as an example).

9 - The authors should comment in the manuscript as to whether the system can be applicable for induction of more restricted areas (e.g., at a single hepatocyte level; in particular metabolic zones, if existing), as well as for ablation of other hepatic cell types such as BECs and endothelial cells.

Response:

Indeed, the optogenetic nature of the LiverZap system allows to induce hepatocyte death at the single cell level, as well as any defined region of interest that can be generated by the light source (e.g. confocal microscope software).

Likewise, the FAP-TAP system can be easily applied to BECs or endothelial cells, or any cell type for which a specific promoter has been identified to drive the genetic FAP component fluorogen-activating protein dL5**.

Response:

PLAN: Both points will be included in the discussion section of the manuscript.

Reviewer #2 (Evidence, reproducibility and clarity):

MAJOR COMMENTS:

1 - The LiverZap is an elegant new tool to induce localized ablation of hepatocytes. It is not as claimed by the authors a real breakthrough: (1) While localized ablation is nice compared to NTR-MTZ model in zebrafish, mice model such as CCl4 chronic injury can also study the interaction between healthy and injured tissue. (2) Although not using MTZ, the system still requires injection or exposure to malachite green derivate dye MG-2I. A few searches suggest that this compound could induce toxicity. Can the authors study and compare the toxicity of malachite green derivate dye MG-2I to the toxicity of MTZ? This is important as this would be indeed a strong argument in favor of the presented tool.

Response:

Point 1 – studying interactions between healthy and injured liver tissue: The reviewer is of course correct that interactions between healthy and injured tissue can also be studied in the mouse. However, ROI ablation with the LiverZap system can be combined with live imaging, thereby enabling the observation of cellular responses of the same sample over time, at a resolution currently difficult to achieve in mammals. Moreover, the possibility to induce cell death in a defined ROI, also allows to simultaneously employ other genetic tools, including cell-type specific lineage tracing by photoconversion, which is difficult to achieve in mammalian systems. The finding that BECs beyond the ROI of hepatocyte ablation produce new hepatocytes by a LPC response, illustrates the power of this approach. The optogenetic LiverZap ablation system would therefore complement existing mammalian and zebrafish liver regeneration models.

PLAN: to include a more detailed discussion of this point and the complementary knowledge that can be gained in the discussion section.

Point 2 – MG-2I toxicity__: Indeed, as described in the manuscript, the FAP-TAP system, underlying LiverZap hepatocyte ablation, requires MG-2I incubation for the formation of the photosensitiser. Compared to the NTR/MTZ system, incubation with MG2I is short, requiring <3 hours in contrast to more than 24hours MTZ incubation. The system, including MG-2I has also been employed in cells, as well as in the zebrafish heart and nervous system without reported adverse effects (He et al., 2016; Xie et al., 2020). Consistently, we have not observed any apparent adverse effects between 0-72 hpi following 3-18 hour MG-2I incubation (unpublished). Nevertheless, toxicity studies evaluating survival upon MG-2I incubation have not yet been carried out and may be required for comparison with MTZ.

PLAN: To perform toxicity studies for MG-2I, similar to those previously performed for MTZ (e.g. Mathias et al. 2014), in which larval survival after 3, 24 and 48 hour MG-2I exposure starting at 4 dpf will be assessed daily until 8 days post fertilisation.

2 -The term ablation is choose because it is anticipated that it induces heaptospecific death. However, the consequences of cell death is not shown. In particular, the inflammatory immune response is not shown nor discussed.

Response:

The reviewer raises an interesting point, namely the inflammatory immune response, which is not the focus of this manuscript. Acridine Orange- and TUNEL-positive cells during the ablation process indicate that the reactive oxygen species produced by the FAP-TAP system cause hepatocyte apoptosis. We predict that this would recruit and be cleared by macrophages with little or no inflammatory response, like findings for the NTR-MTZ system (Stoddard et al., 2019). However, the role of neutrophils is unclear due to a possible direct effect of MTZ on this cell type.

PLAN: We will include this point in the discussion.

Future in-depth live imaging of transgenic reporters will be required for detailed studies of macrophage and neutrophil recruitment and their role in efferocytosis, including transcriptome analysis of specific gene signatures to detect an inflammatory response.

3 - The difference between mild and severe ablation is hard to grasp. Can the authors explain more clearly the differences between mild and severe: what are the criteria as there is no difference in liver volume between mild and severe ablation? How do you achieve mild or severe ablation? It appears that the severity of the ablation is judged a posteriori and not decided per the experiment.

Response:

Concerning the first point, there must be a misunderstanding. Mild and severe hepatocyte ablation result in clearly different liver sizes, for instance at 30 hpi, the end of ablation, liver volumes are reduced by 23 % for mild or 64 % for severe cases (Fig. 1Q). This is supported by representative image data in Figs. 1F-P and S1A-C. Nevertheless, for consistency, we had represented the 12 hpi volume data as the same two data bars, although we cannot distinguish them yet at that timepoint of the experiment, as shown by images in Fig. 1F-G.

PLAN: Adjust Fig.1Q and represent the 12 hpi liver volume data as a shared graph for mild/severe ablation, see included figure 1Q. We propose to similarly represent all 12 hpi quantifications, as represented in Figs. S1F, 2D-F and S2A.

For the second point, the reviewer is correct that ablation severity is evaluated and determined between 24-30 hpi, at the end of hepatocyte ablation, given there is some variability in the response. Nonetheless, both length of 660nm illumination and oxygen availability can be used to shift the proportion of mild and severe ablation, depending on the desired outcome (Figs. 1Q, S1G-H).

NO CHANGES PLANNED.

4 - The work supports that biliary-driven regeneration also occurs when hepatocyte ablation happens in a small area of interest. Our knowledge is that you need a large defect in hepatocyte or a chronic liver injury ro activate the BDC-driven auxiliary process for regeneration. Could this be a specificity of the fish model?

Response:

Like the reviewer, our understanding is that severe hepatocyte loss, senescence or chronic liver injury activate BEC-derived regeneration in mammals and in zebrafish. All these cases are characterised by substantial reduction of local hepatocyte density or loss of function (in senescence). Given the overall hepatocyte loss is only 10-20% in the ROI model, the induction of the local LPC response was very surprising, on the other hand it corresponds to a near complete local hepatocyte depletion. The hepatobiliary architecture in zebrafish is similar to that of the mammalian ductular reaction, an adaptation of the biliary network to severe hepatocyte loss. In both cases, the majority of hepatocytes connect directly via their apical canaliculi to biliary ductules to ensure physiologic transport of hepatocyte products, often preceding the LPC response (Sato et al., 2019; Caviglia et al., 2022). Therefore, we propose that the LPC response following ROI hepatocyte ablation is not specific to the zebrafish model, but a common mechanism elicited across species and related to the severity of the injury and the configuration of the hepatobiliary network at the time of injury, such as the ductular reaction.

PLAN: To edit the text and discuss this point clearly.

5 - Pathways revealed to control liver regeneration or BEC-driven regeneration in fish have not be found to have a similar drastic predominance in rodents. This mitigate perhaps the use of fish for this type of research?

Response:

On the contrary, zebrafish has been established and validated as a model to investigate and elucidate developmental hepatic programs as well as regeneration (Goessling and Sadler, 2015; Wang et al., 2017). However, we acknowledge that more comparative studies are needed to understand the molecular pathways driving regeneration both in zebrafish and mammals and their similarity.

Specifically, zebrafish and mammals display high conservation in the parenchymal and non-parenchymal cell types of the liver as well as their developmental programs (Goessling and Sadler, 2015; Wang et al., 2017). Using different injury paradigms in zebrafish, including ethanol, acetaminophen toxicity and the pharmacogenetic NTR-MTZ model, it has been shown that cellular responses to liver injury are also remarkably conserved with mammals where hepatocyte proliferation governs repair after mild injury while severe injury repair is driven by conversion of BECs into LPCs (So, et al., 2020; Forbes and Newsome, 2019). Major pathways, such as Wnt, FGF and BMP signaling show conserved functions in restorative hepatocyte proliferation (Goessling et al., 2008; Kan et al. 2009, Böhm et al 2010). At present, only very little is known about the molecular mechanisms controlling the BEC/LPC to hepatocyte conversion particularly in rodent models (Kim et al., 2023), while a number of zebrafish studies have started to elucidate the signals governing the different steps of this process (Kim et al., 2023), due to the relative ease of using the larval zebrafish model for this work. Notably, the Notch pathway plays multiple roles in both mouse and zebrafish LPC-mediated repair (Minnis-Lyons et al., 2021; Huang et al 2014; Russel et al.,2019), however further work will be necessary to determine the detailed corresponding functions. Therefore, future work in both rodents and zebrafish will be essential to uncover the molecular mechanisms of this repair process relevant for chronic injury. Given the large conservation of developmental and repair mechanism between mammals and zebrafish observed so far, it is highly likely that this will also apply to LPC-mediated repair. Studies promise to uncover even greater similarity between zebrafish and human (e.g. Fang et al 2011), underscoring the power of using complementary vertebrate models.

PLAN: To edit the text in the introduction and discussion to clarify and highlight the similarities, differences, and opportunities the zebrafish model offers for understanding the mechanisms of vertebrate liver regeneration in general and in particular by using the LiverZap system.

6 - The authors show that in the case of mild ablation, hepatocytes are responsible for replenishment of the parenchyma, but in the context of severe ablation, LPC-mediated regeneration takes control. However, when the authors perform localized and controlled ablation, which is small (around 10-20%) and, to my understanding, a mild / local ablation, however the authors show that LPC mediates the regeneration. Can the authors explain the discrepancy between their results?

Response:

We agree with the reviewer that the LPC response in the smaller, local ROI ablation was unexpected. However, it could be explained by the following: while such ROI hepatocyte ablation represents only a 10-20% ablation of the total hepatocyte population, by sheer numbers comparable to a mild global ablation, the near-complete local hepatocyte loss however makes it more similar to a severe or chronic global injury. Notably, the zebrafish hepatobiliary architecture in zebrafish is similar to that of the mammalian ductular reaction, an adaptation of the biliary network to severe hepatocyte loss. In both cases, the majority of hepatocytes connect directly via their apical canaliculi to biliary ductules to ensure physiologic transport of hepatocyte products, often preceding the LPC response (Sato et al., 2019; Caviglia et al., 2022). We hypothesize that if a similar local, near complete hepatocyte loss would be induced in a mammalian liver exhibiting a ductular reaction, it would similarly induce local LPC-mediated repair. Since this is, to our knowledge not possible, the LiverZap model represents a unique opportunity to induce the LPC-response in a controlled manner and in addition investigate the underlying cellular and molecular processes of injured and adjacent healthy tissues at high resolution in an in vivo context.

PLAN: We will edit the discussion to clarify this important point.

7 - The last part of the paper about E-Cadherin expression is not convincing. I am not sure about the quality of the IF stainings of E-Cadherin, and it is not helping proving the point of the authors. Can the authors provide better stainings for this figure?

Response:

(Same response as to point 5A+B of reviewer 1). We appreciate that it may be difficult to recognize the changes in E-Cadherin localisation, in particular at BEC membranes, given that there are intracellular puncta and that E-Cadherin is expressed both in BECs and hepatocytes. We are convinced of the related data described in Figures 4 and S4, because the first experiment allowed quantification of the staining using both Tp1:H2B-mCherry to identify BECs and intestinal E-Cadherin for normalisation, which revealed a 51 % E-Cadherin reduction at BEC cell membranes following injury. Unfortunately, the signal to noise ratio declined in consecutive experiments, while we could still observe a change in localisation, it challenged a meaningful quantification. We tested alternative antibodies against E-Cadherin, yet without success.

PLAN: Following both reviewers’ comments and suggestions, we agree to remove the data on E-Cadherin.

8 - Could the authors provide a bit more information on the live imaging. Exactly how do they achieve imaging for such a long time?

Response:

Thank you for pointing this out, the information was not very detailed. We used relatively standard mounting conditions (low-melting point agarose and Tricaine anaesthesia, see below for details), combined with light-sheet microscopy, which was the key to achieving the long imaging. We believe that in addition to the known gentle imaging condition, the mounting set-up is critical as the fish is completely suspended in a very low-percentage, low melting point agarose within a large volume of embryo medium.

PLAN: Update the material and methods section with the following details: Long-term live imaging was performed using a LS1 Live light sheet microscopy system (Viventis Microscopy Sàrl). Larvae were with anesthetized with 0.4% Tricaine and mounted ventrally in 0.8% low melting point agarose in E3/PTU media supplemented with 0.16% tricaine. Once the agarose solidified, the chamber was filled with E3/PTU with 0.16% Tricaine to maintain anaesthesia. A 25X objective was used and acquisition was performed every 20 minutes.

MINOR COMMENTS:

9 - It is hard to imagine the full-size liver in Figure 1, bad contrast. Can the authors manually delineate it?

Response:

The livers in this figure are now outlined in the updated figures, see new Figure 1.

10 - "This finding is very surprising, since current understanding in the field links the generation of new hepatocytes from BECs/LPCs with global hepatocyte death." This statement lacks references.

Response:

PLAN: To add the following primary references to the above sentence: (Choi et al., 2014; He et al., 2014; Manco et al., 2019; Raven et al., 2017) and recent review (Kim et al_._, 2023).

REFERENCES

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Caviglia S, Unterweger IA, Gasiūnaitė A, Vanoosthuyse AE, Cutrale F, Trinh LA, Fraser SE, Neuhauss SCF, Ober EA. Fraeppli: a multispectral imaging toolbox for cell tracing and dense tissue analysis in zebrafish. Development. 2022 doi:10.1242/dev.199615.

Choi TY, Ninov N, Stainier DY, Shin D. Extensive conversion of hepatic biliary epithelial cells to hepatocytes after near total loss of hepatocytes in zebrafish. Gastroenterology. 2014 doi:10.1053/j.gastro.2013.10.019.

Fang L, Green SR, Baek JS, Lee SH, Ellett F, Deer E, Lieschke GJ, Witztum JL, Tsimikas S, Miller YI. In vivo visualization and attenuation of oxidized lipid accumulation in hypercholesterolemic zebrafish. J Clin Invest. 2011 doi: 10.1172/JCI57755.

Forbes SJ, Newsome PN. Liver regeneration - mechanisms and models to clinical application. Nat Rev Gastroenterol Hepatol. 2016 doi:10.1038/nrgastro.2016.97

Goessling W, North TE, Lord AM, Ceol C, Lee S, Weidinger G, Bourque C, Strijbosch R, Haramis AP, Puder M, Clevers H, Moon RT, Zon LI. APC mutant zebrafish uncover a changing temporal requirement for wnt signaling in liver development. Dev Biol. 2008 doi:10.1016/j.ydbio.2008.05.526.

Goessling W, Sadler KC. Zebrafish: an important tool for liver disease research. Gastroenterology. 2015 doi:10.1053/j.gastro.2015.08.034.

He J, Lu H, Zou Q, Luo L. Regeneration of liver after extreme hepatocyte loss occurs mainly via biliary transdifferentiation in zebrafish. Gastroenterology. 2014 doi:10.1053/j.gastro.2013.11.045.

He J, Wang Y, Missinato MA, Onuoha E, Perkins LA, Watkins SC, St Croix CM, Tsang M, Bruchez MP. A genetically targetable near-infrared photosensitizer. NatMethods. 2016 doi:10.1038/nmeth.3735.

Huang M, Chang A, Choi M, Zhou D, Anania FA, Shin CH. Antagonistic interaction between Wnt and Notch activity modulates the regenerative capacity of a zebrafish fibrotic liver model. Hepatology. 2014 doi:10.1002/hep.27285.

Kan NG, Junghans D, Izpisua Belmonte JC. Compensatory growth mechanisms regulated by BMP and FGF signaling mediate liver regeneration in zebrafish after partial hepatectomy. FASEB J. 2009 doi:10.1096/fj.09-131730.

Kim M, Rizvi F, Shin D, Gouon-Evans V. Update on Hepatobiliary Plasticity. Semin Liver Dis. 2023 doi: 10.1055/s-0042-1760306.

Liang P, Kolodieznyi D, Creeger Y, Ballou B, Bruchez MP. Subcellular Singlet Oxygen and Cell Death: Location Matters. Front Chem. 2020. doi:10.3389/fchem.2020.592941.

Manco R, Clerbaux LA, Verhulst S, Bou Nader M, Sempoux C, Ambroise J, Bearzatto B, Gala JL, Horsmans Y, van Grunsven L, Desdouets C, Leclercq I. Reactive cholangiocytes differentiate into proliferative hepatocytes with efficient DNA repair in mice with chronic liver injury. J Hepatol. 2019

doi: 10.1016/j.jhep.2019.02.003.

Mathias JR, Zhang Z, Saxena MT, Mumm JS. Enhanced cell-specific ablation in zebrafish using a triple mutant of Escherichia coli nitroreductase. Zebrafish. 2014 doi: 10.1089/zeb.2013.0937.

Minnis-Lyons SE, Ferreira-González S, Aleksieva N, Man TY, Gadd VL, Williams MJ, Guest RV, Lu WY, Dwyer BJ, Jamieson T, Nixon C, Van Hul N, Lemaigre FP, McCafferty J, Leclercq IA, Sansom OJ, Boulter L, Forbes SJ. Notch-IGF1 signaling during liver regeneration drives biliary epithelial cell expansion and inhibits hepatocyte differentiation. Sci Signal. 2021 doi:10.1126/scisignal.aay9185.

Morrison JK, DeRossi C, Alter IL, Nayar S, Giri M, Zhang C, Cho JH, Chu J. (2022) Single-cell transcriptomics reveals conserved cell identities and fibrogenic phenotypes in zebrafish and human liver. Hepatol Commun. doi: 10.1002/hep4.1930.

Oderberg IM, Goessling W. (2023) Biliary epithelial cells are facultative liver stem cells during liver regeneration in adult zebrafish. JCI Insight. doi: 10.1172/jci.insight.163929.

Ota N, Shiojiri N. Comparative study on a novel lobule structure of the zebrafish liver and that of the mammalian liver. Cell Tissue Res. 2022 doi:10.1007/s00441-022-03607-y.

Raven A, Lu WY, Man TY, Ferreira-Gonzalez S, O'Duibhir E, Dwyer BJ, Thomson JP, Meehan RR, Bogorad R, Koteliansky V, Kotelevtsev Y, Ffrench-Constant C, Boulter L, Forbes SJ. Cholangiocytes act as facultative liver stem cells during impaired hepatocyte regeneration. Nature. 2017 doi:10.1038/nature23015.

Russell JO, Ko S, Monga SP, Shin D. Notch Inhibition Promotes Differentiation of Liver Progenitor Cells into Hepatocytes via _sox9b_Repression in Zebrafish. Stem Cells Int. 2019 doi:10.1155/2019/8451282.

Sato K, Marzioni M, Meng F, Francis H, Glaser S, Alpini G. Ductular Reaction in Liver Diseases: Pathological Mechanisms and Translational Significances. Hepatology. 2019 doi: 10.1002/hep.30150.

So J, Kim A, Lee SH, Shin D. Liver progenitor cell-driven liver regeneration. Exp Mol Med. 2020 doi: 10.1038/s12276-020-0483-0.

Stoddard M, Huang C, Enyedi B, Niethammer P. Live imaging of leukocyte recruitment in a zebrafish model of chemical liver injury. Sci Rep. 2019 doi: 10.1038/s41598-018-36771-9.

Wang S, Miller SR, Ober EA, Sadler KC. Making It New Again: Insight Into Liver Development, Regeneration, and Disease From Zebrafish Research. Curr Top Dev Biol. 2017 doi: 10.1016/bs.ctdb.2016.11.012.

Xie W, Jiao B, Bai Q, Ilin VA, Sun M, Burton CE, Kolodieznyi D, Calderon MJ, Stolz DB, Opresko PL, St Croix CM, Watkins S, Van Houten B, Bruchez MP, Burton EA. Chemoptogenetic ablation of neuronal mitochondria in vivo with spatiotemporal precision and controllable severity. Elife. 2020 doi: 10.7554/eLife.51845.

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Referee #2

Evidence, reproducibility and clarity

In this study, the authors present a new chemoptogenetic tool, LiverZap, to study regeneration in zebrafish. In combination with LiverZap, the authors use live imaging to study longitudinally LPC-mediated regeneration and the implication of the healthy surrounding tissue.

Major comments

The LiverZap is an elegant new tool to induce localized ablation of hepatocytes. It is not as claimed by the authors a real breakthrough: (1) While localized ablation is nice compared to NTR-MTZ model in zebrafish, mice model such as CCl4 chronic injury can also study the interaction between healthy and injured tissue. (2) Although not using MTZ, the system still requires injection or exposure to malachite green derivate dye MG-2I. A few searches suggest that this compound could induce toxicity. Can the authors study and compare the toxicity of malachite green derivate dye MG-2I to the toxicity of MTZ? This is important as this would be indeed a strong argument in favor of the presented tool.<br /> The term ablation is choose because it is anticipated that it induces heaptospecific death. However, the consequences of cell death is not shown. In particular, the inflammatory immune response is not shown nor discussed.<br /> - The difference between mild and severe ablation is hard to grasp. Can the authors explain more clearly the differences between mild and severe: what are the criteria as there is no difference in liver volume between mild and severe ablation? How do you achieve mild or severe ablation? It appears that the severity of the ablation is judged a posteriori and not decided per the experiment.<br /> - The work supports that biliary-driven regeneration also occurs when hepatocyte ablation happens in a small area of interest. Our knowledge is that you need a large defect in hepatocyte or a chronic liver injury ro activate the BDC-driven auxiliary process for regeneration. Could this be a specificity of the fish model?<br /> - Pathways revealed to control liver regeneration or BEC-driven regeneration in fish have not be found to have a similar drastic predominance in rodents. This mitigate perhaps the use of fish for this type of research?

The authors show that in the case of mild ablation, hepatocytes are responsible for replenishment of the parenchyma, but in the context of severe ablation, LPC-mediated regeneration takes control.<br /> However, when the authors perform localized and controlled ablation, which is small (around 10-20%) and, to my understanding, a mild / local ablation, however the authors show that LPC mediates the regeneration. Can the authors explain the discrepancy between their results?<br /> The last part of the paper about E-Cadherin expression is not convincing. I am not sure about the quality of the IF stainings of E-Cadherin, and it is not helping proving the point of the authors. Can the authors provide better stainings for this figure?<br /> Could the authors provide a bit more information on the live imaging. Exactly how do they achieve imaging for such a long time?

Minor comments

It is hard to imagine the full-size liver in Figure 1, bad contrast. Can the authors manually delineate it?<br /> "This finding is very surprising, since current understanding in the field links the generation of new hepatocytes from BECs/LPCs with global hepatocyte death." This statement lacks references.

Significance

General assessment:

Elegant model to ablate hepatocyte in a clean fashion and study regeneration when coupled to imaging technique.<br /> The work supports that biliary-driven regeneration also occurs when hepatocyte ablation happens in a small area of interest. This seems a new concept, the operation of the process needs to be ascertain in other models including humans.<br /> Immune/inflammatory response to the ablation as well as the way it may influence/drive or dictate a regenerative response is not investigated

Advance:

The advance pertains to the model because rodents offer ample possibilities to study interaction between 'intact' and 'diseased' cells. Of course the model is attractive as it is rapid, allows for 'real time' in vivo imaging, ..;

The audience will be a specialised audience (basic research in liver regeneration, in zebrafish technologies, ...)

Expertise

I'm a hepatologist, devoted for the last 15 years to the experimental study of the pathophysiology of liver diseases using animal models, cell cultures models and organoids. I 'm not an expert in zebra fish. I have a large interest in regeneration and in particular I produced pioneer work in BEC-driven regeneration that is studied here.

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Referee #1

Evidence, reproducibility and clarity

Summary:

The manuscript by Ambrosio et al. describes a novel experimental system named "LiverZap", where spatiotemporally-regulated hepatocyte ablation can be achieved in the liver of living zebrafish for the study of the tissue/organ regeneration processes and mechanisms, particularly by in vivo live imaging. Specifically, the authors made use of a binary FAP-TAP system to achieve reactive oxygen species (ROS)-induced hepatocyte cell death upon treatment with the drug MG-2I followed by near-infrared (NIR) illumination in transgenic fish. They found that the system resulted in two categories of hepatocyte ablation, i.e., mild ablation and severe ablation. In the livers where the severe ablation was induced throughout the organ, biliary epithelial cell (BEC)-derived hepatocyte regeneration program was provoked as demonstrated by short-term lineage tracing experiments based on histone inheritance, which is quite consistent with previous studies using different methods of hepatocyte ablation in zebrafish and mice. Taking advantage of the spatial controllability of the LiverZap system, the authors further demonstrated that spatially-restricted severe hepatocyte ablation was sufficient to induce the BEC-dependent regeneration program therein. Interestingly, BECs outside the targeted region also contributed to the local hepatocyte regeneration, as revealed by using a sophisticated photoconvertible BEC labeling system. Finally, a dynamic nature of BEC aggregation and re-distribution upon liver injury was demonstrated to occur in advance of hepatocyte regeneration, reminiscent of the so-called ductular reaction in the mammalian liver. Overall, the authors' claims and the conclusions are well supported by the data presented in the manuscript, except for a few points as listed below.

Major comments:

• The authors assessed acridine orange incorporation in BECs upon LiverZap and concluded that LiverZap triggers hepatocyte-specific cell death without a bystander effect in adjacent cells (Figure 1 D-E). What happened to endothelial cells, which could also be affected either directly by ROS production in hepatocytes or indirectly by gross morphological changes in tissue organization?
• The evaluation criteria for distinguishing mCherry <high> and <low> cells in imaging experiments should be clearly described in the methods section. The authors should also provide some quantitative data regarding the level of correlation between the mCherry<low> hepatocytes and the BEC-derived hepatocytes strictly defined based on the TP1-H2B-EGFP lineage tracing, as the former was used as a surrogate marker for the latter in some experiments.
• OPTIONAL: In the locally restricted ablation model, do hepatocytes located adjacent to the ROI proliferate and/or contribute to the regeneration of the injured region?
• OPTIONAL: Figure 4, A-S. It should be of significant interest if the authors could also analyze the BEC dynamics using the locally restricted hepatocyte ablation model, comparing those in the injured region (ROI) and the outside of the ROI.
• Figure 4, T-V'. The data shown here for the changes in E-cadherin distribution is difficult to understand and interpret. The authors should provide magnified images and better description on how to distinguish the membranous (spotted signals?) and intracellular localization. Quantitative assessment should certainly be a plus, if possible.
• OPTIONAL: In relation to the above point, it is this reviewer's candid impression that the very last part regarding the possible role of E-cadherin dynamics in regulating the biliary network remodeling is still preliminary compared to the remaining parts, thereby rather depreciating the value of the entire manuscript. Perhaps this part could be published separately, together with more functional evidence regarding the causal relationship between them (e.g., showing the effect of E-cadherin knockdown in hepatocytes on the biliary remodeling and the induction of the BEC-dependent regeneration program)
• Do zebrafish livers possess lobular structures with the portal-to-central vein axis and the metabolic zonation as typically observed in mammalian livers? As has been described in the manuscript, the "localized" injury patters in the mammalian livers usually occur at the sub-lobular structure levels (i.e., peri-portal region-restricted vs. peri-central region-restricted). Although the "localized" injury model described in this study using the zebrafish livers was indeed localized from the viewpoint of the entire organ (or the lobe), it still seemed much more "global" when considering those situations in the mammalian livers, so that the authors' claim that the former recapitulating the latter might be too exaggerated and somehow misleading. The authors should clarify and discuss this point in the manuscript.

Minor comments:

• Figure 4. Panels D and G should correspond to the same one image and the way of labeling be changed (as in Figure 1G). Likewise, in panel J, the bars shown separately as "M" and "S" at 12 dpi should correspond to the same data, so that they should be unified as one bar.
• Figure S3L. How was the ROI border defined? Perhaps the shape of the ROI should change significantly during regeneration due to dynamic tissue remodeling processes, thereby moving the position of the border as well.
• The authors should comment in the manuscript as to whether the system can be applicable for induction of more restricted areas (e.g., at a single hepatocyte level; in particular metabolic zones, if existing), as well as for ablation of other hepatic cell types such as BECs and endothelial cells.

Significance

The newly developed LiverZap system described in the present study was well designed and has multifaceted advantages compared to other "global ablation systems" that have so far been used in this research field. Indeed, the authors' original finding that the localized hepatocyte ablation provokes activation of BECs outside the injured region and their contribution to hepatocyte renewal, could have never been obtained using previous models. This finding is of considerable novelty and interest in that the localized injury model should better reflect the pathophysiological conditions in various human liver diseases. Thus, the study should make significant contribution to the field in both technological and conceptual ways, providing useful and relevant platforms for the future studies on the mechanisms of liver injury, repair and regeneration.

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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 an interesting manuscript that explores how epithelial cells respond to genetically induced disruption of occluding junction formation. To ask how epithelial integrity is maintained under these conditions, the authors investigated the developing pupal epidermis in Drosophila, where they used genetic mosaic techniques to induce patches of mutant tissue lacking selected components of bicellular or tricellular septate junctions (SJs), respectively. They show that occluding junction defects result in elevated levels of E-Cadherin, F-actin, and activated myosin II at adherens junctions (AJs) in the mutant tissue, suggesting that epithelial cells sense breaches in barrier integrity and respond by reinforcing adhesion and actomyosin contractility. Consistent with this idea, the authors find mechanosensitive proteins (Ajuba, Vinculin) enriched at AJs in the mutant cells, and show that new cell-cell interfaces after cytokinesis are shortened in cells lacking the tricellular SJ (tSJ) component Aka. Moreover, aka mutant cells accumulate beta-Integrin, F-actin and vinculin on their basal side, suggesting that upon disruption of tSJs cells increase matrix adhesion by forming focal adhesions (although the authors did not address whether these structures are bona fide focal adhesions that connect to ECM). The authors go on to ask how disruption of SJs is sensed and translated into enhanced adhesion and contractility. Previous work (Pannen et al. eLife 2020) established that the ESCRT complex is required for retromer-dependent delivery of SJ components to their correct membrane destination, and that loss of ESCRT function leads to disruption of SJs. Building on this and their own earlier work, the authors show that SJ defects are accompanied by enlarged ESCRT III (Shrub:GFP)-positive structures, elevated numbers of HRS-positive vesicles, and accumulation of polyubiquitinated proteins. The latter effect upon SJ disruption was reminiscent of Shrub/ESCRTIII loss of function, leading authors to propose that modulation of ESCRT activity prevents SJ protein degradation in favor of SJ protein recycling. Such a scenario could be expected to result in elevated SJ protein levels at the plasma membrane, but whether this is the case is not addressed in the paper. Instead, the authors switch here to analyzing effects of shrub RNAi on the apical determinant Crumbs, which accumulates at or near AJs in cells lacking bSJ (nrv2) or tSJ (aka) components, consistent with reduced degradation and/or increased recycling of Crumbs protein. Finally, they show that clusters of beta-integrin (Mys), associated with vinculin and F-actin, appear on the basal side of aka-depleted cells, leading the authors to conclude that SJ-defective cells reinforce their adhesion to the ECM, perhaps to prevent extrusion from the epithelium. While the appearance of Mys clusters on the basal side is convincingly demonstrated, I don´t see evidence for apical focal adhesions, as depicted in the cartoon in Fig. 7. If focal adhesion-like structures exist on the apical side, to what kind of ECM molecules should they attach there?

Overall, the manuscript describes interesting new findings that are well documented and should be of interest to a broad audience of cell and developmental biologists. However, the following questions and technical issues remain to be addressed before the manuscript will be ready for publication.

Major comments:

The title refers to a "mechanism sensing paracellular diffusion barrier alteration", and in the discussion (line 325) authors state that "loss of bSJs and tSJs by altering the paracellular diffusion barrier triggers an ESCRT-dependent response...". However, no experiments to assess paracellular barrier function (epithelial permeability) are shown in the paper, and it is not clear that the ESCRT-dependent responses described here are triggered by altered barrier function per se, as stated by the authors, or by changes in other SJ-dependent parameters, such as cell adhesion or intra-membrane mobility of lipids and proteins. Statements about paracellular barrier alteration should be rephrased accordingly.

Altered epithelial barrier function will likely influence osmoregulation via changes in organismal hormonal status and gene expression, which may contribute to the phenotypes described here. How much time passed between induction of mutant clones and phenotypic analysis? The authors should discuss these aspects, and consider that effects of altered barrier function will depend on the distribution and size of clones with defective SJs.

In the discussion the authors speculate about a "sensing" mechanism based on (hypothetical) altered membrane lipid composition upon loss of SJs. However, such effects would not explain how altered barrier function per se (epithelial permeability) would be sensed by cells, as stated in the title and throughout the text. Please explain.

How Shrb/ESCRTIII activity could be "redirected" or "modulated" by disruption of SJs remains unclear. Can the authors briefly outline possible mechanisms for modulation of ESCRT activity?

The presentation of fluorescence intensity data in a rescaled ("standardized") format is uncommon and non-intuitive, as it obscures the true scale (fold-changes) and variation of the data. Also, if data were plotted as a range from 0 to 10, as stated in Materials & Methods, it is not clear why in all graphs (except for a single datapoint in Fig. 5C'?) values start at 1, not at 0. Highest values appear to cluster at 10 and lowest values at 1, suggesting these represent saturated or clipped signals, respectively. Were these datapoints taken into consideration for calculating mean values? Authors need to explain exactly how the analysis was done. Why was this type of representation chosen, and why should it be more appropriate than showing regular normalized data?

Authors should explain why they jump between different mutant (aka, nrv2) and RNAi (aka, cora nrv2, nrxIV) conditions and different Gal4 driver lines (pnr-Gal4, sca-Gal4) to disrupt SJ integrity. The basis for choosing these different conditions is not always clear and makes results difficult to compare.

The TEM images shown in Fig. 1A are difficult to interpret, because plasma membrane is barely visible. The images do not seem to contribute much and can be removed from the paper.

The position of mutant clones is marked by absence of nuclear RFP (Fig. 1B and elsewhere), but drawings of clone boundaries (Fig. 1B) do not match with the pattern of RFP-positive/ -negative nuclei (Fig. 1B'), presumably because different optical sections are shown in Fig. 1B and and B'. This is confusing and needs to be explained.

Minor comments:

Line 102: "We recently reported that defects at tricellular Septate Junctions (tSJs) are always accompanied by bicellular Septate Junctions (bSJs) defects". Authors may want to mention that in embryonic and larval epithelia lacking tricellular SJs, bicellular SJs assemble initially, but appear to degenerate during later development (Hildebrand et al. 2015, Byri et al. 2015).

Line 192 remove "another".

Line 194: % enrichment and fold enrichment are used; stick to one way.

Line 259 and elsewhere: Crb "activation" vs. accumulation or mislocalization. What do the authors mean by Crb "activation"?

Line 346: "FK2 protein": the FK2 antibody does not detect a particular protein, but the polyubiquitin modification, presumably on many different proteins.

Line 444: "Also, the observed changes at apical level might be mostly due to direct effects." I don´t see experimental evidence to support that the observed changes are mostly due to direct effects. Rephrase or remove.

Information on how mutant clones were induced needs to be included in Materials and Methods.

Results referred to as "not shown" should be shown, or corresponding statements be removed from the paper.

The text needs to be carefully checked for grammatical and typographical errors.

Significance

How epithelial cells cope with disruptions of occluding junctions without losing tissue integrity is an important question with far-reaching implications for understanding epithelial biology and disease. This work makes a significant contribution here by carefully describing the interrelationship between disruption of occluding junctions and possible compensatory mechanisms at the level of adherens junctions.

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Referee #2

Evidence, reproducibility and clarity

Septate junctions provide the barrier function in insect tissues, serving as analogs to the vertebrate tight junctions. Here the authors explore an interesting question-how do epithelial tissues respond to loss of barrier function in vivo. They use a powerful and well-studied system, the Drosophila pupal notum, which allows them to bring powerful genetic tools to bear and use state of the art imaging. Their data are lovely and carefully quantified. Together, they reveal some significant surprises. 1. Disrupting septate junctions leads to elevated accumulation of adherens junction proteins and myosin, and reduced apical area. 2. Disrupting septate junctions led to accumulation of many ESCRT-0-positive vesicles and of enlarged ESCRTIII vesicles. 3. Disrupting septate junctions led to elevated accumulation of Crumbs apically and of integrin-based focal adhesions basally. These observations are well supported by the data and in the results section conclusions are carefully drawn. I had some relatively minor comments outlined below about the results. My only significant suggestion concerns the Abstract and Discussion. The Abstract includes a statement that goes well beyond the data shown, and the Discussion is sometimes hard to follow. With these issues corrected, this will provide important new insights for cell and developmental biologists.

1. The Abstract states: "We report that the weakening of SJ integrity, caused by the depletion of bi- or tricellular SJ components, reduces ESCRT-III/Vps32/Shrub-dependent degradation and promotes instead Retromer-dependent recycling of SJ components." This is too strong, as the role of the retromer, while plausible, is not directly tested. It's fine to speculate about this in the Discussion but drawing a conclusion like this in the Abstract is unwarranted.
2. Similarly, the title suggests that "ESCRT-III-dependent adhesive and mechanical changes are triggered by a mechanism sensing paracellular diffusion barrier alteration". They show that knocking down septate junctions alters localization of vesicle trafficking machinery, and that it leads to alterations in apparent recycling of cargo, but do they ever really assess whether these changes are ESCRT-III-dependent? Wouldn't this require knocking down ESCRT-III in cells with defects in septate junctions? There was a lot of data in this paper and perhaps I missed it but was this experiment done? I am not suggesting they do it, but that they temper this conclusion if not.
3. The authors assessed "poly-ubiquitinylated proteins aggregates appearance, marked using anti-FK2" . They need to define FK2-what does it detect.
4. Fig 4-is this a clone, and are we far from the boundary? Make this clearer
5. The authors state: "Despite these apparent similarities, we noticed that, in contrast to Shrub depletion, NrxIV did not accumulate in enlarged intracellular compartments upon Cora depletion" Could the authors reference a Figure here?
6. The authors state: "Hence, if both Shrub and bSJ/tSJ defects lead to Crumb enhanced signals" It might be better to say "altered" as they then point out the differences.
7. I found the Discussion challenging to follow. Rather than focusing on the core observations, it addresses many, not very well-connected speculative possibilities, and in my opinion, will be challenging for most readers to follow. I would encourage the authors to revisit it from top-to-bottom.

Referees cross-commenting

I think we largely agree that the authors present important data, but that certain points need to be better explained or more clearly documented. While Reviewer 1 is correct that adding context about the basolateral polarity proteins would be helpful, I do not feel as strongly about this as a deficit. The authors did not manipulate Scrib, Dlg or Lgl, and i think their polarity functions may be distinct from those of the more "structural" septate junction proteins analyzed here.

Significance

Septate junctions provide the barrier function in insect tissues, serving as analogs to the vertebrate tight junctions. Here the authors explore an interesting question-how do epithelial tissues respond to loss of barrier function in vivo. They use a powerful and well-studied system, the Drosophila pupal notum, which allows them to bring powerful genetic tools to bear and use state of the art imaging. Their data are lovely and carefully quantified. Together, they reveal some significant surprises. 1. Disrupting septate junctions leads to elevated accumulation of adherens junction proteins and myosin, and reduced apical area. 2. Disrupting septate junctions led to accumulation of many ESCRT-0-positive vesicles and of enlarged ESCRTIII vesicles. 3. Disrupting septate junctions led to elevated accumulation of Crumbs apically and of integrin-based focal adhesions basally. These observations are well supported by the data and in the results section conclusions are carefully drawn. I had some relatively minor comments outlined below about the results. My only significant suggestion concerns the Abstract and Discussion. The Abstract includes a statement that goes well beyond the data shown, and the Discussion is sometimes hard to follow. With these issues corrected, this will provide important new insights for cell and developmental biologists.

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Referee #1

Evidence, reproducibility and clarity

This paper investigates the cellular response of Drosophila epithelia cells in the notum to damage to septate junctions. They find that disruption of tri- and bi-cellular septate junctions (SJ) integrity alters the distribution of adherens junction (AJ) components including E-cadherin, Myosin-II and others. Loss of SJ increases levels of AJ proteins. They then show that loss of the tri-cellular junction protein Anakonda alters the adhesive and the mechanical properties of the epithelia. They showed Myo-II activation was increased, however laser ablation/recoil studies did not reveal a change in local membrane tensions. Changes in membrane tension were observed by quantifying cell divisions in bicellular septate junction (bSJ) mutants. Building on previous work, they show that defects in SJs lead to ESCRT complex defects, and that loss of tricellular or bicellular septate junction components increase apical-medial Crumbs localization and triggers assembly of focal adhesion contacts. Together, these results show that alterations in SJ structures result in apparently compensatory increases in Crbs and focal adhesion-based intercellular adhesions that is mediated by the ESCRT complex.

Major comments:

• Title, abstract and paper body: e.g. title "ESCRT-III-dependent adhesive and mechanical changes are triggered by a mechanism sensing paracellular diffusion barrier alteration in Drosophila epithelial cells"
• The paper is completely focused on the septate junctions as a paracellular diffusion barrier. However, many of the septate junction components, including Scribble, Dlg, and Lgl, have well documented (if poorly understood) basolateral polarity functions, and considering that septate junctions contain 15 or more cell-cell adhesion proteins, they are also likely to have a adhesive/structural function in addition to paracellular barrier and polarity functions. There is no attempt in the paper to consider or disentangle these multiple roles. Indeed, the introduction and discussion consider the vertebrate tight junction as the analogue of the insect septate junctions when a better view would be that the septate junction is a combination of the claudin-based barrier function of the vertebrate tight junction and the vertebrate basolateral polarity proteins Scribble, Dlg and Lgl that localize similarly and presumably have a function similar to the Drosophila basolateral polarity/SJ proteins for which they are named. Moreover, there are no experiments in the paper to address whether the relevant parameter being sensed in SJ defects is loss of the paracellular barrier, loss of cell adhesion/contact/structure or disruption of the polarity function of the SJ complex. Notably, there aren't any experiments in the paper that test paracellular barrier function. This criticism does not in any way reduce the importance of the paper or the results, but to avoid presenting an overly simplistic and probably misleading view of the cellular processes in play, a more comprehensive discussion of SJs is in order.
• line 245: "We propose that it is the Shrub activity that is being modified upon SJ alteration, preventing SJ component degradation in favour of SJ component recycling."<br /> line 288, "Thus, as proposed above for Nrx-IV, these data further suggest a hijacking of Shrub activity toward recycling components upon alteration of SJ integrity."<br /> Model in Fig. 7 Arrows showing increased SJ protein delivery in right bottom panel, but decreased bicellular SJ complex formation in the left bottom panel.<br /> The authors demonstrate that in bicellular SJ mutants, there is increased accumulation of Crb, adherens junction components, focal adhesion components, and in the text and in the model in Fig 7 focus on the upregulation of recycling activity. However, as indicated by the reduced bSJs in the left bottom panel in Fig 7, and in the reduced Nrx levels in 3C' and in the text in lines 351-53, the levels of most septate junction proteins drop in the absence of any of 15+ bicellular septate junction mutants. Previously the authors should that reduction of tricellular septate junction proteins increased levels of septate junction proteins in bicellular junctions which the authors translate to increased delivery of "SJ components" to the membrane in SJ mutants as shown in Fig 7 bottom right panel and stated in lines 245 and 288. But the data in the paper, which is consistent with statements on lines 351-353 saying that bicellular SJ mutations cause a general reduction of SJ protein levels, suggests either a more nuanced role of recycling such that Crbs and other proteins show increased recycling in bicellular SJ mutants, but biclellular SJ proteins show decreased recycling, or an alternative scenario in that the SJ proteins are recycled more in a SJ mutant, like Crb is, but SJ proteins don't form stable complexes which leads to their modification that targets them for destruction despite being recycled more. Regardless of the actual explanation, I think readers will be confused by the statements in the current version of the paper about upregulation of recycling activity but apparent reduction of SJ proteins. The authors should address this issue with appropriate changes to text and the model figure.

Minor comments:

• The assumption in the paper is that the changes in protein levels result from changes in recycling of the proteins. However, it would be nice to rule out transcriptional regulation. Has anyone established smFISH in the notum that would allow quantification of Crb or other marker RNA to show that there is not increased accumulation of the Crb RNA in the SJ mutant backgrounds?
• line 58. SJ are only the functional equivalent of tight junctions for paracellular barrier function. SJ have basolateral polarity function that correspond to basolateral polarity proteins in vertebrates, whereas vertebrate TJs are associated with apical complexes. In addition, the mechanical properties of SJ and TJ are probably wildly different since the SJ is a much more elaborate structure with many more cell-cell adhesion proteins than TJs. I feel the presented over-simplification do not adequately inform the reader about alternative functions and therefore hypotheses about the data in the paper.
• lines 120-121 , Figure 1A-A'. Please quantify the relative frequency of holes observed in the EM sections. Is it every tricellular junction or 1 in 100? Is WT statistically different than mutant?
• line 126-127 (data not shown). Does EMBO allow data not shown? Just checking current rules.
• lines 134-135. "We observed similar results upon loss of Gli and M6". Is this data not shown? I couldn't find it. Please either reference a figure or note as "data not shown" if that is allowed.
• line 319 "We propose that the disruption of SJ barrier in the ...", also line 326 . I suggest the use of "SJ complex" instead of SJ barrier or paracellular diffusion barrier, otherwise the authors need to provide some evidence or rationale that it is the barrier function of the SJ that is triggering the recycling changes rather than the disruption of the polarity or adhesive/structural functions of the SJs.
• line 341 "Our work shows that a part of the sensing mechanism involves the ESCRT machinery."<br /> I think that the ESCRT machinery is better described as part of a response mechanism to SJ defects than as a "sensor". I don't think the paper presents any evidence that the ESCRT machinery is part of the sensing mechanism for SJ defects. There is lots of evidence that the ESCRT machinery is modified by SJ defects, but that supports a role as part of the response machinery, not as the sensor that directly detects SJ defects.

Significance

The topic and results of the paper will be of interest to a wide range of the cell biology community including those studying epithelial integrity, junctions, polarity and endocytic trafficking. The results break new ground in looking at the dynamic relationships between junctional complexes. This paper is generally well written, with the exception of the major comments below which, and the experiments well done. Overall a very interesting paper that is appropriate for a top tier journal.

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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 study, the authors used metabolic labeling of newly-replicated or nascent chromatin followed by quantitative Mass spectrometry (iPOND-MS) to characterize protein composition of nascent chromatin at time points after DNA replication: immediately after a short pulse of EdU labeling (nascent), and after 1 and 2 hours of Thymidine chase (maturing chromatin). The iPOND method was established before but in the current manuscript the authors combined this with inhibiting RNA Pol II transcription at distinct stages to determine the effects on transcription and RNA Pol II cycle on chromatin protein dynamics at the wake of DNA replication. The inhibitors they used are Triptolide, which blocks transcription initiation and induces a proteasomal degradation of all chromatin bound RNA PolII, and DRB, which blocks transcription elongation causing an enrichment of paused RNA PolII. The authors compared the relative enrichment of ~1200 proteins on nascent and maturing chromatin and the effects on transcription inhibition on these proteins.

The authors found that RNA PolII does not affect the loading or retention of most histones on nascent chromatin except for the histone variant H2A.Z, which requires RNA PolII loading. However, DRB treatment (no elongation) resulted in stabilization of all histones (which the authors do not seem to catch on). Interesting, unlike the histone, both replication-coupled and -independent histone chaperons seem to be enriched immediately behind the fork and are affected by RNA PolII to different extents. They next look at ATP-dependent remodelers and find that most remodeler families are facilitated by RNA PolII loading, while elongation affects some remodeler families and not others. They see the same trend looking at a wide variety of transcription factors. Interestingly, while RNA PolII loading is required for the establishment of some histone post translational modifications (H3K36me3), some others such as H3K9me3 and H4K20me2 are negatively affected. Finally, the authors find that RNA PolII elongation promotes binding of several DNA repair proteins, and speculate that this is because of DNA damage from replication-transcription conflict.

My main concern about this manuscript is that the relative enrichment of most factors show variability across the time points, which make the interpretation of the data difficult. This becomes more concerning when we look at protein complexes such as the ATP-dependent remodelers. Subunits of the same complex which are expected to bind together show different patterns of enrichment. This raises the concern as to how data was normalized. Furthermore, how do the replicates compare to each other? The others selected ~1200 proteins which were enriched in all three replicates, but how does their relative enrichment compare in the replicates? The authors need to show some kind of comparison across replicates to confirm that the differential relative enrichments are real and biologically meaningful.

Also, the TF data is very descriptive. Insightful analysis of similarities/differences between types of TFs would be interesting.

Minor comment: The formaldehyde cross linking used in iPOND makes it difficult to interpret/distinguish what is actually chromatin bound versus what is enriched due to protein-protein cross linking. The authors should highlight that in the limitations section.

Referees cross-commenting

I agree with most of Reviewer 1's comments about the lack of proper controls and normalization, which make the interpretations difficult. Particularly all of the controls mentioned under point 1 should not be difficult to perform, and if included, would strengthen the study and the manuscript.<br /> Reviewer 1 makes an important point about normalization, which I totally agree with. Ideally, a spike-in approach would help obtain a much more quantitative and reliable understanding of differential protein enrichment. However, repeating all iPOND experiments with spike-in might be a big ask. What the authors could do at minimum is show how replicates compare with each other. It looks like they pooled all three replicates for analysis, but comparing relative enrichment of all 1257 proteins across replicates would help. The point about delayed histone occupancy is a critical one and difficult to rationalize. To note, histone chaperons are enriched on nascent, but histones are not. Besides, in the current way that the data is analyzed and presented, there are a lot of fluctuations in protein enrichment across the 1-2 hour timepoints of chromatin maturation, which would be very interesting if real. For e.g., Fig. 1I, Triptolide treatment, most of the cluster I and cluster II proteins show medium-high enrichment on nascent, depleted in 1h, but recover in 2h. If the binding/recruitment of these proteins on newly-replicated chromatin is RNA Pol II dependent, why would they come back after 1h? If this real, this would be very interesting. There are several additional examples of problems with quantification/normalization. As for SWI/SNF subunits, both SMARCA4 and SMARCC1 are core subunits and based on several thorough biochemical studies, cannot be expected to bind separately. However, they show different kinetics in DMSO as well as TPL and DRB.

Another problem of the assay is that it shows genome-wide average. As Reviewer 1 rightly pointed out, transcription inhibition could disproportionally affect chromatin maturation kinetics in different genomic regions. Perhaps it would be interesting to analyze sets of genomic regions separately, such as highly transcribed and lowly transcribed genes. This might be achieved by adding a purification step using pools of DNA sequence probes before or after the streptavidin enrichment.

Additional comment: The formaldehyde cross linking used in iPOND makes it difficult to interpret/distinguish what is actually chromatin bound versus what is enriched due to protein-protein cross linking. The authors should highlight that in the limitations section.

