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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

In this paper, authors report that radiation, acidic pH, hypoxia, and drugs that interfere with lipid synthesis, all of which affect lipid droplets (LD), also affect the production of small extracellular vesicles (sEVs). In addition, they also report that LD content and sEV secretion are also modulated in CR-CSCs. Authors conclude that sEV formation and secretion is directly linked to LDs, and that their studies may open the way to new clinical perspectives. However, some important issues need to be addressed before the paper can be considered for publication.

My main concern is that the notion that LDs and sEVs are linked remains vague. Do cells contain more LDs and secrete more sEVs because these two pathways are selectively up-regulated via some mechanism that controls both pathways in a concerted manner? Or do cells with more LDs and more sEVs also contain more of everything, perhaps as a result of metabolic activity? A direct corollary of this issue is whether increased sEV secretion reflects more endosomes and lysosomes (e.g. LysoTracker-positive compartments) or whether sEV secretion is selectively up-regulated. At one point, authors argue that cells that secrete more sEVs also contain more MVBs, but this issue remains elusive. To what extent is the increase in LDs and sEVS correlated in particular with an increase in endosome-lysosomes, and ER-Golgi (LDs originate from the ER)? Authors conclude that the data with lipid inhibitors strengthen the connection between LDs and sEVs (Fig 2 and S2). However, is this regulation selective, or does it merely reflect the general effect of these inhibitors on membrane-related processes? The same comment applies to the role of iron metabolism after knockdown of ferritin heavy chain (Fig 3 and S3), acidic pH and X-ray radiation (Fig 4 and S4)

Other comments

1. Which cell line is used for sEV analysis (markers vs contaminants (Fig S1B)? In any case, the data should be shown for both cell types.
2. The Tsg101 blot is not impressive (Fig S1B): the difference between cells and sEVs is not easy to see. It would be nice if blots were quantified.
3. From Fig 1B it cannot be concluded that the size of sEVs ranges from 30 to 200nm: the micrograph only shows a few structures.
4. HT29 cells contain far more LDs than LoVo cells (Fig 1A). Similarly, sEV proteins (CD63, CD81, CD9, Hsc-70) are more abundant in HT29 sEVS than in LoVo sEVs (Fig 1D). However, the sEV preparation from HT29 cells contains only approx. 50% more total protein than LoVo sEVs (Fig S1D-E). Are sEVs prepared from LoVo cells far more contaminated with cell debris etc.. than sEV fractions from HT29 cells?
5. LD staining should be shown for the corresponding populations of cells with high/low CD63 (Fig 1E). Cells in culture can be somewhat heterogeneous, but the difference between low and high CD63 is quite extreme (Fig 1E). Is such high heterogeneity also observed with other proteins of the endocytic and biosynthetic pathways? Authors conclude that cells containing high CD63 levels also contain more MVBs (Fig 1E): are all late endosomal proteins (e.g. LAMP1, RAB7) upregulated in cells with high CD63?
6. Inhibitors of lipid synthesis reduce LD formation (Fig 2B), sEV production and CD63 / CD81/ CD9 secretion (Fig2C-D, Fig S2B). Are the cellular levels of these (and other endosomal) proteins also reduced after inhibitor treatment? Does the stimulation of LD formation with oleic acid also stimulate CD63 synthesis and sEV production?
7. It seems that pH and irradiation increase sEV markers far more significantly (Fig 4 B-C and Fig S4A-E) than FTH1 depletion decreases sEV markers (Fig 3 D-E). In fact, authors mention that they cannot exclude a contamination of sEVs with small apoptotic / autophagic vesicles after irradiation (Fig 4). To facilitate comparison, it would be nice to also show the number of secreted particles per cell (like after FTH1 depletion Fig 3D), as well as the distribution of possible contaminants (e.g. Fig S1). Also, authors state that the increase in the number CD63+ MVBs after irradiation is shown, but this is not the case.
8. Are the proteomic data (Fig 6) with LDlow and LDhigh cells obtained after cell sorting, as in Fig 1E? Did authors compare the proteome of LoVo and HT29 sEVs? How do the protein profiles (in particular proteins involved in lipid metabolism) obtained under different conditions compare with each other, in particular after irradiation (Fig4N) and knockdown of ferritin heavy chain (Fig 3, Fig S3)? It would also be interesting to compare these data with the data obtained in CR-CSCs culture under hypoxia (Fig S5). Are common proteins involved in sEV production and LD biosynthesis identified in the analysis of these biological processes? Is there a common set of proteins/genes revealed by this analysis, which may potentially control sEV production and LD biosynthesis?

Minor comments

1. Some parts of the text are still a bit rough, and should be read and corrected carefully. For example: i) isn't it obvious that a common source of lipids builds up the membrane of sEVS, much like any other membrane (line 90, p.2); ii) what does this sentence mean: "LD have been considered as mere fat storage organelles for a long time, although important evidence could be traced back to the early 1960's". Important evidence for what? iii) why is the acronym AdExo used? iv) (line 138) the text should probably be "sEVs released during 72h were studied" and not "released sEVs were studied ... 72 h after seeding".
2. The captions are far too small in most figures and diagrams (for example x and Y axis in Fig 1C-D, text in Fig 1E; Fig S1; Fig 3C proteins in the heatmap).
3. The color code for LoVO and HT29 cells is reversed in Fig S1D-E
4. In Fig 1D, I cannot see CD81 in the LoVo blot.
5. Wording is not adequate in following sentences: "62.7% of proteins related to the exosomal pathway are downregulated in MCF7 shFTH1 cells" (line 233) and a few lines below: ".. the expression of almost all exosomal markers was downregulated in MCF7 shFTH1 cells" (line 239). Does 62.7% represent all proteins?
6. In Fig 3E authors compare sEV markers secreted by cells treated with shFTH1 or control shRNA. The Anx5 and CD63 blots are not very convincing (quantification would be helpful).
7. The micrographs in Fig 4L are too small: gold particles cannot be seen, even in the high magnification views.
8. The micrographs showing ALIX and CD63 (Fig 4J) in irradiated and unirradiated Panc01 cells should be shown for comparison.

Significance

The topic of the paper is clearly interesting, since the mechanisms that regulate sEV formation and secretion are not fully understood and since the notion that their fate is linked to LDs is potentially exciting.

My expertise: subcellular organization, endocytosis, membrane traffic, organelle biogenesis

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

Learn more at Review Commons

---

Reply to the reviewers

We thank the reviewers for their thoughtful comments. Here we provide a point-by-point response to their reviews. All additional experiments that are present in the revised manuscript, or that we plan to include in the final manuscript, are numbered.

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

The concept introduced by this paper is exciting and novel. However, the current paucity of presented data can lead to incorrect interpretations of the findings and speculations that might not hold true after a more rigorous assessment of the observed phenomenon.

The premise of this study builds upon an interaction between the PAXT complex and nuclear YTH domain containing proteins. However, figures 1B and C should be improved. The interacting band for the ZFC3H1 presented in panel B does not seem to match the size of the construct used in panel C. Is the Flag version of ZFC3H1 expressing a smaller isoform for this protein? __

The reviewer is correct in that endogenous ZFC3H1 (which migrates at 250kD with a minor band at 150kD, see Figure 1B in the initial manuscript) appears to differ from the FLAG-tagged construct as expressed from a plasmid transfected in HEK293 cells (which migrates as two bands at 180kD and 200kD, see Figure 1C in the initial manuscript). For the endogenous protein, the predicted molecular weight is 226kD and the 250kD band disappears when cells are transduced with lentivirus containing shRNAs against ZFC3H1 (see Figure 4A in the initial manuscript), indicating that it is the correct protein. Both the 250kD endogenous protein (*) and the 200kD overexpressed protein (**) in transfected HEK293 and U2OS cells are detected in immunoblots using anti-ZFC3H1 antibodies (see Figure 1 in this document) indicating that the over-expressed protein is indeed ZFC3H1.

[ Figure 1]

_Figure 1. Molecular Weight Size Comparison of Endogenous ZFC3H1 and FLAG-ZFC3H1 (1-1233). _Lysates from HEK293 and U2OS that were either untransfected or transfected with FLAG-ZFC3H1 (1-1233) plasmid. We labelled the bands corresponding to the endogenous ZFC3H1 “*” and FLAG-ZFC3H1 (1-1233) “**”.

We have sequenced the plasmid, and discovered that it contains an additional sequence inserted within the middle of the ZFC3H1 cDNA with a premature stop codon. As such, the version of the protein that is expressed from the plasmid only contains amino acids 1-1233 of the endogenous protein and is missing amino acids 1234-1989. The deleted region only contains TPR repeats, and is not known to interact with any of the well characterized interactors of ZFC3H1 (Wang, Nuc Acid Res 2021, Figure 3). We have renamed this construct FLAG-ZFC3H1 (1-1233). Given these new considerations, our results are consistent with the idea that the N-terminal portion of ZFC3H1 interacts with U1-70K, YTHDC1 and YTHDC2. We will change the text to reflect this.

We are currently in the process of deleting the small insertion to obtain a plasmid that encodes a full length version of human ZFC3H1. For the final manuscript:

Experiment #1) We will repeat the co-immunoprecipitation experiment with the full length FLAG-ZFC3H1 to determine whether it interacts with YTHDC1 and YTHDC2. This will take a few weeks.

__Also, the YTHDC1-2 interaction in panel C is not as convincing considering the negative controls lane show some degree of binding. __

Although the reviewer is correct that there is substantial background binding in the YTHDC1 immunoblot, we disagree with their characterization of the results with the YTHDC2 immunoblot (see Figure 1B-C in the initial manuscript). In the new manuscript we have included:

Experiment #2) A new co-immunoprecipitate of the FLAG-tagged ZFC3H1 (1-1233) from HEK293 cells under more stringent conditions where the background level of YTHDC1 binding to beads is negligible. We have already completed this experiment (see Figure 1D in the revised manuscript).

__Additionally, can the authors test if their RNaseA treatment worked? __

In the new manuscript we have included:

Experiment #3) A new co-immunoprecipitate of FLAG-YTHDC1 immunoblotted for eIF4AIII from HEK293 cell lysates. We find that without RNAse, there is some eIF4AIII in the precipitates but that the levels diminish substantially after RNAse A/T1 treatment. We have already completed this experiment (see Figure 1B in the preliminary revised manuscript).

__Why do you need 18 hours to observe the nuclear export of your modifiable construct when inhibiting METTL3 in figure 3? Is it possible that your observation is secondary to phenotypes these cells develop as a result of blocking METTL3? __

We treated cells for this period of time so that during the expression of the reporter, all of the newly synthesized mRNA is expressed in the absence of m6A methyl transferase activity. For shorter treatment times, it is unclear whether the bulk of the reporter mRNA, which would be synthesized before the treatment, would lose any pre-existing m6A marks, making a negative result hard to interpret. Previously we found that although 50% of intronic polyadenylated (IPA) transcripts from our reporters are rapidly degraded, about 50% are stable and are nuclear retained over extended periods of time (see Lee at al., PLOS ONE 2015; https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0122743 Figure 3B-G). We believe that the bulk of the reporter mRNA that we are visualizing is stable and accumulates in the nucleus. Given that METTL3-depletion inhibits nuclear retention and that versions of the IPA reporter that lack m6A modification motifs are exported, we think that the most likely interpretation of the 18 hour STM2457 treatment experiments is that the lack of methyltransferase activity had a direct effect, rather than an indirect effect, on nuclear retention. We would be open to performing more experiments if the editors insist, however we ordered STM2457 four weeks ago and it has yet to arrive from Sigma-Millipore. Performing this experiment may substantially delay our ability to resubmit the manuscript in a timely manner.

__Is ALKBH5 nuclear and/or cytoplasmic in the cell system used? __

According to The Human Protein Atlas, ALKBH5 is predominantly nuclear in U2OS cells, with some present in the cytoplasm (https://www.proteinatlas.org/ENSG00000091542-ALKBH5/subcellular#human).

In the revised manuscript we have included:

Experiment #4) Data from subcellular fractionation demonstrating that ALKBH5 is present in both the nucleus and cytoplasm that we have already performed (see Figure 4J in the preliminary revised manuscript).

__Reviewer #1 (Significance (Required)):

The study is highly significant __

------

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

Summary: In the manuscript by Lee et al. entitled "N-6-methyladenosine (m6A) Promotes the Nuclear Retention of mRNAs with Intact 5'Splice Site Motifs", the authors provide evidence that m6A modifications within specific regions of transcripts can confer nuclear retention. These results are important because they add to our understanding of how m6A modifications can contribute to post-transcriptional regulation. Although the authors do not quite come out and say this, data seem to be accumulating to suggest that the location of the m6A modifications within a given transcript can dictate the functional consequences of those modifications.__

We thank the reviewer for pointing this out. We have included a few sentences in the new preliminary revised manuscript pointing out that the location of the m6A modification in IPA transcripts, with respect to intact 5’SS and poly(A) signals, may play a role in promoting nuclear retention.

__The current work builds on previous findings from these authors identifying factors critical for retention of intronic polyadenylated (IPA) transcripts. The present study identified m6A modification as one of the signals for the retention of such transcripts. The authors use reporters for their analysis and also examine validated endogenous IPA transcripts. The data presented supports the conclusions albeit they show a surprising finding for one of the m6A erasers, ALKBH5. However, there is some controversy over the mechanism by which ALKBH5 functions and whether the m6A mark is truly reversible, so these results may continue to add to this point of view.

Major Comments: One experiment that might add to the argument would be overexpression of Mettl3 as compared to catalytically inactive Mettl3. The prediction would be that the reporter transcript with intact DRACH sequences would be even more retained in the nucleus in a manner that depends on Mettl3 catalytic activity. For some of the data presented, the reporter is already wholly nuclear so no difference could be detected, but in the U2OS cells shown in Figure 2B, it appears that an increase in nuclear localization might be evident. Such an experiment would add an orthogonal approach to demonstrate that the methylation by Mettl3 is required for retention. If such an experiment would work with the endogenous IPA transcripts shown in Figure 4, but these transcripts may already be too nuclear to detect any increase in nuclear retention.

__

We have performed two experiments that try to address this but they gave negative results:

Experiment #5) We have over-expressed wildtype and a methyl transferase mutant FLAG-METTL3 and assessed the nuclear export/retention of ftz-Δi-5’SS mRNA. There was no effect (see Figure 2 in this document).

[Figure 2]

__Figure 2. Over-expression of METTL3 does not increase the nuclear retention of ftz-Δi-5’SS. __U2OS cells were co-transfected with ftz-Δi-5’SS reporter and either FLAG-METTL3 or FLAG-METTL3-D395A, which lacks methyl-transferase activity (Wang, Mol Cell 2016). Cells were fixed, stained for ftz mRNA by fluorescent in situ hybridization and METTL3 using anti-FLAG antibodies. The nuclear and cytoplasmic distribution of ftz mRNA was quantified as described in the manuscript. Note that this is the average of one independent experiment (each bar consisting of the average of at least 50 cells). We plan to repeat this two more times, but we anticipate that these will show the same result.

We could include this negative data as a supplemental figure. We believe that there are two possible reasons for this experimental result. First, as the reviewer points out, the reporter transcripts are already too nuclear to detect any significant change. Second, METTL3 is part of a larger complex that includes several proteins including METTL14, WTAP and potentially other proteins (for example see Covelo-Molares, Nuc Acid Res 2021). We may need to co-express all of these proteins to see an effect.

Experiment #6) We have also expressed versions of ftz-Δi and ftz-Δi-5’SS mRNA with optimized m6A modification (i.e. DRACH) motifs (AGACT) to enhance methylation (“e-m6A-ftz”). We only observed a slight increase in nuclear retention but it is not significant (see Figure 2A,C in the revised manuscript).

Again, this result could be explained by the fact that the reporter is too nuclear to detect any significant increase in retention. We had originally performed this in parallel with the no-m6A-ftz-Δi-5’SS reporters but did not report this negative data in the original manuscript.

__Some rather minor changes to the presentation of the data could enhance the impact of this study.

Specific Comments:

The primary question in this manuscript is comparing reporters with m6A site (intact DRACH sequences) to those without. For this reason, organizing the data to the +/- DRACH sites are adjacent to one another might make the most sense. This point is evident in Figure 1C where perhaps simply changing the order of the bars presented to put the ones directly compared adjacent would be preferable. Then the p-value would compare sets of data directly adjacent to one another. __

We thank the reviewer for this suggestion and we have made these changes to the figures in the preliminary revised manuscript.

__While the authors show representative fields/cells for most assays, they do an excellent job of providing quantitation as well. One exception is Figure 3D, which shows a single cell image for the most key panel (the 5'SS-containing reporter upon Mettl3 depletion). If there is not a field with more cells, the authors could create a montage. __

In the revised manuscript, we have replaced this image with one containing multiple cells expressing the reporter.

__Minor Comments:

Figure presentation:

The text in a number of the figures is VERY small (Figures 1B,1C, and 4A) for example. __

We have fixed this in the new manuscript.

__Figure 3A includes the label "shRNA:" at the top, but these cells are treated with Mettl3 inhibitor and there does not appear to be any shRNA employed, so this seems like a labeling error. __

We have fixed this in the new manuscript.

__In Figure 3C, the immunoblot of Mettl3, there are three bands that all disappear completely upon knockdown of Mettl3- are these all Mettl3? This should at least be mentioned in the legend and perhaps indicated in the figure. The authors do mention in the text employing shRNAs to target multiple Mettl3 isoforms, so likely this is the case. __

We have clarified these issues in the new manuscript.

__Minor points (some really minor to just polish the presentation for clarity):

The word "since" should only be used if there is a time element- otherwise the word "as" is preferable.

For example on p. 4, the sentence: "Since inhibition of mRNA export typically enhances the nuclear retention of RNAs with intact 5'SS motifs (Lee et al. 2020),.." would more precisely read "As inhibition of mRNA export typically enhances the nuclear retention of RNAs with intact 5'SS motifs (Lee et al. 2020),..". __

We thank the reviewer for pointing this out. We have fixed this issue in the revised manuscript.

__Reviewer #2 (Significance (Required)):

Summary: In the manuscript by Lee et al. entitled "N-6-methyladenosine (m6A) Promotes the Nuclear Retention of mRNAs with Intact 5'Splice Site Motifs", the authors provide evidence that m6A modifications within specific regions of transcripts can confer nuclear retention. These results are important because they add to our understanding of how m6A modifications can contribute to post-transcriptional regulation. Although the authors do not quite come out and say this, data seem to be accumulating to suggest that the location of the m6A modifications within a given transcript can dictate the functional consequences of those modifications.

This study would be of significant interest to those that study gene expression in any context as well as cell biologists as the data add to our understanding of export of mRNA from the nucleus. This work also adds to our understanding of the biological consequences of m6A modification, which is an area of significant interest. In my opinion, the authors could make a broader conclusion that we do, which is that the location of the modification significantly dictates function- an extension of previous findings mostly focused on processed mRNA transcripts. __

-------

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

Quality control of mRNA is vital for all types of cells. In eukaryotic cells, nuclear export of misprocessed mRNAs containing the 5' splice site is prevented. In this manuscript, Lee and colleagues demonstrate that the nuclear retention of intronic polyadenylated transcripts is dependent on m6A modification. Based on the results shown in yeast, they perform immunoprecipitation experiments and demonstrate the interaction between ZFC3H1, a component of the PAXT complex, and YTHDC1 and YTHDC 2, nuclear YTH RNA-binding proteins that recognize m6A-modified transcripts. The study also shows the interaction of U1-70K with YTHDC1 and with ZFC3H1. Depletion of YTHDC1/2 prevents the nuclear retention of IPA transcripts. Additionally, CLIP-seq analysis is performed, demonstrating that m6A modification is enriched around the 5' splice site motif and the 3' polyadenylation site in IPAs. From these observations, they conclude that m6A modification contributes to the quality control of mRNA by promoting nuclear retention of misprocessed transcripts.

Major Points 1. The interaction between ZFC3H1 and YTHDC1 is clearly shown by immunoprecipitation of FLAG-tagged YTHDC1 in Figure 1B. However, the co-purification of YTHDC1 with FLAG-tagged ZFC3H1 in Figure 1C is rather ambiguous. Additionally, the immunoprecipitated samples do not appear to show signals corresponding to FLAG-tagged ZFC3H1, making it unclear if the immunoprecipitation is working. It is essential to provide a better quality result to clarify these observations. __

Please see our responses to reviewer #1. We have repeated the co-immunoprecipitation of FLAG-ZFC3H1 (1-1233) with YTHDC1 under more stringent conditions and have reduced the background binding (see Figure 1B and D in the new manuscript). We have also determined why the FLAG-ZFC3H1 is smaller than expected as the construct contains a premature stop codon. As explained above, we are in the midst of generating a full-length FLAG-ZFC3H1 and we plan to repeat the co-immunoprecipitation with this new construct.

2. While the authors demonstrate that the m6A modification is dispensable for the targeting of IPA reporter transcripts to the nuclear speckles, it would be valuable to investigate whether m6A is required for their exit from the nuclear speckles. Do reporter transcripts with m6A motifs remain in the nuclear speckles at later time points?

We have now analyzed the colocalization of nuclear speckles (SC35) with ftz-Δi-5’SS, which contains both a 5’SS and DRACH motifs, and no-m6A-ftz-Δi-5’SS, which contains a 5’SS but lacks DRACH motifs, at steady state – i.e. after 18-24 hours of transfection (as opposed to at early time points as shown in Figure 2D-E of the initial manuscript). Unexpectedly, we see that both mRNAs continue to colocalize with nuclear speckles, although the no-m6A-ftz-Δi-5’SS mRNA is well exported from the nucleus and its signal in nuclear speckles is faint (see Figure 2F-H in the new manuscript).

Previously, we observed that ftz-Δi-5’SS required the 5’SS motif to remain in nuclear speckles at these later time points (Lee PLOS ONE 2015 and Lee RNA 2022). Upon closer inspection, ftz-Δi-5’SS mRNA also accumulates in additional nuclear foci that are not SC35-positive. Our new results may indicate that m6A marks promote the transfer of mRNAs from nuclear speckles to other foci, but more data is required to make a firm statement. Given this, we plan to conduct further experiments which may take a month to complete:

Experiment #7) We are now assessing whether these additional ftz-Δi-5’SS foci correspond to either YTHDC-positive foci which were previously shown to partially overlap nuclear speckles and sequester m6A-rich mRNAs (Cheng Cancer Cell 2022), or “pA+ RNA foci” which accumulate MTR4/ZFC3H1-targetted RNAs when the nuclear exosome is inhibited (Silla Cell Reports 2018). These foci are enriched in ZFC3H1. We plan on co-staining ftz-Δi, ftz-Δi-5’SS, no-m6A-ftz-Δi and no-m6A-ftz-Δi-5’SS with SC35, YTHDC1 and ZFC3H1 to determine whether m6A may help to transfer mRNAs from nuclear speckles to YTHDC1 or ZFC3H1-enriched foci.

__3. Figures 5B and 5C suggest that ZFC3H1 is required for the degradation of IPA transcripts. However, the range of the vertical axis is inappropriate and it is difficult to assess the extent of the increase in expression levels. Please adjust the vertical axis range for improved clarity. __

We thank the reviewer for the feedback we have added additional graphs with an expanded vertical axis to demonstrate that ZFC3H1 is required for the degradation IPA transcripts.

Minor Points 1. page 4, line 2 "RNAse" should be corrected to "RNase".

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

__ 2. page 7, line 5: Is the statement "prevents the nuclear export and decay of non-functional and misprocessed RNAs" correct? m6A modification promotes the decay of such RNAs. __

We thank the reviewer for pointing this out. We have altered the text to clarify that m6A promotes decay.

__3. Figure 2E: ftz-∆i should be ftz-∆i-5'SS. __

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

__4. Figure 5A: It would be helpful to indicate the number of IPA transcripts analyzed. __

We have included this information.

__Reviewer #3 (Significance (Required)):

Overall, the work is sound and generally well-controlled. This study advances our understanding of the quality control of misprocessed transcripts in higher eukaryotes. This reviewer suggests a few points for clarification or improvement. __

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Quality control of mRNA is vital for all types of cells. In eukaryotic cells, nuclear export of misprocessed mRNAs containing the 5' splice site is prevented. In this manuscript, Lee and colleagues demonstrate that the nuclear retention of intronic polyadenylated transcripts is dependent on m6A modification. Based on the results shown in yeast, they perform immunoprecipitation experiments and demonstrate the interaction between ZFC3H1, a component of the PAXT complex, and YTHDC1 and YTHDC 2, nuclear YTH RNA-binding proteins that recognize m6A-modified transcripts. The study also shows the interaction of U1-70K with YTHDC1 and with ZFC3H1. Depletion of YTHDC1/2 prevents the nuclear retention of IPA transcripts. Additionally, CLIP-seq analysis is performed, demonstrating that m6A modification is enriched around the 5' splice site motif and the 3' polyadenylation site in IPAs. From these observations, they conclude that m6A modification contributes to the quality control of mRNA by promoting nuclear retention of misprocessed transcripts.

Major Points

1. The interaction between ZFC3H1 and YTHDC1 is clearly shown by immunoprecipitation of FLAG-tagged YTHDC1 in Figure 1B. However, the co-purification of YTHDC1 with FLAG-tagged ZFC3H1 in Figure 1C is rather ambiguous. Additionally, the immunoprecipitated samples do not appear to show signals corresponding to FLAG-tagged ZFC3H1, making it unclear if the immunoprecipitation is working. It is essential to provide a better quality result to clarify these observations.
2. While the authors demonstrate that the m6A modification is dispensable for the targeting of IPA reporter transcripts to the nuclear speckles, it would be valuable to investigate whether m6A is required for their exit from the nuclear speckles. Do reporter transcripts with m6A motifs remain in the nuclear speckles at later time points?
3. Figures 5B and 5C suggest that ZFC3H1 is required for the degradation of IPA transcripts. However, the range of the vertical axis is inappropriate and it is difficult to assess the extent of the increase in expression levels. Please adjust the vertical axis range for improved clarity.

Minor Points

1. page 4, line 2 "RNAse" should be corrected to "RNase".
2. page 7, line 5: Is the statement "prevents the nuclear export and decay of non-functional and misprocessed RNAs" correct? m6A modification promotes the decay of such RNAs.
3. Figure 2E: ftz-∆i should be ftz-∆i-5'SS.
4. Figure 5A: It would be helpful to indicate the number of IPA transcripts analyzed.

Significance

Overall, the work is sound and generally well-controlled. This study advances our understanding of the quality control of misprocessed transcripts in higher eukaryotes. This reviewer suggests a few points for clarification or improvement.

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

Summary: In the manuscript by Lee et al. entitled "N-6-methyladenosine (m6A) Promotes the Nuclear Retention of mRNAs with Intact 5'Splice Site Motifs", the authors provide evidence that m6A modifications within specific regions of transcripts can confer nuclear retention. These results are important because they add to our understanding of how m6A modifications can contribute to post-transcriptional regulation. Although the authors do not quite come out and say this, data seem to be accumulating to suggest that the location of the m6A modifications within a given transcript can dictate the functional consequences of those modifications.

The current work builds on previous findings from these authors identifying factors critical for retention of intronic polyadenylated (IPA) transcripts. The present study identified m6A modification as one of the signals for the retention of such transcripts. The authors use reporters for their analysis and also examine validated endogenous IPA transcripts. The data presented supports the conclusions albeit they show a surprising finding for one of the m6A erasers, ALKBH5. However, there is some controversy over the mechanism by which ALKBH5 functions and whether the m6A mark is truly reversible, so these results may continue to add to this point of view.

Major Comments: One experiment that might add to the argument would be overexpression of Mettl3 as compared to catalytically inactive Mettl3. The prediction would be that the reporter transcript with intact DRACH sequences would be even more retained in the nucleus in a manner that depends on Mettl3 catalytic activity. For some of the data presented, the reporter is already wholly nuclear so no difference could be detected, but in the U2OS cells shown in Figure 2B, it appears that an increase in nuclear localization might be evident. Such an experiment would add an orthogonal approach to demonstrate that the methylation by Mettl3 is required for retention. If such an experiment would work with the endogenous IPA transcripts shown in Figure 4, but these transcripts may already be too nuclear to detect any increase in nuclear retention.

Some rather minor changes to the presentation of the data could enhance the impact of this study.

Specific Comments:

The primary question in this manuscript is comparing reporters with m6A site (intact DRACH sequences) to those without. For this reason, organizing the data to the +/- DRACH sites are adjacent to one another might make the most sense. This point is evident in Figure 1C where perhaps simply changing the order of the bars presented to put the ones directly compared adjacent would be preferable. Then the p-value would compare sets of data directly adjacent to one another.

While the authors show representative fields/cells for most assays, they do an excellent job of providing quantitation as well. One exception is Figure 3D, which shows a single cell image for the most key panel (the 5'SS-containing reporter upon Mettl3 depletion). If there is not a field with more cells, the authors could create a montage.

Minor Comments:

Figure presentation:

The text in a number of the figures is VERY small (Figures 1B,1C, and 4A) for example.

Figure 3A includes the label "shRNA:" at the top, but these cells are treated with Mettl3 inhibitor and there does not appear to be any shRNA employed, so this seems like a labeling error.

In Figure 3C, the immunoblot of Mettl3, there are three bands that all disappear completely upon knockdown of Mettl3- are these all Mettl3? This should at least be mentioned in the legend and perhaps indicated in the figure. The authors do mention in the text employing shRNAs to target multiple Mettl3 isoforms, so likely this is the case.

Minor points (some really minor to just polish the presentation for clarity):

The word "since" should only be used if there is a time element- otherwise the word "as" is preferable.

For example on p. 4, the sentence: "Since inhibition of mRNA export typically enhances the nuclear retention of RNAs with intact 5'SS motifs (Lee et al. 2020),.." would more precisely read "As inhibition of mRNA export typically enhances the nuclear retention of RNAs with intact 5'SS motifs (Lee et al. 2020),..".

Significance

Summary: In the manuscript by Lee et al. entitled "N-6-methyladenosine (m6A) Promotes the Nuclear Retention of mRNAs with Intact 5'Splice Site Motifs", the authors provide evidence that m6A modifications within specific regions of transcripts can confer nuclear retention. These results are important because they add to our understanding of how m6A modifications can contribute to post-transcriptional regulation. Although the authors do not quite come out and say this, data seem to be accumulating to suggest that the location of the m6A modifications within a given transcript can dictate the functional consequences of those modifications.

This study would be of significant interest to those that study gene expression in any context as well as cell biologists as the data add to our understanding of export of mRNA from the nucleus. This work also adds to our understanding of the biological consequences of m6A modification, which is an area of significant interest. In my opinion, the authors could make a broader conclusion that we do, which is that the location of the modification significantly dictates function- an extension of previous findings mostly focused on processed mRNA transcripts.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

The concept introduced by this paper is exciting and novel. However, the current paucity of presented data can lead to incorrect interpretations of the findings and speculations that might not hold true after a more rigorous assessment of the observed phenomenon.

The premise of this study builds upon an interaction between the PAXT complex and nuclear YTH domain containing proteins. However, figures 1B and C should be improved. The interacting band for the ZFC3H1 presented in panel B does not seem to match the size of the construct used in panel C. Is the Flag version of ZFC3H1 expressing a smaller isoform for this protein? Also, the YTHDC1-2 interaction in panel C is not as convincing considering the negative controls lane show some degree of binding. Additionally, can the authors test if their RNaseA treatment worked?

Why do you need 18 hours to observe the nuclear export of your modifiable construct when inhibiting METTL3 in figure 3? Is it possible that your observation is secondary to phenotypes these cells develop as a result of blocking METTL3?

Is ALKBH5 nuclear and/or cytoplasmic in the cell system used?

Significance

The study is highly significant

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

Learn more at Review Commons

---

Reply to the reviewers

1. General Statements

We would like to thank the editorial staff and the reviewers for their handling of our manuscript. We were very pleased with the timely communications from Review Commons, and we are grateful to have been assigned this insightful and constructive group of reviewers.

The reviewers were well-suited to evaluate our work based on their stated areas of expertise (cancer biology, image analysis, machine learning, cell-based screening, etc.). As such, we received thoughtful and constructive feedback, which we have already incorporated into our attached revision. We are confident that these reviews have improved our manuscript.

Our goal with this manuscript is to present a proof-of-concept study where high-content imaging and morphological profiling are used to characterize drug resistance in clonal cell lines. The main criticism from reviewers was that our original manuscript may have overstated our method’s ability to discriminate the signal of bortezomib resistance and that any extension beyond cultured cells (to patient samples for example) would require significant follow-up studies. The reviewers suggested that such work would be beyond the scope of our study, and recommended toning down our language to better reflect the limitations of this proof-of-concept work. We have embraced this suggestion, extensively revising our text, and we now believe our language and tone more accurately reflects our results. The reviewers also suggested follow-up computational analyses to more robustly characterize the bortezomib resistance signature. We have performed these analyses and added their description to our revised manuscript. We feel that these analyses have improved understanding of the signature, and will help a reader to gain a deeper understanding of our results and methodology.

The reviewers also suggested several minor changes; many of which we embraced fully, but others that we chose not to incorporate. We felt that a lack of clarity in our text contributed to these reviewer suggestions. In these cases, we improved clarity in the text and responded to each comment point-by-point in the “prefer not to carry out” section. Further, we address all reviewer comments in the following document point-by-point, grouped by common themes across reviewers (e.g., tone, clarity, analyses, etc.).

Lastly, a common theme among reviewer comments was their appreciation for our strong methodology and data transparency (examples pasted below). We are extremely gratified by this observation as we feel this is a particular strength of our manuscript. In addition, we were pleased to see reviewers engaged by our work, acknowledging the interest this manuscript is likely to generate among a broad range of scientific disciplines.

Examples of reviewer appreciation of our strong methodology and data transparency:

Reviewer 1: “However, this does not imply that the same approach can not achieve the goal, perhaps by using other cell painting markers for bortezomib-sensitivity, or with the same markers to assess sensitivity of different drugs. The cell painting + analysis approaches are not new and the clinical impact is questionable, but the technical aspects (data, analysis) are exceptional and the concept may hold as I described above.”

Reviewer 2: “The paper is well written, and the text is clear, as is the presentation of data and transparency of methods being utilized. The methods were applied appropriately and followed established standards in the field. The paper's premise is timely and interesting, addressing a pressing issue in cancer therapy: making informed treatment decisions fast, based on markers found in tumors early in tumor development, and using image-based screening for characterizing drug resistance before treatment could be an option. A fascinating bit of the manuscript is the description of the feature selection from the screen is done systematically, considering the technical and biological variability and technical artifacts and modeling covariates using linear models seems a very appropriate way of doing so and could serve as another proof of concept that this is indeed the most robust way of modeling and removing signal of technical covariates from the data.”

Reviewer 3: “The strengths of this study are the machine learning best practice and detailed methodology. The experiments could be reproduced and statistical analysis is more than adequate. The analysis takes into account batch effects, well position, differences in cell numbers, and other sources of technical variation that complicate high-content image analysis. It is a good exemplar of how unsupervised morphological profiling can be applied to imaging data. The major limitation is the generalizability of this particular method for patient samples. This could be addressed in the Discussion.”

1. Description of the planned revisions

We have incorporated all planned revisions.

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

Text revisions already carried out

1. [Text revision] We have materially toned down our claims in the manuscript in two distinct areas: A) model performance and B) potential clinical application. A) Model performance. We specifically balanced our discussion of the discriminative signal of the Bortezomib Signature. While the signature adequately separated never-before-seen wildtype and resistant clones with metrics well above randomly permuted baselines (accuracy near 80%, average precision about 70%, area under the ROC curve (AUROC) about 84%), there were many limitations that we should have more explicitly highlighted. For example, many individual profiles were incorrectly classified, some clones were predicted entirely incorrectly, and many profiles did not receive Bortezomib Signature scores above the randomly permuted baseline. We have more clearly discussed these limitations and used more balanced language (see key examples of text-based changes below). Additionally, we modified a figure (now Figure 3) to include boxplots of clones that explicitly show the Bortezomib Signature scores of each well profile and permit examination of the strength of the signature for each clone (previously found in Figure 2-Supplement 9). Lastly, we add a new supplementary figure (now Figure 5-Supplement 1) that describes a feature space analysis of misclassified samples. Please note that this figure rearrangement and new analysis helped to balance our claims, but were also performed in response to other tangential reviewer comments. B) Clinical application. In the abstract, introduction, and discussion, we further emphasized that this work is a proof of concept, and that more advances must be made prior to clinical application.

We made these changes in direct response to the following reviewer comments:

Reviewer 1 - Major Comment 1 (relevant excerpts)

While I am convinced that the signature captures morphological phenotypes associated with drug resistance, at the cumulative scale, the discriminative signal of a single cell type seems weak… With Fig. 4, the data fully supports the argument that the bortezomib-signature encodes bortezomib-resistance, but the signal is weak. Thus statements such as "We found the Bortezomib Signature could predict whether a cell line was bortezomib-resistant or bortezomib-sensitive" (line #172) and the specificity statements in the abstract" (line #28) are not supported by the data in my opinion. I would recommend the authors to tune down these and other related statements throughout the manuscript.

Reviewer cross-commenting - Reviewer 1

My main critic is regarding "over selling" a weak discriminative signal. Specifically, I am not convinced that the major claims regarding predicting sensitivity and specificity at the single cell types scales are supported by the data. Since reviewer #2 and #3 did not raise this concern I think it is worth discussion here.

Once these statements are tuned down - I think no significant additional work is needed to make the point that they can measure a discriminative signal. If they want to make these claims, perhaps they'd like to collect more data to gain statistical power (but I am not optimistic this will work at the single cell level).

Personally, I was happy with the authors' choice of cell lines not included in the training dataset. I am not convinced that additional cell lines + validations are necessary for making the point of a proof of principle.

Reviewer cross-commenting - Reviewer 2

I agree that, perhaps, my major criticism of the paper was the manuscript's 'overselling' of claims that were only weakly supported by the data. Yes, if the authors tune down their claims and clearly state that this is an interesting starting point and proof of concept study, it might be ok to publish with only minor revisions. If the claims should be more generalized, then this study needs more data supporting the conclusions and the method's predictive power.

Reviewer 2 - Major Comment 8

Lastly, I find some misfits between the question, the model used, and the conclusions drawn. The authors start by exploring the problem of bortezomib resistance in cancer treatment, which they say is a devastating issue for patients with, e.g., multiple myeloma. Yet, the authors use HCT116 as their model cell line, a microsatellite instable, colorectal cell line with several intrinsic mutations that make it a difficult model to address physiologically relevant medical problems after all. The authors then go on to suppose that their method might be suitable to diagnose resistance in patient samples, but I am not convinced this conclusion can be speculated based on data from HCT cells. I suggest the authors test their approach on at least two other cell lines (maybe from different tissues) and benchmark their results against a dataset of digital pathology where such predictions are made from stained and analyzed tissue slices. This way, after a thorough benchmark against related third-party data sets, the method would significantly gain relevance, the paper would appeal to a broader audience, and the advance gains more merit.

Reviewer 3 - Major Comment 5

It is not clear from the Discussion whether this type of analysis is more broadly applicable to cell lines derived from patients, rather than selected from a parental cell line, or if this approach would be more efficient than genotyping or next-gen sequencing. How many replicates and ground truth cell lines would be necessary for predictive confidence?

We edited the last two sentences of the abstract to tone down specificity claims (“provide evidence”) and clarify that we are establishing a “proof-of-concept framework”.

• This signature predicted bortezomib resistance better than resistance to other drugs targeting the ubiquitin-proteasome system. Our results establish a proof-of-concept framework for the unbiased analysis of drug resistance using high-content microscopy of cancer cells, in the absence of drug treatment.

We revised the last paragraph of the introduction to contrast bortezomib predictions with ixazomib/CB-5083 predictions, and to remove claims about “using microscopy to guide therapy”.

• This morphological signature correctly predicted the bortezomib resistance of seven out of ten clones not included in the signature training dataset. Overall, our results establish a proof-of-concept framework for identifying unbiased signatures of drug resistance using high-content microscopy. The ability to identify drug-resistant cells based on morphological features provides a valuable orthogonal method for characterizing resistance in the absence of drug treatment.

To tone down claims in the figures, we added boxplots to Figure 3 (previous Figure 2) showing specific distribution of signature scores per well profile and updated Figure 4 legend (previous Figure 3).

• Figure 4. Bortezomib Signature has limited ability to characterize clones resistant to other ubiquitin-proteasome system inhibitors.

We modify the following text in the discussion to tone down claims of specificity and clinical utility:

• This Bortezomib Signature correctly predicted the bortezomib resistance of seven out of ten clones not included in the training dataset and was more specific to bortezomib-resistance given its limited ability to identify clones that were resistant to other UPS-targeting drugs.

Though it is unclear whether this method can be extended to patient samples, where identifying intrinsic drug resistance in cells prior to treatment has the potential to improve targeted cancer therapy, our results are an encouraging proof of concept. We expect that further refinement may develop Cell Painting as a tool for identifying drug-resistant cells, perhaps even guiding strategies to overcome intrinsic resistance.

1. [Text revision] We defined LD50 in text (originally line #97), changed description of resistant clone selection to remove main text references to LD90 (originally line #87), and stated drug concentrations used for selection in Methods. We also defined LD90 in the Methods and described its role in determining the drug concentrations to use for clone selection. This change was in response to the following comments:

Reviewer 1 - Minor Comment 2

What is LD90 (line #87)? LD50 (line #97)?

Reviewer 2 - Minor Comment 5

What was the LD 90 per drug on HCT cells? Rather than LD90 foldchanges, absolute concentrations should be used in the results and discussion to allow the reader to vet the conclusions.

• To determine the appropriate drug concentrations to use in order to isolate drug-resistant clones, we performed proliferation assays on HCT116 parental cells with our drugs of interest: bortezomib (proteasome inhibitor), ixazomib (proteasome inhibitor), or CB-5083 (p97 inhibitor) (Fig. 1-Supplement 1 A-D).
• We characterized the bortezomib-resistant clones and found that the median lethal doses (LD50s) were ~2.8- to ~9-fold that of HCT116 parental cells (Fig. 1-Supplement 2 B).
• Briefly, HCT116 cells were plated in 150 mm dishes and grown in the presence of the desired drug at a concentration that resulted in the death of the majority of cells (selection concentrations: bortezomib, 12 nM; ixazomib, 150 nM; CB-5083, 600 and 700 nM).

• Using the data from our proliferation assays, we calculated the median lethal dose (LD50) for each of our drugs of interest by fitting data of normalized growth vs. log[drug concentration] to a sigmoidal dose-response curve using GraphPad Prism (v.9.2.0) (Fig. 1-Supplement 1 D).

• [Text revision] We thank the reviewer for allowing us an opportunity to improve clarity on the clones we used. We now describe the total number of clones generated and removed unnecessary references to specific clones for ease of reading (originally lines #96-98) (We maintain all references to specific clones in the figures, legends, supplement, and methods)

Reviewer 1 - Minor Comment 3

It was not clear to me in the text which and how many cell lines were evaluated and the reader is forced to go to the SI. For example, "(BZ01-10 and BZ clones A and E)" (line #96-97) and "wild-type clones (WT01-05, 10, and 12-15)" (line #98) appeared when presenting the results without a clear explanation and made it harder for me to follow. Summary of the data (for example, based on Figure 2-Supplement 8) can be briefly mentioned in the text to make it more clear for the reader.

We added the following to the second paragraph of the results:

• Together these methods provided a total of twelve bortezomib-resistant, five ixazomib-resistant, five CB-5083-resistant, and twelve bortezomib-sensitive clones as well as HCT116 parental cells for our experiments.

[Text revision] We removed duplicate text (originally lines #115-125).

Reviewer 1 - Minor Comment 5

1. Lines #104-111 were duplicated in lines #114-122.

Reviewer 3 - Minor Comment 4

Ten lines of text are duplicated on page 5.

Reviewer 2 - Minor Comment 4

on page 5, paragraph 4, there is a sizeable copy-and-paste error of text being identically replicated.

1. [Text revision] We provided more intuition of the Bortezomib Signature in the results section (originally lines #150-151).

Reviewer 1 - Minor Comment 6

The "Bortezomib Signature" is a critical measurement but is only briefly mentioned in lines 150-151 ("..based on the direction-sensitive ranking method for phenotype analysis, singscore (Foroutan et al., 2018)"). Please provide more information/intuition.

• We used these 45 features to compute a rank-based resistance score or “Bortezomib Signature” for each well profile based on the direction-sensitive method called singscore (Foroutan et al. 2018). Singscore ranks these 45 resistance-related features on a per sample basis and calculates a normalized score between -1 and 1, with higher values expected for bortezomib-resistant clones and lower values expected for bortezomib-sensitive clones.

• [Text revision] We clarified that DNA sequencing had been performed solely on clones A and E in a previous study (originally lines #88-90). Furthermore, one of the strengths of our approach is that it can identify resistant clones in an unbiased fashion prior to molecular characterization. It is beyond scope to perform these sequencing studies in the present paper.

Reviewer 2 - Minor Comment 3

The authors talk about validating the mutation - PSMB5 by RNA-seq. However, the data for the genotyping/sequencing/characterization of these newly generated BZ-resistant lines are missing.<br />

In the results, we clarify DNA sequencing that was previously performed on clones A and E

• We also isolated bortezomib-sensitive (wild-type; WT) clones by dilution of the HCT116 parental cell line and acquired two bortezomib-resistant clones (BZ clones A and E) both with mutations in PSMB5 identified by RNA sequencing performed in previous work (Fig. 1-Supplement 1 E) (Wacker et al. 2012).

In the last paragraph of the discussion, we highlight the strength of our unbiased approach

• Together, our work has demonstrated the potential for morphological profiling with Cell Painting to be used as an unbiased method to characterize resistance in the absence of drug treatment. Our results indicate that different mechanisms of bortezomib resistance may generate distinct morphological profiles; with larger and broader training datasets, it may be possible to identify signatures for distinct mechanisms of bortezomib resistance as well as signatures of resistance to other drugs. Though it is unclear whether this method can be extended to patient samples, where identifying intrinsic drug resistance in cells prior to treatment has the potential to improve targeted cancer therapy, our results are an encouraging proof of concept. We expect that further refinement may develop Cell Painting as a tool for identifying drug-resistant cells, perhaps even guiding strategies to overcome intrinsic resistance.

• [Text revision] We thank the reviewers for their suggestions. We agree that the description of the experimental design was somewhat unclear and have provided greater detail and clarity, particularly regarding the generation of clones. We used the HCT116 parental cell line to generate drug-resistant clones by identifying single surviving cells after drug treatment and allowing these cells to expand prior to isolating colonies for experimentation. We did not perform experiments to confirm whether these “clones” were isogenic and can not exclude cell migration during expansion or genetic drift as convoluting factors. However, we have provided greater detail in the descriptions of our method for clone isolation in order to address this concern.

Reviewer 1 - Minor Comment 1

More information in Fig. 1's legend would be helpful to follow the experimental design. I found it hard to follow in its current form and had to go back to carefully reading the main text to fully understand.

Reviewer 2 - Minor Comment 6

The description of the resistant clonal populations is confusing. As I understand, no single-cell clones were isolated during the selection procedure. Thus, the training lines are not yet isogenic clones but oligoclonal sub-populations of the parental cell line. The authors could provide more details here and discuss the different characteristics of their sub-populations, e.g., their growth kinetics or molecular alterations.

We bolstered the description in the results.

• We first isolated and characterized drug-resistant cells (Fig. 1 A). To isolate drug-resistant clones, we used an approach we have described previously (Wacker et al. 2012; Kasap, Elemento, and Kapoor 2014) and the HCT116 cell line. These cancer cells express multidrug resistance pumps at low levels and are mismatch repair deficient, providing a genetically heterogeneous polyclonal population of cells (Umar et al. 1994; Papadopoulos et al. 1994; Teraishi et al. 2005) allowing for isolation of drug-resistant clones in 2-3 weeks. We hypothesize that a rapid selection of resistance could favor the isolation of clones with intrinsic resistance. To determine the appropriate drug concentrations to use in order to isolate drug-resistant clones, we performed proliferation assays on HCT116 parental cells with our drugs of interest: bortezomib, ixazomib, or CB-5083 (Fig. 1-Supplement 1 A-D). We also isolated bortezomib-sensitive (wild-type; WT) clones by dilution of the HCT116 parental cell line and acquired two published bortezomib-resistant clones (BZ clones A and E) both with mutations in PSMB5 identified by RNA sequencing performed in previous work (Fig. 1-Supplement 1 E) (Wacker et al. 2012). We characterized the bortezomib-resistant clones and found that the median lethal doses (LD50s) for bortezomib were ~2.8- to ~9-fold that of HCT116 parental cells (Fig. 1-Supplement 2 B). In contrast, bortezomib-sensitive clones had LD50s for bortezomib that ranged from ~0.7- to ~1.2-fold that of HCT116 parental cells (Fig. 1-Supplement 2 A). Together these methods provided a total of twelve bortezomib-resistant, five ixazomib-resistant, five CB-5083-resistant, and twelve bortezomib-sensitive clones as well as HCT116 parental cells for our experiments.

We also updated the legend for Figure 1A.

• Figure 1. Experimental design for using Cell Painting to examine morphological profiles of drug-resistant cells. (A) Graphic of the experimental workflow: we isolated drug-resistant clones by treating parental HCT116 cells with a high dose of the desired drug and then expanded them for experiments. We isolated drug-sensitive clones by diluting HCT116 cells and then expanded them for experiments. We then performed proliferation assays on select clones to screen for multidrug resistance. Next, we performed Cell Painting on both drug-resistant and -sensitive clones, using multiplexed high-throughput fluorescence microscopy of fixed cells followed by feature extraction and morphological profiling to search for features that contribute to a signature of drug resistance.

• [Text revision] We clarified that the Bortezomib Signature did not correspond to well position (originally lines #155-157).

Reviewer 1 - Minor Comment 9

Line #155-156: "We found that the pattern of Bortezomib Signatures corresponded to the cell identity plate layout", the word "not" is missing before "corresponded".

We found that the pattern of Bortezomib Signatures did not correspond to well position relative to the plate (Fig. 2-Supplement 7 B), indicating that the well position for each clone was not strongly contributing to its Bortezomib Signature.

1. [Text revision] We explicitly described the result that some misclassified clones (WT10, WT15, and BZ06) did not have unexpected bortezomib sensitivity as determined by proliferation assays. We also moved the supplementary figure to an updated Figure 3 to better highlight this result (described below in “Figure revisions already carried out”). Lastly, we add a new figure (Figure 5-Supplement 1) to more explicitly analyze the misclassified lines (described below in “New analyses already carried out”).

Reviewer 3 - Minor Comment 3

The bortezomib sensitivity of the WT lines used in the last experiments was determined and did not seem to be greater than parental. This could be mentioned in the text; the figure raises the question and the answer is provided, but it's in the supplemental material.

While the Bortezomib Signature correctly characterized the bortezomib sensitivity of most clones, it consistently misclassified others (WT10, WT15, and BZ06) (Fig 5-Supplement 1 A). Proliferation assays conducted in earlier experiments showed that WT10 and WT15 were sensitive to bortezomib while BZ06 was resistant (Fig. 1-Supplement 2 A and B). By comparing these incorrect predictions with high-confidence correct predictions, we observed differences that varied by clone type, suggesting unique morphology may be driving each of these misclassifications (Fig. 5-Supplement 1 B and C). These results are consistent with the Bortezomib Signature being generalizable to clones not included in the training dataset and suggest that morphological profiling has the potential to identify bortezomib-resistant clones based on the morphological features of cells in the absence of drug treatment.

1. [Text revision] We clarified that the metrics (accuracy and average precision) were based on median Bortezomib Signature scores of all replicate well-level profiles per clone. We can compare samples based on rank, and difference from 95% confidence interval of permuted data. There is no current way for our method to assign a likelihood. Also note that we have updated the discussion to discuss alternative metrics (see Reviewer 1 - Minor Comment 7) These are very important distinctions, and we are grateful to the reviewer for bringing them up.

Reviewer 3 - Major Comment 3

The study classifies cells as binary sensitive or resistant, but would results be improved by scoring based on likelihood of being resistant/sensitive?

Reviewer 3 - Minor Comment 2

It is not clear whether the accuracy was based on a percentage of replicates per cell line that were classified correctly or whether that was referring to classification of the cell line overall as sensitive/resistant.

• We next examined whether the Bortezomib Signature was able to predict the bortezomib resistance of a clone based on morphological profiling data (Fig. 3 A-E and Fig. 3-Supplement 2 A and B). We called the clone bortezomib-resistant if the median Bortezomib Signature of all replicate well profiles was greater than zero and bortezomib-sensitive if the median Bortezomib Signature less than zero. In the training dataset, the Bortezomib Signature correctly predicted the bortezomib resistance of all ten clones, with median Bortezomib Signatures for eight out of ten clones beyond the 95% confidence interval for the randomly permuted data (Fig. 3 A). The accuracy of the Bortezomib Signature was 88% while the average precision was 81% for the training dataset (Fig. 3-Supplement 2 A and B) (see Methods). The signature performed similarly well in the validation dataset (Fig. 3 B), with an accuracy of 92% and an average precision of 89% (Fig. 3-Supplement 2 A and B). In the test dataset the Bortezomib Signature correctly predicted the bortezomib resistance of all clones, though only HCT116 parental cells had a median Bortezomib Signature outside the 95% confidence interval for the randomly permuted data (Fig. 3 C). The test dataset had an accuracy of 80% and an average precision of 68% (Fig. 3-Supplement 2 A and B). Similarly, in the holdout dataset the Bortezomib Signature had an accuracy of 78% and an average precision of 69% (Fig.3 -Supplement 2 A and B), and correctly predicted the bortezomib resistance of twelve out of thirteen clones, with WT01 misclassified as bortezomib-resistant (Fig. 3 D). In the holdout dataset, four of the twelve correctly characterized clones had median Bortezomib Signatures outside the 95% confidence interval for the randomly permuted data.

We also mirrored language when discussing the ixazomib and CB-5083 results.

• However, only two of the four correctly identified ixazomib-resistant clones and one of the three CB-5083-resistant clones had median Bortezomib Signatures outside the 95% confidence interval of the randomly permuted data. The area under the ROC (AUROC) curve for ixazomib-resistant and CB-5083-resistant clones (0.63 and 0.60, respectively) was lower than those calculated for the training, validation, test, and holdout datasets. In addition, many of the Bortezomib Signatures for well profiles of ixazomib- and CB-5083-resistant clones, particularly those for CB-5083-resistant clones, landed within the 95% confidence interval of the randomly permuted data. These results suggest that the Bortezomib Signature is not a general signature of UPS-targeting drug resistance and instead has some specificity for bortezomib.

• [Text revision] We added an explicit note that our image analysis pipelines are also publicly available. Our reporting of our data processing pipelines are documented fully and well above standards in our field. Linking the publicly-available resources with these methods maximizes reproducibility.

Reviewer 1 - Minor Comment 10

Additional details on the processing steps in the analysis pipeline in the Methods will be highly appreciated.

We include all image analysis pipelines at https://github.com/broadinstitute/profiling-resistance-mechanisms (G. Way et al. 2023).

1. [Text revision] We have compared our approach to the on-disease/off-disease scores as introduced in (Heiser et al. 2020). We agree with the reviewer that a discussion of these two methods would help clarify our phenotypic signature concept. The on/off score is about the degree to which a perturbation pushes disease towards a healthy state. In this case we have 3 sets of data: healthy samples (used for training), disease samples (used for training), and the sample we want to score, which should be of the form "disease + perturbation". With our approach, based on singscore, we also have 3 sets of data: sensitive samples (used for training), resistance samples (used for training), and the sample we want to score. Here, our sample we want to score could be anything, not necessarily of the form "resistance + perturbation". Furthermore, singscore does not have the concept of orthogonality to resistance/sensitivity. This would become relevant if we were exploring perturbations or conditions that would induce a resistant cell line to become sensitive, but we are not doing that here. There are other statistical differences (projection vs. rank based etc.) but the key difference is the applicability of the method to the specific problem at hand.

Reviewer 1 - Minor Comment 7

How is the Bortezomib Signature related to the "on-disease"/"off-disease" scores described in https://www.biorxiv.org/content/10.1101/2020.04.21.054387v1.full? Are there other alternatives used for similar binary phenotypic signatures? What is the justification for using these measurements? I would love to see this generalized concept explicitly discussed in the Discussion.

We added the following to the discussion.

• The Bortezomib Signature is conceptually similar to the on-disease/off-disease score (Heiser et al. 2020). Both require three phenotypic measurements: a target phenotype representing ideal, a disease phenotype, and a new phenotype to classify. However, our approach is technically different (non-parametric compared to linear projection) and our goals are different (phenotypic classification compared to perturbation alignment). Other methods also enable phenotype labeling, but they focus on single-sample annotation without regard to a target phenotype (Wawer et al. 2014; Rohban et al. 2017; Simm et al. 2018; Nyffeler et al. 2020).

Figure revisions already carried out

1. [Figure revision] We moved all boxplots from the original Fig. 2-Supplement 9 to the main text (also splitting Fig. 2 into Fig. 2 and 3). From the original Figure 2, we moved the accuracy and average precision bar graphs to the supplement. We also note that this change increases transparency of the discriminative signal of our signature.

Reviewer 1 - Minor Comment 8

I would highly recommend showing the Bortezomib Signatures from Figure 2-Supplement 9. in Fig. 2. This was the main measurement used throughout the manuscript and in my opinion, it is very important to consistently visualize the data along the manuscript, for clarity and easier reader interpretation.

1. [Figure revision] We adjusted the position of the legend in the accuracy and average precision bar graphs (originally Fig. 2 C and D, now Fig. 3-Supplement 2) for clarity. We also note that keeping the bar chart here is standard best practice (compared to a dot plot).

Reviewer 1 - Minor Comment 4

I found the visualization in Fig. 2C-D not intuitive (it is properly explained in the legend). I suggest replacing the accuracy colorbar with a color marker to make it more distinct from the random permutation (|--*--|) The location of the text "mean +- SD of 100 random permutation" made me first think that it is linked to the holdout.

1. [Figure revision] We changed the point distribution in the boxplots (from expanded to standard) to minimize overlap with the boxplot lines. We also updated the legend text to indicate that individual points in boxplots represent the Bortezomib Signature for well profiles. Note, we paste a representative example of this change above (new Figure 3).

Reviewer 3 - Minor Comment 1

I found the box plots somewhat difficult to interpret (especially where the WT lines had a lot of overlap with the red shaded area). Do the points in these charts correspond to replicate wells?

We also update the figure legend.

• Plots show values for individual well profiles (points), range (error bars), 25th and 75th percentiles (box boundaries), and median.

• [Figure revision] [Response to Reviewer 2 - Major Comment 7] We thank the reviewer for allowing us an opportunity to clarify the mechanism. We feel that it is beyond scope of this manuscript to disentangle the molecular alterations that cause bortezomib resistance based on our Cell Painting insights. This wet lab experimental process is arduous and cost prohibitive, and we argue that one of the benefits of taking a morphology approach to resistance status is that we can detect resistant cells (and therefore cells that won’t die when presented with a treatment) without knowing the molecular mechanism.

Nevertheless, the reviewer has encouraged us to enhance the ability for a reader to view and interpret the signature to perhaps more easily facilitate future work. Previously, we presented our signature in text form in Figure 2-Supplement 4 and in heatmap form in Figure 2-Supplement 5. Here, we add a new figure (Figure 2-Supplement 6; pasted below) which will improve interpretability.

Reviewer 2 - Major Comment 7:

Next to feature importance, the authors do not discuss (or I missed) what biology the features represent. Such the reader is left wondering what the actual mechanism of bortezomib resistance could be and if cell painting could shed light on the molecular alterations that cause the treatment resistance. While reviewing, I thus wondered which audience the authors targeted with their manuscript. A more focused analysis of their data that highlights aspects of the study either for the machine learning community, the cell biology community, or the precision oncology community would greatly benefit the manuscript's impact. In its current form, the study's findings seem diluted and spread across a wide range of research questions.<br />

• Figure 2-Supplement 6. Bortezomib Signature visualized by CellProfiler features. Visualization of CellProfiler features contributing to the Bortezomib Signature. Features with high values (mean signature estimates) in resistant cells are purple while features with low values in resistant cells are green. The mean signature estimates were based on Tukey's Honestly Significant Difference test score and the number in each box represents the number of features used to calculate the mean signature estimate.

Additionally, we add the following to the results section:

• We then examined the grouping of features across compartments and channels and found radial distribution features were higher in resistant cells (Fig 2-Supplement 6).

The code change to generate the signature visualization summary is available at: https://github.com/broadinstitute/profiling-resistance-mechanisms/pull/131

New analyses already carried out

1. [New analysis] [Response to Reviewer 2 - Major Comment 5] We agree that a systematic analysis of feature selection methods will provide additional insights not already in the manuscript. Therefore, we have performed two new computational experiments to compare our linear modeling feature selection approach against other standard approaches. We demonstrate that our linear modeling approach is effective at isolating the core differences between resistant and sensitive classes.

Specifically, we performed two analyses: A) UMAP and B) k-means cluster analysis. We analyzed profiles defined by four different feature selection approaches: 1) Using all traditional CellProfiler features; 2) Using the traditional CellProfiler feature selection approach (removing low variance features, high correlating features, etc.); 3) Using 45 random features (same size as Bortezomib Signature); and 4) Using only the bortezomib signature features. We performed Fisher’s exact tests to derive odds ratios of cluster membership by resistance status and calculated Silhouette widths to quantify relative proximity of clusters.

This analysis generates a new supplementary figure (see below), and demonstrates that the linear-modeling-based feature selection isolated the features driving the differences between the clone types (resistance vs. wildtype) while the standard approaches do not as effectively separate.

Reviewer 2 - Major Comment 5:

A fascinating bit of the manuscript is the description of the feature selection from the screen is done systematically, considering the technical and biological variability and technical artifacts and modeling covariates using linear models seems a very appropriate way of doing so and could serve as another proof of concept that this is indeed the most robust way of modeling and removing signal of technical covariates from the data. Yet, I wondered why the authors do not discuss other means of feature selection or dimensionality reduction; further, they need to show how the features cluster the cell lines or why impact (information content) different features deliver. For an audience interested in the technical aspects of cell painting analysis and machine learning based on the data, that would, IMHO, be the most exciting questions.

• Figure 3-Supplement 3. Benchmarking linear-modeling feature selection to separate clones by bortezomib resistance. Uniform Manifold Approximation and Projection (UMAP) analysis of the qualitative separability of (A) resistance status and (B) Bortezomib Signature scores across four different feature spaces. (C) k-means clustering from k=2 to k=14 of average odds ratio, maximum odds ratio (Fisher’s exact test), and Silhouette width using Bortezomib Signature features.

Additionally, we add the following to the results section:

• We then compared our linear-modeling approach to feature selection against other feature spaces and found that the Bortezomib Signature clusters same-type clones (bortezomib-resistant vs. bortezomib-sensitive) with higher enrichment compared to the full feature space, standard feature selection (see Methods), or a random selection of 45 features (Fig 3-Supplement 3).

And methods section, describing this analysis:

• We were also interested in comparing the ability of different feature spaces to cluster clones of the same type (resistant vs. sensitive). This analysis would determine if the Bortezomib Signature features, which we derived using linear modeling to isolate biological from technical variables, had a greater ability to cluster. We compared the Bortezomib Signature against three other feature spaces: 1) the full feature space, 2) standard feature selection (see Image data processing methods), and 3) 45 randomly selected features. We performed two analyses using these four feature spaces including Uniform Manifold Approximation and Projection (UMAP) (McInnes et al. 2018) and k-means clustering. For UMAP, we used default umap-learn parameters to identify two UMAP coordinates per feature space. We then visualized the clusters by their resistance status and Bortezomib Signature score. The UMAP analysis represents a qualitative analysis. Next, we applied k-means clustering with 25 initializations across a range of 2-14 clusters (k). Prior to clustering and for each feature space, we applied principal component analysis (PCA) and transformed each feature space into 30 principal components. This step was necessary to compare k-means clustering metrics, which are sensitive to the feature space dimensionality. We applied a Fisher’s exact test to each cluster using a two-by-two contingency matrix that specified cluster membership for each clone classification (resistant vs. sensitive). We visualized the mean odds ratio and max cluster odds ratio for each feature space across k. A high odds ratio tells us that the feature space effectively clusters clones of the same resistance status. Lastly, we calculated Silhouette width (the average proximity between samples in one cluster to the second nearest cluster) for each feature space across k.

The code change to derive the UMAP coordinates, perform clustering, and generate the figure is available at https://github.com/broadinstitute/profiling-resistance-mechanisms/pull/132

1. [New analysis] [Response to Reviewer 3 - Major Comment 1] We thank the reviewer for this suggestion, which allowed us to explore the misclassified samples in more depth. We added a new supplementary figure in which we summarized all bortezomib clones (wildtype and resistant) in their accuracy based on the bortezomib signature (panel A). We did not include training set samples in this analysis. Using samples that were consistently incorrectly classified with high confidence (three samples: WT15, BZ06, WT10) we performed two separate two-sample Kolmogorov–Smirnov (KS) tests. Specifically, we compared high incorrect wildtype to high correct wildtype and high incorrect resistant to high correct resistant. Our results indicate that most bortezomib signatures were significantly different between correct and incorrect assignments (panel B), and that the signature features varied between resistant and wildtype misclassification tests (panel C).

Reviewer 3 - Major Comment 1:

While the claims are largely substantiated, there are a few points where further consideration would improve the manuscript. Several cell lines were mis-classified with what appears to be a high degree of certainty. Can the authors tell what was driving those predictions? Was there something in the morphological signature that weighed more heavily in those cases?

• Figure 5-Supplement 1. Examining the accuracy of clone classification and misclassification of clones. (A) Proportion of high-confidence correct, low-confidence correct, low-confidence incorrect, and high-confidence incorrect predictions of well profiles across clones in the test, holdout, and validation sets. High-confidence predictions (high) had a Bortezomib Signatures greater (resistant clones) or less than (sensitive) the 95% confidence interval of randomly permuted data while low-confidence predictions (low) had Bortezomib Signatures within the 95% confidence interval of randomly permuted data. (B) Visualization of Kolmogorov-Smirnov (KS) test statistic means of feature groups across channels and cellular compartments. (C) Plot of the KS test statistic means for feature groups in bortezomib-resistant vs. -sensitive cells. Each feature group is color coded by the imaging channel.

Additionally, we add the following to the results section:

• While the Bortezomib Signature correctly characterized the bortezomib sensitivity of most clones, it consistently misclassified others (WT10, WT15, and BZ06) (Fig 5-Supplement 1 A). Proliferation assays conducted in earlier experiments showed that WT10 and WT15 were sensitive to bortezomib while BZ06 was resistant (Fig. 1-Supplement 2 A and B). By comparing these incorrect predictions with high-confidence correct predictions, we observed differences that varied by clone type, suggesting unique morphology may be driving each of these misclassifications (Fig. 5-Supplement 1 B and C). These results are consistent with the Bortezomib Signature being generalizable to clones not included in the training dataset and suggest that morphological profiling has the potential to identify bortezomib-resistant clones based on the morphological features of cells in the absence of drug treatment.

And methods section, describing this analysis:

Some profiles were consistently predicted incorrectly with high confidence but in the opposite direction (see Figure 5-Supplement 1). For a well-level profile to be categorized as high-confidence (in either the correct or incorrect directions), it needed to score beyond the 95% confidence interval of the randomly permuted data range. For example, a high-confidence incorrect resistant profile would have a Bortezomib Signature below 95% confidence interval of the randomly permuted data. To evaluate the features driving the differences in these samples, we applied two-sample Kolmogorov–Smirnov (KS) tests per Bortezomib Signature feature. We applied these tests to two separate groups: 1) misclassified bortezomib-sensitive vs. high-confidence accurate bortezomib-sensitive and 2) misclassified bortezomib-resistant vs. high-confidence accurate bortezomib-resistant.

The code change to generate the UMAP coordinates and figure is available at https://github.com/broadinstitute/profiling-resistance-mechanisms/pull/130

Description of analyses that authors prefer not to carry out

1. [Response to Reviewer 2 - Minor Comments 1 and 2]: These are interesting suggestions! Still, we prefer not to speculate on the biological mechanism of the Bortezomib signature. Connecting morphological features identified as contributing to the Bortezomib Signature by Cell Painting to specific biological pathways would demand considerable cell-based assays to validate. In addition, our analyses suggest that the features contributing to the Bortezomib Signature are spread across a range of cellular compartments and channels, making it difficult to pin down specific mechanisms or pathways as likely contributors to bortezomib resistance. However, we are adding a figure to increase interpretability of the signature, which will aid in developing future hypotheses. Note that the signature was not possible to detect by eye (Fig. 2 A).

Reviewer 2 - Minor Comment 1:

There could be some speculation on the mechanism of Bortezomib resistance concerning the literature with the existing image data. For example, Bortezomib resistance is connected to serine synthesis and how a particular feature could contribute to the known mechanism.<br />

Reviewer 2 - Minor Comment 2:

Along the same lines, the authors could show that larger cells lead to resistance with microscopic images.

2. [Response to Reviewer 2 - Major Comment 8]: We appreciate the reviewer’s concern that our work using HCT116 clonal cells lines may not directly reflect results from patient samples. Our choice was based on previously published work demonstrating the efficiency with which HCT116 cells generate resistant clones due to diminished DNA mismatch repair and decreased expression of drug efflux pumps. Since our work is a proof of concept rather than a comprehensive demonstration of translating morphological profiling into clinical practice, we believe that experiments using multiple patient cell lines from different tissues as well as digital pathology records to be beyond the scope of this work. We instead chose to tone down the language of our manuscript to more clearly acknowledge the limitations of our work and clarify this as a proof of concept.

Reviewer 2 - Major Comment 8 (relevant excerpt):

I suggest the authors test their approach on at least two other cell lines (maybe from different tissues) and benchmark their results against a dataset of digital pathology where such predictions are made from stained and analyzed tissue slices. This way, after a thorough benchmark against related third-party data sets, the method would significantly gain relevance, the paper would appeal to a broader audience, and the advance gains more merit.<br />

3. [Response to Reviewer 3 - Major Comment 2]: The bortezomib sensitivity of ixazomib- and CB-5083-resistant clones was not determined, and hence can not be ruled out as a possible explanation for their high Bortezomib Signature scores. However, we prefer not to conduct additional proliferation assays for the misclassified clones (IX02, WT06, CB14, CB16) in the presence of bortezomib to determine whether coincidental bortezomib resistance might explain the signature performance. Our rationale is that three other misclassified clones (WT10, WT15, and BZ06) had the expected bortezomib sensitivity in proliferation assays (Fig. 1-Supplement 2), meaning that additional proliferation assays may not reveal any insights regarding the signature performance.

Reviewer 3 - Major Comment 2:

Was the bortezomib sensitivity of the IX (or CB) resistant cell lines determined? If there were differences, this could explain some of the variation in the morphological signatures. This could be easily done in one or two growth experiments.

4. [Response to Reviewer 2 - Major Comment 7]: Thank you for pointing this out. Our goal is to keep the study multi-disciplinary. We are adding a figure to increase interpretability of the signature, and adding text-based clarifications.

Reviewer 2 - Major Comment 7 (relevant excerpt):

While reviewing, I thus wondered which audience the authors targeted with their manuscript. A more focused analysis of their data that highlights aspects of the study either for the machine learning community, the cell biology community, or the precision oncology community would greatly benefit the manuscript's impact. In its current form, the study's findings seem diluted and spread across a wide range of research questions.<br />

5. [Response to Reviewer 2 and 3 - Major Comments 6 and 4]: We prefer not to expand the scope of the model to predict other drug signatures. This would require a substantial amount of work to generate the appropriate drug-resistant clones, collect the imaging data, and analyze it, and we think it important to convey the purpose of our paper is proof of concept. We do not feel that the time invested in performing this analysis would result in adequate returns beyond what we already demonstrate.

Reviewer 2 - Major Comment 6.

Interestingly, the Bortezomib signature is specific to the drug and not a broad range of proteasomal inhibitors. However, seeing the common features between all the proteasomal inhibitors would be interesting.

Reviewer 3 - Major Comment 4

There was some predictive ability of the Bortezomib Signature for ixazomib resistance. Were there some features that were correlated with IX-resistance, i.e. UPS pathway, versus specific to bortezomib? Do the features suggest anything about resistance mechanisms or is the feature set too abstruse to interpret?

References

Foroutan, Momeneh, Dharmesh D. Bhuva, Ruqian Lyu, Kristy Horan, Joseph Cursons, and Melissa J. Davis. 2018. “Single Sample Scoring of Molecular Phenotypes.” BMC Bioinformatics 19 (1): 404.

Heiser, Katie, Peter F. McLean, Chadwick T. Davis, Ben Fogelson, Hannah B. Gordon, Pamela Jacobson, Brett Hurst, et al. 2020. “Identification of Potential Treatments for COVID-19 through Artificial Intelligence-Enabled Phenomic Analysis of Human Cells Infected with SARS-CoV-2.” bioRxiv. https://doi.org/10.1101/2020.04.21.054387.

McInnes, Leland, John Healy, Nathaniel Saul, and Lukas Großberger. 2018. “UMAP: Uniform Manifold Approximation and Projection.” Journal of Open Source Software 3 (29): 861.

Nyffeler, Johanna, Clinton Willis, Ryan Lougee, Ann Richard, Katie Paul-Friedman, and Joshua A. Harrill. 2020. “Bioactivity Screening of Environmental Chemicals Using Imaging-Based High-Throughput Phenotypic Profiling.” Toxicology and Applied Pharmacology 389 (January): 114876.

Rohban, Mohammad Hossein, Shantanu Singh, Xiaoyun Wu, Julia B. Berthet, Mark-Anthony Bray, Yashaswi Shrestha, Xaralabos Varelas, Jesse S. Boehm, and Anne E. Carpenter. 2017. “Systematic Morphological Profiling of Human Gene and Allele Function via Cell Painting.” eLife 6 (March). https://doi.org/10.7554/eLife.24060.