On a positive note, it is a very important and timely study and the manuscript has a lot to consider. Addition of proper controls and normalization/analysis of replicates will make it stronger

Significance

Overall, it is a very important and timely study, and the manuscript has a lot to consider. There are several recent papers on the kinetics of chromatin maturation behind the replication fork, and this study adds a very important dimension to this ongoing investigation, and will be of interest to a broad readership in the chromatin and transcription field.

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Referee #2

Evidence, reproducibility and clarity

In this manuscript, the authors characterized the re-establishment of chromatin after DNA replication in fibroblasts using iPOND-MS. By using a short pulse of EdU, followed by different length of thymidine-chase, the authors compare the proteome at nascent DNA (just after the EdU pulse) with the proteome on re-established chromatin (1h and 2h post EdU pulse). Moreover, by using two different transcription inhibitors, they investigate the implication of active transcription elongation and of RNAPII binding itself on the reestablishment of chromatin. They show that different transcription factors bind to newly replicated DNA with different kinetics and are affected differentially by transcription inhibition. They also show that upon transcription inhibition by DRB, certain DNA damage repair proteins are depleted, implicating transcription in the recruitment of these factors at nascent DNA. Chromatin remodelers were shown to be enriched on nascent DNA, but triptolide-transcription inhibition reduced their enrichment, implicating RNAPII in the reestablishment of chromatin structure and of steady-state chromatin accessibility. Lastly, the authors show that histone incorporation and histone modification restoration on nascent DNA is mostly uncoupled from transcription with the exceptions of H3.3K36me2 (transcription inhibition by triptolide or DRB drastically reduces restoration) and H4K16ac (DRB treatment increases its incorporation in nascent DNA).

Overall, the results and the analysis of the datasets appear robust and well executed. Nevertheless, the work provided by the authors feels mainly descriptive and does not provide further mechanistic insights beyond the current state of the art. Some follow-up experiments to study the functional impact on the different enrichment patterns on nascent DNA or the function of the dependency on RNAPII for the reestablishment of steady-state enrichment on chromatin of some factors would have greatly increased the scientific impact of the manuscript. Nevertheless, the proteome of nascent DNA, its kinetic, and the effect of transcription inhibitors will provide interesting information and a useful resource for research groups in the DNA replication, chromatin, epigenetic, and DNA damage repair fields. Thus, in conclusion, I would recommend this manuscript to be published in its current state in a lower tier journal such as MBoC or PLOS ONE journals. If the authors can provide additional mechanistic insights by addressing at least a few of the specific points listed below, I think it would become a stronger candidate for a journal with higher impact.

Major comments:

1. At p.7, the authors state: "Altogether, this analysis further confirms that RNAPII's binding and elongation on newly replicated chromatin are a source of genotoxic stress, and identifies dedicated repair factors handling transcription replication conflicts.". I don't think that depleted DNA repair proteins from nascent chromatin upon DRB treatment is enough to claim that the analysis confirms that transcription on nascent DNA is a source of stress. Another possibility could be that transcription helps handling prior DNA damage on nascent DNA without causing the damage. A useful experiment to clarify this point would be the direct quantification of DNA damage markers on nascent chromatin (e.g yH2AX-EdU colocalization quantification by immunofluorescence). Has the yH2AX variant been detected in the iPOND MS dataset? Another possible follow-up experiment could be to detect direct physical DNA damage on nascent DNA for example by using a TUNEL assay or similar DSB mapping method. Can the DNA damage be prevented by DRB or TRP addition?
2. Figure 1B-E: Can the authors also show quantifications of EU, RNAPII and EdU at the 1h and 2h timepoints after the chase?
3. The authors state in p.7 that "The other proteins are DNA repair proteins involved in fork quality control and HR as well as transcription replication conflicts (Berti et al., 2020).". I think this gives rise to the question if the effect of DRB treatments on the enrichment of certain proteins at nascent DNA is due to the inhibition of transcription elongation inhibition on nascent DNA or in front of replication forks, affecting the enrichment of proteins implicated in handling transcription-replication conflicts in front of the fork and not on nascent DNA itself. The authors should address the possibility that some of the proteins enriched in the iPOND-MS datasets could be there because they are enriched in front of the replisome instead of on the nascent DNA.
4. On this topic, transcription inhibition is performed for two hours prior to the EdU pulse and iPOND-MS procedures. For the DRB treatment, I would expect RNAPII to be paused/stalled prior to the passage of the replication fork that will replicate the analyzed EdU-labelled nascent DNA. This would mean that replication forks during the EdU pulse will encounter paused/stalled RNAPII, generating potential problems. Such interference would most probably lead to chromatin removal of RNAPII from the chromatin. Surprisingly, the authors show enrichment of RNAPII at nascent DNA. How can the author differentiate from accumulation of RNAPII in front of the fork, leading to purification by iPOND, and RNAPII on nascent DNA. Also, if the accumulation of RNAPII is on the nascent DNA, do the authors suggests that RNAPII gets loaded more on nascent DNA while under DRB inhibition or that stalled RNAPII are mainly by-passed by replication forks, leading to their enrichment on nascent DNA?
5. At p.14, the authors state: "Because they share the same DNA template, transcription is known to challenge replisome progression at high frequency, from RNAPII constituting a roadblock to progressing replisomes, to generate RNA:DNA hybrids (Berti et al., 2020). It is therefore remarkable that behind replisomes, only a handful of DNA repair factors appear to be involved in response to RNAPII binding and elongation.". How does the fact that transcription represents a roadblock in front of the forks makes it remarkable that only a handful of DNA damage repair pathways are involved behind the fork (where they are not a roadblock to any replisome)?
6. At p.11, the authors states: "As di and tri-methylations require several hours to be re-established following DNA replication (Alabert et al., 2015; Reveron-Gomez et al., 2018), 11 minutes after the passage of the fork, such increase most probably reflects an increase of H4K20me2 and H3K9me3 on recycled parental histones.". Can the authors extend their interpretation of this result? Do the authors think that DRB treatments increase methylation of histones in G1, prior to replication, or specifically in front of the fork (due to conflicts? DNA damage?), and that those methylated histones get recycled on nascent DNA?
7. Figure 4: The authors perform the histone PTM analysis under 0h (nascent chromatin) versus 2h (re-established chromatin) timepoints. It would have been insightful to also include a 1h timepoint in this experiment. There appear to be some trends/changes but they do not show statistical significance (e.g. H4K5K12ac or H3K14ac). It might be useful to increase the number of biological replicates (including the 1h timepoint) here, which could improve the confidence in the results and/or discover additional transcription-dependent changes of histone PTM restoration.

Minor comments:

1. Fig3I: It would be nice to show a TF from the "Restored within 11 min" category as a comparison point.
2. In page 14, th authors state: "However, we did not detect significant signs of DNA damage in DRB treated cells (Fig. 2A, 2B).". Which signs the authors looked at?
3. In the iPOND experiment, which size of DNA fragments is achieved?
4. At p.14, the authors state: "Because they share the same DNA template, transcription is known to challenge replisome progression at high frequency, from RNAPII constituting a roadblock to progressing replisomes, to generate RNA:DNA hybrids (Berti et al., 2020)." The paper has not addressed the role of RNA:DNA hybrids in these processes.
5. Fig3D: Is there enough datapoints to state a conclusion?
6. S1A: mistakes in the x axis labels ("no EU" in a EdU quantification graph, "no EdU" in a EU quantification graph).
7. S1F is not sufficiently described in the legend. It took me some time and additional efforts to understand what the right panel of S1F was showing.
8. S2E-F: are the axis wrong? Is it supposed to be Nascent when its comparing total extracts?
9. A lot of graphs have non-precise axis labels that needs reading of the manuscript and/or legends to understand. For example: 1K-L (distribution, %), 2L (% of the max), 3B-C-D log2(Nascent/2h), 3G IP/Input, 4C (Inhibitor treatment/DMSO (%)), S2E-F (TPL/DRB Nascent/ DMSO Nascent), S3A (IP/Input), S4A (No Y axis label).
10. FigS4: Assignment of colors in bar graphs of C-J to treatments is not shown. Heatmaps in H and K do not show if these are 0 or 2h. The heatmap in H shows H3 modification and the heatmap in K shows modification in H3.3 but the labels of the modification in K (except the first one) are the names of the modifications of H3, not H3.3. In the legend, GAPDH is written GABDH.

Significance

In this manuscript, the authors characterized the re-establishment of chromatin after DNA replication in fibroblasts using iPOND-MS. As mentioned above, the work provided by the authors feels mainly descriptive and incremental and therefore does not provide further mechanistic insights beyond the current state of the art. Some follow-up experiments to study the functional impact on the different enrichment patterns on nascent DNA or the function of the dependency on RNAPII for the reestablishment of steady-state enrichment on chromatin of some factors would have greatly increased the scientific impact of the manuscript. Nevertheless, the proteome of nascent DNA, its kinetic, and the effect of transcription inhibitors will provide interesting information and a useful resource for research groups in the DNA replication, chromatin, epigenetic, and DNA damage repair fields. Thus, in conclusion, I would recommend this manuscript to be published in its current state in a lower tier journal. If the authors can provide additional mechanistic insights by addressing at least a few of the specific points, I think it would become a stronger candidate for a journal with higher impact.

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Referee #1

Evidence, reproducibility and clarity

The goal was to characterize the changes in the composition of the proteome associated with replicated DNA in conditions of genome-wide inhibition of transcription initiation or transcription elongation. They use iPOND, a MS based technique that identifies proteins specifically associated with replicated DNA labeled with EdU. They use non-synchronized foetal human lung fibroblasts and examine time points immediately after replication (after the 11 min EdU pulse) and 1 and 2 hrs after the Thymidine "chase" later when chromatin has "matured", to assess how the inhibition of transcription influences chromatin maturation and the binding of chromatin associated proteins to replicated DNA.

The question is pertinent and is in line with the long-standing interest of the group in chromatin replication dynamics. They conclude that 1. RNAPII loading is necessary for the binding of some TFs, chromatin remodelers and DNA repair factors and 2. RNAPII elongation is needed for H2A.Z incorporation , H3K36me2 restoration and DNA repair factor binding. Transcription is on the other hand not needed for nucleosome assembly, histone acetylation and H3K9me3, H3K27me3 and H4K20me2 incorporation or restoration.

There are two main issues that make the interpretation of their results very difficult and make me question their conclusions:

1. They don't provide sufficient evidence that the treatments with TPL and DRB do not interfere with replication. The distributions of EdU intensity per EDU+ cell after treatment in Figures 1D-E and S1A are not sufficient. It is not clear why EdU incorporation is so heterogeneous in the cell population (the range of intensities goes from near 0 to 50000!), which makes me wonder if the DMSO treatment also has an effect on replication. I don't think this heterogeneity can simply be explained by the fact that the the cell population is asynchronous. They need to show a -DMSO control as well. Besides since they are only using a positive EdU signal as their criteria for replicating cells, they cannot rule out that some of the EdU signal is coming from DNA repair after replication and depending on how deleterious DMSO/TPL/DRB are to replication the fraction of cells that undergo DNA repair might be significant. More importantly, they need to show that the various treatments don't interfere with the replication program, especially since replication is coupled with new nucleosome assembly and the transcription of replication dependent histone variants is induced during S-phase. Transcription inhibition could disproportionally affect the replication of some parts of the genome more than others and since there is no evidence to the contrary the differences that they observe between the TPL/DRM treated and DMSO treated proteomes bound to replicated DNA could just be because they were isolated from different genomic loci. I am also not convinced that they are able to stop EdU incorporation after 11min with the addition of only equimolar amounts of Thymidine (20µM EDU and 20µM Thymidine). Equimolar amounts of Thymidine are not sufficient to stop EdU incorporation rapidly. They need to show the kinetics of EdU incorporation in synchronized cells +/- Thymidine.<br /> Without these controls it is impossible to draw any meaningful conclusions from the iPOND data.
2. The normalization of iPOND and total protein MS data is problematic. It seems that each time point from each treatment was first normalized internally to the median of all protein levels in each dataset and then the relative abundances of each protein were normalized to 100% over all treatments and time points. Internal normalization makes it impossible to directly compare time points and treatments between each other. If the enrichment of a protein goes down from one time point to the next it doesn't mean that there is less of that protein on replicated DNA in absolute terms, it just means that there is less of that protein relative to the median of the whole set of proteins at that time point. Their claim that they are comparing iPOND enrichments to total protein abundance is misleading since the data from total protein extracts was also internally normalized so they are comparing relative enrichments in iPOND data to relative enrichments in total cell extracts, which unsurprisingly do not correlate. It is impossible to make any meaningful conclusions about proteome dynamics using this kind of analysis. They should have used external normalization with a "spiked in" protein to be able to directly compare time points and treatments.<br /> Such as it is right now, their analysis produces some puzzling conclusions that I suspect will turn out to be artefacts of their normalization procedure. It is not clear for example why the appearance of histones on replicated DNA would be delayed as they claim: in yeast nucleosomes (new and old recycled ones) are assembled on replicated DNA within minutes of the passage of the replication fork, I don't see why this would not be the case in human cells since the replication machinery is essentially the same in humans and yeast. It is also puzzling why RNAP2 is enriched in the nascent and 1hr time points but then becomes depleted in the 2hr time point in the DRB treatment since global RNAPII levels don't change in the DRB treatment compared to DMSO (Figure 1C). All the conclusions for PTM restoration/incorporation are essentially meaningless: internal normalization makes it impossible to detect whether PTM levels double at the 2hr time point compared to the Nascent time point in the DMSO treatment, as would be expected for all examined PTMs except for H4K5K12Kac which are marks of new histones. Right now, relative PTM levels are all over the place: only histone acetylations seem to increase, while H3K9me3 and H3K27me3 don't change even though they should also double since heterochromatin should also be restored on both sister chromatids. They will only be able to accurately assess the impact of transcription inhibition on PTM restoration when they are able to reliably measure the rate of increase of PTM levels during chromatin maturation.

Referees cross-commenting

On reviewer's 2 comment on significance:<br /> I think a thorough descriptive analysis of a biological process is extremely valuable and unlike my colleague, I think these types of studies need to be published in high impact journals with a broad readership. Biological processes need to be described first as completely as possible before we can propose meaningful models on how they function and identify the molecular mechanisms that execute and regulate them. As my colleague is surely aware, thorough descriptive studies of any poorly characterized biological process take years (i.e. at least one grant cycle) and comprehensive follow up mechanistic studies can take even longer than the initial descriptive study and can only be done during the following grant cycle, if the authors were lucky enough to obtain funding. Funding agencies however are more likely to award grants to perform these follow up mechanistic studies if the authors (especially if they are junior PIs) have published in higher impact journals in their previous grant cycle. The kind of thinking exhibited by reviewer 2 disproportionately disadvantages junior PIs that work on understudied biological processes. It is a disservice to scientific progress to dismiss excellent descriptive studies and "downgrade" them to lower impact journals where they will be unfairly labeled as a "work of lesser importance". This kind of thinking is also a disservice to the lower impact journals that often publish works whose quality is comparable to articles published in high impact journals. I value more any comprehensive description of a biological process over what most of the time passes for mechanistic insight that is deemed worthy of publication in a high impact journal i.e. a hastily analyzed phenotype of, more often than not, one single mutant tacked on at the end of a descriptive study. This one mutant phenotype then forms the basis of a somewhat "slapdash" model that is often proven wrong by subsequent publications and that the authors would have probably dismissed themselves had they been given more time to develop and test their model in a follow up publication.<br /> I do not think the main issue with the present study is its descriptive nature. As I said in my review, the main issues are technical: the lack of external normalization of MS data and insufficient evidence of the impact of transcription inhibitors on replication dynamics. The study should not be published in any journal (high or low impact) before those issues are resolved.

on reviewer 2's remarque 4. in major comments:<br /> iPOND identifies proteins bound to 100-300bp fragments labeled with EdU (i.e. after replication or DNA repair). It is by definition identifying proteins bound to chromatin behind the fork, so I don't think that the isolation of RNAPolII bound in from of the fork is a major issue

Significance

I am not convinced by their conclusions and I cannot recommend that the the study be published at this stage due to normalization issues and insufficient evidence that transcription inhibition does not perturb the replication program (see above). They would need to redo all the iPOND experiments using external "spike in" normalization and monitor replication genome-wide before they can make any meaningful conclusions about the transcription dependent composition of the proteome associated with replicated DNA.

Expertise keywords: Chromatin, Genomics (assay development and bioinformatics analysis) , Replication, Transcription

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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 manuscript under evaluation investigates the mutation rate between generations and during regeneration in the planarian species S. polychroa. Abundant adult pluripotent stem cells, the potential somatic stem cell contributions to the germ line, and the regeneration of entire animals from tiny tissue fragments provide interesting conceptual background to these questions. Specifically, the authors assemble a draft genome of a purportedly triploid S. polychroa strain with an accompanying de novo transcriptome. Via shallow whole genome shot gut sequencing, the authors subsequently attempt to estimate the germline mutation rate and the effect of regeneration on the number and the spectrum of detectable mutations. As stated in the abstract, the study "...provides, for the first time, the draft genome assembly of S. polychroa, the germline mutation rate for a planarian species and the mutational spectrum of the regeneration process of a living organism". As detailed under "major points" below, the draft genome assembly is not great and significant concerns remain regarding both regeneration rate statements.

Major points

Genome and transcriptome assembly:

1. As the authors state, ploidy is known to be highly variable across S. polychroa strains and ploidy is an important variable in the estimation of mutation rates. The authors should therefore provide additional experimental evidence that their strain is indeed triploid (e.g., through karyology or FACS genome size estimation).
2. Assembly quality assessments: As stated, the authors intend to use a de novo assembled short-read transcriptome as an independent assessment of assembly quality. However, no information on the quality of the transcriptome reference is provided. Salient quality control metrics on the size, completeness, and assembly contiguity of their transcriptome need to be provided. The published and publically available S. polychroa transcriptome on PlanMine [cited by the authors] might provide a further useful reference.
3. The assembly is highly fragmented ( 8700 contigs) and the authors detect a significant number of scaffolding errors within contigs (Fig. 3d) . Moreover, the large number of multi mappers might indicate that the draft assembly has been insufficiently purged of haplotigs. This is especially a concern in a potentially triploid species and should be assessed via a kmer-based approach such as Merqury. Ideally, an independent Illumina dataset from the mutation screening and the reads used for polishing should be used. The analysis of synteny and structural variation relative to S. mediterranea in Figure three is therefore of questionable relevance and should be dropped or significantly condensed.

Mutation analysis:

1. The SNP analysis is based on a pipeline that the authors published previously. Beyond this, the manuscript provides insufficient information in terms of technical details (e.g., the salient IsoMut settings, how duplicate reads were treated, and how the SNP calling approach guards against the ever-present possibility of sequencing artifacts). In addition, the authors should discuss whether the pipeline adequately accounts for the i) triploid genome and ii) the fragmented and potentially insufficiently purged assembly. In absence of such information, the validity of the results remains difficult to ascertain.
2. The statistical support for the germline mutation rate is weak (Fig. 5a). The sample size of the experiment is rather low for such studies, with only four Filia in each group. Furthermore, in both the control and regenerate group, two of the filia are siblings. This creates a data dependence that is not adequately discussed or taken into account for the analysis. For example, the authors conduct a t-test to determine if the number of detected mutations differs between the groups. A critical assumption of the t-test is that the samples are independent, an assumption that is violated when a relatedness structure is present. Similarly, this dependence could further influence the analysis of the mutational profile. Hence the authors either have to increase the sample size or temper the interpretation of their results, including the claimed estimation of germline mutation rate.
3. The possibility of somatic mosaicism that the authors discuss extensively in the context of regeneration also complicates the interpretation of the clonal mutations between parents and filia. First, somatic mosaicism has been already demonstrated in a different planarian species and discussed in multiple reviews (e.g., PMID: 31221097, PMID: 35862435). This literature needs to be cited adequately.<br /> Second, the plausible contribution of individual somatic stem cells to the germ line leaves open the possibility that the observed parent/offspring differences in the control group also reflect rare pre-existing allele heterogeneities within the parental population of pluripotent stem cells. Therefore, clonal differences between parents and offspring cannot simply be attributed to germline mutations. Third, low, but measurable rates of sex are known to occur even in predominantly parthenogenetic S. polychroa populations (e.g., PMID: 16721392; PMID: 15293852]. These studies need to be cited and the possibility of parental genome contributions needs to be explicitly examined, as it would violate the requirement for an isogenic background stated on page 4. Overall, this means that the author's claim of providing the first quantification of the germ cell mutation rate in planarians is therefore insufficiently justified.<br /> The possibility of somatic mosaicism also impacts the interpretation of the apparent increase in genetic variation during regeneration. Given the limited depth of the sequencing assays, it remains difficult to refute the null hypothesis that the apparent increase in the mutation load of regenerates represents a subsampling of the standing genetic variation in the parent animals (and without the single-cell populational bottleneck of parthenogenetic reproduction). Also, the claims regarding the mutagenic nature of the regeneration process should therefore need to be dropped or significantly toned down.

Minor comments:

Fig.2a: The S. polychroa genome size estimates from genomesize.com Table S1 and Figure 2 a: The entries from the animal genome Size Database need to be removed from the figure, as this is published background information and not an analysis result.

Page 6: The text description of the transcriptome backmapping results (Fig. 3A) is confusing: "...17.4 % were not mapped by GMAP,... the remaining transcripts were mapped as duplicates, at multiple positions or in two chimeric fragments... The authors need to insert the fraction of single mappers, as otherwise, they imply that they only obtain multi-mappers.

Page 7: PlanMine needs to be cited as the source of the orthology information between S.med and S. pol.

Page 10: What is the COSMIC database? Please explain/reference.

Fig. 4 and 5: The experimental set-up cartoon in Fig. 4a is confusing and should more clearly illustrate which of the experimental groups involved regeneration, how many individuals were sequenced, and the meaning of the A/B terminology in subsequent graphs. Moreover, the authors need to ensure consistent symbol use, e.g., Fr1, 2, 3, 4 instead of the current F1, F2, ... in Fig. 5a.

The authors discuss the potential contribution of methylation to the observed mutation spectrum and conclude that it might not be present in S. mediterranea and S. polychroa. Indeed, the lack of measurable mC in the planarian genome has already been demonstrated (PMID: 24063805). Please cite and shorten the respective text section.

Fig. 6e: The authors estimate the number of stem cells in tail segments using H3P staining. However, H3P marks only a short segment of the cell cycle and therefore underestimates the number of resident stem cells. This caveat needs to be discussed.

Typo in Figure S2: The splice site is marked wirth a black

Significance

Planarian flatworms harbor abundant pluripotent adult stem cells. These cells are the only division-competent cells in the animal and of pivotal importance to planarian biology. For example, they enable the regeneration of entire animals from tiny tissue pieces or the re-formation of the germ line in sexually reproducing strains. How planarians maintain their genetic identity in the face of abundant pluripotent adult stem cells and a strict soma/germline divide raises many intriguing questions.

The manuscript provides a preliminary and highly fragmented draft genome assembly of the planarian species S. polychroa, which adds to the available planarian genome information. Based on the genome assembly, the manuscript attempts to measure generational mutation rates during parthenogenetic reproduction and regeneration. The quality of the SNP detection is somewhat difficult to evaluate in the current manuscript and the possibility of somatic heterogeneity in the parents raises concerns regarding the interpretation of the supposed germline mutation rate. The data provide further evidence for somatic mosaicism, which has already been demonstrated in a different planarian species. The extent by which regeneration is mutagenic per se or uncovers standing genetic variation due to the inherent population sub-sampling also remains unclear. Overall, the manuscript stands out as one of the first intra-organismal population genomics studies in the field. But I think not all its claims are sufficiently supported by data.

I am a planarian biologist with experience in planarian genomics. I am not an explicit population genetics/genomics expert.

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Referee #2

Evidence, reproducibility and clarity

Summary:

This paper presents the genome of the planarian Schmidtea polychroa, a sister species to the widely used regenerative model S. mediterranea. The preliminary analysis of the genome is sound and the authors establish that they have produced a good draft assembly. The authors then leverage this assembly to ask novel questions about mutation rates in regenerative planarians, a question that has not been well addressed previously. They use a clear and logical approach to measure mutation rates in relation to both development and regeneration and establish that different clones of stem cells exist in planarians and contribute to regeneration and production of germ cells.

Overall the work is of a high quality, and logically explained.

Major comment.

I could find no statement about raw data availability or metadata availability, or availability of intermediate data analysis files. This makes proper review and consideration of the authors analysis essentially impossible, so all of this must be taken on trust and easy to do but helpful further analyses in the context of the existing data structure can't really be suggested. This is a great shame. Furthermore, in this reviewers' opinion this goes against the principle of open science. A revision must address this issue unless the reviewers' are planning to publish this paper in the 1990s print format only (forgive the sarcasm, but I hope the authors can concede this isn't a good way forward). Without data access the full impact of their very exciting work cannot land. If I have missed reference to access to the data or a GitHub link etc in the paper then I apologise, but I have looked extensively. Sequence Data submission can take time so they should do this in advance and perhaps share the link to the unreleased link too reviewers, and intermediate files and metadata can be shared on GitHub or the like.

Minor comments.

I enjoyed reading the paper immensely and I think it touches on many important and interesting theoretical ideas in the field.<br /> With regards to their comments on methylation they should note that previous work on S. mediterranea has rigorously shown that methylation is absent or very low, probably any residual comes from base scavenging from the calf liver food source. Additionally, DMNT 1 and 3 are absent from S. mediterranea, so canonical enzymes for methyl-cytosine addition and maintenance are not available. Citing this would be useful (Jaber-Hijazi et al, 2013, Developmental Biology https://doi.org/10.1016/j.ydbio.2013.09.020). Other work suggests there might be methylation in this group using retriction enzyme based approaches.

I have some questions that relate to evolution of a parthenogen.<br /> Did the authors ever detect homozygous changes between "parental" generations and offspring or changes from a heterozygous state to a homozygous state?<br /> Given the parthogenic and triploid nature of Polychroa did the authors detect high levels of/accumulation of heterozygous alleles generally in the genome?

Significance

This paper will eventually be very significant to the regenerative biology community as it will give us comparative genomic capabilities for the well-established model S. mediterranea. Although not commented on much in the manuscript this is very important. Furthermore, the paper begins the important work of characterising mutation rates in this group of animals that avoid the ageing process entirely, this work will be another important foundation stone in understanding the phenomena that allow for this in this group of animals.

I have expertise in genome assembly, analysis and annotation, as well in assessing variation in genomes. I also have expertise in the model system used here and its general biology, including regeneration.

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Referee #1

Evidence, reproducibility and clarity

In this paper, using the triploid biotype of planarian Schmidea polychroa, the first half of the paper presents the results of the analysis of genome structure and the second half shows that (de novo) mutations in individuals that undergo regeneration are passed on by the next generation.

While I think this paper contains interesting biological findings, I am skeptical about its novelty. I was convinced by the results and discussion of the analysis of genome structure, but the results and that of the analysis of (de novo) mutation were very confusing. This may be due to my lack of knowledge in this field. But even so, the author needs to improve this manuscript so that the general reader will better understand it.

Major comments:

1. The author mentions that it is important to note that this study was conducted using a parthenogenetic triploid biotype. However, I think that the parthenogenesis undergoing by a triploid biotype of S. polychroa is very unusual. It is not typical apomictic parthenogenesis. Triploid oocytes arise by meiosis from hexaploid oocytes derived from triploid adult somatic stem cells called neoblasts. On the other hand, haploid sperm arise by meiosis from diploid spermatogonia derived from neoblasts. Embryogenesis of triploid eggs then occurs by pseudogamy. Occasional sex is also known to occur even if the offspring's chromosome number remains triploid. I think this background is important information to give the reader. Also, don't the authors need to treat the results in this paper with this complex phenomenon also taken into account?
2. Fig.4B-C: Analysis by lineage-specific mutations of parental controls.<br /> The authors do not specifically mention or discuss this result. What about the accumulation of mutations within such populations in typical parthenogenesis (daphnia and aphids)? In other words, are the results in Fig. 4B-C due to the special mechanism for parthenogenesis in the triploid S.polychroa as described above?
3. Throughout this paper, the authors show that regeneration increases de novo mutations in the progeny. The authors conclude that many of the mutations occurred in neoblasts during regeneration. However, I would like you to explain the biological significance of this results in S. polychroa, which naturally does not reproduce by fission and regeneration. There are already reports of mutations accumulating in neoblasts in Dugesia japonica, which reproduce aexually by fission. For these reasons, I do not think this paper presents extremely novel results.
4. p15, Discussion:<br /> "Tissue regeneration is best seen in the liver of mammals, and the regrowth of relapsed tumours following surgery can also be considered an example of a regenerative process. Mutagenesis accompanying these processes is relevant to subsequent tumorigenesis or the development of resistance, and the planarian system can provide a useful model for the mutagenic effect of tissue regeneration."

Isn't it an overstatement to associate the regenerative system of planaria with the liver regeneration of mammals?<br /> 5. p10, Results:<br /> "We compared the two de novo spectra to the spectrum of germline heterozygous SNPs, present in all animals, and found that the pattern of germline substitutions resembled more closely the de novo spectrum of the control group (Fig 5D, Fig S3), implying that regeneration has a minor contribution to germline mutations in S. polychroa populations."<br /> p14, Discussion:<br /> "The high similarity of the spectrum of heterozygous SNPs and de novo mutations of control animals suggests that the species primarily reproduces in a non-regenerative manner. The increased mutation rate and the altered mutation spectrum upon regeneration confirmed our hypothesis that regeneration is a mutagenic process."

I was very confused by these sentences and it took me some time to understand them. Triploid S. polychroa naturally does not reproduce by fission and regeneration, namely a non-regenerative manner. I do not understand why the author insists on this. Please explain the results for the regenerated case in Fig. 5D (0.88) in a way that is also easy to understand. Also, what is the biological significance of asserting here that de novo mutation by regeneration increases in a species that does not increase by regeneration and division in the first place?

Minor comments:

1. The author should add a schematic diagram showing the distribution of reproductive organs in Fig.1 to help the reader understand that the ovaries are not included in the regenerative fragment.
2. P12, line12: Fig 6D-E, it's F, not E, right?
3. P9, line 8:<br /> "these mutations were missing from the original egg but were present in the egg laid by the parent and thus represent the total mutation load of a generation."

The author mentions that the de novo mutation found in offspring derived from parents that do not undergo regeneration was already present in the eggs, but I can find no evidence of this. Can you rule out the possibility that these mutations occurred between hatching and adulthood?<br /> 4. p10, Results:<br /> "Interestingly, the majority of mutations were shared in the siblings F4A and F4B. This suggests that the germ cells of these animals were descendants of the same stem cell, which underwent a high number of cell divisions early during the regeneration process prior to oocyte differentiation. The same finding also confirms that the detected clonal filial mutations were present in the respective oocyte and were not generated by embryonic cell divisions."

The shared de novo mutations detected in the siblings (F4A and F4B) derived from the parent that underwent regeneration in Fig. 5A suggest that the germ cells of these siblings are descended from the same stem cell. The authors say that these mutations occurred in a large number of cell divisions early in the regenerative process prior to oocyte differentiation.

So why is there no shared de novo mutation in the siblings (Fc4A and Fc4B) derived from the non-regenerating parent in Fig. 5A? As mentioned in Minor comment 3, the author states that the de novo mutations were already present in the parent-laid eggs, but when did these mutations, which are not shared, arise?<br /> 5. p11, Results:<br /> "Interestingly, in the case of FR4A-FR4B sibling pair, shared de novo mutations present in both were subclonal in R4 in a proportion comparable to the other samples (7/15 by WGS, 46.7%), while the three unique mutations could not be detected in R4 by the PCR approach, indicating again that the unique mutations, which amounted to approximately 10% of total clonal filial mutations in these two animals, arose late during germ cell regeneration."

"during germ cell regeneration." the expression is too vague to know which stage you are referring to. In relation to minor comment 4, why not create a new chart to clearly show when the expected mutations occurred?<br /> 6. p12, Results:<br /> "Altogether 7/30 regenerant mutations were detected in PR animals, and these included those with the highest AF in the regenerants (Fig. 6C). This suggests that parental animals, even before regeneration, contained a diverse set of stem cells, and some of the detected de novo mutations in the filial generation resulted from the expansion of mutation-containing stem cell clones contributing also to germ cells in the regenerant animals."

If the mutation in the offspring is derived from the parent (PR) prior to the time of tail amputation, wouldn't it be wouldn't it be strange to assume that it is a de novo mutation?<br /> 7. p12, Results:<br /> "The remaining 23/30 R- subclonal mutations may have arisen during regeneration. On average, ~250 dividing neoblasts were detected in cut tails of animals from the same population as the sequenced individuals, as determined by immunofluorescence of phosphorylated H3 histone (Fig 6D-E). However, the high proportions of body cells carrying regenerant-specific mutations suggest that certain stem cells contribute to disproportionately large parts of the regenerated body, including the germline."

I did not quite understand the relevance of this discussion to the photos shown here of the M period (Fig. 6e).

Significance

General assessment: This paper contains important biological information. The finding that mutations in planarian stem cells cause diversity in the next generation of parthenogenesis is very interesting. However, I think that the author needs to carefully explain and change his argument, for example, that the mutations were caused by regeneration, which does not naturally occur in the species used.

Advance: The finding that accumulation of mutations is occurring in planarian stem cells has already been reported in Dugesia japonica. Please cite the papers and clarify what is the key finding in this paper.

Audience: Basic Research_Evolutionary Ecology, Developmental Biology (Stem Cells), Reproductive Biology

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.

My field of study is reproductive biology. I am familiar with the transcriptome but unfamiliar with genome analysis.

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Reply to the reviewers

We thank the three reviewers for carefully reading our manuscript and for all considerations, ideas, suggestions, and comments. These were all very helpful for us to strengthen the scientific statements of our manuscript. Please, note that all changes are marked in red in the manuscript and supplement. Below you will find, point by point, our responses to all questions and comments.

Reviewer #1 (Evidence, reproducibility and clarity):

Overall, this is an exciting work. There are, however, several open questions that the authors could address to facilitate understanding of their work. These points are:

1.) On page 5, lines 113ff, the authors mention the membrane bulges that they analyse in figure 1. They show these deformations by light (confocal) and electron microscopy. However, the bulges seen by confocal microscopy seem to be bigger that those seen by electron microscopy. The authors could quantify the sizes of the bulges for clarification.

We quantified the size of the membrane bulges. At the confocal we measured in average 750nm as mean value of identified bulges (n=12) with 650nm as minimal and 890nm as maximal sizes. At the TEM we measure ~243nm as mean value (n=61), with a range between 62nm as minimum and 442 as maximum value. These measurements are shown as Figure 1E.

Please note that measurements of TEM images do not always capture the three-dimensionality of bulges and may show only parts of them. In addition, ultrastructure is more sensitive and can easily detect small membrane changes that we cannot observe with confocal and airsycan microscopy. In contrast, even with our high-quality objective (63x Zeiss Plan Neofluar, Glycerin, 1.3 NA), standard confocal analysis is limited at ~200nm on the XY axis (airyscan ~110nm) and ~450nm on Z-axis. Therefore, TEM analysis detects smaller bulges than confocal analysis, and consequently, this method detected a large range of bulge lengths between 63nm and 441nm. In contrast, the airyscan method detected a range of bulge length between 0.65 and 0.83 µm. However, confocal and TEM analyses provide evidence of membrane bulges in pio mutant embryos. Please note that we extended our studies and now show membrane bulges in two different pio mutant alleles (17C and 5M) with airsycan microscopy.

2.) The subject of the manuscript is rather complicated; presentation of data from Figure 1C and D on lines 113ff and 169ff is confusing.

We apologize and thank the reviewer for careful reading. We revised both paragraphs (lines 108 – 123 and lines 166 - 174) and are confident that the descriptions are now much more understandable. All changes are marked in red.

3.) The quality of the sub-images of Figure 2E differs. Especially, the phenotype of the wurst, pio transheterozygous embryo is not well visible.

We apologize for it. We repeated the experiment with wurst;pio transheterozygotes, and generated wurst;pio double mutant embryos to improve the quality. The gas filling assay is shown in Fig. 3. With brightfield microscopy in overview images (10x air objective) and close-ups of the dorsal trunks (25x Glycerin objectives). Both show the gas-filling defects of dorsal trunk tubes. In a subsequent confocal analysis of chitin stainings in late-stage 17 embryos, we found that tracheal tube lumens are collapsed in the transheterozygotes and double mutant embryos.

4.) Lines 246ff: the protein size are given for the mCherry:chimeric proteins; an estimate of the native Pio portions should be given.

The endogenous Pio protein has a calculated mass of about 50.82 kDa. We state it now in the according legend of Fig. 6.

5.) In Figure 6A, the appearance of chitin in the wildtype tube is different compared to the Np mutant situation, more filamentous. Can the authors comment on that?

The author is correct. The chitin cable formation in Np mutant embryos is normal but lacks the condensation process, and, therefore, fiber structure of the chitin matrix differs from control embryos in late stage 16 and stage 17 embryos (see Drees et al., PLOS Genetics, 2019).

6.) In the discussion section, I would appreciate if the timing of events was discussed or even shown in a model. The central question is: how are the functions of Pio and Np coordinated in time? As I understand, Np should not cleave Pio before morphogenesis is completed. Is there any example in the literature for how such an interaction could be controlled? The overexpression of Np shows that either the ratio between Np and Pio is important, or the btl promoter expresses Np at the "wrong" time point.

We thank the reviewer for this interesting comment.

Of course, we did not measure forces, but it has been published that axial forces appear at the apical cell membrane during stage 16 tube expansion. Our data show that Np cleaves Pio ZP domain and subsequent release increase during stage 16. The cleaved and released Pio enriches in the lumen during stage 16, from where cleaved Pio is internalized during stage 17 with the help of Wurst-mediated endocytosis. This is supported by several in vivo studies, video microscopy, antibody stainings and biochemical data, such as the interaction of Pio and Dumpy as well as the identification of different Pio products with and without Np cleavage. Moreover, we found membrane bulges that increase in size during stage 16 and identified a subsequent tear-off of the chitin matrix in Np mutant embryos. Thus, we propose that Np is required to cleave Pio-Dumpy linkages at the membrane-matrix when tubes elongate and postulated forces appear at the cell membrane during tube elongation in stage 16 embryos.

We stated this in the discussion as follows:

“The membrane defects observed in both Pio and Np mutants indicate errors in the coupling of the membrane matrix due to the involvement of Pio (Figs. 1,7). ..., the large membrane bulges in Np mutants affect the membrane and the apical matrix (Fig. 7). Since apical Pio is not cleaved in Np mutants (Fig. 7D), the matrix is not uncoupled from the membrane as in pio mutant embryos but is likely more intensely coupled, which leads to tearing of the matrix axially along the membrane bulges (Figs. 7, 9), when the tube expands in length.”

How could Np be regulated at the membrane? Np is a zymogen that very likely undergoes ectodomain shedding for activation, similar to what has been described for matriptases. Additionally, human matriptase requires transient interaction of the stem region with its cognate inhibitor HAI-2, which Drosophila lacks (see Drees et al., PLOS Gen, 2019). Thus, the regulation of Np activation is not known.

Further, we observed that Dumpy is not degraded in Np mutant embryos during stage 17. Nevertheless, in a previous publication, we showed that btl-G4 driven Np expression rescues Np mutant phenotypes in a time-specific manner. We used the btl-G4 driver line for these rescue experiments to express Np in tracheal cells. This restored tracheal Dumpy degradation in Np mutant embryos. Thus, btlG-G4 driven Np overexpression is able to rescue Np mutant tracheal phenotypes in a time-specific manner, although Gal4 is expressed from early tracheal development onwards. Further, btl-Gal4 driven Np expression mimics the endogenous Np, which is expressed from stage 11 onwards in all tracheal cells throughout embryogenesis (see Drees et al., PLOS Gen, 2019).

Based on these experiments, we conclude that the btl-G4-driven Np overexpression can cleave Pio ZP domain in stage 16 embryos at the correct time.

However, the ratio of Np expression and Pio is essential in the way that btl-Gal4 driven Gal4 Np overexpression may cause cleavage of a higher number of Pio proteins and the release of critical Pio-Dumpy linkages at the cell membrane and matrix. Thus, increased Pio shedding into the lumen reduces Pio linkages at the membrane, resulting in a pio mutant like tracheal overexpansion in btl-Gal4 driven Gal4 Np overexpression.

Finally, we were able to prove the reviewer’s question in a new experiment. We used btl-Gal4 driven UAS-Np embryos for Pio antibody staining. This revealed Pio enrichment at the tracheal chitin cable in stage 14 and 15 embryos. In contrast, stage 16 embryos showed numerous Pio puncta appearing across the entire tube lumen, indicating that Np mediates Pio shedding specifically in stage 16 embryos and not before. This Np-controlled Pio releases modifies tube length control.

Therefore, we stated this in the manuscript as follows:

Results:

“Our data assumes that Np overexpression may enhance Pio shedding in stage 16 embryos, affecting the Pio-mediated ZP matrix function. Upon breathless (btl)-Gal4-mediated expression of UAS-Np in tracheal cells, we observed a high amount of Pio puncta across the entire tracheal tube lumen, specifically in stage 16 embryos but not in earlier stages (Fig. S13). Consistently tracheal Np overexpression led to tube overexpansion in stage 16 embryos resembling the pio mutant phenotype (Fig. 8A,B). Thus, Np-mediated Pio shedding controls Pio function.”

Discussion:

“The btl-Gal4-driven Np expression mimics the endogenous Np from stage 11 onwards in all tracheal cells throughout embryogenesis (Drees et al., 2019), suggesting that Np is not expressed at a wrong time point. However, the ratio between Np and Pio is essential. We assume that Np overexpression increases Pio shedding, resulting in a pio loss-of-function phenotype. Thus, the tube length overexpansion upon Np overexpression indicates that Pio cleavage is required for tube length control.

Our observation that the membrane deformations are maintained in Np mutant embryos supports our postulated Np function to redistribute and deregulate membrane-matrix associations in stage 16 embryos when tracheal tube length expands. In contrast, Np overexpression potentially uncouples the Pio-Dpy ZP matrix membrane linkages resulting very likely in unbalanced forces causing sinusoidal tubes.”

7.) Also for the discussion: We have two situations where Pio amounts/density are enhanced at the apical plasma membrane. The wurst experiments on lines 136ff show that Pio amount and density depends on endocytosis; is the wurst phenotype (Figure 2), at least partially, due to over-presentation of Pio? Likewise, in Figure 2C, there is more Pio in Cht2 overexpressing tracheae (but there is overall more Pio in these tracheae) - is actually endocytosis reduced in chitin-less luminal matrices? First: does the Pio signal at the apical plasma membrane correspond to membrane-Pio or free-Pio? Second, as in the case of wurst: would more Pio on the membrane (density) affect tracheal dimensions in Cht2 over expressing tracheae? Or are the consequences of Pio accumulation in the apical plasma membrane different in Cht2 and wurst backgrounds? Maybe cleavage of Pio and its endocytosis are dependent on its interaction with the chitin matrix. These questions connect to the question immediately above: how are the functions of the different players coordinated in space and time? We need a discussion on this issue.

We thank the reviewer for this very important idea to discuss the functions of the different players in a coordinated space and time and apologize that we haven’t done before.

As this is an important point, we tried to figure out all questions raised by the reviewer and discussed it in several new paragraphs in the discussion:

"Indeed, the anti-Pio antibody, which can detect all different Pio variants, showed a punctuate Pio pattern overlapping with the apical cell membrane marker Uif at the dorsal trunk cells of stage 16 embryos. Additionally, Pio antibody also revealed early tracheal expression from embryonic stage 11 onwards, and due to Pio function in narrow dorsal and ventral branches, strong luminal Pio staining is detectable from early stage 14 until stage 17, when airway protein clearance removes luminal contents.

We generated mCherry::Pio as a tool for in vivo Pio expression and localization pattern analysis during tube lumen length expansion. The mCherry::Pio resembled the Pio antibody expression pattern from early tracheal development onwards. However, luminal mCherry::Pio enrichment occurs specifically during stage 16, when tubes expand. The stage 16 embryos showed mCherry::Pio puncta accumulating apically in dorsal trunk cells. Moreover, mCherry::Pio puncta partially overlapped with Dpy::YFP and chitin at the taenidial folds, forming at apical cell membranes. Supported by several observations, such as antibody staining, Video monitoring, FRAP experiments, and Western Blot studies (Figs. 4,5), these findings indicate that Pio may play a significant role at the apical cell membrane and matrix in dorsal trunk cells of stage 16 embryos.

Furthermore, we show that Np-mediates Pio ZP domain cleavage for luminal release of the short Pio variant during ongoing tube length expansion. The luminal cleaved mCherry::Pio is enriched at the end of stage 16 and finally internalized by the subsequent airway clearance process during stage 17 after tube length expansion. Such rapid luminal Pio internalization is consistent with a sharp pulse of endocytosis rapidly internalizing the luminal contents during stage 17 (Tsarouhas et al., 2007). Wurst is required to mediate the internalization of proteins in the airways (Behr et al., 2007; Stümpges and Behr, 2011). In consistence, during stage 17, luminal Pio antibody staining fades in control embryos but not in Wurst deficient embryos.

Nevertheless, Pio and its endocytosis depend on its interaction with the chitin matrix and the Np-mediated cleavage. In stage 16 wurst and mega mutant embryos, we detect Pio antibody staining at the chitin cable, suggesting that Pio is cleaved and released into the dorsal trunk tube lumen. Also, the Cht2 overexpression did not prevent the luminal release of Pio. However, reduced wurst, mega function, and Cht2 overexpression caused an enrichment of punctuate Pio staining at the apical cell membrane and matrix (Figs. 1,2). Although the three proteins are involved in different subcellular requirements, they all contribute to the determination of tube size by affecting either the apical cell membrane or the formation of a well-structured apical extracellular chitin matrix, indicating that changes at the apical cell membrane and matrix in stage 16 embryos affect the Pio pattern at the membrane. It also shows that local Pio linkages at the cell membrane and matrix are still cleaved by the Np function for luminal Pio release, which explains why those mutant embryos do not show pio mutant-like membrane deformations and Np-mutant-like bulges. This is in line with our observations that tracheal Pio overexpression cannot cause tube size defects as the Np function is sufficient to organize local Pio linkages at the membrane and matrix. Therefore, it is unlikely that tracheal tube length defects in wurst and mega mutants as well as in Cht2 misexpression embryos are caused the apical Pio density enrichment.

Nevertheless, oversized tube length due to the misregulation of the apical cell membrane and adjacent chitin matrix may cause changes to local Pio set linkages and the need for Np-mediated cleavage. Strikingly, we observe a lack of Pio release in Np mutants. This shows that Pio density at the membrane versus lumen depends predominantly on Np function. The molecular mechanisms that coordinate the Np-mediated Pio cleavage are unknown and will be necessary for understanding how tubes resist forces that impact cell membranes and matrices. On the other hand, Pio is required for the extracellular secretion of its interaction partner Dpy. At the same time, Dpy is needed for Pio localization at the cell membrane and its distribution into the tube lumen. Consistently, in vivo, mCherry::Pio and Dpy::eYFP localization patterns overlap at the apical cell surface and within the tube lumen. These observations support our model that Pio and Dpy interact at the cell surface where Np-mediates Pio cleavage to support luminal Pio release by the large and stretchable matrix protein Dpy (Fig. 9).

Taenidial organization prevents the collapse of the tracheal tube. Therefore, cortical (apical) actin organizes into parallel-running bundles that proceed to the onset of cuticle secretion and correspond precisely to the cuticle's taenidial folds (Matusek et al., 2006; Öztürk-Çolak et al., 2016). Mutant larvae of the F-actin nucleator formin DAAM show mosaic taenidial fold patterns, indicating a failure of alignment with each other and along the tracheal tubes (Matusek et al., 2006). In contrast, pio mutant dorsal tracheal trunks contained increased ring spacing (Fig. 3A). Fusion cells are narrow doughnut-shaped cells where actin accumulates into a spotted pattern. Formins, such as Diaphanous, are essential in organizing the actin cytoskeleton. However, we do not observe dorsal trunk tube fusion defects as found in the presence of the activated diaphanous.

On the other hand, ectopic expression of DAAM in fusion cells induces changes in apical actin organization but does not cause any phenotypic effects (Matusek et al., 2006). DAAM is associated with the tyrosine kinase Src42A (Nelson et al., 2012), which orients membrane growth in the axial tube dimension (Förster and Luschnig, 2012). The Src42 overexpression elongates tracheal tubes due to flattened axially elongated dorsal trunk cells and AJ remodeling. Although flattened cells and tube overexpansion are similar in pio mutant embryos, we did not observe a mislocalization of AJ components, as found upon constitutive Src42 activation (Förster and Luschnig, 2012). Instead, we detected an unusual stretched appearance of AJs at the fusion cells of pio mutant dorsal trunks, which to our knowledge, has not been observed before and may play a role in regulating axial taenidial fold spacing and tube elongation.

Self-organizing physical principles govern the regular spacing pattern of the tracheal taenidial folds (Hannezo et al., 2015). The actomyosin cortex and increased actin activity before and turnover at stage 16 drive the regular pattern formation. However, the cell cortex and actomyosin are in frictional contact with a rigid apical ECM. The Src42A mutant embryos contain shortened tube length but increased taenidial fold period pattern due to decreased friction. In contrast, the chitinase synthase mutant kkv1 has tube dilation defects and no regular but an aberrant pearling pattern caused by zero fiction (Hannezo et al., 2015).

In contrast, pio mutant embryos do not contain tube dilation defects or shortened tubes but increased tube length (Figs. 1; 8; S1). Furthermore, our cbp and antibody stainings reveal the presence of a luminal chitin cable and a solid aECM structure in pio mutant stage 16 embryos (Figs. 8, S1; S6). In addition, apical actin enrichment in tracheal cells of pio mutant embryos appeared wt-like. Nonetheless, pio mutant embryos show an increased taenidial fold period compared with wt, indicating a decreased friction. Thus, we propose that the lack of Pio reduces friction. Reasons might be subtle defects of actomyosin constriction or chitin matrix, which we have not detected in the pio mutant tracheal cells. Further reasons for lower friction might be the loss of Pio set local linkages between apical cortex and aECM in stage 16 embryos, which are modified by Np, as proposed in our model (Fig. 9).

Heterozygous and homozygous pio mutant embryos generally do not show tubal collapse. However, the loss of Pio and accompanying lack of Dpy secretion in stage 17 pio mutant embryos led to the loss of a Pio/Dpy matrix, impacting the late embryonic maturation and differentiation of a normal chitin matrix at the apical cell surface. TEM images reveal reduced dense chitin matrix material at taenidial folds and misarranged taenidial fold pattern (Figs. 1; S2), suggesting impaired taenidial function prevents tube lumen from collapsing after tube protein clearance. Wurst knockdown and mutant embryos do not show general tube collapse, but luminal chitin fiber organization is disturbed in stage 17 embryos (Behr et al., 2007). Therefore, transheterozygous wurst;pio mutant embryos may combine both defects and suffer from maturation deficits of the chitin/ZP matrix at the apical cell surface and within the tube lumen, which finally causes a high number of embryos with incomplete gas filling due to tube collapse. These maturation deficits are even more dramatic in the wurst;pio double mutants, which show no gas filling.”