Simm, Jaak, Günter Klambauer, Adam Arany, Marvin Steijaert, Jörg Kurt Wegner, Emmanuel Gustin, Vladimir Chupakhin, et al. 2018. “Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.” Cell Chemical Biology 25 (5): 611–18.e3.

Wacker, Sarah A., Benjamin R. Houghtaling, Olivier Elemento, and Tarun M. Kapoor. 2012. “Using Transcriptome Sequencing to Identify Mechanisms of Drug Action and Resistance.” Nature Chemical Biology 8 (3): 235–37.

Wawer, Mathias J., Kejie Li, Sigrun M. Gustafsdottir, Vebjorn Ljosa, Nicole E. Bodycombe, Melissa A. Marton, Katherine L. Sokolnicki, et al. 2014. “Toward Performance-Diverse Small-Molecule Libraries for Cell-Based Phenotypic Screening Using Multiplexed High-Dimensional Profiling.” Proceedings of the National Academy of Sciences of the United States of America 111 (30): 10911–16.

Way, Gregory, Yu Han, David Stirling, and Shantanu Singh. 2023. Broadinstitute/profiling-Resistance-Mechanisms: Analysis for Preprint. Zenodo. https://doi.org/10.5281/ZENODO.7803787.

Way, Gregory P., Maria Kost-Alimova, Tsukasa Shibue, William F. Harrington, Stanley Gill, Federica Piccioni, Tim Becker, et al. 2021. “Predicting Cell Health Phenotypes Using Image-Based Morphology Profiling.” Molecular Biology of the Cell 32 (9): 995–1005.

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Summary

This study aimed to determine a morphological signature based on CellPainting that could predict resistance of multiple myeloma cells to bortezomib. Bortezombi-resistant clones were derived from parental wild type cells and tested for multidrug resistance. Best practice machine learning methods were applied to identify features that were not correlated with technical variation or nonspecific heterogeneity between cell lines. A Bortezomib Signature comprised of 45 selected features complied using a robust ranked method was described. This signature score was then used to classify cell lines, including wild-type and bortezomib-resistant clones not included in the training set and clonal lines selected for resistance to other drugs. The Bortezomib Signature performed better than chance for predicting resistance to this drug in validation and holdout datasets, and for an independent dataset of clones not used in the initial training. Some predictive power was observed for a drug targeting the same pathway (UPS), but with lower accuracy.

Major comments

While the claims are largely substantiated, there are a few points where further consideration would improve the manuscript.<br /> Several cell lines were mis-classified with what appears to be a high degree of certainty. Can the authors tell what was driving those predictions? Was there something in the morphological signature that weighed more heavily in those cases?<br /> Was the bortezomib sensitivity of the IX (or CB) resistant cell lines determined? If there were differences, this could explain some of the variation in the morphological signatures. This could be easily done in one or two growth experiments.<br /> The study classifies cells as binary sensitive or resistant, but would results be improved by scoring based on likelihood of being resistant/sensitive?<br /> There was some predictive ability of the Bortezomib Signature for ixazomib resistance. Were there some features that were correlated with IX-resistance, i.e. UPS pathway, versus specific to bortezomib? Do the features suggest anything about resistance mechanisms or is the feature set too abstruse to interpret?<br /> It is not clear from the Discussion whether this type of analysis is more broadly applicable to cell lines derived from patients, rather than selected from a parental cell line, or if this approach would be more efficient than genotyping or next-gen sequencing. How many replicates and ground truth cell lines would be necessary for predictive confidence?

Minor comments

I found the box plots somewhat difficult to interpret (especially where the WT lines had a lot of overlap with the red shaded area). Do the points in these charts correspond to replicate wells?<br /> It is not clear whether the accuracy was based on a percentage of replicates per cell line that were classified correctly or whether that was referring to classification of the cell line overall as sensitive/resistant.<br /> The bortezomib sensitivity of the WT lines used in the last experiments was determined and did not seem to be greater than parental. This could be mentioned in the text; the figure raises the question and the answer is provided, but it's in the supplemental material.<br /> Ten lines of text are duplicated on page 5.

Significance

The strengths of this study are the machine learning best practice and detailed methodology. The experiments could be reproduced and statistical analysis is more than adequate. The analysis takes into account batch effects, well position, differences in cell numbers, and other sources of technical variation that complicate high-content image analysis. It is a good exemplar of how unsupervised morphological profiling can be applied to imaging data. The major limitation is the generalizability of this particular method for patient samples. This could be addressed in the Discussion.

The advances presented here are largely technical, as machine learning best practices are implemented to address a specific type of drug resistance.

This study would be especially valuable to computationally-oriented biologists and has some translational appeal, which could be broadened by including some more information in the Discussion regarding the logistics of this approach in the clinic and whether the signatures identified have interpretability as well as predictive power.

Areas of expertise: image analysis, systems biology, cancer biology

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

Summary:

In the study reviewed herewith, Kelley et al. present an interesting approach to evaluate whether image-based profiling via the cell painting assay can enable a model to predict if a cell line is resistant to the anti-cancer drug bortezomib (a specific inhibition of the proteasome). Therefore, they employed the human colorectal cancer-derived derived cell line HCT116 and used a previously published selection protocol to derive bortezomib resistant clonal subpopulation. These sub-populations were then subjected to cell painting, and it was tested (by dividing the data set into training, test, validation, and holdout) if a machine learning model could be trained on selected image-derived features that would predict if the cell line is indeed resistant to bortezomib treatment. This worked in 7 out of ten cases and two commercially available resistant HCT116 clones. Theoretically, this implies that image-based cellular profiling of tissue materials could work as a fast and reliable method to gauge the treatment resistance of cancer patients before treatment and open new avenues for personalized medicine.

Major comments:

• the paper is well written, and the text is clear, as is the presentation of data and transparency of methods being utilized.
• the methods were applied appropriately and followed established standards in the field.
• The paper's premise is timely and interesting, addressing a pressing issue in cancer therapy: making informed treatment decisions fast, based on markers found in tumors early in tumor development, and using image-based screening for characterizing drug resistance before treatment could be an option.
• A fascinating bit of the manuscript is the description of the feature selection from the screen is done systematically, considering the technical and biological variability and technical artifacts and modeling covariates using linear models seems a very appropriate way of doing so and could serve as another proof of concept that this is indeed the most robust way of modeling and removing signal of technical covariates from the data.
• Yet, I wondered why the authors do not discuss other means of feature selection or dimensionality reduction; further, they need to show how the features cluster the cell lines or why impact (information content) different features deliver. For an audience interested in the technical aspects of cell painting analysis and machine learning based on the data, that would, IMHO, be the most exciting questions.
• Interestingly, the Bortezomib signature is specific to the drug and not a broad range of proteasomal inhibitors. However, seeing the common features between all the proteasomal inhibitors would be interesting.
• Next to feature importance, the authors do not discuss (or I missed) what biology the features represent. Such the reader is left wondering what the actual mechanism of bortezomib resistance could be and if cell painting could shed light on the molecular alterations that cause the treatment resistance. While reviewing, I thus wondered which audience the authors targeted with their manuscript. A more focused analysis of their data that highlights aspects of the study either for the machine learning community, the cell biology community, or the precision oncology community would greatly benefit the manuscript's impact. In its current form, the study's findings seem diluted and spread across a wide range of research questions.
• Lastly, I find some misfits between the question, the model used, and the conclusions drawn. The authors start by exploring the problem of bortezomib resistance in cancer treatment, which they say is a devastating issue for patients with, e.g., multiple myeloma. Yet, the authors use HCT116 as their model cell line, a microsatellite instable, colorectal cell line with several intrinsic mutations that make it a difficult model to address physiologically relevant medical problems after all. The authors then go on to suppose that their method might be suitable to diagnose resistance in patient samples, but I am not convinced this conclusion can be speculated based on data from HCT cells. I suggest the authors test their approach on at least two other cell lines (maybe from different tissues) and benchmark their results against a dataset of digital pathology where such predictions are made from stained and analyzed tissue slices. This way, after a thorough benchmark against related third-party data sets, the method would significantly gain relevance, the paper would appeal to a broader audience, and the advance gains more merit.

Minor comments

• There could be some speculation on the mechanism of Bortezomib resistance concerning the literature with the existing image data. For example, Bortezomib resistance is connected to serine synthesis and how a particular feature could contribute to the known mechanism.
• Along the same lines, the authors could show that larger cells lead to resistance with microscopic images.
• The authors talk about validating the mutation - PSMB5 by RNA-seq. However, the data for the genotyping/sequencing/characterization of these newly generated BZ-resistant lines are missing.
• on page 5, paragraph 4, there is a sizeable copy-and-paste error of text being identically replicated.
• What was the LD 90 per drug on HCT cells? Rather than LD90 foldchanges, absolute concentrations should be used in the results and discussion to allow the reader to vet the conclusions.
• The description of the resistant clonal populations is confusing. As I understand, no single-cell clones were isolated during the selection procedure. Thus, the training lines are not yet isogenic clones but oligoclonal sub-populations of the parental cell line. The authors could provide more details here and discuss the different characteristics of their sub-populations, e.g., their growth kinetics or molecular alterations.

Referees cross-commenting

I agree that, perhaps, my major criticism of the paper was the manuscript's 'overselling' of claims that were only weakly supported by the data. Yes, if the authors tune down their claims and clearly state that this is an interesting starting point and proof of concept study, it might be ok to publish with only minor revisions. If the claims should be more generalized, then this study needs more data supporting the conclusions and the method's predictive power.

Significance

In its current form, the manuscript describes an incremental technical advance that addresses an interesting premise for precision oncology but explores it on a single cell line. The manuscript is timely in that it adds to a growing body of research around the utilization of image-based profiling in various areas of biomedical research using cell painting to create reference datasets for training advanced machine learning models for diagnosis. This research might be interesting and relevant for cell biology, precision medicine, oncology, image-based profiling, and machine-learning communities.

My expertise includes image-based profiling, cell-based screening, assay development, functional genomics, cancer research, drug discovery, machine learning, and data science. There is no aspect of the study I cannot review.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

The authors use Cell Painting, a high-content image-based phenotypic assay, to distinguish between clonal cancer cell lines that are resistant versus sensitive to a proteasome inhibitor anti-myeloma drug called bortezomib. The authors characterized a high-dimensional cell morphology signature for bortezomib-resistance, evaluated it on an independent subset of cell lines, and evaluated specificity in respect to other drugs targeting the ubiquitin-proteasome system. The authors thus propose image-based morphology characterization as an alternative method for characterizing drug resistance.

Strengths: solid methodology - cell lines validation of drug resistance, extensive data collection, thorough validation of the analysis pipeline, avoiding potential confounders, biases and proper data partitioning to test and hold-out (what the authors refer to as "machine learning best practices").

Weakness: weak discriminative signal. Some aspects of the writing could be improved to make the manuscript easier to follow (see Minor comments).

Major comments:

While I am convinced that the signature captures morphological phenotypes associated with drug resistance, at the cumulative scale, the discriminative signal of a single cell type seems weak. Specifically, it is not clear whether the signature can effectively capture the drug resistance of a single cell line. In Figure 2-Supplement 9, considering the test (C) and the holdout (D), only 1/9 BZ clones' median signatures were beyond the 95% confidence interval, with 4/6 and 2/6 WT cell types with median signatures beyond the positive and negative 95% confidence interval correspondingly. When defining bortezomib-sensitivity according to the median signatures' sign (>0 or <0) of a cell line, Figure 2-Supplement 9 shows that in the test+holdout there are 9/9 correct bortezomib-resistance (BZ) and 6/7 correct bortezomib-sensitive (WT) predictions. However, similar discrimination levels also appeared in the other drugs (ixazomib, CB-5083), making the statements about specificity less grounded. When the authors evaluate the AUROC they report ~0.6 (line #194) for the non-specific (ixazomib, CB-5083) drugs versus ~0.75 for bortezomib-resistance (line #202). With Fig. 4, the data fully supports the argument that the bortezomib-signature encodes bortezomib-resistance, but the signal is weak. Thus statements such as "We found the Bortezomib Signature could predict whether a cell line was bortezomib-resistant or bortezomib-sensitive" (line #172) and the specificity statements in the abstract" (line #28) are not supported by the data in my opinion. I would recommend the authors to tune down these and other related statements throughout the manuscript. An alternative would be to increase the number of wells and see whether this weak signal can indeed be statistically amplified with many replicates to make a robust and specific characterization of a cell line's bortezomib-sensitivity (but I assume this is a lot of work and probably out of scope of this manuscript). I think it is also important to discuss in more detail the interpretation of these results (including Figure 2-Supplement 9), in this context, in the Discussion.

Minor comments:

Suggested clarifications (some might be less relevant if the manuscript is designed for experts in the more clinical domain who are familiar with these terms / style):

1. More information in Fig. 1's legend would be helpful to follow the experimental design. I found it hard to follow in its current form and had to go back to carefully reading the main text to fully understand.
2. What is LD90 (line #87)? LD50 (line #97)?
3. It was not clear to me in the text which and how many cell lines were evaluated and the reader is forced to go to the SI. For example, "(BZ01-10 and BZ clones A and E)" (line #96-97) and "wild-type clones (WT01-05, 10, and 12-15)" (line #98) appeared when presenting the results without a clear explanation and made it harder for me to follow. Summary of the data (for example, based on Figure 2-Supplement 8) can be briefly mentioned in the text to make it more clear for the reader.
4. I found the visualization in Fig. 2C-D not intuitive (it is properly explained in the legend). I suggest replacing the accuracy colorbar with a color marker to make it more distinct from the random permutation (|--*--|) The location of the text "mean +- SD of 100 random permutation" made me first think that it is linked to the holdout.
5. Lines #104-111 were duplicated in lines #114-122.
6. The "Bortezomib Signature" is a critical measurement but is only briefly mentioned in lines 150-151 ("..based on the direction-sensitive ranking method for phenotype analysis, singscore (Foroutan et al., 2018)"). Please provide more information/intuition.
7. How is the Bortezomib Signature related to the "on-disease"/"off-disease" scores described in https://www.biorxiv.org/content/10.1101/2020.04.21.054387v1.full? Are there other alternatives used for similar binary phenotypic signatures? What is the justification for using these measurements? I would love to see this generalized concept explicitly discussed in the Discussion.
8. I would highly recommend showing the Bortezomib Signatures from Figure 2-Supplement 9. in Fig. 2. This was the main measurement used throughout the manuscript and in my opinion, it is very important to consistently visualize the data along the manuscript, for clarity and easier reader interpretation.
9. Line #155-156: "We found that the pattern of Bortezomib Signatures corresponded to the cell identity plate layout", the word "not" is missing before "corresponded".
10. Additional details on the processing steps in the analysis pipeline in the Methods will be highly appreciated.

Referees cross-commenting

My main critic is regarding "over selling" a weak discriminative signal. Specifically, I am not convinced that the major claims regarding predicting sensitivity and specificity at the single cell types scales are supported by the data. Since reviewer #2 and #3 did not raise this concern I think it is worth discussion here.

Once these statements are tuned down - I think no significant additional work is needed to make the point that they can measure a discriminative signal. If they want to make these claims, perhaps they'd like to collect more data to gain statistical power (but I am not optimistic this will work at the single cell level).

Personally, I was happy with the authors' choice of cell lines not included in the training dataset. I am not convinced that additional cell lines + validations are necessary for making the point of a proof of principle.

Significance

Cell Painting was applied to many applications, but as far as I am aware this is the first attempt for an image-based phenotypic characterization of drug resistance. While the authors established that this approach can measure, to some extent, bortezomib-sensitivity, at the current state of the results, I am not convinced that cell painting can be practically used to assess bortezomib-sensitivity of a single cell line. However, this does not imply that the same approach can not achieve the goal, perhaps by using other cell painting markers for bortezomib-sensitivity, or with the same markers to assess sensitivity of different drugs. The cell painting + analysis approaches are not new and the clinical impact is questionable, but the technical aspects (data, analysis) are exceptional and the concept may hold as I described above.

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

Learn more at Review Commons

---

Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity):

Summary: Forer and Otsuka provide first-rate evidence for tethers fixed in place between separating anaphase chromosomes using electron tomography. The authors traced the anaphase movement of a number of living cells before fixation for examination using electron tomography. The manuscript is clearly written and provides an excellent introduction and discussion of the known literature. The reader will have an excellent background to see the importance of this work.

Major comments:<br /> - Are the claims and the conclusions supported by the data or do they require additional experiments or analyses to support them?

No further experiments are needed. The data are very supportive, and extremely clear.<br /> - Are the data and the methods presented in such a way that they can be reproduced? Yes.<br /> - Are the experiments adequately replicated and statistical analysis adequate? Yes.

Minor comments:<br /> - Are prior studies referenced appropriately? Yes.<br /> - Are the text and figures clear and accurate? Absulotely.<br /> - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

The authors are to congratulated on their major contribution to this study on tethers between separated daughter chromosomes. It is a tpur deforce to go from the living cells to fixing and identifying the same separated chromosomes using electron tomography to see the ultrastructure of the fibers seen fir.

Referees cross-commenting<br /> Thank you reviewer #2. The manuscript should be published. It is an excellent contribution.

We thank the reviewer for the appreciation of the clarity and quality of our work.

Reviewer #1 (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.

This manuscript is the first to use electron tomography to identify the tethers between separated anaphase chromosomes. Forer and the laetMichael Berns and their co-authors have published a number of papers using phase microscopy and lasers to report on the physical nature and elastic properties of these fibres in the past. Forer and Otsuka have presented first-rate evidence for the reality of these structures using electron tomography. This manuscript should highlighted in the published journal.<br /> The chemical identity of these fibers as the authors state is unclear.

The following aspects are important:

• Audience: describe the type of audience ("specialized", "broad", "basic research", "translational/clinical", etc...) that will be interested or influenced by this research; how will this research be used by others; will it be of interest beyond the specific field?

This exciting contribution will be read by anyone interested in mitosis. It will be of interest to all Cell Biologists because of the careful manner in which the living cells were studied before they were fixed for examination using electron tomography. The readers will be dreaming how they can use this process on their Cell Biology problems._

• 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.

I am a cell Biologist who has made contributions, both in light microscopy and in transmission microscopy on diving cells, both in tissue culture and in situ in aviav and zebrafish embryos.

We thank the reviewer for appreciating the significance of our work.

Reviewer #2 (Evidence, reproducibility and clarity):

In this paper, the authors use light microscopy and electron tomography to study anaphase chromosomes in crane fly spermatocytes. They find that there are two "tether" structures that connect telomeres of sister chromatids. One tether is thicker (denser) and extends between sister chromatids during early but not late anaphase, whereas a second, less-dense tether maintains contact with both sister chromatids in all examined stages of anaphase. The paper makes arguments as to what the tethers could or could not be. Specifically, they are too numerous to be ultrafine DNA bridges seen in various normal or abnormal segregation events and they also do not affect anaphase chromosome motion the same way ultrafine DNA bridges do.

Major comments:<br /> The major claim that there are tethers that connect sister chromatids in anaphase is supported by the data. Moreover, the data resolves two types of tethers on the basis of their density. While it is unclear what the composition of the tethers are, the paper makes a convincing case that they cannot be the DNA ultrafine bridges seen in other studies. The discussion has sufficient caveats that most readers will see that more work is needed to identify the composition of the two tethers. In my opinion, no further experiments are needed to support the modest claims of this paper. Therefore, I only have minor comments that may hopefully improve the paper's clarity.

We thank the reviewer for the positive evaluation of our work.

Minor comments:<br /> It was argued that the tethers reported here were also seen in other species and cellular contexts, where the imaging work was done with projection EM imaging. Presumably, what is new here is the usage of electron tomography. It would help readers if the authors explained why the electron tomography done here was essential to arrive at key conclusions.

Thank you for the useful comment. We have added the explanation of why electron tomography was critical to visualise small tether structures to the last paragraph of the Discussion on page 7.

p.3 mitochondria appeared to be fixed properly ... (e.g., Figs. 1C, 2B) - I don't see any mitochondria in any figures. Perhaps this observation should be noted as "not shown"?

We thank the reviewer for pointing this out. We have added an electron micrograph of mitochondria to the Supplementary Figure 1.

p.3 The images shown in Figs. 1, 2, 4 - The figures should be called out in the order; in this case, Fig 3 has not been called out yet.

We have corrected the order of the figures.

p.4 we did not find any other connecting structures - Because the sample was processed by traditional EM methods, it's safer to add a caveat that other connecting structures could be missed if they were disrupted by sample prep or if they did not pick up stain as well as the two structures presented in this paper.

We have clarified that our sample was chemically fixed in the first paragraph of the Discussion on page 4. Because the details of how our samples were prepared are described in the Method section, we did not add further details to this paragraph.

p.7 we expect such structures to be commonly seen in other cell types as well if they are examined carefully - Instead of saying that examinations should be done "carefully", it would be more helpful to specify how other cell types should be examined. This work shows that the bridges can be found if the cells are either sectioned parallel to the spindle axis or if a sufficiently large volume is sampled.

We have now clarified that 3D electron microscopy techniques such as electron tomography are critical to visualise small tether structures in the last paragraph of the Discussion on page 7.

Please use consistent spelling/hyphenation of ultrafine/ultra-fine and word choice (strands vs. bridges).

Referees cross-commenting<br /> I agree with my co-reviewers's comments and have no further suggestions._

Reviewer #2 (Significance):

This may be the first use of electron tomography to study the structural details of tethers that connect chromosomes in anaphase cells. The data is of sufficient quality to reveal differences in density. Namely, one class of tether appears to be an extension of the chromosome while the other class is composed of thin filaments. This study is novel in that it characterizes a mitosis-associated complex that is poorly studied compared to the microtubule-based spindle apparatus and the kinetochore. Hopefully, the tethers will draw more attention and further characterization by methods like super-resolution microscopy and cryo-electron microscopy. My expertise is in chromatin, mitotic machines, and cryo-electron tomography.

We thank the reviewer for appreciating the novelty and the impact of our work.

Reviewer #3 (Evidence, reproducibility and clarity):

Summary:

Tethers between telomeres of chromosomes in anaphase were inferred from earlier studies of laser microbeam cutting experiments. The current paper presents images from electron tomography of crane fly spermatocytes that substantiates the earlier inference. The authors deduce that the darker filaments and the lighter filaments that they visualize may be the structural tethers at telomeres.

Major comments:

The experiments are carefully done, and the conclusions are appropriately worded to qualify any caveats. This short communication is well-presented, and I have only a few comments._

We thank the reviewer for appreciating the clarity and quality of our work.

The authors should expand their list of references on bridges to include those listed by Warecki et al (Curr Biol 33:1-17, 2023; refs 15-26, etc).

We do not think it is necessary to expand the list of references for ultra-fine DNA bridges. In the article we submitted, we discussed the Warecki at al article in the penultimate paragraph of the Discussion; we concluded that the bridges that Warecki at al described are different from ours in having so few per cell that they couldn’t be tethers, and further that there was no evidence that those bridges were elastic. For those reasons, we do not find discussion of those proteins relevant to tethers, any more than would listing all the proteins associated with ultra-fine DNA bridges be relevant to the elastic tethers.

In the Discussion, we discussed data suggesting that a known elastic protein titin was present; that is as far as we wanted to go on speculation of what the elastic component of tethers might be.

The authors present arguments that the tethers are not the DNA bridges observed by others. However, they should try to address this experimentally by treatment of their preparations with DNase to see if the thick and/or thin filaments disappear.

While we agree that it would be important to identify the components of the tethers, we are concerned that those experiments are beyond the scope of this manuscript. Nevertheless, we appreciate the constructive suggestion for the future research direction.

Moreover, they should discuss in more detail the possible functions of (DNA) bridges, including the recent model from Bill Sullivan's lab (Warecki et al, Curr Biol, 2023) that they help to retain fragments of broken chromosomes. In addition, the authors should summarize the various proteins that may be associated with the bridges (as enumerated in the Warecki et al 2023 paper).

As we describe above, we concluded that the bridges Warecki at al described are different from the tethers that we report in our manuscript. Therefore, we do not think it is necessary to expand the discussion on the proteins and functions associated with ultra-fine DNA.

The authors could add a sentence to the Results or Discussion of whether the thicker tethers might become stretched as anaphase progresses to become the thinner tethers (Fig. 4G).

We thank the reviewer for this suggestion. We actually mentioned this possibility in the third paragraph of our Discussion on page 7.

The authors may want to add a few sentences to the Discussion about the "chromosomal bouquet" stage of leptotene of meiosis prophase I where the telomeres of chromosomes seem pulled together and associate with the nuclear envelope --- they could speculate if this might also be due to the tethers that they describe in spermatocytes.

This is a very interesting possibility. While we would refrain from adding this speculation to our manuscript as it is beyond the scope of the main points, it is certainly an interesting avenue of future research.

Minor comments:

A few additional comments are as follows:

p. 2 last sentence of first paragraph -modify the wording about "no structural evidence that identifies physical connections between separating telomeres", since there is some information from genetic and cell biology light microscopy experiments. Perhaps simply change "structural" to "ultrastructural".

We have changed the wording as the reviewer recommended

p. 6, 5th line of second paragraph - change "ribosome DNA" to "ribosomal DNA"

We have corrected it.

Figure 1D - add the chromosome to the right of the schematic model (as suggested by Fig. 1B).

We are sorry for the confusion. In Figure 1D, the left half of the tethers are 3D modelled and shown. We have clarified this point by modifying the legend of Figure 1D

p. 17 (Methods), line 10 of first paragraph - state if this is light or heavy Halocarbon oil (give details).

It is a mixture of heavy and light Halocarbon oil. We have clarified it on page 17.

p. 17 (Methods), line 12 of first paragraph- state the concentration for fibrinogen and for thrombin.

As we wrote in the original manuscript, the procedures are described in detail in our previous publication (Forer A. & Pickett-Heaps J. (2005) Fibrin clots keep non-adhering living cells in place on glass for perfusion or fixation. Cell Biology International 29: 721–730). Nonetheless, to clarify this point, we have modified the text on page 17.

p. 17 (Methods), line 4 of second paragraph - is there any data to show that the filaments (tethers) occur if there is no cold shock?

Yes, we do see similar filamentous structures in the sample without cold shock. For your information, we show one of the electron micrographs below. In our manuscript, we show the data from the samples prepared with cold shock, because it better visualizes the filamentous structures. We now show these electron micrographs in the Supplementary Figure 2.

Referees cross-commenting<br /> I concur with Reviewers #1 and #2 that this is a fine paper that should be published. My detailed comments submitted with my review are simply meant as revisions to further strengthen this paper.

We thank the reviewer for supporting the publication of our manuscript.

Reviewer #3 (Significance):

Strengths: This is an important conceptual advance and the carefully done ultrastructural imaging provides the foundation for future studies that could delve into the molecular composition and functional significance of the tethers at telomeres of anaphase chromosomes seen here by 3D electron microscopy.

Limitations: the molecular composition and functional roles are not yet known for the tethers seen here by 3D electron microscopy, but to do so would involve an entire new program of experimentation.

Advances: there have only been two earlier ultrastructural papers on tethers at telomeres, and the tethers were peripheral to the main focus of those papers. Thus, the current paper extends our ultrastructural information about tethers.

Audience: this work is of importance for scientists who study the mechanics of chromosome movement on spindles, including regulation to combat aneuploidy. This work will also be important for a broader audience to inform them about transmission of the hereditary information to daughter cells._

We thank the reviewer for appreciating the significance and the impact of our work.

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Summary:

Tethers between telomeres of chromosomes in anaphase were inferred from earlier studies of laser microbeam cutting experiments. The current paper presents images from electron tomography of crane fly spermatocytes that substantiates the earlier inference. The authors deduce that the darker filaments and the lighter filaments that they visualize may be the structural tethers at telomeres.

Major comments:

The experiments are carefully done, and the conclusions are appropriately worded to qualify any caveats. This short communication is well-presented, and I have only a few comments. The authors should expand their list of references on bridges to include those listed by Warecki et al (Curr Biol 33:1-17, 2023; refs 15-26, etc). The authors present arguments that the tethers are not the DNA bridges observed by others. However, they should try to address this experimentally by treatment of their preparations with DNase to see if the thick and/or thin filaments disappear. Moreover, they should discuss in more detail the possible functions of (DNA) bridges, including the recent model from Bill Sullivan's lab (Warecki et al, Curr Biol, 2023) that they help to retain fragments of broken chromosomes. In addition, the authors should summarize the various proteins that may be associated with the bridges (as enumerated in the Warecki et al 2023 paper).

The authors could add a sentence to the Results or Discussion of whether the thicker tethers might become stretched as anaphase progresses to become the thinner tethers (Fig. 4G).

The authors may want to add a few sentences to the Discussion about the "chromosomal bouquet" stage of leptotene of meiosis prophase I where the telomeres of chromosomes seem pulled together and associate with the nuclear envelope --- they could speculate if this might also be due to the tethers that they describe in spermatocytes.

Minor comments:

A few additional comments are as follows:

p. 2 last sentence of first paragraph -modify the wording about "no structural evidence that identifies physical connections between separating telomeres", since there is some information from genetic and cell biology light microscopy experiments. Perhaps simply change "structural" to "ultrastructural".

p. 6, 5th line of second paragraph - change "ribosome DNA" to "ribosomal DNA"

Figure 1D - add the chromosome to the right of the schematic model (as suggested by Fig. 1B).

p. 17 (Methods), line 10 of first paragraph - state if this is light or heavy Halocarbon oil (give details).

p. 17 (Methods), line 12 of first paragraph- state the concentration for fibrinogen and for thrombin.

p. 17 (Methods), line 4 of second paragraph - is there any data to show that the filaments (tethers) occur if there is no cold shock?

Referees cross-commenting

I concur with Reviewers #1 and #2 that this is a fine paper that should be published. My detailed comments submitted with my review are simply meant as revisions to further strengthen this paper.

Significance

Strengths: This is an important conceptual advance and the carefully done ultrastructural imaging provides the foundation for future studies that could delve into the molecular composition and functional significance of the tethers at telomeres of anaphase chromosomes seen here by 3D electron microscopy.

Limitations: the molecular composition and functional roles are not yet known for the tethers seen here by 3D electron microscopy, but to do so would involve an entire new program of experimentation.

Advances: there have only been two earlier ultrastructural papers on tethers at telomeres, and the tethers were peripheral to the main focus of those papers. Thus, the current paper extends our ultrastructural information about tethers.

Audience: this work is of importance for scientists who study the mechanics of chromosome movement on spindles, including regulation to combat aneuploidy. This work will also be important for a broader audience to inform them about transmission of the hereditary information to daughter cells.

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

In this paper, the authors use light microscopy and electron tomography to study anaphase chromosomes in crane fly spermatocytes. They find that there are two "tether" structures that connect telomeres of sister chromatids. One tether is thicker (denser) and extends between sister chromatids during early but not late anaphase, whereas a second, less-dense tether maintains contact with both sister chromatids in all examined stages of anaphase. The paper makes arguments as to what the tethers could or could not be. Specifically, they are too numerous to be ultrafine DNA bridges seen in various normal or abnormal segregation events and they also do not affect anaphase chromosome motion the same way ultrafine DNA bridges do.

Major comments:

The major claim that there are tethers that connect sister chromatids in anaphase is supported by the data. Moreover, the data resolves two types of tethers on the basis of their density. While it is unclear what the composition of the tethers are, the paper makes a convincing case that they cannot be the DNA ultrafine bridges seen in other studies. The discussion has sufficient caveats that most readers will see that more work is needed to identify the composition of the two tethers. In my opinion, no further experiments are needed to support the modest claims of this paper. Therefore, I only have minor comments that may hopefully improve the paper's clarity.

Minor comments:

It was argued that the tethers reported here were also seen in other species and cellular contexts, where the imaging work was done with projection EM imaging. Presumably, what is new here is the usage of electron tomography. It would help readers if the authors explained why the electron tomography done here was essential to arrive at key conclusions.

p.3 mitochondria appeared to be fixed properly ... (e.g., Figs. 1C, 2B) - I don't see any mitochondria in any figures. Perhaps this observation should be noted as "not shown"?

p.3 The images shown in Figs. 1, 2, 4 - The figures should be called out in the order; in this case, Fig 3 has not been called out yet.

p.4 we did not find any other connecting structures - Because the sample was processed by traditional EM methods, it's safer to add a caveat that other connecting structures could be missed if they were disrupted by sample prep or if they did not pick up stain as well as the two structures presented in this paper.

p.7 we expect such structures to be commonly seen in other cell types as well if they are examined carefully - Instead of saying that examinations should be done "carefully", it would be more helpful to specify how other cell types should be examined. This work shows that the bridges can be found if the cells are either sectioned parallel to the spindle axis or if a sufficiently large volume is sampled.

Please use consistent spelling/hyphenation of ultrafine/ultra-fine and word choice (strands vs. bridges).

Referees cross-commenting

I agree with my co-reviewers's comments and have no further suggestions.

Significance

This may be the first use of electron tomography to study the structural details of tethers that connect chromosomes in anaphase cells. The data is of sufficient quality to reveal differences in density. Namely, one class of tether appears to be an extension of the chromosome while the other class is composed of thin filaments. This study is novel in that it characterizes a mitosis-associated complex that is poorly studied compared to the microtubule-based spindle apparatus and the kinetochore. Hopefully, the tethers will draw more attention and further characterization by methods like super-resolution microscopy and cryo-electron microscopy. My expertise is in chromatin, mitotic machines, and cryo-electron tomography.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Summary: Forer and Otsuka provide first-rate evidence for tethers fixed in place between separating anaphase chromosomes using electron tomography. The authors traced the anaphase movement of a number of living cells before fixation for examination using electron tomography. The manuscript is clearly written and provides an excellent introduction and discussion of the known literature. The reader will have an excellent background to see the importance of this work.

Major comments:

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

No further experiments are needed. The data are very supportive, and extremely clear.<br /> - Are the data and the methods presented in such a way that they can be reproduced? Yes.<br /> - Are the experiments adequately replicated and statistical analysis adequate? Yes.

Minor comments:

• Are prior studies referenced appropriately? Yes.
• Are the text and figures clear and accurate? Absulotely.
• Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

The authors are to congratulated on their major contribution to this study on tethers between separated daughter chromosomes. It is a tpur deforce to go from the living cells to fixing and identifying the same separated chromosomes using electron tomography to see the ultrastructure of the fibers seen fir.

Referees cross-commenting<br /> Thank you reviewer #2. The manuscript should be published. It is an excellent contribution.

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.

This manuscript is the first to use electron tomography toidentify the tethers between separated anaphase chromosomes. Forer and the laetMichael Berns and their co-authors have published a number of papers using phase microscopy and lasers to report on the physical nature and elastic properties of these fibres in the past. Forer and Otsuka have presented first-rate evidence for the reality of these structures using electron tomography. This manuscript should highlighted in the published journal.<br /> The chemical identity of these fibers as the authors state is unclear.

The following aspects are important:

• Audience: describe the type of audience ("specialized", "broad", "basic research", "translational/clinical", etc...) that will be interested or influenced by this research; how will this research be used by others; will it be of interest beyond the specific field?

This exciting contribution will be read by anyone interested in mitosis. It will be of interest to all Cell Biologists because of the careful manner in which the living cells were studied before they were fixed for examination using electron tomography. The readers will be dreaming how they can use this process on their Cell Biology problems.<br /> - 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.

I am a cell Biologist who has made contributions, both in light microscopy and in transmission microscopy on diving cells, both in tissue culture and in situ in aviav and zebrafish embryos.

Transparent Peer Review

---

Download the complete Review Process [PDF] including:

• reviews
• authors' reply
• editorial decisions

</br>

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

Learn more at Review Commons

---

Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity):

The manuscript by Rigger and Brenner details the role of vimentin network, in advancing OA pathogenesis by exacerbating premature senescence. The data is well presented and the study of interest, in that there is little known about vimentin in cartilage biology.<br /> The authors used OA derived cartilage explants and chondrocytes cultures, were graded for severity and compared accordingly. Figure 1 shows that markers of senescence are increased with structural damage, which is well established and consistant with the literature. Using a DOX model the authors induce premature senescence and exhibit a disrupted vimentin network. However, upon KD of CDKN2A, a marker of senescence, but did not observe complete reversal of CSV presentation.<br /> Next the authors show in figure 4 and 5, that the reduction or dismemberment of vimentin structures are linked to senescence and may act as contributing factors.<br /> Figures 6 and 7 then go on to show that upon advanced passage chondrocytes lose their vimentin network, and tend to senesce and mineralize.

Reviewer #1 (Significance):

Strength:<br /> This is a very novel study showing a link between vimentin and senescence in chondrocytes. The data are in line with other data. The work is clearly written structured and well displayed.

Author´s response:<br /> We thank reviewer #1 for their interest in our work and their overall positive report.

Suggestions for improvement:

While the study is very thorough ought in describing the markers of senescence and vimentin network, it lacks insight regarding mechanism which isn't completely deciphered. Are there links to key transcription factors?

Author´s response:<br /> The transcriptional regulation of vimentin in human cells is very complex. The VIM promoter region comprises multiple elements, such as a NF-kB- binding site, a PEA3-binding site and two AP1-binding sites (Zhang et al., 2003). Moreover, it was recently demonstrated that redox signaling is involved in vimentin expression at the wound margin after tissue injury in zebra fish (LeBert et al., 2018). However, it has also been reported that IL-1ß stimulation results in reduced gene expression of vimentin via p38-signalling in cartilage degeneration and OA progression (see manuscript REF. 36,37).

In our study, we observed that enhanced CSV levels are associated with a decreased vimentin gene expression, indicating a lower stability of the mRNA or decreased transcription of VIM in senescent chondrocytes (maybe due to enhanced p38-signalling as mentioned above). Since the transcriptome in senescent cells is radically changed, this question cannot be answered easily.

In future studies, we will rather try to clarify the underlying mechanism of vimentin externalization. There are still many questions to be answered: is the CSV anchored in the cell membrane (which anchor protein?) and is there still a connection to the intracellular vimentin network? Which proteins are involved in the externalization process: maybe comparable to phosphatidylserine exposure, mediated by flippases, scramblases, and lipid transfer proteins or rather by vesicles?

Literature mentioned above (not included in manuscript):

LeBert et al., 2018: Damage-induced reactive oxygen species regulate vimentin and dynamic collagen-based projections to mediate wound repair. DOI: 10.7554/eLife.30703

Zhang et al., 2003: ZBP-89 represses vimentin gene transcription by interacting with the transcriptional activator, Sp1. DOI: 10.1093/nar/gkg380

It is also unclear if disruption of the network is more detrimental than KD in promoting senescence.

Author´s response:<br /> KD of Vimentin led to a gradually decrease of intracellular Vimentin content and consequent stress. The cells were analyzed 7 days after induction of the KD and exhibited a stable senescent phenotype, comparable to Doxorubicin-treated chondrocytes (treated with very low concentrations over several days to produce only mild but ongoing stress). These models might reflect the pathophysiologic situation: We think that cellular stress due to mechanical impact and subsequent oxidative stress/ low-grade inflammation might lead to a gradual disruption or re-organization of the vimentin network, which is accompanied by decreased vimentin gene expression.

In case of the disruption of the vimentin network by Simvastatin, the stress response was very intense and rapid (24 h), and was only conducted as a proof-of-principle experiment. Despite the upregulation of some senescence-associated markers, we don`t think that permanent Simvastatin treatment would be suitable to obtain a stable senescent phenotype, but rather expect the cells to die due to excessive stress.

It would have been good to include models OA murine models to understand these processes better, and make a stronger physiological connection with OA of the joint.

Author´s response:<br /> The CSV antibody is only suitable for human cells and cannot be used for immunohistochemistry. Therefore, all previous reports of CSV are based on human (isolated) cells. At the current time point, it would not be possible to stain CSV in joints of mice after induction of PTOA due to the methodological limitations. We actually tested the CSV-antibody in isolated lapine chondrocytes and found a high percentage of CSV-positive cells, even at low passages. Although stress increased the amount of CSV-positive lapine cells, we did not consider the results as reliable due to the high percentage in un-stressed cells, which might result from unspecific antibody binding.

Overall, we think that the usage of clinical OA samples is convincing and reflect the pathophysiologic situation in the human OA joint.

Reviewer #2 (Evidence, reproducibility and clarity):

The manuscript provides solid evidence for an association between cell surface vimentin (CSV) and chondrocyte senescence. Human cartilage and cultured chondrocytes are used with a wide range of approaches to provoke senescence: natural osteoarthritis, traumatic loading ex vivo, doxorubicin to cells in monolayer, vimentin siRNA, and simvastatin. In contrast, relatively little was done to try and interrupt or reverse the role of CSV in senescence, with CDKN2A siRNA representing one attempted intervention. The manuscript is well written and the data are presented in a logical and clear manner, with a high likelihood of being reproduced in subsequent studies.

Author´s response:<br /> We thank reviewer #2 for their interest in our work and their mainly positive report.<br /> Regarding their comment on our attempts to reverse CSV on senescent chondrocytes, we would like to add the following: Reversal of cellular senescence is a very ambitious challenge. But in fact, we are currently preparing a manuscript in which we characterize an appropriate senolytic strategy to “rejuvenate” human chondrocytes and plan to use this approach to reduce the amount of senescent and thus CSV-positive cells in future experiments.

_Major comments:

In the doxorubicin experiments, the senescent cells show a spread morphology as expected. Given the importance of vimentin in cell spreading (as the authors own data show), the possibility that spread morphology itself (and not senescence) leads to CSV should probably be examined. This could perhaps be achieved by plating with different concentrations of fibronectin or other matrix proteins that produce a spread morphology to a degree that matches the doxo. If the cells remain spread for ~10 days but don't become senescent and don't have CSV, this would provide further support for a direct relationship.

Author´s response:<br /> We agree that cell spreading is associated with various cellular processes (for example by the YAP signaling pathway). Moreover, we would like to thank the reviewer for the proposed experiment.

Seeding of cartilage cells on fibronectin coated plates is a commonly used procedure to isolate chondrogenic stem progenitor cells, due to their higher affinity to fibronectin. The cells are usually cultured for several days on the coated plates and do not exhibit a flattened, senescent-like phenotype (as we observe for Doxorubicin-treated cells), but an elongated, fibroblast-/ stem cell-like shape. Our results (Figure 6E) demonstrate that CSPC have no increased CSV levels, despite their elongated (not flat) morphology.

There are some findings supporting the assumption that CSV leads to enhanced cell adhesion, but not that adhesion or cell spreading promotes CSV: we included experiments with HeLa (low CSV levels) and SaOS-2 (high CSV levels), which demonstrated that high CSV levels are associated with increased plastic adhesion (Figure S5). In line with this, we demonstrated that higher CSV levels on chondrocytes were associated with enhanced fibronectin and vitronectin binding, which might explain increased plastic adhesion. Moreover, Simvastatin stimulation and subsequent cellular stress by Vimentin disruption resulted in enhanced CSV but did not lead to cell spreading (Actin not affected, cells rather elongated, not flattened).

Minor comments:

The CSV antibody and staining method appeared to have generated some signal from debris, which makes it challenging to assess the localization of true staining. Presumably the true staining would be present only on the cell surface. While the widefiled view is appreciated, perhaps insets with a higher magnification would clarify.

Author´s response:<br /> In Figure 2h and Figure 2i, we provide insets of the IF-staining and an exemplary image made by scanning electron microscopy (SEM). CSV is not localized on debris – Figure 2h, actually represents the cell surface. The magnified, Doxo-treated cell is highly senescent and thus flattened. The uneven (rather spotted) staining pattern of CSV and the unusual shape of the cell might suggest that this is debris, not the cell membrane.

For figure 1k, it is a bit surprising that CDKN2A would peak so early after injury and then drop off. Most studies in other systems show a gradual increase in CDKN2A levels with persistent stress as opposed to a rapid increase in response to acute stress. Could the drop-off be due to preferential death of these cells? The CSV % in 1m was taken from 7d after trauma (plus 7 days in monolayer it appears). Further discussion on the timing of traditional senescence markers as compared to the emergence of CSV would be useful.

Author´s response:

We would like to thank the reviewer for this comment. That CDKN1A was induced by mechanical trauma without significant decrease at the later time points was in line with the P53 expression, which we detected via immunohistochemistry (IHC; positive staining of chondrocyte nuclei in cartilage). P53 and P21 are regarded as interconnected senescence markers. Interestingly, P53 is not regulated on gene expression level upon cartilage trauma or Doxorubicine stimulation – but there is a significant increase in P53 nuclear translocation.

Although such a discrepancy between gene expression and protein activity has not been reported in case of P16 or P21, we plan to investigate the dynamics of these cell cycle regulators and its connection to CSV after cartilage trauma in more detail in future studies.

We included the following statement in the discussion part:

“In the current study, we observed that CSV on chondrocytes was reduced by siRNA-mediated silencing of CDKN2A and increased after Doxo treatment or cartilage trauma. While we confirmed that mRNA levels of both CDKN1A and CDKN2A were significantly enhanced upon injury but exhibited different expression levels over time, we determined CSV-positive cells only at one time point after ex vivo cartilage trauma. Future studies might also consider earlier and later time points after cartilage injury to identify a potential time-dependent peak or decline in CSV-positive chondrocytes. In this way a potential association between CSV and the expression levels of CDKN1A and CDKN2A, which are thought to play differential roles in initiating and maintenance of senescence, respectively [50], might be clarified.”

[50] Stein G, Drullinger L, Soulard A, and Dulić V. Differential Roles for Cyclin-Dependent Kinase Inhibitors p21 and p16 in the Mechanisms of Senescence and Differentiation in Human Fibroblasts. Mol Cell Biol. 1999;19(3): 2109–2117. https://doi.org/10.1128/mcb.19.3.2109.

There is no CSV staining shown for figures 4 and 5. While the quantification of CSV was done by flow cytometry, it would nice confirmation to see the increase in CSV on the surface of cells with either siRNA for vimentin or the simvastatin.

Author´s response:

CSV-IF of simvastatin-treated chondrocytes is provided in Figure 5 (b). We did not perform exemplary staining of CSV after VIM-KD, because the quantification was performed via flow cytometry.

Reviewer #2 (Significance):

The strengths of the study include a rigorous design and the establishment of a potential new cell surface marker of chondrocyte senescence. The main limitation is that the conclusions are largely descriptive in nature.

If CSV is confirmed as a robust marker of senescence, this would be of value to the field. While this marker has been explored previously in other systems, there is value in this manuscript given the wide range of contexts investigated for a cell type in which senescence likely has an important role.

Reviewer #3 (Evidence, reproducibility and clarity):

This study presents a sound piece of science in the puzzle about extracellular vimentin in the differentiation/dedifferentiation of human chondrocytes and senescence and osteoarthritis. Eventhough, no mechanism is elucidated, the results clearly point towards a correlation of the amount of extra cellular vimentin and the level of chondrocyte senescence, and therefore signs of osteoarthritic changes in the cultivated chondrocytes. The methods applied are state-of-the art and provide the means to generate meaningful results in this experimental setting. The paper is concise and clearly written, there are only minor remarks.

Author´s response:

We thank reviewer #3 for their interest in our work and their overall positive report.

Minor comments:

1. The main clue of the paper is extra cellular vinemtin around chondrites in culture, please provide better pictures (1g) to support this. Why is the extra cellular staining seen so broad and not concentrated on the cells surface? The picture chosen imply a huge amount of vimentin to be externilized in disease states. It also indicates that in diseased chondrocytes no intact or semi-intact vimentin network is found intracellular. Please comment.

Author´s response:

In Figure 1g, CSV is located on the cell membrane. The pattern of the staining was surprising to us, as well. CSV was not equally distributed on the membrane, but rather represented an inconsistent pattern. Sometimes the staining was located at the filopodia of the cells, sometimes the whole cell was covered by spots. We also observed this on cancer cells, which was in line with other studies using this antibody. It remains unclear whether the distribution of the CSV has any effect. But we assume that the high abundance in filopodia might be connected with cell adhesion and mobility, which was positively associated with CSV.

Yes, chondrocytes isolated from highly degenerated tissue exhibited higher CSV levels as compared to cells derived from macroscopically intact regions. Although we did not investigate the vimentin network of these cells, our observations in Doxo-treated cells imply, indeed, that intracellular vimentin might be altered in diseased chondrocytes. According to this, Blain et al (Ref. 13) reported that there is a disassembly of the intracellular vimentin network in OA chondrocytes, which can disturb the chondrocyte phenotype and contributes to the development of OA (see discussion).

1. In the doxo experiment no extracellular vimentin is found? Please explain.

Author´s response:

Doxo-treated cells are highly positive for CSV (= extracellular vimentin on membrane). However, the intracellular vimentin is strongly decreased and some cells seem to be negative. We have not clarified the underlying mechanism by now, but it seems that senescence/ disease progression negatively affects the transcription of vimentin and, at the same time, promotes the externalization of the existing intracellular vimentin. Altogether, this might result in a decline in intracellular vimentin.

1. The SEM picture is showing what. IGH? The red dots are colloidal gold particles? In any case the quantity of stain gathered EM level would not correlate to the huge amount seen in LM staining. Please comment.

Author´s response:

For the SEM analysis, a gold particle-coated secondary antibody was used. The positive signal usually appears in white and was subsequently colored via a software. In IF and ICC staining, we had a signal amplification due to the biotin-streptavidin system and the magnification makes, of course, a huge difference.

1. Why the ICC in Fig. 3c? The siRNA is not detected in the KD? A reduction of Vimentin could be shown via WB.

Author´s response:

In Figure 3c, the KD of P16 was confirmed on protein level. In addition to the gene expression analysis, we chose the ICC (IF) to confirm that there is a decline in active (nuclear) CDKN2A. In case of P53, we made the experience that gene expression and the amount of cytoplasmic/ nuclear protein might not be consistent.

In Figure 4, we confirmed the successful KD of vimentin on mRNA and protein level (flow cytometry plus IF). Of course, WB would also be possible, but we decided to use the methods in which the antibody was well established and we wanted to visualize the disturbance of the intracellular vimentin network upon KD.

1. Fig. 4c, why are there no remnants of the vimentin networks seen in the chondrocytes? A Knock-down, not a KO is shown.

Author´s response:

In fact, most of the intracellular vimentin seems to be gone. However, there are some remnants (condensed fibers/ bundles) of the former vimentin network. We applied the VIM-KD over seven days. Usually, a KD experiment is only conducted for 2-3 days. But since we were not sure how stable the vimentin protein would be, we chose seven days. This long-lasting KD might have resulted in a strong decline of the protein. Moreover, the CSV levels on these cells were very high, indicating that existing vimentin was externalized and additionally decreased the amount of intracellular vimentin.

1. Please comment of the concentration of simvastatin, why not nmolar?

Author´s response:

The concentration of Simvastatin was chosen in accordance with Trogden et al. (Ref. 26), who first described the effects of simvastatin on the vimentin network. A lower concentration might have had the advantage, that the effects were less severe, allowing a longer observation time than 24h. However, as a proof-of-principle model to demonstrate the connection between vimentin network collapse ant CSV expression, the concentration worked quite well.

1. CSV+ is misleading in Fig. 6g, it's not an over expression.

Author´s response:

We would like to thank the reviewer for this comment and removed the “+” to make it less misleading.

1. The concept of EMT is debatable, at least in kidney fibrosis, and chondrocytes are not epithelial cells. Please add a more critical discussion point.

Author´s response: The authors agree with the reviewer’s argument that chondrocytes are no epithelial cells ant that the term EMT doesn’t seem to be appropriate. However, this is one leading hypothesis proposed by the working group of Prof. Mayán, who described CX43 and other EMT-markers on/ in senescent chondrocytes (see reference 31; more recently: Cell Death Dis. 2022;13(8):681. doi: 10.1038/s41419-022-05089-w).

We added the following passage in the discussion part to indicate that this hypothesis is a controversial concept:

“Nevertheless, the hypothesis that chondrocytes might undergo an EMT-like process remains controversially discussed, because chondrocytes are mesenchymal and not epithelial cells. In a recent review, Gems and Kern propose to consider senescent chondrocytes as activated and hyperfunctional remodeling cells occurring during OA progression [49]. Accordingly, chondrosenescence might represent an unsuccessful attempt of tissue repair. They further suppose that the senescent or activated chondrocytes are associated with a hypertrophic, bone-forming phenotype, following the process of bone development rather than hyaline cartilage formation. In line with this, we observed that CSV was associated with enhanced osteogenic capacities and a decline in chondrogenic properties.”

[49] Gems and Kern, 2022): Geroscience. 2022;44(5):2461-2469. doi: 10.1007/s11357-022-00652-x.

Reviewer #3 (Significance):

The manuscript provides novel insight in the role of intermediary filaments, i.e. vimentin, on chondrocyte senescence and osteoarthritic changes in vitro. It's strength is a thorough elucidation of the connection with a wealth of experimental data, a weakness is the missing elucidation, or first experiments in the direction, of the cell biological mechanism.<br /> It is well suited for a broad audience, because it deals with fundamental cell biological phenomena, definitely it's important for the OA /chondrocyte biology community.

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

This study presents a sound piece of science in the puzzle about extracellular vimentin in the differentiation/dedifferentiation of human chondrocytes and senescence and osteoarthritis. Eventhough, no mechanism is elucidated, the results clearly point towards a correlation of the amount of extra cellular vimentin and the level of chondrocyte senescence, and therefore signs of osteoarthritic changes in the cultivated chondrocytes. The methods applied are state-of-the art and provide the means to generate meaningful results in this experimental setting. The paper is concise and clearly written, there are only minor remarks.

Minor comments:

1. The main clue of the paper is extra cellular vine tin around chondrites in culture, please provide better pictures (1g) to support this.<br /> Why is the extra cellular staining seen so broad and not concentrated on the cells surface? The picture chosen imply a huge amount of vimentin to be externilized in disease states. It also indicates that in diseased chondrocytes no intact or semi-intact vimentin network is found intracellular. Please comment.
2. In the doxo experiment no extracellular vimentin is found? Please explain.
3. The SEM picture is showing what. IGH? The red dots are colloidal gold particles? In any case the quantity of stain gathered EM level would not correlate to the huge amount seen in LM staining. Please comment.
4. Why the ICC in Fig. 3c? The siRNA is not detected in the KD? A redyuction of Vimeo tin could be shown via WB.
5. Fig. 4c, why are there so remenants of the vimentin networks seen in the chondrocytes? A Knock-down, not a KO is shown.
6. Please comment of the concentration of simvastatin, why not nmolar?
7. CSV+ is misleading in Fig. 6g, it's not an over expression.
8. The concept of EMT is debatable, at least in kidney fibrosis, and chondrocytes are not epithelial cells. Please add a more critical discussion point.

Significance

The manuscript provides novel insight in the role of intermediary filaments, i.e. vimentin, on chondrocyte senescence and osteoarthritic changes in vitro. It's strength is a thorough elucidation of the connection with a wealth of experimental data, a weakness is the missing elucidation, or first experiments in the direction, of the cell biological mechanism.

It is well suited for a broad audience, because it deals with fundamental cell biological phenomena, definitely it's important for the OA /chondrocyte biology community.

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

The manuscript provides solid evidence for an association between cell surface vimentin (CSV) and chondrocyte senescence. Human cartilage and cultured chondrocytes are used with a wide range of approaches to provoke senescence: natural osteoarthritis, traumatic loading ex vivo, doxorubicin to cells in monolayer, vimentin siRNA, and simvastatin. In contrast, relatively little was done to try and interrupt or reverse the role of CSV in senescence, with CDKN2A siRNA representing one attempted intervention. The manuscript is well written and the data are presented in a logical and clear manner, with a high likelihood of being reproduced in subsequent studies.

Major comments:

In the doxorubicin experiments, the senescent cells show a spread morphology as expected. Given the importance of vimentin in cell spreading (as the authors own data show), the possibility that spread morphology itself (and not senescence) leads to CSV should probably be examined. This could perhaps be achieved by plating with different concentrations of fibronectin or other matrix proteins that produce a spread morphology to a degree that matches the doxo. If the cells remain spread for ~10 days but don't become senescent and don't have CSV, this would provide further support for a direct relationship.

Minor comments:

The CSV antibody and staining method appeared to have generated some signal from debris, which makes it challenging to assess the localization of true staining. Presumably the true staining would be present only on the cell surface. While the widefiled view is appreciated, perhaps insets with a higher magnification would clarify.

For figure 1k, it is a bit surprising that CDKN2A would peak so early after injury and then drop off. Most studies in other systems show a gradual increase in CDKN2A levels with persistent stress as opposed to a rapid increase in response to acute stress. Could the drop-off be due to preferential death of these cells? The CSV % in 1m was taken from 7d after trauma (plus 7 days in monolayer it appears). Further discussion on the timing of traditional senescence markers as compared to the emergence of CSV would be useful.

There is no CSV staining shown for figures 4 and 5. While the quantification of CSV was done by flow cytometry, it would nice confirmation to see the increase in CSV on the surface of cells with either siRNA for vimentin or the simvastatin.

Significance

The strengths of the study include a rigorous design and the establishment of a potential new cell surface marker of chondrocyte senescence. The main limitation is that the conclusions are largely descriptive in nature.

If CSV is confirmed as a robust marker of senescence, this would be of value to the field. While this marker has been explored previously in other systems, there is value in this manuscript given the wide range of contexts investigated for a cell type in which senescence likely has an important role.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

The manuscript by Rigger and Brenner details the role of vimentin network, in advancing OA pathogenesis by exacerbating premature senescence. The data is well presented and the study of interest, in that there is little known about vimentin in cartilage biology.

The authors used OA derived cartilage explants and chondrocytes cultures, were graded for severity and compared accordingly. Figure 1 shows that markers of senescence are increased with structural damage, which is well established and consistant with the literature. Using a DOX model the authors induce premature senescence and exhibit a disrupted vimentin network. However, upon KD of CDKN2A, a marker of senescence, but did not observe complete reversal of CSV presentation.

Next the authors show in figure 4 and 5, that the reduction or dismemberment of vimentin structures are linked to senescence and may act as contributing factors.

Figures 6 and 7 then go on to show that upon advanced passage chondrocytes lose their vimentin network, and tend to senesce and mineralize.

Significance

Strength:

This us a very novel study showing a kink between vimentin and senescence e in chondrocytes. The data are in line with other data. The work is clearly written structured and well displayed.

Suggestions for improvement:

While the study is very thorough ought in describing the markers of senescence and vimentin network, it lacks insight regarding mechanism which isn't completely deciphered. Are there links to key transcription factors? It is also unclear if disruption of the network is more detrimental than KD in promoting senescence. It would have been good to include models OA murine models to understand these processes better, and make a stronger physiological connection with OA of the joint.

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

Learn more at Review Commons

---

The authors do not wish to provide a response at this time as only a revision plan is provided at this time.

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Using an elegant set of experiments, the authors probe the function of PfPK2 in asexual blood stage development. Using a rapamycin inducible dimerizable Cre recombinase-based strategy for the conditional knockdown of PK2, coupled with immunofluorescence assay, live cell imaging and phosphoproteomics the authors demonstrate the role of PK2 in invasion of red blood cells and signalling pathways in the parasite. Results show that PK2 is critical for the formation of tight junctions between merozoites and host red blood cells and that PfPK2 regulates cGMP levels and calcium release.

Major comments:

1. Is PK2 expressed in other life cycle stages? The authors should discuss what is known about the role of PK2 in other stages of parasite development. Would PK2 inhibitors be expected to have activity against liver or sexual stages of the parasite?
2. Have any inhibitors of PK2 been reported to date? If so, were these tested against the PK2 cKD parasite line? Do they show similar phenotypic effects to knockdown of PK2? Do these studies give any insight on how vulnerable PK2 is as a target? To what extent does PK2 need to be inhibited/knocked down to lead to parasite death/growth inhibition?
3. What were the expression yields and purity for the recombinantly expressed wild-type PK2 and mutant/ΔRD and ΔCD deletions? Has the ATP Km for PK2 been reported/determined? How did the deletions affect protein expression and stability? Could these deletions be influencing protein folding/amount of active protein in the preparation rather than regulating catalytic activity? How were protein concentrations normalised for the assay?
4. Does rapamycin have any effect on wild-type parasites? What controls were included to ensure that observed effects were a result of rapamycin-induced PK2 knockdown, rather than rapamycin acting on other pathways/interfering directly with parasite biology. This should be discussed for readers less familiar with this system. Presumably the cHA-PfPK2-loxP line was used as the control to account for this for at least some of the experiments.

Minor comments:

1. "Malaria contributes to almost 400,000 deaths globally (Hay et al, 2004)."It should be made clear that this is the number of deaths reported annually. The references and statistic should be updated based on the most recent WHO Malaria report.
2. "Several of these kinases are regulated by second messengers like calcium, PIPs, cAMP, cGMP Plasmodium kinases like CDPKs, PKA, PKG etc and are crucial for diverse parasitic functions." This sentence could be reworded for clarity.
3. "However, the precise function of this protein kinase in parasite life cycle has remained unknown." Add word "the" should be added before "parasite".
4. "Present studies demonstrate that PfPK2 regulates the invasion of host erythrocyte by P. falciparum." Should be erythrocytes (plural).
5. "but the sequence similarity is mainly between kinase domains of human CamKIand PfPK2 (~80%)". Change "mainly" to "highest".
6. "PfPK2 has a long N-terminal extension compared to CamKIand a CaM binding domain was predicted within a postulated regulatory domain present downstream of the kinase domain, which is the case with CamKI (Kato et al, 2008)." Please check this sentence and reword for clarity.
7. References to "www.plasmodb.org" should be replaced with specific references to the source of the information listed in the database.
8. Figure 2b. Please explain the relevance of adding/excluding EDTA and the effect of this on PK2 activity.
9. "Correct integration of the targeting plasmid at the desired locus was confirmed by PCR as amplicons of expected size were obtained parasites from a clone that lacked wild type PfPK2 (Fig. 2B)." Remove the word "parasites".
10. "Successful expression of GFP-PfPK2 was indicated by Western blotting (Fig. 2D) as well as by IFA (Supp. Fig. S1A), which wasundetectable after rapamycin treatment suggesting efficient depletion of this kinase from the parasite (Fig. 2D and Supp. Fig. S1B)." Write IFA in full the first time it is used in the main text. "was undetectable" should be two words.
11. "The release of another microneme protein EBA-175, which interacts with glycophorin A on the 11 surface of the erythrocytes (Sim et al, 1994), was also reduced (Fig. 5A, Supp. Fig. S3B). but its localization to the microneme was unaltered (Supp. Fig. S4)." Remove full stop mid-sentence.
12. "Therefore, we focussed on a possible role of PfPK2 in the release of AMA1, which is involved in late inavsion events like Tight Junction formation and PfPK2 plays a role at this stage of invasion (Fig. 4)." Correct "inavsion" to "invasion".
13. Figure 5b. What is the difference between upper and lower panels. Please label or include details in figure legend. Figure legends should also include details on the DAPI, DIC and merged images for readers less familiar with microscopy images.
14. "AMA1 plays a role in the formation of Tight-Junction (TJ) is via its association with rhoptry neck proteins (RONs) that are released by the rhoptries "Just-in-Time" on to erythrocyte surface (Riglar et al, 2011)." Remove "is".
15. "Interestingly, phosphorylation site S1214 which is regulated by PfPK2 (Fig. 6B, 7B) resides in this insert This phosphositeis conserved only in GC" Add full stop after "insert". Replace "phoshositeis" with "phoshosite is"
16. Order of Materials and Methods should be consistent with order of the Results section. For example, "Expression of recombinant proteins" and "Kinase assays" sections should come first.
17. Please ensure all abbreviations, panels and labels in Figures are clearly explained in the relevant figure legends.

Significance

This study provides new insight into the role of PK2 in Plasmodium falciparum asexual blood stage development. While this study gives provides information on parasite biology, it does not provide significant advances in terms of understanding the value of PK2 as a drug target. However, this study does lay the groundwork for future studies using PK2 inhibitors as tool compounds for phenotypic validation.

Audience: Specialised audience interested in parasite biology/signalling pathways.

Reviewer's expertise: Target-based malaria drug discovery, Plasmodium kinase inhibitors, Target deconvolution for phenotypic hits in Plasmodium, kinase assay development.

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

Summary:

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

The authors present a biochemical and functional characterisation of the Protein Kinase 2 in Plasmodium falciparum (PfPK2). They state that PfPK2 is an active protein kinase, as shown by phosphorylation of a histone protein (Figure 1). The next 6 figures of the paper describe the functional characterisation of PfPK2. It is a protein essential for the propagation of asexual malaria parasites in the clinical blood stage (Figure 2). The protein is expressed in the schizont stage and deletion of the PfPK2 gene by the conditional DiCre-LoxP system prevents parasite invasion, while not affecting egress (Figure 3 and 4), reduces the protein levels of two invasion molecules (Figure 5), modifies phosphorylation status on a variety of schizont stage proteins that play a role in invasion (Figure 6). PfPK2 deletion also leads to the decrease in the molecule cGMP which plays a role in parasite invasion (Figure 7).

Major comments:

• Are the key conclusions convincing?

The conclusions made in Figure 2, 3, 4 and 7 are adequate but I have added questions in my detailed analysis on these figures that should assist in increasing the confidence on the conclusions.<br /> In my view, conclusions made in Figure 1, 5 and 6 are not convincing as they are missing key quality control data including loading control. Detailed comments on each figure is attached.<br /> - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?<br /> Conclusions drawn from Figures 1,5,6 should be supplemented with the experiments suggested, otherwise the claims should be marked as speculative.<br /> - Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.<br /> The experiments suggested in the detailed figure comments are necessary for supporting the claims of the paper.<br /> - 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.<br /> To improve the phosphoproteomics data, I would strongly suggest the creation or acquisition of a parasite line in which a related kinase has also been conditionally regulated and analysis of the phosphoproteome. I would suggest PfPKA made in the Wilde et al study. These experiments are required in order to qualify the statements made in the discussion section such as<br /> "A novel pathway was deciphered in which it is an upstream regulator of cGMP-calcium signalling axis, which is critical for invasion"<br /> - Are the data and the methods presented in such a way that they can be reproduced?

How many times were the experiments mentioned in the following figures repeated?<br /> Figure 1C: PfPK2 phosphorylation assay<br /> Figure 1D: Kinase assay<br /> Figure 2B,C, D<br /> How many cells were counted in Figure 2F?<br /> How many biological replicates were used in Figure 6B?<br /> - Are the experiments adequately replicated and statistical analysis adequate?<br /> For figures not stated above, experiments were adequately replicated and analysis is adequate.

Minor comments:

• Specific experimental issues that are easily addressable.
• Are prior studies referenced appropriately?<br /> Yes.
• Are the text and figures clear and accurate?<br /> Axes on Figure 5A require editing as the values are unable to be seen clearly. Other figures are clear and well presented. Specific figure related comments are attached to this document.
• Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

This data, in its current state, requires supplementation with necessary controls in order to be convincing and also additional experiments as suggested in the detailed figure related information.<br /> - Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.<br /> The data included advances the field in characterising the role of PfPK2 and may influence the thinking of researchers studying Apicomplexan invasion biology. The PfPK2 phosphoproteomics and invasion imaging help knowledge gain in this area.<br /> - Place the work in the context of the existing literature (provide references, where appropriate).<br /> This work advances the data identified by Kato et al (2008) in the characterisation of PfPK2. Kato et al identified the activity of PfPK2, it's dependence on calmodulin and calcium for activity and the localisation of PfPK2 at the merozoite. Kato et al attempted to delete PK2 in the rodent malaria parasite P. berghei, but were unsuccessful, suggesting that the gene is essential for malaria parasites.<br /> Rawat et al recapitulate the kinase activity data and advance Kato et al's findings in creating a conditionally deletable PfPK2 parasite strain. Using this strain, they confirm the essentiality of the gene and characterise it's effect on invasion related processes in the parasite.<br /> - State what audience might be interested in and influenced by the reported findings.<br /> Researchers in Apicomplexan parasite biology may find this data interesting.<br /> - 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.<br /> My expertise is in malaria parasite biology including parasite invasion, genetic manipulation and protein export.

Specific Figure related comments:

Figure 1:

C: Where is the data on the purification of PfPK2? Looking at Image 1C, I don't know what has been added to the reaction to phosphorylate Histone IIa.<br /> I would like to see Coomassie or western blots of the His-PfPK2 purification and the presence of Histone IIa so that I can be convinced that only PfPK2 and not a contaminant E-coli protein is responsible for the histone phosphorylation.

Without knowing this data, I cannot be convinced that PfPK2 is phosphorylating Histone IIa

Da: Again, without a Coomassie of western blot to show that K140M/WT PfPK2 as well as Histone IIa have been included in the reaction, I can't know that it is the single point mutation that has led to the lack of autophosphorylation of PfPK2 and the lack of Histone IIa phorphorylation.<br /> Please include this data.

Db:<br /> Once again, there is no Coomassie or western to show what proteins are included in each treatment. Please include there.<br /> Why is there a band of the size of 32P-HIIa in the WT lane lacking HIIa? Is there a breakdown product of PfPK2 that gets autophosphorylated?

Figure 2:

A, B: The PCR results are conclusive in showing integration of the plasmid.<br /> C: The PCR and western blots of excision are conclusive and show efficient excision.<br /> D: Ideally, I would like to see the growth of the 1G5DC parasite strain on DMSO and rapamycin as well alongside the PK2 parasite line. 200nM of rapamycin is double the concentration used by Collins et al 2013 when creating the 1G5DC strain.

Supplementary Figure 2A: Figure is missing a loading control here. Rest of the figure is conclusive and the complementation has worked nicely. I expect that the reason the complemented parasite isn't behaving exactly like the DiCre strain is due to the fact the complementation is done via an episomal plasmid which may segregate differentially in daughter merozoites.<br /> Supp Figure 2C: The Y-axis is hidden behind the legend for the same axis.

Figure 3

A + B: In my view the data from Figure 3A and 3B are effectively the one figure and therefore does not require an A/B division. The data shows no change in schizont maturation while invasion rate of rapa treatment is ~50% of DMSO control.<br /> C: Data shows that parasite invasion is impaired when PK2 is not present and that the cytochalasin D treatment was successful.

Figure 4:

The data shows reduction in the invasion rate upon Rapa treatment and an increased rate of prolonged echinocytosis. The video stills demonstrate the defects nicely.

The data suggest that upon Rapa treatment, 40% of all invasion events are successful (Figure 4B). This result does not seem to match with Figure 2E, where rapa treatment leads to a reduction in parasitemia much less that 40% of control.<br /> Can the authors comment on this discrepancy?

Figure 5 and Supp Figure S3

A loading control is required for culture supernatant and lysate in all conditions (Supp Figure S3A,B,C). Otherwise we cannot interpret the loss of AMA1/EBA175 shedding as well as the non-effect on RhopH3. Without this data, the interpretations made in Figure 5A cannot be assessed.<br /> B: The figure needs to be better labelled to represent the E64 treatment as well.<br /> The representative image for PK2-LoxP + Rapa + E64 does not show any level of AMA1 on the surface, but the graph to the right shows 30% of parasites with surface AMA1 levels. Can the authors attach a series of images of this condition, showing the variation of AMA1 on the parasite surface?<br /> C: This figure shows nicely that AMA1 levels are reduced during invasion in rapa treated parasites.

Figure 6:

A. Do the authors identify PfPK2 peptides also being depleted upon PK2 knockdown?<br /> If so, please update Figure 6B. If not, then it makes the autophosphorylation data from Figure 1D contradictory.

The data from Figure 6B and 6C identifies many invasion related proteins that are hyper/hypo phosphorylated upon rapamycin addition. It would have been interesting to include another invasion related kinase as a control line in all conditions (For example PfPKAc) that would allow finely dissecting the involvement of PfPK2 vs PfPKA.

Figure 7A:

1. What happens to the total protein levels of PDE and GCa upon PfPK2 deletion? Does the level of cGMP reflect the increased stability or loss of these two antagonistic proteins?<br /> I.E Does PK2 depletion lead to lower GCa activity (=less cGMP production) or increased stability and action of PDE (= more degradation of cGMP)?

Significance

This work advances the data identified by Kato et al (2008) in the characterisation of PfPK2. Researchers in Apicomplexan parasite biology may find this data interesting.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Summary: The manuscript by Rawat et al presents study to define the mechanism of action of an essential Plasmodium protein kinase PfPK2 using a conditional knockout line. The data show that PfPK2 has a role in the invasion of RBC as well as in the intraerythrocytic maturation of the parasite. In addition, quantitative phosphoproteomics was done to identify potential cellular targets and pathway analysis. The manuscript reports several important findings. I have following comments and suggestions:

Major:

1. Page 3. The data of malaria mortality is from 2004! Current WHO data needs to be included.
2. Page 4. As per recent analysis (Adderley and Doerig,2022), number of P. falciparum kinases is higher than 85.
3. Page 5. Homology analysis references are quite old. Is there any update from recent comparative analysis or alpha fold-based structural similarity.
4. Page 7, line 4. It should be "Conditional Knockout". Needs to be corrected elsewhere as well.
5. Page 8, line 18. Based on the methods section, parasites were treated at the ring-stage- needs to stated here as well.
6. Page 12, line 16. It would be helpful to define "significant" in terms of phosphorylation changes. p<0.5?
7. Page 12, line 23. It is mentioned that PfPK2-depleted samples have an increase in PPM2 phosphorylation. Is there a reference for these specific phosphosites?
8. It would be bit of a stretch to say that the differentially phosphorylated proteins are substrate/targets (as in Table 1). PfPK2 depletion occurred in ring stage, and the sample was collected at ~44 HPI, leaving ample time for compensatory changes.
9. Table 1. Criteria used for selecting proteins for the table needs to be defined in the legend. Example: p<0.5 FC>|1.2|. It would be also useful to see the fold change difference in a column for each protein.
10. Fig 6B. Looks like there are 8 phosphorites with a greater negative fold change than those annotated. Are these all "unknown proteins"? They may not fall into the invasion or signaling groups in Table 1, but they still need to be included.
11. Fig 6C. In the STRING analysis, PfPK2 is included as a yellow diamond but not referenced in the legend. Also, it is not clear if PfPK2 was differentially phosphorylated or was placed in the STRING network manually. "CPPUF is a nice abbreviation for "conserved Plasmodium protein, unknown function" but it would be useful to include the PlasmoDb number.
12. Fig 6C. What is the significance of the line thickness or the circle size? Needs to be specified in the legend.
13. It is not clear how many replicates of small collection was done for phosphoproteomic analysis.