8.) The sentence on line 242ff should be rephrased: "dynamic" and "elastic" are not opposites.

We thank the reviewer for careful reading. We revised the sentence as follow:

“Our FRAP data suggest that Pio is the dynamic part of the tracheal ZP-matrix, while the static Dpy modulates mechanical tension within the matrix”

9.) A central question to me is the amounts and the density of factors in different genetic backgrounds as mentioned above. Is there any mechanism adjusting the amounts or the density of the players according to the size of the apical plasma membrane or the tracheal lumen? Pio seemingly responds to these changes.

We would like to know the molecular mechanisms that control the density of players at the apical membrane. This question is important and could be the starting point for novel scientific investigations. Mechanisms of protein trafficking, such as exocytosis, recycling and endocytosis regulate delivery and internalization of proteins at the apical cell membrane. Furthermore, protein junctions at the lateral membrane may recognize and therefore may respond to low and high mechanical stresses between cells that appear during tube length expansion. However, we did not observe any hint for misregulation of Pio expression levels in the different mutants which affect endocytosis, SJs and luminal ECM. But we observed a shift of Pio levels between apical cell membrane/matrix and lumen in wurst, mega mutants and Cht2 overexpression. This shift is analyzed with diverse ZEN tools and quantified (Fig. 2D-F; Fig. S4B). As discussed in the new paragraph, this shift is very likely caused by changes at the apical cell membrane and chitin matrix which impact Pio shedding. Moreover, we observe the lack of Pio release in Np mutants. This shows that Pio density at the membrane versus lumen depends predominantly on Np-mediated cleavage. As discussed above, how Np is activated at the apical cell membrane to cleave Pio is not known.

10.) The connection of Pio and taenidia is mentioned in the results section (page 7) but not discussed.

We appreciate the careful reading and comments of the reviewer very much. We included the connection of Pio and taenidial in the discussion section as follows:

“Taenidial organization prevents the collapse of the tracheal tube. Therefore, cortical (apical) actin organizes into parallel-running bundles that proceed to the onset of cuticle secretion and correspond precisely to the cuticle's taenidial folds (Matusek et al., 2006; Öztürk-Çolak et al., 2016). Mutant larvae of the F-actin nucleator formin DAAM show mosaic taenidial fold patterns, indicating a failure of alignment with each other and along the tracheal tubes (Matusek et al., 2006). In contrast, pio mutant dorsal tracheal trunks contained increased ring spacing (Fig. 3A). Fusion cells are narrow doughnut-shaped cells where actin accumulates into a spotted pattern. Formins, such as Diaphanous, are essential in organizing the actin cytoskeleton. However, we do not observe dorsal trunk tube fusion defects as found in the presence of the activated diaphanous.

On the other hand, ectopic expression of DAAM in fusion cells induces changes in apical actin organization but does not cause any phenotypic effects (Matusek et al., 2006). DAAM is associated with the tyrosine kinase Src42A (Nelson et al., 2012), which orients membrane growth in the axial tube dimension (Förster and Luschnig, 2012). The Src42 overexpression elongates tracheal tubes due to flattened axially elongated dorsal trunk cells and AJ remodeling. Although flattened cells and tube overexpansion are similar in pio mutant embryos, we did not observe a mislocalization of AJ components, as found upon constitutive Src42 activation (Förster and Luschnig, 2012). Instead, we detected an unusual stretched appearance of AJs at the fusion cells of pio mutant dorsal trunks, which to our knowledge, has not been observed before and may play a role in regulating axial taenidial fold spacing and tube elongation.

Self-organizing physical principles govern the regular spacing pattern of the tracheal taenidial folds (Hannezo et al., 2015). The actomyosin cortex and increased actin activity before and turnover at stage 16 drive the regular pattern formation. However, the cell cortex and actomyosin are in frictional contact with a rigid apical ECM. The Src42A mutant embryos contain shortened tube length but increased taenidial fold period pattern due to decreased friction. In contrast, the chitinase synthase mutant kkv1 has tube dilation defects and no regular but an aberrant pearling pattern caused by zero fiction (Hannezo et al., 2015).

In contrast, pio mutant embryos do not contain tube dilation defects or shortened tubes but increased tube length (Figs. 1; 8; S1). Furthermore, our cbp and antibody stainings reveal the presence of a luminal chitin cable and a solid aECM structure in pio mutant stage 16 embryos (Figs. 8, S1; S6). In addition, apical actin enrichment in tracheal cells of pio mutant embryos appeared wt-like. Nonetheless, pio mutant embryos show an increased taenidial fold period compared with wt, indicating a decreased friction. Thus, we propose that the lack of Pio reduces friction. Reasons might be subtle defects of actomyosin constriction or chitin matrix, which we have not detected in the pio mutant tracheal cells. Further reasons for lower friction might also be the loss of Pio set local linkages between apical cortex and aECM in stage 16 embryos, which are modified by Np, as proposed in our model (Fig. 9).

Heterozygous and homozygous pio mutant embryos generally do not show tubal collapse. However, the loss of Pio and accompanying lack of Dpy secretion in stage 17 pio mutant embryos led to the loss of a Pio/Dpy matrix, impacting the late embryonic maturation and differentiation of a normal chitin matrix at the apical cell surface. TEM images reveal reduced dense chitin matrix material at taenidial folds and misarranged taenidial fold pattern (Figs. 1; S2), suggesting impaired taenidial function prevents tube lumen from collapsing after tube protein clearance. Wurst knockdown and mutant embryos do not show general tube collapse, but luminal chitin fiber organization is disturbed in stage 17 embryos (Behr et al., 2007). Therefore, transheterozygous wurst;pio mutant embryos may combine both defects and suffer from maturation deficits of the chitin/ZP matrix at the apical cell surface and within the tube lumen, which finally causes a high number of embryos with incomplete gas filling due to tube collapse. These maturation deficits are even more dramatic in the wurst;pio double mutants, which show no gas filling.”

11.) Dp remains cytoplasmic in pio mutant background - is the pio mutant phenotype due to defects by lack of Pio AND Dp function? What is the tracheal phenotype of dp mutants?

It has been discussed that dumpyolvr and pio mutants show similar phenotypes in early tracheal development (Jazwinska, 2003) and it has been discussed that dumpyolvr mutant embryos compromise tube size in combination with shrub mutants. The additional quantifications of the dumpyolvr mutant showed significantly increased tube length (Dong 2014). We used dumpyolvr mutant [In(2L)dpyolvr], an X-ray induced mutation of the dumpy gene locus (Wilkin 2000). dumpyolvr mutant resemble pio null mutant tracheal phenotypes including detached dorsal and ventral branches and oversized tracheal dorsal trunk with curly appearance in late embryos. We included chitin and Uif staining’s of stage 16 dumpy mutant embryos (Fig. S10).

This data suggest that Pio mutant phenotype is due to a lack of Pio and Dumpy, which would support our model, of Pio and Dumpy protein interaction in the extracellular space of the tube lumen.

In wt embryos Pio is predominantly in the luminal chitin cable, in contrast in dumpy mutant embryos most Pio is predominantly not at the luminal chitin cable. Less luminal Pio staining in dumpy mutant embryos but Pio accumulation apically shows that Dumpy is required for luminal Pio release in stage 16 embryos. This supports our model that Pio and Dumpy interaction may link membrane and matrix and that this link reacts on mechanical stress during tube expansion by Np-mediated cleavage of Pio and its accompanied luminal release due to linked Dumpy.

12.) Lines 374ff: the reduced dorsal trunk in Np mutants is not significant; the respective statement should be formulated carefully. If we believe the statistics (no significance), this would mean that attachment of the apical plasma membrane to the luminal chitin via Pio is needed to restrict axial extension; release of Pio is needed for differentiation (taenidia formation, luminal clearance) beyond morphogenesis.

We agree with the reviewer that the reduction of the dorsal trunks in Np mutant is statistically not significant. However, the mean value is clearly below that of WT. Therefore, we revised our statement as follow: “In Np mutant embryos, tracheal dorsal trunk length shows the tends to be reduced compared to wt embryos.” Further, the btlG4-driven UAS-Np overexpression of Np suggests strong Pio release from the apical membrane and therefore resembles the pio mutant tube length overexpansion (Fig. 8A,B; Fig S13). Thus, our current observations indicate that Np-mediated Pio release at the cell membrane enables precise tube length elongation.

We thank the referee for discussing that Pio is needed for taenidial fold formation which would fit to our findings in pio null mutant embryos. Pio mutant embryos show the appearance of taenidial folds in stage 16 embryos (airyscan) and stage 17 embryos (TEM images). However, TEM images also show chitin matrix reduction in pio mutant stage 17 embryos. Further, co-stainings of Pio with Crb and Uif, as well as co-stainings of mCherry::Pio with Dpy-GFP and cbp confirms that the Pio localize at the apical cell membrane where taenidial folds form in late stage 16 embryos. Thus, our observations suggest that Pio and Dumpy are required at the apical membrane and matrix to stabilize taenidial folds and tube lumen during 17. This also includes the Np-mediated Pio release at the apical cell membrane. As requested by the referee we summarized Pio function during late tracheal development in our simplified model (see Fig. 9).

However, it is of note that Np-mediated Pio release increases at late stage 16 (Fig. 5A, 6D; Fig. S13) but is strongly reduced in stage 17 embryos. In contrast, thin taenidial fold are formed at late stage 16 and becomes thicker and form at fusion points during stage 17 and reach their most mature form when the intraluminal chitin cable is cleared (Öztürk-Colak et al., elife, 2016). Thus, the pattern of Pio release and taenidial fold differentiation do not fully match. Moreover, in preliminary experiments we observe Pio antibody staining in stage 17 embryos at the apical cell membrane of dorsal trunks (data not shown). Furthermore, lumen clearance of Obst-A, Knk, Sepr and Verm are not affected in pio mutant embryos, but unknown luminal ECM contents remained (Fig. 1D). Therefore, we will follow this very interesting idea in future experiments.

Nonetheless, we state in the results that Pio shedding is essential:

“Our data assumes that Np overexpression may enhance Pio shedding in stage 16 embryos, affecting the Pio-mediated ZP matrix function. Upon breathless (btl)-Gal4-mediated expression of UAS-Np in tracheal cells, we observed a high amount of Pio puncta across the entire tracheal tube lumen, specifically in stage 16 embryos but not in earlier stages (Fig. S13). Consistently tracheal Np overexpression led to tube overexpansion in stage 16 embryos resembling the pio mutant phenotype (Fig. 8A,B). Thus, Np-mediated Pio shedding controls Pio function.”

13.) Why don't we see the apical Pio signal in Figure 4B?<br />

The red arrowhead points to apical mCherry::Pio punctuate staining in the Fig. 5B (before 4B) in the close up of the “bleached area” before bleaching and 56min post bleaching. However, in vivo bleaching experiments do not allow additional antibody stainings to detect precisely the apical cell membrane. Further, the Dpy::eYFP marks the tube lumen and the apical cell surface. The latter showed adjacent mCherry::Pio punctuate staining. However, due to bleaching Dpy signal was not detectable in the area.

14.) The Strep signals in the merges in Figure 7C are not well visible.

We are not sure which Strep signal the reviewer is referring to in Fig. 7C, which is now Fig. 8C. The top panel shows the Strep signal (right panel) overlapping with GFP in cells that do not express Np or human matriptase. Thus, the TGFB3 ZP domain is not cleaved, and the intracellular GFP and also the extracellular Strep signals are maintained and overlap.

In contrast, when Np or human matriptase is added, the TGFB3 ZP domain is cleaved and only the intercellular GFP signal is retained, whereas the extracellular Strep signal is released from the cell surface. This explains why the Strep signal is barely detectable in the middle and lower panels of Fig. 8C.

Reviewer #1 (Significance):

This work brings together several factors (Pio, Dp, Np, Wst etc) already known to be needed for tracheal morphogenesis and differentiation in the embryo of D. melanogaster. Having worked myself with some of these factors, however, I recognize that the interaction between these factors is novel and very exciting. The experiments strongly indicate a new mechanism of cell-ECM connection that seems to be conserved to some extent (as they provide preliminary data on an example from humans). By integrating the functions of different factors, the work provides ample opportunity for future projects to elucidate this mechanism in detail. Therefore, I expect that it will have a significant impact not only on the field of developmental cell biology but also, due to the conserved proteins involved (ZP proteins, Matriptase), on the field of cell biology of human diseases.

Reviewer #2 (Evidence, reproducibility and clarity):

_The figures are clear, and the questions well addressed. However, I find that some of the claims are not completely backed by the data presented and have some suggestions that will hopefully make some points clearer.

Major comments

1.) In the abstract and at the end of the introduction the authors claim that they show that Pio, Dpy and Np support the balancing of mechanical stresses during tracheal tube elongation. However, this is not shown in this manuscript, where tension or mechanical stress were not measured and it is therefore speculative._

As requested by the reviewer, we deleted “support balancing of” at the final sentence of the Introduction. Please, note that we did not use the term balancing of mechanical stresses at the abstract.

However, we revised the abstract.

It has been shown previously that forces and mechanical tension rise when apical membrane expands and elastic extracellular matrix, which is anchored to the membrane balances theses forces (Dong et al., 2014). Furthermore, its has been shown that the gigantic and elastic Dumpy protein modulates mechanical tension (Wilkin et al., 2000). Thus, these previous publications state that mechanical tension rise at the apical cell membrane and matrix when tubes expand during stage 16 and that Dpy is part of that molecular process, which we included in the abstract as essential background information.

“The apical membrane is anchored to the apical extracellular matrix (aECM) and causes expansion forces that elongate the tracheal tubes. The aECM provides a mechanical tension that balances the resulting expansion forces, with Dumpy being an elastic molecule that modulates the mechanical stress on the matrix during tracheal tube expansion.”

Nonetheless, our results show that Np-mediated Pio cleavage increases during stage 16 as response to tube length expansion which is accompanied by forces as postulated by others (see above). We further observe that the membrane bulges and chitin matrix tear off, when Pio cleavage does not occur in Np mutant embryos. Our data further show that Pio and Dumpy interact and that Pio release is prevented in Dpy mutant embryos. Altogether this suggests that the Np-mediated Pio cleavage responds to tube expansion and requires Dpy for luminal Pio release.

We therefore claim in the final sentence of the introduction that “…ZP domain proteins Pio and, Dumpy, as well as the protease Np respond to mechanical stresses when tracheal tubes elongate”. The according changes are marked in red.

2.) The authors state that all pio CRISPR/Cas9 generated mutants display identical tracheal phenotypes, however these data are not shown. Tracheal phenotypes, in particular DT phenotypes, of all mutants generated should be shown in supplementary materials.

As requested by the reviewer, we included the data in the supplement. The pio5M and pio11R alleles showed embryonic lethality and a 100% gas filling defect resembling the pio17C allele. Additionally, we extended the tracheal analysis with the pio5M allele and identified tube size defects, irregular pattern of taenidial folds and apical membrane deformation, altogether resembling the pio17C allele. These new data are shown in the supplement Fig. S1.

We clarify this in the results section as follows:

“The tracheal phenotypes of pio5m are shown in the supplement (Fig. S1B-F). In all other Figures, we show images of the pio17c allele. “

3.) At stage 16, pio null mutants display DT overelongation phenotypes (Fig. 1). The authors should quantify this phenotype.

As requested by the reviewer, we quantified the DT overelongation phenotypes for pio5M (Fig. S1). The quantification of pio17C was shown already in Fig. 6B, now Fig 8B.

4.) The authors analyse Pio distribution under tubular stress, using mega mutants and Chitinase overexpression. Pio localization changes in these genetic backgrounds and this is shown in Figure 2 only in a qualitative manner. The authors should measure Pio localization at the lumen and at the membrane and provide quantitative data.

As requested by the referee, we measured Pio localization recognized by the anti-Pio antibody at the lumen and at the membrane to provide quantitative data. These are shown in Fig. 2E.

All images were taken with a Zeiss Airyscan. For statistical analysis we used the the profile tool of the Zeiss ZEN 2.3 black software. This tool allows the measurement and comparison of fluorescence pixel intensities of individual channels. We determined the fluorescent intensities profile across the tube to identify values at apical membrane and tube lumen at minimum 10 different position of DTs (metameres 5 to 6) of two distinct embryos for each genetic background. The maximum values of membranes versus tube lumen were set into ratio and compared between control, mega mutant and Cht2 overexpression. The control embryos showed a ration below 0.4, the Cht2 overexpression a ratio of 1.2 and mega mutants a ratio of about ~0.9. These quantitative data confirm the statement that Pio localization increases at and near the apical cell membrane with respect to the lumen in mega mutants and in Cht2 overexpression embryos.

5.) Surprisingly and interestingly, wurst;pio transheterozygotes display very strong tracheal defects. The authors say they observe gas filling defects; however it is not clear from figure 2E if this indeed the case. From the panel in the figure, it looks like these embryos suffer from strong tracheal morphogenetic defects. It would be necessary to have a better analysis of these embryos. What is the penetrance of this phenotype. If this is 100% penetrant, one would expect it to be lethal. Therefore, double mutant balanced stocks are not viable? Having analyzed the phenotypes and confirmed which morphogenetic defects the transheterozygote embryos present, how does this genetic interaction fit with the model presented?

We are thankful to the reviewer for this interesting point of view suggesting that the wurst;pio embryos display tracheal morphogenetic defects. First, our data show that only 11.6% of the wurst;pio transheterozygous embryos completed gas filling and survived until adulthood. In contrast, 88.4% of transheterozygous wurst;pio mutant embryos did not complete gas filling which is now presented in Fig. 3B. The corresponding quantifications is presented in Fig. 3D. Importantly, the 88.4% wurst;pio transheterozygous embryos which show gas filling defects do not hatch as larvae and die.

As requested, we performed a better morphogenetic analysis, which is presented in Fig. 3C. Analysis of the gas filling defects with light microscopy were repeated with a better objective (Zeiss Apochromat 25x Gly; 0.8 NA). Indeed, this analysis revealed a strongly compromised tube lumen morphology with irregular tube lumen pattern as if tubes twist and bend. This tube lumen deformation was further confirmed with the confocal analysis of chitin staining (cbp). The tube lumen of stage 17 transheterozygous wurst;pio mutant embryos showed irregular lumen pattern with unusual twists and even partially collapsed tubes.

Furthermore, as asked by the referee, we generated the wurst,pio double mutation. All wurst,pio double mutant embryos lacked gas filling. In a more in-depth analysis of the tube lumen with a high-performance objective we could not identify any normal tube lumen in stage 17 embryos. Instead the double mutant embryos revealed completely collapsed tracheal tubes. This was confirmed by the chitin staining and confocal analysis. All new data are presented in the supplement.

As shown in our manuscript and in previous publications, neither pio nor wurst mutant embryos affect cell polarity or gross organization of the actin and tubulin cytoskeleton. However, we found that wurst mutant embryos showed irregular apical membrane expansion at tube lumen (Behr et al., 2007; legend Fig. 4), irregular chitin fiber organization and to some extend collapsed tube lumen. In pio mutant embryos we found deformed apical membrane of DTs, irregular pattern of taenidial folds and to some extend collapsed tube lumen. Thus, the apical membrane is their common target of both proteins in late embryonic development, suggesting that pio functions provide stability and wurst functions the internalization of proteins at the apical membrane.

We discussed it as follows:

“Nevertheless, Pio and its endocytosis depend on its interaction with the chitin matrix and the Np-mediated cleavage. In stage 16 wurst and mega mutant embryos, we detect Pio antibody staining at the chitin cable, suggesting that Pio is cleaved and released into the dorsal trunk tube lumen. Also, the Cht2 overexpression did not prevent the luminal release of Pio. However, reduced wurst, mega function, and Cht2 overexpression caused an enrichment of punctuate Pio staining at the apical cell membrane and matrix (Figs. 1,2). Although the three proteins are involved in different subcellular requirements, they all contribute to the determination of tube size by affecting either the apical cell membrane or the formation of a well-structured apical extracellular chitin matrix, indicating that changes at the apical cell membrane and matrix in stage 16 embryos affect the Pio pattern at the membrane. It also shows that local Pio linkages at the cell membrane and matrix are still cleaved by the Np function for luminal Pio release, which explains why those mutant embryos do not show pio mutant-like membrane deformations and Np-mutant-like bulges. This is in line with our observations that tracheal Pio overexpression cannot cause tube size defects as the Np function is sufficient to organize local Pio linkages at the membrane and matrix. Therefore, it is unlikely that tracheal tube length defects in wurst and mega mutants as well as in Cht2 misexpression embryos are caused by the apical Pio density enrichment.”

“Heterozygous and homozygous pio mutant embryos generally do not show tubal collapse. However, the loss of Pio and accompanying lack of Dpy secretion in stage 17 pio mutant embryos led to the loss of a Pio/Dpy matrix, impacting the late embryonic maturation and differentiation of a normal chitin matrix at the apical cell surface. TEM images reveal reduced dense chitin matrix material at taenidial folds and misarranged taenidial fold pattern (Figs. 1; S2), suggesting impaired taenidial function prevents tube lumen from collapsing after tube protein clearance. Wurst knockdown and mutant embryos do not show general tube collapse, but luminal chitin fiber organization is disturbed in stage 17 embryos (Behr et al., 2007). Therefore, transheterozygous wurst;pio mutant embryos may combine both defects and suffer from maturation deficits of the chitin/ZP matrix at the apical cell surface and within the tube lumen, which finally causes a high number of embryos with incomplete gas filling due to tube collapse. These maturation deficits are even more dramatic in the wurst;pio double mutants, which show no gas filling.”

6.) mCherry::Pio Dpy::eYFP time lapse analysis and FRAP experiments is very interesting. However, it is not clear to which degree bleaching occurs in the tracheal lumen. The authors claim that recovery is very fast and can be seen from minute 2, however, frame-by-frame analysis of Movie S2 does not show a clear different between luminal Pio from minute 0 to minute 2. Rough comparison with the luminal area surrounding the bleached area, does not show a clear difference in luminal Pio before and after photobleaching. To claim fast recovery of luminal Pio after photobleaching, the authors should quantify luminal Pio, before and after bleaching.

We agree with the reviewer and deleted “fast”. The Video2 shows intracellular mCherry::Pio recovery within 2min after photobleaching. The Video 2 shows extracellular (luminal) recovery within 6min after photobleaching, when first large mCherry::Pio puncta appear at the apical surface of the bleached area. Nonetheless, mCherry::Pio puncta appear in the lumen indicating recovery, whereas Dpy::eYFP did not.

We state this in the Results section as follows:

“In stage 16 embryos mCherry::Pio puncta reappeared in tracheal cells within 2 minutes of bleaching and in the tubular lumen within 6 minutes.”

In addition, in figure 4D, the normalized mCherry::Pio fluorescence in the graph what does it refer to? Intracellular Pio?

Figure 4D, now 5D, shows Western Blot signals. We guess that you refer to Fig 4B which is Fig. 5B.

We are sorry for confusion and named it now Fig. 5B’.

We stated in the Material section:

“The bleaching was performed with 405nm full laser power (50mW) at the ROI for 20 seconds. A Z-stack covering the whole depth of the tracheal tubes in the ROI were taken at each imaging step. “Fluorescence intensity in the bleached ROIs was measured after correction for embryonic movements using Fiji.”

Thus, to clarify this point, we added to the legends:

“Fluorescence intensities refer to the bleached ROIs as indicated with the frame in corresponding Movie S2 and was measured after correction for embryonic movements.”

7.) When mCherry::Pio Dpy::eYFP time lapse analysis and FRAP experiments was done in an Np mutant background, the authors describe lack of Pio recovery within the lumen (Movie S3). However, when comparing control and Np mutant background embryos, Pio is not properly released into the lumen of Np mutants (as stated by the authors and seen by comparing movies S1 and S4). Furthermore, on minute 0 of the FRAP experiment in Np embryos, there is no detectable Pio in the DT lumen. Therefore, recovery was not expected in Np mutants and should not be claimed as a conclusion for this experiment.

We thank the reviewer for careful reading and apologize our wrong description. We changed it accordingly as follows:

“In contrast to the control, extracellular mCherry::Pio is not released into the tube lumen within 56 min after bleaching in Np mutant embryos (Fig. 6C, Video S3).”

8.) Brodu et al (Dev Cell 2010) have shown that Pio is important for cytoskeletal modulation during tracheal maturation. Pio is important for non-centrosomal microtubule (MT) arrays anchored at the tracheal cell apical membranes. In addition, MT disruption in tracheal cells leads to lumen formation defects (Brodu et al, Dev Cell 2010). In the absence of Pio, the tracheal cytoskeleton is altered, and this could explain some of the results observed. Ideally, the work should be complemented with a basic cytoskeletal analysis, but if this is not possible, the authors should discuss some of the phenotypes in light of this Pio function.

Dear reviewer, this is a great idea. Therefore, we analyzed F-actin with Phalloidin and beta tubulin (E7 antibody, DSHB) in the dorsal trunk cells of stage 16 control and pio mutant embryos. However, tracheal cells are tiny and only gross irregularities can be realized. So, confocal Z-stack analysis of the stainings did not show gross differences between control and pio mutant embryos. We observe the expected apical subcortical accumulation for the actin and tubulin cytoskeleton in dorsal trunk cells of pio stage 16 mutant embryos which also has been shown for wt embryos elsewhere. These new data are presented in the supplement Fig. S7.

Minor comments<br /> The model should not be in supplementary materials and should be moved to the main manuscript.

We thank the reviewer for this suggestion and moved the model to the main part – now Fig.9. As requested by the reviewer 1, we extended the model, showing the timing events of Pio function.

Throughout the manuscript embryonic stages are described using different nomenclature (stage X, stX and st X). Either way is correct, but the same nomenclature should be used throughout.

We apologize for the different nomenclature and use "stage X" in the manuscript and "stX" in the figures for space reasons. Legend 1 clarifies the abbreviation.

In Fig. S1 B and C the authors should specify which pio allele is being analysed (as in Fig. 7). The same should be done in the text.

That's a fairly good point. To be clear from the beginning, we now state the following in the first paragraph of the results:

“The tracheal phenotypes of pio5m are shown in the supplement (Fig. S1B-F). In the all other Figures, we show phenotypes of the pio17c allele.”

Line 131, it is not correct to say that WGA visualizes cell membranes. WGA marks/stains cell membranes.

Thanks for finding this mistake, it’s now corrected.

Line 165 "leads to excessive tube dilation and length expansion due to strongly reduced luminal chitin" is not correct. Chitin reduction leads to excessive tube dilation but not to length expansion, as reported in the papers cited at the end of the sentence.

Thanks very much for careful reading, we deleted “and length expansion” from the sentence.

Line 220-221, what do authors refer to as "stage 16 wt-like control embryos"?

Thanks for finding these mistakes. We corrected as follows:

“In stage 16 embryos mCherry::Pio puncta….”

Line 221, "some minutes" should be replaced by a specific number of minutes. According to Movie S2 reappearance of tracheal cell Pio happens from minute 16.

We agree with the reviewer to state the time when mCerry::Pio puncta reappear. We observe first large puncta within two minutes after bleaching in tracheal cells at the ROI (Video S2, lower cell row at the movie). We further observe the reappearance of first large puncta at the ROI within 6 minutes in the tracheal tube lumen.

We corrected it as follows: “In stage 16 embryos mCherry::Pio puncta reappeared in tracheal cells within 2 minutes of bleaching and in the tubular lumen within 6 minutes.”

Line 291 "time laps" should be lapse.

Thanks for finding the typo, it is corrected now.

Line 302, "Pio was not shedded into the lumen but remained at the cell" should be "Pio was not shed into the lumen but remained in the cell".

Thanks for finding the typo, it is corrected now.

_Referees cross-commenting

I agree. Taken together, all the comments will improve the quality of the work and of a future manuscript. Also, everything seems quite doable and will not present any problems._

Reviewer #2 (Significance):

_The findings shown in this manuscript shed light on the regulation of tubulogenesis by ZP proteins and how their interaction with the ECM can be regulated by proteolysis. It was known that Pio is involved in tracheal development, is secreted into the lumen, regulating tube elongation (Jaźwińska et al., Nat.Cell Biol., 2003) and anchoring MTs to the apical membrane during tubulogenesis (Brodu et al, Dev. Cell 2010). This work provides additional molecular insights into Pio dynamics and regulation during tube maturation.<br /> This work will be of interest to a broad cell and developmental biology community as they provide a mechanistic advance in ZP proteins involved in morphogenesis. It is of specific interest to the specialized field of tubulogenesis and tracheal morphogenesis.

Field of expertise:<br /> Drosophila, morphogenesis, tracheal tubulogenesis, cytoskeleton_

Reviewer #3 (Evidence, reproducibility and clarity):

_Summary<br /> In this manuscript, Drees and colleagues analysed, during the formation and growth of tubular systems, how cells combine forces at the cell membranes while maintaining tubular network integrity. A fundamental question is to understand how cells manage to integrate the axial forces to stabilise the cell membrane and the apical extracellular matrix (aECM).<br /> To address this question, the authors study the formation of the tracheal system in Drosophila embryos, a well-established and detailed model system to investigate formation of tubular networks. In particular, they focused on the formation of the larger tube of the tracheal network, the dorsal trunk. The formation of this tube depends in part of axial extension along the antero-posterior axis.<br /> They concentrated their work on the function of Piopio (Pio), a Zona-Pellucida (ZP)-domain protein. They showed that Pio together with the protease Notopleural (Np) contribute the sense and support mechanical stresses when tracheal tubes elongate, thus ensuring normal membrane -aECM morphology.

Major Comments

In a previous work, Drees et al. (PLOS Genetics 2019), showed the matriptase-prostasin proteolytic cascade (MPPC), is conserved and essential for both Drosophila ECM morphogenesis and physiology.<br /> The functionally conserved components of the MPPC mediate cleavage of zona pellucida-domain (ZP-domain) proteins, which play crucial roles in organizing apical structures of the ECM in both vertebrates and invertebrates. They showed that ZP-proteins are molecular targets of the conserved MPPC and that cleavage within the ZP-domains is a conserved mechanism of ECM development and differentiation.<br /> Here, Drees et al. investigate further how the coupling between membrane and matrix takes place to ensure proper tube growth.<br /> Pio distribution and phenotypes<br /> They first focused on the tracheal phenotypes observed in a pio null mutant context. So far, the only pio mutant characterised was a point mutation in the ZP domain. Using CRISPR/Cas9, they generated new alleles of pio which are lack of function alleles. In the context, Drees and colleagues observed over-elongated dorsal trunk tubes, with bulges appearing at stage 16 between the apical domain of tracheal cells and adjacent extra-luminal matrix.<br /> Additionally, pio mutant embryos showed impaired tube lumen clearance of the some of the aECM components, which prevent gas-filling of the airways.<br /> To detect Pio distribution, the authors used either anti-Pio antibody directed toward a short stretch with the Pio ZP domain or generated a CRISPR/Cas9 piomCherry::pio line.

_

1.) The Pio antibody shows a strong luminal staining as already published. But the authors reported an apical membrane signal in tracheal cells. I find this apical membrane signal really difficult to observe in panel Fig. 2B. The overlap between the Pio dots and the apical membrane labelled with Uif showed in Fig 2C can be due to the 3D projection. It is only when endocytosis is unpaired (Suppl Fig. 2), that data are more convincing.

We thank the reviewer for this important point, we are sorry for the unconvincing presentation and for having the chance to improve it.

We show the 3D image of Pio puncta as voxels overlapping with Uif at the apical cell membrane. The amount of Pio voxels overlapping with the Uif marked apical cell membrane increased in mega mutant and due to tracheal Cht2 overexpression. This result was indicated by a representative region (frame) and white arrows and is shown now in Fig. 2C.

We further used orthogonal projections across the tracheal tube of the airyscan Z-stacks. Random usage confirmed that puncta of Pio antibody staining overlap with Uif at the tube lumen. We observed overlap in controls, but increasing overlap in mega mutant and Cht2 overexpressing embryos. This result is shown now in Fig. 2E.

However, to overcome any misinterpretations of projections, we used single images of the original airyscan Z-stacks for co-localization analysis with the Zeiss ZEN software (black, 2.3, sp1). We used two available and independent standard methods to compare fluorescence pixel intensities of different channels namely the ZEN co-localization and the ZEN profile tool. Both are described in the Materials section.

a.) With the co-localization tool we compared directly fluorescence pixel intensities of Pio and Uif. Highest overlap of the intensities, shown in the ZEN tool as third quadrant, were set to white for better visualization in the images. These new images are included as Fig. 2D and show recurrent overlap of Pio and Uif antibody stainings (punctuate pattern) along the apical cell membrane at the dorsal trunk of stage 16 control embryos. This overlap pattern increased in mega mutant and Cht2 overexpression embryos.

b.) A second approach for comparing fluorescence intensities is the ZEN “profile” tool. Drawing a line across the tube allowed us to compare peak fluorescence pixel intensities of the different channels at distinct regions, such as the apical cell membrane and the tube lumen including the cbp marked chitin cable. This tool detected overlap of peak fluorescence intensities of UIF and Pio antibody staining’s, confirming that Pio is located together with UIF at the apical membrane of dorsal trunk tracheal cells. These new intensity profiles and the corresponding images are presented in the supplement as Fig. S4B-D. Quantifications of this method comparing the ration of Pio peak intensities between the apical cell membrane and the tube lumen are presented as Fig. 2F (as requested by Reviewer 2).

2.) When the author used their CRISPR/Cas9 piomCherry::pio line to characterise Pio distribution (Fig.4), Pio is localised at the apical plasma membrane before stage 16. Only at stage 16, Pio is detected within the lumen. This timing of Pio release in the lumen is critical for the model proposed by Drees at al. This is an important point to assess the difference between the use of the antibody (which mostly label the lumen) while piomCherry::pio line is mostly at the membrane.

We agree with the reviewer that the Pio antibody shows a different pattern within the tube lumen of earlier stages. The Pio antibody shows intense extracellular staining from early stage 12 onwards, presumably due to its early function at dorsal and ventral branches, as shown by Anna Jazwinska (Jazwinska et al., 2003). The intense luminal Pio antibody staining, predominantly at the chitin cable, persist until its disappearance due to airway protein clearance during stage 17. Unfortunately, this strong luminal Pio staining made it impossible to examine the Pio distribution pattern in more detail during stage 16. Nevertheless, Np overexpression experiments indicate that luminal Pio release occurs specifically in stage 16 embryos (Fig. S13), which was tested with the Pio antibody, see results, second last paragraph:

“Our data assumes that Np overexpression may enhance Pio shedding in stage 16 embryos, affecting the Pio-mediated ZP matrix function. Upon breathless (btl)-Gal4-mediated expression of UAS-Np in tracheal cells, we observed a high amount of Pio puncta across the entire tracheal tube lumen, specifically in stage 16 embryos but not in earlier stages (Fig. S13).”

We further agree with the reviewer that mCherry::Pio was used to characterize in vivo Pio distribution within the dorsal trunk cells and tube lumen during stage 16. The Fig. 5A shows apical mCherry::Pio distribution pattern in early and late stage 16 embryos. Importantly, the appearance of luminal mCherry::Pio increased during stage 16 and mainly enriched at late stage 16. See Figure 5A, red arrowheads point to apical Pio and red arrows to luminal Pio staining.

Furthermore, as discussed above and shown by different ZEN tools, such as co-localization and fluorescence intensity profile tools, Pio antibody stainings revealed a punctuate pattern at the apical cell membrane of dorsal trunk cells in stage 16 embryos, which is reflected also by the appearance of apical mCherry::Pio puncta at the membrane surface. Additionally, we observed mCherry::Pio puncta also within the tube lumen (see the new Figures S4B & S8). Thus, subcellular Pio distribution at the apical cell membrane and lumen were observed for both, Pio antibody staining and mCherry::pio pattern.

Nonetheless, there is different luminal appearance between the Pio antibody staining and mCherry::Pio. Pio antibody detects a short stretch at the ZP domain and thus detects all possible Pio variants, uncleaved and cleaved. Due to early tracheal Pio function, Pio enriches within the tube lumen in an intense core-like structure, which is recognized by the Pio antibody and is comparable with the Dpy::eYFP pattern. Also mCherry::Pio labels all Pio variants, uncleaved and cleaved. The spatial temporal mCherry::Pio expression pattern (Fig. S5) is comparable with the Pio antibody pattern and the staining at the membrane in stage 16 embryos. However, mCherry::Pio did not enrich in the lumen in a core-like structure, nonetheless, shows overlap with luminal Dpy::eYFP.

Jaswinska showed that Pio antibody staining is intracellular in the trachea of stage 11 pio2R-16 point mutation embryos (Jaswinska et al., 2003; Fig 2d). To understand more about the specificity of the antibody, we performed stainings in the null mutant embryos. In contrast, to the high number of intracellular Pio puncta in pio2R-16 point mutation embryos, Pio stainings were much more reduced in pio5m and pio17c mutants, but a low number of Pio puncta were still detectable in the embryos (Fig. S1G,H). It is of note that also dpy mutants showed strongly reduced Pio antibody staining (Fig. S10E). Thus, discussing underlying causes of enriched (Pio antibody) versus non-enriched (mCherry::Pio) luminal staining are speculative. However, observations by Jaswinska et al. (2003) and our new observations, investigating the Pio antibody stainings in pio null mutants, dpy mutants, eYFP::Dpy embryos and NP overexpression may hint to the possibility of cross-reactivity of the Pio antibody to other ZP domains which may intensify the appearance of luminal Pio antibody staining in control embryos.

Anyway, we clarify the difference in luminal Pio pattern in the discussion as follows:

“Indeed, the anti-Pio antibody, which detects all different Pio variants, showed a punctuate Pio pattern overlapping with the apical cell membrane markers Crb and Uif at the dorsal trunk cells of stage 16 embryos (Fig. 2; Fig. S3,S4). Additionally, Pio antibody also revealed early tracheal expression from embryonic stage 11 onwards, and due to Pio function in narrow dorsal and ventral branches, strong luminal Pio antibody staining is detectable from early stage 14 until stage 17, when airway protein clearance removes luminal contents. In the pio5m and pio17c mutants Pio stainings were strongly reduced although some puncta were still detectable in the trachea (Fig. S1G,H). Similarly, Pio antibody staining is intracellular in the trachea of stage 11 pio2R-16 point mutation embryos (Jaźwińska et al., 2003). Interestingly, also dpy mutants showed strongly reduced and intracellular Pio antibody staining (Fig. S10E).

We generated mCherry::Pio as a tool for in vivo Pio expression and localization pattern analysis during tube lumen length expansion. The mCherry::Pio resembled the Pio antibody expression pattern from early tracheal development onwards. However, luminal mCherry::Pio enrichment occurs specifically during stage 16, when tubes expand. The stage 16 embryos showed mCherry::Pio puncta accumulating apically in dorsal trunk cells. Moreover, mCherry::Pio puncta partially overlapped with Dpy::YFP and chitin at the taenidial folds, forming at apical cell membranes. Supported by several observations, such as antibody staining, Video monitoring, FRAP experiments, and Western Blot studies (Figs. 4,5), these findings indicate that Pio may play a significant role at the apical cell membrane and matrix in dorsal trunk cells of stage 16 embryos.”

3.) Another important point is to explain the discrepancy between the pio mutant alleles. The allele containing a point mutation in the ZP domain shows no over-elongated tubes (Dong et al 2014, Jazwinska et al. 2003) while the lack of function alleles does.

The reviewer is correct that the pio2R-16 mutation shows only a disintegration phenotype whereas our pio null mutations show in addition tube length defects. However, Dong et al. showed significantly increased dorsal trunk length in shrub; pio2R-16 double mutant embryos when compared with shrub mutant embryos (Supplemental Fig. S4A). Also, the shrub;dpyolvR double mutant embryos revealed increased tube length expansion when compared with shrub mutant embryos. Moreover, their quantifications show that the also dpyolvR mutant embryos revealed significantly increased tube expansion when compared with wt. Altogether these previous findings suggests that Pio and Dpy are involved in controlling tube length control during stage 16.

Furthermore, we generated three independent pio null mutation alleles, which lost all the essential Pio protein domains, and caused all embryonic lethality, gas-filling defects, branch disintegration phenotype and tube length defects (quantifications are shown in Figs. 9 and S1). In addition, pio null mutations prevent Dpy::eYFP secretion. Thus, we are confident that the observed tube length defects as well as the air-filling defects are due to the loss of Pio, and in particular since these defects could be rescued by Pio Expression in the pio null mutation background, as shown in Fig. 3B.

So, what could make the difference?

The described pio2R-16 mutation allele contains a X-ray induced single point mutation that led to an amino acid replacement (V159D) in the ZP domain. It is not clear how the amino acid exchange affects the protein and the ZP domain. It may hamper pio function and maybe this amino acid replacement is problematic for the early tracheal function but not during stage 16. As stated by Jazwinska et al. 2003 (Fig. 2 legend), Pio antibody staining is intracellular in the mutants and extracellular in the trachea of wt at stage 13.

They further speculate that the mutant Pio protein may retain in the secretory pathway, but this is not confirmed with co-markers. As luminal Pio function is required to provide a barrier for autocellular AJ formation, this fails in pio2R-16 mutation. In contrast, it is still possible that Pio interacts and supports Dpy secretion in pio2R-16 mutation and additionally it is thinkable that intracellular Pio may reach to some extend the apical cell membrane in pio2R-16 mutation stage 16 and thus can support tube size control. But these assumptions are speculations.

Nevertheless, to clarify this point we explain the discrepancy between the pio2R-16 mutation and pio null mutations alleles as follows:

“Using CRISPR/Cas9, we generated three pio lack of function alleles (Fig. S1A), all exhibiting embryonic lethality and identical tracheal mutant phenotypes. The tracheal phenotypes of pio5m are shown in the supplement (Fig. S1B-F). In all other Figures, we show images of the pio17c allele. The pio17c and pio5m null mutant embryos revealed the dorsal and ventral branch disintegration phenotype known from a previously described pio2R-16 mutation allele which contains a X-ray induced single point mutation that led to an amino acid replacement (V159D) in the ZP domain (Jaźwińska et al., 2003). Additionally, the late stage 16 pio17c and pio5m null mutant embryos showed over-elongated tracheal dorsal trunk tubes (see below).”

4.) A minor point, the author should provide hypothesis to explain why only the clearance of CBP, Obstructor-A and Knickkopf are affected in a pio mutant background and not Serpentine and Vermiform.

We thank the reviewer for careful reading and the comment on this point. We would be happy to see such a scenario which could give us a hind of Pio interaction partners at the chitinous matrix. However, we stated that luminal material, such as Obst-A and Knk are removed from the lumen (see Fig. S5A). We further describe that in pio mutant embryos, luminal Serp and Verm staining appeared reduced but showed wt-like distribution (see Fig. S6) in stage 16 embryos. We do not show Serp and Verm in stage 17 embryos, but they are removed from the tube lumen (not shown). These data are received from immune-staining’s and confocal analysis.

Nevertheless, we also state that pio mutant embryos revealed lumen clearance defects in TEM analysis, of undefined material in the tube lumen (see Fig. 1D and Fig. S2B).

To clarify this point we state in the results as follows:

“Fourth, ultrastructure TEM images revealed aECM remnants in the airway lumen of pio mutant stage 17 embryos, while control embryos cleared their airways (Fig. S2B). Consistently, the in vivo analysis of airways in stage 17 pio mutant embryos revealed lack of tracheal air-filling (Fig 3B). The pan-tracheal expression of Pio in pio mutant embryos rescued the lack of gas filling (Fig 3B). Thus, TEM images suggest that pio mutant embryos showed impaired tube lumen clearance of aECM, which prevented subsequent airway gas-filling. “

And

“Also, the pio mutant embryos showed tracheal lumen clearance defects of chitin fibers in ultrastructure (TEM) analysis (Figs. 1D, S2B). In contrast, confocal analysis revealed that well-known chitin matrix proteins, such as Obstructor-A (Obst-A) and Knickkopf (Knk), are removed from the lumen of pio mutants (Fig. S5A). These results suggest that the Pio function did not affect airway clearance of Obst-A and Knk and therefore did not play a central role in airway clearance like Wurst. Nevertheless, airway clearance defects observed in TEM images in pio null mutant embryos and, in addition, defective tube lumen morphology in wurst;pio transheterozygous mutant embryos explain the occurrence of airway gas filling defects.”

5.) Pio and Dumpy. Dumpy (Dpy) is another ZP domain protein secreted by the tracheal cells and detected in the lumen. To follow Dpy distribution, Drees and colleagues used a Dpy::eYFP protein trap line, the same used in Dong et al. However, in this latter paper, Dong et al. stated, using a Crb staining, that Dpy is not at the apical cell surface but only in the lumen. However, Drees and colleagues reported (line 227 and Fig. 4C) that Dpy appears both at the apical cell surface and in the lumen of the tracheal system. But they did not show a co-localisation with an apical marker. Furthermore, in their previous work, (Drees et al. 2019) they called the apical staining a "peripheral shell" layer. In addition, in S2R+ cell culture, it is only when Pio and Dpy co-express that Dpy is detected at the cell membrane. The in vivo localisation of Dpy is an important point that needs to be clarified as it is of importance for the final model proposed Supp Fig. 9.<br /> Drees at al. also performed FRAP experiments on Dpy::eYFP protein trap embryos. As excepted as already shown by Dong et al.

The referee is correct, we state “In stage 16 embryos Dpy::eYFP (Lye et al., 2014) appears at the tracheal apical cell surface and predominantly within the lumen (Fig. 4C).” The corresponding Fig. 4C reveals Dumpy::eYFP staining overlapping with chitin at two subcellular regions: Dpy is enriched as a core-like structure within the lumen overlapping with the chitin cable of the control embryos. Additionally, Dpy::eYFP overlaps with the chitin part that might be part of the apical cell surface. But this observation is hard to see in images in Fig. 4C and we apologize it. We therefore repeated the Dpy::eYFP localization analysis and analyzed in more detail with the ZEN profile tools, which shows peak fluorescence pixel intensities of different channels and provides the possibility to prove, if they overlap in XY axis.

We asked first, if cbp (chitin) appears at the apical surface of dorsal trunk cells, when Pio becomes cleaved and released. In mid stage 16 embryos cbp staining appeared in the luminal chitin cable and additionally in a distinctive pattern, which fits to the pattern of taenidial folds that start to form. We therefore used the apical cell membrane marker Crumbs to co-stain cbp. Airycsan microscopy fluorescence intensity profile analysis and corresponding close ups images confirmed the overlap of Crb and cbp stainings at this distinctive pattern indicating this shows the chitin matrix at the apical cell surface (Fig. S8A). But there was no overlap of cbp and Crb at the chitin cable structure. Thus, knowing the localization of the apical cell surface chitin matrix, we performed co-stainings of cbp with mCherry::Pio (RFP antibody). This revealed, as expected, overlap of cbp and RFP antibody staining at the apical cell surface chitin matrix (distinct pattern) and with the luminal chitin-cable (Fig. S8B,C). Finally we repeated the stainings and analysis with cbp, mCherry::Pio (RFP antibody) and Dpy::eYFP (GFP antibody). First, these results revealed overlap of Dpy::eYFP and cbp at the apical cell surface and in the tube lumen (Fig. S8D) and second, overlap of punctuate staining of Dpy::eYFP, cbp and mCherry::Pio at the apical cell surface chitin matrix and also at the luminal chitin cable (Fig. S8E).

Very obvious from images and Z-projection in Fig. 4C is the lack of extracellular Dpy::eYFP staining in pio mutant embryos. Dpy::eYFP enriched intracellularly, and thus, the pio mutant caused Dpy::eYFP mis-expression fits well to our results from S2R+ cell culture. As the reviewer notes, it is only when Pio and Dpy co-express that Dpy is detected at the cell membrane.

Altogether, Fig. 4C, cell culture experiments and our new stainings support our model, that Pio and Dumpy interact and are co-secreted at the apical cell membrane/surface, where Np mediates Pio cleavage. As requested by reviewer 2, we moved the model to Fig. 9. As requested by reviewer 1, we extended the model for timing events.

A minor point, the Dpy::eYFP protein trap line used in this study is not listed in the Materials and Methods section of the supplementary data.

Thanks, we included it into the List of sources (Supplement). This YFP-trap line (called CPTI lines) was published by Claire M. Lye et al., Development, 141, 2014. We cite it in our manuscript.

6.) The serine protease NP and Pio release. Drees and colleagues have pervious shown, preforming in vitro studies, that protease Notopleural (Np) cleaves the Pio ZP domain (Drees at al. 2019). Here the authors went a step further in demonstrating that it is also true in vivo at stage 17. In addition, they showed that, in Np mutant embryos, mCherry::Pio is mostly detected within tracheal cells and the luminal staining is strongly reduced. In this mutant context, the authors conducted FRAP experiment on the mCherry::Pio signal even very weak in the lumen. They showed hardly no recovery after photobleaching.<br /> In Drosophila S2 cells, Drees and colleagues showed that co-expression of the catalytically inactive NpS990A with mCherry::Pio in showed as a prominent signal the 90kDa mCherry::Pio variant in the cell lysate (Fig. 5B), and live imaging revealed mCherry::Pio localisation at the cell surface (Fig. S6B). However, in this inactive form context, a strong signal is also detected at 60kDA corresponding to a cleaved form of the Pio ZP domain (Fig. 5B), and Pio localisation at the cell surface appears weaker than in controls. They authors did not consider that another protease could be at play.<br /> On the other hand, in their previous work, Drees et al. identified a mutant form of Pio (PioR196A) which is resistant to NP cleavage in vitro. It will be a step forward to establish by CRISPR/cas9, as the authors seems to be successful with this technique, a mutant line carrying this point mutation. It will be important to determine whether the observed phenotype resembles that of a mutant Np phenotype.<br /> In their previous work (PLOS Genetics 2019), in Np mutant embryos, Drees et al. did not report "budge-like" deformations from stage 16 onwards leading to the detachment of the tracheal cell from their adjacent aECM. Either the alleles or the allelic combination is different between the two studies which could explain this difference, or it is a new phenotype that has not been previously described. In the latter case, it becomes important to quantify the proportion of segments showing these bubbles. Is this a rare phenotype to observe?

We thank the reviewer for the very interesting comments and the careful reading of our manuscripts and the very useful suggestions. We agree, the we cannot exclude the possibility that another protease is involved in the cleavage of Pio. Therefore, we included this important point in the discussion section as follows:

“Unknown proteases may likely be involved in Pio processing since cleaved mCherry::Pio is also detectable in inactive NpS990A cells.”