Minor:

1. Page 5, line 3. It would useful to include PlasmoDb ID of PfPK2.
2. Page 5, line 17: should read "....it has long N and a C-terminal...."
3. Page 7, line 21: should be " was undetectable"...
4. Page 9, line 17. It would be better to rephrase as.. "To better understand defects in the invasion following PfPK2 depletion live cell imaging was performed".
5. Page 11, line 5. should be " late invasion".
6. Page 30. Expression of recombinant protein and kinases assay should be moved to the beginning of the Methods as it is mentioned first in the results.
7. Page 31, line 10. Concentration of imidazole needs to be mentioned.

Significance

The manuscript defines the role of PFPK2 in parasite invasion as well as in asexual maturation. Although unambiguous PfPK2 targets have not been defined, but the phosphoroteomic analysis alludes to the role of PfPK2 in cellular processes, particularly in invasion.

The manuscript will be of general interest to readership of the journals listed.

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

Learn more at Review Commons

---

Reply to the reviewers

We thank all Reviewers for their detailed and helpful comments and suggestions for this manuscript. The overall goal of this study is to interrogate which transcriptional and metabolic pathways lose oscillation when MYC is amplified or activated. We have now added additional replicates to our RNA-sequencing and nutrient transporter expression analyses, and have demonstrated that MYC disrupts oscillation of metabolic and biosynthetic gene expression, nutrient transporter oscillation, and metabolite pathways. On the suggestion of Reviewer #3, we have also strengthened this work by directly contrasting the transcriptional oscillations we observe in cancer cells with well-established primary cell models of transcriptional oscillation, MEFs and macrophages. We have carefully responded to each comment and have noted which Figures or lines in the manuscript address each comment. We hope that our revised manuscript is now suitable for publication.

Reviewer #1:

This is an interesting paper from the Altman, Weljie and Dang labs that furthers their previous publications looking at the effect of "oncogenic" Myc levels have on circadian gene expression. They provide compelling data that in neuroblastoma and osteosarcoma models of Myc amplification circadian gene expression and metabolite fluctuation are lost. The data is convincing and comprehensive and should be of broad general interest. There are a few major issues that need to be addressed.

(Significance (Required)):

The Myc oncogene is dysregulated in many cancer types, so there is considerable interest in the mechanisms that underpin its function as a transforming oncogene. This group of authors has previously described that Myc can disrupt circadian gene expression, which is linked to several types of cancer. This paper extends the authors previously findings by performing careful timed RNA-seq analysis and metabolomic analysis. The work is well done, and the findings justify the conclusions. This paper should be of interest to those who study Myc, circadian gene expression and cancer. Two key limitations are noted: 1) the cells that are analyzed are grown entirely in vitro in serum and nutrient replete media, 2) there is no direct evidence that the blockage of circadian gene expression by Myc is important for Myc-dependent transformation, although it seems likely. These two limitations do not detract from the significance of the manuscript.

My expertise is in cancer-centric gene regulatory mechanisms

We thank Reviewer #1 for finding the data compelling and comprehensive, and for suggesting key experiments and revisions. We also thank the Reviewer for noting that this will be of interest to those who study MYC and cancer (noted in the Significance section below). We have addressed all suggestions below.

1) Is there a control (done here or in prior literature) showing that simply adding tam to cells doesn't change circadian gene expression?

We previously performed this experiment in our 2015 Cell Metabolism paper (Altman and Hsieh, et al). In particular, by using either cells that did not express MYC-ER, or a control mutant MYC-ER that lacks transcriptional activity, we found the 4OHT did not blunt clock function in U2OS cells. This is now discussed in Lines 120-121 of the revised manuscript.

2) All of the experiments rely on Myc:ER fusions. The authors should mine other datasets to determine of systems that rely on conditional expression of wt Myc drive a similar loss of circadian gene expression.

This is an important point: the work in this manuscript focuses on cancers with endogenous levels of MYC where MYC-ER fusions drive changes in gene expression. In our previous works, we tested systems such as the Reviewer suggested, where endogenous MYC was conditionally overexpressed (Altman and Hsieh et al. Cell Metabolism 2015, Altman et al Nature Communications 2017). In these systems (liver cancer and Burkitt’s Lymphoma), elevated MYC also leads to dysfunction of circadian gene expression and oscillation. We reference this work on lines 123-126. In addition, two papers from the laboratory of Michael Brunner (Shostak et al Nature Communications 2016, Shostak et al Nature Communications 2017) used a tetracycline-inducible model of wild-type MYC in U2OS instead of MYC-ER. Their results largely mirrored our own, where BMAL1 was suppressed and molecular circadian oscillation was disrupted. These two papers are cited extensively throughout manuscript.

3) The authors argue Myc:ER fusions mimic Myc amplification which is common in cancer and they discuss several previous papers that at least correlate the presence of amplified Myc with loss of circadian gene expression. It should be possible to test whether reduction of Myc by knockdown or using a Myc inhibitor restores circadian gene expression in a cell line known to be Myc amplified. This need not be an exhaustive RNA-seq experiment, but looking at a handful of circadian genes using a qPCR approach would be informative.

Thank you for the suggestion. Our previous work in Burkitt’s Lymphoma and liver cancer cell lines, as well as analysis of data from primary liver cancer, drew on MYC Tet-OFF systems, where amplified MYC is suppressed by addition of tetracycline or doxycycline. In these experiments, the ‘control’ is amplified MYC, and the ‘experimental’ condition is tet- or dox-treated cells where MYC has been suppressed. In all cases, suppressing MYC led to predictable changes in circadian gene expression (suppression of REV-ERBα, upregulation of BMAL1, etc).

To support these findings, upon the suggestion of the Reviewer, we identified a recent study where the PC3 prostate cancer cell line, known to harbor highly elevated endogenous MYC levels, was treated with the new generation MYC inhibitor MYCi361. We downloaded their RNA-sequencing data and performed differential expression analysis, and showed that several circadian genes were significantly altered upon treatment with the inhibitor, including BMAL1, PER2, and the REV-ERB genes. This is now included as Supplemental Figure S1C, and the text for this is on lines 126-136.

4) The data pretty clearly shows that metabolites lose their periodicity MycON cells. Can these be linked back to loss of circadian expression of specific genes in those metabolic pathways? If so, are genes direct Myc transcriptional targets in other studies?

Thank you for bringing this up. We now have computational evidence from multiple replicate circadian time-series experiments that MYC disrupts oscillation of the LAT1 amino acid transporter across multiple cell lines (Figure 6), and that MYC upregulates LAT1 and 4F2hc protein and mRNA (Supplemental Figure 6 and not shown). Indeed, LAT1 is known to be a direct MYC target, which is now mentioned on lines 493-499 of the discussion.

In U2OS, where we performed our metabolomics studies, while LAT1 oscillates at the protein level, we saw less evidence of metabolic program oscillation at the transcriptional level, which we acknowledge on lines 274-277. This may be due to the fact that not all metabolic and protein oscillations arise solely from transcriptional oscillation, which we mention on lines 48-49 of the introduction, and revisit in lines 430-432 of the discussion. Nonetheless, our findings that MYC disrupts oscillation of nutrient transporters and metabolites fits in with the overall theme of this manuscript that MYC disrupts circadian control of metabolism.

5) The finding Myc activation "releases" metabolic and biosynthetic pathways from circadian control implies that this must have something to do with Myc-dependent transformation. A priori, it is not obvious why this should be the case. Do metabolic precursors and biosynthetic molecules become periodically limiting when their levels oscillate in MycOFF cells? In MycOn cells do the non-oscillating metabolites, provide a growth advantage? This is a difficult question to address and one that is certainly beyond the scope of this manuscript. The authors should address this issue in their discussion.

Thank you for the suggestion to discuss this idea in more detail. While we propose the hypothesis that circadian metabolic oscillations are limiting for tumor cells, testing this directly is indeed outside the scope of this current study. We address this issue on lines 506-518 of the discussion, where we contrast our hypothesis with the idea that alternate metabolic oscillations (those tied to cell cycle or faster-than-circadian) may arise in the absence of circadian control.

Minor points<br /> 1) phrase "for the first time" is used multiple times in the discussion. Gets a bit redundant ( and loses impact). Consider revising.

Thank you for this suggestion. We have revised our Discussion section accordingly.

2) In figure 4, the periodicity in expression of the proteins in figure 4 is fairly clear, but it might be beneficial to bracket (or denote in some other way) the circadian fluctuation in expression.

In response to other Reviewer comments, we performed multiple replicates of the nutrient transporter protein expression time-series, quantified protein, and calculated circadian oscillations. This is now presented in the new Figure 6.

Referees cross-commenting

I had not considered the important points raised by reviewer 3. The authors definitely need to address the concern over replicates and whether the gene expression of truly rhythmic. If not, this seems like a fatal flaw in the MS.

We have carefully addressed both of these concerns by adding replicates to our RNA-sequencing and protein expression assays, and contrasting our gene expression oscillation findings with those in established primary cell models (Supplemental Figure 2A). Please see the Response to Reviewer 3 for more detail.

Reviewer #2:

(Significance (Required)):<br /> Using the circadian synchronized cancer cell lines, DeRollo and colleagues characterized the MYC oncoprotein role in metabolic role through the circadian clock disruption. Authors found that forced activation of MYC disrupts up to 85% of genes oscillation particularly nutrient transporter glycosylation and amino acid metabolism. This work addresses important questions in the circadian clock and cancer field through the oncogene activation, and the manuscript is well-written. However, there are a few concerns that should be addressed to improve the manuscript quality.

We thank Reviewer #2 for their detailed and astute suggestions on demonstrating the degree of MYC overexpression and the synchronization / entrainment of our cells, as well as the suggestion to add and quantify multiple replicates. We also appreciate the Reviewer’s comments in the Significance section that the manuscript addresses important questions in the field and is well-written. We have individually addressed each comment below and made several revisions and additions in response to them.

Major comments:<br /> 1) The 3 cell lines used in this paper, what is the expression levels of MYC protein under -OFF and -ON conditions? It is important to demonstrate this information through the western blot data. Since the 4-hydroxy tamoxifen was used to activate MYC, what is the vehicle/control for MYC OFF cells? Otherwise, it will be difficult to assess with everything observed on this manuscript under MYC-ON could be due to 4-hydroxy tamoxifen treatment.

Thank you for this important consideration. We have clarified in the manuscript that the MYC-ER system is constitutively expressed, and when cells are treated with 4OHT, MYC-ER is activated and translocates to the nucleus, while MYC-OFF control cells are treated with ethanol as a vehicle (Lines 100-105). In response to the suggestion to quantify the degree of overexpression, we have also added new experiments to quantify the degree of MYC-ER overexpression, in Supplemental Figure 1A and 1B. Finally, we previously showed in our 2015 Cell Metabolism paper (Altman and Hsieh, et al) that 4OHT does not affect the molecular clock on its own. In particular, by using either cells that did not express MYC-ER, or a control mutant MYC-ER that lacks transcriptional activity, we found the 4OHT did not blunt clock function in U2OS cells. This is discussed in Lines 120-121 of the revised manuscript.

2) In Fig. 1A, it is crucial to demonstrate that the circadian synchronization protocol is working by performing statistical analysis with at least 3 biological replicates. This should be performed by either cosinor analysis and/or JTK cycle analysis of all the canonical clock genes including BMAL1 (ARNTL), CLOCK, CRY1, CRY2, PER1, PER2, DBP and NR1D1. This reviewer would like to see both transcripts (qPCR) and protein levels (western blot data) of those clock genes expression pattern. Without these results, rest of the data will be hard to conclude the connection with the circadian/molecular clock.

Thank you for bringing of the need for quantitation of circadian transcripts. In the new Figure 1, we have quantified and performed ECHO analysis (which is a parametric method of oscillation analysis used through the manuscript) on several circadian transcripts. We chose to specifically show the same n=2 input RNA that we used for RNA-seq for each cell lines. Additionally, our updated RNA-sequencing and analysis of oscillating genes in MYC-OFF shows that CRY2, PER2, PER3 oscillate in all three cell lines (Figure 2B). These findings agree with extensive literature by us and others that the molecular circadian clock is functional after dexamethasone entrainment in U2OS, SHEP, and SKNAS: Baggs et al Plos Biology 2009, Zhang et al Cell 2009, Hughes et al Plos Genetics 2009, Altman and Hsieh et al. Cell Metabolism 2015, Altman et al Nature Communications 2017, Shostak et al Nature Communications 2016, Shostak et al Nature Communications 2017.

3) In Fig. 5A-C: It is important to repeat this western blot experiment at least 3 times and have the quantitation to demonstrate the circadian rhythmicity significance by probing to majority of the canonical clock proteins as discussed above.

Thank you for this suggestion. The western blot experiments have now been repeated and have n=3-4 replicates, have been quantified, and oscillation assessed. We also quantified and plotted the oscillation of BMAL1 and REV-ERBα as comparisons. This is in the new Figure 6.

Minor Comments:

1) For all of the western blot images, authors need to show the molecular weight of the corresponding protein bands detected on the blots.

All raw western blot images, including molecular weights, will either be published as Supplemental Material or on FigShare (with a persistent doi), depending on the preference of the Journal. A private link is available for Reviewers with all the relevant background data, including westerns with molecular weights.

2) As a proof of concept, it would be interesting if knockout/knockout the MYC gene in these cell lines and look for the expression pattern of canonical clock gene expression levels to see whether it will help enhancing circadian rhythmicity. If authors cannot perform this experiment, it is important to address under discussion.

Thank you for this idea. Reviewer 1 had a similar idea / comment. We addressed it through previous studies, and a new analysis of MYC-high PC3 prostate cancer cells treated with the MYC inhibitor MYCi361 (Supplemental Figure 1C). See response to Review 1 Major Point 3 for more details.

3) It is not discussed, how many biological replicates were used for RNA-seq analysis?

In the revised manuscript, each RNA-sequencing experiment is performed from n=2 biological replicates and n=13-14 time points per replicate.

Referees cross-commenting

I completely agree with reviewer #3. In fact, I have raised the similar points in my major comments #2 and # 3.

As discussed below, we have responded to Reviewer comments with more replicates and new analyses of oscillating genes and proteins.

Reviewer #3:

Review of "MYC Disrupts Transcriptional and Metabolic Circadian Oscillations in Cancer and Promotes Enhanced Biosynthesis"<br /> DeRollo et al. attempt to find commonalities in how MYC affects transcriptional and metabolic programming by examining MYC-switchable U2OS, SHEP, and SKNAS cell lines. They claim that oncogenic MYC both represses transcriptional oscillation of many genes and supports rhythmic expression of other genes. They use RNA-Seq and UPLC-MS/MS with the appropriate bioinformatics analyses. In some cases, they employ qPCR and immunoblotting. In the three different cell lines, they observed that MYC either statically upregulates or downregulates oscillatory genes.

(Significance (Required)):

Myc is known to interfere with the rhythmic expression of core circadian clock genes. Myc seems to do this in order to rewire control-clock expression programs in favor of cell growth and proliferation.<br /> DeRollo et al intended to investigate which clock-controlled expression programs are deregulated by MYC. For this purpose, they investigated three cell lines. Unfortunately, it seems that clock-controlled genes are not really express with a (sufficiently) substantial amplitude in these cultured cells. It is therefore not possible to distinguish by RNA-seq the truly rhythmic genes from false positives. Therefore, it is not possible to reliably determine which metabolic rhythmic programs are deregulated by MYC.

We thank Reviewer #3 for their important observations and suggestions with regards to the number of replicates employed, and the confidence in the oscillations we observe. We have responded to these comments in a detailed fashion by adding replicates to our RNA-sequencing and immunoblot, and by comparing the oscillations in our cell lines to established primary models of circadian oscillation to determine the amplitudes of oscillations we observed.

As it stands, the work has technical and conceptual weaknesses.<br /> First, it is not clear how many replications the authors performed for RNA seq. For U2OS, this is explicitly stated. Replicate 1: four-hours sampling, ribosomal RNA depleted; replicate 2: two-hours sampling, polyA+ RNA. There do not appear to be replicates for the other two cell lines?

Thank you for this observation. In the initial manuscript submission, we used n=2 replicates for U2OS and SHEP, and n=1 replicate for SKNAS (apologies for this not being clear). In response to your comment and others, we added a new biological replicate for RNA-sequencing for SKNAS, so each cell line now has n=2 replicates. This allowed us to more confidently identify oscillating genes across biological replicates for each cell line.

U2OS cells are widely used in circadian research. These cells rhythmically express clock genes with a decent amplitude, which the authors confirmed by qPCR. However, the clock-controlled genes are generally expressed at a very low amplitude (in the range of standard deviation of RNA-Seq). It is therefore extremely difficult to identify and distinguish them from nonrhythmic genes by RNA seq. The fact that the authors find approximately the same number of rhythmic genes in MYC-OFF (Fig. 1B) as in MYC-ON (Supplemental Fig. 1B) and no overlap between the three cell lines tells that most of the genes shown in the heat maps are not truly rhythmic. Rather, they appear to represent those genes that are called rhythmic because a cosine wave happens to fit the data (better than a line). I suspect that true replicates (which are missing) would also show little or no overlap because most genes in these cells are probably not really rhythmic with any significant amplitude (and why would they be under constant conditions in a Petri dish?).

Thus, if there are no rhythmic clock-controlled genes that can be clearly distinguished from non-rhythmic genes, there is no way to tell which rhythms are attenuated by MYC (apart from the core clock genes shown in Fig. 1A), or to identify potentially rhythmic pathways.

Thank you for bringing up this important point about the confidence in the rhythmicity of genes examined. As is correctly noted and as brought up in response to Reviewer #2, cell lines such as U2OS, SKNAS, and SHEP have extensively been used for molecular clock studies (see Reviewer 2 Major Point 2). We also note that each cell line is now n=2 biological replicates, so all oscillating transcripts represent genes that were oscillating in both biological replicates. We take seriously the concern that the oscillating transcripts are not truly rhythmic, or of insufficient amplitude to be biologically significant. We employed a published algorithm, ECHO (De Los Santos et al, Bioinformatics 2019), which uses a conservative parametric approach to determine oscillations from sequencing data, and filters out genes that are too lowly expressed for oscillations to be determined, and those where a sharp increase or decrease in gene expression would preclude determining oscillations.

To directly test the strength of our observed oscillations in MYC-OFF conditions, we downloaded and analyzed time-series RNA-sequencing data from two entrained primary cell models that are known to have robust transcriptional circadian oscillations: MEFs and macrophages. These two datasets were analyzed in the same fashion as our cell lines, using the ECHO parametric algorithm, and we plotted the median amplitude of oscillation for all transcripts that had significant circadian oscillation (Supplemental Figure 2A). We found that the median amplitude of oscillation was within the same range as those from primary cells: SHEP cells showed nearly identical median amplitude to MEFs, while U2OS and SKNAS had slightly higher median amplitudes than macrophages. These suggest that the oscillating transcripts we observe and measure represent true oscillations above background noise that are similar to those observed in primary cell models where transcriptomic oscillation has been extensively studied.

With regards to oscillations observed in MYC-ON: we would first like to note that in some cases, there are fewer oscillating genes, especially in SKNAS, where there are less than half the number of oscillating genes in MYC-ON as compared to MYC-OFF. Nonetheless, the observation of emergent oscillations in MYC-ON cells is interesting, and we devote a paragraph to this in the Discussion (lines 457-482). We note that major perturbations to the molecular clock, such as DKO of REV-ERBα and β, result in emergent oscillations in the liver (Guan D et al, Science, 2020), and speculate that oscillations observed in MYC-ON may be from residual activity of CLOCK and BMAL1, which may occupy new sites when MYC is overexpressed.

If there are no strong rhythmic clock-controlled genes, there are probably no strong rhythms in clock-controlled metabolism. Indeed, the authors found no overlap in rhythmic metabolites.

Because metabolomics is far less sensitive than RNA-sequencing, we performed KEGG enrichment analysis on oscillating metabolites from both our replicates. We found that in MYC-OFF, the enriched metabolic pathways were identical in timing and identity of enriched pathways (Figure 8, Supplementary Figure 9), while these were quite divergent in MYC-ON. Thus, we concluded that common oscillating metabolic pathways in the absence of MYC are altered or disrupted by MYC activation.

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Review of "MYC Disrupts Transcriptional and Metabolic Circadian Oscillations in Cancer and Promotes Enhanced Biosynthesis"<br /> DeRollo et al. attempt to find commonalities in how MYC affects transcriptional and metabolic programming by examining MYC-switchable U2OS, SHEP, and SKNAS cell lines. They claim that oncogenic MYC both represses transcriptional oscillation of many genes and supports rhythmic expression of other genes. They use RNA-Seq and UPLC-MS/MS with the appropriate bioinformatics analyses. In some cases, they employ qPCR and immunoblotting. In the three different cell lines, they observed that MYC either statically upregulates or downregulates oscillatory genes.<br /> As it stands, the work has technical and conceptual weaknesses.<br /> First, it is not clear how many replications the authors performed for RNA seq. For U2OS, this is explicitly stated. Replicate 1: four-hours sampling, ribosomal RNA depleted; replicate 2: two-hours sampling, polyA+ RNA. There do not appear to be replicates for the other two cell lines?<br /> U2OS cells are widely used in circadian research. These cells rhythmically express clock genes with a decent amplitude, which the authors confirmed by qPCR. However, the clock-controlled genes are generally expressed at a very low amplitude (in the range of standard deviation of RNA-Seq). It is therefore extremely difficult to identify and distinguish them from nonrhythmic genes by RNA seq. The fact that the authors find approximately the same number of rhythmic genes in MYC-OFF (Fig. 1B) as in MYC-ON (Supplemental Fig. 1B) and no overlap between the three cell lines tells that most of the genes shown in the heat maps are not truly rhythmic. Rather, they appear to represent those genes that are called rhythmic because a cosine wave happens to fit the data (better than a line). I suspect that true replicates (which are missing) would also show little or no overlap because most genes in these cells are probably not really rhythmic with any significant amplitude (and why would they be under constant conditions in a Petri dish?).<br /> Thus, if there are no rhythmic clock-controlled genes that can be clearly distinguished from non-rhythmic genes, there is no way to tell which rhythms are attenuated by MYC (apart from the core clock genes shown in Fig. 1A), or to identify potentially rhythmic pathways.<br /> If there are no strong rhythmic clock-controlled genes, there are probably no strong rhythms in clock-controlled metabolism. Indeed, the authors found no overlap in rhythmic metabolites.

Significance

Myc is known to interfere with the rhythmic expression of core circadian clock genes. Myc seems to do this in order to rewire control-clock expression programs in favor of cell growth and proliferation.<br /> DeRollo et al intended to investigate which clock-controlled expression programs are deregulated by MYC. For this purpose, they investigated three cell lines. Unfortunately, it seems that clock-controlled genes are not really express with a (sufficiently) substantial amplitude in these cultured cells. It is therefore not possible to distinguish by RNA-seq the truly rhythmic genes from false positives. Therefore, it is not possible to reliably determine which metabolic rhythmic programs are deregulated by MYC.

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

Major comments:

1. The 3 cell lines used in this paper, what is the expression levels of MYC protein under -OFF and -ON conditions? It is important to demonstrate this information through the western blot data. Since the 4-hydroxy tamoxifen was used to activate MYC, what is the vehicle/control for MYC OFF cells? Otherwise, it will be difficult to assess with everything observed on this manuscript under MYC-ON could be due to 4-hydroxy tamoxifen treatment.
2. In Fig. 1A, it is crucial to demonstrate that the circadian synchronization protocol is working by performing statistical analysis with at least 3 biological replicates. This should be performed by either cosinor analysis and/or JTK cycle analysis of all the canonical clock genes including BMAL1 (ARNTL), CLOCK, CRY1, CRY2, PER1, PER2, DBP and NR1D1. This reviewer would like to see both transcripts (qPCR) and protein levels (western blot data) of those clock genes expression pattern. Without these results, rest of the data will be hard to conclude the connection with the circadian/molecular clock.
3. In Fig. 5A-C: It is important to repeat this western blot experiment at least 3 times and have the quantitation to demonstrate the circadian rhythmicity significance by probing to majority of the canonical clock proteins as discussed above.

Minor Comments:

1. For all of the western blot images, authors need to show the molecular weight of the corresponding protein bands detected on the blots.
2. As a proof of concept, it would be interesting if knockout/knockout the MYC gene in these cell lines and look for the expression pattern of canonical clock gene expression levels to see whether it will help enhancing circadian rhythmicity. If authors cannot perform this experiment, it is important to address under discussion.
3. It is not discussed, how many biological replicates were used for RNA-seq analysis?

Referees cross-commenting

I completely agree with reviewer #3. In fact, I have raised the similar points in my major comments #2 and # 3.

Significance

Using the circadian synchronized cancer cell lines, DeRollo and colleagues characterized the MYC oncoprotein role in metabolic role through the circadian clock disruption. Authors found that forced activation of MYC disrupts up to 85% of genes oscillation particularly nutrient transporter glycosylation and amino acid metabolism. This work addresses important questions in the circadian clock and cancer field through the oncogene activation, and the manuscript is well-written. However, there are a few concerns that should be addressed to improve the manuscript quality.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

This is an interesting paper from the Altman, Weljie and Dang labs that furthers their previous publications looking at the effect of "oncogenic" Myc levels have on circadian gene expression. They provide compelling data that in neuroblastoma and osteosarcoma models of Myc amplification circadian gene expression and metabolite fluctuation are lost. The data is convincing and comprehensive and should be of broad general interest. There are a few major issues that need to be addressed.

1. Is there a control (done here or in prior literature) showing that simply adding tam to cells doesn't change circadian gene expression?
2. All of the experiments rely on Myc:ER fusions. The authors should mine other datasets to determine of systems that rely on conditional expression of wt Myc drive a similar loss of circadian gene expression.
3. The authors argue Myc:ER fusions mimic Myc amplification which is common in cancer and they discuss several previous papers that at least correlate the presence of amplified Myc with loss of circadian gene expression. It should be possible to test whether reduction of Myc by knockdown or using a Myc inhibitor restores circadian gene expression in a cell line known to be Myc amplified. This need not be an exhaustive RNA-seq experiment, but looking at a handful of circadian genes using a qPCR approach would be informative.
4. The data pretty clearly shows that metabolites lose their periodicity MycON cells. Can these be linked back to loss of circadian expression of specific genes in those metabolic pathways? If so, are genes direct Myc transcriptional targets in other studies?
5. The finding Myc activation "releases" metabolic and biosynthetic pathways from circadian control implies that this must have something to do with Myc-dependent transformation. A priori, it is not obvious why this should be the case. Do metabolic precursors and biosynthetic molecules become periodically limiting when their levels oscillate in MycOFF cells? In MycOn cells do the non-oscillating metabolites, provide a growth advantage? This is a difficult question to address and one that is certainly beyond the scope of this manuscript. The authors should address this issue in their discussion

Minor points

1. phrase "for the first time" is used multiple times in the discussion. Gets a bit redundant ( and loses impact). Consider revising.
2. In figure 4, the periodicity in expression of the proteins in figure 4 is fairly clear, but it might be beneficial to bracket (or denote in some other way) the circadian fluctuation in expression.

Referees cross-commenting

I had not considered the important points raised by reviewer 3. The authors definitely need to address the concern over replicates and whether the gene expression of truly rhythmic. If not, this seems like a fatal flaw in the MS.

Significance

The Myc oncogene is dysregulated in many cancer types, so there is considerable interest in the mechanisms that underpin its function as a transforming oncogene. This group of authors has previously described that Myc can disrupt circadian gene expression, which is linked to several types of cancer. This paper extends the authors previously findings by performing careful timed RNA-seq analysis and metabolomic analysis. The work is well done, and the findings justify the conclusions. This paper should be of interest to those who study Myc, circadian gene expression and cancer. Two key limitations are noted: 1) the cells that are analyzed are grown entirely in vitro in serum and nutrient replete media, 2) there is no direct evidence that the blockage of circadian gene expression by Myc is important for Myc-dependent transformation, although it seems likely. These two limitations do not detract from the significance of the manuscript.

My expertise is in cancer-centric gene regulatory mechanisms

Transparent Peer Review

---

Download the complete Review Process [PDF] including:

• reviews
• authors' reply
• editorial decisions

</br>

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

Learn more at Review Commons

---

Reply to the reviewers

We would like to thank the Review Commons editor and three reviewers for their enthusiastic response, including their constructive suggestions and appreciation of the high impact and originality of our study. We have completed the revisions and new analyses suggested by the reviewers, and we thank the reviewers for their suggestions to increase the impact and interest in this work and for guiding us towards this much improved manuscript.

In this response letter, we present the response to each reviewer comment and associated revisions made to the text and figures as bullet points below the reviewers' text (black text).

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

Summary:

Yang et al. took advantage of recently published long-read-based genomic sequences of nearly homozygous genomes from complete hydatidiform moles to retrieve allelic sequences of LINE-1, the currently only active and autonomous retrotransposon of the human genome, and produced the repertoire of intact LINE-1 in a genome. The authors performed cell-culture-based retrotransposition assays measurements and in vivo fitness estimations of all identified intact LINE-1 to infer evolutionary dynamics. In this article, the authors further validate the major contribution of polymorphic LINE-1 to the de novo retrotransposition events in the human genome. They also described, at unprecedented resolution, allelic variations among LINE-1 loci and the potential impact of these variations to the interpretation of mutagenic potential of each LINE-1 locus.

Major comments:

1 - The key conclusions of the article are mostly convincing. However, it would be a substantial improvement to consolidate the data of the article with information about known active LINE-1s in germ cells or in cancer by using data from recent publications of the Devine and Tubio labs (for example PMID: 34772701, 32024998, 25082706). Across the article, no mention is made of the transductions generated during LINE-1 de novo retrotransposition, which is instrumental to monitor in vivo activity of a group of LINE-1 active copies. It would be of particular interest to make a link between in vitro activity from this study with LINE-1 classification based on their observed activity in cancer (PMID: 32024998, Figure 3b).

• We thank this and the other reviewers for this suggestion. We agree that a more explicit comparison to the often-reported counts of 3’ transductions would be a valuable addition to our analyses. We have added the 3’ transduction counts from PMID:34772701, PMID:32024998 and PMID:25082706 to Table S2 (column Y, Z and AA), and made a comparison between these data and our Hamming-distance-based in vivo activity, as the new Figure S5. We found correlations between the two measurements in a significant proportion of LINE-1s, but some interesting exceptions exist which likely reflects the fact that most catalogued 3’ transductions come from cancer genomes, and cancer and germline cells represent distinct cellular environments in which distinct sets of LINE-1s are able to replicate (and leave 3’ transductions). In addition to the new figure (Figure S5), we have added a discussion paragraph focused on this interesting comparison.

2 - The use of CHM1 BAC library Sanger sequencing validation and comparison with CHM13 and hg38 sequences is instrumental to support the building of LINE-1 repertoire in CHM1 genome, which is a valuable contribution of the article. The use of a distance-based metric to infer fitness of a LINE-1 is an interesting approach and allow to group LINE-1 copies based on their in vivo activity potential. Again, it would be beneficial to correlate the inferred fitness and retrotransposition activity of copies/alleles, when known, from the above-mentioned literature.

• The sequence validation of LINE-1 sequences in CHM1 is an important point which we have addressed in the edited manuscript. Specifically, we used three forms of sequence validation including end-sequencing of one clone of each LINE-1 after it was cloned into the retrotransposition vector and whole-plasmid sequencing of select LINE-1s with discrepant activity amongst the three clones we assayed. In addition, we sequenced the entire LINE-1 sequence for four LINE-1s which had the largest number of mutations relative to their allelic counterpart in CHM13. Please see the above response to ‘Major comment 1’ for details of our new analysis comparing the previous literature to our data.

3 - Some aspects of the writing of the article should be improved to better support the conclusions.

• We thank the reviewer for providing these examples of parts of the text that were particularly difficult to read and comprehend. We have deeply streamlined and improved the text throughout the manuscript based upon detailed editing for readability and clarity by two experienced scientific writers. Below, we detail how we revised the particular sections presented by the reviewer, but we think the entire manuscript is now more succinct and clearer.

• In general, the descriptions are dense, and details could be provided in a more direct way to lighten the results section. Several redundancies in the discussion can be combined to increase clarity.

• We have spent considerable time tightening up the text, including removing several overlapping sections from the discussion which can be seen in the included version with changes tracked.

• There is a lack of clarity in the description of how was handled each pair of alleles for which retrotransposition measurements vary between the study and the literature (last paragraph of the "Comprehensive measurement of LINE-1 in vitro activity in a human genome" section). It is not completely clear how the analysis was done and the way the data is presented in File S3 is not helping to support the conclusion. It could be useful to include some illustrative examples in a panel of Figure 2.

• We agree that this description was hard to parse, and we have rewritten this and accompanying methods to simplify our explanation of these results. In addition, we have revised Figure 2 to show the data in much more detail. To further aid the logic flow related to this section, we moved the previous Figure 5B to Figure 2B, updated it with more suitable examples and edited the associated descriptions.

• Regarding inferred in vivo activity, the text contains alternative description with the use of "fit" / "unfit", in vivo "active" / "inactive" or "no closely related LINE-1s" terms. The authors should find a way to clearly define and systematically use one set of terms to enhance clarity along the article. To parallel with in vitro active/inactive, it would be useful to use in vivo fit/unfit.

• We thank the reviewer for this suggestion and agree with their suggested unified use of ‘in vivo fit/unfit’. To clarify and simplify these terms as much as possible, we added detailed explanations of in vivo / in vitro activity and systematically defined in vitro "active/inactive" (page 5, right column, line 50) and in vivo "fit/unfit" (page 8, left column, line 26) at their first appearance in the article, and we changed most instances of "in vivo activity" to "in vivo fitness" when context permits.

4 - The authors suggest that in vitro activity can be predicted by integration of population frequency and in vivo activity (/fitness) (second paragraph of the "An analysis of LINE-1 evolutionary history [...] and in vivo activity" section). It would be beneficial to strengthen the writing of this section and ultimately validate/test the model by including data from some of the previous studies (e.g. Brouha 2003, Lutz 2003, Seleme 2006, Beck 2010, Rodriguez-Martin 2020, Chuang 2021).

• We have thoroughly revised this section of the results (see response to ‘Major comment 3’ above), per the reviewers suggestion, to increase reader comprehension of this important data. In addition, we greatly appreciate the reviewer’s suggestion of a very interesting experimental direction – moving beyond a single long-read-based genome to many diverse genomes, and ultimately calculating the in vivo fitness of the LINE-1s from these diverse genomes. For a long time this has not been possible, but the recent publication of the Human Pangenome presents an opportunity to study this interesting question. Though beyond the scope of this paper, our lab is actively working on this fascinating question, and we appreciate the reviewer’s shared interest in this question.

5 - The identification of adaptive mutations is only partially described and not strongly supported by experimental or analytical data. It would be interesting to explore the role of phylogenetically informative sites described in Figure 5B/C by testing non CHM1 alleles in retrotransposition assay (by introducing amino acid changes into the cloned CHM1 LINE-1 alleles) or by positioning the sites in ORF1p or ORF2p structure and/or domains to infer impact on functionality.

• The reviewer rightly points out that this is one of the most interesting and novel findings of our manuscript. However, the testing of potentially adaptive mutations is potentially complicated and nuanced. Specifically, we don’t know the mechanism by which these mutations might be adaptive. It is possible that they simply increase in vivo germline retrotransposition activity and this increase would be reflected by an increase of in vitro retrotransposition activity. However, another possibility is that these adaptive phenotypes only show themselves in vivo or in the context of the host restriction factors expressed in the germline. We strongly agree with the reviewer that experimental and analytical data on the phylogenetic informative sites associated with the Figure 5 phylogeny is the key to finding out the mechanisms for these changes to affect LINE-1 activity/fitness, and we are, indeed, exploring this very question in the lab now with related projects. We respectfully suggest that these (extremely cool) experiments are beyond scope of this paper, but we have also added some more detailed description and analyses of the potentially adaptive LINE-1 variations from Figure 5 (from page 9, right column, line 50 to page 10, left column, line 5).

Minor comments:

1 - Regarding the in vitro retrotransposition assay, it would be beneficial to provide more data. The current Figure 2 could be enriched by the addition of data related to the variation in the replicates of the experiment (technical but mostly biological with the three clones per LINE-1 tested). Figure 2 could include a dashed line for 100% L1RP and 5% (since it is used as a threshold). It would be useful to provide an additional panel in Figure 2 to illustrate alleles of LINE-1 that are active in this study and compare the values obtained previously in other studies. Similarly, a supplemental table or alignment could be provided to document amino acid changes in the two alleles of each pair (see comment above in the Major Comment 5). The L1Hs subfamilies could also be included in the graph of Figure 2 to support the conclusions of remaining active old L1Hs at allelic forms in the human genome.