We think the generation of the pioR196A mutant to address Pio localization and tracheal phenotypes is a great idea, which we would like to address in future experiments. Unfortunately, the production of this fly line with such a specific point mutation at this position will take several months, not included the subsequent evaluation and phenotypic analysis of this fly line and mutants. Therefore, we apologize that we cannot pursue this question experimentally. Nevertheless, mentioning the possibility and the requirement of such an experiment is important and we discuss it as follows:

“Previously we identified a mutation at the Pio ZP domain (R196A) resistant to NP cleavage in cell culture experiments (Drees et al., 2019). Establishing a corresponding mutant fly line would be essential in determining whether the observed phenotype resembles the phenotype of the Np mutant embryos.”

However, knowing that we are not able to provide a new mutant fly line to evaluate the formation of the dorsal tube when an NP non-cleavable form of Pio is expressed, we sought to use an alternative approach by overexpressing Np in the trachea with btl-Gal4. This shows a clear pairing of Np overexpression and Pio release specifically at stage 16 dorsal trunk and associated tube overexpansion.

Finally, the reviewer is correct, we did not mention the appearance of bulges in Np mutant tracheal dorsal trunk cells in our previous publication. We used that same Np alleles in 2019 and a closer look at the publication of 2019 likewise shows the appearance of bulges in Np mutant embryos, e.g. Fig. 1B (red-dextran, left part of the tracheal lumen shows bulges) and even the Dpy::YFP matrix tear off at the site of bulges (Fig. 4F’’, above the arrowhead). But we did not know at the time the link with Pio and Dumpy

However, we agree, it is important to know more about the appearance of the phenotype by means of quantifications. The quantifications of bulges per dorsal trunk (n=16) is shown in Fig. 7B.

7.) Minor point: I don't understand what the authors are trying to show in supplementary Figure 8. Tracheal cells detach and are found in the lumen?

We are sorry for the unclear description in the legend. We corrected it as follows in the legend of Fig. S12:

“This indicates disintegration of apical cell membrane at bulges and subsequent leaking of cellular content into the lumen.”

8.) Np function conserved matriptase.<br /> In this work, Drees and colleagues showed that Np controls in vivo the cleavage of the Pio ZP domain.<br /> Dumpy and Piopio are not conserved in vertebrates but they both contain a ZP domain which is conserved. The authors tested if other ZP proteins can be cleaved by Np or the human homolog Matriptase. The authors tested in cell culture the ability of the type III Transforming growth factor-β receptor which contains a ZP domain to be cleaved either by Np or Matriptase.<br /> This could be a general mechanism that needs to be extended to other ZP domain proteins and that could be at play to structure the matrix and give it its physical properties.<br /> However, as it is all speculative, I find the discussion section related to these data, for too long and that does not help to understand better the work done in the formation of the tracheal tubes of the drosophila embryo.

We show that Np mediates cleavage of the Pio ZP domain in vitro and in vivo in Drosophila embryos. We further showed that also the human matriptase was able to cleave the Pio ZP domain. To understand if this is a more general mechanism, we extended our studies with the human TβIII and its ZP domain. These data show that both Drosophila and human matriptases are able to cleave ZP domains of different proteins from different species. These data suggest that Matriptase-mediated ZP domain cleavage is not a Drosophila specific mechanism. We cannot follow the argumentation of the referee to state it all speculative. Nevertheless, we agree that it will need follow up studies to show that the mechanism is more general than two different species and ZP domain proteins. Anyway, as requested by the referee, we deleted the following sentences of the paragraph, since they are speculative in the context of our manuscript and do not directly describe a potential matriptase and ZP domain function:

“Matriptase degrades receptors and ECM in pulmonary fibrinogenesis in squamous cell carcinoma (Bardou et al., 2016; Martin and List, 2019). TβRIII is a membrane-bound proteoglycan that generates a soluble form upon shedding (López-Casillas et al., 1991), a potent neutralizing agent of TGF-β. Expression of the soluble TβRIII inhibits tumor growth due to the inhibition of angiogenesis (Bandyopadhyay et al., 2002). Idiopathic pulmonary fibrosis (IPF) is associated with a progressive loss of lung function due to fibroblast accumulation and relentless ECM deposition (King et al., 2011; Loomis-King et al., 2013). “

However, the comparisons of the tubular organ and the phenotypic expressions of the bulging membrane and the aortic aneurysm appear to us as an important element of the article. In both cases, cell membrane loses its integrity and can break in tubular networks. Thus, with our findings on the modification of extracellular ZP proteins, we offer a potential new molecular approach even for clinical investigation.

9.) Minor points: Pio and cytoskeleton organisation.<br /> Line 78-79, the authors wrongly quoted a work from Brodu et al (2010). Pio does not anchor the microtubule severing enzyme Spastin. Instead, Spastin releases the microtubule-organising centre from its centrosomal location, then Pio contributes to its apical membrane anchoring. It can therefore be assumed that the organisation of the microtubule network is affected in a pio null mutant. In addition, ZP proteins have been shown to link the aECM to the actin cytoskeleton. Therefore, it would be interesting to look at the organisation of the actin and microtubule cytoskeletons in a pio mutant context in which enlarged apical cell surface area are observed.

We are very thankful for finding this mistake in the introduction. We corrected it as follows:

“Further, Pio is involved in relocating microtubule organizing center components γ-TuRC (γ-tubulin and Grips; gamma-tubulin ring proteins). This requires Spastin-mediated release from the centrosome and Pio-mediated γ-TuRC anchoring in the apical membrane.”

Studying cytoskeleton in pio mutant embryos is a helpful idea. Therefore, we analyzed F-actin with Phalloidin and beta tubulin (E7 antibody, DSHB) in the dorsal trunk cells of stage 16 control and pio mutant embryos. However, tracheal cells are tiny and only gross changes can be realized. The confocal Z-stack analysis of the stainings did not show gross differences between control and pio mutant embryos. We observe the expected apical subcortical accumulation for the actin and tubulin cytoskeleton in dorsal trunk cells of pio stage 16 mutant embryos which also has been shown for wt embryos elsewhere. These new data are presented in the supplement Fig. S7.

_Referees cross-commenting

I have just read the comments of the other two reviewers, who like me are specialists in the formation of the tracheal system in the drosophila embryo.<br /> I find the comments very fair and balanced. They are in the same spirit as my comments and are very complementary. I hope that all our comments will be constructive for the authors and will improve the quality of their work._

Reviewer #3 (Significance):

_Overall, the methodology is sound, the quality of the data is good and the paper is very well written. Authors combine in vivo, in vitro studies as well a cell culture approach. Using CRISPR/Cas9, they generated a large number of new tools allowing in vivo studies.<br /> Drees and colleagues generated new alleles of pio which are lack of function alleles. They described a new phenotype for pio mutant embryos, namely over-elongated tubes. But they authors do not comment on why these new alleles reveal a new phenotype. Furthermore, using their piomCherry::pio line, the authors state that Pio is localised to the plasma membrane. This location is very difficult to assess. Both new results require clarification.<br /> The authors had already demonstrated that Np cleaves the ZP domain of Pio in vitro. Here they demonstrate this in vivo. It appears important to evaluate the formation of the dorsal tube when an NP non-cleavable form of Pio is expressed.<br /> Finally, the model proposing a coupling between the extracellular matrix and the membrane of tracheal cells is very interesting. The demonstration that cleavage of Pio by Np could participate in this coupling is very interesting for those interested in the integration of mechanical stress and cellular deformation. However, such a model has already been discussed in Dong et al (2014). In this article, Dong et al. proposed that a "coupling of the apical membrane and Dpy matrix core is essential for tube length regulation".

The audience for this article should be specialised and oriented towards basic research. It may be of interest to people working on tubular systems or working on ZP proteins.

My field of expertise is cell biology and developmental biology in drosophila and formation of tubular networks._

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Referee #3

Evidence, reproducibility and clarity

Summary

In this manuscript, Drees and colleagues analysed, during the formation and growth of tubular systems, how cells combine forces at the cell membranes while maintaining tubular network integrity. A fundamental question is to understand how cells manage to integrate the axial forces to stabilise the cell membrane and the apical extracellular matrix (aECM).<br /> To address this question, the authors study the formation of the tracheal system in Drosophila embryos, a well-established and detailed model system to investigate formation of tubular networks. In particular, they focused on the formation of the larger tube of the tracheal network, the dorsal trunk. The formation of this tube depends in part of axial extension along the antero-posterior axis.<br /> They concentrated their work on the function of Piopio (Pio), a Zona-Pellucida (ZP)-domain protein. They showed that Pio together with the protease Notopleural (Np) contribute the sense and support mechanical stresses when tracheal tubes elongate, thus ensuring normal membrane -aECM morphology.

Major Comments

In a previous work, Drees et al. (PLOS Genetics 2019), showed the matriptase-prostasin proteolytic cascade (MPPC), is conserved and essential for both Drosophila ECM morphogenesis and physiology.<br /> The functionally conserved components of the MPPC mediate cleavage of zona pellucida-domain (ZP-domain) proteins, which play crucial roles in organizing apical structures of the ECM in both vertebrates and invertebrates. They showed that ZP-proteins are molecular targets of the conserved MPPC and that cleavage within the ZP-domains is a conserved mechanism of ECM development and differentiation.<br /> Here, Drees et al. investigate further how the coupling between membrane and matrix takes place to ensure proper tube growth.<br /> Pio distribution and phenotypes<br /> They first focused on the tracheal phenotypes observed in a pio null mutant context. So far, the only pio mutant characterised was a point mutation in the ZP domain. Using CRISPR/Cas9, they generated new alleles of pio which are lack of function alleles. In the context, Drees and colleagues observed over-elongated dorsal trunk tubes, with bulges appearing at stage 16 between the apical domain of tracheal cells and adjacent extra-luminal matrix.<br /> Additionally, pio mutant embryos showed impaired tube lumen clearance of the some of the aECM components, which prevent gas-filling of the airways.<br /> To detect Pio distribution, the authors used either anti-Pio antibody directed toward a short stretch with the Pio ZP domain or generated a CRISPR/Cas9 piomCherry::pio line.<br /> The Pio antibody shows a strong luminal staining as already published. But the authors reported an apical membrane signal in tracheal cells. I find this apical membrane signal really difficult to observe in panel Fig. 2B. The overlap between the Pio dots and the apical membrane labelled with Uif showed in Fig 2C can be due to the 3D projection. It is only when endocytosis is unpaired (Suppl Fig. 2), that data are more convincing.<br /> When the author used their CRISPR/Cas9 piomCherry::pio line to characterise Pio distribution (Fig.4), Pio is localised at the apical plasma membrane before stage 16. Only at stage 16, Pio is detected within the lumen.<br /> This timing of Pio release in the lumen is critical for the model proposed by Drees at al. This is an important point to assess the difference between the use of the antibody (which mostly label the lumen) while piomCherry::pio line is mostly at the membrane.<br /> Another important point is to explain the discrepancy between the pio mutant alleles. The allele containing a point mutation in the ZP domain shows no over-elongated tubes (Dong et al 2014, Jazwinska et al. 2003) while the lack of function alleles does.<br /> A minor point, the author should provide hypothesis to explain why only the clearance of CBP, Obstructor-A and Knickkopf are affected in a pio mutant background and not Serpentine and Vermiform.

Pio and Dumpy<br /> Dumpy (Dpy) is another ZP domain protein secreted by the tracheal cells and detected in the lumen. To follow Dpy distribution, Drees and colleagues used a Dpy::eYFP protein trap line, the same used in Dong et al. However, in this latter paper, Dong et al. stated, using a Crb staining, that Dpy is not at the apical cell surface but only in the lumen. However, Drees and colleagues reported (line 227 and Fig. 4C) that Dpy appears both at the apical cell surface and in the lumen of the tracheal system. But they did not show a co-localisation with an apical marker. Furthermore, in their previous work, (Drees et al. 2019) they called the apical staining a "peripheral shell" layer. In addition, in S2R+ cell culture, it is only when Pio and Dpy co-express that Dpy is detected at the cell membrane. The in vivo localisation of Dpy is an important point that needs to be clarified as it is of importance for the final model proposed Supp Fig. 9.<br /> Drees at al. also performed FRAP experiments on Dpy::eYFP protein trap embryos. As excepted as already shown by Dong et al.<br /> A minor point, the Dpy::eYFP protein trap line used in this study is not listed in the Materials and Methods section of the supplementary data.

The serine protease NP and Pio release.<br /> Drees and colleagues have pervious shown, preforming in vitro studies, that protease Notopleural (Np) cleaves the Pio ZP domain (Drees at al. 2019). Here the authors went a step further in demonstrating that it is also true in vivo at stage 17. In addition, they showed that, in Np mutant embryos, mCherry::Pio is mostly detected within tracheal cells and the luminal staining is strongly reduced. In this mutant context, the authors conducted FRAP experiment on the mCherry::Pio signal even very weak in the lumen. They showed hardly no recovery after photobleaching.<br /> In Drosophila S2 cells, Drees and colleagues showed that co-expression of the catalytically inactive NpS990A with mCherry::Pio in showed as a prominent signal the 90kDa mCherry::Pio variant in the cell lysate (Fig. 5B), and live imaging revealed mCherry::Pio localisation at the cell surface (Fig. S6B). However, in this inactive form context, a strong signal is also detected at 60kDA corresponding to a cleaved form of the Pio ZP domain (Fig. 5B), and Pio localisation at the cell surface appears weaker than in controls. They authors did not consider that another protease could be at play.<br /> On the other hand, in their previous work, Drees et al. identified a mutant form of Pio (PioR196A) which is resistant to NP cleavage in vitro. It will be a step forward to establish by CRISPR/cas9, as the authors seems to be successful with this technique, a mutant line carrying this point mutation. It will be important to determine whether the observed phenotype resembles that of a mutant Np phenotype.<br /> In their previous work (PLOS Genetics 2019), in Np mutant embryos, Drees et al. did not report "budge-like" deformations from stage 16 onwards leading to the detachment of the tracheal cell from their adjacent aECM. Either the alleles or the allelic combination is different between the two studies which could explain this difference, or it is a new phenotype that has not been previously described. In the latter case, it becomes important to quantify the proportion of segments showing these bubbles. Is this a rare phenotype to observe?<br /> Minor point: I don't understand what the authors are trying to show in supplementary Figure 8. Tracheal cells detach and are found in the lumen?

Np function conserved matriptase.<br /> In this work, Drees and colleagues showed that Np controls in vivo the cleavage of the Pio ZP domain.<br /> Dumpy and Piopio are not conserved in vertebrates but they both contain a ZP domain which is conserved. The authors tested if other ZP proteins can be cleaved by Np or the human homolog Matriptase. The authors tested in cell culture the ability of the type III Transforming growth factor-β receptor which contains a ZP domain to be cleaved either by Np or Matriptase.<br /> This could be a general mechanism that needs to be extended to other ZP domain proteins and that could be at play to structure the matrix and give it its physical properties.<br /> However, as it is all speculative, I find the discussion section related to these data, for too long and that does not help to understand better the work done in the formation of the tracheal tubes of the drosophila embryo.

Minor points: Pio and cytoskeleton organisation.<br /> Line 78-79, the authors wrongly quoted a work from Brodu et al (2010). Pio does not anchor the microtubule severing enzyme Spastin. Instead, Spastin releases the microtubule-organising centre from its centrosomal location, then Pio contributes to its apical membrane anchoring. It can therefore be assumed that the organisation of the microtubule network is affected in a pio null mutant. In addition, ZP proteins have been shown to link the aECM to the actin cytoskeleton. Therefore, it would be interesting to look at the organisation of the actin and microtubule cytoskeletons in a pio mutant context in which enlarged apical cell surface area are observed.

Referees cross-commenting

I have just read the comments of the other two reviewers, who like me are specialists in the formation of the tracheal system in the drosophila embryo.<br /> I find the comments very fair and balanced. They are in the same spirit as my comments and are very complementary. I hope that all our comments will be constructive for the authors and will improve the quality of their work.

Significance

Overall, the methodology is sound, the quality of the data is good and the paper is very well written. Authors combine in vivo, in vitro studies as well a cell culture approach. Using CRISPR/Cas9, they generated a large number of new tools allowing in vivo studies.<br /> Drees and colleagues generated new alleles of pio which are lack of function alleles. They described a new phenotype for pio mutant embryos, namely over-elongated tubes. But they authors do not comment on why these new alleles reveal a new phenotype. Furthermore, using their piomCherry::pio line, the authors state that Pio is localised to the plasma membrane. This location is very difficult to assess. Both new results require clarification.

The authors had already demonstrated that Np cleaves the ZP domain of Pio in vitro. Here they demonstrate this in vivo. It appears important to evaluate the formation of the dorsal tube when an NP non-cleavable form of Pio is expressed.

Finally, the model proposing a coupling between the extracellular matrix and the membrane of tracheal cells is very interesting. The demonstration that cleavage of Pio by Np could participate in this coupling is very interesting for those interested in the integration of mechanical stress and cellular deformation. However, such a model has already been discussed in Dong et al (2014). In this article, Dong et al. proposed that a "coupling of the apical membrane and Dpy matrix core is essential for tube length regulation".

The audience for this article should be specialised and oriented towards basic research. It may be of interest to people working on tubular systems or working on ZP proteins.

My field of expertise is cell biology and developmental biology in drosophila and formation of tubular networks.

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 provides valuable evidence showing a role for ZP proteins Piopio (Pio) and Dumpy (Dpy) during tracheal tube maturation. Following up on previous studies from the same group (Drees, et al, PLOS Genetics, 2019), the authors show that Piopio localization and function is regulated by the protease Notopleural (Np). Failure in this process leads to defects in trachea tubular defects.<br /> Overall, this work reinforces the previously known importance of the protein Pio in tracheal morphogenesis, specifically in tube expansion, and provides new mechanistic insight on how Pio is regulated by proteolysis during this process.<br /> The figures are clear, and the questions well addressed. However, I find that some of the claims are not completely backed by the data presented and have some suggestions that will hopefully make some points clearer.

Major comments

In the abstract and at the end of the introduction the authors claim that they show that Pio, Dpy and Np support the balancing of mechanical stresses during tracheal tube elongation. However, this is not shown in this manuscript, where tension or mechanical stress were not measured and it is therefore speculative.

The authors state that all pio CRISPR/Cas9 generated mutants display identical tracheal phenotypes, however these data are not shown. Tracheal phenotypes, in particular DT phenotypes, of all mutants generated should be shown in supplementary materials.

At stage 16, pio null mutants display DT overelongation phenotypes (Fig. 1). The authors should quantify this phenotype.

The authors analyse Pio distribution under tubular stress, using mega mutants and Chitinase overexpression. Pio localization changes in these genetic backgrounds and this is shown in Figure 2 only in a qualitative manner. The authors should measure Pio localization at the lumen and at the membrane and provide quantitative data.

Surprisingly and interestingly, wurst;pio transheterozygotes display very strong tracheal defects. The authors say they observe gas filling defects; however it is not clear from figure 2E if this indeed the case. From the panel in the figure, it looks like these embryos suffer from strong tracheal morphogenetic defects. It would be necessary to have a better analysis of these embryos. What is the penetrance of this phenotype. If this is 100% penetrant, one would expect it to be lethal. Therefore, double mutant balanced stocks are not viable? Having analyzed the phenotypes and confirmed which morphogenetic defects the transheterozygote embryos present, how does this genetic interaction fit with the model presented?

mCherry::Pio Dpy::eYFP time lapse analysis and FRAP experiments is very interesting. However, it is not clear to which degree bleaching occurs in the tracheal lumen. The authors claim that recovery is very fast and can be seen from minute 2, however, frame-by-frame analysis of Movie S2 does not show a clear different between luminal Pio from minute 0 to minute 2. Rough comparison with the luminal area surrounding the bleached area, does not show a clear difference in luminal Pio before and after photobleaching. To claim fast recovery of luminal Pio after photobleaching, the authors should quantify luminal Pio, before and after bleaching. In addition, in figure 4D, the normalized mCherry::Pio fluorescence in the graph what does it refer to? Intracellular Pio?

When mCherry::Pio Dpy::eYFP time lapse analysis and FRAP experiments was done in an Np mutant background, the authors describe lack of Pio recovery within the lumen (Movie S3). However, when comparing control and Np mutant background embryos, Pio is not properly released into the lumen of Np mutants (as stated by the authors and seen by comparing movies S1 and S4). Furthermore, on minute 0 of the FRAP experiment in Np embryos, there is no detectable Pio in the DT lumen. Therefore, recovery was not expected in Np mutants and should not be claimed as a conclusion for this experiment.

Brodu et al (Dev Cell 2010) have shown that Pio is important for cytoskeletal modulation during tracheal maturation. Pio is important for non-centrosomal microtubule (MT) arrays anchored at the tracheal cell apical membranes. In addition, MT disruption in tracheal cells leads to lumen formation defects (Brodu et al, Dev Cell 2010). In the absence of Pio, the tracheal cytoskeleton is altered, and this could explain some of the results observed. Ideally, the work should be complemented with a basic cytoskeletal analysis, but if this is not possible, the authors should discuss some of the phenotypes in light of this Pio function.

Minor comments

The model should not be in supplementary materials and should be moved to the main manuscript.

Throughout the manuscript embryonic stages are described using different nomenclature (stage X, stX and st X). Either way is correct, but the same nomenclature should be used throughout.

In Fig. S1 B and C the authors should specify which pio allele is being analysed (as in Fig. 7). The same should be done in the text.

Line 131, it is not correct to say that WGA visualizes cell membranes. WGA marks/stains cell membranes.

Line 165 "leads to excessive tube dilation and length expansion due to strongly reduced luminal chitin" is not correct. Chitin reduction leads to excessive tube dilation but not to length expansion, as reported in the papers cited at the end of the sentence.

Line 220-221, what do authors refer to as "stage 16 wt-like control embryos"?

Line 221, "some minutes" should be replaced by a specific number of minutes. According to Movie S2 reappearance of tracheal cell Pio happens from minute 16.

Line 291 "time laps" should be lapse.

Line 302, "Pio was not shedded into the lumen but remained at the cell" should be "Pio was not shed into the lumen but remained in the cell".

Referees cross-commenting

I agree. Taken together, all the comments will improve the quality of the work and of a future manuscript. Also, everything seems quite doable and will not present any problems.

Significance

The findings shown in this manuscript shed light on the regulation of tubulogenesis by ZP proteins and how their interaction with the ECM can be regulated by proteolysis. It was known that Pio is involved in tracheal development, is secreted into the lumen, regulating tube elongation (Jaźwińska et al., Nat.Cell Biol., 2003) and anchoring MTs to the apical membrane during tubulogenesis (Brodu et al, Dev. Cell 2010). This work provides additional molecular insights into Pio dynamics and regulation during tube maturation.<br /> This work will be of interest to a broad cell and developmental biology community as they provide a mechanistic advance in ZP proteins involved in morphogenesis. It is of specific interest to the specialized field of tubulogenesis and tracheal morphogenesis.

Field of expertise:

Drosophila, morphogenesis, tracheal tubulogenesis, cytoskeleton

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Referee #1

Evidence, reproducibility and clarity

In the manuscript entitled "The proteolysis of ZP proteins is essential to control cell membrane structure and integrity of developing tubes" the authors Leonard Drees, Dietmar Riedel, Reinhard Schuh and Matthias Behr report on their study on the molecular and cellular mechanisms of tracheal tube size determination in the embryo of the fruity fly Drosophila melanogaster. The tracheal tubes of D. melanogaster are a model tissue to understand the molecular and cellular mechanisms of tube formation in animals. In brief, morphogenesis and terminal differentiation of this epithelial tissue runs through several overlapping events starting with the invagination of tracheal precursor cells, their fusion to tubes, the formation of a luminal matrix consisting of chitin and associated proteins for diameter and length determination, endocytosis of luminal material and gas filling at the end. L. Dress and colleagues show that the ZP protein Piopio (Pio), its partner Dumpy (Dp, also a ZP protein) and the Matriptase homolog Notopleural (Np) are needed for tube length determination. Pio with Dp constitutes a molecular anchor between the apical cell membrane and the luminal matrix thereby coordinating growth of the epithelial cells and the luminal matrix. After termination of morphogenesis, Pio is cleaved by the protease Np to initiate tracheal differentiation.

Overall, this is an exciting work. There are, however, several open questions that the authors could address to facilitate understanding of their work. These points are:

• On page 5, lines 113ff, the authors mention the membrane bulges that they analyse in figure 1. They show these deformations by light (confocal) and electron microscopy. However, the bulges seen by confocal microscopy seem to be bigger that those seen by electron microscopy. The authors could quantify the sizes of the bulges for clarification.
• The subject of the manuscript is rather complicated; presentation of data from Figure 1C and D on lines 113ff and 169ff is confusing.
• The quality of the sub-images of Figure 2E differs. Especially, the phenotype of the wurst, pio transheterozygous embryo is not well visible.
• Lines 246ff: the protein size are given for the mCherry:chimeric proteins; an estimate of the native Pio portions should be given.
• In Figure 6A, the appearance of chitin in the wildtype tube is different compared to the Np mutant situation, more filamentous. Can the authors comment on that?
• In the discussion section, I would appreciate if the timing of events was discussed or even shown in a model. The central question is: how are the functions of Pio and Np coordinated in time? As I understand, Np should not cleave Pio before morphogenesis is completed. Is there any example in the literature for how such an interaction could be controlled? The overexpression of Np shows that either the ratio between Np and Pio is important, or the btl promoter expresses Np at the "wrong" time point.
• Also for the discussion: We have two situations where Pio amounts/density are enhanced at the apical plasma membrane. The wurst experiments on lines 136ff show that Pio amount and density depends on endocytosis; is the wurst phenotype (Figure 2), at least partially, due to over-presentation of Pio? Likewise, in Figure 2C, there is more Pio in Cht2 overexpressing tracheae (but there is overall more Pio in these tracheae) - is actually endocytosis reduced in chitin-less luminal matrices? First: does the Pio signal at the apical plasma membrane correspond to membrane-Pio or free-Pio? Second, as in the case of wurst: would more Pio on the membrane (density) affect tracheal dimensions in Cht2 over expressing tracheae? Or are the consequences of Pio accumulation in the apical plasma membrane different in Cht2 and wurst backgrounds? Maybe cleavage of Pio and its endocytosis are dependent on its interaction with the chitin matrix. These questions connect to the question immediately above: how are the functions of the different players coordinated in space and time? We need a discussion on this issue.
• The sentence on line 242ff should be rephrased: "dynamic" and "elastic" are not opposites.
• A central question to me is the amounts and the density of factors in different genetic backgrounds as mentioned above. Is there any mechanism adjusting the amounts or the density of the players according to the size of the apical plasma membrane or the tracheal lumen? Pio seemingly responds to these changes.
• The connection of Pio and taenidia is mentioned in the results section (page 7) but not discussed.
• Dp remains cytoplasmic in pio mutant background - is the pio mutant phenotype due to defects by lack of Pio AND Dp function? What is the tracheal phenotype of dp mutants?
• Lines 374ff: the reduced dorsal trunk in Np mutants is not significant; the respective statement should be formulated carefully. If we believe the statistics (no significance), this would mean that attachment of the apical plasma membrane to the luminal chitin via Pio is needed to restrict axial extension; release of Pio is needed for differentiation (taenidia formation, luminal clearance) beyond morphogenesis.
• Why don't we see the apical Pio signal in Figure 4B?
• The Strep signals in the merges in Figure 7C are not well visible.

Significance

This work brings together several factors (Pio, Dp, Np, Wst etc) already known to be needed for tracheal morphogenesis and differentiation in the embryo of D. melanogaster. Having worked myself with some of these factors, however, I recognize that the interaction between these factors is novel and very exciting. The experiments strongly indicate a new mechanism of cell-ECM connection that seems to be conserved to some extent (as they provide preliminary data on an example from humans). By integrating the functions of different factors, the work provides ample opportunity for future projects to elucidate this mechanism in detail. Therefore, I expect that it will have a significant impact not only on the field of developmental cell biology but also, due to the conserved proteins involved (ZP proteins, Matriptase), on the field of cell biology of human diseases.

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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 manuscript describes the strategy to efficiently synthesize a natural truncated version of the chemokine CXCL10 that lacks the last 4 amminoacids. In addition, it describes the biological activities of the CXCL10 truncated version (1-73) compared to the full length chemokine (1-77). By performing in vitro and in vivo experiments, authors have found that CXCl10 1-73 is not able to induce signalling and chemotaxis of CXCR3 expressing cells such as T lymphocytes. In addition, this C terminal truncated version does not bind GAGs while retains angiostatic activity, blocking migration and proliferation of endothelial cells.<br /> The paper is written very well, results are presented in a very logical sequence.

Major comment

The in vivo experiments shown in supplementary figures 7 and 8 are not significant and I suggest removing them from the manuscript.

Minor comment

In figure 9D authors showed the in vivo migration of CXCR3 positive T lymphocytes in the peritoneal cavity. However, the gating strategy showed in supplementary figure 6 is showing all the leukocytes CXCR3 positive. Please clarify.

Significance

The manuscript describes the biological activity of a truncated version of CXCL10 a very important chemokine that recruit Th1 lymphocytes and NK cells. The C terminal truncated version of CXCL10 is naturally occurring, but its functions were never described until now.

The strength of the manuscript is the precise description of the synthesis and of the in vitro biological functions of the truncated CXCL10.

For this reason, these results are of interest not only for a specialized audience working in the chemokine field, but also for a more broad audience for the development of an inhibitor of CXCR3 or for an angiostatic molecule.

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Referee #2

Evidence, reproducibility and clarity

Summary:

It has been reported that CXCL10 has several truncated forms (proteoforms) with different C-terminal truncation states, each with different functions. The authors have discovered and reported an efficient peptide synthesis method for CXCL10(a.a. 1-73) proteoform. The authors indicated that they could synthesize CXCL10(a.a. 1-73) proteoform consistent with the known functions of natural CXCL10(a.a. 1-73). The synthesized CXCL10(a.a. 1-73) successfully indicated the reduced effects on lymphocyte migration and similar effects on angiogenesis. These findings open the way for detailed functional analysis of CXCL10 (a.a. 1-73), which has been difficult to study in vivo and has potential for therapeutic use. However, as discussed below, the authors have made several statements that confuse their findings with the discoveries made by previous studies. The Introduction is a typical example of this. Also, there are several major issues noted in the next section.

Major comments:

1. Figure 4: Possibly an overinterpretation of results in CXCR3A overexpressing model cells<br /> The authors build their logic for the entire paper by drawing conclusions based on their assumption that CXCR3A overexpression model is equivalent to physiological lymphocytes and endothelial cells. However, CXCR3 has isoforms, including CXCR3A/B/alternative. They have different effects on cell proliferation and migration. Expression levels of CXCR3A/3B may vary among cell types and microenvironments. In addition, the downstream signals pAKT and pERK of CXCR3A/B are regulated by various regulatory factors. Therefore, it is important to perform the experiments shown in Figure 4 with primary lymphocytes and vascular endothelial cells, which are the subject of this paper. Based on the data presented by the authors, experiments with Primary lymphocytes and Endothelial cells would not be difficult.
2. Figure 5: "In line with the observation of the signaling assays, COOH-terminal processing of CXCL10 also significantly diminishes its chemotactic properties on primary CXCR3+ T lymphocytes."<br /> The authors draw the conclusions described above from the results in Figure 4 and Figure 5. In other words, authors excluded other possibilities without data.<br /> In Figure 5, the Chemotaxis assay was performed in Transwells with 5 miro-meter pores pre-coated with fibronectin. CXCL10 is also known to interact with fibronectin. This suggests that, potentially, the interaction with fibronectin may be important for CXCL10 gradient formation on the transwell. However, interaction data between CXCL10(a.a. 1-73) proteoform and fibronectin is not shown. This information is essential in the interpretation of Figure 5 results.<br /> The authors should consider the possibility that readers unfamiliar with this experimental system may be given a false understanding that Chemotaxis shown here is determined solely via CXCR3A.<br /> Also, please indicate whether the conclusions here are supported in different Pre-coating (e.g. type I collagen, type 4 collagen, human fibronectin). How the activation changes with each Coating here is important information when considering how CXCL10(a.a. 1-73) behaves in the extracellular matrix in vivo. These add to the value of this study and provide important insights for readers to further work with CXCL10(a.a. 1-73).<br /> Furthermore, the Migration chamber here is pre-coated with bovine serum fibronectin. Please provide Lot and purity information for this Serum derived fibronectin. This is considered important both for the reader to reproduce the data and to interpret the results. Since Bovine serum fibronectin is a different species than human CXCL10 (a.a. 1-73), in order to correctly interpret its contribution to the Chemotaxis assay, it is interactions, respectively, should be evaluated.
3. Figure 6: Over-interpretation of the results<br /> From Figure 6, the authors conclude that CXCL10 (a.a. 1-73) has no change in antiangiogenic action based on data on vascular endothelial cell migration and viability. Cell migration and endothelial cell viability are only one aspect of angiogenesis. It is problematic to conclude from these results that there is no change in "antiangiogenic action".<br /> Also, in Figure 6A, the authors cultured cells in the presence of FGF2 and in the presence of CXCL10 (a.a. 1-73) and CXCL10 (a.a. 1-77) for as long as 49 hours to evaluate Migration. Therefore, the results here include not only pure migration but also its effect on proliferation. However, Figures 6C/6D only show data on the viability of cells, not on the effects on cell proliferation. Therefore, in order to correctly interpret the results, the proliferation of vascular endothelial cells needs to be examined and presented.
4. Figure 9 and supplemental Figure S6: Gating for T cells (gated as CD3+ NK1.1-) and activated CXCR3+ T cells (gated as CD3+ NK1.1- CXCR3+)<br /> Supplemental Fig. S6 raises a question as to whether the location of the Gating of CD3 and NK1.1 is correct. Please verify if this gating is proper by presenting Isotype control data as the basis.<br /> Gating for CXCR3 also seems to be gated in an unnatural position. Please present Isotype controls data and positive control data and explain the basis for this gating.

5. Figure 9: Over-interpretation of the results<br /> It would be an oversimplified interpretation of the results here to explain them solely in terms of lymphocyte Migration. The authors should not rule out the possibility that the results obtained here could be due to effects quite different from those shown so far in vitro.<br /> Conclusions should be drawn after examining the following items

6. Expression of lymphocyte adhesion-related molecules on the surface of vascular endothelial cells

7. Effects on Tight junction of blood vessels
8. Effect on vascular permeability

If the above data are not presented, the authors should clearly describe that the author's conclusion is just one of the possibilities. The readers should be informed of the above possibilities, and the different potential mechanisms involved so that the readers do not misunderstand that the authors' conclusions are definitive conclusions.

Minor comments:

Figure 7C: Please provide higher-resolution images

The quality and resolution of the images are low and very difficult to see. The image is of such low quality that it is barely possible to determine the presence or absence of cells. Here, providing higher-resolution images is important to give the reader a deeper understanding. The desired resolution is a resolution that allows determining what the Filopodia and Lamelipodia morphology of the cell looks like at the Edge of the Scratch, and how it differs or does not differ between CXCL10 (1-73) and 1-77, etc., desirable. Such an image could underpin the other data in this paper. Furthermore, such detailed forms can give the reader insights into more precise molecular mechanisms. In this sense, it is essential to provide high-quality images.

Line 360-362, page 12 (Results)

"Various naturally-occurring COOH-terminally truncated CXCL10 proteoforms were detected in human cell-culture supernatant of IFN-γ-stimulated human diploid skin/muscle-derived fibroblasts and primary human keratinocytes and potential processing enzymes were identified (Suppl. fig. 1). "<br /> This statement could be interpreted to mean that what is described in Supplemental figure 1 is identified in this paper. Although it is unlikely that most readers would make such a mistake, unnecessary misleading statements should be avoided.

Line 508-509, page 16 (Discussion)

"In the present study, we characterized the effects of a natural COOH-terminal truncation of CXCL10, which involves the shedding of the four endmost COOH-terminal amino-acids, on hallmark chemokine properties of CXCL10."

The authors state that "we characterized the effects of a natural COOH-terminal truncation of CXCL10," which gives the reader the wrong impression.

"Natural truncation of CXCL10" means physiological CXCL10, which is truncated form that normally occurs in vivo. These findings have been done in prior papers and were not first characterized in this paper. This should be described as a characterization of the synthesized peptide. This sounds like the authors have taken credit for prior studies.

Figure 6A&6B: What is the "HRMVEs" on the Y-axis? Nowhere in the paper is there a description of this term.

Figure 8A&8B: Some error bars are only on one side.

Significance

It has been reported that the functions of CXCL10 change dynamically in tissues depending on the C-terminal truncation state. However, this dynamic nature created a mixture of each Proteoforms (CXCL10 with different terminal truncation states), making the analysis of their functions difficult. CXCL10(a.a.1-73) is not commercially available like CXCL10(a.a.1-77) due to its difficult peptide synthesis; pure functional analysis of CXCL10(a.a.1-73) could not be performed in vivo. Therefore, the functions of CXCL10(a.a. 1-73) has been mainly reported as circumstantial evidence or in vitro studies using trace amounts of purified product purified using HPLC.

In this study, the authors clarify the challenges of peptide synthesis and enable the synthesis of more CXCL10(a.a. 1-73). Thereby paving the way for implementing the function of pure CXCL10(a. 1-73) proteoform not only in vitro but also in vivo. It also potentially opens the door for the application of CXCL10(a.a. 1-73) in therapeutic interventions such as tissue repair.

However, the paper has the problems mentioned above, and it would be desirable to verify and reinforce the reliability and logical development of the conclusions. Reinforcing additional experimental data such as that and validating the derivation of the conclusions would be a study of significance to basic medical researchers in vascular biology, immunology, and tissue repair, as well as to the clinical research community.

General assessment:

Strength:

The authors have discovered and reported a stable method for synthesizing CXCL10 (a.a. 1-73), which has been difficult to synthesize in the past. This may provide researchers a way to solve the problem that it has been difficult to analyze clear molecular mechanisms due to the mixture of diverse CXCL10 proteoforms. The progress reported here may be expected to facilitate other researchers to investigate more detailed molecular mechanisms and explore unknown functions of CXCL10 (a.a. 1-73).

It is also expected to solve the problem of in vivo analysis of CXCL10(a.a. 1-73) function, which has been impossible due to yield issues. In the future, this synthetic peptide may open the door to a variety of useful applications, such as therapeutic intervention for severe wound healing.

Advance:

The authors wrote the "Introduction" and "Abstract" focusing on the functional "discovery" of CXCL10 (a.a. 1-73). This may prevent the readers from understanding the true value of this study. The most significant finding of this study is the technological advance of increasing the yield of CXCL10 (a.a. 1-73), which has been difficult to synthesize to a level that allows in vivo experiments. Although there are many improvements to be made, I believe this is a significant study for the community described above if this synthesized peptide is widely available in the community.

Audience:

The current manuscript is suitable for a Specialized audience. If the issues raised here were solved, it might be suitable for broader audiences, including translational/clinical researchers.

My field of expertise:

Molecular biology, biochemistry, vascular biology, hematology and cancer

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Referee #1

Evidence, reproducibility and clarity

The manuscript by Dillemans et al reports that synthesis, purification and functional characterisation of the truncated CXCL10 proteoform CXCL10(1-73). This lacks the four endmost COOH-terminal amino acids . The authors report that compared to the full length CXCL10(1- 77), CXCL10(1-73) had (i) diminished affinity for glycosaminoglycans, (ii) exhibited reduced capacity to induce signaling events (e.g. calcium mobilization as well as ERK and Akt phosphorylation) and (ii) reduced chemotactic T lymphocyte responses in vitro and in vivo. However, CXCL10(1-73) retained its anti-angiogenic properties, as assessed by inhibition of spontaneous and FGF-2-induced migration, wound healing and sprouting of human microvascular endothelial cells.

The work is well performed though the pharmacological analysis is a little superficial and under-developed with incomplete/inconsistent concentration-dependent responses. The manuscript is rather verbose in places.

Specific points:

1. Fig 4: how do the authors know that the reduced calcium responses to full length CXCL10 following pr-treatment with the C-terminal truncated CXCL(1-73) is due to desensitisation rather than say partial agonism? They should compare internalisation of CXCR3 and/or loss of surface expression of CXCR3 following treatment with CXCL10 (1-73) versus CXCL13(1-77) to validate this.
2. The choice of concentration ranges used for CXCL10(1.77) and CXCL10(1-73) across figs 4, 5 and 6 is inconsistent with no explanation given as to why.
3. Figs 4: The dose response curves are rather limited narrow e.g.1, 3, 10 nM for CXCL10(1-77). The choice of concentrations for CXCL10(1-73) in fig 4 is a little unusual in Fig 4 (9, 45, 270nM). Has the maximum response to CXCL10(1-73) in figs 4-6 been achieved? It would be useful to know the EC50 values for both full length and truncated forms of CXCL10 in figs 4 and 5
4. Fig 5: in contrast, to Fig 4, this figure has comparable concentration ranges at 5 points across (1-100 nM). What is the rationale for the inconsistent concentration ranges used across different assays?
5. The bar graphs for pERK, pAkt responses would look better as line graphs and more complete concentration ranges (perhaps use 5 concentrations e.g. over 1-100 nM for CXCL10(1-77).
6. Fig 6: the inhibitory effects of CXCL10(1-77) and CXCL10( 1-73) seem to occur at a single concentration (120 nM), Can the spontaneous HMVEC migration be further inhibited at higher doses of truncated and full length CXCL10? Both appear to have just reached 50% inhibition at 120 nM.
7. Fig 7. What is the impact of both proteoforms on FGF-stimulated wound healing?
8. Why is it necessary to provide Kd values in the main results text when these are already provided in Table 1. This is just one example of verbosity that that is often present in the manuscript
9. The methods section is also very long.
10. What phosphorylation sites are detected in the ERK1/2 and Akt ELISA assays? The authors should provide more details on this point. The ELISA assays alone does not really provide convincing analysis of phosphorylation and should be backed up with more robust assays to assess ERK and Akt phosphorylation e.g western blots and/or flow cytometry with phospho-specific Abs.

Significance

The study reveals that the COOH-terminal residues of CXCL10 Lys74-Pro77 are important for GAG binding, CXCR3A signaling, T lymphocyte chemotaxis, but dispensable for angiostasis .

Study is of interest to basic researchers in areas of pharmacology, immunology and structural biology with relevance to drug discovery, inflammation and cancer biology.

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Reply to the reviewers

We thank the reviewers for their constructive criticism that helped us to improve the paper. We modified Fig.6I and Fig.7, replaced Fig.8, and added supplementary Figs. 3-5 and supplementary Tables S1-2. The manuscript was extensively re-written. A new paragraph was added in the Discussion section where relative adhesiveness was related to absolute adhesion strength and the cadherin knockdown result to earlier findings.

Reviewer #1 (Evidence, reproducibility and clarity):

Summary: This work examines the relationship between cell-cell contacts and pericellular matrix in Xenopus chordamesoderm, which is a tissue actively involved in convergent extension during gastrulation. By lanthanum staining of pericellular materials, the authors found that different types of pericellular matrix are present in cell-cell contacts in the chordamesoderm, which may mediate cell-cell adhesion. Knockdown of C-cadherin, Syndecan-4, fibronectin, and hyaluronic acid leads to the reduced abundance of cell contacts and cell packing density, but this does not seem to affect convergent extension. Based on these observations, the authors propose a model in which cell-cell contacts involve the interdigitation of distinct pericellular matrix units.<br /> Major points:

1. Knockdown of adhesion molecules separates cells and leads to wide contacts with large interstitial spaces. Data in figure 1 show loosely packed morphant chordamesoderm cells. Intuitively, these should reduce cell-cell adhesion. However, a main conclusion from this manuscript is that reduced abundance of narrower contacts does not decrease adhesiveness. Although depletion of adhesion molecules modifies but not abolishes a contact, non-attached free surfaces increase significantly in morphant cells. It is therefore not easy to understand that how reduced cell contacts have no effect on cell adhesion.

We added a section to the Discussion to address this issue (p.11ff). We show in the Results section (modified Fig.7) that relative adhesiveness is indeed significantly reduced in the morphants (Syn-4 always being the exception) when compared in the contact width range of normal chordamesoderm. However, contact width is strongly increased in the morphants, and adhesiveness increases linearly with width. We argue that these effects compensate for the initial lowering of adhesiveness. In other words, adhesive contacts become shorter (more gap surface) but wider (see Fig.6I), and become the more adhesive the wider they become. As in the original version of this paper, we then propose a model that explains the empirically observed increase of adhesiveness with width. How the abundance of cell-cell contact is reduced is less clear yet. Pericellular matrix deployment and structure is strongly affected by adhesion factor knockdown, and contact types are altered. Some contact types seem to widen but remain adhesive, others become non-adhesive, and still others may disappear without being replaced (see last paragraph of Discussion). To add detail to these notions and clarify this important issue to satisfaction will require future research.

Importantly, the adhesiveness was not experimentally tested.

Due to external circumstances, we were unable to perform additional experiments. However, we used our previously published quantitative data on adhesion in gastrula tissues including the chordamesoderm to interpret our present results for normal and C-cad-depleted chordamesoderm, and to relate relative adhesiveness to absolute adhesion strength, in a new section of the Discussion (p.11ff).

1. It is surprising that reduced cell contacts, at least narrower cell contacts, do not affect convergent extension. Does this mean that active cell behavior changes in the chordamesoderm, which are required for convergent extension, are independent of cell contact types?

We actually claimed that all treatments inhibited convergent extension, except for Syn-4 (Barua et al. 2021, and this manuscript, p.3, Fig.1B,C). Syn-4 knockdown had a dramatic effect on cell contacts, cell density and cell shape but none on convergent extension, at least up to the middle gastrula stage. This is surprising and does not fit easily to current views of cell intercalation during convergent extension, but analysing the underlying cell behaviors is beyond the scope of this article.

1. Although the formation and localization of pericellular materials are differentially affected after knockdown of adhesion molecules, there is no clear evidence showing that different types of pericellular matrix mediate cell-cell adhesion in the chordamesoderm. It is possible that the disrupted distribution of pericellular materials in morphants only represents a secondary consequence of changed cell contacts. This may be supported by the fact that knockdown of adhesion molecules reduces narrow contacts and increases LSM-free gaps.
2. The relationship between contact width spectra and LSM is also very elusive. Again, changes in contact width or abundance and distribution of LSM may be indirectly caused by loss of adhesion molecules. Therefore, although knockdown of adhesion molecules leads to changes of LSM localization, it cannot be concluded that cell-cell contacts in chordamesoderm are mediated different types of pericellular matrix.

We find it difficult to interpret for example Fig.5A-F other than assuming an adhesive role for the pericellular matrix, in this case LSM, in normal and morphant tissue. What else would here hold two cells between two gaps together? The contacts are often much too wide for cadherin-cadherin binding. We indeed believe that changes in contact width or abundance are caused by the loss of adhesion molecules, directly or indirectly. Our LSM images show that remarkably, modified contacts (e.g. Fig.3D,F; Fig.5B,C) are still able to keep cells together over some distance, between interstitial gaps, and our quantitative data indicate similarly that e.g. contact widening is consistent with continued adhesion. However, some of the contacts may become non-adhesive, or be lost without being replaced, increasing non-adhesive gap surface. This is discussed now on p.11, middle paragraph.

1. In contrast to the present observations, works by others using the same morpholinos have shown that Cadherin-dependent cell adhesion, fibronectin-rich extracellular matrix, and Syndecan-4-regulated non-canonical Wnt signaling are required for convergent extension. These discrepancies need to be appropriately addressed.

As mentioned above, we found that all treatments affected convergent extension, as expected from the work of others and our own, except for Syn-4 depletion. We noticed that in the paper by Munoz et al. on Syn-4 overexpression and knockdown, only late gastrula/early neurula stages were evaluated. Syn-4 knockdown produced moderately strong axis defects, perhaps in part related to impaired neural plate closure. Unfortunately, we did not follow our morphants to these later stages to see whether defects developed then. But our main interest here is cell-cell contacts.

1. If LSM and LSM-free contacts are similarly adhesive, what will be role of LSM in cell adhesion and how cell adhesion is established in these LSM-free contacts?

We discuss now more explicitly the notion that gastrula non-epithelial cell adhesion is mediated by a mosaic of pericellular matrix patches of different composition, some containing LSM in different configurations, others not, but each similarly adhesive.

Minor points:<br /> 1. It may be helpful to clearly define the pericellular matrix in this particular context and its relationship with LSM. It is also necessary to clarify whether the adhesion molecules examined in this work are considered as components of the pericellular matrix.

We explain the use of these terms at the end of the first paragraph of the Introduction. The most general term is pericellular matrix; part of it is La3+ labeled – LSM; and some of the LSM can be compared to structures which in other systems are termed glycocalyx. We consider the adhesion molecules examined to be part of the pericellular matrix but are aware of other putative functions, like in cell signaling, which may indirectly affect contacts and thus contribute nevertheless to the phenomena studied here.

1. In figure 1B, it appears that the Cadherin morphant has defects in chordamesoderm elongation and archenteron formation, suggesting impaired convergent extension.

We find, in agreement with the work of others, that C-cad knockdown impairs convergent extension, and mention this when we describe Fig.1B.

1. In figure 1C, the Syndecan-4 morphant gastrula clearly shows enhanced anteroposterior elongation of chordamesoderm and archenteron in comparison with the wild-type embryo. This seems to suggest that loss of Syndecan-4 promotes the movements of convergent extension. However, previous studies indicate that both gain and loss of Syndecan-4 impairs convergent extension.

As mentioned above, late gastrula/early neurula stages were evaluated in the Munoz et al. paper, mid-gastrula stages in our work. One possible explanation would be that mild axis defects develop later, partly in connection with neural tube elongation and closure.

1. Ideally, in knockdown experiments, control embryos should be injected with corresponding mismatch morpholinos.

We explain in the Methods section that we only used morpholinos that were extensively characterized in previous publications.

1. In figure 1E, it is unclear what type of cell contacts the light green arrowheads indicate.

This is explained now in the figure legend.

1. Figure 1 legend, "(wt) is from Barua et al. 2021". I am not sure it is appropriate to use previously published data.

The present data were derived by further evaluations of the same samples and TEM sections as used in Barua et al. 2021. We show the previously published data (acknowledged in the legends) here for easy comparison (instead of citing the previous paper).

1. There is no light blue arrowhead in figure 2, and in figure 3B and 3I, it seems that the same colored arrows are used to indicate different structures.

This has been corrected.

1. Triple-layered contacts are not clearly defined.

We define this term now repeatedly, as consisting of two LSM layers enclosing a non-labeled layer between them.

1. Page 2, "based on driven by" should be either "based on" or "driven by".

Has been corrected.

1. Page 8, "selectin" should be "selecting".

Has been corrected.