• Upon consideration of this helpful comment, we now augment the presentation of our in vitro activity data with a remade Figure 2 with boxplots to show the variation of the data, as well as a horizontal dashed line showing the active-cutoffs and star signs showing which LINE-1s belong to L1Hs or L1PA2.

2 - Also, the validation of cloning is not well described. The choice of PCR validation must be supported by more technical details on the design of the primers used to validate each copy. The authors should clearly state that the strategy chosen for retrotransposition assay does not rely on the transcription from LINE-1 5UTR but from an upstream strong promoter, ruling out the role of potential mutations in LINE-1 promoter.

• As detailed above in the response to ‘Major Comment 1’, we used a combination of end sequencing, whole plasmid sequencing, and multi-read Sanger sequencing to validate the sequences of each LINE-1 cloned from a CHM1 clone. When cloning each LINE-1, we used a specific set of primers designed for the ends of the UTRs for each LINE-1. We have updated the methods and text to clarify this cloning step, and the sequences of these oligos are included in Table S2.
• To clarify the fact that our retrotransposition assays use a common, strong promoter, we added text in several places stating this setup and discussing (paragraph that starts at page 11, right column, line 18) how 5'UTRs and other non-ORF factors can affect the rate of LINE-1 in vitro activity.

3 - There are discrepancies with the reported numbers of LINE-1s between Figure 1A and Table S1: 154 vs. 151 in CHM1, 144 vs. 143 in CHM13, respectively.

• We thank the reviewer for spotting this error on our part. The numbers in Figure 1 and the main text were correct, and we have revised Table S1 to reflect this data.

4 - The choice of colors in Figure 3 is not perfectly clear and sometimes not as reported in the text (green highlight and orange highlight). Part of the Figure 3 legend is missing. It should include a description of the color code chosen for the right histogram.

• We thank the reviewer for bringing this inconsistency to our attention. Based upon feedback from all reviewers, we have simplified the color scheme in Figure 3 and Figure 5 to focus on the core conclusions of these two figures. Specifically, in Figure 3, we have removed the quadrant shading and more clearly presented the cutoffs of ‘polymorphic/high frequency’ and ‘in vitro active/inactive’ as dashed lines in the scatter plot. In Figure 5, we have simplified to two colors – black for in vivo unfit and orange to show the in vivo fit LINE-1s which is also used in Figure 4 to show the definition of in vivo activity. These updated colors are now defined in the figure legends and main text, and we have made references to these colors consistent throughout.

5 - For Figure 4, it would be useful to define in the legends the color code for the top histogram. To better read the scatter plot, the words "fit" and "unfit" could be added on each side of the vertical dashed line.

• We thank the reviewer again for suggestions to improve the clarity of our figures. As mentioned above in ‘Minor comment 1’, we have removed unnecessary colors including the gradient of the histograms in Figure 3 and Figure 4, since the boundaries of each bin are already defined by the axis labels and tics. As suggested, we have also added ‘fit’ and ‘unfit’ labels to the dashed cutoff line in Figure 4 to clarify the meaning of this line.

6 - In panel B of Figure 5, it seems that the color code and hot/cold description is not fully formatted.

• This formatting error has been corrected.

Reviewer #1 (Significance (Required)):

In this article, Yang and colleagues present an unprecedented view of the allelic diversity of young LINE-1 copies related to variable retrotransposition activity in an individual genome. One key aspect of their work is the description of the presence of young active LINE-1 alleles that are absent or non-intact in other genome assemblies, while described at a lower scale in initial work from the Kazazian and Moran labs, cited in the manuscript. The work of Yang et al. demonstrates the requirement of multiple approaches and long-read-based sequencing of individual genomes to fully infer the mutagenesis risk of LINE-1 activity.

The data and methods provided by the authors open the door to a more systematic analysis of mutations and rare allelic forms to understand both mechanistic aspects and evolution of LINE-1 retrotransposition in the human genome. The identification of rare allelic forms of old LINE-1 that retain activity despite previously being considered as inactive is particularly interesting in the light of LINE-1 evolution in the human genome. The authors also describe allelic diversity inside of the Ta1d subfamily, suggesting further diversification and emergence of LINE-1 subgroups. Together with the identification of nucleotide polymorphism among LINE-1 copies, these findings strengthen the notion of individual genomes with individual set of potentially mutagenic LINE-1 alleles.

The findings and methods described in this article are of great interest to a wide audience including the fields of research focusing on human genome evolution, transposable elements, genomic instability, human genetic variation, and personalized medical diagnostic.

Aurélien J. Doucet CNRS - Université Côte d'Azur

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

This manuscript is an interesting and well-crafted study of LINE-1 activity at the single genome human genome level using long read-based haploid assemblies. The manuscript has some real gems and address critical aspects of LINE- biology that are typically not rigorously examined. The authors are to be commended for undertaking this exercise and for providing interesting perspectives that challenge the dogma that dominates the field in several areas. Despite the noted strengths of the contributions, the manuscript ignores the clear limitations inherent to the approaches taken and at times appears as dogmatic as the dogma that they themselves are trying to challenge. These deficiencies should be addressed before this manuscript is published.

• We thank Reviewer 2 for their enthusiastic appreciation of the value and innovation of our manuscript. We also thank the reviewer for encouraging us to make careful consideration of the missing references relevant to our findings. We have had two researchers with experience in relevant fields edit our text for both readability, clarity, and proper inclusion of relevant references. We have added these throughout and taken careful effort to replace ‘dogmatic’ statements with clear presentations of the data and thorough referencing of the relevant literature.

Several major and minor points to consider during revision include:

Major:

1. Several strategies have been published in the past that have confidently assign LINE-1s to specific loci despite use of shorter reads. These works should be acknowledged, even if as stated in the manuscript, use of longer reads will only continue to add confidence and validity to future assignments.

2. We thank the reviewer for this suggestion, and we apologize for the omission of these important publications. As noted above, we have added numerous relevant references (reference 17-27 in the revised text) throughout the text including previous work that used short reads to confidently assign polymorphic/non-reference LINE-1s to specific loci. For example, we now cite the MELT pipeline to detect de novo L1 insertions with short reads (PMID: 28855259), and Iskow et al. 2010, which detects LINE-1s with junction fragment sequencing (PMID: 20603005). We have also added additional text to clarify that short reads are, indeed, often sufficient to place new LINE-1 insertions, while long reads are especially useful for resolving the sequence and location of these insertions. The new text (page 2, left column, line 22-30) presents the advantages/disadvantages of both short reads and long reads.

3. One of the important requirements for precise quantification of LINE-1 activity and predicted risk scores cited in the manuscript was the need to predict activity based on sequence and location. This requirement, as posited in the manuscript, ignores the critical role of epigenetic control in the regulation of LINE-1 activity. As such, a discussion that acknowledges the critical roles of histone and DNA covalent modifications, and that integrates epigenomic insight into predictions of LINE-1 activity must be included in the manuscript.

4. We thank the reviewer for suggesting this important discussion point. In response, we have expanded our discussion of this topic to place our data in the context of other literature on the effects of epigenomic regulation on in vivo LINE-1 activity, including histone and DNA modifications, as well as the effects of post transcriptional restriction factors (paragraph starting at page 11, right column, line 42).

5. The limitations associated with the use of the CHMI were not addressed in the manuscript. While CHMI contain a paternal only genome, with no maternal contribution, the moles may arise from fertilization of an anuclear empty ovum by a haploid 23,X sperm or fertilization by two sperm giving rise to 46,XX or 46,XY karyotype. As such, generalizable conclusions about CHMI genetics should be carefully made given that the loss of maternal epigenetic imprinting and gain of paternally imprinted expression may result in abnormal gene expression, including that of LINE-1s. These variances will in turn impact LINE-1 activity profiles.

6. We thank the reviewer for pointing out this confusingly written section of our manuscript, and we agree with the reviewer that LINE-1 activity measurements could be complicated in the CHM cell lines; however, all of our retrotransposition assays were carried out in the common background of 293T cells (chosen because of their low expression of know LINE-1 restriction factors (PMID: 25182477). We have modified the text (page 11, right column, line 52) to clarify these points.

Minor

1. Important citations of previously published work are not properly referenced throughout the manuscript. These are too numerous to identify individually, but the authors should carefully read the manuscript to ensure that proper documentation and reference to previous work is duly acknowledged.

2. Please see our above response to ‘Major point 1’.

There are several typos and missing prepositions that should be corrected. For instance, on page 7, the word "great" should be "greater".

• Please see our above response to ‘Major point 1’ and Reviewer 1’s ‘Major comment 3’ for details on our in depth editing of the manuscript.

Reviewer #2 (Significance (Required)):

The contribution is highly significant as it challenges previously held concepts and advances our understanding of critical structure and function relationships of Line-1s.

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

Yang et al. perform an in-depth analysis of potentially mobile source L1 alleles in a single human genome (CHM1) previously subjected to Pacbio whole genome sequencing. The retrotransposition efficiencies of source L1 alleles with intact ORFs were tested in vitro, and these efficiencies compared to a model of in vivo activity based on Hamming distance to other ORF-intact L1 alleles. Comparisons of CHM1 L1 alleles are made to CHM13 (used for the recent T2T reference assembly), and also to population-scale sequencing efforts to establish how widespread each source L1 allele is. These data showcase the advantages of being able to resolve L1 alleles with long-read sequencing, allowing the field to make much more accurate predictions of retrotransposition potential in a given genome. The core analyses appear robust and for the most part enough detail is provided to follow what was done.

• We thank Reviewer 3 for their in depth reading and analysis of our manuscript and data, and for their enthusiasm about the importance of this work in the context of foundational research from their lab and many others in the field. We have carefully considered each comment and completed several new analyses of our data and related data from other publications. We feel that our manuscript is much improved with this new data, as detailed below. Comments:

1) The text overlooks the potential importance of L1 5'UTR mutations in L1 activity and evolution, as per PMID:25274305, PMID:1701022, and other studies, as well as the impact of genomic context on source L1 activity, as per PMID:27016617, PMID: 33186547 etc. L1 promoter evolution is arguably a major driver of L1 lineage emergence.

• We thank the reviewer for suggesting these important additions. To present the relevance of 5'UTR mutations on LINE-1 activity and evolution, we added a discussion paragraph (paragraph starting at page 11, right column, line 16) to address how 5'UTRs and other non-ORF factors can affect the rate of LINE-1 in vitro activity. Several key references have been added and discussed in the paragraph: PMID:25274305 reported the regulation of human LINE-1 by the evolution of its 5'UTR; PMID:1701022 was one of the earliest papers that found the effect the 5'UTR promoters on human LINE-1 retrotransposition; PMID: 27016617 and PMID: 33186547 reported specific L1 loci regulated by different promoters and was included in the discussion; PMID:9430649 was one of the examples of non-human LINE-1 lineages emerging because of different promoters and was cited in the added discussion paragraph. We have also added discussion points to make clear that genomic content has a clear role in the activity of source LINE-1s (paragraph starting at page 11, right column, line 42).

2) The way the retrotransposition assay is done here (I think) removes parts of the UTRs as part of introducing L1s into retrotransposition vectors, meaning that the assay tests the biochemical activity of the ORFs. It would be helpful to readers to have a more detailed method for this assay, including the origins of the reporter plasmids, whether there is a CMVp boosting the L1 promoter etc, and some clarity about how much of each L1 was cloned into the assay.

• We have added relevant details to the results (page 6, left column, line 5), discussion (page 11, right column, line 52), and methods (page 13, right column, line 16 and 30) sections to clarify the reviewer’s important points. The LINE-1s tested for in vitro activity were cloned in their entirety (UTRs and ORFs) but driven by both their native promoters in the 5'UTR as well as an upstream CMV promoter. Also, please see our response to Reviewer 1 ‘Minor comment 2’ above.

3) Pacbio long-read sequencing has been used previously to locate and characterise L1 alleles in human DNA. The Introduction states: "These represent the first scalable methods to catalog LINE-1 locations and sequences in individual human genomes". The "first" here is questionable. Citations to PMID:31853540 and PMID:34772701 should be included. The latter is particularly relevant at it not only resolves source L1 sequences with PacBio sequencing but also summarises their retrotransposition efficiencies in vitro and population frequencies.

• We apologize for leaving out these and other important references, and we agree that the “first” claim is unnecessary. We have added the references suggested for the reviewer as well as several other important references as detailed in the above response to Reviewer 2 ‘Major point 1’. In addition, we have revised the adjacent text and deleted any references to our work as the “first” in these approaches.

4) I am very interested in the two source L1s (on chr7 and chr9) that were found here to be more active in vitro than L1RP (to my knowledge the most active such element isolated to date, or close to it). Is there anything unusual about these two L1s? A quick look at the supplemental suggested the chr9 element was 5' truncated, was it tested as such in vitro? Also I think it would be worth contrasting the assay (all in HEKs) used here to test efficiency with the assay used by Brouha ... I feel readers may be surprised to find two L1s more mobile than L1RP in one genome.

• To provide more details about the two active L1s (chr7 and chr9), we investigated key changes that could be related to the in vitro activity of these elements and now show them in Figure 2B and File S3. In the process of this updated analysis and suggested modifications to Figure 2 by this reviewer and Reviewer 1, we saw that the chr7 L1, mentioned here, had one very high activity measurement pulling its activity above L1RP. As such, we decided to more rigorously normalize our data by using the positive and negative controls across all plates of each day instead of normalizing to the controls of individual plates, as we had previously done. In addition, for any L1 with discrepant activity among the three clones we assayed, we used whole plasmid sequencing to confirm the identity and consistency of all three clones. In three cases, we found that one or two of the three clones was the wrong L1, and hence excluded them for the in vitro activity calculation. After this validation and testing of additional clones, all clones from the same L1 have consistent in vitro activity (see updated Figure 2). The updated in vitro activity of the chr7 L1 is at 86.7% L1RP, and the chr9 L1 is at 261.4% L1RP in addition to the chr17 LINE-1 with 117% L1RP and two additional LINE-1s that have near-L1RP activity levels (Table S2, column S). These changes in L1 activity were updated in the text, figures, and supplemental materials. Also, we note that the chr9 element is 6019bp in length and was tested as such in vitro. Current work in the lab is attempting to understand the mechanisms of increased LINE-1 in vitro and in vivo activity, as described in detail in response to Reviewer 1’s ‘Major comment 5’.

5) In several places it is mentioned how L1 alleles may differ from sequences provided in reference assemblies, and may therefore explain discrepancies between assay results here and in other studies (e.g. Brouha). The Seleme and Lutz papers are correctly mentioned here, but arguably the most complete demonstration of this concept, from PMID:31230816, is overlooked. This study reports a chr13 source L1 that was previously found to be inactive by Brouha, and with broken ORFs in the reference genome, has both mobile and immobile alleles in the human population. This L1 is actually in CHM13, but not CHM1, and is "hot" in some individuals and not others. There are several places in the manuscript where this earlier study is very relevant and it would be fair to ask it to be mentioned, especially as the results are concordant. The same concept is reinforced by an even more recent paper (PMID:35728967), except in macaque, showing that this is a general consideration for primate L1 lineages, and actually that source L1 is relatively old and yet jumps extremely well in vitro, which fits an observation made in the present study. Mutually supporting observations like these really add confidence that what is reported in the present study is robust.

• We thank the reviewer for their suggestion to include these highly relevant and important papers; we apologize for this initial omission. We have now added several sentences to the introduction and discussion (top left paragraph page 11) in addition to citations of these papers.

6) Hamming distance between ORF-intact source L1 alleles is used to assess in vivo activity. This seems reasonable. However, in other works, transductions have been used to identify families of very closely related L1s. I realise that many highly mobile source L1s will rarely generate insertions carrying transductions, and yet I wonder if any of the youngest L1s in the present study form transduction families, and whether estimates of in vivo activity based on transductions found in population-scale data would reconcile better with in vitro retrotransposition assay data.

• We thank the reviewer for pointing out our exclusion of data on 3' transductions, the most commonly used surrogates of in vivo activity, while also acknowledging that only a small percent of new L1 retrotranspositions carry 3' transduction. Please see our above response to Reviewer 1’s ‘Major comment 1’ for details on our newly added comparison of our in vivo activity data to the 3' transduction-based somatic LINE-1 retrotransposition landscape of those reported in PMID:34772701, PMID:32024998 and PMID:25082706.

7) In the Introduction, it is stated that L1 only transmits vertically. It may be prudent to mildly qualify this position, based on PMID:29983116.

• The referenced text in the introduction has been changed from "LINE-1s only transmit vertically" to "LINE-1s generally transmit vertically with few exceptions", with the addition of the suggested citation.

8) A column in Table S2 looks mislabelled: Column R should be CHM1 not CHM13?

• We thank the reviewer for seeing this error. Column P (Column R in the previous version) of Table S2 is now correctly labeled as "CHM1 L1 intactness".

Geoff Faulkner (University of Queensland)

Reviewer #3 (Significance (Required)):

This is a well-executed study of considerable interest to the mobile DNA field, and anyone working with long-read DNA sequencing. Its strengths are the genomic and bioinformatic analysis, leveraging the PacBio long-read data and BAC library available for CHM1 to full effect. One limitation (in current form) is its near-exclusive focus on ORFs to encapsulate how mobile a given L1 allele is, when genomic context and L1 promoter mutations could also contribute heavily. Although I liked the manuscript very much and enjoyed reviewing it, some of the conceptual advances are encroached upon by other work (including some very relevant and yet uncited literature). These issues can very likely be addressed via a revision, additional analyses may be required but not new experiments.

Geoff Faulkner (University of Queensland)

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Yang et al. perform an in-depth analysis of potentially mobile source L1 alleles in a single human genome (CHM1) previously subjected to Pacbio whole genome sequencing. The retrotransposition efficiencies of source L1 alleles with intact ORFs were tested in vitro, and these efficiencies compared to a model of in vivo activity based on Hamming distance to other ORF-intact L1 alleles. Comparisons of CHM1 L1 alleles are made to CHM13 (used for the recent T2T reference assembly), and also to population-scale sequencing efforts to establish how widespread each source L1 allele is. These data showcase the advantages of being able to resolve L1 alleles with long-read sequencing, allowing the field to make much more accurate predictions of retrotransposition potential in a given genome. The core analyses appear robust and for the most part enough detail is provided to follow what was done.

Comments:

1. The text overlooks the potential importance of L1 5'UTR mutations in L1 activity and evolution, as per PMID:25274305, PMID:1701022, and other studies, as well as the impact of genomic context on source L1 activity, as per PMID:27016617, PMID: 33186547 etc. L1 promoter evolution is arguably a major driver of L1 lineage emergence.
2. The way the retrotransposition assay is done here (I think) removes parts of the UTRs as part of introducing L1s into retrotransposition vectors, meaning that the assay tests the biochemical activity of the ORFs. It would be helpful to readers to have a more detailed method for this assay, including the origins of the reporter plasmids, whether there is a CMVp boosting the L1 promoter etc, and some clarity about how much of each L1 was cloned into the assay.
3. Pacbio long-read sequencing has been used previously to locate and characterise L1 alleles in human DNA. The Introduction states: "These represent the first scalable methods to catalog LINE-1 locations and sequences in individual human genomes". The "first" here is questionable. Citations to PMID:31853540 and PMID:34772701 should be included. The latter is particularly relevant at it not only resolves source L1 sequences with PacBio sequencing but also summarises their retrotransposition efficiencies in vitro and population frequencies.
4. I am very interested in the two source L1s (on chr7 and chr9) that were found here to be more active in vitro than L1RP (to my knowledge the most active such element isolated to date, or close to it). Is there anything unusual about these two L1s? A quick look at the supplemental suggested the chr9 element was 5' truncated, was it tested as such in vitro? Also I think it would be worth contrasting the assay (all in HEKs) used here to test efficiency with the assay used by Brouha ... I feel readers may be surprised to find two L1s more mobile than L1RP in one genome.
5. In several places it is mentioned how L1 alleles may differ from sequences provided in reference assemblies, and may therefore explain discrepancies between assay results here and in other studies (e.g. Brouha). The Seleme and Lutz papers are correctly mentioned here, but arguably the most complete demonstration of this concept, from PMID:31230816, is overlooked. This study reports a chr13 source L1 that was previously found to be inactive by Brouha, and with broken ORFs in the reference genome, has both mobile and immobile alleles in the human population. This L1 is actually in CHM13, but not CHM1, and is "hot" in some individuals and not others. There are several places in the manuscript where this earlier study is very relevant and it would be fair to ask it to be mentioned, especially as the results are concordant. The same concept is reinforced by an even more recent paper (PMID:35728967), except in macaque, showing that this is a general consideration for primate L1 lineages, and actually that source L1 is relatively old and yet jumps extremely well in vitro, which fits an observation made in the present study. Mutually supporting observations like these really add confidence that what is reported in the present study is robust.
6. Hamming distance between ORF-intact source L1 alleles is used to assess in vivo activity. This seems reasonable. However, in other works, transductions have been used to identify families of very closely related L1s. I realise that many highly mobile source L1s will rarely generate insertions carrying transductions, and yet I wonder if any of the youngest L1s in the present study form transduction families, and whether estimates of in vivo activity based on transductions found in population-scale data would reconcile better with in vitro retrotransposition assay data.
7. In the Introduction, it is stated that L1 only transmits vertically. It may be prudent to mildly qualify this position, based on PMID:29983116.
8. A column in Table S2 looks mislabelled: Column R should be CHM1 not CHM13?

Geoff Faulkner (University of Queensland)

Significance

This is a well-executed study of considerable interest to the mobile DNA field, and anyone working with long-read DNA sequencing. Its strengths are the genomic and bioinformatic analysis, leveraging the PacBio long-read data and BAC library available for CHM1 to full effect. One limitation (in current form) is its near-exclusive focus on ORFs to encapsulate how mobile a given L1 allele is, when genomic context and L1 promoter mutations could also contribute heavily. Although I liked the manuscript very much and enjoyed reviewing it, some of the conceptual advances are encroached upon by other work (including some very relevant and yet uncited literature). These issues can very likely be addressed via a revision, additional analyses may be required but not new experiments.

Geoff Faulkner (University of Queensland)

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

This manuscript is an interesting and well-crafted study of LINE-1 activity at the single genome human genome level using long read-based haploid assemblies. The manuscript has some real gems and address critical aspects of LINE- biology that are typically not rigorously examined. The authors are to be commended for undertaking this exercise and for providing interesting perspectives that challenge the dogma that dominates the field in several areas. Despite the noted strengths of the contributions, the manuscript ignores the clear limitations inherent to the approaches taken and at times appears as dogmatic as the dogma that they themselves are trying to challenge. These deficiencies should be addressed before this manuscript is published.

Several major and minor points to consider during revision include:

Major:

1. Several strategies have been published in the past that have confidently assign LINE-1s to specific loci despite use of shorter reads. These works should be acknowledged, even if as stated in the manuscript, use of longer reads will only continue to add confidence and validity to future assignments.
2. One of the important requirements for precise quantification of LINE-1 activity and predicted risk scores cited in the manuscript was the need to predict activity based on sequence and location. This requirement, as posited in the manuscript, ignores the critical role of epigenetic control in the regulation of LINE-1 activity. As such, a discussion that acknowledges the critical roles of histone and DNA covalent modifications, and that integrates epigenomic insight into predictions of LINE-1 activity must be included in the manuscript.
3. The limitations associated with the use of the CHMI were not addressed in the manuscript. While CHMI contain a paternal only genome, with no maternal contribution, the moles may arise from fertilization of an anuclear empty ovum by a haploid 23,X sperm or fertilization by two sperm giving rise to 46,XX or 46,XY karyotype. As such, generalizable conclusions about CHMI genetics should be carefully made given that the loss of maternal epigenetic imprinting and gain of paternally imprinted expression may result in abnormal gene expression, including that of LINE-1s. These variances will in turn impact LINE-1 activity profiles.

Minor

1. Important citations of previously published work are not properly referenced throughout the manuscript. These are too numerous to identify individually, but the authors should carefully read the manuscript to ensure that proper documentation and reference to previous work is duly acknowledged.
2. There are several typos and missing prepositions that should be corrected. For instance, on page 7, the word "great" should be "greater".

Significance

The contribution is highly significant as it challenges previously held concepts and advances our understanding of critical structure and function relationships of Line-1s.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Summary:

Yang et al. took advantage of recently published long-read-based genomic sequences of nearly homozygous genomes from complete hydatidiform moles to retrieve allelic sequences of LINE-1, the currently only active and autonomous retrotransposon of the human genome, and produced the repertoire of intact LINE-1 in a genome. The authors performed cell-culture-based retrotransposition assays measurements and in vivo fitness estimations of all identified intact LINE-1 to infer evolutionary dynamics. In this article, the authors further validate the major contribution of polymorphic LINE-1 to the de novo retrotransposition events in the human genome. They also described, at unprecedented resolution, allelic variations among LINE-1 loci and the potential impact of these variations to the interpretation of mutagenic potential of each LINE-1 locus.

Major comments:

1. The key conclusions of the article are mostly convincing. However, it would be a substantial improvement to consolidate the data of the article with information about known active LINE-1s in germ cells or in cancer by using data from recent publications of the Devine and Tubio labs (for example PMID: 34772701, 32024998, 25082706). Across the article, no mention is made of the transductions generated during LINE-1 de novo retrotransposition, which is instrumental to monitor in vivo activity of a group of LINE-1 active copies. It would be of particular interest to make a link between in vitro activity from this study with LINE-1 classification based on their observed activity in cancer (PMID: 32024998, Figure 3b).
2. The use of CHM1 BAC library Sanger sequencing validation and comparison with CHM13 and hg38 sequences is instrumental to support the building of LINE-1 repertoire in CHM1 genome, which is a valuable contribution of the article. The use of a distance-based metric to infer fitness of a LINE-1 is an interesting approach and allow to group LINE-1 copies based on their in vivo activity potential. Again, it would be beneficial to correlate the inferred fitness and retrotransposition activity of copies/alleles, when known, from the above-mentioned literature.
3. Some aspects of the writing of the article should be improved to better support the conclusions.
   • In general, the descriptions are dense, and details could be provided in a more direct way to lighten the results section. Several redundancies in the discussion can be combined to increase clarity.
   • There is a lack of clarity in the description of how was handled each pair of alleles for which retrotransposition measurements vary between the study and the literature (last paragraph of the "Comprehensive measurement of LINE-1 in vitro activity in a human genome" section). It is not completely clear how the analysis was done and the way the data is presented in File S3 is not helping to support the conclusion. It could be useful to include some illustrative examples in a panel of Figure 2.
   • Regarding inferred in vivo activity, the text contains alternative description with the use of "fit" / "unfit", in vivo "active" / "inactive" or "no closely related LINE-1s" terms. The authors should find a way to clearly define and systematically use one set of terms to enhance clarity along the article. To parallel with in vitro active/inactive, it would be useful to use in vivo fit/unfit.
4. The authors suggest that in vitro activity can be predicted by integration of population frequency and in vivo activity (/fitness) (second paragraph of the "An analysis of LINE-1 evolutionary history [...] and in vivo activity" section). It would be beneficial to strengthen the writing of this section and ultimately validate/test the model by including data from some of the previous studies (e.g. Brouha 2003, Lutz 2003, Seleme 2006, Beck 2010, Rodriguez-Martin 2020, Chuang 2021).
5. The identification of adaptive mutations is only partially described and not strongly supported by experimental or analytical data. It would be interesting to explore the role of phylogenetically informative sites described in Figure 5B/C by testing non CHM1 alleles in retrotransposition assay (by introducing amino acid changes into the cloned CHM1 LINE-1 alleles) or by positioning the sites in ORF1p or ORF2p structure and/or domains to infer impact on functionality.

Minor comments:

1. Regarding the in vitro retrotransposition assay, it would be beneficial to provide more data. The current Figure 2 could be enriched by the addition of data related to the variation in the replicates of the experiment (technical but mostly biological with the three clones per LINE-1 tested). Figure 2 could include a dashed line for 100% L1RP and 5% (since it is used as a threshold). It would be useful to provide an additional panel in Figure 2 to illustrate alleles of LINE-1 that are active in this study and compare the values obtained previously in other studies. Similarly, a supplemental table or alignment could be provided to document amino acid changes in the two alleles of each pair (see comment above in the Major Comment 5). The L1Hs subfamilies could also be included in the graph of Figure 2 to support the conclusions of remaining active old L1Hs at allelic forms in the human genome.
2. Also, the validation of cloning is not well described. The choice of PCR validation must be supported by more technical details on the design of the primers used to validate each copy. The authors should clearly state that the strategy chosen for retrotransposition assay does not rely on the transcription from LINE-1 5UTR but from an upstream strong promoter, ruling out the role of potential mutations in LINE-1 promoter.
3. There are discrepancies with the reported numbers of LINE-1s between Figure 1A and Table S1: 154 vs. 151 in CHM1, 144 vs. 143 in CHM13, respectively.
4. The choice of colors in Figure 3 is not perfectly clear and sometimes not as reported in the text (green highlight and orange highlight). Part of the Figure 3 legend is missing. It should include a description of the color code chosen for the right histogram.
5. For Figure 4, it would be useful to define in the legends the color code for the top histogram. To better read the scatter plot, the words "fit" and "unfit" could be added on each side of the vertical dashed line.
6. In panel B of Figure 5, it seems that the color code and hot/cold description is not fully formatted.

Significance

In this article, Yang and colleagues present an unprecedented view of the allelic diversity of young LINE-1 copies related to variable retrotransposition activity in an individual genome. One key aspect of their work is the description of the presence of young active LINE-1 alleles that are absent or non-intact in other genome assemblies, while described at a lower scale in initial work from the Kazazian and Moran labs, cited in the manuscript. The work of Yang et al. demonstrates the requirement of multiple approaches and long-read-based sequencing of individual genomes to fully infer the mutagenesis risk of LINE-1 activity. The data and methods provided by the authors open the door to a more systematic analysis of mutations and rare allelic forms to understand both mechanistic aspects and evolution of LINE-1 retrotransposition in the human genome. The identification of rare allelic forms of old LINE-1 that retain activity despite previously being considered as inactive is particularly interesting in the light of LINE-1 evolution in the human genome. The authors also describe allelic diversity inside of the Ta1d subfamily, suggesting further diversification and emergence of LINE-1 subgroups. Together with the identification of nucleotide polymorphism among LINE-1 copies, these findings strengthen the notion of individual genomes with individual set of potentially mutagenic LINE-1 alleles. The findings and methods described in this article are of great interest to a wide audience including the fields of research focusing on human genome evolution, transposable elements, genomic instability, human genetic variation, and personalized medical diagnostic.

Aurélien J. Doucet CNRS - Université Côte d'Azur

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

Learn more at Review Commons

---

Reply to the reviewers

Responses to Reviewers’ Comments

__Reviewer_ #1 (Evidence, reproducibility and clarity (Required)):_ __ *Summary In this study, using genetic labeling and deletion modeling, the authors discovered that Tbx1 myoprogenitors, rather than Pax3+/Myf5+ cells, give rise to supraclavicular brown adipose tissue (scBAT). This finding is both intriguing and significant. Furthermore, the genetic ablation of PPARγ or PRDM16, driven by Tbx1-Cre, reduced the size/weight of scBAT and its thermogenesis function capacity, supporting the importance of Tbx-1 cells. Interestingly, the authors found that human scBAT, located in the deep neck region, exhibits higher Tbx1 expression than subcutaneous neck WAT, potentially indicating a similar origin of scBAT in rodents and humans. Overall, this novel finding is exciting and could push the BAT field into a new phase. The manuscript is also well-written and organized.

Comments 1. The authors assert that Myf5+ progenitors do not contribute to scBAT adipocytes. However, Figure 2C shows that 7% of medial scBAT are mG positive, suggesting a minor contribution of Myf5+ progenitors to scBAT. The conclusion that scBAT does not originate from Myf5+ precursor cells may be overly strong.*

__Response____: __We thank the reviewer for pointing out the overstatement. We have rephased the conclusion from Figure 2 as “Myf5+ progenitors seldom give rise to scBAT adipocytes”.

The authors claim that "prdm16 is dispensable for the development of scBAT." However, supporting data seems insufficient. The absence of a difference in scBAT weight does not guarantee that development was unaffected. Additional experiments, like H&E staining and immunofluorescence (IF) staining of RFP/GFP, could help demonstrate a similar number of GFP+ brown adipocytes in scBAT, thereby supporting this statement.

Response____: __We do not have direct evidence that Prdm16 is dispensable for scBAT development; therefore, we have removed such statement in the revised manuscript. In addition, we provided H&E staining of scBAT, demonstrating evident adipose whitening and fibrosis in Prdm16ΔTbx1 mice (__Figure 7C). These results are consistent with previous findings that PRDM16 is required for the maintenance of brown adipocyte identity (PMID: 24703692).

• In the "scBAT contributes to temperature maintenance in mice" section, this phenomenon only seems to apply to female mice (Figure 5). This conclusion may need adjustment to account for this sex difference. Moreover, for females, are there H&E staining results available for scBAT? For males, is there a change in Ucp1 expression? It could be beneficial to examine mRNA expression levels for additional thermogenic genes, such as Dio2, Prdm16, Cidea, and PGC-1a.*

Response____: __Following the reviewer’s suggestion, we rephased our conclusion from Figure 5 to "scBAT contributes to temperature maintenance in __female mice". Also as requested, we provided the H&E staining of female scBAT (Figure 5E), showing a partial loss of brown adipose identity in PpargΔTbx1 mice. For males, we performed RT-qPCR and calculated total gene expression based on tissue weight. While Pparg, Prdm16 and Dio2 total expression was downregulated in Pparg-deficient scBAT, total Ucp1 expression was unchanged in scBAT and iBAT of male mice (Figure 5N, O). This might explain the similar cold tolerance between wildtype and PpargΔTbx1 males (Figure 5P).

• Considering that mutant mice have smaller scBAT, how does this difference influence glucose homeostasis between WT and mutants?*

Response____: __We performed glucose tolerance test and found no difference in glucose homeostasis of HFD PpargΔTbx1 mice (__Figure 6C). This could be due to intact iBAT in these animals, which is a much larger glucose consumer than scBAT.

• In Figures 5G & M, it seems more accurate for the y-axis label to read "Body temperature change."*

__Response____: __We changed the y-axis label. Thank you for the suggestions.

• There is inconsistency in scale bar labeling: o Figure 3A vs 3D o Figure 4B vs 4C o Figure 5L, where scale bars are missing in the H&E staining images o Figure S1, where the scale bar is in the middle of the image*

__Response____: __In the revised manuscript, we have provided consistent scale bars in all figures, including all these pointed by the reviewer. Thank you.

• In Figure 3, the western blot data should be quantified, and the molecular weight (kDa) should be included to clarify the band's position.*

Response____: __We have now indicated molecular weights in __Figure 3C, F and provided quantified UCP1 and PPARγ expression levels to the right of Western blots.

• The statement "RT-qPCR revealed much higher levels of TBX expression in total lysates from deep neck BAT (Figure 8A)" could be clarified by adding "than neck WAT" at the end. *

__Response____: __Done. Thank you for your suggestion.

Reviewer____ #1 (Significance (Required)): Significance The major advancement of this study lies in the authors' novel finding of the embryonic lineage of brown adipocytes in the supraclavicular brown adipose tissue (scBAT) depot. They demonstrated that this lineage differs from those in the dorsal BAT depots by utilizing Myf5-Cre, Pax3-Cre, and TBX1-Cre reporter mouse models.

__Reviewer____ #2 (Evidence, reproducibility and clarity (Required)): __ *This study aimed to investigate the developmental origin of brown adipose tissue (BAT) in the supraclavicular region and its implications for metabolic health. The authors have used genetic fate mapping in mice to trace the lineage of brown adipocytes in the supraclavicular region. The findings revealed that supraclavicular brown adipocytes do not originate from the Pax3+/Myf5+ epaxial dermomyotome, which is responsible for the development of interscapular BAT. Instead, most supraclavicular brown adipocytes were marked by the Tbx1+ lineage, indicating that the pharyngeal mesoderm is involved in their development. This work provides the first evidence that scBAT adipocytes do not share the same embryonic origins as iBAT fat cells. By identifying the location-specific myogenic progenitors for supraclavicular BAT versus interscapular BAT, the researchers shed light on the distinct developmental origins of different BAT depots. Overall, these findings provide new insights into the developmental origin of supraclavicular BAT and highlight the need to consider the anatomical locations and developmental origins in studying BAT development and function.

Major comments: The manuscript addresses an important yet understudied area and provides convincing results that support the key conclusions. The authors also engage in extensive discussion, speculating on the broader implications of the findings and outlining the limitations of their study. The observation that the loss of Pparg in Tbx1-expressing cells leads to a reduction in supraclavicular BAT is intriguing. However, as the authors acknowledge, Tbx1 is expressed in inguinal white adipocytes as well. Therefore, it remains unclear how changes in Tbx1 in ingWAT in this model might affect BAT depots. The authors should provide further clarification on this matter and include additional discussion regarding the potential indirect effects and limitations of these models. *

Response____: __We thank the reviewer for their overall enthusiasm about our manuscript, in which we primarily focus on Tbx1 lineage cells in BAT, the supraclavicular depot to be more specific. Tbx1-Cre mediated genetic deletion of the Pparg gene will inevitably perturb PPARγ function in other Tbx1-expressing tissues, such as scapular muscles and certain WAT depots. In a recent publication (PMID: 32240964), the Tbx1 gene was shown to be expressed in mouse inguinal WAT (iWAT) at a much higher level than interscapular BAT. TBX1 overexpression was sufficient to induce UCP1 protein in iWAT, while TBX1 deficiency rendered mice more sensitive to cold-induced body temperature drop. However, in our PpargΔTbx1 mice, we did not observe any significant loss of Pparg gene expression in iWAT (__Figure S3F), suggesting the possibility that Tbx1-positive cells are only a small proportion of iWAT. Nevertheless, we did not see any reduced expression of thermogenic genes in iWAT of PpargΔTbx1 mice (Figure S3F), indicating either that Tbx1-expressing cells are dispensable for thermogenesis or that other still-undefined mechanisms exist to compensate for the loss of PPARγ. We acknowledge the limitations of our animal models and have discussed these points in the second paragraph of Discussion.

In Figure 5, it would be beneficial to include the expression of a broader range of thermogenic genes and proteins in both males and females. This would strengthen the argument that the loss of Pparg in Tbx1+ progenitors impairs scBAT function.

Response____: __Thank you for the suggestion and we have now provided the expression of additional thermogenic genes including Ucp1, Prdm16, Ppargc1a, Cidea, and Dio2 in both males and females (__Figure 5F, G, N, and O). These results demonstrate that loss of PPARγ in Tbx1+ myoprogenitors impairs scBAT thermogenic function, with more profound impact on males than females.

*Minor Comments: It would be more appropriate to present the results of the cold challenge studies as absolute body temperature rather than just the difference between groups. This is important because there could be baseline differences in basal body temperature among the experimental groups. *

__Response____: __Thank you for the suggestion. The results summarized in Figure 5H and 5P were from several batches of independent experiments that were carried out at different times. Plotting absolute body temperature created a bigger variance that precluded us from drawing any conclusion. Therefore, we decided to plot the data as changes in body temperature in Figure 5H and 5P. As shown in Figure 8, we did not observe baseline differences in body temperature between wildtype and Prdm16ΔTbx1 mice, suggesting that loss of scBAT thermogenic function would not affect basal body temperature.

*It is recommended to include representative images of cre-negative animals to validate the reagents and models used in the study. Including such images would enhance the reliability of the experimental approach and strengthen the overall validity of the findings. *

Response____: __Representative images of Cre-negative mT/mG reporter animals have now been provided in __Figure S1. Thank you for the suggestion.

The manuscript would benefit from placing the findings in the context of the broader field. For instance, discussing whether the loss of Prdm16 in Myf5 progenitors has a similar impact on interscapular BAT (iBAT) development or thermogenic function would provide valuable insights. Additionally, exploring the relationship between Tbx1 progenitors and adipocyte progenitors in adult BAT depots, such as Pdgfra+ and Trpv1+ progenitors, could further enhance our understanding of the developmental origins and functional characteristics of different adipocyte populations

__Response____: __The reviewer raised an important point that we should place our finders in the context of the broader field. Indeed, it has been reported earlier that loss of PRDM16 in Myf5 progenitors leads to iBAT dysfunction in adult mice (PMID: 24703692), a similar phenotype to what we found in scBAT of Prdm16ΔTbx1 mice. The early embryonic development was not evidently perturbed in iBAT (using Myf5-cre) or scBAT (using Tbx1-cre), which might be compensated by other PRDM family protein, such as PRDM3. However, using Adipoq-Cre to knock out PRDM16 only leads to defects in beige adipocyte, but not classic BAT (PMID: 24439384). Together, these results demonstrate that PRDM16 in myoprogenitors is required for brown adipocyte identity maintenance during aging and similar transcriptional regulatory circuits control the differentiation and/or activity of both iBAT and scBAT. Further investigations are warranted to identify depot-specific regulations and functions of BAT. In adult BAT, progenitors that are marked by genes like Pdgfra and Trpv1 have been reported to contribute to cold-induced BAT recruitment and tissue homeostasis. While not the scope of our current research, future endeavors are needed to test if embryonic Tbx1+ myoprogenitors give rise to all or only some populations of adult BAT progenitors. These points have now been added to the revised Discussion section.

Reviewer____ #2 (Significance (Required)): * Field of expertise: Adipose biology, Developmental biology, Thermogenesis

The manuscript addresses an important and previously understudied area in the field of brown adipose tissue (BAT) development. The study challenges the long-standing assumption that Pax3+/Myf5+ progenitors in the dermomyotome are the sole developmental source of brown adipocytes in mice, including both interscapular BAT (iBAT) and other brown adipocytes.

This work provides experimental evidence that the supraclavicular BAT (scBAT) adipocytes have a distinct embryonic origin compared to iBAT fat cells. While the developmental source of iBAT has been known for over a decade, this study demonstrates for the first time that scBAT adipocytes do not arise from the Pax3+/Myf5+ progenitors in the dermomyotome.

The findings presented in this manuscript have the potential to make a lasting impact on the brown adipose tissue research community, particularly those interested in the developmental aspects of brown fat. *

__Reviewer____ #3 (Evidence, reproducibility and clarity (Required)): __ *This manuscript explores the cell origin of supraclavicular brown adipose tissue (scBAT). UCP1-expressing brown/beige adipocytes are found in several anatomical locations but most studies have been focused on intrascapular brown adipose tissue (iBAT) in rodents, a depot that only exist in infants (but not adults) in humans. Very little is known about the biology (including the origin) of other BAT deposes. Here using multiple lineage tracing tools and conditional KO mice the authors convincingly demonstrate that about 50% of the scBAT cells originate from Tbx1+ myoprogenitors and provide functional evidence that ablation of Pparg or Prdm16 in Tbx1-cells blocks development of scBAT or affects thermogenic function of mice. The study design is straightforward, well carried out and the conclusion is supported by the data. The discovery has significant implication as brown adipocytes are mainly found in the supraclavicular region in the human body. I have few relative minor comments.

Tbx-Cre lineage tracing indicates that 50% scBAT cells are marked by Tbx1. The authors discussed this may be either due to low recombination efficiency of Tbx1-Cre or due to multiple lineage origin of scBAT cells. The possibility of Cre recombination efficiency can be addressed easily by genomic DNA recombination analysis. *

Response____: __To test recombination efficiency, we performed RT-PCR to detect wildtype and mutant Pparg mRNA using primers provided in the original report of the Pparg-floxed mice (PMID: 14660788). The mutant Pparg mRNA could only be detected in scBAT, not iBAT, of PpargΔTbx1 mice (__Figure S3A). The similar abundance of wildtype and mutant Pparg transcripts in PpargΔTbx1 scBAT indicates a 50% recombination rate. However, we currently cannot distinguish the following possible reasons for the incomplete recombination: 1) only half of scBAT adipocytes are Tbx1-lineage cells; 2) a portion of Tbx1-progeny cells have low Cre expression and thus no recombination; 3) The Tbx1 promoter does not fully recapitulate the endogenous Tbx1 gene expression. The identity of non-Tbx1 progeny adipocytes in the scBAT depot requires future investigations.

*In the introduction the authors conclude that Myf5, Pax3 are "location markers" instead of cell identity markers. While I agree with this statement it is quite confusing. It implies that the study aims to identify cell identify markers but based on the analogy Tbx1 is also a location marker. *

__Response____: __We apologize for the confusion caused by using “identity” to describe both lineage origins and functional cell types. Based on previous and our current studies, we propose Myf5, Pax3, and Tbx1 as location markers that distinguish BAT depots at different locations. They are not identity markers as these progenitors also give rise to other cell types, such as muscles, white adipocytes, fibroblasts, and others. We removed any statements indicating Tbx1 as an identity marker.

*Figure 8 human expression compares TBX1 mRNA levels in neck fat to subcutaneous white fat. This is different from the comparison of dorsal and ventral BAT in mice. Therefore, the data are not particularly relevant to this study and should be moved to a supplemental figure. *

__Response____: __We agree with the reviewer that the comparison of human TBX1 was not made between dorsal and ventral BAT. This is due the loss of dorsal BAT in adult humans, which make it almost impossible to make such direct comparison in humans. Nonetheless, the higher expression of TBX1 in deep neck BAT compared to subcutaneous neck WAT suggests that TBX1 might be functionally important for BAT thermogenesis. This is consistent with a recent report using transgenic Tbx1 mouse models that demonstrates the role of adipose TBX1 in thermogenic capacity (PMID: 32240964). We believe that data in Figure 8 is relevant to our current study, but we are also receptive to move it to the supplementary if the reviewer insists so.

*Can the authors speculate/discuss on why there is no Pax3 labelled cells but 7% Myf5 labeled cells in scBAT? *

__Response____: __We would like to clarify that both Pax3+ (6.7%) and Myf5+ (7.2%) progenitors label a similar percentage of brown adipocytes in the medial scBAT. These percentages are now provided in the revised text and can be visualized in Figure 1H and 2D. On the other hand, nearly none of lateral scBAT adipocytes were labelled by either Pax3+ or Myf5+ progenitors.

Reviewer____ #3 (Significance (Required)): The discovery has significant implication as brown adipocytes are mainly found in the supraclavicular region in the human body.

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

This manuscript explores the cell origin of supraclavicular brown adipose tissue (scBAT). UCP1-expressing brown/beige adipocytes are found in several anatomical locations but most studies have been focused on intrascapular brown adipose tissue (iBAT) in rodents, a depot that only exist in infants (but not adults) in humans. Very little is known about the biology (including the origin) of other BAT deposes. Here using multiple lineage tracing tools and conditional KO mice the authors convincingly demonstrate that about 50% of the scBAT cells originate from Tbx1+ myoprogenitors and provide functional evidence that ablation of Pparg or Prdm16 in Tbx1-cells blocks development of scBAT or affects thermogenic function of mice. The study design is straightforward, well carried out and the conclusion is supported by the data. The discovery has significant implication as brown adipocytes are mainly found in the supraclavicular region in the human body. I have few relative minor comments.

Tbx-Cre lineage tracing indicates that 50% scBAT cells are marked by Tbx1. The authors discussed this may be either due to low recombination efficiency of Tbx1-Cre or due to multiple lineage origin of scBAT cells. The possibility of Cre recombination efficiency can be addressed easily by genomic DNA recombination analysis.

In the introduction the authors conclude that Myf5, Pax3 are "location markers" instead of cell identity markers. While I agree with this statement it is quite confusing. It implies that the study aims to identify cell identify markers but based on the analogy Tbx1 is also a location marker.

Figure 8 human expression compares TBX1 mRNA levels in neck fat to subcutaneous white fat. This is different from the comparison of dorsal and ventral BAT in mice. Therefore, the data are not particularly relevant to this study and should be moved to a supplemental figure.

Can the authors speculate/discuss on why there is no Pax3 labelled cells but 7% Myf5 labeled cells in scBAT?

Significance

The discovery has significant implication as brown adipocytes are mainly found in the supraclavicular region in the human body.

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

This study aimed to investigate the developmental origin of brown adipose tissue (BAT) in the supraclavicular region and its implications for metabolic health. The authors have used genetic fate mapping in mice to trace the lineage of brown adipocytes in the supraclavicular region. The findings revealed that supraclavicular brown adipocytes do not originate from the Pax3+/Myf5+ epaxial dermomyotome, which is responsible for the development of interscapular BAT. Instead, most supraclavicular brown adipocytes were marked by the Tbx1+ lineage, indicating that the pharyngeal mesoderm is involved in their development. This work provides the first evidence that scBAT adipocytes do not share the same embryonic origins as iBAT fat cells. By identifying the location-specific myogenic progenitors for supraclavicular BAT versus interscapular BAT, the researchers shed light on the distinct developmental origins of different BAT depots. Overall, these findings provide new insights into the developmental origin of supraclavicular BAT and highlight the need to consider the anatomical locations and developmental origins in studying BAT development and function.

Major comments:

The manuscript addresses an important yet understudied area and provides convincing results that support the key conclusions. The authors also engage in extensive discussion, speculating on the broader implications of the findings and outlining the limitations of their study.

The observation that the loss of Pparg in Tbx1-expressing cells leads to a reduction in supraclavicular BAT is intriguing. However, as the authors acknowledge, Tbx1 is expressed in inguinal white adipocytes as well. Therefore, it remains unclear how changes in Tbx1 in ingWAT in this model might affect BAT depots. The authors should provide further clarification on this matter and include additional discussion regarding the potential indirect effects and limitations of these models.

In Figure 5, it would be beneficial to include the expression of a broader range of thermogenic genes and proteins in both males and females. This would strengthen the argument that the loss of Pparg in Tbx1+ progenitors impairs scBAT function.

Minor Comments:

It would be more appropriate to present the results of the cold challenge studies as absolute body temperature rather than just the difference between groups. This is important because there could be baseline differences in basal body temperature among the experimental groups.

It is recommended to include representative images of cre-negative animals to validate the reagents and models used in the study. Including such images would enhance the reliability of the experimental approach and strengthen the overall validity of the findings.

The manuscript would benefit from placing the findings in the context of the broader field. For instance, discussing whether the loss of Prdm16 in Myf5 progenitors has a similar impact on interscapular BAT (iBAT) development or thermogenic function would provide valuable insights. Additionally, exploring the relationship between Tbx1 progenitors and adipocyte progenitors in adult BAT depots, such as Pdgfra+ and Trpv1+ progenitors, could further enhance our understanding of the developmental origins and functional characteristics of different adipocyte populations

Significance

Field of expertise: Adipose biology, Developmental biology, Thermogenesis

The manuscript addresses an important and previously understudied area in the field of brown adipose tissue (BAT) development. The study challenges the long-standing assumption that Pax3+/Myf5+ progenitors in the dermomyotome are the sole developmental source of brown adipocytes in mice, including both interscapular BAT (iBAT) and other brown adipocytes.

This work provides experimental evidence that the supraclavicular BAT (scBAT) adipocytes have a distinct embryonic origin compared to iBAT fat cells. While the developmental source of iBAT has been known for over a decade, this study demonstrates for the first time that scBAT adipocytes do not arise from the Pax3+/Myf5+ progenitors in the dermomyotome.

The findings presented in this manuscript have the potential to make a lasting impact on the brown adipose tissue research community, particularly those interested in the developmental aspects of brown fat.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Summary

In this study, using genetic labeling and deletion modeling, the authors discovered that Tbx1 myoprogenitors, rather than Pax3+/Myf5+ cells, give rise to supraclavicular brown adipose tissue (scBAT). This finding is both intriguing and significant. Furthermore, the genetic ablation of PPARγ or PRDM16, driven by Tbx1-Cre, reduced the size/weight of scBAT and its thermogenesis function capacity, supporting the importance of Tbx-1 cells. Interestingly, the authors found that human scBAT, located in the deep neck region, exhibits higher Tbx1 expression than subcutaneous neck WAT, potentially indicating a similar origin of scBAT in rodents and humans. Overall, this novel finding is exciting and could push the BAT field into a new phase. The manuscript is also well-written and organized.

Comments

1. The authors assert that Myf5+ progenitors do not contribute to scBAT adipocytes. However, Figure 2C shows that 7% of medial scBAT are mG positive, suggesting a minor contribution of Myf5+ progenitors to scBAT. The conclusion that scBAT does not originate from Myf5+ precursor cells may be overly strong.
2. The authors claim that "prdm16 is dispensable for the development of scBAT." However, supporting data seems insufficient. The absence of a difference in scBAT weight does not guarantee that development was unaffected. Additional experiments, like H&E staining and immunofluorescence (IF) staining of RFP/GFP, could help demonstrate a similar number of GFP+ brown adipocytes in scBAT, thereby supporting this statement.
3. In the "scBAT contributes to temperature maintenance in mice" section, this phenomenon only seems to apply to female mice (Figure 5). This conclusion may need adjustment to account for this sex difference. Moreover, for females, are there H&E staining results available for scBAT? For males, is there a change in Ucp1 expression? It could be beneficial to examine mRNA expression levels for additional thermogenic genes, such as Dio2, Prdm16, Cidea, and PGC-1a.
4. Considering that mutant mice have smaller scBAT, how does this difference influence glucose homeostasis between WT and mutants?
5. In Figures 5G & M, it seems more accurate for the y-axis label to read "Body temperature change."
6. There is inconsistency in scale bar labeling:
   • Figure 3A vs 3D
   • Figure 4B vs 4C
   • Figure 5L, where scale bars are missing in the H&E staining images
   • Figure S1, where the scale bar is in the middle of the image
7. In Figure 3, the western blot data should be quantified, and the molecular weight (kDa) should be included to clarify the band's position.
8. The statement "RT-qPCR revealed much higher levels of TBX expression in total lysates from deep neck BAT (Figure 8A)" could be clarified by adding "than neck WAT" at the end.

Significance

The major advancement of this study lies in the authors' novel finding of the embryonic lineage of brown adipocytes in the supraclavicular brown adipose tissue (scBAT) depot. They demonstrated that this lineage differs from those in the dorsal BAT depots by utilizing Myf5-Cre, Pax3-Cre, and TBX1-Cre reporter mouse models.

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

Learn more at Review Commons

---

Reply to the reviewers

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

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.

Our response:

We thank the reviewer for the careful assessment and recognition of our work. In the subsequent sections, we have tried to address all the concerns raised by the reviewer.

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.

Our response:

We thank the reviewer for acknowledging our recently published work, which is focusing on the active branching phase during late embryogenesis/around birth. In the current proliferation analysis, however, our focus was on a different aspect of embryonic mammary gland development: understanding the mechanism underlying the ability to acquire competence to branch, i.e. how the epithelium changes between late bud and sprout stages. Our data obtained from tissue recombination and 3D culture experiments suggest that heterotypic mesenchymes or mesenchyme-free 3D organoid culture conditions do not provide sufficient signals to support branching of mammary epithelia before E16.5. We have rephrased the text to better emphasize this point.

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).

__Our response: __

We agree with all the reviewers in that this part of the manuscript was not mature enough and provided only indirect evidence on the potential link between lineage segregation and branching ability. This is an important question in the field that merits a study of its own and should be addressed with better tools than those available to us at present. As suggested by reviewers #1 and #3, we have omitted this part in the revised manuscript.

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?

__Our response: __

In the original manuscript (lines 339-342), we have performed the GSVA analysis comparing the KEGG database, and the significantly altered pathways comparing different mammary mesenchymes with salivary gland mesenchyme have been pooled and displayed as heatmap in Supplementary Fig 4b. The WNT signaling pathway is lower in the mammary mesenchyme, especially at E16.5.

As suggested by the reviewer, we have analyzed Axin2, the most commonly used readout of WNT/CTNNB1 signaling activity in our RNA-seq data that we include as a __new Supplemental Fig. 4c __in the preliminary revised manuscript. Axin2 data indicate that Wnt/β-catenin signaling activity is lower in the E16.5 fat pad, where branching takes place, compared to younger stages of mammary gland and the salivary gland.

Plan for the final revision:

Additionally, we will provide expression data of a transgenic Wnt reporter from the same developmental stages and tissues that were used to generate the RNA-seq data.

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.

Our response:

As shown in the current manuscript, Igf1 is expressed in the mammary and salivary gland mesenchyme. This finding is in line with E14 in situ expression data available in Genepaint (https://gp3.mpg.de/results/Igf1) showing that overall in embryonic tissues, Igf1 is mainly produced in mesenchymal tissues. Of note, in Genepaint, a clear signal can be detected in the salivary gland mesenchyme, not the epithelium. Published E16 and E18 datasets indicate low level of Igf1 expression in the mammary epithelium (https://wahl-lab-salk.shinyapps.io/Mammary_snATAC/). Hence, we conclude that Igf1 is mainly produced by mesenchymal cells. Instead, Igf1r appears to be rather ubiquitously expressed.

A previous study assessed BrdU incorporation in Igf1r-/- mammary buds at E14.5, and reported a specific proliferation defect in the epithelium, while no difference was detected in the mesenchyme (Fig. 9, Heckman et al., 2007; PMID:17662267). However, we cannot exclude the possibility of autocrine, mesenchymal Igf1/Igf1r signaling, which in turn could lead to upregulation of a paracrine factor to regulate epithelial growth.

We agree with the reviewer in that novel conditional mouse models are beyond the scope of the current study. However, we do not think that small molecule drugs could be used to block Igf1r activity in a tissue-specific manner neither.

Plan for the final revision:

To further delineate the paracrine and/or autocrine role of Igf1/Igf1r pathway during mammary epithelial growth and branching, we will perform tissue recombination experiments between Igf1r-/- and control mammary epithelium and mesenchyme, as suggested by the reviewer.

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.

Our response:

We apologize for these slips. They have been corrected in the revised manuscript.

• Line 517-518: please also include the details for the Eda mice.

Our response:

We apologize for missing this important information in materials and methods. We have included a short introduction of the K14-Eda mice, a new reference for the original publication producing them, as well as the Jackson Laboratories strain number for Eda-/- (a.k.a. Tabby) mice in the revised manuscript.

• 1f spelling error: separation

Our response:

The spelling error has been corrected in the revised manuscript.

**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.

Our response:

We are grateful to the reviewer for the reliance on the technical aspect of our experiments. We do routinely monitor tissue purity in the recombinants (for more details, see our response to reviewer #2). To demonstrate this, we have included new data in new Supplementary Fig. 1a,b and new Supplementary Fig. 3. We believe these additions will further enhance the validity of our findings and effectively address the concerns raised by reviewer 2.

Reviewer #1 (Significance (Required)):

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

__Reviewer #2 (Evidence, reproducibility and clarity (Required)): __

The mammary gland is a branched structure that consists of a bilayered epithelium embedded in a specialized mesenchyme. In mice, at 11,5 days of embryogenesis, the ectoderm thickens forming 5 pairs of peculiar structures called placodes. During the following days, the placodes will grow and invaginate into the surrounding mammary mesenchyme and they will finally start to branch by the end of embryogenesis (E16). It has been suggested that the bidirectional communication between the growing mammary gland and the surrounding mesenchyme plays a pivotal role in the determination of each step of mammary gland development (placode formation, mammary bud invagination, gland outgrowth, branching). The role of different signalling molecules has already been shown, particularly for the placode growth and mammary bud invagination. Nevertheless, the pathways regulating embryonic mammary gland branching are still incompletely understood. In this manuscript, Lan and colleagues aim to decipher the correlation between different stages of mammary gland development such as proliferation, lineage segregation and ductal branching. Furthermore, they want to define which stage of mammary development is intrinsically determined by the epithelium and which one requires the supportive guidance of the mesenchyme. Lastly, they aim to discover the key signal for the growth and branching of mammary epithelium. To these purposes, they used an ex vivo model of heterochronic epithelial-mesenchymal recombination. In particular, they micro-dissected the epithelium and/or the mesenchyme from murine mammary glands at different stages of embryonic development (i.e. at E13,5 for the quiescent phase or 16,5 for branching phase) and explanted them together in different combinations using fluorescent reporters. To assess the role of the mesenchyme they also cultured the epithelium in a mesenchyme free 3d structure. Through this model they demonstrated that the presence of the mesenchyme is necessary for the priming of mammary epithelium for branching, since only E16,5 epithelial cells were able to grow and branch in a mesenchyme free 3D experiment. Nevertheless, intrinsic properties of the epithelium are necessary for the timing of branching, since E16,5 mesenchyme was not able to accelerate the outgrowth of E13,5 epithelia. In order to determine which epithelial properties are important, the authors correlated the beginning of cell proliferation in the embryonic mammary gland to the beginning of the branching phase. They indeed used the Fucci2a mouse model to carefully characterise the timing of mammary cells proliferation at different stages of embryonic development, concluding that the great majority of proliferating cells reside in the inner part of the mammary bud until E14,5, while in the external part at later stages. Regarding the importance of cell proliferation, Lan and colleagues claim that the beginning of the branching phase is not its direct consequence, thanks to the use of the K14Cre- Eda mouse model, known to have anticipated mammary gland development. Using this and the Eda-/- models, the authors also sustain that the branching occurs independently of the lineage specification of the epithelium. The use of salivary mesenchyme instead the mammary one was able to increase the number of branching of E16,5 mammary epithelium. Nevertheless, this model demonstrated that the branching pattern (side branching vs tip bifurcation) is an intrinsic feature of the epithelium. Lan and colleagues also defined the transcriptomic profiles of the mammary and salivary mesenchymes at different stages. In particular, they observed an increased expression of negative regulators of Wnt pathway in the mammary mesenchyme compared to the salivary mesenchyme. Moreover, using a mouse model where B-catenin is stabilised, they observed increased tip production in the mammary gland epithelium. They also showed that IGF1 production is increased after Wnt pathway activation and they tested its function, both treating their ex vivo cultures with exogenous IGF1 and using Igf1r-/- mouse models.

Major comments 1- The great majority of the results of the manuscript are based on an ex vivo model of heterochronic epithelial-mesenchymal recombination. Since the authors are studying the effect of the mesenchyme of different stages on the epithelium (and vice versa), the purity of the two compartments after the dissection is particularly important. Although they said that the purity is evaluated (line 112), it would be important to show a control staining in which they use known markers of the mesenchyme with no colocalization with the fluorescent reporter of the epithelium.

Our response:

We agree with the reviewer that the purity of the separated tissues is very important for our conclusions. This is why we have used genetically labeled tissues in all recombination experiments: the epithelium and the mesenchyme were always isolated from embryos ubiquitously expressing GFP or tdTomato. We find this the most reliable way to assess the origin and purity of the isolated tissues. If there was any carry-over mesenchyme isolated with the GFP+ epithelium, this would be revealed as GFP+ mesenchymal cells in the recombinants consisting of otherwise tdTomato+ mesenchyme. And vice versa: any carry-over tdTomato+ epithelium isolated with the mesenchyme would be revealed as tdTomato+ epithelial cells in the recombinants. We apologize for not making this clear enough in the original manuscript. In the revised manuscript, we now provide confocal high-resolution images of the recombinant explants (new Supplementary Fig. 1a,b). The explants have been co-stained with the epithelial marker EpCAM, revealing a robust colocalization between the ubiquitously expressed florescent labels in the designated epithelial tissues and the EpCAM.

2- Another important point for understanding the quality and impact of these findings is to assess the similarities and differences, if there are, between the in vivo mesenchyme and the ex vivo one. Indeed, once explanted and put in culture, mesenchymal cells could change their transcriptomic profile and consequently change their signals to the epithelium. The authors should assess the expression of the genes and pathways studied during embryonic development in vivo.

Our response:

The reviewer is correct in that the transcriptomes will likely undergo some changes when organs are cultured ex vivo. This is why RNA-seq was done on freshly isolated tissues. Regarding the potential changes taking place ex vivo, however, we do not consider them relevant with respect to the questions we are addressing in this study. The reason is (as reported in the manuscript) that all control recombinations (homochronic recombinations such as E13 epithelium + E13 mesenchyme, E16 epithelium + E16 mesenchyme etc.) branched essentially as in vivo. Therefore, we find the results and conclusions made from the tissue recombination experiments solid.

3- The authors clearly showed that E16,5 epithelium is able to branch in a mesenchyme free 3D culture model, while epithelia from earlier stages don't. This led to the conclusion that mesenchyme is necessary for acquiring the branching ability. Nevertheless, the authors also said that early stages epithelia scarcely grow in the mesenchyme free 3D culture. Therefore, the lack of branching may be due to the lack of growth, if not the increase of death, of epithelial cells. The authors should quantify the size and the cell death of the epithelia in the different culture conditions and discuss better this point.

Our response:

The reviewer is correct in that one of the key functions of the mammary mesenchyme up to E16.5 may be to provide survival signals for the epithelium, and this might explain why epithelia younger than E16.5 fail to grow/branch when recombined with salivary gland mesenchyme and in mesenchyme-free organoid culture.

Plan for the final revision:

To address this issue, we will assess apoptosis in mammary epithelia cultured in the mesenchyme-free 3D culture organoid set-up.

4- The Fucci2a model allowed to assess the proliferation of embryonic mammary epithelium, showing that the great majority of proliferating cells are basal, at late stages of development (line 182). As it has already been shown, lineage specification is a late process during mammary gland development. The fact that the proliferating cells reside at the external part of the bud does not mean that they are basal cells yet. A p63/K8 staining could be important to understand if the increased proliferation occured in already specified basal cells or not.

__Our response: __

Indeed, mammary lineage specification is a later process. As pointed out in the manuscript and by reviewer #1, the widely used basal and luminal lineage markers have not yet segregated to separate compartments at the developmental stages analyzed in our study, and therefore cannot be used as tools for this purpose. We would like to emphasize that in the manuscript, we analyzed the cells based on their position, and have used the term basal to indicate the basal position, not the prospective lineage. Accordingly, we used the term inner instead of luminal cells to indicate their location, not lineage. We have further clarified this point in the preliminary revised manuscript.

5- The use of Fucci2a model showed that 20% of epithelial cells are proliferative at E13,5. This phase is considered as "quiescent" by the authors (line 120), but the moderate proliferation rate shown in this experiment demonstrated that it is not. A change of the nomenclature is needed.

__Our response: __

We have removed the word “quiescent” from the text.

6- Through the use of K14-Eda and Eda-/- models, the authors claimed that the lineage specification is not a prerequisite for ductal branching. To support this point, they showed that the K14-Eda mice have an anticipated branching although the expression of K8 in the inner part of the bud is transitorily decreased. The authors link the K8 downregulation to a transient suppression of the luminal lineage, but this is clearly overclaimed. Although K8 is a known marker of luminal lineage, the downregulation of one marker is not sufficient to support their thesis. They should first check more markers and in particular critical regulators of luminal lineage as Notch1, Foxa1 and Elf5. Lately, the use of different models that drive embryonic epithelial cells to a forced lineage commitment (Notch1 or Δnp63 overexpression) would support more their claim. As additional evidence, the authors showed that Eda is able to promote basal cell signature. Firstly, the authors should better explain why this point would support their thesis. Secondly, the supplementary figure 2b does not show which genes are taken into account to define the basal signature. A list of these genes would be helpful, as well as staining for some representative proteins.

Our response:

We thank the reviewer for these constructive suggestions. We agree with all reviewers in that this part of the manuscript was not mature enough and provided only indirect evidence on the potential link between lineage segregation and branching ability. This is an important question in the field that merits a study of its own to be addressed with better tools than those available to us at present. As suggested by reviewers #1 and #3, we have omitted this part in the revised manuscript.

7- The authors used the same mouse models to assess the importance of proliferation in the determination of ductal branching and they claimed that proliferation is not a sufficient feature. This conclusion was supported by two observations. The first one is the fact that the K14-Eda model shows an increased cell proliferation at early stages compared to wt, coupled with anticipated branching. Secondly, although having smaller glands compared to wt and showing a delay in ductal branching, Eda-/- mice have an epithelial proliferation rate very similar to wt. Again, the conclusion that proliferation is not sufficient for branching is overclaimed. Firstly, the authors should explain how the buds in wt and Eda-/- mice have different sizes although the similar proliferation (increased cell death?, cellular volume?). Secondly, to support the thesis that proliferation is not sufficient for branching, functional experiments should be performed (see point 12). For instance, the short-time treatments with inhibitors or promotors of proliferation may help to understand the effective role of proliferation in the determination of branching.

Our response:

We show that there is no direct link between onset of proliferation and acquisition of branching ability. However, we are not claiming that proliferation is not important for branching, as obviously new cells are needed as building blocks of growing tissues. In a recently published paper, we have assessed the role of proliferation in branch point formation in embryonic mammary glands. Using mitomycin C to block proliferation, we showed that initiation of new branches occurs even when proliferation is blocked (Myllymäki et al., JCB2023, PMID: 37367826).

The reviewer was also asking why Eda-/- mammary primordia are smaller at E15.5-E16.5 despite similar proliferation rates. In the revised manuscript, we have quantified the volume of E13.5 Eda-/- and control mammary buds and show that Eda-/- buds are ~25% smaller (3.5 ± 0.8 x 105 µm3 in Eda-/- vs. 4.6 ± 0.7 x 105 µm3 in control, mean ± SD) already at the bud stage (new Supplementary Fig. 2c,d).

We have also quantified the cellular size in Eda-/- and control mammary glands at E13.5 and E15.5 and found that mammary epithelial cells in Eda-/- embryos are ~15% smaller (new Supplementary Fig. 2e,f). Together, these data indicate that the smaller size of E15.5-E16.5 Eda-/- mammary glands is a combinatorial effect the smaller mammary anlage at E13.5 and smaller cell size. These findings, while interesting on their own, do not challenge our conclusions regarding the link between onset of proliferation and acquisition of branching ability.

8- The heterotypic epithelial-mesenchymal recombination using the salivary gland is interesting. Nevertheless, some stainings to assess the purity of their systems are again required (e.g., marker of salivary epithelium to verify the purity of the mesenchyme and vice versa).

__Our response: __

As mentioned above, all tissue recombination experiments were performed so that the epithelium and the mesenchyme originated from genetically labelled embryos expressing different fluorescent proteins. In the revised manuscript, we provide confocal images of the salivary-mammary tissue recombinants (new Supplementary Fig. 3), confirming the purity of the tissue compartments used in these experiments.

This model clearly showed that the mammary epithelium can form more branching when combined with the salivary mesenchyme. Moreover, the salivary epithelium preferentially branches through tip bifurcation, while mammary epithelium combined with the salivary mesenchyme has a mixed pattern of tip bifurcation and side branching (typical of the mammary gland). The authors thus concluded that the branching pattern is an intrinsic feature of the epithelium. However, a comparison between the percentage of tip bifurcation and side branching in the heterotypic combination and the homotypic combination between mammary epithelium and mammary mesenchyme is crucial to understand this point. Indeed, these results are not sufficient to exclude that the branching pattern is partially determined by intrinsic features and partially by extrinsic signals. The authors should carefully quantify the branching pattern in the homotypic combination and compare that to the heterotypic one. If the percentage of tip bifurcation do not change, their conclusion is correct; if this percentage increases in the heterotypic combination, it would be a sign of a partial effect of the signals of the mesenchyme.

Our response:

We thank the reviewer for raising this question. We have independently generated data on the type of mammary gland branching events in two papers with somewhat different culture and imaging conditions (Lindström et al., BiorXiv 2022 and Myllymäki et al., JCB, 2023, PMID: 37367826). Both analyses showed that in embryonic mammary glands, the majority of branching events (~70%) occurs by side-branching. These data are in line with the current study that we have now complemented to include also the mammary-mammary recombination experiments (revised Supplementary Video 1, revised Fig. 4b). Quantification of branching events revealed no significant difference in the type of branching events of mammary epithelia grown with salivary or mammary gland mesenchyme (revised Fig. 4c), further supporting our initial conclusions.

9- Through the analysis of their transcriptomic data, Lan and colleagues found that the mammary mesenchyme expresses higher levels of negative regulators of Wnt pathway compared to the salivary mesenchyme. To demonstrate the value of their findings, they should confirm this in vivo, through staining of known Wnt proteins on the salivary and mammary mesenchymes at the embryonic stage.

Our response:

In mammals, there are 19 Wnt ligands, over a dozen secreted Wnt inhibitors, 10 Frizzled receptors, two Lrp co-receptors, and numerous other pathway modifiers that contribute to the net Wnt signaling activity in a complex manner. Furthermore, it has been “notoriously difficult to generate useful antibodies to vertebrate Wnt proteins...In general, these sera do not detect endogenous Wnt proteins in cell extracts, nor do they detect Wnt proteins in tissues by staining techniques. Hence, there are few data on Wnt protein distribution in intact vertebrate animals.” This is a direct citation from the Wnt Homepage, maintained by the Nusse Lab; https://web.stanford.edu/group/nusselab/cgi-bin/wnt/reagents#antibod.

For all these reasons, we do not find this approach feasible nor informative.

Instead, in the revised manuscript, we report the expression levels of Axin2, the most commonly used transcriptional readout of canonical Wnt activity in our RNA-seq data (new Supplementary Fig. 4c). Axin2 levels are lowest in the E16 fat pad where mammary branching takes place, much lower than in any other tissues analyzed in the study.

Plan for the final revision:

To complement these findings, we will additionally provide expression data of a transgenic Wnt reporter from the same developmental stages and tissues that were used to generate the RNA-seq data.

10- Since the ability of the salivary mesenchyme to promote a higher rate of branching in the mammary epithelium, the authors wanted to assess what could be the role of Wnt signalling. To do so, they used a mouse model where B-catenin is stabilised, allowing an increased Wnt signalling in the mammary mesenchyme. As a result, they observed increased branching in the mammary epithelium. They also found that IGF1 is a ligand regulated by Wnt pathway in the mesenchyme. Therefore, the use of exogenous IGF1 in their ex vivo model was able to increase the branching of the mammary epithelium. Moreover, Igf1r-/- embryos showed a significant decrease of mammary gland branching. The conclusion based on these experiments was that the Wnt-Igf1-Igf1r axis plays a pivotal role in the promotion of mammary gland branching during embryogenesis. This conclusion is overclaimed for different reasons. Firstly, the normalization of the ductal branching to the body weight is insufficient to exclude that the impact of the Igf1r knockout may have severe consequences on the mammary gland formation, upstream of the ductal branching. Another parameter for this normalization is required (e.g., size of the bud before branching, proliferation status, etc).