Reviewer #1 (Significance):

Strengths:<br /> Demonstrated the effects of several adhesion molecules on the formation of cell contacts and pericellular matrix in Xenopus chordamesoderm.<br /> Limitations:<br /> The significance of chordamesoderm cell contact changes in convergent extension or gastrulation is not clear;

Effects on gastrulation of PCM or membrane adhesion molecule depletion have very often been described as mediated by effects on cell signaling. Without excluding such possibilities, we liked to redirect attention here to other putative mechanisms by describing basic effects of treatments on cell-cell contacts including PCM deployment and structure. Future work must relate the specific, often dramatic, contact changes upon depletion of a specific factor to cell behavior during convergent extension and other tissue movements.

there is no direct evidence showing the functional link between pericellular matrix, cell contacts and cell adhesion;

Please see our response to main points 3 and 4 above.

the absence of effects on convergent extension after depletion of several adhesion molecules is not fully consistent with previous reports.

Please see our response to main points 2 and 5 and minor point 3 above.

Advance: This work likely provides some fundamental and methodological advances for studying cell-cell adhesion. It shows promise for elucidating mechanisms underlying the regulation of cell contact changes in tissues involved in morphogenetic movements.<br /> Audience:<br /> This work likely interests readership studying embryonic cell adhesion in the field of developmental biology and cell biology. It may be also potentially interesting for people working on glycocalyx pericellular matrix in adult tissues.

Reviewer #2 (Evidence, reproducibility and clarity):

Summary: During gastrulation, cells within vertebrate embryos require the ability to both adhere to one another and rearrange with their neighbors to shape the emerging body plan. These authors posit that such flexible adhesive contacts are mediated in part by the pericellular matrix (PCM), including multiple types of glycocalyces containing molecules such as fibronectin, hyaluronic acid, and syndecans, which they previously characterized in multiple embryonic tissues (Barua et al, PNAS, 2021). Here, in a follow-up to their 2021 study, the authors use electron microscopy to characterize the pericellular matrix within the chordamesoderm of Xenopus gastrulae. They identify several types of adhesive contacts within the chordamesoderm and assess how they are altered in the absence of key PCM molecules via morpholino knock-down. They conclude that syndecan-4 and hyaluronic acid comprise and promote assembly of PCM plaques whereas fibronectin and C-cadherin anchor them to cell surfaces. Cell packing density is decreased upon loss of all 4 of these molecules, which the authors attribute to a decrease in the number of cell contacts without affecting the strength of the remaining contacts. They further conclude that adhesiveness increases linearly with contact width, and that this relationship is unaffected by loss of any aforementioned adhesive/ PCM molecules.

Major comments:<br /> Many conclusions in this manuscript are based on measurements of cell contact angles, which indicate the reduction of tension at cell contacts vs. free cell surfaces and thus relative adhesive strength. While this lab previously applied the same approach to live tissues (David et al, 2014), it is not clear to what extent such measurements accurately reflect adhesive strength in fixed tissues and/or electron micrographs. Especially given the issue of random sectioning planes, which cause distortion of contact angles. Although a correction was applied, the authors note this is not theoretically derived because the heterogeneity of gap sizes made such calculations too difficult. Indeed, it appears that the large gaps between cells within morphant embryos affect contact angle measurements, but if this is corrected for in any way, it is not mentioned.

Geometrically determined contact angle distortion should affect angle or relative adhesiveness distributions in all conditions or treatments similarly and thus should not or only little affect comparisons of distribution peaks, averages, etc. Beyond this effect of random sectioning planes, we don’t see how large contact width should by itself affect measurements of angles.

Because this is the sole measure of cell adhesion provided in the study, this reviewer is not convinced of the conclusion that loss of PCM components does not affect adhesive strength.

In response to this criticism, we re-evaluated our adhesiveness-width data (Fig.7A-E). We noticed that there is indeed a reduction of relative adhesiveness when morphants are compared to normal chordamesoderm within the width range of the latter. But the addition of increased widths in the morphants and the linear increase of adhesiveness with width compensated or overcompensated the initial reduction of adhesiveness.

Could such measurements not be made from live cells/tissues after manipulating PCM components, as the lab has done previously? Because the lab already has the necessary reagents and expertise for such experiments, the time and resources needed for such measurements shouldn't be prohibitive.

Due to circumstances, we were unable to perform additional experiments. However, we used our previously published quantitative data on adhesion in gastrula tissues including the chordamesoderm to analyze our present results for normal and C-cad-depleted chordamesoderm, and to relate relative adhesiveness to absolute adhesion strength, in a section added to the Discussion (p.11ff).

• As mentioned above, these authors previously measured adhesive strength in live Xenopus cells and tissues (David et al, 2014). In that study, they found that C-cadherin MO reduced relative adhesiveness whereas the current study found that relative adhesiveness actually increases in this condition. What explains this discrepancy?

We explain now in the new Discussion section (p.11ff) and with the help of supplementary Figure S5 how adhesion strength and relative adhesiveness are related overall (tissue surface vs. cell contacts) and at gaps within a tissue (gap free cell surface vs. cell contacts). In the previous study (David et al, 2014), we discussed relative adhesiveness in relation to overall adhesion strength, and both are decreased upon C-cad knockdown. Here we examined these parameters at interstitial gaps, where we find a small increase of relative adhesiveness, due to overcompensation caused by a strong increase of adhesiveness with contact width. Using our David et al, 2014 data we quantitated the effects. We previously found a similar increase of relative adhesiveness at gaps in C-cad morphant ectoderm (Barua et al. 2017) which we could not explain at the time, but explain now by analogy to our chordamesoderm results.

• No control morpholinos are used, and for the morpholinos that are used, the doses are very large. An equally high dose of control MO should be used to ensure that all observed phenotypes are specific.

We detail in the Methods section that we used here and in previous publications only previously characterized morpholinos.

• It appears that all the images analyzed were collected in the sagittal plane, and the analyses don't seem to consider the intrinsic polarity of the chordamesoderm. For example: cells in different positions within the tissue (basal vs. apical), or that WT chordamesoderm cells are mediolaterally polarized and actively intercalating whereas disruption of PCM components like fibronectin disrupts cell intercalation and randomizes cell polarity. It is possible that 1) cell-matrix (in basal cells) and 2) cell-cell (during intercalation) interactions may affect the measurements made in this study. In other words, that cell contacts could differ by position within the embryo and intercalation/polarity status... have such effects been accounted for in the current analysis?

Here we only analyzed cell contacts deep in the chordamesoderm. Basal contacts were examined to some extent in Barua and Winklbauer, 2022, apical contacts not yet. Our present analysis is based on sagittal sections. The cells in the chordamesoderm are elongated and aligned mediolaterally but not in register, i.e. they are randomly wedged between each other. Thus, all mediolateral positions in cells should be present in our samples. Nevertheless, trends in the occurrence of contacts related to medial-to-lateral positions on cells (e.g. recognizable in spindle-shaped cells as wide vs narrow cell cross-sections) may have escaped our attention, and in particular, the protrusion-bearing medial and lateral ends of cells may develop special contacts. However, our goal in this study was to analyse basic properties of cell-cell contacts in this tissue, as a foundation for further detailed studies.

• In this study, the authors state that chordamesoderm movements are preserved in syndecan-4 morphants, and in their 2021 article (Barua et al) they state that convergent extension movements are accelerated. But another study describing this MO found that it causes severe convergent extension defects (Munoz et al, NCB, 2006). What explains this discrepancy?

In their knockdown experiments, Munoz et al. find relatively mild axis defects in late gastrula/early neurula stage embryos while we studied the mid-gastrula. Perhaps defects develop during later stages in Syn-4 morphant embryos.

Also, the syn-4 morphant showed in Fig. 1 appears more developmentally advanced than the other embryo... if the embryos are not stage matched it could affect the measurements and conclusions drawn from them.

Stage matching was not possible since C-cad and FN morphants did not involute or engage in convergent extension (i.e. were arrested at the initial gastrula stage), Syn-4 morphants appeared to gastrulate faster than normally. Therefore, embryos were strictly time matched. A limitation remains, that the time course of cell contact development over gastrulation was considered low priority in this initial study and was thus not determined.

• In figure 7, the authors plot relative adhesion (measured from contact angles) vs. contact width, then fit regression lines to the lower boundaries of these scatter plots. It is not clear why this analysis is focused only on the lower boundaries rather than considering the full spread of the data. Particularly for syn-4 morphants, whose values do not appear to be concentrated along the lower boundary. This analysis is further confused by the introduction of alpha*, which represents relative adhesiveness relative to the regression.

The lower boundary line is most convenient to extract (Fig.7A’-E’). But we agree that the “interior” of the scatter plot distribution should also be analyzed. Using average adhesiveness gives rise to artifacts since the density of data points decreases strongly with contact width but also with distance from the lower boundary, leading to the preferential disappearance of large adhesiveness values for higher widths. Instead, we constructed a line tracing the highest density in the scatter plot near the lower boundary (Fig.7B’’-E’’), by determining the positions of adhesiveness distribution peaks in consecutive width brackets (new Fig.8, Fig.S3). We abstained from introducing alpha*.

• Based on these regression lines alone, the authors conclude that all 4 conditions are similar enough to pool the data for further analysis. If these contacts have different properties, which the data in Figures 1-6 suggest they do, it seems inappropriate to pool them together.

We no longer pooled the data, except in supplementary Fig.S4 where we consider angle distortion. Instead, we show in Fig.8 relative-adhesiveness frequency distributions for different treatments and width brackets. This emphasizes differences between the different adhesion factor depletions and shows that adhesiveness is not simply normal or log-normal distributed, in agreement with different contact types contributing differently though similarly to overall adhesion. It also allows to follow main peaks as they shift position with width, roughly in proportion to the lower surface boundary.

Based on this pooling, the authors then conclude that relative adhesiveness increases linearly with contact width over the entire width range, regardless of adhesion factor depletion. This again assumes that all contacts (morphant and WT) are functionally equivalent, and that what is observed in morphant embryos in very wide contacts would also hold true in WT contacts. But because WT contacts occupy only a small portion of the width range, we cannot know how they would behave if scaled to be wider, and I am not convinced that very wide morphant contacts are representative of or functionally equivalent to WT. In other words, we cannot know that contact width is the only factor increasing their relative adhesion, given the experimental manipulations that structurally alter these contacts.

Although differences between contact types are apparent, we think that the contacts function very similarly. We still hold that relative adhesiveness increases with contact width, as seen in each of the separate plots for wt and adhesion factor depletions. But re-evaluating the alpha-width scatter plots now we show that in the narrow width range of normal chordamesoderm, C-cad, FN and Has depletions show similar, significantly decreased relative adhesiveness (Fig.7A-E). With alpha proportional to width, and width strongly increased in morphants, this initial decrease is compensated in total adhesiveness averages. The relative independence of adhesiveness from contact type could hint at non-specific PCM-PCM adhesion (Winklbauer, 2019). We think that although adhesion factor depletion leads to the loss of some contact types or renders others non-adhesive (thus lowering contact abundances), it modifies some contact types (e.g. by widening them) while only moderately lowering their adhesiveness per unit interaction surface.

Minor comments<br /> - In their descriptions of PCM in different experimental conditions, the authors overstate some conclusions drawn from EM data. For example, that type I glycocalyces are absent in chordamesoderm (although this signal is only reduced),

We qualified the statement.

or that because the Has2 morphant phenotype is intermediate between C-cad and fibronectin morphants this indicates an adhesive role for hyaluronic acid.

Overall, Has2MO increases the abundance of gaps, i.e. HA normally reduces gaps between cells, strongly suggesting an adhesive role of HA. HA is also required for the formation of 10-20 nm gaps, again proposing a direct or at least indirect adhesion-promoting role.

• The authors state of the data in figure 1 that "All treatments significantly increase the size of non-adhesive gaps", but they don't show a quantification of the gaps size (they show the abundance).

Has been corrected.

• The authors state that LSM contacts exist as 10-20 and 20-50 nm subtypes. It is not clear what about the data suggest this division.

In the LSM width difference spectra, CadMO and SynMO both increase the abundances of ≤ 20 nm contacts and decrease those of 20-50 nm contacts (Fig.4). The different response suggests at least two differently reacting subtypes.

• In the same paragraph, the authors state that "C-cad and Syn-4... favor LSM width between 20-50 nm." What is meant by "favor"? Given that the number of 20 nm contacts is increased and 50 nm contacts is decreased in both conditions, this statement is unclear.

The whole paragraph has been reworded.

• On page 7, the authors say that the size of LSM structures is "consistent with larger plaques being assembled from small units", but if that were the case, wouldn't the plaque sizes be multiples of the size of a single unit? I.e. 100, 200, and 300 nm peaks? Because this is not the case, the data seem more consistent with a continuous range of LSM plaque sizes than with discrete units.

The size of the units has a peak at 100 nm but a long tail (Fig.6F-H). Moreover, we discuss lateral compression (piling up of PCM material) or active stretching of plaques (to separate units for interdigitation), all factors that would blur plaque length patterns, i.e. we did not expect plaque sizes to be multiples of 100 nm.

• On page 8, the authors refer repeatedly to LSM volume. Given that these measurements are made from TEM sections, how is volume being measured?

This is explained now (p.7).

• The authors present a model in which PCM interdigitates within cell contacts, but this is based on measurements from static tissues alone. Could the measurements of contact width instead be explained by compression of the PCM or some other mechanism? The data as presented don't rule out such possibilities.

The model is in agreement with the linear increase of relative adhesiveness with contact width, with LSM height at gap surfaces not adding up to adjacent contact width, with visible interdigitation of glycocalyx units (“bushes”) described previously for prechordal mesoderm (Barua et al. 2021), and with the good agreement of calculated unit size with the size of measured LSM units. In addition, it agrees with literature data on endothelial glycocalyx plaques being composed of 100 nm units and of complete interpenetration of glycocalyces during blood cell adhesion.

Some terms used are not clear, for example: "partial LSM", "triple layer contact", "random removal [of LSM plaques]".

We point out the meaning of the terms now more clearly. That “partial LSM” is identical with “triple layer contact” (but shorter, for use in figure) is explained in the legend to fig.6.

• In figure 5, the graphs depict negative "abundance". Recommend "difference in abundance" instead.

Done. For shortness, Δ Abundance.

• Statistics: In figure 1I, it is not clear what the asterisk in this graph means or if statistical differences between these groups was determined. And in figure 6, some groups are marked as n.s., but P values for groups that are statistically different are not presented.

The asterisk in fig.1I was meant to indicate that this column is from Debanjan et al. 2021, but this is indicated by different shading and mentioned in the legend. The non-used n.s. marks were removed.

Reviewer #2 (Significance):

This detailed electron microscopy study advances our understanding of pericellular matrix within vertebrate embryos and how loss of its constituent molecules affects cell interactions. It further addresses the relationship between structurally distinct pericellular matrices and their adhesive properties, although this analysis is less convincing. This study adds to a body of literature in which cell-cell and cell-matrix adhesion are known to regulate morphogenetic cell movements, but how such contacts are remodeled as cells rearrange is poorly understood. Previous work has also used measurements from live cells, embryos, and tissues to infer physical forces within embryos such as adhesive strength, cortical tension, and viscosity. This work follows up directly on a previous study from this group that characterized glycocalyces within various tissues within Xenopus gastrulae by electron microscopy. The hypothesis that pericellular matrix enables flexible/fluid adhesion within highly dynamic embryonic tissues is exciting, and is likely to be of interest to developmental biologists - particularly those who apply mechanical concepts to embryos. However, additional evidence, preferably from live tissues and embryos, is needed to support this hypothesis. This assessment is based on over 15 years' experience studying gastrulation morphogenesis in multiple vertebrate species.

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Referee #2

Evidence, reproducibility and clarity

Summary:

During gastrulation, cells within vertebrate embryos require the ability to both adhere to one another and rearrange with their neighbors to shape the emerging body plan. These authors posit that such flexible adhesive contacts are mediated in part by the pericellular matrix (PCM), including multiple types of glycocalyces containing molecules such as fibronectin, hyaluronic acid, and syndecans, which they previously characterized in multiple embryonic tissues (Barua et al, PNAS, 2021). Here, in a follow-up to their 2021 study, the authors use electron microscopy to characterize the pericellular matrix within the chordamesoderm of Xenopus gastrulae. They identify several types of adhesive contacts within the chordamesoderm and assess how they are altered in the absence of key PCM molecules via morpholino knock-down. They conclude that syndecan-4 and hyaluronic acid comprise and promote assembly of PCM plaques whereas fibronectin and C-cadherin anchor them to cell surfaces. Cell packing density is decreased upon loss of all 4 of these molecules, which the authors attribute to a decrease in the number of cell contacts without affecting the strength of the remaining contacts. They further conclude that adhesiveness increases linearly with contact width, and that this relationship is unaffected by loss of any aforementioned adhesive/ PCM molecules.

Major comments:

• Many conclusions in this manuscript are based on measurements of cell contact angles, which indicate the reduction of tension at cell contacts vs. free cell surfaces and thus relative adhesive strength. While this lab previously applied the same approach to live tissues (David et al, 2014), it is not clear to what extent such measurements accurately reflect adhesive strength in fixed tissues and/or electron micrographs. Especially given the issue of random sectioning planes, which cause distortion of contact angles. Although a correction was applied, the authors note this is not theoretically derived because the heterogeneity of gap sizes made such calculations too difficult. Indeed, it appears that the large gaps between cells within morphant embryos affect contact angle measurements, but if this is corrected for in any way, it is not mentioned. Because this is the sole measure of cell adhesion provided in the study, this reviewer is not convinced of the conclusion that loss of PCM components does not affect adhesive strength. Could such measurements not be made from live cells/tissues after manipulating PCM components, as the lab has done previously? Because the lab already has the necessary reagents and expertise for such experiments, the time and resources needed for such measurements shouldn't be prohibitive.
• As mentioned above, these authors previously measured adhesive strength in live Xenopus cells and tissues (David et al, 2014). In that study, they found that C-cadherin MO reduced relative adhesiveness whereas the current study found that relative adhesiveness actually increases in this condition. What explains this discrepancy?
• No control morpholinos are used, and for the morpholinos that are used, the doses are very large. An equally high dose of control MO should be used to ensure that all observed phenotypes are specific.
• It appears that all the images analyzed were collected in the sagittal plane, and the analyses don't seem to consider the intrinsic polarity of the chordamesoderm. For example: cells in different positions within the tissue (basal vs. apical), or that WT chordamesoderm cells are mediolaterally polarized and actively intercalating whereas disruption of PCM components like fibronectin disrupts cell intercalation and randomizes cell polarity. It is possible that 1) cell-matrix (in basal cells) and 2) cell-cell (during intercalation) interactions may affect the measurements made in this study. In other words, that cell contacts could differ by position within the embryo and intercalation/polarity status... have such effects been accounted for in the current analysis?
• In this study, the authors state that chordamesoderm movements are preserved in syndecan-4 morphants, and in their 2021 article (Barua et al) they state that convergent extension movements are accelerated. But another study describing this MO found that it causes severe convergent extension defects (Munoz et al, NCB, 2006). What explains this discrepancy? Also, the syn-4 morphant showed in Fig. 1 appears more developmentally advanced than the other embryo... if the embryos are not stage matched it could affect the measurements and conclusions drawn from them.
• In figure 7, the authors plot relative adhesion (measured from contact angles) vs. contact width, then fit regression lines to the lower boundaries of these scatter plots. It is not clear why this analysis is focused only on the lower boundaries rather than considering the full spread of the data. Particularly for syn-4 morphants, whose values do not appear to be concentrated along the lower boundary. This analysis is further confused by the introduction of alpha*, which represents relative adhesiveness relative to the regression.
• Based on these regression lines alone, the authors conclude that all 4 conditions are similar enough to pool the data for further analysis. If these contacts have different properties, which the data in Figures 1-6 suggest they do, it seems inappropriate to pool them together. Based on this pooling, the authors then conclude that relative adhesiveness increases linearly with contact width over the entire width range, regardless of adhesion factor depletion. This again assumes that all contacts (morphant and WT) are functionally equivalent, and that what is observed in morphant embryos in very wide contacts would also hold true in WT contacts. But because WT contacts occupy only a small portion of the width range, we cannot know how they would behave if scaled to be wider, and I am not convinced that very wide morphant contacts are representative of or functionally equivalent to WT. In other words, we cannot know that contact width is the only factor increasing their relative adhesion, given the experimental manipulations that structurally alter these contacts.

Minor comments

• In their descriptions of PCM in different experimental conditions, the authors overstate some conclusions drawn from EM data. For example, that type I glycocalyces are absent in chordamesoderm (although this signal is only reduced), or that because the Has2 morphant phenotype is intermediate between C-cad and fibronectin morphants this indicates an adhesive role for hyaluronic acid.
• The authors state of the data in figure 1 that "All treatments significantly increase the size of non-adhesive gaps", but they don't show a quantification of the gaps size (they show the abundance).
• The authors state that LSM contacts exist as 10-20 and 20-50 nm subtypes. It is not clear what about the data suggest this division.
• In the same paragraph, the authors state that "C-cad and Syn-4... favor LSM width between 20-50 nm." What is meant by "favor"? Given that the number of 20 nm contacts is increased and 50 nm contacts is decreased in both conditions, this statement is unclear.
• On page 7, the authors say that the size of LSM structures is "consistent with larger plaques being assembled from small units", but if that were the case, wouldn't the plaque sizes be multiples of the size of a single unit? I.e. 100, 200, and 300 nm peaks? Because this is not the case, the data seem more consistent with a continuous range of LSM plaque sizes than with discrete units.
• On page 8, the authors refer repeatedly to LSM volume. Given that these measurements are made from TEM sections, how is volume being measured?
• The authors present a model in which PCM interdigitates within cell contacts, but this is based on measurements from static tissues alone. Could the measurements of contact width instead be explained by compression of the PCM or some other mechanism? The data as presented don't rule out such possibilities.
• Some terms used are not clear, for example: "partial LSM", "triple layer contact", "random removal [of LSM plaques]".
• In figure 5, the graphs depict negative "abundance". Recommend "difference in abundance" instead.
• Statistics: In figure 1I, it is not clear what the asterisk in this graph means or if statistical differences between these groups was determined. And in figure 6, some groups are marked as n.s., but P values for groups that are statistically different are not presented.

Significance

This detailed electron microscopy study advances our understanding of pericellular matrix within vertebrate embryos and how loss of its constituent molecules affects cell interactions. It further addresses the relationship between structurally distinct pericellular matrices and their adhesive properties, although this analysis is less convincing. This study adds to a body of literature in which cell-cell and cell-matrix adhesion are known to regulate morphogenetic cell movements, but how such contacts are remodeled as cells rearrange is poorly understood. Previous work has also used measurements from live cells, embryos, and tissues to infer physical forces within embryos such as adhesive strength, cortical tension, and viscosity. This work follows up directly on a previous study from this group that characterized glycocalyces within various tissues within Xenopus gastrulae by electron microscopy. The hypothesis that pericellular matrix enables flexible/fluid adhesion within highly dynamic embryonic tissues is exciting, and is likely to be of interest to developmental biologists - particularly those who apply mechanical concepts to embryos. However, additional evidence, preferably from live tissues and embryos, is needed to support this hypothesis. This assessment is based on over 15 years' experience studying gastrulation morphogenesis in multiple vertebrate species.

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Referee #1

Evidence, reproducibility and clarity

Summary:

This work examines the relationship between cell-cell contacts and pericellular matrix in Xenopus chordamesoderm, which is a tissue actively involved in convergent extension during gastrulation. By lanthanum staining of pericellular materials, the authors found that different types of pericellular matrix are present in cell-cell contacts in the chordamesoderm, which may mediate cell-cell adhesion. Knockdown of C-cadherin, Syndecan-4, fibronectin, and hyaluronic acid leads to the reduced abundance of cell contacts and cell packing density, but this does not seem to affect convergent extension. Based on these observations, the authors propose a model in which cell-cell contacts involve the interdigitation of distinct pericellular matrix units.

Major points:

1. Knockdown of adhesion molecules separates cells and leads to wide contacts with large interstitial spaces. Data in figure 1 show loosely packed morphant chordamesoderm cells. Intuitively, these should reduce cell-cell adhesion. However, a main conclusion from this manuscript is that reduced abundance of narrower contacts does not decrease adhesiveness. Although depletion of adhesion molecules modifies but not abolishes a contact, non-attached free surfaces increase significantly in morphant cells. It is therefore not easy to understand that how reduced cell contacts have no effect on cell adhesion. Importantly, the adhesiveness was not experimentally tested.
2. It is surprising that reduced cell contacts, at least narrower cell contacts, do not affect convergent extension. Does this mean that active cell behavior changes in the chordamesoderm, which are required for convergent extension, are independent of cell contact types?
3. Although the formation and localization of pericellular materials are differentially affected after knockdown of adhesion molecules, there is no clear evidence showing that different types of pericellular matrix mediate cell-cell adhesion in the chordamesoderm. It is possible that the disrupted distribution of pericellular materials in morphants only represents a secondary consequence of changed cell contacts. This may be supported by the fact that knockdown of adhesion molecules reduces narrow contacts and increases LSM-free gaps.
4. The relationship between contact width spectra and LSM is also very elusive. Again, changes in contact width or abundance and distribution of LSM may be indirectly caused by loss of adhesion molecules. Therefore, although knockdown of adhesion molecules leads to changes of LSM localization, it cannot be concluded that cell-cell contacts in chordamesoderm are mediated different types of pericellular matrix.
5. In contrast to the present observations, works by others using the same morpholinos have shown that Cadherin-dependent cell adhesion, fibronectin-rich extracellular matrix, and Syndecan-4-regulated non-canonical Wnt signaling are required for convergent extension. These discrepancies need to be appropriately addressed.
6. If LSM and LSM-free contacts are similarly adhesive, what will be role of LSM in cell adhesion and how cell adhesion is established in these LSM-free contacts?

Minor points:

1. It may be helpful to clearly define the pericellular matrix in this particular context and its relationship with LSM. It is also necessary to clarify whether the adhesion molecules examined in this work are considered as components of the pericellular matrix.
2. In figure 1B, it appears that the Cadherin morphant has defects in chordamesoderm elongation and archenteron formation, suggesting impaired convergent extension.
3. In figure 1C, the Syndecan-4 morphant gastrula clearly shows enhanced anteroposterior elongation of chordamesoderm and archenteron in comparison with the wild-type embryo. This seems to suggest that loss of Syndecan-4 promotes the movements of convergent extension. However, previous studies indicate that both gain and loss of Syndecan-4 impairs convergent extension.
4. Ideally, in knockdown experiments, control embryos should be injected with corresponding mismatch morpholinos.
5. In figure 1E, it is unclear what type of cell contacts the light green arrowheads indicate.
6. Figure 1 legend, "(wt) is from Barua et al. 2021". I am not sure it is appropriate to use previously published data.
7. There is no light blue arrowhead in figure 2, and in figure 3B and 3I, it seems that the same colored arrows are used to indicate different structures.
8. Triple-layered contacts are not clearly defined.
9. Page 2, "based on driven by" should be either "based on" or "driven by".
10. Page 8, "selectin" should be "selecting".

Significance

Strengths:

Demonstrated the effects of several adhesion molecules on the formation of cell contacts and pericellular matrix in Xenopus chordamesoderm.

Limitations:

The significance of chordamesoderm cell contact changes in convergent extension or gastrulation is not clear; there is no direct evidence showing the functional link between pericellular matrix, cell contacts and cell adhesion; the absence of effects on convergent extension after depletion of several adhesion molecules is not fully consistent with previous reports.

Advance:

This work likely provides some fundamental and methodological advances for studying cell-cell adhesion. It shows promise for elucidating mechanisms underlying the regulation of cell contact changes in tissues involved in morphogenetic movements.

Audience:

This work likely interests readership studying embryonic cell adhesion in the field of developmental biology and cell biology. It may be also potentially interesting for people working on glycocalyx pericellular matrix in adult tissues.

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Reply to the reviewers

Please find our point-to-point response to the reviewer’s comments below, where we marked all changes implemented in the manuscript in italics.

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

With the emergence and spread of resistance to Artemisinin (ART), a key component of current frontline malaria combination therapies, there is a growing effort to understand the mechanisms that lead to ART resistance. Previous work has shown that ART resistant parasites harbour mutations in the Kelch13 protein, which in turn leads to reduced endocytosis of host haemoglobin. The digestion of haemoglobin is thought to be critical for the activation of the artemisinin endoperoxide bridge, leading to the production of free radicals and parasite death. However, the mechanisms by which the parasites endocytose host cell haemoglobin remain poorly understood.

Previous work by the authors identified several proteins in the proximity of K13 using proximity-based labelling (BioID) (Birnbaum et al. 2020). The authors then went on to characterise several of these proteins, showing that when proteins including EPS15, AP2mu, UBP1 and KIC7 are disrupted, this leads to ART resistance and defects in endocytosis leading to the hypothesis that these two processes are inextricably linked.

In this manuscript, Schmidt et al. set themselves the task of characterising more K13 component candidates identified in their previous work (Birnbaum et al. 2020) that were not previously validated or characterised. They chose 10 candidates and investigated their localisations, and colocalisation with K13, and their involvement in endocytosis and in vitro ART resistance, 2 processes mediated by K13 and some members of the K13 compartments

The authors show that of their 10 candidates, only 4 can be co-localised with K13. Then, using a combination of targeted gene disruption (TGD) as well as knock sideways (KS), they characterised these 4 proteins found in the K13 compartment. They show that MyoF and KIC12 are involved in endocytosis and are important for parasite growth, however their disruption does not lead to a change in ART sensitivity. The authors also confirm the findings of their previous publication (Birnbaum et al. 2020), using a slightly different TGD

(note from the authors: we apologise if this has not properly transpired from the manuscript but the difference between the TGDs is substantial and relevant: one has less than 3% of the protein left and hence can be considered to fully inactivate MCA2 and has a growth defect whereas the other contains about two thirds of the protein (1344 amino acids/~66% are left), has no growth defect, although it lacks the MCA2 domain (hence that domain can not be critical for the growth defect)),

that MCA2 is involved in ART resistance, however they did not check whether its disruption impacts haemoglobin uptake. They also show that KIC11 is not involved in mediating haemoglobin uptake or ART resistance. To finish, the authors used AlphaFold to identify new domains in the proteins of the K13 compartment. This led them to the conclusion that vesicle trafficking domains are enriched in proteins of the K13 compartment involved in endocytosis and in vitro ART resistance.

The majority of the experiments conducted by the authors are performed to a good standard in biological and technical replicates, with the correct controls. Their findings provide confirmation that their 4 candidate genes seem to be important for parasite growth, and show that some of their candidates are involved in endocytosis. While the KD and KS approaches employed by the authors to study their candidate genes each have their own advantages and can be excellent tools for studying a large sets or genes, this manuscript highlights the many limitations of these approaches. For example, the large tag used for the KS approach can mislocalise proteins or disrupt their function (as is the case for MyoF), resulting in spurious results, or indeed the inability to generate the tagged line (as is the case for MCA2). The KS approach also makes the results of a protein with a dual localisation, like KIC12, extremely difficult to interpret.

We thank the reviewer for this thorough and insightful review.

The limitations mentioned above were addressed in the response to the main points and a general detailed response in regards to the systems used for this research are added at the end of this rebuttal. Briefly summarised here: while we agree that there are limitations of the system used, we are convinced that

• the advantages of using a large tag in most cases outweighs the drawbacks as it permits to track the inactivation of the target, if need be on the individual cell level

• while not optimal for MyoF, the partial inactivation actually helps in its functional study as detailed in major point 23&28 or reviewer#3 major point 11: it shows a consistent correlation of the phenotype with different causes and degrees of inactivation (this is now better illustrated in Figure 1L1M). Further, regarding the concern of the large tag: the effect of the tag based on localisation was overestimated in the review by what seems to have been a mix up comparing numbers from MyoF with a number from MCA2 (there is a difference, but it is only small) (see reviewer#1 major point #23).

• KS is the optimal method for most of the assays in this work (e.g. bloated food vacuole assays and RSAs); these assays would be impossible or difficult to use with other inactivation systems currently used in P. falciparum research (see details in the response to the specific points and after the rebuttal)

In regards to the difficulty to interpret KIC12 data: this is only true for measuring absolute essentiality, everything else we believe we actually have the optimal method. If not KS, which method targets a specific pool of a protein with a dual localisastion? Again, our assays targeting the K13 pool and revealing the specific function would have been difficult or impossible with any other system.

Ultimately the question is whether any other system would have resulted in a different conclusion on the function of the proteins studied. At present we are confident this would not be the case and other systems probably would not have delivered the specific functional data shown in this work. Clearly, more in depth work will provide more nuanced and detailed insights into the proteins analysed in this work and this likely will also include the use of other systems for specific aspects they are most suitable for. However, this (e.g. different complementations in a diCre cKO) is complex and therefore beyond what fits into this work which had the goal to assess which proteins are true positives for the K13 compartment and to place them into functional groups in regards to endocytosis.

Moreover, the manuscript is disjointed at times, with the authors choosing to conduct certain experiments for only a subset of genes, but not for others. For example, considering that the aim of this paper was to identify more proteins involved in ART resistance and endocytosis, it is confusing why the authors do not perform the endocytosis assays for all their selected proteins, and why they do not do this for the proteins they identify in their domain search. There is significant room for improvement for this manuscript, and a generally interesting question.

The reviewer remarks that not every experiment was done for every target. Based on the rebuttal we tried to amend this but also note that there was some sentiment by the reviewers to better stick to the point and not make the manuscript more disjointed. We attempted to balance that as much as possible and hope we were able to honour both aspects (amendments were done as detailed in the point by point response below).

In regards to endocytosis and choice of targets: We did do endocytosis assays for all proteins that showed a growth phenotype upon inactivation in this work. We therefore assume the reviewer here refers to major point #40 asking for endocytosis assays with KIC4 and KIC5 (which were not studied in this manuscript) as well as MCA2 (point 17). We fully agree with the reviewer that this would fill a gap in the work on K13 compartment proteins but such assays are difficult with TGDs (there are issues with non-comparable samples and compensatory effects) and proteins that are not essential (and hence likely have a smaller impact on endocytosis when truncated). We nevertheless now carried them out, but due to the limitations to do this with these lines would be hesitant to draw definite conclusions (see major point 17 and 40 for details and outcomes).

But in it's current format, other than confirming that MCA2 is involved in ART resistance (which was already known from the Birnbaum paper), the authors do not further expand our understanding of the link between ART resistance and endocytosis in this manuscript.

We would like to point out that the importance of the K13 compartment and endocytosis goes beyond ART resistance (see e.g. also newly published papers on the K13 compartment in Toxoplasma, (Wan et al., 2023; Koreny et al., 2023)). Endocytosis is an essential and prominent process in blood stages. However, in contrast to processes such as invasion, our understanding about endocytosis is only rudimentary. Hence, this manuscript provides important insights on an emerging topic that in our opinion deserves more attention:

• it identifies novel proteins at the K13 compartment and provides 2 new proteins in endocytosis (MyoF and KIC12); getting an as complete as possible list of proteins involved in the process will be critical to study and understand it

• it leads to the realisation that not all growth-relevant proteins detected at the K13 compartment are needed for endocytosis

• it provides domains and stage specificity of function for several K13 compartment proteins, overall bolstering the model of endocytosis in ART resistance and providing a framework critical to direct future studies on endocytosis and their detailed mechanistic function at the cytostome

• the identified vesicle trafficking domains (for instance now also found in UBP1) are expected to strengthen the support for the role of endocytosis of the K13 compartment; this and also the above points are important as (based on the current literature) there still seems to be prominent sentiment in the field that (in part due to the involvement of UBP1 and K13) the cause of ART resistance is due to various unclearly defined stress response pathways

• with MyoF it also shows the first protein in connection with the K13 compartment that acts downstream of the generation of hemoglobin-filled containers in the parasite and provides the first protein that explains the suspected involvement of actin in endocytosis (so far this was only based on CytD studies)

Overall we therefore believe this manuscript contains critical information and a framework for future studies on endocytosis and the K13 compartment. We hope the relevance of endocytosis as one of the most prominent and essential processes in the parasites and the connection to various aspects linked with many commercial drugs (in addition to the role of endocytosis in ART resistance), is adequately explained in the introduction. We also would like to mention that the main focus of the work is reflected in the title of the manuscript which does not mention ART susceptibility.

Major Comments

1) line 31: please change defined to characterised - defined suggests that novel proteins were identified in this study, which is not the case.

We apologise, but we do not fully understand this comment. We did identify novel proteins not before known to be at the K13 compartment (MCA2 (admittedly this one was likely but had not previously been verified), MyoF, KIC11 and KIC12). In our view "further defining the composition of the K13 compartment" therefore is an accurate statement. Additionally, the identification of previously not-discovered domains, the stage-specificity and function of these proteins helped to further define the K13 compartment.

If the reviewer is referring to the fact that the proteins analysed in this study were taken from a previously generated list of hits, we would like to stress that the presence in such a list (obtained from a BioID, but also if from an IP etc) can not be equalled for them to be true positives, they are merely candidates that still need to be experimentally validated. This is what we did in this work to find out which further proteins from the list can be classified as K13 compartment proteins (for hits with lower FDRs this is even more relevant as illustrated by the fact that 6 of the here analysed hits were not at the K13 compartment). In an attempt to address this comment in the manuscript, we changed the wording of this sentence to (line 31): "Here we further defined the composition of the K13 compartment by analysing more hits from a previous BioID, showing that MyoF and MCA2 as well as Kelch13 interaction candidate (KIC) 11 and 12 are found at this site."

2) line 37: please change 'second' to "another". As explained further below, the authors identified 3 classes of proteins (confer ART resistance + involved in HCCU, involved in HCCU only, or involved in neither).

We realized that the groups description wasn’t clear in the abstract. Please see response to major comment #41 for a detailed answer to this (endocytosis is an overarching criterion, ART resistance is a subgroup and applies only to those proteins with a function in endocytosis in ring stages). To clarify this (see also major point #8) we added an explanation on the influence of stage-specificity of endocytosis on ART susceptibility to the introduction (line 76): “In contrast to K13 which is only needed for endocytosis in ring stages (the stage relevant for in vitro ART resistance), some of these proteins (AP2µ and UBP1) are also needed for endocytosis in later stage parasites (Birnbaum et al., 2020). At least in the case of UBP1, this is associated with a higher fitness cost but lower resistance compared to K13 mutations (Behrens et al., 2021; Behrens et al., 2023). Hence, the stage-specificity of endocytosis functions is relevant for in vitro ART resistance: proteins influencing endocytosis in trophozoites are expected to have a high fitness cost whereas proteins not needed for endocytosis in rings would not be expected to influence resistance.” The abstract was changed in response to this and other comments and hope it is now clearer in regards to the groups.

3) Line 40: You define KIC11 as essential but according to your data some parasites are still alive and replicating 2 cycles after induction of the knock sideways. Please consider changing "essential" to "important for asexual parasite growth".

We fully agree with the reviewer, we reworded the sentence as suggested.

4) Line 40: please change 'second group' to 'this group'

We reworded this part of the abstract and it know reads: (line 38): “While this strengthened the link of the K13 compartment to endocytosis, many proteins of this group showed unusual domain combinations and large parasite-specific regions, indicating a high level of taxon-specific adaptation of this process.”

5) line 41: state here that despite it being essential, it is unknown what it is involved in.

With the newly added data we show that this protein either has a function in invasion or very early ring development although we did not see any evidence for the latter. We therefore changed the sentence to (line 43): “We here identified the first protein of this group that is important for asexual blood stage development and showed that it likely is involved in invasion*..” *

6) Line 50: the authors should state here that there is actually a reversal in this trend over the last few years.

Done as suggested.

7) Line 54: please separate out the references for each of the two statements made in this line (a: that ART resistance is widespread in SEA, and b: that ART resistance is now in Africa) Reference 14 also seems to reference ART resistance in Amazonia - which is not covered by the statement made by the authors (in which case the authors should state ART is now present in Africa and South America). The authors should also reference PMID: 34279219 for their statement that ART resistance is now found in Africa (albeit a different mutation to the one found in SEA).

Done as suggested.

8) Line 65: it is also worth mentioning here that there are other mutations in proteins other than K13, such as AP2mu and UBP1 (PMID: 24994911;24270944) that can lead to ART resistance.

As suggested by the reviewer, we included a sentence about non-K13 mutations linked with reduced ART susceptibility in the introduction (line 74): “Beside K13 mutations in other genes, such as Coronin (Demas et al., 2018) UBP1 (Borrmann et al., 2013; Henrici et al., 2020b; Birnbaum et al., 2020; Simwela et al., 2020) or AP2µ (Henriques et al., 2014; Henrici et al., 2020b)* have also been linked with reduced ART susceptibility." *

We here also added data on fitness cost that is related to this and is also relevant for the issue of proteins with a stage-specific function in endocytosis, making a transition for this statement which might help clarifying the grouping of K13 compartment proteins (see also major point #2).

9) Line 80, 86: ref 43 is misused. Reference 43 refers to Maurer's clefts trafficking which takes place in the erythrocyte cytosol and is not involved in haemoglobin uptake as far as I know. Please replace ref 43 with one showing the role of actin in haemoglobin uptake.

We thank the reviewer for pointing this out, Ref 43 was removed from the manuscript.

10) Line 98: the authors state here that they 'identified' further candidates from the K13 proxiome. This suggests that they identified new proteins in this paper, when in fact the list was already generated in ref 26. All they did was characterise proteins from that list that were not previously characterised. The authors should therefore remove identified from this statement.

We agree with the reviewer that we did not identify further candidates, we identified new K13 compartment proteins from the list of potential K13 compartment proteins. We therefore changed “identified further candidates” into “identified further K13 compartment proteins” (line 116). Please see also response to major comment #1.

11) Line 107-108: it is not clear from this sentence why these proteins were left out of the initial analysis in Ref 26. A sentence here explaining this would be valuable for the reader.

This is a good point. One reason why we did not analyse more in our previous publication was that we had to stop somewhere and adding more would have been very difficult to fit into what was already a packed paper. However, as shown in this work, the list does contain further interesting candidates (e.g. K13 compartment proteins that are involved in endocytosis).

We altered the relevant part of the introduction to highlight that we previously analysed the top hits, clarifying that the 'remaining' hits analysed in this work were further down in the list. This now reads: (line 113)“We reasoned that due to the high number of proteins that turned out to belong to the K13 compartment when validating the top hits of the K13 BioID (Birnbaum et al., 2020), the remaining hits of these experiments might contain further proteins belonging to the K13 compartment.” We hope this clarifies that we simply moved further down in the candidate list.

12) Line 117-123: The authors say that PF3D7_0204300, PF3D7_1117900 and PF3D7_1016200 were not studied because they were not in the top 10 hits. However, the current organisation of Supplementary Table 1 shows all 3 proteins among the top 10 hits (MyoF, KIC12, UIS14 and 0907200 being after them). I think the authors should reorganise their table. It is also unclear according to what the proteins in the table are ranked. Could the authors indicate the metric used for the ranking?

We thank the reviewer for alerting us to this. The issue here is that the 3 non-analysed proteins belong to a 'lower stringency' group comprising hits significant with FDRThe information about ranking is now also included as “Table legend” in the revised manuscript and the Table heading has been changed to: “List of putative K13 compartment proteins, proteins selected for further characterization in this manuscript are highlighted.”

13) Line 129-141: Can the authors be clearer with their explanations of the identification of mutation Y1344Stop? One dataset (ref 61) shows that 52% of African parasites have a mutation in MCA2 in position 1344 leading to a STOP codon. But another dataset (ref 62) shows that the next base is also mutated, reverting the stop codon. That should have been seen in the first dataset as well. Could the authors please clarify.

This mutation was first spotted in the MalariaGEN database (https://www.malariagen.net) (MalariaGEN et al., 2021), which allows online accessing of the data by using the “variant catalogue” tool, which is in a table format of frequency rather than in a sequence context. Hence, only after further research later on it became evident to us, that this mutation does not occur alone when looking at individual MCA2 sequences from patient samples in (Wichers et al., 2021b). We hope this is accurately reflected in our results section.

14) Line 147: the authors say that MCA2 is expressed throughout the intraerythrocytic cycle as shown by live cell imaging. In Birnbaum et al 2020 fig 4I, the authors show that MCA2 is mainly expressed between 4 and 16hpi. But in Figure 1B of this manuscript there is a clear multiplication of MCA2 signal between trophozoite and schizont. How do the authors explain this discrepancy? Could expression of the truncated MCA2 be different than the full length? This cannot be assessed as expression and localisation of the full-length HA tag MCA2 is not shown in Schizonts.

The key difference lies in transcription vs protein expression (usually protein levels peak after mRNA levels peak and - depending on turnover - protein levels can stay high even after mRNA levels have declined). Figure 4 of the Birnbaum et al paper presents transcriptomic data, but with a peak in trophozoites (The axis label in Fig. 4l of that publication is a bit confusing, as hour 0 is at the top, 48 h at the bottom; it is clearer in Fig. S13 of that paper) which would fit very well with the multiplication of the signal between trophozoites and schizonts mentioned by the reviewer. So, overall, the temporal peaks of transcripts and protein of that protein fit well.

For the signal in rings: Likely the protein has a turnover rate that is sufficiently low for some protein to be taken into the new cycle after re-invasion. Also different transcriptomic datasets e.g. (Otto et al., 2010; Wichers et al., 2019; Subudhi et al., 2020) available on plasmoDB show some mRNA present across the complete asexual development cycle, with each dataset showing maximum peak at a slightly different stage.

Even when located in foci and hence aiding detection of small amounts of protein (as is the case for MCA2-Y1344-GFP), the MCA2 signal in rings is not strong. For MCA2-TGD, the GFP signal is dispersed and therefore likely below our detection limit, while the same amount of protein concentrated at the K13 compartment is visible as foci in the MCA2-Y1344 cell line. Please note that MCA2-TGD has only 2.8% of the protein left whereas MCA2-Y1344 has 66.5% left and based on our manuscript is almost fully functional, hence fitting the different locations between the two versions.

Overall we believe this shows that there are actually no significant discrepancies of the expression of the different MCA2 versions.

15) Line 158: would it not have been more useful for the authors to have episomally expressed MCA2-3xHA in their MCA2Y1344STOP-GFPENDO line to make sure that the truncated protein is indeed going to the correct compartment? The experiments done by the authors suggests that the MCA2Y1344STOP goes to the right location but does not really confirm it.

We appreciate the reviewers caution here. However, considering that MCA2Y1344STOP-GFPendo co-locates with mCherryK13 and endogenously HA-tagged full length MCA2 does the same to a similar extent, there is in our opinion little doubt that MCA2 is found at the K13 compartment and that this is similar with both constructs. If there are minor differences, these might as well occur if MCA2 is episomally (as suggested in the comment) instead of endogenously expressed. Given the limited insight, we therefore decided against the episomal overexpression (which due to its size of > 6000bp may also be somewhat less straight forward than it may sound).

16) Line 191: it is stated that MCA2 confers resistance independently of the MCA domain, however in both the MCA2-TGD and MCA2Y1344STOP-GFPENDO parasites, the MCA domain is deleted, and for both parasites, there is resistance (albeit to a lower level in the MCA2Y1344STOP-GFPENDO line). Therefore, how can the authors state that the ART resistance is independent of the MCA domain? This statement should be that resistance is dependent on the loss of the MCA domain.

We agree that this can’t be categorically excluded. However, a ~5 fold difference in ART sensitivity was observed between the parasites with MCA2 truncated at amino acid 57 compared to those with MCA at amino acid 1344 even though both do not contain the MCA2 domain. Hence, at least this difference is not dependent on the MCA2 domain. The larger construct missing the MCA domain shows only a very moderate reduction in RSA survival, again suggesting the MCA domain is not the main factor. We amended our statement in an attempt to more accurately reflect the data (line 487): “This considerable reduction in ART susceptibility in the parasites with the truncation at MCA2 position 57 compared to the parasites still expressing 1344 amino acids of MCA2, despite both versions of the protein lacking the MCA domain, indicates that the influence on ART resistance is not, or only partially due to the MCA domain.” We would be hesitant to state the reviewer's conclusion that “resistance is dependent on the loss of the MCA domain”, as the larger construct missing the MCA2 domain has a milder RSA effect compared to MCA2-TGD, which suggests the reduction in ART susceptibility is independent of the MCA domain. These considerations also agree with the fact that the parasites with the longer MCA2 version (in contrast to the MCA2-TGD) do not have any detectable growth defect which indicates that the protein can fulfil its function without the MCA2 domain.

17) Line 192: Why did the authors not check if MCA2 is involved in endocytosis? They state later on in the manuscript that they did not do endocytosis assays with TGD lines, however if the authors include the correct controls, this could be easily done. It would also be really interesting to see whether endocytosis gets progressively worse going from WT to MCA2Y1344STOP to MAC2TGD. This experiment (as well as doing endocytosis assays for KIC4 and KIC5 TGD lines) would drastically increase the impact of this study. These experiments would not take more than 3 weeks to perform, and would not require the generation of new lines.

So far were very hesitant to do bloated FV assays with TGDs (even though TGDs were available for the genes encoding MCA2 and KIC4 and KIC5). The reason for this was:

1. the fact that these proteins could be disrupted indicated either redundancy or only a partial effect on endocytosis which might lead to only small effects that likely are difficult to pick up in an assay scoring for the rather absolute phenotype of bloated vs non-bloated. Using the refined assay measuring FV size could partly amend this but we note that also FV without hemoglobin have a certain size, reducing the relative effect if there are smaller differences.
2. a TGD line does not permit tightly controlled inactivation of the target which makes comparing the outcome of bloated food vacuole assays difficult if there are smaller growth and stage differences to the 3D7 control.
3. in contrast to conditional inactivation parasites, the TGD lines had ample times to adapt to loss of the target protein (compensatory mechanisms are well known for endocytosis, for instance in clathrin mediated endocytosis loss of individual components can be compensated (Chen and Schmid, 2020)). We nevertheless see the reviewer's point that this should at least be attempted and now conducted these assays (see also major point 40). For MCA2 (as requested in this point), the data is shown in Figure S5C-E. This assay showed that in MCA2-TGD, MCA2Y1344STOP-GFPendo (similar to the 3D7 control) >95% of parasites developed bloated food vacuoles. Additionally, we also measured the parasite and food vacuole size of individual cells in an attempt to solve some of the problems with TGDs with such assays. In order to specifically solve problem 2 mentioned above, we analysed the food vacuoles of similarly sized parasites, however, they were non-distinguishable between the three lines. Of note, in agreement with the reduced parasite proliferation rate (Birnbaum et al., 2020) a general effect on parasite and food vacuole size was observed for MCA2-TGD parasites, indicating reduced development speed in these parasites. Hence, it is possible that a potential endocytosis reduction was accompanied by a slowed growth, and the comparison of similarly sized parasites may have obscured the effect. It is therefore not sure if there indeed is no endocytosis phenotype, although we can exclude a strong effect in trophozoites.