Our response:

We agree with the reviewer in that Igf1r knockout may affect mammary gland formation in multiple ways, and also prior to onset of branching, as already indicated in the original manuscript: “…apart from one study reporting the smaller size of the E14 mammary bud in IGF-1R deficient embryos …” (line 398-399 in the revised version) and ‘…mammary gland 3 that was consistently absent.’ (line 414-415 in the revised version).

To assess whether the reduced size and branching of E16.5/E18.5 Igf1r-/- mammary glands is merely a consequence of the smaller anlage, the revised manuscript includes new data reporting quantification of the volume of mammary gland 2 of Igf1r-/- and wild type littermate embryos at E13.5, E16.5, and E18.5 from 3D confocal images of whole mount EpCAM stained mammary glands. As can be seen from the new Fig. 7g-h, at E13.5, the mutant mammary buds are about 60% of the size of the controls, at E16.5, 25% and at E18.5 only 20 % revealing a progressive defect, indicative of a specific defect at the outgrowth and branching stage. This conclusion was validated by normalization to the body weight: at E13.5 the size of Igf1r-/- mammary anlage did not differ from that of the wild type embryos (p = 0.11), at E16.5 the sprouts were smaller in the mutants, though the difference did not reach statistical significance (p = 0.08), while at E18.5, the Igf1r-/- mammary glands were significantly smaller (p = 0.000021) (new Fig. 7i). We find these data compelling evidence for a specific role for Igf1r in outgrowth and branching of the embryonic mammary gland.

The use of alternative models to specifically knockout the receptor in the epithelium or the ligand in the mesenchyme (e.g. viruses) would be even more useful to specifically focus on the role of this pathway for ductal branching excluding side effects.

Our response:

We thank the reviewer for this suggestion. Unfortunately, based on our experience, viral shRNA delivery is not sufficiently efficient for effective gene silencing, unlike Cre delivery for a gain-of-function approach (used in the current study to flox out exon 3 of beta-catenin) in case where the endogenous pathway activity is very low and therefore, targeting even a subset of cells is sufficient for upregulation of paracrine factors.

Plan for the final revision:

To address the question on the autocrine or paracrine role of Igf1r, we will perform tissue recombination experiments between Igf1r-/- and control mammary epithelium and mesenchyme.

Another limit of this model is the fact that Igfr1 can be bound by Igf2 as well and we cannot exclude that this has an impact too (except if Igf2 is not expressed at this stage). A quantification of Igf2 expression may be useful.

Our response:

Indeed, we cannot exclude the possibility that Igf2 could also play a role (Igf2 expression was similar to Igf1 in our RNA-seq dataset, see Supplementary Fig. 5), but the connection of mesenchymal Wnt signaling activity was to Igf1, not Igf2 – in fact Igf2 was somewhat downregulated in Wnt3A treated sample reported by Wang et al. (Wang et al., 2021) (highlighted by an arrow in the revised Fig. 6). We have also clarified this point in the Discussion of the preliminary revised manuscript.

11- From the experiments presented in this section it is clear that Wnt-Igf1-Igf1r axis has to be finely regulated to have the correct amount of ductal branching in the embryonic mammary epithelium. Nevertheless, the author just showed the RNA levels of Igf1 in the different compartments they have analysed. Stainings to see the effective presence of the ligand on the tissue is mandatory to clarify the role of this axis in the ductal branching in vivo.

Our response:

Igf1-Igf1r signaling plays a critical growth promoting function during embryonic and postnatal development. The expression of Igf1 at RNA and protein level has been detected in almost all tissues in humans (Daughaday et al., Endocr. Rev., 1989; PMID: 2666112). Given that Igf1 is a secreted protein and multiple Igf binding proteins (Igfpbs) (that regulate the bioactivity of Igf1 by sequestering it) are expressed in the mammary and salivary gland mesenchyme (Supplementary Fig. 5), we find it unlikely that Igf1 staining would provide any additional information to the current study, as they cannot be used to assess the source of Igf1, nor the location of the signaling activity.

Furthermore, as underlined by the authors, this axis is specifically important and upregulated in the salivary gland. Due the limit of the Igf1R-/- model, we cannot exclude that, although Wnt-Igf1-Igf1r axis is able to increase the branching ability of mammary epithelium, the normal branching rate observed in wt mice is due to other pathways.

Our response:

We agree with the reviewer in that other pathways are also important in regulating normal mammary gland branching, for example, Eda/NF-κB and FGF pathways as we described in the Introduction. Our results do not exclude the possibility that also pathways other than Wnt regulate Igf1 expression. The reviewer is correct that if a paracrine factor is expressed in the salivary gland but not in the mammary mesenchyme, its physiological effect may be limited to the salivary gland. Indeed, cluster 5 identified by the mFuzzy analysis (Fig. 5f) is likely to include some genes like that. This is why we decided to focus on cluster 6 genes like Igf1. In the revised manuscript, we have better highlighted the difference between cluster 5 and 6 genes.

Unfortunately, with the currently available tools, we cannot test the importance of the endogenous mesenchymal Wnt signaling activity by inactivating Wnt signaling activity specifically in the mesenchyme at the time point when branching begins. This would require an inducible mesenchymal Cre line (mesenchymal β-catenin is essential for the early fate specification of the primary mammary mesenchyme; Hiremath et al., 2012, PMID: 23034629), and conditional β-catenin null mouse. We do not have such mice available and we find that these experiments are beyond the scope of the current study.

12- Lastly, once claimed to have found the key factor necessary for ductal branching promotion, the authors should also test if the proliferation and lineage segregations are unaffected in this context, confirming their dispensable role claimed in the initial part of the manuscript.

__Our response: __

Igf1/Igf1r is well-known for its growth promoting function via cell proliferation. We have no reasons to think that this would not be the case also in the mammary gland, and it was not our intention to give the impression that proliferation was not affected. In fact, Hiremath et al. (2012) already reported a defect in epithelial cell proliferation in Igf1rmammary buds at E14. Our key finding is that compared to other organs, the mammary gland is particularly sensitive to loss of Igf1r during branching morphogenesis. Finally, as pointed out earlier, better tools will be needed to assess the potential link between lineage segregation and onset of branching, a topic that we hope to address in the future.

Minor comments: 1- An important paper on mammary gland ductal branching was published on Nature in 2017 by Scheele and colleagues and should be presented in the introduction, even though it is at later stages (after birth).

Our response:

We thank the reviewer for the suggestion. In the revised manuscript, we have added the findings from Scheele et al. 2017 in the introduction.

2- In line 136 and 139 the authors referred to Fig 2 but it should be Fig 1

Our response:

We apologize for these slips. They have been corrected in the revised manuscript.

3- The sentence on line 142 should be rephrased, since "advanced developmental stages" may be referred to pubertal development. The authors should specify that they are talking about embryonic development.

Our response: We apologize for the potential misunderstanding. In the revised manuscript, we have used the phrase “advanced embryonic developmental stage” to describe our conclusion more precisely.

Reviewer #2 (Significance (Required)):

Overall, the authors concluded that embryonic mammary gland development and branching are extremely sensitive to the loss of IGF1, normally produced by the mesenchyme. The topic of the paper is interesting, the experimental approaches are well conceived, the data are convincing and the findings are of interest to developmental biologists. Nevertheless, there are some significant points that need to be further investigated before considering the manuscript suitable for publication:

Our response:

We thank the reviewer for the careful assessment and positive feedback of our manuscript. We have already addressed most of the points raised and most remaining ones will be addressed in the final revised manuscript.

__Reviewer #3 (Evidence, reproducibility and clarity (Required)): __

Here the authors use classical embryonic tissue recombination and pharmacological manipulation of explants in conjunction with cutting edge 3D imaging of tissue derived from highly sophisticated reporter and knock-out mouse models and state of the art transcriptomic analysis to masterfully delineate and dissect regulatory pathways critical for embryonic mammary development. Specifically, they set out to parse regulation of proliferation from that of branch patterning.

While it has long been established that epithelial-mesenchymal interaction is necessary for mammary branching this work shows by heterochronic recombination that initiation mammary branching is not advanced by mesenchymal stage. By examining Fucci2a embryos the authors demonstrate that branching is preceded by a significant increase in basal cell-biased proliferation but, through further analysis of Eda gain and loss of function mice, conclude that proliferation per se does not cause branching. They show by heterotypic recombination with salivary tissue that early mammary epithelia rudiments require their own mesenchyme for survival and that although later E16.5 rudiments expand more robustly when in contact with salivary mesenchyme they nevertheless retain their characteristic mammary branch pattern. Thus, they establish that initiation and patterning are intrinsic properties of the epithelium but that early survival and later expansion/proliferation is regulated by the mesenchymal context. By transcriptomic comparison of mammary and salivary mesenchyme they reveal that genes encoding canonical Wnt attenuators and antagonists are highly expressed in early mammary mesenchyme and drop as branching ensues. The low expression of these negative regulators of Wnt signaling in salivary mesenchyme is proposed as an explanation for its growth and branch stimulating capability. In keeping with these observations, the authors show that experimental activation of mammary mesenchymal Wnt signaling augments both growth and branching. Lastly, they identify transcriptomic changes in IGF1 coincident with the initiation of mammary branching and confirm its role by extending analyses of the effects of gain and loss of function of IGF1 on embryonic mammary development.

This is a thorough, well-constructed paper that adds new knowledge and important conceptual nuance and mechanistic insight to classical findings on branch patterning. This work is a technical tour de force and backed by solid quantitative and statistical analysis throughout. Their experimental approach is superb and the conclusions are sound. Their findings will be of great interest to the community of mammary gland biologists and to the wider field of embryologists focused on early development of a broad range of ectodermal appendages.

I have some minor criticisms that I believe can be quickly remedied in a minor rewrite and suggestions for the authors consideration to improve the manuscript discussion as follows:

Minor issues Abstract, line 37: The authors misuse the word "decompose" - it should be "deconstruct"

__Our response: __ We thank the reviewer for pointing out our mistake, which we have corrected in the revised manuscript.

Results, p7 line 48: Add "The" to the sentence: "The majority...."

__Our response: __ Corrected it in the revised manuscript.

P8 line 173 This sentence refers to Figure 2G which is a quantitative plot. I would suggest replacing the word "cluster" which implies a spatial organization with the word "subset" or "significant fraction" The spatial data in Fig 2d support basal bias but do NOT to my eye show any clustering - in fact the proliferative basal cells appear to be evenly dispersed within the basal layer.

Our response:

We thank the reviewer for highlighting this aspect. We agree that “significant fraction” is a more suitable term than “cluster”.

P9 line 188: The statement on basal cell lineage specification needs a reference.

__Our response: __

Following the suggestions from reviewers #1 and 3, we have removed the content about lineage segregation in Results, together with this sentence.

P10 line 201-216 I found the section on lineage specification (fig S2) weaker than the rest and a distraction from the main thrust of the paper making it difficult for the reader to focus. I suggest omitting this section and supplemental figures associated with it altogether.

__Our response: __

We agree with all reviewers in that this part of the manuscript was not mature enough and provided only indirect evidence on the potential link between lineage segregation and branching ability. This is an important question in the field that merits a study of its own that should be addressed with better tools than those available to us at present. As suggested by reviewers #1 and #3, we have omitted this part in the revised manuscript.

P9 line 190: "displays precocious onset of branching" it is sufficient to say: displays precocious branching - the use of both "precocious" and "onset' is redundant.

P10 line 229 Similarly, delete "the onset of branching was delayed" it is sufficient to say: branching was delayed.

__Our response: __ Both sentences have been corrected it in the revised manuscript.

P11 line 243: Delete "on the regulation of the" and substitute the word "to" in the sentence: "Next, we shifted our focus on the regulation of the branching pattern, which is thought to be determined by mesenchymal cues."

__Our response: __ Corrected it in the revised manuscript.

P11 line 241 subtitle and Figure 4 title: The disparity in titles here is jarring for the reader: Results text subtitle: "Salivary gland mesenchyme is rich in growth-promoting cues, but does not alter the mode of branch point formation of the mammary epithelium". Figure 4 Title: "Mammary mesenchyme is indispensable for the branching ability of the mammary gland". I suggest to the authors divide the figure as well as the text to make the two points indicated by their disparate titles separately.

__Our response: __ We thank reviewer for the suggestion to clarify the Results part of the manuscript. As suggested, we have split the data under two separate subtitles, but due to limitations in figure numbers, we prefer to report these data in one figure panel.

P12 line 279 From here on out the manuscript has a tendency to use the term "growth" ambiguously - in many instances it is unclear do they mean expansion, proliferation, increased branch number/ morphology?? Please try to clarify.

__Our response: __

Our aim is to use the term growth to mean tissue growth (expansion). We hope that this is clearer in the revised manuscript.

P16 line 341 use word "prompted" instead of word "promoted"

__Our response: __ We thank reviewer for spotting out the slip, which we have corrected in the revised manuscript.

P16 line 382: include word "embryonic" before "mammary development"

__Our response: __ We have modified the text in the revised manuscript.

Discussion P18 line 416: Add the words "later stage (E16.5)" to the sentence: "Importantly, we demonstrate that salivary gland mesenchyme could only promote the growth of later stage (E16.5) mammary epithelium"

__Our response: __ We thank reviewer for the suggestion. We have modified the text in the revised manuscript.

P19 line 437: Given the authors statement "Instead, cell motility is critical for branch point formation in the mammary gland" they should consider a brief sentence mentioning their transcriptomic findings on cadherin 11 and Tenascin.

__Our response: __ We thank the reviewer for appreciation of our transcriptomic data. In the revised manuscript, we have added the following text in discussion: “Accordingly, we observed significantly increased expression of cell migration promoting genes such as Cdh11 (encoding Cadherin 11), and Tnc (encoding Tenascin C) 60,61 in the E16.5 mesenchyme compared to E13.5 (Supplementary Table 2).”

P19 line 451: Similarly, given their statement "This observation suggests that mammary epithelium itself carries the instructions dictating the mode of branching" they could consider their transcriptomic data on Ltbp1 in "mammary specific" clusters 7,8,9 as a matrix molecule initially expressed by mammary mesenchyme but which becomes expressed by luminal epithelial cells at precisely the time they acquire lineage specification and intrinsic branching capability.

__Our response: __ This is an excellent suggestion. We have added following text in discussion: “It is worth noting that certain mesenchymal factors, such as Ltbp1, began transitioning towards epithelium-specific expression around E16.5 69. Exploring the potential impact of these factors on the self-instructed branching capacity of the mammary epithelium could yield valuable insights.”

P20 lines 462-470 The authors should address their theory of Wnt suppression in the mammary mesenchyme in the context, albeit conflictingly, of earlier studies showing expression of Wnt signaling reporters, in either epithelial or mesenchymal locations during early stages.

Our response: __ We thank reviewer for the suggestion. In the preliminary revised manuscript, we report Axin2 expression data as __new Supplementary Fig. 4c. Axin2 expression data suggest that Wnt/β-catenin activity is lowest in the E16.5 fat pad (where branching takes place) compared to all other tissues analyzed in the study.

Plan for the final revision:

For the final revised manuscript, we will additionally generate transgenic Wnt reporter expression data (see also our response to point 3 of Reviewer #1). These results will be discussed in light of the published Wnt reported literature in the final revised manuscript.

Reviewer #3 (Significance (Required)):

Here the authors use classical embryonic tissue recombination and pharmacological manipulation of explants in conjunction with cutting edge 3D imaging of tissue derived from highly sophisticated reporter and knock-out mouse models and state of the art transcriptomic analysis to masterfully delineate and dissect regulatory pathways critical for embryonic mammary development. Specifically, they set out to parse regulation of proliferation from that of branch patterning.

This is a thorough, well-constructed paper that adds new knowledge and important conceptual nuance and mechanistic insight to classical findings on branch patterning. This work is a technical tour de force and backed by solid quantitative and statistical analysis throughout. Their experimental approach is superb and the conclusions are sound. Their findings will be of great interest to the community of mammary gland biologists and to the wider field of embryologists focused on early development of a broad range of ectodermal appendages.

Our response:

We much appreciate the positive evaluation of our manuscript. We have addressed all the feedback provided by the reviewer 3 in the preliminary revised manuscript, except the last point, which will be included in the final revision along with the new data on the Wnt reporter expression.

Field of expertise: Embryonic and adult mammary development, Wnt signaling, cell adhesion

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Here the authors use classical embryonic tissue recombination and pharmacological manipulation of explants in conjunction with cutting edge 3D imaging of tissue derived from highly sophisticated reporter and knock-out mouse models and state of the art transcriptomic analysis to masterfully delineate and dissect regulatory pathways critical for embryonic mammary development. Specifically, they set out to parse regulation of proliferation from that of branch patterning.

While it has long been established that epithelial-mesenchymal interaction is necessary for mammary branching this work shows by heterochronic recombination that initiation mammary branching is not advanced by mesenchymal stage. By examining Fucci2a embryos the authors demonstrate that branching is preceded by a significant increase in basal cell-biased proliferation but, through further analysis of Eda gain and loss of function mice, conclude that proliferation per se does not cause branching. They show by heterotypic recombination with salivary tissue that early mammary epithelia rudiments require their own mesenchyme for survival and that although later E16.5 rudiments expand more robustly when in contact with salivary mesenchyme they nevertheless retain their characteristic mammary branch pattern. Thus, they establish that initiation and patterning are intrinsic properties of the epithelium but that early survival and later expansion/proliferation is regulated by the mesenchymal context. By transcriptomic comparison of mammary and salivary mesenchyme they reveal that genes encoding canonical Wnt attenuators and antagonists are highly expressed in early mammary mesenchyme and drop as branching ensues. The low expression of these negative regulators of Wnt signaling in salivary mesenchyme is proposed as an explanation for its growth and branch stimulating capability. In keeping with these observations, the authors show that experimental activation of mammary mesenchymal Wnt signaling augments both growth and branching. Lastly, they identify transcriptomic changes in IGF1 coincident with the initiation of mammary branching and confirm its role by extending analyses of the effects of gain and loss of function of IGF1 on embryonic mammary development.

This is a thorough, well-constructed paper that adds new knowledge and important conceptual nuance and mechanistic insight to classical findings on branch patterning. This work is a technical tour de force and backed by solid quantitative and statistical analysis throughout. Their experimental approach is superb and the conclusions are sound. Their findings will be of great interest to the community of mammary gland biologists and to the wider field of embryologists focused on early development of a broad range of ectodermal appendages.

I have some minor criticisms that I believe can be quickly remedied in a minor rewrite and suggestions for the authors consideration to improve the manuscript discussion as follows:

Minor issues

Abstract, line 37: The authors misuse the word "decompose" - it should be "deconstruct"

Results, p7 line 48: Add "The" to the sentence: "The majority...."

P8 line 173 This sentence refers to Figure 2G which is a quantitative plot. I would suggest replacing the word "cluster" which implies a spatial organization with the word "subset" or "significant fraction" The spatial data in Fig 2d support basal bias but do NOT to my eye show any clustering - in fact the proliferative basal cells appear to be evenly dispersed within the basal layer.

P9 line 188: The statement on basal cell lineage specification needs a reference.

P10 line 201-216 I found the section on lineage specification (fig S2) weaker than the rest and a distraction from the main thrust of the paper making it difficult for the reader to focus. I suggest omitting this section and supplemental figures associated with it altogether.

P9 line 190: "displays precocious onset of branching" it is sufficient to say: displays precocious branching - the use of both "precocious" and "onset' is redundant.

P10 line 229 Similarly, delete "the onset of branching was delayed" it is sufficient to say: branching was delayed.

P11 line 243: Delete "on the regulation of the" and substitute the word "to" in the sentence: "Next, we shifted our focus on the regulation of the branching pattern, which is thought to be determined by mesenchymal cues."

P11 line 241 subtitle and Figure 4 title: The disparity in titles here is jarring for the reader: Results text subtitle: "Salivary gland mesenchyme is rich in growth-promoting cues, but does not alter the mode of branch point formation of the mammary epithelium". Figure 4 Title: "Mammary mesenchyme is indispensable for the branching ability of the mammary gland". I suggest to the authors divide the figure as well as the text to make the two points indicated by their disparate titles separately.

P12 line 279 From here on out the manuscript has a tendency to use the term "growth" ambiguously - in many instances it is unclear do they mean expansion, proliferation, increased branch number/ morphology?? Please try to clarify.

P16 line 341 use word "prompted" instead of word "promoted"

P16 line 382: include word "embryonic" before "mammary development"

Discussion P18 line 416: Add the words "later stage (E16.5)" to the sentence: "Importantly, we demonstrate that salivary gland mesenchyme could only promote the growth of later stage (E16.5) mammary epithelium"

P19 line 437: Given the authors statement "Instead, cell motility is critical for branch point formation in the mammary gland" they should consider a brief sentence mentioning their transcriptomic findings on cadherin 11 and Tenascin.

P19 line 451: Similarly, given their statement "This observation suggests that mammary epithelium itself carries the instructions dictating the mode of branching" they could consider their transcriptomic data on Ltbp1 in "mammary specific" clusters 7,8,9 as a matrix molecule initially expressed by mammary mesenchyme but which becomes expressed by luminal epithelial cells at precisely the time they acquire lineage specification and intrinsic branching capability.

P20 lines 462-470 The authors should address their theory of Wnt suppression in the mammary mesenchyme in the context, albeit conflictingly, of earlier studies showing expression of Wnt signaling reporters, in either epithelial or mesenchymal locations during early stages.

Significance

Here the authors use classical embryonic tissue recombination and pharmacological manipulation of explants in conjunction with cutting edge 3D imaging of tissue derived from highly sophisticated reporter and knock-out mouse models and state of the art transcriptomic analysis to masterfully delineate and dissect regulatory pathways critical for embryonic mammary development. Specifically, they set out to parse regulation of proliferation from that of branch patterning.

This is a thorough, well-constructed paper that adds new knowledge and important conceptual nuance and mechanistic insight to classical findings on branch patterning. This work is a technical tour de force and backed by solid quantitative and statistical analysis throughout. Their experimental approach is superb and the conclusions are sound. Their findings will be of great interest to the community of mammary gland biologists and to the wider field of embryologists focused on early development of a broad range of ectodermal appendages.

Field of expertise: Embryonic and adult mammary development, Wnt signaling, cell adhesion

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

The mammary gland is a branched structure that consists of a bilayered epithelium embedded in a specialized mesenchyme. In mice, at 11,5 days of embryogenesis, the ectoderm thickens forming 5 pairs of peculiar structures called placodes. During the following days, the placodes will grow and invaginate into the surrounding mammary mesenchyme and they will finally start to branch by the end of embryogenesis (E16). It has been suggested that the bidirectional communication between the growing mammary gland and the surrounding mesenchyme plays a pivotal role in the determination of each step of mammary gland development (placode formation, mammary bud invagination, gland outgrowth, branching). The role of different signalling molecules has already been shown, particularly for the placode growth and mammary bud invagination. Nevertheless, the pathways regulating embryonic mammary gland branching are still incompletely understood. In this manuscript, Lan and colleagues aim to decipher the correlation between different stages of mammary gland development such as proliferation, lineage segregation and ductal branching. Furthermore, they want to define which stage of mammary development is intrinsically determined by the epithelium and which one requires the supportive guidance of the mesenchyme. Lastly, they aim to discover the key signal for the growth and branching of mammary epithelium.

To these purposes, they used an ex vivo model of heterochronic epithelial-mesenchymal recombination. In particular, they micro-dissected the epithelium and/or the mesenchyme from murine mammary glands at different stages of embryonic development (i.e. at E13,5 for the quiescent phase or 16,5 for branching phase) and explanted them together in different combinations using fluorescent reporters. To assess the role of the mesenchyme they also cultured the epithelium in a mesenchyme free 3d structure. Through this model they demonstrated that the presence of the mesenchyme is necessary for the priming of mammary epithelium for branching, since only E16,5 epithelial cells were able to grow and branch in a mesenchyme free 3D experiment. Nevertheless, intrinsic properties of the epithelium are necessary for the timing of branching, since E16,5 mesenchyme was not able to accelerate the outgrowth of E13,5 epithelia. In order to determine which epithelial properties are important, the authors correlated the beginning of cell proliferation in the embryonic mammary gland to the beginning of the branching phase. They indeed used the Fucci2a mouse model to carefully characterise the timing of mammary cells proliferation at different stages of embryonic development, concluding that the great majority of proliferating cells reside in the inner part of the mammary bud until E14,5, while in the external part at later stages.

Regarding the importance of cell proliferation, Lan and colleagues claim that the beginning of the branching phase is not its direct consequence, thanks to the use of the K14Cre- Eda mouse model, known to have anticipated mammary gland development. Using this and the Eda-/- models, the authors also sustain that the branching occurs independently of the lineage specification of the epithelium. The use of salivary mesenchyme instead the mammary one was able to increase the number of branching of E16,5 mammary epithelium. Nevertheless, this model demonstrated that the branching pattern (side branching vs tip bifurcation) is an intrinsic feature of the epithelium. Lan and colleagues also defined the transcriptomic profiles of the mammary and salivary mesenchymes at different stages. In particular, they observed an increased expression of negative regulators of Wnt pathway in the mammary mesenchyme compared to the salivary mesenchyme. Moreover, using a mouse model where B-catenin is stabilised, they observed increased tip production in the mammary gland epithelium. They also showed that IGF1 production is increased after Wnt pathway activation and they tested its function, both treating their ex vivo cultures with exogenous IGF1 and using Igf1r-/- mouse models.

Major comments

1. The great majority of the results of the manuscript are based on an ex vivo model of heterochronic epithelial-mesenchymal recombination. Since the authors are studying the effect of the mesenchyme of different stages on the epithelium (and vice versa), the purity of the two compartments after the dissection is particularly important. Although they said that the purity is evaluated (line 112), it would be important to show a control staining in which they use known markers of the mesenchyme with no colocalization with the fluorescent reporter of the epithelium.
2. Another important point for understanding the quality and impact of these findings is to assess the similarities and differences, if there are, between the in vivo mesenchyme and the ex vivo one. Indeed, once explanted and put in culture, mesenchymal cells could change their transcriptomic profile and consequently change their signals to the epithelium. The authors should assess the expression of the genes and pathways studied during embryonic development in vivo .
3. The authors clearly showed that E16,5 epithelium is able to branch in a mesenchyme free 3D culture model, while epithelia from earlier stages don't. This led to the conclusion that mesenchyme is necessary for acquiring the branching ability. Nevertheless, the authors also said that early stages epithelia scarcely grow in the mesenchyme free 3D culture. Therefore, the lack of branching may be due to the lack of growth, if not the increase of death, of epithelial cells. The authors should quantify the size and the cell death of the epithelia in the different culture conditions and discuss better this point.
4. The Fucci2a model allowed to assess the proliferation of embryonic mammary epithelium, showing that the great majority of proliferating cells are basal, at late stages of development (line 182). As it has already been shown, lineage specification is a late process during mammary gland development. The fact that the proliferating cells reside at the external part of the bud does not mean that they are basal cells yet. A p63/K8 staining could be important to understand if the increased proliferation occured in already specified basal cells or not.
5. The use of Fucci2a model showed that 20% of epithelial cells are proliferative at E13,5. This phase is considered as "quiescent" by the authors (line 120), but the moderate proliferation rate shown in this experiment demonstrated that it is not. A change of the nomenclature is needed.
6. Through the use of K14-Eda and Eda-/- models, the authors claimed that the lineage specification is not a prerequisite for ductal branching. To support this point, they showed that the K14-Eda mice have an anticipated branching although the expression of K8 in the inner part of the bud is transitorily decreased. The authors link the K8 downregulation to a transient suppression of the luminal lineage, but this is clearly overclaimed. Although K8 is a known marker of luminal lineage, the downregulation of one marker is not sufficient to support their thesis. They should first check more markers and in particular critical regulators of luminal lineage as Notch1, Foxa1 and Elf5. Lately, the use of different models that drive embryonic epithelial cells to a forced lineage commitment (Notch1 or Δnp63 overexpression) would support more their claim. As additional evidence, the authors showed that Eda is able to promote basal cell signature. Firstly, the authors should better explain why this point would support their thesis. Secondly, the supplementary figure 2b does not show which genes are taken into account to define the basal signature. A list of these genes would be helpful, as well as staining for some representative proteins.
7. The authors used the same mouse models to assess the importance of proliferation in the determination of ductal branching and they claimed that proliferation is not a sufficient feature. This conclusion was supported by two observations. The first one is the fact that the K14-Eda model shows an increased cell proliferation at early stages compared to wt, coupled with anticipated branching. Secondly, although having smaller glands compared to wt and showing a delay in ductal branching, Eda-/- mice have an epithelial proliferation rate very similar to wt. Again, the conclusion that proliferation is not sufficient for branching is overclaimed. Firstly, the authors should explain how the buds in wt and Eda-/- mice have different sizes although the similar proliferation (increased cell death?, cellular volume?). Secondly, to support the thesis that proliferation is not sufficient for branching, functional experiments should be performed (see point 12). For instance, the short-time treatments with inhibitors or promotors of proliferation may help to understand the effective role of proliferation in the determination of branching.
8. The heterotypic epithelial-mesenchymal recombination using the salivary gland is interesting. Nevertheless, some stainings to assess the purity of their systems are again required (e.g., marker of salivary epithelium to verify the purity of the mesenchyme and vice versa). This model clearly showed that the mammary epithelium can form more branching when combined with the salivary mesenchyme. Moreover, the salivary epithelium preferentially branches through tip bifurcation, while mammary epithelium combined with the salivary mesenchyme has a mixed pattern of tip bifurcation and side branching (typical of the mammary gland). The authors thus concluded that the branching pattern is an intrinsic feature of the epithelium. However, a comparison between the percentage of tip bifurcation and side branching in the heterotypic combination and the homotypic combination between mammary epithelium and mammary mesenchyme is crucial to understand this point. Indeed, these results are not sufficient to exclude that the branching pattern is partially determined by intrinsic features and partially by extrinsic signals. The authors should carefully quantify the branching pattern in the homotypic combination and compare that to the heterotypic one. If the percentage of tip bifurcation do not change, their conclusion is correct; if this percentage increases in the heterotypic combination, it would be a sign of a partial effect of the signals of the mesenchyme.
9. Through the analysis of their transcriptomic data, Lan and colleagues found that the mammary mesenchyme expresses higher levels of negative regulators of Wnt pathway compared to the salivary mesenchyme. To demonstrate the value of their findings, they should confirm this in vivo, through staining of known Wnt proteins on the salivary and mammary mesenchymes at the embryonic stage.
10. Since the ability of the salivary mesenchyme to promote a higher rate of branching in the mammary epithelium, the authors wanted to assess what could be the role of Wnt signalling. To do so, they used a mouse model where B-catenin is stabilised, allowing an increased Wnt signalling in the mammary mesenchyme. As a result, they observed increased branching in the mammary epithelium. They also found that IGF1 is a ligand regulated by Wnt pathway in the mesenchyme. Therefore, the use of exogenous IGF1 in their ex vivo model was able to increase the branching of the mammary epithelium. Moreover, Igf1r-/- embryos showed a significant decrease of mammary gland branching. The conclusion based on these experiments was that the Wnt-Igf1-Igf1r axis plays a pivotal role in the promotion of mammary gland branching during embryogenesis. This conclusion is overclaimed for different reasons. Firstly, the normalization of the ductal branching to the body weight is insufficient to exclude that the impact of the Igf1r knockout may have severe consequences on the mammary gland formation, upstream of the ductal branching. Another parameter for this normalization is required (e.g., size of the bud before branching, proliferation status, etc). The use of alternative models to specifically knockout the receptor in the epithelium or the ligand in the mesenchyme (e.g. viruses) would be even more useful to specifically focus on the role of this pathway for ductal branching excluding side effects. Another limit of this model is the fact that Igfr1 can be bound by Igf2 as well and we cannot exclude that this has an impact too (except if Igf2 is not expressed at this stage). A quantification of Igf2 expression may be useful.
11. From the experiments presented in this section it is clear that Wnt-Igf1-Igf1r axis has to be finely regulated to have the correct amount of ductal branching in the embryonic mammary epithelium. Nevertheless, the author just showed the RNA levels of Igf1 in the different compartments they have analysed. Stainings to see the effective presence of the ligand on the tissue is mandatory to clarify the role of this axis in the ductal branching in vivo. Furthermore, as underlined by the authors, this axis is specifically important and upregulated in the salivary gland. Due the limit of the Igf1R-/- model, we cannot exclude that, although Wnt-Igf1-Igf1r axis is able to increase the branching ability of mammary epithelium, the normal branching rate observed in wt mice is due to other pathways.
12. Lastly, once claimed to have found the key factor necessary for ductal branching promotion, the authors should also test if the proliferation and lineage segregations are unaffected in this context, confirming their dispensable role claimed in the initial part of the manuscript.

Minor comments:

1. An important paper on mammary gland ductal branching was published on Nature in 2017 by Scheele and colleagues and should be presented in the introduction, even though it is at later stages (after birth).
2. In line 136 and 139 the authors referred to Fig 2 but it should be Fig 1
3. The sentence on line 142 should be rephrased, since "advanced developmental stages" may be referred to pubertal development. The authors should specify that they are talking about embryonic development.

Significance

Overall, the authors concluded that embryonic mammary gland development and branching are extremely sensitive to the loss of IGF1, normally produced by the mesenchyme. The topic of the paper is interesting, the experimental approaches are well conceived, the data are convincing and the findings are of interest to developmental biologists. Nevertheless, there are some significant points that need to be further investigated before considering the manuscript suitable for publication:

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Summary:

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

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

Learn more at Review Commons

---

Reply to the reviewers

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

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Summary:

In this 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

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

The 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.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

In 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

---

Download the complete Review Process [PDF] including:

• reviews
• authors' reply
• editorial decisions

</br>

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

Learn more at Review Commons

---

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.

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

Learn more at Review Commons

---

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.

Learn more at Review Commons

---

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.

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

In 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.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Summary

The 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.

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

Learn more at Review Commons

---

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.

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

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.

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

Summary: This 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.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

This is 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

---

Download the complete Review Process [PDF] including:

• reviews
• authors' reply
• editorial decisions

</br>

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

Learn more at Review Commons

---

Reply to the reviewers

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

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

In the 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

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

Summary

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.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

This 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.

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

Learn more at Review Commons

---

Reply to the reviewers

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

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

This 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.

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

In 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.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Summary:

The 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.

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

Learn more at Review Commons

---

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.

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

Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. If no revisions have been carried out yet, please leave this section empty.

-

Description of analyses that authors prefer not to carry out

Please include a point-by-point response explaining why some of the requested data or additional analyses might not be necessary or cannot be provided within the scope of a revision. This can be due to time or resource limitations or in case of disagreement about the necessity of such additional data given the scope of the study. Please leave empty if not applicable.

-

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Summary:

This manuscript 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.

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

Summary:

The authors 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.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Summary:

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.

Transparent Peer Review

---

Download the complete Review Process [PDF] including:

• reviews
• authors' reply
• editorial decisions

</br>

Transparent Peer Review

---

Download the complete Review Process [PDF] including:

• reviews
• authors' reply
• editorial decisions

</br>

Transparent Peer Review

---

Download the complete Review Process [PDF] including:

• reviews
• authors' reply
• editorial decisions

</br>

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

Learn more at Review Commons

---

Reply to the reviewers

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

The 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.

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

Summary:

In this manuscript, 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.

Learn more at Review Commons

---

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.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

The manuscript 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.

Transparent Peer Review

---

Download the complete Review Process [PDF] including:

• reviews
• authors' reply
• editorial decisions

</br>

Transparent Peer Review

---

Download the complete Review Process [PDF] including:

• reviews
• authors' reply
• editorial decisions

</br>

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

Learn more at Review Commons

---

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).

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

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.

Learn more at Review Commons

---

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.

Transparent Peer Review

---

Download the complete Review Process [PDF] including:

• reviews
• authors' reply
• editorial decisions

</br>

Transparent Peer Review

---

Download the complete Review Process [PDF] including:

• reviews
• authors' reply
• editorial decisions

</br>

Transparent Peer Review

---

Download the complete Review Process [PDF] including:

• reviews
• authors' reply
• editorial decisions

</br>

Transparent Peer Review

---

Download the complete Review Process [PDF] including:

• reviews
• authors' reply
• editorial decisions

</br>

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

Learn more at Review Commons

---

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

Böhm F, Köhler UA, Speicher T, Werner S. Regulation of liver regeneration by growth factors and cytokines. EMBO Mol Med. 2010 doi:10.1002/emmm.201000085.

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.

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

In this study, the authors present 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.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Summary:

The 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.

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

Learn more at Review Commons

---

Reply to the reviewers

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

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

This 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.

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

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.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

This 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.

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

Learn more at Review Commons

---

Reply to the reviewers

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

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

In this study, the authors 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.

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

In this manuscript, 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.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

The 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

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

Learn more at Review Commons

---

Reply to the reviewers

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

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

Learn more at Review Commons

---

Referee #3

Evidence, reproducibility and clarity

The 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.

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

Summary:

This 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.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

In 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.