Based on the RSA results at least rings can be expected to have a reduced endocytosis in the MCA2-TGD. Apart from options 1-3 mentioned above, it is therefore possible there is an effect restricted to rings, although in that case the reduced growth in trophozoites would be due to other functions of MCA2. Overall, we can conclude that the MCA2-TGD parasites do not have a strongly reduced endocytosis, but given the fact that the parasites are viable, this is not surprising. Whether the MCA2-TGD has no effect at all on endocytosis we would be very hesitant to postulate based on these results.

18) The authors should consider re-organising the MCA2 section, first showing that the 3xHA tagged line colocalises with K13, then performing the new truncation.

We attempted to re-organise as suggested but because we now included additional fluorescence microscopy images of schizont and merozoites (in response to reviewer 2 major comment 3) the main figure would become even larger. To prevent this, we kept the 3xHA data in the supplement.

19) Line 197: Once again ref 43 is not correct to illustrate that actin/myosin is involved in endocytosis

We thank the reviewer for pointing this out – we removed Ref 43.

20) Line 202: the authors state that MyoF localises near the food vacuole from ring stage/trophs onwards. However, how can this statement be made in schizonts based on these images (Fig. 2A), where it doesn't look like MyoF is anywhere near the FV? This statement can only be made for schizonts if co-localised with a FV marker (which is done in Fig. 2B), however, based on the number of MyoF foci, it appears that this was not done for schizonts. Please either remove the statement that MyoF is near the food vacuole from trophs onwards (because it is only seen near the FV up until trophs) or show the data in Fig. 2B of schizonts to substantiate these claims.

This is a valid point. We originally did not focus on schizonts because most markers end up in some focal area in the forming merozoite but other proteins (such as e.g. K13) also have one or more additional foci at the FV, making interpretation unclear, particularly if the schizont is still organizing to become fully segmented. This is why we generally focused the K13 co-localisations on the trophozoite stage to obtain the clearest information on endocytosis. However, given the fact that this manuscript gives the first localization of MyoF in P. falciparum parasites, we now provide a comprehensive time course (Figure 1C, S1A) including schizonts, which show quite a complex pattern: while the MyoF-GFP localization in trophozoites appeared as multiple foci close to K13 and also the FV, the MyoF-GFP pattern changes in late schizonts (fully segmented) and merozoites, appearing as elongated foci no longer close to K13 or the FV. Of note, this pattern has been previously reported for MyoE in P. berghei (Wall et al., 2019).

We therefore revised the statement about MyoF localization in schizont to better reflect the observed localization: (line 175): “In late schizonts and merozoite the MyoF-GFP signal was not associated with K13, but showed elongated GFP foci (Figure 1C, S2A) reminiscent of the MyoE signal previously reported in P. berghei schizonts (Wall et al., 2019).”

21) Line 204-206: what does this statement bring to the paper? Is it to show that it is the real localisation of MyoF because 2 tag cell line show the same localisation? I don't think this is needed, especially as later in the manuscript an HA-tag MyoF line is used and show similar localisation.

We see the reviewers point, but prefer to keep this data included in the supplement, particularly because potential differences in the location of tagged MyoF were a major concern.

Related to the tag issue: in order to get a better understanding of the effect of C-terminally tagging with different sized tags we now performed a more detailed analysis of the MyoF-3xHA cell line (Figure S2F-G), showing that this cell line shows a growth rate similar to the 3D7 wild type parasites, and has less vesicles than the 2x-FKBP-GFP-2xFKBP cell line, but still slightly, but significantly more than 3D7 parasites. Overall, this indicates that the smaller 3xHA tag has less effect on the parasite, than the larger 2x-FKBP-GFP-2xFKBP tag (see also new Figure 1L, showing a correlation of level of inactivation and the endocytosis phenotype for MyoF).

22) Line 212: The overlap of K13 with MyoF in Figure 2C 3rd panel (1st trophozoite panel) is not obvious, especially as the MyoF signal seems inexistant. I would advise the authors to replace with a better image. Also, why are there no images of schizonts shown in Figure 2C?

As suggested we exchanged the trophozoite image of panel Figure 2 C (now Figure 1C) and expanded this panel with images covering the complete asexual development cycle including schizonts in response to this and the previous points. As indicated above (point 20), schizont stages are complex to interpret. While late schizonts likely are not very relevant for endocytosis this is the first description of the location of the protein in this parasite and we therefore now provide a more thorough representation of the MyoF location across asexual stages in Figure1C and S2A.

23) Line 217: the spatial association of MyoF with K13 is very different when it is tagged with GFP and when it is tagged with 3xHA. The way the authors word it here, it seems that there is agreement with the two datasets, when this is not in fact the case (59% overlap for MyoF-GFP and only 16% overlap with MyoF-3xHA). These data suggest that the GFP and the multiple FKBP tags are doing something to the protein and therefore maybe the ensuing results using this line should not be trusted or be taken with a pinch of salt.

We agree with the reviewer that the location of this MyoF-GFP in the cell might differ due to the partial inactivation but in contrast to this comment, the data does not indicate any large differences. It seems the reviewer mixed something up (the 59% mentioned might come from the MCA2 figure?). The data with the two lines with differently tagged MyoF co-localised with K13 are actually quite comparable: GFP-tagged vs HA-tagged MyoF overlapping with K13 was 8% vs 16% full overlap, 12% vs 19% partially overlapping foci, 36% vs 63% foci that were touching but not overlapping (compare what now is Figure 1D and Figure S2C). Only in the 'no overlap' there is a much smaller proportion in the HA-tagged line. However, given that these are IFAs which on the one hand are more sensitive to see small protein pools but on the other hand also have pitfalls due to fixing of the cells (e.g. tiny increase in focus size due to fixing could increase the number of touching foci that in live cells might be close but did not touch), some variation can be expected to the live cells. We agree though that the partly reduced functionality of MyoF might be the reason for the consistent tendency of a lower overlap even though the difference is much less than indicated in the comment. We added "with a tendency for higher overlap with K13 which might be due to the partial inactivation of the GFP-tagged MyoF" to the sentence "IFA confirmed the focal localisation of MyoF and its spatial association with mCherry-K13 foci"

While we expect the fact that the difference between these parasites is only small somewhat reduces the "pinch of salt" with the MyoF line, we do agree that the partial functional inactivation of the GFP-tagged MyoF line may have some impact. However, we do not think that this means the results with the MyoF-GFP line are untrustworthy. On the contrary, it provides insights into its function that in some ways is equivalent to a knock down or TGD. Overall all the MyoF lines show: few vesicles occur in the MyoF-HA-line, more in the MyoF-GFP line and even more after knock sideways of MyoF-GFP. Importantly the severity of this phenotype correlates with the growth rates in these lines. Hence, together with the bloated food vacuole assays, this provides consistent data indicating that MyoF has a role in the transport of HCC to the FV and its level of activity correlates with the number of vesicles and growth. To better highlight this, it is now summarised in Figure 1M.

24) Line 219: the authors state here that they could not detect MyoF-GFP in rings, when in Figure 2C they show MyoF-GFP in rings, and also show that they could detect MyoF in Sup Fig. 3B with the 3xHA tagged line. Is this a labelling mistake in Figure 2C? If the authors could indeed not see MoyF-GFP in rings, this statement should have been made when Figure 2A was presented, and not so late in the manuscript, which causes confusion.

We thank the reviewer for pointing this out. We now provide a detailed time course (see also previous points) which shows that there is no detectable MyoF-GFP signal during ring stage development until the stage where the parasites starts the transition to trophozoites (i.e. MyoF-GFP signal could only be observed in parasites already containing hemozoin). In addition to the extended time course in Figure 1C (previously 2C) we included a panel of example ring stage images below to further highlight this. We also changed the labelling of the parasite with MyoF-GFP signal the reviewer mentions in Figure 1C to “late ring stage” (it already contains hemozoin) to clarify this.

The description of Figure 1A is now changed to: (line 153) *“The tagged MyoF was detectable as foci close to the food vacuole from the stage parasites turned from late rings to young trophozoite stage onwards, while in schizonts multiple MyoF foci were visible (Figure 1A, S2A).” *

Please see our answer to major comment #45 where we provide an explanation for the difference between MyoF-3xHA and MyoF-GFP signal in ring stage parasites.

[Figure MyoF]

25) Line 237: Showing a DNA marker (DAPI, Hoecht) for Figure 2E, and subsequent figures using mislocalisation to the nucleus, would help the reader assess efficiency of the mislocalisation.

Please see response to major comment #64 for a detailed answer on why we did not include DNA staining in the imaging used to assess mislocalization upon knock-sideways.

26) Line 254-256: authors should show the results of the bloating assay for parental 3D7 parasites (+ and - rapalog) to see whether the MyoF line - rapalog has increased baseline bloating. This applies to all subsequent FV bloating assays.

We did do several controls for bloated assays (including +/- rapalog of an irrelevant knock sideways line as well as using a chemical insult for which the control was 3D7 without treatment) in previous work (Birnbaum et al., 2020), which indicated that there is no effect of rapalog to reduce bloating. Although these controls are more stringent, we nevertheless did a 3D7 +/- rapalog control and added this to the manuscript (Figure S2I). As it is not possible to do this side by side with the assays that are already in the manuscript and the +/- rapalog 3D7 cells consistently showed no or very low numbers of cells without bloating (and stringent controls in the past equally did not show an effect), we believe adding this control once suffices.

27) Line 254-257: The authors say that because fewer parasites show a bloated food vacuole upon inactivation of MyoF it means that less hemoglobin reached the food vacuole. I understand the authors statement, however, shouldn't they look at the size of the food vacuole, instead of the number of parasites with bloated FV, to make such a statement? This has been done for KIC12 so why not doing it for MyoF?

This was now done and is provided as Figure 1J-K, S2J. The results confirm the assessment scoring bloated vs non-boated food vacuoles.

28) Line 259-261: these results would be difficult to interpret namely because the authors have dying parasites, which is exacerbated with the protein being knocked sideways. The authors should mention the pitfalls their knock sideways and tagging design here. Line 260-261: RSA is an assay relying on measuring parasite growth 1 cycle after a challenge with ART for 6 hours.

Fortunately, this concern is unfounded, as the survival (measured by parasitemia after one cycle) of the same sample + and - DHA is assessed, isolating the DHA effect independent of potential growth defects which are cancelled out. Hence, if there were parasites dying in the MyoF line (please note that they might not actually die, but simply grow more slowly), this factor applies for both the + and - ART condition. As we are testing for a decreased susceptibility to ART which would manifest as an increased survival in RSA surfacing above 1%, antagonistic effects of reduced MyoF function and ART treatment would not result in detectable differences as without effect, the RSA survival is always close to zero.

The same applies for the knock sideways where we assess the survival of +rapalog between +ART and -ART. If the reduced MyoF activity of the knock sideways leads to a decreased survival, this applies to both +ART and -ART. Please also note that rapalog was lifted after the DHA pulse (see e.g. Figure S2K).

That effects on growth are cancelled out is nicely illustrated for proteins where there is a stronger and more rapid effect on growth upon their conditional inactivation. For instance when KIC7 is knocked aside, there is a considerable increased of RSA survival, even though continued inactivation of KIC7 would have a severe growth defect (Birnbaum et al., 2020). Vice versa, a growth defect alone does not result in reduced RSA susceptibility as evident from knock sideways of an unrelated protein or using a chemical insult (Figure 4H in (Birnbaum et al., 2020) or simply slowing the ring stage by e.g. reducing EXP1 levels (Mesén-Ramírez et al., 2019). Hence, a growth reduction is not expected to alter the RSA outcome. And even if it did, it would only lead to an underestimation of the readout if growth is too severely affected (which would be obvious in the + rapalog without DHA sample, which was not the case).

In that respect it is valuable to have the rapid kinetics of knock sideways which permit inactivation of a protein before severe growth defects occur (although the only partial responsiveness of MyoF clearly is not the most optimal). In contrast, the absolute loss of a gene (as is the case if diCre is used) prevents (or at least makes it extremely difficult as the timing would need to exactly hit sufficient protein reduction without killing the parasite until the end of the RSA) using this system in these experiments (again see (Mesén-Ramírez et al., 2021) where in a EXP1 diCre based knock out RSA was only possible because we complemented with a lowly, episomally expressed EXP1 copy to have parasites with only a partial phenotype to do this assay).

29) Line 261-263: the authors sate that MyoF has a function in endocytosis but at a different step compared to K13 compartment proteins. I am not sure what they mean here. Can this be clarified?

The different steps in endocytosis are explained in the introduction and we now tried to further clarify this (line 98). “So far VPS45 (Jonscher et al., 2019), Rbsn5 (Sabitzki et al., 2023), Rab5b (Sabitzki et al., 2023), the phosphoinositide-binding protein PX1 (Mukherjee et al., 2022), the host enzyme peroxiredoxin 6 (Wagner et al., 2022) and K13 and some of its compartment proteins (Eps15, AP2µ, KIC7, UBP1) (Birnbaum et al., 2020) have been reported to act at different steps in the endocytic uptake pathway of hemoglobin. While inactivation of VPS45, Rbsn5, Rab5b, PX1 or actin resulted in an accumulation of hemoglobin filled vesicles (Lazarus et al., 2008; Jonscher et al., 2019; Mukherjee et al., 2022; Sabitzki et al., 2023), indicative of a block during endosomal transport (late steps in endocytosis), no such vesicles were observed upon inactivation of K13 and its compartment proteins (Birnbaum et al., 2020), suggesting a role of these proteins during initiation of endocytosis (early steps in endocytosis).“

VPS45 has not apparent spatial connection to the K13 compartment but the fact that MyoF does - and its inactivation also results in vesicle accumulation - indicates that it is downstream of vesicle initiation, providing the first connection from the initiation phase to the transport phase. More evidence for these different steps of endocytosis has been published in a recent preprint from our lab, where we simultaneously inactivated a protein of both “endocytosis steps” (Sabitzki et al., 2023).

To clarify this in the results as requested, we changed the statement to: (line 256) “Overall, our results indicate a close association of MyoF foci with the K13 compartment and a role of MyoF in endocytosis albeit not in rings and at a step in the endocytosis pathway when hemoglobin-filled vesicles had already formed and hence is subsequent to the function of the other so far known K13 compartment proteins.”

30) Do the authors mean that it is involved in endocytosis but not in ART resistance? If so, this is a very difficult statement to make since the parasites are dying. Is there any evidence of point mutations in MyoF in the field?

We split this point to address all issues raised here. Please see response to point 29 which clarifies that this was meant in a different way and our response to point 28 which explains why the dying parasite issue is not expected to affect the RSA (please also note that we do not have evidence of actually dying parasites in the MyoF-2xFKBP-GFP-2xFKBP line, most likely the growth is slowed).

The mutation issue is interesting. In fact evidence exists that MyoF mutations may be associated with resistance (Cerqueira et al., 2017) (please note that there it is still called MyoC) but in a recent preprint from our lab we did not find any evidence for a significantly changed RSA survival in 12 tested mutations in the corresponding gene (Behrens et al., 2023).

To clarify this we added the following statement to the discussion (line 709): "Of note, mutations in myoF have previously been found to be associated with reduced ART susceptibility (Cerqueira et al., 2017), but 12 mutations tested in the laboratory strain 3D7 did not result in increased RSA survival (Behrens et al., 2023)*. *

31) Line 298: the authors state that there is no growth defect in the first cycle when rapalog is added to the KIC11 line, however based on Figure 3D, there is evidently a 25% reduction in growth compared to - rapalog at day 1 post treatment, and a 60% reduction by day 2, which is still within the 1st growth cycle. The authors should either revise their statement or provide an explanation for these findings. The authors should also explain why their Giemsa data in Fig. 3E is not in accordance with their FACS data.

We think there is a misunderstanding here, as our figure legend was not detailed enough and we apologise if this had been misleading. The growth effect is restricted to invasion or possibly the first hours of ring stage development (see point 4&5, reviewer 2), which in asynchronous cultures more rapidly takes effect as the culture also contains schizonts that immediately generate cells that re-invade but can't due to inactivation of KIC11 (due to the rapid action of the knock sideways, KIC11 is already inactivated). In contrast, in highly synchronous cultures, this effect can only be evident once the parasites reached the schizont stage (starting with rings this takes close to 2 days). We now clarify that Figure 2E (previously Figure 3D) shows growth data obtained with an asynchronous parasite culture, while in Figure 2F the growth assay is performed with tightly synchronized (4h window) parasites as stated in the Figure legend.

We now explicitly state in each Figure legend and for each growth experiment throughout the manuscript whether we used asynchronous or synchronized parasites for growth assays.

Related to this, the incorrect y-axis label of what is now Figure 2E mentioned in major comment #58 is now corrected.

32) Line 301: KIC11 could also be important very early for establishment of the ring stage for example for establishment of the PV. Also, was mislocalisation assessed in rapalog-treated parasites at 72 hours or in cycle 3?

This is a valid point and this has now been addressed. We performed an invasion/egress assay revealing similar schizont rupture rates, but significantly reduced numbers of newly formed ring stage parasites (Figure 2H, S3G), indicating an effect of KIC11 inactivation either on invasion or possibly the first hours of ring stage development. A very similar point was raised by Reviewer 2, please see reviewer 2; major comment #4. This is now also reflected in line 302, which now reads: ”… indicating an invasion defect or an effect on parasite viability in merozoites or early rings but no effect on other parasite stages (Figure 2F-H, Figure S3F-G).”

We further included an assessment of mislocalization 80 hours after the induction of knock-sideways by addition of rapalog in Figure S3E which showed mislocalization of KIC11 to the nucleus.

33) Line 311: the authors should change the sentence from 'not related to endocytosis' to 'not related to endocytosis or ART resistance'.

Done as suggested.

34) Line 323-325: Authors say that a nuclear GFP signal can be observed in early schizonts for KIC12. According to the pictures provided in Figure 4A and Figure S5A it is not very obvious. Also faint cytoplasmic GFP signal could only be background as we can see that exposure is higher for schizont pictures

We changed the sentence (line 339) to: “…nuclear signal and a faint uniform cytoplasmic GFP signal was detected in late trophozoites and early schizonts and these signals were absent in later schizonts and merozoites (Figure 3A, Figure S4A,B).” in order to emphasize that the nuclear signal disappears early during schizont development.

35) Line 326-328: The authors say that kic12 transcriptional profile indicate mRNA levels peak (no s at peak) in merozoites. Should they show live cell imaging of merozoites then? Because from the Figure 4A schizont pictures where schizonts are almost fully segmented no signal can be observed.

The observation that mRNA levels of early ring stage expressed proteins tend to increase already in mature schizonts and merozoites is well established (e.g. (Bozdech et al., 2003)). A very good example for this are exported proteins of which most show a transcription peak in schizonts but the proteins are only detected in rings see e.g. (Marti et al., 2004). Hence, our observation for KIC12 is quite typical.

We originally did not include merozoites, as in the last row of Figure 3B fully developed merozoites within a schizont with already ruptured PVM are shown and no GFP signal can be detected in these parasites. We now provide images of free merozoites in Figure S4A-B showing again no detectable GFP signal.

We thank the reviewer for pointing out the typo, "peak" has been corrected.

36) Line 347: The authors state that using the Lyn mislocaliser the nuclear pool of KIC12 is inactivated by mislocalisation to the PPM. This tends to suggest that only the nuclear pool of KIC12 is mislocalised. How is it possible that only the nuclear pool is mislocalised?

The Lyn mislocaliser is at the PPM which is continuous with the cytostomal neck where the K13 compartment likely is found. The effect of the Lyn mislocalizer on the KIC12 protein pool localizing at the K13 compartment is therefore somewhat unclear. For this reason we already had the following statement in the original submission (line 400): “Foci were still detected in the parasite periphery and it is unclear whether these remained with the K13 compartment or were also in some way affected by the Lyn-mislocaliser.” We would like to stress here that the same does not apply to the nuclear mislocaliser, which is only a trafficking signal delivering KIC12 to the nucleus and hence likely does not affect the nuclear pool of KIC12, only the K13 compartment pool (the main interest of this manuscript).

We realised that the statement towards the end of this paragraph was unnecessarily ambiguous in regards to the K13 compartment pool of KIC12 which might have caused some confusion about the function of this pool of KIC12 and therefore modified it to (line 374): "Due to the possible influence on the K13 compartment located foci of KIC12 with the Lyn mislocaliser, a clear interpretation in regard to the functional importance of the nuclear pool of KIC12 other than that it confirms the importance of this protein for asexual blood stages is not possible. In contrast, the results with the nuclear mislocaliser indicate that the K13 located pool of KIC12 is important for efficient parasite growth.". It is also important to note that this limitation does not apply to the NLS knock sideways in regard to the K13 compartment and that the endocytosis function of this pool of KIC12 seems solid which with this statement is enforced.

37) Line 368-369: Effect was also only partial for MyoF. Why didn't you measure the same metrics for MyoF?

This was now done and is provided as Figure 1J-K, S2J, confirming our previous interpretation, see also point #27 which raises the same point.

38) Line 379: you don't know if all proteins acting later in endocytosis will have an increased number of vesicles as a phenotype

This is based on our current definition as stated in the introduction. It assumes a directional vesicular transport of hemoglobin to the food vacuole where inhibition of early stages will prevent transport before HCC-filled autonomous vesicular containers have formed and entered the cell. In contrast later inhibition stops such containers from further transport, leading to their accumulation. Such an accumulation is visible after VPS45-inactivation and other proteins (Jonscher et al., 2019; Mukherjee et al., 2022; Sabitzki et al., 2023) or treatment with cytochalasin D (Lazarus et al., 2008). While it is possible that there may be smaller intermediates formed at the K13 compartment that later on unite or fuse with the compartment evident after VPS45 inactivation and these might be missed due to small size (i.e. inhibition of a step between K13 compartment and an early endosome or equivalent), this would still be upstream of the VPS45 induced containers and hence would be earlier. We therefore believe that based on the framework given in the introduction (see also (Spielmann et al., 2020)) to assume that a phenotype manifesting as reduced food vacuole bloating without formation of detectable vesicles likely signifies inhibition of the process early whereas reduced bloating but with vesicles signifies inhibition later in the process.

39) Line 413-414: The authors state that no growth defect was observed upon KS of 1365800. Is growth alone enough to say that there is no impact on endocytosis?

This is an interesting point. The endocytosis proteins we studied so far indicate that efficient impairment of endocytosis manifests as a severe growth defect. Hence, lack of a growth defect can be assumed to be an indicator for absence of an important role for endocytosis (or any other growth relevant process). Clearly there is a gradual response, such as seen in the different MyoF versions resulting in proportional growth and vesicle appearance phenotypes. Hence, a protein with a minor role might have slipped our attention but then it probably is also not a very important protein in endocytosis.

To further strengthen our assessment of PF3D7_1365800 importance for asexual blood stage development, we now also generated a cell line expressing the PPM Mislocalizer, enabling knock sideways to the PPM. This was done because this protein consistently has a focus at the nucleus that may be within the nucleus. Again this revealed no growth defect upon inactivation (Figure S7D).

40) Line 432: in this section, the authors state that KIC4 and KIC5 seem to have domains that may suggest these proteins are involved in endocytosis, based on the alpha fold data that is publicly available. Considering the authors have TGD-SLI versions of these lines (Birnbaum et al. 2020) and have already confirmed in this previous publication that they confer resistance to ART; it would make sense to look at endocytosis for these genes. This would be a relatively simple and straightforward experiment, taking no longer than two to three weeks, and would require no additional reagents or line generation. Doing these experiments would add a lot more weight to this final section. The authors later state that KIC4 and 5 are TGD lines, so not the best for endocytosis assays. It is unclear why this would be difficult to do if an adequate control is contained in the experiment (such as parental 3D7). It explains why they did not perform the MCA2 endocytosis assays further up, but in my opinion, an attempt at doing these assays is important and would significantly increase the impact of this paper. Identical as major comment #17.

As stated in the manuscript and above, we were originally hesitant to do these assays due to the fact that we can't induce inactivation which is less ideal than comparing the identical parasite population split into plus and minus and is further complicated by the likely smaller effect as the TGDs still permitted growth. However, we see the point of the reviewer and now performed these assays using 3D7 as controls and taking extra care to account for stage differences between the TGD lines and 3D7. However, there was no significant difference in the bloated food vacuole assays with these cell lines. Due to the reasons mentioned in major point 17, we are not sure this indeed means these proteins have no role in endocytosis. One possible reason why we were able to obtain these TGDs may have been because the effect on endocytosis is less than in the essential proteins (or is ring stage specific) and in a TGD an endocytosis defect may therefore not be detectable with our assays (see details and further possible explanations in response to point 17).

In an attempt to address the TGD issue, we generated knock sideways cell lines for KIC4 and KIC5. Unfortunately, the mislocalization of KIC5 to the nucleus was inefficient (see figure below). As this did not result in a growth defect (in contrast to the clear KIC5-TGD growth defect (Birnbaum et al., 2020)), this line is not suitable to study a potential role of this protein in endocytosis. Therefore, we performed the bloated food vacuole assay only with KIC4-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser parasites. However, this revealed no effect on HHC uptake, which is in line with the normal growth of KIC4-TGD parasites (Birnbaum et al., 2020) and suggests that this protein could only have a minor or redundant role in endocytosis (it is the line that shows the smallest effect in RSA). As the KIC4 and KIC5 knock sideway lines did not permit any conclusions, we did not include them into the revised manuscript but they can be found here:

[Figure KIC4 knock sideways & KIC5 knocksideways]

Figure legend: (A) Live-cell microscopy of knock sideways (+ rapalog) and control (without rapalog) KIC4-2xFKBP-GFP-2xFKBPendo+ 1xNLS mislocaliser parasites 4 and 20 hours after the induction of knock-sideways by addition of rapalog. Scale bar, 5 µm. Relative growth of asynchronous KIC4-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser plus rapalog compared with control parasites over five days. Three independent experiments were performed. Growth of knock sideways (+ rapalog) compared to control (without rapalog) KIC4-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser (blue) or KIC5-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser (red) parasites over five days. Mean relative parasitemia ± SD is shown. (B) Live-cell microscopy of knock sideways (+ rapalog) and control (without rapalog) KIC5-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser parasites 4 and 20 hours after the induction of knock-sideways by addition of rapalog. Scale bar, 5 µm. Growth of asynchronous KIC5-2xFKBP-GFP-2xFKBPendo+ 1xNLSmislocaliser plus rapalog compared with control parasites over five days. Four independent experiments were performed. __(C) __Bloated food vacuole assay with KIC4-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser parasites 8 hours after inactivation of KIC4 (+rapalog). Cells were categorized as with ‘bloated FV’ or ‘non-bloated FV’ and percentage of cells with bloated FV is displayed; n = 3 independent experiments with each n=19-30 (mean 21.4) parasites analysed per condition. Representative DIC are displayed. Area of the FV, area of the parasite and area of FV divided by area of the corresponding parasites were determined. Mean of each independent experiment indicated by coloured symbols, individual datapoints by grey dots. Data presented according to SuperPlot guidelines (Lord et al., 2020); Error bars represent mean ± SD. P-value determined by paired t-test. Area of FV of individual cells plotted versus the area of the corresponding parasite. Line represents linear regression with error indicated by dashed line.

41) Line 490-493: the authors state that the K13 compartment proteins fall in two groups, some that are involved in ART resistance AND endocytosis, and some that have different functions. However, in this manuscript the authors have demonstrated 3 flavours that K13 compartment proteins can come in: • Some that confer ART resistance and are involved in HCCU (MCA2) • Some that are involved in HCCU but not ART resistance (MyoF & KIC12) • Some that are involved in neither (KIC11) The authors should therefore revise this statement.

We agree that this was not well phrased. To account for the fact that not all endocytosis proteins confer increased RSA survival to the parasites when inactivated we changed this statement (line 604): "This analysis suggests that proteins detected at the K13 compartment can be classified into at least two groups of which one comprises proteins involved in endocytosis or in vitro ART resistance whereas the other group might have different functions yet to be discovered.“

Generally, we believe that endocytosis is the overarching criterion and we therefore would like to keep the definitions of the main groups (endocytosis or not). As indicated by the title, the focus of the manuscript is on the K13 compartment for which so far endocytosis is the only experimentally associated function. That this group contains proteins that do not confer reduced ART susceptibility when conditionally inactivated (KIC12 and MyoF) is explained by their stage-specificity, making this a subgroup of the overarching endocytosis group.

We realise that with the endocytosis data on the KIC4, KIC5 and MCA2 TGD there is now also a subgroup we were unable to demonstrate an endocytosis effect in trophozoites although they show changes in RSA survival. However, as indicated above, we would be hesitant to fully exclude some role of these proteins in endocytosis in rings. Particularly as a comparably small reduction in endocytosis protein activity or abundance is sufficient to increase RSA survival (Behrens et al., 2023). A principal classification of "endocytosis or ART resistance" or "neither endocytosis nor ART resistance" still accounts for this and therefore seems to us to be the most useful, particularly also in light of our domain identification that then can be linked with one or the other group.

42) Line 508: the authors state that they expanded the repertoire of K13 compartments, when in fact they functionally analysed them - they did not do another BioID to identify more candidates.

We respectfully disagree with the reviewer in this point, we did expand the repertoire of known K13 compartment proteins. Only independently experimentally validated proteins from proximity biotinylation experiments can be considered part of the K13 compartment (or any other cellular site or complex). Without validation of the location, the identified proteins can only be considered candidates. This is highlighted in this manuscript by the finding that several proteins of the list did not localize at the K13 compartment.

43) Line 570-572: has anyone ever tested whether CytoD or JAS treatment in rings, is sufficient to mediate ART resistance? Something similar to what was done in PMID 21709259 with protease inhibitors. If not this would be a pretty interesting experiment for the authors to do that could shed more light on the MyoF data. It would take maybe 2 weeks to do and not require the generation of any new lines. This would clarify whether other Myosins other than MyoF are involved in endocytosis, as is suggested by previous publications (PMID: 17944961).

We now included this experiment. In agreement with a lacking need of MyoF in rings and no effect on RSA survival, there was no increased survival of the parasites in RSA (neither on 3D7 nor on K13 C580Y parasites) after cytD treatment (new part in Figure 1M). We thank the reviewer for pointing out that this experiment might also inform on whether other myosins influence endocytosis in ring stages. We added (line 250): “Similarly, also incubation with the actin destabilising agent Cytochalasin D (Casella et al., 1981), had no effect on RSA survival in 3D7 or K13C580Y (Birnbaum et al., 2020) parasites, indicating an actin/myosin independent endocytosis pathway in ring stage parasites (Figure 1M) and speaking against other myosins taking over the MyoF endocytosis function in rings.”

44) Line 608: inhibitors targeting the metacaspase domain of MCA2 may inadvertently inactivate other essential parts of the protein. They authors should acknowledge this possibility in the text.

The inhibitors used in the cited studies (Kumari et al., 2018) are validated metacaspase inhibitors, such as Z-FA-FMK (Lopez-Hernandez et al., 2003). Activity against the other parts of PfMCA2 - which apart from the MCA domain shows no homology to other proteins - is therefore unlikely.

45) Line 624-625: the authors state that MyoF is 'lowly expressed in rings' - indeed this is the case in their MyoF-2xFKBP-GFP-2xFKBP line which the authors established has defects due to the tag, but it appears from their MyoF-3xHA tagged line that it is expressed in rings. The authors should therefore revise their statement, and be careful of making claims based on their defective line and using fluorescence imaging as their only metric. If they do want to make the statement that it is not there in rings, they should also do a western blot, which is much more sensitive since it amplifies the signal compared to an image of one parasite.

This comment is related to major point #24. We also would like to stress that while the MyoF-GFP line already shows a phenotype, the impression of defectiveness based on its location is due to a mix up (see major point #23).

We now provide a comprehensive time course of the MyoF-GFP signal (Figure 1C, S2A) showing that there is no detectable MyoF-GFP signal until the transition from ring to trophozoite stage. As this is all under the endogenous promoter, we do not think the partial functional inactivation of the tagging is the reason for the absence of the signal. If anything, we would have expected adding a stably folded structure such as GFP to increase the stability of the protein. The main reason for the discrepancy of MyoF signal in rings between the GFP-tagged line (of note there is also no detectable MyoF-GFP signal in MyoF-2xFKBP-GFP ring stage parasites (Figure S2B)) and the HA-tagged line likely is that IFA is much more sensitive than live GFP detection (similar to the high sensitivity the reviewer mentions in regards to WB). This discrepancy therefore is likely due to the fact that the lowly expressed MyoF only become apparent with the HA-tagged line due to the IFA. We therefore believe that MyoF is 'lowly expressed in rings' is an appropriate description of our results obtained with three different cell lines (MyoF-2xFKBP-GFP-2xFKBP, MyoF-2xFKBP-GFP and MyoF-3xHA). We hope this is sufficiently well reflected in the manuscript where we write ‘a low level of expression of MyoF in ring stage parasites.’ not that it is ‘not there in rings’ (line 174).

46) Line 635: arguably this is the 3rd variety and not the 2nd (the authors already mentioned 2 types - ones that are involved in HCCU AND ART and those involved in HCCU only). See comment for line 490-493 above.

See response for major comment #41, we now consistently used "or" instead of "and". See line 490-493 how this was resolved for what previously was line 635.

47) Line 785: Bloated food vacuole assay/E64 hemoglobin uptake assay method specify that a concentration of 33mM E64protease inhibitor was used. However, in reference 44, cited in the manuscript, a concentration of 33µM E64 was used. Please confirmed if this is just a typo or if 1000x E64 concentration was used which renders the experiment invalid.

We thank the reviewer for pointing this out, we corrected this typo and will look out for symbol font conversion errors for the resubmission.

48) Line 788: it is unclear from this section what is considered a bloated food vacuole - is there an area above which the FV is considered bloated? Do the authors do these measurements manually or use an addon in FIJI/ImageJ? What is the cutoff for if a FV is bloated? Please clarify. Additionally, for the representative images + rapalog for Figures 2H and 4H, it would be useful to see where the authors delineate the FV (add a white circle showing what is actually measured).

The bloated FV assay is well established (Jonscher et al., 2019; Birnbaum et al., 2020; Sabitzki et al., 2023). Although the bloating of the FV is a human judgment call, it is actually quite obvious: bloating appears as an easily spotted bulging of the FV in DIC. As also minor bloating is scored as 'bloated', it is a very conservative assay. Using an-add on to measure this is not straight forward. It is unclear how this bulging effect of the FV in DIC could be spotted by a software and due to the obviousness to human operators, potentially lengthy and complicated efforts to design appropriate machine learning options were not undertaken. The situation faced by the scorer of the assay is evident from Figure S4F-G which contains close to 50 "on rapalog" cells and close to 50 control cells, giving representative cells from all replicas of bloated FV assays with KIC12. Please note that these images shows the most complicated situation as far as bloated assays go, because the phenotype is not 100% (see Figure 3F) compared to e.g. KIC7 inactivation which leads to lack of bloating in almost all cells (see (Birnbaum et al., 2020) Figure 3E) but nevertheless the difference is still obvious. We are aware that in such situations (less than absolute inhibition) this assay scoring of "yes" or "no" is a surrogate for the actual level of inhibition and may be more subjective. This is why in this case we also did the FV size measurements (which are less dependent on human judgment) to further support this and give a better quantifiable measure. Of note, the bloated food vacuole judgments are done "blinded", i.e. the examiner does not know which sample they are looking at.

In response to this reviewer's point we now also added the FV size refinement of the assay for MyoF inactivation which is one of the cases where inhibition of bloating is not in 100% of the cells (see major comment #27). Please also note here the advantage of the rapidly acting knock sideways technique for these assays which shows the sum of effect 8 h after initiating inactivation and for which we carefully control size of the cells which shows that there is no significant growth reduction over the assay time, excluding secondary effects due to a generally reduced viability. Compared to slower acting systems suggested to have been used instead (see introductory part and significance of this review), the rapid speed of knock sideways reduces the risk of potential pleiotropic or compensatory effects due to the time needed for proteins to be depleted if the gene or mRNA is targeted instead.

The suggestion to include a ‘white circle’ (raised also as minor comment#27) is useful as an aid to see the food vacuole. However, in contrast to the Figures in (Birnbaum et al., 2020) (where we did add such a circle), we here included the DHE staining images in the figure, labelling the parasite cytosol which readily shows the FV (the FV corresponds to the region where there is no DHE staining). As this shows the position of the FV we would prefer to not obscure the DIC images with additional features to permit the reader to see the difference between bloated or non-bloated food vacuoles and keeping the image as natural as possible.

49) Line 863-864: this sentence seems to be out of place.

We thank the reviewer for pointing this out, the details of nucleus staining were moved to the correct part.

50) Line 875: the authors state that there is a light blue wedge, when the circle consists of grey and black wedges. Please revise this.

This has been corrected.

51) Line 1059-1061: it is unclear whether the individual growth curves are different clones or whether they are just the same experiment repeated? If it is the latter, then why are they not combined, as is traditionally done?

These are the individual replicates of the growth curves shown in Figure 1G of the same cell lines done on a different occasion. We always try to show as much of the primary data as possible and believe that showing individual data points from the different experiments is better than only the combined values which obscure the actual course of each experiment.

52) Line 919-924: the authors mention a blue and red line, but there is only a black line in figure 3D. Moreover, the experiment of using the LYN mislocaliser was only done for KIC12 according to the manuscript. Additionally, the y axis of the figure states relative growth day 4[%] compared to rapalog, but then on the x axis there are several days. In the text it says there is no growth defect until the second cycle, but from this graph it appears the growth defect is evident as early as 1 day post rapalog treatment. Can the authors please clarify and correct the issues pointed out.

We thank the reviewer for pointing this out, this was due to a copy & paste error in the figure legend that was now amended. We also fixed the incorrect axis label. For the last part (growth defect) please see detailed answer to Major comment#31 raising the same concern for KIC11 (in synchronous parasites the defect only takes effect once the cells reached the relevant stage whereas in asynchronous cultures there are always cells in the relevant stage that due to the rapid effect of the knock sideways already have a growth phenotype).

53) Figure 1 panel B & C: the label of the figure where the signal from MCA2Y1344STOP-GFP is shown with the DAPI signal overlayed is deceptive since it suggests that this is the signal of full length MCA2. Please change the label of this panel from MAC2/DAPI to MCA2Y1344STOP/DAPI. The same is true for Panel C for the image labeled MCA2/K13 - please change this to MCA2Y1344STOP/K13.

Done as requested.

54) Figure 2B: what stages are these parasites? Please state this in the figure. Based on the MyoF pattern, it looks like rings in the upper panel and trophs in the bottom pannel. Why were schizonts not shown?

Both are trophozoites (early trophozoite in top panel and late trophozoite in bottom panel). This is now labelled in what now is figure 1B. As stated above, schizont stages are less relevant for the topic of this manuscript and in order to prevent the manuscript from getting more disjointed and keeping it more focussed on the main topic, we decided to not include a schizont in the manuscript. Nevertheless, we included an example image below.

[Figure MyoF_p40px schizont]

55) Figure 2D&F: it is not very meaningful when growth assays are shown as a final bar after 4 days of growth. It is much more useful and informative to see a growth curve instead (as is shown in the supplementary), since it shows if the defect is apparent in the first growth cycle or later. With the way the data is currently shown, this is not apparent. I would advise the authors to switch the graph in 2F out of a combined graph of all the biological replicates growth curves for S3D - showing error bars.

While we in principle fully agree with the reviewer in showing the course of the full experiment (which is available in Figure S2E), the key here is to show the overall difference. Hence, we would like to keep this comparison of the overall effect on growth in what now is Figure 1E and G. It is part of the argument to the doubts this reviewer raises to the function of MyoF (mainly in the overall assessment and the significance statement) to show that the phenotype is actually very consistent (partial inactivation through tagging or further inactivation using knock sideways increases endocytosis phenotypes, correlating with parasite viability).

Please also note, that the growth curves upon knock sideways shown in Figure 1G, S2E are performed with asynchronous parasite cultures, which doesn’t allow us to draw direct conclusions about growth cycle effects.

Nevertheless, we now also included the suggested combined data representation in Figure S2E.

56) Figure 3: why were the calculation of FV area, parasite area and FV/parasite area only done for KIC12 and not done for MyoF? It would be interesting to see if any of these values are different for MyoF - whether the parasites are smaller in area and therefore FV smaller. Please present them Figure 2. Images should be already available and would not require further experiments to be done, only the analysis.

This now has been done (confirming our results) and is included as Figure 1J-K, S2J. This point was also raised as major comment #37, please also see detailed answer there.

57) Figure 3B: why is there no spatial association assessment for KIC11 and K13 as was done for the MCA2 and MyoF? The authors should show a pie chart showing the degree of association here as was done for the other proteins.

This is now included in Figure 2C.

58) Figure 3D: The y axis of the figure states relative growth day 4[%] compared to rapalog, but then on the x axis the experiment takes place over several days. Is this a typo in the y axis? Additionally, the authors state in line 287-290 that the growth defect upon addition of rapalog is only seen in the second cycle, but from this graph it appears the growth defect is already evident 1 day post rapalog addition. The figure legend also does not make sense for this figure since it mentions a blue and a red line, when there is only a black line present. The legend also mentions the LYN mislocaliser which was used for KIC12 not KIC 11 (see above).

We apologise for the inadequate legend and colour issues, this was amended. This point was also raised in major comment #31 and #52, please find detailed answer there.

59) Figure 3E: the colour for Control and Rapalog 4 hpi are very similar and very hard to discern. Please choose an alternative colour or add a pattern to one of the samples. The y axis is also missing a label. Is this supposed to be parasitemia (%)?

We thank the reviewer for pointing this out, the missing label is now included and the colour has been adapted to make them better distinguishable.

60) Figure 4A: the ring shown in this figure does not appear to be a ring (it is far too large and appears to have multiple nuclei?). Do the authors have any other representative images to show instead?

This is in fact a ring, but we realize that we accidentally included an incorrect size bar in the ring image of Figure 4A (now Figure 3A) (size bar for 63x objective instead of the correct one for the 100x objective), we apologise for this oversight. We don’t think this parasite has multiple nuclei, instead the Hoechst signal shows the often elongated nucleus seen in rings that can appear as two foci in Giemsa stained smears which leads to the typical diagnostic feature of P. falciparum rings in diagnostics. In order to exclude any doubts about the nuclear localization of KIC12 in rings, we here attached a panel with more examples of KIC12-2xFKBP-GFP-2xFKBP ring stage parasites.

[Figure KIC12]

61) Figure 4B: why is there no spatial association assessment for KIC12 and K13 as was done for the MCA2 and MyoF? The authors should show a pie chart showing the degree of association here as was done for the other proteins. This should be done for the different life cycle stages considering the changing localisation of KIC12.

This is now provided in Figure S4A. As suggested by the reviewer, we independently quantified the association for ring stage, early trophozoite and late trophozoites stage. As there is no KI12 signal in schizonts, we did not include a quantification for this stage.

62) Figures 4C&E: it is extremely important to show the DNA stain in both these samples considering that a portion of KIC12 is in the nucleus! Please add the DAPI signal for these figures (as for all other figures!).

Please see major comment #64 for a detailed answer why we did not include DNA staining in the imaging used to assess mislocalization upon knock-sideways.

63) Figure 4E: this figure should be presented before 4D (considering the line being presented in 4E is used in an experiment in 4D). The authors should switch the order of these two.

We see the point the reviewer is raising here, Figure 4D (now Figure 3D) also contains the data with the Lyn mislocaliser while we first talk about the NLS mislocaliser. This permits a better comparison between the two mislocaliser lines. However, first explaining the Lyn-mislocaliser and then going back to the NLS would make it rather complicated for the reader to follow the storyline and therefore we would like to keep the order as it is. We realise that this means the reader has to go back one figure part for seeing the Lyn growth data, but believe this is worth the benefit that the data is there compared to the NLS result.

64) It is unclear why in many of the fluorescence images the authors do not show the DAPI signal - particularly when colocalising with K13 and when doing the knock sideways experiments. Please add these images to the figures - I would assume they have already been taken, so would simply involved adding the images to the panel.

We did not include DNA staining (DAPI or Hoechst) for any of the images used to assess the efficacy of mislocalization, as we would prefer to keep the parasites as representative of a viable parasites in culture as possible. Hence they were imaged without DNA stain (these stains are toxic). We would like to point out that a DNA stain is not necessary, as the mislocaliser already marks the nucleus (in the case of the NLS mislocaliser), actually even somewhat more accurately, as it fills the entire nuclear space rather than only the DNA which is marked by DAPI or Hoechst.

For LYN this admittedly is not the case, there the mislocaliser marks the plasma membrane. However, we think the proper control for efficient mislocalisation is the comparison between the GFP-tagged protein of interest and the mCherry mislocaliser to show mislocalisation, as previously done in our lab (e.g. (Birnbaum et al., 2017; Jonscher et al., 2019; Birnbaum et al., 2020)).

Due to their toxicity, we also avoided nuclear staining in some other parts of the manuscript when we were of the opinion that a nucleus signal was not necessary.

65) Throughout the manuscript, there is no western blot confirming the correct size of their modified proteins. This should be provided.

We did perform Western blot analysis for both MCA2 cell lines. MCA2 is the only gene-product for which we generated a disruption for this work, and together with the severe truncation from previous work, we provided a Western blot-based confirmation of the correct size.

The MCA2 disruptions are at least partially dispensable for in vitro parasite growth, hence if degradation occurred, this might not have been noticed. In that case we considered it relevant to show that the truncations were of the expected size. The other proteins in the main figures are essential for growth. Hence, if the tagging approach would lead to unexpected changes in protein integrity (which we assume is what was intended by this concern to be assessed with a Western blot), the parasites expressing the tagged MyoF, KIC11 and KIC12 would - due to their importance for asexual blood stage development - not have been obtained. Hence, we can assume the integrity of the tagged protein is very unlikely to have been affected in a functionally relevant way.

66) None of the figures are appropriate for individuals with colour blindness, limiting their accessibility to the paper. Please change the colour schemes for all fluorescent images using magenta/green or an alternative colour combination appropriate for colourblind individuals.

We thank the reviewer for this comment. This has now been amended, individual channels of fluorescence microscopy images are now shown in greyscale, while the overlay was changed to green/magenta.

Minor Comments

1) line 29: remove 'are'.

Done.

2) Line 29: the text says "HCCU is critical for parasite survival but is poorly understood, with the K13 compartment proteins are among the few proteins so far functionally linked to this process." The sentence should be: 'HCCU is critical for parasite survival but is poorly understood, with the K13 compartment proteins among the few proteins so far functionally linked to this process."

Done.

3) line 44: remove 'the'

Done.

4) Line 48: consider mentioning here that malaria is caused by the parasite Plasmodium - otherwise the first mention of parasite in line 52 is confusing for the non-specialist reader.

Done.

5) Line 49: estimated malaria-related death and case numbers are from the 2021 WHO World malaria report. You cite the 2020 WHO World malaria report.

We now cite the newest WHO report.

6) Line 53: please insert the word 'have' between now and also.

Done.

7) Line 54: please change 'was linked' to is linked

Done

8) Line 72: I would specify that free heme is toxic to the parasite. Especially as you mention that hemozoin is nontoxic.

Sentence would be "where digestion results in the generation of free heme, toxic to the parasite, which is further converted into nontoxic hemozoin"

Done.

9) Line 90: authors should either say "in previous works" or "in a previous work"

The text has been altered to say: “ in a previous work”.

10) Line 91: "We designated these proteins as K13 interaction candidates (KICs)"

Done.

11) Line 95: please change 'rate' to number

Done.

12) Line 109: Please include a coma before (ii).

Done.

13) Line 112: as shown by Rudlaff et al in the paper you are citing, PPP8 is actually associated with the basal complex. You can say that "(ii) were either linked or had been shown to localise to the inner membrane complex (IMC) or the basal complex (PF3D7...).

Done.

14) Line 114: Protein PF3D7_1141300 is called APR1 in the manuscript but ARP1 in Supplementary Table 1. Please correct.

Done.

15) Line 131: please define SNP - this is the first use of the acronym.

Done.

16) Line 133-134: South-East Asia instead of "South Asia"

Done.

17) Line 135: please explain what TGD is - it is referred to over and over again in the manuscript without ever being explained.

We apologise for this oversight. We now explain what is meant with TGD at the suggested point of the manuscript.

18) Line 145: change 'Western blot' to western blot - only Southern blot is capitalised since it is named after an individual, while the other techniques are not.

To the best of our knowledge this issue has not been resolved, some Journals capitalize the “W” (e.g. Science), while others don’t (e.g. Nature). We would prefer to continue to capitalize the “W”, as this is consistent with the original publication from (Burnette, 1981), but if there are strong objections, we would be happy to change this____.

19) Line 152: add "the" between 'and spatial'

Done.

20) Line 158: please define SLI as selected linked integration, since it is the first use of the acronym.

Done.

21) Line 178: introduce a coma after protein. Sentence should be "Proliferation assays with the MCAY1344STOP-GFPendo parasites which express a larger portion of this protein, yet still lacking the MCA domain (Figure 1), indicated no growth ...

Done.

22) Line 195: the authors could mention that MyoF was previously called MyoC in the Birnbaum 2020 paper. I wanted to check back in the Birnbaum 2020 paper and could not find MyoF

Good point, this was done.

23) Line 200: "Expression and localisation of the fusion protein was analysed by fluorescent microscopy". Why expression was not analysed also by western Blot same as for MCA2?

Please see major comment #64 for a detailed answer.

24) Line 204: I could not find any mention of MyoF (Pf3D7_1329100) in reference 65. Please remove reference 65 if not correct. Also reference 66 looks at Plasmodium chabaudii transcriptomes so I would specify that "This expression pattern is in agreement with the transcriptional profile of its Plasmodium chabaudii orthologue"

Reference 65 (Wichers et al., 2019) provides an RNAseq transcriptome dataset for asexual blood stage development of 3D7 (originating from the same source as the 3D7 used in this study). While Ref 66 (Subudhi et al., 2020) indeed contain transcriptomic data from P. chabaudi, the authors also provide a nice 2h window RNAseq transcriptome dataset for asexual blood stage development of Plasmodium falciparum. Both datasets are therefore suitable as reference for the statement about myoF transcription pattern. Both datasets are also easily accessible and show the pattern in a graph in PlasmoDB.

25) Line 208: Please indicate a reference for P40 being a marker of the food vacuole

Done.

26) Line 220-224: The authors should consider changing to " Taken together these results show that MyoF is in foci that are mainly close to K13 and, at times, overlapping, indicating that MyoF is found in a regular close spatial association with the K13 compartment."

The suggested wording introduces "mainly" for "frequently" and likely was in part motivated by the discrepancy in location between cell lines that we hope we now could clarify to be only minor (see major point #23). We therefore think the original wording appropriately summarises the findings (line 178): “*Taken together these results show that MyoF is in foci that are frequently close or overlapping with K13, indicating that MyoF is found in a regular close spatial association with the K13 compartment and at times overlaps with that compartment.” *

27) Line 255: In Figure 2H, and subsequent figures showing bloated FV assay, I would delineate the food vacuole with dashed line as in Birnbaum et al. 2020 to help the reader understanding where the food vacuole is.

In contrast to the Figures in Birnbaum et al. 2020, we here included the DHE staining (parasite cytosol) in images of bloated FV assays which visualizes the FV. We therefore decided to avoid any further marking, to keep the image as unprocessed as possible (see also major point 48).

28) Line 265-266: Here the title says that KIC11 is a K13 compartment associated protein, but the title of Figure 3 says KIC11 is a K13 compartment protein. I noticed that you make the difference between K13 compartment protein et K13 compartment associated protein for MyoF for example which is not clearly associated with the K13 compartment. Which one is it for KIC11?

The interpretation of the reviewer is correct, we indeed graded this subconsciously based on level of overlap. Based on the newly added quantification shown in Figure 2C, we describe KIC11 now as K13 compartment protein.

29) Line 309-310: indicate a reference for your statement "which is in contrast to previously characterised essential K13 compartment proteins".

Done, we now included Birnbaum et al. 2020 as reference for this.

30) Line 377: Figure 4I, please correct 1st panel Y axis legend

Done.

31) Line 404: replace "dispensability" with dispensable

Done.

32) Line 416: can the authors provide any speculation as to why they observed these proteins as hits in the BioID experiments?

As some of these proteins were less well or less consistently enriched, they could be background of the experiment. Alternatively, some could be proteins that only transiently interact with the K13 compartment.

33) Line 451: Where the "97% of proteins containing these domains also contain an Adaptin_N domain and function in vesicle adaptor complexes as subunit a" come from. Do you have a reference?

The statement now includes references and reads (with small changes to original submission): "More than 97% of proteins containing these domains also contain an Adaptin_N (IPR002553) domain (Blum et al., 2021) and in this combination typically function in vesicle adaptor complexes as subunit α (Hirst and Robinson, 1998; Traub et al., 1999) (Figure 5D) but no such domain was detectable in KIC5."

34) Line 465-467: the same could be said for KIC4 as it also has a VHS domain.

The critical issue is the combination of domains and their position within the protein. While KIC4 also contains a VHS domain, the VHS domain in KIC4 is N-terminal, not in a central position and it is also not the first structural domain to be identified in KIC4. The similarity to adaptin domains was already described ((Birnbaum et al., 2020) and annotated in PlasmoDB) and these domains are also involved in vesicle formation and trafficking. These aspects of the statement can therefore not be extended to KIC4. With regards to VHS domains being involved in vesicle trafficking, this is already stated in line 538: «KIC4 contained an N-terminal VHS domain (IPR002014), followed by a GAT domain (IPR004152) and an Ig-like clathrin adaptor α/β/γ adaptin appendage domain (IPR008152) (Figure 5A-C, Figure S8). This is an arrangement typical for GGAs (Golgi-localised gamma ear-containing Arf-binding proteins) which are vesicle adaptors first found to function at the trans-Golgi (Dell’Angelica et al., 2000; Hirst et al., 2000).»

35) Line 477-479: Can be rephrased to "However, we found this protein as being likely dispensable for intra-erythrocytic parasite development and no colocalisation with K13 could be demonstrated, suggesting a limited role for PF3D7_1365800 in endocytosis. Or something like that. Makes it clearer.

We rephrased this sentence and it now reads (line 592): “However, we found this protein as being likely dispensable for intra-erythrocytic parasite development and no colocalisation with K13 was observed, suggesting PF3D7_1365800 is not needed for endocytosis“.

36) Line 535: Have AP-2a or AP-2b been shown to be at the K13 compartment?

AP2m is at the K13 compartment (Birnbaum et al., 2020). Adaptor complexes are heterotetramers and their subunits do not typically function on their own and this is conserved across evolutionarily distant organisms. In agreement that this is also the case in P. falciparum, Henrici et al. (Henrici et al., 2020a) showed that both, AP-2a and AP-2b, were present in an AP2µ Co-IP, indicating that the AP2 complex consist of the ‘classical’ subunits in P. falciparum. Therefore, the presence of all subunits at the K13 compartment is very likely, although this has only been experimentally confirmed for AP2µ. Of note, for Toxoplasma gondii the presence of AP-2a and AP-2b at the micropore has been experimentally confirmed (Wan et al., 2023; Koreny et al., 2023) and interaction suggested by presence in the same IP as DRPC (Heredero-Bermejo et al., 2019).

37) Line 569: reference 43 is wrong

We thanks the reviewer for pointing this out – we removed Ref 43.

38) Line 746: typo "ot" instead of or.

Changed.

39) Line 801: method for Domain Identification using AlphaFold specify that RMSDs of under 5Å over more than 60 amino acids are listed in the results. However, there is a typo in Figure 5B for KIC5 where it says "RMSD 4.0 Å over 8 aa". Please correct.

Done. In addition, we have now applied a more stringent cut-off of 4Å over more than 60 amino acids to ensure a higher reliability of our hits. This decision was based on results from our preprint (Behrens and Spielmann, 2023). Because of this the phosphatase domain in KIC12 is no longer included in this manuscript and accordingly the following sentence has been deleted. “In KIC12 we identified a potential purple acid phosphatase (PAP) domain. However, with the high RMSD of 4.9 Å, the domain might also be a divergent similar fold, such as a C2 domain, which targets proteins to membranes.”

40) Line 856: In Figure 1E, please use the same Y axis legend as in Figure 2D "relative growth at day 4 [%] compared with 3D7"

Done.

41) Figure S1: Some PCR gels check for integration are presented as 5', 3' and ori whereas other gels are presented as ori, 5' and 3'. This is confusing.

We agree that ideally the order of sample loading should be consistent and we apologise for this. The explanation for this is that these gels were run by different people at different times before we were able to better standardize the loading scheme. However, in the interest of not unnecessarily using resources for something that has a similar meaning, we would prefer not to repeat these PCRs and re-run them only for consistency reasons (as the conclusion is not affected by the different loading schemes).

42) Figure S1: Why was the expression of only MCA2 was verified by Western blot? What about the other proteins?

See response to major comment 56.

43) Line 493: Considering KIC11 was not involved in HCCU or ART resistance it might be worth mentioning in this section that it is of note that there are no domains detected that would be involved in endocytosis.

We agree that this is the case, however it is also the case for all other proteins that either are not involved in endocytosis and/or lowered susceptibility to ART. We therefore now added a summary statement addressing this in line 602: “In contrast, the K13 compartment proteins where no role in ART resistance (based on RSA) or endocytosis was detected, KIC1, KIC2, KIC6, KIC8, KIC9 and KIC11, do not contain such domains (Figure 5E).” We did not add this at the suggested part of the manuscript as at that point the domain search results are not yet introduced and doing this each time for all the individual proteins would disconnect the flow of the manuscript.

44) Line 503-506: is it wise to generate more drugs that target a pathway that is already highly susceptible to mutations? The authors should add a statement explaining how this might be avoided.

The only protein for which mutations do not have a large fitness cost is K13 (see also our preprint on fitness cost of ubp1 mutation (Behrens et al., 2023) and even with K13 the level of resistance seems to be limited by amino acid deprivation when endocytosis is reduced (Mesén-Ramírez et al., 2021). We therefore do not think that this pathway is particularly prone for mutations. Further, the number of commercial drugs targeting the "endproduct" of endocytosis (hemoglobin digestion and detoxification of heme) highlight it as the most prominent vulnerability for drug-based intervention if we go by number of commercially available drugs acting on things associated with a single process.

45) Throughout, scale bars are stated in the figure legends at the end of the legend. This is a slightly confusing format. The authors should consider stating the scale bar for each sub-legend where a fluorescence image is taken.

Done.

** Referees cross-commenting**

After reading reviewer 2 and 3's comments, I think there are significant overlaps in the key points raised in terms of questions about fusion proteins and their potential partial mis-localisation, better descripton of results and target selection. Overall I think we agree that the work has potential, but in its current form does not represent a major advance. It would be immensely helpful if the manuscript would be carefully edited for a better flow and linear description of results.

We now rearranged the manuscript for better flow but would like to highlight that the many requests for smaller experimental issues (and "better description of results") worked somewhat in the opposite way of a more linear description. We hope the rearranged version acceptably balances these two issues. The issues raised in regards to target selection and potential partial mis-localisation are addressed in our responses mainly to this reviewer. Please also see comments on systems used at the end of the rebuttal.

Reviewer #1 (Significance (Required)):

The authors set out to test whether other proteins that are in the vicinity of K13 are involved in mediating ART resistance and endocytosis. This is an interesting question. However, other than MCA2 which was already known to be involved in mediating ART resistance (and was not tested for its involvement in endocytosis), none of their candidate proteins seem to be involved in mediating both these functions. The authors show that the other proteins tested appear important for parasite growth, with KIC12 and MyoF involved in mediating endocytosis. While these findings are novel, the KS approach used by the authors casts some doubt over the findings, and would mean that these findings would have to be re-tested with a more reliable approach, such as the GlmS system or generating a conditional knockout using the DiCre system. Despite not advancing our understanding of ART resistance, or identifying further players involved in this process, this manuscripts provides two candidates that are involved in mediating endocytosis and a further candidate that appears to be important for parasite growth. Further work on these proteins will be required to understand their exact roles. As stated above, there is currently limited interest for these results (limited to researchers working on endocytosis in apicomplexan parasites and possibly the wider endocytosis field from an evolutionary perspective), however with further work, this could increase the impact and interest of this work substantially.

The authors do not describe any novel methods/approaches within this work.

In the significance statement the reviewer indicates that other systems would have been more reliable for the work here. This is addressed in our response above and in a detailed considerations on the properties of conditional inactivation systems at the end of the rebuttal. The systems used in this work were not only chosen because they permit rapid targeting of many different proteins, but because they have merits that are beneficial for our assays. In fact many of the functional assays in this manuscript are difficult or impossible to carry with the suggested conditional inactivation systems (please note that we have extensive experience with the systems considered preferable:

• DiCre (Birnbaum et al., 2017; Mesén-Ramírez et al., 2019; Mesén-Ramírez et al., 2021; Wichers et al., 2022; Kimmel et al., 2023)

• glmS (Wichers et al., 2021c; Wichers et al., 2021a; Wichers et al., 2022; Wichers-Misterek et al., 2023)).

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

In a previous publication the Spielmann lab identified the molecular mechanism of ART resistance in P. falciparum by connecting reduced levels of the protein K13 to decreased endocytosis (uptake of hemoglobin from the RBC cytosol), which results in reduced ART susceptibility. Using quantitative BioID the authors further identified proteins belonging to a K13 compartment, highlighting an unusual endocytosis mechanism.

In the present manuscript the authors follow up on this work and closely examine ten more proteins of the K13/Eps15-related "proxiome". They successfully link MCA2 to ART resistance in vitro, while the proteins MyoF and KIC12 are involved in endocytosis but do not confer in vitro ART resistance when impaired. They further characterize one candidate (KIC11) that partially colocalizes with K13 in trophozoites but to a lesser degree in schizonts. Growth assays suggest an important function for KIC11 in late stages of the intraerythrocytic developmental cycle. Five analyzed proteins however do not colocalize with the K13 compartment, while a sixth was refractory to endogenous tagging.

Using AlphaFold predictions of the KIC protein structures the author identify domains in most constituents of the K13 compartment, highlighting vesicle trafficking-related features that were not identified on primary sequence level before.

The combination of functional data together with structure predictions leads them to propose a refinement of the K13 compartment as being divided into proteins participating in endocytosis and proteins that have an unknown function.

We thank the reviewer for the assessment of the manuscript and the constructive comments.

Major comments:

1) -Table 1 is missing

We apologise for this mistake; Table 1 is now included.

2) -Lines 117-123: Given the total list of uncharacterized candidates encompasses 13 proteins, can the author gives the reason why only the top 10 and not all 13 were characterized in this study?

A similar point has been raised by Reviewer 1 in major comment #12, please see our response there for an explanation why we chose which targets.

3) -Line 174: 20% of observed MCA2 foci show no overlap with K13 and 21% only partially overlap, can the author confirm that the observed MCA2 foci in schizonts are the ones that co-localize with K13. (Addition of a schizont stage image in Fig 1C would be sufficient).

We now extended Figure 4C with images of MCA2-Y1344STOP-GFP+mCherryK13 parasites covering the schizont and merozoite stage, showing that the majority of the MCA2 foci in schizonts are also mCherry-K13 positive.

4) -The localization and observed phenotype of KIC11 is interesting but unfortunately the authors do not explore it further. Does KIC11 localize with markers of e.g. the secretory organelles (micronemes or rhoptries) in schizonts and could therefore be involved in RBC invasion?

While we intended to focus mainly on the endocytosis aspect of these proteins, we see the reviewer's point and now generated new cell lines enabling assessment of spatial association of KIC11 with markers for rhoptry (ARO), micronemes (AMA1), and inner membrane complex (IMC1c). This revealed that the KIC11-GFP signal in schizonts does not overlap with apical organelle markers and the signal does not resemble a typical apical localization. In addition, we assessed all three organelle markers after inactivating KIC11 by knock sideways which showed that KIC11 inactivation has no apparent effect on the appearance of these markers, suggesting no major alterations in schizont morphology in respect to apical markers. These results are now presented as Figure S3A and in line 304 of the results.

5) Can the author distinguish if KIC11 is involved in RBC invasion or in establishment of the ring-stage parasite?

In order to look into this, we performed egress/invasion assays, quantifying schizont and ring stage parasites in tightly synchronized parasites at two different time points (pre-egress: 38-42 hpi & post-egress: 46-50 hpi). This revealed a significant decrease in newly formed ring stage parasite per ruptured schizont in parasites with inactivated KIC11, while the egress efficacy remained unaffected. This indicated an invasion or very early ring stage development defect (new Figure 2H, Figure S3G). To further determine at which point exactly the phenotype occurs (ie during invasion or early after invasion) would require extensive experimentation that goes beyond the scope of this study (e.g. invasion assays using video microscopy with a representative number of parasites or sophisticated flow based quantification assays). We hope by excluding egress and gross changes of apical organelles as well as no indication for similar number of early rings (indicating it is invasion or a very early ring-establishment phenotype) will sufficiently narrow down the phenotype for labs interested in invasion to more definitely answer this question.

Minor comments:

1) Table S1: Please add the criterion for the order of proteins (abundance in "proxiome"?) in the table as a separate column. I would also suggest adding a new column that highlights the 10 proteins investigated in this study as I found the color-coding slightly confusing.

Done as suggested: we now include the “average log2 Ratio normalized Kelch13” values from the four DiQ-BioID experiments performed with K13 in (Birnbaum et al., 2020), as well as the suggested column to highlight the investigated proteins. Please also see reviewer 1 major point # 12 for additional information on the selection criteria and how this was added to the manuscript.

2) -154-155: There is a discrepancy between the text and Fig1C regarding the % of partial overlapping and non-overlapping foci.

We thank the reviewer for pointing this out, this was corrected.

3) -The y-axis label is missing in Fig 3E

Done.

4) -Fig 4I left graph, the superscript 2 is missing in μm2

We thank the reviewer for pointing this out, this is now changed.

5) -Did the author colocalize KIC11 in schizonts with other proteins found in the K13 compartment group of proteins not involved in endocytosis/ART resistance? This may help to further subgroup these proteins.

This is an interesting point but would actually be technically challenging to do. For this we would need to generate a KIC11endo parasite line for each of these KICs and then do co-localisation in schizonts. However, the outcome of this likely would not be very clear. The reason for this is as follows. There are foci of KIC11 that do overlap with K13 in schizonts. One can expect that these foci show KIC11 at the K13 compartment and that the other KICs would overlap with KIC11 in these K13 foci in schizonts. Hence, we would also need to see K13 to find the non-K13 compartment KIC11 foci and see if these contained the KIC of interest. This is technically challenging because it would mean we would need a third fluorescent protein which is not that trivial to do. Due to the difficulty to do this and the large amount of work involved and the already considerable amount of data in this manuscript, we believe this will be better suited for a different study.

6) -As a general comment: to make the beautiful IFAs more accessible to a broader readership, I would encourage the authors to switch the color-coding to green/magenta/blue or an equivalent color system or add grayscale images.

This was done as suggested, all fluorescence images are now provided as greyscale images and the overlays are shown in magenta/green.

Reviewer #2 (Significance (Required)):

Characterizing the molecular components involved in Plasmodium endocytosis will not only reveal interesting biology in these highly adapted parasites, but will more importantly lead to a better understanding and potentially open new avenues for intervention of ART resistance. The here presented manuscript is a carefully executed follow-up on previous work done in Dr. Spielmann's lab focusing on the K13 compartment. The authors use established assays to characterize novel components and reveal three new players in endocytosis with one mediating ART resistance in vitro. The proposition that parts of the K13 compartment have a function other than endocytosis is interesting, but will have to await more data from future studies. Taken together this manuscript adds significantly to our understanding of endocytosis in P. falciparum.

This work is of interest for cell and molecular biologists working on Apicomplexa, but especially for the Plasmodium community.

We thank the reviewer for this positive assessment.

I am a cell and molecular biologist working on Toxoplasma gondii

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

Summary: The authors characterized 4 proteins from P. falciparum via cellular (co-)localization, endocytosis, parasite growth, and artemisinin resistance assays. These proteins have been identified as candidates for Kelch13 compartment and a possible role in endocytosis in their previously work with quantitative BioID for potential proximity to K13 and Eps15 (Birnbaum et al. 2020). In the current work, additional 6 proteins were not confirmed as being associated to the K13 compartment. This experimental work was complemented by an in-silico analysis of protein domains based on AlphaFold algorithm. For this protein structure evaluation all proteins were chosen, which were experimentally confirmed to be linked to the K13 compartment in the current publication and previous work. With the work 3 novel proteins linked to artemisinin resistance or endocytosis could be functionally described (KIC12, MCA2, and MyoF) and a number of hypotheses were generated.

We thank the reviewer for the assessment of the manuscript and the constructive comments.

Major comments:

The quality of the presented work is solid, the experimental design is adequate, and methods are presented clearly. The publication contains a lot of results both presented in text and in the figures and it is not always straight forward for the reader to follow the descriptions due to many details presented and a lack of context for some of these experiments.

We thank the reviewer for this overall positive assessment.

We now reordered the results section in an attempt to increase the flow of the manuscript. We also made changes to improve the context for the results. Given the further (very valid) requests for data on schizonts and invasion, there was an increased danger for a less linear manuscript that we hope to have acceptably managed with the re-arrange.

Specific suggestions for consideration by the authors to improve the manuscript. Abstract: 1) R 31: Mention how the 4 proteins were identified as candidates, you need to refer to previous work to clarify this

To clarify this the sentence was changed to (line 31): "Here we further defined the composition of the K13 compartment by analysing more hits from a previous BioID, showing that MyoF and MCA2 as well as Kelch13 interaction candidate (KIC) 11 and 12 are found at this site."

2) R38: "Second group of proteins" is confusing - different from the 4 mentioned above? Significance to endocytosis unclear. Please unify terminology in the manuscript, see also comment below on proxiome.

We changed the wording to clarify the group issue in the abstract as follows line 34: "Functional analyses, tests for ART susceptibility as well as comparisons of structural similarities using AlphaFold2 predictions of these and previously identified proteins showed that canonical vesicle trafficking and endocytosis domains were frequent in proteins involved in resistance or endocytosis (or both), comprising one group of K13 compartment proteins, While this strengthened the link of the K13 compartment to endocytosis, many proteins of this group showed unusual domain combinations and large parasite-specific regions, indicating a high level of taxon-specific adaptation of this process. Another group of K13 compartment proteins did not influence endocytosis or ART susceptibility and lacked detectable vesicle trafficking domains. We here identified the first protein of this group that is important for asexual blood stage development and showed that it likely is involved in invasion.”

3) Abstract can only be understood after reading the full publication

We attempted to amend this by expanding the abstract, particularly the changes highlighted in the previous two points.

Results: 4) Table 1 is missing from the submitted materials

We apologise for this mistake. Table 1 is now included.

5) Consider to shorten and stratify the result section to focus on the significant data

We rearranged the results in an attempt to streamline this section and are now starting with MyoF in the revised manuscript. However, as highlighted by the requests from reviewer 1, many details need to be available to support our conclusions. For instance the fact that GFP-tagging partially inactivated MyoF asked for further data to support our conclusion (HA-tagged version, showing that the location of the GFP-tagged version was consistent with the HA-tagged version, showing to what extent the different constructs affected growth and correlated with number of vesicles and bloating, see new figure 1M) or that KIC12 has two locations. Overall, we are therefore hesitant to remove data or description from the result part.

6) Unclear how the localization and functionalization assays might be impaired by the fusion proteins Significance of ART resistance assay is not clear, in presence of strong growth effects due to inactivation or truncation of genes/proteins

As indicated also in the example given in the previous point (this reviewer #5), the use of different cell lines (GFP-tagged live cells and small epitope tag in IFA) for targets with an indication for an effect of the tagging confirm that the location we assigned is reasonable. In the case of MyoF, the HA-tagged line, the partial inactivation due to GFP and the further inactivation in the GFP-tagged line by knock sideways show plausible increase of phenotypes (vesicle accumulation and bloated FV assays). Thereby the GFP-tagged line can be seen as a partial inactivation line that further supports our conclusions and overall this paints a consistent picture of the function of this protein in endocytosis (see new Figure 1M better illustrating this). Please note that the difference in location shown by this line compared to the HA-tagged proteins is only small (see also reviewer 1 major point 23ff). See also general discussion on tags at the end of this rebuttal.

Significance of ART resistance assay: The ‘ART resistance assay’ is done comparing +/- ART (DHA) in identical parasites (originating from the same culture and the same condition). Hence, any growth effects are cancelled out and effects in reducing ART susceptibility would - if at all - be underestimated (see more detailed response to point 28, reviewer 1 and controls in Birnbaum et al., 2020 where we tested an unrelated essential protein, unrelated chemical insult and rapalog on 3D7 and did not detect any effect on RSA survival).

MCA 7) Stratify results, order by significance of findings, it appears to be described in chronological order, improve readability/flow, eg ART resistance if mentioned in r138, but only reported in r183ff

We attempted to stratify, but then the reason for generating the partial MCA2 disruption parasite line becomes very arbitrary and would leave the reader wondering why we at all truncated the protein at two thirds of the protein. Hence, we do not see a way around this chronological reporting. However, this part is now not at the start of the experimental results section anymore, possibly making it overall a bit more palatable.

MyoF 8) R195 to 197 - consider moving to discussion as it is distracting here

This was shortened and additional information (asked for by reviewer 1, major point 22) to clarify that MyoF was previously called MyoC, was added (line 147): “The presence of MyosinF (MyoF; PF3D7_1329100 previously also MyoC), in the K13 proxiome could indicate an involvement of actin/myosin in endocytosis in malaria parasites. "

9) Term proxiome is introduced above, but not used in result section - suggest to unify language, eg r195 uses "K13 compartment DiQ-BioIDs" instead, which is not very convenient for the reader

We carefully reviewed this and made this more consistent.

10) What is the enrichment factor? Please provide for this and the following proteins, eg in Table 1

The enrichment factor is log2 enrichment over control and this is now provided in table S1 (see also detailed answer for Reviewer 1 major point 12).

11) R225 to 243 - overall significance of the growth experiments with mislocaliser is not clear, consider removing from manuscript or explain relevance more clearly

See also point 28, reviewer 1: This experiment is actually quite important. It shows that if we conditionally inactivate the GFP-tagged MyoF, the growth is further reduced, as stated in line 208. It might have been confusing that the mislocalisation is only partial, but this is equivalent to a partial knock down and hence is useful. This becomes even more relevant with the specific assays following in the next paragraph: while the tagging of MyoF already resulted in vesicles, conditional inactivation with KS generated even more vesicles, showing that the same phenotype was rapidly increased when MyoF was further inactivated by a different means and this also correlated with growth. Hence, this is actually a very consistent phenotype that despite some shortcomings of the tools available to analyse this protein (due to the partial inactivation by the GFP tag) in our eyes looks very convincing. We now added a graph showing the correlation of growth and phenotypes to illustrate this (Figure 1L).

We also tried to make this clearer by changing line 200 to: “Hence, conditional inactivation of MyoF further reduced growth despite the fact that the tag on MyoF already led to a substantial growth defect, indicating an important role for MyoF during asexual blood stage development.” And line 208 to:“ This was even more pronounced upon conditional inactivation of MyoF by KS (Figure 1H), suggesting this is due to a reduced function of MyoF.”

12) KIC11/KIC12 Enrichment factor?

The enrichment (’average log2 Ratio normalized Kelch13 from Birnbaum et al. 2020’) is 1.65 for KIC11 and 1.32 for KIC12, which is now also explicitly shown in column D of Table S1.

** Referees cross-commenting**

I would like to applaud reviewer #1 for a great, very thorough review and lots of detailed suggestions. I agree with the conclusions mentioned in the significance evaluation from reviewer #1 and #2: the work presented does not contain novel methods and the scope is rather narrow with the current results. (I am working on clinical studies with novel antimalarial agents)

Reviewer #3 (Significance (Required)):

On the one hand side, the authors have wrapped up some of the remaining protein candidates of the K13 compartment and could verify 4 of 10 proteins. The work is of interest for the scientific community working on endocytosis and malaria drug resistance mechanisms. Overall, the conclusions and findings from the previous work, Birnbaum et al. 2020, could be confirmed and extended mainly using the methods previously described. On the other hand, the authors made use of progress in protein structure predictions and identified domains linking the K13 compartment proteins to putative functions. The overlaid protein folds of the newly identified domains in figure 5 look convincing, but I can't comment on the technical details or cut-off used for this in-silico analysis.

Extended general remarks on the systems used for this work:

Mainly reviewer 1 suggest (in the general comments and the significance statement) that other systems would have been better suited to use for this work, namely glmS and diCre and also has concerns about the large tag which is seconded by a comment of reviewer 3. In light of this we here provide some extended considerations on the properties for conditional systems and tagging in regards to the goals of this work.

We would like to point out that we do have experience with the systems considered better-suited by the reviewer (one of the first authors has extensively used glmS (Wichers et al., 2021c; Wichers et al., 2021a; Wichers et al., 2022; Wichers-Misterek et al., 2023) and our lab was one of the first to adopt the diCre system in P. falciparum parasites and we regularly us it (Birnbaum et al., 2017; Mesén-Ramírez et al., 2019; Kimmel et al., 2023)). Clearly, these methods have a lot of strengths but there are a number of issues to be considered for the assays we use in this work (see the next section on conditional inactivation systems). In a nutshell, we believe diCre would give a more reliable readout of the absolute level of "essentiality" (i.e. importance for growth) but is unsuitable or at least difficult to use for the assays that reveal the function of our interest in this work. GlmS basically combines the drawbacks of diCre and knock sideways and hence for most targets is not expected to give a better readout of level of "essentiality" but is similarly difficult to use for our specific assays. The fact that both of these systems are possible to use without adding a tag to the target may be an advantage but without tag one loses some very important features that can be critical to understand the outcome with a given system (see considerations on the tag further below).

Conditional inactivation systems:

1. __ speed of inactivation:__ glms acts on mRNA and diCre on the gene level, which makes them slower than techniques acting directly on the protein such as DD or KS. With diCre, mRNA and protein is still left, even if the gene is very rapidly excised. For instance for Kelch13 it takes 3-4 days after excising the gene until protein levels have waned enough that this manifests in a reduced growth (Birnbaum et al., 2017). While in some instances diCre permits same cycle analyses if the protein has a very rapid turn-over (e.g. Rab5a, (Birnbaum et al., 2017)), control in a few hours is still difficult. For vesicle accumulation and bloated food vacuole assays, which are done over comparably short time frames and with specific stages, it is rather challenging to hit the correct time of induction to have all the cells at the correct stage with suitably (and uniformly, ie all cells) sufficiently reduced target protein levels during the assay time. Slow acting systems are also more prone to secondary effects. The more immediate the inactivation, the closer it is to the core of the affected function. With vesicle trafficking processes this is particularly relevant as all vesicle trafficking in a cell is interconnected and there are always recycling pathways that maintain the membrane and protein homeostasis of individual compartments. Particularly for endocytosis there seem to be compensatory capacities at least in other organisms (see e.g. (Chen and Schmid, 2020)). One reason why knock sideways was developed is that it permitted to avoid compensatory changes when vesicle adaptors are inactivated (Robinson et al., 2010).

The comparably short time frame for malaria parasites to go through different stages during blood stage development also is an issue relevant for inactivation speed. The advantage of speed and the danger of obscured phenotypes is highlighted by our work on VPS45 which showed that in trophozoites this protein is involved in the transport of hemoglobin to the FV whereas in late stages it also has a role in secretory processes. Both of these functions we were able to specifically assess in the same growth cycle using KS to rapidly inactivate the protein (Bisio et al., 2020) but with a slower system would have been more complicated to dissect.

Speed of effect with glmS: unless the KS does not work well, glmS is slower acting than KS (it does not target the already synthesised protein which can remain in the cell) and also often suffers from only partial inactivation, hence the benefit of using it here is unclear. The option to have an untagged protein is a plus, however it also is a minus, as assessing efficiency (particularly in live cells e.g. for bloated assays etc a fluorescent tag is the only direct option to assess inactivation of target) is critical to ensure the phenotype manifests at the stage of interest.

lethality/absolute phenotypic effects are detrimental to some assays to study the functions we are interested in for this work: no RSA can be conducted, if the gene is lost and the parasites die. Again, with diCre, one could attempt to hit the point when the parasites have lost sufficient amounts of the target protein when they are placed under ART but then the parasites need to continue growing for ~3 days, which is not possible if the cKO is lethal except for very slowly turning over proteins. However, in that latter case, the parasites likely still had full functionality of the target protein at the beginning of the RSA, when the drug pulse happens and there would be no effect. Knock sideways solves these problems by permitting knock sideways inactivation only under ART (or with a few hours pre-incubation depending on the inactivation speed) to not yet affect growth in a severe manner but inhibiting the process the protein is involved in. It may be possible to use glmS for RSAs, but the slow speed would complicate it (it would not permit control of target protein levels in a matter of a few hours to inactivate the target protein and then re-install it).

None-absolute inactivation is also a strength for some functional assays. While we really like using diCre, in the case of EXP1 it made it necessary to complement the exp1 cKO parasites with low levels of EXP1 to be able to do functional assays without killing the parasites (Mesén-Ramírez et al., 2019; Mesén-Ramírez et al., 2021). While the lethality issue does not apply to glmS (like knock sideways, it also can be tuned), it is unclear what would be gained over knock sideways. Knockdown levels with glmS vary from gene to gene and cannot be predicted, it is in most cases considerably slower than KS, it requires glucosamine which becomes toxic at higher concentrations and might introduce off target effects and tracking protein levels during the assay would equally need GFP tagging.

Integration of properties of conditional systems

Given the above discussed properties, several factors have to be considered to be able to use a system for a given assay. Stage-specific transcription is one example. For diCre a protein not expressed in e.g. rings permits to remove the gene and the protein is never made in that parasite development cycle. We exploited this for instance for two proteins only expressed from the trophozoite stage onwards (Kimmel et al., 2023). However, if lethal (absolute effect problem), this also means one can also only see the phenotype on onset of expression of the target (e.g. if in mitosis, the first nuclear division in case the protein is absolutely essential for the process). This is just one example of such issues. Expression timing, turnover of the protein and homogeneity of stage-specific loss of protein will all influence how clearly the phenotype can be determined. All this will decide the exact time of loss/inactivation of the target protein to levels generating a phenotype and ideally therefore can be monitored during an assay (see considerations on tagging).

For these reasons vesicle accumulation or bloated food vacuole assays are difficult with slow systems as ideally the target should rapidly be inactivated at the trophozoite stage and the result monitored before the cells have moved to the schizont stage. For this a well responding knock sideways is ideal as the protein can be rapidly taken away (sometimes within seconds) to visualise the immediate, direct effect in the cell.

As shown for KIC11, there is also no disadvantage of using KS for proteins with other assays or proteins that result in different phenotypes. It permits stage-specific same cycle inactivation without having to worry about the turnover of mRNA and protein (Fig. 2F,G). Thus, besides the advantages of knock sideways for endocytosis related assays and RSAs, we also see no disadvantage of using knock sideways for the functional study of KIC11 which has a role other than endocytosis. KS also permits to specifically target the K13 pool of KIC12, something impossible or very difficult to do with other systems. Hence, we are of the opinion that the system for inactivation was adequate for most of the proteins analysed in this manuscript.

Large tag: we agree that GFP-tagging can be a disadvantage but in our opinion its benefits often outweigh the drawbacks because it permits easy and immediate (on individual cell level, if need be) monitoring of the presence/location of the target protein (e.g. after KS, but given the discrepancy of the timing between gene excision and protein loss, it might be even more important for techniques such as diCre). No fixing/permeabilisation (prone to artifacts, prevents immediate view of cells) to detect a target with specific antibodies or via a small tag is needed with GFP. Similarly, the use of Western blots to do this is time consuming and impractical if monitoring of left-over protein in the course of an assay such as a bloated food vacuole assay is needed.

In many cases, adding GFP has no negative effect. In addition, if the bulky folded structure of GFP is tolerated, it usually also tolerates the 2 to 4 12kDa FKBP domains in our standard tag. We also typically add a linker. This approach has worked for a large number of different proteins, including many essential ones for which we would not otherwise have obtained the integration cell lines (Birnbaum et al., 2017; Jonscher et al., 2019; Hoeijmakers et al., 2019; Birnbaum et al., 2020; Kimmel et al., 2023; Sabitzki et al., 2023). Hence, whenever a cell line is obtained with it, this tag in most cases is not a disadvantage. Admittedly an exception in this is MyoF and to some extent maybe MCA2 (we would like to stress that in the case of MCA2 the reason for not being able to obtain the full length tagged cell line is unclear: the protein can be severely truncated to less than 3% of its amino acid sequence and a GFP-tag is tolerated on the version with 2/3s of the protein left, which gives no good reason why the full length was not obtained; a potential reason could be a dominant negative effect). However, we obtained the full length with a small tag detected by IFA for both, MyoF and MCA2 and the location of these agreed well with the GFP tagged versions, indicating that the GFP-tagged versions are useful to show the location of these proteins in live cells.

There are also tricks to attempt monitoring the effect of e.g. diCre without tagging the target. For instance, if a fluorescent protein is connected to excision without actually being fused to the target (ie excision of the gene leads to its expression of e.g. GFP), which would avoid adding a tag to the target itself. However, the problem with this is that expression of GFP does only show excision, but mRNA producing the target protein and left over target protein may still be there in the cell. All in all, the GFP-tag on the target, while with some drawbacks, is still our preferred method to control to monitor the target protein in the cell (in principle permitting quantification of ablation efficiency on the individual cell level).

Conclusion on these considerations for this manuscript

Based on these considerations we do not see the immediate benefit of changing the system for the conclusions drawn from this study and are unsure if they are indeed better suited for this work as suggested. While a more exact readout of "essentiality" might be possible with the diCre system we are of the opinion this is less important than learning the function of a protein which - as outlined above - we believe to be considerably more difficult with diCre and even more so with glmS considering our target functions. The same applies to target specific cellular pools of a protein as done here for KIC12. Clearly MyoF is one example where the employed systems shows limitations, but with the new Figure part showing consistency in phenotype with degree of inactivation (importantly with two different forms of inactivation) and the clarification that the location of the GFP-tagged and HA-tagged versions are actually quite similar in location, we do not think employing an extra system is warranted for the conclusions of this work. Admittedly, the apparent lack of need in ring stags might give an opening to attack MyoF using diCre (by excision before its major expression peak), but depending on lethality this might preclude extended analyses (possibly vesicle assays, for sure not RSAs).

In the end the question is, if our approach provides the function of target analysed in this work and based on the data in our manuscript and the arguments in the rebuttal, we are reasonably confident that this is the case. It is not very likely the other mentioned techniques would result in a different conclusion on the function of the here studied proteins. In fact, we expect other commonly used techniques to be less suitable for the key assays in this work.

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Referee #3

Evidence, reproducibility and clarity

Summary:

The authors characterized 4 proteins from P. falciparum via cellular (co-)localization, endocytosis, parasite growth, and artemisinin resistance assays. These proteins have been identified as candidates for Kelch13 compartment and a possible role in endocytosis in their previously work with quantitative BioID for potential proximity to K13 and Eps15 (Birnbaum et al. 2020). In the current work, additional 6 proteins were not confirmed as being associated to the K13 compartment. This experimental work was complemented by an in-silico analysis of protein domains based on AlphaFold algorithm. For this protein structure evaluation all proteins were chosen, which were experimentally confirmed to be linked to the K13 compartment in the current publication and previous work. With the work 3 novel proteins linked to artemisinin resistance or endocytosis could be functionally described (KIC12, MCA2, and MyoF) and a number of hypotheses were generated.

Major comments:

The quality of the presented work is solid, the experimental design is adequate, and methods are presented clearly. The publication contains a lot of results both presented in text and in the figures and it is not always straight forward for the reader to follow the descriptions due to many details presented and a lack of context for some of these experiments.

Specific suggestions for consideration by the authors to improve the manuscript.

Abstract: - R 31: Mention how the 4 proteins were identified as candidates, you need to refer to previous work to clarify this - R38: "Second group of proteins" is confusing - different from the 4 mentioned above? Significance to endocytosis unclear. Please unify terminology in the manuscript, see also comment below on proxiome - Abstract can only be understood after reading the full publication

Results: Table 1 is missing from the submitted materials Consider to shorten and stratify the result section to focus on the significant data Unclear how the localization and functionalization assays might be impaired by the fusion proteins Significance of ART resistance assay is not clear, in presence of strong growth effects due to inactivation or truncation of genes/proteins

MCA Stratify results, order by significance of findings, it appears to be described in chronological order, improve readability/flow, eg ART resistance if mentioned in r138, but only reported in r183ff MyoF R195 to 197 - consider moving to discussion as it is distracting here Term proxiome is introduced above, but not used in result section - suggest to unify language, eg r195 uses "K13 compartment DiQ-BioIDs" instead, which is not very convenient for the reader What is the enrichment factor? Please provide for this and the following proteins, eg in Table 1 R225 to 243 - overall significance of the growth experiments with mislocaliser is not clear, consider removing from manuscript or explain relevance more clearly KIC11/KIC12 Enrichment factor?

Referees cross-commenting

I would like to applaud reviewer #1 for a great, very thorough review and lots of detailed suggestions. I agree with the conclusions mentioned in the significance evaluation from reviewer #1 and #2: the work presented does not contain novel methods and the scope is rather narrow with the current results. (I am working on clinical studies with novel antimalarial agents)

Significance

On the one hand side, the authors have wrapped up some of the remaining protein candidates of the K13 compartment and could verify 4 of 10 proteins. The work is of interest for the scientific community working on endocytosis and malaria drug resistance mechanisms. Overall, the conclusions and findings from the previous work, Birnbaum et al. 2020, could be confirmed and extended mainly using the methods previously described. On the other hand, the authors made use of progress in protein structure predictions and identified domains linking the K13 compartment proteins to putative functions. The overlaid protein folds of the newly identified domains in figure 5 look convincing, but I can't comment on the technical details or cut-off used for this in-silico analysis.

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Referee #2

Evidence, reproducibility and clarity

In a previous publication the Spielmann lab identified the molecular mechanism of ART resistance in P. falciparum by connecting reduced levels of the protein K13 to decreased endocytosis (uptake of hemoglobin from the RBC cytosol), which results in reduced ART susceptibility. Using quantitative BioID the authors further identified proteins belonging to a K13 compartment, highlighting an unusual endocytosis mechanism.

In the present manuscript the authors follow up on this work and closely examine ten more proteins of the K13/Eps15-related "proxiome". They successfully link MCA2 to ART resistance in vitro, while the proteins MyoF and KIC12 are involved in endocytosis but do not confer in vitro ART resistance when impaired. They further characterize one candidate (KIC11) that partially colocalizes with K13 in trophozoites but to a lesser degree in schizonts. Growth assays suggest an important function for KIC11 in late stages of the intraerythrocytic developmental cycle. Five analyzed proteins however do not colocalize with the K13 compartment, while a sixth was refractory to endogenous tagging.

Using AlphaFold predictions of the KIC protein structures the author identify domains in most constituents of the K13 compartment, highlighting vesicle trafficking-related features that were not identified on primary sequence level before. The combination of functional data together with structure predictions leads them to propose a refinement of the K13 compartment as being divided into proteins participating in endocytosis and proteins that have an unknown function.

Major comments:

• Table 1 is missing
• Lines 117-123: Given the total list of uncharacterized candidates encompasses 13 proteins, can the author gives the reason why only the top 10 and not all 13 were characterized in this study?
• Line 174: 20% of observed MCA2 foci show no overlap with K13 and 21% only partially overlap, can the author confirm that the observed MCA2 foci in schizonts are the ones that co-localize with K13. (Addition of a schizont stage image in Fig 1C would be sufficient).
• The localization and observed phenotype of KIC11 is interesting but unfortunately the authors do not explore it further. Does KIC11 localize with markers of e.g. the secretory organelles (micronemes or rhoptries) in schizonts and could therefore be involved in RBC invasion? Can the author distinguish if KIC11 is involved in RBC invasion or in establishment of the ring-stage parasite?

Minor comments:

• Table S1: Please add the criterion for the order of proteins (abundance in "proxiome"?) in the table as a separate column. I would also suggest adding a new column that highlights the 10 proteins investigated in this study as I found the color-coding slightly confusing.
• 154-155: There is a discrepancy between the text and Fig1C regarding the % of partial overlapping and non overlapping foci.
• The y-axis label is missing in Fig 3E
• Fig 4I left graph, the superscript 2 is missing in μm2
• Did the author colocalize KIC11 in schizonts with other proteins found in the K13 compartment group of proteins not involved in endocytosis/ART resistance? This may help to further subgroup these proteins.
• As a general comment: to make the beautiful IFAs more accessible to a broader readership, I would encourage the authors to switch the color-coding to green/magenta/blue or an equivalent color system or add grayscale images.

Significance

Characterizing the molecular components involved in Plasmodium endocytosis will not only reveal interesting biology in these highly adapted parasites, but will more importantly lead to a better understanding and potentially open new avenues for intervention of ART resistance. The here presented manuscript is a carefully executed follow-up on previous work done in Dr. Spielmann's lab focusing on the K13 compartment. The authors use established assays to characterize novel components and reveal three new players in endocytosis with one mediating ART resistance in vitro. The proposition that parts of the K13 compartment have a function other than endocytosis is interesting, but will have to await more data from future studies. Taken together this manuscript adds significantly to our understanding of endocytosis in P. falciparum.

This work is of interest for cell and molecular biologists working on Apicomplexa, but especially for the Plasmodium community.

I am a cell and molecular biologist working on Toxoplasma gondii

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Referee #1

Evidence, reproducibility and clarity

With the emergence and spread of resistance to Artemisinin (ART), a key component of current frontline malaria combination therapies, there is a growing effort to understand the mechanisms that lead to ART resistance. Previous work has shown that ART resistant parasites harbour mutations in the Kelch13 protein, which in turn leads to reduced endocytosis of host haemoglobin. The digestion of haemoglobin is thought to be critical for the activation of the artemisinin endoperoxide bridge, leading to the production of free radicals and parasite death. However, the mechanisms by which the parasites endocytose host cell haemoglobin remain poorly understood.

Previous work by the authors identified several proteins in the proximity of K13 using proximity-based labelling (BioID) (Birnbaum et al. 2020). The authors then went on to characterise several of these proteins, showing that when proteins including EPS15, AP2mu, UBP1 and KIC7 are disrupted, this leads to ART resistance and defects in endocytosis leading to the hypothesis that these two processes are inextricably linked.

In this manuscript, Schmidt et al. set themselves the task of characterising more K13 component candidates identified in their previous work (Birnbaum et al. 2020) that were not previously validated or characterised. They chose 10 candidates and investigated their localisations, and colocalisation with K13, and their involvement in endocytosis and in vitro ART resistance, 2 processes mediated by K13 and some members of the K13 compartments

The authors show that of their 10 candidates, only 4 can be co-localised with K13. Then, using a combination of targeted gene disruption (TGD) as well as knock sideways (KS), they characterised these 4 proteins found in the K13 compartment. They show that MyoF and KIC12 are involved in endocytosis and are important for parasite growth, however their disruption does not lead to a change in ART sensitivity. The authors also confirm the findings of their previous publication (Birnbaum et al. 2020), using a slightly different TGD, that MCA2 is involved in ART resistance, however they did not check whether its disruption impacts haemoglobin uptake. They also show that KIC11 is not involved in mediating haemoglobin uptake or ART resistance. To finish, the authors used AlphaFold to identify new domains in the proteins of the K13 compartment. This led them to the conclusion that vesicle trafficking domains are enriched in proteins of the K13 compartment involved in endocytosis and in vitro ART resistance.

The majority of the experiments conducted by the authors are performed to a good standard in biological and technical replicates, with the correct controls. Their findings provide confirmation that their 4 candidate genes seem to be important for parasite growth, and show that some of their candidates are involved in endocytosis. While the KD and KS approaches employed by the authors to study their candidate genes each have their own advantages and can be excellent tools for studying a large sets or genes, this manuscript highlights the many limitations of these approaches. For example, the large tag used for the KS approach can mislocalise proteins or disrupt their function (as is the case for MyoF), resulting in spurious results, or indeed the inability to generate the tagged line (as is the case for MCA2). The KS approach also makes the results of a protein with a dual localisation, like KIC12, extremely difficult to interpret.

Moreover, the manuscript is disjointed at times, with the authors choosing to conduct certain experiments for only a subset of genes, but not for others. For example, considering that the aim of this paper was to identify more proteins involved in ART resistance and endocytosis, it is confusing why the authors do not perform the endocytosis assays for all their selected proteins, and why they do not do this for the proteins they identify in their domain search. There is significant room for improvement for this manuscript, and a generally interesting question. But in it's current format, other than confirming that MCA2 is involved in ART resistance (which was already known from the Birnbaum paper), the authors do not further expand our understanding of the link between ART resistance and endocytosis in this manuscript.

Major Comments

line 31: please change defined to characterised - defined suggests that novel proteins were identified in this study, which is not the case.

line 37: please change 'second' to "another". As explained further below, the authors identified 3 classes of proteins (confer ART resistance + involved in HCCU, involved in HCCU only, or involved in neither).

Line 40: You define KIC11 as essential but according to your data some parasites are still alive and replicating 2 cycles after induction of the knock sideways. Please consider changing "essential" to "important for asexual parasite growth"

Line 40: please change 'second group' to 'this group'

line 41: state here that despite it being essential, it is unknown what it is involved in.

Line 50: the authors should state here that there is actually a reversal in this trend over the last few years.

Line 54: please separate out the references for each of the two statements made in this line (a: that ART resistance is widespread in SEA, and b: that ART resistance is now in Africa) Reference 14 also seems to reference ART resistance in Amazonia - which is not covered by the statement made by the authors (in which case the authors should state ART is now present in Africa and South America). The authors should also reference PMID: 34279219 for their statement that ART resistance is now found in Africa (albeit a different mutation to the one found in SEA).

Line 65: it is also worth mentioning here that there are other mutations in proteins other than K13, such as AP2mu and UBP1 (PMID: 24994911;24270944) that can lead to ART resistance.

Line 80, 86: ref 43 is misused. Reference 43 refers to Maurer's clefts trafficking which takes place in the erythrocyte cytosol and is not involved in haemoglobin uptake as far as I know. Please replace ref 43 with one showing the role of actin in haemoglobin uptake.

Line 98: the authors state here that they 'identified' further candidates from the K13 proxiome. This suggests that they identified new proteins in this paper, when in fact the list was already generated in ref 26. All they did was characterise proteins from that list that were not previously characterised. The authors should therefore remove identified from this statement.

Line 107-108: it is not clear from this sentence why these proteins were left out of the initial analysis in Ref 26. A sentence here explaining this would be valuable for the reader.

Line 117-123: The authors say that PF3D7_0204300, PF3D7_1117900 and PF3D7_1016200 were not studied because they were not in the top 10 hits. However, the current organisation of Supplementary Table 1 shows all 3 proteins among the top 10 hits (MyoF, KIC12, UIS14 and 0907200 being after them). I think the authors should reorganise their table. It is also unclear according to what the proteins in the table are ranked. Could the authors indicate the metric used for the ranking?

Line 129-141: Can the authors be clearer with their explanations of the identification of mutation Y1344Stop? One dataset (ref 61) shows that 52% of African parasites have a mutation in MCA2 in position 1344 leading to a STOP codon. But another dataset (ref 62) shows that the next base is also mutated, reverting the stop codon. That should have been seen in the first dataset as well. Could the authors please clarify.

Line 147: the authors say that MCA2 is expressed throughout the intraerythrocytic cycle as shown by live cell imaging. In Birnbaum et al 2020 fig 4I, the authors show that MCA2 is mainly expressed between 4 and 16hpi. But in Figure 1B of this manuscript there is a clear multiplication of MCA2 signal between trophozoite and schizont. How do the authors explain this discrepancy? Could expression of the truncated MCA2 be different than the full length? This cannot be assessed as expression and localisation of the full-length HA tag MCA2 is not shown in Schizonts. MCA2 expression seems also different for the MCA2TGD-GFP with no expression in rings.

Line 158: would it not have been more useful for the authors to have episomally expressed MCA2-3xHA in their MCA2Y1344STOP-GFPENDO line to make sure that the truncated protein is indeed going to the correct compartment? The experiments done by the authors suggests that the MCA2Y1344STOP goes to the right location but does not really confirm it.

Line 191: it is stated that MCA2 confers resistance independently of the MCA domain, however in both the MCA2-TGD and MCA2Y1344STOP-GFPENDO parasites, the MCA domain is deleted, and for both parasites, there is resistance (albeit to a lower level in the MCA2Y1344STOP-GFPENDO line). Therefore, how can the authors state that the ART resistance is independent of the MCA domain? This statement should be that resistance is dependent on the loss of the MCA domain.

Line 192: Why did the authors not check if MCA2 is involved in endocytosis? They state later on in the manuscript that they did not do endocytosis assays with TGD lines, however if the authors include the correct controls, this could be easily done. It would also be really interesting to see whether endocytosis gets progressively worse going from WT to MCA2Y1344STOP to MAC2TGD. This experiment (as well as doing endocytosis assays for KIC4 and KIC5 TGD lines) would drastically increase the impact of this study. These experiments would not take more than 3 weeks to perform, and would not require the generation of new lines.

The authors should consider re-organising the MCA2 section, first showing that the 3xHA tagged line colocalises with K13, then performing the new truncation.

Line 197: Once again ref 43 is not correct to illustrate that actin/myosin is involved in endocytosis

Line 202: the authors state that MyoF localises near the food vacuole from ring stage/trophs onwards. However, how can this statement be made in schizonts based on these images (Fig. 2A), where it doesn't look like MyoF is anywhere near the FV? This statement can only be made for schizonts if co-localised with a FV marker (which is done in Fig. 2B), however, based on the number of MyoF foci, it appears that this was not done for schizonts. Please either remove the statement that MyoF is near the food vacuole from trophs onwards (because it is only seen near the FV up until trophs) or show the data in Fig. 2B of schizonts to substantiate these claims.

Line 204-206: what does this statement bring to the paper? Is it to show that it is the real localisation of MyoF because 2 tag cell line show the same localisation? I don't think this is needed, especially as later in the manuscript an HA-tag MyoF line is used and show similar localisation.

Line 212: The overlap of K13 with MyoF in Fig 2C 3rd panel (1st trophozoite panel) is not obvious, especially as the MyoF signal seems inexistant. I would advise the authors to replace with a better image. Also, why are there no images of schizonts shown in Figure 2C?

Line 217: the spatial association of MyoF with K13 is very different when it is tagged with GFP and when it is tagged with 3xHA. The way the authors word it here, it seems that there is agreement with the two datasets, when this is not in fact the case (59% overlap for MyoF-GFP and only 16% overlap with MyoF-3xHA). These data suggest that the GFP and the multiple FKBP tags are doing something to the protein and therefore maybe the ensuing results using this line should not be trusted or be taken with a pinch of salt.

Line 219: the authors state here that they could not detect MyoF-GFP in rings, when in Figure 2C they show MyoF-GFP in rings, and also show that they could detect MyoF in Sup Fig. 3B with the 3xHA tagged line. Is this a labelling mistake in Figure 2C? If the authors could indeed not see MoyF-GFP in rings, this statement should have been made when Figure 2A was presented, and not so late in the manuscript, which causes confusion. Line 237: Showing a DNA marker (DAPI, Hoescht) for Figure 2E, and subsequent figures using mislocalisation to the nucleus, would help the reader assess efficiency of the mislocalisation.

Line 254-256: authors should show the results of the bloating assay for parental 3D7 parasites (+ and - rapalog) to see whether the MyoF line - rapalog has increased baseline bloating. This applies to all subsequent FV bloating assays.

Line 254-257: The authors say that because fewer parasites show a bloated food vacuole upon inactivation of MyoF it means that less hemoglobin reached the food vacuole. I understand the authors statement, however, shouldn't they look at the size of the food vacuole, instead of the number of parasites with bloated FV, to make such a statement? This has been done for KIC12 so why not doing it for MyoF?

Line 259-261: these results would be difficult to interpret namely because the authors have dying parasites, which is exacerbated with the protein being knocked sideways. The authors should mention the pitfalls their knock sideways and tagging design here.<br /> Line 260-261: RSA is an assay relying on measuring parasite growth 1 cycle after a challenge with ART for 6 hours.

Line 261-263: the authors sate that MyoF has a function in endocytosis but at a different step compared to K13 compartment proteins. I am not sure what they mean here. Can this be clarified? Do the authors mean that it is involved in endocytosis but not in ART resistance? If so, this is a very difficult statement to make since the parasites are dying. Is there any evidence of point mutations in MyoF in the field?

Line 298: the authors state that there is no growth defect in the first cycle when rapalog is added to the KIC11 line, however based on Figure 3D, there is evidently a 25% reduction in growth compared to - rapalog at day 1 post treatment, and a 60% reduction by day 2, which is still within the 1st growth cycle. The authors should either revise their statement or provide an explanation for these findings. The authors should also explain why their Giemsa data in Fig. 3E is not in accordance with their FACS data.

Line 301: KIC11 could also be important very early for establishment of the ring stage for example for establishment of the PV. Also, was mislocalisation assessed in rapalog-treated parasites at 72 hours or in cycle 3?

Line 311: the authors should change the sentence from 'not related to endocytosis' to 'not related to endocytosis or ART resistance'.

Line 323-325: Authors say that a nuclear GFP signal can be observed in early schizonts for KIC12. According to the pictures provided in Figure 4A and Figure S5A it is not very obvious. Also faint cytoplasmic GFP signal could only be background as we can see that exposure is higher for schizont pictures

Line 326-328: The authors say that kic12 transcriptional profile indicate mRNA levels peak (no s at peak) in merozoites. Should they show live cell imaging of merozoites then? Because from the Figure 4A schizont pictures where schizonts are almost fully segmented no signal can be observed. Line 347: The authors state that using the Lyn mislocaliser the nuclear pool of KIC12 is inactivated by mislocalisation to the PPM. This tends to suggest that only the nuclear pool of KIC12 is mislocalised. How is it possible that only the nuclear pool is mislocalised? Line 368-369: Effect was also only partial for MyoF. Why didn't you measure the same metrics for MyoF? Line 379: you don't know if all proteins acting later in endocytosis will have an increased number of vesicles as a phenotype

Line 413-414: The authors state that no growth defect was observed upon KS of 1365800. Is growth alone enough to say that there is no impact on endocytosis?

Line 432: in this section, the authors state that KIC4 and KIC5 seem to have domains that may suggest these proteins are involved in endocytosis, based on the alpha fold data that is publicly available. Considering the authors have TGD-SLI versions of these lines (Birnbaum et al. 2020) and have already confirmed in this previous publication that they confer resistance to ART; it would make sense to look at endocytosis for these genes. This would be a relatively simple and straightforward experiment, taking no longer than two to three weeks, and would require no additional reagents or line generation. Doing these experiments would add a lot more weight to this final section. The authors later state that KIC4 and 5 are TGD lines, so not the best for endocytosis assays. It is unclear why this would be difficult to do if an adequate control is contained in the experiment (such as parental 3D7). It explains why they did not perform the MCA2 endocytosis assays further up, but in my opinion, an attempt at doing these assays is important and would significantly increase the impact of this paper.

Line 490-493: the authors state that the K13 compartment proteins fall in two groups, some that are involved in ART resistance AND endocytosis, and some that have different functions. However, in this manuscript the authors have demonstrated 3 flavours that K13 compartment proteins can come in: • Some that confer ART resistance and are involved in HCCU (MCA2) • Some that are involved in HCCU but not ART resistance (MyoF & KIC12) • Some that are involved in neither (KIC11) The authors should therefore revise this statement.

Line 508: the authors state that they expanded the repertoire of K13 compartments, when in fact they functionally analysed them - they did not do another BioID to identify more candidates.

Line 570-572: has anyone ever tested whether CytoD or JAS treatment in rings, is sufficient to mediate ART resistance? Something similar to what was done in PMID 21709259 with protease inhibitors. If not this would be a pretty interesting experiment for the authors to do that could shed more light on the MyoF data. It would take maybe 2 weeks to do and not require the generation of any new lines. This would clarify whether other Myosins other than MyoF are involved in endocytosis, as is suggested by previous publications (PMID: 17944961).

Line 608: inhibitors targeting the metacaspase domain of MCA2 may inadvertently inactivate other essential parts of the protein. They authors should acknowledge this possibility in the text.

Line 624-625: the authors state that MyoF is 'lowly expressed in rings' - indeed this is the case in their MyoF-2xFKBP-GFP-2xFKBP line which the authors established has defects due to the tag, but it appears from their MyoF-3xHA tagged line that it is expressed in rings. The authors should therefore revise their statement, and be careful of making claims based on their defective line and using fluorescence imaging as their only metric. If they do want to make the statement that it is not there in rings, they should also do a western blot, which is much more sensitive since it amplifies the signal compared to an image of one parasite.

Line 635: arguably this is the 3rd variety and not the 2nd (the authors already mentioned 2 types - ones that are involved in HCCU AND ART and those involved in HCCU only). See comment for line 490-493 above.

Line 785: Bloated food vacuole assay/E64 hemoglobin uptake assay method specify that a concentration of 33mM E64protease inhibitor was used. However, in reference 44, cited in the manuscript, a concentration of 33µM E64 was used. Please confirmed if this is just a typo or if 1000x E64 concentration was used which renders the experiment invalid.

Line 788: it is unclear from this section what is considered a bloated food vacuole - is there an area above which the FV is considered bloated? Do the authors do these measurements manually or use an addon in FIJI/ImageJ? What is the cutoff for if a FV is bloated? Please clarify. Additionally, for the representative images + rapalog for Figures 2H and 4H, it would be useful to see where the authors delineate the FV (add a white circle showing what is actually measured).

Line 863-864: this sentence seems to be out of place.

Line 875: the authors state that there is a light blue wedge, when the circle consists of grey and black wedges. Please revise this.

Line 1059-1061: it is unclear whether the individual growth curves are different clones or whether they are just the same experiment repeated? If it is the latter, then why are they not combined, as is traditionally done?

Line 919-924: the authors mention a blue and red line, but there is only a black line in figure 3D. Moreover, the experiment of using the LYN mislocaliser was only done for KIC12 according to the manuscript. Additionally, the y axis of the figure states relative growth day 4[%] compared to rapalog, but then on the x axis there are several days. In the text it says there is no growth defect until the second cycle, but from this graph it appears the growth defect is evident as early as 1 day post rapalog treatment. Can the authors please clarify and correct the issues pointed out.

Figure 1 panel B & C: the label of the figure where the signal from MCA2Y1344STOP-GFP is shown with the DAPI signal overlayed is deceptive since it suggests that this is the signal of full length MCA2. Please change the label of this panel from MAC2/DAPI to MCA2Y1344STOP/DAPI. The same is true for Panel C for the image labeled MCA2/K13 - please change this to MCA2Y1344STOP/K13.

Figure 2B: what stages are these parasites? Please state this in the figure. Based on the MyoF pattern, it looks like rings in the upper panel and trophs in the bottom pannel. Why were schizonts not shown?

Figure 2D&F: it is not very meaningful when growth assays are shown as a final bar after 4 days of growth. It is much more useful and informative to see a growth curve instead (as is shown in the supplementary), since it shows if the defect is apparent in the first growth cycle or later. With the way the data is currently shown, this is not apparent. I would advise the authors to switch the graph in 2F out of a combined graph of all the biological replicates growth curves for S3D - showing error bars.

Figure 3: why were the calculation of FV area, parasite area and FV/parasite area only done for KIC12 and not done for MyoF? It would be interesting to see if any of these values are different for MyoF - whether the parasites are smaller in area and therefore FV smaller. Please present them Figure 2. Images should be already available and would not require further experiments to be done, only the analysis.

Figure 3B: why is there no spatial association assessment for KIC11 and K13 as was done for the MCA2 and MyoF? The authors should show a pie chart showing the degree of association here as was done for the other proteins.

Figure 3D: The y axis of the figure states relative growth day 4[%] compared to rapalog, but then on the x axis the experiment takes place over several days. Is this a typo in the y axis? Additionally, the authors state in line 287-290 that the growth defect upon addition of rapalog is only seen in the second cycle, but from this graph it appears the growth defect is already evident 1 day post rapalog addition. The figure legend also does not make sense for this figure since it mentions a blue and a red line, when there is only a black line present. The legend also mentions the LYN mislocaliser which was used for KIC12 not KIC 11 (see above).

Figure 3E: the colour for Control and Rapalog 4 hpi are very similar and very hard to discern. Please choose an alternative colour or add a pattern to one of the samples. The y axis is also missing a label. Is this supposed to be parasitemia (%)?

Figure 4A: the ring shown in this figure does not appear to be a ring (it is far too large and appears to have multiple nuclei?). Do the authors have any other representative images to show instead?

Figure 4B: why is there no spatial association assessment for KIC12 and K13 as was done for the MCA2 and MyoF? The authors should show a pie chart showing the degree of association here as was done for the other proteins. This should be done for the different life cycle stages considering the changing localisation of KIC12.

Figures 4C&E: it is extremely important to show the DNA stain in both these samples considering that a portion of KIC12 is in the nucleus! Please add the DAPI signal for these figures (as for all other figures!).

Figure 4E: this figure should be presented before 4D (considering the line being presented in 4E is used in an experiment in 4D). The authors should switch the order of these two.

It is unclear why in many of the fluorescence images the authors do not show the DAPI signal - particularly when colocalising with K13 and when doing the knock sideways experiments. Please add these images to the figures - I would assume they have already been taken, so would simply involved adding the images to the panel.

Throughout the manuscript, there is no western blot confirming the correct size of their modified proteins. This should be provided.

None of the figures are appropriate for individuals with colour blindness, limiting their accessibility to the paper. Please change the colour schemes for all fluorescent images using magenta/green or an alternative colour combination appropriate for colourblind individuals.

Minor Comments

line 29: remove 'are'.

Line 29: the text says "HCCU is critical for parasite survival but is poorly understood, with the K13 compartment proteins are among the few proteins so far functionally linked to this process." The sentence should be: 'HCCU is critical for parasite survival but is poorly understood, with the K13 compartment proteins among the few proteins so far functionally linked to this process."

line 44: remove 'the'

Line 48: consider mentioning here that malaria is caused by the parasite Plasmodium - otherwise the first mention of parasite in line 52 is confusing for the non-specialist reader.

Line 49: estimated malaria-related death and case numbers are from the 2021 WHO World malaria report. You cite the 2020 WHO World malaria report.

Line 53: please insert the word 'have' between now and also.

Line 54: please change 'was linked' to is linked

Line 72: I would specify that free heme is toxic to the parasite. Especially as you mention that hemozoin is nontoxic. Sentence would be "where digestion results in the generation of free heme, toxic to the parasite, which is further converted into nontoxic hemozoin"

Line 90: authors should either say "in previous works" or "in a previous work"

Line 91: "We designated these proteins as K13 interaction candidates (KICs)"

Line 95: please change 'rate' to number

Line 109: Please include a coma before (ii).

Line 112: as shown by Rudlaff et al in the paper you are citing, PPP8 is actually associated with the basal complex. You can say that "(ii) were either linked or had been shown to localise to the inner membrane complex (IMC) or the basal complex (PF3D7...).

Line 114: Protein PF3D7_1141300 is called APR1 in the manuscript but ARP1 in Supplementary Table 1. Please correct.

Line 131: please define SNP - this is the first use of the acronym.

Line 133-134: South-East Asia instead of "South Asia"

Line 135: please explain what TGD is - it is referred to over and over again in the manuscript without ever being explained.

Line 145: change 'Western blot' to western blot - only Southern blot is capitalised since it is named after an individual, while the other techniques are not.

Line 152: add "the" between 'and spatial'

Line 158: please define SLI as selected linked integration, since it is the first use of the acronym.

Line 178: introduce a coma after protein. Sentence should be "Proliferation assays with the MCAY1344STOP-GFPendo parasites which express a larger portion of this protein, yet still lacking the MCA domain (Figure 1), indicated no growth ...

Line 195: the authors could mention that MyoF was previously called MyoC in the Birnbaum 2020 paper. I wanted to check back in the Birnbaum 2020 paper and could not find MyoF

Line 200: "Expression and localisation of the fusion protein was analysed by fluorescent microscopy". Why expression was not analysed also by western Blot same as for MCA2?

Line 204: I could not find any mention of MyoF (Pf3D7_1329100) in reference 65. Please remove reference 65 if not correct. Also reference 66 looks at Plasmodium chabaudii transcriptomes so I would specify that "This expression pattern is in agreement with the transcriptional profile of its Plasmodium chabaudii orthologue"

Line 208: Please indicate a reference for P40 being a marker of the food vacuole

Line 220-224: The authors should consider changing to " Taken together these results show that MyoF is in foci that are mainly close to K13 and, at times, overlapping, indicating that MyoF is found in a regular close spatial association with the K13 compartment."

Line 255: In Figure 2H, and subsequent figures showing bloated FV assay, I would delineate the food vacuole with dashed line as in Birnbaum et al. 2020 to help the reader understanding where the food vacuole is.

Line 265-266: Here the title says that KIC11 is a K13 compartment associated protein, but the title of Figure 3 says KIC11 is a K13 compartment protein. I noticed that you make the difference between K13 compartment protein et K13 compartment associated protein for MyoF for example which is not clearly associated with the K13 compartment. Which one is it for KIC11?

Line 309-310: indicate a reference for your statement "which is in contrast to previously characterised essential K13 compartment proteins".

Line 377: Figure 4I, please correct 1st panel Y axis legend

Line 404: replace "dispensability" with dispensable

Line 416: can the authors provide any speculation as to why they observed these proteins as hits in the BioID experiments?

Line 451: Where the "97% of proteins containing these domains also contain an Adaptin_N domain and function in vesicle adaptor complexes as subunit " come from. Do you have a reference?

Line 465-467: the same could be said for KIC4 as it also has a VHS domain.

Line 477-479: Can be rephrased to "However, we found this protein as being likely dispensable for intra-erythrocytic parasite development and no colocalisation with K13 could be demonstrated, suggesting a limited role for PF3D7_1365800 in endocytosis. Or something like that. Makes it clearer.

Line 535: Have AP-2 or AP-2 been shown to be at the K13 compartment?

Line 569: reference 43 is wrong

Line 746: typo "ot" instead of or.

Line 801: method for Domain Identification using AlphaFold specify that RMSDs of under 5Å over more than 60 amino acids are listed in the results. However, there is a typo in Figure 5B for KIC5 where it says "RMSD 4.0 Å over 8 aa". Please correct.

Line 856: In Figure 1E, please use the same Y axis legend as in Figure 2D "relative growth at day 4 [%] compared with 3D7"

Figure S1: Some PCR gels check for integration are presented as 5', 3' and ori whereas other gels are presented as ori, 5' and 3'. This is confusing. Figure S1: Why was the expression of only MCA2 was verified by Western blot? What about the other proteins?

Line 493: Considering KIC11 was not involved in HCCU or ART resistance it might be worth mentioning in this section that it is of note that there are no domains detected that would be involved in endocytosis.

Line 503-506: is it wise to generate more drugs that target a pathway that is already highly susceptible to mutations? The authors should add a statement explaining how this might be avoided.

Throughout, scale bars are stated in the figure legends at the end of the legend. This is a slightly confusing format. The authors should consider stating the scale bar for each sub-legend where a fluorescence image is taken.

Referees cross-commenting

After reading reviewer 2 and 3's comments, I think there are significant overlaps in the key points raised in terms of questions about fusion proteins and their potential partial mis-localisation, better descripton of results and target selection. Overall I think we agree that the work has potential, but in its current form does not represent a major advance. It would be immensely helpful if the manuscript would be carefully edited for a better flow and linear description of results.

Significance

The authors set out to test whether other proteins that are in the vicinity of K13 are involved in mediating ART resistance and endocytosis. This is an interesting question. However, other than MCA2 which was already known to be involved in mediating ART resistance (and was not tested for its involvement in endocytosis), none of their candidate proteins seem to be involved in mediating both these functions. The authors show that the other proteins tested appear important for parasite growth, with KIC12 and MyoF involved in mediating endocytosis. While these findings are novel, the KS approach used by the authors casts some doubt over the findings, and would mean that these findings would have to be re-tested with a more reliable approach, such as the GlmS system or generating a conditional knockout using the DiCre system. Despite not advancing our understanding of ART resistance, or identifying further players involved in this process, this manuscripts provides two candidates that are involved in mediating endocytosis and a further candidate that appears to be important for parasite growth. Further work on these proteins will be required to understand their exact roles. As stated above, there is currently limited interest for these results (limited to researchers working on endocytosis in apicomplexan parasites and possibly the wider endocytosis field from an evolutionary perspective), however with further work, this could increase the impact and interest of this work substantially.

The authors do not describe any novel methods/approaches within this work.

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Reply to the reviewers

1. General Statements

We thank all four reviewers for their helpful and constructive comments. We have gone through each and every comment and proposed how we would address each point raised by the reviewers. We are confident our proposed revisions are feasible within a reasonable and expected time frame. Some of the comments regarding minor typo/aesthetics and extra references have already been addressed in the transferred manuscript. The changes are highlighted in yellow in the transferred manuscript.

2. Description of the planned revisions

Reviewer #1

Major points:

1. The presented work itself (Figures 1-4) does not need significant adjustments prior to publication, in my view, with only a few points to address. However, the work in Figure 5- doesn't really support the claims the authors make on its own, and would require some additional experiments or at the very least discussion of the caveats to its current form.

We thank the reviewer for these comments and will follow the reviewer’s suggestion by discussing the caveats regarding the interpretation of Figure 5. We will also add to the discussion to suggest future research approaches beyond the scope of this manuscript that would address the functional importance of localised mRNA translation. We will briefly mention in the discussion methods such as the quantification of the mRNA foci and the disruption of the mRNA localisation signals to disrupt localised translation and the use of techniques such as Sun-Tag (Tanenbaum et al, 2014) and FLARIM (Richer et al, 2021) to visualise local translation directly.

Tanenbaum et al, 2014 DOI: 10.1016/j.cell.2014.09.039

Richer et al, 2021 DOI: 10.1101/2021.08.13.456301

1. Localized glia transcripts, are they "glial/CNS/PNS" significant or are they similar to other known datasets of protrusion transcriptomes? The authors compared their 4801 "total" localized to a local transcriptome dataset from the Chekulaeva lab finding that a significant fraction are localized in both. As the authors note, this is in good agreement with a recent paper from the Talifarro lab showing conservation of localization of mRNAs across different cell types. What the authors haven't done here, is further test this by looking at other non-neuronal projection transcriptomic datasets (for example Mardakheh Developmental Cell 2015, among others). If the predicted glia-localized processes are similar to non-neuronal processes transcriptomes, this would further strengthen this claim and rule out some level of CNS/PNS derived linage driving the similarities between glia and neuronal localized transcripts.

This is a good point and we thank the review for pointing out this interesting cancer data set. We will do as the reviewer suggests and intersect our data with Mardakheh Dev Cell 2015 to test the further generality of localisation in neurons and glia, in other cell types. Specifically, we plan to intersect both glial (this study) and neuronal (von Kuegelgen & Chekulaeva, 2020) dataset with protrusive breast cancer cells (Mardakeh et al, 2015).

von Kuegelgen & Chekulaeva, 2020 DOI: 10.1002/wrna.1590

Mardakeh et al, 2015 DOI: 10.1016/j.devcel.2015.10.005

1. The presentation/discussion around Figure 3 is a bit weaker than other parts of the manuscript, and it doesn't really contribute to the story in its current form. Notably there is no discussion about the significance of glia in neurological disorders until the very end of the manuscript (page 21), meaning when its first brought up.. it just sits there as a one off side point. The authors might consider strengthening/tightening up the discussion here, if they really want to keep it as a solo main figure rather than integrating it somewhere else/putting it into supplemental. In my view, Figures 2 & 3 should be merged into something a bit more streamlined.

This is a good point. We plan to strengthen the presentation of Figure 3 and discussion of the significance of glia in neurological disorders by adding a description of the Figure in the Results section and highlighting the significance of glia in nervous system disorders in the Discussion section.

1. Why aren't there more examples of different mRNAs in Figure 4? Seems a waste to kick them all to supplemental.

We agree that it could be helpful to show different expression patterns in the main figure. To address this point we will add Pdi (Fig. S4D), which shows mRNA expression in both the glia and the surrounding muscle cell. This pattern is in contrast to Gs2, which is highly specific to glial cells. We will also note that although pdi mRNA is present in both the glia and muscle, Pdi protein is only abundant in the glia, suggesting that translation of pdi mRNA to protein is regulated in a cell-specific manner.

1. The plasticity experiments, while creative, I think need to be approached far more cautiously in their interpretation. Given that the siRNAs will completely deplete these mRNAs- it really needs to be stressed any/all of the effects seen could just be the result of "defective" or "altered" states in this glial population- which has spill over effects on plasticity in at the NMJ. Without directly visualizing if these mRNAs are locally translated in these processes and assessing if their translation is modulated by their plasticity paradigm, all these experiments can say is that these RNAs are needed in glia to modulate ghost bouton formation in axons. This represents the weakest part of this manuscript, and the part that I feel does not actually backup the claims currently being made. Without any experiments to A. quantify how much of these transcripts are localized vs in the cell body of these glia, B. visualize/quantify the translation of these mRNAs during baseline and during plasticity; the authors cannot use these data to claim that localized mRNAs are required for synaptic plasticity.

We are grateful to the reviewer for pointing out that we were not precise enough in defining our interpretation of the structural plasticity assay. We did not intend to claim that our results show that local translation of these transcripts is necessary for plasticity, only that these transcripts are localized and are required in the glia for plasticity in the adjacent neuron (in which the transcript levels are not disrupted in the experiment). Definitively proving that these transcripts are required locally and translated in response to synaptic activity would require genetic/chemical perturbations and imaging assays that would require a year or more to complete, so are beyond the scope of this manuscript. To address this point, we will clarify that the results do not show that localized transcripts are required, only that the transcripts are required somewhere specifically in the glial cell (without affecting the neuron level), and we can indeed show in an independent experiment that there are localized transcripts.

Reviewer #2

Major points:

1. The authors analyse the 1700 shortlisted genes for Gene Ontology and associations with austism spectrum disorder, leading to interesting results. However, it is not clear to what extent the enrichments they observe are driven by their presumptive localization or if the associations are driven to a significant extent by the presence of these genes in the selected cell types in the Fly Cell Atlas. One way to address this would be to perform the GO and SFARI analysis on genes that are expressed in the same cells in the Fly Cell Atlas but were not shortlisted from the mammalian cell datasets - the results could then be compared to those obtained with the 1700 localized transcripts.

This is a fair point raised by the reviewer as genes involved in neurological disease such as Autism Spectrum Disorder may be enriched in CNS/PNS cell types. We will follow the reviewer’s suggestion to perform GO and SFARI gene enrichment analysis in genes that were not shortlisted for presumptive glial localisation.

1. Although the authors attempt to justify its inclusion, I'm not convinced why it was important to use the whole cell transcriptome of perisynaptic Schwann cells as part of the selection process for localizing transcripts. Including this dataset may reduce the power of the pipeline by including mRNAs that are not localized to protrusions. How many of the shortlisted 1700 genes, and how many of the 11 glial localized mRNAs in Table 5, would be lost if the whole cell transcriptome were excluded. More generally, what is the distribution of the 11 validated localizing transcripts in each dataset in Table 4? This information might be valuable for determining which dataset(s), if any, has the best predictive power in this context.

We thank the reviewer for raising this point, which we will address with further analysis and adding to the discussion. We propose to address the criticism by running our analysis pipeline without the inclusion of the dataset using Perisynaptic Schwann Cells (PSCs) and then intersect with the PSCs-expressed genes, since their functional similarity with polarised Drosophila glial cells is highly relevant. We also agree with the reviewer that it would be a useful control for us to assess the ‘predictive power’ of each glial dataset by calculating their contribution to the shortlisted 1,700 glial localised transcripts and to the 11 experimentally validated transcripts via in situ hybridisation. To address this point, we plan to add this information in the revised manuscript.

1. Did the authors check if any of the RNAi constructs are reducing levels of the target mRNA or protein? Doing so would strengthen the confidence in these important results significantly. In any case, the authors should also mention the caveat of potential off-target effects of RNAi.

We thank the reviewer for their useful comment and agree that the extent to which the RNAi expression reduces the levels of mRNA is not specifically known. We will add a FISH experiment on lac, pdi and gs2 RNAi showing very strong reduction in mRNA levels. We will also add an explanation of the caveats of the use of the RNAi system to the discussion.

1. Methods: what is the justification for assuming that if the RNAi cross caused embryonic or larval lethality then the 'next most suitable' RNAi line is reporting on a phenotype specific to the gene. If the authors want to claim the effect is associated with different degrees of knockdown they should show this experimentally. An alternative explanation is that the line used for phenotypic analysis in glia is associated with an off-target effect.

We thank the reviewer for this comment. We agree that off target effects cannot in principle be completely ruled out without considerable additional experimental analysis beyond the scope of this manuscript. To address the criticism we will remove the expression data of the lines that cause lethality and revise the discussion to explain that the level of knockdown in each line is unknown, and would require further experimental exploration.

Minor points:

1. It would be helpful to have in the Introduction (rather than the Results, as is currently the case) an operational definition of mRNA localization in the context of the study. And is it known whether or not localization in protrusions is the norm in mammalian glia or the Drosophila larval glia? I ask because it may be that almost all mRNAs diffuse into the protrusion, so this is not a selective process. One interesting approach to test this idea might be to test if the 1700 shortlisted transcripts have a significant underrepresentation of 'housekeeping' functions.

We thank the reviewer for this excellent suggestion. To address the comment, we will move our explanation of the operational definition of mRNA localization to the Introduction. We will also perform enrichment analysis of housekeeping genes within 1,700 shortlisted transcripts compared to the transcriptome background, as the reviewer suggested.

Reviewer #3

Major points:

1. The authors have pooled data from different studies across different type of glial cells performed from in vitro to in vivo. While pooling datasets may reveal common transcripts enriched in processes, this may not be the best approach considering these are completely different types of glial cells with distinct function in neuronal physiology.

We thank the reviewer for highlighting the need for us to further justify why we pooled datasets. We will revise the manuscript to better emphasise that the overarching goal of our study was to try to discern a common set of localised transcripts shared between the cells. The problem with analysing and comparing individual data sets is that much of the variation may be due to differences in the methods used and amount of material, rather than differences in the type of cells used. We will revise the discussion to make this point and plan to explain that our approach corresponds well with a previous publication pooling localised mRNA datasets in neurons (von Kugelgen & Chekulaeva 2021).

von Kuegelgen & Chekulaeva, 2020 DOI: 10.1002/wrna.1590

1. It is important to note the limitations of the study. For example, DeSeq2 is biased for highly expressed transcripts. How robust was the prediction for low abundance transcripts?

The presented 1,700 transcripts were shortlisted based on their presence and expression level (TPM) in glial protrusions rather than their relative enrichment. Nevertheless, the reviewer makes a valid criticism of our use of DESeq2, where we compared enriched transcripts in glial and neuronal protrusions in Figure 1D. To address this point we will discuss this caveat in the relevant section.

The issue raised regarding low abundance transcript prediction raises an important question: does the likelihood of localisation to cell extremities correlate with mRNA abundance? We have already partially addressed this point, since our analysis of the fraction of localised transcripts per expression level quantiles shows only limited correlation. To address this comment, we will add these results in the revised manuscript as a supplementary figure.

1. The authors identify 1,700 transcripts that they classify as "predicted to be present" in the projections of the Drosophila PNS glia. This was based on the comparison to all the mammalian glial transcripts. Since the authors have access to a transcriptomic study from Perisynaptic Schwann cells (PSCs), the nonmyelinating glia associated with the NMJ isolated from mice; it would be more convincing to then validate the extent of overlap between Drosophila peripheral glial with the mammalian PSCs. This may reveal conserved features of localized transcripts in the PNS, particularly associated with the NMJ function.

Thank you for the valuable suggestion. A similar point was also raised by [Reviewer #2 - Major point 2] to re-run our pipeline excluding the PSCs dataset and intersect with the PSC transcriptome post-hoc. Please see the above section for our detailed response.

1. Fig 2: What is the extent of overlap between the translating fractions versus the localized fraction? It will be informative to perform the functional annotation of the translating glial transcripts as identified from Fig 1D.

This is an interesting question. To address this point, we plan to: (i) compare transcripts that are translated vs. localised in glial protrusions, and (ii) perform functional annotation enrichment analysis on the translated fraction of genes.

1. "We conclude predicted group of 1,700 are highly likely to be peripherally localized in Drosophila cytoplasmic glial projections". To validate their predictions, the authors test some of these candidates in only one glial cell type. It might be worthy to extend this for other differentially expressed genes localized in another glial type as well.

The presented in vivo analyses made use of the repo-GAL4 driver, which is active in all glial subtypes, including subperineurial, perineurial and wrapping glia that make distal projection to the larval neuromuscular junction. We agree that subtype-specific analysis would be highly informative, but we believe this is outside the scope of the current work where we aimed to identify conserved localised transcriptomes across all glial subtypes. Nevertheless, to address the comment, we plan to further clarify our use of pan-glial repo-GAL4 driver in the Results and Method section of the revised manuscript.

1. Figure 5: The authors perform KD of candidate transcripts to test the effect on synapse formation. However, these are KD with RNAi that spans across the entire cell. To make the claim about the importance of "target" RNA localization in glia stronger, ideally, they should disrupt the enrichment specifically in the glial protusions and test the impact on bouton formation. Do these three RNAs have any putative localization elements?

We agree with the review, that we would ideally test the effect of disruption of mRNA localization (and therefore localised translation). However, we feel these experiments are beyond the scope of this current study, as they will require a long road of defining localisation signals that are small enough to disrupt without affecting other functions. To address this comment we will revise the Discussion section to mention those difficulties explicitly, and clarify the limitations of the approach used in our study for greater transparency.

Reviewer #4

Major points:

1. The authors use FISH to validate the glial expression of their target genes, though these experiments are not quantified, and no controls are shown. The authors should provide a supplemental figure with "no probe" controls, and/or validate the specificity of the probe via glial knockdown of the target gene (see point 2). Furthermore, these data should be quantified (e.g. number of puncta colocalized with NMJ glia membrans).

Thank you for requesting further information regarding the YFP smFISH probes. We have validated the specificity and sensitivity of the YFP probe in our recent publication (Titlow et al, 2023, Figure 1 and S1). Specifically, we demonstrated the lack of YFP probe signal from wild-type untagged biosamples and showed colocalization of YFP spots with additional probes targeting the endogenous exon of the transcript. Nevertheless, we will address this comment by adding control image panels of smFISH in wild-type (OrR) neuromuscular junction preparations.

Titlow et al, 2023 DOI: 10.1083/jcb.202205129

1. For the most part, the authors only use one RNAi line for their functional studies, and they only show data for one line, even if multiple were used. To rule out potential false negatives, the authors should leverage their FISH probes to show the efficacy of their knockdowns in glia. This would serve the dual purpose of validating the new probes (see point 1).

Thank you for the suggestion. This point was also raised by [Reviewer #2 - Major point 3]. Please see above for our detailed response.

1. In Figure 5 E, given the severe reduction in size in the stimulated Pdi KD animals, the authors should show images of the unstimulated nerve as well. Do the nerve terminals actually shrink in size in these animals following stimulation, rather than expand? The NMJ looks substantially smaller than a normal L3 NMJ, though their quantification of neurite size in F suggests they're normal until stimulation.

We share the same interpretation of the data with the reviewer that the neurite area is reduced post-potassium stimulation in pdi knockdown animals. We will follow the reviewer’s suggestion and add an image showing unstimulated neuromuscular junctions.

Minor points:

1. The authors claim that there is an enrichment of ASD-related genes in their final list of ~1400 genes that are enriched in glial processes. It is well-appreciated that synaptically-localized mRNAs are generally linked to ASDs. Can the authors comment on whether the transcripts localized to glial processes are even more linked to ASDs and neurological disorders than transcripts known to be localized to neuronal processes?

This is an interesting point. To address the comment, we will add a comparison of the degree of enrichment of ASD-related genes in neurite vs. glial protrusions in the revised manuscript.

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

Reviewer #1

1. The use of blue/green or blue/green/magenta is difficult to resolve in some places. Swapping blue for cyan would greatly aid in visualizing their data.

This comment is much appreciated. We have swapped blue for cyan in Figures 4 and S4. We have also changed Figure S1 to increase contrast and visibility as per reviewer’s comment.

1. Make the colouring/formatting of the tables more consistent, its distracting when its constantly changing (also there is no need for a blue background.. just use a basic white table).

This comment is much appreciated. We have applied a consistent colour palette to the Tables without background colourings and made the formatting uniform.

Reviewer #2

1. Introduction: 'Asymmetric mRNA localization is likely to be as important in glia, as it is in neurons,...'. Remove commas

Thank you for pointing this mistake out. We have made the corresponding edits.

Reviewer #3

1. RNA localization in oligodendrocytes has been well studied and characterized. The authors should cite and discuss those papers (PMID: 18442491; PMID: 9281585).

We thank the reviewer for this useful suggestion. We have added these references to the paper.

Reviewer #4

1. In Figure 5D, the authors should include a label to indicate that these images are from an unstimulated condition.

We thank the reviewer for pointing this out. We have added the label as requested.

1. The authors are missing a number of key citations for studies that have explored the functional significance of mRNA trafficking in glia, and those that have validated activity-dependent translation:

- https://pubmed.ncbi.nlm.nih.gov/18490510/

-https://pubmed.ncbi.nlm.nih.gov/7691830/

-https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3001053

-https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7450274/

-https://pubmed.ncbi.nlm.nih.gov/36261025**_/

_**

We thank the reviewer for the comment. We have added these references to the text.

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Referee #4

Evidence, reproducibility and clarity

Peripheral localization of mRNAs to cellular protrusions (e.g. axons, astrocyte peri-synaptic processes, myelin sheaths) is important for activity-dependent regulation of nervous system function. In Gala et al., the authors aim to identify conserved, peripherally located mRNAs in through a combination of unbiased transcriptomics and in vivo validation in Drosophila NMJ glia. To that end, they mine several published datasets enriched for peripherally located mRNAs in glia, identify which of these transcripts are conserved in fly, filtered for mRNAs that are enriched in processes over soma, and filtered for mRNAs that were enriched in three glial subtypes that ensheath their model system: Drosophila NMJ. Finally, they go on to validate 11 (of 15) predicted genes as located in NMJ glia, demonstrating that loss of these transcripts, in some cases, impacts synaptic plasticity.<br /> This is an interesting study that complements a growing interest in the community: how do glia locally support the neurons that interact with. I have a number of suggestions to support the conclusions made in this manuscript:

Major:

1. The authors use FISH to validate the glial expression of their target genes, though these experiments are not quantified, and no controls are shown. The authors should provide a supplemental figure with "no probe" controls, and/or validate the specificity of the probe via glial knockdown of the target gene (see point 2). Furthermore, these data should be quantified (e.g. number of puncta colocalized with NMJ glia membrans).
2. For the most part, the authors only use one RNAi line for their functional studies, and they only show data for one line, even if multiple were used. To rule out potential false negatives, the authors should leverage their FISH probes to show the efficacy of their knockdowns in glia. This would serve the dual purpose of validating the new probes (see point 1).
3. In Figure 5 E, given the severe reduction in size in the stimulated Pdi KD animals, the authors should show images of the unstimulated nerve as well. Do the nerve terminals actually shrink in size in these animals following stimulation, rather than expand? The NMJ looks substantially smaller than a normal L3 NMJ, though their quantification of neurite size in F suggests they're normal until stimulation.

Minor:

1. In Figure 5 D, the authors should include a label to indicate that these images are from an unstimulated condition.
2. The authors claim that there is an enrichment of ASD-related genes in their final list of ~1400 genes that are enriched in glial processes. It is well-appreciated that synaptically-localized mRNAs are generally linked to ASDs. Can the authors comment on whether the transcripts localized to glial processes are even more linked to ASDs and neurological disorders than transcripts known to be localized to neuronal processes?
3. The authors are missing a number of key citations for studies that have explored the functional significance of mRNA trafficking in glia, and those that have validated activity-dependent translation:
4. https://pubmed.ncbi.nlm.nih.gov/18490510/
5. https://pubmed.ncbi.nlm.nih.gov/7691830/
6. https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3001053
7. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7450274/
8. https://pubmed.ncbi.nlm.nih.gov/36261025/

Significance

Glia are morphologically complex cells that extend tens (microglia/oligodendrocytes) to thousands<br /> (astrocytes) of processes to interact with and support neurons. Given this complex morphology, and the ability of glia to dynamically respond to changes in neuronal activity, there has been a push in recent years to characterize local mechanisms of glia-neuron support. These mechanisms include mRNA trafficking and activity-dependent translation in distal processes. The authors of this study did a nice job computationally identifying a set of putative genes that are enriched in glial processes, which should be of broad interest to the glial community.

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Referee #3

Evidence, reproducibility and clarity

In the manuscript by Gala et al, the authors perform meta-analysis of transcriptomic datasets from different studies focused on synaptically-associated mammalian glial cells. Based on a detailed analysis, the authors predict 1700 localized transcripts and attempted to identify the local transcriptome in glial cells conserved in Drosophila and mammals. This kind of data mining is informative, and can predict the top candidates relatively well, however, the study suffers from lack of depth and a careful assessment comparing across the different datasets. The main concerns have been listed below and suggestions for a more detailed an careful assessment of the data.<br /> 1. The authors have pooled data from different studies across different type of glial cells performed from in vitro to in vivo. While pooling datasets may reveal common transcripts enriched in processes, this may not be the best approach considering these are completely different types of glial cells with distinct function in neuronal physiology.<br /> 2. It is important to note the limitations of the study. For example, DeSeq2 is biased for highly expressed transcripts. How robust was the prediction for low abundance transcripts?<br /> 3. The authors identify 1,700 transcripts that they classify as "predicted to be present" in the projections of the Drosophila PNS glia. This was based on the comparison to all the mammalian glial transcripts. Since the authors have access to a transcriptomic study from Perisynaptic Schwann cells (PSCs), the nonmyelinating glia associated with the NMJ isolated from mice; it would be more convincing to then validate the extent of overlap between Drosophila peripheral glial with the mammalian PSCs. This may reveal conserved features of localized transcripts in the PNS, particularly associated with the NMJ function.<br /> 4. Fig 2: What is the extent of overlap between the translating fractions versus the localized fraction? It will be informative to perform the functional annotation of the translating glial transcripts as identified from Fig 1D.<br /> 5. "We conclude predicted group of 1,700 are highly likely to be peripherally localized in Drosophila cytoplasmic glial projections". To validate their predictions, the authors test some of these candidates in only one glial cell type. It might be worthy to extend this for other differentially expressed genes localized in another glial type as well.<br /> 6. Figure 5: The authors perform KD of candidate transcripts to test the effect on synapse formation. However, these are KD with RNAi that spans across the entire cell. To make the claim about the importance of "target" RNA localization in glia stronger, ideally, they should disrupt the enrichment specifically in the glial protusions and test the impact on bouton formation. Do these three RNAs have any putative localization elements?<br /> 7. RNA localization in oligodendrocytes has been well studied and characterized. The authors should cite and discuss those papers (PMID: 18442491; PMID: 9281585).

Significance

In the manuscript by Gala et al, the authors perform meta-analysis of transcriptomic datasets from different studies focused on synaptically-associated mammalian glial cells. Based on a detailed analysis, the authors predict 1700 localized transcripts and attempted to identify the local transcriptome in glial cells conserved in Drosophila and mammals. This kind of data mining is informative, and can predict the top candidates relatively well, however, the study suffers from lack of depth and a careful assessment comparing across the different datasets and the biological significance.

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Referee #2

Evidence, reproducibility and clarity

Summary:

The manuscript by Gala et al. describes efforts to systematically identify candidate localizing mRNAs within glial cells of the Drosophila larval nervous system. They address this issue with an interesting and novel approach that involves compiling candidate localized transcripts from available mammalian cell datasets and cross-referencing a list of mRNAs from homologous Drosophila genes with a small number of candidates for mRNA localization in Drosophila glia cells that this team identified in a previous study (which they have now validated further). The results provide compelling evidence that their pipeline has predictive power. The authors then go on to perform functional analysis of a small number of validated localizing transcripts and provide evidence that several of these genes are functionally important in glia, including in processes related to synaptic plasticity. These observations raise the possibility that the localization process is functionally important but this was not tested directly (doing so would require a separate long-term study).

The manuscript is well written and the figures are of high quality. Methodological details are provided, as is quantification where appropriate. However, some points are not yet sufficiently strongly supported by the data yet and the justification for some aspects of the workflow needs clarifying.

Major points:

1. The authors analyse the 1700 shortlisted genes for Gene Ontology and associations with austism spectrum disorder, leading to interesting results. However, it is not clear to what extent the enrichments they observe are driven by their presumptive localization or if the associations are driven to a significant extent by the presence of these genes in the selected cell types in the Fly Cell Atlas. One way to address this would be to perform the GO and SFARI analysis on genes that are expressed in the same cells in the Fly Cell Atlas but were not shortlisted from the mammalian cell datasets - the results could then be compared to those obtained with the 1700 localized transcripts.
2. Although the authors attempt to justify its inclusion, I'm not convinced why it was important to use the whole cell transcriptome of perisynaptic Schwann cells as part of the selection process for localizing transcripts. Including this dataset may reduce the power of the pipeline by including mRNAs that are not localized to protrusions. How many of the shortlisted 1700 genes, and how many of the 11 glial localized mRNAs in Table 5, would be lost if the whole cell transcriptome were excluded. More generally, what is the distribution of the 11 validated localizing transcripts in each dataset in Table 4? This information might be valuable for determining which dataset(s), if any, has the best predictive power in this context.
3. Did the authors check if any of the RNAi constructs are reducing levels of the target mRNA or protein? Doing so would strengthen the confidence in these important results significantly. In any case, the authors should also mention the caveat of potential off-target effects of RNAi.
4. Methods: what is the justification for assuming that if the RNAi cross caused embryonic or larval lethality then the 'next most suitable' RNAi line is reporting on a phenotype specific to the gene. If the authors want to claim the effect is associated with different degrees of knockdown they should show this experimentally. An alternative explanation is that the line used for phenotypic analysis in glia is associated with an off-target effect.

Minor points:

1. It would be helpful to have in the Introduction (rather than the Results, as is currently the case) an operational definition of mRNA localization in the context of the study. And is it known whether or not localization in protrusions is the norm in mammalian glia or the Drosophila larval glia? I ask because it may be that almost all mRNAs diffuse into the protrusion, so this is not a selective process. One interesting approach to test this idea might be to test if the 1700 shortlisted transcripts have a significant underrepresentation of 'housekeeping' functions.
2. Introduction: 'Asymmetric mRNA localization is likely to be as important in glia, as it is in neurons,...'. Remove commas

Significance

Whilst glial mRNA localization has been reported in other systems, this study is significant as it paves the way for functional and mechanistic dissection of this process in a genetically tractable model system that involves physiologically relevant neuron-glia interactions. The successful results of the data mining approach may also encourage others to address other problems in this manner. The study would be more impactful if additional hits from the 1700 transcripts were validated for glial localization but the findings in the current manuscript are still important. The advance is more methodological than conceptual. The work will appeal to cell biology and systems biology audiences.

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Referee #1

Evidence, reproducibility and clarity

The study of mRNA localization in glia has been largely overlooked in comparison to neurons. However, glia are also polarized cells with long cytoplasmic processes that play important roles in neural function. In this manuscript, Gala and Lee et al attempt to fill in this missing void in the literature. They first use a meta-analysis of existing, cross-species, transcriptomic data to identify a set of 1,700 transcripts that are likely to be localized to the periphery of glia in Drosophila. They then used this list of transcripts to predict which mammalian glial transcripts are also likely to be localized. They're analysis suggests that a large proportion of the mammalian glial transcripts are predicted to be localized to the periphery of glia, and that these transcripts are enriched for functions involved in membrane trafficking, cytoskeleton regulation, local translation, and cell-cell communication. A connection with cross-cellular communication (ie glia-glia, glia-neuron, glia-muscle) at the neuromuscular junction, prompting the authors to assess if some of these transcripts play a role in plasticity of at the NMJ. Using siRNA driver lines, that loss of some of their assessed transcripts prevent new synapse formation- suggestive of a role for mRNA localization and local protein synthesis in driving synaptic plasticity. These findings suggest that mRNA localization is a widespread phenomenon in glia, and that it plays an equally important role as the more widely studied neuronal mRNA localization.

Key Points

• 1,700 transcripts are predicted to be localized to the periphery of PNS glia in Drosophila at the NMJ.
• A large proportion of the mammalian glial transcripts are predicted to be localized to the periphery of glia.
• Localized transcripts are enriched for functions involved in membrane trafficking, cytoskeleton regulation, local translation, and cell-cell communication.
• Localized glial transcripts may function in synaptic plasticity.

Major comments

Overall, the work presented within manuscript is well reasoned and supports the points the authors generally are trying to make. The work as is, does fall a little on the light side, resting on almost exclusive bioinformatic analysis with some limited validation. The presented work itself (Figures 1-4) does not need significant adjustments prior to publication, in my view, with only a few points to address. However, the work in Figure 5- doesn't really support the claims the authors make on its own, and would require some additional experiments or at the very least discussion of the caveats to its current form.

1. Localized glia transcripts, are they "glial/CNS/PNS" significant or are they similar to other known datasets of protrusion transcriptomes? The authors compared their 4801 "total" localized to a local transcriptome dataset from the Chekulaeva lab finding that a significant fraction are localized in both. As the authors note, this is in good agreement with a recent paper from the Talifarro lab showing conservation of localization of mRNAs across different cell types. What the authors haven't done here, is further test this by looking at other non-neuronal projection transcriptomic datasets (for example Mardakheh Developmental Cell 2015, among others). If the predicted glia-localized processes are similar to non-neuronal processes transcriptomes, this would further strengthen this claim and rule out some level of CNS/PNS derived linage driving the similarities between glia and neuronal localized transcripts.
2. The presentation/discussion around Figure 3 is a bit weaker than other parts of the manuscript, and it doesn't really contribute to the story in its current form. Notably there is no discussion about the significance of glia in neurological disorders until the very end of the manuscript (page 21), meaning when its first brought up.. it just sits there as a one off side point. The authors might consider strengthening/tightening up the discussion here, if they really want to keep it as a solo main figure rather than integrating it somewhere else/putting it into supplemental. In my view, Figures 2 & 3 should be merged into something a bit more streamlined.
3. Why aren't there more examples of different mRNAs in Figure 4? Seems a waste to kick them all to supplemental.
4. The plasticity experiments, while creative, I think need to be approached far more cautiously in their interpretation. Given that the siRNAs will completely deplete these mRNAs- it really needs to be stressed any/all of the effects seen could just be the result of "defective" or "altered" states in this glial population- which has spill over effects on plasticity in at the NMJ. Without directly visualizing if these mRNAs are locally translated in these processes and assessing if their translation is modulated by their plasticity paradigm, all these experiments can say is that these RNAs are needed in glia to modulate ghost bouton formation in axons. This represents the weakest part of this manuscript, and the part that I feel does not actually backup the claims currently being made. Without any experiments to A. quantify how much of these transcripts are localized vs in the cell body of these glia, B. visualize/quantify the translation of these mRNAs during baseline and during plasticity; the authors cannot use these data to claim that localized mRNAs are required for synaptic plasticity.

Minor points:

1. The use of blue/green or blue/green/magenta is difficult to resolve in some places. Swapping blue for cyan would greatly aid in visualizing their data.
2. Make the colouring/formatting of the tables more consistent, its distracting when its constantly changing (also there is no need for a blue background.. just use a basic white table).

Significance

This work would be well received within the field, being at a time where increasing focus on mRNA localization and local protein synthesis are major players in glia along with the more widely studied neurons. Additionally, that mRNAs localized in glia are relevant to neurological disorders also comes at a time where increasingly, especially in neurodegenerative disorders, glia are believed to be drivers of the diseases as well- suggesting that dysregulation of local protein synthesis in glia may play a role. The major weakness of this work is that being largely bioinformatic (from existing datasets), a lot of this is speculative and no conclusive data is shown to demonstrate how/that this glia population is utilizing mRNA localization in protrusions to fuel local protein synthesis for a specific purpose (ie synaptic plasticity).

This work would be of interested to those broadly interested in glial biology and mRNA localization.

The reviewers background is in RNA localization and local protein synthesis in neurons.